diff --git a/PIL/AvifImagePlugin.py b/PIL/AvifImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..43c39a9fbe78b17bfd4a5440bad787bc8070be1e --- /dev/null +++ b/PIL/AvifImagePlugin.py @@ -0,0 +1,293 @@ +from __future__ import annotations + +import os +from io import BytesIO +from typing import IO + +from . import ExifTags, Image, ImageFile + +try: + from . import _avif + + SUPPORTED = True +except ImportError: + SUPPORTED = False + +# Decoder options as module globals, until there is a way to pass parameters +# to Image.open (see https://github.com/python-pillow/Pillow/issues/569) +DECODE_CODEC_CHOICE = "auto" +DEFAULT_MAX_THREADS = 0 + + +def get_codec_version(codec_name: str) -> str | None: + versions = _avif.codec_versions() + for version in versions.split(", "): + if version.split(" [")[0] == codec_name: + return version.split(":")[-1].split(" ")[0] + return None + + +def _accept(prefix: bytes) -> bool | str: + if prefix[4:8] != b"ftyp": + return False + major_brand = prefix[8:12] + if major_brand in ( + # coding brands + b"avif", + b"avis", + # We accept files with AVIF container brands; we can't yet know if + # the ftyp box has the correct compatible brands, but if it doesn't + # then the plugin will raise a SyntaxError which Pillow will catch + # before moving on to the next plugin that accepts the file. + # + # Also, because this file might not actually be an AVIF file, we + # don't raise an error if AVIF support isn't properly compiled. + b"mif1", + b"msf1", + ): + if not SUPPORTED: + return ( + "image file could not be identified because AVIF support not installed" + ) + return True + return False + + +def _get_default_max_threads() -> int: + if DEFAULT_MAX_THREADS: + return DEFAULT_MAX_THREADS + if hasattr(os, "sched_getaffinity"): + return len(os.sched_getaffinity(0)) + else: + return os.cpu_count() or 1 + + +class AvifImageFile(ImageFile.ImageFile): + format = "AVIF" + format_description = "AVIF image" + __frame = -1 + + def _open(self) -> None: + if not SUPPORTED: + msg = "image file could not be opened because AVIF support not installed" + raise SyntaxError(msg) + + if DECODE_CODEC_CHOICE != "auto" and not _avif.decoder_codec_available( + DECODE_CODEC_CHOICE + ): + msg = "Invalid opening codec" + raise ValueError(msg) + + assert self.fp is not None + self._decoder = _avif.AvifDecoder( + self.fp.read(), + DECODE_CODEC_CHOICE, + _get_default_max_threads(), + ) + + # Get info from decoder + self._size, self.n_frames, self._mode, icc, exif, exif_orientation, xmp = ( + self._decoder.get_info() + ) + self.is_animated = self.n_frames > 1 + + if icc: + self.info["icc_profile"] = icc + if xmp: + self.info["xmp"] = xmp + + if exif_orientation != 1 or exif: + exif_data = Image.Exif() + if exif: + exif_data.load(exif) + original_orientation = exif_data.get(ExifTags.Base.Orientation, 1) + else: + original_orientation = 1 + if exif_orientation != original_orientation: + exif_data[ExifTags.Base.Orientation] = exif_orientation + exif = exif_data.tobytes() + if exif: + self.info["exif"] = exif + self.seek(0) + + def seek(self, frame: int) -> None: + if not self._seek_check(frame): + return + + # Set tile + self.__frame = frame + self.tile = [ImageFile._Tile("raw", (0, 0) + self.size, 0, self.mode)] + + def load(self) -> Image.core.PixelAccess | None: + if self.tile: + # We need to load the image data for this frame + data, timescale, pts_in_timescales, duration_in_timescales = ( + self._decoder.get_frame(self.__frame) + ) + self.info["timestamp"] = round(1000 * (pts_in_timescales / timescale)) + self.info["duration"] = round(1000 * (duration_in_timescales / timescale)) + + if self.fp and self._exclusive_fp: + self.fp.close() + self.fp = BytesIO(data) + + return super().load() + + def load_seek(self, pos: int) -> None: + pass + + def tell(self) -> int: + return self.__frame + + +def _save_all(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + _save(im, fp, filename, save_all=True) + + +def _save( + im: Image.Image, fp: IO[bytes], filename: str | bytes, save_all: bool = False +) -> None: + info = im.encoderinfo.copy() + if save_all: + append_images = list(info.get("append_images", [])) + else: + append_images = [] + + total = 0 + for ims in [im] + append_images: + total += getattr(ims, "n_frames", 1) + + quality = info.get("quality", 75) + if not isinstance(quality, int) or quality < 0 or quality > 100: + msg = "Invalid quality setting" + raise ValueError(msg) + + duration = info.get("duration", 0) + subsampling = info.get("subsampling", "4:2:0") + speed = info.get("speed", 6) + max_threads = info.get("max_threads", _get_default_max_threads()) + codec = info.get("codec", "auto") + if codec != "auto" and not _avif.encoder_codec_available(codec): + msg = "Invalid saving codec" + raise ValueError(msg) + range_ = info.get("range", "full") + tile_rows_log2 = info.get("tile_rows", 0) + tile_cols_log2 = info.get("tile_cols", 0) + alpha_premultiplied = bool(info.get("alpha_premultiplied", False)) + autotiling = bool(info.get("autotiling", tile_rows_log2 == tile_cols_log2 == 0)) + + icc_profile = info.get("icc_profile", im.info.get("icc_profile")) + exif_orientation = 1 + if exif := info.get("exif"): + if isinstance(exif, Image.Exif): + exif_data = exif + else: + exif_data = Image.Exif() + exif_data.load(exif) + if ExifTags.Base.Orientation in exif_data: + exif_orientation = exif_data.pop(ExifTags.Base.Orientation) + exif = exif_data.tobytes() if exif_data else b"" + elif isinstance(exif, Image.Exif): + exif = exif_data.tobytes() + + xmp = info.get("xmp") + + if isinstance(xmp, str): + xmp = xmp.encode("utf-8") + + advanced = info.get("advanced") + if advanced is not None: + if isinstance(advanced, dict): + advanced = advanced.items() + try: + advanced = tuple(advanced) + except TypeError: + invalid = True + else: + invalid = any(not isinstance(v, tuple) or len(v) != 2 for v in advanced) + if invalid: + msg = ( + "advanced codec options must be a dict of key-value string " + "pairs or a series of key-value two-tuples" + ) + raise ValueError(msg) + + # Setup the AVIF encoder + enc = _avif.AvifEncoder( + im.size, + subsampling, + quality, + speed, + max_threads, + codec, + range_, + tile_rows_log2, + tile_cols_log2, + alpha_premultiplied, + autotiling, + icc_profile or b"", + exif or b"", + exif_orientation, + xmp or b"", + advanced, + ) + + # Add each frame + frame_idx = 0 + frame_duration = 0 + cur_idx = im.tell() + is_single_frame = total == 1 + try: + for ims in [im] + append_images: + # Get number of frames in this image + nfr = getattr(ims, "n_frames", 1) + + for idx in range(nfr): + ims.seek(idx) + + # Make sure image mode is supported + frame = ims + rawmode = ims.mode + if ims.mode not in {"RGB", "RGBA"}: + rawmode = "RGBA" if ims.has_transparency_data else "RGB" + frame = ims.convert(rawmode) + + # Update frame duration + if isinstance(duration, (list, tuple)): + frame_duration = duration[frame_idx] + else: + frame_duration = duration + + # Append the frame to the animation encoder + enc.add( + frame.tobytes("raw", rawmode), + frame_duration, + frame.size, + rawmode, + is_single_frame, + ) + + # Update frame index + frame_idx += 1 + + if not save_all: + break + + finally: + im.seek(cur_idx) + + # Get the final output from the encoder + data = enc.finish() + if data is None: + msg = "cannot write file as AVIF (encoder returned None)" + raise OSError(msg) + + fp.write(data) + + +Image.register_open(AvifImageFile.format, AvifImageFile, _accept) +if SUPPORTED: + Image.register_save(AvifImageFile.format, _save) + Image.register_save_all(AvifImageFile.format, _save_all) + Image.register_extensions(AvifImageFile.format, [".avif", ".avifs"]) + Image.register_mime(AvifImageFile.format, "image/avif") diff --git a/PIL/BdfFontFile.py b/PIL/BdfFontFile.py new file mode 100644 index 0000000000000000000000000000000000000000..f175e2f4f80b1b232d79f15a6db0667296917c97 --- /dev/null +++ b/PIL/BdfFontFile.py @@ -0,0 +1,122 @@ +# +# The Python Imaging Library +# $Id$ +# +# bitmap distribution font (bdf) file parser +# +# history: +# 1996-05-16 fl created (as bdf2pil) +# 1997-08-25 fl converted to FontFile driver +# 2001-05-25 fl removed bogus __init__ call +# 2002-11-20 fl robustification (from Kevin Cazabon, Dmitry Vasiliev) +# 2003-04-22 fl more robustification (from Graham Dumpleton) +# +# Copyright (c) 1997-2003 by Secret Labs AB. +# Copyright (c) 1997-2003 by Fredrik Lundh. +# +# See the README file for information on usage and redistribution. +# + +""" +Parse X Bitmap Distribution Format (BDF) +""" +from __future__ import annotations + +from typing import BinaryIO + +from . import FontFile, Image + + +def bdf_char( + f: BinaryIO, +) -> ( + tuple[ + str, + int, + tuple[tuple[int, int], tuple[int, int, int, int], tuple[int, int, int, int]], + Image.Image, + ] + | None +): + # skip to STARTCHAR + while True: + s = f.readline() + if not s: + return None + if s.startswith(b"STARTCHAR"): + break + id = s[9:].strip().decode("ascii") + + # load symbol properties + props = {} + while True: + s = f.readline() + if not s or s.startswith(b"BITMAP"): + break + i = s.find(b" ") + props[s[:i].decode("ascii")] = s[i + 1 : -1].decode("ascii") + + # load bitmap + bitmap = bytearray() + while True: + s = f.readline() + if not s or s.startswith(b"ENDCHAR"): + break + bitmap += s[:-1] + + # The word BBX + # followed by the width in x (BBw), height in y (BBh), + # and x and y displacement (BBxoff0, BByoff0) + # of the lower left corner from the origin of the character. + width, height, x_disp, y_disp = (int(p) for p in props["BBX"].split()) + + # The word DWIDTH + # followed by the width in x and y of the character in device pixels. + dwx, dwy = (int(p) for p in props["DWIDTH"].split()) + + bbox = ( + (dwx, dwy), + (x_disp, -y_disp - height, width + x_disp, -y_disp), + (0, 0, width, height), + ) + + try: + im = Image.frombytes("1", (width, height), bitmap, "hex", "1") + except ValueError: + # deal with zero-width characters + im = Image.new("1", (width, height)) + + return id, int(props["ENCODING"]), bbox, im + + +class BdfFontFile(FontFile.FontFile): + """Font file plugin for the X11 BDF format.""" + + def __init__(self, fp: BinaryIO) -> None: + super().__init__() + + s = fp.readline() + if not s.startswith(b"STARTFONT 2.1"): + msg = "not a valid BDF file" + raise SyntaxError(msg) + + props = {} + comments = [] + + while True: + s = fp.readline() + if not s or s.startswith(b"ENDPROPERTIES"): + break + i = s.find(b" ") + props[s[:i].decode("ascii")] = s[i + 1 : -1].decode("ascii") + if s[:i] in [b"COMMENT", b"COPYRIGHT"]: + if s.find(b"LogicalFontDescription") < 0: + comments.append(s[i + 1 : -1].decode("ascii")) + + while True: + c = bdf_char(fp) + if not c: + break + id, ch, (xy, dst, src), im = c + if 0 <= ch < len(self.glyph): + self.glyph[ch] = xy, dst, src, im diff --git a/PIL/BlpImagePlugin.py b/PIL/BlpImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..6bb92edf8911ab9afa18e3b3dc49b4134792b794 --- /dev/null +++ b/PIL/BlpImagePlugin.py @@ -0,0 +1,498 @@ +""" +Blizzard Mipmap Format (.blp) +Jerome Leclanche + +The contents of this file are hereby released in the public domain (CC0) +Full text of the CC0 license: + https://creativecommons.org/publicdomain/zero/1.0/ + +BLP1 files, used mostly in Warcraft III, are not fully supported. +All types of BLP2 files used in World of Warcraft are supported. + +The BLP file structure consists of a header, up to 16 mipmaps of the +texture + +Texture sizes must be powers of two, though the two dimensions do +not have to be equal; 512x256 is valid, but 512x200 is not. +The first mipmap (mipmap #0) is the full size image; each subsequent +mipmap halves both dimensions. The final mipmap should be 1x1. + +BLP files come in many different flavours: +* JPEG-compressed (type == 0) - only supported for BLP1. +* RAW images (type == 1, encoding == 1). Each mipmap is stored as an + array of 8-bit values, one per pixel, left to right, top to bottom. + Each value is an index to the palette. +* DXT-compressed (type == 1, encoding == 2): +- DXT1 compression is used if alpha_encoding == 0. + - An additional alpha bit is used if alpha_depth == 1. + - DXT3 compression is used if alpha_encoding == 1. + - DXT5 compression is used if alpha_encoding == 7. +""" + +from __future__ import annotations + +import abc +import os +import struct +from enum import IntEnum +from io import BytesIO +from typing import IO + +from . import Image, ImageFile + + +class Format(IntEnum): + JPEG = 0 + + +class Encoding(IntEnum): + UNCOMPRESSED = 1 + DXT = 2 + UNCOMPRESSED_RAW_BGRA = 3 + + +class AlphaEncoding(IntEnum): + DXT1 = 0 + DXT3 = 1 + DXT5 = 7 + + +def unpack_565(i: int) -> tuple[int, int, int]: + return ((i >> 11) & 0x1F) << 3, ((i >> 5) & 0x3F) << 2, (i & 0x1F) << 3 + + +def decode_dxt1( + data: bytes, alpha: bool = False +) -> tuple[bytearray, bytearray, bytearray, bytearray]: + """ + input: one "row" of data (i.e. will produce 4*width pixels) + """ + + blocks = len(data) // 8 # number of blocks in row + ret = (bytearray(), bytearray(), bytearray(), bytearray()) + + for block_index in range(blocks): + # Decode next 8-byte block. + idx = block_index * 8 + color0, color1, bits = struct.unpack_from("> 2 + + a = 0xFF + if control == 0: + r, g, b = r0, g0, b0 + elif control == 1: + r, g, b = r1, g1, b1 + elif control == 2: + if color0 > color1: + r = (2 * r0 + r1) // 3 + g = (2 * g0 + g1) // 3 + b = (2 * b0 + b1) // 3 + else: + r = (r0 + r1) // 2 + g = (g0 + g1) // 2 + b = (b0 + b1) // 2 + elif control == 3: + if color0 > color1: + r = (2 * r1 + r0) // 3 + g = (2 * g1 + g0) // 3 + b = (2 * b1 + b0) // 3 + else: + r, g, b, a = 0, 0, 0, 0 + + if alpha: + ret[j].extend([r, g, b, a]) + else: + ret[j].extend([r, g, b]) + + return ret + + +def decode_dxt3(data: bytes) -> tuple[bytearray, bytearray, bytearray, bytearray]: + """ + input: one "row" of data (i.e. will produce 4*width pixels) + """ + + blocks = len(data) // 16 # number of blocks in row + ret = (bytearray(), bytearray(), bytearray(), bytearray()) + + for block_index in range(blocks): + idx = block_index * 16 + block = data[idx : idx + 16] + # Decode next 16-byte block. + bits = struct.unpack_from("<8B", block) + color0, color1 = struct.unpack_from(">= 4 + else: + high = True + a &= 0xF + a *= 17 # We get a value between 0 and 15 + + color_code = (code >> 2 * (4 * j + i)) & 0x03 + + if color_code == 0: + r, g, b = r0, g0, b0 + elif color_code == 1: + r, g, b = r1, g1, b1 + elif color_code == 2: + r = (2 * r0 + r1) // 3 + g = (2 * g0 + g1) // 3 + b = (2 * b0 + b1) // 3 + elif color_code == 3: + r = (2 * r1 + r0) // 3 + g = (2 * g1 + g0) // 3 + b = (2 * b1 + b0) // 3 + + ret[j].extend([r, g, b, a]) + + return ret + + +def decode_dxt5(data: bytes) -> tuple[bytearray, bytearray, bytearray, bytearray]: + """ + input: one "row" of data (i.e. will produce 4 * width pixels) + """ + + blocks = len(data) // 16 # number of blocks in row + ret = (bytearray(), bytearray(), bytearray(), bytearray()) + + for block_index in range(blocks): + idx = block_index * 16 + block = data[idx : idx + 16] + # Decode next 16-byte block. + a0, a1 = struct.unpack_from("> alphacode_index) & 0x07 + elif alphacode_index == 15: + alphacode = (alphacode2 >> 15) | ((alphacode1 << 1) & 0x06) + else: # alphacode_index >= 18 and alphacode_index <= 45 + alphacode = (alphacode1 >> (alphacode_index - 16)) & 0x07 + + if alphacode == 0: + a = a0 + elif alphacode == 1: + a = a1 + elif a0 > a1: + a = ((8 - alphacode) * a0 + (alphacode - 1) * a1) // 7 + elif alphacode == 6: + a = 0 + elif alphacode == 7: + a = 255 + else: + a = ((6 - alphacode) * a0 + (alphacode - 1) * a1) // 5 + + color_code = (code >> 2 * (4 * j + i)) & 0x03 + + if color_code == 0: + r, g, b = r0, g0, b0 + elif color_code == 1: + r, g, b = r1, g1, b1 + elif color_code == 2: + r = (2 * r0 + r1) // 3 + g = (2 * g0 + g1) // 3 + b = (2 * b0 + b1) // 3 + elif color_code == 3: + r = (2 * r1 + r0) // 3 + g = (2 * g1 + g0) // 3 + b = (2 * b1 + b0) // 3 + + ret[j].extend([r, g, b, a]) + + return ret + + +class BLPFormatError(NotImplementedError): + pass + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith((b"BLP1", b"BLP2")) + + +class BlpImageFile(ImageFile.ImageFile): + """ + Blizzard Mipmap Format + """ + + format = "BLP" + format_description = "Blizzard Mipmap Format" + + def _open(self) -> None: + assert self.fp is not None + self.magic = self.fp.read(4) + if not _accept(self.magic): + msg = f"Bad BLP magic {repr(self.magic)}" + raise BLPFormatError(msg) + + compression = struct.unpack(" tuple[int, int]: + try: + self._read_header() + self._load() + except struct.error as e: + msg = "Truncated BLP file" + raise OSError(msg) from e + return -1, 0 + + @abc.abstractmethod + def _load(self) -> None: + pass + + def _read_header(self) -> None: + self._offsets = struct.unpack("<16I", self._safe_read(16 * 4)) + self._lengths = struct.unpack("<16I", self._safe_read(16 * 4)) + + def _safe_read(self, length: int) -> bytes: + assert self.fd is not None + return ImageFile._safe_read(self.fd, length) + + def _read_palette(self) -> list[tuple[int, int, int, int]]: + ret = [] + for i in range(256): + try: + b, g, r, a = struct.unpack("<4B", self._safe_read(4)) + except struct.error: + break + ret.append((b, g, r, a)) + return ret + + def _read_bgra( + self, palette: list[tuple[int, int, int, int]], alpha: bool + ) -> bytearray: + data = bytearray() + _data = BytesIO(self._safe_read(self._lengths[0])) + while True: + try: + (offset,) = struct.unpack(" None: + self._compression, self._encoding, alpha = self.args + + if self._compression == Format.JPEG: + self._decode_jpeg_stream() + + elif self._compression == 1: + if self._encoding in (4, 5): + palette = self._read_palette() + data = self._read_bgra(palette, alpha) + self.set_as_raw(data) + else: + msg = f"Unsupported BLP encoding {repr(self._encoding)}" + raise BLPFormatError(msg) + else: + msg = f"Unsupported BLP compression {repr(self._encoding)}" + raise BLPFormatError(msg) + + def _decode_jpeg_stream(self) -> None: + from .JpegImagePlugin import JpegImageFile + + (jpeg_header_size,) = struct.unpack(" None: + self._compression, self._encoding, alpha, self._alpha_encoding = self.args + + palette = self._read_palette() + + assert self.fd is not None + self.fd.seek(self._offsets[0]) + + if self._compression == 1: + # Uncompressed or DirectX compression + + if self._encoding == Encoding.UNCOMPRESSED: + data = self._read_bgra(palette, alpha) + + elif self._encoding == Encoding.DXT: + data = bytearray() + if self._alpha_encoding == AlphaEncoding.DXT1: + linesize = (self.state.xsize + 3) // 4 * 8 + for yb in range((self.state.ysize + 3) // 4): + for d in decode_dxt1(self._safe_read(linesize), alpha): + data += d + + elif self._alpha_encoding == AlphaEncoding.DXT3: + linesize = (self.state.xsize + 3) // 4 * 16 + for yb in range((self.state.ysize + 3) // 4): + for d in decode_dxt3(self._safe_read(linesize)): + data += d + + elif self._alpha_encoding == AlphaEncoding.DXT5: + linesize = (self.state.xsize + 3) // 4 * 16 + for yb in range((self.state.ysize + 3) // 4): + for d in decode_dxt5(self._safe_read(linesize)): + data += d + else: + msg = f"Unsupported alpha encoding {repr(self._alpha_encoding)}" + raise BLPFormatError(msg) + else: + msg = f"Unknown BLP encoding {repr(self._encoding)}" + raise BLPFormatError(msg) + + else: + msg = f"Unknown BLP compression {repr(self._compression)}" + raise BLPFormatError(msg) + + self.set_as_raw(data) + + +class BLPEncoder(ImageFile.PyEncoder): + _pushes_fd = True + + def _write_palette(self) -> bytes: + data = b"" + assert self.im is not None + palette = self.im.getpalette("RGBA", "RGBA") + for i in range(len(palette) // 4): + r, g, b, a = palette[i * 4 : (i + 1) * 4] + data += struct.pack("<4B", b, g, r, a) + while len(data) < 256 * 4: + data += b"\x00" * 4 + return data + + def encode(self, bufsize: int) -> tuple[int, int, bytes]: + palette_data = self._write_palette() + + offset = 20 + 16 * 4 * 2 + len(palette_data) + data = struct.pack("<16I", offset, *((0,) * 15)) + + assert self.im is not None + w, h = self.im.size + data += struct.pack("<16I", w * h, *((0,) * 15)) + + data += palette_data + + for y in range(h): + for x in range(w): + data += struct.pack(" None: + if im.mode != "P": + msg = "Unsupported BLP image mode" + raise ValueError(msg) + + magic = b"BLP1" if im.encoderinfo.get("blp_version") == "BLP1" else b"BLP2" + fp.write(magic) + + assert im.palette is not None + fp.write(struct.pack(" mode, rawmode + 1: ("P", "P;1"), + 4: ("P", "P;4"), + 8: ("P", "P"), + 16: ("RGB", "BGR;15"), + 24: ("RGB", "BGR"), + 32: ("RGB", "BGRX"), +} + +USE_RAW_ALPHA = False + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith(b"BM") + + +def _dib_accept(prefix: bytes) -> bool: + return i32(prefix) in [12, 40, 52, 56, 64, 108, 124] + + +# ============================================================================= +# Image plugin for the Windows BMP format. +# ============================================================================= +class BmpImageFile(ImageFile.ImageFile): + """Image plugin for the Windows Bitmap format (BMP)""" + + # ------------------------------------------------------------- Description + format_description = "Windows Bitmap" + format = "BMP" + + # -------------------------------------------------- BMP Compression values + COMPRESSIONS = {"RAW": 0, "RLE8": 1, "RLE4": 2, "BITFIELDS": 3, "JPEG": 4, "PNG": 5} + for k, v in COMPRESSIONS.items(): + vars()[k] = v + + def _bitmap(self, header: int = 0, offset: int = 0) -> None: + """Read relevant info about the BMP""" + assert self.fp is not None + read, seek = self.fp.read, self.fp.seek + if header: + seek(header) + # read bmp header size @offset 14 (this is part of the header size) + file_info: dict[str, bool | int | tuple[int, ...]] = { + "header_size": i32(read(4)), + "direction": -1, + } + + # -------------------- If requested, read header at a specific position + # read the rest of the bmp header, without its size + assert isinstance(file_info["header_size"], int) + header_data = ImageFile._safe_read(self.fp, file_info["header_size"] - 4) + + # ------------------------------- Windows Bitmap v2, IBM OS/2 Bitmap v1 + # ----- This format has different offsets because of width/height types + # 12: BITMAPCOREHEADER/OS21XBITMAPHEADER + if file_info["header_size"] == 12: + file_info["width"] = i16(header_data, 0) + file_info["height"] = i16(header_data, 2) + file_info["planes"] = i16(header_data, 4) + file_info["bits"] = i16(header_data, 6) + file_info["compression"] = self.COMPRESSIONS["RAW"] + file_info["palette_padding"] = 3 + + # --------------------------------------------- Windows Bitmap v3 to v5 + # 40: BITMAPINFOHEADER + # 52: BITMAPV2HEADER + # 56: BITMAPV3HEADER + # 64: BITMAPCOREHEADER2/OS22XBITMAPHEADER + # 108: BITMAPV4HEADER + # 124: BITMAPV5HEADER + elif file_info["header_size"] in (40, 52, 56, 64, 108, 124): + file_info["y_flip"] = header_data[7] == 0xFF + file_info["direction"] = 1 if file_info["y_flip"] else -1 + file_info["width"] = i32(header_data, 0) + file_info["height"] = ( + i32(header_data, 4) + if not file_info["y_flip"] + else 2**32 - i32(header_data, 4) + ) + file_info["planes"] = i16(header_data, 8) + file_info["bits"] = i16(header_data, 10) + file_info["compression"] = i32(header_data, 12) + # byte size of pixel data + file_info["data_size"] = i32(header_data, 16) + file_info["pixels_per_meter"] = ( + i32(header_data, 20), + i32(header_data, 24), + ) + file_info["colors"] = i32(header_data, 28) + file_info["palette_padding"] = 4 + assert isinstance(file_info["pixels_per_meter"], tuple) + self.info["dpi"] = tuple(x / 39.3701 for x in file_info["pixels_per_meter"]) + if file_info["compression"] == self.COMPRESSIONS["BITFIELDS"]: + masks = ["r_mask", "g_mask", "b_mask"] + if len(header_data) >= 48: + if len(header_data) >= 52: + masks.append("a_mask") + else: + file_info["a_mask"] = 0x0 + for idx, mask in enumerate(masks): + file_info[mask] = i32(header_data, 36 + idx * 4) + else: + # 40 byte headers only have the three components in the + # bitfields masks, ref: + # https://msdn.microsoft.com/en-us/library/windows/desktop/dd183376(v=vs.85).aspx + # See also + # https://github.com/python-pillow/Pillow/issues/1293 + # There is a 4th component in the RGBQuad, in the alpha + # location, but it is listed as a reserved component, + # and it is not generally an alpha channel + file_info["a_mask"] = 0x0 + for mask in masks: + file_info[mask] = i32(read(4)) + assert isinstance(file_info["r_mask"], int) + assert isinstance(file_info["g_mask"], int) + assert isinstance(file_info["b_mask"], int) + assert isinstance(file_info["a_mask"], int) + file_info["rgb_mask"] = ( + file_info["r_mask"], + file_info["g_mask"], + file_info["b_mask"], + ) + file_info["rgba_mask"] = ( + file_info["r_mask"], + file_info["g_mask"], + file_info["b_mask"], + file_info["a_mask"], + ) + else: + msg = f"Unsupported BMP header type ({file_info['header_size']})" + raise OSError(msg) + + # ------------------ Special case : header is reported 40, which + # ---------------------- is shorter than real size for bpp >= 16 + assert isinstance(file_info["width"], int) + assert isinstance(file_info["height"], int) + self._size = file_info["width"], file_info["height"] + + # ------- If color count was not found in the header, compute from bits + assert isinstance(file_info["bits"], int) + file_info["colors"] = ( + file_info["colors"] + if file_info.get("colors", 0) + else (1 << file_info["bits"]) + ) + assert isinstance(file_info["colors"], int) + if offset == 14 + file_info["header_size"] and file_info["bits"] <= 8: + offset += 4 * file_info["colors"] + + # ---------------------- Check bit depth for unusual unsupported values + self._mode, raw_mode = BIT2MODE.get(file_info["bits"], ("", "")) + if not self.mode: + msg = f"Unsupported BMP pixel depth ({file_info['bits']})" + raise OSError(msg) + + # ---------------- Process BMP with Bitfields compression (not palette) + decoder_name = "raw" + if file_info["compression"] == self.COMPRESSIONS["BITFIELDS"]: + SUPPORTED: dict[int, list[tuple[int, ...]]] = { + 32: [ + (0xFF0000, 0xFF00, 0xFF, 0x0), + (0xFF000000, 0xFF0000, 0xFF00, 0x0), + (0xFF000000, 0xFF00, 0xFF, 0x0), + (0xFF000000, 0xFF0000, 0xFF00, 0xFF), + (0xFF, 0xFF00, 0xFF0000, 0xFF000000), + (0xFF0000, 0xFF00, 0xFF, 0xFF000000), + (0xFF000000, 0xFF00, 0xFF, 0xFF0000), + (0x0, 0x0, 0x0, 0x0), + ], + 24: [(0xFF0000, 0xFF00, 0xFF)], + 16: [(0xF800, 0x7E0, 0x1F), (0x7C00, 0x3E0, 0x1F)], + } + MASK_MODES = { + (32, (0xFF0000, 0xFF00, 0xFF, 0x0)): "BGRX", + (32, (0xFF000000, 0xFF0000, 0xFF00, 0x0)): "XBGR", + (32, (0xFF000000, 0xFF00, 0xFF, 0x0)): "BGXR", + (32, (0xFF000000, 0xFF0000, 0xFF00, 0xFF)): "ABGR", + (32, (0xFF, 0xFF00, 0xFF0000, 0xFF000000)): "RGBA", + (32, (0xFF0000, 0xFF00, 0xFF, 0xFF000000)): "BGRA", + (32, (0xFF000000, 0xFF00, 0xFF, 0xFF0000)): "BGAR", + (32, (0x0, 0x0, 0x0, 0x0)): "BGRA", + (24, (0xFF0000, 0xFF00, 0xFF)): "BGR", + (16, (0xF800, 0x7E0, 0x1F)): "BGR;16", + (16, (0x7C00, 0x3E0, 0x1F)): "BGR;15", + } + if file_info["bits"] in SUPPORTED: + if ( + file_info["bits"] == 32 + and file_info["rgba_mask"] in SUPPORTED[file_info["bits"]] + ): + assert isinstance(file_info["rgba_mask"], tuple) + raw_mode = MASK_MODES[(file_info["bits"], file_info["rgba_mask"])] + self._mode = "RGBA" if "A" in raw_mode else self.mode + elif ( + file_info["bits"] in (24, 16) + and file_info["rgb_mask"] in SUPPORTED[file_info["bits"]] + ): + assert isinstance(file_info["rgb_mask"], tuple) + raw_mode = MASK_MODES[(file_info["bits"], file_info["rgb_mask"])] + else: + msg = "Unsupported BMP bitfields layout" + raise OSError(msg) + else: + msg = "Unsupported BMP bitfields layout" + raise OSError(msg) + elif file_info["compression"] == self.COMPRESSIONS["RAW"]: + if file_info["bits"] == 32 and ( + header == 22 or USE_RAW_ALPHA # 32-bit .cur offset + ): + raw_mode, self._mode = "BGRA", "RGBA" + elif file_info["compression"] in ( + self.COMPRESSIONS["RLE8"], + self.COMPRESSIONS["RLE4"], + ): + decoder_name = "bmp_rle" + else: + msg = f"Unsupported BMP compression ({file_info['compression']})" + raise OSError(msg) + + # --------------- Once the header is processed, process the palette/LUT + if self.mode == "P": # Paletted for 1, 4 and 8 bit images + # ---------------------------------------------------- 1-bit images + if not (0 < file_info["colors"] <= 65536): + msg = f"Unsupported BMP Palette size ({file_info['colors']})" + raise OSError(msg) + else: + assert isinstance(file_info["palette_padding"], int) + padding = file_info["palette_padding"] + palette = read(padding * file_info["colors"]) + grayscale = True + indices = ( + (0, 255) + if file_info["colors"] == 2 + else list(range(file_info["colors"])) + ) + + # ----------------- Check if grayscale and ignore palette if so + for ind, val in enumerate(indices): + rgb = palette[ind * padding : ind * padding + 3] + if rgb != o8(val) * 3: + grayscale = False + + # ------- If all colors are gray, white or black, ditch palette + if grayscale: + self._mode = "1" if file_info["colors"] == 2 else "L" + raw_mode = self.mode + else: + self._mode = "P" + self.palette = ImagePalette.raw( + "BGRX" if padding == 4 else "BGR", palette + ) + + # ---------------------------- Finally set the tile data for the plugin + self.info["compression"] = file_info["compression"] + args: list[Any] = [raw_mode] + if decoder_name == "bmp_rle": + args.append(file_info["compression"] == self.COMPRESSIONS["RLE4"]) + else: + assert isinstance(file_info["width"], int) + args.append(((file_info["width"] * file_info["bits"] + 31) >> 3) & (~3)) + args.append(file_info["direction"]) + self.tile = [ + ImageFile._Tile( + decoder_name, + (0, 0, file_info["width"], file_info["height"]), + offset or self.fp.tell(), + tuple(args), + ) + ] + + def _open(self) -> None: + """Open file, check magic number and read header""" + # read 14 bytes: magic number, filesize, reserved, header final offset + assert self.fp is not None + head_data = self.fp.read(14) + # choke if the file does not have the required magic bytes + if not _accept(head_data): + msg = "Not a BMP file" + raise SyntaxError(msg) + # read the start position of the BMP image data (u32) + offset = i32(head_data, 10) + # load bitmap information (offset=raster info) + self._bitmap(offset=offset) + + +class BmpRleDecoder(ImageFile.PyDecoder): + _pulls_fd = True + + def decode(self, buffer: bytes | Image.SupportsArrayInterface) -> tuple[int, int]: + assert self.fd is not None + rle4 = self.args[1] + data = bytearray() + x = 0 + dest_length = self.state.xsize * self.state.ysize + while len(data) < dest_length: + pixels = self.fd.read(1) + byte = self.fd.read(1) + if not pixels or not byte: + break + num_pixels = pixels[0] + if num_pixels: + # encoded mode + if x + num_pixels > self.state.xsize: + # Too much data for row + num_pixels = max(0, self.state.xsize - x) + if rle4: + first_pixel = o8(byte[0] >> 4) + second_pixel = o8(byte[0] & 0x0F) + for index in range(num_pixels): + if index % 2 == 0: + data += first_pixel + else: + data += second_pixel + else: + data += byte * num_pixels + x += num_pixels + else: + if byte[0] == 0: + # end of line + while len(data) % self.state.xsize != 0: + data += b"\x00" + x = 0 + elif byte[0] == 1: + # end of bitmap + break + elif byte[0] == 2: + # delta + bytes_read = self.fd.read(2) + if len(bytes_read) < 2: + break + right, up = self.fd.read(2) + data += b"\x00" * (right + up * self.state.xsize) + x = len(data) % self.state.xsize + else: + # absolute mode + if rle4: + # 2 pixels per byte + byte_count = byte[0] // 2 + bytes_read = self.fd.read(byte_count) + for byte_read in bytes_read: + data += o8(byte_read >> 4) + data += o8(byte_read & 0x0F) + else: + byte_count = byte[0] + bytes_read = self.fd.read(byte_count) + data += bytes_read + if len(bytes_read) < byte_count: + break + x += byte[0] + + # align to 16-bit word boundary + if self.fd.tell() % 2 != 0: + self.fd.seek(1, os.SEEK_CUR) + rawmode = "L" if self.mode == "L" else "P" + self.set_as_raw(bytes(data), rawmode, (0, self.args[-1])) + return -1, 0 + + +# ============================================================================= +# Image plugin for the DIB format (BMP alias) +# ============================================================================= +class DibImageFile(BmpImageFile): + format = "DIB" + format_description = "Windows Bitmap" + + def _open(self) -> None: + self._bitmap() + + +# +# -------------------------------------------------------------------- +# Write BMP file + + +SAVE = { + "1": ("1", 1, 2), + "L": ("L", 8, 256), + "P": ("P", 8, 256), + "RGB": ("BGR", 24, 0), + "RGBA": ("BGRA", 32, 0), +} + + +def _dib_save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + _save(im, fp, filename, False) + + +def _save( + im: Image.Image, fp: IO[bytes], filename: str | bytes, bitmap_header: bool = True +) -> None: + try: + rawmode, bits, colors = SAVE[im.mode] + except KeyError as e: + msg = f"cannot write mode {im.mode} as BMP" + raise OSError(msg) from e + + info = im.encoderinfo + + dpi = info.get("dpi", (96, 96)) + + # 1 meter == 39.3701 inches + ppm = tuple(int(x * 39.3701 + 0.5) for x in dpi) + + stride = ((im.size[0] * bits + 7) // 8 + 3) & (~3) + header = 40 # or 64 for OS/2 version 2 + image = stride * im.size[1] + + if im.mode == "1": + palette = b"".join(o8(i) * 3 + b"\x00" for i in (0, 255)) + elif im.mode == "L": + palette = b"".join(o8(i) * 3 + b"\x00" for i in range(256)) + elif im.mode == "P": + palette = im.im.getpalette("RGB", "BGRX") + colors = len(palette) // 4 + else: + palette = None + + # bitmap header + if bitmap_header: + offset = 14 + header + colors * 4 + file_size = offset + image + if file_size > 2**32 - 1: + msg = "File size is too large for the BMP format" + raise ValueError(msg) + fp.write( + b"BM" # file type (magic) + + o32(file_size) # file size + + o32(0) # reserved + + o32(offset) # image data offset + ) + + # bitmap info header + fp.write( + o32(header) # info header size + + o32(im.size[0]) # width + + o32(im.size[1]) # height + + o16(1) # planes + + o16(bits) # depth + + o32(0) # compression (0=uncompressed) + + o32(image) # size of bitmap + + o32(ppm[0]) # resolution + + o32(ppm[1]) # resolution + + o32(colors) # colors used + + o32(colors) # colors important + ) + + fp.write(b"\0" * (header - 40)) # padding (for OS/2 format) + + if palette: + fp.write(palette) + + ImageFile._save( + im, fp, [ImageFile._Tile("raw", (0, 0) + im.size, 0, (rawmode, stride, -1))] + ) + + +# +# -------------------------------------------------------------------- +# Registry + + +Image.register_open(BmpImageFile.format, BmpImageFile, _accept) +Image.register_save(BmpImageFile.format, _save) + +Image.register_extension(BmpImageFile.format, ".bmp") + +Image.register_mime(BmpImageFile.format, "image/bmp") + +Image.register_decoder("bmp_rle", BmpRleDecoder) + +Image.register_open(DibImageFile.format, DibImageFile, _dib_accept) +Image.register_save(DibImageFile.format, _dib_save) + +Image.register_extension(DibImageFile.format, ".dib") + +Image.register_mime(DibImageFile.format, "image/bmp") diff --git a/PIL/ContainerIO.py b/PIL/ContainerIO.py new file mode 100644 index 0000000000000000000000000000000000000000..ec9e66c714fbbfec8c597f6127e5d932b0da521f --- /dev/null +++ b/PIL/ContainerIO.py @@ -0,0 +1,173 @@ +# +# The Python Imaging Library. +# $Id$ +# +# a class to read from a container file +# +# History: +# 1995-06-18 fl Created +# 1995-09-07 fl Added readline(), readlines() +# +# Copyright (c) 1997-2001 by Secret Labs AB +# Copyright (c) 1995 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import io +from collections.abc import Iterable +from typing import IO, AnyStr, NoReturn + + +class ContainerIO(IO[AnyStr]): + """ + A file object that provides read access to a part of an existing + file (for example a TAR file). + """ + + def __init__(self, file: IO[AnyStr], offset: int, length: int) -> None: + """ + Create file object. + + :param file: Existing file. + :param offset: Start of region, in bytes. + :param length: Size of region, in bytes. + """ + self.fh: IO[AnyStr] = file + self.pos = 0 + self.offset = offset + self.length = length + self.fh.seek(offset) + + ## + # Always false. + + def isatty(self) -> bool: + return False + + def seekable(self) -> bool: + return True + + def seek(self, offset: int, mode: int = io.SEEK_SET) -> int: + """ + Move file pointer. + + :param offset: Offset in bytes. + :param mode: Starting position. Use 0 for beginning of region, 1 + for current offset, and 2 for end of region. You cannot move + the pointer outside the defined region. + :returns: Offset from start of region, in bytes. + """ + if mode == 1: + self.pos = self.pos + offset + elif mode == 2: + self.pos = self.length + offset + else: + self.pos = offset + # clamp + self.pos = max(0, min(self.pos, self.length)) + self.fh.seek(self.offset + self.pos) + return self.pos + + def tell(self) -> int: + """ + Get current file pointer. + + :returns: Offset from start of region, in bytes. + """ + return self.pos + + def readable(self) -> bool: + return True + + def read(self, n: int = -1) -> AnyStr: + """ + Read data. + + :param n: Number of bytes to read. If omitted, zero or negative, + read until end of region. + :returns: An 8-bit string. + """ + if n > 0: + n = min(n, self.length - self.pos) + else: + n = self.length - self.pos + if n <= 0: # EOF + return b"" if "b" in self.fh.mode else "" # type: ignore[return-value] + self.pos = self.pos + n + return self.fh.read(n) + + def readline(self, n: int = -1) -> AnyStr: + """ + Read a line of text. + + :param n: Number of bytes to read. If omitted, zero or negative, + read until end of line. + :returns: An 8-bit string. + """ + s: AnyStr = b"" if "b" in self.fh.mode else "" # type: ignore[assignment] + newline_character = b"\n" if "b" in self.fh.mode else "\n" + while True: + c = self.read(1) + if not c: + break + s = s + c + if c == newline_character or len(s) == n: + break + return s + + def readlines(self, n: int | None = -1) -> list[AnyStr]: + """ + Read multiple lines of text. + + :param n: Number of lines to read. If omitted, zero, negative or None, + read until end of region. + :returns: A list of 8-bit strings. + """ + lines = [] + while True: + s = self.readline() + if not s: + break + lines.append(s) + if len(lines) == n: + break + return lines + + def writable(self) -> bool: + return False + + def write(self, b: AnyStr) -> NoReturn: + raise NotImplementedError() + + def writelines(self, lines: Iterable[AnyStr]) -> NoReturn: + raise NotImplementedError() + + def truncate(self, size: int | None = None) -> int: + raise NotImplementedError() + + def __enter__(self) -> ContainerIO[AnyStr]: + return self + + def __exit__(self, *args: object) -> None: + self.close() + + def __iter__(self) -> ContainerIO[AnyStr]: + return self + + def __next__(self) -> AnyStr: + line = self.readline() + if not line: + msg = "end of region" + raise StopIteration(msg) + return line + + def fileno(self) -> int: + return self.fh.fileno() + + def flush(self) -> None: + self.fh.flush() + + def close(self) -> None: + self.fh.close() diff --git a/PIL/CurImagePlugin.py b/PIL/CurImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..9c188e084463dd0607934196ff9ad0dd1e51b210 --- /dev/null +++ b/PIL/CurImagePlugin.py @@ -0,0 +1,75 @@ +# +# The Python Imaging Library. +# $Id$ +# +# Windows Cursor support for PIL +# +# notes: +# uses BmpImagePlugin.py to read the bitmap data. +# +# history: +# 96-05-27 fl Created +# +# Copyright (c) Secret Labs AB 1997. +# Copyright (c) Fredrik Lundh 1996. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +from . import BmpImagePlugin, Image +from ._binary import i16le as i16 +from ._binary import i32le as i32 + +# +# -------------------------------------------------------------------- + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith(b"\0\0\2\0") + + +## +# Image plugin for Windows Cursor files. + + +class CurImageFile(BmpImagePlugin.BmpImageFile): + format = "CUR" + format_description = "Windows Cursor" + + def _open(self) -> None: + assert self.fp is not None + offset = self.fp.tell() + + # check magic + s = self.fp.read(6) + if not _accept(s): + msg = "not a CUR file" + raise SyntaxError(msg) + + # pick the largest cursor in the file + m = b"" + for i in range(i16(s, 4)): + s = self.fp.read(16) + if not m: + m = s + elif s[0] > m[0] and s[1] > m[1]: + m = s + if not m: + msg = "No cursors were found" + raise TypeError(msg) + + # load as bitmap + self._bitmap(i32(m, 12) + offset) + + # patch up the bitmap height + self._size = self.size[0], self.size[1] // 2 + self.tile = [self.tile[0]._replace(extents=(0, 0) + self.size)] + + +# +# -------------------------------------------------------------------- + +Image.register_open(CurImageFile.format, CurImageFile, _accept) + +Image.register_extension(CurImageFile.format, ".cur") diff --git a/PIL/DcxImagePlugin.py b/PIL/DcxImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..d3f456ddcc4aabac81d53bfb3972b398bb2f86b1 --- /dev/null +++ b/PIL/DcxImagePlugin.py @@ -0,0 +1,84 @@ +# +# The Python Imaging Library. +# $Id$ +# +# DCX file handling +# +# DCX is a container file format defined by Intel, commonly used +# for fax applications. Each DCX file consists of a directory +# (a list of file offsets) followed by a set of (usually 1-bit) +# PCX files. +# +# History: +# 1995-09-09 fl Created +# 1996-03-20 fl Properly derived from PcxImageFile. +# 1998-07-15 fl Renamed offset attribute to avoid name clash +# 2002-07-30 fl Fixed file handling +# +# Copyright (c) 1997-98 by Secret Labs AB. +# Copyright (c) 1995-96 by Fredrik Lundh. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +from . import Image +from ._binary import i32le as i32 +from ._util import DeferredError +from .PcxImagePlugin import PcxImageFile + +MAGIC = 0x3ADE68B1 # QUIZ: what's this value, then? + + +def _accept(prefix: bytes) -> bool: + return len(prefix) >= 4 and i32(prefix) == MAGIC + + +## +# Image plugin for the Intel DCX format. + + +class DcxImageFile(PcxImageFile): + format = "DCX" + format_description = "Intel DCX" + _close_exclusive_fp_after_loading = False + + def _open(self) -> None: + # Header + assert self.fp is not None + s = self.fp.read(4) + if not _accept(s): + msg = "not a DCX file" + raise SyntaxError(msg) + + # Component directory + self._offset = [] + for i in range(1024): + offset = i32(self.fp.read(4)) + if not offset: + break + self._offset.append(offset) + + self._fp = self.fp + self.frame = -1 + self.n_frames = len(self._offset) + self.is_animated = self.n_frames > 1 + self.seek(0) + + def seek(self, frame: int) -> None: + if not self._seek_check(frame): + return + if isinstance(self._fp, DeferredError): + raise self._fp.ex + self.frame = frame + self.fp = self._fp + self.fp.seek(self._offset[frame]) + PcxImageFile._open(self) + + def tell(self) -> int: + return self.frame + + +Image.register_open(DcxImageFile.format, DcxImageFile, _accept) + +Image.register_extension(DcxImageFile.format, ".dcx") diff --git a/PIL/DdsImagePlugin.py b/PIL/DdsImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..312f602a6b18edfcd0826e44be7ef668b5e28804 --- /dev/null +++ b/PIL/DdsImagePlugin.py @@ -0,0 +1,625 @@ +""" +A Pillow plugin for .dds files (S3TC-compressed aka DXTC) +Jerome Leclanche + +Documentation: +https://web.archive.org/web/20170802060935/http://oss.sgi.com/projects/ogl-sample/registry/EXT/texture_compression_s3tc.txt + +The contents of this file are hereby released in the public domain (CC0) +Full text of the CC0 license: +https://creativecommons.org/publicdomain/zero/1.0/ +""" + +from __future__ import annotations + +import struct +import sys +from enum import IntEnum, IntFlag +from typing import IO + +from . import Image, ImageFile, ImagePalette +from ._binary import i32le as i32 +from ._binary import o8 +from ._binary import o32le as o32 + +# Magic ("DDS ") +DDS_MAGIC = 0x20534444 + + +# DDS flags +class DDSD(IntFlag): + CAPS = 0x1 + HEIGHT = 0x2 + WIDTH = 0x4 + PITCH = 0x8 + PIXELFORMAT = 0x1000 + MIPMAPCOUNT = 0x20000 + LINEARSIZE = 0x80000 + DEPTH = 0x800000 + + +# DDS caps +class DDSCAPS(IntFlag): + COMPLEX = 0x8 + TEXTURE = 0x1000 + MIPMAP = 0x400000 + + +class DDSCAPS2(IntFlag): + CUBEMAP = 0x200 + CUBEMAP_POSITIVEX = 0x400 + CUBEMAP_NEGATIVEX = 0x800 + CUBEMAP_POSITIVEY = 0x1000 + CUBEMAP_NEGATIVEY = 0x2000 + CUBEMAP_POSITIVEZ = 0x4000 + CUBEMAP_NEGATIVEZ = 0x8000 + VOLUME = 0x200000 + + +# Pixel Format +class DDPF(IntFlag): + ALPHAPIXELS = 0x1 + ALPHA = 0x2 + FOURCC = 0x4 + PALETTEINDEXED8 = 0x20 + RGB = 0x40 + LUMINANCE = 0x20000 + + +# dxgiformat.h +class DXGI_FORMAT(IntEnum): + UNKNOWN = 0 + R32G32B32A32_TYPELESS = 1 + R32G32B32A32_FLOAT = 2 + R32G32B32A32_UINT = 3 + R32G32B32A32_SINT = 4 + R32G32B32_TYPELESS = 5 + R32G32B32_FLOAT = 6 + R32G32B32_UINT = 7 + R32G32B32_SINT = 8 + R16G16B16A16_TYPELESS = 9 + R16G16B16A16_FLOAT = 10 + R16G16B16A16_UNORM = 11 + R16G16B16A16_UINT = 12 + R16G16B16A16_SNORM = 13 + R16G16B16A16_SINT = 14 + R32G32_TYPELESS = 15 + R32G32_FLOAT = 16 + R32G32_UINT = 17 + R32G32_SINT = 18 + R32G8X24_TYPELESS = 19 + D32_FLOAT_S8X24_UINT = 20 + R32_FLOAT_X8X24_TYPELESS = 21 + X32_TYPELESS_G8X24_UINT = 22 + R10G10B10A2_TYPELESS = 23 + R10G10B10A2_UNORM = 24 + R10G10B10A2_UINT = 25 + R11G11B10_FLOAT = 26 + R8G8B8A8_TYPELESS = 27 + R8G8B8A8_UNORM = 28 + R8G8B8A8_UNORM_SRGB = 29 + R8G8B8A8_UINT = 30 + R8G8B8A8_SNORM = 31 + R8G8B8A8_SINT = 32 + R16G16_TYPELESS = 33 + R16G16_FLOAT = 34 + R16G16_UNORM = 35 + R16G16_UINT = 36 + R16G16_SNORM = 37 + R16G16_SINT = 38 + R32_TYPELESS = 39 + D32_FLOAT = 40 + R32_FLOAT = 41 + R32_UINT = 42 + R32_SINT = 43 + R24G8_TYPELESS = 44 + D24_UNORM_S8_UINT = 45 + R24_UNORM_X8_TYPELESS = 46 + X24_TYPELESS_G8_UINT = 47 + R8G8_TYPELESS = 48 + R8G8_UNORM = 49 + R8G8_UINT = 50 + R8G8_SNORM = 51 + R8G8_SINT = 52 + R16_TYPELESS = 53 + R16_FLOAT = 54 + D16_UNORM = 55 + R16_UNORM = 56 + R16_UINT = 57 + R16_SNORM = 58 + R16_SINT = 59 + R8_TYPELESS = 60 + R8_UNORM = 61 + R8_UINT = 62 + R8_SNORM = 63 + R8_SINT = 64 + A8_UNORM = 65 + R1_UNORM = 66 + R9G9B9E5_SHAREDEXP = 67 + R8G8_B8G8_UNORM = 68 + G8R8_G8B8_UNORM = 69 + BC1_TYPELESS = 70 + BC1_UNORM = 71 + BC1_UNORM_SRGB = 72 + BC2_TYPELESS = 73 + BC2_UNORM = 74 + BC2_UNORM_SRGB = 75 + BC3_TYPELESS = 76 + BC3_UNORM = 77 + BC3_UNORM_SRGB = 78 + BC4_TYPELESS = 79 + BC4_UNORM = 80 + BC4_SNORM = 81 + BC5_TYPELESS = 82 + BC5_UNORM = 83 + BC5_SNORM = 84 + B5G6R5_UNORM = 85 + B5G5R5A1_UNORM = 86 + B8G8R8A8_UNORM = 87 + B8G8R8X8_UNORM = 88 + R10G10B10_XR_BIAS_A2_UNORM = 89 + B8G8R8A8_TYPELESS = 90 + B8G8R8A8_UNORM_SRGB = 91 + B8G8R8X8_TYPELESS = 92 + B8G8R8X8_UNORM_SRGB = 93 + BC6H_TYPELESS = 94 + BC6H_UF16 = 95 + BC6H_SF16 = 96 + BC7_TYPELESS = 97 + BC7_UNORM = 98 + BC7_UNORM_SRGB = 99 + AYUV = 100 + Y410 = 101 + Y416 = 102 + NV12 = 103 + P010 = 104 + P016 = 105 + OPAQUE_420 = 106 + YUY2 = 107 + Y210 = 108 + Y216 = 109 + NV11 = 110 + AI44 = 111 + IA44 = 112 + P8 = 113 + A8P8 = 114 + B4G4R4A4_UNORM = 115 + P208 = 130 + V208 = 131 + V408 = 132 + SAMPLER_FEEDBACK_MIN_MIP_OPAQUE = 189 + SAMPLER_FEEDBACK_MIP_REGION_USED_OPAQUE = 190 + + +class D3DFMT(IntEnum): + UNKNOWN = 0 + R8G8B8 = 20 + A8R8G8B8 = 21 + X8R8G8B8 = 22 + R5G6B5 = 23 + X1R5G5B5 = 24 + A1R5G5B5 = 25 + A4R4G4B4 = 26 + R3G3B2 = 27 + A8 = 28 + A8R3G3B2 = 29 + X4R4G4B4 = 30 + A2B10G10R10 = 31 + A8B8G8R8 = 32 + X8B8G8R8 = 33 + G16R16 = 34 + A2R10G10B10 = 35 + A16B16G16R16 = 36 + A8P8 = 40 + P8 = 41 + L8 = 50 + A8L8 = 51 + A4L4 = 52 + V8U8 = 60 + L6V5U5 = 61 + X8L8V8U8 = 62 + Q8W8V8U8 = 63 + V16U16 = 64 + A2W10V10U10 = 67 + D16_LOCKABLE = 70 + D32 = 71 + D15S1 = 73 + D24S8 = 75 + D24X8 = 77 + D24X4S4 = 79 + D16 = 80 + D32F_LOCKABLE = 82 + D24FS8 = 83 + D32_LOCKABLE = 84 + S8_LOCKABLE = 85 + L16 = 81 + VERTEXDATA = 100 + INDEX16 = 101 + INDEX32 = 102 + Q16W16V16U16 = 110 + R16F = 111 + G16R16F = 112 + A16B16G16R16F = 113 + R32F = 114 + G32R32F = 115 + A32B32G32R32F = 116 + CxV8U8 = 117 + A1 = 118 + A2B10G10R10_XR_BIAS = 119 + BINARYBUFFER = 199 + + UYVY = i32(b"UYVY") + R8G8_B8G8 = i32(b"RGBG") + YUY2 = i32(b"YUY2") + G8R8_G8B8 = i32(b"GRGB") + DXT1 = i32(b"DXT1") + DXT2 = i32(b"DXT2") + DXT3 = i32(b"DXT3") + DXT4 = i32(b"DXT4") + DXT5 = i32(b"DXT5") + DX10 = i32(b"DX10") + BC4S = i32(b"BC4S") + BC4U = i32(b"BC4U") + BC5S = i32(b"BC5S") + BC5U = i32(b"BC5U") + ATI1 = i32(b"ATI1") + ATI2 = i32(b"ATI2") + MULTI2_ARGB8 = i32(b"MET1") + + +# Backward compatibility layer +module = sys.modules[__name__] +for item in DDSD: + assert item.name is not None + setattr(module, f"DDSD_{item.name}", item.value) +for item1 in DDSCAPS: + assert item1.name is not None + setattr(module, f"DDSCAPS_{item1.name}", item1.value) +for item2 in DDSCAPS2: + assert item2.name is not None + setattr(module, f"DDSCAPS2_{item2.name}", item2.value) +for item3 in DDPF: + assert item3.name is not None + setattr(module, f"DDPF_{item3.name}", item3.value) + +DDS_FOURCC = DDPF.FOURCC +DDS_RGB = DDPF.RGB +DDS_RGBA = DDPF.RGB | DDPF.ALPHAPIXELS +DDS_LUMINANCE = DDPF.LUMINANCE +DDS_LUMINANCEA = DDPF.LUMINANCE | DDPF.ALPHAPIXELS +DDS_ALPHA = DDPF.ALPHA +DDS_PAL8 = DDPF.PALETTEINDEXED8 + +DDS_HEADER_FLAGS_TEXTURE = DDSD.CAPS | DDSD.HEIGHT | DDSD.WIDTH | DDSD.PIXELFORMAT +DDS_HEADER_FLAGS_MIPMAP = DDSD.MIPMAPCOUNT +DDS_HEADER_FLAGS_VOLUME = DDSD.DEPTH +DDS_HEADER_FLAGS_PITCH = DDSD.PITCH +DDS_HEADER_FLAGS_LINEARSIZE = DDSD.LINEARSIZE + +DDS_HEIGHT = DDSD.HEIGHT +DDS_WIDTH = DDSD.WIDTH + +DDS_SURFACE_FLAGS_TEXTURE = DDSCAPS.TEXTURE +DDS_SURFACE_FLAGS_MIPMAP = DDSCAPS.COMPLEX | DDSCAPS.MIPMAP +DDS_SURFACE_FLAGS_CUBEMAP = DDSCAPS.COMPLEX + +DDS_CUBEMAP_POSITIVEX = DDSCAPS2.CUBEMAP | DDSCAPS2.CUBEMAP_POSITIVEX +DDS_CUBEMAP_NEGATIVEX = DDSCAPS2.CUBEMAP | DDSCAPS2.CUBEMAP_NEGATIVEX +DDS_CUBEMAP_POSITIVEY = DDSCAPS2.CUBEMAP | DDSCAPS2.CUBEMAP_POSITIVEY +DDS_CUBEMAP_NEGATIVEY = DDSCAPS2.CUBEMAP | DDSCAPS2.CUBEMAP_NEGATIVEY +DDS_CUBEMAP_POSITIVEZ = DDSCAPS2.CUBEMAP | DDSCAPS2.CUBEMAP_POSITIVEZ +DDS_CUBEMAP_NEGATIVEZ = DDSCAPS2.CUBEMAP | DDSCAPS2.CUBEMAP_NEGATIVEZ + +DXT1_FOURCC = D3DFMT.DXT1 +DXT3_FOURCC = D3DFMT.DXT3 +DXT5_FOURCC = D3DFMT.DXT5 + +DXGI_FORMAT_R8G8B8A8_TYPELESS = DXGI_FORMAT.R8G8B8A8_TYPELESS +DXGI_FORMAT_R8G8B8A8_UNORM = DXGI_FORMAT.R8G8B8A8_UNORM +DXGI_FORMAT_R8G8B8A8_UNORM_SRGB = DXGI_FORMAT.R8G8B8A8_UNORM_SRGB +DXGI_FORMAT_BC5_TYPELESS = DXGI_FORMAT.BC5_TYPELESS +DXGI_FORMAT_BC5_UNORM = DXGI_FORMAT.BC5_UNORM +DXGI_FORMAT_BC5_SNORM = DXGI_FORMAT.BC5_SNORM +DXGI_FORMAT_BC6H_UF16 = DXGI_FORMAT.BC6H_UF16 +DXGI_FORMAT_BC6H_SF16 = DXGI_FORMAT.BC6H_SF16 +DXGI_FORMAT_BC7_TYPELESS = DXGI_FORMAT.BC7_TYPELESS +DXGI_FORMAT_BC7_UNORM = DXGI_FORMAT.BC7_UNORM +DXGI_FORMAT_BC7_UNORM_SRGB = DXGI_FORMAT.BC7_UNORM_SRGB + + +class DdsImageFile(ImageFile.ImageFile): + format = "DDS" + format_description = "DirectDraw Surface" + + def _open(self) -> None: + assert self.fp is not None + if not _accept(self.fp.read(4)): + msg = "not a DDS file" + raise SyntaxError(msg) + (header_size,) = struct.unpack(" None: + pass + + +class DdsRgbDecoder(ImageFile.PyDecoder): + _pulls_fd = True + + def decode(self, buffer: bytes | Image.SupportsArrayInterface) -> tuple[int, int]: + assert self.fd is not None + bitcount, masks = self.args + + # Some masks will be padded with zeros, e.g. R 0b11 G 0b1100 + # Calculate how many zeros each mask is padded with + mask_offsets = [] + # And the maximum value of each channel without the padding + mask_totals = [] + for mask in masks: + offset = 0 + if mask != 0: + while mask >> (offset + 1) << (offset + 1) == mask: + offset += 1 + mask_offsets.append(offset) + mask_totals.append(mask >> offset) + + data = bytearray() + bytecount = bitcount // 8 + dest_length = self.state.xsize * self.state.ysize * len(masks) + while len(data) < dest_length: + value = int.from_bytes(self.fd.read(bytecount), "little") + for i, mask in enumerate(masks): + masked_value = value & mask + # Remove the zero padding, and scale it to 8 bits + data += o8( + int(((masked_value >> mask_offsets[i]) / mask_totals[i]) * 255) + if mask_totals[i] + else 0 + ) + self.set_as_raw(data) + return -1, 0 + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + if im.mode not in ("RGB", "RGBA", "L", "LA"): + msg = f"cannot write mode {im.mode} as DDS" + raise OSError(msg) + + flags = DDSD.CAPS | DDSD.HEIGHT | DDSD.WIDTH | DDSD.PIXELFORMAT + bitcount = len(im.getbands()) * 8 + pixel_format = im.encoderinfo.get("pixel_format") + args: tuple[int] | str + if pixel_format: + codec_name = "bcn" + flags |= DDSD.LINEARSIZE + pitch = (im.width + 3) * 4 + rgba_mask = [0, 0, 0, 0] + pixel_flags = DDPF.FOURCC + if pixel_format == "DXT1": + fourcc = D3DFMT.DXT1 + args = (1,) + elif pixel_format == "DXT3": + fourcc = D3DFMT.DXT3 + args = (2,) + elif pixel_format == "DXT5": + fourcc = D3DFMT.DXT5 + args = (3,) + else: + fourcc = D3DFMT.DX10 + if pixel_format == "BC2": + args = (2,) + dxgi_format = DXGI_FORMAT.BC2_TYPELESS + elif pixel_format == "BC3": + args = (3,) + dxgi_format = DXGI_FORMAT.BC3_TYPELESS + elif pixel_format == "BC5": + args = (5,) + dxgi_format = DXGI_FORMAT.BC5_TYPELESS + if im.mode != "RGB": + msg = "only RGB mode can be written as BC5" + raise OSError(msg) + else: + msg = f"cannot write pixel format {pixel_format}" + raise OSError(msg) + else: + codec_name = "raw" + flags |= DDSD.PITCH + pitch = (im.width * bitcount + 7) // 8 + + alpha = im.mode[-1] == "A" + if im.mode[0] == "L": + pixel_flags = DDPF.LUMINANCE + args = im.mode + if alpha: + rgba_mask = [0x000000FF, 0x000000FF, 0x000000FF] + else: + rgba_mask = [0xFF000000, 0xFF000000, 0xFF000000] + else: + pixel_flags = DDPF.RGB + args = im.mode[::-1] + rgba_mask = [0x00FF0000, 0x0000FF00, 0x000000FF] + + if alpha: + r, g, b, a = im.split() + im = Image.merge("RGBA", (a, r, g, b)) + if alpha: + pixel_flags |= DDPF.ALPHAPIXELS + rgba_mask.append(0xFF000000 if alpha else 0) + + fourcc = D3DFMT.UNKNOWN + fp.write( + o32(DDS_MAGIC) + + struct.pack( + "<7I", + 124, # header size + flags, # flags + im.height, + im.width, + pitch, + 0, # depth + 0, # mipmaps + ) + + struct.pack("11I", *((0,) * 11)) # reserved + # pfsize, pfflags, fourcc, bitcount + + struct.pack("<4I", 32, pixel_flags, fourcc, bitcount) + + struct.pack("<4I", *rgba_mask) # dwRGBABitMask + + struct.pack("<5I", DDSCAPS.TEXTURE, 0, 0, 0, 0) + ) + if fourcc == D3DFMT.DX10: + fp.write( + # dxgi_format, 2D resource, misc, array size, straight alpha + struct.pack("<5I", dxgi_format, 3, 0, 0, 1) + ) + ImageFile._save(im, fp, [ImageFile._Tile(codec_name, (0, 0) + im.size, 0, args)]) + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith(b"DDS ") + + +Image.register_open(DdsImageFile.format, DdsImageFile, _accept) +Image.register_decoder("dds_rgb", DdsRgbDecoder) +Image.register_save(DdsImageFile.format, _save) +Image.register_extension(DdsImageFile.format, ".dds") diff --git a/PIL/EpsImagePlugin.py b/PIL/EpsImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..2effb816cfb0ab4b26c08fa082cea4fadab607c7 --- /dev/null +++ b/PIL/EpsImagePlugin.py @@ -0,0 +1,481 @@ +# +# The Python Imaging Library. +# $Id$ +# +# EPS file handling +# +# History: +# 1995-09-01 fl Created (0.1) +# 1996-05-18 fl Don't choke on "atend" fields, Ghostscript interface (0.2) +# 1996-08-22 fl Don't choke on floating point BoundingBox values +# 1996-08-23 fl Handle files from Macintosh (0.3) +# 2001-02-17 fl Use 're' instead of 'regex' (Python 2.1) (0.4) +# 2003-09-07 fl Check gs.close status (from Federico Di Gregorio) (0.5) +# 2014-05-07 e Handling of EPS with binary preview and fixed resolution +# resizing +# +# Copyright (c) 1997-2003 by Secret Labs AB. +# Copyright (c) 1995-2003 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import io +import os +import re +import subprocess +import sys +import tempfile +from typing import IO + +from . import Image, ImageFile +from ._binary import i32le as i32 + +# -------------------------------------------------------------------- + + +split = re.compile(r"^%%([^:]*):[ \t]*(.*)[ \t]*$") +field = re.compile(r"^%[%!\w]([^:]*)[ \t]*$") + +gs_binary: str | bool | None = None +gs_windows_binary = None + + +def has_ghostscript() -> bool: + global gs_binary, gs_windows_binary + if gs_binary is None: + if sys.platform.startswith("win"): + if gs_windows_binary is None: + import shutil + + for binary in ("gswin32c", "gswin64c", "gs"): + if shutil.which(binary) is not None: + gs_windows_binary = binary + break + else: + gs_windows_binary = False + gs_binary = gs_windows_binary + else: + try: + subprocess.check_call(["gs", "--version"], stdout=subprocess.DEVNULL) + gs_binary = "gs" + except OSError: + gs_binary = False + return gs_binary is not False + + +def Ghostscript( + tile: list[ImageFile._Tile], + size: tuple[int, int], + fp: IO[bytes], + scale: int = 1, + transparency: bool = False, +) -> Image.core.ImagingCore: + """Render an image using Ghostscript""" + global gs_binary + if not has_ghostscript(): + msg = "Unable to locate Ghostscript on paths" + raise OSError(msg) + assert isinstance(gs_binary, str) + + # Unpack decoder tile + args = tile[0].args + assert isinstance(args, tuple) + length, bbox = args + + # Hack to support hi-res rendering + scale = int(scale) or 1 + width = size[0] * scale + height = size[1] * scale + # resolution is dependent on bbox and size + res_x = 72.0 * width / (bbox[2] - bbox[0]) + res_y = 72.0 * height / (bbox[3] - bbox[1]) + + out_fd, outfile = tempfile.mkstemp() + os.close(out_fd) + + infile_temp = None + if hasattr(fp, "name") and os.path.exists(fp.name): + infile = fp.name + else: + in_fd, infile_temp = tempfile.mkstemp() + os.close(in_fd) + infile = infile_temp + + # Ignore length and offset! + # Ghostscript can read it + # Copy whole file to read in Ghostscript + with open(infile_temp, "wb") as f: + # fetch length of fp + fp.seek(0, io.SEEK_END) + fsize = fp.tell() + # ensure start position + # go back + fp.seek(0) + lengthfile = fsize + while lengthfile > 0: + s = fp.read(min(lengthfile, 100 * 1024)) + if not s: + break + lengthfile -= len(s) + f.write(s) + + if transparency: + # "RGBA" + device = "pngalpha" + else: + # "pnmraw" automatically chooses between + # PBM ("1"), PGM ("L"), and PPM ("RGB"). + device = "pnmraw" + + # Build Ghostscript command + command = [ + gs_binary, + "-q", # quiet mode + f"-g{width:d}x{height:d}", # set output geometry (pixels) + f"-r{res_x:f}x{res_y:f}", # set input DPI (dots per inch) + "-dBATCH", # exit after processing + "-dNOPAUSE", # don't pause between pages + "-dSAFER", # safe mode + f"-sDEVICE={device}", + f"-sOutputFile={outfile}", # output file + # adjust for image origin + "-c", + f"{-bbox[0]} {-bbox[1]} translate", + "-f", + infile, # input file + # showpage (see https://bugs.ghostscript.com/show_bug.cgi?id=698272) + "-c", + "showpage", + ] + + # push data through Ghostscript + try: + startupinfo = None + if sys.platform.startswith("win"): + startupinfo = subprocess.STARTUPINFO() + startupinfo.dwFlags |= subprocess.STARTF_USESHOWWINDOW + subprocess.check_call(command, startupinfo=startupinfo) + with Image.open(outfile) as out_im: + out_im.load() + return out_im.im.copy() + finally: + try: + os.unlink(outfile) + if infile_temp: + os.unlink(infile_temp) + except OSError: + pass + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith(b"%!PS") or ( + len(prefix) >= 4 and i32(prefix) == 0xC6D3D0C5 + ) + + +## +# Image plugin for Encapsulated PostScript. This plugin supports only +# a few variants of this format. + + +class EpsImageFile(ImageFile.ImageFile): + """EPS File Parser for the Python Imaging Library""" + + format = "EPS" + format_description = "Encapsulated Postscript" + + mode_map = {1: "L", 2: "LAB", 3: "RGB", 4: "CMYK"} + + def _open(self) -> None: + assert self.fp is not None + (length, offset) = self._find_offset(self.fp) + + # go to offset - start of "%!PS" + self.fp.seek(offset) + + self._mode = "RGB" + + # When reading header comments, the first comment is used. + # When reading trailer comments, the last comment is used. + bounding_box: list[int] | None = None + imagedata_size: tuple[int, int] | None = None + + byte_arr = bytearray(255) + bytes_mv = memoryview(byte_arr) + bytes_read = 0 + reading_header_comments = True + reading_trailer_comments = False + trailer_reached = False + + def check_required_header_comments() -> None: + """ + The EPS specification requires that some headers exist. + This should be checked when the header comments formally end, + when image data starts, or when the file ends, whichever comes first. + """ + if "PS-Adobe" not in self.info: + msg = 'EPS header missing "%!PS-Adobe" comment' + raise SyntaxError(msg) + if "BoundingBox" not in self.info: + msg = 'EPS header missing "%%BoundingBox" comment' + raise SyntaxError(msg) + + def read_comment(s: str) -> bool: + nonlocal bounding_box, reading_trailer_comments + try: + m = split.match(s) + except re.error as e: + msg = "not an EPS file" + raise SyntaxError(msg) from e + + if not m: + return False + + k, v = m.group(1, 2) + self.info[k] = v + if k == "BoundingBox": + if v == "(atend)": + reading_trailer_comments = True + elif not bounding_box or (trailer_reached and reading_trailer_comments): + try: + # Note: The DSC spec says that BoundingBox + # fields should be integers, but some drivers + # put floating point values there anyway. + bounding_box = [int(float(i)) for i in v.split()] + except Exception: + pass + return True + + while True: + byte = self.fp.read(1) + if byte == b"": + # if we didn't read a byte we must be at the end of the file + if bytes_read == 0: + if reading_header_comments: + check_required_header_comments() + break + elif byte in b"\r\n": + # if we read a line ending character, ignore it and parse what + # we have already read. if we haven't read any other characters, + # continue reading + if bytes_read == 0: + continue + else: + # ASCII/hexadecimal lines in an EPS file must not exceed + # 255 characters, not including line ending characters + if bytes_read >= 255: + # only enforce this for lines starting with a "%", + # otherwise assume it's binary data + if byte_arr[0] == ord("%"): + msg = "not an EPS file" + raise SyntaxError(msg) + else: + if reading_header_comments: + check_required_header_comments() + reading_header_comments = False + # reset bytes_read so we can keep reading + # data until the end of the line + bytes_read = 0 + byte_arr[bytes_read] = byte[0] + bytes_read += 1 + continue + + if reading_header_comments: + # Load EPS header + + # if this line doesn't start with a "%", + # or does start with "%%EndComments", + # then we've reached the end of the header/comments + if byte_arr[0] != ord("%") or bytes_mv[:13] == b"%%EndComments": + check_required_header_comments() + reading_header_comments = False + continue + + s = str(bytes_mv[:bytes_read], "latin-1") + if not read_comment(s): + m = field.match(s) + if m: + k = m.group(1) + if k.startswith("PS-Adobe"): + self.info["PS-Adobe"] = k[9:] + else: + self.info[k] = "" + elif s[0] == "%": + # handle non-DSC PostScript comments that some + # tools mistakenly put in the Comments section + pass + else: + msg = "bad EPS header" + raise OSError(msg) + elif bytes_mv[:11] == b"%ImageData:": + # Check for an "ImageData" descriptor + # https://www.adobe.com/devnet-apps/photoshop/fileformatashtml/#50577413_pgfId-1035096 + + # If we've already read an "ImageData" descriptor, + # don't read another one. + if imagedata_size: + bytes_read = 0 + continue + + # Values: + # columns + # rows + # bit depth (1 or 8) + # mode (1: L, 2: LAB, 3: RGB, 4: CMYK) + # number of padding channels + # block size (number of bytes per row per channel) + # binary/ascii (1: binary, 2: ascii) + # data start identifier (the image data follows after a single line + # consisting only of this quoted value) + image_data_values = byte_arr[11:bytes_read].split(None, 7) + columns, rows, bit_depth, mode_id = ( + int(value) for value in image_data_values[:4] + ) + + if bit_depth == 1: + self._mode = "1" + elif bit_depth == 8: + try: + self._mode = self.mode_map[mode_id] + except ValueError: + break + else: + break + + # Parse the columns and rows after checking the bit depth and mode + # in case the bit depth and/or mode are invalid. + imagedata_size = columns, rows + elif bytes_mv[:5] == b"%%EOF": + break + elif trailer_reached and reading_trailer_comments: + # Load EPS trailer + s = str(bytes_mv[:bytes_read], "latin-1") + read_comment(s) + elif bytes_mv[:9] == b"%%Trailer": + trailer_reached = True + elif bytes_mv[:14] == b"%%BeginBinary:": + bytecount = int(byte_arr[14:bytes_read]) + self.fp.seek(bytecount, os.SEEK_CUR) + bytes_read = 0 + + # A "BoundingBox" is always required, + # even if an "ImageData" descriptor size exists. + if not bounding_box: + msg = "cannot determine EPS bounding box" + raise OSError(msg) + + # An "ImageData" size takes precedence over the "BoundingBox". + self._size = imagedata_size or ( + bounding_box[2] - bounding_box[0], + bounding_box[3] - bounding_box[1], + ) + + self.tile = [ + ImageFile._Tile("eps", (0, 0) + self.size, offset, (length, bounding_box)) + ] + + def _find_offset(self, fp: IO[bytes]) -> tuple[int, int]: + s = fp.read(4) + + if s == b"%!PS": + # for HEAD without binary preview + fp.seek(0, io.SEEK_END) + length = fp.tell() + offset = 0 + elif i32(s) == 0xC6D3D0C5: + # FIX for: Some EPS file not handled correctly / issue #302 + # EPS can contain binary data + # or start directly with latin coding + # more info see: + # https://web.archive.org/web/20160528181353/http://partners.adobe.com/public/developer/en/ps/5002.EPSF_Spec.pdf + s = fp.read(8) + offset = i32(s) + length = i32(s, 4) + else: + msg = "not an EPS file" + raise SyntaxError(msg) + + return length, offset + + def load( + self, scale: int = 1, transparency: bool = False + ) -> Image.core.PixelAccess | None: + # Load EPS via Ghostscript + if self.tile: + assert self.fp is not None + self.im = Ghostscript(self.tile, self.size, self.fp, scale, transparency) + self._mode = self.im.mode + self._size = self.im.size + self.tile = [] + return Image.Image.load(self) + + def load_seek(self, pos: int) -> None: + # we can't incrementally load, so force ImageFile.parser to + # use our custom load method by defining this method. + pass + + +# -------------------------------------------------------------------- + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes, eps: int = 1) -> None: + """EPS Writer for the Python Imaging Library.""" + + # make sure image data is available + im.load() + + # determine PostScript image mode + if im.mode == "L": + operator = (8, 1, b"image") + elif im.mode == "RGB": + operator = (8, 3, b"false 3 colorimage") + elif im.mode == "CMYK": + operator = (8, 4, b"false 4 colorimage") + else: + msg = "image mode is not supported" + raise ValueError(msg) + + if eps: + # write EPS header + fp.write(b"%!PS-Adobe-3.0 EPSF-3.0\n") + fp.write(b"%%Creator: PIL 0.1 EpsEncode\n") + # fp.write("%%CreationDate: %s"...) + fp.write(b"%%%%BoundingBox: 0 0 %d %d\n" % im.size) + fp.write(b"%%Pages: 1\n") + fp.write(b"%%EndComments\n") + fp.write(b"%%Page: 1 1\n") + fp.write(b"%%ImageData: %d %d " % im.size) + fp.write(b'%d %d 0 1 1 "%s"\n' % operator) + + # image header + fp.write(b"gsave\n") + fp.write(b"10 dict begin\n") + fp.write(b"/buf %d string def\n" % (im.size[0] * operator[1])) + fp.write(b"%d %d scale\n" % im.size) + fp.write(b"%d %d 8\n" % im.size) # <= bits + fp.write(b"[%d 0 0 -%d 0 %d]\n" % (im.size[0], im.size[1], im.size[1])) + fp.write(b"{ currentfile buf readhexstring pop } bind\n") + fp.write(operator[2] + b"\n") + if hasattr(fp, "flush"): + fp.flush() + + ImageFile._save(im, fp, [ImageFile._Tile("eps", (0, 0) + im.size)]) + + fp.write(b"\n%%%%EndBinary\n") + fp.write(b"grestore end\n") + if hasattr(fp, "flush"): + fp.flush() + + +# -------------------------------------------------------------------- + + +Image.register_open(EpsImageFile.format, EpsImageFile, _accept) + +Image.register_save(EpsImageFile.format, _save) + +Image.register_extensions(EpsImageFile.format, [".ps", ".eps"]) + +Image.register_mime(EpsImageFile.format, "application/postscript") diff --git a/PIL/FitsImagePlugin.py b/PIL/FitsImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..a3fdc0efeec6f7ec195112ded41d8ff1e248a6a0 --- /dev/null +++ b/PIL/FitsImagePlugin.py @@ -0,0 +1,152 @@ +# +# The Python Imaging Library +# $Id$ +# +# FITS file handling +# +# Copyright (c) 1998-2003 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import gzip +import math + +from . import Image, ImageFile + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith(b"SIMPLE") + + +class FitsImageFile(ImageFile.ImageFile): + format = "FITS" + format_description = "FITS" + + def _open(self) -> None: + assert self.fp is not None + + headers: dict[bytes, bytes] = {} + header_in_progress = False + decoder_name = "" + while True: + header = self.fp.read(80) + if not header: + msg = "Truncated FITS file" + raise OSError(msg) + keyword = header[:8].strip() + if keyword in (b"SIMPLE", b"XTENSION"): + header_in_progress = True + elif headers and not header_in_progress: + # This is now a data unit + break + elif keyword == b"END": + # Seek to the end of the header unit + self.fp.seek(math.ceil(self.fp.tell() / 2880) * 2880) + if not decoder_name: + decoder_name, offset, args = self._parse_headers(headers) + + header_in_progress = False + continue + + if decoder_name: + # Keep going to read past the headers + continue + + value = header[8:].split(b"/")[0].strip() + if value.startswith(b"="): + value = value[1:].strip() + if not headers and (not _accept(keyword) or value != b"T"): + msg = "Not a FITS file" + raise SyntaxError(msg) + headers[keyword] = value + + if not decoder_name: + msg = "No image data" + raise ValueError(msg) + + offset += self.fp.tell() - 80 + self.tile = [ImageFile._Tile(decoder_name, (0, 0) + self.size, offset, args)] + + def _get_size( + self, headers: dict[bytes, bytes], prefix: bytes + ) -> tuple[int, int] | None: + naxis = int(headers[prefix + b"NAXIS"]) + if naxis == 0: + return None + + if naxis == 1: + return 1, int(headers[prefix + b"NAXIS1"]) + else: + return int(headers[prefix + b"NAXIS1"]), int(headers[prefix + b"NAXIS2"]) + + def _parse_headers( + self, headers: dict[bytes, bytes] + ) -> tuple[str, int, tuple[str | int, ...]]: + prefix = b"" + decoder_name = "raw" + offset = 0 + if ( + headers.get(b"XTENSION") == b"'BINTABLE'" + and headers.get(b"ZIMAGE") == b"T" + and headers[b"ZCMPTYPE"] == b"'GZIP_1 '" + ): + no_prefix_size = self._get_size(headers, prefix) or (0, 0) + number_of_bits = int(headers[b"BITPIX"]) + offset = no_prefix_size[0] * no_prefix_size[1] * (number_of_bits // 8) + + prefix = b"Z" + decoder_name = "fits_gzip" + + size = self._get_size(headers, prefix) + if not size: + return "", 0, () + + self._size = size + + number_of_bits = int(headers[prefix + b"BITPIX"]) + if number_of_bits == 8: + self._mode = "L" + elif number_of_bits == 16: + self._mode = "I;16" + elif number_of_bits == 32: + self._mode = "I" + elif number_of_bits in (-32, -64): + self._mode = "F" + + args: tuple[str | int, ...] + if decoder_name == "raw": + args = (self.mode, 0, -1) + else: + args = (number_of_bits,) + return decoder_name, offset, args + + +class FitsGzipDecoder(ImageFile.PyDecoder): + _pulls_fd = True + + def decode(self, buffer: bytes | Image.SupportsArrayInterface) -> tuple[int, int]: + assert self.fd is not None + value = gzip.decompress(self.fd.read()) + + rows = [] + offset = 0 + number_of_bits = min(self.args[0] // 8, 4) + for y in range(self.state.ysize): + row = bytearray() + for x in range(self.state.xsize): + row += value[offset + (4 - number_of_bits) : offset + 4] + offset += 4 + rows.append(row) + self.set_as_raw(bytes([pixel for row in rows[::-1] for pixel in row])) + return -1, 0 + + +# -------------------------------------------------------------------- +# Registry + +Image.register_open(FitsImageFile.format, FitsImageFile, _accept) +Image.register_decoder("fits_gzip", FitsGzipDecoder) + +Image.register_extensions(FitsImageFile.format, [".fit", ".fits"]) diff --git a/PIL/FliImagePlugin.py b/PIL/FliImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..da1e8e95cf3263bb2e22ba45d6d2934fc4f2b54f --- /dev/null +++ b/PIL/FliImagePlugin.py @@ -0,0 +1,184 @@ +# +# The Python Imaging Library. +# $Id$ +# +# FLI/FLC file handling. +# +# History: +# 95-09-01 fl Created +# 97-01-03 fl Fixed parser, setup decoder tile +# 98-07-15 fl Renamed offset attribute to avoid name clash +# +# Copyright (c) Secret Labs AB 1997-98. +# Copyright (c) Fredrik Lundh 1995-97. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import os + +from . import Image, ImageFile, ImagePalette +from ._binary import i16le as i16 +from ._binary import i32le as i32 +from ._binary import o8 +from ._util import DeferredError + +# +# decoder + + +def _accept(prefix: bytes) -> bool: + return ( + len(prefix) >= 16 + and i16(prefix, 4) in [0xAF11, 0xAF12] + and i16(prefix, 14) in [0, 3] # flags + ) + + +## +# Image plugin for the FLI/FLC animation format. Use the seek +# method to load individual frames. + + +class FliImageFile(ImageFile.ImageFile): + format = "FLI" + format_description = "Autodesk FLI/FLC Animation" + _close_exclusive_fp_after_loading = False + + def _open(self) -> None: + # HEAD + assert self.fp is not None + s = self.fp.read(128) + if not ( + _accept(s) + and s[20:22] == b"\x00" * 2 + and s[42:80] == b"\x00" * 38 + and s[88:] == b"\x00" * 40 + ): + msg = "not an FLI/FLC file" + raise SyntaxError(msg) + + # frames + self.n_frames = i16(s, 6) + self.is_animated = self.n_frames > 1 + + # image characteristics + self._mode = "P" + self._size = i16(s, 8), i16(s, 10) + + # animation speed + duration = i32(s, 16) + magic = i16(s, 4) + if magic == 0xAF11: + duration = (duration * 1000) // 70 + self.info["duration"] = duration + + # look for palette + palette = [(a, a, a) for a in range(256)] + + s = self.fp.read(16) + + self.__offset = 128 + + if i16(s, 4) == 0xF100: + # prefix chunk; ignore it + self.fp.seek(self.__offset + i32(s)) + s = self.fp.read(16) + + if i16(s, 4) == 0xF1FA: + # look for palette chunk + number_of_subchunks = i16(s, 6) + chunk_size: int | None = None + for _ in range(number_of_subchunks): + if chunk_size is not None: + self.fp.seek(chunk_size - 6, os.SEEK_CUR) + s = self.fp.read(6) + chunk_type = i16(s, 4) + if chunk_type in (4, 11): + self._palette(palette, 2 if chunk_type == 11 else 0) + break + chunk_size = i32(s) + if not chunk_size: + break + + self.palette = ImagePalette.raw( + "RGB", b"".join(o8(r) + o8(g) + o8(b) for (r, g, b) in palette) + ) + + # set things up to decode first frame + self.__frame = -1 + self._fp = self.fp + self.__rewind = self.fp.tell() + self.seek(0) + + def _palette(self, palette: list[tuple[int, int, int]], shift: int) -> None: + # load palette + + i = 0 + assert self.fp is not None + for e in range(i16(self.fp.read(2))): + s = self.fp.read(2) + i = i + s[0] + n = s[1] + if n == 0: + n = 256 + s = self.fp.read(n * 3) + for n in range(0, len(s), 3): + r = s[n] << shift + g = s[n + 1] << shift + b = s[n + 2] << shift + palette[i] = (r, g, b) + i += 1 + + def seek(self, frame: int) -> None: + if not self._seek_check(frame): + return + if frame < self.__frame: + self._seek(0) + + for f in range(self.__frame + 1, frame + 1): + self._seek(f) + + def _seek(self, frame: int) -> None: + if isinstance(self._fp, DeferredError): + raise self._fp.ex + if frame == 0: + self.__frame = -1 + self._fp.seek(self.__rewind) + self.__offset = 128 + else: + # ensure that the previous frame was loaded + self.load() + + if frame != self.__frame + 1: + msg = f"cannot seek to frame {frame}" + raise ValueError(msg) + self.__frame = frame + + # move to next frame + self.fp = self._fp + self.fp.seek(self.__offset) + + s = self.fp.read(4) + if not s: + msg = "missing frame size" + raise EOFError(msg) + + framesize = i32(s) + + self.decodermaxblock = framesize + self.tile = [ImageFile._Tile("fli", (0, 0) + self.size, self.__offset)] + + self.__offset += framesize + + def tell(self) -> int: + return self.__frame + + +# +# registry + +Image.register_open(FliImageFile.format, FliImageFile, _accept) + +Image.register_extensions(FliImageFile.format, [".fli", ".flc"]) diff --git a/PIL/FtexImagePlugin.py b/PIL/FtexImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..e4d836cbdb27cc891f2cf62659eabcfaa37ffb70 --- /dev/null +++ b/PIL/FtexImagePlugin.py @@ -0,0 +1,115 @@ +""" +A Pillow loader for .ftc and .ftu files (FTEX) +Jerome Leclanche + +The contents of this file are hereby released in the public domain (CC0) +Full text of the CC0 license: + https://creativecommons.org/publicdomain/zero/1.0/ + +Independence War 2: Edge Of Chaos - Texture File Format - 16 October 2001 + +The textures used for 3D objects in Independence War 2: Edge Of Chaos are in a +packed custom format called FTEX. This file format uses file extensions FTC +and FTU. +* FTC files are compressed textures (using standard texture compression). +* FTU files are not compressed. +Texture File Format +The FTC and FTU texture files both use the same format. This +has the following structure: +{header} +{format_directory} +{data} +Where: +{header} = { + u32:magic, + u32:version, + u32:width, + u32:height, + u32:mipmap_count, + u32:format_count +} + +* The "magic" number is "FTEX". +* "width" and "height" are the dimensions of the texture. +* "mipmap_count" is the number of mipmaps in the texture. +* "format_count" is the number of texture formats (different versions of the +same texture) in this file. + +{format_directory} = format_count * { u32:format, u32:where } + +The format value is 0 for DXT1 compressed textures and 1 for 24-bit RGB +uncompressed textures. +The texture data for a format starts at the position "where" in the file. + +Each set of texture data in the file has the following structure: +{data} = format_count * { u32:mipmap_size, mipmap_size * { u8 } } +* "mipmap_size" is the number of bytes in that mip level. For compressed +textures this is the size of the texture data compressed with DXT1. For 24 bit +uncompressed textures, this is 3 * width * height. Following this are the image +bytes for that mipmap level. + +Note: All data is stored in little-Endian (Intel) byte order. +""" + +from __future__ import annotations + +import struct +from enum import IntEnum +from io import BytesIO + +from . import Image, ImageFile + +MAGIC = b"FTEX" + + +class Format(IntEnum): + DXT1 = 0 + UNCOMPRESSED = 1 + + +class FtexImageFile(ImageFile.ImageFile): + format = "FTEX" + format_description = "Texture File Format (IW2:EOC)" + + def _open(self) -> None: + assert self.fp is not None + if not _accept(self.fp.read(4)): + msg = "not an FTEX file" + raise SyntaxError(msg) + struct.unpack(" None: + pass + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith(MAGIC) + + +Image.register_open(FtexImageFile.format, FtexImageFile, _accept) +Image.register_extensions(FtexImageFile.format, [".ftc", ".ftu"]) diff --git a/PIL/GbrImagePlugin.py b/PIL/GbrImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..ec666c81c2c6aab6d243747e844e13a0cc1d296f --- /dev/null +++ b/PIL/GbrImagePlugin.py @@ -0,0 +1,103 @@ +# +# The Python Imaging Library +# +# load a GIMP brush file +# +# History: +# 96-03-14 fl Created +# 16-01-08 es Version 2 +# +# Copyright (c) Secret Labs AB 1997. +# Copyright (c) Fredrik Lundh 1996. +# Copyright (c) Eric Soroos 2016. +# +# See the README file for information on usage and redistribution. +# +# +# See https://github.com/GNOME/gimp/blob/mainline/devel-docs/gbr.txt for +# format documentation. +# +# This code Interprets version 1 and 2 .gbr files. +# Version 1 files are obsolete, and should not be used for new +# brushes. +# Version 2 files are saved by GIMP v2.8 (at least) +# Version 3 files have a format specifier of 18 for 16bit floats in +# the color depth field. This is currently unsupported by Pillow. +from __future__ import annotations + +from . import Image, ImageFile +from ._binary import i32be as i32 + + +def _accept(prefix: bytes) -> bool: + return len(prefix) >= 8 and i32(prefix, 0) >= 20 and i32(prefix, 4) in (1, 2) + + +## +# Image plugin for the GIMP brush format. + + +class GbrImageFile(ImageFile.ImageFile): + format = "GBR" + format_description = "GIMP brush file" + + def _open(self) -> None: + assert self.fp is not None + header_size = i32(self.fp.read(4)) + if header_size < 20: + msg = "not a GIMP brush" + raise SyntaxError(msg) + version = i32(self.fp.read(4)) + if version not in (1, 2): + msg = f"Unsupported GIMP brush version: {version}" + raise SyntaxError(msg) + + width = i32(self.fp.read(4)) + height = i32(self.fp.read(4)) + color_depth = i32(self.fp.read(4)) + if width == 0 or height == 0: + msg = "not a GIMP brush" + raise SyntaxError(msg) + if color_depth not in (1, 4): + msg = f"Unsupported GIMP brush color depth: {color_depth}" + raise SyntaxError(msg) + + if version == 1: + comment_length = header_size - 20 + else: + comment_length = header_size - 28 + magic_number = self.fp.read(4) + if magic_number != b"GIMP": + msg = "not a GIMP brush, bad magic number" + raise SyntaxError(msg) + self.info["spacing"] = i32(self.fp.read(4)) + + self.info["comment"] = self.fp.read(comment_length)[:-1] + + if color_depth == 1: + self._mode = "L" + else: + self._mode = "RGBA" + + self._size = width, height + + # Image might not be small + Image._decompression_bomb_check(self.size) + + # Data is an uncompressed block of w * h * bytes/pixel + self._data_size = width * height * color_depth + + def load(self) -> Image.core.PixelAccess | None: + if self._im is None: + assert self.fp is not None + self.im = Image.core.new(self.mode, self.size) + self.frombytes(self.fp.read(self._data_size)) + return Image.Image.load(self) + + +# +# registry + + +Image.register_open(GbrImageFile.format, GbrImageFile, _accept) +Image.register_extension(GbrImageFile.format, ".gbr") diff --git a/PIL/GdImageFile.py b/PIL/GdImageFile.py new file mode 100644 index 0000000000000000000000000000000000000000..891225ce2fd034a11963bb64212cfa7311190441 --- /dev/null +++ b/PIL/GdImageFile.py @@ -0,0 +1,102 @@ +# +# The Python Imaging Library. +# $Id$ +# +# GD file handling +# +# History: +# 1996-04-12 fl Created +# +# Copyright (c) 1997 by Secret Labs AB. +# Copyright (c) 1996 by Fredrik Lundh. +# +# See the README file for information on usage and redistribution. +# + + +""" +.. note:: + This format cannot be automatically recognized, so the + class is not registered for use with :py:func:`PIL.Image.open()`. To open a + gd file, use the :py:func:`PIL.GdImageFile.open()` function instead. + +.. warning:: + THE GD FORMAT IS NOT DESIGNED FOR DATA INTERCHANGE. This + implementation is provided for convenience and demonstrational + purposes only. +""" +from __future__ import annotations + +from typing import IO + +from . import ImageFile, ImagePalette, UnidentifiedImageError +from ._binary import i16be as i16 +from ._binary import i32be as i32 +from ._typing import StrOrBytesPath + + +class GdImageFile(ImageFile.ImageFile): + """ + Image plugin for the GD uncompressed format. Note that this format + is not supported by the standard :py:func:`PIL.Image.open()` function. To use + this plugin, you have to import the :py:mod:`PIL.GdImageFile` module and + use the :py:func:`PIL.GdImageFile.open()` function. + """ + + format = "GD" + format_description = "GD uncompressed images" + + def _open(self) -> None: + # Header + assert self.fp is not None + + s = self.fp.read(1037) + + if i16(s) not in [65534, 65535]: + msg = "Not a valid GD 2.x .gd file" + raise SyntaxError(msg) + + self._mode = "P" + self._size = i16(s, 2), i16(s, 4) + + true_color = s[6] + true_color_offset = 2 if true_color else 0 + + # transparency index + tindex = i32(s, 7 + true_color_offset) + if tindex < 256: + self.info["transparency"] = tindex + + self.palette = ImagePalette.raw( + "RGBX", s[7 + true_color_offset + 6 : 7 + true_color_offset + 6 + 256 * 4] + ) + + self.tile = [ + ImageFile._Tile( + "raw", + (0, 0) + self.size, + 7 + true_color_offset + 6 + 256 * 4, + "L", + ) + ] + + +def open(fp: StrOrBytesPath | IO[bytes], mode: str = "r") -> GdImageFile: + """ + Load texture from a GD image file. + + :param fp: GD file name, or an opened file handle. + :param mode: Optional mode. In this version, if the mode argument + is given, it must be "r". + :returns: An image instance. + :raises OSError: If the image could not be read. + """ + if mode != "r": + msg = "bad mode" + raise ValueError(msg) + + try: + return GdImageFile(fp) + except SyntaxError as e: + msg = "cannot identify this image file" + raise UnidentifiedImageError(msg) from e diff --git a/PIL/GimpGradientFile.py b/PIL/GimpGradientFile.py new file mode 100644 index 0000000000000000000000000000000000000000..5f2691882c46130fc2f83c45f01db34e6ce1efe6 --- /dev/null +++ b/PIL/GimpGradientFile.py @@ -0,0 +1,153 @@ +# +# Python Imaging Library +# $Id$ +# +# stuff to read (and render) GIMP gradient files +# +# History: +# 97-08-23 fl Created +# +# Copyright (c) Secret Labs AB 1997. +# Copyright (c) Fredrik Lundh 1997. +# +# See the README file for information on usage and redistribution. +# + +""" +Stuff to translate curve segments to palette values (derived from +the corresponding code in GIMP, written by Federico Mena Quintero. +See the GIMP distribution for more information.) +""" +from __future__ import annotations + +from math import log, pi, sin, sqrt + +from ._binary import o8 + +TYPE_CHECKING = False +if TYPE_CHECKING: + from collections.abc import Callable + from typing import IO + +EPSILON = 1e-10 +"""""" # Enable auto-doc for data member + + +def linear(middle: float, pos: float) -> float: + if pos <= middle: + if middle < EPSILON: + return 0.0 + else: + return 0.5 * pos / middle + else: + pos = pos - middle + middle = 1.0 - middle + if middle < EPSILON: + return 1.0 + else: + return 0.5 + 0.5 * pos / middle + + +def curved(middle: float, pos: float) -> float: + return pos ** (log(0.5) / log(max(middle, EPSILON))) + + +def sine(middle: float, pos: float) -> float: + return (sin((-pi / 2.0) + pi * linear(middle, pos)) + 1.0) / 2.0 + + +def sphere_increasing(middle: float, pos: float) -> float: + return sqrt(1.0 - (linear(middle, pos) - 1.0) ** 2) + + +def sphere_decreasing(middle: float, pos: float) -> float: + return 1.0 - sqrt(1.0 - linear(middle, pos) ** 2) + + +SEGMENTS = [linear, curved, sine, sphere_increasing, sphere_decreasing] +"""""" # Enable auto-doc for data member + + +class GradientFile: + gradient: ( + list[ + tuple[ + float, + float, + float, + list[float], + list[float], + Callable[[float, float], float], + ] + ] + | None + ) = None + + def getpalette(self, entries: int = 256) -> tuple[bytes, str]: + assert self.gradient is not None + palette = [] + + ix = 0 + x0, x1, xm, rgb0, rgb1, segment = self.gradient[ix] + + for i in range(entries): + x = i / (entries - 1) + + while x1 < x: + ix += 1 + x0, x1, xm, rgb0, rgb1, segment = self.gradient[ix] + + w = x1 - x0 + + if w < EPSILON: + scale = segment(0.5, 0.5) + else: + scale = segment((xm - x0) / w, (x - x0) / w) + + # expand to RGBA + r = o8(int(255 * ((rgb1[0] - rgb0[0]) * scale + rgb0[0]) + 0.5)) + g = o8(int(255 * ((rgb1[1] - rgb0[1]) * scale + rgb0[1]) + 0.5)) + b = o8(int(255 * ((rgb1[2] - rgb0[2]) * scale + rgb0[2]) + 0.5)) + a = o8(int(255 * ((rgb1[3] - rgb0[3]) * scale + rgb0[3]) + 0.5)) + + # add to palette + palette.append(r + g + b + a) + + return b"".join(palette), "RGBA" + + +class GimpGradientFile(GradientFile): + """File handler for GIMP's gradient format.""" + + def __init__(self, fp: IO[bytes]) -> None: + if not fp.readline().startswith(b"GIMP Gradient"): + msg = "not a GIMP gradient file" + raise SyntaxError(msg) + + line = fp.readline() + + # GIMP 1.2 gradient files don't contain a name, but GIMP 1.3 files do + if line.startswith(b"Name: "): + line = fp.readline().strip() + + count = int(line) + + self.gradient = [] + + for i in range(count): + s = fp.readline().split() + w = [float(x) for x in s[:11]] + + x0, x1 = w[0], w[2] + xm = w[1] + rgb0 = w[3:7] + rgb1 = w[7:11] + + segment = SEGMENTS[int(s[11])] + cspace = int(s[12]) + + if cspace != 0: + msg = "cannot handle HSV colour space" + raise OSError(msg) + + self.gradient.append((x0, x1, xm, rgb0, rgb1, segment)) diff --git a/PIL/GimpPaletteFile.py b/PIL/GimpPaletteFile.py new file mode 100644 index 0000000000000000000000000000000000000000..016257d3dd29e83ed8d68f89363965dc39b93811 --- /dev/null +++ b/PIL/GimpPaletteFile.py @@ -0,0 +1,75 @@ +# +# Python Imaging Library +# $Id$ +# +# stuff to read GIMP palette files +# +# History: +# 1997-08-23 fl Created +# 2004-09-07 fl Support GIMP 2.0 palette files. +# +# Copyright (c) Secret Labs AB 1997-2004. All rights reserved. +# Copyright (c) Fredrik Lundh 1997-2004. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import re +from io import BytesIO + +TYPE_CHECKING = False +if TYPE_CHECKING: + from typing import IO + + +class GimpPaletteFile: + """File handler for GIMP's palette format.""" + + rawmode = "RGB" + + def _read(self, fp: IO[bytes], limit: bool = True) -> None: + if not fp.readline().startswith(b"GIMP Palette"): + msg = "not a GIMP palette file" + raise SyntaxError(msg) + + palette: list[int] = [] + i = 0 + while True: + if limit and i == 256 + 3: + break + + i += 1 + s = fp.readline() + if not s: + break + + # skip fields and comment lines + if re.match(rb"\w+:|#", s): + continue + if limit and len(s) > 100: + msg = "bad palette file" + raise SyntaxError(msg) + + v = s.split(maxsplit=3) + if len(v) < 3: + msg = "bad palette entry" + raise ValueError(msg) + + palette += (int(v[i]) for i in range(3)) + if limit and len(palette) == 768: + break + + self.palette = bytes(palette) + + def __init__(self, fp: IO[bytes]) -> None: + self._read(fp) + + @classmethod + def frombytes(cls, data: bytes) -> GimpPaletteFile: + self = cls.__new__(cls) + self._read(BytesIO(data), False) + return self + + def getpalette(self) -> tuple[bytes, str]: + return self.palette, self.rawmode diff --git a/PIL/GribStubImagePlugin.py b/PIL/GribStubImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..146a6fa0df0d886b13e4b7ec5ae0689e89504f7e --- /dev/null +++ b/PIL/GribStubImagePlugin.py @@ -0,0 +1,76 @@ +# +# The Python Imaging Library +# $Id$ +# +# GRIB stub adapter +# +# Copyright (c) 1996-2003 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import os +from typing import IO + +from . import Image, ImageFile + +_handler = None + + +def register_handler(handler: ImageFile.StubHandler | None) -> None: + """ + Install application-specific GRIB image handler. + + :param handler: Handler object. + """ + global _handler + _handler = handler + + +# -------------------------------------------------------------------- +# Image adapter + + +def _accept(prefix: bytes) -> bool: + return len(prefix) >= 8 and prefix.startswith(b"GRIB") and prefix[7] == 1 + + +class GribStubImageFile(ImageFile.StubImageFile): + format = "GRIB" + format_description = "GRIB" + + def _open(self) -> None: + assert self.fp is not None + if not _accept(self.fp.read(8)): + msg = "Not a GRIB file" + raise SyntaxError(msg) + + self.fp.seek(-8, os.SEEK_CUR) + + # make something up + self._mode = "F" + self._size = 1, 1 + + loader = self._load() + if loader: + loader.open(self) + + def _load(self) -> ImageFile.StubHandler | None: + return _handler + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + if _handler is None or not hasattr(_handler, "save"): + msg = "GRIB save handler not installed" + raise OSError(msg) + _handler.save(im, fp, filename) + + +# -------------------------------------------------------------------- +# Registry + +Image.register_open(GribStubImageFile.format, GribStubImageFile, _accept) +Image.register_save(GribStubImageFile.format, _save) + +Image.register_extension(GribStubImageFile.format, ".grib") diff --git a/PIL/Hdf5StubImagePlugin.py b/PIL/Hdf5StubImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..1523e95d58c0f1fad893a2ea56312237c45e6117 --- /dev/null +++ b/PIL/Hdf5StubImagePlugin.py @@ -0,0 +1,76 @@ +# +# The Python Imaging Library +# $Id$ +# +# HDF5 stub adapter +# +# Copyright (c) 2000-2003 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import os +from typing import IO + +from . import Image, ImageFile + +_handler = None + + +def register_handler(handler: ImageFile.StubHandler | None) -> None: + """ + Install application-specific HDF5 image handler. + + :param handler: Handler object. + """ + global _handler + _handler = handler + + +# -------------------------------------------------------------------- +# Image adapter + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith(b"\x89HDF\r\n\x1a\n") + + +class HDF5StubImageFile(ImageFile.StubImageFile): + format = "HDF5" + format_description = "HDF5" + + def _open(self) -> None: + assert self.fp is not None + if not _accept(self.fp.read(8)): + msg = "Not an HDF file" + raise SyntaxError(msg) + + self.fp.seek(-8, os.SEEK_CUR) + + # make something up + self._mode = "F" + self._size = 1, 1 + + loader = self._load() + if loader: + loader.open(self) + + def _load(self) -> ImageFile.StubHandler | None: + return _handler + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + if _handler is None or not hasattr(_handler, "save"): + msg = "HDF5 save handler not installed" + raise OSError(msg) + _handler.save(im, fp, filename) + + +# -------------------------------------------------------------------- +# Registry + +Image.register_open(HDF5StubImageFile.format, HDF5StubImageFile, _accept) +Image.register_save(HDF5StubImageFile.format, _save) + +Image.register_extensions(HDF5StubImageFile.format, [".h5", ".hdf"]) diff --git a/PIL/IcnsImagePlugin.py b/PIL/IcnsImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..058861d67e511324de620f283d62fd5c1f2dbfeb --- /dev/null +++ b/PIL/IcnsImagePlugin.py @@ -0,0 +1,402 @@ +# +# The Python Imaging Library. +# $Id$ +# +# macOS icns file decoder, based on icns.py by Bob Ippolito. +# +# history: +# 2004-10-09 fl Turned into a PIL plugin; removed 2.3 dependencies. +# 2020-04-04 Allow saving on all operating systems. +# +# Copyright (c) 2004 by Bob Ippolito. +# Copyright (c) 2004 by Secret Labs. +# Copyright (c) 2004 by Fredrik Lundh. +# Copyright (c) 2014 by Alastair Houghton. +# Copyright (c) 2020 by Pan Jing. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import io +import os +import struct +import sys +from typing import IO + +from . import Image, ImageFile, PngImagePlugin, features + +enable_jpeg2k = features.check_codec("jpg_2000") +if enable_jpeg2k: + from . import Jpeg2KImagePlugin + +MAGIC = b"icns" +HEADERSIZE = 8 + + +def nextheader(fobj: IO[bytes]) -> tuple[bytes, int]: + return struct.unpack(">4sI", fobj.read(HEADERSIZE)) + + +def read_32t( + fobj: IO[bytes], start_length: tuple[int, int], size: tuple[int, int, int] +) -> dict[str, Image.Image]: + # The 128x128 icon seems to have an extra header for some reason. + (start, length) = start_length + fobj.seek(start) + sig = fobj.read(4) + if sig != b"\x00\x00\x00\x00": + msg = "Unknown signature, expecting 0x00000000" + raise SyntaxError(msg) + return read_32(fobj, (start + 4, length - 4), size) + + +def read_32( + fobj: IO[bytes], start_length: tuple[int, int], size: tuple[int, int, int] +) -> dict[str, Image.Image]: + """ + Read a 32bit RGB icon resource. Seems to be either uncompressed or + an RLE packbits-like scheme. + """ + (start, length) = start_length + fobj.seek(start) + pixel_size = (size[0] * size[2], size[1] * size[2]) + sizesq = pixel_size[0] * pixel_size[1] + if length == sizesq * 3: + # uncompressed ("RGBRGBGB") + indata = fobj.read(length) + im = Image.frombuffer("RGB", pixel_size, indata, "raw", "RGB", 0, 1) + else: + # decode image + im = Image.new("RGB", pixel_size, None) + for band_ix in range(3): + data = [] + bytesleft = sizesq + while bytesleft > 0: + byte = fobj.read(1) + if not byte: + break + byte_int = byte[0] + if byte_int & 0x80: + blocksize = byte_int - 125 + byte = fobj.read(1) + for i in range(blocksize): + data.append(byte) + else: + blocksize = byte_int + 1 + data.append(fobj.read(blocksize)) + bytesleft -= blocksize + if bytesleft <= 0: + break + if bytesleft != 0: + msg = f"Error reading channel [{repr(bytesleft)} left]" + raise SyntaxError(msg) + band = Image.frombuffer("L", pixel_size, b"".join(data), "raw", "L", 0, 1) + im.im.putband(band.im, band_ix) + return {"RGB": im} + + +def read_mk( + fobj: IO[bytes], start_length: tuple[int, int], size: tuple[int, int, int] +) -> dict[str, Image.Image]: + # Alpha masks seem to be uncompressed + start = start_length[0] + fobj.seek(start) + pixel_size = (size[0] * size[2], size[1] * size[2]) + sizesq = pixel_size[0] * pixel_size[1] + band = Image.frombuffer("L", pixel_size, fobj.read(sizesq), "raw", "L", 0, 1) + return {"A": band} + + +def read_png_or_jpeg2000( + fobj: IO[bytes], start_length: tuple[int, int], size: tuple[int, int, int] +) -> dict[str, Image.Image]: + (start, length) = start_length + fobj.seek(start) + sig = fobj.read(12) + + im: Image.Image + if sig.startswith(b"\x89PNG\x0d\x0a\x1a\x0a"): + fobj.seek(start) + im = PngImagePlugin.PngImageFile(fobj) + Image._decompression_bomb_check(im.size) + return {"RGBA": im} + elif ( + sig.startswith((b"\xff\x4f\xff\x51", b"\x0d\x0a\x87\x0a")) + or sig == b"\x00\x00\x00\x0cjP \x0d\x0a\x87\x0a" + ): + if not enable_jpeg2k: + msg = ( + "Unsupported icon subimage format (rebuild PIL " + "with JPEG 2000 support to fix this)" + ) + raise ValueError(msg) + # j2k, jpc or j2c + fobj.seek(start) + jp2kstream = fobj.read(length) + f = io.BytesIO(jp2kstream) + im = Jpeg2KImagePlugin.Jpeg2KImageFile(f) + Image._decompression_bomb_check(im.size) + if im.mode != "RGBA": + im = im.convert("RGBA") + return {"RGBA": im} + else: + msg = "Unsupported icon subimage format" + raise ValueError(msg) + + +class IcnsFile: + SIZES = { + (512, 512, 2): [(b"ic10", read_png_or_jpeg2000)], + (512, 512, 1): [(b"ic09", read_png_or_jpeg2000)], + (256, 256, 2): [(b"ic14", read_png_or_jpeg2000)], + (256, 256, 1): [(b"ic08", read_png_or_jpeg2000)], + (128, 128, 2): [(b"ic13", read_png_or_jpeg2000)], + (128, 128, 1): [ + (b"ic07", read_png_or_jpeg2000), + (b"it32", read_32t), + (b"t8mk", read_mk), + ], + (64, 64, 1): [(b"icp6", read_png_or_jpeg2000)], + (32, 32, 2): [(b"ic12", read_png_or_jpeg2000)], + (48, 48, 1): [(b"ih32", read_32), (b"h8mk", read_mk)], + (32, 32, 1): [ + (b"icp5", read_png_or_jpeg2000), + (b"il32", read_32), + (b"l8mk", read_mk), + ], + (16, 16, 2): [(b"ic11", read_png_or_jpeg2000)], + (16, 16, 1): [ + (b"icp4", read_png_or_jpeg2000), + (b"is32", read_32), + (b"s8mk", read_mk), + ], + } + + def __init__(self, fobj: IO[bytes]) -> None: + """ + fobj is a file-like object as an icns resource + """ + # signature : (start, length) + self.dct = {} + self.fobj = fobj + sig, filesize = nextheader(fobj) + if not _accept(sig): + msg = "not an icns file" + raise SyntaxError(msg) + i = HEADERSIZE + while i < filesize: + sig, blocksize = nextheader(fobj) + if blocksize <= 0: + msg = "invalid block header" + raise SyntaxError(msg) + i += HEADERSIZE + blocksize -= HEADERSIZE + self.dct[sig] = (i, blocksize) + fobj.seek(blocksize, io.SEEK_CUR) + i += blocksize + + def itersizes(self) -> list[tuple[int, int, int]]: + sizes = [] + for size, fmts in self.SIZES.items(): + for fmt, reader in fmts: + if fmt in self.dct: + sizes.append(size) + break + return sizes + + def bestsize(self) -> tuple[int, int, int]: + sizes = self.itersizes() + if not sizes: + msg = "No 32bit icon resources found" + raise SyntaxError(msg) + return max(sizes) + + def dataforsize(self, size: tuple[int, int, int]) -> dict[str, Image.Image]: + """ + Get an icon resource as {channel: array}. Note that + the arrays are bottom-up like windows bitmaps and will likely + need to be flipped or transposed in some way. + """ + dct = {} + for code, reader in self.SIZES[size]: + desc = self.dct.get(code) + if desc is not None: + dct.update(reader(self.fobj, desc, size)) + return dct + + def getimage( + self, size: tuple[int, int] | tuple[int, int, int] | None = None + ) -> Image.Image: + if size is None: + size = self.bestsize() + elif len(size) == 2: + size = (size[0], size[1], 1) + channels = self.dataforsize(size) + + im = channels.get("RGBA") + if im: + return im + + im = channels["RGB"].copy() + try: + im.putalpha(channels["A"]) + except KeyError: + pass + return im + + +## +# Image plugin for Mac OS icons. + + +class IcnsImageFile(ImageFile.ImageFile): + """ + PIL image support for Mac OS .icns files. + Chooses the best resolution, but will possibly load + a different size image if you mutate the size attribute + before calling 'load'. + + The info dictionary has a key 'sizes' that is a list + of sizes that the icns file has. + """ + + format = "ICNS" + format_description = "Mac OS icns resource" + + def _open(self) -> None: + assert self.fp is not None + self.icns = IcnsFile(self.fp) + self._mode = "RGBA" + self.info["sizes"] = self.icns.itersizes() + self.best_size = self.icns.bestsize() + self.size = ( + self.best_size[0] * self.best_size[2], + self.best_size[1] * self.best_size[2], + ) + + @property + def size(self) -> tuple[int, int]: + return self._size + + @size.setter + def size(self, value: tuple[int, int]) -> None: + # Check that a matching size exists, + # or that there is a scale that would create a size that matches + for size in self.info["sizes"]: + simple_size = size[0] * size[2], size[1] * size[2] + scale = simple_size[0] // value[0] + if simple_size[1] / value[1] == scale: + self._size = value + return + msg = "This is not one of the allowed sizes of this image" + raise ValueError(msg) + + def load(self, scale: int | None = None) -> Image.core.PixelAccess | None: + if scale is not None: + width, height = self.size[:2] + self.size = width * scale, height * scale + self.best_size = width, height, scale + + px = Image.Image.load(self) + if self._im is not None and self.im.size == self.size: + # Already loaded + return px + self.load_prepare() + # This is likely NOT the best way to do it, but whatever. + im = self.icns.getimage(self.best_size) + + # If this is a PNG or JPEG 2000, it won't be loaded yet + px = im.load() + + self.im = im.im + self._mode = im.mode + self.size = im.size + + return px + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + """ + Saves the image as a series of PNG files, + that are then combined into a .icns file. + """ + if hasattr(fp, "flush"): + fp.flush() + + sizes = { + b"ic07": 128, + b"ic08": 256, + b"ic09": 512, + b"ic10": 1024, + b"ic11": 32, + b"ic12": 64, + b"ic13": 256, + b"ic14": 512, + } + provided_images = {im.width: im for im in im.encoderinfo.get("append_images", [])} + size_streams = {} + for size in set(sizes.values()): + image = ( + provided_images[size] + if size in provided_images + else im.resize((size, size)) + ) + + temp = io.BytesIO() + image.save(temp, "png") + size_streams[size] = temp.getvalue() + + entries = [] + for type, size in sizes.items(): + stream = size_streams[size] + entries.append((type, HEADERSIZE + len(stream), stream)) + + # Header + fp.write(MAGIC) + file_length = HEADERSIZE # Header + file_length += HEADERSIZE + 8 * len(entries) # TOC + file_length += sum(entry[1] for entry in entries) + fp.write(struct.pack(">i", file_length)) + + # TOC + fp.write(b"TOC ") + fp.write(struct.pack(">i", HEADERSIZE + len(entries) * HEADERSIZE)) + for entry in entries: + fp.write(entry[0]) + fp.write(struct.pack(">i", entry[1])) + + # Data + for entry in entries: + fp.write(entry[0]) + fp.write(struct.pack(">i", entry[1])) + fp.write(entry[2]) + + if hasattr(fp, "flush"): + fp.flush() + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith(MAGIC) + + +Image.register_open(IcnsImageFile.format, IcnsImageFile, _accept) +Image.register_extension(IcnsImageFile.format, ".icns") + +Image.register_save(IcnsImageFile.format, _save) +Image.register_mime(IcnsImageFile.format, "image/icns") + +if __name__ == "__main__": + if len(sys.argv) < 2: + print("Syntax: python3 IcnsImagePlugin.py [file]") + sys.exit() + + with open(sys.argv[1], "rb") as fp: + imf = IcnsImageFile(fp) + for size in imf.info["sizes"]: + width, height, scale = imf.size = size + imf.save(f"out-{width}-{height}-{scale}.png") + with Image.open(sys.argv[1]) as im: + im.save("out.png") + if sys.platform == "windows": + os.startfile("out.png") diff --git a/PIL/IcoImagePlugin.py b/PIL/IcoImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..8dd57ff858ab9aca62434699d9fef8ae956a4867 --- /dev/null +++ b/PIL/IcoImagePlugin.py @@ -0,0 +1,396 @@ +# +# The Python Imaging Library. +# $Id$ +# +# Windows Icon support for PIL +# +# History: +# 96-05-27 fl Created +# +# Copyright (c) Secret Labs AB 1997. +# Copyright (c) Fredrik Lundh 1996. +# +# See the README file for information on usage and redistribution. +# + +# This plugin is a refactored version of Win32IconImagePlugin by Bryan Davis +# . +# https://code.google.com/archive/p/casadebender/wikis/Win32IconImagePlugin.wiki +# +# Copyright 2008 Bryan Davis +# +# Licensed under the Apache License, Version 2.0 (the "License"); you may +# not use this file except in compliance with the License. You may obtain +# a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# Icon format references: +# * https://en.wikipedia.org/wiki/ICO_(file_format) +# * https://msdn.microsoft.com/en-us/library/ms997538.aspx +from __future__ import annotations + +import warnings +from io import BytesIO +from math import ceil, log +from typing import IO, NamedTuple + +from . import BmpImagePlugin, Image, ImageFile, PngImagePlugin +from ._binary import i16le as i16 +from ._binary import i32le as i32 +from ._binary import o8 +from ._binary import o16le as o16 +from ._binary import o32le as o32 + +# +# -------------------------------------------------------------------- + +_MAGIC = b"\0\0\1\0" + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + fp.write(_MAGIC) # (2+2) + bmp = im.encoderinfo.get("bitmap_format") == "bmp" + sizes = im.encoderinfo.get( + "sizes", + [(16, 16), (24, 24), (32, 32), (48, 48), (64, 64), (128, 128), (256, 256)], + ) + frames = [] + provided_ims = [im] + im.encoderinfo.get("append_images", []) + width, height = im.size + for size in sorted(set(sizes)): + if size[0] > width or size[1] > height or size[0] > 256 or size[1] > 256: + continue + + for provided_im in provided_ims: + if provided_im.size != size: + continue + frames.append(provided_im) + if bmp: + bits = BmpImagePlugin.SAVE[provided_im.mode][1] + bits_used = [bits] + for other_im in provided_ims: + if other_im.size != size: + continue + bits = BmpImagePlugin.SAVE[other_im.mode][1] + if bits not in bits_used: + # Another image has been supplied for this size + # with a different bit depth + frames.append(other_im) + bits_used.append(bits) + break + else: + # TODO: invent a more convenient method for proportional scalings + frame = provided_im.copy() + frame.thumbnail(size, Image.Resampling.LANCZOS, reducing_gap=None) + frames.append(frame) + fp.write(o16(len(frames))) # idCount(2) + offset = fp.tell() + len(frames) * 16 + for frame in frames: + width, height = frame.size + # 0 means 256 + fp.write(o8(width if width < 256 else 0)) # bWidth(1) + fp.write(o8(height if height < 256 else 0)) # bHeight(1) + + bits, colors = BmpImagePlugin.SAVE[frame.mode][1:] if bmp else (32, 0) + fp.write(o8(colors)) # bColorCount(1) + fp.write(b"\0") # bReserved(1) + fp.write(b"\0\0") # wPlanes(2) + fp.write(o16(bits)) # wBitCount(2) + + image_io = BytesIO() + if bmp: + frame.save(image_io, "dib") + + if bits != 32: + and_mask = Image.new("1", size) + ImageFile._save( + and_mask, + image_io, + [ImageFile._Tile("raw", (0, 0) + size, 0, ("1", 0, -1))], + ) + else: + frame.save(image_io, "png") + image_io.seek(0) + image_bytes = image_io.read() + if bmp: + image_bytes = image_bytes[:8] + o32(height * 2) + image_bytes[12:] + bytes_len = len(image_bytes) + fp.write(o32(bytes_len)) # dwBytesInRes(4) + fp.write(o32(offset)) # dwImageOffset(4) + current = fp.tell() + fp.seek(offset) + fp.write(image_bytes) + offset = offset + bytes_len + fp.seek(current) + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith(_MAGIC) + + +class IconHeader(NamedTuple): + width: int + height: int + nb_color: int + reserved: int + planes: int + bpp: int + size: int + offset: int + dim: tuple[int, int] + square: int + color_depth: int + + +class IcoFile: + def __init__(self, buf: IO[bytes]) -> None: + """ + Parse image from file-like object containing ico file data + """ + + # check magic + s = buf.read(6) + if not _accept(s): + msg = "not an ICO file" + raise SyntaxError(msg) + + self.buf = buf + self.entry = [] + + # Number of items in file + self.nb_items = i16(s, 4) + + # Get headers for each item + for i in range(self.nb_items): + s = buf.read(16) + + # See Wikipedia + width = s[0] or 256 + height = s[1] or 256 + + # No. of colors in image (0 if >=8bpp) + nb_color = s[2] + bpp = i16(s, 6) + icon_header = IconHeader( + width=width, + height=height, + nb_color=nb_color, + reserved=s[3], + planes=i16(s, 4), + bpp=i16(s, 6), + size=i32(s, 8), + offset=i32(s, 12), + dim=(width, height), + square=width * height, + # See Wikipedia notes about color depth. + # We need this just to differ images with equal sizes + color_depth=bpp or (nb_color != 0 and ceil(log(nb_color, 2))) or 256, + ) + + self.entry.append(icon_header) + + self.entry = sorted(self.entry, key=lambda x: x.color_depth) + # ICO images are usually squares + self.entry = sorted(self.entry, key=lambda x: x.square, reverse=True) + + def sizes(self) -> set[tuple[int, int]]: + """ + Get a set of all available icon sizes and color depths. + """ + return {(h.width, h.height) for h in self.entry} + + def getentryindex(self, size: tuple[int, int], bpp: int | bool = False) -> int: + for i, h in enumerate(self.entry): + if size == h.dim and (bpp is False or bpp == h.color_depth): + return i + return 0 + + def getimage(self, size: tuple[int, int], bpp: int | bool = False) -> Image.Image: + """ + Get an image from the icon + """ + return self.frame(self.getentryindex(size, bpp)) + + def frame(self, idx: int) -> Image.Image: + """ + Get an image from frame idx + """ + + header = self.entry[idx] + + self.buf.seek(header.offset) + data = self.buf.read(8) + self.buf.seek(header.offset) + + im: Image.Image + if data[:8] == PngImagePlugin._MAGIC: + # png frame + im = PngImagePlugin.PngImageFile(self.buf) + Image._decompression_bomb_check(im.size) + else: + # XOR + AND mask bmp frame + im = BmpImagePlugin.DibImageFile(self.buf) + Image._decompression_bomb_check(im.size) + + # change tile dimension to only encompass XOR image + im._size = (im.size[0], int(im.size[1] / 2)) + d, e, o, a = im.tile[0] + im.tile[0] = ImageFile._Tile(d, (0, 0) + im.size, o, a) + + # figure out where AND mask image starts + if header.bpp == 32: + # 32-bit color depth icon image allows semitransparent areas + # PIL's DIB format ignores transparency bits, recover them. + # The DIB is packed in BGRX byte order where X is the alpha + # channel. + + # Back up to start of bmp data + self.buf.seek(o) + # extract every 4th byte (eg. 3,7,11,15,...) + alpha_bytes = self.buf.read(im.size[0] * im.size[1] * 4)[3::4] + + # convert to an 8bpp grayscale image + try: + mask = Image.frombuffer( + "L", # 8bpp + im.size, # (w, h) + alpha_bytes, # source chars + "raw", # raw decoder + ("L", 0, -1), # 8bpp inverted, unpadded, reversed + ) + except ValueError: + if ImageFile.LOAD_TRUNCATED_IMAGES: + mask = None + else: + raise + else: + # get AND image from end of bitmap + w = im.size[0] + if (w % 32) > 0: + # bitmap row data is aligned to word boundaries + w += 32 - (im.size[0] % 32) + + # the total mask data is + # padded row size * height / bits per char + + total_bytes = int((w * im.size[1]) / 8) + and_mask_offset = header.offset + header.size - total_bytes + + self.buf.seek(and_mask_offset) + mask_data = self.buf.read(total_bytes) + + # convert raw data to image + try: + mask = Image.frombuffer( + "1", # 1 bpp + im.size, # (w, h) + mask_data, # source chars + "raw", # raw decoder + ("1;I", int(w / 8), -1), # 1bpp inverted, padded, reversed + ) + except ValueError: + if ImageFile.LOAD_TRUNCATED_IMAGES: + mask = None + else: + raise + + # now we have two images, im is XOR image and mask is AND image + + # apply mask image as alpha channel + if mask: + im = im.convert("RGBA") + im.putalpha(mask) + + return im + + +## +# Image plugin for Windows Icon files. + + +class IcoImageFile(ImageFile.ImageFile): + """ + PIL read-only image support for Microsoft Windows .ico files. + + By default the largest resolution image in the file will be loaded. This + can be changed by altering the 'size' attribute before calling 'load'. + + The info dictionary has a key 'sizes' that is a list of the sizes available + in the icon file. + + Handles classic, XP and Vista icon formats. + + When saving, PNG compression is used. Support for this was only added in + Windows Vista. If you are unable to view the icon in Windows, convert the + image to "RGBA" mode before saving. + + This plugin is a refactored version of Win32IconImagePlugin by Bryan Davis + . + https://code.google.com/archive/p/casadebender/wikis/Win32IconImagePlugin.wiki + """ + + format = "ICO" + format_description = "Windows Icon" + + def _open(self) -> None: + assert self.fp is not None + self.ico = IcoFile(self.fp) + self.info["sizes"] = self.ico.sizes() + self.size = self.ico.entry[0].dim + self.load() + + @property + def size(self) -> tuple[int, int]: + return self._size + + @size.setter + def size(self, value: tuple[int, int]) -> None: + if value not in self.info["sizes"]: + msg = "This is not one of the allowed sizes of this image" + raise ValueError(msg) + self._size = value + + def load(self) -> Image.core.PixelAccess | None: + if self._im is not None and self.im.size == self.size: + # Already loaded + return Image.Image.load(self) + im = self.ico.getimage(self.size) + # if tile is PNG, it won't really be loaded yet + im.load() + self.im = im.im + self._mode = im.mode + if im.palette: + self.palette = im.palette + if im.size != self.size: + warnings.warn("Image was not the expected size") + + index = self.ico.getentryindex(self.size) + sizes = list(self.info["sizes"]) + sizes[index] = im.size + self.info["sizes"] = set(sizes) + + self.size = im.size + return Image.Image.load(self) + + def load_seek(self, pos: int) -> None: + # Flag the ImageFile.Parser so that it + # just does all the decode at the end. + pass + + +# +# -------------------------------------------------------------------- + + +Image.register_open(IcoImageFile.format, IcoImageFile, _accept) +Image.register_save(IcoImageFile.format, _save) +Image.register_extension(IcoImageFile.format, ".ico") + +Image.register_mime(IcoImageFile.format, "image/x-icon") diff --git a/PIL/ImImagePlugin.py b/PIL/ImImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..ef54f16e97e69a1410880e48ffecb1a2cbf15ea8 --- /dev/null +++ b/PIL/ImImagePlugin.py @@ -0,0 +1,390 @@ +# +# The Python Imaging Library. +# $Id$ +# +# IFUNC IM file handling for PIL +# +# history: +# 1995-09-01 fl Created. +# 1997-01-03 fl Save palette images +# 1997-01-08 fl Added sequence support +# 1997-01-23 fl Added P and RGB save support +# 1997-05-31 fl Read floating point images +# 1997-06-22 fl Save floating point images +# 1997-08-27 fl Read and save 1-bit images +# 1998-06-25 fl Added support for RGB+LUT images +# 1998-07-02 fl Added support for YCC images +# 1998-07-15 fl Renamed offset attribute to avoid name clash +# 1998-12-29 fl Added I;16 support +# 2001-02-17 fl Use 're' instead of 'regex' (Python 2.1) (0.7) +# 2003-09-26 fl Added LA/PA support +# +# Copyright (c) 1997-2003 by Secret Labs AB. +# Copyright (c) 1995-2001 by Fredrik Lundh. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import os +import re +from typing import IO, Any + +from . import Image, ImageFile, ImagePalette +from ._util import DeferredError + +# -------------------------------------------------------------------- +# Standard tags + +COMMENT = "Comment" +DATE = "Date" +EQUIPMENT = "Digitalization equipment" +FRAMES = "File size (no of images)" +LUT = "Lut" +NAME = "Name" +SCALE = "Scale (x,y)" +SIZE = "Image size (x*y)" +MODE = "Image type" + +TAGS = { + COMMENT: 0, + DATE: 0, + EQUIPMENT: 0, + FRAMES: 0, + LUT: 0, + NAME: 0, + SCALE: 0, + SIZE: 0, + MODE: 0, +} + +OPEN = { + # ifunc93/p3cfunc formats + "0 1 image": ("1", "1"), + "L 1 image": ("1", "1"), + "Greyscale image": ("L", "L"), + "Grayscale image": ("L", "L"), + "RGB image": ("RGB", "RGB;L"), + "RLB image": ("RGB", "RLB"), + "RYB image": ("RGB", "RLB"), + "B1 image": ("1", "1"), + "B2 image": ("P", "P;2"), + "B4 image": ("P", "P;4"), + "X 24 image": ("RGB", "RGB"), + "L 32 S image": ("I", "I;32"), + "L 32 F image": ("F", "F;32"), + # old p3cfunc formats + "RGB3 image": ("RGB", "RGB;T"), + "RYB3 image": ("RGB", "RYB;T"), + # extensions + "LA image": ("LA", "LA;L"), + "PA image": ("LA", "PA;L"), + "RGBA image": ("RGBA", "RGBA;L"), + "RGBX image": ("RGB", "RGBX;L"), + "CMYK image": ("CMYK", "CMYK;L"), + "YCC image": ("YCbCr", "YCbCr;L"), +} + +# ifunc95 extensions +for i in ["8", "8S", "16", "16S", "32", "32F"]: + OPEN[f"L {i} image"] = ("F", f"F;{i}") + OPEN[f"L*{i} image"] = ("F", f"F;{i}") +for i in ["16", "16L", "16B"]: + OPEN[f"L {i} image"] = (f"I;{i}", f"I;{i}") + OPEN[f"L*{i} image"] = (f"I;{i}", f"I;{i}") +for i in ["32S"]: + OPEN[f"L {i} image"] = ("I", f"I;{i}") + OPEN[f"L*{i} image"] = ("I", f"I;{i}") +for j in range(2, 33): + OPEN[f"L*{j} image"] = ("F", f"F;{j}") + + +# -------------------------------------------------------------------- +# Read IM directory + +split = re.compile(rb"^([A-Za-z][^:]*):[ \t]*(.*)[ \t]*$") + + +def number(s: Any) -> float: + try: + return int(s) + except ValueError: + return float(s) + + +## +# Image plugin for the IFUNC IM file format. + + +class ImImageFile(ImageFile.ImageFile): + format = "IM" + format_description = "IFUNC Image Memory" + _close_exclusive_fp_after_loading = False + + def _open(self) -> None: + # Quick rejection: if there's not an LF among the first + # 100 bytes, this is (probably) not a text header. + + assert self.fp is not None + if b"\n" not in self.fp.read(100): + msg = "not an IM file" + raise SyntaxError(msg) + self.fp.seek(0) + + n = 0 + + # Default values + self.info[MODE] = "L" + self.info[SIZE] = (512, 512) + self.info[FRAMES] = 1 + + self.rawmode = "L" + + while True: + s = self.fp.read(1) + + # Some versions of IFUNC uses \n\r instead of \r\n... + if s == b"\r": + continue + + if not s or s == b"\0" or s == b"\x1a": + break + + # FIXME: this may read whole file if not a text file + s = s + self.fp.readline() + + if len(s) > 100: + msg = "not an IM file" + raise SyntaxError(msg) + + if s.endswith(b"\r\n"): + s = s[:-2] + elif s.endswith(b"\n"): + s = s[:-1] + + try: + m = split.match(s) + except re.error as e: + msg = "not an IM file" + raise SyntaxError(msg) from e + + if m: + k, v = m.group(1, 2) + + # Don't know if this is the correct encoding, + # but a decent guess (I guess) + k = k.decode("latin-1", "replace") + v = v.decode("latin-1", "replace") + + # Convert value as appropriate + if k in [FRAMES, SCALE, SIZE]: + v = v.replace("*", ",") + v = tuple(map(number, v.split(","))) + if len(v) == 1: + v = v[0] + elif k == MODE and v in OPEN: + v, self.rawmode = OPEN[v] + + # Add to dictionary. Note that COMMENT tags are + # combined into a list of strings. + if k == COMMENT: + if k in self.info: + self.info[k].append(v) + else: + self.info[k] = [v] + else: + self.info[k] = v + + if k in TAGS: + n += 1 + + else: + msg = f"Syntax error in IM header: {s.decode('ascii', 'replace')}" + raise SyntaxError(msg) + + if not n: + msg = "Not an IM file" + raise SyntaxError(msg) + + # Basic attributes + self._size = self.info[SIZE] + self._mode = self.info[MODE] + + # Skip forward to start of image data + while s and not s.startswith(b"\x1a"): + s = self.fp.read(1) + if not s: + msg = "File truncated" + raise SyntaxError(msg) + + if LUT in self.info: + # convert lookup table to palette or lut attribute + palette = self.fp.read(768) + greyscale = 1 # greyscale palette + linear = 1 # linear greyscale palette + for i in range(256): + if palette[i] == palette[i + 256] == palette[i + 512]: + if palette[i] != i: + linear = 0 + else: + greyscale = 0 + if self.mode in ["L", "LA", "P", "PA"]: + if greyscale: + if not linear: + self.lut = list(palette[:256]) + else: + if self.mode in ["L", "P"]: + self._mode = self.rawmode = "P" + elif self.mode in ["LA", "PA"]: + self._mode = "PA" + self.rawmode = "PA;L" + self.palette = ImagePalette.raw("RGB;L", palette) + elif self.mode == "RGB": + if not greyscale or not linear: + self.lut = list(palette) + + self.frame = 0 + + self.__offset = offs = self.fp.tell() + + self._fp = self.fp # FIXME: hack + + if self.rawmode.startswith("F;"): + # ifunc95 formats + try: + # use bit decoder (if necessary) + bits = int(self.rawmode[2:]) + if bits not in [8, 16, 32]: + self.tile = [ + ImageFile._Tile( + "bit", (0, 0) + self.size, offs, (bits, 8, 3, 0, -1) + ) + ] + return + except ValueError: + pass + + if self.rawmode in ["RGB;T", "RYB;T"]: + # Old LabEye/3PC files. Would be very surprised if anyone + # ever stumbled upon such a file ;-) + size = self.size[0] * self.size[1] + self.tile = [ + ImageFile._Tile("raw", (0, 0) + self.size, offs, ("G", 0, -1)), + ImageFile._Tile("raw", (0, 0) + self.size, offs + size, ("R", 0, -1)), + ImageFile._Tile( + "raw", (0, 0) + self.size, offs + 2 * size, ("B", 0, -1) + ), + ] + else: + # LabEye/IFUNC files + self.tile = [ + ImageFile._Tile("raw", (0, 0) + self.size, offs, (self.rawmode, 0, -1)) + ] + + @property + def n_frames(self) -> int: + return self.info[FRAMES] + + @property + def is_animated(self) -> bool: + return self.info[FRAMES] > 1 + + def seek(self, frame: int) -> None: + if not self._seek_check(frame): + return + if isinstance(self._fp, DeferredError): + raise self._fp.ex + + self.frame = frame + + if self.mode == "1": + bits = 1 + else: + bits = 8 * len(self.mode) + + size = ((self.size[0] * bits + 7) // 8) * self.size[1] + offs = self.__offset + frame * size + + self.fp = self._fp + + self.tile = [ + ImageFile._Tile("raw", (0, 0) + self.size, offs, (self.rawmode, 0, -1)) + ] + + def tell(self) -> int: + return self.frame + + +# +# -------------------------------------------------------------------- +# Save IM files + + +SAVE = { + # mode: (im type, raw mode) + "1": ("0 1", "1"), + "L": ("Greyscale", "L"), + "LA": ("LA", "LA;L"), + "P": ("Greyscale", "P"), + "PA": ("LA", "PA;L"), + "I": ("L 32S", "I;32S"), + "I;16": ("L 16", "I;16"), + "I;16L": ("L 16L", "I;16L"), + "I;16B": ("L 16B", "I;16B"), + "F": ("L 32F", "F;32F"), + "RGB": ("RGB", "RGB;L"), + "RGBA": ("RGBA", "RGBA;L"), + "RGBX": ("RGBX", "RGBX;L"), + "CMYK": ("CMYK", "CMYK;L"), + "YCbCr": ("YCC", "YCbCr;L"), +} + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + try: + image_type, rawmode = SAVE[im.mode] + except KeyError as e: + msg = f"Cannot save {im.mode} images as IM" + raise ValueError(msg) from e + + frames = im.encoderinfo.get("frames", 1) + + fp.write(f"Image type: {image_type} image\r\n".encode("ascii")) + if filename: + # Each line must be 100 characters or less, + # or: SyntaxError("not an IM file") + # 8 characters are used for "Name: " and "\r\n" + # Keep just the filename, ditch the potentially overlong path + if isinstance(filename, bytes): + filename = filename.decode("ascii") + name, ext = os.path.splitext(os.path.basename(filename)) + name = "".join([name[: 92 - len(ext)], ext]) + + fp.write(f"Name: {name}\r\n".encode("ascii")) + fp.write(f"Image size (x*y): {im.size[0]}*{im.size[1]}\r\n".encode("ascii")) + fp.write(f"File size (no of images): {frames}\r\n".encode("ascii")) + if im.mode in ["P", "PA"]: + fp.write(b"Lut: 1\r\n") + fp.write(b"\000" * (511 - fp.tell()) + b"\032") + if im.mode in ["P", "PA"]: + im_palette = im.im.getpalette("RGB", "RGB;L") + colors = len(im_palette) // 3 + palette = b"" + for i in range(3): + palette += im_palette[colors * i : colors * (i + 1)] + palette += b"\x00" * (256 - colors) + fp.write(palette) # 768 bytes + ImageFile._save( + im, fp, [ImageFile._Tile("raw", (0, 0) + im.size, 0, (rawmode, 0, -1))] + ) + + +# +# -------------------------------------------------------------------- +# Registry + + +Image.register_open(ImImageFile.format, ImImageFile) +Image.register_save(ImImageFile.format, _save) + +Image.register_extension(ImImageFile.format, ".im") diff --git a/PIL/Image.py b/PIL/Image.py new file mode 100644 index 0000000000000000000000000000000000000000..57ebea689642d9b307e0ec39bb08ed01eebcf4d3 --- /dev/null +++ b/PIL/Image.py @@ -0,0 +1,4246 @@ +# +# The Python Imaging Library. +# $Id$ +# +# the Image class wrapper +# +# partial release history: +# 1995-09-09 fl Created +# 1996-03-11 fl PIL release 0.0 (proof of concept) +# 1996-04-30 fl PIL release 0.1b1 +# 1999-07-28 fl PIL release 1.0 final +# 2000-06-07 fl PIL release 1.1 +# 2000-10-20 fl PIL release 1.1.1 +# 2001-05-07 fl PIL release 1.1.2 +# 2002-03-15 fl PIL release 1.1.3 +# 2003-05-10 fl PIL release 1.1.4 +# 2005-03-28 fl PIL release 1.1.5 +# 2006-12-02 fl PIL release 1.1.6 +# 2009-11-15 fl PIL release 1.1.7 +# +# Copyright (c) 1997-2009 by Secret Labs AB. All rights reserved. +# Copyright (c) 1995-2009 by Fredrik Lundh. +# +# See the README file for information on usage and redistribution. +# + +from __future__ import annotations + +import abc +import atexit +import builtins +import io +import logging +import math +import os +import re +import struct +import sys +import tempfile +import warnings +from collections.abc import MutableMapping +from enum import IntEnum +from typing import IO, Protocol, cast + +# VERSION was removed in Pillow 6.0.0. +# PILLOW_VERSION was removed in Pillow 9.0.0. +# Use __version__ instead. +from . import ( + ExifTags, + ImageMode, + TiffTags, + UnidentifiedImageError, + __version__, + _plugins, +) +from ._binary import i32le, o32be, o32le +from ._deprecate import deprecate +from ._util import DeferredError, is_path + +ElementTree: ModuleType | None +try: + from defusedxml import ElementTree +except ImportError: + ElementTree = None + +TYPE_CHECKING = False +if TYPE_CHECKING: + from collections.abc import Callable, Iterator, Sequence + from types import ModuleType + from typing import Any, Literal + +logger = logging.getLogger(__name__) + + +class DecompressionBombWarning(RuntimeWarning): + pass + + +class DecompressionBombError(Exception): + pass + + +WARN_POSSIBLE_FORMATS: bool = False + +# Limit to around a quarter gigabyte for a 24-bit (3 bpp) image +MAX_IMAGE_PIXELS: int | None = int(1024 * 1024 * 1024 // 4 // 3) + + +try: + # If the _imaging C module is not present, Pillow will not load. + # Note that other modules should not refer to _imaging directly; + # import Image and use the Image.core variable instead. + # Also note that Image.core is not a publicly documented interface, + # and should be considered private and subject to change. + from . import _imaging as core + + if __version__ != getattr(core, "PILLOW_VERSION", None): + msg = ( + "The _imaging extension was built for another version of Pillow or PIL:\n" + f"Core version: {getattr(core, 'PILLOW_VERSION', None)}\n" + f"Pillow version: {__version__}" + ) + raise ImportError(msg) + +except ImportError as v: + # Explanations for ways that we know we might have an import error + if str(v).startswith("Module use of python"): + # The _imaging C module is present, but not compiled for + # the right version (windows only). Print a warning, if + # possible. + warnings.warn( + "The _imaging extension was built for another version of Python.", + RuntimeWarning, + ) + elif str(v).startswith("The _imaging extension"): + warnings.warn(str(v), RuntimeWarning) + # Fail here anyway. Don't let people run with a mostly broken Pillow. + # see docs/porting.rst + raise + + +# +# Constants + + +# transpose +class Transpose(IntEnum): + FLIP_LEFT_RIGHT = 0 + FLIP_TOP_BOTTOM = 1 + ROTATE_90 = 2 + ROTATE_180 = 3 + ROTATE_270 = 4 + TRANSPOSE = 5 + TRANSVERSE = 6 + + +# transforms (also defined in Imaging.h) +class Transform(IntEnum): + AFFINE = 0 + EXTENT = 1 + PERSPECTIVE = 2 + QUAD = 3 + MESH = 4 + + +# resampling filters (also defined in Imaging.h) +class Resampling(IntEnum): + NEAREST = 0 + BOX = 4 + BILINEAR = 2 + HAMMING = 5 + BICUBIC = 3 + LANCZOS = 1 + + +_filters_support = { + Resampling.BOX: 0.5, + Resampling.BILINEAR: 1.0, + Resampling.HAMMING: 1.0, + Resampling.BICUBIC: 2.0, + Resampling.LANCZOS: 3.0, +} + + +# dithers +class Dither(IntEnum): + NONE = 0 + ORDERED = 1 # Not yet implemented + RASTERIZE = 2 # Not yet implemented + FLOYDSTEINBERG = 3 # default + + +# palettes/quantizers +class Palette(IntEnum): + WEB = 0 + ADAPTIVE = 1 + + +class Quantize(IntEnum): + MEDIANCUT = 0 + MAXCOVERAGE = 1 + FASTOCTREE = 2 + LIBIMAGEQUANT = 3 + + +module = sys.modules[__name__] +for enum in (Transpose, Transform, Resampling, Dither, Palette, Quantize): + for item in enum: + setattr(module, item.name, item.value) + + +if hasattr(core, "DEFAULT_STRATEGY"): + DEFAULT_STRATEGY = core.DEFAULT_STRATEGY + FILTERED = core.FILTERED + HUFFMAN_ONLY = core.HUFFMAN_ONLY + RLE = core.RLE + FIXED = core.FIXED + + +# -------------------------------------------------------------------- +# Registries + +TYPE_CHECKING = False +if TYPE_CHECKING: + import mmap + from xml.etree.ElementTree import Element + + from IPython.lib.pretty import PrettyPrinter + + from . import ImageFile, ImageFilter, ImagePalette, ImageQt, TiffImagePlugin + from ._typing import CapsuleType, NumpyArray, StrOrBytesPath +ID: list[str] = [] +OPEN: dict[ + str, + tuple[ + Callable[[IO[bytes], str | bytes], ImageFile.ImageFile], + Callable[[bytes], bool | str] | None, + ], +] = {} +MIME: dict[str, str] = {} +SAVE: dict[str, Callable[[Image, IO[bytes], str | bytes], None]] = {} +SAVE_ALL: dict[str, Callable[[Image, IO[bytes], str | bytes], None]] = {} +EXTENSION: dict[str, str] = {} +DECODERS: dict[str, type[ImageFile.PyDecoder]] = {} +ENCODERS: dict[str, type[ImageFile.PyEncoder]] = {} + +# -------------------------------------------------------------------- +# Modes + +_ENDIAN = "<" if sys.byteorder == "little" else ">" + + +def _conv_type_shape(im: Image) -> tuple[tuple[int, ...], str]: + m = ImageMode.getmode(im.mode) + shape: tuple[int, ...] = (im.height, im.width) + extra = len(m.bands) + if extra != 1: + shape += (extra,) + return shape, m.typestr + + +MODES = [ + "1", + "CMYK", + "F", + "HSV", + "I", + "I;16", + "I;16B", + "I;16L", + "I;16N", + "L", + "LA", + "La", + "LAB", + "P", + "PA", + "RGB", + "RGBA", + "RGBa", + "RGBX", + "YCbCr", +] + +# raw modes that may be memory mapped. NOTE: if you change this, you +# may have to modify the stride calculation in map.c too! +_MAPMODES = ("L", "P", "RGBX", "RGBA", "CMYK", "I;16", "I;16L", "I;16B") + + +def getmodebase(mode: str) -> str: + """ + Gets the "base" mode for given mode. This function returns "L" for + images that contain grayscale data, and "RGB" for images that + contain color data. + + :param mode: Input mode. + :returns: "L" or "RGB". + :exception KeyError: If the input mode was not a standard mode. + """ + return ImageMode.getmode(mode).basemode + + +def getmodetype(mode: str) -> str: + """ + Gets the storage type mode. Given a mode, this function returns a + single-layer mode suitable for storing individual bands. + + :param mode: Input mode. + :returns: "L", "I", or "F". + :exception KeyError: If the input mode was not a standard mode. + """ + return ImageMode.getmode(mode).basetype + + +def getmodebandnames(mode: str) -> tuple[str, ...]: + """ + Gets a list of individual band names. Given a mode, this function returns + a tuple containing the names of individual bands (use + :py:method:`~PIL.Image.getmodetype` to get the mode used to store each + individual band. + + :param mode: Input mode. + :returns: A tuple containing band names. The length of the tuple + gives the number of bands in an image of the given mode. + :exception KeyError: If the input mode was not a standard mode. + """ + return ImageMode.getmode(mode).bands + + +def getmodebands(mode: str) -> int: + """ + Gets the number of individual bands for this mode. + + :param mode: Input mode. + :returns: The number of bands in this mode. + :exception KeyError: If the input mode was not a standard mode. + """ + return len(ImageMode.getmode(mode).bands) + + +# -------------------------------------------------------------------- +# Helpers + +_initialized = 0 + + +def preinit() -> None: + """ + Explicitly loads BMP, GIF, JPEG, PPM and PPM file format drivers. + + It is called when opening or saving images. + """ + + global _initialized + if _initialized >= 1: + return + + try: + from . import BmpImagePlugin + + assert BmpImagePlugin + except ImportError: + pass + try: + from . import GifImagePlugin + + assert GifImagePlugin + except ImportError: + pass + try: + from . import JpegImagePlugin + + assert JpegImagePlugin + except ImportError: + pass + try: + from . import PpmImagePlugin + + assert PpmImagePlugin + except ImportError: + pass + try: + from . import PngImagePlugin + + assert PngImagePlugin + except ImportError: + pass + + _initialized = 1 + + +def init() -> bool: + """ + Explicitly initializes the Python Imaging Library. This function + loads all available file format drivers. + + It is called when opening or saving images if :py:meth:`~preinit()` is + insufficient, and by :py:meth:`~PIL.features.pilinfo`. + """ + + global _initialized + if _initialized >= 2: + return False + + parent_name = __name__.rpartition(".")[0] + for plugin in _plugins: + try: + logger.debug("Importing %s", plugin) + __import__(f"{parent_name}.{plugin}", globals(), locals(), []) + except ImportError as e: + logger.debug("Image: failed to import %s: %s", plugin, e) + + if OPEN or SAVE: + _initialized = 2 + return True + return False + + +# -------------------------------------------------------------------- +# Codec factories (used by tobytes/frombytes and ImageFile.load) + + +def _getdecoder( + mode: str, decoder_name: str, args: Any, extra: tuple[Any, ...] = () +) -> core.ImagingDecoder | ImageFile.PyDecoder: + # tweak arguments + if args is None: + args = () + elif not isinstance(args, tuple): + args = (args,) + + try: + decoder = DECODERS[decoder_name] + except KeyError: + pass + else: + return decoder(mode, *args + extra) + + try: + # get decoder + decoder = getattr(core, f"{decoder_name}_decoder") + except AttributeError as e: + msg = f"decoder {decoder_name} not available" + raise OSError(msg) from e + return decoder(mode, *args + extra) + + +def _getencoder( + mode: str, encoder_name: str, args: Any, extra: tuple[Any, ...] = () +) -> core.ImagingEncoder | ImageFile.PyEncoder: + # tweak arguments + if args is None: + args = () + elif not isinstance(args, tuple): + args = (args,) + + try: + encoder = ENCODERS[encoder_name] + except KeyError: + pass + else: + return encoder(mode, *args + extra) + + try: + # get encoder + encoder = getattr(core, f"{encoder_name}_encoder") + except AttributeError as e: + msg = f"encoder {encoder_name} not available" + raise OSError(msg) from e + return encoder(mode, *args + extra) + + +# -------------------------------------------------------------------- +# Simple expression analyzer + + +class ImagePointTransform: + """ + Used with :py:meth:`~PIL.Image.Image.point` for single band images with more than + 8 bits, this represents an affine transformation, where the value is multiplied by + ``scale`` and ``offset`` is added. + """ + + def __init__(self, scale: float, offset: float) -> None: + self.scale = scale + self.offset = offset + + def __neg__(self) -> ImagePointTransform: + return ImagePointTransform(-self.scale, -self.offset) + + def __add__(self, other: ImagePointTransform | float) -> ImagePointTransform: + if isinstance(other, ImagePointTransform): + return ImagePointTransform( + self.scale + other.scale, self.offset + other.offset + ) + return ImagePointTransform(self.scale, self.offset + other) + + __radd__ = __add__ + + def __sub__(self, other: ImagePointTransform | float) -> ImagePointTransform: + return self + -other + + def __rsub__(self, other: ImagePointTransform | float) -> ImagePointTransform: + return other + -self + + def __mul__(self, other: ImagePointTransform | float) -> ImagePointTransform: + if isinstance(other, ImagePointTransform): + return NotImplemented + return ImagePointTransform(self.scale * other, self.offset * other) + + __rmul__ = __mul__ + + def __truediv__(self, other: ImagePointTransform | float) -> ImagePointTransform: + if isinstance(other, ImagePointTransform): + return NotImplemented + return ImagePointTransform(self.scale / other, self.offset / other) + + +def _getscaleoffset( + expr: Callable[[ImagePointTransform], ImagePointTransform | float], +) -> tuple[float, float]: + a = expr(ImagePointTransform(1, 0)) + return (a.scale, a.offset) if isinstance(a, ImagePointTransform) else (0, a) + + +# -------------------------------------------------------------------- +# Implementation wrapper + + +class SupportsGetData(Protocol): + def getdata( + self, + ) -> tuple[Transform, Sequence[int]]: ... + + +class Image: + """ + This class represents an image object. To create + :py:class:`~PIL.Image.Image` objects, use the appropriate factory + functions. There's hardly ever any reason to call the Image constructor + directly. + + * :py:func:`~PIL.Image.open` + * :py:func:`~PIL.Image.new` + * :py:func:`~PIL.Image.frombytes` + """ + + format: str | None = None + format_description: str | None = None + _close_exclusive_fp_after_loading = True + + def __init__(self) -> None: + # FIXME: take "new" parameters / other image? + self._im: core.ImagingCore | DeferredError | None = None + self._mode = "" + self._size = (0, 0) + self.palette: ImagePalette.ImagePalette | None = None + self.info: dict[str | tuple[int, int], Any] = {} + self.readonly = 0 + self._exif: Exif | None = None + + @property + def im(self) -> core.ImagingCore: + if isinstance(self._im, DeferredError): + raise self._im.ex + assert self._im is not None + return self._im + + @im.setter + def im(self, im: core.ImagingCore) -> None: + self._im = im + + @property + def width(self) -> int: + return self.size[0] + + @property + def height(self) -> int: + return self.size[1] + + @property + def size(self) -> tuple[int, int]: + return self._size + + @property + def mode(self) -> str: + return self._mode + + @property + def readonly(self) -> int: + return (self._im and self._im.readonly) or self._readonly + + @readonly.setter + def readonly(self, readonly: int) -> None: + self._readonly = readonly + + def _new(self, im: core.ImagingCore) -> Image: + new = Image() + new.im = im + new._mode = im.mode + new._size = im.size + if im.mode in ("P", "PA"): + if self.palette: + new.palette = self.palette.copy() + else: + from . import ImagePalette + + new.palette = ImagePalette.ImagePalette() + new.info = self.info.copy() + return new + + # Context manager support + def __enter__(self) -> Image: + return self + + def __exit__(self, *args: object) -> None: + pass + + def close(self) -> None: + """ + This operation will destroy the image core and release its memory. + The image data will be unusable afterward. + + This function is required to close images that have multiple frames or + have not had their file read and closed by the + :py:meth:`~PIL.Image.Image.load` method. See :ref:`file-handling` for + more information. + """ + if getattr(self, "map", None): + if sys.platform == "win32" and hasattr(sys, "pypy_version_info"): + self.map.close() + self.map: mmap.mmap | None = None + + # Instead of simply setting to None, we're setting up a + # deferred error that will better explain that the core image + # object is gone. + self._im = DeferredError(ValueError("Operation on closed image")) + + def _copy(self) -> None: + self.load() + self.im = self.im.copy() + self.readonly = 0 + + def _ensure_mutable(self) -> None: + if self.readonly: + self._copy() + else: + self.load() + + def _dump( + self, file: str | None = None, format: str | None = None, **options: Any + ) -> str: + suffix = "" + if format: + suffix = f".{format}" + + if not file: + f, filename = tempfile.mkstemp(suffix) + os.close(f) + else: + filename = file + if not filename.endswith(suffix): + filename = filename + suffix + + self.load() + + if not format or format == "PPM": + self.im.save_ppm(filename) + else: + self.save(filename, format, **options) + + return filename + + def __eq__(self, other: object) -> bool: + if self.__class__ is not other.__class__: + return False + assert isinstance(other, Image) + return ( + self.mode == other.mode + and self.size == other.size + and self.info == other.info + and self.getpalette() == other.getpalette() + and self.tobytes() == other.tobytes() + ) + + def __repr__(self) -> str: + return ( + f"<{self.__class__.__module__}.{self.__class__.__name__} " + f"image mode={self.mode} size={self.size[0]}x{self.size[1]} " + f"at 0x{id(self):X}>" + ) + + def _repr_pretty_(self, p: PrettyPrinter, cycle: bool) -> None: + """IPython plain text display support""" + + # Same as __repr__ but without unpredictable id(self), + # to keep Jupyter notebook `text/plain` output stable. + p.text( + f"<{self.__class__.__module__}.{self.__class__.__name__} " + f"image mode={self.mode} size={self.size[0]}x{self.size[1]}>" + ) + + def _repr_image(self, image_format: str, **kwargs: Any) -> bytes | None: + """Helper function for iPython display hook. + + :param image_format: Image format. + :returns: image as bytes, saved into the given format. + """ + b = io.BytesIO() + try: + self.save(b, image_format, **kwargs) + except Exception: + return None + return b.getvalue() + + def _repr_png_(self) -> bytes | None: + """iPython display hook support for PNG format. + + :returns: PNG version of the image as bytes + """ + return self._repr_image("PNG", compress_level=1) + + def _repr_jpeg_(self) -> bytes | None: + """iPython display hook support for JPEG format. + + :returns: JPEG version of the image as bytes + """ + return self._repr_image("JPEG") + + @property + def __array_interface__(self) -> dict[str, str | bytes | int | tuple[int, ...]]: + # numpy array interface support + new: dict[str, str | bytes | int | tuple[int, ...]] = {"version": 3} + if self.mode == "1": + # Binary images need to be extended from bits to bytes + # See: https://github.com/python-pillow/Pillow/issues/350 + new["data"] = self.tobytes("raw", "L") + else: + new["data"] = self.tobytes() + new["shape"], new["typestr"] = _conv_type_shape(self) + return new + + def __arrow_c_schema__(self) -> object: + self.load() + return self.im.__arrow_c_schema__() + + def __arrow_c_array__( + self, requested_schema: object | None = None + ) -> tuple[object, object]: + self.load() + return (self.im.__arrow_c_schema__(), self.im.__arrow_c_array__()) + + def __getstate__(self) -> list[Any]: + im_data = self.tobytes() # load image first + return [self.info, self.mode, self.size, self.getpalette(), im_data] + + def __setstate__(self, state: list[Any]) -> None: + Image.__init__(self) + info, mode, size, palette, data = state[:5] + self.info = info + self._mode = mode + self._size = size + self.im = core.new(mode, size) + if mode in ("L", "LA", "P", "PA") and palette: + self.putpalette(palette) + self.frombytes(data) + + def tobytes(self, encoder_name: str = "raw", *args: Any) -> bytes: + """ + Return image as a bytes object. + + .. warning:: + + This method returns raw image data derived from Pillow's internal + storage. For compressed image data (e.g. PNG, JPEG) use + :meth:`~.save`, with a BytesIO parameter for in-memory data. + + :param encoder_name: What encoder to use. + + The default is to use the standard "raw" encoder. + To see how this packs pixel data into the returned + bytes, see :file:`libImaging/Pack.c`. + + A list of C encoders can be seen under codecs + section of the function array in + :file:`_imaging.c`. Python encoders are registered + within the relevant plugins. + :param args: Extra arguments to the encoder. + :returns: A :py:class:`bytes` object. + """ + + encoder_args: Any = args + if len(encoder_args) == 1 and isinstance(encoder_args[0], tuple): + # may pass tuple instead of argument list + encoder_args = encoder_args[0] + + if encoder_name == "raw" and encoder_args == (): + encoder_args = self.mode + + self.load() + + if self.width == 0 or self.height == 0: + return b"" + + # unpack data + e = _getencoder(self.mode, encoder_name, encoder_args) + e.setimage(self.im) + + from . import ImageFile + + bufsize = max(ImageFile.MAXBLOCK, self.size[0] * 4) # see RawEncode.c + + output = [] + while True: + bytes_consumed, errcode, data = e.encode(bufsize) + output.append(data) + if errcode: + break + if errcode < 0: + msg = f"encoder error {errcode} in tobytes" + raise RuntimeError(msg) + + return b"".join(output) + + def tobitmap(self, name: str = "image") -> bytes: + """ + Returns the image converted to an X11 bitmap. + + .. note:: This method only works for mode "1" images. + + :param name: The name prefix to use for the bitmap variables. + :returns: A string containing an X11 bitmap. + :raises ValueError: If the mode is not "1" + """ + + self.load() + if self.mode != "1": + msg = "not a bitmap" + raise ValueError(msg) + data = self.tobytes("xbm") + return b"".join( + [ + f"#define {name}_width {self.size[0]}\n".encode("ascii"), + f"#define {name}_height {self.size[1]}\n".encode("ascii"), + f"static char {name}_bits[] = {{\n".encode("ascii"), + data, + b"};", + ] + ) + + def frombytes( + self, + data: bytes | bytearray | SupportsArrayInterface, + decoder_name: str = "raw", + *args: Any, + ) -> None: + """ + Loads this image with pixel data from a bytes object. + + This method is similar to the :py:func:`~PIL.Image.frombytes` function, + but loads data into this image instead of creating a new image object. + """ + + if self.width == 0 or self.height == 0: + return + + decoder_args: Any = args + if len(decoder_args) == 1 and isinstance(decoder_args[0], tuple): + # may pass tuple instead of argument list + decoder_args = decoder_args[0] + + # default format + if decoder_name == "raw" and decoder_args == (): + decoder_args = self.mode + + # unpack data + d = _getdecoder(self.mode, decoder_name, decoder_args) + d.setimage(self.im) + s = d.decode(data) + + if s[0] >= 0: + msg = "not enough image data" + raise ValueError(msg) + if s[1] != 0: + msg = "cannot decode image data" + raise ValueError(msg) + + def load(self) -> core.PixelAccess | None: + """ + Allocates storage for the image and loads the pixel data. In + normal cases, you don't need to call this method, since the + Image class automatically loads an opened image when it is + accessed for the first time. + + If the file associated with the image was opened by Pillow, then this + method will close it. The exception to this is if the image has + multiple frames, in which case the file will be left open for seek + operations. See :ref:`file-handling` for more information. + + :returns: An image access object. + :rtype: :py:class:`.PixelAccess` + """ + if self._im is not None and self.palette and self.palette.dirty: + # realize palette + mode, arr = self.palette.getdata() + self.im.putpalette(self.palette.mode, mode, arr) + self.palette.dirty = 0 + self.palette.rawmode = None + if "transparency" in self.info and mode in ("LA", "PA"): + if isinstance(self.info["transparency"], int): + self.im.putpalettealpha(self.info["transparency"], 0) + else: + self.im.putpalettealphas(self.info["transparency"]) + self.palette.mode = "RGBA" + else: + self.palette.palette = self.im.getpalette( + self.palette.mode, self.palette.mode + ) + + if self._im is not None: + return self.im.pixel_access(self.readonly) + return None + + def verify(self) -> None: + """ + Verifies the contents of a file. For data read from a file, this + method attempts to determine if the file is broken, without + actually decoding the image data. If this method finds any + problems, it raises suitable exceptions. If you need to load + the image after using this method, you must reopen the image + file. + """ + pass + + def convert( + self, + mode: str | None = None, + matrix: tuple[float, ...] | None = None, + dither: Dither | None = None, + palette: Palette = Palette.WEB, + colors: int = 256, + ) -> Image: + """ + Returns a converted copy of this image. For the "P" mode, this + method translates pixels through the palette. If mode is + omitted, a mode is chosen so that all information in the image + and the palette can be represented without a palette. + + This supports all possible conversions between "L", "RGB" and "CMYK". The + ``matrix`` argument only supports "L" and "RGB". + + When translating a color image to grayscale (mode "L"), + the library uses the ITU-R 601-2 luma transform:: + + L = R * 299/1000 + G * 587/1000 + B * 114/1000 + + The default method of converting a grayscale ("L") or "RGB" + image into a bilevel (mode "1") image uses Floyd-Steinberg + dither to approximate the original image luminosity levels. If + dither is ``None``, all values larger than 127 are set to 255 (white), + all other values to 0 (black). To use other thresholds, use the + :py:meth:`~PIL.Image.Image.point` method. + + When converting from "RGBA" to "P" without a ``matrix`` argument, + this passes the operation to :py:meth:`~PIL.Image.Image.quantize`, + and ``dither`` and ``palette`` are ignored. + + When converting from "PA", if an "RGBA" palette is present, the alpha + channel from the image will be used instead of the values from the palette. + + :param mode: The requested mode. See: :ref:`concept-modes`. + :param matrix: An optional conversion matrix. If given, this + should be 4- or 12-tuple containing floating point values. + :param dither: Dithering method, used when converting from + mode "RGB" to "P" or from "RGB" or "L" to "1". + Available methods are :data:`Dither.NONE` or :data:`Dither.FLOYDSTEINBERG` + (default). Note that this is not used when ``matrix`` is supplied. + :param palette: Palette to use when converting from mode "RGB" + to "P". Available palettes are :data:`Palette.WEB` or + :data:`Palette.ADAPTIVE`. + :param colors: Number of colors to use for the :data:`Palette.ADAPTIVE` + palette. Defaults to 256. + :rtype: :py:class:`~PIL.Image.Image` + :returns: An :py:class:`~PIL.Image.Image` object. + """ + + self.load() + + has_transparency = "transparency" in self.info + if not mode and self.mode == "P": + # determine default mode + if self.palette: + mode = self.palette.mode + else: + mode = "RGB" + if mode == "RGB" and has_transparency: + mode = "RGBA" + if not mode or (mode == self.mode and not matrix): + return self.copy() + + if matrix: + # matrix conversion + if mode not in ("L", "RGB"): + msg = "illegal conversion" + raise ValueError(msg) + im = self.im.convert_matrix(mode, matrix) + new_im = self._new(im) + if has_transparency and self.im.bands == 3: + transparency = new_im.info["transparency"] + + def convert_transparency( + m: tuple[float, ...], v: tuple[int, int, int] + ) -> int: + value = m[0] * v[0] + m[1] * v[1] + m[2] * v[2] + m[3] * 0.5 + return max(0, min(255, int(value))) + + if mode == "L": + transparency = convert_transparency(matrix, transparency) + elif len(mode) == 3: + transparency = tuple( + convert_transparency(matrix[i * 4 : i * 4 + 4], transparency) + for i in range(len(transparency)) + ) + new_im.info["transparency"] = transparency + return new_im + + if self.mode == "RGBA": + if mode == "P": + return self.quantize(colors) + elif mode == "PA": + r, g, b, a = self.split() + rgb = merge("RGB", (r, g, b)) + p = rgb.quantize(colors) + return merge("PA", (p, a)) + + trns = None + delete_trns = False + # transparency handling + if has_transparency: + if (self.mode in ("1", "L", "I", "I;16") and mode in ("LA", "RGBA")) or ( + self.mode == "RGB" and mode in ("La", "LA", "RGBa", "RGBA") + ): + # Use transparent conversion to promote from transparent + # color to an alpha channel. + new_im = self._new( + self.im.convert_transparent(mode, self.info["transparency"]) + ) + del new_im.info["transparency"] + return new_im + elif self.mode in ("L", "RGB", "P") and mode in ("L", "RGB", "P"): + t = self.info["transparency"] + if isinstance(t, bytes): + # Dragons. This can't be represented by a single color + warnings.warn( + "Palette images with Transparency expressed in bytes should be " + "converted to RGBA images" + ) + delete_trns = True + else: + # get the new transparency color. + # use existing conversions + trns_im = new(self.mode, (1, 1)) + if self.mode == "P": + assert self.palette is not None + trns_im.putpalette(self.palette, self.palette.mode) + if isinstance(t, tuple): + err = "Couldn't allocate a palette color for transparency" + assert trns_im.palette is not None + try: + t = trns_im.palette.getcolor(t, self) + except ValueError as e: + if str(e) == "cannot allocate more than 256 colors": + # If all 256 colors are in use, + # then there is no need for transparency + t = None + else: + raise ValueError(err) from e + if t is None: + trns = None + else: + trns_im.putpixel((0, 0), t) + + if mode in ("L", "RGB"): + trns_im = trns_im.convert(mode) + else: + # can't just retrieve the palette number, got to do it + # after quantization. + trns_im = trns_im.convert("RGB") + trns = trns_im.getpixel((0, 0)) + + elif self.mode == "P" and mode in ("LA", "PA", "RGBA"): + t = self.info["transparency"] + delete_trns = True + + if isinstance(t, bytes): + self.im.putpalettealphas(t) + elif isinstance(t, int): + self.im.putpalettealpha(t, 0) + else: + msg = "Transparency for P mode should be bytes or int" + raise ValueError(msg) + + if mode == "P" and palette == Palette.ADAPTIVE: + im = self.im.quantize(colors) + new_im = self._new(im) + from . import ImagePalette + + new_im.palette = ImagePalette.ImagePalette( + "RGB", new_im.im.getpalette("RGB") + ) + if delete_trns: + # This could possibly happen if we requantize to fewer colors. + # The transparency would be totally off in that case. + del new_im.info["transparency"] + if trns is not None: + try: + new_im.info["transparency"] = new_im.palette.getcolor( + cast(tuple[int, ...], trns), # trns was converted to RGB + new_im, + ) + except Exception: + # if we can't make a transparent color, don't leave the old + # transparency hanging around to mess us up. + del new_im.info["transparency"] + warnings.warn("Couldn't allocate palette entry for transparency") + return new_im + + if "LAB" in (self.mode, mode): + im = self + if mode == "LAB": + if im.mode not in ("RGB", "RGBA", "RGBX"): + im = im.convert("RGBA") + other_mode = im.mode + else: + other_mode = mode + if other_mode in ("RGB", "RGBA", "RGBX"): + from . import ImageCms + + srgb = ImageCms.createProfile("sRGB") + lab = ImageCms.createProfile("LAB") + profiles = [lab, srgb] if im.mode == "LAB" else [srgb, lab] + transform = ImageCms.buildTransform( + profiles[0], profiles[1], im.mode, mode + ) + return transform.apply(im) + + # colorspace conversion + if dither is None: + dither = Dither.FLOYDSTEINBERG + + try: + im = self.im.convert(mode, dither) + except ValueError: + try: + # normalize source image and try again + modebase = getmodebase(self.mode) + if modebase == self.mode: + raise + im = self.im.convert(modebase) + im = im.convert(mode, dither) + except KeyError as e: + msg = "illegal conversion" + raise ValueError(msg) from e + + new_im = self._new(im) + if mode in ("P", "PA") and palette != Palette.ADAPTIVE: + from . import ImagePalette + + new_im.palette = ImagePalette.ImagePalette("RGB", im.getpalette("RGB")) + if delete_trns: + # crash fail if we leave a bytes transparency in an rgb/l mode. + del new_im.info["transparency"] + if trns is not None: + if new_im.mode == "P" and new_im.palette: + try: + new_im.info["transparency"] = new_im.palette.getcolor( + cast(tuple[int, ...], trns), new_im # trns was converted to RGB + ) + except ValueError as e: + del new_im.info["transparency"] + if str(e) != "cannot allocate more than 256 colors": + # If all 256 colors are in use, + # then there is no need for transparency + warnings.warn( + "Couldn't allocate palette entry for transparency" + ) + else: + new_im.info["transparency"] = trns + return new_im + + def quantize( + self, + colors: int = 256, + method: int | None = None, + kmeans: int = 0, + palette: Image | None = None, + dither: Dither = Dither.FLOYDSTEINBERG, + ) -> Image: + """ + Convert the image to 'P' mode with the specified number + of colors. + + :param colors: The desired number of colors, <= 256 + :param method: :data:`Quantize.MEDIANCUT` (median cut), + :data:`Quantize.MAXCOVERAGE` (maximum coverage), + :data:`Quantize.FASTOCTREE` (fast octree), + :data:`Quantize.LIBIMAGEQUANT` (libimagequant; check support + using :py:func:`PIL.features.check_feature` with + ``feature="libimagequant"``). + + By default, :data:`Quantize.MEDIANCUT` will be used. + + The exception to this is RGBA images. :data:`Quantize.MEDIANCUT` + and :data:`Quantize.MAXCOVERAGE` do not support RGBA images, so + :data:`Quantize.FASTOCTREE` is used by default instead. + :param kmeans: Integer greater than or equal to zero. + :param palette: Quantize to the palette of given + :py:class:`PIL.Image.Image`. + :param dither: Dithering method, used when converting from + mode "RGB" to "P" or from "RGB" or "L" to "1". + Available methods are :data:`Dither.NONE` or :data:`Dither.FLOYDSTEINBERG` + (default). + :returns: A new image + """ + + self.load() + + if method is None: + # defaults: + method = Quantize.MEDIANCUT + if self.mode == "RGBA": + method = Quantize.FASTOCTREE + + if self.mode == "RGBA" and method not in ( + Quantize.FASTOCTREE, + Quantize.LIBIMAGEQUANT, + ): + # Caller specified an invalid mode. + msg = ( + "Fast Octree (method == 2) and libimagequant (method == 3) " + "are the only valid methods for quantizing RGBA images" + ) + raise ValueError(msg) + + if palette: + # use palette from reference image + palette.load() + if palette.mode != "P": + msg = "bad mode for palette image" + raise ValueError(msg) + if self.mode not in {"RGB", "L"}: + msg = "only RGB or L mode images can be quantized to a palette" + raise ValueError(msg) + im = self.im.convert("P", dither, palette.im) + new_im = self._new(im) + assert palette.palette is not None + new_im.palette = palette.palette.copy() + return new_im + + if kmeans < 0: + msg = "kmeans must not be negative" + raise ValueError(msg) + + im = self._new(self.im.quantize(colors, method, kmeans)) + + from . import ImagePalette + + mode = im.im.getpalettemode() + palette_data = im.im.getpalette(mode, mode)[: colors * len(mode)] + im.palette = ImagePalette.ImagePalette(mode, palette_data) + + return im + + def copy(self) -> Image: + """ + Copies this image. Use this method if you wish to paste things + into an image, but still retain the original. + + :rtype: :py:class:`~PIL.Image.Image` + :returns: An :py:class:`~PIL.Image.Image` object. + """ + self.load() + return self._new(self.im.copy()) + + __copy__ = copy + + def crop(self, box: tuple[float, float, float, float] | None = None) -> Image: + """ + Returns a rectangular region from this image. The box is a + 4-tuple defining the left, upper, right, and lower pixel + coordinate. See :ref:`coordinate-system`. + + Note: Prior to Pillow 3.4.0, this was a lazy operation. + + :param box: The crop rectangle, as a (left, upper, right, lower)-tuple. + :rtype: :py:class:`~PIL.Image.Image` + :returns: An :py:class:`~PIL.Image.Image` object. + """ + + if box is None: + return self.copy() + + if box[2] < box[0]: + msg = "Coordinate 'right' is less than 'left'" + raise ValueError(msg) + elif box[3] < box[1]: + msg = "Coordinate 'lower' is less than 'upper'" + raise ValueError(msg) + + self.load() + return self._new(self._crop(self.im, box)) + + def _crop( + self, im: core.ImagingCore, box: tuple[float, float, float, float] + ) -> core.ImagingCore: + """ + Returns a rectangular region from the core image object im. + + This is equivalent to calling im.crop((x0, y0, x1, y1)), but + includes additional sanity checks. + + :param im: a core image object + :param box: The crop rectangle, as a (left, upper, right, lower)-tuple. + :returns: A core image object. + """ + + x0, y0, x1, y1 = map(int, map(round, box)) + + absolute_values = (abs(x1 - x0), abs(y1 - y0)) + + _decompression_bomb_check(absolute_values) + + return im.crop((x0, y0, x1, y1)) + + def draft( + self, mode: str | None, size: tuple[int, int] | None + ) -> tuple[str, tuple[int, int, float, float]] | None: + """ + Configures the image file loader so it returns a version of the + image that as closely as possible matches the given mode and + size. For example, you can use this method to convert a color + JPEG to grayscale while loading it. + + If any changes are made, returns a tuple with the chosen ``mode`` and + ``box`` with coordinates of the original image within the altered one. + + Note that this method modifies the :py:class:`~PIL.Image.Image` object + in place. If the image has already been loaded, this method has no + effect. + + Note: This method is not implemented for most images. It is + currently implemented only for JPEG and MPO images. + + :param mode: The requested mode. + :param size: The requested size in pixels, as a 2-tuple: + (width, height). + """ + pass + + def filter(self, filter: ImageFilter.Filter | type[ImageFilter.Filter]) -> Image: + """ + Filters this image using the given filter. For a list of + available filters, see the :py:mod:`~PIL.ImageFilter` module. + + :param filter: Filter kernel. + :returns: An :py:class:`~PIL.Image.Image` object.""" + + from . import ImageFilter + + self.load() + + if callable(filter): + filter = filter() + if not hasattr(filter, "filter"): + msg = "filter argument should be ImageFilter.Filter instance or class" + raise TypeError(msg) + + multiband = isinstance(filter, ImageFilter.MultibandFilter) + if self.im.bands == 1 or multiband: + return self._new(filter.filter(self.im)) + + ims = [ + self._new(filter.filter(self.im.getband(c))) for c in range(self.im.bands) + ] + return merge(self.mode, ims) + + def getbands(self) -> tuple[str, ...]: + """ + Returns a tuple containing the name of each band in this image. + For example, ``getbands`` on an RGB image returns ("R", "G", "B"). + + :returns: A tuple containing band names. + :rtype: tuple + """ + return ImageMode.getmode(self.mode).bands + + def getbbox(self, *, alpha_only: bool = True) -> tuple[int, int, int, int] | None: + """ + Calculates the bounding box of the non-zero regions in the + image. + + :param alpha_only: Optional flag, defaulting to ``True``. + If ``True`` and the image has an alpha channel, trim transparent pixels. + Otherwise, trim pixels when all channels are zero. + Keyword-only argument. + :returns: The bounding box is returned as a 4-tuple defining the + left, upper, right, and lower pixel coordinate. See + :ref:`coordinate-system`. If the image is completely empty, this + method returns None. + + """ + + self.load() + return self.im.getbbox(alpha_only) + + def getcolors( + self, maxcolors: int = 256 + ) -> list[tuple[int, tuple[int, ...]]] | list[tuple[int, float]] | None: + """ + Returns a list of colors used in this image. + + The colors will be in the image's mode. For example, an RGB image will + return a tuple of (red, green, blue) color values, and a P image will + return the index of the color in the palette. + + :param maxcolors: Maximum number of colors. If this number is + exceeded, this method returns None. The default limit is + 256 colors. + :returns: An unsorted list of (count, pixel) values. + """ + + self.load() + if self.mode in ("1", "L", "P"): + h = self.im.histogram() + out: list[tuple[int, float]] = [(h[i], i) for i in range(256) if h[i]] + if len(out) > maxcolors: + return None + return out + return self.im.getcolors(maxcolors) + + def getdata(self, band: int | None = None) -> core.ImagingCore: + """ + Returns the contents of this image as a sequence object + containing pixel values. The sequence object is flattened, so + that values for line one follow directly after the values of + line zero, and so on. + + Note that the sequence object returned by this method is an + internal PIL data type, which only supports certain sequence + operations. To convert it to an ordinary sequence (e.g. for + printing), use ``list(im.getdata())``. + + :param band: What band to return. The default is to return + all bands. To return a single band, pass in the index + value (e.g. 0 to get the "R" band from an "RGB" image). + :returns: A sequence-like object. + """ + deprecate("Image.Image.getdata", 14, "get_flattened_data") + + self.load() + if band is not None: + return self.im.getband(band) + return self.im # could be abused + + def get_flattened_data( + self, band: int | None = None + ) -> tuple[tuple[int, ...], ...] | tuple[float, ...]: + """ + Returns the contents of this image as a tuple containing pixel values. + The sequence object is flattened, so that values for line one follow + directly after the values of line zero, and so on. + + :param band: What band to return. The default is to return + all bands. To return a single band, pass in the index + value (e.g. 0 to get the "R" band from an "RGB" image). + :returns: A tuple containing pixel values. + """ + self.load() + if band is not None: + return tuple(self.im.getband(band)) + return tuple(self.im) + + def getextrema(self) -> tuple[float, float] | tuple[tuple[int, int], ...]: + """ + Gets the minimum and maximum pixel values for each band in + the image. + + :returns: For a single-band image, a 2-tuple containing the + minimum and maximum pixel value. For a multi-band image, + a tuple containing one 2-tuple for each band. + """ + + self.load() + if self.im.bands > 1: + return tuple(self.im.getband(i).getextrema() for i in range(self.im.bands)) + return self.im.getextrema() + + def getxmp(self) -> dict[str, Any]: + """ + Returns a dictionary containing the XMP tags. + Requires defusedxml to be installed. + + :returns: XMP tags in a dictionary. + """ + + def get_name(tag: str) -> str: + return re.sub("^{[^}]+}", "", tag) + + def get_value(element: Element) -> str | dict[str, Any] | None: + value: dict[str, Any] = {get_name(k): v for k, v in element.attrib.items()} + children = list(element) + if children: + for child in children: + name = get_name(child.tag) + child_value = get_value(child) + if name in value: + if not isinstance(value[name], list): + value[name] = [value[name]] + value[name].append(child_value) + else: + value[name] = child_value + elif value: + if element.text: + value["text"] = element.text + else: + return element.text + return value + + if ElementTree is None: + warnings.warn("XMP data cannot be read without defusedxml dependency") + return {} + if "xmp" not in self.info: + return {} + root = ElementTree.fromstring(self.info["xmp"].rstrip(b"\x00 ")) + return {get_name(root.tag): get_value(root)} + + def getexif(self) -> Exif: + """ + Gets EXIF data from the image. + + :returns: an :py:class:`~PIL.Image.Exif` object. + """ + if self._exif is None: + self._exif = Exif() + elif self._exif._loaded: + return self._exif + self._exif._loaded = True + + exif_info = self.info.get("exif") + if exif_info is None: + if "Raw profile type exif" in self.info: + exif_info = bytes.fromhex( + "".join(self.info["Raw profile type exif"].split("\n")[3:]) + ) + elif hasattr(self, "tag_v2"): + from . import TiffImagePlugin + + assert isinstance(self, TiffImagePlugin.TiffImageFile) + self._exif.bigtiff = self.tag_v2._bigtiff + self._exif.endian = self.tag_v2._endian + + assert self.fp is not None + self._exif.load_from_fp(self.fp, self.tag_v2._offset) + if exif_info is not None: + self._exif.load(exif_info) + + # XMP tags + if ExifTags.Base.Orientation not in self._exif: + xmp_tags = self.info.get("XML:com.adobe.xmp") + pattern: str | bytes = r'tiff:Orientation(="|>)([0-9])' + if not xmp_tags and (xmp_tags := self.info.get("xmp")): + pattern = rb'tiff:Orientation(="|>)([0-9])' + if xmp_tags: + match = re.search(pattern, xmp_tags) + if match: + self._exif[ExifTags.Base.Orientation] = int(match[2]) + + return self._exif + + def _reload_exif(self) -> None: + if self._exif is None or not self._exif._loaded: + return + self._exif._loaded = False + self.getexif() + + def get_child_images(self) -> list[ImageFile.ImageFile]: + from . import ImageFile + + deprecate("Image.Image.get_child_images", 13) + return ImageFile.ImageFile.get_child_images(self) # type: ignore[arg-type] + + def getim(self) -> CapsuleType: + """ + Returns a capsule that points to the internal image memory. + + :returns: A capsule object. + """ + + self.load() + return self.im.ptr + + def getpalette(self, rawmode: str | None = "RGB") -> list[int] | None: + """ + Returns the image palette as a list. + + :param rawmode: The mode in which to return the palette. ``None`` will + return the palette in its current mode. + + .. versionadded:: 9.1.0 + + :returns: A list of color values [r, g, b, ...], or None if the + image has no palette. + """ + + self.load() + try: + mode = self.im.getpalettemode() + except ValueError: + return None # no palette + if rawmode is None: + rawmode = mode + return list(self.im.getpalette(mode, rawmode)) + + @property + def has_transparency_data(self) -> bool: + """ + Determine if an image has transparency data, whether in the form of an + alpha channel, a palette with an alpha channel, or a "transparency" key + in the info dictionary. + + Note the image might still appear solid, if all of the values shown + within are opaque. + + :returns: A boolean. + """ + if ( + self.mode in ("LA", "La", "PA", "RGBA", "RGBa") + or "transparency" in self.info + ): + return True + if self.mode == "P": + assert self.palette is not None + return self.palette.mode.endswith("A") + return False + + def apply_transparency(self) -> None: + """ + If a P mode image has a "transparency" key in the info dictionary, + remove the key and instead apply the transparency to the palette. + Otherwise, the image is unchanged. + """ + if self.mode != "P" or "transparency" not in self.info: + return + + from . import ImagePalette + + palette = self.getpalette("RGBA") + assert palette is not None + transparency = self.info["transparency"] + if isinstance(transparency, bytes): + for i, alpha in enumerate(transparency): + palette[i * 4 + 3] = alpha + else: + palette[transparency * 4 + 3] = 0 + self.palette = ImagePalette.ImagePalette("RGBA", bytes(palette)) + self.palette.dirty = 1 + + del self.info["transparency"] + + def getpixel( + self, xy: tuple[int, int] | list[int] + ) -> float | tuple[int, ...] | None: + """ + Returns the pixel value at a given position. + + :param xy: The coordinate, given as (x, y). See + :ref:`coordinate-system`. + :returns: The pixel value. If the image is a multi-layer image, + this method returns a tuple. + """ + + self.load() + return self.im.getpixel(tuple(xy)) + + def getprojection(self) -> tuple[list[int], list[int]]: + """ + Get projection to x and y axes + + :returns: Two sequences, indicating where there are non-zero + pixels along the X-axis and the Y-axis, respectively. + """ + + self.load() + x, y = self.im.getprojection() + return list(x), list(y) + + def histogram( + self, mask: Image | None = None, extrema: tuple[float, float] | None = None + ) -> list[int]: + """ + Returns a histogram for the image. The histogram is returned as a + list of pixel counts, one for each pixel value in the source + image. Counts are grouped into 256 bins for each band, even if + the image has more than 8 bits per band. If the image has more + than one band, the histograms for all bands are concatenated (for + example, the histogram for an "RGB" image contains 768 values). + + A bilevel image (mode "1") is treated as a grayscale ("L") image + by this method. + + If a mask is provided, the method returns a histogram for those + parts of the image where the mask image is non-zero. The mask + image must have the same size as the image, and be either a + bi-level image (mode "1") or a grayscale image ("L"). + + :param mask: An optional mask. + :param extrema: An optional tuple of manually-specified extrema. + :returns: A list containing pixel counts. + """ + self.load() + if mask: + mask.load() + return self.im.histogram((0, 0), mask.im) + if self.mode in ("I", "F"): + return self.im.histogram( + extrema if extrema is not None else self.getextrema() + ) + return self.im.histogram() + + def entropy( + self, mask: Image | None = None, extrema: tuple[float, float] | None = None + ) -> float: + """ + Calculates and returns the entropy for the image. + + A bilevel image (mode "1") is treated as a grayscale ("L") + image by this method. + + If a mask is provided, the method employs the histogram for + those parts of the image where the mask image is non-zero. + The mask image must have the same size as the image, and be + either a bi-level image (mode "1") or a grayscale image ("L"). + + :param mask: An optional mask. + :param extrema: An optional tuple of manually-specified extrema. + :returns: A float value representing the image entropy + """ + self.load() + if mask: + mask.load() + return self.im.entropy((0, 0), mask.im) + if self.mode in ("I", "F"): + return self.im.entropy( + extrema if extrema is not None else self.getextrema() + ) + return self.im.entropy() + + def paste( + self, + im: Image | str | float | tuple[float, ...], + box: Image | tuple[int, int, int, int] | tuple[int, int] | None = None, + mask: Image | None = None, + ) -> None: + """ + Pastes another image into this image. The box argument is either + a 2-tuple giving the upper left corner, a 4-tuple defining the + left, upper, right, and lower pixel coordinate, or None (same as + (0, 0)). See :ref:`coordinate-system`. If a 4-tuple is given, the size + of the pasted image must match the size of the region. + + If the modes don't match, the pasted image is converted to the mode of + this image (see the :py:meth:`~PIL.Image.Image.convert` method for + details). + + Instead of an image, the source can be a integer or tuple + containing pixel values. The method then fills the region + with the given color. When creating RGB images, you can + also use color strings as supported by the ImageColor module. See + :ref:`colors` for more information. + + If a mask is given, this method updates only the regions + indicated by the mask. You can use either "1", "L", "LA", "RGBA" + or "RGBa" images (if present, the alpha band is used as mask). + Where the mask is 255, the given image is copied as is. Where + the mask is 0, the current value is preserved. Intermediate + values will mix the two images together, including their alpha + channels if they have them. + + See :py:meth:`~PIL.Image.Image.alpha_composite` if you want to + combine images with respect to their alpha channels. + + :param im: Source image or pixel value (integer, float or tuple). + :param box: An optional 4-tuple giving the region to paste into. + If a 2-tuple is used instead, it's treated as the upper left + corner. If omitted or None, the source is pasted into the + upper left corner. + + If an image is given as the second argument and there is no + third, the box defaults to (0, 0), and the second argument + is interpreted as a mask image. + :param mask: An optional mask image. + """ + + if isinstance(box, Image): + if mask is not None: + msg = "If using second argument as mask, third argument must be None" + raise ValueError(msg) + # abbreviated paste(im, mask) syntax + mask = box + box = None + + if box is None: + box = (0, 0) + + if len(box) == 2: + # upper left corner given; get size from image or mask + if isinstance(im, Image): + size = im.size + elif isinstance(mask, Image): + size = mask.size + else: + # FIXME: use self.size here? + msg = "cannot determine region size; use 4-item box" + raise ValueError(msg) + box += (box[0] + size[0], box[1] + size[1]) + + source: core.ImagingCore | str | float | tuple[float, ...] + if isinstance(im, str): + from . import ImageColor + + source = ImageColor.getcolor(im, self.mode) + elif isinstance(im, Image): + im.load() + if self.mode != im.mode: + if self.mode != "RGB" or im.mode not in ("LA", "RGBA", "RGBa"): + # should use an adapter for this! + im = im.convert(self.mode) + source = im.im + else: + source = im + + self._ensure_mutable() + + if mask: + mask.load() + self.im.paste(source, box, mask.im) + else: + self.im.paste(source, box) + + def alpha_composite( + self, im: Image, dest: Sequence[int] = (0, 0), source: Sequence[int] = (0, 0) + ) -> None: + """'In-place' analog of Image.alpha_composite. Composites an image + onto this image. + + :param im: image to composite over this one + :param dest: Optional 2 tuple (left, top) specifying the upper + left corner in this (destination) image. + :param source: Optional 2 (left, top) tuple for the upper left + corner in the overlay source image, or 4 tuple (left, top, right, + bottom) for the bounds of the source rectangle + + Performance Note: Not currently implemented in-place in the core layer. + """ + + if not isinstance(source, (list, tuple)): + msg = "Source must be a list or tuple" + raise ValueError(msg) + if not isinstance(dest, (list, tuple)): + msg = "Destination must be a list or tuple" + raise ValueError(msg) + + if len(source) == 4: + overlay_crop_box = tuple(source) + elif len(source) == 2: + overlay_crop_box = tuple(source) + im.size + else: + msg = "Source must be a sequence of length 2 or 4" + raise ValueError(msg) + + if not len(dest) == 2: + msg = "Destination must be a sequence of length 2" + raise ValueError(msg) + if min(source) < 0: + msg = "Source must be non-negative" + raise ValueError(msg) + + # over image, crop if it's not the whole image. + if overlay_crop_box == (0, 0) + im.size: + overlay = im + else: + overlay = im.crop(overlay_crop_box) + + # target for the paste + box = tuple(dest) + (dest[0] + overlay.width, dest[1] + overlay.height) + + # destination image. don't copy if we're using the whole image. + if box == (0, 0) + self.size: + background = self + else: + background = self.crop(box) + + result = alpha_composite(background, overlay) + self.paste(result, box) + + def point( + self, + lut: ( + Sequence[float] + | NumpyArray + | Callable[[int], float] + | Callable[[ImagePointTransform], ImagePointTransform | float] + | ImagePointHandler + ), + mode: str | None = None, + ) -> Image: + """ + Maps this image through a lookup table or function. + + :param lut: A lookup table, containing 256 (or 65536 if + self.mode=="I" and mode == "L") values per band in the + image. A function can be used instead, it should take a + single argument. The function is called once for each + possible pixel value, and the resulting table is applied to + all bands of the image. + + It may also be an :py:class:`~PIL.Image.ImagePointHandler` + object:: + + class Example(Image.ImagePointHandler): + def point(self, im: Image) -> Image: + # Return result + :param mode: Output mode (default is same as input). This can only be used if + the source image has mode "L" or "P", and the output has mode "1" or the + source image mode is "I" and the output mode is "L". + :returns: An :py:class:`~PIL.Image.Image` object. + """ + + self.load() + + if isinstance(lut, ImagePointHandler): + return lut.point(self) + + if callable(lut): + # if it isn't a list, it should be a function + if self.mode in ("I", "I;16", "F"): + # check if the function can be used with point_transform + # UNDONE wiredfool -- I think this prevents us from ever doing + # a gamma function point transform on > 8bit images. + scale, offset = _getscaleoffset(lut) # type: ignore[arg-type] + return self._new(self.im.point_transform(scale, offset)) + # for other modes, convert the function to a table + flatLut = [lut(i) for i in range(256)] * self.im.bands # type: ignore[arg-type] + else: + flatLut = lut + + if self.mode == "F": + # FIXME: _imaging returns a confusing error message for this case + msg = "point operation not supported for this mode" + raise ValueError(msg) + + if mode != "F": + flatLut = [round(i) for i in flatLut] + return self._new(self.im.point(flatLut, mode)) + + def putalpha(self, alpha: Image | int) -> None: + """ + Adds or replaces the alpha layer in this image. If the image + does not have an alpha layer, it's converted to "LA" or "RGBA". + The new layer must be either "L" or "1". + + :param alpha: The new alpha layer. This can either be an "L" or "1" + image having the same size as this image, or an integer. + """ + + self._ensure_mutable() + + if self.mode not in ("LA", "PA", "RGBA"): + # attempt to promote self to a matching alpha mode + try: + mode = getmodebase(self.mode) + "A" + try: + self.im.setmode(mode) + except (AttributeError, ValueError) as e: + # do things the hard way + im = self.im.convert(mode) + if im.mode not in ("LA", "PA", "RGBA"): + msg = "alpha channel could not be added" + raise ValueError(msg) from e # sanity check + self.im = im + self._mode = self.im.mode + except KeyError as e: + msg = "illegal image mode" + raise ValueError(msg) from e + + if self.mode in ("LA", "PA"): + band = 1 + else: + band = 3 + + if isinstance(alpha, Image): + # alpha layer + if alpha.mode not in ("1", "L"): + msg = "illegal image mode" + raise ValueError(msg) + alpha.load() + if alpha.mode == "1": + alpha = alpha.convert("L") + else: + # constant alpha + try: + self.im.fillband(band, alpha) + except (AttributeError, ValueError): + # do things the hard way + alpha = new("L", self.size, alpha) + else: + return + + self.im.putband(alpha.im, band) + + def putdata( + self, + data: Sequence[float] | Sequence[Sequence[int]] | core.ImagingCore | NumpyArray, + scale: float = 1.0, + offset: float = 0.0, + ) -> None: + """ + Copies pixel data from a flattened sequence object into the image. The + values should start at the upper left corner (0, 0), continue to the + end of the line, followed directly by the first value of the second + line, and so on. Data will be read until either the image or the + sequence ends. The scale and offset values are used to adjust the + sequence values: **pixel = value*scale + offset**. + + :param data: A flattened sequence object. See :ref:`colors` for more + information about values. + :param scale: An optional scale value. The default is 1.0. + :param offset: An optional offset value. The default is 0.0. + """ + + self._ensure_mutable() + + self.im.putdata(data, scale, offset) + + def putpalette( + self, + data: ImagePalette.ImagePalette | bytes | Sequence[int], + rawmode: str = "RGB", + ) -> None: + """ + Attaches a palette to this image. The image must be a "P", "PA", "L" + or "LA" image. + + The palette sequence must contain at most 256 colors, made up of one + integer value for each channel in the raw mode. + For example, if the raw mode is "RGB", then it can contain at most 768 + values, made up of red, green and blue values for the corresponding pixel + index in the 256 colors. + If the raw mode is "RGBA", then it can contain at most 1024 values, + containing red, green, blue and alpha values. + + Alternatively, an 8-bit string may be used instead of an integer sequence. + + :param data: A palette sequence (either a list or a string). + :param rawmode: The raw mode of the palette. Either "RGB", "RGBA", or a mode + that can be transformed to "RGB" or "RGBA" (e.g. "R", "BGR;15", "RGBA;L"). + """ + from . import ImagePalette + + if self.mode not in ("L", "LA", "P", "PA"): + msg = "illegal image mode" + raise ValueError(msg) + if isinstance(data, ImagePalette.ImagePalette): + if data.rawmode is not None: + palette = ImagePalette.raw(data.rawmode, data.palette) + else: + palette = ImagePalette.ImagePalette(palette=data.palette) + palette.dirty = 1 + else: + if not isinstance(data, bytes): + data = bytes(data) + palette = ImagePalette.raw(rawmode, data) + self._mode = "PA" if "A" in self.mode else "P" + self.palette = palette + self.palette.mode = "RGBA" if "A" in rawmode else "RGB" + self.load() # install new palette + + def putpixel( + self, xy: tuple[int, int], value: float | tuple[int, ...] | list[int] + ) -> None: + """ + Modifies the pixel at the given position. The color is given as + a single numerical value for single-band images, and a tuple for + multi-band images. In addition to this, RGB and RGBA tuples are + accepted for P and PA images. See :ref:`colors` for more information. + + Note that this method is relatively slow. For more extensive changes, + use :py:meth:`~PIL.Image.Image.paste` or the :py:mod:`~PIL.ImageDraw` + module instead. + + See: + + * :py:meth:`~PIL.Image.Image.paste` + * :py:meth:`~PIL.Image.Image.putdata` + * :py:mod:`~PIL.ImageDraw` + + :param xy: The pixel coordinate, given as (x, y). See + :ref:`coordinate-system`. + :param value: The pixel value. + """ + + self._ensure_mutable() + + if ( + self.mode in ("P", "PA") + and isinstance(value, (list, tuple)) + and len(value) in [3, 4] + ): + # RGB or RGBA value for a P or PA image + if self.mode == "PA": + alpha = value[3] if len(value) == 4 else 255 + value = value[:3] + assert self.palette is not None + palette_index = self.palette.getcolor(tuple(value), self) + value = (palette_index, alpha) if self.mode == "PA" else palette_index + return self.im.putpixel(xy, value) + + def remap_palette( + self, dest_map: list[int], source_palette: bytes | bytearray | None = None + ) -> Image: + """ + Rewrites the image to reorder the palette. + + :param dest_map: A list of indexes into the original palette. + e.g. ``[1,0]`` would swap a two item palette, and ``list(range(256))`` + is the identity transform. + :param source_palette: Bytes or None. + :returns: An :py:class:`~PIL.Image.Image` object. + + """ + from . import ImagePalette + + if self.mode not in ("L", "P"): + msg = "illegal image mode" + raise ValueError(msg) + + bands = 3 + palette_mode = "RGB" + if source_palette is None: + if self.mode == "P": + self.load() + palette_mode = self.im.getpalettemode() + if palette_mode == "RGBA": + bands = 4 + source_palette = self.im.getpalette(palette_mode, palette_mode) + else: # L-mode + source_palette = bytearray(i // 3 for i in range(768)) + elif len(source_palette) > 768: + bands = 4 + palette_mode = "RGBA" + + palette_bytes = b"" + new_positions = [0] * 256 + + # pick only the used colors from the palette + for i, oldPosition in enumerate(dest_map): + palette_bytes += source_palette[ + oldPosition * bands : oldPosition * bands + bands + ] + new_positions[oldPosition] = i + + # replace the palette color id of all pixel with the new id + + # Palette images are [0..255], mapped through a 1 or 3 + # byte/color map. We need to remap the whole image + # from palette 1 to palette 2. New_positions is + # an array of indexes into palette 1. Palette 2 is + # palette 1 with any holes removed. + + # We're going to leverage the convert mechanism to use the + # C code to remap the image from palette 1 to palette 2, + # by forcing the source image into 'L' mode and adding a + # mapping 'L' mode palette, then converting back to 'L' + # sans palette thus converting the image bytes, then + # assigning the optimized RGB palette. + + # perf reference, 9500x4000 gif, w/~135 colors + # 14 sec prepatch, 1 sec postpatch with optimization forced. + + mapping_palette = bytearray(new_positions) + + m_im = self.copy() + m_im._mode = "P" + + m_im.palette = ImagePalette.ImagePalette( + palette_mode, palette=mapping_palette * bands + ) + # possibly set palette dirty, then + # m_im.putpalette(mapping_palette, 'L') # converts to 'P' + # or just force it. + # UNDONE -- this is part of the general issue with palettes + m_im.im.putpalette(palette_mode, palette_mode + ";L", m_im.palette.tobytes()) + + m_im = m_im.convert("L") + + m_im.putpalette(palette_bytes, palette_mode) + m_im.palette = ImagePalette.ImagePalette(palette_mode, palette=palette_bytes) + + if "transparency" in self.info: + try: + m_im.info["transparency"] = dest_map.index(self.info["transparency"]) + except ValueError: + if "transparency" in m_im.info: + del m_im.info["transparency"] + + return m_im + + def _get_safe_box( + self, + size: tuple[int, int], + resample: Resampling, + box: tuple[float, float, float, float], + ) -> tuple[int, int, int, int]: + """Expands the box so it includes adjacent pixels + that may be used by resampling with the given resampling filter. + """ + filter_support = _filters_support[resample] - 0.5 + scale_x = (box[2] - box[0]) / size[0] + scale_y = (box[3] - box[1]) / size[1] + support_x = filter_support * scale_x + support_y = filter_support * scale_y + + return ( + max(0, int(box[0] - support_x)), + max(0, int(box[1] - support_y)), + min(self.size[0], math.ceil(box[2] + support_x)), + min(self.size[1], math.ceil(box[3] + support_y)), + ) + + def resize( + self, + size: tuple[int, int] | list[int] | NumpyArray, + resample: int | None = None, + box: tuple[float, float, float, float] | None = None, + reducing_gap: float | None = None, + ) -> Image: + """ + Returns a resized copy of this image. + + :param size: The requested size in pixels, as a tuple or array: + (width, height). + :param resample: An optional resampling filter. This can be + one of :py:data:`Resampling.NEAREST`, :py:data:`Resampling.BOX`, + :py:data:`Resampling.BILINEAR`, :py:data:`Resampling.HAMMING`, + :py:data:`Resampling.BICUBIC` or :py:data:`Resampling.LANCZOS`. + If the image has mode "1" or "P", it is always set to + :py:data:`Resampling.NEAREST`. Otherwise, the default filter is + :py:data:`Resampling.BICUBIC`. See: :ref:`concept-filters`. + :param box: An optional 4-tuple of floats providing + the source image region to be scaled. + The values must be within (0, 0, width, height) rectangle. + If omitted or None, the entire source is used. + :param reducing_gap: Apply optimization by resizing the image + in two steps. First, reducing the image by integer times + using :py:meth:`~PIL.Image.Image.reduce`. + Second, resizing using regular resampling. The last step + changes size no less than by ``reducing_gap`` times. + ``reducing_gap`` may be None (no first step is performed) + or should be greater than 1.0. The bigger ``reducing_gap``, + the closer the result to the fair resampling. + The smaller ``reducing_gap``, the faster resizing. + With ``reducing_gap`` greater or equal to 3.0, the result is + indistinguishable from fair resampling in most cases. + The default value is None (no optimization). + :returns: An :py:class:`~PIL.Image.Image` object. + """ + + if resample is None: + resample = Resampling.BICUBIC + elif resample not in ( + Resampling.NEAREST, + Resampling.BILINEAR, + Resampling.BICUBIC, + Resampling.LANCZOS, + Resampling.BOX, + Resampling.HAMMING, + ): + msg = f"Unknown resampling filter ({resample})." + + filters = [ + f"{filter[1]} ({filter[0]})" + for filter in ( + (Resampling.NEAREST, "Image.Resampling.NEAREST"), + (Resampling.LANCZOS, "Image.Resampling.LANCZOS"), + (Resampling.BILINEAR, "Image.Resampling.BILINEAR"), + (Resampling.BICUBIC, "Image.Resampling.BICUBIC"), + (Resampling.BOX, "Image.Resampling.BOX"), + (Resampling.HAMMING, "Image.Resampling.HAMMING"), + ) + ] + msg += f" Use {', '.join(filters[:-1])} or {filters[-1]}" + raise ValueError(msg) + + if reducing_gap is not None and reducing_gap < 1.0: + msg = "reducing_gap must be 1.0 or greater" + raise ValueError(msg) + + if box is None: + box = (0, 0) + self.size + + size = tuple(size) + if self.size == size and box == (0, 0) + self.size: + return self.copy() + + if self.mode in ("1", "P"): + resample = Resampling.NEAREST + + if self.mode in ["LA", "RGBA"] and resample != Resampling.NEAREST: + im = self.convert({"LA": "La", "RGBA": "RGBa"}[self.mode]) + im = im.resize(size, resample, box) + return im.convert(self.mode) + + self.load() + + if reducing_gap is not None and resample != Resampling.NEAREST: + factor_x = int((box[2] - box[0]) / size[0] / reducing_gap) or 1 + factor_y = int((box[3] - box[1]) / size[1] / reducing_gap) or 1 + if factor_x > 1 or factor_y > 1: + reduce_box = self._get_safe_box(size, cast(Resampling, resample), box) + factor = (factor_x, factor_y) + self = ( + self.reduce(factor, box=reduce_box) + if callable(self.reduce) + else Image.reduce(self, factor, box=reduce_box) + ) + box = ( + (box[0] - reduce_box[0]) / factor_x, + (box[1] - reduce_box[1]) / factor_y, + (box[2] - reduce_box[0]) / factor_x, + (box[3] - reduce_box[1]) / factor_y, + ) + + return self._new(self.im.resize(size, resample, box)) + + def reduce( + self, + factor: int | tuple[int, int], + box: tuple[int, int, int, int] | None = None, + ) -> Image: + """ + Returns a copy of the image reduced ``factor`` times. + If the size of the image is not dividable by ``factor``, + the resulting size will be rounded up. + + :param factor: A greater than 0 integer or tuple of two integers + for width and height separately. + :param box: An optional 4-tuple of ints providing + the source image region to be reduced. + The values must be within ``(0, 0, width, height)`` rectangle. + If omitted or ``None``, the entire source is used. + """ + if not isinstance(factor, (list, tuple)): + factor = (factor, factor) + + if box is None: + box = (0, 0) + self.size + + if factor == (1, 1) and box == (0, 0) + self.size: + return self.copy() + + if self.mode in ["LA", "RGBA"]: + im = self.convert({"LA": "La", "RGBA": "RGBa"}[self.mode]) + im = im.reduce(factor, box) + return im.convert(self.mode) + + self.load() + + return self._new(self.im.reduce(factor, box)) + + def rotate( + self, + angle: float, + resample: Resampling = Resampling.NEAREST, + expand: int | bool = False, + center: tuple[float, float] | None = None, + translate: tuple[int, int] | None = None, + fillcolor: float | tuple[float, ...] | str | None = None, + ) -> Image: + """ + Returns a rotated copy of this image. This method returns a + copy of this image, rotated the given number of degrees counter + clockwise around its centre. + + :param angle: In degrees counter clockwise. + :param resample: An optional resampling filter. This can be + one of :py:data:`Resampling.NEAREST` (use nearest neighbour), + :py:data:`Resampling.BILINEAR` (linear interpolation in a 2x2 + environment), or :py:data:`Resampling.BICUBIC` (cubic spline + interpolation in a 4x4 environment). If omitted, or if the image has + mode "1" or "P", it is set to :py:data:`Resampling.NEAREST`. + See :ref:`concept-filters`. + :param expand: Optional expansion flag. If true, expands the output + image to make it large enough to hold the entire rotated image. + If false or omitted, make the output image the same size as the + input image. Note that the expand flag assumes rotation around + the center and no translation. + :param center: Optional center of rotation (a 2-tuple). Origin is + the upper left corner. Default is the center of the image. + :param translate: An optional post-rotate translation (a 2-tuple). + :param fillcolor: An optional color for area outside the rotated image. + :returns: An :py:class:`~PIL.Image.Image` object. + """ + + angle = angle % 360.0 + + # Fast paths regardless of filter, as long as we're not + # translating or changing the center. + if not (center or translate): + if angle == 0: + return self.copy() + if angle == 180: + return self.transpose(Transpose.ROTATE_180) + if angle in (90, 270) and (expand or self.width == self.height): + return self.transpose( + Transpose.ROTATE_90 if angle == 90 else Transpose.ROTATE_270 + ) + + # Calculate the affine matrix. Note that this is the reverse + # transformation (from destination image to source) because we + # want to interpolate the (discrete) destination pixel from + # the local area around the (floating) source pixel. + + # The matrix we actually want (note that it operates from the right): + # (1, 0, tx) (1, 0, cx) ( cos a, sin a, 0) (1, 0, -cx) + # (0, 1, ty) * (0, 1, cy) * (-sin a, cos a, 0) * (0, 1, -cy) + # (0, 0, 1) (0, 0, 1) ( 0, 0, 1) (0, 0, 1) + + # The reverse matrix is thus: + # (1, 0, cx) ( cos -a, sin -a, 0) (1, 0, -cx) (1, 0, -tx) + # (0, 1, cy) * (-sin -a, cos -a, 0) * (0, 1, -cy) * (0, 1, -ty) + # (0, 0, 1) ( 0, 0, 1) (0, 0, 1) (0, 0, 1) + + # In any case, the final translation may be updated at the end to + # compensate for the expand flag. + + w, h = self.size + + if translate is None: + post_trans = (0, 0) + else: + post_trans = translate + if center is None: + center = (w / 2, h / 2) + + angle = -math.radians(angle) + matrix = [ + round(math.cos(angle), 15), + round(math.sin(angle), 15), + 0.0, + round(-math.sin(angle), 15), + round(math.cos(angle), 15), + 0.0, + ] + + def transform(x: float, y: float, matrix: list[float]) -> tuple[float, float]: + (a, b, c, d, e, f) = matrix + return a * x + b * y + c, d * x + e * y + f + + matrix[2], matrix[5] = transform( + -center[0] - post_trans[0], -center[1] - post_trans[1], matrix + ) + matrix[2] += center[0] + matrix[5] += center[1] + + if expand: + # calculate output size + xx = [] + yy = [] + for x, y in ((0, 0), (w, 0), (w, h), (0, h)): + transformed_x, transformed_y = transform(x, y, matrix) + xx.append(transformed_x) + yy.append(transformed_y) + nw = math.ceil(max(xx)) - math.floor(min(xx)) + nh = math.ceil(max(yy)) - math.floor(min(yy)) + + # We multiply a translation matrix from the right. Because of its + # special form, this is the same as taking the image of the + # translation vector as new translation vector. + matrix[2], matrix[5] = transform(-(nw - w) / 2.0, -(nh - h) / 2.0, matrix) + w, h = nw, nh + + return self.transform( + (w, h), Transform.AFFINE, matrix, resample, fillcolor=fillcolor + ) + + def save( + self, fp: StrOrBytesPath | IO[bytes], format: str | None = None, **params: Any + ) -> None: + """ + Saves this image under the given filename. If no format is + specified, the format to use is determined from the filename + extension, if possible. + + Keyword options can be used to provide additional instructions + to the writer. If a writer doesn't recognise an option, it is + silently ignored. The available options are described in the + :doc:`image format documentation + <../handbook/image-file-formats>` for each writer. + + You can use a file object instead of a filename. In this case, + you must always specify the format. The file object must + implement the ``seek``, ``tell``, and ``write`` + methods, and be opened in binary mode. + + :param fp: A filename (string), os.PathLike object or file object. + :param format: Optional format override. If omitted, the + format to use is determined from the filename extension. + If a file object was used instead of a filename, this + parameter should always be used. + :param params: Extra parameters to the image writer. These can also be + set on the image itself through ``encoderinfo``. This is useful when + saving multiple images:: + + # Saving XMP data to a single image + from PIL import Image + red = Image.new("RGB", (1, 1), "#f00") + red.save("out.mpo", xmp=b"test") + + # Saving XMP data to the second frame of an image + from PIL import Image + black = Image.new("RGB", (1, 1)) + red = Image.new("RGB", (1, 1), "#f00") + red.encoderinfo = {"xmp": b"test"} + black.save("out.mpo", save_all=True, append_images=[red]) + :returns: None + :exception ValueError: If the output format could not be determined + from the file name. Use the format option to solve this. + :exception OSError: If the file could not be written. The file + may have been created, and may contain partial data. + """ + + filename: str | bytes = "" + open_fp = False + if is_path(fp): + filename = os.fspath(fp) + open_fp = True + elif fp == sys.stdout: + try: + fp = sys.stdout.buffer + except AttributeError: + pass + if not filename and hasattr(fp, "name") and is_path(fp.name): + # only set the name for metadata purposes + filename = os.fspath(fp.name) + + preinit() + + filename_ext = os.path.splitext(filename)[1].lower() + ext = filename_ext.decode() if isinstance(filename_ext, bytes) else filename_ext + + if not format: + if ext not in EXTENSION: + init() + try: + format = EXTENSION[ext] + except KeyError as e: + msg = f"unknown file extension: {ext}" + raise ValueError(msg) from e + + from . import ImageFile + + # may mutate self! + if isinstance(self, ImageFile.ImageFile) and os.path.abspath( + filename + ) == os.path.abspath(self.filename): + self._ensure_mutable() + else: + self.load() + + save_all = params.pop("save_all", None) + self._default_encoderinfo = params + encoderinfo = getattr(self, "encoderinfo", {}) + self._attach_default_encoderinfo(self) + self.encoderconfig: tuple[Any, ...] = () + + if format.upper() not in SAVE: + init() + if save_all or ( + save_all is None + and params.get("append_images") + and format.upper() in SAVE_ALL + ): + save_handler = SAVE_ALL[format.upper()] + else: + save_handler = SAVE[format.upper()] + + created = False + if open_fp: + created = not os.path.exists(filename) + if params.get("append", False): + # Open also for reading ("+"), because TIFF save_all + # writer needs to go back and edit the written data. + fp = builtins.open(filename, "r+b") + else: + fp = builtins.open(filename, "w+b") + else: + fp = cast(IO[bytes], fp) + + try: + save_handler(self, fp, filename) + except Exception: + if open_fp: + fp.close() + if created: + try: + os.remove(filename) + except PermissionError: + pass + raise + finally: + self.encoderinfo = encoderinfo + if open_fp: + fp.close() + + def _attach_default_encoderinfo(self, im: Image) -> dict[str, Any]: + encoderinfo = getattr(self, "encoderinfo", {}) + self.encoderinfo = {**im._default_encoderinfo, **encoderinfo} + return encoderinfo + + def seek(self, frame: int) -> None: + """ + Seeks to the given frame in this sequence file. If you seek + beyond the end of the sequence, the method raises an + ``EOFError`` exception. When a sequence file is opened, the + library automatically seeks to frame 0. + + See :py:meth:`~PIL.Image.Image.tell`. + + If defined, :attr:`~PIL.Image.Image.n_frames` refers to the + number of available frames. + + :param frame: Frame number, starting at 0. + :exception EOFError: If the call attempts to seek beyond the end + of the sequence. + """ + + # overridden by file handlers + if frame != 0: + msg = "no more images in file" + raise EOFError(msg) + + def show(self, title: str | None = None) -> None: + """ + Displays this image. This method is mainly intended for debugging purposes. + + This method calls :py:func:`PIL.ImageShow.show` internally. You can use + :py:func:`PIL.ImageShow.register` to override its default behaviour. + + The image is first saved to a temporary file. By default, it will be in + PNG format. + + On Unix, the image is then opened using the **xdg-open**, **display**, + **gm**, **eog** or **xv** utility, depending on which one can be found. + + On macOS, the image is opened with the native Preview application. + + On Windows, the image is opened with the standard PNG display utility. + + :param title: Optional title to use for the image window, where possible. + """ + + from . import ImageShow + + ImageShow.show(self, title) + + def split(self) -> tuple[Image, ...]: + """ + Split this image into individual bands. This method returns a + tuple of individual image bands from an image. For example, + splitting an "RGB" image creates three new images each + containing a copy of one of the original bands (red, green, + blue). + + If you need only one band, :py:meth:`~PIL.Image.Image.getchannel` + method can be more convenient and faster. + + :returns: A tuple containing bands. + """ + + self.load() + if self.im.bands == 1: + return (self.copy(),) + return tuple(map(self._new, self.im.split())) + + def getchannel(self, channel: int | str) -> Image: + """ + Returns an image containing a single channel of the source image. + + :param channel: What channel to return. Could be index + (0 for "R" channel of "RGB") or channel name + ("A" for alpha channel of "RGBA"). + :returns: An image in "L" mode. + + .. versionadded:: 4.3.0 + """ + self.load() + + if isinstance(channel, str): + try: + channel = self.getbands().index(channel) + except ValueError as e: + msg = f'The image has no channel "{channel}"' + raise ValueError(msg) from e + + return self._new(self.im.getband(channel)) + + def tell(self) -> int: + """ + Returns the current frame number. See :py:meth:`~PIL.Image.Image.seek`. + + If defined, :attr:`~PIL.Image.Image.n_frames` refers to the + number of available frames. + + :returns: Frame number, starting with 0. + """ + return 0 + + def thumbnail( + self, + size: tuple[float, float], + resample: Resampling = Resampling.BICUBIC, + reducing_gap: float | None = 2.0, + ) -> None: + """ + Make this image into a thumbnail. This method modifies the + image to contain a thumbnail version of itself, no larger than + the given size. This method calculates an appropriate thumbnail + size to preserve the aspect of the image, calls the + :py:meth:`~PIL.Image.Image.draft` method to configure the file reader + (where applicable), and finally resizes the image. + + Note that this function modifies the :py:class:`~PIL.Image.Image` + object in place. If you need to use the full resolution image as well, + apply this method to a :py:meth:`~PIL.Image.Image.copy` of the original + image. + + :param size: The requested size in pixels, as a 2-tuple: + (width, height). + :param resample: Optional resampling filter. This can be one + of :py:data:`Resampling.NEAREST`, :py:data:`Resampling.BOX`, + :py:data:`Resampling.BILINEAR`, :py:data:`Resampling.HAMMING`, + :py:data:`Resampling.BICUBIC` or :py:data:`Resampling.LANCZOS`. + If omitted, it defaults to :py:data:`Resampling.BICUBIC`. + (was :py:data:`Resampling.NEAREST` prior to version 2.5.0). + See: :ref:`concept-filters`. + :param reducing_gap: Apply optimization by resizing the image + in two steps. First, reducing the image by integer times + using :py:meth:`~PIL.Image.Image.reduce` or + :py:meth:`~PIL.Image.Image.draft` for JPEG images. + Second, resizing using regular resampling. The last step + changes size no less than by ``reducing_gap`` times. + ``reducing_gap`` may be None (no first step is performed) + or should be greater than 1.0. The bigger ``reducing_gap``, + the closer the result to the fair resampling. + The smaller ``reducing_gap``, the faster resizing. + With ``reducing_gap`` greater or equal to 3.0, the result is + indistinguishable from fair resampling in most cases. + The default value is 2.0 (very close to fair resampling + while still being faster in many cases). + :returns: None + """ + + provided_size = tuple(map(math.floor, size)) + + def preserve_aspect_ratio() -> tuple[int, int] | None: + def round_aspect(number: float, key: Callable[[int], float]) -> int: + return max(min(math.floor(number), math.ceil(number), key=key), 1) + + x, y = provided_size + if x >= self.width and y >= self.height: + return None + + aspect = self.width / self.height + if x / y >= aspect: + x = round_aspect(y * aspect, key=lambda n: abs(aspect - n / y)) + else: + y = round_aspect( + x / aspect, key=lambda n: 0 if n == 0 else abs(aspect - x / n) + ) + return x, y + + preserved_size = preserve_aspect_ratio() + if preserved_size is None: + return + final_size = preserved_size + + box = None + if reducing_gap is not None: + res = self.draft( + None, (int(size[0] * reducing_gap), int(size[1] * reducing_gap)) + ) + if res is not None: + box = res[1] + + if self.size != final_size: + im = self.resize(final_size, resample, box=box, reducing_gap=reducing_gap) + + self.im = im.im + self._size = final_size + self._mode = self.im.mode + + self.readonly = 0 + + # FIXME: the different transform methods need further explanation + # instead of bloating the method docs, add a separate chapter. + def transform( + self, + size: tuple[int, int], + method: Transform | ImageTransformHandler | SupportsGetData, + data: Sequence[Any] | None = None, + resample: int = Resampling.NEAREST, + fill: int = 1, + fillcolor: float | tuple[float, ...] | str | None = None, + ) -> Image: + """ + Transforms this image. This method creates a new image with the + given size, and the same mode as the original, and copies data + to the new image using the given transform. + + :param size: The output size in pixels, as a 2-tuple: + (width, height). + :param method: The transformation method. This is one of + :py:data:`Transform.EXTENT` (cut out a rectangular subregion), + :py:data:`Transform.AFFINE` (affine transform), + :py:data:`Transform.PERSPECTIVE` (perspective transform), + :py:data:`Transform.QUAD` (map a quadrilateral to a rectangle), or + :py:data:`Transform.MESH` (map a number of source quadrilaterals + in one operation). + + It may also be an :py:class:`~PIL.Image.ImageTransformHandler` + object:: + + class Example(Image.ImageTransformHandler): + def transform(self, size, data, resample, fill=1): + # Return result + + Implementations of :py:class:`~PIL.Image.ImageTransformHandler` + for some of the :py:class:`Transform` methods are provided + in :py:mod:`~PIL.ImageTransform`. + + It may also be an object with a ``method.getdata`` method + that returns a tuple supplying new ``method`` and ``data`` values:: + + class Example: + def getdata(self): + method = Image.Transform.EXTENT + data = (0, 0, 100, 100) + return method, data + :param data: Extra data to the transformation method. + :param resample: Optional resampling filter. It can be one of + :py:data:`Resampling.NEAREST` (use nearest neighbour), + :py:data:`Resampling.BILINEAR` (linear interpolation in a 2x2 + environment), or :py:data:`Resampling.BICUBIC` (cubic spline + interpolation in a 4x4 environment). If omitted, or if the image + has mode "1" or "P", it is set to :py:data:`Resampling.NEAREST`. + See: :ref:`concept-filters`. + :param fill: If ``method`` is an + :py:class:`~PIL.Image.ImageTransformHandler` object, this is one of + the arguments passed to it. Otherwise, it is unused. + :param fillcolor: Optional fill color for the area outside the + transform in the output image. + :returns: An :py:class:`~PIL.Image.Image` object. + """ + + if self.mode in ("LA", "RGBA") and resample != Resampling.NEAREST: + return ( + self.convert({"LA": "La", "RGBA": "RGBa"}[self.mode]) + .transform(size, method, data, resample, fill, fillcolor) + .convert(self.mode) + ) + + if isinstance(method, ImageTransformHandler): + return method.transform(size, self, resample=resample, fill=fill) + + if hasattr(method, "getdata"): + # compatibility w. old-style transform objects + method, data = method.getdata() + + if data is None: + msg = "missing method data" + raise ValueError(msg) + + im = new(self.mode, size, fillcolor) + if self.mode == "P" and self.palette: + im.palette = self.palette.copy() + im.info = self.info.copy() + if method == Transform.MESH: + # list of quads + for box, quad in data: + im.__transformer( + box, self, Transform.QUAD, quad, resample, fillcolor is None + ) + else: + im.__transformer( + (0, 0) + size, self, method, data, resample, fillcolor is None + ) + + return im + + def __transformer( + self, + box: tuple[int, int, int, int], + image: Image, + method: Transform, + data: Sequence[float], + resample: int = Resampling.NEAREST, + fill: bool = True, + ) -> None: + w = box[2] - box[0] + h = box[3] - box[1] + + if method == Transform.AFFINE: + data = data[:6] + + elif method == Transform.EXTENT: + # convert extent to an affine transform + x0, y0, x1, y1 = data + xs = (x1 - x0) / w + ys = (y1 - y0) / h + method = Transform.AFFINE + data = (xs, 0, x0, 0, ys, y0) + + elif method == Transform.PERSPECTIVE: + data = data[:8] + + elif method == Transform.QUAD: + # quadrilateral warp. data specifies the four corners + # given as NW, SW, SE, and NE. + nw = data[:2] + sw = data[2:4] + se = data[4:6] + ne = data[6:8] + x0, y0 = nw + As = 1.0 / w + At = 1.0 / h + data = ( + x0, + (ne[0] - x0) * As, + (sw[0] - x0) * At, + (se[0] - sw[0] - ne[0] + x0) * As * At, + y0, + (ne[1] - y0) * As, + (sw[1] - y0) * At, + (se[1] - sw[1] - ne[1] + y0) * As * At, + ) + + else: + msg = "unknown transformation method" + raise ValueError(msg) + + if resample not in ( + Resampling.NEAREST, + Resampling.BILINEAR, + Resampling.BICUBIC, + ): + if resample in (Resampling.BOX, Resampling.HAMMING, Resampling.LANCZOS): + unusable: dict[int, str] = { + Resampling.BOX: "Image.Resampling.BOX", + Resampling.HAMMING: "Image.Resampling.HAMMING", + Resampling.LANCZOS: "Image.Resampling.LANCZOS", + } + msg = unusable[resample] + f" ({resample}) cannot be used." + else: + msg = f"Unknown resampling filter ({resample})." + + filters = [ + f"{filter[1]} ({filter[0]})" + for filter in ( + (Resampling.NEAREST, "Image.Resampling.NEAREST"), + (Resampling.BILINEAR, "Image.Resampling.BILINEAR"), + (Resampling.BICUBIC, "Image.Resampling.BICUBIC"), + ) + ] + msg += f" Use {', '.join(filters[:-1])} or {filters[-1]}" + raise ValueError(msg) + + image.load() + + self.load() + + if image.mode in ("1", "P"): + resample = Resampling.NEAREST + + self.im.transform(box, image.im, method, data, resample, fill) + + def transpose(self, method: Transpose) -> Image: + """ + Transpose image (flip or rotate in 90 degree steps) + + :param method: One of :py:data:`Transpose.FLIP_LEFT_RIGHT`, + :py:data:`Transpose.FLIP_TOP_BOTTOM`, :py:data:`Transpose.ROTATE_90`, + :py:data:`Transpose.ROTATE_180`, :py:data:`Transpose.ROTATE_270`, + :py:data:`Transpose.TRANSPOSE` or :py:data:`Transpose.TRANSVERSE`. + :returns: Returns a flipped or rotated copy of this image. + """ + + self.load() + return self._new(self.im.transpose(method)) + + def effect_spread(self, distance: int) -> Image: + """ + Randomly spread pixels in an image. + + :param distance: Distance to spread pixels. + """ + self.load() + return self._new(self.im.effect_spread(distance)) + + def toqimage(self) -> ImageQt.ImageQt: + """Returns a QImage copy of this image""" + from . import ImageQt + + if not ImageQt.qt_is_installed: + msg = "Qt bindings are not installed" + raise ImportError(msg) + return ImageQt.toqimage(self) + + def toqpixmap(self) -> ImageQt.QPixmap: + """Returns a QPixmap copy of this image""" + from . import ImageQt + + if not ImageQt.qt_is_installed: + msg = "Qt bindings are not installed" + raise ImportError(msg) + return ImageQt.toqpixmap(self) + + +# -------------------------------------------------------------------- +# Abstract handlers. + + +class ImagePointHandler(abc.ABC): + """ + Used as a mixin by point transforms + (for use with :py:meth:`~PIL.Image.Image.point`) + """ + + @abc.abstractmethod + def point(self, im: Image) -> Image: + pass + + +class ImageTransformHandler(abc.ABC): + """ + Used as a mixin by geometry transforms + (for use with :py:meth:`~PIL.Image.Image.transform`) + """ + + @abc.abstractmethod + def transform( + self, + size: tuple[int, int], + image: Image, + **options: Any, + ) -> Image: + pass + + +# -------------------------------------------------------------------- +# Factories + + +def _check_size(size: Any) -> None: + """ + Common check to enforce type and sanity check on size tuples + + :param size: Should be a 2 tuple of (width, height) + :returns: None, or raises a ValueError + """ + + if not isinstance(size, (list, tuple)): + msg = "Size must be a list or tuple" + raise ValueError(msg) + if len(size) != 2: + msg = "Size must be a sequence of length 2" + raise ValueError(msg) + if size[0] < 0 or size[1] < 0: + msg = "Width and height must be >= 0" + raise ValueError(msg) + + +def new( + mode: str, + size: tuple[int, int] | list[int], + color: float | tuple[float, ...] | str | None = 0, +) -> Image: + """ + Creates a new image with the given mode and size. + + :param mode: The mode to use for the new image. See: + :ref:`concept-modes`. + :param size: A 2-tuple, containing (width, height) in pixels. + :param color: What color to use for the image. Default is black. If given, + this should be a single integer or floating point value for single-band + modes, and a tuple for multi-band modes (one value per band). When + creating RGB or HSV images, you can also use color strings as supported + by the ImageColor module. See :ref:`colors` for more information. If the + color is None, the image is not initialised. + :returns: An :py:class:`~PIL.Image.Image` object. + """ + + _check_size(size) + + if color is None: + # don't initialize + return Image()._new(core.new(mode, size)) + + if isinstance(color, str): + # css3-style specifier + + from . import ImageColor + + color = ImageColor.getcolor(color, mode) + + im = Image() + if ( + mode == "P" + and isinstance(color, (list, tuple)) + and all(isinstance(i, int) for i in color) + ): + color_ints: tuple[int, ...] = cast(tuple[int, ...], tuple(color)) + if len(color_ints) == 3 or len(color_ints) == 4: + # RGB or RGBA value for a P image + from . import ImagePalette + + im.palette = ImagePalette.ImagePalette() + color = im.palette.getcolor(color_ints) + return im._new(core.fill(mode, size, color)) + + +def frombytes( + mode: str, + size: tuple[int, int], + data: bytes | bytearray | SupportsArrayInterface, + decoder_name: str = "raw", + *args: Any, +) -> Image: + """ + Creates a copy of an image memory from pixel data in a buffer. + + In its simplest form, this function takes three arguments + (mode, size, and unpacked pixel data). + + You can also use any pixel decoder supported by PIL. For more + information on available decoders, see the section + :ref:`Writing Your Own File Codec `. + + Note that this function decodes pixel data only, not entire images. + If you have an entire image in a string, wrap it in a + :py:class:`~io.BytesIO` object, and use :py:func:`~PIL.Image.open` to load + it. + + :param mode: The image mode. See: :ref:`concept-modes`. + :param size: The image size. + :param data: A byte buffer containing raw data for the given mode. + :param decoder_name: What decoder to use. + :param args: Additional parameters for the given decoder. + :returns: An :py:class:`~PIL.Image.Image` object. + """ + + _check_size(size) + + im = new(mode, size) + if im.width != 0 and im.height != 0: + decoder_args: Any = args + if len(decoder_args) == 1 and isinstance(decoder_args[0], tuple): + # may pass tuple instead of argument list + decoder_args = decoder_args[0] + + if decoder_name == "raw" and decoder_args == (): + decoder_args = mode + + im.frombytes(data, decoder_name, decoder_args) + return im + + +def frombuffer( + mode: str, + size: tuple[int, int], + data: bytes | SupportsArrayInterface, + decoder_name: str = "raw", + *args: Any, +) -> Image: + """ + Creates an image memory referencing pixel data in a byte buffer. + + This function is similar to :py:func:`~PIL.Image.frombytes`, but uses data + in the byte buffer, where possible. This means that changes to the + original buffer object are reflected in this image). Not all modes can + share memory; supported modes include "L", "RGBX", "RGBA", and "CMYK". + + Note that this function decodes pixel data only, not entire images. + If you have an entire image file in a string, wrap it in a + :py:class:`~io.BytesIO` object, and use :py:func:`~PIL.Image.open` to load it. + + The default parameters used for the "raw" decoder differs from that used for + :py:func:`~PIL.Image.frombytes`. This is a bug, and will probably be fixed in a + future release. The current release issues a warning if you do this; to disable + the warning, you should provide the full set of parameters. See below for details. + + :param mode: The image mode. See: :ref:`concept-modes`. + :param size: The image size. + :param data: A bytes or other buffer object containing raw + data for the given mode. + :param decoder_name: What decoder to use. + :param args: Additional parameters for the given decoder. For the + default encoder ("raw"), it's recommended that you provide the + full set of parameters:: + + frombuffer(mode, size, data, "raw", mode, 0, 1) + + :returns: An :py:class:`~PIL.Image.Image` object. + + .. versionadded:: 1.1.4 + """ + + _check_size(size) + + # may pass tuple instead of argument list + if len(args) == 1 and isinstance(args[0], tuple): + args = args[0] + + if decoder_name == "raw": + if args == (): + args = mode, 0, 1 + if args[0] in _MAPMODES: + im = new(mode, (0, 0)) + im = im._new(core.map_buffer(data, size, decoder_name, 0, args)) + if mode == "P": + from . import ImagePalette + + im.palette = ImagePalette.ImagePalette("RGB", im.im.getpalette("RGB")) + im.readonly = 1 + return im + + return frombytes(mode, size, data, decoder_name, args) + + +class SupportsArrayInterface(Protocol): + """ + An object that has an ``__array_interface__`` dictionary. + """ + + @property + def __array_interface__(self) -> dict[str, Any]: + raise NotImplementedError() + + +class SupportsArrowArrayInterface(Protocol): + """ + An object that has an ``__arrow_c_array__`` method corresponding to the arrow c + data interface. + """ + + def __arrow_c_array__( + self, requested_schema: "PyCapsule" = None # type: ignore[name-defined] # noqa: F821, UP037 + ) -> tuple["PyCapsule", "PyCapsule"]: # type: ignore[name-defined] # noqa: F821, UP037 + raise NotImplementedError() + + +def fromarray(obj: SupportsArrayInterface, mode: str | None = None) -> Image: + """ + Creates an image memory from an object exporting the array interface + (using the buffer protocol):: + + from PIL import Image + import numpy as np + a = np.zeros((5, 5)) + im = Image.fromarray(a) + + If ``obj`` is not contiguous, then the ``tobytes`` method is called + and :py:func:`~PIL.Image.frombuffer` is used. + + In the case of NumPy, be aware that Pillow modes do not always correspond + to NumPy dtypes. Pillow modes only offer 1-bit pixels, 8-bit pixels, + 32-bit signed integer pixels, and 32-bit floating point pixels. + + Pillow images can also be converted to arrays:: + + from PIL import Image + import numpy as np + im = Image.open("hopper.jpg") + a = np.asarray(im) + + When converting Pillow images to arrays however, only pixel values are + transferred. This means that P and PA mode images will lose their palette. + + :param obj: Object with array interface + :param mode: Optional mode to use when reading ``obj``. Since pixel values do not + contain information about palettes or color spaces, this can be used to place + grayscale L mode data within a P mode image, or read RGB data as YCbCr for + example. + + See: :ref:`concept-modes` for general information about modes. + :returns: An image object. + + .. versionadded:: 1.1.6 + """ + arr = obj.__array_interface__ + shape = arr["shape"] + ndim = len(shape) + strides = arr.get("strides", None) + try: + typekey = (1, 1) + shape[2:], arr["typestr"] + except KeyError as e: + if mode is not None: + typekey = None + color_modes: list[str] = [] + else: + msg = "Cannot handle this data type" + raise TypeError(msg) from e + if typekey is not None: + try: + typemode, rawmode, color_modes = _fromarray_typemap[typekey] + except KeyError as e: + typekey_shape, typestr = typekey + msg = f"Cannot handle this data type: {typekey_shape}, {typestr}" + raise TypeError(msg) from e + if mode is not None: + if mode != typemode and mode not in color_modes: + deprecate("'mode' parameter for changing data types", 13) + rawmode = mode + else: + mode = typemode + if mode in ["1", "L", "I", "P", "F"]: + ndmax = 2 + elif mode == "RGB": + ndmax = 3 + else: + ndmax = 4 + if ndim > ndmax: + msg = f"Too many dimensions: {ndim} > {ndmax}." + raise ValueError(msg) + + size = 1 if ndim == 1 else shape[1], shape[0] + if strides is not None: + if hasattr(obj, "tobytes"): + obj = obj.tobytes() + elif hasattr(obj, "tostring"): + obj = obj.tostring() + else: + msg = "'strides' requires either tobytes() or tostring()" + raise ValueError(msg) + + return frombuffer(mode, size, obj, "raw", rawmode, 0, 1) + + +def fromarrow( + obj: SupportsArrowArrayInterface, mode: str, size: tuple[int, int] +) -> Image: + """Creates an image with zero-copy shared memory from an object exporting + the arrow_c_array interface protocol:: + + from PIL import Image + import pyarrow as pa + arr = pa.array([0]*(5*5*4), type=pa.uint8()) + im = Image.fromarrow(arr, 'RGBA', (5, 5)) + + If the data representation of the ``obj`` is not compatible with + Pillow internal storage, a ValueError is raised. + + Pillow images can also be converted to Arrow objects:: + + from PIL import Image + import pyarrow as pa + im = Image.open('hopper.jpg') + arr = pa.array(im) + + As with array support, when converting Pillow images to arrays, + only pixel values are transferred. This means that P and PA mode + images will lose their palette. + + :param obj: Object with an arrow_c_array interface + :param mode: Image mode. + :param size: Image size. This must match the storage of the arrow object. + :returns: An Image object + + Note that according to the Arrow spec, both the producer and the + consumer should consider the exported array to be immutable, as + unsynchronized updates will potentially cause inconsistent data. + + See: :ref:`arrow-support` for more detailed information + + .. versionadded:: 11.2.1 + + """ + if not hasattr(obj, "__arrow_c_array__"): + msg = "arrow_c_array interface not found" + raise ValueError(msg) + + (schema_capsule, array_capsule) = obj.__arrow_c_array__() + _im = core.new_arrow(mode, size, schema_capsule, array_capsule) + if _im: + return Image()._new(_im) + + msg = "new_arrow returned None without an exception" + raise ValueError(msg) + + +def fromqimage(im: ImageQt.QImage) -> ImageFile.ImageFile: + """Creates an image instance from a QImage image""" + from . import ImageQt + + if not ImageQt.qt_is_installed: + msg = "Qt bindings are not installed" + raise ImportError(msg) + return ImageQt.fromqimage(im) + + +def fromqpixmap(im: ImageQt.QPixmap) -> ImageFile.ImageFile: + """Creates an image instance from a QPixmap image""" + from . import ImageQt + + if not ImageQt.qt_is_installed: + msg = "Qt bindings are not installed" + raise ImportError(msg) + return ImageQt.fromqpixmap(im) + + +_fromarray_typemap = { + # (shape, typestr) => mode, rawmode, color modes + # first two members of shape are set to one + ((1, 1), "|b1"): ("1", "1;8", []), + ((1, 1), "|u1"): ("L", "L", ["P"]), + ((1, 1), "|i1"): ("I", "I;8", []), + ((1, 1), "u2"): ("I", "I;16B", []), + ((1, 1), "i2"): ("I", "I;16BS", []), + ((1, 1), "u4"): ("I", "I;32B", []), + ((1, 1), "i4"): ("I", "I;32BS", []), + ((1, 1), "f4"): ("F", "F;32BF", []), + ((1, 1), "f8"): ("F", "F;64BF", []), + ((1, 1, 2), "|u1"): ("LA", "LA", ["La", "PA"]), + ((1, 1, 3), "|u1"): ("RGB", "RGB", ["YCbCr", "LAB", "HSV"]), + ((1, 1, 4), "|u1"): ("RGBA", "RGBA", ["RGBa", "RGBX", "CMYK"]), + # shortcuts: + ((1, 1), f"{_ENDIAN}i4"): ("I", "I", []), + ((1, 1), f"{_ENDIAN}f4"): ("F", "F", []), +} + + +def _decompression_bomb_check(size: tuple[int, int]) -> None: + if MAX_IMAGE_PIXELS is None: + return + + pixels = max(1, size[0]) * max(1, size[1]) + + if pixels > 2 * MAX_IMAGE_PIXELS: + msg = ( + f"Image size ({pixels} pixels) exceeds limit of {2 * MAX_IMAGE_PIXELS} " + "pixels, could be decompression bomb DOS attack." + ) + raise DecompressionBombError(msg) + + if pixels > MAX_IMAGE_PIXELS: + warnings.warn( + f"Image size ({pixels} pixels) exceeds limit of {MAX_IMAGE_PIXELS} pixels, " + "could be decompression bomb DOS attack.", + DecompressionBombWarning, + ) + + +def open( + fp: StrOrBytesPath | IO[bytes], + mode: Literal["r"] = "r", + formats: list[str] | tuple[str, ...] | None = None, +) -> ImageFile.ImageFile: + """ + Opens and identifies the given image file. + + This is a lazy operation; this function identifies the file, but + the file remains open and the actual image data is not read from + the file until you try to process the data (or call the + :py:meth:`~PIL.Image.Image.load` method). See + :py:func:`~PIL.Image.new`. See :ref:`file-handling`. + + :param fp: A filename (string), os.PathLike object or a file object. + The file object must implement ``file.read``, + ``file.seek``, and ``file.tell`` methods, + and be opened in binary mode. The file object will also seek to zero + before reading. + :param mode: The mode. If given, this argument must be "r". + :param formats: A list or tuple of formats to attempt to load the file in. + This can be used to restrict the set of formats checked. + Pass ``None`` to try all supported formats. You can print the set of + available formats by running ``python3 -m PIL`` or using + the :py:func:`PIL.features.pilinfo` function. + :returns: An :py:class:`~PIL.Image.Image` object. + :exception FileNotFoundError: If the file cannot be found. + :exception PIL.UnidentifiedImageError: If the image cannot be opened and + identified. + :exception ValueError: If the ``mode`` is not "r", or if a ``StringIO`` + instance is used for ``fp``. + :exception TypeError: If ``formats`` is not ``None``, a list or a tuple. + """ + + if mode != "r": + msg = f"bad mode {repr(mode)}" # type: ignore[unreachable] + raise ValueError(msg) + elif isinstance(fp, io.StringIO): + msg = ( # type: ignore[unreachable] + "StringIO cannot be used to open an image. " + "Binary data must be used instead." + ) + raise ValueError(msg) + + if formats is None: + formats = ID + elif not isinstance(formats, (list, tuple)): + msg = "formats must be a list or tuple" # type: ignore[unreachable] + raise TypeError(msg) + + exclusive_fp = False + filename: str | bytes = "" + if is_path(fp): + filename = os.fspath(fp) + fp = builtins.open(filename, "rb") + exclusive_fp = True + else: + fp = cast(IO[bytes], fp) + + try: + fp.seek(0) + except (AttributeError, io.UnsupportedOperation): + fp = io.BytesIO(fp.read()) + exclusive_fp = True + + prefix = fp.read(16) + + preinit() + + warning_messages: list[str] = [] + + def _open_core( + fp: IO[bytes], + filename: str | bytes, + prefix: bytes, + formats: list[str] | tuple[str, ...], + ) -> ImageFile.ImageFile | None: + for i in formats: + i = i.upper() + if i not in OPEN: + init() + try: + factory, accept = OPEN[i] + result = not accept or accept(prefix) + if isinstance(result, str): + warning_messages.append(result) + elif result: + fp.seek(0) + im = factory(fp, filename) + _decompression_bomb_check(im.size) + return im + except (SyntaxError, IndexError, TypeError, struct.error) as e: + if WARN_POSSIBLE_FORMATS: + warning_messages.append(i + " opening failed. " + str(e)) + except BaseException: + if exclusive_fp: + fp.close() + raise + return None + + im = _open_core(fp, filename, prefix, formats) + + if im is None and formats is ID: + checked_formats = ID.copy() + if init(): + im = _open_core( + fp, + filename, + prefix, + tuple(format for format in formats if format not in checked_formats), + ) + + if im: + im._exclusive_fp = exclusive_fp + return im + + if exclusive_fp: + fp.close() + for message in warning_messages: + warnings.warn(message) + msg = "cannot identify image file %r" % (filename if filename else fp) + raise UnidentifiedImageError(msg) + + +# +# Image processing. + + +def alpha_composite(im1: Image, im2: Image) -> Image: + """ + Alpha composite im2 over im1. + + :param im1: The first image. Must have mode RGBA or LA. + :param im2: The second image. Must have the same mode and size as the first image. + :returns: An :py:class:`~PIL.Image.Image` object. + """ + + im1.load() + im2.load() + return im1._new(core.alpha_composite(im1.im, im2.im)) + + +def blend(im1: Image, im2: Image, alpha: float) -> Image: + """ + Creates a new image by interpolating between two input images, using + a constant alpha:: + + out = image1 * (1.0 - alpha) + image2 * alpha + + :param im1: The first image. + :param im2: The second image. Must have the same mode and size as + the first image. + :param alpha: The interpolation alpha factor. If alpha is 0.0, a + copy of the first image is returned. If alpha is 1.0, a copy of + the second image is returned. There are no restrictions on the + alpha value. If necessary, the result is clipped to fit into + the allowed output range. + :returns: An :py:class:`~PIL.Image.Image` object. + """ + + im1.load() + im2.load() + return im1._new(core.blend(im1.im, im2.im, alpha)) + + +def composite(image1: Image, image2: Image, mask: Image) -> Image: + """ + Create composite image by blending images using a transparency mask. + + :param image1: The first image. + :param image2: The second image. Must have the same mode and + size as the first image. + :param mask: A mask image. This image can have mode + "1", "L", or "RGBA", and must have the same size as the + other two images. + """ + + image = image2.copy() + image.paste(image1, None, mask) + return image + + +def eval(image: Image, *args: Callable[[int], float]) -> Image: + """ + Applies the function (which should take one argument) to each pixel + in the given image. If the image has more than one band, the same + function is applied to each band. Note that the function is + evaluated once for each possible pixel value, so you cannot use + random components or other generators. + + :param image: The input image. + :param function: A function object, taking one integer argument. + :returns: An :py:class:`~PIL.Image.Image` object. + """ + + return image.point(args[0]) + + +def merge(mode: str, bands: Sequence[Image]) -> Image: + """ + Merge a set of single band images into a new multiband image. + + :param mode: The mode to use for the output image. See: + :ref:`concept-modes`. + :param bands: A sequence containing one single-band image for + each band in the output image. All bands must have the + same size. + :returns: An :py:class:`~PIL.Image.Image` object. + """ + + if getmodebands(mode) != len(bands) or "*" in mode: + msg = "wrong number of bands" + raise ValueError(msg) + for band in bands[1:]: + if band.mode != getmodetype(mode): + msg = "mode mismatch" + raise ValueError(msg) + if band.size != bands[0].size: + msg = "size mismatch" + raise ValueError(msg) + for band in bands: + band.load() + return bands[0]._new(core.merge(mode, *[b.im for b in bands])) + + +# -------------------------------------------------------------------- +# Plugin registry + + +def register_open( + id: str, + factory: ( + Callable[[IO[bytes], str | bytes], ImageFile.ImageFile] + | type[ImageFile.ImageFile] + ), + accept: Callable[[bytes], bool | str] | None = None, +) -> None: + """ + Register an image file plugin. This function should not be used + in application code. + + :param id: An image format identifier. + :param factory: An image file factory method. + :param accept: An optional function that can be used to quickly + reject images having another format. + """ + id = id.upper() + if id not in ID: + ID.append(id) + OPEN[id] = factory, accept + + +def register_mime(id: str, mimetype: str) -> None: + """ + Registers an image MIME type by populating ``Image.MIME``. This function + should not be used in application code. + + ``Image.MIME`` provides a mapping from image format identifiers to mime + formats, but :py:meth:`~PIL.ImageFile.ImageFile.get_format_mimetype` can + provide a different result for specific images. + + :param id: An image format identifier. + :param mimetype: The image MIME type for this format. + """ + MIME[id.upper()] = mimetype + + +def register_save( + id: str, driver: Callable[[Image, IO[bytes], str | bytes], None] +) -> None: + """ + Registers an image save function. This function should not be + used in application code. + + :param id: An image format identifier. + :param driver: A function to save images in this format. + """ + SAVE[id.upper()] = driver + + +def register_save_all( + id: str, driver: Callable[[Image, IO[bytes], str | bytes], None] +) -> None: + """ + Registers an image function to save all the frames + of a multiframe format. This function should not be + used in application code. + + :param id: An image format identifier. + :param driver: A function to save images in this format. + """ + SAVE_ALL[id.upper()] = driver + + +def register_extension(id: str, extension: str) -> None: + """ + Registers an image extension. This function should not be + used in application code. + + :param id: An image format identifier. + :param extension: An extension used for this format. + """ + EXTENSION[extension.lower()] = id.upper() + + +def register_extensions(id: str, extensions: list[str]) -> None: + """ + Registers image extensions. This function should not be + used in application code. + + :param id: An image format identifier. + :param extensions: A list of extensions used for this format. + """ + for extension in extensions: + register_extension(id, extension) + + +def registered_extensions() -> dict[str, str]: + """ + Returns a dictionary containing all file extensions belonging + to registered plugins + """ + init() + return EXTENSION + + +def register_decoder(name: str, decoder: type[ImageFile.PyDecoder]) -> None: + """ + Registers an image decoder. This function should not be + used in application code. + + :param name: The name of the decoder + :param decoder: An ImageFile.PyDecoder object + + .. versionadded:: 4.1.0 + """ + DECODERS[name] = decoder + + +def register_encoder(name: str, encoder: type[ImageFile.PyEncoder]) -> None: + """ + Registers an image encoder. This function should not be + used in application code. + + :param name: The name of the encoder + :param encoder: An ImageFile.PyEncoder object + + .. versionadded:: 4.1.0 + """ + ENCODERS[name] = encoder + + +# -------------------------------------------------------------------- +# Simple display support. + + +def _show(image: Image, **options: Any) -> None: + from . import ImageShow + + deprecate("Image._show", 13, "ImageShow.show") + ImageShow.show(image, **options) + + +# -------------------------------------------------------------------- +# Effects + + +def effect_mandelbrot( + size: tuple[int, int], extent: tuple[float, float, float, float], quality: int +) -> Image: + """ + Generate a Mandelbrot set covering the given extent. + + :param size: The requested size in pixels, as a 2-tuple: + (width, height). + :param extent: The extent to cover, as a 4-tuple: + (x0, y0, x1, y1). + :param quality: Quality. + """ + return Image()._new(core.effect_mandelbrot(size, extent, quality)) + + +def effect_noise(size: tuple[int, int], sigma: float) -> Image: + """ + Generate Gaussian noise centered around 128. + + :param size: The requested size in pixels, as a 2-tuple: + (width, height). + :param sigma: Standard deviation of noise. + """ + return Image()._new(core.effect_noise(size, sigma)) + + +def linear_gradient(mode: str) -> Image: + """ + Generate 256x256 linear gradient from black to white, top to bottom. + + :param mode: Input mode. + """ + return Image()._new(core.linear_gradient(mode)) + + +def radial_gradient(mode: str) -> Image: + """ + Generate 256x256 radial gradient from black to white, centre to edge. + + :param mode: Input mode. + """ + return Image()._new(core.radial_gradient(mode)) + + +# -------------------------------------------------------------------- +# Resources + + +def _apply_env_variables(env: dict[str, str] | None = None) -> None: + env_dict = env if env is not None else os.environ + + for var_name, setter in [ + ("PILLOW_ALIGNMENT", core.set_alignment), + ("PILLOW_BLOCK_SIZE", core.set_block_size), + ("PILLOW_BLOCKS_MAX", core.set_blocks_max), + ]: + if var_name not in env_dict: + continue + + var = env_dict[var_name].lower() + + units = 1 + for postfix, mul in [("k", 1024), ("m", 1024 * 1024)]: + if var.endswith(postfix): + units = mul + var = var[: -len(postfix)] + + try: + var_int = int(var) * units + except ValueError: + warnings.warn(f"{var_name} is not int") + continue + + try: + setter(var_int) + except ValueError as e: + warnings.warn(f"{var_name}: {e}") + + +_apply_env_variables() +atexit.register(core.clear_cache) + + +if TYPE_CHECKING: + _ExifBase = MutableMapping[int, Any] +else: + _ExifBase = MutableMapping + + +class Exif(_ExifBase): + """ + This class provides read and write access to EXIF image data:: + + from PIL import Image + im = Image.open("exif.png") + exif = im.getexif() # Returns an instance of this class + + Information can be read and written, iterated over or deleted:: + + print(exif[274]) # 1 + exif[274] = 2 + for k, v in exif.items(): + print("Tag", k, "Value", v) # Tag 274 Value 2 + del exif[274] + + To access information beyond IFD0, :py:meth:`~PIL.Image.Exif.get_ifd` + returns a dictionary:: + + from PIL import ExifTags + im = Image.open("exif_gps.jpg") + exif = im.getexif() + gps_ifd = exif.get_ifd(ExifTags.IFD.GPSInfo) + print(gps_ifd) + + Other IFDs include ``ExifTags.IFD.Exif``, ``ExifTags.IFD.MakerNote``, + ``ExifTags.IFD.Interop`` and ``ExifTags.IFD.IFD1``. + + :py:mod:`~PIL.ExifTags` also has enum classes to provide names for data:: + + print(exif[ExifTags.Base.Software]) # PIL + print(gps_ifd[ExifTags.GPS.GPSDateStamp]) # 1999:99:99 99:99:99 + """ + + endian: str | None = None + bigtiff = False + _loaded = False + + def __init__(self) -> None: + self._data: dict[int, Any] = {} + self._hidden_data: dict[int, Any] = {} + self._ifds: dict[int, dict[int, Any]] = {} + self._info: TiffImagePlugin.ImageFileDirectory_v2 | None = None + self._loaded_exif: bytes | None = None + + def _fixup(self, value: Any) -> Any: + try: + if len(value) == 1 and isinstance(value, tuple): + return value[0] + except Exception: + pass + return value + + def _fixup_dict(self, src_dict: dict[int, Any]) -> dict[int, Any]: + # Helper function + # returns a dict with any single item tuples/lists as individual values + return {k: self._fixup(v) for k, v in src_dict.items()} + + def _get_ifd_dict( + self, offset: int, group: int | None = None + ) -> dict[int, Any] | None: + try: + # an offset pointer to the location of the nested embedded IFD. + # It should be a long, but may be corrupted. + self.fp.seek(offset) + except (KeyError, TypeError): + return None + else: + from . import TiffImagePlugin + + info = TiffImagePlugin.ImageFileDirectory_v2(self.head, group=group) + info.load(self.fp) + return self._fixup_dict(dict(info)) + + def _get_head(self) -> bytes: + version = b"\x2b" if self.bigtiff else b"\x2a" + if self.endian == "<": + head = b"II" + version + b"\x00" + o32le(8) + else: + head = b"MM\x00" + version + o32be(8) + if self.bigtiff: + head += o32le(8) if self.endian == "<" else o32be(8) + head += b"\x00\x00\x00\x00" + return head + + def load(self, data: bytes) -> None: + # Extract EXIF information. This is highly experimental, + # and is likely to be replaced with something better in a future + # version. + + # The EXIF record consists of a TIFF file embedded in a JPEG + # application marker (!). + if data == self._loaded_exif: + return + self._loaded_exif = data + self._data.clear() + self._hidden_data.clear() + self._ifds.clear() + while data and data.startswith(b"Exif\x00\x00"): + data = data[6:] + if not data: + self._info = None + return + + self.fp: IO[bytes] = io.BytesIO(data) + self.head = self.fp.read(8) + # process dictionary + from . import TiffImagePlugin + + self._info = TiffImagePlugin.ImageFileDirectory_v2(self.head) + self.endian = self._info._endian + self.fp.seek(self._info.next) + self._info.load(self.fp) + + def load_from_fp(self, fp: IO[bytes], offset: int | None = None) -> None: + self._loaded_exif = None + self._data.clear() + self._hidden_data.clear() + self._ifds.clear() + + # process dictionary + from . import TiffImagePlugin + + self.fp = fp + if offset is not None: + self.head = self._get_head() + else: + self.head = self.fp.read(8) + self._info = TiffImagePlugin.ImageFileDirectory_v2(self.head) + if self.endian is None: + self.endian = self._info._endian + if offset is None: + offset = self._info.next + self.fp.tell() + self.fp.seek(offset) + self._info.load(self.fp) + + def _get_merged_dict(self) -> dict[int, Any]: + merged_dict = dict(self) + + # get EXIF extension + if ExifTags.IFD.Exif in self: + ifd = self._get_ifd_dict(self[ExifTags.IFD.Exif], ExifTags.IFD.Exif) + if ifd: + merged_dict.update(ifd) + + # GPS + if ExifTags.IFD.GPSInfo in self: + merged_dict[ExifTags.IFD.GPSInfo] = self._get_ifd_dict( + self[ExifTags.IFD.GPSInfo], ExifTags.IFD.GPSInfo + ) + + return merged_dict + + def tobytes(self, offset: int = 8) -> bytes: + from . import TiffImagePlugin + + head = self._get_head() + ifd = TiffImagePlugin.ImageFileDirectory_v2(ifh=head) + for tag, ifd_dict in self._ifds.items(): + if tag not in self: + ifd[tag] = ifd_dict + for tag, value in self.items(): + if tag in [ + ExifTags.IFD.Exif, + ExifTags.IFD.GPSInfo, + ] and not isinstance(value, dict): + value = self.get_ifd(tag) + if ( + tag == ExifTags.IFD.Exif + and ExifTags.IFD.Interop in value + and not isinstance(value[ExifTags.IFD.Interop], dict) + ): + value = value.copy() + value[ExifTags.IFD.Interop] = self.get_ifd(ExifTags.IFD.Interop) + ifd[tag] = value + return b"Exif\x00\x00" + head + ifd.tobytes(offset) + + def get_ifd(self, tag: int) -> dict[int, Any]: + if tag not in self._ifds: + if tag == ExifTags.IFD.IFD1: + if self._info is not None and self._info.next != 0: + ifd = self._get_ifd_dict(self._info.next) + if ifd is not None: + self._ifds[tag] = ifd + elif tag in [ExifTags.IFD.Exif, ExifTags.IFD.GPSInfo]: + offset = self._hidden_data.get(tag, self.get(tag)) + if offset is not None: + ifd = self._get_ifd_dict(offset, tag) + if ifd is not None: + self._ifds[tag] = ifd + elif tag in [ExifTags.IFD.Interop, ExifTags.IFD.MakerNote]: + if ExifTags.IFD.Exif not in self._ifds: + self.get_ifd(ExifTags.IFD.Exif) + tag_data = self._ifds[ExifTags.IFD.Exif][tag] + if tag == ExifTags.IFD.MakerNote: + from .TiffImagePlugin import ImageFileDirectory_v2 + + if tag_data.startswith(b"FUJIFILM"): + ifd_offset = i32le(tag_data, 8) + ifd_data = tag_data[ifd_offset:] + + makernote = {} + for i in range(struct.unpack(" 4: + (offset,) = struct.unpack("H", tag_data[:2])[0]): + ifd_tag, typ, count, data = struct.unpack( + ">HHL4s", tag_data[i * 12 + 2 : (i + 1) * 12 + 2] + ) + if ifd_tag == 0x1101: + # CameraInfo + (offset,) = struct.unpack(">L", data) + self.fp.seek(offset) + + camerainfo: dict[str, int | bytes] = { + "ModelID": self.fp.read(4) + } + + self.fp.read(4) + # Seconds since 2000 + camerainfo["TimeStamp"] = i32le(self.fp.read(12)) + + self.fp.read(4) + camerainfo["InternalSerialNumber"] = self.fp.read(4) + + self.fp.read(12) + parallax = self.fp.read(4) + handler = ImageFileDirectory_v2._load_dispatch[ + TiffTags.FLOAT + ][1] + camerainfo["Parallax"] = handler( + ImageFileDirectory_v2(), parallax, False + )[0] + + self.fp.read(4) + camerainfo["Category"] = self.fp.read(2) + + makernote = {0x1101: camerainfo} + self._ifds[tag] = makernote + else: + # Interop + ifd = self._get_ifd_dict(tag_data, tag) + if ifd is not None: + self._ifds[tag] = ifd + ifd = self._ifds.setdefault(tag, {}) + if tag == ExifTags.IFD.Exif and self._hidden_data: + ifd = { + k: v + for (k, v) in ifd.items() + if k not in (ExifTags.IFD.Interop, ExifTags.IFD.MakerNote) + } + return ifd + + def hide_offsets(self) -> None: + for tag in (ExifTags.IFD.Exif, ExifTags.IFD.GPSInfo): + if tag in self: + self._hidden_data[tag] = self[tag] + del self[tag] + + def __str__(self) -> str: + if self._info is not None: + # Load all keys into self._data + for tag in self._info: + self[tag] + + return str(self._data) + + def __len__(self) -> int: + keys = set(self._data) + if self._info is not None: + keys.update(self._info) + return len(keys) + + def __getitem__(self, tag: int) -> Any: + if self._info is not None and tag not in self._data and tag in self._info: + self._data[tag] = self._fixup(self._info[tag]) + del self._info[tag] + return self._data[tag] + + def __contains__(self, tag: object) -> bool: + return tag in self._data or (self._info is not None and tag in self._info) + + def __setitem__(self, tag: int, value: Any) -> None: + if self._info is not None and tag in self._info: + del self._info[tag] + self._data[tag] = value + + def __delitem__(self, tag: int) -> None: + if self._info is not None and tag in self._info: + del self._info[tag] + else: + del self._data[tag] + if tag in self._ifds: + del self._ifds[tag] + + def __iter__(self) -> Iterator[int]: + keys = set(self._data) + if self._info is not None: + keys.update(self._info) + return iter(keys) diff --git a/PIL/ImageColor.py b/PIL/ImageColor.py new file mode 100644 index 0000000000000000000000000000000000000000..9a15a8eb7597998f1bc9a01e8eae3588c087838b --- /dev/null +++ b/PIL/ImageColor.py @@ -0,0 +1,320 @@ +# +# The Python Imaging Library +# $Id$ +# +# map CSS3-style colour description strings to RGB +# +# History: +# 2002-10-24 fl Added support for CSS-style color strings +# 2002-12-15 fl Added RGBA support +# 2004-03-27 fl Fixed remaining int() problems for Python 1.5.2 +# 2004-07-19 fl Fixed gray/grey spelling issues +# 2009-03-05 fl Fixed rounding error in grayscale calculation +# +# Copyright (c) 2002-2004 by Secret Labs AB +# Copyright (c) 2002-2004 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import re +from functools import lru_cache + +from . import Image + + +@lru_cache +def getrgb(color: str) -> tuple[int, int, int] | tuple[int, int, int, int]: + """ + Convert a color string to an RGB or RGBA tuple. If the string cannot be + parsed, this function raises a :py:exc:`ValueError` exception. + + .. versionadded:: 1.1.4 + + :param color: A color string + :return: ``(red, green, blue[, alpha])`` + """ + if len(color) > 100: + msg = "color specifier is too long" + raise ValueError(msg) + color = color.lower() + + rgb = colormap.get(color, None) + if rgb: + if isinstance(rgb, tuple): + return rgb + rgb_tuple = getrgb(rgb) + assert len(rgb_tuple) == 3 + colormap[color] = rgb_tuple + return rgb_tuple + + # check for known string formats + if re.match("#[a-f0-9]{3}$", color): + return int(color[1] * 2, 16), int(color[2] * 2, 16), int(color[3] * 2, 16) + + if re.match("#[a-f0-9]{4}$", color): + return ( + int(color[1] * 2, 16), + int(color[2] * 2, 16), + int(color[3] * 2, 16), + int(color[4] * 2, 16), + ) + + if re.match("#[a-f0-9]{6}$", color): + return int(color[1:3], 16), int(color[3:5], 16), int(color[5:7], 16) + + if re.match("#[a-f0-9]{8}$", color): + return ( + int(color[1:3], 16), + int(color[3:5], 16), + int(color[5:7], 16), + int(color[7:9], 16), + ) + + m = re.match(r"rgb\(\s*(\d+)\s*,\s*(\d+)\s*,\s*(\d+)\s*\)$", color) + if m: + return int(m.group(1)), int(m.group(2)), int(m.group(3)) + + m = re.match(r"rgb\(\s*(\d+)%\s*,\s*(\d+)%\s*,\s*(\d+)%\s*\)$", color) + if m: + return ( + int((int(m.group(1)) * 255) / 100.0 + 0.5), + int((int(m.group(2)) * 255) / 100.0 + 0.5), + int((int(m.group(3)) * 255) / 100.0 + 0.5), + ) + + m = re.match( + r"hsl\(\s*(\d+\.?\d*)\s*,\s*(\d+\.?\d*)%\s*,\s*(\d+\.?\d*)%\s*\)$", color + ) + if m: + from colorsys import hls_to_rgb + + rgb_floats = hls_to_rgb( + float(m.group(1)) / 360.0, + float(m.group(3)) / 100.0, + float(m.group(2)) / 100.0, + ) + return ( + int(rgb_floats[0] * 255 + 0.5), + int(rgb_floats[1] * 255 + 0.5), + int(rgb_floats[2] * 255 + 0.5), + ) + + m = re.match( + r"hs[bv]\(\s*(\d+\.?\d*)\s*,\s*(\d+\.?\d*)%\s*,\s*(\d+\.?\d*)%\s*\)$", color + ) + if m: + from colorsys import hsv_to_rgb + + rgb_floats = hsv_to_rgb( + float(m.group(1)) / 360.0, + float(m.group(2)) / 100.0, + float(m.group(3)) / 100.0, + ) + return ( + int(rgb_floats[0] * 255 + 0.5), + int(rgb_floats[1] * 255 + 0.5), + int(rgb_floats[2] * 255 + 0.5), + ) + + m = re.match(r"rgba\(\s*(\d+)\s*,\s*(\d+)\s*,\s*(\d+)\s*,\s*(\d+)\s*\)$", color) + if m: + return int(m.group(1)), int(m.group(2)), int(m.group(3)), int(m.group(4)) + msg = f"unknown color specifier: {repr(color)}" + raise ValueError(msg) + + +@lru_cache +def getcolor(color: str, mode: str) -> int | tuple[int, ...]: + """ + Same as :py:func:`~PIL.ImageColor.getrgb` for most modes. However, if + ``mode`` is HSV, converts the RGB value to a HSV value, or if ``mode`` is + not color or a palette image, converts the RGB value to a grayscale value. + If the string cannot be parsed, this function raises a :py:exc:`ValueError` + exception. + + .. versionadded:: 1.1.4 + + :param color: A color string + :param mode: Convert result to this mode + :return: ``graylevel, (graylevel, alpha) or (red, green, blue[, alpha])`` + """ + # same as getrgb, but converts the result to the given mode + rgb, alpha = getrgb(color), 255 + if len(rgb) == 4: + alpha = rgb[3] + rgb = rgb[:3] + + if mode == "HSV": + from colorsys import rgb_to_hsv + + r, g, b = rgb + h, s, v = rgb_to_hsv(r / 255, g / 255, b / 255) + return int(h * 255), int(s * 255), int(v * 255) + elif Image.getmodebase(mode) == "L": + r, g, b = rgb + # ITU-R Recommendation 601-2 for nonlinear RGB + # scaled to 24 bits to match the convert's implementation. + graylevel = (r * 19595 + g * 38470 + b * 7471 + 0x8000) >> 16 + if mode[-1] == "A": + return graylevel, alpha + return graylevel + elif mode[-1] == "A": + return rgb + (alpha,) + return rgb + + +colormap: dict[str, str | tuple[int, int, int]] = { + # X11 colour table from https://drafts.csswg.org/css-color-4/, with + # gray/grey spelling issues fixed. This is a superset of HTML 4.0 + # colour names used in CSS 1. + "aliceblue": "#f0f8ff", + "antiquewhite": "#faebd7", + "aqua": "#00ffff", + "aquamarine": "#7fffd4", + "azure": "#f0ffff", + "beige": "#f5f5dc", + "bisque": "#ffe4c4", + "black": "#000000", + "blanchedalmond": "#ffebcd", + "blue": "#0000ff", + "blueviolet": "#8a2be2", + "brown": "#a52a2a", + "burlywood": "#deb887", + "cadetblue": "#5f9ea0", + "chartreuse": "#7fff00", + "chocolate": "#d2691e", + "coral": "#ff7f50", + "cornflowerblue": "#6495ed", + "cornsilk": "#fff8dc", + "crimson": "#dc143c", + "cyan": "#00ffff", + "darkblue": "#00008b", + "darkcyan": "#008b8b", + "darkgoldenrod": "#b8860b", + "darkgray": "#a9a9a9", + "darkgrey": "#a9a9a9", + "darkgreen": "#006400", + "darkkhaki": "#bdb76b", + "darkmagenta": "#8b008b", + "darkolivegreen": "#556b2f", + "darkorange": "#ff8c00", + "darkorchid": "#9932cc", + "darkred": "#8b0000", + "darksalmon": "#e9967a", + "darkseagreen": "#8fbc8f", + "darkslateblue": "#483d8b", + "darkslategray": "#2f4f4f", + "darkslategrey": "#2f4f4f", + "darkturquoise": "#00ced1", + "darkviolet": "#9400d3", + "deeppink": "#ff1493", + "deepskyblue": "#00bfff", + "dimgray": "#696969", + "dimgrey": "#696969", + "dodgerblue": "#1e90ff", + "firebrick": "#b22222", + "floralwhite": "#fffaf0", + "forestgreen": "#228b22", + "fuchsia": "#ff00ff", + "gainsboro": "#dcdcdc", + "ghostwhite": "#f8f8ff", + "gold": "#ffd700", + "goldenrod": "#daa520", + "gray": "#808080", + "grey": "#808080", + "green": "#008000", + "greenyellow": "#adff2f", + "honeydew": "#f0fff0", + "hotpink": "#ff69b4", + "indianred": "#cd5c5c", + "indigo": "#4b0082", + "ivory": "#fffff0", + "khaki": "#f0e68c", + "lavender": "#e6e6fa", + "lavenderblush": "#fff0f5", + "lawngreen": "#7cfc00", + "lemonchiffon": "#fffacd", + "lightblue": "#add8e6", + "lightcoral": "#f08080", + "lightcyan": "#e0ffff", + "lightgoldenrodyellow": "#fafad2", + "lightgreen": "#90ee90", + "lightgray": "#d3d3d3", + "lightgrey": "#d3d3d3", + "lightpink": "#ffb6c1", + "lightsalmon": "#ffa07a", + "lightseagreen": "#20b2aa", + "lightskyblue": "#87cefa", + "lightslategray": "#778899", + "lightslategrey": "#778899", + "lightsteelblue": "#b0c4de", + "lightyellow": "#ffffe0", + "lime": "#00ff00", + "limegreen": "#32cd32", + "linen": "#faf0e6", + "magenta": "#ff00ff", + "maroon": "#800000", + "mediumaquamarine": "#66cdaa", + "mediumblue": "#0000cd", + "mediumorchid": "#ba55d3", + "mediumpurple": "#9370db", + "mediumseagreen": "#3cb371", + "mediumslateblue": "#7b68ee", + "mediumspringgreen": "#00fa9a", + "mediumturquoise": "#48d1cc", + "mediumvioletred": "#c71585", + "midnightblue": "#191970", + "mintcream": "#f5fffa", + "mistyrose": "#ffe4e1", + "moccasin": "#ffe4b5", + "navajowhite": "#ffdead", + "navy": "#000080", + "oldlace": "#fdf5e6", + "olive": "#808000", + "olivedrab": "#6b8e23", + "orange": "#ffa500", + "orangered": "#ff4500", + "orchid": "#da70d6", + "palegoldenrod": "#eee8aa", + "palegreen": "#98fb98", + "paleturquoise": "#afeeee", + "palevioletred": "#db7093", + "papayawhip": "#ffefd5", + "peachpuff": "#ffdab9", + "peru": "#cd853f", + "pink": "#ffc0cb", + "plum": "#dda0dd", + "powderblue": "#b0e0e6", + "purple": "#800080", + "rebeccapurple": "#663399", + "red": "#ff0000", + "rosybrown": "#bc8f8f", + "royalblue": "#4169e1", + "saddlebrown": "#8b4513", + "salmon": "#fa8072", + "sandybrown": "#f4a460", + "seagreen": "#2e8b57", + "seashell": "#fff5ee", + "sienna": "#a0522d", + "silver": "#c0c0c0", + "skyblue": "#87ceeb", + "slateblue": "#6a5acd", + "slategray": "#708090", + "slategrey": "#708090", + "snow": "#fffafa", + "springgreen": "#00ff7f", + "steelblue": "#4682b4", + "tan": "#d2b48c", + "teal": "#008080", + "thistle": "#d8bfd8", + "tomato": "#ff6347", + "turquoise": "#40e0d0", + "violet": "#ee82ee", + "wheat": "#f5deb3", + "white": "#ffffff", + "whitesmoke": "#f5f5f5", + "yellow": "#ffff00", + "yellowgreen": "#9acd32", +} diff --git a/PIL/ImageDraw.py b/PIL/ImageDraw.py new file mode 100644 index 0000000000000000000000000000000000000000..8bcf2d8ee06ff87e966cf7bab9e1f448848cedc8 --- /dev/null +++ b/PIL/ImageDraw.py @@ -0,0 +1,1036 @@ +# +# The Python Imaging Library +# $Id$ +# +# drawing interface operations +# +# History: +# 1996-04-13 fl Created (experimental) +# 1996-08-07 fl Filled polygons, ellipses. +# 1996-08-13 fl Added text support +# 1998-06-28 fl Handle I and F images +# 1998-12-29 fl Added arc; use arc primitive to draw ellipses +# 1999-01-10 fl Added shape stuff (experimental) +# 1999-02-06 fl Added bitmap support +# 1999-02-11 fl Changed all primitives to take options +# 1999-02-20 fl Fixed backwards compatibility +# 2000-10-12 fl Copy on write, when necessary +# 2001-02-18 fl Use default ink for bitmap/text also in fill mode +# 2002-10-24 fl Added support for CSS-style color strings +# 2002-12-10 fl Added experimental support for RGBA-on-RGB drawing +# 2002-12-11 fl Refactored low-level drawing API (work in progress) +# 2004-08-26 fl Made Draw() a factory function, added getdraw() support +# 2004-09-04 fl Added width support to line primitive +# 2004-09-10 fl Added font mode handling +# 2006-06-19 fl Added font bearing support (getmask2) +# +# Copyright (c) 1997-2006 by Secret Labs AB +# Copyright (c) 1996-2006 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import math +import struct +from collections.abc import Sequence +from typing import cast + +from . import Image, ImageColor, ImageText + +TYPE_CHECKING = False +if TYPE_CHECKING: + from collections.abc import Callable + from types import ModuleType + from typing import Any, AnyStr + + from . import ImageDraw2, ImageFont + from ._typing import Coords, _Ink + +# experimental access to the outline API +Outline: Callable[[], Image.core._Outline] = Image.core.outline + +""" +A simple 2D drawing interface for PIL images. +

+Application code should use the Draw factory, instead of +directly. +""" + + +class ImageDraw: + font: ( + ImageFont.ImageFont | ImageFont.FreeTypeFont | ImageFont.TransposedFont | None + ) = None + + def __init__(self, im: Image.Image, mode: str | None = None) -> None: + """ + Create a drawing instance. + + :param im: The image to draw in. + :param mode: Optional mode to use for color values. For RGB + images, this argument can be RGB or RGBA (to blend the + drawing into the image). For all other modes, this argument + must be the same as the image mode. If omitted, the mode + defaults to the mode of the image. + """ + im._ensure_mutable() + blend = 0 + if mode is None: + mode = im.mode + if mode != im.mode: + if mode == "RGBA" and im.mode == "RGB": + blend = 1 + else: + msg = "mode mismatch" + raise ValueError(msg) + if mode == "P": + self.palette = im.palette + else: + self.palette = None + self._image = im + self.im = im.im + self.draw = Image.core.draw(self.im, blend) + self.mode = mode + if mode in ("I", "F"): + self.ink = self.draw.draw_ink(1) + else: + self.ink = self.draw.draw_ink(-1) + if mode in ("1", "P", "I", "F"): + # FIXME: fix Fill2 to properly support matte for I+F images + self.fontmode = "1" + else: + self.fontmode = "L" # aliasing is okay for other modes + self.fill = False + + def getfont( + self, + ) -> ImageFont.ImageFont | ImageFont.FreeTypeFont | ImageFont.TransposedFont: + """ + Get the current default font. + + To set the default font for this ImageDraw instance:: + + from PIL import ImageDraw, ImageFont + draw.font = ImageFont.truetype("Tests/fonts/FreeMono.ttf") + + To set the default font for all future ImageDraw instances:: + + from PIL import ImageDraw, ImageFont + ImageDraw.ImageDraw.font = ImageFont.truetype("Tests/fonts/FreeMono.ttf") + + If the current default font is ``None``, + it is initialized with ``ImageFont.load_default()``. + + :returns: An image font.""" + if not self.font: + # FIXME: should add a font repository + from . import ImageFont + + self.font = ImageFont.load_default() + return self.font + + def _getfont( + self, font_size: float | None + ) -> ImageFont.ImageFont | ImageFont.FreeTypeFont | ImageFont.TransposedFont: + if font_size is not None: + from . import ImageFont + + return ImageFont.load_default(font_size) + else: + return self.getfont() + + def _getink( + self, ink: _Ink | None, fill: _Ink | None = None + ) -> tuple[int | None, int | None]: + result_ink = None + result_fill = None + if ink is None and fill is None: + if self.fill: + result_fill = self.ink + else: + result_ink = self.ink + else: + if ink is not None: + if isinstance(ink, str): + ink = ImageColor.getcolor(ink, self.mode) + if self.palette and isinstance(ink, tuple): + ink = self.palette.getcolor(ink, self._image) + result_ink = self.draw.draw_ink(ink) + if fill is not None: + if isinstance(fill, str): + fill = ImageColor.getcolor(fill, self.mode) + if self.palette and isinstance(fill, tuple): + fill = self.palette.getcolor(fill, self._image) + result_fill = self.draw.draw_ink(fill) + return result_ink, result_fill + + def arc( + self, + xy: Coords, + start: float, + end: float, + fill: _Ink | None = None, + width: int = 1, + ) -> None: + """Draw an arc.""" + ink, fill = self._getink(fill) + if ink is not None: + self.draw.draw_arc(xy, start, end, ink, width) + + def bitmap( + self, xy: Sequence[int], bitmap: Image.Image, fill: _Ink | None = None + ) -> None: + """Draw a bitmap.""" + bitmap.load() + ink, fill = self._getink(fill) + if ink is None: + ink = fill + if ink is not None: + self.draw.draw_bitmap(xy, bitmap.im, ink) + + def chord( + self, + xy: Coords, + start: float, + end: float, + fill: _Ink | None = None, + outline: _Ink | None = None, + width: int = 1, + ) -> None: + """Draw a chord.""" + ink, fill_ink = self._getink(outline, fill) + if fill_ink is not None: + self.draw.draw_chord(xy, start, end, fill_ink, 1) + if ink is not None and ink != fill_ink and width != 0: + self.draw.draw_chord(xy, start, end, ink, 0, width) + + def ellipse( + self, + xy: Coords, + fill: _Ink | None = None, + outline: _Ink | None = None, + width: int = 1, + ) -> None: + """Draw an ellipse.""" + ink, fill_ink = self._getink(outline, fill) + if fill_ink is not None: + self.draw.draw_ellipse(xy, fill_ink, 1) + if ink is not None and ink != fill_ink and width != 0: + self.draw.draw_ellipse(xy, ink, 0, width) + + def circle( + self, + xy: Sequence[float], + radius: float, + fill: _Ink | None = None, + outline: _Ink | None = None, + width: int = 1, + ) -> None: + """Draw a circle given center coordinates and a radius.""" + ellipse_xy = (xy[0] - radius, xy[1] - radius, xy[0] + radius, xy[1] + radius) + self.ellipse(ellipse_xy, fill, outline, width) + + def line( + self, + xy: Coords, + fill: _Ink | None = None, + width: int = 0, + joint: str | None = None, + ) -> None: + """Draw a line, or a connected sequence of line segments.""" + ink = self._getink(fill)[0] + if ink is not None: + self.draw.draw_lines(xy, ink, width) + if joint == "curve" and width > 4: + points: Sequence[Sequence[float]] + if isinstance(xy[0], (list, tuple)): + points = cast(Sequence[Sequence[float]], xy) + else: + points = [ + cast(Sequence[float], tuple(xy[i : i + 2])) + for i in range(0, len(xy), 2) + ] + for i in range(1, len(points) - 1): + point = points[i] + angles = [ + math.degrees(math.atan2(end[0] - start[0], start[1] - end[1])) + % 360 + for start, end in ( + (points[i - 1], point), + (point, points[i + 1]), + ) + ] + if angles[0] == angles[1]: + # This is a straight line, so no joint is required + continue + + def coord_at_angle( + coord: Sequence[float], angle: float + ) -> tuple[float, ...]: + x, y = coord + angle -= 90 + distance = width / 2 - 1 + return tuple( + p + (math.floor(p_d) if p_d > 0 else math.ceil(p_d)) + for p, p_d in ( + (x, distance * math.cos(math.radians(angle))), + (y, distance * math.sin(math.radians(angle))), + ) + ) + + flipped = ( + angles[1] > angles[0] and angles[1] - 180 > angles[0] + ) or (angles[1] < angles[0] and angles[1] + 180 > angles[0]) + coords = [ + (point[0] - width / 2 + 1, point[1] - width / 2 + 1), + (point[0] + width / 2 - 1, point[1] + width / 2 - 1), + ] + if flipped: + start, end = (angles[1] + 90, angles[0] + 90) + else: + start, end = (angles[0] - 90, angles[1] - 90) + self.pieslice(coords, start - 90, end - 90, fill) + + if width > 8: + # Cover potential gaps between the line and the joint + if flipped: + gap_coords = [ + coord_at_angle(point, angles[0] + 90), + point, + coord_at_angle(point, angles[1] + 90), + ] + else: + gap_coords = [ + coord_at_angle(point, angles[0] - 90), + point, + coord_at_angle(point, angles[1] - 90), + ] + self.line(gap_coords, fill, width=3) + + def shape( + self, + shape: Image.core._Outline, + fill: _Ink | None = None, + outline: _Ink | None = None, + ) -> None: + """(Experimental) Draw a shape.""" + shape.close() + ink, fill_ink = self._getink(outline, fill) + if fill_ink is not None: + self.draw.draw_outline(shape, fill_ink, 1) + if ink is not None and ink != fill_ink: + self.draw.draw_outline(shape, ink, 0) + + def pieslice( + self, + xy: Coords, + start: float, + end: float, + fill: _Ink | None = None, + outline: _Ink | None = None, + width: int = 1, + ) -> None: + """Draw a pieslice.""" + ink, fill_ink = self._getink(outline, fill) + if fill_ink is not None: + self.draw.draw_pieslice(xy, start, end, fill_ink, 1) + if ink is not None and ink != fill_ink and width != 0: + self.draw.draw_pieslice(xy, start, end, ink, 0, width) + + def point(self, xy: Coords, fill: _Ink | None = None) -> None: + """Draw one or more individual pixels.""" + ink, fill = self._getink(fill) + if ink is not None: + self.draw.draw_points(xy, ink) + + def polygon( + self, + xy: Coords, + fill: _Ink | None = None, + outline: _Ink | None = None, + width: int = 1, + ) -> None: + """Draw a polygon.""" + ink, fill_ink = self._getink(outline, fill) + if fill_ink is not None: + self.draw.draw_polygon(xy, fill_ink, 1) + if ink is not None and ink != fill_ink and width != 0: + if width == 1: + self.draw.draw_polygon(xy, ink, 0, width) + elif self.im is not None: + # To avoid expanding the polygon outwards, + # use the fill as a mask + mask = Image.new("1", self.im.size) + mask_ink = self._getink(1)[0] + draw = Draw(mask) + draw.draw.draw_polygon(xy, mask_ink, 1) + + self.draw.draw_polygon(xy, ink, 0, width * 2 - 1, mask.im) + + def regular_polygon( + self, + bounding_circle: Sequence[Sequence[float] | float], + n_sides: int, + rotation: float = 0, + fill: _Ink | None = None, + outline: _Ink | None = None, + width: int = 1, + ) -> None: + """Draw a regular polygon.""" + xy = _compute_regular_polygon_vertices(bounding_circle, n_sides, rotation) + self.polygon(xy, fill, outline, width) + + def rectangle( + self, + xy: Coords, + fill: _Ink | None = None, + outline: _Ink | None = None, + width: int = 1, + ) -> None: + """Draw a rectangle.""" + ink, fill_ink = self._getink(outline, fill) + if fill_ink is not None: + self.draw.draw_rectangle(xy, fill_ink, 1) + if ink is not None and ink != fill_ink and width != 0: + self.draw.draw_rectangle(xy, ink, 0, width) + + def rounded_rectangle( + self, + xy: Coords, + radius: float = 0, + fill: _Ink | None = None, + outline: _Ink | None = None, + width: int = 1, + *, + corners: tuple[bool, bool, bool, bool] | None = None, + ) -> None: + """Draw a rounded rectangle.""" + if isinstance(xy[0], (list, tuple)): + (x0, y0), (x1, y1) = cast(Sequence[Sequence[float]], xy) + else: + x0, y0, x1, y1 = cast(Sequence[float], xy) + if x1 < x0: + msg = "x1 must be greater than or equal to x0" + raise ValueError(msg) + if y1 < y0: + msg = "y1 must be greater than or equal to y0" + raise ValueError(msg) + if corners is None: + corners = (True, True, True, True) + + d = radius * 2 + + x0 = round(x0) + y0 = round(y0) + x1 = round(x1) + y1 = round(y1) + full_x, full_y = False, False + if all(corners): + full_x = d >= x1 - x0 - 1 + if full_x: + # The two left and two right corners are joined + d = x1 - x0 + full_y = d >= y1 - y0 - 1 + if full_y: + # The two top and two bottom corners are joined + d = y1 - y0 + if full_x and full_y: + # If all corners are joined, that is a circle + return self.ellipse(xy, fill, outline, width) + + if d == 0 or not any(corners): + # If the corners have no curve, + # or there are no corners, + # that is a rectangle + return self.rectangle(xy, fill, outline, width) + + r = int(d // 2) + ink, fill_ink = self._getink(outline, fill) + + def draw_corners(pieslice: bool) -> None: + parts: tuple[tuple[tuple[float, float, float, float], int, int], ...] + if full_x: + # Draw top and bottom halves + parts = ( + ((x0, y0, x0 + d, y0 + d), 180, 360), + ((x0, y1 - d, x0 + d, y1), 0, 180), + ) + elif full_y: + # Draw left and right halves + parts = ( + ((x0, y0, x0 + d, y0 + d), 90, 270), + ((x1 - d, y0, x1, y0 + d), 270, 90), + ) + else: + # Draw four separate corners + parts = tuple( + part + for i, part in enumerate( + ( + ((x0, y0, x0 + d, y0 + d), 180, 270), + ((x1 - d, y0, x1, y0 + d), 270, 360), + ((x1 - d, y1 - d, x1, y1), 0, 90), + ((x0, y1 - d, x0 + d, y1), 90, 180), + ) + ) + if corners[i] + ) + for part in parts: + if pieslice: + self.draw.draw_pieslice(*(part + (fill_ink, 1))) + else: + self.draw.draw_arc(*(part + (ink, width))) + + if fill_ink is not None: + draw_corners(True) + + if full_x: + self.draw.draw_rectangle((x0, y0 + r + 1, x1, y1 - r - 1), fill_ink, 1) + elif x1 - r - 1 > x0 + r + 1: + self.draw.draw_rectangle((x0 + r + 1, y0, x1 - r - 1, y1), fill_ink, 1) + if not full_x and not full_y: + left = [x0, y0, x0 + r, y1] + if corners[0]: + left[1] += r + 1 + if corners[3]: + left[3] -= r + 1 + self.draw.draw_rectangle(left, fill_ink, 1) + + right = [x1 - r, y0, x1, y1] + if corners[1]: + right[1] += r + 1 + if corners[2]: + right[3] -= r + 1 + self.draw.draw_rectangle(right, fill_ink, 1) + if ink is not None and ink != fill_ink and width != 0: + draw_corners(False) + + if not full_x: + top = [x0, y0, x1, y0 + width - 1] + if corners[0]: + top[0] += r + 1 + if corners[1]: + top[2] -= r + 1 + self.draw.draw_rectangle(top, ink, 1) + + bottom = [x0, y1 - width + 1, x1, y1] + if corners[3]: + bottom[0] += r + 1 + if corners[2]: + bottom[2] -= r + 1 + self.draw.draw_rectangle(bottom, ink, 1) + if not full_y: + left = [x0, y0, x0 + width - 1, y1] + if corners[0]: + left[1] += r + 1 + if corners[3]: + left[3] -= r + 1 + self.draw.draw_rectangle(left, ink, 1) + + right = [x1 - width + 1, y0, x1, y1] + if corners[1]: + right[1] += r + 1 + if corners[2]: + right[3] -= r + 1 + self.draw.draw_rectangle(right, ink, 1) + + def text( + self, + xy: tuple[float, float], + text: AnyStr | ImageText.Text, + fill: _Ink | None = None, + font: ( + ImageFont.ImageFont + | ImageFont.FreeTypeFont + | ImageFont.TransposedFont + | None + ) = None, + anchor: str | None = None, + spacing: float = 4, + align: str = "left", + direction: str | None = None, + features: list[str] | None = None, + language: str | None = None, + stroke_width: float = 0, + stroke_fill: _Ink | None = None, + embedded_color: bool = False, + *args: Any, + **kwargs: Any, + ) -> None: + """Draw text.""" + if isinstance(text, ImageText.Text): + image_text = text + else: + if font is None: + font = self._getfont(kwargs.get("font_size")) + image_text = ImageText.Text( + text, font, self.mode, spacing, direction, features, language + ) + if embedded_color: + image_text.embed_color() + if stroke_width: + image_text.stroke(stroke_width, stroke_fill) + + def getink(fill: _Ink | None) -> int: + ink, fill_ink = self._getink(fill) + if ink is None: + assert fill_ink is not None + return fill_ink + return ink + + ink = getink(fill) + if ink is None: + return + + stroke_ink = None + if image_text.stroke_width: + stroke_ink = ( + getink(image_text.stroke_fill) + if image_text.stroke_fill is not None + else ink + ) + + for xy, anchor, line in image_text._split(xy, anchor, align): + + def draw_text(ink: int, stroke_width: float = 0) -> None: + mode = self.fontmode + if stroke_width == 0 and embedded_color: + mode = "RGBA" + coord = [] + for i in range(2): + coord.append(int(xy[i])) + start = (math.modf(xy[0])[0], math.modf(xy[1])[0]) + try: + mask, offset = image_text.font.getmask2( # type: ignore[union-attr,misc] + line, + mode, + direction=direction, + features=features, + language=language, + stroke_width=stroke_width, + stroke_filled=True, + anchor=anchor, + ink=ink, + start=start, + *args, + **kwargs, + ) + coord = [coord[0] + offset[0], coord[1] + offset[1]] + except AttributeError: + try: + mask = image_text.font.getmask( # type: ignore[misc] + line, + mode, + direction, + features, + language, + stroke_width, + anchor, + ink, + start=start, + *args, + **kwargs, + ) + except TypeError: + mask = image_text.font.getmask(line) + if mode == "RGBA": + # image_text.font.getmask2(mode="RGBA") + # returns color in RGB bands and mask in A + # extract mask and set text alpha + color, mask = mask, mask.getband(3) + ink_alpha = struct.pack("i", ink)[3] + color.fillband(3, ink_alpha) + x, y = coord + if self.im is not None: + self.im.paste( + color, (x, y, x + mask.size[0], y + mask.size[1]), mask + ) + else: + self.draw.draw_bitmap(coord, mask, ink) + + if stroke_ink is not None: + # Draw stroked text + draw_text(stroke_ink, image_text.stroke_width) + + # Draw normal text + if ink != stroke_ink: + draw_text(ink) + else: + # Only draw normal text + draw_text(ink) + + def multiline_text( + self, + xy: tuple[float, float], + text: AnyStr, + fill: _Ink | None = None, + font: ( + ImageFont.ImageFont + | ImageFont.FreeTypeFont + | ImageFont.TransposedFont + | None + ) = None, + anchor: str | None = None, + spacing: float = 4, + align: str = "left", + direction: str | None = None, + features: list[str] | None = None, + language: str | None = None, + stroke_width: float = 0, + stroke_fill: _Ink | None = None, + embedded_color: bool = False, + *, + font_size: float | None = None, + ) -> None: + return self.text( + xy, + text, + fill, + font, + anchor, + spacing, + align, + direction, + features, + language, + stroke_width, + stroke_fill, + embedded_color, + font_size=font_size, + ) + + def textlength( + self, + text: AnyStr, + font: ( + ImageFont.ImageFont + | ImageFont.FreeTypeFont + | ImageFont.TransposedFont + | None + ) = None, + direction: str | None = None, + features: list[str] | None = None, + language: str | None = None, + embedded_color: bool = False, + *, + font_size: float | None = None, + ) -> float: + """Get the length of a given string, in pixels with 1/64 precision.""" + if font is None: + font = self._getfont(font_size) + image_text = ImageText.Text( + text, + font, + self.mode, + direction=direction, + features=features, + language=language, + ) + if embedded_color: + image_text.embed_color() + return image_text.get_length() + + def textbbox( + self, + xy: tuple[float, float], + text: AnyStr, + font: ( + ImageFont.ImageFont + | ImageFont.FreeTypeFont + | ImageFont.TransposedFont + | None + ) = None, + anchor: str | None = None, + spacing: float = 4, + align: str = "left", + direction: str | None = None, + features: list[str] | None = None, + language: str | None = None, + stroke_width: float = 0, + embedded_color: bool = False, + *, + font_size: float | None = None, + ) -> tuple[float, float, float, float]: + """Get the bounding box of a given string, in pixels.""" + if font is None: + font = self._getfont(font_size) + image_text = ImageText.Text( + text, font, self.mode, spacing, direction, features, language + ) + if embedded_color: + image_text.embed_color() + if stroke_width: + image_text.stroke(stroke_width) + return image_text.get_bbox(xy, anchor, align) + + def multiline_textbbox( + self, + xy: tuple[float, float], + text: AnyStr, + font: ( + ImageFont.ImageFont + | ImageFont.FreeTypeFont + | ImageFont.TransposedFont + | None + ) = None, + anchor: str | None = None, + spacing: float = 4, + align: str = "left", + direction: str | None = None, + features: list[str] | None = None, + language: str | None = None, + stroke_width: float = 0, + embedded_color: bool = False, + *, + font_size: float | None = None, + ) -> tuple[float, float, float, float]: + return self.textbbox( + xy, + text, + font, + anchor, + spacing, + align, + direction, + features, + language, + stroke_width, + embedded_color, + font_size=font_size, + ) + + +def Draw(im: Image.Image, mode: str | None = None) -> ImageDraw: + """ + A simple 2D drawing interface for PIL images. + + :param im: The image to draw in. + :param mode: Optional mode to use for color values. For RGB + images, this argument can be RGB or RGBA (to blend the + drawing into the image). For all other modes, this argument + must be the same as the image mode. If omitted, the mode + defaults to the mode of the image. + """ + try: + return getattr(im, "getdraw")(mode) + except AttributeError: + return ImageDraw(im, mode) + + +def getdraw(im: Image.Image | None = None) -> tuple[ImageDraw2.Draw | None, ModuleType]: + """ + :param im: The image to draw in. + :returns: A (drawing context, drawing resource factory) tuple. + """ + from . import ImageDraw2 + + draw = ImageDraw2.Draw(im) if im is not None else None + return draw, ImageDraw2 + + +def floodfill( + image: Image.Image, + xy: tuple[int, int], + value: float | tuple[int, ...], + border: float | tuple[int, ...] | None = None, + thresh: float = 0, +) -> None: + """ + .. warning:: This method is experimental. + + Fills a bounded region with a given color. + + :param image: Target image. + :param xy: Seed position (a 2-item coordinate tuple). See + :ref:`coordinate-system`. + :param value: Fill color. + :param border: Optional border value. If given, the region consists of + pixels with a color different from the border color. If not given, + the region consists of pixels having the same color as the seed + pixel. + :param thresh: Optional threshold value which specifies a maximum + tolerable difference of a pixel value from the 'background' in + order for it to be replaced. Useful for filling regions of + non-homogeneous, but similar, colors. + """ + # based on an implementation by Eric S. Raymond + # amended by yo1995 @20180806 + pixel = image.load() + assert pixel is not None + x, y = xy + try: + background = pixel[x, y] + if _color_diff(value, background) <= thresh: + return # seed point already has fill color + pixel[x, y] = value + except (ValueError, IndexError): + return # seed point outside image + edge = {(x, y)} + # use a set to keep record of current and previous edge pixels + # to reduce memory consumption + full_edge = set() + while edge: + new_edge = set() + for x, y in edge: # 4 adjacent method + for s, t in ((x + 1, y), (x - 1, y), (x, y + 1), (x, y - 1)): + # If already processed, or if a coordinate is negative, skip + if (s, t) in full_edge or s < 0 or t < 0: + continue + try: + p = pixel[s, t] + except (ValueError, IndexError): + pass + else: + full_edge.add((s, t)) + if border is None: + fill = _color_diff(p, background) <= thresh + else: + fill = p not in (value, border) + if fill: + pixel[s, t] = value + new_edge.add((s, t)) + full_edge = edge # discard pixels processed + edge = new_edge + + +def _compute_regular_polygon_vertices( + bounding_circle: Sequence[Sequence[float] | float], n_sides: int, rotation: float +) -> list[tuple[float, float]]: + """ + Generate a list of vertices for a 2D regular polygon. + + :param bounding_circle: The bounding circle is a sequence defined + by a point and radius. The polygon is inscribed in this circle. + (e.g. ``bounding_circle=(x, y, r)`` or ``((x, y), r)``) + :param n_sides: Number of sides + (e.g. ``n_sides=3`` for a triangle, ``6`` for a hexagon) + :param rotation: Apply an arbitrary rotation to the polygon + (e.g. ``rotation=90``, applies a 90 degree rotation) + :return: List of regular polygon vertices + (e.g. ``[(25, 50), (50, 50), (50, 25), (25, 25)]``) + + How are the vertices computed? + 1. Compute the following variables + - theta: Angle between the apothem & the nearest polygon vertex + - side_length: Length of each polygon edge + - centroid: Center of bounding circle (1st, 2nd elements of bounding_circle) + - polygon_radius: Polygon radius (last element of bounding_circle) + - angles: Location of each polygon vertex in polar grid + (e.g. A square with 0 degree rotation => [225.0, 315.0, 45.0, 135.0]) + + 2. For each angle in angles, get the polygon vertex at that angle + The vertex is computed using the equation below. + X= xcos(φ) + ysin(φ) + Y= −xsin(φ) + ycos(φ) + + Note: + φ = angle in degrees + x = 0 + y = polygon_radius + + The formula above assumes rotation around the origin. + In our case, we are rotating around the centroid. + To account for this, we use the formula below + X = xcos(φ) + ysin(φ) + centroid_x + Y = −xsin(φ) + ycos(φ) + centroid_y + """ + # 1. Error Handling + # 1.1 Check `n_sides` has an appropriate value + if not isinstance(n_sides, int): + msg = "n_sides should be an int" # type: ignore[unreachable] + raise TypeError(msg) + if n_sides < 3: + msg = "n_sides should be an int > 2" + raise ValueError(msg) + + # 1.2 Check `bounding_circle` has an appropriate value + if not isinstance(bounding_circle, (list, tuple)): + msg = "bounding_circle should be a sequence" + raise TypeError(msg) + + if len(bounding_circle) == 3: + if not all(isinstance(i, (int, float)) for i in bounding_circle): + msg = "bounding_circle should only contain numeric data" + raise ValueError(msg) + + *centroid, polygon_radius = cast(list[float], list(bounding_circle)) + elif len(bounding_circle) == 2 and isinstance(bounding_circle[0], (list, tuple)): + if not all( + isinstance(i, (int, float)) for i in bounding_circle[0] + ) or not isinstance(bounding_circle[1], (int, float)): + msg = "bounding_circle should only contain numeric data" + raise ValueError(msg) + + if len(bounding_circle[0]) != 2: + msg = "bounding_circle centre should contain 2D coordinates (e.g. (x, y))" + raise ValueError(msg) + + centroid = cast(list[float], list(bounding_circle[0])) + polygon_radius = cast(float, bounding_circle[1]) + else: + msg = ( + "bounding_circle should contain 2D coordinates " + "and a radius (e.g. (x, y, r) or ((x, y), r) )" + ) + raise ValueError(msg) + + if polygon_radius <= 0: + msg = "bounding_circle radius should be > 0" + raise ValueError(msg) + + # 1.3 Check `rotation` has an appropriate value + if not isinstance(rotation, (int, float)): + msg = "rotation should be an int or float" # type: ignore[unreachable] + raise ValueError(msg) + + # 2. Define Helper Functions + def _apply_rotation(point: list[float], degrees: float) -> tuple[float, float]: + return ( + round( + point[0] * math.cos(math.radians(360 - degrees)) + - point[1] * math.sin(math.radians(360 - degrees)) + + centroid[0], + 2, + ), + round( + point[1] * math.cos(math.radians(360 - degrees)) + + point[0] * math.sin(math.radians(360 - degrees)) + + centroid[1], + 2, + ), + ) + + def _compute_polygon_vertex(angle: float) -> tuple[float, float]: + start_point = [polygon_radius, 0] + return _apply_rotation(start_point, angle) + + def _get_angles(n_sides: int, rotation: float) -> list[float]: + angles = [] + degrees = 360 / n_sides + # Start with the bottom left polygon vertex + current_angle = (270 - 0.5 * degrees) + rotation + for _ in range(n_sides): + angles.append(current_angle) + current_angle += degrees + if current_angle > 360: + current_angle -= 360 + return angles + + # 3. Variable Declarations + angles = _get_angles(n_sides, rotation) + + # 4. Compute Vertices + return [_compute_polygon_vertex(angle) for angle in angles] + + +def _color_diff( + color1: float | tuple[int, ...], color2: float | tuple[int, ...] +) -> float: + """ + Uses 1-norm distance to calculate difference between two values. + """ + first = color1 if isinstance(color1, tuple) else (color1,) + second = color2 if isinstance(color2, tuple) else (color2,) + + return sum(abs(first[i] - second[i]) for i in range(len(second))) diff --git a/PIL/ImageDraw2.py b/PIL/ImageDraw2.py new file mode 100644 index 0000000000000000000000000000000000000000..3d68658ed5b79a36597e4953b888c41aa82fc7da --- /dev/null +++ b/PIL/ImageDraw2.py @@ -0,0 +1,243 @@ +# +# The Python Imaging Library +# $Id$ +# +# WCK-style drawing interface operations +# +# History: +# 2003-12-07 fl created +# 2005-05-15 fl updated; added to PIL as ImageDraw2 +# 2005-05-15 fl added text support +# 2005-05-20 fl added arc/chord/pieslice support +# +# Copyright (c) 2003-2005 by Secret Labs AB +# Copyright (c) 2003-2005 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# + + +""" +(Experimental) WCK-style drawing interface operations + +.. seealso:: :py:mod:`PIL.ImageDraw` +""" +from __future__ import annotations + +from typing import Any, AnyStr, BinaryIO + +from . import Image, ImageColor, ImageDraw, ImageFont, ImagePath +from ._typing import Coords, StrOrBytesPath + + +class Pen: + """Stores an outline color and width.""" + + def __init__(self, color: str, width: int = 1, opacity: int = 255) -> None: + self.color = ImageColor.getrgb(color) + self.width = width + + +class Brush: + """Stores a fill color""" + + def __init__(self, color: str, opacity: int = 255) -> None: + self.color = ImageColor.getrgb(color) + + +class Font: + """Stores a TrueType font and color""" + + def __init__( + self, color: str, file: StrOrBytesPath | BinaryIO, size: float = 12 + ) -> None: + # FIXME: add support for bitmap fonts + self.color = ImageColor.getrgb(color) + self.font = ImageFont.truetype(file, size) + + +class Draw: + """ + (Experimental) WCK-style drawing interface + """ + + def __init__( + self, + image: Image.Image | str, + size: tuple[int, int] | list[int] | None = None, + color: float | tuple[float, ...] | str | None = None, + ) -> None: + if isinstance(image, str): + if size is None: + msg = "If image argument is mode string, size must be a list or tuple" + raise ValueError(msg) + image = Image.new(image, size, color) + self.draw = ImageDraw.Draw(image) + self.image = image + self.transform: tuple[float, float, float, float, float, float] | None = None + + def flush(self) -> Image.Image: + return self.image + + def render( + self, + op: str, + xy: Coords, + pen: Pen | Brush | None, + brush: Brush | Pen | None = None, + **kwargs: Any, + ) -> None: + # handle color arguments + outline = fill = None + width = 1 + if isinstance(pen, Pen): + outline = pen.color + width = pen.width + elif isinstance(brush, Pen): + outline = brush.color + width = brush.width + if isinstance(brush, Brush): + fill = brush.color + elif isinstance(pen, Brush): + fill = pen.color + # handle transformation + if self.transform: + path = ImagePath.Path(xy) + path.transform(self.transform) + xy = path + # render the item + if op in ("arc", "line"): + kwargs.setdefault("fill", outline) + else: + kwargs.setdefault("fill", fill) + kwargs.setdefault("outline", outline) + if op == "line": + kwargs.setdefault("width", width) + getattr(self.draw, op)(xy, **kwargs) + + def settransform(self, offset: tuple[float, float]) -> None: + """Sets a transformation offset.""" + (xoffset, yoffset) = offset + self.transform = (1, 0, xoffset, 0, 1, yoffset) + + def arc( + self, + xy: Coords, + pen: Pen | Brush | None, + start: float, + end: float, + *options: Any, + ) -> None: + """ + Draws an arc (a portion of a circle outline) between the start and end + angles, inside the given bounding box. + + .. seealso:: :py:meth:`PIL.ImageDraw.ImageDraw.arc` + """ + self.render("arc", xy, pen, *options, start=start, end=end) + + def chord( + self, + xy: Coords, + pen: Pen | Brush | None, + start: float, + end: float, + *options: Any, + ) -> None: + """ + Same as :py:meth:`~PIL.ImageDraw2.Draw.arc`, but connects the end points + with a straight line. + + .. seealso:: :py:meth:`PIL.ImageDraw.ImageDraw.chord` + """ + self.render("chord", xy, pen, *options, start=start, end=end) + + def ellipse(self, xy: Coords, pen: Pen | Brush | None, *options: Any) -> None: + """ + Draws an ellipse inside the given bounding box. + + .. seealso:: :py:meth:`PIL.ImageDraw.ImageDraw.ellipse` + """ + self.render("ellipse", xy, pen, *options) + + def line(self, xy: Coords, pen: Pen | Brush | None, *options: Any) -> None: + """ + Draws a line between the coordinates in the ``xy`` list. + + .. seealso:: :py:meth:`PIL.ImageDraw.ImageDraw.line` + """ + self.render("line", xy, pen, *options) + + def pieslice( + self, + xy: Coords, + pen: Pen | Brush | None, + start: float, + end: float, + *options: Any, + ) -> None: + """ + Same as arc, but also draws straight lines between the end points and the + center of the bounding box. + + .. seealso:: :py:meth:`PIL.ImageDraw.ImageDraw.pieslice` + """ + self.render("pieslice", xy, pen, *options, start=start, end=end) + + def polygon(self, xy: Coords, pen: Pen | Brush | None, *options: Any) -> None: + """ + Draws a polygon. + + The polygon outline consists of straight lines between the given + coordinates, plus a straight line between the last and the first + coordinate. + + + .. seealso:: :py:meth:`PIL.ImageDraw.ImageDraw.polygon` + """ + self.render("polygon", xy, pen, *options) + + def rectangle(self, xy: Coords, pen: Pen | Brush | None, *options: Any) -> None: + """ + Draws a rectangle. + + .. seealso:: :py:meth:`PIL.ImageDraw.ImageDraw.rectangle` + """ + self.render("rectangle", xy, pen, *options) + + def text(self, xy: tuple[float, float], text: AnyStr, font: Font) -> None: + """ + Draws the string at the given position. + + .. seealso:: :py:meth:`PIL.ImageDraw.ImageDraw.text` + """ + if self.transform: + path = ImagePath.Path(xy) + path.transform(self.transform) + xy = path + self.draw.text(xy, text, font=font.font, fill=font.color) + + def textbbox( + self, xy: tuple[float, float], text: AnyStr, font: Font + ) -> tuple[float, float, float, float]: + """ + Returns bounding box (in pixels) of given text. + + :return: ``(left, top, right, bottom)`` bounding box + + .. seealso:: :py:meth:`PIL.ImageDraw.ImageDraw.textbbox` + """ + if self.transform: + path = ImagePath.Path(xy) + path.transform(self.transform) + xy = path + return self.draw.textbbox(xy, text, font=font.font) + + def textlength(self, text: AnyStr, font: Font) -> float: + """ + Returns length (in pixels) of given text. + This is the amount by which following text should be offset. + + .. seealso:: :py:meth:`PIL.ImageDraw.ImageDraw.textlength` + """ + return self.draw.textlength(text, font=font.font) diff --git a/PIL/ImageEnhance.py b/PIL/ImageEnhance.py new file mode 100644 index 0000000000000000000000000000000000000000..0e7e6dd8ae631ad3577bda1d3e823bd2a3227536 --- /dev/null +++ b/PIL/ImageEnhance.py @@ -0,0 +1,113 @@ +# +# The Python Imaging Library. +# $Id$ +# +# image enhancement classes +# +# For a background, see "Image Processing By Interpolation and +# Extrapolation", Paul Haeberli and Douglas Voorhies. Available +# at http://www.graficaobscura.com/interp/index.html +# +# History: +# 1996-03-23 fl Created +# 2009-06-16 fl Fixed mean calculation +# +# Copyright (c) Secret Labs AB 1997. +# Copyright (c) Fredrik Lundh 1996. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +from . import Image, ImageFilter, ImageStat + + +class _Enhance: + image: Image.Image + degenerate: Image.Image + + def enhance(self, factor: float) -> Image.Image: + """ + Returns an enhanced image. + + :param factor: A floating point value controlling the enhancement. + Factor 1.0 always returns a copy of the original image, + lower factors mean less color (brightness, contrast, + etc), and higher values more. There are no restrictions + on this value. + :rtype: :py:class:`~PIL.Image.Image` + """ + return Image.blend(self.degenerate, self.image, factor) + + +class Color(_Enhance): + """Adjust image color balance. + + This class can be used to adjust the colour balance of an image, in + a manner similar to the controls on a colour TV set. An enhancement + factor of 0.0 gives a black and white image. A factor of 1.0 gives + the original image. + """ + + def __init__(self, image: Image.Image) -> None: + self.image = image + self.intermediate_mode = "L" + if "A" in image.getbands(): + self.intermediate_mode = "LA" + + if self.intermediate_mode != image.mode: + image = image.convert(self.intermediate_mode).convert(image.mode) + self.degenerate = image + + +class Contrast(_Enhance): + """Adjust image contrast. + + This class can be used to control the contrast of an image, similar + to the contrast control on a TV set. An enhancement factor of 0.0 + gives a solid gray image. A factor of 1.0 gives the original image. + """ + + def __init__(self, image: Image.Image) -> None: + self.image = image + if image.mode != "L": + image = image.convert("L") + mean = int(ImageStat.Stat(image).mean[0] + 0.5) + self.degenerate = Image.new("L", image.size, mean) + if self.degenerate.mode != self.image.mode: + self.degenerate = self.degenerate.convert(self.image.mode) + + if "A" in self.image.getbands(): + self.degenerate.putalpha(self.image.getchannel("A")) + + +class Brightness(_Enhance): + """Adjust image brightness. + + This class can be used to control the brightness of an image. An + enhancement factor of 0.0 gives a black image. A factor of 1.0 gives the + original image. + """ + + def __init__(self, image: Image.Image) -> None: + self.image = image + self.degenerate = Image.new(image.mode, image.size, 0) + + if "A" in image.getbands(): + self.degenerate.putalpha(image.getchannel("A")) + + +class Sharpness(_Enhance): + """Adjust image sharpness. + + This class can be used to adjust the sharpness of an image. An + enhancement factor of 0.0 gives a blurred image, a factor of 1.0 gives the + original image, and a factor of 2.0 gives a sharpened image. + """ + + def __init__(self, image: Image.Image) -> None: + self.image = image + self.degenerate = image.filter(ImageFilter.SMOOTH) + + if "A" in image.getbands(): + self.degenerate.putalpha(image.getchannel("A")) diff --git a/PIL/ImageFile.py b/PIL/ImageFile.py new file mode 100644 index 0000000000000000000000000000000000000000..3390dfa97dd176891379c4cf0653ea45b62ab1c0 --- /dev/null +++ b/PIL/ImageFile.py @@ -0,0 +1,938 @@ +# +# The Python Imaging Library. +# $Id$ +# +# base class for image file handlers +# +# history: +# 1995-09-09 fl Created +# 1996-03-11 fl Fixed load mechanism. +# 1996-04-15 fl Added pcx/xbm decoders. +# 1996-04-30 fl Added encoders. +# 1996-12-14 fl Added load helpers +# 1997-01-11 fl Use encode_to_file where possible +# 1997-08-27 fl Flush output in _save +# 1998-03-05 fl Use memory mapping for some modes +# 1999-02-04 fl Use memory mapping also for "I;16" and "I;16B" +# 1999-05-31 fl Added image parser +# 2000-10-12 fl Set readonly flag on memory-mapped images +# 2002-03-20 fl Use better messages for common decoder errors +# 2003-04-21 fl Fall back on mmap/map_buffer if map is not available +# 2003-10-30 fl Added StubImageFile class +# 2004-02-25 fl Made incremental parser more robust +# +# Copyright (c) 1997-2004 by Secret Labs AB +# Copyright (c) 1995-2004 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import abc +import io +import itertools +import logging +import os +import struct +from typing import IO, Any, NamedTuple, cast + +from . import ExifTags, Image +from ._util import DeferredError, is_path + +TYPE_CHECKING = False +if TYPE_CHECKING: + from ._typing import StrOrBytesPath + +logger = logging.getLogger(__name__) + +MAXBLOCK = 65536 +""" +By default, Pillow processes image data in blocks. This helps to prevent excessive use +of resources. Codecs may disable this behaviour with ``_pulls_fd`` or ``_pushes_fd``. + +When reading an image, this is the number of bytes to read at once. + +When writing an image, this is the number of bytes to write at once. +If the image width times 4 is greater, then that will be used instead. +Plugins may also set a greater number. + +User code may set this to another number. +""" + +SAFEBLOCK = 1024 * 1024 + +LOAD_TRUNCATED_IMAGES = False +"""Whether or not to load truncated image files. User code may change this.""" + +ERRORS = { + -1: "image buffer overrun error", + -2: "decoding error", + -3: "unknown error", + -8: "bad configuration", + -9: "out of memory error", +} +""" +Dict of known error codes returned from :meth:`.PyDecoder.decode`, +:meth:`.PyEncoder.encode` :meth:`.PyEncoder.encode_to_pyfd` and +:meth:`.PyEncoder.encode_to_file`. +""" + + +# +# -------------------------------------------------------------------- +# Helpers + + +def _get_oserror(error: int, *, encoder: bool) -> OSError: + try: + msg = Image.core.getcodecstatus(error) + except AttributeError: + msg = ERRORS.get(error) + if not msg: + msg = f"{'encoder' if encoder else 'decoder'} error {error}" + msg += f" when {'writing' if encoder else 'reading'} image file" + return OSError(msg) + + +def _tilesort(t: _Tile) -> int: + # sort on offset + return t[2] + + +class _Tile(NamedTuple): + codec_name: str + extents: tuple[int, int, int, int] | None + offset: int = 0 + args: tuple[Any, ...] | str | None = None + + +# +# -------------------------------------------------------------------- +# ImageFile base class + + +class ImageFile(Image.Image): + """Base class for image file format handlers.""" + + def __init__( + self, fp: StrOrBytesPath | IO[bytes], filename: str | bytes | None = None + ) -> None: + super().__init__() + + self._min_frame = 0 + + self.custom_mimetype: str | None = None + + self.tile: list[_Tile] = [] + """ A list of tile descriptors """ + + self.readonly = 1 # until we know better + + self.decoderconfig: tuple[Any, ...] = () + self.decodermaxblock = MAXBLOCK + + self.fp: IO[bytes] | None + self._fp: IO[bytes] | DeferredError + if is_path(fp): + # filename + self.fp = open(fp, "rb") + self.filename = os.fspath(fp) + self._exclusive_fp = True + else: + # stream + self.fp = cast(IO[bytes], fp) + self.filename = filename if filename is not None else "" + # can be overridden + self._exclusive_fp = False + + try: + try: + self._open() + except ( + IndexError, # end of data + TypeError, # end of data (ord) + KeyError, # unsupported mode + EOFError, # got header but not the first frame + struct.error, + ) as v: + raise SyntaxError(v) from v + + if not self.mode or self.size[0] <= 0 or self.size[1] <= 0: + msg = "not identified by this driver" + raise SyntaxError(msg) + except BaseException: + # close the file only if we have opened it this constructor + if self._exclusive_fp: + self.fp.close() + raise + + def _open(self) -> None: + pass + + # Context manager support + def __enter__(self) -> ImageFile: + return self + + def _close_fp(self) -> None: + if getattr(self, "_fp", False) and not isinstance(self._fp, DeferredError): + if self._fp != self.fp: + self._fp.close() + self._fp = DeferredError(ValueError("Operation on closed image")) + if self.fp: + self.fp.close() + + def __exit__(self, *args: object) -> None: + if getattr(self, "_exclusive_fp", False): + self._close_fp() + self.fp = None + + def close(self) -> None: + """ + Closes the file pointer, if possible. + + This operation will destroy the image core and release its memory. + The image data will be unusable afterward. + + This function is required to close images that have multiple frames or + have not had their file read and closed by the + :py:meth:`~PIL.Image.Image.load` method. See :ref:`file-handling` for + more information. + """ + try: + self._close_fp() + self.fp = None + except Exception as msg: + logger.debug("Error closing: %s", msg) + + super().close() + + def get_child_images(self) -> list[ImageFile]: + child_images = [] + exif = self.getexif() + ifds = [] + if ExifTags.Base.SubIFDs in exif: + subifd_offsets = exif[ExifTags.Base.SubIFDs] + if subifd_offsets: + if not isinstance(subifd_offsets, tuple): + subifd_offsets = (subifd_offsets,) + for subifd_offset in subifd_offsets: + ifds.append((exif._get_ifd_dict(subifd_offset), subifd_offset)) + ifd1 = exif.get_ifd(ExifTags.IFD.IFD1) + if ifd1 and ifd1.get(ExifTags.Base.JpegIFOffset): + assert exif._info is not None + ifds.append((ifd1, exif._info.next)) + + offset = None + for ifd, ifd_offset in ifds: + assert self.fp is not None + current_offset = self.fp.tell() + if offset is None: + offset = current_offset + + fp = self.fp + if ifd is not None: + thumbnail_offset = ifd.get(ExifTags.Base.JpegIFOffset) + if thumbnail_offset is not None: + thumbnail_offset += getattr(self, "_exif_offset", 0) + self.fp.seek(thumbnail_offset) + + length = ifd.get(ExifTags.Base.JpegIFByteCount) + assert isinstance(length, int) + data = self.fp.read(length) + fp = io.BytesIO(data) + + with Image.open(fp) as im: + from . import TiffImagePlugin + + if thumbnail_offset is None and isinstance( + im, TiffImagePlugin.TiffImageFile + ): + im._frame_pos = [ifd_offset] + im._seek(0) + im.load() + child_images.append(im) + + if offset is not None: + assert self.fp is not None + self.fp.seek(offset) + return child_images + + def get_format_mimetype(self) -> str | None: + if self.custom_mimetype: + return self.custom_mimetype + if self.format is not None: + return Image.MIME.get(self.format.upper()) + return None + + def __getstate__(self) -> list[Any]: + return super().__getstate__() + [self.filename] + + def __setstate__(self, state: list[Any]) -> None: + self.tile = [] + if len(state) > 5: + self.filename = state[5] + super().__setstate__(state) + + def verify(self) -> None: + """Check file integrity""" + + # raise exception if something's wrong. must be called + # directly after open, and closes file when finished. + if self._exclusive_fp and self.fp: + self.fp.close() + self.fp = None + + def load(self) -> Image.core.PixelAccess | None: + """Load image data based on tile list""" + + if not self.tile and self._im is None: + msg = "cannot load this image" + raise OSError(msg) + + pixel = Image.Image.load(self) + if not self.tile: + return pixel + + self.map: mmap.mmap | None = None + use_mmap = self.filename and len(self.tile) == 1 + + assert self.fp is not None + readonly = 0 + + # look for read/seek overrides + if hasattr(self, "load_read"): + read = self.load_read + # don't use mmap if there are custom read/seek functions + use_mmap = False + else: + read = self.fp.read + + if hasattr(self, "load_seek"): + seek = self.load_seek + use_mmap = False + else: + seek = self.fp.seek + + if use_mmap: + # try memory mapping + decoder_name, extents, offset, args = self.tile[0] + if isinstance(args, str): + args = (args, 0, 1) + if ( + decoder_name == "raw" + and isinstance(args, tuple) + and len(args) >= 3 + and args[0] == self.mode + and args[0] in Image._MAPMODES + ): + if offset < 0: + msg = "Tile offset cannot be negative" + raise ValueError(msg) + try: + # use mmap, if possible + import mmap + + with open(self.filename) as fp: + self.map = mmap.mmap(fp.fileno(), 0, access=mmap.ACCESS_READ) + if offset + self.size[1] * args[1] > self.map.size(): + msg = "buffer is not large enough" + raise OSError(msg) + self.im = Image.core.map_buffer( + self.map, self.size, decoder_name, offset, args + ) + readonly = 1 + # After trashing self.im, + # we might need to reload the palette data. + if self.palette: + self.palette.dirty = 1 + except (AttributeError, OSError, ImportError): + self.map = None + + self.load_prepare() + err_code = -3 # initialize to unknown error + if not self.map: + # sort tiles in file order + self.tile.sort(key=_tilesort) + + # FIXME: This is a hack to handle TIFF's JpegTables tag. + prefix = getattr(self, "tile_prefix", b"") + + # Remove consecutive duplicates that only differ by their offset + self.tile = [ + list(tiles)[-1] + for _, tiles in itertools.groupby( + self.tile, lambda tile: (tile[0], tile[1], tile[3]) + ) + ] + for i, (decoder_name, extents, offset, args) in enumerate(self.tile): + seek(offset) + decoder = Image._getdecoder( + self.mode, decoder_name, args, self.decoderconfig + ) + try: + decoder.setimage(self.im, extents) + if decoder.pulls_fd: + decoder.setfd(self.fp) + err_code = decoder.decode(b"")[1] + else: + b = prefix + while True: + read_bytes = self.decodermaxblock + if i + 1 < len(self.tile): + next_offset = self.tile[i + 1].offset + if next_offset > offset: + read_bytes = next_offset - offset + try: + s = read(read_bytes) + except (IndexError, struct.error) as e: + # truncated png/gif + if LOAD_TRUNCATED_IMAGES: + break + else: + msg = "image file is truncated" + raise OSError(msg) from e + + if not s: # truncated jpeg + if LOAD_TRUNCATED_IMAGES: + break + else: + msg = ( + "image file is truncated " + f"({len(b)} bytes not processed)" + ) + raise OSError(msg) + + b = b + s + n, err_code = decoder.decode(b) + if n < 0: + break + b = b[n:] + finally: + # Need to cleanup here to prevent leaks + decoder.cleanup() + + self.tile = [] + self.readonly = readonly + + self.load_end() + + if self._exclusive_fp and self._close_exclusive_fp_after_loading: + self.fp.close() + self.fp = None + + if not self.map and not LOAD_TRUNCATED_IMAGES and err_code < 0: + # still raised if decoder fails to return anything + raise _get_oserror(err_code, encoder=False) + + return Image.Image.load(self) + + def load_prepare(self) -> None: + # create image memory if necessary + if self._im is None: + self.im = Image.core.new(self.mode, self.size) + # create palette (optional) + if self.mode == "P": + Image.Image.load(self) + + def load_end(self) -> None: + # may be overridden + pass + + # may be defined for contained formats + # def load_seek(self, pos: int) -> None: + # pass + + # may be defined for blocked formats (e.g. PNG) + # def load_read(self, read_bytes: int) -> bytes: + # pass + + def _seek_check(self, frame: int) -> bool: + if ( + frame < self._min_frame + # Only check upper limit on frames if additional seek operations + # are not required to do so + or ( + not (hasattr(self, "_n_frames") and self._n_frames is None) + and frame >= getattr(self, "n_frames") + self._min_frame + ) + ): + msg = "attempt to seek outside sequence" + raise EOFError(msg) + + return self.tell() != frame + + +class StubHandler(abc.ABC): + def open(self, im: StubImageFile) -> None: + pass + + @abc.abstractmethod + def load(self, im: StubImageFile) -> Image.Image: + pass + + +class StubImageFile(ImageFile, metaclass=abc.ABCMeta): + """ + Base class for stub image loaders. + + A stub loader is an image loader that can identify files of a + certain format, but relies on external code to load the file. + """ + + @abc.abstractmethod + def _open(self) -> None: + pass + + def load(self) -> Image.core.PixelAccess | None: + loader = self._load() + if loader is None: + msg = f"cannot find loader for this {self.format} file" + raise OSError(msg) + image = loader.load(self) + assert image is not None + # become the other object (!) + self.__class__ = image.__class__ # type: ignore[assignment] + self.__dict__ = image.__dict__ + return image.load() + + @abc.abstractmethod + def _load(self) -> StubHandler | None: + """(Hook) Find actual image loader.""" + pass + + +class Parser: + """ + Incremental image parser. This class implements the standard + feed/close consumer interface. + """ + + incremental = None + image: Image.Image | None = None + data: bytes | None = None + decoder: Image.core.ImagingDecoder | PyDecoder | None = None + offset = 0 + finished = 0 + + def reset(self) -> None: + """ + (Consumer) Reset the parser. Note that you can only call this + method immediately after you've created a parser; parser + instances cannot be reused. + """ + assert self.data is None, "cannot reuse parsers" + + def feed(self, data: bytes) -> None: + """ + (Consumer) Feed data to the parser. + + :param data: A string buffer. + :exception OSError: If the parser failed to parse the image file. + """ + # collect data + + if self.finished: + return + + if self.data is None: + self.data = data + else: + self.data = self.data + data + + # parse what we have + if self.decoder: + if self.offset > 0: + # skip header + skip = min(len(self.data), self.offset) + self.data = self.data[skip:] + self.offset = self.offset - skip + if self.offset > 0 or not self.data: + return + + n, e = self.decoder.decode(self.data) + + if n < 0: + # end of stream + self.data = None + self.finished = 1 + if e < 0: + # decoding error + self.image = None + raise _get_oserror(e, encoder=False) + else: + # end of image + return + self.data = self.data[n:] + + elif self.image: + # if we end up here with no decoder, this file cannot + # be incrementally parsed. wait until we've gotten all + # available data + pass + + else: + # attempt to open this file + try: + with io.BytesIO(self.data) as fp: + im = Image.open(fp) + except OSError: + pass # not enough data + else: + flag = hasattr(im, "load_seek") or hasattr(im, "load_read") + if flag or len(im.tile) != 1: + # custom load code, or multiple tiles + self.decode = None + else: + # initialize decoder + im.load_prepare() + d, e, o, a = im.tile[0] + im.tile = [] + self.decoder = Image._getdecoder(im.mode, d, a, im.decoderconfig) + self.decoder.setimage(im.im, e) + + # calculate decoder offset + self.offset = o + if self.offset <= len(self.data): + self.data = self.data[self.offset :] + self.offset = 0 + + self.image = im + + def __enter__(self) -> Parser: + return self + + def __exit__(self, *args: object) -> None: + self.close() + + def close(self) -> Image.Image: + """ + (Consumer) Close the stream. + + :returns: An image object. + :exception OSError: If the parser failed to parse the image file either + because it cannot be identified or cannot be + decoded. + """ + # finish decoding + if self.decoder: + # get rid of what's left in the buffers + self.feed(b"") + self.data = self.decoder = None + if not self.finished: + msg = "image was incomplete" + raise OSError(msg) + if not self.image: + msg = "cannot parse this image" + raise OSError(msg) + if self.data: + # incremental parsing not possible; reopen the file + # not that we have all data + with io.BytesIO(self.data) as fp: + try: + self.image = Image.open(fp) + finally: + self.image.load() + return self.image + + +# -------------------------------------------------------------------- + + +def _save(im: Image.Image, fp: IO[bytes], tile: list[_Tile], bufsize: int = 0) -> None: + """Helper to save image based on tile list + + :param im: Image object. + :param fp: File object. + :param tile: Tile list. + :param bufsize: Optional buffer size + """ + + im.load() + if not hasattr(im, "encoderconfig"): + im.encoderconfig = () + tile.sort(key=_tilesort) + # FIXME: make MAXBLOCK a configuration parameter + # It would be great if we could have the encoder specify what it needs + # But, it would need at least the image size in most cases. RawEncode is + # a tricky case. + bufsize = max(MAXBLOCK, bufsize, im.size[0] * 4) # see RawEncode.c + try: + fh = fp.fileno() + fp.flush() + _encode_tile(im, fp, tile, bufsize, fh) + except (AttributeError, io.UnsupportedOperation) as exc: + _encode_tile(im, fp, tile, bufsize, None, exc) + if hasattr(fp, "flush"): + fp.flush() + + +def _encode_tile( + im: Image.Image, + fp: IO[bytes], + tile: list[_Tile], + bufsize: int, + fh: int | None, + exc: BaseException | None = None, +) -> None: + for encoder_name, extents, offset, args in tile: + if offset > 0: + fp.seek(offset) + encoder = Image._getencoder(im.mode, encoder_name, args, im.encoderconfig) + try: + encoder.setimage(im.im, extents) + if encoder.pushes_fd: + encoder.setfd(fp) + errcode = encoder.encode_to_pyfd()[1] + else: + if exc: + # compress to Python file-compatible object + while True: + errcode, data = encoder.encode(bufsize)[1:] + fp.write(data) + if errcode: + break + else: + # slight speedup: compress to real file object + assert fh is not None + errcode = encoder.encode_to_file(fh, bufsize) + if errcode < 0: + raise _get_oserror(errcode, encoder=True) from exc + finally: + encoder.cleanup() + + +def _safe_read(fp: IO[bytes], size: int) -> bytes: + """ + Reads large blocks in a safe way. Unlike fp.read(n), this function + doesn't trust the user. If the requested size is larger than + SAFEBLOCK, the file is read block by block. + + :param fp: File handle. Must implement a read method. + :param size: Number of bytes to read. + :returns: A string containing size bytes of data. + + Raises an OSError if the file is truncated and the read cannot be completed + + """ + if size <= 0: + return b"" + if size <= SAFEBLOCK: + data = fp.read(size) + if len(data) < size: + msg = "Truncated File Read" + raise OSError(msg) + return data + blocks: list[bytes] = [] + remaining_size = size + while remaining_size > 0: + block = fp.read(min(remaining_size, SAFEBLOCK)) + if not block: + break + blocks.append(block) + remaining_size -= len(block) + if sum(len(block) for block in blocks) < size: + msg = "Truncated File Read" + raise OSError(msg) + return b"".join(blocks) + + +class PyCodecState: + def __init__(self) -> None: + self.xsize = 0 + self.ysize = 0 + self.xoff = 0 + self.yoff = 0 + + def extents(self) -> tuple[int, int, int, int]: + return self.xoff, self.yoff, self.xoff + self.xsize, self.yoff + self.ysize + + +class PyCodec: + fd: IO[bytes] | None + + def __init__(self, mode: str, *args: Any) -> None: + self.im: Image.core.ImagingCore | None = None + self.state = PyCodecState() + self.fd = None + self.mode = mode + self.init(args) + + def init(self, args: tuple[Any, ...]) -> None: + """ + Override to perform codec specific initialization + + :param args: Tuple of arg items from the tile entry + :returns: None + """ + self.args = args + + def cleanup(self) -> None: + """ + Override to perform codec specific cleanup + + :returns: None + """ + pass + + def setfd(self, fd: IO[bytes]) -> None: + """ + Called from ImageFile to set the Python file-like object + + :param fd: A Python file-like object + :returns: None + """ + self.fd = fd + + def setimage( + self, + im: Image.core.ImagingCore, + extents: tuple[int, int, int, int] | None = None, + ) -> None: + """ + Called from ImageFile to set the core output image for the codec + + :param im: A core image object + :param extents: a 4 tuple of (x0, y0, x1, y1) defining the rectangle + for this tile + :returns: None + """ + + # following c code + self.im = im + + if extents: + (x0, y0, x1, y1) = extents + else: + (x0, y0, x1, y1) = (0, 0, 0, 0) + + if x0 == 0 and x1 == 0: + self.state.xsize, self.state.ysize = self.im.size + else: + self.state.xoff = x0 + self.state.yoff = y0 + self.state.xsize = x1 - x0 + self.state.ysize = y1 - y0 + + if self.state.xsize <= 0 or self.state.ysize <= 0: + msg = "Size cannot be negative" + raise ValueError(msg) + + if ( + self.state.xsize + self.state.xoff > self.im.size[0] + or self.state.ysize + self.state.yoff > self.im.size[1] + ): + msg = "Tile cannot extend outside image" + raise ValueError(msg) + + +class PyDecoder(PyCodec): + """ + Python implementation of a format decoder. Override this class and + add the decoding logic in the :meth:`decode` method. + + See :ref:`Writing Your Own File Codec in Python` + """ + + _pulls_fd = False + + @property + def pulls_fd(self) -> bool: + return self._pulls_fd + + def decode(self, buffer: bytes | Image.SupportsArrayInterface) -> tuple[int, int]: + """ + Override to perform the decoding process. + + :param buffer: A bytes object with the data to be decoded. + :returns: A tuple of ``(bytes consumed, errcode)``. + If finished with decoding return -1 for the bytes consumed. + Err codes are from :data:`.ImageFile.ERRORS`. + """ + msg = "unavailable in base decoder" + raise NotImplementedError(msg) + + def set_as_raw( + self, data: bytes, rawmode: str | None = None, extra: tuple[Any, ...] = () + ) -> None: + """ + Convenience method to set the internal image from a stream of raw data + + :param data: Bytes to be set + :param rawmode: The rawmode to be used for the decoder. + If not specified, it will default to the mode of the image + :param extra: Extra arguments for the decoder. + :returns: None + """ + + if not rawmode: + rawmode = self.mode + d = Image._getdecoder(self.mode, "raw", rawmode, extra) + assert self.im is not None + d.setimage(self.im, self.state.extents()) + s = d.decode(data) + + if s[0] >= 0: + msg = "not enough image data" + raise ValueError(msg) + if s[1] != 0: + msg = "cannot decode image data" + raise ValueError(msg) + + +class PyEncoder(PyCodec): + """ + Python implementation of a format encoder. Override this class and + add the decoding logic in the :meth:`encode` method. + + See :ref:`Writing Your Own File Codec in Python` + """ + + _pushes_fd = False + + @property + def pushes_fd(self) -> bool: + return self._pushes_fd + + def encode(self, bufsize: int) -> tuple[int, int, bytes]: + """ + Override to perform the encoding process. + + :param bufsize: Buffer size. + :returns: A tuple of ``(bytes encoded, errcode, bytes)``. + If finished with encoding return 1 for the error code. + Err codes are from :data:`.ImageFile.ERRORS`. + """ + msg = "unavailable in base encoder" + raise NotImplementedError(msg) + + def encode_to_pyfd(self) -> tuple[int, int]: + """ + If ``pushes_fd`` is ``True``, then this method will be used, + and ``encode()`` will only be called once. + + :returns: A tuple of ``(bytes consumed, errcode)``. + Err codes are from :data:`.ImageFile.ERRORS`. + """ + if not self.pushes_fd: + return 0, -8 # bad configuration + bytes_consumed, errcode, data = self.encode(0) + if data: + assert self.fd is not None + self.fd.write(data) + return bytes_consumed, errcode + + def encode_to_file(self, fh: int, bufsize: int) -> int: + """ + :param fh: File handle. + :param bufsize: Buffer size. + + :returns: If finished successfully, return 0. + Otherwise, return an error code. Err codes are from + :data:`.ImageFile.ERRORS`. + """ + errcode = 0 + while errcode == 0: + status, errcode, buf = self.encode(bufsize) + if status > 0: + os.write(fh, buf[status:]) + return errcode diff --git a/PIL/ImageFont.py b/PIL/ImageFont.py new file mode 100644 index 0000000000000000000000000000000000000000..d11f7bf01ad062ae376b3c01c8014541b7037abb --- /dev/null +++ b/PIL/ImageFont.py @@ -0,0 +1,1320 @@ +# +# The Python Imaging Library. +# $Id$ +# +# PIL raster font management +# +# History: +# 1996-08-07 fl created (experimental) +# 1997-08-25 fl minor adjustments to handle fonts from pilfont 0.3 +# 1999-02-06 fl rewrote most font management stuff in C +# 1999-03-17 fl take pth files into account in load_path (from Richard Jones) +# 2001-02-17 fl added freetype support +# 2001-05-09 fl added TransposedFont wrapper class +# 2002-03-04 fl make sure we have a "L" or "1" font +# 2002-12-04 fl skip non-directory entries in the system path +# 2003-04-29 fl add embedded default font +# 2003-09-27 fl added support for truetype charmap encodings +# +# Todo: +# Adapt to PILFONT2 format (16-bit fonts, compressed, single file) +# +# Copyright (c) 1997-2003 by Secret Labs AB +# Copyright (c) 1996-2003 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# + +from __future__ import annotations + +import base64 +import os +import sys +import warnings +from enum import IntEnum +from io import BytesIO +from types import ModuleType +from typing import IO, Any, BinaryIO, TypedDict, cast + +from . import Image +from ._typing import StrOrBytesPath +from ._util import DeferredError, is_path + +TYPE_CHECKING = False +if TYPE_CHECKING: + from . import ImageFile + from ._imaging import ImagingFont + from ._imagingft import Font + + +class Axis(TypedDict): + minimum: int | None + default: int | None + maximum: int | None + name: bytes | None + + +class Layout(IntEnum): + BASIC = 0 + RAQM = 1 + + +MAX_STRING_LENGTH = 1_000_000 + + +core: ModuleType | DeferredError +try: + from . import _imagingft as core +except ImportError as ex: + core = DeferredError.new(ex) + + +def _string_length_check(text: str | bytes | bytearray) -> None: + if MAX_STRING_LENGTH is not None and len(text) > MAX_STRING_LENGTH: + msg = "too many characters in string" + raise ValueError(msg) + + +# FIXME: add support for pilfont2 format (see FontFile.py) + +# -------------------------------------------------------------------- +# Font metrics format: +# "PILfont" LF +# fontdescriptor LF +# (optional) key=value... LF +# "DATA" LF +# binary data: 256*10*2 bytes (dx, dy, dstbox, srcbox) +# +# To place a character, cut out srcbox and paste at dstbox, +# relative to the character position. Then move the character +# position according to dx, dy. +# -------------------------------------------------------------------- + + +class ImageFont: + """PIL font wrapper""" + + font: ImagingFont + + def _load_pilfont(self, filename: str) -> None: + with open(filename, "rb") as fp: + image: ImageFile.ImageFile | None = None + root = os.path.splitext(filename)[0] + + for ext in (".png", ".gif", ".pbm"): + if image: + image.close() + try: + fullname = root + ext + image = Image.open(fullname) + except Exception: + pass + else: + if image and image.mode in ("1", "L"): + break + else: + if image: + image.close() + + msg = f"cannot find glyph data file {root}.{{gif|pbm|png}}" + raise OSError(msg) + + self.file = fullname + + self._load_pilfont_data(fp, image) + image.close() + + def _load_pilfont_data(self, file: IO[bytes], image: Image.Image) -> None: + # check image + if image.mode not in ("1", "L"): + image.close() + + msg = "invalid font image mode" + raise TypeError(msg) + + # read PILfont header + if file.read(8) != b"PILfont\n": + image.close() + + msg = "Not a PILfont file" + raise SyntaxError(msg) + file.readline() + self.info = [] # FIXME: should be a dictionary + while True: + s = file.readline() + if not s or s == b"DATA\n": + break + self.info.append(s) + + # read PILfont metrics + data = file.read(256 * 20) + + image.load() + + self.font = Image.core.font(image.im, data) + + def getmask( + self, text: str | bytes, mode: str = "", *args: Any, **kwargs: Any + ) -> Image.core.ImagingCore: + """ + Create a bitmap for the text. + + If the font uses antialiasing, the bitmap should have mode ``L`` and use a + maximum value of 255. Otherwise, it should have mode ``1``. + + :param text: Text to render. + :param mode: Used by some graphics drivers to indicate what mode the + driver prefers; if empty, the renderer may return either + mode. Note that the mode is always a string, to simplify + C-level implementations. + + .. versionadded:: 1.1.5 + + :return: An internal PIL storage memory instance as defined by the + :py:mod:`PIL.Image.core` interface module. + """ + _string_length_check(text) + Image._decompression_bomb_check(self.font.getsize(text)) + return self.font.getmask(text, mode) + + def getbbox( + self, text: str | bytes | bytearray, *args: Any, **kwargs: Any + ) -> tuple[int, int, int, int]: + """ + Returns bounding box (in pixels) of given text. + + .. versionadded:: 9.2.0 + + :param text: Text to render. + + :return: ``(left, top, right, bottom)`` bounding box + """ + _string_length_check(text) + width, height = self.font.getsize(text) + return 0, 0, width, height + + def getlength( + self, text: str | bytes | bytearray, *args: Any, **kwargs: Any + ) -> int: + """ + Returns length (in pixels) of given text. + This is the amount by which following text should be offset. + + .. versionadded:: 9.2.0 + """ + _string_length_check(text) + width, height = self.font.getsize(text) + return width + + +## +# Wrapper for FreeType fonts. Application code should use the +# truetype factory function to create font objects. + + +class FreeTypeFont: + """FreeType font wrapper (requires _imagingft service)""" + + font: Font + font_bytes: bytes + + def __init__( + self, + font: StrOrBytesPath | BinaryIO, + size: float = 10, + index: int = 0, + encoding: str = "", + layout_engine: Layout | None = None, + ) -> None: + # FIXME: use service provider instead + + if isinstance(core, DeferredError): + raise core.ex + + if size <= 0: + msg = f"font size must be greater than 0, not {size}" + raise ValueError(msg) + + self.path = font + self.size = size + self.index = index + self.encoding = encoding + + if layout_engine not in (Layout.BASIC, Layout.RAQM): + layout_engine = Layout.BASIC + if core.HAVE_RAQM: + layout_engine = Layout.RAQM + elif layout_engine == Layout.RAQM and not core.HAVE_RAQM: + warnings.warn( + "Raqm layout was requested, but Raqm is not available. " + "Falling back to basic layout." + ) + layout_engine = Layout.BASIC + + self.layout_engine = layout_engine + + def load_from_bytes(f: IO[bytes]) -> None: + self.font_bytes = f.read() + self.font = core.getfont( + "", size, index, encoding, self.font_bytes, layout_engine + ) + + if is_path(font): + font = os.fspath(font) + if sys.platform == "win32": + font_bytes_path = font if isinstance(font, bytes) else font.encode() + try: + font_bytes_path.decode("ascii") + except UnicodeDecodeError: + # FreeType cannot load fonts with non-ASCII characters on Windows + # So load it into memory first + with open(font, "rb") as f: + load_from_bytes(f) + return + self.font = core.getfont( + font, size, index, encoding, layout_engine=layout_engine + ) + else: + load_from_bytes(cast(IO[bytes], font)) + + def __getstate__(self) -> list[Any]: + return [self.path, self.size, self.index, self.encoding, self.layout_engine] + + def __setstate__(self, state: list[Any]) -> None: + path, size, index, encoding, layout_engine = state + FreeTypeFont.__init__(self, path, size, index, encoding, layout_engine) + + def getname(self) -> tuple[str | None, str | None]: + """ + :return: A tuple of the font family (e.g. Helvetica) and the font style + (e.g. Bold) + """ + return self.font.family, self.font.style + + def getmetrics(self) -> tuple[int, int]: + """ + :return: A tuple of the font ascent (the distance from the baseline to + the highest outline point) and descent (the distance from the + baseline to the lowest outline point, a negative value) + """ + return self.font.ascent, self.font.descent + + def getlength( + self, + text: str | bytes, + mode: str = "", + direction: str | None = None, + features: list[str] | None = None, + language: str | None = None, + ) -> float: + """ + Returns length (in pixels with 1/64 precision) of given text when rendered + in font with provided direction, features, and language. + + This is the amount by which following text should be offset. + Text bounding box may extend past the length in some fonts, + e.g. when using italics or accents. + + The result is returned as a float; it is a whole number if using basic layout. + + Note that the sum of two lengths may not equal the length of a concatenated + string due to kerning. If you need to adjust for kerning, include the following + character and subtract its length. + + For example, instead of :: + + hello = font.getlength("Hello") + world = font.getlength("World") + hello_world = hello + world # not adjusted for kerning + assert hello_world == font.getlength("HelloWorld") # may fail + + use :: + + hello = font.getlength("HelloW") - font.getlength("W") # adjusted for kerning + world = font.getlength("World") + hello_world = hello + world # adjusted for kerning + assert hello_world == font.getlength("HelloWorld") # True + + or disable kerning with (requires libraqm) :: + + hello = draw.textlength("Hello", font, features=["-kern"]) + world = draw.textlength("World", font, features=["-kern"]) + hello_world = hello + world # kerning is disabled, no need to adjust + assert hello_world == draw.textlength("HelloWorld", font, features=["-kern"]) + + .. versionadded:: 8.0.0 + + :param text: Text to measure. + :param mode: Used by some graphics drivers to indicate what mode the + driver prefers; if empty, the renderer may return either + mode. Note that the mode is always a string, to simplify + C-level implementations. + + :param direction: Direction of the text. It can be 'rtl' (right to + left), 'ltr' (left to right) or 'ttb' (top to bottom). + Requires libraqm. + + :param features: A list of OpenType font features to be used during text + layout. This is usually used to turn on optional + font features that are not enabled by default, + for example 'dlig' or 'ss01', but can be also + used to turn off default font features for + example '-liga' to disable ligatures or '-kern' + to disable kerning. To get all supported + features, see + https://learn.microsoft.com/en-us/typography/opentype/spec/featurelist + Requires libraqm. + + :param language: Language of the text. Different languages may use + different glyph shapes or ligatures. This parameter tells + the font which language the text is in, and to apply the + correct substitutions as appropriate, if available. + It should be a `BCP 47 language code + `_ + Requires libraqm. + + :return: Either width for horizontal text, or height for vertical text. + """ + _string_length_check(text) + return self.font.getlength(text, mode, direction, features, language) / 64 + + def getbbox( + self, + text: str | bytes, + mode: str = "", + direction: str | None = None, + features: list[str] | None = None, + language: str | None = None, + stroke_width: float = 0, + anchor: str | None = None, + ) -> tuple[float, float, float, float]: + """ + Returns bounding box (in pixels) of given text relative to given anchor + when rendered in font with provided direction, features, and language. + + Use :py:meth:`getlength()` to get the offset of following text with + 1/64 pixel precision. The bounding box includes extra margins for + some fonts, e.g. italics or accents. + + .. versionadded:: 8.0.0 + + :param text: Text to render. + :param mode: Used by some graphics drivers to indicate what mode the + driver prefers; if empty, the renderer may return either + mode. Note that the mode is always a string, to simplify + C-level implementations. + + :param direction: Direction of the text. It can be 'rtl' (right to + left), 'ltr' (left to right) or 'ttb' (top to bottom). + Requires libraqm. + + :param features: A list of OpenType font features to be used during text + layout. This is usually used to turn on optional + font features that are not enabled by default, + for example 'dlig' or 'ss01', but can be also + used to turn off default font features for + example '-liga' to disable ligatures or '-kern' + to disable kerning. To get all supported + features, see + https://learn.microsoft.com/en-us/typography/opentype/spec/featurelist + Requires libraqm. + + :param language: Language of the text. Different languages may use + different glyph shapes or ligatures. This parameter tells + the font which language the text is in, and to apply the + correct substitutions as appropriate, if available. + It should be a `BCP 47 language code + `_ + Requires libraqm. + + :param stroke_width: The width of the text stroke. + + :param anchor: The text anchor alignment. Determines the relative location of + the anchor to the text. The default alignment is top left, + specifically ``la`` for horizontal text and ``lt`` for + vertical text. See :ref:`text-anchors` for details. + + :return: ``(left, top, right, bottom)`` bounding box + """ + _string_length_check(text) + size, offset = self.font.getsize( + text, mode, direction, features, language, anchor + ) + left, top = offset[0] - stroke_width, offset[1] - stroke_width + width, height = size[0] + 2 * stroke_width, size[1] + 2 * stroke_width + return left, top, left + width, top + height + + def getmask( + self, + text: str | bytes, + mode: str = "", + direction: str | None = None, + features: list[str] | None = None, + language: str | None = None, + stroke_width: float = 0, + anchor: str | None = None, + ink: int = 0, + start: tuple[float, float] | None = None, + ) -> Image.core.ImagingCore: + """ + Create a bitmap for the text. + + If the font uses antialiasing, the bitmap should have mode ``L`` and use a + maximum value of 255. If the font has embedded color data, the bitmap + should have mode ``RGBA``. Otherwise, it should have mode ``1``. + + :param text: Text to render. + :param mode: Used by some graphics drivers to indicate what mode the + driver prefers; if empty, the renderer may return either + mode. Note that the mode is always a string, to simplify + C-level implementations. + + .. versionadded:: 1.1.5 + + :param direction: Direction of the text. It can be 'rtl' (right to + left), 'ltr' (left to right) or 'ttb' (top to bottom). + Requires libraqm. + + .. versionadded:: 4.2.0 + + :param features: A list of OpenType font features to be used during text + layout. This is usually used to turn on optional + font features that are not enabled by default, + for example 'dlig' or 'ss01', but can be also + used to turn off default font features for + example '-liga' to disable ligatures or '-kern' + to disable kerning. To get all supported + features, see + https://learn.microsoft.com/en-us/typography/opentype/spec/featurelist + Requires libraqm. + + .. versionadded:: 4.2.0 + + :param language: Language of the text. Different languages may use + different glyph shapes or ligatures. This parameter tells + the font which language the text is in, and to apply the + correct substitutions as appropriate, if available. + It should be a `BCP 47 language code + `_ + Requires libraqm. + + .. versionadded:: 6.0.0 + + :param stroke_width: The width of the text stroke. + + .. versionadded:: 6.2.0 + + :param anchor: The text anchor alignment. Determines the relative location of + the anchor to the text. The default alignment is top left, + specifically ``la`` for horizontal text and ``lt`` for + vertical text. See :ref:`text-anchors` for details. + + .. versionadded:: 8.0.0 + + :param ink: Foreground ink for rendering in RGBA mode. + + .. versionadded:: 8.0.0 + + :param start: Tuple of horizontal and vertical offset, as text may render + differently when starting at fractional coordinates. + + .. versionadded:: 9.4.0 + + :return: An internal PIL storage memory instance as defined by the + :py:mod:`PIL.Image.core` interface module. + """ + return self.getmask2( + text, + mode, + direction=direction, + features=features, + language=language, + stroke_width=stroke_width, + anchor=anchor, + ink=ink, + start=start, + )[0] + + def getmask2( + self, + text: str | bytes, + mode: str = "", + direction: str | None = None, + features: list[str] | None = None, + language: str | None = None, + stroke_width: float = 0, + anchor: str | None = None, + ink: int = 0, + start: tuple[float, float] | None = None, + *args: Any, + **kwargs: Any, + ) -> tuple[Image.core.ImagingCore, tuple[int, int]]: + """ + Create a bitmap for the text. + + If the font uses antialiasing, the bitmap should have mode ``L`` and use a + maximum value of 255. If the font has embedded color data, the bitmap + should have mode ``RGBA``. Otherwise, it should have mode ``1``. + + :param text: Text to render. + :param mode: Used by some graphics drivers to indicate what mode the + driver prefers; if empty, the renderer may return either + mode. Note that the mode is always a string, to simplify + C-level implementations. + + .. versionadded:: 1.1.5 + + :param direction: Direction of the text. It can be 'rtl' (right to + left), 'ltr' (left to right) or 'ttb' (top to bottom). + Requires libraqm. + + .. versionadded:: 4.2.0 + + :param features: A list of OpenType font features to be used during text + layout. This is usually used to turn on optional + font features that are not enabled by default, + for example 'dlig' or 'ss01', but can be also + used to turn off default font features for + example '-liga' to disable ligatures or '-kern' + to disable kerning. To get all supported + features, see + https://learn.microsoft.com/en-us/typography/opentype/spec/featurelist + Requires libraqm. + + .. versionadded:: 4.2.0 + + :param language: Language of the text. Different languages may use + different glyph shapes or ligatures. This parameter tells + the font which language the text is in, and to apply the + correct substitutions as appropriate, if available. + It should be a `BCP 47 language code + `_ + Requires libraqm. + + .. versionadded:: 6.0.0 + + :param stroke_width: The width of the text stroke. + + .. versionadded:: 6.2.0 + + :param anchor: The text anchor alignment. Determines the relative location of + the anchor to the text. The default alignment is top left, + specifically ``la`` for horizontal text and ``lt`` for + vertical text. See :ref:`text-anchors` for details. + + .. versionadded:: 8.0.0 + + :param ink: Foreground ink for rendering in RGBA mode. + + .. versionadded:: 8.0.0 + + :param start: Tuple of horizontal and vertical offset, as text may render + differently when starting at fractional coordinates. + + .. versionadded:: 9.4.0 + + :return: A tuple of an internal PIL storage memory instance as defined by the + :py:mod:`PIL.Image.core` interface module, and the text offset, the + gap between the starting coordinate and the first marking + """ + _string_length_check(text) + if start is None: + start = (0, 0) + + def fill(width: int, height: int) -> Image.core.ImagingCore: + size = (width, height) + Image._decompression_bomb_check(size) + return Image.core.fill("RGBA" if mode == "RGBA" else "L", size) + + return self.font.render( + text, + fill, + mode, + direction, + features, + language, + stroke_width, + kwargs.get("stroke_filled", False), + anchor, + ink, + start, + ) + + def font_variant( + self, + font: StrOrBytesPath | BinaryIO | None = None, + size: float | None = None, + index: int | None = None, + encoding: str | None = None, + layout_engine: Layout | None = None, + ) -> FreeTypeFont: + """ + Create a copy of this FreeTypeFont object, + using any specified arguments to override the settings. + + Parameters are identical to the parameters used to initialize this + object. + + :return: A FreeTypeFont object. + """ + if font is None: + try: + font = BytesIO(self.font_bytes) + except AttributeError: + font = self.path + return FreeTypeFont( + font=font, + size=self.size if size is None else size, + index=self.index if index is None else index, + encoding=self.encoding if encoding is None else encoding, + layout_engine=layout_engine or self.layout_engine, + ) + + def get_variation_names(self) -> list[bytes]: + """ + :returns: A list of the named styles in a variation font. + :exception OSError: If the font is not a variation font. + """ + names = [] + for name in self.font.getvarnames(): + name = name.replace(b"\x00", b"") + if name not in names: + names.append(name) + return names + + def set_variation_by_name(self, name: str | bytes) -> None: + """ + :param name: The name of the style. + :exception OSError: If the font is not a variation font. + """ + names = self.get_variation_names() + if not isinstance(name, bytes): + name = name.encode() + index = names.index(name) + 1 + + if index == getattr(self, "_last_variation_index", None): + # When the same name is set twice in a row, + # there is an 'unknown freetype error' + # https://savannah.nongnu.org/bugs/?56186 + return + self._last_variation_index = index + + self.font.setvarname(index) + + def get_variation_axes(self) -> list[Axis]: + """ + :returns: A list of the axes in a variation font. + :exception OSError: If the font is not a variation font. + """ + axes = self.font.getvaraxes() + for axis in axes: + if axis["name"]: + axis["name"] = axis["name"].replace(b"\x00", b"") + return axes + + def set_variation_by_axes(self, axes: list[float]) -> None: + """ + :param axes: A list of values for each axis. + :exception OSError: If the font is not a variation font. + """ + self.font.setvaraxes(axes) + + +class TransposedFont: + """Wrapper for writing rotated or mirrored text""" + + def __init__( + self, font: ImageFont | FreeTypeFont, orientation: Image.Transpose | None = None + ): + """ + Wrapper that creates a transposed font from any existing font + object. + + :param font: A font object. + :param orientation: An optional orientation. If given, this should + be one of Image.Transpose.FLIP_LEFT_RIGHT, Image.Transpose.FLIP_TOP_BOTTOM, + Image.Transpose.ROTATE_90, Image.Transpose.ROTATE_180, or + Image.Transpose.ROTATE_270. + """ + self.font = font + self.orientation = orientation # any 'transpose' argument, or None + + def getmask( + self, text: str | bytes, mode: str = "", *args: Any, **kwargs: Any + ) -> Image.core.ImagingCore: + im = self.font.getmask(text, mode, *args, **kwargs) + if self.orientation is not None: + return im.transpose(self.orientation) + return im + + def getbbox( + self, text: str | bytes, *args: Any, **kwargs: Any + ) -> tuple[int, int, float, float]: + # TransposedFont doesn't support getmask2, move top-left point to (0, 0) + # this has no effect on ImageFont and simulates anchor="lt" for FreeTypeFont + left, top, right, bottom = self.font.getbbox(text, *args, **kwargs) + width = right - left + height = bottom - top + if self.orientation in (Image.Transpose.ROTATE_90, Image.Transpose.ROTATE_270): + return 0, 0, height, width + return 0, 0, width, height + + def getlength(self, text: str | bytes, *args: Any, **kwargs: Any) -> float: + if self.orientation in (Image.Transpose.ROTATE_90, Image.Transpose.ROTATE_270): + msg = "text length is undefined for text rotated by 90 or 270 degrees" + raise ValueError(msg) + return self.font.getlength(text, *args, **kwargs) + + +def load(filename: str) -> ImageFont: + """ + Load a font file. This function loads a font object from the given + bitmap font file, and returns the corresponding font object. For loading TrueType + or OpenType fonts instead, see :py:func:`~PIL.ImageFont.truetype`. + + :param filename: Name of font file. + :return: A font object. + :exception OSError: If the file could not be read. + """ + f = ImageFont() + f._load_pilfont(filename) + return f + + +def truetype( + font: StrOrBytesPath | BinaryIO, + size: float = 10, + index: int = 0, + encoding: str = "", + layout_engine: Layout | None = None, +) -> FreeTypeFont: + """ + Load a TrueType or OpenType font from a file or file-like object, + and create a font object. This function loads a font object from the given + file or file-like object, and creates a font object for a font of the given + size. For loading bitmap fonts instead, see :py:func:`~PIL.ImageFont.load` + and :py:func:`~PIL.ImageFont.load_path`. + + Pillow uses FreeType to open font files. On Windows, be aware that FreeType + will keep the file open as long as the FreeTypeFont object exists. Windows + limits the number of files that can be open in C at once to 512, so if many + fonts are opened simultaneously and that limit is approached, an + ``OSError`` may be thrown, reporting that FreeType "cannot open resource". + A workaround would be to copy the file(s) into memory, and open that instead. + + This function requires the _imagingft service. + + :param font: A filename or file-like object containing a TrueType font. + If the file is not found in this filename, the loader may also + search in other directories, such as: + + * The :file:`fonts/` directory on Windows, + * :file:`/Library/Fonts/`, :file:`/System/Library/Fonts/` + and :file:`~/Library/Fonts/` on macOS. + * :file:`~/.local/share/fonts`, :file:`/usr/local/share/fonts`, + and :file:`/usr/share/fonts` on Linux; or those specified by + the ``XDG_DATA_HOME`` and ``XDG_DATA_DIRS`` environment variables + for user-installed and system-wide fonts, respectively. + + :param size: The requested size, in pixels. + :param index: Which font face to load (default is first available face). + :param encoding: Which font encoding to use (default is Unicode). Possible + encodings include (see the FreeType documentation for more + information): + + * "unic" (Unicode) + * "symb" (Microsoft Symbol) + * "ADOB" (Adobe Standard) + * "ADBE" (Adobe Expert) + * "ADBC" (Adobe Custom) + * "armn" (Apple Roman) + * "sjis" (Shift JIS) + * "gb " (PRC) + * "big5" + * "wans" (Extended Wansung) + * "joha" (Johab) + * "lat1" (Latin-1) + + This specifies the character set to use. It does not alter the + encoding of any text provided in subsequent operations. + :param layout_engine: Which layout engine to use, if available: + :attr:`.ImageFont.Layout.BASIC` or :attr:`.ImageFont.Layout.RAQM`. + If it is available, Raqm layout will be used by default. + Otherwise, basic layout will be used. + + Raqm layout is recommended for all non-English text. If Raqm layout + is not required, basic layout will have better performance. + + You can check support for Raqm layout using + :py:func:`PIL.features.check_feature` with ``feature="raqm"``. + + .. versionadded:: 4.2.0 + :return: A font object. + :exception OSError: If the file could not be read. + :exception ValueError: If the font size is not greater than zero. + """ + + def freetype(font: StrOrBytesPath | BinaryIO) -> FreeTypeFont: + return FreeTypeFont(font, size, index, encoding, layout_engine) + + try: + return freetype(font) + except OSError: + if not is_path(font): + raise + ttf_filename = os.path.basename(font) + + dirs = [] + if sys.platform == "win32": + # check the windows font repository + # NOTE: must use uppercase WINDIR, to work around bugs in + # 1.5.2's os.environ.get() + windir = os.environ.get("WINDIR") + if windir: + dirs.append(os.path.join(windir, "fonts")) + elif sys.platform in ("linux", "linux2"): + data_home = os.environ.get("XDG_DATA_HOME") + if not data_home: + # The freedesktop spec defines the following default directory for + # when XDG_DATA_HOME is unset or empty. This user-level directory + # takes precedence over system-level directories. + data_home = os.path.expanduser("~/.local/share") + xdg_dirs = [data_home] + + data_dirs = os.environ.get("XDG_DATA_DIRS") + if not data_dirs: + # Similarly, defaults are defined for the system-level directories + data_dirs = "/usr/local/share:/usr/share" + xdg_dirs += data_dirs.split(":") + + dirs += [os.path.join(xdg_dir, "fonts") for xdg_dir in xdg_dirs] + elif sys.platform == "darwin": + dirs += [ + "/Library/Fonts", + "/System/Library/Fonts", + os.path.expanduser("~/Library/Fonts"), + ] + + ext = os.path.splitext(ttf_filename)[1] + first_font_with_a_different_extension = None + for directory in dirs: + for walkroot, walkdir, walkfilenames in os.walk(directory): + for walkfilename in walkfilenames: + if ext and walkfilename == ttf_filename: + return freetype(os.path.join(walkroot, walkfilename)) + elif not ext and os.path.splitext(walkfilename)[0] == ttf_filename: + fontpath = os.path.join(walkroot, walkfilename) + if os.path.splitext(fontpath)[1] == ".ttf": + return freetype(fontpath) + if not ext and first_font_with_a_different_extension is None: + first_font_with_a_different_extension = fontpath + if first_font_with_a_different_extension: + return freetype(first_font_with_a_different_extension) + raise + + +def load_path(filename: str | bytes) -> ImageFont: + """ + Load font file. Same as :py:func:`~PIL.ImageFont.load`, but searches for a + bitmap font along the Python path. + + :param filename: Name of font file. + :return: A font object. + :exception OSError: If the file could not be read. + """ + if not isinstance(filename, str): + filename = filename.decode("utf-8") + for directory in sys.path: + try: + return load(os.path.join(directory, filename)) + except OSError: + pass + msg = f'cannot find font file "{filename}" in sys.path' + if os.path.exists(filename): + msg += f', did you mean ImageFont.load("{filename}") instead?' + + raise OSError(msg) + + +def load_default_imagefont() -> ImageFont: + f = ImageFont() + f._load_pilfont_data( + # courB08 + BytesIO( + base64.b64decode( + b""" +UElMZm9udAo7Ozs7OzsxMDsKREFUQQoAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA 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+ ), + 10 if size is None else size, + layout_engine=Layout.BASIC, + ) + return load_default_imagefont() diff --git a/PIL/ImageGrab.py b/PIL/ImageGrab.py new file mode 100644 index 0000000000000000000000000000000000000000..4228078b11b097fe0423aaf757158cbd1b96dd26 --- /dev/null +++ b/PIL/ImageGrab.py @@ -0,0 +1,224 @@ +# +# The Python Imaging Library +# $Id$ +# +# screen grabber +# +# History: +# 2001-04-26 fl created +# 2001-09-17 fl use builtin driver, if present +# 2002-11-19 fl added grabclipboard support +# +# Copyright (c) 2001-2002 by Secret Labs AB +# Copyright (c) 2001-2002 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import io +import os +import shutil +import subprocess +import sys +import tempfile + +from . import Image + +TYPE_CHECKING = False +if TYPE_CHECKING: + from . import ImageWin + + +def grab( + bbox: tuple[int, int, int, int] | None = None, + include_layered_windows: bool = False, + all_screens: bool = False, + xdisplay: str | None = None, + window: int | ImageWin.HWND | None = None, +) -> Image.Image: + im: Image.Image + if xdisplay is None: + if sys.platform == "darwin": + fh, filepath = tempfile.mkstemp(".png") + os.close(fh) + args = ["screencapture"] + if window: + args += ["-l", str(window)] + elif bbox: + left, top, right, bottom = bbox + args += ["-R", f"{left},{top},{right-left},{bottom-top}"] + subprocess.call(args + ["-x", filepath]) + im = Image.open(filepath) + im.load() + os.unlink(filepath) + if bbox: + if window: + # Determine if the window was in Retina mode or not + # by capturing it without the shadow, + # and checking how different the width is + fh, filepath = tempfile.mkstemp(".png") + os.close(fh) + subprocess.call( + ["screencapture", "-l", str(window), "-o", "-x", filepath] + ) + with Image.open(filepath) as im_no_shadow: + retina = im.width - im_no_shadow.width > 100 + os.unlink(filepath) + + # Since screencapture's -R does not work with -l, + # crop the image manually + if retina: + left, top, right, bottom = bbox + im_cropped = im.resize( + (right - left, bottom - top), + box=tuple(coord * 2 for coord in bbox), + ) + else: + im_cropped = im.crop(bbox) + im.close() + return im_cropped + else: + im_resized = im.resize((right - left, bottom - top)) + im.close() + return im_resized + return im + elif sys.platform == "win32": + if window is not None: + all_screens = -1 + offset, size, data = Image.core.grabscreen_win32( + include_layered_windows, + all_screens, + int(window) if window is not None else 0, + ) + im = Image.frombytes( + "RGB", + size, + data, + # RGB, 32-bit line padding, origin lower left corner + "raw", + "BGR", + (size[0] * 3 + 3) & -4, + -1, + ) + if bbox: + x0, y0 = offset + left, top, right, bottom = bbox + im = im.crop((left - x0, top - y0, right - x0, bottom - y0)) + return im + # Cast to Optional[str] needed for Windows and macOS. + display_name: str | None = xdisplay + try: + if not Image.core.HAVE_XCB: + msg = "Pillow was built without XCB support" + raise OSError(msg) + size, data = Image.core.grabscreen_x11(display_name) + except OSError: + if display_name is None and sys.platform not in ("darwin", "win32"): + if shutil.which("gnome-screenshot"): + args = ["gnome-screenshot", "-f"] + elif shutil.which("grim"): + args = ["grim"] + elif shutil.which("spectacle"): + args = ["spectacle", "-n", "-b", "-f", "-o"] + else: + raise + fh, filepath = tempfile.mkstemp(".png") + os.close(fh) + subprocess.call(args + [filepath]) + im = Image.open(filepath) + im.load() + os.unlink(filepath) + if bbox: + im_cropped = im.crop(bbox) + im.close() + return im_cropped + return im + else: + raise + else: + im = Image.frombytes("RGB", size, data, "raw", "BGRX", size[0] * 4, 1) + if bbox: + im = im.crop(bbox) + return im + + +def grabclipboard() -> Image.Image | list[str] | None: + if sys.platform == "darwin": + p = subprocess.run( + ["osascript", "-e", "get the clipboard as «class PNGf»"], + capture_output=True, + ) + if p.returncode != 0: + return None + + import binascii + + data = io.BytesIO(binascii.unhexlify(p.stdout[11:-3])) + return Image.open(data) + elif sys.platform == "win32": + fmt, data = Image.core.grabclipboard_win32() + if fmt == "file": # CF_HDROP + import struct + + o = struct.unpack_from("I", data)[0] + if data[16] == 0: + files = data[o:].decode("mbcs").split("\0") + else: + files = data[o:].decode("utf-16le").split("\0") + return files[: files.index("")] + if isinstance(data, bytes): + data = io.BytesIO(data) + if fmt == "png": + from . import PngImagePlugin + + return PngImagePlugin.PngImageFile(data) + elif fmt == "DIB": + from . import BmpImagePlugin + + return BmpImagePlugin.DibImageFile(data) + return None + else: + if os.getenv("WAYLAND_DISPLAY"): + session_type = "wayland" + elif os.getenv("DISPLAY"): + session_type = "x11" + else: # Session type check failed + session_type = None + + if shutil.which("wl-paste") and session_type in ("wayland", None): + args = ["wl-paste", "-t", "image"] + elif shutil.which("xclip") and session_type in ("x11", None): + args = ["xclip", "-selection", "clipboard", "-t", "image/png", "-o"] + else: + msg = "wl-paste or xclip is required for ImageGrab.grabclipboard() on Linux" + raise NotImplementedError(msg) + + p = subprocess.run(args, capture_output=True) + if p.returncode != 0: + err = p.stderr + for silent_error in [ + # wl-paste, when the clipboard is empty + b"Nothing is copied", + # Ubuntu/Debian wl-paste, when the clipboard is empty + b"No selection", + # Ubuntu/Debian wl-paste, when an image isn't available + b"No suitable type of content copied", + # wl-paste or Ubuntu/Debian xclip, when an image isn't available + b" not available", + # xclip, when an image isn't available + b"cannot convert ", + # xclip, when the clipboard isn't initialized + b"xclip: Error: There is no owner for the ", + ]: + if silent_error in err: + return None + msg = f"{args[0]} error" + if err: + msg += f": {err.strip().decode()}" + raise ChildProcessError(msg) + + data = io.BytesIO(p.stdout) + im = Image.open(data) + im.load() + return im diff --git a/PIL/ImageMode.py b/PIL/ImageMode.py new file mode 100644 index 0000000000000000000000000000000000000000..b7c6c863659b93416cac4acd8d8d31587566a9e6 --- /dev/null +++ b/PIL/ImageMode.py @@ -0,0 +1,85 @@ +# +# The Python Imaging Library. +# $Id$ +# +# standard mode descriptors +# +# History: +# 2006-03-20 fl Added +# +# Copyright (c) 2006 by Secret Labs AB. +# Copyright (c) 2006 by Fredrik Lundh. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import sys +from functools import lru_cache +from typing import NamedTuple + + +class ModeDescriptor(NamedTuple): + """Wrapper for mode strings.""" + + mode: str + bands: tuple[str, ...] + basemode: str + basetype: str + typestr: str + + def __str__(self) -> str: + return self.mode + + +@lru_cache +def getmode(mode: str) -> ModeDescriptor: + """Gets a mode descriptor for the given mode.""" + endian = "<" if sys.byteorder == "little" else ">" + + modes = { + # core modes + # Bits need to be extended to bytes + "1": ("L", "L", ("1",), "|b1"), + "L": ("L", "L", ("L",), "|u1"), + "I": ("L", "I", ("I",), f"{endian}i4"), + "F": ("L", "F", ("F",), f"{endian}f4"), + "P": ("P", "L", ("P",), "|u1"), + "RGB": ("RGB", "L", ("R", "G", "B"), "|u1"), + "RGBX": ("RGB", "L", ("R", "G", "B", "X"), "|u1"), + "RGBA": ("RGB", "L", ("R", "G", "B", "A"), "|u1"), + "CMYK": ("RGB", "L", ("C", "M", "Y", "K"), "|u1"), + "YCbCr": ("RGB", "L", ("Y", "Cb", "Cr"), "|u1"), + # UNDONE - unsigned |u1i1i1 + "LAB": ("RGB", "L", ("L", "A", "B"), "|u1"), + "HSV": ("RGB", "L", ("H", "S", "V"), "|u1"), + # extra experimental modes + "RGBa": ("RGB", "L", ("R", "G", "B", "a"), "|u1"), + "LA": ("L", "L", ("L", "A"), "|u1"), + "La": ("L", "L", ("L", "a"), "|u1"), + "PA": ("RGB", "L", ("P", "A"), "|u1"), + } + if mode in modes: + base_mode, base_type, bands, type_str = modes[mode] + return ModeDescriptor(mode, bands, base_mode, base_type, type_str) + + mapping_modes = { + # I;16 == I;16L, and I;32 == I;32L + "I;16": "u2", + "I;16BS": ">i2", + "I;16N": f"{endian}u2", + "I;16NS": f"{endian}i2", + "I;32": "u4", + "I;32L": "i4", + "I;32LS": " +from __future__ import annotations + +import re + +from . import Image, _imagingmorph + +LUT_SIZE = 1 << 9 + +# fmt: off +ROTATION_MATRIX = [ + 6, 3, 0, + 7, 4, 1, + 8, 5, 2, +] +MIRROR_MATRIX = [ + 2, 1, 0, + 5, 4, 3, + 8, 7, 6, +] +# fmt: on + + +class LutBuilder: + """A class for building a MorphLut from a descriptive language + + The input patterns is a list of a strings sequences like these:: + + 4:(... + .1. + 111)->1 + + (whitespaces including linebreaks are ignored). The option 4 + describes a series of symmetry operations (in this case a + 4-rotation), the pattern is described by: + + - . or X - Ignore + - 1 - Pixel is on + - 0 - Pixel is off + + The result of the operation is described after "->" string. + + The default is to return the current pixel value, which is + returned if no other match is found. + + Operations: + + - 4 - 4 way rotation + - N - Negate + - 1 - Dummy op for no other operation (an op must always be given) + - M - Mirroring + + Example:: + + lb = LutBuilder(patterns = ["4:(... .1. 111)->1"]) + lut = lb.build_lut() + + """ + + def __init__( + self, patterns: list[str] | None = None, op_name: str | None = None + ) -> None: + """ + :param patterns: A list of input patterns, or None. + :param op_name: The name of a known pattern. One of "corner", "dilation4", + "dilation8", "erosion4", "erosion8" or "edge". + :exception Exception: If the op_name is not recognized. + """ + self.lut: bytearray | None = None + if op_name is not None: + known_patterns = { + "corner": ["1:(... ... ...)->0", "4:(00. 01. ...)->1"], + "dilation4": ["4:(... .0. .1.)->1"], + "dilation8": ["4:(... .0. .1.)->1", "4:(... .0. ..1)->1"], + "erosion4": ["4:(... .1. .0.)->0"], + "erosion8": ["4:(... .1. .0.)->0", "4:(... .1. ..0)->0"], + "edge": [ + "1:(... ... ...)->0", + "4:(.0. .1. ...)->1", + "4:(01. .1. ...)->1", + ], + } + if op_name not in known_patterns: + msg = f"Unknown pattern {op_name}!" + raise Exception(msg) + + self.patterns = known_patterns[op_name] + elif patterns is not None: + self.patterns = patterns + else: + self.patterns = [] + + def add_patterns(self, patterns: list[str]) -> None: + """ + Append to list of patterns. + + :param patterns: Additional patterns. + """ + self.patterns += patterns + + def build_default_lut(self) -> bytearray: + """ + Set the current LUT, and return it. + + This is the default LUT that patterns will be applied against when building. + """ + symbols = [0, 1] + m = 1 << 4 # pos of current pixel + self.lut = bytearray(symbols[(i & m) > 0] for i in range(LUT_SIZE)) + return self.lut + + def get_lut(self) -> bytearray | None: + """ + Returns the current LUT + """ + return self.lut + + def _string_permute(self, pattern: str, permutation: list[int]) -> str: + """Takes a pattern and a permutation and returns the + string permuted according to the permutation list. + """ + assert len(permutation) == 9 + return "".join(pattern[p] for p in permutation) + + def _pattern_permute( + self, basic_pattern: str, options: str, basic_result: int + ) -> list[tuple[str, int]]: + """Takes a basic pattern and its result and clones + the pattern according to the modifications described in the $options + parameter. It returns a list of all cloned patterns.""" + patterns = [(basic_pattern, basic_result)] + + # rotations + if "4" in options: + res = patterns[-1][1] + for i in range(4): + patterns.append( + (self._string_permute(patterns[-1][0], ROTATION_MATRIX), res) + ) + # mirror + if "M" in options: + n = len(patterns) + for pattern, res in patterns[:n]: + patterns.append((self._string_permute(pattern, MIRROR_MATRIX), res)) + + # negate + if "N" in options: + n = len(patterns) + for pattern, res in patterns[:n]: + # Swap 0 and 1 + pattern = pattern.replace("0", "Z").replace("1", "0").replace("Z", "1") + res = 1 - int(res) + patterns.append((pattern, res)) + + return patterns + + def build_lut(self) -> bytearray: + """Compile all patterns into a morphology LUT, and return it. + + This is the data to be passed into MorphOp.""" + self.build_default_lut() + assert self.lut is not None + patterns = [] + + # Parse and create symmetries of the patterns strings + for p in self.patterns: + m = re.search(r"(\w):?\s*\((.+?)\)\s*->\s*(\d)", p.replace("\n", "")) + if not m: + msg = 'Syntax error in pattern "' + p + '"' + raise Exception(msg) + options = m.group(1) + pattern = m.group(2) + result = int(m.group(3)) + + # Get rid of spaces + pattern = pattern.replace(" ", "").replace("\n", "") + + patterns += self._pattern_permute(pattern, options, result) + + # Compile the patterns into regular expressions for speed + compiled_patterns = [] + for pattern in patterns: + p = pattern[0].replace(".", "X").replace("X", "[01]") + compiled_patterns.append((re.compile(p), pattern[1])) + + # Step through table and find patterns that match. + # Note that all the patterns are searched. The last one found takes priority + for i in range(LUT_SIZE): + # Build the bit pattern + bitpattern = bin(i)[2:] + bitpattern = ("0" * (9 - len(bitpattern)) + bitpattern)[::-1] + + for pattern, r in compiled_patterns: + if pattern.match(bitpattern): + self.lut[i] = [0, 1][r] + + return self.lut + + +class MorphOp: + """A class for binary morphological operators""" + + def __init__( + self, + lut: bytearray | None = None, + op_name: str | None = None, + patterns: list[str] | None = None, + ) -> None: + """Create a binary morphological operator. + + If the LUT is not provided, then it is built using LutBuilder from the op_name + or the patterns. + + :param lut: The LUT data. + :param patterns: A list of input patterns, or None. + :param op_name: The name of a known pattern. One of "corner", "dilation4", + "dilation8", "erosion4", "erosion8", "edge". + :exception Exception: If the op_name is not recognized. + """ + if patterns is None and op_name is None: + self.lut = lut + else: + self.lut = LutBuilder(patterns, op_name).build_lut() + + def apply(self, image: Image.Image) -> tuple[int, Image.Image]: + """Run a single morphological operation on an image. + + Returns a tuple of the number of changed pixels and the + morphed image. + + :param image: A 1-mode or L-mode image. + :exception Exception: If the current operator is None. + :exception ValueError: If the image is not 1 or L mode.""" + if self.lut is None: + msg = "No operator loaded" + raise Exception(msg) + + if image.mode not in ("1", "L"): + msg = "Image mode must be 1 or L" + raise ValueError(msg) + outimage = Image.new(image.mode, image.size) + count = _imagingmorph.apply(bytes(self.lut), image.getim(), outimage.getim()) + return count, outimage + + def match(self, image: Image.Image) -> list[tuple[int, int]]: + """Get a list of coordinates matching the morphological operation on + an image. + + Returns a list of tuples of (x,y) coordinates of all matching pixels. See + :ref:`coordinate-system`. + + :param image: A 1-mode or L-mode image. + :exception Exception: If the current operator is None. + :exception ValueError: If the image is not 1 or L mode.""" + if self.lut is None: + msg = "No operator loaded" + raise Exception(msg) + + if image.mode not in ("1", "L"): + msg = "Image mode must be 1 or L" + raise ValueError(msg) + return _imagingmorph.match(bytes(self.lut), image.getim()) + + def get_on_pixels(self, image: Image.Image) -> list[tuple[int, int]]: + """Get a list of all turned on pixels in a 1 or L mode image. + + Returns a list of tuples of (x,y) coordinates of all non-empty pixels. See + :ref:`coordinate-system`. + + :param image: A 1-mode or L-mode image. + :exception ValueError: If the image is not 1 or L mode.""" + + if image.mode not in ("1", "L"): + msg = "Image mode must be 1 or L" + raise ValueError(msg) + return _imagingmorph.get_on_pixels(image.getim()) + + def load_lut(self, filename: str) -> None: + """ + Load an operator from an mrl file + + :param filename: The file to read from. + :exception Exception: If the length of the file data is not 512. + """ + with open(filename, "rb") as f: + self.lut = bytearray(f.read()) + + if len(self.lut) != LUT_SIZE: + self.lut = None + msg = "Wrong size operator file!" + raise Exception(msg) + + def save_lut(self, filename: str) -> None: + """ + Save an operator to an mrl file. + + :param filename: The destination file. + :exception Exception: If the current operator is None. + """ + if self.lut is None: + msg = "No operator loaded" + raise Exception(msg) + with open(filename, "wb") as f: + f.write(self.lut) + + def set_lut(self, lut: bytearray | None) -> None: + """ + Set the LUT from an external source + + :param lut: A new LUT. + """ + self.lut = lut diff --git a/PIL/ImageOps.py b/PIL/ImageOps.py new file mode 100644 index 0000000000000000000000000000000000000000..42b10bd7bc8d40bc6aa5ea77e1097461d5196b96 --- /dev/null +++ b/PIL/ImageOps.py @@ -0,0 +1,746 @@ +# +# The Python Imaging Library. +# $Id$ +# +# standard image operations +# +# History: +# 2001-10-20 fl Created +# 2001-10-23 fl Added autocontrast operator +# 2001-12-18 fl Added Kevin's fit operator +# 2004-03-14 fl Fixed potential division by zero in equalize +# 2005-05-05 fl Fixed equalize for low number of values +# +# Copyright (c) 2001-2004 by Secret Labs AB +# Copyright (c) 2001-2004 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import functools +import operator +import re +from collections.abc import Sequence +from typing import Literal, Protocol, cast, overload + +from . import ExifTags, Image, ImagePalette + +# +# helpers + + +def _border(border: int | tuple[int, ...]) -> tuple[int, int, int, int]: + if isinstance(border, tuple): + if len(border) == 2: + left, top = right, bottom = border + elif len(border) == 4: + left, top, right, bottom = border + else: + left = top = right = bottom = border + return left, top, right, bottom + + +def _color(color: str | int | tuple[int, ...], mode: str) -> int | tuple[int, ...]: + if isinstance(color, str): + from . import ImageColor + + color = ImageColor.getcolor(color, mode) + return color + + +def _lut(image: Image.Image, lut: list[int]) -> Image.Image: + if image.mode == "P": + # FIXME: apply to lookup table, not image data + msg = "mode P support coming soon" + raise NotImplementedError(msg) + elif image.mode in ("L", "RGB"): + if image.mode == "RGB" and len(lut) == 256: + lut = lut + lut + lut + return image.point(lut) + else: + msg = f"not supported for mode {image.mode}" + raise OSError(msg) + + +# +# actions + + +def autocontrast( + image: Image.Image, + cutoff: float | tuple[float, float] = 0, + ignore: int | Sequence[int] | None = None, + mask: Image.Image | None = None, + preserve_tone: bool = False, +) -> Image.Image: + """ + Maximize (normalize) image contrast. This function calculates a + histogram of the input image (or mask region), removes ``cutoff`` percent of the + lightest and darkest pixels from the histogram, and remaps the image + so that the darkest pixel becomes black (0), and the lightest + becomes white (255). + + :param image: The image to process. + :param cutoff: The percent to cut off from the histogram on the low and + high ends. Either a tuple of (low, high), or a single + number for both. + :param ignore: The background pixel value (use None for no background). + :param mask: Histogram used in contrast operation is computed using pixels + within the mask. If no mask is given the entire image is used + for histogram computation. + :param preserve_tone: Preserve image tone in Photoshop-like style autocontrast. + + .. versionadded:: 8.2.0 + + :return: An image. + """ + if preserve_tone: + histogram = image.convert("L").histogram(mask) + else: + histogram = image.histogram(mask) + + lut = [] + for layer in range(0, len(histogram), 256): + h = histogram[layer : layer + 256] + if ignore is not None: + # get rid of outliers + if isinstance(ignore, int): + h[ignore] = 0 + else: + for ix in ignore: + h[ix] = 0 + if cutoff: + # cut off pixels from both ends of the histogram + if not isinstance(cutoff, tuple): + cutoff = (cutoff, cutoff) + # get number of pixels + n = 0 + for ix in range(256): + n = n + h[ix] + # remove cutoff% pixels from the low end + cut = int(n * cutoff[0] // 100) + for lo in range(256): + if cut > h[lo]: + cut = cut - h[lo] + h[lo] = 0 + else: + h[lo] -= cut + cut = 0 + if cut <= 0: + break + # remove cutoff% samples from the high end + cut = int(n * cutoff[1] // 100) + for hi in range(255, -1, -1): + if cut > h[hi]: + cut = cut - h[hi] + h[hi] = 0 + else: + h[hi] -= cut + cut = 0 + if cut <= 0: + break + # find lowest/highest samples after preprocessing + for lo in range(256): + if h[lo]: + break + for hi in range(255, -1, -1): + if h[hi]: + break + if hi <= lo: + # don't bother + lut.extend(list(range(256))) + else: + scale = 255.0 / (hi - lo) + offset = -lo * scale + for ix in range(256): + ix = int(ix * scale + offset) + if ix < 0: + ix = 0 + elif ix > 255: + ix = 255 + lut.append(ix) + return _lut(image, lut) + + +def colorize( + image: Image.Image, + black: str | tuple[int, ...], + white: str | tuple[int, ...], + mid: str | int | tuple[int, ...] | None = None, + blackpoint: int = 0, + whitepoint: int = 255, + midpoint: int = 127, +) -> Image.Image: + """ + Colorize grayscale image. + This function calculates a color wedge which maps all black pixels in + the source image to the first color and all white pixels to the + second color. If ``mid`` is specified, it uses three-color mapping. + The ``black`` and ``white`` arguments should be RGB tuples or color names; + optionally you can use three-color mapping by also specifying ``mid``. + Mapping positions for any of the colors can be specified + (e.g. ``blackpoint``), where these parameters are the integer + value corresponding to where the corresponding color should be mapped. + These parameters must have logical order, such that + ``blackpoint <= midpoint <= whitepoint`` (if ``mid`` is specified). + + :param image: The image to colorize. + :param black: The color to use for black input pixels. + :param white: The color to use for white input pixels. + :param mid: The color to use for midtone input pixels. + :param blackpoint: an int value [0, 255] for the black mapping. + :param whitepoint: an int value [0, 255] for the white mapping. + :param midpoint: an int value [0, 255] for the midtone mapping. + :return: An image. + """ + + # Initial asserts + assert image.mode == "L" + if mid is None: + assert 0 <= blackpoint <= whitepoint <= 255 + else: + assert 0 <= blackpoint <= midpoint <= whitepoint <= 255 + + # Define colors from arguments + rgb_black = cast(Sequence[int], _color(black, "RGB")) + rgb_white = cast(Sequence[int], _color(white, "RGB")) + rgb_mid = cast(Sequence[int], _color(mid, "RGB")) if mid is not None else None + + # Empty lists for the mapping + red = [] + green = [] + blue = [] + + # Create the low-end values + for i in range(blackpoint): + red.append(rgb_black[0]) + green.append(rgb_black[1]) + blue.append(rgb_black[2]) + + # Create the mapping (2-color) + if rgb_mid is None: + range_map = range(whitepoint - blackpoint) + + for i in range_map: + red.append( + rgb_black[0] + i * (rgb_white[0] - rgb_black[0]) // len(range_map) + ) + green.append( + rgb_black[1] + i * (rgb_white[1] - rgb_black[1]) // len(range_map) + ) + blue.append( + rgb_black[2] + i * (rgb_white[2] - rgb_black[2]) // len(range_map) + ) + + # Create the mapping (3-color) + else: + range_map1 = range(midpoint - blackpoint) + range_map2 = range(whitepoint - midpoint) + + for i in range_map1: + red.append( + rgb_black[0] + i * (rgb_mid[0] - rgb_black[0]) // len(range_map1) + ) + green.append( + rgb_black[1] + i * (rgb_mid[1] - rgb_black[1]) // len(range_map1) + ) + blue.append( + rgb_black[2] + i * (rgb_mid[2] - rgb_black[2]) // len(range_map1) + ) + for i in range_map2: + red.append(rgb_mid[0] + i * (rgb_white[0] - rgb_mid[0]) // len(range_map2)) + green.append( + rgb_mid[1] + i * (rgb_white[1] - rgb_mid[1]) // len(range_map2) + ) + blue.append(rgb_mid[2] + i * (rgb_white[2] - rgb_mid[2]) // len(range_map2)) + + # Create the high-end values + for i in range(256 - whitepoint): + red.append(rgb_white[0]) + green.append(rgb_white[1]) + blue.append(rgb_white[2]) + + # Return converted image + image = image.convert("RGB") + return _lut(image, red + green + blue) + + +def contain( + image: Image.Image, size: tuple[int, int], method: int = Image.Resampling.BICUBIC +) -> Image.Image: + """ + Returns a resized version of the image, set to the maximum width and height + within the requested size, while maintaining the original aspect ratio. + + :param image: The image to resize. + :param size: The requested output size in pixels, given as a + (width, height) tuple. + :param method: Resampling method to use. Default is + :py:attr:`~PIL.Image.Resampling.BICUBIC`. + See :ref:`concept-filters`. + :return: An image. + """ + + im_ratio = image.width / image.height + dest_ratio = size[0] / size[1] + + if im_ratio != dest_ratio: + if im_ratio > dest_ratio: + new_height = round(image.height / image.width * size[0]) + if new_height != size[1]: + size = (size[0], new_height) + else: + new_width = round(image.width / image.height * size[1]) + if new_width != size[0]: + size = (new_width, size[1]) + return image.resize(size, resample=method) + + +def cover( + image: Image.Image, size: tuple[int, int], method: int = Image.Resampling.BICUBIC +) -> Image.Image: + """ + Returns a resized version of the image, so that the requested size is + covered, while maintaining the original aspect ratio. + + :param image: The image to resize. + :param size: The requested output size in pixels, given as a + (width, height) tuple. + :param method: Resampling method to use. Default is + :py:attr:`~PIL.Image.Resampling.BICUBIC`. + See :ref:`concept-filters`. + :return: An image. + """ + + im_ratio = image.width / image.height + dest_ratio = size[0] / size[1] + + if im_ratio != dest_ratio: + if im_ratio < dest_ratio: + new_height = round(image.height / image.width * size[0]) + if new_height != size[1]: + size = (size[0], new_height) + else: + new_width = round(image.width / image.height * size[1]) + if new_width != size[0]: + size = (new_width, size[1]) + return image.resize(size, resample=method) + + +def pad( + image: Image.Image, + size: tuple[int, int], + method: int = Image.Resampling.BICUBIC, + color: str | int | tuple[int, ...] | None = None, + centering: tuple[float, float] = (0.5, 0.5), +) -> Image.Image: + """ + Returns a resized and padded version of the image, expanded to fill the + requested aspect ratio and size. + + :param image: The image to resize and crop. + :param size: The requested output size in pixels, given as a + (width, height) tuple. + :param method: Resampling method to use. Default is + :py:attr:`~PIL.Image.Resampling.BICUBIC`. + See :ref:`concept-filters`. + :param color: The background color of the padded image. + :param centering: Control the position of the original image within the + padded version. + + (0.5, 0.5) will keep the image centered + (0, 0) will keep the image aligned to the top left + (1, 1) will keep the image aligned to the bottom + right + :return: An image. + """ + + resized = contain(image, size, method) + if resized.size == size: + out = resized + else: + out = Image.new(image.mode, size, color) + if resized.palette: + palette = resized.getpalette() + if palette is not None: + out.putpalette(palette) + if resized.width != size[0]: + x = round((size[0] - resized.width) * max(0, min(centering[0], 1))) + out.paste(resized, (x, 0)) + else: + y = round((size[1] - resized.height) * max(0, min(centering[1], 1))) + out.paste(resized, (0, y)) + return out + + +def crop(image: Image.Image, border: int = 0) -> Image.Image: + """ + Remove border from image. The same amount of pixels are removed + from all four sides. This function works on all image modes. + + .. seealso:: :py:meth:`~PIL.Image.Image.crop` + + :param image: The image to crop. + :param border: The number of pixels to remove. + :return: An image. + """ + left, top, right, bottom = _border(border) + return image.crop((left, top, image.size[0] - right, image.size[1] - bottom)) + + +def scale( + image: Image.Image, factor: float, resample: int = Image.Resampling.BICUBIC +) -> Image.Image: + """ + Returns a rescaled image by a specific factor given in parameter. + A factor greater than 1 expands the image, between 0 and 1 contracts the + image. + + :param image: The image to rescale. + :param factor: The expansion factor, as a float. + :param resample: Resampling method to use. Default is + :py:attr:`~PIL.Image.Resampling.BICUBIC`. + See :ref:`concept-filters`. + :returns: An :py:class:`~PIL.Image.Image` object. + """ + if factor == 1: + return image.copy() + elif factor <= 0: + msg = "the factor must be greater than 0" + raise ValueError(msg) + else: + size = (round(factor * image.width), round(factor * image.height)) + return image.resize(size, resample) + + +class SupportsGetMesh(Protocol): + """ + An object that supports the ``getmesh`` method, taking an image as an + argument, and returning a list of tuples. Each tuple contains two tuples, + the source box as a tuple of 4 integers, and a tuple of 8 integers for the + final quadrilateral, in order of top left, bottom left, bottom right, top + right. + """ + + def getmesh( + self, image: Image.Image + ) -> list[ + tuple[tuple[int, int, int, int], tuple[int, int, int, int, int, int, int, int]] + ]: ... + + +def deform( + image: Image.Image, + deformer: SupportsGetMesh, + resample: int = Image.Resampling.BILINEAR, +) -> Image.Image: + """ + Deform the image. + + :param image: The image to deform. + :param deformer: A deformer object. Any object that implements a + ``getmesh`` method can be used. + :param resample: An optional resampling filter. Same values possible as + in the PIL.Image.transform function. + :return: An image. + """ + return image.transform( + image.size, Image.Transform.MESH, deformer.getmesh(image), resample + ) + + +def equalize(image: Image.Image, mask: Image.Image | None = None) -> Image.Image: + """ + Equalize the image histogram. This function applies a non-linear + mapping to the input image, in order to create a uniform + distribution of grayscale values in the output image. + + :param image: The image to equalize. + :param mask: An optional mask. If given, only the pixels selected by + the mask are included in the analysis. + :return: An image. + """ + if image.mode == "P": + image = image.convert("RGB") + h = image.histogram(mask) + lut = [] + for b in range(0, len(h), 256): + histo = [_f for _f in h[b : b + 256] if _f] + if len(histo) <= 1: + lut.extend(list(range(256))) + else: + step = (functools.reduce(operator.add, histo) - histo[-1]) // 255 + if not step: + lut.extend(list(range(256))) + else: + n = step // 2 + for i in range(256): + lut.append(n // step) + n = n + h[i + b] + return _lut(image, lut) + + +def expand( + image: Image.Image, + border: int | tuple[int, ...] = 0, + fill: str | int | tuple[int, ...] = 0, +) -> Image.Image: + """ + Add border to the image + + :param image: The image to expand. + :param border: Border width, in pixels. + :param fill: Pixel fill value (a color value). Default is 0 (black). + :return: An image. + """ + left, top, right, bottom = _border(border) + width = left + image.size[0] + right + height = top + image.size[1] + bottom + color = _color(fill, image.mode) + if image.palette: + mode = image.palette.mode + palette = ImagePalette.ImagePalette(mode, image.getpalette(mode)) + if isinstance(color, tuple) and (len(color) == 3 or len(color) == 4): + color = palette.getcolor(color) + else: + palette = None + out = Image.new(image.mode, (width, height), color) + if palette: + out.putpalette(palette.palette, mode) + out.paste(image, (left, top)) + return out + + +def fit( + image: Image.Image, + size: tuple[int, int], + method: int = Image.Resampling.BICUBIC, + bleed: float = 0.0, + centering: tuple[float, float] = (0.5, 0.5), +) -> Image.Image: + """ + Returns a resized and cropped version of the image, cropped to the + requested aspect ratio and size. + + This function was contributed by Kevin Cazabon. + + :param image: The image to resize and crop. + :param size: The requested output size in pixels, given as a + (width, height) tuple. + :param method: Resampling method to use. Default is + :py:attr:`~PIL.Image.Resampling.BICUBIC`. + See :ref:`concept-filters`. + :param bleed: Remove a border around the outside of the image from all + four edges. The value is a decimal percentage (use 0.01 for + one percent). The default value is 0 (no border). + Cannot be greater than or equal to 0.5. + :param centering: Control the cropping position. Use (0.5, 0.5) for + center cropping (e.g. if cropping the width, take 50% off + of the left side, and therefore 50% off the right side). + (0.0, 0.0) will crop from the top left corner (i.e. if + cropping the width, take all of the crop off of the right + side, and if cropping the height, take all of it off the + bottom). (1.0, 0.0) will crop from the bottom left + corner, etc. (i.e. if cropping the width, take all of the + crop off the left side, and if cropping the height take + none from the top, and therefore all off the bottom). + :return: An image. + """ + + # by Kevin Cazabon, Feb 17/2000 + # kevin@cazabon.com + # https://www.cazabon.com + + centering_x, centering_y = centering + + if not 0.0 <= centering_x <= 1.0: + centering_x = 0.5 + if not 0.0 <= centering_y <= 1.0: + centering_y = 0.5 + + if not 0.0 <= bleed < 0.5: + bleed = 0.0 + + # calculate the area to use for resizing and cropping, subtracting + # the 'bleed' around the edges + + # number of pixels to trim off on Top and Bottom, Left and Right + bleed_pixels = (bleed * image.size[0], bleed * image.size[1]) + + live_size = ( + image.size[0] - bleed_pixels[0] * 2, + image.size[1] - bleed_pixels[1] * 2, + ) + + # calculate the aspect ratio of the live_size + live_size_ratio = live_size[0] / live_size[1] + + # calculate the aspect ratio of the output image + output_ratio = size[0] / size[1] + + # figure out if the sides or top/bottom will be cropped off + if live_size_ratio == output_ratio: + # live_size is already the needed ratio + crop_width = live_size[0] + crop_height = live_size[1] + elif live_size_ratio >= output_ratio: + # live_size is wider than what's needed, crop the sides + crop_width = output_ratio * live_size[1] + crop_height = live_size[1] + else: + # live_size is taller than what's needed, crop the top and bottom + crop_width = live_size[0] + crop_height = live_size[0] / output_ratio + + # make the crop + crop_left = bleed_pixels[0] + (live_size[0] - crop_width) * centering_x + crop_top = bleed_pixels[1] + (live_size[1] - crop_height) * centering_y + + crop = (crop_left, crop_top, crop_left + crop_width, crop_top + crop_height) + + # resize the image and return it + return image.resize(size, method, box=crop) + + +def flip(image: Image.Image) -> Image.Image: + """ + Flip the image vertically (top to bottom). + + :param image: The image to flip. + :return: An image. + """ + return image.transpose(Image.Transpose.FLIP_TOP_BOTTOM) + + +def grayscale(image: Image.Image) -> Image.Image: + """ + Convert the image to grayscale. + + :param image: The image to convert. + :return: An image. + """ + return image.convert("L") + + +def invert(image: Image.Image) -> Image.Image: + """ + Invert (negate) the image. + + :param image: The image to invert. + :return: An image. + """ + lut = list(range(255, -1, -1)) + return image.point(lut) if image.mode == "1" else _lut(image, lut) + + +def mirror(image: Image.Image) -> Image.Image: + """ + Flip image horizontally (left to right). + + :param image: The image to mirror. + :return: An image. + """ + return image.transpose(Image.Transpose.FLIP_LEFT_RIGHT) + + +def posterize(image: Image.Image, bits: int) -> Image.Image: + """ + Reduce the number of bits for each color channel. + + :param image: The image to posterize. + :param bits: The number of bits to keep for each channel (1-8). + :return: An image. + """ + mask = ~(2 ** (8 - bits) - 1) + lut = [i & mask for i in range(256)] + return _lut(image, lut) + + +def solarize(image: Image.Image, threshold: int = 128) -> Image.Image: + """ + Invert all pixel values above a threshold. + + :param image: The image to solarize. + :param threshold: All pixels above this grayscale level are inverted. + :return: An image. + """ + lut = [] + for i in range(256): + if i < threshold: + lut.append(i) + else: + lut.append(255 - i) + return _lut(image, lut) + + +@overload +def exif_transpose(image: Image.Image, *, in_place: Literal[True]) -> None: ... + + +@overload +def exif_transpose( + image: Image.Image, *, in_place: Literal[False] = False +) -> Image.Image: ... + + +def exif_transpose(image: Image.Image, *, in_place: bool = False) -> Image.Image | None: + """ + If an image has an EXIF Orientation tag, other than 1, transpose the image + accordingly, and remove the orientation data. + + :param image: The image to transpose. + :param in_place: Boolean. Keyword-only argument. + If ``True``, the original image is modified in-place, and ``None`` is returned. + If ``False`` (default), a new :py:class:`~PIL.Image.Image` object is returned + with the transposition applied. If there is no transposition, a copy of the + image will be returned. + """ + image.load() + image_exif = image.getexif() + orientation = image_exif.get(ExifTags.Base.Orientation, 1) + method = { + 2: Image.Transpose.FLIP_LEFT_RIGHT, + 3: Image.Transpose.ROTATE_180, + 4: Image.Transpose.FLIP_TOP_BOTTOM, + 5: Image.Transpose.TRANSPOSE, + 6: Image.Transpose.ROTATE_270, + 7: Image.Transpose.TRANSVERSE, + 8: Image.Transpose.ROTATE_90, + }.get(orientation) + if method is not None: + if in_place: + image.im = image.im.transpose(method) + image._size = image.im.size + else: + transposed_image = image.transpose(method) + exif_image = image if in_place else transposed_image + + exif = exif_image.getexif() + if ExifTags.Base.Orientation in exif: + del exif[ExifTags.Base.Orientation] + if "exif" in exif_image.info: + exif_image.info["exif"] = exif.tobytes() + elif "Raw profile type exif" in exif_image.info: + exif_image.info["Raw profile type exif"] = exif.tobytes().hex() + for key in ("XML:com.adobe.xmp", "xmp"): + if key in exif_image.info: + for pattern in ( + r'tiff:Orientation="([0-9])"', + r"([0-9])", + ): + value = exif_image.info[key] + if isinstance(value, str): + value = re.sub(pattern, "", value) + elif isinstance(value, tuple): + value = tuple( + re.sub(pattern.encode(), b"", v) for v in value + ) + else: + value = re.sub(pattern.encode(), b"", value) + exif_image.info[key] = value + if not in_place: + return transposed_image + elif not in_place: + return image.copy() + return None diff --git a/PIL/ImagePalette.py b/PIL/ImagePalette.py new file mode 100644 index 0000000000000000000000000000000000000000..eae7aea8fc3d50ba239646de633441aa1c7b0965 --- /dev/null +++ b/PIL/ImagePalette.py @@ -0,0 +1,287 @@ +# +# The Python Imaging Library. +# $Id$ +# +# image palette object +# +# History: +# 1996-03-11 fl Rewritten. +# 1997-01-03 fl Up and running. +# 1997-08-23 fl Added load hack +# 2001-04-16 fl Fixed randint shadow bug in random() +# +# Copyright (c) 1997-2001 by Secret Labs AB +# Copyright (c) 1996-1997 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import array +from collections.abc import Sequence +from typing import IO + +from . import GimpGradientFile, GimpPaletteFile, ImageColor, PaletteFile + +TYPE_CHECKING = False +if TYPE_CHECKING: + from . import Image + + +class ImagePalette: + """ + Color palette for palette mapped images + + :param mode: The mode to use for the palette. See: + :ref:`concept-modes`. Defaults to "RGB" + :param palette: An optional palette. If given, it must be a bytearray, + an array or a list of ints between 0-255. The list must consist of + all channels for one color followed by the next color (e.g. RGBRGBRGB). + Defaults to an empty palette. + """ + + def __init__( + self, + mode: str = "RGB", + palette: Sequence[int] | bytes | bytearray | None = None, + ) -> None: + self.mode = mode + self.rawmode: str | None = None # if set, palette contains raw data + self.palette = palette or bytearray() + self.dirty: int | None = None + + @property + def palette(self) -> Sequence[int] | bytes | bytearray: + return self._palette + + @palette.setter + def palette(self, palette: Sequence[int] | bytes | bytearray) -> None: + self._colors: dict[tuple[int, ...], int] | None = None + self._palette = palette + + @property + def colors(self) -> dict[tuple[int, ...], int]: + if self._colors is None: + mode_len = len(self.mode) + self._colors = {} + for i in range(0, len(self.palette), mode_len): + color = tuple(self.palette[i : i + mode_len]) + if color in self._colors: + continue + self._colors[color] = i // mode_len + return self._colors + + @colors.setter + def colors(self, colors: dict[tuple[int, ...], int]) -> None: + self._colors = colors + + def copy(self) -> ImagePalette: + new = ImagePalette() + + new.mode = self.mode + new.rawmode = self.rawmode + if self.palette is not None: + new.palette = self.palette[:] + new.dirty = self.dirty + + return new + + def getdata(self) -> tuple[str, Sequence[int] | bytes | bytearray]: + """ + Get palette contents in format suitable for the low-level + ``im.putpalette`` primitive. + + .. warning:: This method is experimental. + """ + if self.rawmode: + return self.rawmode, self.palette + return self.mode, self.tobytes() + + def tobytes(self) -> bytes: + """Convert palette to bytes. + + .. warning:: This method is experimental. + """ + if self.rawmode: + msg = "palette contains raw palette data" + raise ValueError(msg) + if isinstance(self.palette, bytes): + return self.palette + arr = array.array("B", self.palette) + return arr.tobytes() + + # Declare tostring as an alias for tobytes + tostring = tobytes + + def _new_color_index( + self, image: Image.Image | None = None, e: Exception | None = None + ) -> int: + if not isinstance(self.palette, bytearray): + self._palette = bytearray(self.palette) + index = len(self.palette) // len(self.mode) + special_colors: tuple[int | tuple[int, ...] | None, ...] = () + if image: + special_colors = ( + image.info.get("background"), + image.info.get("transparency"), + ) + while index in special_colors: + index += 1 + if index >= 256: + if image: + # Search for an unused index + for i, count in reversed(list(enumerate(image.histogram()))): + if count == 0 and i not in special_colors: + index = i + break + if index >= 256: + msg = "cannot allocate more than 256 colors" + raise ValueError(msg) from e + return index + + def getcolor( + self, + color: tuple[int, ...], + image: Image.Image | None = None, + ) -> int: + """Given an rgb tuple, allocate palette entry. + + .. warning:: This method is experimental. + """ + if self.rawmode: + msg = "palette contains raw palette data" + raise ValueError(msg) + if isinstance(color, tuple): + if self.mode == "RGB": + if len(color) == 4: + if color[3] != 255: + msg = "cannot add non-opaque RGBA color to RGB palette" + raise ValueError(msg) + color = color[:3] + elif self.mode == "RGBA": + if len(color) == 3: + color += (255,) + try: + return self.colors[color] + except KeyError as e: + # allocate new color slot + index = self._new_color_index(image, e) + assert isinstance(self._palette, bytearray) + self.colors[color] = index + mode_len = len(self.mode) + if index * mode_len < len(self.palette): + self._palette = ( + self._palette[: index * mode_len] + + bytes(color) + + self._palette[index * mode_len + mode_len :] + ) + else: + self._palette += bytes(color) + self.dirty = 1 + return index + else: + msg = f"unknown color specifier: {repr(color)}" # type: ignore[unreachable] + raise ValueError(msg) + + def save(self, fp: str | IO[str]) -> None: + """Save palette to text file. + + .. warning:: This method is experimental. + """ + if self.rawmode: + msg = "palette contains raw palette data" + raise ValueError(msg) + if isinstance(fp, str): + fp = open(fp, "w") + fp.write("# Palette\n") + fp.write(f"# Mode: {self.mode}\n") + for i in range(256): + fp.write(f"{i}") + for j in range(i * len(self.mode), (i + 1) * len(self.mode)): + try: + fp.write(f" {self.palette[j]}") + except IndexError: + fp.write(" 0") + fp.write("\n") + fp.close() + + +# -------------------------------------------------------------------- +# Internal + + +def raw(rawmode: str, data: Sequence[int] | bytes | bytearray) -> ImagePalette: + palette = ImagePalette() + palette.rawmode = rawmode + palette.palette = data + palette.dirty = 1 + return palette + + +# -------------------------------------------------------------------- +# Factories + + +def make_linear_lut(black: int, white: float) -> list[int]: + if black == 0: + return [int(white * i // 255) for i in range(256)] + + msg = "unavailable when black is non-zero" + raise NotImplementedError(msg) # FIXME + + +def make_gamma_lut(exp: float) -> list[int]: + return [int(((i / 255.0) ** exp) * 255.0 + 0.5) for i in range(256)] + + +def negative(mode: str = "RGB") -> ImagePalette: + palette = list(range(256 * len(mode))) + palette.reverse() + return ImagePalette(mode, [i // len(mode) for i in palette]) + + +def random(mode: str = "RGB") -> ImagePalette: + from random import randint + + palette = [randint(0, 255) for _ in range(256 * len(mode))] + return ImagePalette(mode, palette) + + +def sepia(white: str = "#fff0c0") -> ImagePalette: + bands = [make_linear_lut(0, band) for band in ImageColor.getrgb(white)] + return ImagePalette("RGB", [bands[i % 3][i // 3] for i in range(256 * 3)]) + + +def wedge(mode: str = "RGB") -> ImagePalette: + palette = list(range(256 * len(mode))) + return ImagePalette(mode, [i // len(mode) for i in palette]) + + +def load(filename: str) -> tuple[bytes, str]: + # FIXME: supports GIMP gradients only + + with open(filename, "rb") as fp: + paletteHandlers: list[ + type[ + GimpPaletteFile.GimpPaletteFile + | GimpGradientFile.GimpGradientFile + | PaletteFile.PaletteFile + ] + ] = [ + GimpPaletteFile.GimpPaletteFile, + GimpGradientFile.GimpGradientFile, + PaletteFile.PaletteFile, + ] + for paletteHandler in paletteHandlers: + try: + fp.seek(0) + lut = paletteHandler(fp).getpalette() + if lut: + break + except (SyntaxError, ValueError): + pass + else: + msg = "cannot load palette" + raise OSError(msg) + + return lut # data, rawmode diff --git a/PIL/ImagePath.py b/PIL/ImagePath.py new file mode 100644 index 0000000000000000000000000000000000000000..77e8a609a552ae7d8c6b87e78a36ecbfc1cdce89 --- /dev/null +++ b/PIL/ImagePath.py @@ -0,0 +1,20 @@ +# +# The Python Imaging Library +# $Id$ +# +# path interface +# +# History: +# 1996-11-04 fl Created +# 2002-04-14 fl Added documentation stub class +# +# Copyright (c) Secret Labs AB 1997. +# Copyright (c) Fredrik Lundh 1996. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +from . import Image + +Path = Image.core.path diff --git a/PIL/ImageSequence.py b/PIL/ImageSequence.py new file mode 100644 index 0000000000000000000000000000000000000000..361be48971e0446ef39e2428b613f75951e04e87 --- /dev/null +++ b/PIL/ImageSequence.py @@ -0,0 +1,88 @@ +# +# The Python Imaging Library. +# $Id$ +# +# sequence support classes +# +# history: +# 1997-02-20 fl Created +# +# Copyright (c) 1997 by Secret Labs AB. +# Copyright (c) 1997 by Fredrik Lundh. +# +# See the README file for information on usage and redistribution. +# + +## +from __future__ import annotations + +from . import Image + +TYPE_CHECKING = False +if TYPE_CHECKING: + from collections.abc import Callable + + +class Iterator: + """ + This class implements an iterator object that can be used to loop + over an image sequence. + + You can use the ``[]`` operator to access elements by index. This operator + will raise an :py:exc:`IndexError` if you try to access a nonexistent + frame. + + :param im: An image object. + """ + + def __init__(self, im: Image.Image) -> None: + if not hasattr(im, "seek"): + msg = "im must have seek method" + raise AttributeError(msg) + self.im = im + self.position = getattr(self.im, "_min_frame", 0) + + def __getitem__(self, ix: int) -> Image.Image: + try: + self.im.seek(ix) + return self.im + except EOFError as e: + msg = "end of sequence" + raise IndexError(msg) from e + + def __iter__(self) -> Iterator: + return self + + def __next__(self) -> Image.Image: + try: + self.im.seek(self.position) + self.position += 1 + return self.im + except EOFError as e: + msg = "end of sequence" + raise StopIteration(msg) from e + + +def all_frames( + im: Image.Image | list[Image.Image], + func: Callable[[Image.Image], Image.Image] | None = None, +) -> list[Image.Image]: + """ + Applies a given function to all frames in an image or a list of images. + The frames are returned as a list of separate images. + + :param im: An image, or a list of images. + :param func: The function to apply to all of the image frames. + :returns: A list of images. + """ + if not isinstance(im, list): + im = [im] + + ims = [] + for imSequence in im: + current = imSequence.tell() + + ims += [im_frame.copy() for im_frame in Iterator(imSequence)] + + imSequence.seek(current) + return [func(im) for im in ims] if func else ims diff --git a/PIL/ImageShow.py b/PIL/ImageShow.py new file mode 100644 index 0000000000000000000000000000000000000000..7705608e3eccd5e82cfca87daa1264df2c81dacd --- /dev/null +++ b/PIL/ImageShow.py @@ -0,0 +1,362 @@ +# +# The Python Imaging Library. +# $Id$ +# +# im.show() drivers +# +# History: +# 2008-04-06 fl Created +# +# Copyright (c) Secret Labs AB 2008. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import abc +import os +import shutil +import subprocess +import sys +from shlex import quote +from typing import Any + +from . import Image + +_viewers = [] + + +def register(viewer: type[Viewer] | Viewer, order: int = 1) -> None: + """ + The :py:func:`register` function is used to register additional viewers:: + + from PIL import ImageShow + ImageShow.register(MyViewer()) # MyViewer will be used as a last resort + ImageShow.register(MySecondViewer(), 0) # MySecondViewer will be prioritised + ImageShow.register(ImageShow.XVViewer(), 0) # XVViewer will be prioritised + + :param viewer: The viewer to be registered. + :param order: + Zero or a negative integer to prepend this viewer to the list, + a positive integer to append it. + """ + if isinstance(viewer, type) and issubclass(viewer, Viewer): + viewer = viewer() + if order > 0: + _viewers.append(viewer) + else: + _viewers.insert(0, viewer) + + +def show(image: Image.Image, title: str | None = None, **options: Any) -> bool: + r""" + Display a given image. + + :param image: An image object. + :param title: Optional title. Not all viewers can display the title. + :param \**options: Additional viewer options. + :returns: ``True`` if a suitable viewer was found, ``False`` otherwise. + """ + for viewer in _viewers: + if viewer.show(image, title=title, **options): + return True + return False + + +class Viewer: + """Base class for viewers.""" + + # main api + + def show(self, image: Image.Image, **options: Any) -> int: + """ + The main function for displaying an image. + Converts the given image to the target format and displays it. + """ + + if not ( + image.mode in ("1", "RGBA") + or (self.format == "PNG" and image.mode in ("I;16", "LA")) + ): + base = Image.getmodebase(image.mode) + if image.mode != base: + image = image.convert(base) + + return self.show_image(image, **options) + + # hook methods + + format: str | None = None + """The format to convert the image into.""" + options: dict[str, Any] = {} + """Additional options used to convert the image.""" + + def get_format(self, image: Image.Image) -> str | None: + """Return format name, or ``None`` to save as PGM/PPM.""" + return self.format + + def get_command(self, file: str, **options: Any) -> str: + """ + Returns the command used to display the file. + Not implemented in the base class. + """ + msg = "unavailable in base viewer" + raise NotImplementedError(msg) + + def save_image(self, image: Image.Image) -> str: + """Save to temporary file and return filename.""" + return image._dump(format=self.get_format(image), **self.options) + + def show_image(self, image: Image.Image, **options: Any) -> int: + """Display the given image.""" + return self.show_file(self.save_image(image), **options) + + def show_file(self, path: str, **options: Any) -> int: + """ + Display given file. + """ + if not os.path.exists(path): + raise FileNotFoundError + os.system(self.get_command(path, **options)) # nosec + return 1 + + +# -------------------------------------------------------------------- + + +class WindowsViewer(Viewer): + """The default viewer on Windows is the default system application for PNG files.""" + + format = "PNG" + options = {"compress_level": 1, "save_all": True} + + def get_command(self, file: str, **options: Any) -> str: + return ( + f'start "Pillow" /WAIT "{file}" ' + "&& ping -n 4 127.0.0.1 >NUL " + f'&& del /f "{file}"' + ) + + def show_file(self, path: str, **options: Any) -> int: + """ + Display given file. + """ + if not os.path.exists(path): + raise FileNotFoundError + subprocess.Popen( + self.get_command(path, **options), + shell=True, + creationflags=getattr(subprocess, "CREATE_NO_WINDOW"), + ) # nosec + return 1 + + +if sys.platform == "win32": + register(WindowsViewer) + + +class MacViewer(Viewer): + """The default viewer on macOS using ``Preview.app``.""" + + format = "PNG" + options = {"compress_level": 1, "save_all": True} + + def get_command(self, file: str, **options: Any) -> str: + # on darwin open returns immediately resulting in the temp + # file removal while app is opening + command = "open -a Preview.app" + command = f"({command} {quote(file)}; sleep 20; rm -f {quote(file)})&" + return command + + def show_file(self, path: str, **options: Any) -> int: + """ + Display given file. + """ + if not os.path.exists(path): + raise FileNotFoundError + subprocess.call(["open", "-a", "Preview.app", path]) + + pyinstaller = getattr(sys, "frozen", False) and hasattr(sys, "_MEIPASS") + executable = (not pyinstaller and sys.executable) or shutil.which("python3") + if executable: + subprocess.Popen( + [ + executable, + "-c", + "import os, sys, time; time.sleep(20); os.remove(sys.argv[1])", + path, + ] + ) + return 1 + + +if sys.platform == "darwin": + register(MacViewer) + + +class UnixViewer(abc.ABC, Viewer): + format = "PNG" + options = {"compress_level": 1, "save_all": True} + + @abc.abstractmethod + def get_command_ex(self, file: str, **options: Any) -> tuple[str, str]: + pass + + def get_command(self, file: str, **options: Any) -> str: + command = self.get_command_ex(file, **options)[0] + return f"{command} {quote(file)}" + + +class XDGViewer(UnixViewer): + """ + The freedesktop.org ``xdg-open`` command. + """ + + def get_command_ex(self, file: str, **options: Any) -> tuple[str, str]: + command = executable = "xdg-open" + return command, executable + + def show_file(self, path: str, **options: Any) -> int: + """ + Display given file. + """ + if not os.path.exists(path): + raise FileNotFoundError + subprocess.Popen(["xdg-open", path]) + return 1 + + +class DisplayViewer(UnixViewer): + """ + The ImageMagick ``display`` command. + This viewer supports the ``title`` parameter. + """ + + def get_command_ex( + self, file: str, title: str | None = None, **options: Any + ) -> tuple[str, str]: + command = executable = "display" + if title: + command += f" -title {quote(title)}" + return command, executable + + def show_file(self, path: str, **options: Any) -> int: + """ + Display given file. + """ + if not os.path.exists(path): + raise FileNotFoundError + args = ["display"] + title = options.get("title") + if title: + args += ["-title", title] + args.append(path) + + subprocess.Popen(args) + return 1 + + +class GmDisplayViewer(UnixViewer): + """The GraphicsMagick ``gm display`` command.""" + + def get_command_ex(self, file: str, **options: Any) -> tuple[str, str]: + executable = "gm" + command = "gm display" + return command, executable + + def show_file(self, path: str, **options: Any) -> int: + """ + Display given file. + """ + if not os.path.exists(path): + raise FileNotFoundError + subprocess.Popen(["gm", "display", path]) + return 1 + + +class EogViewer(UnixViewer): + """The GNOME Image Viewer ``eog`` command.""" + + def get_command_ex(self, file: str, **options: Any) -> tuple[str, str]: + executable = "eog" + command = "eog -n" + return command, executable + + def show_file(self, path: str, **options: Any) -> int: + """ + Display given file. + """ + if not os.path.exists(path): + raise FileNotFoundError + subprocess.Popen(["eog", "-n", path]) + return 1 + + +class XVViewer(UnixViewer): + """ + The X Viewer ``xv`` command. + This viewer supports the ``title`` parameter. + """ + + def get_command_ex( + self, file: str, title: str | None = None, **options: Any + ) -> tuple[str, str]: + # note: xv is pretty outdated. most modern systems have + # imagemagick's display command instead. + command = executable = "xv" + if title: + command += f" -name {quote(title)}" + return command, executable + + def show_file(self, path: str, **options: Any) -> int: + """ + Display given file. + """ + if not os.path.exists(path): + raise FileNotFoundError + args = ["xv"] + title = options.get("title") + if title: + args += ["-name", title] + args.append(path) + + subprocess.Popen(args) + return 1 + + +if sys.platform not in ("win32", "darwin"): # unixoids + if shutil.which("xdg-open"): + register(XDGViewer) + if shutil.which("display"): + register(DisplayViewer) + if shutil.which("gm"): + register(GmDisplayViewer) + if shutil.which("eog"): + register(EogViewer) + if shutil.which("xv"): + register(XVViewer) + + +class IPythonViewer(Viewer): + """The viewer for IPython frontends.""" + + def show_image(self, image: Image.Image, **options: Any) -> int: + ipython_display(image) + return 1 + + +try: + from IPython.display import display as ipython_display +except ImportError: + pass +else: + register(IPythonViewer) + + +if __name__ == "__main__": + if len(sys.argv) < 2: + print("Syntax: python3 ImageShow.py imagefile [title]") + sys.exit() + + with Image.open(sys.argv[1]) as im: + print(show(im, *sys.argv[2:])) diff --git a/PIL/ImageStat.py b/PIL/ImageStat.py new file mode 100644 index 0000000000000000000000000000000000000000..3a1044ba449408cd038e81bb4f6cc45a2149e3ce --- /dev/null +++ b/PIL/ImageStat.py @@ -0,0 +1,167 @@ +# +# The Python Imaging Library. +# $Id$ +# +# global image statistics +# +# History: +# 1996-04-05 fl Created +# 1997-05-21 fl Added mask; added rms, var, stddev attributes +# 1997-08-05 fl Added median +# 1998-07-05 hk Fixed integer overflow error +# +# Notes: +# This class shows how to implement delayed evaluation of attributes. +# To get a certain value, simply access the corresponding attribute. +# The __getattr__ dispatcher takes care of the rest. +# +# Copyright (c) Secret Labs AB 1997. +# Copyright (c) Fredrik Lundh 1996-97. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import math +from functools import cached_property + +from . import Image + + +class Stat: + def __init__( + self, image_or_list: Image.Image | list[int], mask: Image.Image | None = None + ) -> None: + """ + Calculate statistics for the given image. If a mask is included, + only the regions covered by that mask are included in the + statistics. You can also pass in a previously calculated histogram. + + :param image: A PIL image, or a precalculated histogram. + + .. note:: + + For a PIL image, calculations rely on the + :py:meth:`~PIL.Image.Image.histogram` method. The pixel counts are + grouped into 256 bins, even if the image has more than 8 bits per + channel. So ``I`` and ``F`` mode images have a maximum ``mean``, + ``median`` and ``rms`` of 255, and cannot have an ``extrema`` maximum + of more than 255. + + :param mask: An optional mask. + """ + if isinstance(image_or_list, Image.Image): + self.h = image_or_list.histogram(mask) + elif isinstance(image_or_list, list): + self.h = image_or_list + else: + msg = "first argument must be image or list" # type: ignore[unreachable] + raise TypeError(msg) + self.bands = list(range(len(self.h) // 256)) + + @cached_property + def extrema(self) -> list[tuple[int, int]]: + """ + Min/max values for each band in the image. + + .. note:: + This relies on the :py:meth:`~PIL.Image.Image.histogram` method, and + simply returns the low and high bins used. This is correct for + images with 8 bits per channel, but fails for other modes such as + ``I`` or ``F``. Instead, use :py:meth:`~PIL.Image.Image.getextrema` to + return per-band extrema for the image. This is more correct and + efficient because, for non-8-bit modes, the histogram method uses + :py:meth:`~PIL.Image.Image.getextrema` to determine the bins used. + """ + + def minmax(histogram: list[int]) -> tuple[int, int]: + res_min, res_max = 255, 0 + for i in range(256): + if histogram[i]: + res_min = i + break + for i in range(255, -1, -1): + if histogram[i]: + res_max = i + break + return res_min, res_max + + return [minmax(self.h[i:]) for i in range(0, len(self.h), 256)] + + @cached_property + def count(self) -> list[int]: + """Total number of pixels for each band in the image.""" + return [sum(self.h[i : i + 256]) for i in range(0, len(self.h), 256)] + + @cached_property + def sum(self) -> list[float]: + """Sum of all pixels for each band in the image.""" + + v = [] + for i in range(0, len(self.h), 256): + layer_sum = 0.0 + for j in range(256): + layer_sum += j * self.h[i + j] + v.append(layer_sum) + return v + + @cached_property + def sum2(self) -> list[float]: + """Squared sum of all pixels for each band in the image.""" + + v = [] + for i in range(0, len(self.h), 256): + sum2 = 0.0 + for j in range(256): + sum2 += (j**2) * float(self.h[i + j]) + v.append(sum2) + return v + + @cached_property + def mean(self) -> list[float]: + """Average (arithmetic mean) pixel level for each band in the image.""" + return [self.sum[i] / self.count[i] if self.count[i] else 0 for i in self.bands] + + @cached_property + def median(self) -> list[int]: + """Median pixel level for each band in the image.""" + + v = [] + for i in self.bands: + s = 0 + half = self.count[i] // 2 + b = i * 256 + for j in range(256): + s = s + self.h[b + j] + if s > half: + break + v.append(j) + return v + + @cached_property + def rms(self) -> list[float]: + """RMS (root-mean-square) for each band in the image.""" + return [ + math.sqrt(self.sum2[i] / self.count[i]) if self.count[i] else 0 + for i in self.bands + ] + + @cached_property + def var(self) -> list[float]: + """Variance for each band in the image.""" + return [ + ( + (self.sum2[i] - (self.sum[i] ** 2.0) / self.count[i]) / self.count[i] + if self.count[i] + else 0 + ) + for i in self.bands + ] + + @cached_property + def stddev(self) -> list[float]: + """Standard deviation for each band in the image.""" + return [math.sqrt(self.var[i]) for i in self.bands] + + +Global = Stat # compatibility diff --git a/PIL/ImageText.py b/PIL/ImageText.py new file mode 100644 index 0000000000000000000000000000000000000000..e6ccd8243321f52141f569972400175e308afc20 --- /dev/null +++ b/PIL/ImageText.py @@ -0,0 +1,320 @@ +from __future__ import annotations + +from . import ImageFont +from ._typing import _Ink + + +class Text: + def __init__( + self, + text: str | bytes, + font: ( + ImageFont.ImageFont + | ImageFont.FreeTypeFont + | ImageFont.TransposedFont + | None + ) = None, + mode: str = "RGB", + spacing: float = 4, + direction: str | None = None, + features: list[str] | None = None, + language: str | None = None, + ) -> None: + """ + :param text: String to be drawn. + :param font: Either an :py:class:`~PIL.ImageFont.ImageFont` instance, + :py:class:`~PIL.ImageFont.FreeTypeFont` instance, + :py:class:`~PIL.ImageFont.TransposedFont` instance or ``None``. If + ``None``, the default font from :py:meth:`.ImageFont.load_default` + will be used. + :param mode: The image mode this will be used with. + :param spacing: The number of pixels between lines. + :param direction: Direction of the text. It can be ``"rtl"`` (right to left), + ``"ltr"`` (left to right) or ``"ttb"`` (top to bottom). + Requires libraqm. + :param features: A list of OpenType font features to be used during text + layout. This is usually used to turn on optional font features + that are not enabled by default, for example ``"dlig"`` or + ``"ss01"``, but can be also used to turn off default font + features, for example ``"-liga"`` to disable ligatures or + ``"-kern"`` to disable kerning. To get all supported + features, see `OpenType docs`_. + Requires libraqm. + :param language: Language of the text. Different languages may use + different glyph shapes or ligatures. This parameter tells + the font which language the text is in, and to apply the + correct substitutions as appropriate, if available. + It should be a `BCP 47 language code`_. + Requires libraqm. + """ + self.text = text + self.font = font or ImageFont.load_default() + + self.mode = mode + self.spacing = spacing + self.direction = direction + self.features = features + self.language = language + + self.embedded_color = False + + self.stroke_width: float = 0 + self.stroke_fill: _Ink | None = None + + def embed_color(self) -> None: + """ + Use embedded color glyphs (COLR, CBDT, SBIX). + """ + if self.mode not in ("RGB", "RGBA"): + msg = "Embedded color supported only in RGB and RGBA modes" + raise ValueError(msg) + self.embedded_color = True + + def stroke(self, width: float = 0, fill: _Ink | None = None) -> None: + """ + :param width: The width of the text stroke. + :param fill: Color to use for the text stroke when drawing. If not given, will + default to the ``fill`` parameter from + :py:meth:`.ImageDraw.ImageDraw.text`. + """ + self.stroke_width = width + self.stroke_fill = fill + + def _get_fontmode(self) -> str: + if self.mode in ("1", "P", "I", "F"): + return "1" + elif self.embedded_color: + return "RGBA" + else: + return "L" + + def get_length(self) -> float: + """ + Returns length (in pixels with 1/64 precision) of text. + + This is the amount by which following text should be offset. + Text bounding box may extend past the length in some fonts, + e.g. when using italics or accents. + + The result is returned as a float; it is a whole number if using basic layout. + + Note that the sum of two lengths may not equal the length of a concatenated + string due to kerning. If you need to adjust for kerning, include the following + character and subtract its length. + + For example, instead of:: + + hello = ImageText.Text("Hello", font).get_length() + world = ImageText.Text("World", font).get_length() + helloworld = ImageText.Text("HelloWorld", font).get_length() + assert hello + world == helloworld + + use:: + + hello = ( + ImageText.Text("HelloW", font).get_length() - + ImageText.Text("W", font).get_length() + ) # adjusted for kerning + world = ImageText.Text("World", font).get_length() + helloworld = ImageText.Text("HelloWorld", font).get_length() + assert hello + world == helloworld + + or disable kerning with (requires libraqm):: + + hello = ImageText.Text("Hello", font, features=["-kern"]).get_length() + world = ImageText.Text("World", font, features=["-kern"]).get_length() + helloworld = ImageText.Text( + "HelloWorld", font, features=["-kern"] + ).get_length() + assert hello + world == helloworld + + :return: Either width for horizontal text, or height for vertical text. + """ + if isinstance(self.text, str): + multiline = "\n" in self.text + else: + multiline = b"\n" in self.text + if multiline: + msg = "can't measure length of multiline text" + raise ValueError(msg) + return self.font.getlength( + self.text, + self._get_fontmode(), + self.direction, + self.features, + self.language, + ) + + def _split( + self, xy: tuple[float, float], anchor: str | None, align: str + ) -> list[tuple[tuple[float, float], str, str | bytes]]: + if anchor is None: + anchor = "lt" if self.direction == "ttb" else "la" + elif len(anchor) != 2: + msg = "anchor must be a 2 character string" + raise ValueError(msg) + + lines = ( + self.text.split("\n") + if isinstance(self.text, str) + else self.text.split(b"\n") + ) + if len(lines) == 1: + return [(xy, anchor, self.text)] + + if anchor[1] in "tb" and self.direction != "ttb": + msg = "anchor not supported for multiline text" + raise ValueError(msg) + + fontmode = self._get_fontmode() + line_spacing = ( + self.font.getbbox( + "A", + fontmode, + None, + self.features, + self.language, + self.stroke_width, + )[3] + + self.stroke_width + + self.spacing + ) + + top = xy[1] + parts = [] + if self.direction == "ttb": + left = xy[0] + for line in lines: + parts.append(((left, top), anchor, line)) + left += line_spacing + else: + widths = [] + max_width: float = 0 + for line in lines: + line_width = self.font.getlength( + line, fontmode, self.direction, self.features, self.language + ) + widths.append(line_width) + max_width = max(max_width, line_width) + + if anchor[1] == "m": + top -= (len(lines) - 1) * line_spacing / 2.0 + elif anchor[1] == "d": + top -= (len(lines) - 1) * line_spacing + + idx = -1 + for line in lines: + left = xy[0] + idx += 1 + width_difference = max_width - widths[idx] + + # align by align parameter + if align in ("left", "justify"): + pass + elif align == "center": + left += width_difference / 2.0 + elif align == "right": + left += width_difference + else: + msg = 'align must be "left", "center", "right" or "justify"' + raise ValueError(msg) + + if ( + align == "justify" + and width_difference != 0 + and idx != len(lines) - 1 + ): + words = ( + line.split(" ") if isinstance(line, str) else line.split(b" ") + ) + if len(words) > 1: + # align left by anchor + if anchor[0] == "m": + left -= max_width / 2.0 + elif anchor[0] == "r": + left -= max_width + + word_widths = [ + self.font.getlength( + word, + fontmode, + self.direction, + self.features, + self.language, + ) + for word in words + ] + word_anchor = "l" + anchor[1] + width_difference = max_width - sum(word_widths) + i = 0 + for word in words: + parts.append(((left, top), word_anchor, word)) + left += word_widths[i] + width_difference / (len(words) - 1) + i += 1 + top += line_spacing + continue + + # align left by anchor + if anchor[0] == "m": + left -= width_difference / 2.0 + elif anchor[0] == "r": + left -= width_difference + parts.append(((left, top), anchor, line)) + top += line_spacing + + return parts + + def get_bbox( + self, + xy: tuple[float, float] = (0, 0), + anchor: str | None = None, + align: str = "left", + ) -> tuple[float, float, float, float]: + """ + Returns bounding box (in pixels) of text. + + Use :py:meth:`get_length` to get the offset of following text with 1/64 pixel + precision. The bounding box includes extra margins for some fonts, e.g. italics + or accents. + + :param xy: The anchor coordinates of the text. + :param anchor: The text anchor alignment. Determines the relative location of + the anchor to the text. The default alignment is top left, + specifically ``la`` for horizontal text and ``lt`` for + vertical text. See :ref:`text-anchors` for details. + :param align: For multiline text, ``"left"``, ``"center"``, ``"right"`` or + ``"justify"`` determines the relative alignment of lines. Use the + ``anchor`` parameter to specify the alignment to ``xy``. + + :return: ``(left, top, right, bottom)`` bounding box + """ + bbox: tuple[float, float, float, float] | None = None + fontmode = self._get_fontmode() + for xy, anchor, line in self._split(xy, anchor, align): + bbox_line = self.font.getbbox( + line, + fontmode, + self.direction, + self.features, + self.language, + self.stroke_width, + anchor, + ) + bbox_line = ( + bbox_line[0] + xy[0], + bbox_line[1] + xy[1], + bbox_line[2] + xy[0], + bbox_line[3] + xy[1], + ) + if bbox is None: + bbox = bbox_line + else: + bbox = ( + min(bbox[0], bbox_line[0]), + min(bbox[1], bbox_line[1]), + max(bbox[2], bbox_line[2]), + max(bbox[3], bbox_line[3]), + ) + + assert bbox is not None + return bbox diff --git a/PIL/ImageTk.py b/PIL/ImageTk.py new file mode 100644 index 0000000000000000000000000000000000000000..3a4cb81e9ef5ef4abe617d4a364074c2203571ad --- /dev/null +++ b/PIL/ImageTk.py @@ -0,0 +1,266 @@ +# +# The Python Imaging Library. +# $Id$ +# +# a Tk display interface +# +# History: +# 96-04-08 fl Created +# 96-09-06 fl Added getimage method +# 96-11-01 fl Rewritten, removed image attribute and crop method +# 97-05-09 fl Use PyImagingPaste method instead of image type +# 97-05-12 fl Minor tweaks to match the IFUNC95 interface +# 97-05-17 fl Support the "pilbitmap" booster patch +# 97-06-05 fl Added file= and data= argument to image constructors +# 98-03-09 fl Added width and height methods to Image classes +# 98-07-02 fl Use default mode for "P" images without palette attribute +# 98-07-02 fl Explicitly destroy Tkinter image objects +# 99-07-24 fl Support multiple Tk interpreters (from Greg Couch) +# 99-07-26 fl Automatically hook into Tkinter (if possible) +# 99-08-15 fl Hook uses _imagingtk instead of _imaging +# +# Copyright (c) 1997-1999 by Secret Labs AB +# Copyright (c) 1996-1997 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import tkinter +from io import BytesIO +from typing import Any + +from . import Image, ImageFile + +TYPE_CHECKING = False +if TYPE_CHECKING: + from ._typing import CapsuleType + +# -------------------------------------------------------------------- +# Check for Tkinter interface hooks + + +def _get_image_from_kw(kw: dict[str, Any]) -> ImageFile.ImageFile | None: + source = None + if "file" in kw: + source = kw.pop("file") + elif "data" in kw: + source = BytesIO(kw.pop("data")) + if not source: + return None + return Image.open(source) + + +def _pyimagingtkcall( + command: str, photo: PhotoImage | tkinter.PhotoImage, ptr: CapsuleType +) -> None: + tk = photo.tk + try: + tk.call(command, photo, repr(ptr)) + except tkinter.TclError: + # activate Tkinter hook + # may raise an error if it cannot attach to Tkinter + from . import _imagingtk + + _imagingtk.tkinit(tk.interpaddr()) + tk.call(command, photo, repr(ptr)) + + +# -------------------------------------------------------------------- +# PhotoImage + + +class PhotoImage: + """ + A Tkinter-compatible photo image. This can be used + everywhere Tkinter expects an image object. If the image is an RGBA + image, pixels having alpha 0 are treated as transparent. + + The constructor takes either a PIL image, or a mode and a size. + Alternatively, you can use the ``file`` or ``data`` options to initialize + the photo image object. + + :param image: Either a PIL image, or a mode string. If a mode string is + used, a size must also be given. + :param size: If the first argument is a mode string, this defines the size + of the image. + :keyword file: A filename to load the image from (using + ``Image.open(file)``). + :keyword data: An 8-bit string containing image data (as loaded from an + image file). + """ + + def __init__( + self, + image: Image.Image | str | None = None, + size: tuple[int, int] | None = None, + **kw: Any, + ) -> None: + # Tk compatibility: file or data + if image is None: + image = _get_image_from_kw(kw) + + if image is None: + msg = "Image is required" + raise ValueError(msg) + elif isinstance(image, str): + mode = image + image = None + + if size is None: + msg = "If first argument is mode, size is required" + raise ValueError(msg) + else: + # got an image instead of a mode + mode = image.mode + if mode == "P": + # palette mapped data + image.apply_transparency() + image.load() + mode = image.palette.mode if image.palette else "RGB" + size = image.size + kw["width"], kw["height"] = size + + if mode not in ["1", "L", "RGB", "RGBA"]: + mode = Image.getmodebase(mode) + + self.__mode = mode + self.__size = size + self.__photo = tkinter.PhotoImage(**kw) + self.tk = self.__photo.tk + if image: + self.paste(image) + + def __del__(self) -> None: + try: + name = self.__photo.name + except AttributeError: + return + self.__photo.name = None + try: + self.__photo.tk.call("image", "delete", name) + except Exception: + pass # ignore internal errors + + def __str__(self) -> str: + """ + Get the Tkinter photo image identifier. This method is automatically + called by Tkinter whenever a PhotoImage object is passed to a Tkinter + method. + + :return: A Tkinter photo image identifier (a string). + """ + return str(self.__photo) + + def width(self) -> int: + """ + Get the width of the image. + + :return: The width, in pixels. + """ + return self.__size[0] + + def height(self) -> int: + """ + Get the height of the image. + + :return: The height, in pixels. + """ + return self.__size[1] + + def paste(self, im: Image.Image) -> None: + """ + Paste a PIL image into the photo image. Note that this can + be very slow if the photo image is displayed. + + :param im: A PIL image. The size must match the target region. If the + mode does not match, the image is converted to the mode of + the bitmap image. + """ + # convert to blittable + ptr = im.getim() + image = im.im + if not image.isblock() or im.mode != self.__mode: + block = Image.core.new_block(self.__mode, im.size) + image.convert2(block, image) # convert directly between buffers + ptr = block.ptr + + _pyimagingtkcall("PyImagingPhoto", self.__photo, ptr) + + +# -------------------------------------------------------------------- +# BitmapImage + + +class BitmapImage: + """ + A Tkinter-compatible bitmap image. This can be used everywhere Tkinter + expects an image object. + + The given image must have mode "1". Pixels having value 0 are treated as + transparent. Options, if any, are passed on to Tkinter. The most commonly + used option is ``foreground``, which is used to specify the color for the + non-transparent parts. See the Tkinter documentation for information on + how to specify colours. + + :param image: A PIL image. + """ + + def __init__(self, image: Image.Image | None = None, **kw: Any) -> None: + # Tk compatibility: file or data + if image is None: + image = _get_image_from_kw(kw) + + if image is None: + msg = "Image is required" + raise ValueError(msg) + self.__mode = image.mode + self.__size = image.size + + self.__photo = tkinter.BitmapImage(data=image.tobitmap(), **kw) + + def __del__(self) -> None: + try: + name = self.__photo.name + except AttributeError: + return + self.__photo.name = None + try: + self.__photo.tk.call("image", "delete", name) + except Exception: + pass # ignore internal errors + + def width(self) -> int: + """ + Get the width of the image. + + :return: The width, in pixels. + """ + return self.__size[0] + + def height(self) -> int: + """ + Get the height of the image. + + :return: The height, in pixels. + """ + return self.__size[1] + + def __str__(self) -> str: + """ + Get the Tkinter bitmap image identifier. This method is automatically + called by Tkinter whenever a BitmapImage object is passed to a Tkinter + method. + + :return: A Tkinter bitmap image identifier (a string). + """ + return str(self.__photo) + + +def getimage(photo: PhotoImage) -> Image.Image: + """Copies the contents of a PhotoImage to a PIL image memory.""" + im = Image.new("RGBA", (photo.width(), photo.height())) + + _pyimagingtkcall("PyImagingPhotoGet", photo, im.getim()) + + return im diff --git a/PIL/ImageTransform.py b/PIL/ImageTransform.py new file mode 100644 index 0000000000000000000000000000000000000000..fb144ff38a1ee7ff77cc01f3b941756a60b2b4cd --- /dev/null +++ b/PIL/ImageTransform.py @@ -0,0 +1,136 @@ +# +# The Python Imaging Library. +# $Id$ +# +# transform wrappers +# +# History: +# 2002-04-08 fl Created +# +# Copyright (c) 2002 by Secret Labs AB +# Copyright (c) 2002 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +from collections.abc import Sequence +from typing import Any + +from . import Image + + +class Transform(Image.ImageTransformHandler): + """Base class for other transforms defined in :py:mod:`~PIL.ImageTransform`.""" + + method: Image.Transform + + def __init__(self, data: Sequence[Any]) -> None: + self.data = data + + def getdata(self) -> tuple[Image.Transform, Sequence[int]]: + return self.method, self.data + + def transform( + self, + size: tuple[int, int], + image: Image.Image, + **options: Any, + ) -> Image.Image: + """Perform the transform. Called from :py:meth:`.Image.transform`.""" + # can be overridden + method, data = self.getdata() + return image.transform(size, method, data, **options) + + +class AffineTransform(Transform): + """ + Define an affine image transform. + + This function takes a 6-tuple (a, b, c, d, e, f) which contain the first + two rows from the inverse of an affine transform matrix. For each pixel + (x, y) in the output image, the new value is taken from a position (a x + + b y + c, d x + e y + f) in the input image, rounded to nearest pixel. + + This function can be used to scale, translate, rotate, and shear the + original image. + + See :py:meth:`.Image.transform` + + :param matrix: A 6-tuple (a, b, c, d, e, f) containing the first two rows + from the inverse of an affine transform matrix. + """ + + method = Image.Transform.AFFINE + + +class PerspectiveTransform(Transform): + """ + Define a perspective image transform. + + This function takes an 8-tuple (a, b, c, d, e, f, g, h). For each pixel + (x, y) in the output image, the new value is taken from a position + ((a x + b y + c) / (g x + h y + 1), (d x + e y + f) / (g x + h y + 1)) in + the input image, rounded to nearest pixel. + + This function can be used to scale, translate, rotate, and shear the + original image. + + See :py:meth:`.Image.transform` + + :param matrix: An 8-tuple (a, b, c, d, e, f, g, h). + """ + + method = Image.Transform.PERSPECTIVE + + +class ExtentTransform(Transform): + """ + Define a transform to extract a subregion from an image. + + Maps a rectangle (defined by two corners) from the image to a rectangle of + the given size. The resulting image will contain data sampled from between + the corners, such that (x0, y0) in the input image will end up at (0,0) in + the output image, and (x1, y1) at size. + + This method can be used to crop, stretch, shrink, or mirror an arbitrary + rectangle in the current image. It is slightly slower than crop, but about + as fast as a corresponding resize operation. + + See :py:meth:`.Image.transform` + + :param bbox: A 4-tuple (x0, y0, x1, y1) which specifies two points in the + input image's coordinate system. See :ref:`coordinate-system`. + """ + + method = Image.Transform.EXTENT + + +class QuadTransform(Transform): + """ + Define a quad image transform. + + Maps a quadrilateral (a region defined by four corners) from the image to a + rectangle of the given size. + + See :py:meth:`.Image.transform` + + :param xy: An 8-tuple (x0, y0, x1, y1, x2, y2, x3, y3) which contain the + upper left, lower left, lower right, and upper right corner of the + source quadrilateral. + """ + + method = Image.Transform.QUAD + + +class MeshTransform(Transform): + """ + Define a mesh image transform. A mesh transform consists of one or more + individual quad transforms. + + See :py:meth:`.Image.transform` + + :param data: A list of (bbox, quad) tuples. + """ + + method = Image.Transform.MESH diff --git a/PIL/ImageWin.py b/PIL/ImageWin.py new file mode 100644 index 0000000000000000000000000000000000000000..98c28f29f1dbbb069b68dc9359051b6629148f0d --- /dev/null +++ b/PIL/ImageWin.py @@ -0,0 +1,247 @@ +# +# The Python Imaging Library. +# $Id$ +# +# a Windows DIB display interface +# +# History: +# 1996-05-20 fl Created +# 1996-09-20 fl Fixed subregion exposure +# 1997-09-21 fl Added draw primitive (for tzPrint) +# 2003-05-21 fl Added experimental Window/ImageWindow classes +# 2003-09-05 fl Added fromstring/tostring methods +# +# Copyright (c) Secret Labs AB 1997-2003. +# Copyright (c) Fredrik Lundh 1996-2003. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +from . import Image + + +class HDC: + """ + Wraps an HDC integer. The resulting object can be passed to the + :py:meth:`~PIL.ImageWin.Dib.draw` and :py:meth:`~PIL.ImageWin.Dib.expose` + methods. + """ + + def __init__(self, dc: int) -> None: + self.dc = dc + + def __int__(self) -> int: + return self.dc + + +class HWND: + """ + Wraps an HWND integer. The resulting object can be passed to the + :py:meth:`~PIL.ImageWin.Dib.draw` and :py:meth:`~PIL.ImageWin.Dib.expose` + methods, instead of a DC. + """ + + def __init__(self, wnd: int) -> None: + self.wnd = wnd + + def __int__(self) -> int: + return self.wnd + + +class Dib: + """ + A Windows bitmap with the given mode and size. The mode can be one of "1", + "L", "P", or "RGB". + + If the display requires a palette, this constructor creates a suitable + palette and associates it with the image. For an "L" image, 128 graylevels + are allocated. For an "RGB" image, a 6x6x6 colour cube is used, together + with 20 graylevels. + + To make sure that palettes work properly under Windows, you must call the + ``palette`` method upon certain events from Windows. + + :param image: Either a PIL image, or a mode string. If a mode string is + used, a size must also be given. The mode can be one of "1", + "L", "P", or "RGB". + :param size: If the first argument is a mode string, this + defines the size of the image. + """ + + def __init__( + self, image: Image.Image | str, size: tuple[int, int] | None = None + ) -> None: + if isinstance(image, str): + mode = image + image = "" + if size is None: + msg = "If first argument is mode, size is required" + raise ValueError(msg) + else: + mode = image.mode + size = image.size + if mode not in ["1", "L", "P", "RGB"]: + mode = Image.getmodebase(mode) + self.image = Image.core.display(mode, size) + self.mode = mode + self.size = size + if image: + assert not isinstance(image, str) + self.paste(image) + + def expose(self, handle: int | HDC | HWND) -> None: + """ + Copy the bitmap contents to a device context. + + :param handle: Device context (HDC), cast to a Python integer, or an + HDC or HWND instance. In PythonWin, you can use + ``CDC.GetHandleAttrib()`` to get a suitable handle. + """ + handle_int = int(handle) + if isinstance(handle, HWND): + dc = self.image.getdc(handle_int) + try: + self.image.expose(dc) + finally: + self.image.releasedc(handle_int, dc) + else: + self.image.expose(handle_int) + + def draw( + self, + handle: int | HDC | HWND, + dst: tuple[int, int, int, int], + src: tuple[int, int, int, int] | None = None, + ) -> None: + """ + Same as expose, but allows you to specify where to draw the image, and + what part of it to draw. + + The destination and source areas are given as 4-tuple rectangles. If + the source is omitted, the entire image is copied. If the source and + the destination have different sizes, the image is resized as + necessary. + """ + if src is None: + src = (0, 0) + self.size + handle_int = int(handle) + if isinstance(handle, HWND): + dc = self.image.getdc(handle_int) + try: + self.image.draw(dc, dst, src) + finally: + self.image.releasedc(handle_int, dc) + else: + self.image.draw(handle_int, dst, src) + + def query_palette(self, handle: int | HDC | HWND) -> int: + """ + Installs the palette associated with the image in the given device + context. + + This method should be called upon **QUERYNEWPALETTE** and + **PALETTECHANGED** events from Windows. If this method returns a + non-zero value, one or more display palette entries were changed, and + the image should be redrawn. + + :param handle: Device context (HDC), cast to a Python integer, or an + HDC or HWND instance. + :return: The number of entries that were changed (if one or more entries, + this indicates that the image should be redrawn). + """ + handle_int = int(handle) + if isinstance(handle, HWND): + handle = self.image.getdc(handle_int) + try: + result = self.image.query_palette(handle) + finally: + self.image.releasedc(handle, handle) + else: + result = self.image.query_palette(handle_int) + return result + + def paste( + self, im: Image.Image, box: tuple[int, int, int, int] | None = None + ) -> None: + """ + Paste a PIL image into the bitmap image. + + :param im: A PIL image. The size must match the target region. + If the mode does not match, the image is converted to the + mode of the bitmap image. + :param box: A 4-tuple defining the left, upper, right, and + lower pixel coordinate. See :ref:`coordinate-system`. If + None is given instead of a tuple, all of the image is + assumed. + """ + im.load() + if self.mode != im.mode: + im = im.convert(self.mode) + if box: + self.image.paste(im.im, box) + else: + self.image.paste(im.im) + + def frombytes(self, buffer: bytes) -> None: + """ + Load display memory contents from byte data. + + :param buffer: A buffer containing display data (usually + data returned from :py:func:`~PIL.ImageWin.Dib.tobytes`) + """ + self.image.frombytes(buffer) + + def tobytes(self) -> bytes: + """ + Copy display memory contents to bytes object. + + :return: A bytes object containing display data. + """ + return self.image.tobytes() + + +class Window: + """Create a Window with the given title size.""" + + def __init__( + self, title: str = "PIL", width: int | None = None, height: int | None = None + ) -> None: + self.hwnd = Image.core.createwindow( + title, self.__dispatcher, width or 0, height or 0 + ) + + def __dispatcher(self, action: str, *args: int) -> None: + getattr(self, f"ui_handle_{action}")(*args) + + def ui_handle_clear(self, dc: int, x0: int, y0: int, x1: int, y1: int) -> None: + pass + + def ui_handle_damage(self, x0: int, y0: int, x1: int, y1: int) -> None: + pass + + def ui_handle_destroy(self) -> None: + pass + + def ui_handle_repair(self, dc: int, x0: int, y0: int, x1: int, y1: int) -> None: + pass + + def ui_handle_resize(self, width: int, height: int) -> None: + pass + + def mainloop(self) -> None: + Image.core.eventloop() + + +class ImageWindow(Window): + """Create an image window which displays the given image.""" + + def __init__(self, image: Image.Image | Dib, title: str = "PIL") -> None: + if not isinstance(image, Dib): + image = Dib(image) + self.image = image + width, height = image.size + super().__init__(title, width=width, height=height) + + def ui_handle_repair(self, dc: int, x0: int, y0: int, x1: int, y1: int) -> None: + self.image.draw(dc, (x0, y0, x1, y1)) diff --git a/PIL/IptcImagePlugin.py b/PIL/IptcImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..6fc824e4caa6131de77fe53bc103d015b1080106 --- /dev/null +++ b/PIL/IptcImagePlugin.py @@ -0,0 +1,233 @@ +# +# The Python Imaging Library. +# $Id$ +# +# IPTC/NAA file handling +# +# history: +# 1995-10-01 fl Created +# 1998-03-09 fl Cleaned up and added to PIL +# 2002-06-18 fl Added getiptcinfo helper +# +# Copyright (c) Secret Labs AB 1997-2002. +# Copyright (c) Fredrik Lundh 1995. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +from io import BytesIO +from typing import cast + +from . import Image, ImageFile +from ._binary import i16be as i16 +from ._binary import i32be as i32 + +COMPRESSION = {1: "raw", 5: "jpeg"} + + +# +# Helpers + + +def _i(c: bytes) -> int: + return i32((b"\0\0\0\0" + c)[-4:]) + + +## +# Image plugin for IPTC/NAA datastreams. To read IPTC/NAA fields +# from TIFF and JPEG files, use the getiptcinfo function. + + +class IptcImageFile(ImageFile.ImageFile): + format = "IPTC" + format_description = "IPTC/NAA" + + def getint(self, key: tuple[int, int]) -> int: + return _i(self.info[key]) + + def field(self) -> tuple[tuple[int, int] | None, int]: + # + # get a IPTC field header + assert self.fp is not None + s = self.fp.read(5) + if not s.strip(b"\x00"): + return None, 0 + + tag = s[1], s[2] + + # syntax + if s[0] != 0x1C or tag[0] not in [1, 2, 3, 4, 5, 6, 7, 8, 9, 240]: + msg = "invalid IPTC/NAA file" + raise SyntaxError(msg) + + # field size + size = s[3] + if size > 132: + msg = "illegal field length in IPTC/NAA file" + raise OSError(msg) + elif size == 128: + size = 0 + elif size > 128: + size = _i(self.fp.read(size - 128)) + else: + size = i16(s, 3) + + return tag, size + + def _open(self) -> None: + # load descriptive fields + assert self.fp is not None + while True: + offset = self.fp.tell() + tag, size = self.field() + if not tag or tag == (8, 10): + break + if size: + tagdata = self.fp.read(size) + else: + tagdata = None + if tag in self.info: + if isinstance(self.info[tag], list): + self.info[tag].append(tagdata) + else: + self.info[tag] = [self.info[tag], tagdata] + else: + self.info[tag] = tagdata + + # mode + layers = self.info[(3, 60)][0] + component = self.info[(3, 60)][1] + if layers == 1 and not component: + self._mode = "L" + band = None + else: + if layers == 3 and component: + self._mode = "RGB" + elif layers == 4 and component: + self._mode = "CMYK" + if (3, 65) in self.info: + band = self.info[(3, 65)][0] - 1 + else: + band = 0 + + # size + self._size = self.getint((3, 20)), self.getint((3, 30)) + + # compression + try: + compression = COMPRESSION[self.getint((3, 120))] + except KeyError as e: + msg = "Unknown IPTC image compression" + raise OSError(msg) from e + + # tile + if tag == (8, 10): + self.tile = [ + ImageFile._Tile("iptc", (0, 0) + self.size, offset, (compression, band)) + ] + + def load(self) -> Image.core.PixelAccess | None: + if self.tile: + args = self.tile[0].args + assert isinstance(args, tuple) + compression, band = args + + assert self.fp is not None + self.fp.seek(self.tile[0].offset) + + # Copy image data to temporary file + o = BytesIO() + if compression == "raw": + # To simplify access to the extracted file, + # prepend a PPM header + o.write(b"P5\n%d %d\n255\n" % self.size) + while True: + type, size = self.field() + if type != (8, 10): + break + while size > 0: + s = self.fp.read(min(size, 8192)) + if not s: + break + o.write(s) + size -= len(s) + + with Image.open(o) as _im: + if band is not None: + bands = [Image.new("L", _im.size)] * Image.getmodebands(self.mode) + bands[band] = _im + im = Image.merge(self.mode, bands) + else: + im = _im + im.load() + self.im = im.im + self.tile = [] + return ImageFile.ImageFile.load(self) + + +Image.register_open(IptcImageFile.format, IptcImageFile) + +Image.register_extension(IptcImageFile.format, ".iim") + + +def getiptcinfo( + im: ImageFile.ImageFile, +) -> dict[tuple[int, int], bytes | list[bytes]] | None: + """ + Get IPTC information from TIFF, JPEG, or IPTC file. + + :param im: An image containing IPTC data. + :returns: A dictionary containing IPTC information, or None if + no IPTC information block was found. + """ + from . import JpegImagePlugin, TiffImagePlugin + + data = None + + info: dict[tuple[int, int], bytes | list[bytes]] = {} + if isinstance(im, IptcImageFile): + # return info dictionary right away + for k, v in im.info.items(): + if isinstance(k, tuple): + info[k] = v + return info + + elif isinstance(im, JpegImagePlugin.JpegImageFile): + # extract the IPTC/NAA resource + photoshop = im.info.get("photoshop") + if photoshop: + data = photoshop.get(0x0404) + + elif isinstance(im, TiffImagePlugin.TiffImageFile): + # get raw data from the IPTC/NAA tag (PhotoShop tags the data + # as 4-byte integers, so we cannot use the get method...) + try: + data = im.tag_v2._tagdata[TiffImagePlugin.IPTC_NAA_CHUNK] + except KeyError: + pass + + if data is None: + return None # no properties + + # create an IptcImagePlugin object without initializing it + class FakeImage: + pass + + fake_im = FakeImage() + fake_im.__class__ = IptcImageFile # type: ignore[assignment] + iptc_im = cast(IptcImageFile, fake_im) + + # parse the IPTC information chunk + iptc_im.info = {} + iptc_im.fp = BytesIO(data) + + try: + iptc_im._open() + except (IndexError, KeyError): + pass # expected failure + + for k, v in iptc_im.info.items(): + if isinstance(k, tuple): + info[k] = v + return info diff --git a/PIL/Jpeg2KImagePlugin.py b/PIL/Jpeg2KImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..d6ec38d43101d54f48e179dbc8c79b249eba1a1e --- /dev/null +++ b/PIL/Jpeg2KImagePlugin.py @@ -0,0 +1,448 @@ +# +# The Python Imaging Library +# $Id$ +# +# JPEG2000 file handling +# +# History: +# 2014-03-12 ajh Created +# 2021-06-30 rogermb Extract dpi information from the 'resc' header box +# +# Copyright (c) 2014 Coriolis Systems Limited +# Copyright (c) 2014 Alastair Houghton +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import io +import os +import struct +from typing import cast + +from . import Image, ImageFile, ImagePalette, _binary + +TYPE_CHECKING = False +if TYPE_CHECKING: + from collections.abc import Callable + from typing import IO + + +class BoxReader: + """ + A small helper class to read fields stored in JPEG2000 header boxes + and to easily step into and read sub-boxes. + """ + + def __init__(self, fp: IO[bytes], length: int = -1) -> None: + self.fp = fp + self.has_length = length >= 0 + self.length = length + self.remaining_in_box = -1 + + def _can_read(self, num_bytes: int) -> bool: + if self.has_length and self.fp.tell() + num_bytes > self.length: + # Outside box: ensure we don't read past the known file length + return False + if self.remaining_in_box >= 0: + # Inside box contents: ensure read does not go past box boundaries + return num_bytes <= self.remaining_in_box + else: + return True # No length known, just read + + def _read_bytes(self, num_bytes: int) -> bytes: + if not self._can_read(num_bytes): + msg = "Not enough data in header" + raise SyntaxError(msg) + + data = self.fp.read(num_bytes) + if len(data) < num_bytes: + msg = f"Expected to read {num_bytes} bytes but only got {len(data)}." + raise OSError(msg) + + if self.remaining_in_box > 0: + self.remaining_in_box -= num_bytes + return data + + def read_fields(self, field_format: str) -> tuple[int | bytes, ...]: + size = struct.calcsize(field_format) + data = self._read_bytes(size) + return struct.unpack(field_format, data) + + def read_boxes(self) -> BoxReader: + size = self.remaining_in_box + data = self._read_bytes(size) + return BoxReader(io.BytesIO(data), size) + + def has_next_box(self) -> bool: + if self.has_length: + return self.fp.tell() + self.remaining_in_box < self.length + else: + return True + + def next_box_type(self) -> bytes: + # Skip the rest of the box if it has not been read + if self.remaining_in_box > 0: + self.fp.seek(self.remaining_in_box, os.SEEK_CUR) + self.remaining_in_box = -1 + + # Read the length and type of the next box + lbox, tbox = cast(tuple[int, bytes], self.read_fields(">I4s")) + if lbox == 1: + lbox = cast(int, self.read_fields(">Q")[0]) + hlen = 16 + else: + hlen = 8 + + if lbox < hlen or not self._can_read(lbox - hlen): + msg = "Invalid header length" + raise SyntaxError(msg) + + self.remaining_in_box = lbox - hlen + return tbox + + +def _parse_codestream(fp: IO[bytes]) -> tuple[tuple[int, int], str]: + """Parse the JPEG 2000 codestream to extract the size and component + count from the SIZ marker segment, returning a PIL (size, mode) tuple.""" + + hdr = fp.read(2) + lsiz = _binary.i16be(hdr) + siz = hdr + fp.read(lsiz - 2) + lsiz, rsiz, xsiz, ysiz, xosiz, yosiz, _, _, _, _, csiz = struct.unpack_from( + ">HHIIIIIIIIH", siz + ) + + size = (xsiz - xosiz, ysiz - yosiz) + if csiz == 1: + ssiz = struct.unpack_from(">B", siz, 38) + if (ssiz[0] & 0x7F) + 1 > 8: + mode = "I;16" + else: + mode = "L" + elif csiz == 2: + mode = "LA" + elif csiz == 3: + mode = "RGB" + elif csiz == 4: + mode = "RGBA" + else: + msg = "unable to determine J2K image mode" + raise SyntaxError(msg) + + return size, mode + + +def _res_to_dpi(num: int, denom: int, exp: int) -> float | None: + """Convert JPEG2000's (numerator, denominator, exponent-base-10) resolution, + calculated as (num / denom) * 10^exp and stored in dots per meter, + to floating-point dots per inch.""" + if denom == 0: + return None + return (254 * num * (10**exp)) / (10000 * denom) + + +def _parse_jp2_header( + fp: IO[bytes], +) -> tuple[ + tuple[int, int], + str, + str | None, + tuple[float, float] | None, + ImagePalette.ImagePalette | None, +]: + """Parse the JP2 header box to extract size, component count, + color space information, and optionally DPI information, + returning a (size, mode, mimetype, dpi) tuple.""" + + # Find the JP2 header box + reader = BoxReader(fp) + header = None + mimetype = None + while reader.has_next_box(): + tbox = reader.next_box_type() + + if tbox == b"jp2h": + header = reader.read_boxes() + break + elif tbox == b"ftyp": + if reader.read_fields(">4s")[0] == b"jpx ": + mimetype = "image/jpx" + assert header is not None + + size = None + mode = None + bpc = None + nc = None + dpi = None # 2-tuple of DPI info, or None + palette = None + + while header.has_next_box(): + tbox = header.next_box_type() + + if tbox == b"ihdr": + height, width, nc, bpc = header.read_fields(">IIHB") + assert isinstance(height, int) + assert isinstance(width, int) + assert isinstance(bpc, int) + size = (width, height) + if nc == 1 and (bpc & 0x7F) > 8: + mode = "I;16" + elif nc == 1: + mode = "L" + elif nc == 2: + mode = "LA" + elif nc == 3: + mode = "RGB" + elif nc == 4: + mode = "RGBA" + elif tbox == b"colr" and nc == 4: + meth, _, _, enumcs = header.read_fields(">BBBI") + if meth == 1 and enumcs == 12: + mode = "CMYK" + elif tbox == b"pclr" and mode in ("L", "LA"): + ne, npc = header.read_fields(">HB") + assert isinstance(ne, int) + assert isinstance(npc, int) + max_bitdepth = 0 + for bitdepth in header.read_fields(">" + ("B" * npc)): + assert isinstance(bitdepth, int) + if bitdepth > max_bitdepth: + max_bitdepth = bitdepth + if max_bitdepth <= 8: + palette = ImagePalette.ImagePalette("RGBA" if npc == 4 else "RGB") + for i in range(ne): + color: list[int] = [] + for value in header.read_fields(">" + ("B" * npc)): + assert isinstance(value, int) + color.append(value) + palette.getcolor(tuple(color)) + mode = "P" if mode == "L" else "PA" + elif tbox == b"res ": + res = header.read_boxes() + while res.has_next_box(): + tres = res.next_box_type() + if tres == b"resc": + vrcn, vrcd, hrcn, hrcd, vrce, hrce = res.read_fields(">HHHHBB") + assert isinstance(vrcn, int) + assert isinstance(vrcd, int) + assert isinstance(hrcn, int) + assert isinstance(hrcd, int) + assert isinstance(vrce, int) + assert isinstance(hrce, int) + hres = _res_to_dpi(hrcn, hrcd, hrce) + vres = _res_to_dpi(vrcn, vrcd, vrce) + if hres is not None and vres is not None: + dpi = (hres, vres) + break + + if size is None or mode is None: + msg = "Malformed JP2 header" + raise SyntaxError(msg) + + return size, mode, mimetype, dpi, palette + + +## +# Image plugin for JPEG2000 images. + + +class Jpeg2KImageFile(ImageFile.ImageFile): + format = "JPEG2000" + format_description = "JPEG 2000 (ISO 15444)" + + def _open(self) -> None: + assert self.fp is not None + sig = self.fp.read(4) + if sig == b"\xff\x4f\xff\x51": + self.codec = "j2k" + self._size, self._mode = _parse_codestream(self.fp) + self._parse_comment() + else: + sig = sig + self.fp.read(8) + + if sig == b"\x00\x00\x00\x0cjP \x0d\x0a\x87\x0a": + self.codec = "jp2" + header = _parse_jp2_header(self.fp) + self._size, self._mode, self.custom_mimetype, dpi, self.palette = header + if dpi is not None: + self.info["dpi"] = dpi + if self.fp.read(12).endswith(b"jp2c\xff\x4f\xff\x51"): + hdr = self.fp.read(2) + length = _binary.i16be(hdr) + self.fp.seek(length - 2, os.SEEK_CUR) + self._parse_comment() + else: + msg = "not a JPEG 2000 file" + raise SyntaxError(msg) + + self._reduce = 0 + self.layers = 0 + + fd = -1 + length = -1 + + try: + fd = self.fp.fileno() + length = os.fstat(fd).st_size + except Exception: + fd = -1 + try: + pos = self.fp.tell() + self.fp.seek(0, io.SEEK_END) + length = self.fp.tell() + self.fp.seek(pos) + except Exception: + length = -1 + + self.tile = [ + ImageFile._Tile( + "jpeg2k", + (0, 0) + self.size, + 0, + (self.codec, self._reduce, self.layers, fd, length), + ) + ] + + def _parse_comment(self) -> None: + assert self.fp is not None + while True: + marker = self.fp.read(2) + if not marker: + break + typ = marker[1] + if typ in (0x90, 0xD9): + # Start of tile or end of codestream + break + hdr = self.fp.read(2) + length = _binary.i16be(hdr) + if typ == 0x64: + # Comment + self.info["comment"] = self.fp.read(length - 2)[2:] + break + else: + self.fp.seek(length - 2, os.SEEK_CUR) + + @property # type: ignore[override] + def reduce( + self, + ) -> ( + Callable[[int | tuple[int, int], tuple[int, int, int, int] | None], Image.Image] + | int + ): + # https://github.com/python-pillow/Pillow/issues/4343 found that the + # new Image 'reduce' method was shadowed by this plugin's 'reduce' + # property. This attempts to allow for both scenarios + return self._reduce or super().reduce + + @reduce.setter + def reduce(self, value: int) -> None: + self._reduce = value + + def load(self) -> Image.core.PixelAccess | None: + if self.tile and self._reduce: + power = 1 << self._reduce + adjust = power >> 1 + self._size = ( + int((self.size[0] + adjust) / power), + int((self.size[1] + adjust) / power), + ) + + # Update the reduce and layers settings + t = self.tile[0] + assert isinstance(t[3], tuple) + t3 = (t[3][0], self._reduce, self.layers, t[3][3], t[3][4]) + self.tile = [ImageFile._Tile(t[0], (0, 0) + self.size, t[2], t3)] + + return ImageFile.ImageFile.load(self) + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith( + (b"\xff\x4f\xff\x51", b"\x00\x00\x00\x0cjP \x0d\x0a\x87\x0a") + ) + + +# ------------------------------------------------------------ +# Save support + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + # Get the keyword arguments + info = im.encoderinfo + + if isinstance(filename, str): + filename = filename.encode() + if filename.endswith(b".j2k") or info.get("no_jp2", False): + kind = "j2k" + else: + kind = "jp2" + + offset = info.get("offset", None) + tile_offset = info.get("tile_offset", None) + tile_size = info.get("tile_size", None) + quality_mode = info.get("quality_mode", "rates") + quality_layers = info.get("quality_layers", None) + if quality_layers is not None and not ( + isinstance(quality_layers, (list, tuple)) + and all( + isinstance(quality_layer, (int, float)) for quality_layer in quality_layers + ) + ): + msg = "quality_layers must be a sequence of numbers" + raise ValueError(msg) + + num_resolutions = info.get("num_resolutions", 0) + cblk_size = info.get("codeblock_size", None) + precinct_size = info.get("precinct_size", None) + irreversible = info.get("irreversible", False) + progression = info.get("progression", "LRCP") + cinema_mode = info.get("cinema_mode", "no") + mct = info.get("mct", 0) + signed = info.get("signed", False) + comment = info.get("comment") + if isinstance(comment, str): + comment = comment.encode() + plt = info.get("plt", False) + + fd = -1 + if hasattr(fp, "fileno"): + try: + fd = fp.fileno() + except Exception: + fd = -1 + + im.encoderconfig = ( + offset, + tile_offset, + tile_size, + quality_mode, + quality_layers, + num_resolutions, + cblk_size, + precinct_size, + irreversible, + progression, + cinema_mode, + mct, + signed, + fd, + comment, + plt, + ) + + ImageFile._save(im, fp, [ImageFile._Tile("jpeg2k", (0, 0) + im.size, 0, kind)]) + + +# ------------------------------------------------------------ +# Registry stuff + + +Image.register_open(Jpeg2KImageFile.format, Jpeg2KImageFile, _accept) +Image.register_save(Jpeg2KImageFile.format, _save) + +Image.register_extensions( + Jpeg2KImageFile.format, [".jp2", ".j2k", ".jpc", ".jpf", ".jpx", ".j2c"] +) + +Image.register_mime(Jpeg2KImageFile.format, "image/jp2") diff --git a/PIL/JpegImagePlugin.py b/PIL/JpegImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..894c1547d7b68c2af11495b3040b188c548a62d1 --- /dev/null +++ b/PIL/JpegImagePlugin.py @@ -0,0 +1,895 @@ +# +# The Python Imaging Library. +# $Id$ +# +# JPEG (JFIF) file handling +# +# See "Digital Compression and Coding of Continuous-Tone Still Images, +# Part 1, Requirements and Guidelines" (CCITT T.81 / ISO 10918-1) +# +# History: +# 1995-09-09 fl Created +# 1995-09-13 fl Added full parser +# 1996-03-25 fl Added hack to use the IJG command line utilities +# 1996-05-05 fl Workaround Photoshop 2.5 CMYK polarity bug +# 1996-05-28 fl Added draft support, JFIF version (0.1) +# 1996-12-30 fl Added encoder options, added progression property (0.2) +# 1997-08-27 fl Save mode 1 images as BW (0.3) +# 1998-07-12 fl Added YCbCr to draft and save methods (0.4) +# 1998-10-19 fl Don't hang on files using 16-bit DQT's (0.4.1) +# 2001-04-16 fl Extract DPI settings from JFIF files (0.4.2) +# 2002-07-01 fl Skip pad bytes before markers; identify Exif files (0.4.3) +# 2003-04-25 fl Added experimental EXIF decoder (0.5) +# 2003-06-06 fl Added experimental EXIF GPSinfo decoder +# 2003-09-13 fl Extract COM markers +# 2009-09-06 fl Added icc_profile support (from Florian Hoech) +# 2009-03-06 fl Changed CMYK handling; always use Adobe polarity (0.6) +# 2009-03-08 fl Added subsampling support (from Justin Huff). +# +# Copyright (c) 1997-2003 by Secret Labs AB. +# Copyright (c) 1995-1996 by Fredrik Lundh. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import array +import io +import math +import os +import struct +import subprocess +import sys +import tempfile +import warnings + +from . import Image, ImageFile +from ._binary import i16be as i16 +from ._binary import i32be as i32 +from ._binary import o8 +from ._binary import o16be as o16 +from .JpegPresets import presets + +TYPE_CHECKING = False +if TYPE_CHECKING: + from typing import IO, Any + + from .MpoImagePlugin import MpoImageFile + +# +# Parser + + +def Skip(self: JpegImageFile, marker: int) -> None: + assert self.fp is not None + n = i16(self.fp.read(2)) - 2 + ImageFile._safe_read(self.fp, n) + + +def APP(self: JpegImageFile, marker: int) -> None: + # + # Application marker. Store these in the APP dictionary. + # Also look for well-known application markers. + + assert self.fp is not None + n = i16(self.fp.read(2)) - 2 + s = ImageFile._safe_read(self.fp, n) + + app = f"APP{marker & 15}" + + self.app[app] = s # compatibility + self.applist.append((app, s)) + + if marker == 0xFFE0 and s.startswith(b"JFIF"): + # extract JFIF information + self.info["jfif"] = version = i16(s, 5) # version + self.info["jfif_version"] = divmod(version, 256) + # extract JFIF properties + try: + jfif_unit = s[7] + jfif_density = i16(s, 8), i16(s, 10) + except Exception: + pass + else: + if jfif_unit == 1: + self.info["dpi"] = jfif_density + elif jfif_unit == 2: # cm + # 1 dpcm = 2.54 dpi + self.info["dpi"] = tuple(d * 2.54 for d in jfif_density) + self.info["jfif_unit"] = jfif_unit + self.info["jfif_density"] = jfif_density + elif marker == 0xFFE1 and s.startswith(b"Exif\0\0"): + # extract EXIF information + if "exif" in self.info: + self.info["exif"] += s[6:] + else: + self.info["exif"] = s + self._exif_offset = self.fp.tell() - n + 6 + elif marker == 0xFFE1 and s.startswith(b"http://ns.adobe.com/xap/1.0/\x00"): + self.info["xmp"] = s.split(b"\x00", 1)[1] + elif marker == 0xFFE2 and s.startswith(b"FPXR\0"): + # extract FlashPix information (incomplete) + self.info["flashpix"] = s # FIXME: value will change + elif marker == 0xFFE2 and s.startswith(b"ICC_PROFILE\0"): + # Since an ICC profile can be larger than the maximum size of + # a JPEG marker (64K), we need provisions to split it into + # multiple markers. The format defined by the ICC specifies + # one or more APP2 markers containing the following data: + # Identifying string ASCII "ICC_PROFILE\0" (12 bytes) + # Marker sequence number 1, 2, etc (1 byte) + # Number of markers Total of APP2's used (1 byte) + # Profile data (remainder of APP2 data) + # Decoders should use the marker sequence numbers to + # reassemble the profile, rather than assuming that the APP2 + # markers appear in the correct sequence. + self.icclist.append(s) + elif marker == 0xFFED and s.startswith(b"Photoshop 3.0\x00"): + # parse the image resource block + offset = 14 + photoshop = self.info.setdefault("photoshop", {}) + while s[offset : offset + 4] == b"8BIM": + try: + offset += 4 + # resource code + code = i16(s, offset) + offset += 2 + # resource name (usually empty) + name_len = s[offset] + # name = s[offset+1:offset+1+name_len] + offset += 1 + name_len + offset += offset & 1 # align + # resource data block + size = i32(s, offset) + offset += 4 + data = s[offset : offset + size] + if code == 0x03ED: # ResolutionInfo + photoshop[code] = { + "XResolution": i32(data, 0) / 65536, + "DisplayedUnitsX": i16(data, 4), + "YResolution": i32(data, 8) / 65536, + "DisplayedUnitsY": i16(data, 12), + } + else: + photoshop[code] = data + offset += size + offset += offset & 1 # align + except struct.error: + break # insufficient data + + elif marker == 0xFFEE and s.startswith(b"Adobe"): + self.info["adobe"] = i16(s, 5) + # extract Adobe custom properties + try: + adobe_transform = s[11] + except IndexError: + pass + else: + self.info["adobe_transform"] = adobe_transform + elif marker == 0xFFE2 and s.startswith(b"MPF\0"): + # extract MPO information + self.info["mp"] = s[4:] + # offset is current location minus buffer size + # plus constant header size + self.info["mpoffset"] = self.fp.tell() - n + 4 + + +def COM(self: JpegImageFile, marker: int) -> None: + # + # Comment marker. Store these in the APP dictionary. + assert self.fp is not None + n = i16(self.fp.read(2)) - 2 + s = ImageFile._safe_read(self.fp, n) + + self.info["comment"] = s + self.app["COM"] = s # compatibility + self.applist.append(("COM", s)) + + +def SOF(self: JpegImageFile, marker: int) -> None: + # + # Start of frame marker. Defines the size and mode of the + # image. JPEG is colour blind, so we use some simple + # heuristics to map the number of layers to an appropriate + # mode. Note that this could be made a bit brighter, by + # looking for JFIF and Adobe APP markers. + + assert self.fp is not None + n = i16(self.fp.read(2)) - 2 + s = ImageFile._safe_read(self.fp, n) + self._size = i16(s, 3), i16(s, 1) + if self._im is not None and self.size != self.im.size: + self._im = None + + self.bits = s[0] + if self.bits != 8: + msg = f"cannot handle {self.bits}-bit layers" + raise SyntaxError(msg) + + self.layers = s[5] + if self.layers == 1: + self._mode = "L" + elif self.layers == 3: + self._mode = "RGB" + elif self.layers == 4: + self._mode = "CMYK" + else: + msg = f"cannot handle {self.layers}-layer images" + raise SyntaxError(msg) + + if marker in [0xFFC2, 0xFFC6, 0xFFCA, 0xFFCE]: + self.info["progressive"] = self.info["progression"] = 1 + + if self.icclist: + # fixup icc profile + self.icclist.sort() # sort by sequence number + if self.icclist[0][13] == len(self.icclist): + profile = [p[14:] for p in self.icclist] + icc_profile = b"".join(profile) + else: + icc_profile = None # wrong number of fragments + self.info["icc_profile"] = icc_profile + self.icclist = [] + + for i in range(6, len(s), 3): + t = s[i : i + 3] + # 4-tuples: id, vsamp, hsamp, qtable + self.layer.append((t[0], t[1] // 16, t[1] & 15, t[2])) + + +def DQT(self: JpegImageFile, marker: int) -> None: + # + # Define quantization table. Note that there might be more + # than one table in each marker. + + # FIXME: The quantization tables can be used to estimate the + # compression quality. + + assert self.fp is not None + n = i16(self.fp.read(2)) - 2 + s = ImageFile._safe_read(self.fp, n) + while len(s): + v = s[0] + precision = 1 if (v // 16 == 0) else 2 # in bytes + qt_length = 1 + precision * 64 + if len(s) < qt_length: + msg = "bad quantization table marker" + raise SyntaxError(msg) + data = array.array("B" if precision == 1 else "H", s[1:qt_length]) + if sys.byteorder == "little" and precision > 1: + data.byteswap() # the values are always big-endian + self.quantization[v & 15] = [data[i] for i in zigzag_index] + s = s[qt_length:] + + +# +# JPEG marker table + +MARKER = { + 0xFFC0: ("SOF0", "Baseline DCT", SOF), + 0xFFC1: ("SOF1", "Extended Sequential DCT", SOF), + 0xFFC2: ("SOF2", "Progressive DCT", SOF), + 0xFFC3: ("SOF3", "Spatial lossless", SOF), + 0xFFC4: ("DHT", "Define Huffman table", Skip), + 0xFFC5: ("SOF5", "Differential sequential DCT", SOF), + 0xFFC6: ("SOF6", "Differential progressive DCT", SOF), + 0xFFC7: ("SOF7", "Differential spatial", SOF), + 0xFFC8: ("JPG", "Extension", None), + 0xFFC9: ("SOF9", "Extended sequential DCT (AC)", SOF), + 0xFFCA: ("SOF10", "Progressive DCT (AC)", SOF), + 0xFFCB: ("SOF11", "Spatial lossless DCT (AC)", SOF), + 0xFFCC: ("DAC", "Define arithmetic coding conditioning", Skip), + 0xFFCD: ("SOF13", "Differential sequential DCT (AC)", SOF), + 0xFFCE: ("SOF14", "Differential progressive DCT (AC)", SOF), + 0xFFCF: ("SOF15", "Differential spatial (AC)", SOF), + 0xFFD0: ("RST0", "Restart 0", None), + 0xFFD1: ("RST1", "Restart 1", None), + 0xFFD2: ("RST2", "Restart 2", None), + 0xFFD3: ("RST3", "Restart 3", None), + 0xFFD4: ("RST4", "Restart 4", None), + 0xFFD5: ("RST5", "Restart 5", None), + 0xFFD6: ("RST6", "Restart 6", None), + 0xFFD7: ("RST7", "Restart 7", None), + 0xFFD8: ("SOI", "Start of image", None), + 0xFFD9: ("EOI", "End of image", None), + 0xFFDA: ("SOS", "Start of scan", Skip), + 0xFFDB: ("DQT", "Define quantization table", DQT), + 0xFFDC: ("DNL", "Define number of lines", Skip), + 0xFFDD: ("DRI", "Define restart interval", Skip), + 0xFFDE: ("DHP", "Define hierarchical progression", SOF), + 0xFFDF: ("EXP", "Expand reference component", Skip), + 0xFFE0: ("APP0", "Application segment 0", APP), + 0xFFE1: ("APP1", "Application segment 1", APP), + 0xFFE2: ("APP2", "Application segment 2", APP), + 0xFFE3: ("APP3", "Application segment 3", APP), + 0xFFE4: ("APP4", "Application segment 4", APP), + 0xFFE5: ("APP5", "Application segment 5", APP), + 0xFFE6: ("APP6", "Application segment 6", APP), + 0xFFE7: ("APP7", "Application segment 7", APP), + 0xFFE8: ("APP8", "Application segment 8", APP), + 0xFFE9: ("APP9", "Application segment 9", APP), + 0xFFEA: ("APP10", "Application segment 10", APP), + 0xFFEB: ("APP11", "Application segment 11", APP), + 0xFFEC: ("APP12", "Application segment 12", APP), + 0xFFED: ("APP13", "Application segment 13", APP), + 0xFFEE: ("APP14", "Application segment 14", APP), + 0xFFEF: ("APP15", "Application segment 15", APP), + 0xFFF0: ("JPG0", "Extension 0", None), + 0xFFF1: ("JPG1", "Extension 1", None), + 0xFFF2: ("JPG2", "Extension 2", None), + 0xFFF3: ("JPG3", "Extension 3", None), + 0xFFF4: ("JPG4", "Extension 4", None), + 0xFFF5: ("JPG5", "Extension 5", None), + 0xFFF6: ("JPG6", "Extension 6", None), + 0xFFF7: ("JPG7", "Extension 7", None), + 0xFFF8: ("JPG8", "Extension 8", None), + 0xFFF9: ("JPG9", "Extension 9", None), + 0xFFFA: ("JPG10", "Extension 10", None), + 0xFFFB: ("JPG11", "Extension 11", None), + 0xFFFC: ("JPG12", "Extension 12", None), + 0xFFFD: ("JPG13", "Extension 13", None), + 0xFFFE: ("COM", "Comment", COM), +} + + +def _accept(prefix: bytes) -> bool: + # Magic number was taken from https://en.wikipedia.org/wiki/JPEG + return prefix.startswith(b"\xff\xd8\xff") + + +## +# Image plugin for JPEG and JFIF images. + + +class JpegImageFile(ImageFile.ImageFile): + format = "JPEG" + format_description = "JPEG (ISO 10918)" + + def _open(self) -> None: + assert self.fp is not None + s = self.fp.read(3) + + if not _accept(s): + msg = "not a JPEG file" + raise SyntaxError(msg) + s = b"\xff" + + # Create attributes + self.bits = self.layers = 0 + self._exif_offset = 0 + + # JPEG specifics (internal) + self.layer: list[tuple[int, int, int, int]] = [] + self._huffman_dc: dict[Any, Any] = {} + self._huffman_ac: dict[Any, Any] = {} + self.quantization: dict[int, list[int]] = {} + self.app: dict[str, bytes] = {} # compatibility + self.applist: list[tuple[str, bytes]] = [] + self.icclist: list[bytes] = [] + + while True: + i = s[0] + if i == 0xFF: + s = s + self.fp.read(1) + i = i16(s) + else: + # Skip non-0xFF junk + s = self.fp.read(1) + continue + + if i in MARKER: + name, description, handler = MARKER[i] + if handler is not None: + handler(self, i) + if i == 0xFFDA: # start of scan + rawmode = self.mode + if self.mode == "CMYK": + rawmode = "CMYK;I" # assume adobe conventions + self.tile = [ + ImageFile._Tile("jpeg", (0, 0) + self.size, 0, (rawmode, "")) + ] + # self.__offset = self.fp.tell() + break + s = self.fp.read(1) + elif i in {0, 0xFFFF}: + # padded marker or junk; move on + s = b"\xff" + elif i == 0xFF00: # Skip extraneous data (escaped 0xFF) + s = self.fp.read(1) + else: + msg = "no marker found" + raise SyntaxError(msg) + + self._read_dpi_from_exif() + + def __getstate__(self) -> list[Any]: + return super().__getstate__() + [self.layers, self.layer] + + def __setstate__(self, state: list[Any]) -> None: + self.layers, self.layer = state[6:] + super().__setstate__(state) + + def load_read(self, read_bytes: int) -> bytes: + """ + internal: read more image data + For premature EOF and LOAD_TRUNCATED_IMAGES adds EOI marker + so libjpeg can finish decoding + """ + assert self.fp is not None + s = self.fp.read(read_bytes) + + if not s and ImageFile.LOAD_TRUNCATED_IMAGES and not hasattr(self, "_ended"): + # Premature EOF. + # Pretend file is finished adding EOI marker + self._ended = True + return b"\xff\xd9" + + return s + + def draft( + self, mode: str | None, size: tuple[int, int] | None + ) -> tuple[str, tuple[int, int, float, float]] | None: + if len(self.tile) != 1: + return None + + # Protect from second call + if self.decoderconfig: + return None + + d, e, o, a = self.tile[0] + scale = 1 + original_size = self.size + + assert isinstance(a, tuple) + if a[0] == "RGB" and mode in ["L", "YCbCr"]: + self._mode = mode + a = mode, "" + + if size: + scale = min(self.size[0] // size[0], self.size[1] // size[1]) + for s in [8, 4, 2, 1]: + if scale >= s: + break + assert e is not None + e = ( + e[0], + e[1], + (e[2] - e[0] + s - 1) // s + e[0], + (e[3] - e[1] + s - 1) // s + e[1], + ) + self._size = ((self.size[0] + s - 1) // s, (self.size[1] + s - 1) // s) + scale = s + + self.tile = [ImageFile._Tile(d, e, o, a)] + self.decoderconfig = (scale, 0) + + box = (0, 0, original_size[0] / scale, original_size[1] / scale) + return self.mode, box + + def load_djpeg(self) -> None: + # ALTERNATIVE: handle JPEGs via the IJG command line utilities + + f, path = tempfile.mkstemp() + os.close(f) + if os.path.exists(self.filename): + subprocess.check_call(["djpeg", "-outfile", path, self.filename]) + else: + try: + os.unlink(path) + except OSError: + pass + + msg = "Invalid Filename" + raise ValueError(msg) + + try: + with Image.open(path) as _im: + _im.load() + self.im = _im.im + finally: + try: + os.unlink(path) + except OSError: + pass + + self._mode = self.im.mode + self._size = self.im.size + + self.tile = [] + + def _getexif(self) -> dict[int, Any] | None: + return _getexif(self) + + def _read_dpi_from_exif(self) -> None: + # If DPI isn't in JPEG header, fetch from EXIF + if "dpi" in self.info or "exif" not in self.info: + return + try: + exif = self.getexif() + resolution_unit = exif[0x0128] + x_resolution = exif[0x011A] + try: + dpi = float(x_resolution[0]) / x_resolution[1] + except TypeError: + dpi = x_resolution + if math.isnan(dpi): + msg = "DPI is not a number" + raise ValueError(msg) + if resolution_unit == 3: # cm + # 1 dpcm = 2.54 dpi + dpi *= 2.54 + self.info["dpi"] = dpi, dpi + except ( + struct.error, # truncated EXIF + KeyError, # dpi not included + SyntaxError, # invalid/unreadable EXIF + TypeError, # dpi is an invalid float + ValueError, # dpi is an invalid float + ZeroDivisionError, # invalid dpi rational value + ): + self.info["dpi"] = 72, 72 + + def _getmp(self) -> dict[int, Any] | None: + return _getmp(self) + + +def _getexif(self: JpegImageFile) -> dict[int, Any] | None: + if "exif" not in self.info: + return None + return self.getexif()._get_merged_dict() + + +def _getmp(self: JpegImageFile) -> dict[int, Any] | None: + # Extract MP information. This method was inspired by the "highly + # experimental" _getexif version that's been in use for years now, + # itself based on the ImageFileDirectory class in the TIFF plugin. + + # The MP record essentially consists of a TIFF file embedded in a JPEG + # application marker. + try: + data = self.info["mp"] + except KeyError: + return None + file_contents = io.BytesIO(data) + head = file_contents.read(8) + endianness = ">" if head.startswith(b"\x4d\x4d\x00\x2a") else "<" + # process dictionary + from . import TiffImagePlugin + + try: + info = TiffImagePlugin.ImageFileDirectory_v2(head) + file_contents.seek(info.next) + info.load(file_contents) + mp = dict(info) + except Exception as e: + msg = "malformed MP Index (unreadable directory)" + raise SyntaxError(msg) from e + # it's an error not to have a number of images + try: + quant = mp[0xB001] + except KeyError as e: + msg = "malformed MP Index (no number of images)" + raise SyntaxError(msg) from e + # get MP entries + mpentries = [] + try: + rawmpentries = mp[0xB002] + for entrynum in range(quant): + unpackedentry = struct.unpack_from( + f"{endianness}LLLHH", rawmpentries, entrynum * 16 + ) + labels = ("Attribute", "Size", "DataOffset", "EntryNo1", "EntryNo2") + mpentry = dict(zip(labels, unpackedentry)) + mpentryattr = { + "DependentParentImageFlag": bool(mpentry["Attribute"] & (1 << 31)), + "DependentChildImageFlag": bool(mpentry["Attribute"] & (1 << 30)), + "RepresentativeImageFlag": bool(mpentry["Attribute"] & (1 << 29)), + "Reserved": (mpentry["Attribute"] & (3 << 27)) >> 27, + "ImageDataFormat": (mpentry["Attribute"] & (7 << 24)) >> 24, + "MPType": mpentry["Attribute"] & 0x00FFFFFF, + } + if mpentryattr["ImageDataFormat"] == 0: + mpentryattr["ImageDataFormat"] = "JPEG" + else: + msg = "unsupported picture format in MPO" + raise SyntaxError(msg) + mptypemap = { + 0x000000: "Undefined", + 0x010001: "Large Thumbnail (VGA Equivalent)", + 0x010002: "Large Thumbnail (Full HD Equivalent)", + 0x020001: "Multi-Frame Image (Panorama)", + 0x020002: "Multi-Frame Image: (Disparity)", + 0x020003: "Multi-Frame Image: (Multi-Angle)", + 0x030000: "Baseline MP Primary Image", + } + mpentryattr["MPType"] = mptypemap.get(mpentryattr["MPType"], "Unknown") + mpentry["Attribute"] = mpentryattr + mpentries.append(mpentry) + mp[0xB002] = mpentries + except KeyError as e: + msg = "malformed MP Index (bad MP Entry)" + raise SyntaxError(msg) from e + # Next we should try and parse the individual image unique ID list; + # we don't because I've never seen this actually used in a real MPO + # file and so can't test it. + return mp + + +# -------------------------------------------------------------------- +# stuff to save JPEG files + +RAWMODE = { + "1": "L", + "L": "L", + "RGB": "RGB", + "RGBX": "RGB", + "CMYK": "CMYK;I", # assume adobe conventions + "YCbCr": "YCbCr", +} + +# fmt: off +zigzag_index = ( + 0, 1, 5, 6, 14, 15, 27, 28, + 2, 4, 7, 13, 16, 26, 29, 42, + 3, 8, 12, 17, 25, 30, 41, 43, + 9, 11, 18, 24, 31, 40, 44, 53, + 10, 19, 23, 32, 39, 45, 52, 54, + 20, 22, 33, 38, 46, 51, 55, 60, + 21, 34, 37, 47, 50, 56, 59, 61, + 35, 36, 48, 49, 57, 58, 62, 63, +) + +samplings = { + (1, 1, 1, 1, 1, 1): 0, + (2, 1, 1, 1, 1, 1): 1, + (2, 2, 1, 1, 1, 1): 2, +} +# fmt: on + + +def get_sampling(im: Image.Image) -> int: + # There's no subsampling when images have only 1 layer + # (grayscale images) or when they are CMYK (4 layers), + # so set subsampling to the default value. + # + # NOTE: currently Pillow can't encode JPEG to YCCK format. + # If YCCK support is added in the future, subsampling code will have + # to be updated (here and in JpegEncode.c) to deal with 4 layers. + if not isinstance(im, JpegImageFile) or im.layers in (1, 4): + return -1 + sampling = im.layer[0][1:3] + im.layer[1][1:3] + im.layer[2][1:3] + return samplings.get(sampling, -1) + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + if im.width == 0 or im.height == 0: + msg = "cannot write empty image as JPEG" + raise ValueError(msg) + + try: + rawmode = RAWMODE[im.mode] + except KeyError as e: + msg = f"cannot write mode {im.mode} as JPEG" + raise OSError(msg) from e + + info = im.encoderinfo + + dpi = [round(x) for x in info.get("dpi", (0, 0))] + + quality = info.get("quality", -1) + subsampling = info.get("subsampling", -1) + qtables = info.get("qtables") + + if quality == "keep": + quality = -1 + subsampling = "keep" + qtables = "keep" + elif quality in presets: + preset = presets[quality] + quality = -1 + subsampling = preset.get("subsampling", -1) + qtables = preset.get("quantization") + elif not isinstance(quality, int): + msg = "Invalid quality setting" + raise ValueError(msg) + else: + if subsampling in presets: + subsampling = presets[subsampling].get("subsampling", -1) + if isinstance(qtables, str) and qtables in presets: + qtables = presets[qtables].get("quantization") + + if subsampling == "4:4:4": + subsampling = 0 + elif subsampling == "4:2:2": + subsampling = 1 + elif subsampling == "4:2:0": + subsampling = 2 + elif subsampling == "4:1:1": + # For compatibility. Before Pillow 4.3, 4:1:1 actually meant 4:2:0. + # Set 4:2:0 if someone is still using that value. + subsampling = 2 + elif subsampling == "keep": + if im.format != "JPEG": + msg = "Cannot use 'keep' when original image is not a JPEG" + raise ValueError(msg) + subsampling = get_sampling(im) + + def validate_qtables( + qtables: ( + str | tuple[list[int], ...] | list[list[int]] | dict[int, list[int]] | None + ), + ) -> list[list[int]] | None: + if qtables is None: + return qtables + if isinstance(qtables, str): + try: + lines = [ + int(num) + for line in qtables.splitlines() + for num in line.split("#", 1)[0].split() + ] + except ValueError as e: + msg = "Invalid quantization table" + raise ValueError(msg) from e + else: + qtables = [lines[s : s + 64] for s in range(0, len(lines), 64)] + if isinstance(qtables, (tuple, list, dict)): + if isinstance(qtables, dict): + qtables = [ + qtables[key] for key in range(len(qtables)) if key in qtables + ] + elif isinstance(qtables, tuple): + qtables = list(qtables) + if not (0 < len(qtables) < 5): + msg = "None or too many quantization tables" + raise ValueError(msg) + for idx, table in enumerate(qtables): + try: + if len(table) != 64: + msg = "Invalid quantization table" + raise TypeError(msg) + table_array = array.array("H", table) + except TypeError as e: + msg = "Invalid quantization table" + raise ValueError(msg) from e + else: + qtables[idx] = list(table_array) + return qtables + + if qtables == "keep": + if im.format != "JPEG": + msg = "Cannot use 'keep' when original image is not a JPEG" + raise ValueError(msg) + qtables = getattr(im, "quantization", None) + qtables = validate_qtables(qtables) + + extra = info.get("extra", b"") + + MAX_BYTES_IN_MARKER = 65533 + if xmp := info.get("xmp"): + overhead_len = 29 # b"http://ns.adobe.com/xap/1.0/\x00" + max_data_bytes_in_marker = MAX_BYTES_IN_MARKER - overhead_len + if len(xmp) > max_data_bytes_in_marker: + msg = "XMP data is too long" + raise ValueError(msg) + size = o16(2 + overhead_len + len(xmp)) + extra += b"\xff\xe1" + size + b"http://ns.adobe.com/xap/1.0/\x00" + xmp + + if icc_profile := info.get("icc_profile"): + overhead_len = 14 # b"ICC_PROFILE\0" + o8(i) + o8(len(markers)) + max_data_bytes_in_marker = MAX_BYTES_IN_MARKER - overhead_len + markers = [] + while icc_profile: + markers.append(icc_profile[:max_data_bytes_in_marker]) + icc_profile = icc_profile[max_data_bytes_in_marker:] + i = 1 + for marker in markers: + size = o16(2 + overhead_len + len(marker)) + extra += ( + b"\xff\xe2" + + size + + b"ICC_PROFILE\0" + + o8(i) + + o8(len(markers)) + + marker + ) + i += 1 + + comment = info.get("comment", im.info.get("comment")) + + # "progressive" is the official name, but older documentation + # says "progression" + # FIXME: issue a warning if the wrong form is used (post-1.1.7) + progressive = info.get("progressive", False) or info.get("progression", False) + + optimize = info.get("optimize", False) + + exif = info.get("exif", b"") + if isinstance(exif, Image.Exif): + exif = exif.tobytes() + if len(exif) > MAX_BYTES_IN_MARKER: + msg = "EXIF data is too long" + raise ValueError(msg) + + # get keyword arguments + im.encoderconfig = ( + quality, + progressive, + info.get("smooth", 0), + optimize, + info.get("keep_rgb", False), + info.get("streamtype", 0), + dpi, + subsampling, + info.get("restart_marker_blocks", 0), + info.get("restart_marker_rows", 0), + qtables, + comment, + extra, + exif, + ) + + # if we optimize, libjpeg needs a buffer big enough to hold the whole image + # in a shot. Guessing on the size, at im.size bytes. (raw pixel size is + # channels*size, this is a value that's been used in a django patch. + # https://github.com/matthewwithanm/django-imagekit/issues/50 + if optimize or progressive: + # CMYK can be bigger + if im.mode == "CMYK": + bufsize = 4 * im.size[0] * im.size[1] + # keep sets quality to -1, but the actual value may be high. + elif quality >= 95 or quality == -1: + bufsize = 2 * im.size[0] * im.size[1] + else: + bufsize = im.size[0] * im.size[1] + if exif: + bufsize += len(exif) + 5 + if extra: + bufsize += len(extra) + 1 + else: + # The EXIF info needs to be written as one block, + APP1, + one spare byte. + # Ensure that our buffer is big enough. Same with the icc_profile block. + bufsize = max(len(exif) + 5, len(extra) + 1) + + ImageFile._save( + im, fp, [ImageFile._Tile("jpeg", (0, 0) + im.size, 0, rawmode)], bufsize + ) + + +## +# Factory for making JPEG and MPO instances +def jpeg_factory( + fp: IO[bytes], filename: str | bytes | None = None +) -> JpegImageFile | MpoImageFile: + im = JpegImageFile(fp, filename) + try: + mpheader = im._getmp() + if mpheader is not None and mpheader[45057] > 1: + for segment, content in im.applist: + if segment == "APP1" and b' hdrgm:Version="' in content: + # Ultra HDR images are not yet supported + return im + # It's actually an MPO + from .MpoImagePlugin import MpoImageFile + + # Don't reload everything, just convert it. + im = MpoImageFile.adopt(im, mpheader) + except (TypeError, IndexError): + # It is really a JPEG + pass + except SyntaxError: + warnings.warn( + "Image appears to be a malformed MPO file, it will be " + "interpreted as a base JPEG file" + ) + return im + + +# --------------------------------------------------------------------- +# Registry stuff + +Image.register_open(JpegImageFile.format, jpeg_factory, _accept) +Image.register_save(JpegImageFile.format, _save) + +Image.register_extensions(JpegImageFile.format, [".jfif", ".jpe", ".jpg", ".jpeg"]) + +Image.register_mime(JpegImageFile.format, "image/jpeg") diff --git a/PIL/JpegPresets.py b/PIL/JpegPresets.py new file mode 100644 index 0000000000000000000000000000000000000000..d0e64a35ee1b6fe3ac6da792682a3129253993bb --- /dev/null +++ b/PIL/JpegPresets.py @@ -0,0 +1,242 @@ +""" +JPEG quality settings equivalent to the Photoshop settings. +Can be used when saving JPEG files. + +The following presets are available by default: +``web_low``, ``web_medium``, ``web_high``, ``web_very_high``, ``web_maximum``, +``low``, ``medium``, ``high``, ``maximum``. +More presets can be added to the :py:data:`presets` dict if needed. + +To apply the preset, specify:: + + quality="preset_name" + +To apply only the quantization table:: + + qtables="preset_name" + +To apply only the subsampling setting:: + + subsampling="preset_name" + +Example:: + + im.save("image_name.jpg", quality="web_high") + +Subsampling +----------- + +Subsampling is the practice of encoding images by implementing less resolution +for chroma information than for luma information. +(ref.: https://en.wikipedia.org/wiki/Chroma_subsampling) + +Possible subsampling values are 0, 1 and 2 that correspond to 4:4:4, 4:2:2 and +4:2:0. + +You can get the subsampling of a JPEG with the +:func:`.JpegImagePlugin.get_sampling` function. + +In JPEG compressed data a JPEG marker is used instead of an EXIF tag. +(ref.: https://exiv2.org/tags.html) + + +Quantization tables +------------------- + +They are values use by the DCT (Discrete cosine transform) to remove +*unnecessary* information from the image (the lossy part of the compression). +(ref.: https://en.wikipedia.org/wiki/Quantization_matrix#Quantization_matrices, +https://en.wikipedia.org/wiki/JPEG#Quantization) + +You can get the quantization tables of a JPEG with:: + + im.quantization + +This will return a dict with a number of lists. You can pass this dict +directly as the qtables argument when saving a JPEG. + +The quantization table format in presets is a list with sublists. These formats +are interchangeable. + +Libjpeg ref.: +https://web.archive.org/web/20120328125543/http://www.jpegcameras.com/libjpeg/libjpeg-3.html + +""" + +from __future__ import annotations + +# fmt: off +presets = { + 'web_low': {'subsampling': 2, # "4:2:0" + 'quantization': [ + [20, 16, 25, 39, 50, 46, 62, 68, + 16, 18, 23, 38, 38, 53, 65, 68, + 25, 23, 31, 38, 53, 65, 68, 68, + 39, 38, 38, 53, 65, 68, 68, 68, + 50, 38, 53, 65, 68, 68, 68, 68, + 46, 53, 65, 68, 68, 68, 68, 68, + 62, 65, 68, 68, 68, 68, 68, 68, + 68, 68, 68, 68, 68, 68, 68, 68], + [21, 25, 32, 38, 54, 68, 68, 68, + 25, 28, 24, 38, 54, 68, 68, 68, + 32, 24, 32, 43, 66, 68, 68, 68, + 38, 38, 43, 53, 68, 68, 68, 68, + 54, 54, 66, 68, 68, 68, 68, 68, + 68, 68, 68, 68, 68, 68, 68, 68, + 68, 68, 68, 68, 68, 68, 68, 68, + 68, 68, 68, 68, 68, 68, 68, 68] + ]}, + 'web_medium': {'subsampling': 2, # "4:2:0" + 'quantization': [ + [16, 11, 11, 16, 23, 27, 31, 30, + 11, 12, 12, 15, 20, 23, 23, 30, + 11, 12, 13, 16, 23, 26, 35, 47, + 16, 15, 16, 23, 26, 37, 47, 64, + 23, 20, 23, 26, 39, 51, 64, 64, + 27, 23, 26, 37, 51, 64, 64, 64, + 31, 23, 35, 47, 64, 64, 64, 64, + 30, 30, 47, 64, 64, 64, 64, 64], + [17, 15, 17, 21, 20, 26, 38, 48, + 15, 19, 18, 17, 20, 26, 35, 43, + 17, 18, 20, 22, 26, 30, 46, 53, + 21, 17, 22, 28, 30, 39, 53, 64, + 20, 20, 26, 30, 39, 48, 64, 64, + 26, 26, 30, 39, 48, 63, 64, 64, + 38, 35, 46, 53, 64, 64, 64, 64, + 48, 43, 53, 64, 64, 64, 64, 64] + ]}, + 'web_high': {'subsampling': 0, # "4:4:4" + 'quantization': [ + [6, 4, 4, 6, 9, 11, 12, 16, + 4, 5, 5, 6, 8, 10, 12, 12, + 4, 5, 5, 6, 10, 12, 14, 19, + 6, 6, 6, 11, 12, 15, 19, 28, + 9, 8, 10, 12, 16, 20, 27, 31, + 11, 10, 12, 15, 20, 27, 31, 31, + 12, 12, 14, 19, 27, 31, 31, 31, + 16, 12, 19, 28, 31, 31, 31, 31], + [7, 7, 13, 24, 26, 31, 31, 31, + 7, 12, 16, 21, 31, 31, 31, 31, + 13, 16, 17, 31, 31, 31, 31, 31, + 24, 21, 31, 31, 31, 31, 31, 31, + 26, 31, 31, 31, 31, 31, 31, 31, + 31, 31, 31, 31, 31, 31, 31, 31, + 31, 31, 31, 31, 31, 31, 31, 31, + 31, 31, 31, 31, 31, 31, 31, 31] + ]}, + 'web_very_high': {'subsampling': 0, # "4:4:4" + 'quantization': [ + [2, 2, 2, 2, 3, 4, 5, 6, + 2, 2, 2, 2, 3, 4, 5, 6, + 2, 2, 2, 2, 4, 5, 7, 9, + 2, 2, 2, 4, 5, 7, 9, 12, + 3, 3, 4, 5, 8, 10, 12, 12, + 4, 4, 5, 7, 10, 12, 12, 12, + 5, 5, 7, 9, 12, 12, 12, 12, + 6, 6, 9, 12, 12, 12, 12, 12], + [3, 3, 5, 9, 13, 15, 15, 15, + 3, 4, 6, 11, 14, 12, 12, 12, + 5, 6, 9, 14, 12, 12, 12, 12, + 9, 11, 14, 12, 12, 12, 12, 12, + 13, 14, 12, 12, 12, 12, 12, 12, + 15, 12, 12, 12, 12, 12, 12, 12, + 15, 12, 12, 12, 12, 12, 12, 12, + 15, 12, 12, 12, 12, 12, 12, 12] + ]}, + 'web_maximum': {'subsampling': 0, # "4:4:4" + 'quantization': [ + [1, 1, 1, 1, 1, 1, 1, 1, + 1, 1, 1, 1, 1, 1, 1, 1, + 1, 1, 1, 1, 1, 1, 1, 2, + 1, 1, 1, 1, 1, 1, 2, 2, + 1, 1, 1, 1, 1, 2, 2, 3, + 1, 1, 1, 1, 2, 2, 3, 3, + 1, 1, 1, 2, 2, 3, 3, 3, + 1, 1, 2, 2, 3, 3, 3, 3], + [1, 1, 1, 2, 2, 3, 3, 3, + 1, 1, 1, 2, 3, 3, 3, 3, + 1, 1, 1, 3, 3, 3, 3, 3, + 2, 2, 3, 3, 3, 3, 3, 3, + 2, 3, 3, 3, 3, 3, 3, 3, + 3, 3, 3, 3, 3, 3, 3, 3, + 3, 3, 3, 3, 3, 3, 3, 3, + 3, 3, 3, 3, 3, 3, 3, 3] + ]}, + 'low': {'subsampling': 2, # "4:2:0" + 'quantization': [ + [18, 14, 14, 21, 30, 35, 34, 17, + 14, 16, 16, 19, 26, 23, 12, 12, + 14, 16, 17, 21, 23, 12, 12, 12, + 21, 19, 21, 23, 12, 12, 12, 12, + 30, 26, 23, 12, 12, 12, 12, 12, + 35, 23, 12, 12, 12, 12, 12, 12, + 34, 12, 12, 12, 12, 12, 12, 12, + 17, 12, 12, 12, 12, 12, 12, 12], + [20, 19, 22, 27, 20, 20, 17, 17, + 19, 25, 23, 14, 14, 12, 12, 12, + 22, 23, 14, 14, 12, 12, 12, 12, + 27, 14, 14, 12, 12, 12, 12, 12, + 20, 14, 12, 12, 12, 12, 12, 12, + 20, 12, 12, 12, 12, 12, 12, 12, + 17, 12, 12, 12, 12, 12, 12, 12, + 17, 12, 12, 12, 12, 12, 12, 12] + ]}, + 'medium': {'subsampling': 2, # "4:2:0" + 'quantization': [ + [12, 8, 8, 12, 17, 21, 24, 17, + 8, 9, 9, 11, 15, 19, 12, 12, + 8, 9, 10, 12, 19, 12, 12, 12, + 12, 11, 12, 21, 12, 12, 12, 12, + 17, 15, 19, 12, 12, 12, 12, 12, + 21, 19, 12, 12, 12, 12, 12, 12, + 24, 12, 12, 12, 12, 12, 12, 12, + 17, 12, 12, 12, 12, 12, 12, 12], + [13, 11, 13, 16, 20, 20, 17, 17, + 11, 14, 14, 14, 14, 12, 12, 12, + 13, 14, 14, 14, 12, 12, 12, 12, + 16, 14, 14, 12, 12, 12, 12, 12, + 20, 14, 12, 12, 12, 12, 12, 12, + 20, 12, 12, 12, 12, 12, 12, 12, + 17, 12, 12, 12, 12, 12, 12, 12, + 17, 12, 12, 12, 12, 12, 12, 12] + ]}, + 'high': {'subsampling': 0, # "4:4:4" + 'quantization': [ + [6, 4, 4, 6, 9, 11, 12, 16, + 4, 5, 5, 6, 8, 10, 12, 12, + 4, 5, 5, 6, 10, 12, 12, 12, + 6, 6, 6, 11, 12, 12, 12, 12, + 9, 8, 10, 12, 12, 12, 12, 12, + 11, 10, 12, 12, 12, 12, 12, 12, + 12, 12, 12, 12, 12, 12, 12, 12, + 16, 12, 12, 12, 12, 12, 12, 12], + [7, 7, 13, 24, 20, 20, 17, 17, + 7, 12, 16, 14, 14, 12, 12, 12, + 13, 16, 14, 14, 12, 12, 12, 12, + 24, 14, 14, 12, 12, 12, 12, 12, + 20, 14, 12, 12, 12, 12, 12, 12, + 20, 12, 12, 12, 12, 12, 12, 12, + 17, 12, 12, 12, 12, 12, 12, 12, + 17, 12, 12, 12, 12, 12, 12, 12] + ]}, + 'maximum': {'subsampling': 0, # "4:4:4" + 'quantization': [ + [2, 2, 2, 2, 3, 4, 5, 6, + 2, 2, 2, 2, 3, 4, 5, 6, + 2, 2, 2, 2, 4, 5, 7, 9, + 2, 2, 2, 4, 5, 7, 9, 12, + 3, 3, 4, 5, 8, 10, 12, 12, + 4, 4, 5, 7, 10, 12, 12, 12, + 5, 5, 7, 9, 12, 12, 12, 12, + 6, 6, 9, 12, 12, 12, 12, 12], + [3, 3, 5, 9, 13, 15, 15, 15, + 3, 4, 6, 10, 14, 12, 12, 12, + 5, 6, 9, 14, 12, 12, 12, 12, + 9, 10, 14, 12, 12, 12, 12, 12, + 13, 14, 12, 12, 12, 12, 12, 12, + 15, 12, 12, 12, 12, 12, 12, 12, + 15, 12, 12, 12, 12, 12, 12, 12, + 15, 12, 12, 12, 12, 12, 12, 12] + ]}, +} +# fmt: on diff --git a/PIL/McIdasImagePlugin.py b/PIL/McIdasImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..9a47933b69cbdc628faafb67b2fca8de703abfc1 --- /dev/null +++ b/PIL/McIdasImagePlugin.py @@ -0,0 +1,78 @@ +# +# The Python Imaging Library. +# $Id$ +# +# Basic McIdas support for PIL +# +# History: +# 1997-05-05 fl Created (8-bit images only) +# 2009-03-08 fl Added 16/32-bit support. +# +# Thanks to Richard Jones and Craig Swank for specs and samples. +# +# Copyright (c) Secret Labs AB 1997. +# Copyright (c) Fredrik Lundh 1997. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import struct + +from . import Image, ImageFile + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith(b"\x00\x00\x00\x00\x00\x00\x00\x04") + + +## +# Image plugin for McIdas area images. + + +class McIdasImageFile(ImageFile.ImageFile): + format = "MCIDAS" + format_description = "McIdas area file" + + def _open(self) -> None: + # parse area file directory + assert self.fp is not None + + s = self.fp.read(256) + if not _accept(s) or len(s) != 256: + msg = "not an McIdas area file" + raise SyntaxError(msg) + + self.area_descriptor_raw = s + self.area_descriptor = w = [0, *struct.unpack("!64i", s)] + + # get mode + if w[11] == 1: + mode = rawmode = "L" + elif w[11] == 2: + mode = rawmode = "I;16B" + elif w[11] == 4: + # FIXME: add memory map support + mode = "I" + rawmode = "I;32B" + else: + msg = "unsupported McIdas format" + raise SyntaxError(msg) + + self._mode = mode + self._size = w[10], w[9] + + offset = w[34] + w[15] + stride = w[15] + w[10] * w[11] * w[14] + + self.tile = [ + ImageFile._Tile("raw", (0, 0) + self.size, offset, (rawmode, stride, 1)) + ] + + +# -------------------------------------------------------------------- +# registry + +Image.register_open(McIdasImageFile.format, McIdasImageFile, _accept) + +# no default extension diff --git a/PIL/MicImagePlugin.py b/PIL/MicImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..99a07bae02cc10dfd3dc868ae0a46b9a36838665 --- /dev/null +++ b/PIL/MicImagePlugin.py @@ -0,0 +1,103 @@ +# +# The Python Imaging Library. +# $Id$ +# +# Microsoft Image Composer support for PIL +# +# Notes: +# uses TiffImagePlugin.py to read the actual image streams +# +# History: +# 97-01-20 fl Created +# +# Copyright (c) Secret Labs AB 1997. +# Copyright (c) Fredrik Lundh 1997. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import olefile + +from . import Image, TiffImagePlugin + +# +# -------------------------------------------------------------------- + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith(olefile.MAGIC) + + +## +# Image plugin for Microsoft's Image Composer file format. + + +class MicImageFile(TiffImagePlugin.TiffImageFile): + format = "MIC" + format_description = "Microsoft Image Composer" + _close_exclusive_fp_after_loading = False + + def _open(self) -> None: + # read the OLE directory and see if this is a likely + # to be a Microsoft Image Composer file + + try: + self.ole = olefile.OleFileIO(self.fp) + except OSError as e: + msg = "not an MIC file; invalid OLE file" + raise SyntaxError(msg) from e + + # find ACI subfiles with Image members (maybe not the + # best way to identify MIC files, but what the... ;-) + + self.images = [ + path + for path in self.ole.listdir() + if path[1:] and path[0].endswith(".ACI") and path[1] == "Image" + ] + + # if we didn't find any images, this is probably not + # an MIC file. + if not self.images: + msg = "not an MIC file; no image entries" + raise SyntaxError(msg) + + self.frame = -1 + self._n_frames = len(self.images) + self.is_animated = self._n_frames > 1 + + assert self.fp is not None + self.__fp = self.fp + self.seek(0) + + def seek(self, frame: int) -> None: + if not self._seek_check(frame): + return + filename = self.images[frame] + self.fp = self.ole.openstream(filename) + + TiffImagePlugin.TiffImageFile._open(self) + + self.frame = frame + + def tell(self) -> int: + return self.frame + + def close(self) -> None: + self.__fp.close() + self.ole.close() + super().close() + + def __exit__(self, *args: object) -> None: + self.__fp.close() + self.ole.close() + super().__exit__() + + +# +# -------------------------------------------------------------------- + +Image.register_open(MicImageFile.format, MicImageFile, _accept) + +Image.register_extension(MicImageFile.format, ".mic") diff --git a/PIL/MpegImagePlugin.py b/PIL/MpegImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..47ebe9d62c4edd3b5e97f760ff7e9b0417e5b5ab --- /dev/null +++ b/PIL/MpegImagePlugin.py @@ -0,0 +1,84 @@ +# +# The Python Imaging Library. +# $Id$ +# +# MPEG file handling +# +# History: +# 95-09-09 fl Created +# +# Copyright (c) Secret Labs AB 1997. +# Copyright (c) Fredrik Lundh 1995. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +from . import Image, ImageFile +from ._binary import i8 +from ._typing import SupportsRead + +# +# Bitstream parser + + +class BitStream: + def __init__(self, fp: SupportsRead[bytes]) -> None: + self.fp = fp + self.bits = 0 + self.bitbuffer = 0 + + def next(self) -> int: + return i8(self.fp.read(1)) + + def peek(self, bits: int) -> int: + while self.bits < bits: + self.bitbuffer = (self.bitbuffer << 8) + self.next() + self.bits += 8 + return self.bitbuffer >> (self.bits - bits) & (1 << bits) - 1 + + def skip(self, bits: int) -> None: + while self.bits < bits: + self.bitbuffer = (self.bitbuffer << 8) + i8(self.fp.read(1)) + self.bits += 8 + self.bits = self.bits - bits + + def read(self, bits: int) -> int: + v = self.peek(bits) + self.bits = self.bits - bits + return v + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith(b"\x00\x00\x01\xb3") + + +## +# Image plugin for MPEG streams. This plugin can identify a stream, +# but it cannot read it. + + +class MpegImageFile(ImageFile.ImageFile): + format = "MPEG" + format_description = "MPEG" + + def _open(self) -> None: + assert self.fp is not None + + s = BitStream(self.fp) + if s.read(32) != 0x1B3: + msg = "not an MPEG file" + raise SyntaxError(msg) + + self._mode = "RGB" + self._size = s.read(12), s.read(12) + + +# -------------------------------------------------------------------- +# Registry stuff + +Image.register_open(MpegImageFile.format, MpegImageFile, _accept) + +Image.register_extensions(MpegImageFile.format, [".mpg", ".mpeg"]) + +Image.register_mime(MpegImageFile.format, "video/mpeg") diff --git a/PIL/MpoImagePlugin.py b/PIL/MpoImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..9360061ba1850125f40255919d192a8ca0cbc493 --- /dev/null +++ b/PIL/MpoImagePlugin.py @@ -0,0 +1,204 @@ +# +# The Python Imaging Library. +# $Id$ +# +# MPO file handling +# +# See "Multi-Picture Format" (CIPA DC-007-Translation 2009, Standard of the +# Camera & Imaging Products Association) +# +# The multi-picture object combines multiple JPEG images (with a modified EXIF +# data format) into a single file. While it can theoretically be used much like +# a GIF animation, it is commonly used to represent 3D photographs and is (as +# of this writing) the most commonly used format by 3D cameras. +# +# History: +# 2014-03-13 Feneric Created +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import os +import struct +from typing import IO, Any, cast + +from . import ( + Image, + ImageFile, + ImageSequence, + JpegImagePlugin, + TiffImagePlugin, +) +from ._binary import o32le +from ._util import DeferredError + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + JpegImagePlugin._save(im, fp, filename) + + +def _save_all(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + append_images = im.encoderinfo.get("append_images", []) + if not append_images and not getattr(im, "is_animated", False): + _save(im, fp, filename) + return + + mpf_offset = 28 + offsets: list[int] = [] + im_sequences = [im, *append_images] + total = sum(getattr(seq, "n_frames", 1) for seq in im_sequences) + for im_sequence in im_sequences: + for im_frame in ImageSequence.Iterator(im_sequence): + if not offsets: + # APP2 marker + ifd_length = 66 + 16 * total + im_frame.encoderinfo["extra"] = ( + b"\xff\xe2" + + struct.pack(">H", 6 + ifd_length) + + b"MPF\0" + + b" " * ifd_length + ) + exif = im_frame.encoderinfo.get("exif") + if isinstance(exif, Image.Exif): + exif = exif.tobytes() + im_frame.encoderinfo["exif"] = exif + if exif: + mpf_offset += 4 + len(exif) + + JpegImagePlugin._save(im_frame, fp, filename) + offsets.append(fp.tell()) + else: + encoderinfo = im_frame._attach_default_encoderinfo(im) + im_frame.save(fp, "JPEG") + im_frame.encoderinfo = encoderinfo + offsets.append(fp.tell() - offsets[-1]) + + ifd = TiffImagePlugin.ImageFileDirectory_v2() + ifd[0xB000] = b"0100" + ifd[0xB001] = len(offsets) + + mpentries = b"" + data_offset = 0 + for i, size in enumerate(offsets): + if i == 0: + mptype = 0x030000 # Baseline MP Primary Image + else: + mptype = 0x000000 # Undefined + mpentries += struct.pack(" None: + assert self.fp is not None + self.fp.seek(0) # prep the fp in order to pass the JPEG test + JpegImagePlugin.JpegImageFile._open(self) + self._after_jpeg_open() + + def _after_jpeg_open(self, mpheader: dict[int, Any] | None = None) -> None: + self.mpinfo = mpheader if mpheader is not None else self._getmp() + if self.mpinfo is None: + msg = "Image appears to be a malformed MPO file" + raise ValueError(msg) + self.n_frames = self.mpinfo[0xB001] + self.__mpoffsets = [ + mpent["DataOffset"] + self.info["mpoffset"] for mpent in self.mpinfo[0xB002] + ] + self.__mpoffsets[0] = 0 + # Note that the following assertion will only be invalid if something + # gets broken within JpegImagePlugin. + assert self.n_frames == len(self.__mpoffsets) + del self.info["mpoffset"] # no longer needed + self.is_animated = self.n_frames > 1 + assert self.fp is not None + self._fp = self.fp # FIXME: hack + self._fp.seek(self.__mpoffsets[0]) # get ready to read first frame + self.__frame = 0 + self.offset = 0 + # for now we can only handle reading and individual frame extraction + self.readonly = 1 + + def load_seek(self, pos: int) -> None: + if isinstance(self._fp, DeferredError): + raise self._fp.ex + self._fp.seek(pos) + + def seek(self, frame: int) -> None: + if not self._seek_check(frame): + return + if isinstance(self._fp, DeferredError): + raise self._fp.ex + self.fp = self._fp + self.offset = self.__mpoffsets[frame] + + original_exif = self.info.get("exif") + if "exif" in self.info: + del self.info["exif"] + + self.fp.seek(self.offset + 2) # skip SOI marker + if not self.fp.read(2): + msg = "No data found for frame" + raise ValueError(msg) + self.fp.seek(self.offset) + JpegImagePlugin.JpegImageFile._open(self) + if self.info.get("exif") != original_exif: + self._reload_exif() + + self.tile = [ + ImageFile._Tile("jpeg", (0, 0) + self.size, self.offset, self.tile[0][-1]) + ] + self.__frame = frame + + def tell(self) -> int: + return self.__frame + + @staticmethod + def adopt( + jpeg_instance: JpegImagePlugin.JpegImageFile, + mpheader: dict[int, Any] | None = None, + ) -> MpoImageFile: + """ + Transform the instance of JpegImageFile into + an instance of MpoImageFile. + After the call, the JpegImageFile is extended + to be an MpoImageFile. + + This is essentially useful when opening a JPEG + file that reveals itself as an MPO, to avoid + double call to _open. + """ + jpeg_instance.__class__ = MpoImageFile + mpo_instance = cast(MpoImageFile, jpeg_instance) + mpo_instance._after_jpeg_open(mpheader) + return mpo_instance + + +# --------------------------------------------------------------------- +# Registry stuff + +# Note that since MPO shares a factory with JPEG, we do not need to do a +# separate registration for it here. +# Image.register_open(MpoImageFile.format, +# JpegImagePlugin.jpeg_factory, _accept) +Image.register_save(MpoImageFile.format, _save) +Image.register_save_all(MpoImageFile.format, _save_all) + +Image.register_extension(MpoImageFile.format, ".mpo") + +Image.register_mime(MpoImageFile.format, "image/mpo") diff --git a/PIL/MspImagePlugin.py b/PIL/MspImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..277087a8677708a3a5fe21a3f6d2c3b27f880d03 --- /dev/null +++ b/PIL/MspImagePlugin.py @@ -0,0 +1,200 @@ +# +# The Python Imaging Library. +# +# MSP file handling +# +# This is the format used by the Paint program in Windows 1 and 2. +# +# History: +# 95-09-05 fl Created +# 97-01-03 fl Read/write MSP images +# 17-02-21 es Fixed RLE interpretation +# +# Copyright (c) Secret Labs AB 1997. +# Copyright (c) Fredrik Lundh 1995-97. +# Copyright (c) Eric Soroos 2017. +# +# See the README file for information on usage and redistribution. +# +# More info on this format: https://archive.org/details/gg243631 +# Page 313: +# Figure 205. Windows Paint Version 1: "DanM" Format +# Figure 206. Windows Paint Version 2: "LinS" Format. Used in Windows V2.03 +# +# See also: https://www.fileformat.info/format/mspaint/egff.htm +from __future__ import annotations + +import io +import struct +from typing import IO + +from . import Image, ImageFile +from ._binary import i16le as i16 +from ._binary import o16le as o16 + +# +# read MSP files + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith((b"DanM", b"LinS")) + + +## +# Image plugin for Windows MSP images. This plugin supports both +# uncompressed (Windows 1.0). + + +class MspImageFile(ImageFile.ImageFile): + format = "MSP" + format_description = "Windows Paint" + + def _open(self) -> None: + # Header + assert self.fp is not None + + s = self.fp.read(32) + if not _accept(s): + msg = "not an MSP file" + raise SyntaxError(msg) + + # Header checksum + checksum = 0 + for i in range(0, 32, 2): + checksum = checksum ^ i16(s, i) + if checksum != 0: + msg = "bad MSP checksum" + raise SyntaxError(msg) + + self._mode = "1" + self._size = i16(s, 4), i16(s, 6) + + if s.startswith(b"DanM"): + self.tile = [ImageFile._Tile("raw", (0, 0) + self.size, 32, "1")] + else: + self.tile = [ImageFile._Tile("MSP", (0, 0) + self.size, 32)] + + +class MspDecoder(ImageFile.PyDecoder): + # The algo for the MSP decoder is from + # https://www.fileformat.info/format/mspaint/egff.htm + # cc-by-attribution -- That page references is taken from the + # Encyclopedia of Graphics File Formats and is licensed by + # O'Reilly under the Creative Common/Attribution license + # + # For RLE encoded files, the 32byte header is followed by a scan + # line map, encoded as one 16bit word of encoded byte length per + # line. + # + # NOTE: the encoded length of the line can be 0. This was not + # handled in the previous version of this encoder, and there's no + # mention of how to handle it in the documentation. From the few + # examples I've seen, I've assumed that it is a fill of the + # background color, in this case, white. + # + # + # Pseudocode of the decoder: + # Read a BYTE value as the RunType + # If the RunType value is zero + # Read next byte as the RunCount + # Read the next byte as the RunValue + # Write the RunValue byte RunCount times + # If the RunType value is non-zero + # Use this value as the RunCount + # Read and write the next RunCount bytes literally + # + # e.g.: + # 0x00 03 ff 05 00 01 02 03 04 + # would yield the bytes: + # 0xff ff ff 00 01 02 03 04 + # + # which are then interpreted as a bit packed mode '1' image + + _pulls_fd = True + + def decode(self, buffer: bytes | Image.SupportsArrayInterface) -> tuple[int, int]: + assert self.fd is not None + + img = io.BytesIO() + blank_line = bytearray((0xFF,) * ((self.state.xsize + 7) // 8)) + try: + self.fd.seek(32) + rowmap = struct.unpack_from( + f"<{self.state.ysize}H", self.fd.read(self.state.ysize * 2) + ) + except struct.error as e: + msg = "Truncated MSP file in row map" + raise OSError(msg) from e + + for x, rowlen in enumerate(rowmap): + try: + if rowlen == 0: + img.write(blank_line) + continue + row = self.fd.read(rowlen) + if len(row) != rowlen: + msg = f"Truncated MSP file, expected {rowlen} bytes on row {x}" + raise OSError(msg) + idx = 0 + while idx < rowlen: + runtype = row[idx] + idx += 1 + if runtype == 0: + (runcount, runval) = struct.unpack_from("Bc", row, idx) + img.write(runval * runcount) + idx += 2 + else: + runcount = runtype + img.write(row[idx : idx + runcount]) + idx += runcount + + except struct.error as e: + msg = f"Corrupted MSP file in row {x}" + raise OSError(msg) from e + + self.set_as_raw(img.getvalue(), "1") + + return -1, 0 + + +Image.register_decoder("MSP", MspDecoder) + + +# +# write MSP files (uncompressed only) + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + if im.mode != "1": + msg = f"cannot write mode {im.mode} as MSP" + raise OSError(msg) + + # create MSP header + header = [0] * 16 + + header[0], header[1] = i16(b"Da"), i16(b"nM") # version 1 + header[2], header[3] = im.size + header[4], header[5] = 1, 1 + header[6], header[7] = 1, 1 + header[8], header[9] = im.size + + checksum = 0 + for h in header: + checksum = checksum ^ h + header[12] = checksum # FIXME: is this the right field? + + # header + for h in header: + fp.write(o16(h)) + + # image body + ImageFile._save(im, fp, [ImageFile._Tile("raw", (0, 0) + im.size, 32, "1")]) + + +# +# registry + +Image.register_open(MspImageFile.format, MspImageFile, _accept) +Image.register_save(MspImageFile.format, _save) + +Image.register_extension(MspImageFile.format, ".msp") diff --git a/PIL/PcfFontFile.py b/PIL/PcfFontFile.py new file mode 100644 index 0000000000000000000000000000000000000000..a00e9b9198430c28b2aeb49df57ab17f78369995 --- /dev/null +++ b/PIL/PcfFontFile.py @@ -0,0 +1,258 @@ +# +# THIS IS WORK IN PROGRESS +# +# The Python Imaging Library +# $Id$ +# +# portable compiled font file parser +# +# history: +# 1997-08-19 fl created +# 2003-09-13 fl fixed loading of unicode fonts +# +# Copyright (c) 1997-2003 by Secret Labs AB. +# Copyright (c) 1997-2003 by Fredrik Lundh. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import io + +from . import FontFile, Image +from ._binary import i8 +from ._binary import i16be as b16 +from ._binary import i16le as l16 +from ._binary import i32be as b32 +from ._binary import i32le as l32 + +TYPE_CHECKING = False +if TYPE_CHECKING: + from collections.abc import Callable + from typing import BinaryIO + +# -------------------------------------------------------------------- +# declarations + +PCF_MAGIC = 0x70636601 # "\x01fcp" + +PCF_PROPERTIES = 1 << 0 +PCF_ACCELERATORS = 1 << 1 +PCF_METRICS = 1 << 2 +PCF_BITMAPS = 1 << 3 +PCF_INK_METRICS = 1 << 4 +PCF_BDF_ENCODINGS = 1 << 5 +PCF_SWIDTHS = 1 << 6 +PCF_GLYPH_NAMES = 1 << 7 +PCF_BDF_ACCELERATORS = 1 << 8 + +BYTES_PER_ROW: list[Callable[[int], int]] = [ + lambda bits: ((bits + 7) >> 3), + lambda bits: ((bits + 15) >> 3) & ~1, + lambda bits: ((bits + 31) >> 3) & ~3, + lambda bits: ((bits + 63) >> 3) & ~7, +] + + +def sz(s: bytes, o: int) -> bytes: + return s[o : s.index(b"\0", o)] + + +class PcfFontFile(FontFile.FontFile): + """Font file plugin for the X11 PCF format.""" + + name = "name" + + def __init__(self, fp: BinaryIO, charset_encoding: str = "iso8859-1"): + self.charset_encoding = charset_encoding + + magic = l32(fp.read(4)) + if magic != PCF_MAGIC: + msg = "not a PCF file" + raise SyntaxError(msg) + + super().__init__() + + count = l32(fp.read(4)) + self.toc = {} + for i in range(count): + type = l32(fp.read(4)) + self.toc[type] = l32(fp.read(4)), l32(fp.read(4)), l32(fp.read(4)) + + self.fp = fp + + self.info = self._load_properties() + + metrics = self._load_metrics() + bitmaps = self._load_bitmaps(metrics) + encoding = self._load_encoding() + + # + # create glyph structure + + for ch, ix in enumerate(encoding): + if ix is not None: + ( + xsize, + ysize, + left, + right, + width, + ascent, + descent, + attributes, + ) = metrics[ix] + self.glyph[ch] = ( + (width, 0), + (left, descent - ysize, xsize + left, descent), + (0, 0, xsize, ysize), + bitmaps[ix], + ) + + def _getformat( + self, tag: int + ) -> tuple[BinaryIO, int, Callable[[bytes], int], Callable[[bytes], int]]: + format, size, offset = self.toc[tag] + + fp = self.fp + fp.seek(offset) + + format = l32(fp.read(4)) + + if format & 4: + i16, i32 = b16, b32 + else: + i16, i32 = l16, l32 + + return fp, format, i16, i32 + + def _load_properties(self) -> dict[bytes, bytes | int]: + # + # font properties + + properties = {} + + fp, format, i16, i32 = self._getformat(PCF_PROPERTIES) + + nprops = i32(fp.read(4)) + + # read property description + p = [(i32(fp.read(4)), i8(fp.read(1)), i32(fp.read(4))) for _ in range(nprops)] + + if nprops & 3: + fp.seek(4 - (nprops & 3), io.SEEK_CUR) # pad + + data = fp.read(i32(fp.read(4))) + + for k, s, v in p: + property_value: bytes | int = sz(data, v) if s else v + properties[sz(data, k)] = property_value + + return properties + + def _load_metrics(self) -> list[tuple[int, int, int, int, int, int, int, int]]: + # + # font metrics + + metrics: list[tuple[int, int, int, int, int, int, int, int]] = [] + + fp, format, i16, i32 = self._getformat(PCF_METRICS) + + append = metrics.append + + if (format & 0xFF00) == 0x100: + # "compressed" metrics + for i in range(i16(fp.read(2))): + left = i8(fp.read(1)) - 128 + right = i8(fp.read(1)) - 128 + width = i8(fp.read(1)) - 128 + ascent = i8(fp.read(1)) - 128 + descent = i8(fp.read(1)) - 128 + xsize = right - left + ysize = ascent + descent + append((xsize, ysize, left, right, width, ascent, descent, 0)) + + else: + # "jumbo" metrics + for i in range(i32(fp.read(4))): + left = i16(fp.read(2)) + right = i16(fp.read(2)) + width = i16(fp.read(2)) + ascent = i16(fp.read(2)) + descent = i16(fp.read(2)) + attributes = i16(fp.read(2)) + xsize = right - left + ysize = ascent + descent + append((xsize, ysize, left, right, width, ascent, descent, attributes)) + + return metrics + + def _load_bitmaps( + self, metrics: list[tuple[int, int, int, int, int, int, int, int]] + ) -> list[Image.Image]: + # + # bitmap data + + fp, format, i16, i32 = self._getformat(PCF_BITMAPS) + + nbitmaps = i32(fp.read(4)) + + if nbitmaps != len(metrics): + msg = "Wrong number of bitmaps" + raise OSError(msg) + + offsets = [i32(fp.read(4)) for _ in range(nbitmaps)] + + bitmap_sizes = [i32(fp.read(4)) for _ in range(4)] + + # byteorder = format & 4 # non-zero => MSB + bitorder = format & 8 # non-zero => MSB + padindex = format & 3 + + bitmapsize = bitmap_sizes[padindex] + offsets.append(bitmapsize) + + data = fp.read(bitmapsize) + + pad = BYTES_PER_ROW[padindex] + mode = "1;R" + if bitorder: + mode = "1" + + bitmaps = [] + for i in range(nbitmaps): + xsize, ysize = metrics[i][:2] + b, e = offsets[i : i + 2] + bitmaps.append( + Image.frombytes("1", (xsize, ysize), data[b:e], "raw", mode, pad(xsize)) + ) + + return bitmaps + + def _load_encoding(self) -> list[int | None]: + fp, format, i16, i32 = self._getformat(PCF_BDF_ENCODINGS) + + first_col, last_col = i16(fp.read(2)), i16(fp.read(2)) + first_row, last_row = i16(fp.read(2)), i16(fp.read(2)) + + i16(fp.read(2)) # default + + nencoding = (last_col - first_col + 1) * (last_row - first_row + 1) + + # map character code to bitmap index + encoding: list[int | None] = [None] * min(256, nencoding) + + encoding_offsets = [i16(fp.read(2)) for _ in range(nencoding)] + + for i in range(first_col, len(encoding)): + try: + encoding_offset = encoding_offsets[ + ord(bytearray([i]).decode(self.charset_encoding)) + ] + if encoding_offset != 0xFFFF: + encoding[i] = encoding_offset + except UnicodeDecodeError: + # character is not supported in selected encoding + pass + + return encoding diff --git a/PIL/PcxImagePlugin.py b/PIL/PcxImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..6b16d5385379ea3549f04459b862e60abe85bc93 --- /dev/null +++ b/PIL/PcxImagePlugin.py @@ -0,0 +1,228 @@ +# +# The Python Imaging Library. +# $Id$ +# +# PCX file handling +# +# This format was originally used by ZSoft's popular PaintBrush +# program for the IBM PC. It is also supported by many MS-DOS and +# Windows applications, including the Windows PaintBrush program in +# Windows 3. +# +# history: +# 1995-09-01 fl Created +# 1996-05-20 fl Fixed RGB support +# 1997-01-03 fl Fixed 2-bit and 4-bit support +# 1999-02-03 fl Fixed 8-bit support (broken in 1.0b1) +# 1999-02-07 fl Added write support +# 2002-06-09 fl Made 2-bit and 4-bit support a bit more robust +# 2002-07-30 fl Seek from to current position, not beginning of file +# 2003-06-03 fl Extract DPI settings (info["dpi"]) +# +# Copyright (c) 1997-2003 by Secret Labs AB. +# Copyright (c) 1995-2003 by Fredrik Lundh. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import io +import logging +from typing import IO + +from . import Image, ImageFile, ImagePalette +from ._binary import i16le as i16 +from ._binary import o8 +from ._binary import o16le as o16 + +logger = logging.getLogger(__name__) + + +def _accept(prefix: bytes) -> bool: + return len(prefix) >= 2 and prefix[0] == 10 and prefix[1] in [0, 2, 3, 5] + + +## +# Image plugin for Paintbrush images. + + +class PcxImageFile(ImageFile.ImageFile): + format = "PCX" + format_description = "Paintbrush" + + def _open(self) -> None: + # header + assert self.fp is not None + + s = self.fp.read(68) + if not _accept(s): + msg = "not a PCX file" + raise SyntaxError(msg) + + # image + bbox = i16(s, 4), i16(s, 6), i16(s, 8) + 1, i16(s, 10) + 1 + if bbox[2] <= bbox[0] or bbox[3] <= bbox[1]: + msg = "bad PCX image size" + raise SyntaxError(msg) + logger.debug("BBox: %s %s %s %s", *bbox) + + offset = self.fp.tell() + 60 + + # format + version = s[1] + bits = s[3] + planes = s[65] + provided_stride = i16(s, 66) + logger.debug( + "PCX version %s, bits %s, planes %s, stride %s", + version, + bits, + planes, + provided_stride, + ) + + self.info["dpi"] = i16(s, 12), i16(s, 14) + + if bits == 1 and planes == 1: + mode = rawmode = "1" + + elif bits == 1 and planes in (2, 4): + mode = "P" + rawmode = f"P;{planes}L" + self.palette = ImagePalette.raw("RGB", s[16:64]) + + elif version == 5 and bits == 8 and planes == 1: + mode = rawmode = "L" + # FIXME: hey, this doesn't work with the incremental loader !!! + self.fp.seek(-769, io.SEEK_END) + s = self.fp.read(769) + if len(s) == 769 and s[0] == 12: + # check if the palette is linear grayscale + for i in range(256): + if s[i * 3 + 1 : i * 3 + 4] != o8(i) * 3: + mode = rawmode = "P" + break + if mode == "P": + self.palette = ImagePalette.raw("RGB", s[1:]) + + elif version == 5 and bits == 8 and planes == 3: + mode = "RGB" + rawmode = "RGB;L" + + else: + msg = "unknown PCX mode" + raise OSError(msg) + + self._mode = mode + self._size = bbox[2] - bbox[0], bbox[3] - bbox[1] + + # Don't trust the passed in stride. + # Calculate the approximate position for ourselves. + # CVE-2020-35653 + stride = (self._size[0] * bits + 7) // 8 + + # While the specification states that this must be even, + # not all images follow this + if provided_stride != stride: + stride += stride % 2 + + bbox = (0, 0) + self.size + logger.debug("size: %sx%s", *self.size) + + self.tile = [ImageFile._Tile("pcx", bbox, offset, (rawmode, planes * stride))] + + +# -------------------------------------------------------------------- +# save PCX files + + +SAVE = { + # mode: (version, bits, planes, raw mode) + "1": (2, 1, 1, "1"), + "L": (5, 8, 1, "L"), + "P": (5, 8, 1, "P"), + "RGB": (5, 8, 3, "RGB;L"), +} + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + try: + version, bits, planes, rawmode = SAVE[im.mode] + except KeyError as e: + msg = f"Cannot save {im.mode} images as PCX" + raise ValueError(msg) from e + + # bytes per plane + stride = (im.size[0] * bits + 7) // 8 + # stride should be even + stride += stride % 2 + # Stride needs to be kept in sync with the PcxEncode.c version. + # Ideally it should be passed in in the state, but the bytes value + # gets overwritten. + + logger.debug( + "PcxImagePlugin._save: xwidth: %d, bits: %d, stride: %d", + im.size[0], + bits, + stride, + ) + + # under windows, we could determine the current screen size with + # "Image.core.display_mode()[1]", but I think that's overkill... + + screen = im.size + + dpi = 100, 100 + + # PCX header + fp.write( + o8(10) + + o8(version) + + o8(1) + + o8(bits) + + o16(0) + + o16(0) + + o16(im.size[0] - 1) + + o16(im.size[1] - 1) + + o16(dpi[0]) + + o16(dpi[1]) + + b"\0" * 24 + + b"\xff" * 24 + + b"\0" + + o8(planes) + + o16(stride) + + o16(1) + + o16(screen[0]) + + o16(screen[1]) + + b"\0" * 54 + ) + + assert fp.tell() == 128 + + ImageFile._save( + im, fp, [ImageFile._Tile("pcx", (0, 0) + im.size, 0, (rawmode, bits * planes))] + ) + + if im.mode == "P": + # colour palette + fp.write(o8(12)) + palette = im.im.getpalette("RGB", "RGB") + palette += b"\x00" * (768 - len(palette)) + fp.write(palette) # 768 bytes + elif im.mode == "L": + # grayscale palette + fp.write(o8(12)) + for i in range(256): + fp.write(o8(i) * 3) + + +# -------------------------------------------------------------------- +# registry + + +Image.register_open(PcxImageFile.format, PcxImageFile, _accept) +Image.register_save(PcxImageFile.format, _save) + +Image.register_extension(PcxImageFile.format, ".pcx") + +Image.register_mime(PcxImageFile.format, "image/x-pcx") diff --git a/PIL/PdfImagePlugin.py b/PIL/PdfImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..5594c7e0f2b17b431c27e51ccf2bd66cf45c48b0 --- /dev/null +++ b/PIL/PdfImagePlugin.py @@ -0,0 +1,311 @@ +# +# The Python Imaging Library. +# $Id$ +# +# PDF (Acrobat) file handling +# +# History: +# 1996-07-16 fl Created +# 1997-01-18 fl Fixed header +# 2004-02-21 fl Fixes for 1/L/CMYK images, etc. +# 2004-02-24 fl Fixes for 1 and P images. +# +# Copyright (c) 1997-2004 by Secret Labs AB. All rights reserved. +# Copyright (c) 1996-1997 by Fredrik Lundh. +# +# See the README file for information on usage and redistribution. +# + +## +# Image plugin for PDF images (output only). +## +from __future__ import annotations + +import io +import math +import os +import time +from typing import IO, Any + +from . import Image, ImageFile, ImageSequence, PdfParser, features + +# +# -------------------------------------------------------------------- + +# object ids: +# 1. catalogue +# 2. pages +# 3. image +# 4. page +# 5. page contents + + +def _save_all(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + _save(im, fp, filename, save_all=True) + + +## +# (Internal) Image save plugin for the PDF format. + + +def _write_image( + im: Image.Image, + filename: str | bytes, + existing_pdf: PdfParser.PdfParser, + image_refs: list[PdfParser.IndirectReference], +) -> tuple[PdfParser.IndirectReference, str]: + # FIXME: Should replace ASCIIHexDecode with RunLengthDecode + # (packbits) or LZWDecode (tiff/lzw compression). Note that + # PDF 1.2 also supports Flatedecode (zip compression). + + params = None + decode = None + + # + # Get image characteristics + + width, height = im.size + + dict_obj: dict[str, Any] = {"BitsPerComponent": 8} + if im.mode == "1": + if features.check("libtiff"): + decode_filter = "CCITTFaxDecode" + dict_obj["BitsPerComponent"] = 1 + params = PdfParser.PdfArray( + [ + PdfParser.PdfDict( + { + "K": -1, + "BlackIs1": True, + "Columns": width, + "Rows": height, + } + ) + ] + ) + else: + decode_filter = "DCTDecode" + dict_obj["ColorSpace"] = PdfParser.PdfName("DeviceGray") + procset = "ImageB" # grayscale + elif im.mode == "L": + decode_filter = "DCTDecode" + # params = f"<< /Predictor 15 /Columns {width-2} >>" + dict_obj["ColorSpace"] = PdfParser.PdfName("DeviceGray") + procset = "ImageB" # grayscale + elif im.mode == "LA": + decode_filter = "JPXDecode" + # params = f"<< /Predictor 15 /Columns {width-2} >>" + procset = "ImageB" # grayscale + dict_obj["SMaskInData"] = 1 + elif im.mode == "P": + decode_filter = "ASCIIHexDecode" + palette = im.getpalette() + assert palette is not None + dict_obj["ColorSpace"] = [ + PdfParser.PdfName("Indexed"), + PdfParser.PdfName("DeviceRGB"), + len(palette) // 3 - 1, + PdfParser.PdfBinary(palette), + ] + procset = "ImageI" # indexed color + + if "transparency" in im.info: + smask = im.convert("LA").getchannel("A") + smask.encoderinfo = {} + + image_ref = _write_image(smask, filename, existing_pdf, image_refs)[0] + dict_obj["SMask"] = image_ref + elif im.mode == "RGB": + decode_filter = "DCTDecode" + dict_obj["ColorSpace"] = PdfParser.PdfName("DeviceRGB") + procset = "ImageC" # color images + elif im.mode == "RGBA": + decode_filter = "JPXDecode" + procset = "ImageC" # color images + dict_obj["SMaskInData"] = 1 + elif im.mode == "CMYK": + decode_filter = "DCTDecode" + dict_obj["ColorSpace"] = PdfParser.PdfName("DeviceCMYK") + procset = "ImageC" # color images + decode = [1, 0, 1, 0, 1, 0, 1, 0] + else: + msg = f"cannot save mode {im.mode}" + raise ValueError(msg) + + # + # image + + op = io.BytesIO() + + if decode_filter == "ASCIIHexDecode": + ImageFile._save(im, op, [ImageFile._Tile("hex", (0, 0) + im.size, 0, im.mode)]) + elif decode_filter == "CCITTFaxDecode": + im.save( + op, + "TIFF", + compression="group4", + # use a single strip + strip_size=math.ceil(width / 8) * height, + ) + elif decode_filter == "DCTDecode": + Image.SAVE["JPEG"](im, op, filename) + elif decode_filter == "JPXDecode": + del dict_obj["BitsPerComponent"] + Image.SAVE["JPEG2000"](im, op, filename) + else: + msg = f"unsupported PDF filter ({decode_filter})" + raise ValueError(msg) + + stream = op.getvalue() + filter: PdfParser.PdfArray | PdfParser.PdfName + if decode_filter == "CCITTFaxDecode": + stream = stream[8:] + filter = PdfParser.PdfArray([PdfParser.PdfName(decode_filter)]) + else: + filter = PdfParser.PdfName(decode_filter) + + image_ref = image_refs.pop(0) + existing_pdf.write_obj( + image_ref, + stream=stream, + Type=PdfParser.PdfName("XObject"), + Subtype=PdfParser.PdfName("Image"), + Width=width, # * 72.0 / x_resolution, + Height=height, # * 72.0 / y_resolution, + Filter=filter, + Decode=decode, + DecodeParms=params, + **dict_obj, + ) + + return image_ref, procset + + +def _save( + im: Image.Image, fp: IO[bytes], filename: str | bytes, save_all: bool = False +) -> None: + is_appending = im.encoderinfo.get("append", False) + filename_str = filename.decode() if isinstance(filename, bytes) else filename + if is_appending: + existing_pdf = PdfParser.PdfParser(f=fp, filename=filename_str, mode="r+b") + else: + existing_pdf = PdfParser.PdfParser(f=fp, filename=filename_str, mode="w+b") + + dpi = im.encoderinfo.get("dpi") + if dpi: + x_resolution = dpi[0] + y_resolution = dpi[1] + else: + x_resolution = y_resolution = im.encoderinfo.get("resolution", 72.0) + + info = { + "title": ( + None if is_appending else os.path.splitext(os.path.basename(filename))[0] + ), + "author": None, + "subject": None, + "keywords": None, + "creator": None, + "producer": None, + "creationDate": None if is_appending else time.gmtime(), + "modDate": None if is_appending else time.gmtime(), + } + for k, default in info.items(): + v = im.encoderinfo.get(k) if k in im.encoderinfo else default + if v: + existing_pdf.info[k[0].upper() + k[1:]] = v + + # + # make sure image data is available + im.load() + + existing_pdf.start_writing() + existing_pdf.write_header() + existing_pdf.write_comment("created by Pillow PDF driver") + + # + # pages + ims = [im] + if save_all: + append_images = im.encoderinfo.get("append_images", []) + for append_im in append_images: + append_im.encoderinfo = im.encoderinfo.copy() + ims.append(append_im) + number_of_pages = 0 + image_refs = [] + page_refs = [] + contents_refs = [] + for im in ims: + im_number_of_pages = 1 + if save_all: + im_number_of_pages = getattr(im, "n_frames", 1) + number_of_pages += im_number_of_pages + for i in range(im_number_of_pages): + image_refs.append(existing_pdf.next_object_id(0)) + if im.mode == "P" and "transparency" in im.info: + image_refs.append(existing_pdf.next_object_id(0)) + + page_refs.append(existing_pdf.next_object_id(0)) + contents_refs.append(existing_pdf.next_object_id(0)) + existing_pdf.pages.append(page_refs[-1]) + + # + # catalog and list of pages + existing_pdf.write_catalog() + + page_number = 0 + for im_sequence in ims: + im_pages: ImageSequence.Iterator | list[Image.Image] = ( + ImageSequence.Iterator(im_sequence) if save_all else [im_sequence] + ) + for im in im_pages: + image_ref, procset = _write_image(im, filename, existing_pdf, image_refs) + + # + # page + + existing_pdf.write_page( + page_refs[page_number], + Resources=PdfParser.PdfDict( + ProcSet=[PdfParser.PdfName("PDF"), PdfParser.PdfName(procset)], + XObject=PdfParser.PdfDict(image=image_ref), + ), + MediaBox=[ + 0, + 0, + im.width * 72.0 / x_resolution, + im.height * 72.0 / y_resolution, + ], + Contents=contents_refs[page_number], + ) + + # + # page contents + + page_contents = b"q %f 0 0 %f 0 0 cm /image Do Q\n" % ( + im.width * 72.0 / x_resolution, + im.height * 72.0 / y_resolution, + ) + + existing_pdf.write_obj(contents_refs[page_number], stream=page_contents) + + page_number += 1 + + # + # trailer + existing_pdf.write_xref_and_trailer() + if hasattr(fp, "flush"): + fp.flush() + existing_pdf.close() + + +# +# -------------------------------------------------------------------- + + +Image.register_save("PDF", _save) +Image.register_save_all("PDF", _save_all) + +Image.register_extension("PDF", ".pdf") + +Image.register_mime("PDF", "application/pdf") diff --git a/PIL/PixarImagePlugin.py b/PIL/PixarImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..d2b6d0a97e4bd230134d4741fc997baca5b4507f --- /dev/null +++ b/PIL/PixarImagePlugin.py @@ -0,0 +1,72 @@ +# +# The Python Imaging Library. +# $Id$ +# +# PIXAR raster support for PIL +# +# history: +# 97-01-29 fl Created +# +# notes: +# This is incomplete; it is based on a few samples created with +# Photoshop 2.5 and 3.0, and a summary description provided by +# Greg Coats . Hopefully, "L" and +# "RGBA" support will be added in future versions. +# +# Copyright (c) Secret Labs AB 1997. +# Copyright (c) Fredrik Lundh 1997. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +from . import Image, ImageFile +from ._binary import i16le as i16 + +# +# helpers + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith(b"\200\350\000\000") + + +## +# Image plugin for PIXAR raster images. + + +class PixarImageFile(ImageFile.ImageFile): + format = "PIXAR" + format_description = "PIXAR raster image" + + def _open(self) -> None: + # assuming a 4-byte magic label + assert self.fp is not None + + s = self.fp.read(4) + if not _accept(s): + msg = "not a PIXAR file" + raise SyntaxError(msg) + + # read rest of header + s = s + self.fp.read(508) + + self._size = i16(s, 418), i16(s, 416) + + # get channel/depth descriptions + mode = i16(s, 424), i16(s, 426) + + if mode == (14, 2): + self._mode = "RGB" + # FIXME: to be continued... + + # create tile descriptor (assuming "dumped") + self.tile = [ImageFile._Tile("raw", (0, 0) + self.size, 1024, self.mode)] + + +# +# -------------------------------------------------------------------- + +Image.register_open(PixarImageFile.format, PixarImageFile, _accept) + +Image.register_extension(PixarImageFile.format, ".pxr") diff --git a/PIL/PngImagePlugin.py b/PIL/PngImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..9826a4cd14813035a8c4f12e2fc5ac9c509611b5 --- /dev/null +++ b/PIL/PngImagePlugin.py @@ -0,0 +1,1564 @@ +# +# The Python Imaging Library. +# $Id$ +# +# PNG support code +# +# See "PNG (Portable Network Graphics) Specification, version 1.0; +# W3C Recommendation", 1996-10-01, Thomas Boutell (ed.). +# +# history: +# 1996-05-06 fl Created (couldn't resist it) +# 1996-12-14 fl Upgraded, added read and verify support (0.2) +# 1996-12-15 fl Separate PNG stream parser +# 1996-12-29 fl Added write support, added getchunks +# 1996-12-30 fl Eliminated circular references in decoder (0.3) +# 1998-07-12 fl Read/write 16-bit images as mode I (0.4) +# 2001-02-08 fl Added transparency support (from Zircon) (0.5) +# 2001-04-16 fl Don't close data source in "open" method (0.6) +# 2004-02-24 fl Don't even pretend to support interlaced files (0.7) +# 2004-08-31 fl Do basic sanity check on chunk identifiers (0.8) +# 2004-09-20 fl Added PngInfo chunk container +# 2004-12-18 fl Added DPI read support (based on code by Niki Spahiev) +# 2008-08-13 fl Added tRNS support for RGB images +# 2009-03-06 fl Support for preserving ICC profiles (by Florian Hoech) +# 2009-03-08 fl Added zTXT support (from Lowell Alleman) +# 2009-03-29 fl Read interlaced PNG files (from Conrado Porto Lopes Gouvua) +# +# Copyright (c) 1997-2009 by Secret Labs AB +# Copyright (c) 1996 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import itertools +import logging +import re +import struct +import warnings +import zlib +from enum import IntEnum +from fractions import Fraction +from typing import IO, NamedTuple, cast + +from . import Image, ImageChops, ImageFile, ImagePalette, ImageSequence +from ._binary import i16be as i16 +from ._binary import i32be as i32 +from ._binary import o8 +from ._binary import o16be as o16 +from ._binary import o32be as o32 +from ._deprecate import deprecate +from ._util import DeferredError + +TYPE_CHECKING = False +if TYPE_CHECKING: + from collections.abc import Callable + from typing import Any, NoReturn + + from . import _imaging + +logger = logging.getLogger(__name__) + +is_cid = re.compile(rb"\w\w\w\w").match + + +_MAGIC = b"\211PNG\r\n\032\n" + + +_MODES = { + # supported bits/color combinations, and corresponding modes/rawmodes + # Grayscale + (1, 0): ("1", "1"), + (2, 0): ("L", "L;2"), + (4, 0): ("L", "L;4"), + (8, 0): ("L", "L"), + (16, 0): ("I;16", "I;16B"), + # Truecolour + (8, 2): ("RGB", "RGB"), + (16, 2): ("RGB", "RGB;16B"), + # Indexed-colour + (1, 3): ("P", "P;1"), + (2, 3): ("P", "P;2"), + (4, 3): ("P", "P;4"), + (8, 3): ("P", "P"), + # Grayscale with alpha + (8, 4): ("LA", "LA"), + (16, 4): ("RGBA", "LA;16B"), # LA;16B->LA not yet available + # Truecolour with alpha + (8, 6): ("RGBA", "RGBA"), + (16, 6): ("RGBA", "RGBA;16B"), +} + + +_simple_palette = re.compile(b"^\xff*\x00\xff*$") + +MAX_TEXT_CHUNK = ImageFile.SAFEBLOCK +""" +Maximum decompressed size for a iTXt or zTXt chunk. +Eliminates decompression bombs where compressed chunks can expand 1000x. +See :ref:`Text in PNG File Format`. +""" +MAX_TEXT_MEMORY = 64 * MAX_TEXT_CHUNK +""" +Set the maximum total text chunk size. +See :ref:`Text in PNG File Format`. +""" + + +# APNG frame disposal modes +class Disposal(IntEnum): + OP_NONE = 0 + """ + No disposal is done on this frame before rendering the next frame. + See :ref:`Saving APNG sequences`. + """ + OP_BACKGROUND = 1 + """ + This frame’s modified region is cleared to fully transparent black before rendering + the next frame. + See :ref:`Saving APNG sequences`. + """ + OP_PREVIOUS = 2 + """ + This frame’s modified region is reverted to the previous frame’s contents before + rendering the next frame. + See :ref:`Saving APNG sequences`. + """ + + +# APNG frame blend modes +class Blend(IntEnum): + OP_SOURCE = 0 + """ + All color components of this frame, including alpha, overwrite the previous output + image contents. + See :ref:`Saving APNG sequences`. + """ + OP_OVER = 1 + """ + This frame should be alpha composited with the previous output image contents. + See :ref:`Saving APNG sequences`. + """ + + +def _safe_zlib_decompress(s: bytes) -> bytes: + dobj = zlib.decompressobj() + plaintext = dobj.decompress(s, MAX_TEXT_CHUNK) + if dobj.unconsumed_tail: + msg = "Decompressed data too large for PngImagePlugin.MAX_TEXT_CHUNK" + raise ValueError(msg) + return plaintext + + +def _crc32(data: bytes, seed: int = 0) -> int: + return zlib.crc32(data, seed) & 0xFFFFFFFF + + +# -------------------------------------------------------------------- +# Support classes. Suitable for PNG and related formats like MNG etc. + + +class ChunkStream: + def __init__(self, fp: IO[bytes]) -> None: + self.fp: IO[bytes] | None = fp + self.queue: list[tuple[bytes, int, int]] | None = [] + + def read(self) -> tuple[bytes, int, int]: + """Fetch a new chunk. Returns header information.""" + cid = None + + assert self.fp is not None + if self.queue: + cid, pos, length = self.queue.pop() + self.fp.seek(pos) + else: + s = self.fp.read(8) + cid = s[4:] + pos = self.fp.tell() + length = i32(s) + + if not is_cid(cid): + if not ImageFile.LOAD_TRUNCATED_IMAGES: + msg = f"broken PNG file (chunk {repr(cid)})" + raise SyntaxError(msg) + + return cid, pos, length + + def __enter__(self) -> ChunkStream: + return self + + def __exit__(self, *args: object) -> None: + self.close() + + def close(self) -> None: + self.queue = self.fp = None + + def push(self, cid: bytes, pos: int, length: int) -> None: + assert self.queue is not None + self.queue.append((cid, pos, length)) + + def call(self, cid: bytes, pos: int, length: int) -> bytes: + """Call the appropriate chunk handler""" + + logger.debug("STREAM %r %s %s", cid, pos, length) + return getattr(self, f"chunk_{cid.decode('ascii')}")(pos, length) + + def crc(self, cid: bytes, data: bytes) -> None: + """Read and verify checksum""" + + # Skip CRC checks for ancillary chunks if allowed to load truncated + # images + # 5th byte of first char is 1 [specs, section 5.4] + if ImageFile.LOAD_TRUNCATED_IMAGES and (cid[0] >> 5 & 1): + self.crc_skip(cid, data) + return + + assert self.fp is not None + try: + crc1 = _crc32(data, _crc32(cid)) + crc2 = i32(self.fp.read(4)) + if crc1 != crc2: + msg = f"broken PNG file (bad header checksum in {repr(cid)})" + raise SyntaxError(msg) + except struct.error as e: + msg = f"broken PNG file (incomplete checksum in {repr(cid)})" + raise SyntaxError(msg) from e + + def crc_skip(self, cid: bytes, data: bytes) -> None: + """Read checksum""" + + assert self.fp is not None + self.fp.read(4) + + def verify(self, endchunk: bytes = b"IEND") -> list[bytes]: + # Simple approach; just calculate checksum for all remaining + # blocks. Must be called directly after open. + + cids = [] + + assert self.fp is not None + while True: + try: + cid, pos, length = self.read() + except struct.error as e: + msg = "truncated PNG file" + raise OSError(msg) from e + + if cid == endchunk: + break + self.crc(cid, ImageFile._safe_read(self.fp, length)) + cids.append(cid) + + return cids + + +class iTXt(str): + """ + Subclass of string to allow iTXt chunks to look like strings while + keeping their extra information + + """ + + lang: str | bytes | None + tkey: str | bytes | None + + @staticmethod + def __new__( + cls, text: str, lang: str | None = None, tkey: str | None = None + ) -> iTXt: + """ + :param cls: the class to use when creating the instance + :param text: value for this key + :param lang: language code + :param tkey: UTF-8 version of the key name + """ + + self = str.__new__(cls, text) + self.lang = lang + self.tkey = tkey + return self + + +class PngInfo: + """ + PNG chunk container (for use with save(pnginfo=)) + + """ + + def __init__(self) -> None: + self.chunks: list[tuple[bytes, bytes, bool]] = [] + + def add(self, cid: bytes, data: bytes, after_idat: bool = False) -> None: + """Appends an arbitrary chunk. Use with caution. + + :param cid: a byte string, 4 bytes long. + :param data: a byte string of the encoded data + :param after_idat: for use with private chunks. Whether the chunk + should be written after IDAT + + """ + + self.chunks.append((cid, data, after_idat)) + + def add_itxt( + self, + key: str | bytes, + value: str | bytes, + lang: str | bytes = "", + tkey: str | bytes = "", + zip: bool = False, + ) -> None: + """Appends an iTXt chunk. + + :param key: latin-1 encodable text key name + :param value: value for this key + :param lang: language code + :param tkey: UTF-8 version of the key name + :param zip: compression flag + + """ + + if not isinstance(key, bytes): + key = key.encode("latin-1", "strict") + if not isinstance(value, bytes): + value = value.encode("utf-8", "strict") + if not isinstance(lang, bytes): + lang = lang.encode("utf-8", "strict") + if not isinstance(tkey, bytes): + tkey = tkey.encode("utf-8", "strict") + + if zip: + self.add( + b"iTXt", + key + b"\0\x01\0" + lang + b"\0" + tkey + b"\0" + zlib.compress(value), + ) + else: + self.add(b"iTXt", key + b"\0\0\0" + lang + b"\0" + tkey + b"\0" + value) + + def add_text( + self, key: str | bytes, value: str | bytes | iTXt, zip: bool = False + ) -> None: + """Appends a text chunk. + + :param key: latin-1 encodable text key name + :param value: value for this key, text or an + :py:class:`PIL.PngImagePlugin.iTXt` instance + :param zip: compression flag + + """ + if isinstance(value, iTXt): + return self.add_itxt( + key, + value, + value.lang if value.lang is not None else b"", + value.tkey if value.tkey is not None else b"", + zip=zip, + ) + + # The tEXt chunk stores latin-1 text + if not isinstance(value, bytes): + try: + value = value.encode("latin-1", "strict") + except UnicodeError: + return self.add_itxt(key, value, zip=zip) + + if not isinstance(key, bytes): + key = key.encode("latin-1", "strict") + + if zip: + self.add(b"zTXt", key + b"\0\0" + zlib.compress(value)) + else: + self.add(b"tEXt", key + b"\0" + value) + + +# -------------------------------------------------------------------- +# PNG image stream (IHDR/IEND) + + +class _RewindState(NamedTuple): + info: dict[str | tuple[int, int], Any] + tile: list[ImageFile._Tile] + seq_num: int | None + + +class PngStream(ChunkStream): + def __init__(self, fp: IO[bytes]) -> None: + super().__init__(fp) + + # local copies of Image attributes + self.im_info: dict[str | tuple[int, int], Any] = {} + self.im_text: dict[str, str | iTXt] = {} + self.im_size = (0, 0) + self.im_mode = "" + self.im_tile: list[ImageFile._Tile] = [] + self.im_palette: tuple[str, bytes] | None = None + self.im_custom_mimetype: str | None = None + self.im_n_frames: int | None = None + self._seq_num: int | None = None + self.rewind_state = _RewindState({}, [], None) + + self.text_memory = 0 + + def check_text_memory(self, chunklen: int) -> None: + self.text_memory += chunklen + if self.text_memory > MAX_TEXT_MEMORY: + msg = ( + "Too much memory used in text chunks: " + f"{self.text_memory}>MAX_TEXT_MEMORY" + ) + raise ValueError(msg) + + def save_rewind(self) -> None: + self.rewind_state = _RewindState( + self.im_info.copy(), + self.im_tile, + self._seq_num, + ) + + def rewind(self) -> None: + self.im_info = self.rewind_state.info.copy() + self.im_tile = self.rewind_state.tile + self._seq_num = self.rewind_state.seq_num + + def chunk_iCCP(self, pos: int, length: int) -> bytes: + # ICC profile + assert self.fp is not None + s = ImageFile._safe_read(self.fp, length) + # according to PNG spec, the iCCP chunk contains: + # Profile name 1-79 bytes (character string) + # Null separator 1 byte (null character) + # Compression method 1 byte (0) + # Compressed profile n bytes (zlib with deflate compression) + i = s.find(b"\0") + logger.debug("iCCP profile name %r", s[:i]) + comp_method = s[i + 1] + logger.debug("Compression method %s", comp_method) + if comp_method != 0: + msg = f"Unknown compression method {comp_method} in iCCP chunk" + raise SyntaxError(msg) + try: + icc_profile = _safe_zlib_decompress(s[i + 2 :]) + except ValueError: + if ImageFile.LOAD_TRUNCATED_IMAGES: + icc_profile = None + else: + raise + except zlib.error: + icc_profile = None # FIXME + self.im_info["icc_profile"] = icc_profile + return s + + def chunk_IHDR(self, pos: int, length: int) -> bytes: + # image header + assert self.fp is not None + s = ImageFile._safe_read(self.fp, length) + if length < 13: + if ImageFile.LOAD_TRUNCATED_IMAGES: + return s + msg = "Truncated IHDR chunk" + raise ValueError(msg) + self.im_size = i32(s, 0), i32(s, 4) + try: + self.im_mode, self.im_rawmode = _MODES[(s[8], s[9])] + except Exception: + pass + if s[12]: + self.im_info["interlace"] = 1 + if s[11]: + msg = "unknown filter category" + raise SyntaxError(msg) + return s + + def chunk_IDAT(self, pos: int, length: int) -> NoReturn: + # image data + if "bbox" in self.im_info: + tile = [ImageFile._Tile("zip", self.im_info["bbox"], pos, self.im_rawmode)] + else: + if self.im_n_frames is not None: + self.im_info["default_image"] = True + tile = [ImageFile._Tile("zip", (0, 0) + self.im_size, pos, self.im_rawmode)] + self.im_tile = tile + self.im_idat = length + msg = "image data found" + raise EOFError(msg) + + def chunk_IEND(self, pos: int, length: int) -> NoReturn: + msg = "end of PNG image" + raise EOFError(msg) + + def chunk_PLTE(self, pos: int, length: int) -> bytes: + # palette + assert self.fp is not None + s = ImageFile._safe_read(self.fp, length) + if self.im_mode == "P": + self.im_palette = "RGB", s + return s + + def chunk_tRNS(self, pos: int, length: int) -> bytes: + # transparency + assert self.fp is not None + s = ImageFile._safe_read(self.fp, length) + if self.im_mode == "P": + if _simple_palette.match(s): + # tRNS contains only one full-transparent entry, + # other entries are full opaque + i = s.find(b"\0") + if i >= 0: + self.im_info["transparency"] = i + else: + # otherwise, we have a byte string with one alpha value + # for each palette entry + self.im_info["transparency"] = s + elif self.im_mode == "1": + self.im_info["transparency"] = 255 if i16(s) else 0 + elif self.im_mode in ("L", "I;16"): + self.im_info["transparency"] = i16(s) + elif self.im_mode == "RGB": + self.im_info["transparency"] = i16(s), i16(s, 2), i16(s, 4) + return s + + def chunk_gAMA(self, pos: int, length: int) -> bytes: + # gamma setting + assert self.fp is not None + s = ImageFile._safe_read(self.fp, length) + self.im_info["gamma"] = i32(s) / 100000.0 + return s + + def chunk_cHRM(self, pos: int, length: int) -> bytes: + # chromaticity, 8 unsigned ints, actual value is scaled by 100,000 + # WP x,y, Red x,y, Green x,y Blue x,y + + assert self.fp is not None + s = ImageFile._safe_read(self.fp, length) + raw_vals = struct.unpack(f">{len(s) // 4}I", s) + self.im_info["chromaticity"] = tuple(elt / 100000.0 for elt in raw_vals) + return s + + def chunk_sRGB(self, pos: int, length: int) -> bytes: + # srgb rendering intent, 1 byte + # 0 perceptual + # 1 relative colorimetric + # 2 saturation + # 3 absolute colorimetric + + assert self.fp is not None + s = ImageFile._safe_read(self.fp, length) + if length < 1: + if ImageFile.LOAD_TRUNCATED_IMAGES: + return s + msg = "Truncated sRGB chunk" + raise ValueError(msg) + self.im_info["srgb"] = s[0] + return s + + def chunk_pHYs(self, pos: int, length: int) -> bytes: + # pixels per unit + assert self.fp is not None + s = ImageFile._safe_read(self.fp, length) + if length < 9: + if ImageFile.LOAD_TRUNCATED_IMAGES: + return s + msg = "Truncated pHYs chunk" + raise ValueError(msg) + px, py = i32(s, 0), i32(s, 4) + unit = s[8] + if unit == 1: # meter + dpi = px * 0.0254, py * 0.0254 + self.im_info["dpi"] = dpi + elif unit == 0: + self.im_info["aspect"] = px, py + return s + + def chunk_tEXt(self, pos: int, length: int) -> bytes: + # text + assert self.fp is not None + s = ImageFile._safe_read(self.fp, length) + try: + k, v = s.split(b"\0", 1) + except ValueError: + # fallback for broken tEXt tags + k = s + v = b"" + if k: + k_str = k.decode("latin-1", "strict") + v_str = v.decode("latin-1", "replace") + + self.im_info[k_str] = v if k == b"exif" else v_str + self.im_text[k_str] = v_str + self.check_text_memory(len(v_str)) + + return s + + def chunk_zTXt(self, pos: int, length: int) -> bytes: + # compressed text + assert self.fp is not None + s = ImageFile._safe_read(self.fp, length) + try: + k, v = s.split(b"\0", 1) + except ValueError: + k = s + v = b"" + if v: + comp_method = v[0] + else: + comp_method = 0 + if comp_method != 0: + msg = f"Unknown compression method {comp_method} in zTXt chunk" + raise SyntaxError(msg) + try: + v = _safe_zlib_decompress(v[1:]) + except ValueError: + if ImageFile.LOAD_TRUNCATED_IMAGES: + v = b"" + else: + raise + except zlib.error: + v = b"" + + if k: + k_str = k.decode("latin-1", "strict") + v_str = v.decode("latin-1", "replace") + + self.im_info[k_str] = self.im_text[k_str] = v_str + self.check_text_memory(len(v_str)) + + return s + + def chunk_iTXt(self, pos: int, length: int) -> bytes: + # international text + assert self.fp is not None + r = s = ImageFile._safe_read(self.fp, length) + try: + k, r = r.split(b"\0", 1) + except ValueError: + return s + if len(r) < 2: + return s + cf, cm, r = r[0], r[1], r[2:] + try: + lang, tk, v = r.split(b"\0", 2) + except ValueError: + return s + if cf != 0: + if cm == 0: + try: + v = _safe_zlib_decompress(v) + except ValueError: + if ImageFile.LOAD_TRUNCATED_IMAGES: + return s + else: + raise + except zlib.error: + return s + else: + return s + if k == b"XML:com.adobe.xmp": + self.im_info["xmp"] = v + try: + k_str = k.decode("latin-1", "strict") + lang_str = lang.decode("utf-8", "strict") + tk_str = tk.decode("utf-8", "strict") + v_str = v.decode("utf-8", "strict") + except UnicodeError: + return s + + self.im_info[k_str] = self.im_text[k_str] = iTXt(v_str, lang_str, tk_str) + self.check_text_memory(len(v_str)) + + return s + + def chunk_eXIf(self, pos: int, length: int) -> bytes: + assert self.fp is not None + s = ImageFile._safe_read(self.fp, length) + self.im_info["exif"] = b"Exif\x00\x00" + s + return s + + # APNG chunks + def chunk_acTL(self, pos: int, length: int) -> bytes: + assert self.fp is not None + s = ImageFile._safe_read(self.fp, length) + if length < 8: + if ImageFile.LOAD_TRUNCATED_IMAGES: + return s + msg = "APNG contains truncated acTL chunk" + raise ValueError(msg) + if self.im_n_frames is not None: + self.im_n_frames = None + warnings.warn("Invalid APNG, will use default PNG image if possible") + return s + n_frames = i32(s) + if n_frames == 0 or n_frames > 0x80000000: + warnings.warn("Invalid APNG, will use default PNG image if possible") + return s + self.im_n_frames = n_frames + self.im_info["loop"] = i32(s, 4) + self.im_custom_mimetype = "image/apng" + return s + + def chunk_fcTL(self, pos: int, length: int) -> bytes: + assert self.fp is not None + s = ImageFile._safe_read(self.fp, length) + if length < 26: + if ImageFile.LOAD_TRUNCATED_IMAGES: + return s + msg = "APNG contains truncated fcTL chunk" + raise ValueError(msg) + seq = i32(s) + if (self._seq_num is None and seq != 0) or ( + self._seq_num is not None and self._seq_num != seq - 1 + ): + msg = "APNG contains frame sequence errors" + raise SyntaxError(msg) + self._seq_num = seq + width, height = i32(s, 4), i32(s, 8) + px, py = i32(s, 12), i32(s, 16) + im_w, im_h = self.im_size + if px + width > im_w or py + height > im_h: + msg = "APNG contains invalid frames" + raise SyntaxError(msg) + self.im_info["bbox"] = (px, py, px + width, py + height) + delay_num, delay_den = i16(s, 20), i16(s, 22) + if delay_den == 0: + delay_den = 100 + self.im_info["duration"] = float(delay_num) / float(delay_den) * 1000 + self.im_info["disposal"] = s[24] + self.im_info["blend"] = s[25] + return s + + def chunk_fdAT(self, pos: int, length: int) -> bytes: + assert self.fp is not None + if length < 4: + if ImageFile.LOAD_TRUNCATED_IMAGES: + s = ImageFile._safe_read(self.fp, length) + return s + msg = "APNG contains truncated fDAT chunk" + raise ValueError(msg) + s = ImageFile._safe_read(self.fp, 4) + seq = i32(s) + if self._seq_num != seq - 1: + msg = "APNG contains frame sequence errors" + raise SyntaxError(msg) + self._seq_num = seq + return self.chunk_IDAT(pos + 4, length - 4) + + +# -------------------------------------------------------------------- +# PNG reader + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith(_MAGIC) + + +## +# Image plugin for PNG images. + + +class PngImageFile(ImageFile.ImageFile): + format = "PNG" + format_description = "Portable network graphics" + + def _open(self) -> None: + assert self.fp is not None + if not _accept(self.fp.read(8)): + msg = "not a PNG file" + raise SyntaxError(msg) + self._fp = self.fp + self.__frame = 0 + + # + # Parse headers up to the first IDAT or fDAT chunk + + self.private_chunks: list[tuple[bytes, bytes] | tuple[bytes, bytes, bool]] = [] + self.png: PngStream | None = PngStream(self.fp) + + while True: + # + # get next chunk + + cid, pos, length = self.png.read() + + try: + s = self.png.call(cid, pos, length) + except EOFError: + break + except AttributeError: + logger.debug("%r %s %s (unknown)", cid, pos, length) + s = ImageFile._safe_read(self.fp, length) + if cid[1:2].islower(): + self.private_chunks.append((cid, s)) + + self.png.crc(cid, s) + + # + # Copy relevant attributes from the PngStream. An alternative + # would be to let the PngStream class modify these attributes + # directly, but that introduces circular references which are + # difficult to break if things go wrong in the decoder... + # (believe me, I've tried ;-) + + self._mode = self.png.im_mode + self._size = self.png.im_size + self.info = self.png.im_info + self._text: dict[str, str | iTXt] | None = None + self.tile = self.png.im_tile + self.custom_mimetype = self.png.im_custom_mimetype + self.n_frames = self.png.im_n_frames or 1 + self.default_image = self.info.get("default_image", False) + + if self.png.im_palette: + rawmode, data = self.png.im_palette + self.palette = ImagePalette.raw(rawmode, data) + + if cid == b"fdAT": + self.__prepare_idat = length - 4 + else: + self.__prepare_idat = length # used by load_prepare() + + if self.png.im_n_frames is not None: + self._close_exclusive_fp_after_loading = False + self.png.save_rewind() + self.__rewind_idat = self.__prepare_idat + self.__rewind = self._fp.tell() + if self.default_image: + # IDAT chunk contains default image and not first animation frame + self.n_frames += 1 + self._seek(0) + self.is_animated = self.n_frames > 1 + + @property + def text(self) -> dict[str, str | iTXt]: + # experimental + if self._text is None: + # iTxt, tEXt and zTXt chunks may appear at the end of the file + # So load the file to ensure that they are read + if self.is_animated: + frame = self.__frame + # for APNG, seek to the final frame before loading + self.seek(self.n_frames - 1) + self.load() + if self.is_animated: + self.seek(frame) + assert self._text is not None + return self._text + + def verify(self) -> None: + """Verify PNG file""" + + if self.fp is None: + msg = "verify must be called directly after open" + raise RuntimeError(msg) + + # back up to beginning of IDAT block + self.fp.seek(self.tile[0][2] - 8) + + assert self.png is not None + self.png.verify() + self.png.close() + + super().verify() + + def seek(self, frame: int) -> None: + if not self._seek_check(frame): + return + if frame < self.__frame: + self._seek(0, True) + + last_frame = self.__frame + for f in range(self.__frame + 1, frame + 1): + try: + self._seek(f) + except EOFError as e: + self.seek(last_frame) + msg = "no more images in APNG file" + raise EOFError(msg) from e + + def _seek(self, frame: int, rewind: bool = False) -> None: + assert self.png is not None + if isinstance(self._fp, DeferredError): + raise self._fp.ex + + self.dispose: _imaging.ImagingCore | None + dispose_extent = None + if frame == 0: + if rewind: + self._fp.seek(self.__rewind) + self.png.rewind() + self.__prepare_idat = self.__rewind_idat + self._im = None + self.info = self.png.im_info + self.tile = self.png.im_tile + self.fp = self._fp + self._prev_im = None + self.dispose = None + self.default_image = self.info.get("default_image", False) + self.dispose_op = self.info.get("disposal") + self.blend_op = self.info.get("blend") + dispose_extent = self.info.get("bbox") + self.__frame = 0 + else: + if frame != self.__frame + 1: + msg = f"cannot seek to frame {frame}" + raise ValueError(msg) + + # ensure previous frame was loaded + self.load() + + if self.dispose: + self.im.paste(self.dispose, self.dispose_extent) + self._prev_im = self.im.copy() + + self.fp = self._fp + + # advance to the next frame + if self.__prepare_idat: + ImageFile._safe_read(self.fp, self.__prepare_idat) + self.__prepare_idat = 0 + frame_start = False + while True: + self.fp.read(4) # CRC + + try: + cid, pos, length = self.png.read() + except (struct.error, SyntaxError): + break + + if cid == b"IEND": + msg = "No more images in APNG file" + raise EOFError(msg) + if cid == b"fcTL": + if frame_start: + # there must be at least one fdAT chunk between fcTL chunks + msg = "APNG missing frame data" + raise SyntaxError(msg) + frame_start = True + + try: + self.png.call(cid, pos, length) + except UnicodeDecodeError: + break + except EOFError: + if cid == b"fdAT": + length -= 4 + if frame_start: + self.__prepare_idat = length + break + ImageFile._safe_read(self.fp, length) + except AttributeError: + logger.debug("%r %s %s (unknown)", cid, pos, length) + ImageFile._safe_read(self.fp, length) + + self.__frame = frame + self.tile = self.png.im_tile + self.dispose_op = self.info.get("disposal") + self.blend_op = self.info.get("blend") + dispose_extent = self.info.get("bbox") + + if not self.tile: + msg = "image not found in APNG frame" + raise EOFError(msg) + if dispose_extent: + self.dispose_extent: tuple[float, float, float, float] = dispose_extent + + # setup frame disposal (actual disposal done when needed in the next _seek()) + if self._prev_im is None and self.dispose_op == Disposal.OP_PREVIOUS: + self.dispose_op = Disposal.OP_BACKGROUND + + self.dispose = None + if self.dispose_op == Disposal.OP_PREVIOUS: + if self._prev_im: + self.dispose = self._prev_im.copy() + self.dispose = self._crop(self.dispose, self.dispose_extent) + elif self.dispose_op == Disposal.OP_BACKGROUND: + self.dispose = Image.core.fill(self.mode, self.size) + self.dispose = self._crop(self.dispose, self.dispose_extent) + + def tell(self) -> int: + return self.__frame + + def load_prepare(self) -> None: + """internal: prepare to read PNG file""" + + if self.info.get("interlace"): + self.decoderconfig = self.decoderconfig + (1,) + + self.__idat = self.__prepare_idat # used by load_read() + ImageFile.ImageFile.load_prepare(self) + + def load_read(self, read_bytes: int) -> bytes: + """internal: read more image data""" + + assert self.png is not None + assert self.fp is not None + while self.__idat == 0: + # end of chunk, skip forward to next one + + self.fp.read(4) # CRC + + cid, pos, length = self.png.read() + + if cid not in [b"IDAT", b"DDAT", b"fdAT"]: + self.png.push(cid, pos, length) + return b"" + + if cid == b"fdAT": + try: + self.png.call(cid, pos, length) + except EOFError: + pass + self.__idat = length - 4 # sequence_num has already been read + else: + self.__idat = length # empty chunks are allowed + + # read more data from this chunk + if read_bytes <= 0: + read_bytes = self.__idat + else: + read_bytes = min(read_bytes, self.__idat) + + self.__idat = self.__idat - read_bytes + + return self.fp.read(read_bytes) + + def load_end(self) -> None: + """internal: finished reading image data""" + assert self.png is not None + assert self.fp is not None + if self.__idat != 0: + self.fp.read(self.__idat) + while True: + self.fp.read(4) # CRC + + try: + cid, pos, length = self.png.read() + except (struct.error, SyntaxError): + break + + if cid == b"IEND": + break + elif cid == b"fcTL" and self.is_animated: + # start of the next frame, stop reading + self.__prepare_idat = 0 + self.png.push(cid, pos, length) + break + + try: + self.png.call(cid, pos, length) + except UnicodeDecodeError: + break + except EOFError: + if cid == b"fdAT": + length -= 4 + try: + ImageFile._safe_read(self.fp, length) + except OSError as e: + if ImageFile.LOAD_TRUNCATED_IMAGES: + break + else: + raise e + except AttributeError: + logger.debug("%r %s %s (unknown)", cid, pos, length) + s = ImageFile._safe_read(self.fp, length) + if cid[1:2].islower(): + self.private_chunks.append((cid, s, True)) + self._text = self.png.im_text + if not self.is_animated: + self.png.close() + self.png = None + else: + if self._prev_im and self.blend_op == Blend.OP_OVER: + updated = self._crop(self.im, self.dispose_extent) + if self.im.mode == "RGB" and "transparency" in self.info: + mask = updated.convert_transparent( + "RGBA", self.info["transparency"] + ) + else: + if self.im.mode == "P" and "transparency" in self.info: + t = self.info["transparency"] + if isinstance(t, bytes): + updated.putpalettealphas(t) + elif isinstance(t, int): + updated.putpalettealpha(t) + mask = updated.convert("RGBA") + self._prev_im.paste(updated, self.dispose_extent, mask) + self.im = self._prev_im + + def _getexif(self) -> dict[int, Any] | None: + if "exif" not in self.info: + self.load() + if "exif" not in self.info and "Raw profile type exif" not in self.info: + return None + return self.getexif()._get_merged_dict() + + def getexif(self) -> Image.Exif: + if "exif" not in self.info: + self.load() + + return super().getexif() + + +# -------------------------------------------------------------------- +# PNG writer + +_OUTMODES = { + # supported PIL modes, and corresponding rawmode, bit depth and color type + "1": ("1", b"\x01", b"\x00"), + "L;1": ("L;1", b"\x01", b"\x00"), + "L;2": ("L;2", b"\x02", b"\x00"), + "L;4": ("L;4", b"\x04", b"\x00"), + "L": ("L", b"\x08", b"\x00"), + "LA": ("LA", b"\x08", b"\x04"), + "I": ("I;16B", b"\x10", b"\x00"), + "I;16": ("I;16B", b"\x10", b"\x00"), + "I;16B": ("I;16B", b"\x10", b"\x00"), + "P;1": ("P;1", b"\x01", b"\x03"), + "P;2": ("P;2", b"\x02", b"\x03"), + "P;4": ("P;4", b"\x04", b"\x03"), + "P": ("P", b"\x08", b"\x03"), + "RGB": ("RGB", b"\x08", b"\x02"), + "RGBA": ("RGBA", b"\x08", b"\x06"), +} + + +def putchunk(fp: IO[bytes], cid: bytes, *data: bytes) -> None: + """Write a PNG chunk (including CRC field)""" + + byte_data = b"".join(data) + + fp.write(o32(len(byte_data)) + cid) + fp.write(byte_data) + crc = _crc32(byte_data, _crc32(cid)) + fp.write(o32(crc)) + + +class _idat: + # wrap output from the encoder in IDAT chunks + + def __init__(self, fp: IO[bytes], chunk: Callable[..., None]) -> None: + self.fp = fp + self.chunk = chunk + + def write(self, data: bytes) -> None: + self.chunk(self.fp, b"IDAT", data) + + +class _fdat: + # wrap encoder output in fdAT chunks + + def __init__(self, fp: IO[bytes], chunk: Callable[..., None], seq_num: int) -> None: + self.fp = fp + self.chunk = chunk + self.seq_num = seq_num + + def write(self, data: bytes) -> None: + self.chunk(self.fp, b"fdAT", o32(self.seq_num), data) + self.seq_num += 1 + + +def _apply_encoderinfo(im: Image.Image, encoderinfo: dict[str, Any]) -> None: + im.encoderconfig = ( + encoderinfo.get("optimize", False), + encoderinfo.get("compress_level", -1), + encoderinfo.get("compress_type", -1), + encoderinfo.get("dictionary", b""), + ) + + +class _Frame(NamedTuple): + im: Image.Image + bbox: tuple[int, int, int, int] | None + encoderinfo: dict[str, Any] + + +def _write_multiple_frames( + im: Image.Image, + fp: IO[bytes], + chunk: Callable[..., None], + mode: str, + rawmode: str, + default_image: Image.Image | None, + append_images: list[Image.Image], +) -> Image.Image | None: + duration = im.encoderinfo.get("duration") + loop = im.encoderinfo.get("loop", im.info.get("loop", 0)) + disposal = im.encoderinfo.get("disposal", im.info.get("disposal", Disposal.OP_NONE)) + blend = im.encoderinfo.get("blend", im.info.get("blend", Blend.OP_SOURCE)) + + if default_image: + chain = itertools.chain(append_images) + else: + chain = itertools.chain([im], append_images) + + im_frames: list[_Frame] = [] + frame_count = 0 + for im_seq in chain: + for im_frame in ImageSequence.Iterator(im_seq): + if im_frame.mode == mode: + im_frame = im_frame.copy() + else: + im_frame = im_frame.convert(mode) + encoderinfo = im.encoderinfo.copy() + if isinstance(duration, (list, tuple)): + encoderinfo["duration"] = duration[frame_count] + elif duration is None and "duration" in im_frame.info: + encoderinfo["duration"] = im_frame.info["duration"] + if isinstance(disposal, (list, tuple)): + encoderinfo["disposal"] = disposal[frame_count] + if isinstance(blend, (list, tuple)): + encoderinfo["blend"] = blend[frame_count] + frame_count += 1 + + if im_frames: + previous = im_frames[-1] + prev_disposal = previous.encoderinfo.get("disposal") + prev_blend = previous.encoderinfo.get("blend") + if prev_disposal == Disposal.OP_PREVIOUS and len(im_frames) < 2: + prev_disposal = Disposal.OP_BACKGROUND + + if prev_disposal == Disposal.OP_BACKGROUND: + base_im = previous.im.copy() + dispose = Image.core.fill("RGBA", im.size, (0, 0, 0, 0)) + bbox = previous.bbox + if bbox: + dispose = dispose.crop(bbox) + else: + bbox = (0, 0) + im.size + base_im.paste(dispose, bbox) + elif prev_disposal == Disposal.OP_PREVIOUS: + base_im = im_frames[-2].im + else: + base_im = previous.im + delta = ImageChops.subtract_modulo( + im_frame.convert("RGBA"), base_im.convert("RGBA") + ) + bbox = delta.getbbox(alpha_only=False) + if ( + not bbox + and prev_disposal == encoderinfo.get("disposal") + and prev_blend == encoderinfo.get("blend") + and "duration" in encoderinfo + ): + previous.encoderinfo["duration"] += encoderinfo["duration"] + continue + else: + bbox = None + im_frames.append(_Frame(im_frame, bbox, encoderinfo)) + + if len(im_frames) == 1 and not default_image: + return im_frames[0].im + + # animation control + chunk( + fp, + b"acTL", + o32(len(im_frames)), # 0: num_frames + o32(loop), # 4: num_plays + ) + + # default image IDAT (if it exists) + if default_image: + default_im = im if im.mode == mode else im.convert(mode) + _apply_encoderinfo(default_im, im.encoderinfo) + ImageFile._save( + default_im, + cast(IO[bytes], _idat(fp, chunk)), + [ImageFile._Tile("zip", (0, 0) + im.size, 0, rawmode)], + ) + + seq_num = 0 + for frame, frame_data in enumerate(im_frames): + im_frame = frame_data.im + if not frame_data.bbox: + bbox = (0, 0) + im_frame.size + else: + bbox = frame_data.bbox + im_frame = im_frame.crop(bbox) + size = im_frame.size + encoderinfo = frame_data.encoderinfo + frame_duration = encoderinfo.get("duration", 0) + delay = Fraction(frame_duration / 1000).limit_denominator(65535) + if delay.numerator > 65535: + msg = "cannot write duration" + raise ValueError(msg) + frame_disposal = encoderinfo.get("disposal", disposal) + frame_blend = encoderinfo.get("blend", blend) + # frame control + chunk( + fp, + b"fcTL", + o32(seq_num), # sequence_number + o32(size[0]), # width + o32(size[1]), # height + o32(bbox[0]), # x_offset + o32(bbox[1]), # y_offset + o16(delay.numerator), # delay_numerator + o16(delay.denominator), # delay_denominator + o8(frame_disposal), # dispose_op + o8(frame_blend), # blend_op + ) + seq_num += 1 + # frame data + _apply_encoderinfo(im_frame, im.encoderinfo) + if frame == 0 and not default_image: + # first frame must be in IDAT chunks for backwards compatibility + ImageFile._save( + im_frame, + cast(IO[bytes], _idat(fp, chunk)), + [ImageFile._Tile("zip", (0, 0) + im_frame.size, 0, rawmode)], + ) + else: + fdat_chunks = _fdat(fp, chunk, seq_num) + ImageFile._save( + im_frame, + cast(IO[bytes], fdat_chunks), + [ImageFile._Tile("zip", (0, 0) + im_frame.size, 0, rawmode)], + ) + seq_num = fdat_chunks.seq_num + return None + + +def _save_all(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + _save(im, fp, filename, save_all=True) + + +def _save( + im: Image.Image, + fp: IO[bytes], + filename: str | bytes, + chunk: Callable[..., None] = putchunk, + save_all: bool = False, +) -> None: + # save an image to disk (called by the save method) + + if save_all: + default_image = im.encoderinfo.get( + "default_image", im.info.get("default_image") + ) + modes = set() + sizes = set() + append_images = im.encoderinfo.get("append_images", []) + for im_seq in itertools.chain([im], append_images): + for im_frame in ImageSequence.Iterator(im_seq): + modes.add(im_frame.mode) + sizes.add(im_frame.size) + for mode in ("RGBA", "RGB", "P"): + if mode in modes: + break + else: + mode = modes.pop() + size = tuple(max(frame_size[i] for frame_size in sizes) for i in range(2)) + else: + size = im.size + mode = im.mode + + outmode = mode + if mode == "P": + # + # attempt to minimize storage requirements for palette images + if "bits" in im.encoderinfo: + # number of bits specified by user + colors = min(1 << im.encoderinfo["bits"], 256) + else: + # check palette contents + if im.palette: + colors = max(min(len(im.palette.getdata()[1]) // 3, 256), 1) + else: + colors = 256 + + if colors <= 16: + if colors <= 2: + bits = 1 + elif colors <= 4: + bits = 2 + else: + bits = 4 + outmode += f";{bits}" + + # get the corresponding PNG mode + try: + rawmode, bit_depth, color_type = _OUTMODES[outmode] + except KeyError as e: + msg = f"cannot write mode {mode} as PNG" + raise OSError(msg) from e + if outmode == "I": + deprecate("Saving I mode images as PNG", 13, stacklevel=4) + + # + # write minimal PNG file + + fp.write(_MAGIC) + + chunk( + fp, + b"IHDR", + o32(size[0]), # 0: size + o32(size[1]), + bit_depth, + color_type, + b"\0", # 10: compression + b"\0", # 11: filter category + b"\0", # 12: interlace flag + ) + + chunks = [b"cHRM", b"cICP", b"gAMA", b"sBIT", b"sRGB", b"tIME"] + + icc = im.encoderinfo.get("icc_profile", im.info.get("icc_profile")) + if icc: + # ICC profile + # according to PNG spec, the iCCP chunk contains: + # Profile name 1-79 bytes (character string) + # Null separator 1 byte (null character) + # Compression method 1 byte (0) + # Compressed profile n bytes (zlib with deflate compression) + name = b"ICC Profile" + data = name + b"\0\0" + zlib.compress(icc) + chunk(fp, b"iCCP", data) + + # You must either have sRGB or iCCP. + # Disallow sRGB chunks when an iCCP-chunk has been emitted. + chunks.remove(b"sRGB") + + info = im.encoderinfo.get("pnginfo") + if info: + chunks_multiple_allowed = [b"sPLT", b"iTXt", b"tEXt", b"zTXt"] + for info_chunk in info.chunks: + cid, data = info_chunk[:2] + if cid in chunks: + chunks.remove(cid) + chunk(fp, cid, data) + elif cid in chunks_multiple_allowed: + chunk(fp, cid, data) + elif cid[1:2].islower(): + # Private chunk + after_idat = len(info_chunk) == 3 and info_chunk[2] + if not after_idat: + chunk(fp, cid, data) + + if im.mode == "P": + palette_byte_number = colors * 3 + palette_bytes = im.im.getpalette("RGB")[:palette_byte_number] + while len(palette_bytes) < palette_byte_number: + palette_bytes += b"\0" + chunk(fp, b"PLTE", palette_bytes) + + transparency = im.encoderinfo.get("transparency", im.info.get("transparency", None)) + + if transparency or transparency == 0: + if im.mode == "P": + # limit to actual palette size + alpha_bytes = colors + if isinstance(transparency, bytes): + chunk(fp, b"tRNS", transparency[:alpha_bytes]) + else: + transparency = max(0, min(255, transparency)) + alpha = b"\xff" * transparency + b"\0" + chunk(fp, b"tRNS", alpha[:alpha_bytes]) + elif im.mode in ("1", "L", "I", "I;16"): + transparency = max(0, min(65535, transparency)) + chunk(fp, b"tRNS", o16(transparency)) + elif im.mode == "RGB": + red, green, blue = transparency + chunk(fp, b"tRNS", o16(red) + o16(green) + o16(blue)) + else: + if "transparency" in im.encoderinfo: + # don't bother with transparency if it's an RGBA + # and it's in the info dict. It's probably just stale. + msg = "cannot use transparency for this mode" + raise OSError(msg) + else: + if im.mode == "P" and im.im.getpalettemode() == "RGBA": + alpha = im.im.getpalette("RGBA", "A") + alpha_bytes = colors + chunk(fp, b"tRNS", alpha[:alpha_bytes]) + + dpi = im.encoderinfo.get("dpi") + if dpi: + chunk( + fp, + b"pHYs", + o32(int(dpi[0] / 0.0254 + 0.5)), + o32(int(dpi[1] / 0.0254 + 0.5)), + b"\x01", + ) + + if info: + chunks = [b"bKGD", b"hIST"] + for info_chunk in info.chunks: + cid, data = info_chunk[:2] + if cid in chunks: + chunks.remove(cid) + chunk(fp, cid, data) + + exif = im.encoderinfo.get("exif") + if exif: + if isinstance(exif, Image.Exif): + exif = exif.tobytes(8) + if exif.startswith(b"Exif\x00\x00"): + exif = exif[6:] + chunk(fp, b"eXIf", exif) + + single_im: Image.Image | None = im + if save_all: + single_im = _write_multiple_frames( + im, fp, chunk, mode, rawmode, default_image, append_images + ) + if single_im: + _apply_encoderinfo(single_im, im.encoderinfo) + ImageFile._save( + single_im, + cast(IO[bytes], _idat(fp, chunk)), + [ImageFile._Tile("zip", (0, 0) + single_im.size, 0, rawmode)], + ) + + if info: + for info_chunk in info.chunks: + cid, data = info_chunk[:2] + if cid[1:2].islower(): + # Private chunk + after_idat = len(info_chunk) == 3 and info_chunk[2] + if after_idat: + chunk(fp, cid, data) + + chunk(fp, b"IEND", b"") + + if hasattr(fp, "flush"): + fp.flush() + + +# -------------------------------------------------------------------- +# PNG chunk converter + + +def getchunks(im: Image.Image, **params: Any) -> list[tuple[bytes, bytes, bytes]]: + """Return a list of PNG chunks representing this image.""" + from io import BytesIO + + chunks = [] + + def append(fp: IO[bytes], cid: bytes, *data: bytes) -> None: + byte_data = b"".join(data) + crc = o32(_crc32(byte_data, _crc32(cid))) + chunks.append((cid, byte_data, crc)) + + fp = BytesIO() + + try: + im.encoderinfo = params + _save(im, fp, "", append) + finally: + del im.encoderinfo + + return chunks + + +# -------------------------------------------------------------------- +# Registry + +Image.register_open(PngImageFile.format, PngImageFile, _accept) +Image.register_save(PngImageFile.format, _save) +Image.register_save_all(PngImageFile.format, _save_all) + +Image.register_extensions(PngImageFile.format, [".png", ".apng"]) + +Image.register_mime(PngImageFile.format, "image/png") diff --git a/PIL/PpmImagePlugin.py b/PIL/PpmImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..307bc97ff65160fabf533d12e96ef4382ed5f1e7 --- /dev/null +++ b/PIL/PpmImagePlugin.py @@ -0,0 +1,375 @@ +# +# The Python Imaging Library. +# $Id$ +# +# PPM support for PIL +# +# History: +# 96-03-24 fl Created +# 98-03-06 fl Write RGBA images (as RGB, that is) +# +# Copyright (c) Secret Labs AB 1997-98. +# Copyright (c) Fredrik Lundh 1996. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import math +from typing import IO + +from . import Image, ImageFile +from ._binary import i16be as i16 +from ._binary import o8 +from ._binary import o32le as o32 + +# +# -------------------------------------------------------------------- + +b_whitespace = b"\x20\x09\x0a\x0b\x0c\x0d" + +MODES = { + # standard + b"P1": "1", + b"P2": "L", + b"P3": "RGB", + b"P4": "1", + b"P5": "L", + b"P6": "RGB", + # extensions + b"P0CMYK": "CMYK", + b"Pf": "F", + # PIL extensions (for test purposes only) + b"PyP": "P", + b"PyRGBA": "RGBA", + b"PyCMYK": "CMYK", +} + + +def _accept(prefix: bytes) -> bool: + return len(prefix) >= 2 and prefix.startswith(b"P") and prefix[1] in b"0123456fy" + + +## +# Image plugin for PBM, PGM, and PPM images. + + +class PpmImageFile(ImageFile.ImageFile): + format = "PPM" + format_description = "Pbmplus image" + + def _read_magic(self) -> bytes: + assert self.fp is not None + + magic = b"" + # read until whitespace or longest available magic number + for _ in range(6): + c = self.fp.read(1) + if not c or c in b_whitespace: + break + magic += c + return magic + + def _read_token(self) -> bytes: + assert self.fp is not None + + token = b"" + while len(token) <= 10: # read until next whitespace or limit of 10 characters + c = self.fp.read(1) + if not c: + break + elif c in b_whitespace: # token ended + if not token: + # skip whitespace at start + continue + break + elif c == b"#": + # ignores rest of the line; stops at CR, LF or EOF + while self.fp.read(1) not in b"\r\n": + pass + continue + token += c + if not token: + # Token was not even 1 byte + msg = "Reached EOF while reading header" + raise ValueError(msg) + elif len(token) > 10: + msg_too_long = b"Token too long in file header: %s" % token + raise ValueError(msg_too_long) + return token + + def _open(self) -> None: + assert self.fp is not None + + magic_number = self._read_magic() + try: + mode = MODES[magic_number] + except KeyError: + msg = "not a PPM file" + raise SyntaxError(msg) + self._mode = mode + + if magic_number in (b"P1", b"P4"): + self.custom_mimetype = "image/x-portable-bitmap" + elif magic_number in (b"P2", b"P5"): + self.custom_mimetype = "image/x-portable-graymap" + elif magic_number in (b"P3", b"P6"): + self.custom_mimetype = "image/x-portable-pixmap" + + self._size = int(self._read_token()), int(self._read_token()) + + decoder_name = "raw" + if magic_number in (b"P1", b"P2", b"P3"): + decoder_name = "ppm_plain" + + args: str | tuple[str | int, ...] + if mode == "1": + args = "1;I" + elif mode == "F": + scale = float(self._read_token()) + if scale == 0.0 or not math.isfinite(scale): + msg = "scale must be finite and non-zero" + raise ValueError(msg) + self.info["scale"] = abs(scale) + + rawmode = "F;32F" if scale < 0 else "F;32BF" + args = (rawmode, 0, -1) + else: + maxval = int(self._read_token()) + if not 0 < maxval < 65536: + msg = "maxval must be greater than 0 and less than 65536" + raise ValueError(msg) + if maxval > 255 and mode == "L": + self._mode = "I" + + rawmode = mode + if decoder_name != "ppm_plain": + # If maxval matches a bit depth, use the raw decoder directly + if maxval == 65535 and mode == "L": + rawmode = "I;16B" + elif maxval != 255: + decoder_name = "ppm" + + args = rawmode if decoder_name == "raw" else (rawmode, maxval) + self.tile = [ + ImageFile._Tile(decoder_name, (0, 0) + self.size, self.fp.tell(), args) + ] + + +# +# -------------------------------------------------------------------- + + +class PpmPlainDecoder(ImageFile.PyDecoder): + _pulls_fd = True + _comment_spans: bool + + def _read_block(self) -> bytes: + assert self.fd is not None + + return self.fd.read(ImageFile.SAFEBLOCK) + + def _find_comment_end(self, block: bytes, start: int = 0) -> int: + a = block.find(b"\n", start) + b = block.find(b"\r", start) + return min(a, b) if a * b > 0 else max(a, b) # lowest nonnegative index (or -1) + + def _ignore_comments(self, block: bytes) -> bytes: + if self._comment_spans: + # Finish current comment + while block: + comment_end = self._find_comment_end(block) + if comment_end != -1: + # Comment ends in this block + # Delete tail of comment + block = block[comment_end + 1 :] + break + else: + # Comment spans whole block + # So read the next block, looking for the end + block = self._read_block() + + # Search for any further comments + self._comment_spans = False + while True: + comment_start = block.find(b"#") + if comment_start == -1: + # No comment found + break + comment_end = self._find_comment_end(block, comment_start) + if comment_end != -1: + # Comment ends in this block + # Delete comment + block = block[:comment_start] + block[comment_end + 1 :] + else: + # Comment continues to next block(s) + block = block[:comment_start] + self._comment_spans = True + break + return block + + def _decode_bitonal(self) -> bytearray: + """ + This is a separate method because in the plain PBM format, all data tokens are + exactly one byte, so the inter-token whitespace is optional. + """ + data = bytearray() + total_bytes = self.state.xsize * self.state.ysize + + while len(data) != total_bytes: + block = self._read_block() # read next block + if not block: + # eof + break + + block = self._ignore_comments(block) + + tokens = b"".join(block.split()) + for token in tokens: + if token not in (48, 49): + msg = b"Invalid token for this mode: %s" % bytes([token]) + raise ValueError(msg) + data = (data + tokens)[:total_bytes] + invert = bytes.maketrans(b"01", b"\xff\x00") + return data.translate(invert) + + def _decode_blocks(self, maxval: int) -> bytearray: + data = bytearray() + max_len = 10 + out_byte_count = 4 if self.mode == "I" else 1 + out_max = 65535 if self.mode == "I" else 255 + bands = Image.getmodebands(self.mode) + total_bytes = self.state.xsize * self.state.ysize * bands * out_byte_count + + half_token = b"" + while len(data) != total_bytes: + block = self._read_block() # read next block + if not block: + if half_token: + block = bytearray(b" ") # flush half_token + else: + # eof + break + + block = self._ignore_comments(block) + + if half_token: + block = half_token + block # stitch half_token to new block + half_token = b"" + + tokens = block.split() + + if block and not block[-1:].isspace(): # block might split token + half_token = tokens.pop() # save half token for later + if len(half_token) > max_len: # prevent buildup of half_token + msg = ( + b"Token too long found in data: %s" % half_token[: max_len + 1] + ) + raise ValueError(msg) + + for token in tokens: + if len(token) > max_len: + msg = b"Token too long found in data: %s" % token[: max_len + 1] + raise ValueError(msg) + value = int(token) + if value < 0: + msg_str = f"Channel value is negative: {value}" + raise ValueError(msg_str) + if value > maxval: + msg_str = f"Channel value too large for this mode: {value}" + raise ValueError(msg_str) + value = round(value / maxval * out_max) + data += o32(value) if self.mode == "I" else o8(value) + if len(data) == total_bytes: # finished! + break + return data + + def decode(self, buffer: bytes | Image.SupportsArrayInterface) -> tuple[int, int]: + self._comment_spans = False + if self.mode == "1": + data = self._decode_bitonal() + rawmode = "1;8" + else: + maxval = self.args[-1] + data = self._decode_blocks(maxval) + rawmode = "I;32" if self.mode == "I" else self.mode + self.set_as_raw(bytes(data), rawmode) + return -1, 0 + + +class PpmDecoder(ImageFile.PyDecoder): + _pulls_fd = True + + def decode(self, buffer: bytes | Image.SupportsArrayInterface) -> tuple[int, int]: + assert self.fd is not None + + data = bytearray() + maxval = self.args[-1] + in_byte_count = 1 if maxval < 256 else 2 + out_byte_count = 4 if self.mode == "I" else 1 + out_max = 65535 if self.mode == "I" else 255 + bands = Image.getmodebands(self.mode) + dest_length = self.state.xsize * self.state.ysize * bands * out_byte_count + while len(data) < dest_length: + pixels = self.fd.read(in_byte_count * bands) + if len(pixels) < in_byte_count * bands: + # eof + break + for b in range(bands): + value = ( + pixels[b] if in_byte_count == 1 else i16(pixels, b * in_byte_count) + ) + value = min(out_max, round(value / maxval * out_max)) + data += o32(value) if self.mode == "I" else o8(value) + rawmode = "I;32" if self.mode == "I" else self.mode + self.set_as_raw(bytes(data), rawmode) + return -1, 0 + + +# +# -------------------------------------------------------------------- + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + if im.mode == "1": + rawmode, head = "1;I", b"P4" + elif im.mode == "L": + rawmode, head = "L", b"P5" + elif im.mode in ("I", "I;16"): + rawmode, head = "I;16B", b"P5" + elif im.mode in ("RGB", "RGBA"): + rawmode, head = "RGB", b"P6" + elif im.mode == "F": + rawmode, head = "F;32F", b"Pf" + else: + msg = f"cannot write mode {im.mode} as PPM" + raise OSError(msg) + fp.write(head + b"\n%d %d\n" % im.size) + if head == b"P6": + fp.write(b"255\n") + elif head == b"P5": + if rawmode == "L": + fp.write(b"255\n") + else: + fp.write(b"65535\n") + elif head == b"Pf": + fp.write(b"-1.0\n") + row_order = -1 if im.mode == "F" else 1 + ImageFile._save( + im, fp, [ImageFile._Tile("raw", (0, 0) + im.size, 0, (rawmode, 0, row_order))] + ) + + +# +# -------------------------------------------------------------------- + + +Image.register_open(PpmImageFile.format, PpmImageFile, _accept) +Image.register_save(PpmImageFile.format, _save) + +Image.register_decoder("ppm", PpmDecoder) +Image.register_decoder("ppm_plain", PpmPlainDecoder) + +Image.register_extensions(PpmImageFile.format, [".pbm", ".pgm", ".ppm", ".pnm", ".pfm"]) + +Image.register_mime(PpmImageFile.format, "image/x-portable-anymap") diff --git a/PIL/PsdImagePlugin.py b/PIL/PsdImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..69a8703dd8b5b11261cd7c1200840b1a7764aa79 --- /dev/null +++ b/PIL/PsdImagePlugin.py @@ -0,0 +1,334 @@ +# +# The Python Imaging Library +# $Id$ +# +# Adobe PSD 2.5/3.0 file handling +# +# History: +# 1995-09-01 fl Created +# 1997-01-03 fl Read most PSD images +# 1997-01-18 fl Fixed P and CMYK support +# 2001-10-21 fl Added seek/tell support (for layers) +# +# Copyright (c) 1997-2001 by Secret Labs AB. +# Copyright (c) 1995-2001 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import io +from functools import cached_property +from typing import IO + +from . import Image, ImageFile, ImagePalette +from ._binary import i8 +from ._binary import i16be as i16 +from ._binary import i32be as i32 +from ._binary import si16be as si16 +from ._binary import si32be as si32 +from ._util import DeferredError + +MODES = { + # (photoshop mode, bits) -> (pil mode, required channels) + (0, 1): ("1", 1), + (0, 8): ("L", 1), + (1, 8): ("L", 1), + (2, 8): ("P", 1), + (3, 8): ("RGB", 3), + (4, 8): ("CMYK", 4), + (7, 8): ("L", 1), # FIXME: multilayer + (8, 8): ("L", 1), # duotone + (9, 8): ("LAB", 3), +} + + +# --------------------------------------------------------------------. +# read PSD images + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith(b"8BPS") + + +## +# Image plugin for Photoshop images. + + +class PsdImageFile(ImageFile.ImageFile): + format = "PSD" + format_description = "Adobe Photoshop" + _close_exclusive_fp_after_loading = False + + def _open(self) -> None: + assert self.fp is not None + read = self.fp.read + + # + # header + + s = read(26) + if not _accept(s) or i16(s, 4) != 1: + msg = "not a PSD file" + raise SyntaxError(msg) + + psd_bits = i16(s, 22) + psd_channels = i16(s, 12) + psd_mode = i16(s, 24) + + mode, channels = MODES[(psd_mode, psd_bits)] + + if channels > psd_channels: + msg = "not enough channels" + raise OSError(msg) + if mode == "RGB" and psd_channels == 4: + mode = "RGBA" + channels = 4 + + self._mode = mode + self._size = i32(s, 18), i32(s, 14) + + # + # color mode data + + size = i32(read(4)) + if size: + data = read(size) + if mode == "P" and size == 768: + self.palette = ImagePalette.raw("RGB;L", data) + + # + # image resources + + self.resources = [] + + size = i32(read(4)) + if size: + # load resources + end = self.fp.tell() + size + while self.fp.tell() < end: + read(4) # signature + id = i16(read(2)) + name = read(i8(read(1))) + if not (len(name) & 1): + read(1) # padding + data = read(i32(read(4))) + if len(data) & 1: + read(1) # padding + self.resources.append((id, name, data)) + if id == 1039: # ICC profile + self.info["icc_profile"] = data + + # + # layer and mask information + + self._layers_position = None + + size = i32(read(4)) + if size: + end = self.fp.tell() + size + size = i32(read(4)) + if size: + self._layers_position = self.fp.tell() + self._layers_size = size + self.fp.seek(end) + self._n_frames: int | None = None + + # + # image descriptor + + self.tile = _maketile(self.fp, mode, (0, 0) + self.size, channels) + + # keep the file open + self._fp = self.fp + self.frame = 1 + self._min_frame = 1 + + @cached_property + def layers( + self, + ) -> list[tuple[str, str, tuple[int, int, int, int], list[ImageFile._Tile]]]: + layers = [] + if self._layers_position is not None: + if isinstance(self._fp, DeferredError): + raise self._fp.ex + self._fp.seek(self._layers_position) + _layer_data = io.BytesIO(ImageFile._safe_read(self._fp, self._layers_size)) + layers = _layerinfo(_layer_data, self._layers_size) + self._n_frames = len(layers) + return layers + + @property + def n_frames(self) -> int: + if self._n_frames is None: + self._n_frames = len(self.layers) + return self._n_frames + + @property + def is_animated(self) -> bool: + return len(self.layers) > 1 + + def seek(self, layer: int) -> None: + if not self._seek_check(layer): + return + if isinstance(self._fp, DeferredError): + raise self._fp.ex + + # seek to given layer (1..max) + _, mode, _, tile = self.layers[layer - 1] + self._mode = mode + self.tile = tile + self.frame = layer + self.fp = self._fp + + def tell(self) -> int: + # return layer number (0=image, 1..max=layers) + return self.frame + + +def _layerinfo( + fp: IO[bytes], ct_bytes: int +) -> list[tuple[str, str, tuple[int, int, int, int], list[ImageFile._Tile]]]: + # read layerinfo block + layers = [] + + def read(size: int) -> bytes: + return ImageFile._safe_read(fp, size) + + ct = si16(read(2)) + + # sanity check + if ct_bytes < (abs(ct) * 20): + msg = "Layer block too short for number of layers requested" + raise SyntaxError(msg) + + for _ in range(abs(ct)): + # bounding box + y0 = si32(read(4)) + x0 = si32(read(4)) + y1 = si32(read(4)) + x1 = si32(read(4)) + + # image info + bands = [] + ct_types = i16(read(2)) + if ct_types > 4: + fp.seek(ct_types * 6 + 12, io.SEEK_CUR) + size = i32(read(4)) + fp.seek(size, io.SEEK_CUR) + continue + + for _ in range(ct_types): + type = i16(read(2)) + + if type == 65535: + b = "A" + else: + b = "RGBA"[type] + + bands.append(b) + read(4) # size + + # figure out the image mode + bands.sort() + if bands == ["R"]: + mode = "L" + elif bands == ["B", "G", "R"]: + mode = "RGB" + elif bands == ["A", "B", "G", "R"]: + mode = "RGBA" + else: + mode = "" # unknown + + # skip over blend flags and extra information + read(12) # filler + name = "" + size = i32(read(4)) # length of the extra data field + if size: + data_end = fp.tell() + size + + length = i32(read(4)) + if length: + fp.seek(length - 16, io.SEEK_CUR) + + length = i32(read(4)) + if length: + fp.seek(length, io.SEEK_CUR) + + length = i8(read(1)) + if length: + # Don't know the proper encoding, + # Latin-1 should be a good guess + name = read(length).decode("latin-1", "replace") + + fp.seek(data_end) + layers.append((name, mode, (x0, y0, x1, y1))) + + # get tiles + layerinfo = [] + for i, (name, mode, bbox) in enumerate(layers): + tile = [] + for m in mode: + t = _maketile(fp, m, bbox, 1) + if t: + tile.extend(t) + layerinfo.append((name, mode, bbox, tile)) + + return layerinfo + + +def _maketile( + file: IO[bytes], mode: str, bbox: tuple[int, int, int, int], channels: int +) -> list[ImageFile._Tile]: + tiles = [] + read = file.read + + compression = i16(read(2)) + + xsize = bbox[2] - bbox[0] + ysize = bbox[3] - bbox[1] + + offset = file.tell() + + if compression == 0: + # + # raw compression + for channel in range(channels): + layer = mode[channel] + if mode == "CMYK": + layer += ";I" + tiles.append(ImageFile._Tile("raw", bbox, offset, layer)) + offset = offset + xsize * ysize + + elif compression == 1: + # + # packbits compression + i = 0 + bytecount = read(channels * ysize * 2) + offset = file.tell() + for channel in range(channels): + layer = mode[channel] + if mode == "CMYK": + layer += ";I" + tiles.append(ImageFile._Tile("packbits", bbox, offset, layer)) + for y in range(ysize): + offset = offset + i16(bytecount, i) + i += 2 + + file.seek(offset) + + if offset & 1: + read(1) # padding + + return tiles + + +# -------------------------------------------------------------------- +# registry + + +Image.register_open(PsdImageFile.format, PsdImageFile, _accept) + +Image.register_extension(PsdImageFile.format, ".psd") + +Image.register_mime(PsdImageFile.format, "image/vnd.adobe.photoshop") diff --git a/PIL/QoiImagePlugin.py b/PIL/QoiImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..d0709b1198a4376b8ac228833eb94f14a861ca76 --- /dev/null +++ b/PIL/QoiImagePlugin.py @@ -0,0 +1,235 @@ +# +# The Python Imaging Library. +# +# QOI support for PIL +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import os +from typing import IO + +from . import Image, ImageFile +from ._binary import i32be as i32 +from ._binary import o8 +from ._binary import o32be as o32 + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith(b"qoif") + + +class QoiImageFile(ImageFile.ImageFile): + format = "QOI" + format_description = "Quite OK Image" + + def _open(self) -> None: + assert self.fp is not None + if not _accept(self.fp.read(4)): + msg = "not a QOI file" + raise SyntaxError(msg) + + self._size = i32(self.fp.read(4)), i32(self.fp.read(4)) + + channels = self.fp.read(1)[0] + self._mode = "RGB" if channels == 3 else "RGBA" + + self.fp.seek(1, os.SEEK_CUR) # colorspace + self.tile = [ImageFile._Tile("qoi", (0, 0) + self._size, self.fp.tell())] + + +class QoiDecoder(ImageFile.PyDecoder): + _pulls_fd = True + _previous_pixel: bytes | bytearray | None = None + _previously_seen_pixels: dict[int, bytes | bytearray] = {} + + def _add_to_previous_pixels(self, value: bytes | bytearray) -> None: + self._previous_pixel = value + + r, g, b, a = value + hash_value = (r * 3 + g * 5 + b * 7 + a * 11) % 64 + self._previously_seen_pixels[hash_value] = value + + def decode(self, buffer: bytes | Image.SupportsArrayInterface) -> tuple[int, int]: + assert self.fd is not None + + self._previously_seen_pixels = {} + self._previous_pixel = bytearray((0, 0, 0, 255)) + + data = bytearray() + bands = Image.getmodebands(self.mode) + dest_length = self.state.xsize * self.state.ysize * bands + while len(data) < dest_length: + byte = self.fd.read(1)[0] + value: bytes | bytearray + if byte == 0b11111110 and self._previous_pixel: # QOI_OP_RGB + value = bytearray(self.fd.read(3)) + self._previous_pixel[3:] + elif byte == 0b11111111: # QOI_OP_RGBA + value = self.fd.read(4) + else: + op = byte >> 6 + if op == 0: # QOI_OP_INDEX + op_index = byte & 0b00111111 + value = self._previously_seen_pixels.get( + op_index, bytearray((0, 0, 0, 0)) + ) + elif op == 1 and self._previous_pixel: # QOI_OP_DIFF + value = bytearray( + ( + (self._previous_pixel[0] + ((byte & 0b00110000) >> 4) - 2) + % 256, + (self._previous_pixel[1] + ((byte & 0b00001100) >> 2) - 2) + % 256, + (self._previous_pixel[2] + (byte & 0b00000011) - 2) % 256, + self._previous_pixel[3], + ) + ) + elif op == 2 and self._previous_pixel: # QOI_OP_LUMA + second_byte = self.fd.read(1)[0] + diff_green = (byte & 0b00111111) - 32 + diff_red = ((second_byte & 0b11110000) >> 4) - 8 + diff_blue = (second_byte & 0b00001111) - 8 + + value = bytearray( + tuple( + (self._previous_pixel[i] + diff_green + diff) % 256 + for i, diff in enumerate((diff_red, 0, diff_blue)) + ) + ) + value += self._previous_pixel[3:] + elif op == 3 and self._previous_pixel: # QOI_OP_RUN + run_length = (byte & 0b00111111) + 1 + value = self._previous_pixel + if bands == 3: + value = value[:3] + data += value * run_length + continue + self._add_to_previous_pixels(value) + + if bands == 3: + value = value[:3] + data += value + self.set_as_raw(data) + return -1, 0 + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + if im.mode == "RGB": + channels = 3 + elif im.mode == "RGBA": + channels = 4 + else: + msg = "Unsupported QOI image mode" + raise ValueError(msg) + + colorspace = 0 if im.encoderinfo.get("colorspace") == "sRGB" else 1 + + fp.write(b"qoif") + fp.write(o32(im.size[0])) + fp.write(o32(im.size[1])) + fp.write(o8(channels)) + fp.write(o8(colorspace)) + + ImageFile._save(im, fp, [ImageFile._Tile("qoi", (0, 0) + im.size)]) + + +class QoiEncoder(ImageFile.PyEncoder): + _pushes_fd = True + _previous_pixel: tuple[int, int, int, int] | None = None + _previously_seen_pixels: dict[int, tuple[int, int, int, int]] = {} + _run = 0 + + def _write_run(self) -> bytes: + data = o8(0b11000000 | (self._run - 1)) # QOI_OP_RUN + self._run = 0 + return data + + def _delta(self, left: int, right: int) -> int: + result = (left - right) & 255 + if result >= 128: + result -= 256 + return result + + def encode(self, bufsize: int) -> tuple[int, int, bytes]: + assert self.im is not None + + self._previously_seen_pixels = {0: (0, 0, 0, 0)} + self._previous_pixel = (0, 0, 0, 255) + + data = bytearray() + w, h = self.im.size + bands = Image.getmodebands(self.mode) + + for y in range(h): + for x in range(w): + pixel = self.im.getpixel((x, y)) + if bands == 3: + pixel = (*pixel, 255) + + if pixel == self._previous_pixel: + self._run += 1 + if self._run == 62: + data += self._write_run() + else: + if self._run: + data += self._write_run() + + r, g, b, a = pixel + hash_value = (r * 3 + g * 5 + b * 7 + a * 11) % 64 + if self._previously_seen_pixels.get(hash_value) == pixel: + data += o8(hash_value) # QOI_OP_INDEX + elif self._previous_pixel: + self._previously_seen_pixels[hash_value] = pixel + + prev_r, prev_g, prev_b, prev_a = self._previous_pixel + if prev_a == a: + delta_r = self._delta(r, prev_r) + delta_g = self._delta(g, prev_g) + delta_b = self._delta(b, prev_b) + + if ( + -2 <= delta_r < 2 + and -2 <= delta_g < 2 + and -2 <= delta_b < 2 + ): + data += o8( + 0b01000000 + | (delta_r + 2) << 4 + | (delta_g + 2) << 2 + | (delta_b + 2) + ) # QOI_OP_DIFF + else: + delta_gr = self._delta(delta_r, delta_g) + delta_gb = self._delta(delta_b, delta_g) + if ( + -8 <= delta_gr < 8 + and -32 <= delta_g < 32 + and -8 <= delta_gb < 8 + ): + data += o8( + 0b10000000 | (delta_g + 32) + ) # QOI_OP_LUMA + data += o8((delta_gr + 8) << 4 | (delta_gb + 8)) + else: + data += o8(0b11111110) # QOI_OP_RGB + data += bytes(pixel[:3]) + else: + data += o8(0b11111111) # QOI_OP_RGBA + data += bytes(pixel) + + self._previous_pixel = pixel + + if self._run: + data += self._write_run() + data += bytes((0, 0, 0, 0, 0, 0, 0, 1)) # padding + + return len(data), 0, data + + +Image.register_open(QoiImageFile.format, QoiImageFile, _accept) +Image.register_decoder("qoi", QoiDecoder) +Image.register_extension(QoiImageFile.format, ".qoi") + +Image.register_save(QoiImageFile.format, _save) +Image.register_encoder("qoi", QoiEncoder) diff --git a/PIL/SgiImagePlugin.py b/PIL/SgiImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..853022150ae849e490378e41e831897050c207a2 --- /dev/null +++ b/PIL/SgiImagePlugin.py @@ -0,0 +1,231 @@ +# +# The Python Imaging Library. +# $Id$ +# +# SGI image file handling +# +# See "The SGI Image File Format (Draft version 0.97)", Paul Haeberli. +# +# +# +# History: +# 2017-22-07 mb Add RLE decompression +# 2016-16-10 mb Add save method without compression +# 1995-09-10 fl Created +# +# Copyright (c) 2016 by Mickael Bonfill. +# Copyright (c) 2008 by Karsten Hiddemann. +# Copyright (c) 1997 by Secret Labs AB. +# Copyright (c) 1995 by Fredrik Lundh. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import os +import struct +from typing import IO + +from . import Image, ImageFile +from ._binary import i16be as i16 +from ._binary import o8 + + +def _accept(prefix: bytes) -> bool: + return len(prefix) >= 2 and i16(prefix) == 474 + + +MODES = { + (1, 1, 1): "L", + (1, 2, 1): "L", + (2, 1, 1): "L;16B", + (2, 2, 1): "L;16B", + (1, 3, 3): "RGB", + (2, 3, 3): "RGB;16B", + (1, 3, 4): "RGBA", + (2, 3, 4): "RGBA;16B", +} + + +## +# Image plugin for SGI images. +class SgiImageFile(ImageFile.ImageFile): + format = "SGI" + format_description = "SGI Image File Format" + + def _open(self) -> None: + # HEAD + assert self.fp is not None + + headlen = 512 + s = self.fp.read(headlen) + + if not _accept(s): + msg = "Not an SGI image file" + raise ValueError(msg) + + # compression : verbatim or RLE + compression = s[2] + + # bpc : 1 or 2 bytes (8bits or 16bits) + bpc = s[3] + + # dimension : 1, 2 or 3 (depending on xsize, ysize and zsize) + dimension = i16(s, 4) + + # xsize : width + xsize = i16(s, 6) + + # ysize : height + ysize = i16(s, 8) + + # zsize : channels count + zsize = i16(s, 10) + + # determine mode from bits/zsize + try: + rawmode = MODES[(bpc, dimension, zsize)] + except KeyError: + msg = "Unsupported SGI image mode" + raise ValueError(msg) + + self._size = xsize, ysize + self._mode = rawmode.split(";")[0] + if self.mode == "RGB": + self.custom_mimetype = "image/rgb" + + # orientation -1 : scanlines begins at the bottom-left corner + orientation = -1 + + # decoder info + if compression == 0: + pagesize = xsize * ysize * bpc + if bpc == 2: + self.tile = [ + ImageFile._Tile( + "SGI16", + (0, 0) + self.size, + headlen, + (self.mode, 0, orientation), + ) + ] + else: + self.tile = [] + offset = headlen + for layer in self.mode: + self.tile.append( + ImageFile._Tile( + "raw", (0, 0) + self.size, offset, (layer, 0, orientation) + ) + ) + offset += pagesize + elif compression == 1: + self.tile = [ + ImageFile._Tile( + "sgi_rle", (0, 0) + self.size, headlen, (rawmode, orientation, bpc) + ) + ] + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + if im.mode not in {"RGB", "RGBA", "L"}: + msg = "Unsupported SGI image mode" + raise ValueError(msg) + + # Get the keyword arguments + info = im.encoderinfo + + # Byte-per-pixel precision, 1 = 8bits per pixel + bpc = info.get("bpc", 1) + + if bpc not in (1, 2): + msg = "Unsupported number of bytes per pixel" + raise ValueError(msg) + + # Flip the image, since the origin of SGI file is the bottom-left corner + orientation = -1 + # Define the file as SGI File Format + magic_number = 474 + # Run-Length Encoding Compression - Unsupported at this time + rle = 0 + + # X Dimension = width / Y Dimension = height + x, y = im.size + # Z Dimension: Number of channels + z = len(im.mode) + # Number of dimensions (x,y,z) + if im.mode == "L": + dimension = 1 if y == 1 else 2 + else: + dimension = 3 + + # Minimum Byte value + pinmin = 0 + # Maximum Byte value (255 = 8bits per pixel) + pinmax = 255 + # Image name (79 characters max, truncated below in write) + img_name = os.path.splitext(os.path.basename(filename))[0] + if isinstance(img_name, str): + img_name = img_name.encode("ascii", "ignore") + # Standard representation of pixel in the file + colormap = 0 + fp.write(struct.pack(">h", magic_number)) + fp.write(o8(rle)) + fp.write(o8(bpc)) + fp.write(struct.pack(">H", dimension)) + fp.write(struct.pack(">H", x)) + fp.write(struct.pack(">H", y)) + fp.write(struct.pack(">H", z)) + fp.write(struct.pack(">l", pinmin)) + fp.write(struct.pack(">l", pinmax)) + fp.write(struct.pack("4s", b"")) # dummy + fp.write(struct.pack("79s", img_name)) # truncates to 79 chars + fp.write(struct.pack("s", b"")) # force null byte after img_name + fp.write(struct.pack(">l", colormap)) + fp.write(struct.pack("404s", b"")) # dummy + + rawmode = "L" + if bpc == 2: + rawmode = "L;16B" + + for channel in im.split(): + fp.write(channel.tobytes("raw", rawmode, 0, orientation)) + + if hasattr(fp, "flush"): + fp.flush() + + +class SGI16Decoder(ImageFile.PyDecoder): + _pulls_fd = True + + def decode(self, buffer: bytes | Image.SupportsArrayInterface) -> tuple[int, int]: + assert self.fd is not None + assert self.im is not None + + rawmode, stride, orientation = self.args + pagesize = self.state.xsize * self.state.ysize + zsize = len(self.mode) + self.fd.seek(512) + + for band in range(zsize): + channel = Image.new("L", (self.state.xsize, self.state.ysize)) + channel.frombytes( + self.fd.read(2 * pagesize), "raw", "L;16B", stride, orientation + ) + self.im.putband(channel.im, band) + + return -1, 0 + + +# +# registry + + +Image.register_decoder("SGI16", SGI16Decoder) +Image.register_open(SgiImageFile.format, SgiImageFile, _accept) +Image.register_save(SgiImageFile.format, _save) +Image.register_mime(SgiImageFile.format, "image/sgi") + +Image.register_extensions(SgiImageFile.format, [".bw", ".rgb", ".rgba", ".sgi"]) + +# End of file diff --git a/PIL/SpiderImagePlugin.py b/PIL/SpiderImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..8662922437eaa2977b9b192cb08c94eb6092324d --- /dev/null +++ b/PIL/SpiderImagePlugin.py @@ -0,0 +1,332 @@ +# +# The Python Imaging Library. +# +# SPIDER image file handling +# +# History: +# 2004-08-02 Created BB +# 2006-03-02 added save method +# 2006-03-13 added support for stack images +# +# Copyright (c) 2004 by Health Research Inc. (HRI) RENSSELAER, NY 12144. +# Copyright (c) 2004 by William Baxter. +# Copyright (c) 2004 by Secret Labs AB. +# Copyright (c) 2004 by Fredrik Lundh. +# + +## +# Image plugin for the Spider image format. This format is used +# by the SPIDER software, in processing image data from electron +# microscopy and tomography. +## + +# +# SpiderImagePlugin.py +# +# The Spider image format is used by SPIDER software, in processing +# image data from electron microscopy and tomography. +# +# Spider home page: +# https://spider.wadsworth.org/spider_doc/spider/docs/spider.html +# +# Details about the Spider image format: +# https://spider.wadsworth.org/spider_doc/spider/docs/image_doc.html +# +from __future__ import annotations + +import os +import struct +import sys +from typing import IO, Any, cast + +from . import Image, ImageFile +from ._util import DeferredError + +TYPE_CHECKING = False + + +def isInt(f: Any) -> int: + try: + i = int(f) + if f - i == 0: + return 1 + else: + return 0 + except (ValueError, OverflowError): + return 0 + + +iforms = [1, 3, -11, -12, -21, -22] + + +# There is no magic number to identify Spider files, so just check a +# series of header locations to see if they have reasonable values. +# Returns no. of bytes in the header, if it is a valid Spider header, +# otherwise returns 0 + + +def isSpiderHeader(t: tuple[float, ...]) -> int: + h = (99,) + t # add 1 value so can use spider header index start=1 + # header values 1,2,5,12,13,22,23 should be integers + for i in [1, 2, 5, 12, 13, 22, 23]: + if not isInt(h[i]): + return 0 + # check iform + iform = int(h[5]) + if iform not in iforms: + return 0 + # check other header values + labrec = int(h[13]) # no. records in file header + labbyt = int(h[22]) # total no. of bytes in header + lenbyt = int(h[23]) # record length in bytes + if labbyt != (labrec * lenbyt): + return 0 + # looks like a valid header + return labbyt + + +def isSpiderImage(filename: str) -> int: + with open(filename, "rb") as fp: + f = fp.read(92) # read 23 * 4 bytes + t = struct.unpack(">23f", f) # try big-endian first + hdrlen = isSpiderHeader(t) + if hdrlen == 0: + t = struct.unpack("<23f", f) # little-endian + hdrlen = isSpiderHeader(t) + return hdrlen + + +class SpiderImageFile(ImageFile.ImageFile): + format = "SPIDER" + format_description = "Spider 2D image" + _close_exclusive_fp_after_loading = False + + def _open(self) -> None: + # check header + n = 27 * 4 # read 27 float values + assert self.fp is not None + f = self.fp.read(n) + + try: + self.bigendian = 1 + t = struct.unpack(">27f", f) # try big-endian first + hdrlen = isSpiderHeader(t) + if hdrlen == 0: + self.bigendian = 0 + t = struct.unpack("<27f", f) # little-endian + hdrlen = isSpiderHeader(t) + if hdrlen == 0: + msg = "not a valid Spider file" + raise SyntaxError(msg) + except struct.error as e: + msg = "not a valid Spider file" + raise SyntaxError(msg) from e + + h = (99,) + t # add 1 value : spider header index starts at 1 + iform = int(h[5]) + if iform != 1: + msg = "not a Spider 2D image" + raise SyntaxError(msg) + + self._size = int(h[12]), int(h[2]) # size in pixels (width, height) + self.istack = int(h[24]) + self.imgnumber = int(h[27]) + + if self.istack == 0 and self.imgnumber == 0: + # stk=0, img=0: a regular 2D image + offset = hdrlen + self._nimages = 1 + elif self.istack > 0 and self.imgnumber == 0: + # stk>0, img=0: Opening the stack for the first time + self.imgbytes = int(h[12]) * int(h[2]) * 4 + self.hdrlen = hdrlen + self._nimages = int(h[26]) + # Point to the first image in the stack + offset = hdrlen * 2 + self.imgnumber = 1 + elif self.istack == 0 and self.imgnumber > 0: + # stk=0, img>0: an image within the stack + offset = hdrlen + self.stkoffset + self.istack = 2 # So Image knows it's still a stack + else: + msg = "inconsistent stack header values" + raise SyntaxError(msg) + + if self.bigendian: + self.rawmode = "F;32BF" + else: + self.rawmode = "F;32F" + self._mode = "F" + + self.tile = [ImageFile._Tile("raw", (0, 0) + self.size, offset, self.rawmode)] + self._fp = self.fp # FIXME: hack + + @property + def n_frames(self) -> int: + return self._nimages + + @property + def is_animated(self) -> bool: + return self._nimages > 1 + + # 1st image index is zero (although SPIDER imgnumber starts at 1) + def tell(self) -> int: + if self.imgnumber < 1: + return 0 + else: + return self.imgnumber - 1 + + def seek(self, frame: int) -> None: + if self.istack == 0: + msg = "attempt to seek in a non-stack file" + raise EOFError(msg) + if not self._seek_check(frame): + return + if isinstance(self._fp, DeferredError): + raise self._fp.ex + self.stkoffset = self.hdrlen + frame * (self.hdrlen + self.imgbytes) + self.fp = self._fp + self.fp.seek(self.stkoffset) + self._open() + + # returns a byte image after rescaling to 0..255 + def convert2byte(self, depth: int = 255) -> Image.Image: + extrema = self.getextrema() + assert isinstance(extrema[0], float) + minimum, maximum = cast(tuple[float, float], extrema) + m: float = 1 + if maximum != minimum: + m = depth / (maximum - minimum) + b = -m * minimum + return self.point(lambda i: i * m + b).convert("L") + + if TYPE_CHECKING: + from . import ImageTk + + # returns a ImageTk.PhotoImage object, after rescaling to 0..255 + def tkPhotoImage(self) -> ImageTk.PhotoImage: + from . import ImageTk + + return ImageTk.PhotoImage(self.convert2byte(), palette=256) + + +# -------------------------------------------------------------------- +# Image series + + +# given a list of filenames, return a list of images +def loadImageSeries(filelist: list[str] | None = None) -> list[Image.Image] | None: + """create a list of :py:class:`~PIL.Image.Image` objects for use in a montage""" + if filelist is None or len(filelist) < 1: + return None + + byte_imgs = [] + for img in filelist: + if not os.path.exists(img): + print(f"unable to find {img}") + continue + try: + with Image.open(img) as im: + assert isinstance(im, SpiderImageFile) + byte_im = im.convert2byte() + except Exception: + if not isSpiderImage(img): + print(f"{img} is not a Spider image file") + continue + byte_im.info["filename"] = img + byte_imgs.append(byte_im) + return byte_imgs + + +# -------------------------------------------------------------------- +# For saving images in Spider format + + +def makeSpiderHeader(im: Image.Image) -> list[bytes]: + nsam, nrow = im.size + lenbyt = nsam * 4 # There are labrec records in the header + labrec = int(1024 / lenbyt) + if 1024 % lenbyt != 0: + labrec += 1 + labbyt = labrec * lenbyt + nvalues = int(labbyt / 4) + if nvalues < 23: + return [] + + hdr = [0.0] * nvalues + + # NB these are Fortran indices + hdr[1] = 1.0 # nslice (=1 for an image) + hdr[2] = float(nrow) # number of rows per slice + hdr[3] = float(nrow) # number of records in the image + hdr[5] = 1.0 # iform for 2D image + hdr[12] = float(nsam) # number of pixels per line + hdr[13] = float(labrec) # number of records in file header + hdr[22] = float(labbyt) # total number of bytes in header + hdr[23] = float(lenbyt) # record length in bytes + + # adjust for Fortran indexing + hdr = hdr[1:] + hdr.append(0.0) + # pack binary data into a string + return [struct.pack("f", v) for v in hdr] + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + if im.mode != "F": + im = im.convert("F") + + hdr = makeSpiderHeader(im) + if len(hdr) < 256: + msg = "Error creating Spider header" + raise OSError(msg) + + # write the SPIDER header + fp.writelines(hdr) + + rawmode = "F;32NF" # 32-bit native floating point + ImageFile._save(im, fp, [ImageFile._Tile("raw", (0, 0) + im.size, 0, rawmode)]) + + +def _save_spider(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + # get the filename extension and register it with Image + filename_ext = os.path.splitext(filename)[1] + ext = filename_ext.decode() if isinstance(filename_ext, bytes) else filename_ext + Image.register_extension(SpiderImageFile.format, ext) + _save(im, fp, filename) + + +# -------------------------------------------------------------------- + + +Image.register_open(SpiderImageFile.format, SpiderImageFile) +Image.register_save(SpiderImageFile.format, _save_spider) + +if __name__ == "__main__": + if len(sys.argv) < 2: + print("Syntax: python3 SpiderImagePlugin.py [infile] [outfile]") + sys.exit() + + filename = sys.argv[1] + if not isSpiderImage(filename): + print("input image must be in Spider format") + sys.exit() + + with Image.open(filename) as im: + print(f"image: {im}") + print(f"format: {im.format}") + print(f"size: {im.size}") + print(f"mode: {im.mode}") + print("max, min: ", end=" ") + print(im.getextrema()) + + if len(sys.argv) > 2: + outfile = sys.argv[2] + + # perform some image operation + transposed_im = im.transpose(Image.Transpose.FLIP_LEFT_RIGHT) + print( + f"saving a flipped version of {os.path.basename(filename)} " + f"as {outfile} " + ) + transposed_im.save(outfile, SpiderImageFile.format) diff --git a/PIL/SunImagePlugin.py b/PIL/SunImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..8912379ea3e7801cdac9a557d2bc0c557bce8991 --- /dev/null +++ b/PIL/SunImagePlugin.py @@ -0,0 +1,145 @@ +# +# The Python Imaging Library. +# $Id$ +# +# Sun image file handling +# +# History: +# 1995-09-10 fl Created +# 1996-05-28 fl Fixed 32-bit alignment +# 1998-12-29 fl Import ImagePalette module +# 2001-12-18 fl Fixed palette loading (from Jean-Claude Rimbault) +# +# Copyright (c) 1997-2001 by Secret Labs AB +# Copyright (c) 1995-1996 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +from . import Image, ImageFile, ImagePalette +from ._binary import i32be as i32 + + +def _accept(prefix: bytes) -> bool: + return len(prefix) >= 4 and i32(prefix) == 0x59A66A95 + + +## +# Image plugin for Sun raster files. + + +class SunImageFile(ImageFile.ImageFile): + format = "SUN" + format_description = "Sun Raster File" + + def _open(self) -> None: + # The Sun Raster file header is 32 bytes in length + # and has the following format: + + # typedef struct _SunRaster + # { + # DWORD MagicNumber; /* Magic (identification) number */ + # DWORD Width; /* Width of image in pixels */ + # DWORD Height; /* Height of image in pixels */ + # DWORD Depth; /* Number of bits per pixel */ + # DWORD Length; /* Size of image data in bytes */ + # DWORD Type; /* Type of raster file */ + # DWORD ColorMapType; /* Type of color map */ + # DWORD ColorMapLength; /* Size of the color map in bytes */ + # } SUNRASTER; + + assert self.fp is not None + + # HEAD + s = self.fp.read(32) + if not _accept(s): + msg = "not an SUN raster file" + raise SyntaxError(msg) + + offset = 32 + + self._size = i32(s, 4), i32(s, 8) + + depth = i32(s, 12) + # data_length = i32(s, 16) # unreliable, ignore. + file_type = i32(s, 20) + palette_type = i32(s, 24) # 0: None, 1: RGB, 2: Raw/arbitrary + palette_length = i32(s, 28) + + if depth == 1: + self._mode, rawmode = "1", "1;I" + elif depth == 4: + self._mode, rawmode = "L", "L;4" + elif depth == 8: + self._mode = rawmode = "L" + elif depth == 24: + if file_type == 3: + self._mode, rawmode = "RGB", "RGB" + else: + self._mode, rawmode = "RGB", "BGR" + elif depth == 32: + if file_type == 3: + self._mode, rawmode = "RGB", "RGBX" + else: + self._mode, rawmode = "RGB", "BGRX" + else: + msg = "Unsupported Mode/Bit Depth" + raise SyntaxError(msg) + + if palette_length: + if palette_length > 1024: + msg = "Unsupported Color Palette Length" + raise SyntaxError(msg) + + if palette_type != 1: + msg = "Unsupported Palette Type" + raise SyntaxError(msg) + + offset = offset + palette_length + self.palette = ImagePalette.raw("RGB;L", self.fp.read(palette_length)) + if self.mode == "L": + self._mode = "P" + rawmode = rawmode.replace("L", "P") + + # 16 bit boundaries on stride + stride = ((self.size[0] * depth + 15) // 16) * 2 + + # file type: Type is the version (or flavor) of the bitmap + # file. The following values are typically found in the Type + # field: + # 0000h Old + # 0001h Standard + # 0002h Byte-encoded + # 0003h RGB format + # 0004h TIFF format + # 0005h IFF format + # FFFFh Experimental + + # Old and standard are the same, except for the length tag. + # byte-encoded is run-length-encoded + # RGB looks similar to standard, but RGB byte order + # TIFF and IFF mean that they were converted from T/IFF + # Experimental means that it's something else. + # (https://www.fileformat.info/format/sunraster/egff.htm) + + if file_type in (0, 1, 3, 4, 5): + self.tile = [ + ImageFile._Tile("raw", (0, 0) + self.size, offset, (rawmode, stride)) + ] + elif file_type == 2: + self.tile = [ + ImageFile._Tile("sun_rle", (0, 0) + self.size, offset, rawmode) + ] + else: + msg = "Unsupported Sun Raster file type" + raise SyntaxError(msg) + + +# +# registry + + +Image.register_open(SunImageFile.format, SunImageFile, _accept) + +Image.register_extension(SunImageFile.format, ".ras") diff --git a/PIL/TarIO.py b/PIL/TarIO.py new file mode 100644 index 0000000000000000000000000000000000000000..86490a496f3f106fcc042c03fb235ed5fb41f3a7 --- /dev/null +++ b/PIL/TarIO.py @@ -0,0 +1,61 @@ +# +# The Python Imaging Library. +# $Id$ +# +# read files from within a tar file +# +# History: +# 95-06-18 fl Created +# 96-05-28 fl Open files in binary mode +# +# Copyright (c) Secret Labs AB 1997. +# Copyright (c) Fredrik Lundh 1995-96. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import io + +from . import ContainerIO + + +class TarIO(ContainerIO.ContainerIO[bytes]): + """A file object that provides read access to a given member of a TAR file.""" + + def __init__(self, tarfile: str, file: str) -> None: + """ + Create file object. + + :param tarfile: Name of TAR file. + :param file: Name of member file. + """ + self.fh = open(tarfile, "rb") + + while True: + s = self.fh.read(512) + if len(s) != 512: + self.fh.close() + + msg = "unexpected end of tar file" + raise OSError(msg) + + name = s[:100].decode("utf-8") + i = name.find("\0") + if i == 0: + self.fh.close() + + msg = "cannot find subfile" + raise OSError(msg) + if i > 0: + name = name[:i] + + size = int(s[124:135], 8) + + if file == name: + break + + self.fh.seek((size + 511) & (~511), io.SEEK_CUR) + + # Open region + super().__init__(self.fh, self.fh.tell(), size) diff --git a/PIL/TgaImagePlugin.py b/PIL/TgaImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..90d5b5cf4ee17fc050784bf591adae3247407b56 --- /dev/null +++ b/PIL/TgaImagePlugin.py @@ -0,0 +1,264 @@ +# +# The Python Imaging Library. +# $Id$ +# +# TGA file handling +# +# History: +# 95-09-01 fl created (reads 24-bit files only) +# 97-01-04 fl support more TGA versions, including compressed images +# 98-07-04 fl fixed orientation and alpha layer bugs +# 98-09-11 fl fixed orientation for runlength decoder +# +# Copyright (c) Secret Labs AB 1997-98. +# Copyright (c) Fredrik Lundh 1995-97. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import warnings +from typing import IO + +from . import Image, ImageFile, ImagePalette +from ._binary import i16le as i16 +from ._binary import o8 +from ._binary import o16le as o16 + +# +# -------------------------------------------------------------------- +# Read RGA file + + +MODES = { + # map imagetype/depth to rawmode + (1, 8): "P", + (3, 1): "1", + (3, 8): "L", + (3, 16): "LA", + (2, 16): "BGRA;15Z", + (2, 24): "BGR", + (2, 32): "BGRA", +} + + +## +# Image plugin for Targa files. + + +class TgaImageFile(ImageFile.ImageFile): + format = "TGA" + format_description = "Targa" + + def _open(self) -> None: + # process header + assert self.fp is not None + + s = self.fp.read(18) + + id_len = s[0] + + colormaptype = s[1] + imagetype = s[2] + + depth = s[16] + + flags = s[17] + + self._size = i16(s, 12), i16(s, 14) + + # validate header fields + if ( + colormaptype not in (0, 1) + or self.size[0] <= 0 + or self.size[1] <= 0 + or depth not in (1, 8, 16, 24, 32) + ): + msg = "not a TGA file" + raise SyntaxError(msg) + + # image mode + if imagetype in (3, 11): + self._mode = "L" + if depth == 1: + self._mode = "1" # ??? + elif depth == 16: + self._mode = "LA" + elif imagetype in (1, 9): + self._mode = "P" if colormaptype else "L" + elif imagetype in (2, 10): + self._mode = "RGB" if depth == 24 else "RGBA" + else: + msg = "unknown TGA mode" + raise SyntaxError(msg) + + # orientation + orientation = flags & 0x30 + self._flip_horizontally = orientation in [0x10, 0x30] + if orientation in [0x20, 0x30]: + orientation = 1 + elif orientation in [0, 0x10]: + orientation = -1 + else: + msg = "unknown TGA orientation" + raise SyntaxError(msg) + + self.info["orientation"] = orientation + + if imagetype & 8: + self.info["compression"] = "tga_rle" + + if id_len: + self.info["id_section"] = self.fp.read(id_len) + + if colormaptype: + # read palette + start, size, mapdepth = i16(s, 3), i16(s, 5), s[7] + if mapdepth == 16: + self.palette = ImagePalette.raw( + "BGRA;15Z", bytes(2 * start) + self.fp.read(2 * size) + ) + self.palette.mode = "RGBA" + elif mapdepth == 24: + self.palette = ImagePalette.raw( + "BGR", bytes(3 * start) + self.fp.read(3 * size) + ) + elif mapdepth == 32: + self.palette = ImagePalette.raw( + "BGRA", bytes(4 * start) + self.fp.read(4 * size) + ) + else: + msg = "unknown TGA map depth" + raise SyntaxError(msg) + + # setup tile descriptor + try: + rawmode = MODES[(imagetype & 7, depth)] + if imagetype & 8: + # compressed + self.tile = [ + ImageFile._Tile( + "tga_rle", + (0, 0) + self.size, + self.fp.tell(), + (rawmode, orientation, depth), + ) + ] + else: + self.tile = [ + ImageFile._Tile( + "raw", + (0, 0) + self.size, + self.fp.tell(), + (rawmode, 0, orientation), + ) + ] + except KeyError: + pass # cannot decode + + def load_end(self) -> None: + if self._flip_horizontally: + self.im = self.im.transpose(Image.Transpose.FLIP_LEFT_RIGHT) + + +# +# -------------------------------------------------------------------- +# Write TGA file + + +SAVE = { + "1": ("1", 1, 0, 3), + "L": ("L", 8, 0, 3), + "LA": ("LA", 16, 0, 3), + "P": ("P", 8, 1, 1), + "RGB": ("BGR", 24, 0, 2), + "RGBA": ("BGRA", 32, 0, 2), +} + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + try: + rawmode, bits, colormaptype, imagetype = SAVE[im.mode] + except KeyError as e: + msg = f"cannot write mode {im.mode} as TGA" + raise OSError(msg) from e + + if "rle" in im.encoderinfo: + rle = im.encoderinfo["rle"] + else: + compression = im.encoderinfo.get("compression", im.info.get("compression")) + rle = compression == "tga_rle" + if rle: + imagetype += 8 + + id_section = im.encoderinfo.get("id_section", im.info.get("id_section", "")) + id_len = len(id_section) + if id_len > 255: + id_len = 255 + id_section = id_section[:255] + warnings.warn("id_section has been trimmed to 255 characters") + + if colormaptype: + palette = im.im.getpalette("RGB", "BGR") + colormaplength, colormapentry = len(palette) // 3, 24 + else: + colormaplength, colormapentry = 0, 0 + + if im.mode in ("LA", "RGBA"): + flags = 8 + else: + flags = 0 + + orientation = im.encoderinfo.get("orientation", im.info.get("orientation", -1)) + if orientation > 0: + flags = flags | 0x20 + + fp.write( + o8(id_len) + + o8(colormaptype) + + o8(imagetype) + + o16(0) # colormapfirst + + o16(colormaplength) + + o8(colormapentry) + + o16(0) + + o16(0) + + o16(im.size[0]) + + o16(im.size[1]) + + o8(bits) + + o8(flags) + ) + + if id_section: + fp.write(id_section) + + if colormaptype: + fp.write(palette) + + if rle: + ImageFile._save( + im, + fp, + [ImageFile._Tile("tga_rle", (0, 0) + im.size, 0, (rawmode, orientation))], + ) + else: + ImageFile._save( + im, + fp, + [ImageFile._Tile("raw", (0, 0) + im.size, 0, (rawmode, 0, orientation))], + ) + + # write targa version 2 footer + fp.write(b"\000" * 8 + b"TRUEVISION-XFILE." + b"\000") + + +# +# -------------------------------------------------------------------- +# Registry + + +Image.register_open(TgaImageFile.format, TgaImageFile) +Image.register_save(TgaImageFile.format, _save) + +Image.register_extensions(TgaImageFile.format, [".tga", ".icb", ".vda", ".vst"]) + +Image.register_mime(TgaImageFile.format, "image/x-tga") diff --git a/PIL/TiffImagePlugin.py b/PIL/TiffImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..de2ce066ebf551335c572fdde8b9176585eb0f30 --- /dev/null +++ b/PIL/TiffImagePlugin.py @@ -0,0 +1,2338 @@ +# +# The Python Imaging Library. +# $Id$ +# +# TIFF file handling +# +# TIFF is a flexible, if somewhat aged, image file format originally +# defined by Aldus. Although TIFF supports a wide variety of pixel +# layouts and compression methods, the name doesn't really stand for +# "thousands of incompatible file formats," it just feels that way. +# +# To read TIFF data from a stream, the stream must be seekable. For +# progressive decoding, make sure to use TIFF files where the tag +# directory is placed first in the file. +# +# History: +# 1995-09-01 fl Created +# 1996-05-04 fl Handle JPEGTABLES tag +# 1996-05-18 fl Fixed COLORMAP support +# 1997-01-05 fl Fixed PREDICTOR support +# 1997-08-27 fl Added support for rational tags (from Perry Stoll) +# 1998-01-10 fl Fixed seek/tell (from Jan Blom) +# 1998-07-15 fl Use private names for internal variables +# 1999-06-13 fl Rewritten for PIL 1.0 (1.0) +# 2000-10-11 fl Additional fixes for Python 2.0 (1.1) +# 2001-04-17 fl Fixed rewind support (seek to frame 0) (1.2) +# 2001-05-12 fl Added write support for more tags (from Greg Couch) (1.3) +# 2001-12-18 fl Added workaround for broken Matrox library +# 2002-01-18 fl Don't mess up if photometric tag is missing (D. Alan Stewart) +# 2003-05-19 fl Check FILLORDER tag +# 2003-09-26 fl Added RGBa support +# 2004-02-24 fl Added DPI support; fixed rational write support +# 2005-02-07 fl Added workaround for broken Corel Draw 10 files +# 2006-01-09 fl Added support for float/double tags (from Russell Nelson) +# +# Copyright (c) 1997-2006 by Secret Labs AB. All rights reserved. +# Copyright (c) 1995-1997 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import io +import itertools +import logging +import math +import os +import struct +import warnings +from collections.abc import Callable, MutableMapping +from fractions import Fraction +from numbers import Number, Rational +from typing import IO, Any, cast + +from . import ExifTags, Image, ImageFile, ImageOps, ImagePalette, TiffTags +from ._binary import i16be as i16 +from ._binary import i32be as i32 +from ._binary import o8 +from ._util import DeferredError, is_path +from .TiffTags import TYPES + +TYPE_CHECKING = False +if TYPE_CHECKING: + from collections.abc import Iterator + from typing import NoReturn + + from ._typing import Buffer, IntegralLike, StrOrBytesPath + +logger = logging.getLogger(__name__) + +# Set these to true to force use of libtiff for reading or writing. +READ_LIBTIFF = False +WRITE_LIBTIFF = False +STRIP_SIZE = 65536 + +II = b"II" # little-endian (Intel style) +MM = b"MM" # big-endian (Motorola style) + +# +# -------------------------------------------------------------------- +# Read TIFF files + +# a few tag names, just to make the code below a bit more readable +OSUBFILETYPE = 255 +IMAGEWIDTH = 256 +IMAGELENGTH = 257 +BITSPERSAMPLE = 258 +COMPRESSION = 259 +PHOTOMETRIC_INTERPRETATION = 262 +FILLORDER = 266 +IMAGEDESCRIPTION = 270 +STRIPOFFSETS = 273 +SAMPLESPERPIXEL = 277 +ROWSPERSTRIP = 278 +STRIPBYTECOUNTS = 279 +X_RESOLUTION = 282 +Y_RESOLUTION = 283 +PLANAR_CONFIGURATION = 284 +RESOLUTION_UNIT = 296 +TRANSFERFUNCTION = 301 +SOFTWARE = 305 +DATE_TIME = 306 +ARTIST = 315 +PREDICTOR = 317 +COLORMAP = 320 +TILEWIDTH = 322 +TILELENGTH = 323 +TILEOFFSETS = 324 +TILEBYTECOUNTS = 325 +SUBIFD = 330 +EXTRASAMPLES = 338 +SAMPLEFORMAT = 339 +JPEGTABLES = 347 +YCBCRSUBSAMPLING = 530 +REFERENCEBLACKWHITE = 532 +COPYRIGHT = 33432 +IPTC_NAA_CHUNK = 33723 # newsphoto properties +PHOTOSHOP_CHUNK = 34377 # photoshop properties +ICCPROFILE = 34675 +EXIFIFD = 34665 +XMP = 700 +JPEGQUALITY = 65537 # pseudo-tag by libtiff + +# https://github.com/imagej/ImageJA/blob/master/src/main/java/ij/io/TiffDecoder.java +IMAGEJ_META_DATA_BYTE_COUNTS = 50838 +IMAGEJ_META_DATA = 50839 + +COMPRESSION_INFO = { + # Compression => pil compression name + 1: "raw", + 2: "tiff_ccitt", + 3: "group3", + 4: "group4", + 5: "tiff_lzw", + 6: "tiff_jpeg", # obsolete + 7: "jpeg", + 8: "tiff_adobe_deflate", + 32771: "tiff_raw_16", # 16-bit padding + 32773: "packbits", + 32809: "tiff_thunderscan", + 32946: "tiff_deflate", + 34676: "tiff_sgilog", + 34677: "tiff_sgilog24", + 34925: "lzma", + 50000: "zstd", + 50001: "webp", +} + +COMPRESSION_INFO_REV = {v: k for k, v in COMPRESSION_INFO.items()} + +OPEN_INFO = { + # (ByteOrder, PhotoInterpretation, SampleFormat, FillOrder, BitsPerSample, + # ExtraSamples) => mode, rawmode + (II, 0, (1,), 1, (1,), ()): ("1", "1;I"), + (MM, 0, (1,), 1, (1,), ()): ("1", "1;I"), + (II, 0, (1,), 2, (1,), ()): ("1", "1;IR"), + (MM, 0, (1,), 2, (1,), ()): ("1", "1;IR"), + (II, 1, (1,), 1, (1,), ()): ("1", "1"), + (MM, 1, (1,), 1, (1,), ()): ("1", "1"), + (II, 1, (1,), 2, (1,), ()): ("1", "1;R"), + (MM, 1, (1,), 2, (1,), ()): ("1", "1;R"), + (II, 0, (1,), 1, (2,), ()): ("L", "L;2I"), + (MM, 0, (1,), 1, (2,), ()): ("L", "L;2I"), + (II, 0, (1,), 2, (2,), ()): ("L", "L;2IR"), + (MM, 0, (1,), 2, (2,), ()): ("L", "L;2IR"), + (II, 1, (1,), 1, (2,), ()): ("L", "L;2"), + (MM, 1, (1,), 1, (2,), ()): ("L", "L;2"), + (II, 1, (1,), 2, (2,), ()): ("L", "L;2R"), + (MM, 1, (1,), 2, (2,), ()): ("L", "L;2R"), + (II, 0, (1,), 1, (4,), ()): ("L", "L;4I"), + (MM, 0, (1,), 1, (4,), ()): ("L", "L;4I"), + (II, 0, (1,), 2, (4,), ()): ("L", "L;4IR"), + (MM, 0, (1,), 2, (4,), ()): ("L", "L;4IR"), + (II, 1, (1,), 1, (4,), ()): ("L", "L;4"), + (MM, 1, (1,), 1, (4,), ()): ("L", "L;4"), + (II, 1, (1,), 2, (4,), ()): ("L", "L;4R"), + (MM, 1, (1,), 2, (4,), ()): ("L", "L;4R"), + (II, 0, (1,), 1, (8,), ()): ("L", "L;I"), + (MM, 0, (1,), 1, (8,), ()): ("L", "L;I"), + (II, 0, (1,), 2, (8,), ()): ("L", "L;IR"), + (MM, 0, (1,), 2, (8,), ()): ("L", "L;IR"), + (II, 1, (1,), 1, (8,), ()): ("L", "L"), + (MM, 1, (1,), 1, (8,), ()): ("L", "L"), + (II, 1, (2,), 1, (8,), ()): ("L", "L"), + (MM, 1, (2,), 1, (8,), ()): ("L", "L"), + (II, 1, (1,), 2, (8,), ()): ("L", "L;R"), + (MM, 1, (1,), 2, (8,), ()): ("L", "L;R"), + (II, 1, (1,), 1, (12,), ()): ("I;16", "I;12"), + (II, 0, (1,), 1, (16,), ()): ("I;16", "I;16"), + (II, 1, (1,), 1, (16,), ()): ("I;16", "I;16"), + (MM, 1, (1,), 1, (16,), ()): ("I;16B", "I;16B"), + (II, 1, (1,), 2, (16,), ()): ("I;16", "I;16R"), + (II, 1, (2,), 1, (16,), ()): ("I", "I;16S"), + (MM, 1, (2,), 1, (16,), ()): ("I", "I;16BS"), + (II, 0, (3,), 1, (32,), ()): ("F", "F;32F"), + (MM, 0, (3,), 1, (32,), ()): ("F", "F;32BF"), + (II, 1, (1,), 1, (32,), ()): ("I", "I;32N"), + (II, 1, (2,), 1, (32,), ()): ("I", "I;32S"), + (MM, 1, (2,), 1, (32,), ()): ("I", "I;32BS"), + (II, 1, (3,), 1, (32,), ()): ("F", "F;32F"), + (MM, 1, (3,), 1, (32,), ()): ("F", "F;32BF"), + (II, 1, (1,), 1, (8, 8), (2,)): ("LA", "LA"), + (MM, 1, (1,), 1, (8, 8), (2,)): ("LA", "LA"), + (II, 2, (1,), 1, (8, 8, 8), ()): ("RGB", "RGB"), + (MM, 2, (1,), 1, (8, 8, 8), ()): ("RGB", "RGB"), + (II, 2, (1,), 2, (8, 8, 8), ()): ("RGB", "RGB;R"), + (MM, 2, (1,), 2, (8, 8, 8), ()): ("RGB", "RGB;R"), + (II, 2, (1,), 1, (8, 8, 8, 8), ()): ("RGBA", "RGBA"), # missing ExtraSamples + (MM, 2, (1,), 1, (8, 8, 8, 8), ()): ("RGBA", "RGBA"), # missing ExtraSamples + (II, 2, (1,), 1, (8, 8, 8, 8), (0,)): ("RGB", "RGBX"), + (MM, 2, (1,), 1, (8, 8, 8, 8), (0,)): ("RGB", "RGBX"), + (II, 2, (1,), 1, (8, 8, 8, 8, 8), (0, 0)): ("RGB", "RGBXX"), + (MM, 2, (1,), 1, (8, 8, 8, 8, 8), (0, 0)): ("RGB", "RGBXX"), + (II, 2, (1,), 1, (8, 8, 8, 8, 8, 8), (0, 0, 0)): ("RGB", "RGBXXX"), + (MM, 2, (1,), 1, (8, 8, 8, 8, 8, 8), (0, 0, 0)): ("RGB", "RGBXXX"), + (II, 2, (1,), 1, (8, 8, 8, 8), (1,)): ("RGBA", "RGBa"), + (MM, 2, (1,), 1, (8, 8, 8, 8), (1,)): ("RGBA", "RGBa"), + (II, 2, (1,), 1, (8, 8, 8, 8, 8), (1, 0)): ("RGBA", "RGBaX"), + (MM, 2, (1,), 1, (8, 8, 8, 8, 8), (1, 0)): ("RGBA", "RGBaX"), + (II, 2, (1,), 1, (8, 8, 8, 8, 8, 8), (1, 0, 0)): ("RGBA", "RGBaXX"), + (MM, 2, (1,), 1, (8, 8, 8, 8, 8, 8), (1, 0, 0)): ("RGBA", "RGBaXX"), + (II, 2, (1,), 1, (8, 8, 8, 8), (2,)): ("RGBA", "RGBA"), + (MM, 2, (1,), 1, (8, 8, 8, 8), (2,)): ("RGBA", "RGBA"), + (II, 2, (1,), 1, (8, 8, 8, 8, 8), (2, 0)): ("RGBA", "RGBAX"), + (MM, 2, (1,), 1, (8, 8, 8, 8, 8), (2, 0)): ("RGBA", "RGBAX"), + (II, 2, (1,), 1, (8, 8, 8, 8, 8, 8), (2, 0, 0)): ("RGBA", "RGBAXX"), + (MM, 2, (1,), 1, (8, 8, 8, 8, 8, 8), (2, 0, 0)): ("RGBA", "RGBAXX"), + (II, 2, (1,), 1, (8, 8, 8, 8), (999,)): ("RGBA", "RGBA"), # Corel Draw 10 + (MM, 2, (1,), 1, (8, 8, 8, 8), (999,)): ("RGBA", "RGBA"), # Corel Draw 10 + (II, 2, (1,), 1, (16, 16, 16), ()): ("RGB", "RGB;16L"), + (MM, 2, (1,), 1, (16, 16, 16), ()): ("RGB", "RGB;16B"), + (II, 2, (1,), 1, (16, 16, 16, 16), ()): ("RGBA", "RGBA;16L"), + (MM, 2, (1,), 1, (16, 16, 16, 16), ()): ("RGBA", "RGBA;16B"), + (II, 2, (1,), 1, (16, 16, 16, 16), (0,)): ("RGB", "RGBX;16L"), + (MM, 2, (1,), 1, (16, 16, 16, 16), (0,)): ("RGB", "RGBX;16B"), + (II, 2, (1,), 1, (16, 16, 16, 16), (1,)): ("RGBA", "RGBa;16L"), + (MM, 2, (1,), 1, (16, 16, 16, 16), (1,)): ("RGBA", "RGBa;16B"), + (II, 2, (1,), 1, (16, 16, 16, 16), (2,)): ("RGBA", "RGBA;16L"), + (MM, 2, (1,), 1, (16, 16, 16, 16), (2,)): ("RGBA", "RGBA;16B"), + (II, 3, (1,), 1, (1,), ()): ("P", "P;1"), + (MM, 3, (1,), 1, (1,), ()): ("P", "P;1"), + (II, 3, (1,), 2, (1,), ()): ("P", "P;1R"), + (MM, 3, (1,), 2, (1,), ()): ("P", "P;1R"), + (II, 3, (1,), 1, (2,), ()): ("P", "P;2"), + (MM, 3, (1,), 1, (2,), ()): ("P", "P;2"), + (II, 3, (1,), 2, (2,), ()): ("P", "P;2R"), + (MM, 3, (1,), 2, (2,), ()): ("P", "P;2R"), + (II, 3, (1,), 1, (4,), ()): ("P", "P;4"), + (MM, 3, (1,), 1, (4,), ()): ("P", "P;4"), + (II, 3, (1,), 2, (4,), ()): ("P", "P;4R"), + (MM, 3, (1,), 2, (4,), ()): ("P", "P;4R"), + (II, 3, (1,), 1, (8,), ()): ("P", "P"), + (MM, 3, (1,), 1, (8,), ()): ("P", "P"), + (II, 3, (1,), 1, (8, 8), (0,)): ("P", "PX"), + (MM, 3, (1,), 1, (8, 8), (0,)): ("P", "PX"), + (II, 3, (1,), 1, (8, 8), (2,)): ("PA", "PA"), + (MM, 3, (1,), 1, (8, 8), (2,)): ("PA", "PA"), + (II, 3, (1,), 2, (8,), ()): ("P", "P;R"), + (MM, 3, (1,), 2, (8,), ()): ("P", "P;R"), + (II, 5, (1,), 1, (8, 8, 8, 8), ()): ("CMYK", "CMYK"), + (MM, 5, (1,), 1, (8, 8, 8, 8), ()): ("CMYK", "CMYK"), + (II, 5, (1,), 1, (8, 8, 8, 8, 8), (0,)): ("CMYK", "CMYKX"), + (MM, 5, (1,), 1, (8, 8, 8, 8, 8), (0,)): ("CMYK", "CMYKX"), + (II, 5, (1,), 1, (8, 8, 8, 8, 8, 8), (0, 0)): ("CMYK", "CMYKXX"), + (MM, 5, (1,), 1, (8, 8, 8, 8, 8, 8), (0, 0)): ("CMYK", "CMYKXX"), + (II, 5, (1,), 1, (16, 16, 16, 16), ()): ("CMYK", "CMYK;16L"), + (MM, 5, (1,), 1, (16, 16, 16, 16), ()): ("CMYK", "CMYK;16B"), + (II, 6, (1,), 1, (8,), ()): ("L", "L"), + (MM, 6, (1,), 1, (8,), ()): ("L", "L"), + # JPEG compressed images handled by LibTiff and auto-converted to RGBX + # Minimal Baseline TIFF requires YCbCr images to have 3 SamplesPerPixel + (II, 6, (1,), 1, (8, 8, 8), ()): ("RGB", "RGBX"), + (MM, 6, (1,), 1, (8, 8, 8), ()): ("RGB", "RGBX"), + (II, 8, (1,), 1, (8, 8, 8), ()): ("LAB", "LAB"), + (MM, 8, (1,), 1, (8, 8, 8), ()): ("LAB", "LAB"), +} + +MAX_SAMPLESPERPIXEL = max(len(key_tp[4]) for key_tp in OPEN_INFO) + +PREFIXES = [ + b"MM\x00\x2a", # Valid TIFF header with big-endian byte order + b"II\x2a\x00", # Valid TIFF header with little-endian byte order + b"MM\x2a\x00", # Invalid TIFF header, assume big-endian + b"II\x00\x2a", # Invalid TIFF header, assume little-endian + b"MM\x00\x2b", # BigTIFF with big-endian byte order + b"II\x2b\x00", # BigTIFF with little-endian byte order +] + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith(tuple(PREFIXES)) + + +def _limit_rational( + val: float | Fraction | IFDRational, max_val: int +) -> tuple[IntegralLike, IntegralLike]: + inv = abs(val) > 1 + n_d = IFDRational(1 / val if inv else val).limit_rational(max_val) + return n_d[::-1] if inv else n_d + + +def _limit_signed_rational( + val: IFDRational, max_val: int, min_val: int +) -> tuple[IntegralLike, IntegralLike]: + frac = Fraction(val) + n_d: tuple[IntegralLike, IntegralLike] = frac.numerator, frac.denominator + + if min(float(i) for i in n_d) < min_val: + n_d = _limit_rational(val, abs(min_val)) + + n_d_float = tuple(float(i) for i in n_d) + if max(n_d_float) > max_val: + n_d = _limit_rational(n_d_float[0] / n_d_float[1], max_val) + + return n_d + + +## +# Wrapper for TIFF IFDs. + +_load_dispatch = {} +_write_dispatch = {} + + +def _delegate(op: str) -> Any: + def delegate( + self: IFDRational, *args: tuple[float, ...] + ) -> bool | float | Fraction: + return getattr(self._val, op)(*args) + + return delegate + + +class IFDRational(Rational): + """Implements a rational class where 0/0 is a legal value to match + the in the wild use of exif rationals. + + e.g., DigitalZoomRatio - 0.00/0.00 indicates that no digital zoom was used + """ + + """ If the denominator is 0, store this as a float('nan'), otherwise store + as a fractions.Fraction(). Delegate as appropriate + + """ + + __slots__ = ("_numerator", "_denominator", "_val") + + def __init__( + self, value: float | Fraction | IFDRational, denominator: int = 1 + ) -> None: + """ + :param value: either an integer numerator, a + float/rational/other number, or an IFDRational + :param denominator: Optional integer denominator + """ + self._val: Fraction | float + if isinstance(value, IFDRational): + self._numerator = value.numerator + self._denominator = value.denominator + self._val = value._val + return + + if isinstance(value, Fraction): + self._numerator = value.numerator + self._denominator = value.denominator + else: + if TYPE_CHECKING: + self._numerator = cast(IntegralLike, value) + else: + self._numerator = value + self._denominator = denominator + + if denominator == 0: + self._val = float("nan") + elif denominator == 1: + self._val = Fraction(value) + elif int(value) == value: + self._val = Fraction(int(value), denominator) + else: + self._val = Fraction(value / denominator) + + @property + def numerator(self) -> IntegralLike: + return self._numerator + + @property + def denominator(self) -> int: + return self._denominator + + def limit_rational(self, max_denominator: int) -> tuple[IntegralLike, int]: + """ + + :param max_denominator: Integer, the maximum denominator value + :returns: Tuple of (numerator, denominator) + """ + + if self.denominator == 0: + return self.numerator, self.denominator + + assert isinstance(self._val, Fraction) + f = self._val.limit_denominator(max_denominator) + return f.numerator, f.denominator + + def __repr__(self) -> str: + return str(float(self._val)) + + def __hash__(self) -> int: # type: ignore[override] + return self._val.__hash__() + + def __eq__(self, other: object) -> bool: + val = self._val + if isinstance(other, IFDRational): + other = other._val + if isinstance(other, float): + val = float(val) + return val == other + + def __getstate__(self) -> list[float | Fraction | IntegralLike]: + return [self._val, self._numerator, self._denominator] + + def __setstate__(self, state: list[float | Fraction | IntegralLike]) -> None: + IFDRational.__init__(self, 0) + _val, _numerator, _denominator = state + assert isinstance(_val, (float, Fraction)) + self._val = _val + if TYPE_CHECKING: + self._numerator = cast(IntegralLike, _numerator) + else: + self._numerator = _numerator + assert isinstance(_denominator, int) + self._denominator = _denominator + + """ a = ['add','radd', 'sub', 'rsub', 'mul', 'rmul', + 'truediv', 'rtruediv', 'floordiv', 'rfloordiv', + 'mod','rmod', 'pow','rpow', 'pos', 'neg', + 'abs', 'trunc', 'lt', 'gt', 'le', 'ge', 'bool', + 'ceil', 'floor', 'round'] + print("\n".join("__%s__ = _delegate('__%s__')" % (s,s) for s in a)) + """ + + __add__ = _delegate("__add__") + __radd__ = _delegate("__radd__") + __sub__ = _delegate("__sub__") + __rsub__ = _delegate("__rsub__") + __mul__ = _delegate("__mul__") + __rmul__ = _delegate("__rmul__") + __truediv__ = _delegate("__truediv__") + __rtruediv__ = _delegate("__rtruediv__") + __floordiv__ = _delegate("__floordiv__") + __rfloordiv__ = _delegate("__rfloordiv__") + __mod__ = _delegate("__mod__") + __rmod__ = _delegate("__rmod__") + __pow__ = _delegate("__pow__") + __rpow__ = _delegate("__rpow__") + __pos__ = _delegate("__pos__") + __neg__ = _delegate("__neg__") + __abs__ = _delegate("__abs__") + __trunc__ = _delegate("__trunc__") + __lt__ = _delegate("__lt__") + __gt__ = _delegate("__gt__") + __le__ = _delegate("__le__") + __ge__ = _delegate("__ge__") + __bool__ = _delegate("__bool__") + __ceil__ = _delegate("__ceil__") + __floor__ = _delegate("__floor__") + __round__ = _delegate("__round__") + # Python >= 3.11 + if hasattr(Fraction, "__int__"): + __int__ = _delegate("__int__") + + +_LoaderFunc = Callable[["ImageFileDirectory_v2", bytes, bool], Any] + + +def _register_loader(idx: int, size: int) -> Callable[[_LoaderFunc], _LoaderFunc]: + def decorator(func: _LoaderFunc) -> _LoaderFunc: + from .TiffTags import TYPES + + if func.__name__.startswith("load_"): + TYPES[idx] = func.__name__[5:].replace("_", " ") + _load_dispatch[idx] = size, func # noqa: F821 + return func + + return decorator + + +def _register_writer(idx: int) -> Callable[[Callable[..., Any]], Callable[..., Any]]: + def decorator(func: Callable[..., Any]) -> Callable[..., Any]: + _write_dispatch[idx] = func # noqa: F821 + return func + + return decorator + + +def _register_basic(idx_fmt_name: tuple[int, str, str]) -> None: + from .TiffTags import TYPES + + idx, fmt, name = idx_fmt_name + TYPES[idx] = name + size = struct.calcsize(f"={fmt}") + + def basic_handler( + self: ImageFileDirectory_v2, data: bytes, legacy_api: bool = True + ) -> tuple[Any, ...]: + return self._unpack(f"{len(data) // size}{fmt}", data) + + _load_dispatch[idx] = size, basic_handler # noqa: F821 + _write_dispatch[idx] = lambda self, *values: ( # noqa: F821 + b"".join(self._pack(fmt, value) for value in values) + ) + + +if TYPE_CHECKING: + _IFDv2Base = MutableMapping[int, Any] +else: + _IFDv2Base = MutableMapping + + +class ImageFileDirectory_v2(_IFDv2Base): + """This class represents a TIFF tag directory. To speed things up, we + don't decode tags unless they're asked for. + + Exposes a dictionary interface of the tags in the directory:: + + ifd = ImageFileDirectory_v2() + ifd[key] = 'Some Data' + ifd.tagtype[key] = TiffTags.ASCII + print(ifd[key]) + 'Some Data' + + Individual values are returned as the strings or numbers, sequences are + returned as tuples of the values. + + The tiff metadata type of each item is stored in a dictionary of + tag types in + :attr:`~PIL.TiffImagePlugin.ImageFileDirectory_v2.tagtype`. The types + are read from a tiff file, guessed from the type added, or added + manually. + + Data Structures: + + * ``self.tagtype = {}`` + + * Key: numerical TIFF tag number + * Value: integer corresponding to the data type from + :py:data:`.TiffTags.TYPES` + + .. versionadded:: 3.0.0 + + 'Internal' data structures: + + * ``self._tags_v2 = {}`` + + * Key: numerical TIFF tag number + * Value: decoded data, as tuple for multiple values + + * ``self._tagdata = {}`` + + * Key: numerical TIFF tag number + * Value: undecoded byte string from file + + * ``self._tags_v1 = {}`` + + * Key: numerical TIFF tag number + * Value: decoded data in the v1 format + + Tags will be found in the private attributes ``self._tagdata``, and in + ``self._tags_v2`` once decoded. + + ``self.legacy_api`` is a value for internal use, and shouldn't be changed + from outside code. In cooperation with + :py:class:`~PIL.TiffImagePlugin.ImageFileDirectory_v1`, if ``legacy_api`` + is true, then decoded tags will be populated into both ``_tags_v1`` and + ``_tags_v2``. ``_tags_v2`` will be used if this IFD is used in the TIFF + save routine. Tags should be read from ``_tags_v1`` if + ``legacy_api == true``. + + """ + + _load_dispatch: dict[int, tuple[int, _LoaderFunc]] = {} + _write_dispatch: dict[int, Callable[..., Any]] = {} + + def __init__( + self, + ifh: bytes = b"II\x2a\x00\x00\x00\x00\x00", + prefix: bytes | None = None, + group: int | None = None, + ) -> None: + """Initialize an ImageFileDirectory. + + To construct an ImageFileDirectory from a real file, pass the 8-byte + magic header to the constructor. To only set the endianness, pass it + as the 'prefix' keyword argument. + + :param ifh: One of the accepted magic headers (cf. PREFIXES); also sets + endianness. + :param prefix: Override the endianness of the file. + """ + if not _accept(ifh): + msg = f"not a TIFF file (header {repr(ifh)} not valid)" + raise SyntaxError(msg) + self._prefix = prefix if prefix is not None else ifh[:2] + if self._prefix == MM: + self._endian = ">" + elif self._prefix == II: + self._endian = "<" + else: + msg = "not a TIFF IFD" + raise SyntaxError(msg) + self._bigtiff = ifh[2] == 43 + self.group = group + self.tagtype: dict[int, int] = {} + """ Dictionary of tag types """ + self.reset() + self.next = ( + self._unpack("Q", ifh[8:])[0] + if self._bigtiff + else self._unpack("L", ifh[4:])[0] + ) + self._legacy_api = False + + prefix = property(lambda self: self._prefix) + offset = property(lambda self: self._offset) + + @property + def legacy_api(self) -> bool: + return self._legacy_api + + @legacy_api.setter + def legacy_api(self, value: bool) -> NoReturn: + msg = "Not allowing setting of legacy api" + raise Exception(msg) + + def reset(self) -> None: + self._tags_v1: dict[int, Any] = {} # will remain empty if legacy_api is false + self._tags_v2: dict[int, Any] = {} # main tag storage + self._tagdata: dict[int, bytes] = {} + self.tagtype = {} # added 2008-06-05 by Florian Hoech + self._next = None + self._offset: int | None = None + + def __str__(self) -> str: + return str(dict(self)) + + def named(self) -> dict[str, Any]: + """ + :returns: dict of name|key: value + + Returns the complete tag dictionary, with named tags where possible. + """ + return { + TiffTags.lookup(code, self.group).name: value + for code, value in self.items() + } + + def __len__(self) -> int: + return len(set(self._tagdata) | set(self._tags_v2)) + + def __getitem__(self, tag: int) -> Any: + if tag not in self._tags_v2: # unpack on the fly + data = self._tagdata[tag] + typ = self.tagtype[tag] + size, handler = self._load_dispatch[typ] + self[tag] = handler(self, data, self.legacy_api) # check type + val = self._tags_v2[tag] + if self.legacy_api and not isinstance(val, (tuple, bytes)): + val = (val,) + return val + + def __contains__(self, tag: object) -> bool: + return tag in self._tags_v2 or tag in self._tagdata + + def __setitem__(self, tag: int, value: Any) -> None: + self._setitem(tag, value, self.legacy_api) + + def _setitem(self, tag: int, value: Any, legacy_api: bool) -> None: + basetypes = (Number, bytes, str) + + info = TiffTags.lookup(tag, self.group) + values = [value] if isinstance(value, basetypes) else value + + if tag not in self.tagtype: + if info.type: + self.tagtype[tag] = info.type + else: + self.tagtype[tag] = TiffTags.UNDEFINED + if all(isinstance(v, IFDRational) for v in values): + for v in values: + assert isinstance(v, IFDRational) + if v < 0: + self.tagtype[tag] = TiffTags.SIGNED_RATIONAL + break + else: + self.tagtype[tag] = TiffTags.RATIONAL + elif all(isinstance(v, int) for v in values): + short = True + signed_short = True + long = True + for v in values: + assert isinstance(v, int) + if short and not (0 <= v < 2**16): + short = False + if signed_short and not (-(2**15) < v < 2**15): + signed_short = False + if long and v < 0: + long = False + if short: + self.tagtype[tag] = TiffTags.SHORT + elif signed_short: + self.tagtype[tag] = TiffTags.SIGNED_SHORT + elif long: + self.tagtype[tag] = TiffTags.LONG + else: + self.tagtype[tag] = TiffTags.SIGNED_LONG + elif all(isinstance(v, float) for v in values): + self.tagtype[tag] = TiffTags.DOUBLE + elif all(isinstance(v, str) for v in values): + self.tagtype[tag] = TiffTags.ASCII + elif all(isinstance(v, bytes) for v in values): + self.tagtype[tag] = TiffTags.BYTE + + if self.tagtype[tag] == TiffTags.UNDEFINED: + values = [ + v.encode("ascii", "replace") if isinstance(v, str) else v + for v in values + ] + elif self.tagtype[tag] == TiffTags.RATIONAL: + values = [float(v) if isinstance(v, int) else v for v in values] + + is_ifd = self.tagtype[tag] == TiffTags.LONG and isinstance(values, dict) + if not is_ifd: + values = tuple( + info.cvt_enum(value) if isinstance(value, str) else value + for value in values + ) + + dest = self._tags_v1 if legacy_api else self._tags_v2 + + # Three branches: + # Spec'd length == 1, Actual length 1, store as element + # Spec'd length == 1, Actual > 1, Warn and truncate. Formerly barfed. + # No Spec, Actual length 1, Formerly (<4.2) returned a 1 element tuple. + # Don't mess with the legacy api, since it's frozen. + if not is_ifd and ( + (info.length == 1) + or self.tagtype[tag] == TiffTags.BYTE + or (info.length is None and len(values) == 1 and not legacy_api) + ): + # Don't mess with the legacy api, since it's frozen. + if legacy_api and self.tagtype[tag] in [ + TiffTags.RATIONAL, + TiffTags.SIGNED_RATIONAL, + ]: # rationals + values = (values,) + try: + (dest[tag],) = values + except ValueError: + # We've got a builtin tag with 1 expected entry + warnings.warn( + f"Metadata Warning, tag {tag} had too many entries: " + f"{len(values)}, expected 1" + ) + dest[tag] = values[0] + + else: + # Spec'd length > 1 or undefined + # Unspec'd, and length > 1 + dest[tag] = values + + def __delitem__(self, tag: int) -> None: + self._tags_v2.pop(tag, None) + self._tags_v1.pop(tag, None) + self._tagdata.pop(tag, None) + + def __iter__(self) -> Iterator[int]: + return iter(set(self._tagdata) | set(self._tags_v2)) + + def _unpack(self, fmt: str, data: bytes) -> tuple[Any, ...]: + return struct.unpack(self._endian + fmt, data) + + def _pack(self, fmt: str, *values: Any) -> bytes: + return struct.pack(self._endian + fmt, *values) + + list( + map( + _register_basic, + [ + (TiffTags.SHORT, "H", "short"), + (TiffTags.LONG, "L", "long"), + (TiffTags.SIGNED_BYTE, "b", "signed byte"), + (TiffTags.SIGNED_SHORT, "h", "signed short"), + (TiffTags.SIGNED_LONG, "l", "signed long"), + (TiffTags.FLOAT, "f", "float"), + (TiffTags.DOUBLE, "d", "double"), + (TiffTags.IFD, "L", "long"), + (TiffTags.LONG8, "Q", "long8"), + ], + ) + ) + + @_register_loader(1, 1) # Basic type, except for the legacy API. + def load_byte(self, data: bytes, legacy_api: bool = True) -> bytes: + return data + + @_register_writer(1) # Basic type, except for the legacy API. + def write_byte(self, data: bytes | int | IFDRational) -> bytes: + if isinstance(data, IFDRational): + data = int(data) + if isinstance(data, int): + data = bytes((data,)) + return data + + @_register_loader(2, 1) + def load_string(self, data: bytes, legacy_api: bool = True) -> str: + if data.endswith(b"\0"): + data = data[:-1] + return data.decode("latin-1", "replace") + + @_register_writer(2) + def write_string(self, value: str | bytes | int) -> bytes: + # remerge of https://github.com/python-pillow/Pillow/pull/1416 + if isinstance(value, int): + value = str(value) + if not isinstance(value, bytes): + value = value.encode("ascii", "replace") + return value + b"\0" + + @_register_loader(5, 8) + def load_rational( + self, data: bytes, legacy_api: bool = True + ) -> tuple[tuple[int, int] | IFDRational, ...]: + vals = self._unpack(f"{len(data) // 4}L", data) + + def combine(a: int, b: int) -> tuple[int, int] | IFDRational: + return (a, b) if legacy_api else IFDRational(a, b) + + return tuple(combine(num, denom) for num, denom in zip(vals[::2], vals[1::2])) + + @_register_writer(5) + def write_rational(self, *values: IFDRational) -> bytes: + return b"".join( + self._pack("2L", *_limit_rational(frac, 2**32 - 1)) for frac in values + ) + + @_register_loader(7, 1) + def load_undefined(self, data: bytes, legacy_api: bool = True) -> bytes: + return data + + @_register_writer(7) + def write_undefined(self, value: bytes | int | IFDRational) -> bytes: + if isinstance(value, IFDRational): + value = int(value) + if isinstance(value, int): + value = str(value).encode("ascii", "replace") + return value + + @_register_loader(10, 8) + def load_signed_rational( + self, data: bytes, legacy_api: bool = True + ) -> tuple[tuple[int, int] | IFDRational, ...]: + vals = self._unpack(f"{len(data) // 4}l", data) + + def combine(a: int, b: int) -> tuple[int, int] | IFDRational: + return (a, b) if legacy_api else IFDRational(a, b) + + return tuple(combine(num, denom) for num, denom in zip(vals[::2], vals[1::2])) + + @_register_writer(10) + def write_signed_rational(self, *values: IFDRational) -> bytes: + return b"".join( + self._pack("2l", *_limit_signed_rational(frac, 2**31 - 1, -(2**31))) + for frac in values + ) + + def _ensure_read(self, fp: IO[bytes], size: int) -> bytes: + ret = fp.read(size) + if len(ret) != size: + msg = ( + "Corrupt EXIF data. " + f"Expecting to read {size} bytes but only got {len(ret)}. " + ) + raise OSError(msg) + return ret + + def load(self, fp: IO[bytes]) -> None: + self.reset() + self._offset = fp.tell() + + try: + tag_count = ( + self._unpack("Q", self._ensure_read(fp, 8)) + if self._bigtiff + else self._unpack("H", self._ensure_read(fp, 2)) + )[0] + for i in range(tag_count): + tag, typ, count, data = ( + self._unpack("HHQ8s", self._ensure_read(fp, 20)) + if self._bigtiff + else self._unpack("HHL4s", self._ensure_read(fp, 12)) + ) + + tagname = TiffTags.lookup(tag, self.group).name + typname = TYPES.get(typ, "unknown") + msg = f"tag: {tagname} ({tag}) - type: {typname} ({typ})" + + try: + unit_size, handler = self._load_dispatch[typ] + except KeyError: + logger.debug("%s - unsupported type %s", msg, typ) + continue # ignore unsupported type + size = count * unit_size + if size > (8 if self._bigtiff else 4): + here = fp.tell() + (offset,) = self._unpack("Q" if self._bigtiff else "L", data) + msg += f" Tag Location: {here} - Data Location: {offset}" + fp.seek(offset) + data = ImageFile._safe_read(fp, size) + fp.seek(here) + else: + data = data[:size] + + if len(data) != size: + warnings.warn( + "Possibly corrupt EXIF data. " + f"Expecting to read {size} bytes but only got {len(data)}." + f" Skipping tag {tag}" + ) + logger.debug(msg) + continue + + if not data: + logger.debug(msg) + continue + + self._tagdata[tag] = data + self.tagtype[tag] = typ + + msg += " - value: " + msg += f"" if size > 32 else repr(data) + + logger.debug(msg) + + (self.next,) = ( + self._unpack("Q", self._ensure_read(fp, 8)) + if self._bigtiff + else self._unpack("L", self._ensure_read(fp, 4)) + ) + except OSError as msg: + warnings.warn(str(msg)) + return + + def _get_ifh(self) -> bytes: + ifh = self._prefix + self._pack("H", 43 if self._bigtiff else 42) + if self._bigtiff: + ifh += self._pack("HH", 8, 0) + ifh += self._pack("Q", 16) if self._bigtiff else self._pack("L", 8) + + return ifh + + def tobytes(self, offset: int = 0) -> bytes: + # FIXME What about tagdata? + result = self._pack("Q" if self._bigtiff else "H", len(self._tags_v2)) + + entries: list[tuple[int, int, int, bytes, bytes]] = [] + + fmt = "Q" if self._bigtiff else "L" + fmt_size = 8 if self._bigtiff else 4 + offset += ( + len(result) + len(self._tags_v2) * (20 if self._bigtiff else 12) + fmt_size + ) + stripoffsets = None + + # pass 1: convert tags to binary format + # always write tags in ascending order + for tag, value in sorted(self._tags_v2.items()): + if tag == STRIPOFFSETS: + stripoffsets = len(entries) + typ = self.tagtype[tag] + logger.debug("Tag %s, Type: %s, Value: %s", tag, typ, repr(value)) + is_ifd = typ == TiffTags.LONG and isinstance(value, dict) + if is_ifd: + ifd = ImageFileDirectory_v2(self._get_ifh(), group=tag) + values = self._tags_v2[tag] + for ifd_tag, ifd_value in values.items(): + ifd[ifd_tag] = ifd_value + data = ifd.tobytes(offset) + else: + values = value if isinstance(value, tuple) else (value,) + data = self._write_dispatch[typ](self, *values) + + tagname = TiffTags.lookup(tag, self.group).name + typname = "ifd" if is_ifd else TYPES.get(typ, "unknown") + msg = f"save: {tagname} ({tag}) - type: {typname} ({typ}) - value: " + msg += f"" if len(data) >= 16 else str(values) + logger.debug(msg) + + # count is sum of lengths for string and arbitrary data + if is_ifd: + count = 1 + elif typ in [TiffTags.BYTE, TiffTags.ASCII, TiffTags.UNDEFINED]: + count = len(data) + else: + count = len(values) + # figure out if data fits into the entry + if len(data) <= fmt_size: + entries.append((tag, typ, count, data.ljust(fmt_size, b"\0"), b"")) + else: + entries.append((tag, typ, count, self._pack(fmt, offset), data)) + offset += (len(data) + 1) // 2 * 2 # pad to word + + # update strip offset data to point beyond auxiliary data + if stripoffsets is not None: + tag, typ, count, value, data = entries[stripoffsets] + if data: + size, handler = self._load_dispatch[typ] + values = [val + offset for val in handler(self, data, self.legacy_api)] + data = self._write_dispatch[typ](self, *values) + else: + value = self._pack(fmt, self._unpack(fmt, value)[0] + offset) + entries[stripoffsets] = tag, typ, count, value, data + + # pass 2: write entries to file + for tag, typ, count, value, data in entries: + logger.debug("%s %s %s %s %s", tag, typ, count, repr(value), repr(data)) + result += self._pack( + "HHQ8s" if self._bigtiff else "HHL4s", tag, typ, count, value + ) + + # -- overwrite here for multi-page -- + result += self._pack(fmt, 0) # end of entries + + # pass 3: write auxiliary data to file + for tag, typ, count, value, data in entries: + result += data + if len(data) & 1: + result += b"\0" + + return result + + def save(self, fp: IO[bytes]) -> int: + if fp.tell() == 0: # skip TIFF header on subsequent pages + fp.write(self._get_ifh()) + + offset = fp.tell() + result = self.tobytes(offset) + fp.write(result) + return offset + len(result) + + +ImageFileDirectory_v2._load_dispatch = _load_dispatch +ImageFileDirectory_v2._write_dispatch = _write_dispatch +for idx, name in TYPES.items(): + name = name.replace(" ", "_") + setattr(ImageFileDirectory_v2, f"load_{name}", _load_dispatch[idx][1]) + setattr(ImageFileDirectory_v2, f"write_{name}", _write_dispatch[idx]) +del _load_dispatch, _write_dispatch, idx, name + + +# Legacy ImageFileDirectory support. +class ImageFileDirectory_v1(ImageFileDirectory_v2): + """This class represents the **legacy** interface to a TIFF tag directory. + + Exposes a dictionary interface of the tags in the directory:: + + ifd = ImageFileDirectory_v1() + ifd[key] = 'Some Data' + ifd.tagtype[key] = TiffTags.ASCII + print(ifd[key]) + ('Some Data',) + + Also contains a dictionary of tag types as read from the tiff image file, + :attr:`~PIL.TiffImagePlugin.ImageFileDirectory_v1.tagtype`. + + Values are returned as a tuple. + + .. deprecated:: 3.0.0 + """ + + def __init__(self, *args: Any, **kwargs: Any) -> None: + super().__init__(*args, **kwargs) + self._legacy_api = True + + tags = property(lambda self: self._tags_v1) + tagdata = property(lambda self: self._tagdata) + + # defined in ImageFileDirectory_v2 + tagtype: dict[int, int] + """Dictionary of tag types""" + + @classmethod + def from_v2(cls, original: ImageFileDirectory_v2) -> ImageFileDirectory_v1: + """Returns an + :py:class:`~PIL.TiffImagePlugin.ImageFileDirectory_v1` + instance with the same data as is contained in the original + :py:class:`~PIL.TiffImagePlugin.ImageFileDirectory_v2` + instance. + + :returns: :py:class:`~PIL.TiffImagePlugin.ImageFileDirectory_v1` + + """ + + ifd = cls(prefix=original.prefix) + ifd._tagdata = original._tagdata + ifd.tagtype = original.tagtype + ifd.next = original.next # an indicator for multipage tiffs + return ifd + + def to_v2(self) -> ImageFileDirectory_v2: + """Returns an + :py:class:`~PIL.TiffImagePlugin.ImageFileDirectory_v2` + instance with the same data as is contained in the original + :py:class:`~PIL.TiffImagePlugin.ImageFileDirectory_v1` + instance. + + :returns: :py:class:`~PIL.TiffImagePlugin.ImageFileDirectory_v2` + + """ + + ifd = ImageFileDirectory_v2(prefix=self.prefix) + ifd._tagdata = dict(self._tagdata) + ifd.tagtype = dict(self.tagtype) + ifd._tags_v2 = dict(self._tags_v2) + return ifd + + def __contains__(self, tag: object) -> bool: + return tag in self._tags_v1 or tag in self._tagdata + + def __len__(self) -> int: + return len(set(self._tagdata) | set(self._tags_v1)) + + def __iter__(self) -> Iterator[int]: + return iter(set(self._tagdata) | set(self._tags_v1)) + + def __setitem__(self, tag: int, value: Any) -> None: + for legacy_api in (False, True): + self._setitem(tag, value, legacy_api) + + def __getitem__(self, tag: int) -> Any: + if tag not in self._tags_v1: # unpack on the fly + data = self._tagdata[tag] + typ = self.tagtype[tag] + size, handler = self._load_dispatch[typ] + for legacy in (False, True): + self._setitem(tag, handler(self, data, legacy), legacy) + val = self._tags_v1[tag] + if not isinstance(val, (tuple, bytes)): + val = (val,) + return val + + +# undone -- switch this pointer +ImageFileDirectory = ImageFileDirectory_v1 + + +## +# Image plugin for TIFF files. + + +class TiffImageFile(ImageFile.ImageFile): + format = "TIFF" + format_description = "Adobe TIFF" + _close_exclusive_fp_after_loading = False + + def __init__( + self, + fp: StrOrBytesPath | IO[bytes], + filename: str | bytes | None = None, + ) -> None: + self.tag_v2: ImageFileDirectory_v2 + """ Image file directory (tag dictionary) """ + + self.tag: ImageFileDirectory_v1 + """ Legacy tag entries """ + + super().__init__(fp, filename) + + def _open(self) -> None: + """Open the first image in a TIFF file""" + + # Header + assert self.fp is not None + ifh = self.fp.read(8) + if ifh[2] == 43: + ifh += self.fp.read(8) + + self.tag_v2 = ImageFileDirectory_v2(ifh) + + # setup frame pointers + self.__first = self.__next = self.tag_v2.next + self.__frame = -1 + self._fp = self.fp + self._frame_pos: list[int] = [] + self._n_frames: int | None = None + + logger.debug("*** TiffImageFile._open ***") + logger.debug("- __first: %s", self.__first) + logger.debug("- ifh: %s", repr(ifh)) # Use repr to avoid str(bytes) + + # and load the first frame + self._seek(0) + + @property + def n_frames(self) -> int: + current_n_frames = self._n_frames + if current_n_frames is None: + current = self.tell() + self._seek(len(self._frame_pos)) + while self._n_frames is None: + self._seek(self.tell() + 1) + self.seek(current) + assert self._n_frames is not None + return self._n_frames + + def seek(self, frame: int) -> None: + """Select a given frame as current image""" + if not self._seek_check(frame): + return + self._seek(frame) + if self._im is not None and ( + self.im.size != self._tile_size + or self.im.mode != self.mode + or self.readonly + ): + self._im = None + + def _seek(self, frame: int) -> None: + if isinstance(self._fp, DeferredError): + raise self._fp.ex + self.fp = self._fp + + while len(self._frame_pos) <= frame: + if not self.__next: + msg = "no more images in TIFF file" + raise EOFError(msg) + logger.debug( + "Seeking to frame %s, on frame %s, __next %s, location: %s", + frame, + self.__frame, + self.__next, + self.fp.tell(), + ) + if self.__next >= 2**63: + msg = "Unable to seek to frame" + raise ValueError(msg) + self.fp.seek(self.__next) + self._frame_pos.append(self.__next) + logger.debug("Loading tags, location: %s", self.fp.tell()) + self.tag_v2.load(self.fp) + if self.tag_v2.next in self._frame_pos: + # This IFD has already been processed + # Declare this to be the end of the image + self.__next = 0 + else: + self.__next = self.tag_v2.next + if self.__next == 0: + self._n_frames = frame + 1 + if len(self._frame_pos) == 1: + self.is_animated = self.__next != 0 + self.__frame += 1 + self.fp.seek(self._frame_pos[frame]) + self.tag_v2.load(self.fp) + if XMP in self.tag_v2: + xmp = self.tag_v2[XMP] + if isinstance(xmp, tuple) and len(xmp) == 1: + xmp = xmp[0] + self.info["xmp"] = xmp + elif "xmp" in self.info: + del self.info["xmp"] + self._reload_exif() + # fill the legacy tag/ifd entries + self.tag = self.ifd = ImageFileDirectory_v1.from_v2(self.tag_v2) + self.__frame = frame + self._setup() + + def tell(self) -> int: + """Return the current frame number""" + return self.__frame + + def get_photoshop_blocks(self) -> dict[int, dict[str, bytes]]: + """ + Returns a dictionary of Photoshop "Image Resource Blocks". + The keys are the image resource ID. For more information, see + https://www.adobe.com/devnet-apps/photoshop/fileformatashtml/#50577409_pgfId-1037727 + + :returns: Photoshop "Image Resource Blocks" in a dictionary. + """ + blocks = {} + val = self.tag_v2.get(ExifTags.Base.ImageResources) + if val: + while val.startswith(b"8BIM"): + id = i16(val[4:6]) + n = math.ceil((val[6] + 1) / 2) * 2 + size = i32(val[6 + n : 10 + n]) + data = val[10 + n : 10 + n + size] + blocks[id] = {"data": data} + + val = val[math.ceil((10 + n + size) / 2) * 2 :] + return blocks + + def load(self) -> Image.core.PixelAccess | None: + if self.tile and self.use_load_libtiff: + return self._load_libtiff() + return super().load() + + def load_prepare(self) -> None: + if self._im is None: + Image._decompression_bomb_check(self._tile_size) + self.im = Image.core.new(self.mode, self._tile_size) + ImageFile.ImageFile.load_prepare(self) + + def load_end(self) -> None: + # allow closing if we're on the first frame, there's no next + # This is the ImageFile.load path only, libtiff specific below. + if not self.is_animated: + self._close_exclusive_fp_after_loading = True + + # load IFD data from fp before it is closed + exif = self.getexif() + for key in TiffTags.TAGS_V2_GROUPS: + if key not in exif: + continue + exif.get_ifd(key) + + ImageOps.exif_transpose(self, in_place=True) + if ExifTags.Base.Orientation in self.tag_v2: + del self.tag_v2[ExifTags.Base.Orientation] + + def _load_libtiff(self) -> Image.core.PixelAccess | None: + """Overload method triggered when we detect a compressed tiff + Calls out to libtiff""" + + Image.Image.load(self) + + self.load_prepare() + + if not len(self.tile) == 1: + msg = "Not exactly one tile" + raise OSError(msg) + + # (self._compression, (extents tuple), + # 0, (rawmode, self._compression, fp)) + extents = self.tile[0][1] + args = self.tile[0][3] + + # To be nice on memory footprint, if there's a + # file descriptor, use that instead of reading + # into a string in python. + assert self.fp is not None + try: + fp = hasattr(self.fp, "fileno") and self.fp.fileno() + # flush the file descriptor, prevents error on pypy 2.4+ + # should also eliminate the need for fp.tell + # in _seek + if hasattr(self.fp, "flush"): + self.fp.flush() + except OSError: + # io.BytesIO have a fileno, but returns an OSError if + # it doesn't use a file descriptor. + fp = False + + if fp: + assert isinstance(args, tuple) + args_list = list(args) + args_list[2] = fp + args = tuple(args_list) + + decoder = Image._getdecoder(self.mode, "libtiff", args, self.decoderconfig) + try: + decoder.setimage(self.im, extents) + except ValueError as e: + msg = "Couldn't set the image" + raise OSError(msg) from e + + close_self_fp = self._exclusive_fp and not self.is_animated + if hasattr(self.fp, "getvalue"): + # We've got a stringio like thing passed in. Yay for all in memory. + # The decoder needs the entire file in one shot, so there's not + # a lot we can do here other than give it the entire file. + # unless we could do something like get the address of the + # underlying string for stringio. + # + # Rearranging for supporting byteio items, since they have a fileno + # that returns an OSError if there's no underlying fp. Easier to + # deal with here by reordering. + logger.debug("have getvalue. just sending in a string from getvalue") + n, err = decoder.decode(self.fp.getvalue()) + elif fp: + # we've got a actual file on disk, pass in the fp. + logger.debug("have fileno, calling fileno version of the decoder.") + if not close_self_fp: + self.fp.seek(0) + # Save and restore the file position, because libtiff will move it + # outside of the Python runtime, and that will confuse + # io.BufferedReader and possible others. + # NOTE: This must use os.lseek(), and not fp.tell()/fp.seek(), + # because the buffer read head already may not equal the actual + # file position, and fp.seek() may just adjust it's internal + # pointer and not actually seek the OS file handle. + pos = os.lseek(fp, 0, os.SEEK_CUR) + # 4 bytes, otherwise the trace might error out + n, err = decoder.decode(b"fpfp") + os.lseek(fp, pos, os.SEEK_SET) + else: + # we have something else. + logger.debug("don't have fileno or getvalue. just reading") + self.fp.seek(0) + # UNDONE -- so much for that buffer size thing. + n, err = decoder.decode(self.fp.read()) + + self.tile = [] + self.readonly = 0 + + self.load_end() + + if close_self_fp: + self.fp.close() + self.fp = None # might be shared + + if err < 0: + msg = f"decoder error {err}" + raise OSError(msg) + + return Image.Image.load(self) + + def _setup(self) -> None: + """Setup this image object based on current tags""" + + if 0xBC01 in self.tag_v2: + msg = "Windows Media Photo files not yet supported" + raise OSError(msg) + + # extract relevant tags + self._compression = COMPRESSION_INFO[self.tag_v2.get(COMPRESSION, 1)] + self._planar_configuration = self.tag_v2.get(PLANAR_CONFIGURATION, 1) + + # photometric is a required tag, but not everyone is reading + # the specification + photo = self.tag_v2.get(PHOTOMETRIC_INTERPRETATION, 0) + + # old style jpeg compression images most certainly are YCbCr + if self._compression == "tiff_jpeg": + photo = 6 + + fillorder = self.tag_v2.get(FILLORDER, 1) + + logger.debug("*** Summary ***") + logger.debug("- compression: %s", self._compression) + logger.debug("- photometric_interpretation: %s", photo) + logger.debug("- planar_configuration: %s", self._planar_configuration) + logger.debug("- fill_order: %s", fillorder) + logger.debug("- YCbCr subsampling: %s", self.tag_v2.get(YCBCRSUBSAMPLING)) + + # size + try: + xsize = self.tag_v2[IMAGEWIDTH] + ysize = self.tag_v2[IMAGELENGTH] + except KeyError as e: + msg = "Missing dimensions" + raise TypeError(msg) from e + if not isinstance(xsize, int) or not isinstance(ysize, int): + msg = "Invalid dimensions" + raise ValueError(msg) + self._tile_size = xsize, ysize + orientation = self.tag_v2.get(ExifTags.Base.Orientation) + if orientation in (5, 6, 7, 8): + self._size = ysize, xsize + else: + self._size = xsize, ysize + + logger.debug("- size: %s", self.size) + + sample_format = self.tag_v2.get(SAMPLEFORMAT, (1,)) + if len(sample_format) > 1 and max(sample_format) == min(sample_format) == 1: + # SAMPLEFORMAT is properly per band, so an RGB image will + # be (1,1,1). But, we don't support per band pixel types, + # and anything more than one band is a uint8. So, just + # take the first element. Revisit this if adding support + # for more exotic images. + sample_format = (1,) + + bps_tuple = self.tag_v2.get(BITSPERSAMPLE, (1,)) + extra_tuple = self.tag_v2.get(EXTRASAMPLES, ()) + if photo in (2, 6, 8): # RGB, YCbCr, LAB + bps_count = 3 + elif photo == 5: # CMYK + bps_count = 4 + else: + bps_count = 1 + bps_count += len(extra_tuple) + bps_actual_count = len(bps_tuple) + samples_per_pixel = self.tag_v2.get( + SAMPLESPERPIXEL, + 3 if self._compression == "tiff_jpeg" and photo in (2, 6) else 1, + ) + + if samples_per_pixel > MAX_SAMPLESPERPIXEL: + # DOS check, samples_per_pixel can be a Long, and we extend the tuple below + logger.error( + "More samples per pixel than can be decoded: %s", samples_per_pixel + ) + msg = "Invalid value for samples per pixel" + raise SyntaxError(msg) + + if samples_per_pixel < bps_actual_count: + # If a file has more values in bps_tuple than expected, + # remove the excess. + bps_tuple = bps_tuple[:samples_per_pixel] + elif samples_per_pixel > bps_actual_count and bps_actual_count == 1: + # If a file has only one value in bps_tuple, when it should have more, + # presume it is the same number of bits for all of the samples. + bps_tuple = bps_tuple * samples_per_pixel + + if len(bps_tuple) != samples_per_pixel: + msg = "unknown data organization" + raise SyntaxError(msg) + + # mode: check photometric interpretation and bits per pixel + key = ( + self.tag_v2.prefix, + photo, + sample_format, + fillorder, + bps_tuple, + extra_tuple, + ) + logger.debug("format key: %s", key) + try: + self._mode, rawmode = OPEN_INFO[key] + except KeyError as e: + logger.debug("- unsupported format") + msg = "unknown pixel mode" + raise SyntaxError(msg) from e + + logger.debug("- raw mode: %s", rawmode) + logger.debug("- pil mode: %s", self.mode) + + self.info["compression"] = self._compression + + xres = self.tag_v2.get(X_RESOLUTION, 1) + yres = self.tag_v2.get(Y_RESOLUTION, 1) + + if xres and yres: + resunit = self.tag_v2.get(RESOLUTION_UNIT) + if resunit == 2: # dots per inch + self.info["dpi"] = (xres, yres) + elif resunit == 3: # dots per centimeter. convert to dpi + self.info["dpi"] = (xres * 2.54, yres * 2.54) + elif resunit is None: # used to default to 1, but now 2) + self.info["dpi"] = (xres, yres) + # For backward compatibility, + # we also preserve the old behavior + self.info["resolution"] = xres, yres + else: # No absolute unit of measurement + self.info["resolution"] = xres, yres + + # build tile descriptors + x = y = layer = 0 + self.tile = [] + self.use_load_libtiff = READ_LIBTIFF or self._compression != "raw" + if self.use_load_libtiff: + # Decoder expects entire file as one tile. + # There's a buffer size limit in load (64k) + # so large g4 images will fail if we use that + # function. + # + # Setup the one tile for the whole image, then + # use the _load_libtiff function. + + # libtiff handles the fillmode for us, so 1;IR should + # actually be 1;I. Including the R double reverses the + # bits, so stripes of the image are reversed. See + # https://github.com/python-pillow/Pillow/issues/279 + if fillorder == 2: + # Replace fillorder with fillorder=1 + key = key[:3] + (1,) + key[4:] + logger.debug("format key: %s", key) + # this should always work, since all the + # fillorder==2 modes have a corresponding + # fillorder=1 mode + self._mode, rawmode = OPEN_INFO[key] + # YCbCr images with new jpeg compression with pixels in one plane + # unpacked straight into RGB values + if ( + photo == 6 + and self._compression == "jpeg" + and self._planar_configuration == 1 + ): + rawmode = "RGB" + # libtiff always returns the bytes in native order. + # we're expecting image byte order. So, if the rawmode + # contains I;16, we need to convert from native to image + # byte order. + elif rawmode == "I;16": + rawmode = "I;16N" + elif rawmode.endswith((";16B", ";16L")): + rawmode = rawmode[:-1] + "N" + + # Offset in the tile tuple is 0, we go from 0,0 to + # w,h, and we only do this once -- eds + a = (rawmode, self._compression, False, self.tag_v2.offset) + self.tile.append(ImageFile._Tile("libtiff", (0, 0, xsize, ysize), 0, a)) + + elif STRIPOFFSETS in self.tag_v2 or TILEOFFSETS in self.tag_v2: + # striped image + if STRIPOFFSETS in self.tag_v2: + offsets = self.tag_v2[STRIPOFFSETS] + h = self.tag_v2.get(ROWSPERSTRIP, ysize) + w = xsize + else: + # tiled image + offsets = self.tag_v2[TILEOFFSETS] + tilewidth = self.tag_v2.get(TILEWIDTH) + h = self.tag_v2.get(TILELENGTH) + if not isinstance(tilewidth, int) or not isinstance(h, int): + msg = "Invalid tile dimensions" + raise ValueError(msg) + w = tilewidth + + if w == xsize and h == ysize and self._planar_configuration != 2: + # Every tile covers the image. Only use the last offset + offsets = offsets[-1:] + + for offset in offsets: + if x + w > xsize: + stride = w * sum(bps_tuple) / 8 # bytes per line + else: + stride = 0 + + tile_rawmode = rawmode + if self._planar_configuration == 2: + # each band on it's own layer + tile_rawmode = rawmode[layer] + # adjust stride width accordingly + stride /= bps_count + + args = (tile_rawmode, int(stride), 1) + self.tile.append( + ImageFile._Tile( + self._compression, + (x, y, min(x + w, xsize), min(y + h, ysize)), + offset, + args, + ) + ) + x += w + if x >= xsize: + x, y = 0, y + h + if y >= ysize: + y = 0 + layer += 1 + else: + logger.debug("- unsupported data organization") + msg = "unknown data organization" + raise SyntaxError(msg) + + # Fix up info. + if ICCPROFILE in self.tag_v2: + self.info["icc_profile"] = self.tag_v2[ICCPROFILE] + + # fixup palette descriptor + + if self.mode in ["P", "PA"]: + palette = [o8(b // 256) for b in self.tag_v2[COLORMAP]] + self.palette = ImagePalette.raw("RGB;L", b"".join(palette)) + + +# +# -------------------------------------------------------------------- +# Write TIFF files + +# little endian is default except for image modes with +# explicit big endian byte-order + +SAVE_INFO = { + # mode => rawmode, byteorder, photometrics, + # sampleformat, bitspersample, extra + "1": ("1", II, 1, 1, (1,), None), + "L": ("L", II, 1, 1, (8,), None), + "LA": ("LA", II, 1, 1, (8, 8), 2), + "P": ("P", II, 3, 1, (8,), None), + "PA": ("PA", II, 3, 1, (8, 8), 2), + "I": ("I;32S", II, 1, 2, (32,), None), + "I;16": ("I;16", II, 1, 1, (16,), None), + "I;16L": ("I;16L", II, 1, 1, (16,), None), + "F": ("F;32F", II, 1, 3, (32,), None), + "RGB": ("RGB", II, 2, 1, (8, 8, 8), None), + "RGBX": ("RGBX", II, 2, 1, (8, 8, 8, 8), 0), + "RGBA": ("RGBA", II, 2, 1, (8, 8, 8, 8), 2), + "CMYK": ("CMYK", II, 5, 1, (8, 8, 8, 8), None), + "YCbCr": ("YCbCr", II, 6, 1, (8, 8, 8), None), + "LAB": ("LAB", II, 8, 1, (8, 8, 8), None), + "I;16B": ("I;16B", MM, 1, 1, (16,), None), +} + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + try: + rawmode, prefix, photo, format, bits, extra = SAVE_INFO[im.mode] + except KeyError as e: + msg = f"cannot write mode {im.mode} as TIFF" + raise OSError(msg) from e + + encoderinfo = im.encoderinfo + encoderconfig = im.encoderconfig + + ifd = ImageFileDirectory_v2(prefix=prefix) + if encoderinfo.get("big_tiff"): + ifd._bigtiff = True + + try: + compression = encoderinfo["compression"] + except KeyError: + compression = im.info.get("compression") + if isinstance(compression, int): + # compression value may be from BMP. Ignore it + compression = None + if compression is None: + compression = "raw" + elif compression == "tiff_jpeg": + # OJPEG is obsolete, so use new-style JPEG compression instead + compression = "jpeg" + elif compression == "tiff_deflate": + compression = "tiff_adobe_deflate" + + libtiff = WRITE_LIBTIFF or compression != "raw" + + # required for color libtiff images + ifd[PLANAR_CONFIGURATION] = 1 + + ifd[IMAGEWIDTH] = im.size[0] + ifd[IMAGELENGTH] = im.size[1] + + # write any arbitrary tags passed in as an ImageFileDirectory + if "tiffinfo" in encoderinfo: + info = encoderinfo["tiffinfo"] + elif "exif" in encoderinfo: + info = encoderinfo["exif"] + if isinstance(info, bytes): + exif = Image.Exif() + exif.load(info) + info = exif + else: + info = {} + logger.debug("Tiffinfo Keys: %s", list(info)) + if isinstance(info, ImageFileDirectory_v1): + info = info.to_v2() + for key in info: + if isinstance(info, Image.Exif) and key in TiffTags.TAGS_V2_GROUPS: + ifd[key] = info.get_ifd(key) + else: + ifd[key] = info.get(key) + try: + ifd.tagtype[key] = info.tagtype[key] + except Exception: + pass # might not be an IFD. Might not have populated type + + legacy_ifd = {} + if hasattr(im, "tag"): + legacy_ifd = im.tag.to_v2() + + supplied_tags = {**legacy_ifd, **getattr(im, "tag_v2", {})} + for tag in ( + # IFD offset that may not be correct in the saved image + EXIFIFD, + # Determined by the image format and should not be copied from legacy_ifd. + SAMPLEFORMAT, + ): + if tag in supplied_tags: + del supplied_tags[tag] + + # additions written by Greg Couch, gregc@cgl.ucsf.edu + # inspired by image-sig posting from Kevin Cazabon, kcazabon@home.com + if hasattr(im, "tag_v2"): + # preserve tags from original TIFF image file + for key in ( + RESOLUTION_UNIT, + X_RESOLUTION, + Y_RESOLUTION, + IPTC_NAA_CHUNK, + PHOTOSHOP_CHUNK, + XMP, + ): + if key in im.tag_v2: + if key == IPTC_NAA_CHUNK and im.tag_v2.tagtype[key] not in ( + TiffTags.BYTE, + TiffTags.UNDEFINED, + ): + del supplied_tags[key] + else: + ifd[key] = im.tag_v2[key] + ifd.tagtype[key] = im.tag_v2.tagtype[key] + + # preserve ICC profile (should also work when saving other formats + # which support profiles as TIFF) -- 2008-06-06 Florian Hoech + icc = encoderinfo.get("icc_profile", im.info.get("icc_profile")) + if icc: + ifd[ICCPROFILE] = icc + + for key, name in [ + (IMAGEDESCRIPTION, "description"), + (X_RESOLUTION, "resolution"), + (Y_RESOLUTION, "resolution"), + (X_RESOLUTION, "x_resolution"), + (Y_RESOLUTION, "y_resolution"), + (RESOLUTION_UNIT, "resolution_unit"), + (SOFTWARE, "software"), + (DATE_TIME, "date_time"), + (ARTIST, "artist"), + (COPYRIGHT, "copyright"), + ]: + if name in encoderinfo: + ifd[key] = encoderinfo[name] + + dpi = encoderinfo.get("dpi") + if dpi: + ifd[RESOLUTION_UNIT] = 2 + ifd[X_RESOLUTION] = dpi[0] + ifd[Y_RESOLUTION] = dpi[1] + + if bits != (1,): + ifd[BITSPERSAMPLE] = bits + if len(bits) != 1: + ifd[SAMPLESPERPIXEL] = len(bits) + if extra is not None: + ifd[EXTRASAMPLES] = extra + if format != 1: + ifd[SAMPLEFORMAT] = format + + if PHOTOMETRIC_INTERPRETATION not in ifd: + ifd[PHOTOMETRIC_INTERPRETATION] = photo + elif im.mode in ("1", "L") and ifd[PHOTOMETRIC_INTERPRETATION] == 0: + if im.mode == "1": + inverted_im = im.copy() + px = inverted_im.load() + if px is not None: + for y in range(inverted_im.height): + for x in range(inverted_im.width): + px[x, y] = 0 if px[x, y] == 255 else 255 + im = inverted_im + else: + im = ImageOps.invert(im) + + if im.mode in ["P", "PA"]: + lut = im.im.getpalette("RGB", "RGB;L") + colormap = [] + colors = len(lut) // 3 + for i in range(3): + colormap += [v * 256 for v in lut[colors * i : colors * (i + 1)]] + colormap += [0] * (256 - colors) + ifd[COLORMAP] = colormap + # data orientation + w, h = ifd[IMAGEWIDTH], ifd[IMAGELENGTH] + stride = len(bits) * ((w * bits[0] + 7) // 8) + if ROWSPERSTRIP not in ifd: + # aim for given strip size (64 KB by default) when using libtiff writer + if libtiff: + im_strip_size = encoderinfo.get("strip_size", STRIP_SIZE) + rows_per_strip = 1 if stride == 0 else min(im_strip_size // stride, h) + # JPEG encoder expects multiple of 8 rows + if compression == "jpeg": + rows_per_strip = min(((rows_per_strip + 7) // 8) * 8, h) + else: + rows_per_strip = h + if rows_per_strip == 0: + rows_per_strip = 1 + ifd[ROWSPERSTRIP] = rows_per_strip + strip_byte_counts = 1 if stride == 0 else stride * ifd[ROWSPERSTRIP] + strips_per_image = (h + ifd[ROWSPERSTRIP] - 1) // ifd[ROWSPERSTRIP] + if strip_byte_counts >= 2**16: + ifd.tagtype[STRIPBYTECOUNTS] = TiffTags.LONG + ifd[STRIPBYTECOUNTS] = (strip_byte_counts,) * (strips_per_image - 1) + ( + stride * h - strip_byte_counts * (strips_per_image - 1), + ) + ifd[STRIPOFFSETS] = tuple( + range(0, strip_byte_counts * strips_per_image, strip_byte_counts) + ) # this is adjusted by IFD writer + # no compression by default: + ifd[COMPRESSION] = COMPRESSION_INFO_REV.get(compression, 1) + + if im.mode == "YCbCr": + for tag, default_value in { + YCBCRSUBSAMPLING: (1, 1), + REFERENCEBLACKWHITE: (0, 255, 128, 255, 128, 255), + }.items(): + ifd.setdefault(tag, default_value) + + blocklist = [TILEWIDTH, TILELENGTH, TILEOFFSETS, TILEBYTECOUNTS] + if libtiff: + if "quality" in encoderinfo: + quality = encoderinfo["quality"] + if not isinstance(quality, int) or quality < 0 or quality > 100: + msg = "Invalid quality setting" + raise ValueError(msg) + if compression != "jpeg": + msg = "quality setting only supported for 'jpeg' compression" + raise ValueError(msg) + ifd[JPEGQUALITY] = quality + + logger.debug("Saving using libtiff encoder") + logger.debug("Items: %s", sorted(ifd.items())) + _fp = 0 + if hasattr(fp, "fileno"): + try: + fp.seek(0) + _fp = fp.fileno() + except io.UnsupportedOperation: + pass + + # optional types for non core tags + types = {} + # STRIPOFFSETS and STRIPBYTECOUNTS are added by the library + # based on the data in the strip. + # OSUBFILETYPE is deprecated. + # The other tags expect arrays with a certain length (fixed or depending on + # BITSPERSAMPLE, etc), passing arrays with a different length will result in + # segfaults. Block these tags until we add extra validation. + # SUBIFD may also cause a segfault. + blocklist += [ + OSUBFILETYPE, + REFERENCEBLACKWHITE, + STRIPBYTECOUNTS, + STRIPOFFSETS, + TRANSFERFUNCTION, + SUBIFD, + ] + + # bits per sample is a single short in the tiff directory, not a list. + atts: dict[int, Any] = {BITSPERSAMPLE: bits[0]} + # Merge the ones that we have with (optional) more bits from + # the original file, e.g x,y resolution so that we can + # save(load('')) == original file. + for tag, value in itertools.chain(ifd.items(), supplied_tags.items()): + # Libtiff can only process certain core items without adding + # them to the custom dictionary. + # Custom items are supported for int, float, unicode, string and byte + # values. Other types and tuples require a tagtype. + if tag not in TiffTags.LIBTIFF_CORE: + if tag in TiffTags.TAGS_V2_GROUPS: + types[tag] = TiffTags.LONG8 + elif tag in ifd.tagtype: + types[tag] = ifd.tagtype[tag] + elif isinstance(value, (int, float, str, bytes)) or ( + isinstance(value, tuple) + and all(isinstance(v, (int, float, IFDRational)) for v in value) + ): + type = TiffTags.lookup(tag).type + if type: + types[tag] = type + if tag not in atts and tag not in blocklist: + if isinstance(value, str): + atts[tag] = value.encode("ascii", "replace") + b"\0" + elif isinstance(value, IFDRational): + atts[tag] = float(value) + else: + atts[tag] = value + + if SAMPLEFORMAT in atts and len(atts[SAMPLEFORMAT]) == 1: + atts[SAMPLEFORMAT] = atts[SAMPLEFORMAT][0] + + logger.debug("Converted items: %s", sorted(atts.items())) + + # libtiff always expects the bytes in native order. + # we're storing image byte order. So, if the rawmode + # contains I;16, we need to convert from native to image + # byte order. + if im.mode in ("I;16", "I;16B", "I;16L"): + rawmode = "I;16N" + + # Pass tags as sorted list so that the tags are set in a fixed order. + # This is required by libtiff for some tags. For example, the JPEGQUALITY + # pseudo tag requires that the COMPRESS tag was already set. + tags = list(atts.items()) + tags.sort() + a = (rawmode, compression, _fp, filename, tags, types) + encoder = Image._getencoder(im.mode, "libtiff", a, encoderconfig) + encoder.setimage(im.im, (0, 0) + im.size) + while True: + errcode, data = encoder.encode(ImageFile.MAXBLOCK)[1:] + if not _fp: + fp.write(data) + if errcode: + break + if errcode < 0: + msg = f"encoder error {errcode} when writing image file" + raise OSError(msg) + + else: + for tag in blocklist: + del ifd[tag] + offset = ifd.save(fp) + + ImageFile._save( + im, + fp, + [ImageFile._Tile("raw", (0, 0) + im.size, offset, (rawmode, stride, 1))], + ) + + # -- helper for multi-page save -- + if "_debug_multipage" in encoderinfo: + # just to access o32 and o16 (using correct byte order) + setattr(im, "_debug_multipage", ifd) + + +class AppendingTiffWriter(io.BytesIO): + fieldSizes = [ + 0, # None + 1, # byte + 1, # ascii + 2, # short + 4, # long + 8, # rational + 1, # sbyte + 1, # undefined + 2, # sshort + 4, # slong + 8, # srational + 4, # float + 8, # double + 4, # ifd + 2, # unicode + 4, # complex + 8, # long8 + ] + + Tags = { + 273, # StripOffsets + 288, # FreeOffsets + 324, # TileOffsets + 519, # JPEGQTables + 520, # JPEGDCTables + 521, # JPEGACTables + } + + def __init__(self, fn: StrOrBytesPath | IO[bytes], new: bool = False) -> None: + self.f: IO[bytes] + if is_path(fn): + self.name = fn + self.close_fp = True + try: + self.f = open(fn, "w+b" if new else "r+b") + except OSError: + self.f = open(fn, "w+b") + else: + self.f = cast(IO[bytes], fn) + self.close_fp = False + self.beginning = self.f.tell() + self.setup() + + def setup(self) -> None: + # Reset everything. + self.f.seek(self.beginning, os.SEEK_SET) + + self.whereToWriteNewIFDOffset: int | None = None + self.offsetOfNewPage = 0 + + self.IIMM = iimm = self.f.read(4) + self._bigtiff = b"\x2b" in iimm + if not iimm: + # empty file - first page + self.isFirst = True + return + + self.isFirst = False + if iimm not in PREFIXES: + msg = "Invalid TIFF file header" + raise RuntimeError(msg) + + self.setEndian("<" if iimm.startswith(II) else ">") + + if self._bigtiff: + self.f.seek(4, os.SEEK_CUR) + self.skipIFDs() + self.goToEnd() + + def finalize(self) -> None: + if self.isFirst: + return + + # fix offsets + self.f.seek(self.offsetOfNewPage) + + iimm = self.f.read(4) + if not iimm: + # Make it easy to finish a frame without committing to a new one. + return + + if iimm != self.IIMM: + msg = "IIMM of new page doesn't match IIMM of first page" + raise RuntimeError(msg) + + if self._bigtiff: + self.f.seek(4, os.SEEK_CUR) + ifd_offset = self._read(8 if self._bigtiff else 4) + ifd_offset += self.offsetOfNewPage + assert self.whereToWriteNewIFDOffset is not None + self.f.seek(self.whereToWriteNewIFDOffset) + self._write(ifd_offset, 8 if self._bigtiff else 4) + self.f.seek(ifd_offset) + self.fixIFD() + + def newFrame(self) -> None: + # Call this to finish a frame. + self.finalize() + self.setup() + + def __enter__(self) -> AppendingTiffWriter: + return self + + def __exit__(self, *args: object) -> None: + if self.close_fp: + self.close() + + def tell(self) -> int: + return self.f.tell() - self.offsetOfNewPage + + def seek(self, offset: int, whence: int = io.SEEK_SET) -> int: + """ + :param offset: Distance to seek. + :param whence: Whether the distance is relative to the start, + end or current position. + :returns: The resulting position, relative to the start. + """ + if whence == os.SEEK_SET: + offset += self.offsetOfNewPage + + self.f.seek(offset, whence) + return self.tell() + + def goToEnd(self) -> None: + self.f.seek(0, os.SEEK_END) + pos = self.f.tell() + + # pad to 16 byte boundary + pad_bytes = 16 - pos % 16 + if 0 < pad_bytes < 16: + self.f.write(bytes(pad_bytes)) + self.offsetOfNewPage = self.f.tell() + + def setEndian(self, endian: str) -> None: + self.endian = endian + self.longFmt = f"{self.endian}L" + self.shortFmt = f"{self.endian}H" + self.tagFormat = f"{self.endian}HH" + ("Q" if self._bigtiff else "L") + + def skipIFDs(self) -> None: + while True: + ifd_offset = self._read(8 if self._bigtiff else 4) + if ifd_offset == 0: + self.whereToWriteNewIFDOffset = self.f.tell() - ( + 8 if self._bigtiff else 4 + ) + break + + self.f.seek(ifd_offset) + num_tags = self._read(8 if self._bigtiff else 2) + self.f.seek(num_tags * (20 if self._bigtiff else 12), os.SEEK_CUR) + + def write(self, data: Buffer, /) -> int: + return self.f.write(data) + + def _fmt(self, field_size: int) -> str: + try: + return {2: "H", 4: "L", 8: "Q"}[field_size] + except KeyError: + msg = "offset is not supported" + raise RuntimeError(msg) + + def _read(self, field_size: int) -> int: + (value,) = struct.unpack( + self.endian + self._fmt(field_size), self.f.read(field_size) + ) + return value + + def readShort(self) -> int: + return self._read(2) + + def readLong(self) -> int: + return self._read(4) + + @staticmethod + def _verify_bytes_written(bytes_written: int | None, expected: int) -> None: + if bytes_written is not None and bytes_written != expected: + msg = f"wrote only {bytes_written} bytes but wanted {expected}" + raise RuntimeError(msg) + + def _rewriteLast( + self, value: int, field_size: int, new_field_size: int = 0 + ) -> None: + self.f.seek(-field_size, os.SEEK_CUR) + if not new_field_size: + new_field_size = field_size + bytes_written = self.f.write( + struct.pack(self.endian + self._fmt(new_field_size), value) + ) + self._verify_bytes_written(bytes_written, new_field_size) + + def rewriteLastShortToLong(self, value: int) -> None: + self._rewriteLast(value, 2, 4) + + def rewriteLastShort(self, value: int) -> None: + return self._rewriteLast(value, 2) + + def rewriteLastLong(self, value: int) -> None: + return self._rewriteLast(value, 4) + + def _write(self, value: int, field_size: int) -> None: + bytes_written = self.f.write( + struct.pack(self.endian + self._fmt(field_size), value) + ) + self._verify_bytes_written(bytes_written, field_size) + + def writeShort(self, value: int) -> None: + self._write(value, 2) + + def writeLong(self, value: int) -> None: + self._write(value, 4) + + def close(self) -> None: + self.finalize() + if self.close_fp: + self.f.close() + + def fixIFD(self) -> None: + num_tags = self._read(8 if self._bigtiff else 2) + + for i in range(num_tags): + tag, field_type, count = struct.unpack( + self.tagFormat, self.f.read(12 if self._bigtiff else 8) + ) + + field_size = self.fieldSizes[field_type] + total_size = field_size * count + fmt_size = 8 if self._bigtiff else 4 + is_local = total_size <= fmt_size + if not is_local: + offset = self._read(fmt_size) + self.offsetOfNewPage + self._rewriteLast(offset, fmt_size) + + if tag in self.Tags: + cur_pos = self.f.tell() + + logger.debug( + "fixIFD: %s (%d) - type: %s (%d) - type size: %d - count: %d", + TiffTags.lookup(tag).name, + tag, + TYPES.get(field_type, "unknown"), + field_type, + field_size, + count, + ) + + if is_local: + self._fixOffsets(count, field_size) + self.f.seek(cur_pos + fmt_size) + else: + self.f.seek(offset) + self._fixOffsets(count, field_size) + self.f.seek(cur_pos) + + elif is_local: + # skip the locally stored value that is not an offset + self.f.seek(fmt_size, os.SEEK_CUR) + + def _fixOffsets(self, count: int, field_size: int) -> None: + for i in range(count): + offset = self._read(field_size) + offset += self.offsetOfNewPage + + new_field_size = 0 + if self._bigtiff and field_size in (2, 4) and offset >= 2**32: + # offset is now too large - we must convert long to long8 + new_field_size = 8 + elif field_size == 2 and offset >= 2**16: + # offset is now too large - we must convert short to long + new_field_size = 4 + if new_field_size: + if count != 1: + msg = "not implemented" + raise RuntimeError(msg) # XXX TODO + + # simple case - the offset is just one and therefore it is + # local (not referenced with another offset) + self._rewriteLast(offset, field_size, new_field_size) + # Move back past the new offset, past 'count', and before 'field_type' + rewind = -new_field_size - 4 - 2 + self.f.seek(rewind, os.SEEK_CUR) + self.writeShort(new_field_size) # rewrite the type + self.f.seek(2 - rewind, os.SEEK_CUR) + else: + self._rewriteLast(offset, field_size) + + def fixOffsets( + self, count: int, isShort: bool = False, isLong: bool = False + ) -> None: + if isShort: + field_size = 2 + elif isLong: + field_size = 4 + else: + field_size = 0 + return self._fixOffsets(count, field_size) + + +def _save_all(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + append_images = list(im.encoderinfo.get("append_images", [])) + if not hasattr(im, "n_frames") and not append_images: + return _save(im, fp, filename) + + cur_idx = im.tell() + try: + with AppendingTiffWriter(fp) as tf: + for ims in [im] + append_images: + encoderinfo = ims._attach_default_encoderinfo(im) + if not hasattr(ims, "encoderconfig"): + ims.encoderconfig = () + nfr = getattr(ims, "n_frames", 1) + + for idx in range(nfr): + ims.seek(idx) + ims.load() + _save(ims, tf, filename) + tf.newFrame() + ims.encoderinfo = encoderinfo + finally: + im.seek(cur_idx) + + +# +# -------------------------------------------------------------------- +# Register + +Image.register_open(TiffImageFile.format, TiffImageFile, _accept) +Image.register_save(TiffImageFile.format, _save) +Image.register_save_all(TiffImageFile.format, _save_all) + +Image.register_extensions(TiffImageFile.format, [".tif", ".tiff"]) + +Image.register_mime(TiffImageFile.format, "image/tiff") diff --git a/PIL/TiffTags.py b/PIL/TiffTags.py new file mode 100644 index 0000000000000000000000000000000000000000..613a3b7def7149628039ddb817fcf8dbba395b18 --- /dev/null +++ b/PIL/TiffTags.py @@ -0,0 +1,566 @@ +# +# The Python Imaging Library. +# $Id$ +# +# TIFF tags +# +# This module provides clear-text names for various well-known +# TIFF tags. the TIFF codec works just fine without it. +# +# Copyright (c) Secret Labs AB 1999. +# +# See the README file for information on usage and redistribution. +# + +## +# This module provides constants and clear-text names for various +# well-known TIFF tags. +## +from __future__ import annotations + +from typing import NamedTuple + + +class _TagInfo(NamedTuple): + value: int | None + name: str + type: int | None + length: int | None + enum: dict[str, int] + + +class TagInfo(_TagInfo): + __slots__: list[str] = [] + + def __new__( + cls, + value: int | None = None, + name: str = "unknown", + type: int | None = None, + length: int | None = None, + enum: dict[str, int] | None = None, + ) -> TagInfo: + return super().__new__(cls, value, name, type, length, enum or {}) + + def cvt_enum(self, value: str) -> int | str: + # Using get will call hash(value), which can be expensive + # for some types (e.g. Fraction). Since self.enum is rarely + # used, it's usually better to test it first. + return self.enum.get(value, value) if self.enum else value + + +def lookup(tag: int, group: int | None = None) -> TagInfo: + """ + :param tag: Integer tag number + :param group: Which :py:data:`~PIL.TiffTags.TAGS_V2_GROUPS` to look in + + .. versionadded:: 8.3.0 + + :returns: Taginfo namedtuple, From the ``TAGS_V2`` info if possible, + otherwise just populating the value and name from ``TAGS``. + If the tag is not recognized, "unknown" is returned for the name + + """ + + if group is not None: + info = TAGS_V2_GROUPS[group].get(tag) if group in TAGS_V2_GROUPS else None + else: + info = TAGS_V2.get(tag) + return info or TagInfo(tag, TAGS.get(tag, "unknown")) + + +## +# Map tag numbers to tag info. +# +# id: (Name, Type, Length[, enum_values]) +# +# The length here differs from the length in the tiff spec. For +# numbers, the tiff spec is for the number of fields returned. We +# agree here. For string-like types, the tiff spec uses the length of +# field in bytes. In Pillow, we are using the number of expected +# fields, in general 1 for string-like types. + + +BYTE = 1 +ASCII = 2 +SHORT = 3 +LONG = 4 +RATIONAL = 5 +SIGNED_BYTE = 6 +UNDEFINED = 7 +SIGNED_SHORT = 8 +SIGNED_LONG = 9 +SIGNED_RATIONAL = 10 +FLOAT = 11 +DOUBLE = 12 +IFD = 13 +LONG8 = 16 + +_tags_v2: dict[int, tuple[str, int, int] | tuple[str, int, int, dict[str, int]]] = { + 254: ("NewSubfileType", LONG, 1), + 255: ("SubfileType", SHORT, 1), + 256: ("ImageWidth", LONG, 1), + 257: ("ImageLength", LONG, 1), + 258: ("BitsPerSample", SHORT, 0), + 259: ( + "Compression", + SHORT, + 1, + { + "Uncompressed": 1, + "CCITT 1d": 2, + "Group 3 Fax": 3, + "Group 4 Fax": 4, + "LZW": 5, + "JPEG": 6, + "PackBits": 32773, + }, + ), + 262: ( + "PhotometricInterpretation", + SHORT, + 1, + { + "WhiteIsZero": 0, + "BlackIsZero": 1, + "RGB": 2, + "RGB Palette": 3, + "Transparency Mask": 4, + "CMYK": 5, + "YCbCr": 6, + "CieLAB": 8, + "CFA": 32803, # TIFF/EP, Adobe DNG + "LinearRaw": 32892, # Adobe DNG + }, + ), + 263: ("Threshholding", SHORT, 1), + 264: ("CellWidth", SHORT, 1), + 265: ("CellLength", SHORT, 1), + 266: ("FillOrder", SHORT, 1), + 269: ("DocumentName", ASCII, 1), + 270: ("ImageDescription", ASCII, 1), + 271: ("Make", ASCII, 1), + 272: ("Model", ASCII, 1), + 273: ("StripOffsets", LONG, 0), + 274: ("Orientation", SHORT, 1), + 277: ("SamplesPerPixel", SHORT, 1), + 278: ("RowsPerStrip", LONG, 1), + 279: ("StripByteCounts", LONG, 0), + 280: ("MinSampleValue", SHORT, 0), + 281: ("MaxSampleValue", SHORT, 0), + 282: ("XResolution", RATIONAL, 1), + 283: ("YResolution", RATIONAL, 1), + 284: ("PlanarConfiguration", SHORT, 1, {"Contiguous": 1, "Separate": 2}), + 285: ("PageName", ASCII, 1), + 286: ("XPosition", RATIONAL, 1), + 287: ("YPosition", RATIONAL, 1), + 288: ("FreeOffsets", LONG, 1), + 289: ("FreeByteCounts", LONG, 1), + 290: ("GrayResponseUnit", SHORT, 1), + 291: ("GrayResponseCurve", SHORT, 0), + 292: ("T4Options", LONG, 1), + 293: ("T6Options", LONG, 1), + 296: ("ResolutionUnit", SHORT, 1, {"none": 1, "inch": 2, "cm": 3}), + 297: ("PageNumber", SHORT, 2), + 301: ("TransferFunction", SHORT, 0), + 305: ("Software", ASCII, 1), + 306: ("DateTime", ASCII, 1), + 315: ("Artist", ASCII, 1), + 316: ("HostComputer", ASCII, 1), + 317: ("Predictor", SHORT, 1, {"none": 1, "Horizontal Differencing": 2}), + 318: ("WhitePoint", RATIONAL, 2), + 319: ("PrimaryChromaticities", RATIONAL, 6), + 320: ("ColorMap", SHORT, 0), + 321: ("HalftoneHints", SHORT, 2), + 322: ("TileWidth", LONG, 1), + 323: ("TileLength", LONG, 1), + 324: ("TileOffsets", LONG, 0), + 325: ("TileByteCounts", LONG, 0), + 330: ("SubIFDs", LONG, 0), + 332: ("InkSet", SHORT, 1), + 333: ("InkNames", ASCII, 1), + 334: ("NumberOfInks", SHORT, 1), + 336: ("DotRange", SHORT, 0), + 337: ("TargetPrinter", ASCII, 1), + 338: ("ExtraSamples", SHORT, 0), + 339: ("SampleFormat", SHORT, 0), + 340: ("SMinSampleValue", DOUBLE, 0), + 341: ("SMaxSampleValue", DOUBLE, 0), + 342: ("TransferRange", SHORT, 6), + 347: ("JPEGTables", UNDEFINED, 1), + # obsolete JPEG tags + 512: ("JPEGProc", SHORT, 1), + 513: ("JPEGInterchangeFormat", LONG, 1), + 514: ("JPEGInterchangeFormatLength", LONG, 1), + 515: ("JPEGRestartInterval", SHORT, 1), + 517: ("JPEGLosslessPredictors", SHORT, 0), + 518: ("JPEGPointTransforms", SHORT, 0), + 519: ("JPEGQTables", LONG, 0), + 520: ("JPEGDCTables", LONG, 0), + 521: ("JPEGACTables", LONG, 0), + 529: ("YCbCrCoefficients", RATIONAL, 3), + 530: ("YCbCrSubSampling", SHORT, 2), + 531: ("YCbCrPositioning", SHORT, 1), + 532: ("ReferenceBlackWhite", RATIONAL, 6), + 700: ("XMP", BYTE, 0), + # Four private SGI tags + 32995: ("Matteing", SHORT, 1), + 32996: ("DataType", SHORT, 0), + 32997: ("ImageDepth", LONG, 1), + 32998: ("TileDepth", LONG, 1), + 33432: ("Copyright", ASCII, 1), + 33723: ("IptcNaaInfo", UNDEFINED, 1), + 34377: ("PhotoshopInfo", BYTE, 0), + # FIXME add more tags here + 34665: ("ExifIFD", LONG, 1), + 34675: ("ICCProfile", UNDEFINED, 1), + 34853: ("GPSInfoIFD", LONG, 1), + 36864: ("ExifVersion", UNDEFINED, 1), + 37724: ("ImageSourceData", UNDEFINED, 1), + 40965: ("InteroperabilityIFD", LONG, 1), + 41730: ("CFAPattern", UNDEFINED, 1), + # MPInfo + 45056: ("MPFVersion", UNDEFINED, 1), + 45057: ("NumberOfImages", LONG, 1), + 45058: ("MPEntry", UNDEFINED, 1), + 45059: ("ImageUIDList", UNDEFINED, 0), # UNDONE, check + 45060: ("TotalFrames", LONG, 1), + 45313: ("MPIndividualNum", LONG, 1), + 45569: ("PanOrientation", LONG, 1), + 45570: ("PanOverlap_H", RATIONAL, 1), + 45571: ("PanOverlap_V", RATIONAL, 1), + 45572: ("BaseViewpointNum", LONG, 1), + 45573: ("ConvergenceAngle", SIGNED_RATIONAL, 1), + 45574: ("BaselineLength", RATIONAL, 1), + 45575: ("VerticalDivergence", SIGNED_RATIONAL, 1), + 45576: ("AxisDistance_X", SIGNED_RATIONAL, 1), + 45577: ("AxisDistance_Y", SIGNED_RATIONAL, 1), + 45578: ("AxisDistance_Z", SIGNED_RATIONAL, 1), + 45579: ("YawAngle", SIGNED_RATIONAL, 1), + 45580: ("PitchAngle", SIGNED_RATIONAL, 1), + 45581: ("RollAngle", SIGNED_RATIONAL, 1), + 40960: ("FlashPixVersion", UNDEFINED, 1), + 50741: ("MakerNoteSafety", SHORT, 1, {"Unsafe": 0, "Safe": 1}), + 50780: ("BestQualityScale", RATIONAL, 1), + 50838: ("ImageJMetaDataByteCounts", LONG, 0), # Can be more than one + 50839: ("ImageJMetaData", UNDEFINED, 1), # see Issue #2006 +} +_tags_v2_groups = { + # ExifIFD + 34665: { + 36864: ("ExifVersion", UNDEFINED, 1), + 40960: ("FlashPixVersion", UNDEFINED, 1), + 40965: ("InteroperabilityIFD", LONG, 1), + 41730: ("CFAPattern", UNDEFINED, 1), + }, + # GPSInfoIFD + 34853: { + 0: ("GPSVersionID", BYTE, 4), + 1: ("GPSLatitudeRef", ASCII, 2), + 2: ("GPSLatitude", RATIONAL, 3), + 3: ("GPSLongitudeRef", ASCII, 2), + 4: ("GPSLongitude", RATIONAL, 3), + 5: ("GPSAltitudeRef", BYTE, 1), + 6: ("GPSAltitude", RATIONAL, 1), + 7: ("GPSTimeStamp", RATIONAL, 3), + 8: ("GPSSatellites", ASCII, 0), + 9: ("GPSStatus", ASCII, 2), + 10: ("GPSMeasureMode", ASCII, 2), + 11: ("GPSDOP", RATIONAL, 1), + 12: ("GPSSpeedRef", ASCII, 2), + 13: ("GPSSpeed", RATIONAL, 1), + 14: ("GPSTrackRef", ASCII, 2), + 15: ("GPSTrack", RATIONAL, 1), + 16: ("GPSImgDirectionRef", ASCII, 2), + 17: ("GPSImgDirection", RATIONAL, 1), + 18: ("GPSMapDatum", ASCII, 0), + 19: ("GPSDestLatitudeRef", ASCII, 2), + 20: ("GPSDestLatitude", RATIONAL, 3), + 21: ("GPSDestLongitudeRef", ASCII, 2), + 22: ("GPSDestLongitude", RATIONAL, 3), + 23: ("GPSDestBearingRef", ASCII, 2), + 24: ("GPSDestBearing", RATIONAL, 1), + 25: ("GPSDestDistanceRef", ASCII, 2), + 26: ("GPSDestDistance", RATIONAL, 1), + 27: ("GPSProcessingMethod", UNDEFINED, 0), + 28: ("GPSAreaInformation", UNDEFINED, 0), + 29: ("GPSDateStamp", ASCII, 11), + 30: ("GPSDifferential", SHORT, 1), + }, + # InteroperabilityIFD + 40965: {1: ("InteropIndex", ASCII, 1), 2: ("InteropVersion", UNDEFINED, 1)}, +} + +# Legacy Tags structure +# these tags aren't included above, but were in the previous versions +TAGS: dict[int | tuple[int, int], str] = { + 347: "JPEGTables", + 700: "XMP", + # Additional Exif Info + 32932: "Wang Annotation", + 33434: "ExposureTime", + 33437: "FNumber", + 33445: "MD FileTag", + 33446: "MD ScalePixel", + 33447: "MD ColorTable", + 33448: "MD LabName", + 33449: "MD SampleInfo", + 33450: "MD PrepDate", + 33451: "MD PrepTime", + 33452: "MD FileUnits", + 33550: "ModelPixelScaleTag", + 33723: "IptcNaaInfo", + 33918: "INGR Packet Data Tag", + 33919: "INGR Flag Registers", + 33920: "IrasB Transformation Matrix", + 33922: "ModelTiepointTag", + 34264: "ModelTransformationTag", + 34377: "PhotoshopInfo", + 34735: "GeoKeyDirectoryTag", + 34736: "GeoDoubleParamsTag", + 34737: "GeoAsciiParamsTag", + 34850: "ExposureProgram", + 34852: "SpectralSensitivity", + 34855: "ISOSpeedRatings", + 34856: "OECF", + 34864: "SensitivityType", + 34865: "StandardOutputSensitivity", + 34866: "RecommendedExposureIndex", + 34867: "ISOSpeed", + 34868: "ISOSpeedLatitudeyyy", + 34869: "ISOSpeedLatitudezzz", + 34908: "HylaFAX FaxRecvParams", + 34909: "HylaFAX FaxSubAddress", + 34910: "HylaFAX FaxRecvTime", + 36864: "ExifVersion", + 36867: "DateTimeOriginal", + 36868: "DateTimeDigitized", + 37121: "ComponentsConfiguration", + 37122: "CompressedBitsPerPixel", + 37724: "ImageSourceData", + 37377: "ShutterSpeedValue", + 37378: "ApertureValue", + 37379: "BrightnessValue", + 37380: "ExposureBiasValue", + 37381: "MaxApertureValue", + 37382: "SubjectDistance", + 37383: "MeteringMode", + 37384: "LightSource", + 37385: "Flash", + 37386: "FocalLength", + 37396: "SubjectArea", + 37500: "MakerNote", + 37510: "UserComment", + 37520: "SubSec", + 37521: "SubSecTimeOriginal", + 37522: "SubsecTimeDigitized", + 40960: "FlashPixVersion", + 40961: "ColorSpace", + 40962: "PixelXDimension", + 40963: "PixelYDimension", + 40964: "RelatedSoundFile", + 40965: "InteroperabilityIFD", + 41483: "FlashEnergy", + 41484: "SpatialFrequencyResponse", + 41486: "FocalPlaneXResolution", + 41487: "FocalPlaneYResolution", + 41488: "FocalPlaneResolutionUnit", + 41492: "SubjectLocation", + 41493: "ExposureIndex", + 41495: "SensingMethod", + 41728: "FileSource", + 41729: "SceneType", + 41730: "CFAPattern", + 41985: "CustomRendered", + 41986: "ExposureMode", + 41987: "WhiteBalance", + 41988: "DigitalZoomRatio", + 41989: "FocalLengthIn35mmFilm", + 41990: "SceneCaptureType", + 41991: "GainControl", + 41992: "Contrast", + 41993: "Saturation", + 41994: "Sharpness", + 41995: "DeviceSettingDescription", + 41996: "SubjectDistanceRange", + 42016: "ImageUniqueID", + 42032: "CameraOwnerName", + 42033: "BodySerialNumber", + 42034: "LensSpecification", + 42035: "LensMake", + 42036: "LensModel", + 42037: "LensSerialNumber", + 42112: "GDAL_METADATA", + 42113: "GDAL_NODATA", + 42240: "Gamma", + 50215: "Oce Scanjob Description", + 50216: "Oce Application Selector", + 50217: "Oce Identification Number", + 50218: "Oce ImageLogic Characteristics", + # Adobe DNG + 50706: "DNGVersion", + 50707: "DNGBackwardVersion", + 50708: "UniqueCameraModel", + 50709: "LocalizedCameraModel", + 50710: "CFAPlaneColor", + 50711: "CFALayout", + 50712: "LinearizationTable", + 50713: "BlackLevelRepeatDim", + 50714: "BlackLevel", + 50715: "BlackLevelDeltaH", + 50716: "BlackLevelDeltaV", + 50717: "WhiteLevel", + 50718: "DefaultScale", + 50719: "DefaultCropOrigin", + 50720: "DefaultCropSize", + 50721: "ColorMatrix1", + 50722: "ColorMatrix2", + 50723: "CameraCalibration1", + 50724: "CameraCalibration2", + 50725: "ReductionMatrix1", + 50726: "ReductionMatrix2", + 50727: "AnalogBalance", + 50728: "AsShotNeutral", + 50729: "AsShotWhiteXY", + 50730: "BaselineExposure", + 50731: "BaselineNoise", + 50732: "BaselineSharpness", + 50733: "BayerGreenSplit", + 50734: "LinearResponseLimit", + 50735: "CameraSerialNumber", + 50736: "LensInfo", + 50737: "ChromaBlurRadius", + 50738: "AntiAliasStrength", + 50740: "DNGPrivateData", + 50778: "CalibrationIlluminant1", + 50779: "CalibrationIlluminant2", + 50784: "Alias Layer Metadata", +} + +TAGS_V2: dict[int, TagInfo] = {} +TAGS_V2_GROUPS: dict[int, dict[int, TagInfo]] = {} + + +def _populate() -> None: + for k, v in _tags_v2.items(): + # Populate legacy structure. + TAGS[k] = v[0] + if len(v) == 4: + for sk, sv in v[3].items(): + TAGS[(k, sv)] = sk + + TAGS_V2[k] = TagInfo(k, *v) + + for group, tags in _tags_v2_groups.items(): + TAGS_V2_GROUPS[group] = {k: TagInfo(k, *v) for k, v in tags.items()} + + +_populate() +## +# Map type numbers to type names -- defined in ImageFileDirectory. + +TYPES: dict[int, str] = {} + +# +# These tags are handled by default in libtiff, without +# adding to the custom dictionary. From tif_dir.c, searching for +# case TIFFTAG in the _TIFFVSetField function: +# Line: item. +# 148: case TIFFTAG_SUBFILETYPE: +# 151: case TIFFTAG_IMAGEWIDTH: +# 154: case TIFFTAG_IMAGELENGTH: +# 157: case TIFFTAG_BITSPERSAMPLE: +# 181: case TIFFTAG_COMPRESSION: +# 202: case TIFFTAG_PHOTOMETRIC: +# 205: case TIFFTAG_THRESHHOLDING: +# 208: case TIFFTAG_FILLORDER: +# 214: case TIFFTAG_ORIENTATION: +# 221: case TIFFTAG_SAMPLESPERPIXEL: +# 228: case TIFFTAG_ROWSPERSTRIP: +# 238: case TIFFTAG_MINSAMPLEVALUE: +# 241: case TIFFTAG_MAXSAMPLEVALUE: +# 244: case TIFFTAG_SMINSAMPLEVALUE: +# 247: case TIFFTAG_SMAXSAMPLEVALUE: +# 250: case TIFFTAG_XRESOLUTION: +# 256: case TIFFTAG_YRESOLUTION: +# 262: case TIFFTAG_PLANARCONFIG: +# 268: case TIFFTAG_XPOSITION: +# 271: case TIFFTAG_YPOSITION: +# 274: case TIFFTAG_RESOLUTIONUNIT: +# 280: case TIFFTAG_PAGENUMBER: +# 284: case TIFFTAG_HALFTONEHINTS: +# 288: case TIFFTAG_COLORMAP: +# 294: case TIFFTAG_EXTRASAMPLES: +# 298: case TIFFTAG_MATTEING: +# 305: case TIFFTAG_TILEWIDTH: +# 316: case TIFFTAG_TILELENGTH: +# 327: case TIFFTAG_TILEDEPTH: +# 333: case TIFFTAG_DATATYPE: +# 344: case TIFFTAG_SAMPLEFORMAT: +# 361: case TIFFTAG_IMAGEDEPTH: +# 364: case TIFFTAG_SUBIFD: +# 376: case TIFFTAG_YCBCRPOSITIONING: +# 379: case TIFFTAG_YCBCRSUBSAMPLING: +# 383: case TIFFTAG_TRANSFERFUNCTION: +# 389: case TIFFTAG_REFERENCEBLACKWHITE: +# 393: case TIFFTAG_INKNAMES: + +# Following pseudo-tags are also handled by default in libtiff: +# TIFFTAG_JPEGQUALITY 65537 + +# some of these are not in our TAGS_V2 dict and were included from tiff.h + +# This list also exists in encode.c +LIBTIFF_CORE = { + 255, + 256, + 257, + 258, + 259, + 262, + 263, + 266, + 274, + 277, + 278, + 280, + 281, + 340, + 341, + 282, + 283, + 284, + 286, + 287, + 296, + 297, + 321, + 320, + 338, + 32995, + 322, + 323, + 32998, + 32996, + 339, + 32997, + 330, + 531, + 530, + 301, + 532, + 333, + # as above + 269, # this has been in our tests forever, and works + 65537, +} + +LIBTIFF_CORE.remove(255) # We don't have support for subfiletypes +LIBTIFF_CORE.remove(322) # We don't have support for writing tiled images with libtiff +LIBTIFF_CORE.remove(323) # Tiled images + +# Note to advanced users: There may be combinations of these +# parameters and values that when added properly, will work and +# produce valid tiff images that may work in your application. +# It is safe to add and remove tags from this set from Pillow's point +# of view so long as you test against libtiff. diff --git a/PIL/WalImageFile.py b/PIL/WalImageFile.py new file mode 100644 index 0000000000000000000000000000000000000000..fb3e1c06a323786e8aec7c90958811149e7cd348 --- /dev/null +++ b/PIL/WalImageFile.py @@ -0,0 +1,128 @@ +# +# The Python Imaging Library. +# $Id$ +# +# WAL file handling +# +# History: +# 2003-04-23 fl created +# +# Copyright (c) 2003 by Fredrik Lundh. +# +# See the README file for information on usage and redistribution. +# + +""" +This reader is based on the specification available from: +https://www.flipcode.com/archives/Quake_2_BSP_File_Format.shtml +and has been tested with a few sample files found using google. + +.. note:: + This format cannot be automatically recognized, so the reader + is not registered for use with :py:func:`PIL.Image.open()`. + To open a WAL file, use the :py:func:`PIL.WalImageFile.open()` function instead. +""" +from __future__ import annotations + +from typing import IO + +from . import Image, ImageFile +from ._binary import i32le as i32 +from ._typing import StrOrBytesPath + + +class WalImageFile(ImageFile.ImageFile): + format = "WAL" + format_description = "Quake2 Texture" + + def _open(self) -> None: + self._mode = "P" + + # read header fields + assert self.fp is not None + header = self.fp.read(32 + 24 + 32 + 12) + self._size = i32(header, 32), i32(header, 36) + Image._decompression_bomb_check(self.size) + + # load pixel data + offset = i32(header, 40) + self.fp.seek(offset) + + # strings are null-terminated + self.info["name"] = header[:32].split(b"\0", 1)[0] + if next_name := header[56 : 56 + 32].split(b"\0", 1)[0]: + self.info["next_name"] = next_name + + def load(self) -> Image.core.PixelAccess | None: + if self._im is None: + assert self.fp is not None + self.im = Image.core.new(self.mode, self.size) + self.frombytes(self.fp.read(self.size[0] * self.size[1])) + self.putpalette(quake2palette) + return Image.Image.load(self) + + +def open(filename: StrOrBytesPath | IO[bytes]) -> WalImageFile: + """ + Load texture from a Quake2 WAL texture file. + + By default, a Quake2 standard palette is attached to the texture. + To override the palette, use the :py:func:`PIL.Image.Image.putpalette()` method. + + :param filename: WAL file name, or an opened file handle. + :returns: An image instance. + """ + return WalImageFile(filename) + + +quake2palette = ( + # default palette taken from piffo 0.93 by Hans Häggström + b"\x01\x01\x01\x0b\x0b\x0b\x12\x12\x12\x17\x17\x17\x1b\x1b\x1b\x1e" + b"\x1e\x1e\x22\x22\x22\x26\x26\x26\x29\x29\x29\x2c\x2c\x2c\x2f\x2f" + b"\x2f\x32\x32\x32\x35\x35\x35\x37\x37\x37\x3a\x3a\x3a\x3c\x3c\x3c" + b"\x24\x1e\x13\x22\x1c\x12\x20\x1b\x12\x1f\x1a\x10\x1d\x19\x10\x1b" + b"\x17\x0f\x1a\x16\x0f\x18\x14\x0d\x17\x13\x0d\x16\x12\x0d\x14\x10" + b"\x0b\x13\x0f\x0b\x10\x0d\x0a\x0f\x0b\x0a\x0d\x0b\x07\x0b\x0a\x07" + b"\x23\x23\x26\x22\x22\x25\x22\x20\x23\x21\x1f\x22\x20\x1e\x20\x1f" + b"\x1d\x1e\x1d\x1b\x1c\x1b\x1a\x1a\x1a\x19\x19\x18\x17\x17\x17\x16" + b"\x16\x14\x14\x14\x13\x13\x13\x10\x10\x10\x0f\x0f\x0f\x0d\x0d\x0d" + b"\x2d\x28\x20\x29\x24\x1c\x27\x22\x1a\x25\x1f\x17\x38\x2e\x1e\x31" + b"\x29\x1a\x2c\x25\x17\x26\x20\x14\x3c\x30\x14\x37\x2c\x13\x33\x28" + b"\x12\x2d\x24\x10\x28\x1f\x0f\x22\x1a\x0b\x1b\x14\x0a\x13\x0f\x07" + b"\x31\x1a\x16\x30\x17\x13\x2e\x16\x10\x2c\x14\x0d\x2a\x12\x0b\x27" + b"\x0f\x0a\x25\x0f\x07\x21\x0d\x01\x1e\x0b\x01\x1c\x0b\x01\x1a\x0b" + b"\x01\x18\x0a\x01\x16\x0a\x01\x13\x0a\x01\x10\x07\x01\x0d\x07\x01" + b"\x29\x23\x1e\x27\x21\x1c\x26\x20\x1b\x25\x1f\x1a\x23\x1d\x19\x21" + b"\x1c\x18\x20\x1b\x17\x1e\x19\x16\x1c\x18\x14\x1b\x17\x13\x19\x14" + b"\x10\x17\x13\x0f\x14\x10\x0d\x12\x0f\x0b\x0f\x0b\x0a\x0b\x0a\x07" + b"\x26\x1a\x0f\x23\x19\x0f\x20\x17\x0f\x1c\x16\x0f\x19\x13\x0d\x14" + b"\x10\x0b\x10\x0d\x0a\x0b\x0a\x07\x33\x22\x1f\x35\x29\x26\x37\x2f" + b"\x2d\x39\x35\x34\x37\x39\x3a\x33\x37\x39\x30\x34\x36\x2b\x31\x34" + b"\x27\x2e\x31\x22\x2b\x2f\x1d\x28\x2c\x17\x25\x2a\x0f\x20\x26\x0d" + b"\x1e\x25\x0b\x1c\x22\x0a\x1b\x20\x07\x19\x1e\x07\x17\x1b\x07\x14" + b"\x18\x01\x12\x16\x01\x0f\x12\x01\x0b\x0d\x01\x07\x0a\x01\x01\x01" + b"\x2c\x21\x21\x2a\x1f\x1f\x29\x1d\x1d\x27\x1c\x1c\x26\x1a\x1a\x24" + b"\x18\x18\x22\x17\x17\x21\x16\x16\x1e\x13\x13\x1b\x12\x12\x18\x10" + b"\x10\x16\x0d\x0d\x12\x0b\x0b\x0d\x0a\x0a\x0a\x07\x07\x01\x01\x01" + b"\x2e\x30\x29\x2d\x2e\x27\x2b\x2c\x26\x2a\x2a\x24\x28\x29\x23\x27" + b"\x27\x21\x26\x26\x1f\x24\x24\x1d\x22\x22\x1c\x1f\x1f\x1a\x1c\x1c" + b"\x18\x19\x19\x16\x17\x17\x13\x13\x13\x10\x0f\x0f\x0d\x0b\x0b\x0a" + b"\x30\x1e\x1b\x2d\x1c\x19\x2c\x1a\x17\x2a\x19\x14\x28\x17\x13\x26" + b"\x16\x10\x24\x13\x0f\x21\x12\x0d\x1f\x10\x0b\x1c\x0f\x0a\x19\x0d" + b"\x0a\x16\x0b\x07\x12\x0a\x07\x0f\x07\x01\x0a\x01\x01\x01\x01\x01" + b"\x28\x29\x38\x26\x27\x36\x25\x26\x34\x24\x24\x31\x22\x22\x2f\x20" + b"\x21\x2d\x1e\x1f\x2a\x1d\x1d\x27\x1b\x1b\x25\x19\x19\x21\x17\x17" + b"\x1e\x14\x14\x1b\x13\x12\x17\x10\x0f\x13\x0d\x0b\x0f\x0a\x07\x07" + b"\x2f\x32\x29\x2d\x30\x26\x2b\x2e\x24\x29\x2c\x21\x27\x2a\x1e\x25" + b"\x28\x1c\x23\x26\x1a\x21\x25\x18\x1e\x22\x14\x1b\x1f\x10\x19\x1c" + b"\x0d\x17\x1a\x0a\x13\x17\x07\x10\x13\x01\x0d\x0f\x01\x0a\x0b\x01" + b"\x01\x3f\x01\x13\x3c\x0b\x1b\x39\x10\x20\x35\x14\x23\x31\x17\x23" + b"\x2d\x18\x23\x29\x18\x3f\x3f\x3f\x3f\x3f\x39\x3f\x3f\x31\x3f\x3f" + b"\x2a\x3f\x3f\x20\x3f\x3f\x14\x3f\x3c\x12\x3f\x39\x0f\x3f\x35\x0b" + b"\x3f\x32\x07\x3f\x2d\x01\x3d\x2a\x01\x3b\x26\x01\x39\x21\x01\x37" + b"\x1d\x01\x34\x1a\x01\x32\x16\x01\x2f\x12\x01\x2d\x0f\x01\x2a\x0b" + b"\x01\x27\x07\x01\x23\x01\x01\x1d\x01\x01\x17\x01\x01\x10\x01\x01" + b"\x3d\x01\x01\x19\x19\x3f\x3f\x01\x01\x01\x01\x3f\x16\x16\x13\x10" + b"\x10\x0f\x0d\x0d\x0b\x3c\x2e\x2a\x36\x27\x20\x30\x21\x18\x29\x1b" + b"\x10\x3c\x39\x37\x37\x32\x2f\x31\x2c\x28\x2b\x26\x21\x30\x22\x20" +) diff --git a/PIL/WebPImagePlugin.py b/PIL/WebPImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..e20e40d913fef4111412b8a1865fd0bc0117555a --- /dev/null +++ b/PIL/WebPImagePlugin.py @@ -0,0 +1,317 @@ +from __future__ import annotations + +from io import BytesIO + +from . import Image, ImageFile + +try: + from . import _webp + + SUPPORTED = True +except ImportError: + SUPPORTED = False + +TYPE_CHECKING = False +if TYPE_CHECKING: + from typing import IO, Any + +_VP8_MODES_BY_IDENTIFIER = { + b"VP8 ": "RGB", + b"VP8X": "RGBA", + b"VP8L": "RGBA", # lossless +} + + +def _accept(prefix: bytes) -> bool | str: + is_riff_file_format = prefix.startswith(b"RIFF") + is_webp_file = prefix[8:12] == b"WEBP" + is_valid_vp8_mode = prefix[12:16] in _VP8_MODES_BY_IDENTIFIER + + if is_riff_file_format and is_webp_file and is_valid_vp8_mode: + if not SUPPORTED: + return ( + "image file could not be identified because WEBP support not installed" + ) + return True + return False + + +class WebPImageFile(ImageFile.ImageFile): + format = "WEBP" + format_description = "WebP image" + __loaded = 0 + __logical_frame = 0 + + def _open(self) -> None: + # Use the newer AnimDecoder API to parse the (possibly) animated file, + # and access muxed chunks like ICC/EXIF/XMP. + assert self.fp is not None + self._decoder = _webp.WebPAnimDecoder(self.fp.read()) + + # Get info from decoder + self._size, self.info["loop"], bgcolor, self.n_frames, self.rawmode = ( + self._decoder.get_info() + ) + self.info["background"] = ( + (bgcolor >> 16) & 0xFF, # R + (bgcolor >> 8) & 0xFF, # G + bgcolor & 0xFF, # B + (bgcolor >> 24) & 0xFF, # A + ) + self.is_animated = self.n_frames > 1 + self._mode = "RGB" if self.rawmode == "RGBX" else self.rawmode + + # Attempt to read ICC / EXIF / XMP chunks from file + for key, chunk_name in { + "icc_profile": "ICCP", + "exif": "EXIF", + "xmp": "XMP ", + }.items(): + if value := self._decoder.get_chunk(chunk_name): + self.info[key] = value + + # Initialize seek state + self._reset(reset=False) + + def _getexif(self) -> dict[int, Any] | None: + if "exif" not in self.info: + return None + return self.getexif()._get_merged_dict() + + def seek(self, frame: int) -> None: + if not self._seek_check(frame): + return + + # Set logical frame to requested position + self.__logical_frame = frame + + def _reset(self, reset: bool = True) -> None: + if reset: + self._decoder.reset() + self.__physical_frame = 0 + self.__loaded = -1 + self.__timestamp = 0 + + def _get_next(self) -> tuple[bytes, int, int]: + # Get next frame + ret = self._decoder.get_next() + self.__physical_frame += 1 + + # Check if an error occurred + if ret is None: + self._reset() # Reset just to be safe + self.seek(0) + msg = "failed to decode next frame in WebP file" + raise EOFError(msg) + + # Compute duration + data, timestamp = ret + duration = timestamp - self.__timestamp + self.__timestamp = timestamp + + # libwebp gives frame end, adjust to start of frame + timestamp -= duration + return data, timestamp, duration + + def _seek(self, frame: int) -> None: + if self.__physical_frame == frame: + return # Nothing to do + if frame < self.__physical_frame: + self._reset() # Rewind to beginning + while self.__physical_frame < frame: + self._get_next() # Advance to the requested frame + + def load(self) -> Image.core.PixelAccess | None: + if self.__loaded != self.__logical_frame: + self._seek(self.__logical_frame) + + # We need to load the image data for this frame + data, self.info["timestamp"], self.info["duration"] = self._get_next() + self.__loaded = self.__logical_frame + + # Set tile + if self.fp and self._exclusive_fp: + self.fp.close() + self.fp = BytesIO(data) + self.tile = [ImageFile._Tile("raw", (0, 0) + self.size, 0, self.rawmode)] + + return super().load() + + def load_seek(self, pos: int) -> None: + pass + + def tell(self) -> int: + return self.__logical_frame + + +def _convert_frame(im: Image.Image) -> Image.Image: + # Make sure image mode is supported + if im.mode not in ("RGBX", "RGBA", "RGB"): + im = im.convert("RGBA" if im.has_transparency_data else "RGB") + return im + + +def _save_all(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + encoderinfo = im.encoderinfo.copy() + append_images = list(encoderinfo.get("append_images", [])) + + # If total frame count is 1, then save using the legacy API, which + # will preserve non-alpha modes + total = 0 + for ims in [im] + append_images: + total += getattr(ims, "n_frames", 1) + if total == 1: + _save(im, fp, filename) + return + + background: int | tuple[int, ...] = (0, 0, 0, 0) + if "background" in encoderinfo: + background = encoderinfo["background"] + elif "background" in im.info: + background = im.info["background"] + if isinstance(background, int): + # GifImagePlugin stores a global color table index in + # info["background"]. So it must be converted to an RGBA value + palette = im.getpalette() + if palette: + r, g, b = palette[background * 3 : (background + 1) * 3] + background = (r, g, b, 255) + else: + background = (background, background, background, 255) + + duration = im.encoderinfo.get("duration", im.info.get("duration", 0)) + loop = im.encoderinfo.get("loop", 0) + minimize_size = im.encoderinfo.get("minimize_size", False) + kmin = im.encoderinfo.get("kmin", None) + kmax = im.encoderinfo.get("kmax", None) + allow_mixed = im.encoderinfo.get("allow_mixed", False) + verbose = False + lossless = im.encoderinfo.get("lossless", False) + quality = im.encoderinfo.get("quality", 80) + alpha_quality = im.encoderinfo.get("alpha_quality", 100) + method = im.encoderinfo.get("method", 0) + icc_profile = im.encoderinfo.get("icc_profile") or "" + exif = im.encoderinfo.get("exif", "") + if isinstance(exif, Image.Exif): + exif = exif.tobytes() + xmp = im.encoderinfo.get("xmp", "") + if allow_mixed: + lossless = False + + # Sensible keyframe defaults are from gif2webp.c script + if kmin is None: + kmin = 9 if lossless else 3 + if kmax is None: + kmax = 17 if lossless else 5 + + # Validate background color + if ( + not isinstance(background, (list, tuple)) + or len(background) != 4 + or not all(0 <= v < 256 for v in background) + ): + msg = f"Background color is not an RGBA tuple clamped to (0-255): {background}" + raise OSError(msg) + + # Convert to packed uint + bg_r, bg_g, bg_b, bg_a = background + background = (bg_a << 24) | (bg_r << 16) | (bg_g << 8) | (bg_b << 0) + + # Setup the WebP animation encoder + enc = _webp.WebPAnimEncoder( + im.size, + background, + loop, + minimize_size, + kmin, + kmax, + allow_mixed, + verbose, + ) + + # Add each frame + frame_idx = 0 + timestamp = 0 + cur_idx = im.tell() + try: + for ims in [im] + append_images: + # Get number of frames in this image + nfr = getattr(ims, "n_frames", 1) + + for idx in range(nfr): + ims.seek(idx) + + frame = _convert_frame(ims) + + # Append the frame to the animation encoder + enc.add( + frame.getim(), + round(timestamp), + lossless, + quality, + alpha_quality, + method, + ) + + # Update timestamp and frame index + if isinstance(duration, (list, tuple)): + timestamp += duration[frame_idx] + else: + timestamp += duration + frame_idx += 1 + + finally: + im.seek(cur_idx) + + # Force encoder to flush frames + enc.add(None, round(timestamp), lossless, quality, alpha_quality, 0) + + # Get the final output from the encoder + data = enc.assemble(icc_profile, exif, xmp) + if data is None: + msg = "cannot write file as WebP (encoder returned None)" + raise OSError(msg) + + fp.write(data) + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + lossless = im.encoderinfo.get("lossless", False) + quality = im.encoderinfo.get("quality", 80) + alpha_quality = im.encoderinfo.get("alpha_quality", 100) + icc_profile = im.encoderinfo.get("icc_profile") or "" + exif = im.encoderinfo.get("exif", b"") + if isinstance(exif, Image.Exif): + exif = exif.tobytes() + if exif.startswith(b"Exif\x00\x00"): + exif = exif[6:] + xmp = im.encoderinfo.get("xmp", "") + method = im.encoderinfo.get("method", 4) + exact = 1 if im.encoderinfo.get("exact") else 0 + + im = _convert_frame(im) + + data = _webp.WebPEncode( + im.getim(), + lossless, + float(quality), + float(alpha_quality), + icc_profile, + method, + exact, + exif, + xmp, + ) + if data is None: + msg = "cannot write file as WebP (encoder returned None)" + raise OSError(msg) + + fp.write(data) + + +Image.register_open(WebPImageFile.format, WebPImageFile, _accept) +if SUPPORTED: + Image.register_save(WebPImageFile.format, _save) + Image.register_save_all(WebPImageFile.format, _save_all) + Image.register_extension(WebPImageFile.format, ".webp") + Image.register_mime(WebPImageFile.format, "image/webp") diff --git a/PIL/WmfImagePlugin.py b/PIL/WmfImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..3ae86242a8b4df4b52f31dc5def58cc6411ec6d8 --- /dev/null +++ b/PIL/WmfImagePlugin.py @@ -0,0 +1,188 @@ +# +# The Python Imaging Library +# $Id$ +# +# WMF stub codec +# +# history: +# 1996-12-14 fl Created +# 2004-02-22 fl Turned into a stub driver +# 2004-02-23 fl Added EMF support +# +# Copyright (c) Secret Labs AB 1997-2004. All rights reserved. +# Copyright (c) Fredrik Lundh 1996. +# +# See the README file for information on usage and redistribution. +# +# WMF/EMF reference documentation: +# https://winprotocoldoc.blob.core.windows.net/productionwindowsarchives/MS-WMF/[MS-WMF].pdf +# http://wvware.sourceforge.net/caolan/index.html +# http://wvware.sourceforge.net/caolan/ora-wmf.html +from __future__ import annotations + +from typing import IO + +from . import Image, ImageFile +from ._binary import i16le as word +from ._binary import si16le as short +from ._binary import si32le as _long + +_handler = None + + +def register_handler(handler: ImageFile.StubHandler | None) -> None: + """ + Install application-specific WMF image handler. + + :param handler: Handler object. + """ + global _handler + _handler = handler + + +if hasattr(Image.core, "drawwmf"): + # install default handler (windows only) + + class WmfHandler(ImageFile.StubHandler): + def open(self, im: ImageFile.StubImageFile) -> None: + im._mode = "RGB" + self.bbox = im.info["wmf_bbox"] + + def load(self, im: ImageFile.StubImageFile) -> Image.Image: + assert im.fp is not None + im.fp.seek(0) # rewind + return Image.frombytes( + "RGB", + im.size, + Image.core.drawwmf(im.fp.read(), im.size, self.bbox), + "raw", + "BGR", + (im.size[0] * 3 + 3) & -4, + -1, + ) + + register_handler(WmfHandler()) + +# +# -------------------------------------------------------------------- +# Read WMF file + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith((b"\xd7\xcd\xc6\x9a\x00\x00", b"\x01\x00\x00\x00")) + + +## +# Image plugin for Windows metafiles. + + +class WmfStubImageFile(ImageFile.StubImageFile): + format = "WMF" + format_description = "Windows Metafile" + + def _open(self) -> None: + # check placeable header + assert self.fp is not None + s = self.fp.read(44) + + if s.startswith(b"\xd7\xcd\xc6\x9a\x00\x00"): + # placeable windows metafile + + # get units per inch + inch = word(s, 14) + if inch == 0: + msg = "Invalid inch" + raise ValueError(msg) + self._inch: tuple[float, float] = inch, inch + + # get bounding box + x0 = short(s, 6) + y0 = short(s, 8) + x1 = short(s, 10) + y1 = short(s, 12) + + # normalize size to 72 dots per inch + self.info["dpi"] = 72 + size = ( + (x1 - x0) * self.info["dpi"] // inch, + (y1 - y0) * self.info["dpi"] // inch, + ) + + self.info["wmf_bbox"] = x0, y0, x1, y1 + + # sanity check (standard metafile header) + if s[22:26] != b"\x01\x00\t\x00": + msg = "Unsupported WMF file format" + raise SyntaxError(msg) + + elif s.startswith(b"\x01\x00\x00\x00") and s[40:44] == b" EMF": + # enhanced metafile + + # get bounding box + x0 = _long(s, 8) + y0 = _long(s, 12) + x1 = _long(s, 16) + y1 = _long(s, 20) + + # get frame (in 0.01 millimeter units) + frame = _long(s, 24), _long(s, 28), _long(s, 32), _long(s, 36) + + size = x1 - x0, y1 - y0 + + # calculate dots per inch from bbox and frame + xdpi = 2540.0 * (x1 - x0) / (frame[2] - frame[0]) + ydpi = 2540.0 * (y1 - y0) / (frame[3] - frame[1]) + + self.info["wmf_bbox"] = x0, y0, x1, y1 + + if xdpi == ydpi: + self.info["dpi"] = xdpi + else: + self.info["dpi"] = xdpi, ydpi + self._inch = xdpi, ydpi + + else: + msg = "Unsupported file format" + raise SyntaxError(msg) + + self._mode = "RGB" + self._size = size + + loader = self._load() + if loader: + loader.open(self) + + def _load(self) -> ImageFile.StubHandler | None: + return _handler + + def load( + self, dpi: float | tuple[float, float] | None = None + ) -> Image.core.PixelAccess | None: + if dpi is not None: + self.info["dpi"] = dpi + x0, y0, x1, y1 = self.info["wmf_bbox"] + if not isinstance(dpi, tuple): + dpi = dpi, dpi + self._size = ( + int((x1 - x0) * dpi[0] / self._inch[0]), + int((y1 - y0) * dpi[1] / self._inch[1]), + ) + return super().load() + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + if _handler is None or not hasattr(_handler, "save"): + msg = "WMF save handler not installed" + raise OSError(msg) + _handler.save(im, fp, filename) + + +# +# -------------------------------------------------------------------- +# Registry stuff + + +Image.register_open(WmfStubImageFile.format, WmfStubImageFile, _accept) +Image.register_save(WmfStubImageFile.format, _save) + +Image.register_extensions(WmfStubImageFile.format, [".wmf", ".emf"]) diff --git a/PIL/XVThumbImagePlugin.py b/PIL/XVThumbImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..192c041d94edd900be6520be120df67d88eb7863 --- /dev/null +++ b/PIL/XVThumbImagePlugin.py @@ -0,0 +1,83 @@ +# +# The Python Imaging Library. +# $Id$ +# +# XV Thumbnail file handler by Charles E. "Gene" Cash +# (gcash@magicnet.net) +# +# see xvcolor.c and xvbrowse.c in the sources to John Bradley's XV, +# available from ftp://ftp.cis.upenn.edu/pub/xv/ +# +# history: +# 98-08-15 cec created (b/w only) +# 98-12-09 cec added color palette +# 98-12-28 fl added to PIL (with only a few very minor modifications) +# +# To do: +# FIXME: make save work (this requires quantization support) +# +from __future__ import annotations + +from . import Image, ImageFile, ImagePalette +from ._binary import o8 + +_MAGIC = b"P7 332" + +# standard color palette for thumbnails (RGB332) +PALETTE = b"" +for r in range(8): + for g in range(8): + for b in range(4): + PALETTE = PALETTE + ( + o8((r * 255) // 7) + o8((g * 255) // 7) + o8((b * 255) // 3) + ) + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith(_MAGIC) + + +## +# Image plugin for XV thumbnail images. + + +class XVThumbImageFile(ImageFile.ImageFile): + format = "XVThumb" + format_description = "XV thumbnail image" + + def _open(self) -> None: + # check magic + assert self.fp is not None + + if not _accept(self.fp.read(6)): + msg = "not an XV thumbnail file" + raise SyntaxError(msg) + + # Skip to beginning of next line + self.fp.readline() + + # skip info comments + while True: + s = self.fp.readline() + if not s: + msg = "Unexpected EOF reading XV thumbnail file" + raise SyntaxError(msg) + if s[0] != 35: # ie. when not a comment: '#' + break + + # parse header line (already read) + w, h = s.strip().split(maxsplit=2)[:2] + + self._mode = "P" + self._size = int(w), int(h) + + self.palette = ImagePalette.raw("RGB", PALETTE) + + self.tile = [ + ImageFile._Tile("raw", (0, 0) + self.size, self.fp.tell(), self.mode) + ] + + +# -------------------------------------------------------------------- + +Image.register_open(XVThumbImageFile.format, XVThumbImageFile, _accept) diff --git a/PIL/XbmImagePlugin.py b/PIL/XbmImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..1e57aa162ea4f8618dac66cf042352f73d2199c8 --- /dev/null +++ b/PIL/XbmImagePlugin.py @@ -0,0 +1,98 @@ +# +# The Python Imaging Library. +# $Id$ +# +# XBM File handling +# +# History: +# 1995-09-08 fl Created +# 1996-11-01 fl Added save support +# 1997-07-07 fl Made header parser more tolerant +# 1997-07-22 fl Fixed yet another parser bug +# 2001-02-17 fl Use 're' instead of 'regex' (Python 2.1) (0.4) +# 2001-05-13 fl Added hotspot handling (based on code from Bernhard Herzog) +# 2004-02-24 fl Allow some whitespace before first #define +# +# Copyright (c) 1997-2004 by Secret Labs AB +# Copyright (c) 1996-1997 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import re +from typing import IO + +from . import Image, ImageFile + +# XBM header +xbm_head = re.compile( + rb"\s*#define[ \t]+.*_width[ \t]+(?P[0-9]+)[\r\n]+" + b"#define[ \t]+.*_height[ \t]+(?P[0-9]+)[\r\n]+" + b"(?P" + b"#define[ \t]+[^_]*_x_hot[ \t]+(?P[0-9]+)[\r\n]+" + b"#define[ \t]+[^_]*_y_hot[ \t]+(?P[0-9]+)[\r\n]+" + b")?" + rb"[\000-\377]*_bits\[]" +) + + +def _accept(prefix: bytes) -> bool: + return prefix.lstrip().startswith(b"#define") + + +## +# Image plugin for X11 bitmaps. + + +class XbmImageFile(ImageFile.ImageFile): + format = "XBM" + format_description = "X11 Bitmap" + + def _open(self) -> None: + assert self.fp is not None + + m = xbm_head.match(self.fp.read(512)) + + if not m: + msg = "not a XBM file" + raise SyntaxError(msg) + + xsize = int(m.group("width")) + ysize = int(m.group("height")) + + if m.group("hotspot"): + self.info["hotspot"] = (int(m.group("xhot")), int(m.group("yhot"))) + + self._mode = "1" + self._size = xsize, ysize + + self.tile = [ImageFile._Tile("xbm", (0, 0) + self.size, m.end())] + + +def _save(im: Image.Image, fp: IO[bytes], filename: str | bytes) -> None: + if im.mode != "1": + msg = f"cannot write mode {im.mode} as XBM" + raise OSError(msg) + + fp.write(f"#define im_width {im.size[0]}\n".encode("ascii")) + fp.write(f"#define im_height {im.size[1]}\n".encode("ascii")) + + hotspot = im.encoderinfo.get("hotspot") + if hotspot: + fp.write(f"#define im_x_hot {hotspot[0]}\n".encode("ascii")) + fp.write(f"#define im_y_hot {hotspot[1]}\n".encode("ascii")) + + fp.write(b"static char im_bits[] = {\n") + + ImageFile._save(im, fp, [ImageFile._Tile("xbm", (0, 0) + im.size)]) + + fp.write(b"};\n") + + +Image.register_open(XbmImageFile.format, XbmImageFile, _accept) +Image.register_save(XbmImageFile.format, _save) + +Image.register_extension(XbmImageFile.format, ".xbm") + +Image.register_mime(XbmImageFile.format, "image/xbm") diff --git a/PIL/XpmImagePlugin.py b/PIL/XpmImagePlugin.py new file mode 100644 index 0000000000000000000000000000000000000000..3be240fbc1aeb7660de46fbd4f99f309ce9915dd --- /dev/null +++ b/PIL/XpmImagePlugin.py @@ -0,0 +1,157 @@ +# +# The Python Imaging Library. +# $Id$ +# +# XPM File handling +# +# History: +# 1996-12-29 fl Created +# 2001-02-17 fl Use 're' instead of 'regex' (Python 2.1) (0.7) +# +# Copyright (c) Secret Labs AB 1997-2001. +# Copyright (c) Fredrik Lundh 1996-2001. +# +# See the README file for information on usage and redistribution. +# +from __future__ import annotations + +import re + +from . import Image, ImageFile, ImagePalette +from ._binary import o8 + +# XPM header +xpm_head = re.compile(b'"([0-9]*) ([0-9]*) ([0-9]*) ([0-9]*)') + + +def _accept(prefix: bytes) -> bool: + return prefix.startswith(b"/* XPM */") + + +## +# Image plugin for X11 pixel maps. + + +class XpmImageFile(ImageFile.ImageFile): + format = "XPM" + format_description = "X11 Pixel Map" + + def _open(self) -> None: + assert self.fp is not None + if not _accept(self.fp.read(9)): + msg = "not an XPM file" + raise SyntaxError(msg) + + # skip forward to next string + while True: + line = self.fp.readline() + if not line: + msg = "broken XPM file" + raise SyntaxError(msg) + m = xpm_head.match(line) + if m: + break + + self._size = int(m.group(1)), int(m.group(2)) + + palette_length = int(m.group(3)) + bpp = int(m.group(4)) + + # + # load palette description + + palette = {} + + for _ in range(palette_length): + line = self.fp.readline().rstrip() + + c = line[1 : bpp + 1] + s = line[bpp + 1 : -2].split() + + for i in range(0, len(s), 2): + if s[i] == b"c": + # process colour key + rgb = s[i + 1] + if rgb == b"None": + self.info["transparency"] = c + elif rgb.startswith(b"#"): + rgb_int = int(rgb[1:], 16) + palette[c] = ( + o8((rgb_int >> 16) & 255) + + o8((rgb_int >> 8) & 255) + + o8(rgb_int & 255) + ) + else: + # unknown colour + msg = "cannot read this XPM file" + raise ValueError(msg) + break + + else: + # missing colour key + msg = "cannot read this XPM file" + raise ValueError(msg) + + args: tuple[int, dict[bytes, bytes] | tuple[bytes, ...]] + if palette_length > 256: + self._mode = "RGB" + args = (bpp, palette) + else: + self._mode = "P" + self.palette = ImagePalette.raw("RGB", b"".join(palette.values())) + args = (bpp, tuple(palette.keys())) + + self.tile = [ImageFile._Tile("xpm", (0, 0) + self.size, self.fp.tell(), args)] + + def load_read(self, read_bytes: int) -> bytes: + # + # load all image data in one chunk + + xsize, ysize = self.size + + assert self.fp is not None + s = [self.fp.readline()[1 : xsize + 1].ljust(xsize) for i in range(ysize)] + + return b"".join(s) + + +class XpmDecoder(ImageFile.PyDecoder): + _pulls_fd = True + + def decode(self, buffer: bytes | Image.SupportsArrayInterface) -> tuple[int, int]: + assert self.fd is not None + + data = bytearray() + bpp, palette = self.args + dest_length = self.state.xsize * self.state.ysize + if self.mode == "RGB": + dest_length *= 3 + pixel_header = False + while len(data) < dest_length: + line = self.fd.readline() + if not line: + break + if line.rstrip() == b"/* pixels */" and not pixel_header: + pixel_header = True + continue + line = b'"'.join(line.split(b'"')[1:-1]) + for i in range(0, len(line), bpp): + key = line[i : i + bpp] + if self.mode == "RGB": + data += palette[key] + else: + data += o8(palette.index(key)) + self.set_as_raw(bytes(data)) + return -1, 0 + + +# +# Registry + + +Image.register_open(XpmImageFile.format, XpmImageFile, _accept) +Image.register_decoder("xpm", XpmDecoder) + +Image.register_extension(XpmImageFile.format, ".xpm") + +Image.register_mime(XpmImageFile.format, "image/xpm") diff --git a/PIL/__init__.py b/PIL/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..6e4c23f897f83ef72fc10070bd22e9dc70614cf9 --- /dev/null +++ b/PIL/__init__.py @@ -0,0 +1,87 @@ +"""Pillow (Fork of the Python Imaging Library) + +Pillow is the friendly PIL fork by Jeffrey A. Clark and contributors. + https://github.com/python-pillow/Pillow/ + +Pillow is forked from PIL 1.1.7. + +PIL is the Python Imaging Library by Fredrik Lundh and contributors. +Copyright (c) 1999 by Secret Labs AB. + +Use PIL.__version__ for this Pillow version. + +;-) +""" + +from __future__ import annotations + +from . import _version + +# VERSION was removed in Pillow 6.0.0. +# PILLOW_VERSION was removed in Pillow 9.0.0. +# Use __version__ instead. +__version__ = _version.__version__ +del _version + + +_plugins = [ + "AvifImagePlugin", + "BlpImagePlugin", + "BmpImagePlugin", + "BufrStubImagePlugin", + "CurImagePlugin", + "DcxImagePlugin", + "DdsImagePlugin", + "EpsImagePlugin", + "FitsImagePlugin", + "FliImagePlugin", + "FpxImagePlugin", + "FtexImagePlugin", + "GbrImagePlugin", + "GifImagePlugin", + "GribStubImagePlugin", + "Hdf5StubImagePlugin", + "IcnsImagePlugin", + "IcoImagePlugin", + "ImImagePlugin", + "ImtImagePlugin", + "IptcImagePlugin", + "JpegImagePlugin", + "Jpeg2KImagePlugin", + "McIdasImagePlugin", + "MicImagePlugin", + "MpegImagePlugin", + "MpoImagePlugin", + "MspImagePlugin", + "PalmImagePlugin", + "PcdImagePlugin", + "PcxImagePlugin", + "PdfImagePlugin", + "PixarImagePlugin", + "PngImagePlugin", + "PpmImagePlugin", + "PsdImagePlugin", + "QoiImagePlugin", + "SgiImagePlugin", + "SpiderImagePlugin", + "SunImagePlugin", + "TgaImagePlugin", + "TiffImagePlugin", + "WebPImagePlugin", + "WmfImagePlugin", + "XbmImagePlugin", + "XpmImagePlugin", + "XVThumbImagePlugin", +] + + +class UnidentifiedImageError(OSError): + """ + Raised in :py:meth:`PIL.Image.open` if an image cannot be opened and identified. + + If a PNG image raises this error, setting :data:`.ImageFile.LOAD_TRUNCATED_IMAGES` + to true may allow the image to be opened after all. The setting will ignore missing + data and checksum failures. + """ + + pass diff --git a/PIL/__main__.py b/PIL/__main__.py new file mode 100644 index 0000000000000000000000000000000000000000..043156e892dadc4fb1222b33f5eda33251cd15aa --- /dev/null +++ b/PIL/__main__.py @@ -0,0 +1,7 @@ +from __future__ import annotations + +import sys + +from .features import pilinfo + +pilinfo(supported_formats="--report" not in sys.argv) diff --git a/PIL/_avif.cpython-312-x86_64-linux-gnu.so b/PIL/_avif.cpython-312-x86_64-linux-gnu.so new file mode 100644 index 0000000000000000000000000000000000000000..c83a451ad82942efb4e779a23f164ad58d15ccff Binary files /dev/null and b/PIL/_avif.cpython-312-x86_64-linux-gnu.so differ diff --git a/PIL/_avif.pyi b/PIL/_avif.pyi new file mode 100644 index 0000000000000000000000000000000000000000..e27843e5338213713e26973127c738c14313ff98 --- /dev/null +++ b/PIL/_avif.pyi @@ -0,0 +1,3 @@ +from typing import Any + +def __getattr__(name: str) -> Any: ... diff --git a/PIL/_binary.py b/PIL/_binary.py new file mode 100644 index 0000000000000000000000000000000000000000..4594ccce361168cf77e630cb88ffb09bb4362831 --- /dev/null +++ b/PIL/_binary.py @@ -0,0 +1,112 @@ +# +# The Python Imaging Library. +# $Id$ +# +# Binary input/output support routines. +# +# Copyright (c) 1997-2003 by Secret Labs AB +# Copyright (c) 1995-2003 by Fredrik Lundh +# Copyright (c) 2012 by Brian Crowell +# +# See the README file for information on usage and redistribution. +# + + +"""Binary input/output support routines.""" +from __future__ import annotations + +from struct import pack, unpack_from + + +def i8(c: bytes) -> int: + return c[0] + + +def o8(i: int) -> bytes: + return bytes((i & 255,)) + + +# Input, le = little endian, be = big endian +def i16le(c: bytes, o: int = 0) -> int: + """ + Converts a 2-bytes (16 bits) string to an unsigned integer. + + :param c: string containing bytes to convert + :param o: offset of bytes to convert in string + """ + return unpack_from(" int: + """ + Converts a 2-bytes (16 bits) string to a signed integer. + + :param c: string containing bytes to convert + :param o: offset of bytes to convert in string + """ + return unpack_from(" int: + """ + Converts a 2-bytes (16 bits) string to a signed integer, big endian. + + :param c: string containing bytes to convert + :param o: offset of bytes to convert in string + """ + return unpack_from(">h", c, o)[0] + + +def i32le(c: bytes, o: int = 0) -> int: + """ + Converts a 4-bytes (32 bits) string to an unsigned integer. + + :param c: string containing bytes to convert + :param o: offset of bytes to convert in string + """ + return unpack_from(" int: + """ + Converts a 4-bytes (32 bits) string to a signed integer. + + :param c: string containing bytes to convert + :param o: offset of bytes to convert in string + """ + return unpack_from(" int: + """ + Converts a 4-bytes (32 bits) string to a signed integer, big endian. + + :param c: string containing bytes to convert + :param o: offset of bytes to convert in string + """ + return unpack_from(">i", c, o)[0] + + +def i16be(c: bytes, o: int = 0) -> int: + return unpack_from(">H", c, o)[0] + + +def i32be(c: bytes, o: int = 0) -> int: + return unpack_from(">I", c, o)[0] + + +# Output, le = little endian, be = big endian +def o16le(i: int) -> bytes: + return pack(" bytes: + return pack(" bytes: + return pack(">H", i) + + +def o32be(i: int) -> bytes: + return pack(">I", i) diff --git a/PIL/_imaging.pyi b/PIL/_imaging.pyi new file mode 100644 index 0000000000000000000000000000000000000000..81028a5960ae34ec74285c456d9b691dc6a67a93 --- /dev/null +++ b/PIL/_imaging.pyi @@ -0,0 +1,31 @@ +from typing import Any + +class ImagingCore: + def __getitem__(self, index: int) -> float | tuple[int, ...] | None: ... + def __getattr__(self, name: str) -> Any: ... + +class ImagingFont: + def __getattr__(self, name: str) -> Any: ... + +class ImagingDraw: + def __getattr__(self, name: str) -> Any: ... + +class PixelAccess: + def __getitem__(self, xy: tuple[int, int]) -> float | tuple[int, ...]: ... + def __setitem__( + self, xy: tuple[int, int], color: float | tuple[int, ...] + ) -> None: ... + +class ImagingDecoder: + def __getattr__(self, name: str) -> Any: ... + +class ImagingEncoder: + def __getattr__(self, name: str) -> Any: ... + +class _Outline: + def close(self) -> None: ... + def __getattr__(self, name: str) -> Any: ... + +def font(image: ImagingCore, glyphdata: bytes) -> ImagingFont: ... +def outline() -> _Outline: ... +def __getattr__(name: str) -> Any: ... diff --git a/PIL/_imagingft.pyi b/PIL/_imagingft.pyi new file mode 100644 index 0000000000000000000000000000000000000000..2136810ba6a95e0c025a71cf7fbbc5b60490fed7 --- /dev/null +++ b/PIL/_imagingft.pyi @@ -0,0 +1,70 @@ +from collections.abc import Callable +from typing import Any + +from . import ImageFont, _imaging + +class Font: + @property + def family(self) -> str | None: ... + @property + def style(self) -> str | None: ... + @property + def ascent(self) -> int: ... + @property + def descent(self) -> int: ... + @property + def height(self) -> int: ... + @property + def x_ppem(self) -> int: ... + @property + def y_ppem(self) -> int: ... + @property + def glyphs(self) -> int: ... + def render( + self, + string: str | bytes, + fill: Callable[[int, int], _imaging.ImagingCore], + mode: str, + dir: str | None, + features: list[str] | None, + lang: str | None, + stroke_width: float, + stroke_filled: bool, + anchor: str | None, + foreground_ink_long: int, + start: tuple[float, float], + /, + ) -> tuple[_imaging.ImagingCore, tuple[int, int]]: ... + def getsize( + self, + string: str | bytes | bytearray, + mode: str, + dir: str | None, + features: list[str] | None, + lang: str | None, + anchor: str | None, + /, + ) -> tuple[tuple[int, int], tuple[int, int]]: ... + def getlength( + self, + string: str | bytes, + mode: str, + dir: str | None, + features: list[str] | None, + lang: str | None, + /, + ) -> float: ... + def getvarnames(self) -> list[bytes]: ... + def getvaraxes(self) -> list[ImageFont.Axis]: ... + def setvarname(self, instance_index: int, /) -> None: ... + def setvaraxes(self, axes: list[float], /) -> None: ... + +def getfont( + filename: str | bytes, + size: float, + index: int, + encoding: str, + font_bytes: bytes, + layout_engine: int, +) -> Font: ... +def __getattr__(name: str) -> Any: ... diff --git a/PIL/_imagingmath.pyi b/PIL/_imagingmath.pyi new file mode 100644 index 0000000000000000000000000000000000000000..e27843e5338213713e26973127c738c14313ff98 --- /dev/null +++ b/PIL/_imagingmath.pyi @@ -0,0 +1,3 @@ +from typing import Any + +def __getattr__(name: str) -> Any: ... diff --git a/PIL/_imagingmorph.cpython-312-x86_64-linux-gnu.so b/PIL/_imagingmorph.cpython-312-x86_64-linux-gnu.so new file mode 100644 index 0000000000000000000000000000000000000000..f08e5adce87e423e88889270833997c99346c74d Binary files /dev/null and b/PIL/_imagingmorph.cpython-312-x86_64-linux-gnu.so differ diff --git a/PIL/_imagingmorph.pyi b/PIL/_imagingmorph.pyi new file mode 100644 index 0000000000000000000000000000000000000000..e27843e5338213713e26973127c738c14313ff98 --- /dev/null +++ b/PIL/_imagingmorph.pyi @@ -0,0 +1,3 @@ +from typing import Any + +def __getattr__(name: str) -> Any: ... diff --git a/PIL/_imagingtk.cpython-312-x86_64-linux-gnu.so b/PIL/_imagingtk.cpython-312-x86_64-linux-gnu.so new file mode 100644 index 0000000000000000000000000000000000000000..1e92289e2edbb79f9a091fefe85ca6b1ffdabab0 Binary files /dev/null and b/PIL/_imagingtk.cpython-312-x86_64-linux-gnu.so differ diff --git a/PIL/_imagingtk.pyi b/PIL/_imagingtk.pyi new file mode 100644 index 0000000000000000000000000000000000000000..e27843e5338213713e26973127c738c14313ff98 --- /dev/null +++ b/PIL/_imagingtk.pyi @@ -0,0 +1,3 @@ +from typing import Any + +def __getattr__(name: str) -> Any: ... diff --git a/PIL/_tkinter_finder.py b/PIL/_tkinter_finder.py new file mode 100644 index 0000000000000000000000000000000000000000..9c0143003a7320dd475cfcd168168b82e4f64964 --- /dev/null +++ b/PIL/_tkinter_finder.py @@ -0,0 +1,20 @@ +"""Find compiled module linking to Tcl / Tk libraries""" + +from __future__ import annotations + +import sys +import tkinter + +tk = getattr(tkinter, "_tkinter") + +try: + if hasattr(sys, "pypy_find_executable"): + TKINTER_LIB = tk.tklib_cffi.__file__ + else: + TKINTER_LIB = tk.__file__ +except AttributeError: + # _tkinter may be compiled directly into Python, in which case __file__ is + # not available. load_tkinter_funcs will check the binary first in any case. + TKINTER_LIB = None + +tk_version = str(tkinter.TkVersion) diff --git a/PIL/_typing.py b/PIL/_typing.py new file mode 100644 index 0000000000000000000000000000000000000000..a941f89806faabe61486fc164d8bd3f60fb48626 --- /dev/null +++ b/PIL/_typing.py @@ -0,0 +1,45 @@ +from __future__ import annotations + +import os +import sys +from collections.abc import Sequence +from typing import Any, Protocol, TypeVar + +TYPE_CHECKING = False +if TYPE_CHECKING: + from numbers import _IntegralLike as IntegralLike + + try: + import numpy.typing as npt + + NumpyArray = npt.NDArray[Any] + except ImportError: + pass + +if sys.version_info >= (3, 13): + from types import CapsuleType +else: + CapsuleType = object + +if sys.version_info >= (3, 12): + from collections.abc import Buffer +else: + Buffer = Any + + +_Ink = float | tuple[int, ...] | str + +Coords = Sequence[float] | Sequence[Sequence[float]] + + +_T_co = TypeVar("_T_co", covariant=True) + + +class SupportsRead(Protocol[_T_co]): + def read(self, length: int = ..., /) -> _T_co: ... + + +StrOrBytesPath = str | bytes | os.PathLike[str] | os.PathLike[bytes] + + +__all__ = ["Buffer", "IntegralLike", "StrOrBytesPath", "SupportsRead"] diff --git a/PIL/_util.py b/PIL/_util.py new file mode 100644 index 0000000000000000000000000000000000000000..b1fa6a0f39ed2847723f20fc81462adc9245d970 --- /dev/null +++ b/PIL/_util.py @@ -0,0 +1,29 @@ +from __future__ import annotations + +import os + +TYPE_CHECKING = False +if TYPE_CHECKING: + from typing import Any, NoReturn, TypeGuard + + from ._typing import StrOrBytesPath + + +def is_path(f: Any) -> TypeGuard[StrOrBytesPath]: + return isinstance(f, (bytes, str, os.PathLike)) + + +class DeferredError: + def __init__(self, ex: BaseException): + self.ex = ex + + def __getattr__(self, elt: str) -> NoReturn: + raise self.ex + + @staticmethod + def new(ex: BaseException) -> Any: + """ + Creates an object that raises the wrapped exception ``ex`` when used, + and casts it to :py:obj:`~typing.Any` type. + """ + return DeferredError(ex) diff --git a/PIL/_version.py b/PIL/_version.py new file mode 100644 index 0000000000000000000000000000000000000000..85d2abd6d2d4219c333f4765318f0e6981b0ddd1 --- /dev/null +++ b/PIL/_version.py @@ -0,0 +1,4 @@ +# Master version for Pillow +from __future__ import annotations + +__version__ = "12.1.1" diff --git a/PIL/features.py b/PIL/features.py new file mode 100644 index 0000000000000000000000000000000000000000..ff32c2510453aebb44a0b60d52db29d4718acee6 --- /dev/null +++ b/PIL/features.py @@ -0,0 +1,343 @@ +from __future__ import annotations + +import collections +import os +import sys +import warnings +from typing import IO + +import PIL + +from . import Image + +modules = { + "pil": ("PIL._imaging", "PILLOW_VERSION"), + "tkinter": ("PIL._tkinter_finder", "tk_version"), + "freetype2": ("PIL._imagingft", "freetype2_version"), + "littlecms2": ("PIL._imagingcms", "littlecms_version"), + "webp": ("PIL._webp", "webpdecoder_version"), + "avif": ("PIL._avif", "libavif_version"), +} + + +def check_module(feature: str) -> bool: + """ + Checks if a module is available. + + :param feature: The module to check for. + :returns: ``True`` if available, ``False`` otherwise. + :raises ValueError: If the module is not defined in this version of Pillow. + """ + if feature not in modules: + msg = f"Unknown module {feature}" + raise ValueError(msg) + + module, ver = modules[feature] + + try: + __import__(module) + return True + except ModuleNotFoundError: + return False + except ImportError as ex: + warnings.warn(str(ex)) + return False + + +def version_module(feature: str) -> str | None: + """ + :param feature: The module to check for. + :returns: + The loaded version number as a string, or ``None`` if unknown or not available. + :raises ValueError: If the module is not defined in this version of Pillow. + """ + if not check_module(feature): + return None + + module, ver = modules[feature] + + return getattr(__import__(module, fromlist=[ver]), ver) + + +def get_supported_modules() -> list[str]: + """ + :returns: A list of all supported modules. + """ + return [f for f in modules if check_module(f)] + + +codecs = { + "jpg": ("jpeg", "jpeglib"), + "jpg_2000": ("jpeg2k", "jp2klib"), + "zlib": ("zip", "zlib"), + "libtiff": ("libtiff", "libtiff"), +} + + +def check_codec(feature: str) -> bool: + """ + Checks if a codec is available. + + :param feature: The codec to check for. + :returns: ``True`` if available, ``False`` otherwise. + :raises ValueError: If the codec is not defined in this version of Pillow. + """ + if feature not in codecs: + msg = f"Unknown codec {feature}" + raise ValueError(msg) + + codec, lib = codecs[feature] + + return f"{codec}_encoder" in dir(Image.core) + + +def version_codec(feature: str) -> str | None: + """ + :param feature: The codec to check for. + :returns: + The version number as a string, or ``None`` if not available. + Checked at compile time for ``jpg``, run-time otherwise. + :raises ValueError: If the codec is not defined in this version of Pillow. + """ + if not check_codec(feature): + return None + + codec, lib = codecs[feature] + + version = getattr(Image.core, f"{lib}_version") + + if feature == "libtiff": + return version.split("\n")[0].split("Version ")[1] + + return version + + +def get_supported_codecs() -> list[str]: + """ + :returns: A list of all supported codecs. + """ + return [f for f in codecs if check_codec(f)] + + +features: dict[str, tuple[str, str, str | None]] = { + "raqm": ("PIL._imagingft", "HAVE_RAQM", "raqm_version"), + "fribidi": ("PIL._imagingft", "HAVE_FRIBIDI", "fribidi_version"), + "harfbuzz": ("PIL._imagingft", "HAVE_HARFBUZZ", "harfbuzz_version"), + "libjpeg_turbo": ("PIL._imaging", "HAVE_LIBJPEGTURBO", "libjpeg_turbo_version"), + "mozjpeg": ("PIL._imaging", "HAVE_MOZJPEG", "libjpeg_turbo_version"), + "zlib_ng": ("PIL._imaging", "HAVE_ZLIBNG", "zlib_ng_version"), + "libimagequant": ("PIL._imaging", "HAVE_LIBIMAGEQUANT", "imagequant_version"), + "xcb": ("PIL._imaging", "HAVE_XCB", None), +} + + +def check_feature(feature: str) -> bool | None: + """ + Checks if a feature is available. + + :param feature: The feature to check for. + :returns: ``True`` if available, ``False`` if unavailable, ``None`` if unknown. + :raises ValueError: If the feature is not defined in this version of Pillow. + """ + if feature not in features: + msg = f"Unknown feature {feature}" + raise ValueError(msg) + + module, flag, ver = features[feature] + + try: + imported_module = __import__(module, fromlist=["PIL"]) + return getattr(imported_module, flag) + except ModuleNotFoundError: + return None + except ImportError as ex: + warnings.warn(str(ex)) + return None + + +def version_feature(feature: str) -> str | None: + """ + :param feature: The feature to check for. + :returns: The version number as a string, or ``None`` if not available. + :raises ValueError: If the feature is not defined in this version of Pillow. + """ + if not check_feature(feature): + return None + + module, flag, ver = features[feature] + + if ver is None: + return None + + return getattr(__import__(module, fromlist=[ver]), ver) + + +def get_supported_features() -> list[str]: + """ + :returns: A list of all supported features. + """ + return [f for f in features if check_feature(f)] + + +def check(feature: str) -> bool | None: + """ + :param feature: A module, codec, or feature name. + :returns: + ``True`` if the module, codec, or feature is available, + ``False`` or ``None`` otherwise. + """ + + if feature in modules: + return check_module(feature) + if feature in codecs: + return check_codec(feature) + if feature in features: + return check_feature(feature) + warnings.warn(f"Unknown feature '{feature}'.", stacklevel=2) + return False + + +def version(feature: str) -> str | None: + """ + :param feature: + The module, codec, or feature to check for. + :returns: + The version number as a string, or ``None`` if unknown or not available. + """ + if feature in modules: + return version_module(feature) + if feature in codecs: + return version_codec(feature) + if feature in features: + return version_feature(feature) + return None + + +def get_supported() -> list[str]: + """ + :returns: A list of all supported modules, features, and codecs. + """ + + ret = get_supported_modules() + ret.extend(get_supported_features()) + ret.extend(get_supported_codecs()) + return ret + + +def pilinfo(out: IO[str] | None = None, supported_formats: bool = True) -> None: + """ + Prints information about this installation of Pillow. + This function can be called with ``python3 -m PIL``. + It can also be called with ``python3 -m PIL.report`` or ``python3 -m PIL --report`` + to have "supported_formats" set to ``False``, omitting the list of all supported + image file formats. + + :param out: + The output stream to print to. Defaults to ``sys.stdout`` if ``None``. + :param supported_formats: + If ``True``, a list of all supported image file formats will be printed. + """ + + if out is None: + out = sys.stdout + + Image.init() + + print("-" * 68, file=out) + print(f"Pillow {PIL.__version__}", file=out) + py_version_lines = sys.version.splitlines() + print(f"Python {py_version_lines[0].strip()}", file=out) + for py_version in py_version_lines[1:]: + print(f" {py_version.strip()}", file=out) + print("-" * 68, file=out) + print(f"Python executable is {sys.executable or 'unknown'}", file=out) + if sys.prefix != sys.base_prefix: + print(f"Environment Python files loaded from {sys.prefix}", file=out) + print(f"System Python files loaded from {sys.base_prefix}", file=out) + print("-" * 68, file=out) + print( + f"Python Pillow modules loaded from {os.path.dirname(Image.__file__)}", + file=out, + ) + print( + f"Binary Pillow modules loaded from {os.path.dirname(Image.core.__file__)}", + file=out, + ) + print("-" * 68, file=out) + + for name, feature in [ + ("pil", "PIL CORE"), + ("tkinter", "TKINTER"), + ("freetype2", "FREETYPE2"), + ("littlecms2", "LITTLECMS2"), + ("webp", "WEBP"), + ("avif", "AVIF"), + ("jpg", "JPEG"), + ("jpg_2000", "OPENJPEG (JPEG2000)"), + ("zlib", "ZLIB (PNG/ZIP)"), + ("libtiff", "LIBTIFF"), + ("raqm", "RAQM (Bidirectional Text)"), + ("libimagequant", "LIBIMAGEQUANT (Quantization method)"), + ("xcb", "XCB (X protocol)"), + ]: + if check(name): + v: str | None = None + if name == "jpg": + libjpeg_turbo_version = version_feature("libjpeg_turbo") + if libjpeg_turbo_version is not None: + v = "mozjpeg" if check_feature("mozjpeg") else "libjpeg-turbo" + v += " " + libjpeg_turbo_version + if v is None: + v = version(name) + if v is not None: + version_static = name in ("pil", "jpg") + if name == "littlecms2": + # this check is also in src/_imagingcms.c:setup_module() + version_static = tuple(int(x) for x in v.split(".")) < (2, 7) + t = "compiled for" if version_static else "loaded" + if name == "zlib": + zlib_ng_version = version_feature("zlib_ng") + if zlib_ng_version is not None: + v += ", compiled for zlib-ng " + zlib_ng_version + elif name == "raqm": + for f in ("fribidi", "harfbuzz"): + v2 = version_feature(f) + if v2 is not None: + v += f", {f} {v2}" + print("---", feature, "support ok,", t, v, file=out) + else: + print("---", feature, "support ok", file=out) + else: + print("***", feature, "support not installed", file=out) + print("-" * 68, file=out) + + if supported_formats: + extensions = collections.defaultdict(list) + for ext, i in Image.EXTENSION.items(): + extensions[i].append(ext) + + for i in sorted(Image.ID): + line = f"{i}" + if i in Image.MIME: + line = f"{line} {Image.MIME[i]}" + print(line, file=out) + + if i in extensions: + print( + "Extensions: {}".format(", ".join(sorted(extensions[i]))), file=out + ) + + features = [] + if i in Image.OPEN: + features.append("open") + if i in Image.SAVE: + features.append("save") + if i in Image.SAVE_ALL: + features.append("save_all") + if i in Image.DECODERS: + features.append("decode") + if i in Image.ENCODERS: + features.append("encode") + + print("Features: {}".format(", ".join(features)), file=out) + print("-" * 68, file=out) diff --git a/PIL/py.typed b/PIL/py.typed new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/PIL/report.py b/PIL/report.py new file mode 100644 index 0000000000000000000000000000000000000000..d2815e8455e2ead803de4417314987ce7e9b7598 --- /dev/null +++ b/PIL/report.py @@ -0,0 +1,5 @@ +from __future__ import annotations + +from .features import pilinfo + +pilinfo(supported_formats=False) diff --git a/_multiprocess/__init__.py b/_multiprocess/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..085958182e2246471e6d6f655ff00b6e37e3e99a --- /dev/null +++ b/_multiprocess/__init__.py @@ -0,0 +1,8 @@ +#!/usr/bin/env python +# +# Author: Mike McKerns (mmckerns @caltech and @uqfoundation) +# Copyright (c) 2022-2024 The Uncertainty Quantification Foundation. +# License: 3-clause BSD. The full license text is available at: +# - https://github.com/uqfoundation/multiprocess/blob/master/LICENSE + +from _multiprocessing import * diff --git a/_yaml/__init__.py b/_yaml/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..7baa8c4b68127d5cdf0be9a799429e61347c2694 --- /dev/null +++ b/_yaml/__init__.py @@ -0,0 +1,33 @@ +# This is a stub package designed to roughly emulate the _yaml +# extension module, which previously existed as a standalone module +# and has been moved into the `yaml` package namespace. +# It does not perfectly mimic its old counterpart, but should get +# close enough for anyone who's relying on it even when they shouldn't. +import yaml + +# in some circumstances, the yaml module we imoprted may be from a different version, so we need +# to tread carefully when poking at it here (it may not have the attributes we expect) +if not getattr(yaml, '__with_libyaml__', False): + from sys import version_info + + exc = ModuleNotFoundError if version_info >= (3, 6) else ImportError + raise exc("No module named '_yaml'") +else: + from yaml._yaml import * + import warnings + warnings.warn( + 'The _yaml extension module is now located at yaml._yaml' + ' and its location is subject to change. To use the' + ' LibYAML-based parser and emitter, import from `yaml`:' + ' `from yaml import CLoader as Loader, CDumper as Dumper`.', + DeprecationWarning + ) + del warnings + # Don't `del yaml` here because yaml is actually an existing + # namespace member of _yaml. + +__name__ = '_yaml' +# If the module is top-level (i.e. not a part of any specific package) +# then the attribute should be set to ''. +# https://docs.python.org/3.8/library/types.html +__package__ = '' diff --git a/aiosignal-1.4.0.dist-info/INSTALLER b/aiosignal-1.4.0.dist-info/INSTALLER new file mode 100644 index 0000000000000000000000000000000000000000..5c69047b2eb8235994febeeae1da4a82365a240a --- /dev/null +++ b/aiosignal-1.4.0.dist-info/INSTALLER @@ -0,0 +1 @@ +uv \ No newline at end of file diff --git a/aiosignal-1.4.0.dist-info/METADATA b/aiosignal-1.4.0.dist-info/METADATA new file mode 100644 index 0000000000000000000000000000000000000000..03a6f0f7ff91628f60c4a95c4f3acbfa8d654ea8 --- /dev/null +++ b/aiosignal-1.4.0.dist-info/METADATA @@ -0,0 +1,112 @@ +Metadata-Version: 2.4 +Name: aiosignal +Version: 1.4.0 +Summary: aiosignal: a list of registered asynchronous callbacks +Home-page: https://github.com/aio-libs/aiosignal +Maintainer: aiohttp team +Maintainer-email: team@aiohttp.org +License: Apache 2.0 +Project-URL: Chat: Gitter, https://gitter.im/aio-libs/Lobby +Project-URL: CI: GitHub Actions, https://github.com/aio-libs/aiosignal/actions +Project-URL: Coverage: codecov, https://codecov.io/github/aio-libs/aiosignal +Project-URL: Docs: RTD, https://docs.aiosignal.org +Project-URL: GitHub: issues, https://github.com/aio-libs/aiosignal/issues +Project-URL: GitHub: repo, https://github.com/aio-libs/aiosignal +Classifier: License :: OSI Approved :: Apache Software License +Classifier: Intended Audience :: Developers +Classifier: Programming Language :: Python +Classifier: Programming Language :: Python :: 3 +Classifier: Programming Language :: Python :: 3 :: Only +Classifier: Development Status :: 5 - Production/Stable +Classifier: Operating System :: POSIX +Classifier: Operating System :: MacOS :: MacOS X +Classifier: Operating System :: Microsoft :: Windows +Classifier: Framework :: AsyncIO +Requires-Python: >=3.9 +Description-Content-Type: text/x-rst +License-File: LICENSE +Requires-Dist: frozenlist>=1.1.0 +Requires-Dist: typing-extensions>=4.2; python_version < "3.13" +Dynamic: license-file + +========= +aiosignal +========= + +.. image:: https://github.com/aio-libs/aiosignal/workflows/CI/badge.svg + :target: https://github.com/aio-libs/aiosignal/actions?query=workflow%3ACI + :alt: GitHub status for master branch + +.. image:: https://codecov.io/gh/aio-libs/aiosignal/branch/master/graph/badge.svg?flag=pytest + :target: https://codecov.io/gh/aio-libs/aiosignal?flags[0]=pytest + :alt: codecov.io status for master branch + +.. image:: https://badge.fury.io/py/aiosignal.svg + :target: https://pypi.org/project/aiosignal + :alt: Latest PyPI package version + +.. image:: https://readthedocs.org/projects/aiosignal/badge/?version=latest + :target: https://aiosignal.readthedocs.io/ + :alt: Latest Read The Docs + +.. image:: https://img.shields.io/discourse/topics?server=https%3A%2F%2Faio-libs.discourse.group%2F + :target: https://aio-libs.discourse.group/ + :alt: Discourse group for io-libs + +.. image:: https://badges.gitter.im/Join%20Chat.svg + :target: https://gitter.im/aio-libs/Lobby + :alt: Chat on Gitter + +Introduction +============ + +A project to manage callbacks in `asyncio` projects. + +``Signal`` is a list of registered asynchronous callbacks. + +The signal's life-cycle has two stages: after creation its content +could be filled by using standard list operations: ``sig.append()`` +etc. + +After you call ``sig.freeze()`` the signal is *frozen*: adding, removing +and dropping callbacks is forbidden. + +The only available operation is calling the previously registered +callbacks by using ``await sig.send(data)``. + +For concrete usage examples see the `Signals + +section of the `Web Server Advanced +` chapter of the `aiohttp +documentation`_. + + +Installation +------------ + +:: + + $ pip install aiosignal + + +Documentation +============= + +https://aiosignal.readthedocs.io/ + +License +======= + +``aiosignal`` is offered under the Apache 2 license. + +Source code +=========== + +The project is hosted on GitHub_ + +Please file an issue in the `bug tracker +`_ if you have found a bug +or have some suggestions to improve the library. + +.. _GitHub: https://github.com/aio-libs/aiosignal +.. _aiohttp documentation: https://docs.aiohttp.org/ diff --git a/aiosignal-1.4.0.dist-info/RECORD b/aiosignal-1.4.0.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..efc3848a24dc757901735a58eba259a70c89d605 --- /dev/null +++ b/aiosignal-1.4.0.dist-info/RECORD @@ -0,0 +1,9 @@ +aiosignal-1.4.0.dist-info/INSTALLER,sha256=5hhM4Q4mYTT9z6QB6PGpUAW81PGNFrYrdXMj4oM_6ak,2 +aiosignal-1.4.0.dist-info/METADATA,sha256=CSR-8dqLxpZyjUcTDnAuQwf299EB1sSFv_nzpxznAI0,3662 +aiosignal-1.4.0.dist-info/RECORD,, +aiosignal-1.4.0.dist-info/REQUESTED,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0 +aiosignal-1.4.0.dist-info/WHEEL,sha256=_zCd3N1l69ArxyTb8rzEoP9TpbYXkqRFSNOD5OuxnTs,91 +aiosignal-1.4.0.dist-info/licenses/LICENSE,sha256=b9UkPpLdf5jsacesN3co50kFcJ_1J6W_mNbQJjwE9bY,11332 +aiosignal-1.4.0.dist-info/top_level.txt,sha256=z45aNOKGDdrI1roqZY3BGXQ22kJFPHBmVdwtLYLtXC0,10 +aiosignal/__init__.py,sha256=TIkmUG9HTBt4dfq2nISYBiZiRB2xwvFtEZydLP0HPL4,1537 +aiosignal/py.typed,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0 diff --git a/aiosignal-1.4.0.dist-info/REQUESTED b/aiosignal-1.4.0.dist-info/REQUESTED new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/aiosignal-1.4.0.dist-info/WHEEL b/aiosignal-1.4.0.dist-info/WHEEL new file mode 100644 index 0000000000000000000000000000000000000000..e7fa31b6f3f78deb1022c1f7927f07d4d16da822 --- /dev/null +++ b/aiosignal-1.4.0.dist-info/WHEEL @@ -0,0 +1,5 @@ +Wheel-Version: 1.0 +Generator: setuptools (80.9.0) +Root-Is-Purelib: true +Tag: py3-none-any + diff --git a/aiosignal-1.4.0.dist-info/top_level.txt b/aiosignal-1.4.0.dist-info/top_level.txt new file mode 100644 index 0000000000000000000000000000000000000000..ac6df3afe74a5fd43afc7ab7f8393571a495fdc5 --- /dev/null +++ b/aiosignal-1.4.0.dist-info/top_level.txt @@ -0,0 +1 @@ +aiosignal diff --git a/annotated_doc/__init__.py b/annotated_doc/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..a0152a7d12abc2db37fb26e764a61e0c894a43f3 --- /dev/null +++ b/annotated_doc/__init__.py @@ -0,0 +1,3 @@ +from .main import Doc as Doc + +__version__ = "0.0.4" diff --git a/annotated_doc/main.py b/annotated_doc/main.py new file mode 100644 index 0000000000000000000000000000000000000000..7063c59e4500a1d02bfc9b41887f9e95f8163507 --- /dev/null +++ b/annotated_doc/main.py @@ -0,0 +1,36 @@ +class Doc: + """Define the documentation of a type annotation using `Annotated`, to be + used in class attributes, function and method parameters, return values, + and variables. + + The value should be a positional-only string literal to allow static tools + like editors and documentation generators to use it. + + This complements docstrings. + + The string value passed is available in the attribute `documentation`. + + Example: + + ```Python + from typing import Annotated + from annotated_doc import Doc + + def hi(name: Annotated[str, Doc("Who to say hi to")]) -> None: + print(f"Hi, {name}!") + ``` + """ + + def __init__(self, documentation: str, /) -> None: + self.documentation = documentation + + def __repr__(self) -> str: + return f"Doc({self.documentation!r})" + + def __hash__(self) -> int: + return hash(self.documentation) + + def __eq__(self, other: object) -> bool: + if not isinstance(other, Doc): + return NotImplemented + return self.documentation == other.documentation diff --git a/annotated_doc/py.typed b/annotated_doc/py.typed new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/annotated_types-0.7.0.dist-info/INSTALLER b/annotated_types-0.7.0.dist-info/INSTALLER new file mode 100644 index 0000000000000000000000000000000000000000..5c69047b2eb8235994febeeae1da4a82365a240a --- /dev/null +++ b/annotated_types-0.7.0.dist-info/INSTALLER @@ -0,0 +1 @@ +uv \ No newline at end of file diff --git a/annotated_types-0.7.0.dist-info/METADATA b/annotated_types-0.7.0.dist-info/METADATA new file mode 100644 index 0000000000000000000000000000000000000000..3ac05cfd1077ba5664e98ecd1342f7c54360b936 --- /dev/null +++ b/annotated_types-0.7.0.dist-info/METADATA @@ -0,0 +1,295 @@ +Metadata-Version: 2.3 +Name: annotated-types +Version: 0.7.0 +Summary: Reusable constraint types to use with typing.Annotated +Project-URL: Homepage, https://github.com/annotated-types/annotated-types +Project-URL: Source, https://github.com/annotated-types/annotated-types +Project-URL: Changelog, https://github.com/annotated-types/annotated-types/releases +Author-email: Adrian Garcia Badaracco <1755071+adriangb@users.noreply.github.com>, Samuel Colvin , Zac Hatfield-Dodds +License-File: LICENSE +Classifier: Development Status :: 4 - Beta +Classifier: Environment :: Console +Classifier: Environment :: MacOS X +Classifier: Intended Audience :: Developers +Classifier: Intended Audience :: Information Technology +Classifier: License :: OSI Approved :: MIT License +Classifier: Operating System :: POSIX :: Linux +Classifier: Operating System :: Unix +Classifier: Programming Language :: Python :: 3 :: Only +Classifier: Programming Language :: Python :: 3.8 +Classifier: Programming Language :: Python :: 3.9 +Classifier: Programming Language :: Python :: 3.10 +Classifier: Programming Language :: Python :: 3.11 +Classifier: Programming Language :: Python :: 3.12 +Classifier: Topic :: Software Development :: Libraries :: Python Modules +Classifier: Typing :: Typed +Requires-Python: >=3.8 +Requires-Dist: typing-extensions>=4.0.0; python_version < '3.9' +Description-Content-Type: text/markdown + +# annotated-types + +[![CI](https://github.com/annotated-types/annotated-types/workflows/CI/badge.svg?event=push)](https://github.com/annotated-types/annotated-types/actions?query=event%3Apush+branch%3Amain+workflow%3ACI) +[![pypi](https://img.shields.io/pypi/v/annotated-types.svg)](https://pypi.python.org/pypi/annotated-types) +[![versions](https://img.shields.io/pypi/pyversions/annotated-types.svg)](https://github.com/annotated-types/annotated-types) +[![license](https://img.shields.io/github/license/annotated-types/annotated-types.svg)](https://github.com/annotated-types/annotated-types/blob/main/LICENSE) + +[PEP-593](https://peps.python.org/pep-0593/) added `typing.Annotated` as a way of +adding context-specific metadata to existing types, and specifies that +`Annotated[T, x]` _should_ be treated as `T` by any tool or library without special +logic for `x`. + +This package provides metadata objects which can be used to represent common +constraints such as upper and lower bounds on scalar values and collection sizes, +a `Predicate` marker for runtime checks, and +descriptions of how we intend these metadata to be interpreted. In some cases, +we also note alternative representations which do not require this package. + +## Install + +```bash +pip install annotated-types +``` + +## Examples + +```python +from typing import Annotated +from annotated_types import Gt, Len, Predicate + +class MyClass: + age: Annotated[int, Gt(18)] # Valid: 19, 20, ... + # Invalid: 17, 18, "19", 19.0, ... + factors: list[Annotated[int, Predicate(is_prime)]] # Valid: 2, 3, 5, 7, 11, ... + # Invalid: 4, 8, -2, 5.0, "prime", ... + + my_list: Annotated[list[int], Len(0, 10)] # Valid: [], [10, 20, 30, 40, 50] + # Invalid: (1, 2), ["abc"], [0] * 20 +``` + +## Documentation + +_While `annotated-types` avoids runtime checks for performance, users should not +construct invalid combinations such as `MultipleOf("non-numeric")` or `Annotated[int, Len(3)]`. +Downstream implementors may choose to raise an error, emit a warning, silently ignore +a metadata item, etc., if the metadata objects described below are used with an +incompatible type - or for any other reason!_ + +### Gt, Ge, Lt, Le + +Express inclusive and/or exclusive bounds on orderable values - which may be numbers, +dates, times, strings, sets, etc. Note that the boundary value need not be of the +same type that was annotated, so long as they can be compared: `Annotated[int, Gt(1.5)]` +is fine, for example, and implies that the value is an integer x such that `x > 1.5`. + +We suggest that implementors may also interpret `functools.partial(operator.le, 1.5)` +as being equivalent to `Gt(1.5)`, for users who wish to avoid a runtime dependency on +the `annotated-types` package. + +To be explicit, these types have the following meanings: + +* `Gt(x)` - value must be "Greater Than" `x` - equivalent to exclusive minimum +* `Ge(x)` - value must be "Greater than or Equal" to `x` - equivalent to inclusive minimum +* `Lt(x)` - value must be "Less Than" `x` - equivalent to exclusive maximum +* `Le(x)` - value must be "Less than or Equal" to `x` - equivalent to inclusive maximum + +### Interval + +`Interval(gt, ge, lt, le)` allows you to specify an upper and lower bound with a single +metadata object. `None` attributes should be ignored, and non-`None` attributes +treated as per the single bounds above. + +### MultipleOf + +`MultipleOf(multiple_of=x)` might be interpreted in two ways: + +1. Python semantics, implying `value % multiple_of == 0`, or +2. [JSONschema semantics](https://json-schema.org/draft/2020-12/json-schema-validation.html#rfc.section.6.2.1), + where `int(value / multiple_of) == value / multiple_of`. + +We encourage users to be aware of these two common interpretations and their +distinct behaviours, especially since very large or non-integer numbers make +it easy to cause silent data corruption due to floating-point imprecision. + +We encourage libraries to carefully document which interpretation they implement. + +### MinLen, MaxLen, Len + +`Len()` implies that `min_length <= len(value) <= max_length` - lower and upper bounds are inclusive. + +As well as `Len()` which can optionally include upper and lower bounds, we also +provide `MinLen(x)` and `MaxLen(y)` which are equivalent to `Len(min_length=x)` +and `Len(max_length=y)` respectively. + +`Len`, `MinLen`, and `MaxLen` may be used with any type which supports `len(value)`. + +Examples of usage: + +* `Annotated[list, MaxLen(10)]` (or `Annotated[list, Len(max_length=10))`) - list must have a length of 10 or less +* `Annotated[str, MaxLen(10)]` - string must have a length of 10 or less +* `Annotated[list, MinLen(3))` (or `Annotated[list, Len(min_length=3))`) - list must have a length of 3 or more +* `Annotated[list, Len(4, 6)]` - list must have a length of 4, 5, or 6 +* `Annotated[list, Len(8, 8)]` - list must have a length of exactly 8 + +#### Changed in v0.4.0 + +* `min_inclusive` has been renamed to `min_length`, no change in meaning +* `max_exclusive` has been renamed to `max_length`, upper bound is now **inclusive** instead of **exclusive** +* The recommendation that slices are interpreted as `Len` has been removed due to ambiguity and different semantic + meaning of the upper bound in slices vs. `Len` + +See [issue #23](https://github.com/annotated-types/annotated-types/issues/23) for discussion. + +### Timezone + +`Timezone` can be used with a `datetime` or a `time` to express which timezones +are allowed. `Annotated[datetime, Timezone(None)]` must be a naive datetime. +`Timezone[...]` ([literal ellipsis](https://docs.python.org/3/library/constants.html#Ellipsis)) +expresses that any timezone-aware datetime is allowed. You may also pass a specific +timezone string or [`tzinfo`](https://docs.python.org/3/library/datetime.html#tzinfo-objects) +object such as `Timezone(timezone.utc)` or `Timezone("Africa/Abidjan")` to express that you only +allow a specific timezone, though we note that this is often a symptom of fragile design. + +#### Changed in v0.x.x + +* `Timezone` accepts [`tzinfo`](https://docs.python.org/3/library/datetime.html#tzinfo-objects) objects instead of + `timezone`, extending compatibility to [`zoneinfo`](https://docs.python.org/3/library/zoneinfo.html) and third party libraries. + +### Unit + +`Unit(unit: str)` expresses that the annotated numeric value is the magnitude of +a quantity with the specified unit. For example, `Annotated[float, Unit("m/s")]` +would be a float representing a velocity in meters per second. + +Please note that `annotated_types` itself makes no attempt to parse or validate +the unit string in any way. That is left entirely to downstream libraries, +such as [`pint`](https://pint.readthedocs.io) or +[`astropy.units`](https://docs.astropy.org/en/stable/units/). + +An example of how a library might use this metadata: + +```python +from annotated_types import Unit +from typing import Annotated, TypeVar, Callable, Any, get_origin, get_args + +# given a type annotated with a unit: +Meters = Annotated[float, Unit("m")] + + +# you can cast the annotation to a specific unit type with any +# callable that accepts a string and returns the desired type +T = TypeVar("T") +def cast_unit(tp: Any, unit_cls: Callable[[str], T]) -> T | None: + if get_origin(tp) is Annotated: + for arg in get_args(tp): + if isinstance(arg, Unit): + return unit_cls(arg.unit) + return None + + +# using `pint` +import pint +pint_unit = cast_unit(Meters, pint.Unit) + + +# using `astropy.units` +import astropy.units as u +astropy_unit = cast_unit(Meters, u.Unit) +``` + +### Predicate + +`Predicate(func: Callable)` expresses that `func(value)` is truthy for valid values. +Users should prefer the statically inspectable metadata above, but if you need +the full power and flexibility of arbitrary runtime predicates... here it is. + +For some common constraints, we provide generic types: + +* `IsLower = Annotated[T, Predicate(str.islower)]` +* `IsUpper = Annotated[T, Predicate(str.isupper)]` +* `IsDigit = Annotated[T, Predicate(str.isdigit)]` +* `IsFinite = Annotated[T, Predicate(math.isfinite)]` +* `IsNotFinite = Annotated[T, Predicate(Not(math.isfinite))]` +* `IsNan = Annotated[T, Predicate(math.isnan)]` +* `IsNotNan = Annotated[T, Predicate(Not(math.isnan))]` +* `IsInfinite = Annotated[T, Predicate(math.isinf)]` +* `IsNotInfinite = Annotated[T, Predicate(Not(math.isinf))]` + +so that you can write e.g. `x: IsFinite[float] = 2.0` instead of the longer +(but exactly equivalent) `x: Annotated[float, Predicate(math.isfinite)] = 2.0`. + +Some libraries might have special logic to handle known or understandable predicates, +for example by checking for `str.isdigit` and using its presence to both call custom +logic to enforce digit-only strings, and customise some generated external schema. +Users are therefore encouraged to avoid indirection like `lambda s: s.lower()`, in +favor of introspectable methods such as `str.lower` or `re.compile("pattern").search`. + +To enable basic negation of commonly used predicates like `math.isnan` without introducing introspection that makes it impossible for implementers to introspect the predicate we provide a `Not` wrapper that simply negates the predicate in an introspectable manner. Several of the predicates listed above are created in this manner. + +We do not specify what behaviour should be expected for predicates that raise +an exception. For example `Annotated[int, Predicate(str.isdigit)]` might silently +skip invalid constraints, or statically raise an error; or it might try calling it +and then propagate or discard the resulting +`TypeError: descriptor 'isdigit' for 'str' objects doesn't apply to a 'int' object` +exception. We encourage libraries to document the behaviour they choose. + +### Doc + +`doc()` can be used to add documentation information in `Annotated`, for function and method parameters, variables, class attributes, return types, and any place where `Annotated` can be used. + +It expects a value that can be statically analyzed, as the main use case is for static analysis, editors, documentation generators, and similar tools. + +It returns a `DocInfo` class with a single attribute `documentation` containing the value passed to `doc()`. + +This is the early adopter's alternative form of the [`typing-doc` proposal](https://github.com/tiangolo/fastapi/blob/typing-doc/typing_doc.md). + +### Integrating downstream types with `GroupedMetadata` + +Implementers may choose to provide a convenience wrapper that groups multiple pieces of metadata. +This can help reduce verbosity and cognitive overhead for users. +For example, an implementer like Pydantic might provide a `Field` or `Meta` type that accepts keyword arguments and transforms these into low-level metadata: + +```python +from dataclasses import dataclass +from typing import Iterator +from annotated_types import GroupedMetadata, Ge + +@dataclass +class Field(GroupedMetadata): + ge: int | None = None + description: str | None = None + + def __iter__(self) -> Iterator[object]: + # Iterating over a GroupedMetadata object should yield annotated-types + # constraint metadata objects which describe it as fully as possible, + # and may include other unknown objects too. + if self.ge is not None: + yield Ge(self.ge) + if self.description is not None: + yield Description(self.description) +``` + +Libraries consuming annotated-types constraints should check for `GroupedMetadata` and unpack it by iterating over the object and treating the results as if they had been "unpacked" in the `Annotated` type. The same logic should be applied to the [PEP 646 `Unpack` type](https://peps.python.org/pep-0646/), so that `Annotated[T, Field(...)]`, `Annotated[T, Unpack[Field(...)]]` and `Annotated[T, *Field(...)]` are all treated consistently. + +Libraries consuming annotated-types should also ignore any metadata they do not recongize that came from unpacking a `GroupedMetadata`, just like they ignore unrecognized metadata in `Annotated` itself. + +Our own `annotated_types.Interval` class is a `GroupedMetadata` which unpacks itself into `Gt`, `Lt`, etc., so this is not an abstract concern. Similarly, `annotated_types.Len` is a `GroupedMetadata` which unpacks itself into `MinLen` (optionally) and `MaxLen`. + +### Consuming metadata + +We intend to not be prescriptive as to _how_ the metadata and constraints are used, but as an example of how one might parse constraints from types annotations see our [implementation in `test_main.py`](https://github.com/annotated-types/annotated-types/blob/f59cf6d1b5255a0fe359b93896759a180bec30ae/tests/test_main.py#L94-L103). + +It is up to the implementer to determine how this metadata is used. +You could use the metadata for runtime type checking, for generating schemas or to generate example data, amongst other use cases. + +## Design & History + +This package was designed at the PyCon 2022 sprints by the maintainers of Pydantic +and Hypothesis, with the goal of making it as easy as possible for end-users to +provide more informative annotations for use by runtime libraries. + +It is deliberately minimal, and following PEP-593 allows considerable downstream +discretion in what (if anything!) they choose to support. Nonetheless, we expect +that staying simple and covering _only_ the most common use-cases will give users +and maintainers the best experience we can. If you'd like more constraints for your +types - follow our lead, by defining them and documenting them downstream! diff --git a/annotated_types-0.7.0.dist-info/RECORD b/annotated_types-0.7.0.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..26cf057877348bfcb4b5724d950a401295b1c5bf --- /dev/null +++ b/annotated_types-0.7.0.dist-info/RECORD @@ -0,0 +1,9 @@ +annotated_types-0.7.0.dist-info/INSTALLER,sha256=5hhM4Q4mYTT9z6QB6PGpUAW81PGNFrYrdXMj4oM_6ak,2 +annotated_types-0.7.0.dist-info/METADATA,sha256=7ltqxksJJ0wCYFGBNIQCWTlWQGeAH0hRFdnK3CB895E,15046 +annotated_types-0.7.0.dist-info/RECORD,, +annotated_types-0.7.0.dist-info/REQUESTED,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0 +annotated_types-0.7.0.dist-info/WHEEL,sha256=zEMcRr9Kr03x1ozGwg5v9NQBKn3kndp6LSoSlVg-jhU,87 +annotated_types-0.7.0.dist-info/licenses/LICENSE,sha256=_hBJiEsaDZNCkB6I4H8ykl0ksxIdmXK2poBfuYJLCV0,1083 +annotated_types/__init__.py,sha256=RynLsRKUEGI0KimXydlD1fZEfEzWwDo0Uon3zOKhG1Q,13819 +annotated_types/py.typed,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0 +annotated_types/test_cases.py,sha256=zHFX6EpcMbGJ8FzBYDbO56bPwx_DYIVSKbZM-4B3_lg,6421 diff --git a/annotated_types-0.7.0.dist-info/REQUESTED b/annotated_types-0.7.0.dist-info/REQUESTED new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/annotated_types-0.7.0.dist-info/WHEEL b/annotated_types-0.7.0.dist-info/WHEEL new file mode 100644 index 0000000000000000000000000000000000000000..516596c76787b10928cbab24f22c0ea00433b15d --- /dev/null +++ b/annotated_types-0.7.0.dist-info/WHEEL @@ -0,0 +1,4 @@ +Wheel-Version: 1.0 +Generator: hatchling 1.24.2 +Root-Is-Purelib: true +Tag: py3-none-any diff --git a/attr/__init__.py b/attr/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..5c6e0650bc4bf53806420d7ef5f881ecd2bd77ea --- /dev/null +++ b/attr/__init__.py @@ -0,0 +1,104 @@ +# SPDX-License-Identifier: MIT + +""" +Classes Without Boilerplate +""" + +from functools import partial +from typing import Callable, Literal, Protocol + +from . import converters, exceptions, filters, setters, validators +from ._cmp import cmp_using +from ._config import get_run_validators, set_run_validators +from ._funcs import asdict, assoc, astuple, has, resolve_types +from ._make import ( + NOTHING, + Attribute, + Converter, + Factory, + _Nothing, + attrib, + attrs, + evolve, + fields, + fields_dict, + make_class, + validate, +) +from ._next_gen import define, field, frozen, mutable +from ._version_info import VersionInfo + + +s = attributes = attrs +ib = attr = attrib +dataclass = partial(attrs, auto_attribs=True) # happy Easter ;) + + +class AttrsInstance(Protocol): + pass + + +NothingType = Literal[_Nothing.NOTHING] + +__all__ = [ + "NOTHING", + "Attribute", + "AttrsInstance", + "Converter", + "Factory", + "NothingType", + "asdict", + "assoc", + "astuple", + "attr", + "attrib", + "attributes", + "attrs", + "cmp_using", + "converters", + "define", + "evolve", + "exceptions", + "field", + "fields", + "fields_dict", + "filters", + "frozen", + "get_run_validators", + "has", + "ib", + "make_class", + "mutable", + "resolve_types", + "s", + "set_run_validators", + "setters", + "validate", + "validators", +] + + +def _make_getattr(mod_name: str) -> Callable: + """ + Create a metadata proxy for packaging information that uses *mod_name* in + its warnings and errors. + """ + + def __getattr__(name: str) -> str: + if name not in ("__version__", "__version_info__"): + msg = f"module {mod_name} has no attribute {name}" + raise AttributeError(msg) + + from importlib.metadata import metadata + + meta = metadata("attrs") + + if name == "__version_info__": + return VersionInfo._from_version_string(meta["version"]) + + return meta["version"] + + return __getattr__ + + +__getattr__ = _make_getattr(__name__) diff --git a/attr/__init__.pyi b/attr/__init__.pyi new file mode 100644 index 0000000000000000000000000000000000000000..758decf8ffcb55833a7136219db2b99542bfc7a4 --- /dev/null +++ b/attr/__init__.pyi @@ -0,0 +1,389 @@ +import enum +import sys + +from typing import ( + Any, + Callable, + Generic, + Literal, + Mapping, + Protocol, + Sequence, + TypeVar, + overload, +) + +# `import X as X` is required to make these public +from . import converters as converters +from . import exceptions as exceptions +from . import filters as filters +from . import setters as setters +from . import validators as validators +from ._cmp import cmp_using as cmp_using +from ._typing_compat import AttrsInstance_ +from ._version_info import VersionInfo +from attrs import ( + define as define, + field as field, + mutable as mutable, + frozen as frozen, + _EqOrderType, + _ValidatorType, + _ConverterType, + _ReprArgType, + _OnSetAttrType, + _OnSetAttrArgType, + _FieldTransformer, + _ValidatorArgType, +) + +if sys.version_info >= (3, 10): + from typing import TypeGuard, TypeAlias +else: + from typing_extensions import TypeGuard, TypeAlias + +if sys.version_info >= (3, 11): + from typing import dataclass_transform +else: + from typing_extensions import dataclass_transform + +__version__: str +__version_info__: VersionInfo +__title__: str +__description__: str +__url__: str +__uri__: str +__author__: str +__email__: str +__license__: str +__copyright__: str + +_T = TypeVar("_T") +_C = TypeVar("_C", bound=type) + +_FilterType = Callable[["Attribute[_T]", _T], bool] + +# We subclass this here to keep the protocol's qualified name clean. +class AttrsInstance(AttrsInstance_, Protocol): + pass + +_A = TypeVar("_A", bound=type[AttrsInstance]) + +class _Nothing(enum.Enum): + NOTHING = enum.auto() + +NOTHING = _Nothing.NOTHING +NothingType: TypeAlias = Literal[_Nothing.NOTHING] + +# NOTE: Factory lies about its return type to make this possible: +# `x: List[int] # = Factory(list)` +# Work around mypy issue #4554 in the common case by using an overload. + +@overload +def Factory(factory: Callable[[], _T]) -> _T: ... +@overload +def Factory( + factory: Callable[[Any], _T], + takes_self: Literal[True], +) -> _T: ... +@overload +def Factory( + factory: Callable[[], _T], + takes_self: Literal[False], +) -> _T: ... + +In = TypeVar("In") +Out = TypeVar("Out") + +class Converter(Generic[In, Out]): + @overload + def __init__(self, converter: Callable[[In], Out]) -> None: ... + @overload + def __init__( + self, + converter: Callable[[In, AttrsInstance, Attribute], Out], + *, + takes_self: Literal[True], + takes_field: Literal[True], + ) -> None: ... + @overload + def __init__( + self, + converter: Callable[[In, Attribute], Out], + *, + takes_field: Literal[True], + ) -> None: ... + @overload + def __init__( + self, + converter: Callable[[In, AttrsInstance], Out], + *, + takes_self: Literal[True], + ) -> None: ... + +class Attribute(Generic[_T]): + name: str + default: _T | None + validator: _ValidatorType[_T] | None + repr: _ReprArgType + cmp: _EqOrderType + eq: _EqOrderType + order: _EqOrderType + hash: bool | None + init: bool + converter: Converter | None + metadata: dict[Any, Any] + type: type[_T] | None + kw_only: bool + on_setattr: _OnSetAttrType + alias: str | None + + def evolve(self, **changes: Any) -> "Attribute[Any]": ... + +# NOTE: We had several choices for the annotation to use for type arg: +# 1) Type[_T] +# - Pros: Handles simple cases correctly +# - Cons: Might produce less informative errors in the case of conflicting +# TypeVars e.g. `attr.ib(default='bad', type=int)` +# 2) Callable[..., _T] +# - Pros: Better error messages than #1 for conflicting TypeVars +# - Cons: Terrible error messages for validator checks. +# e.g. attr.ib(type=int, validator=validate_str) +# -> error: Cannot infer function type argument +# 3) type (and do all of the work in the mypy plugin) +# - Pros: Simple here, and we could customize the plugin with our own errors. +# - Cons: Would need to write mypy plugin code to handle all the cases. +# We chose option #1. + +# `attr` lies about its return type to make the following possible: +# attr() -> Any +# attr(8) -> int +# attr(validator=) -> Whatever the callable expects. +# This makes this type of assignments possible: +# x: int = attr(8) +# +# This form catches explicit None or no default but with no other arguments +# returns Any. +@overload +def attrib( + default: None = ..., + validator: None = ..., + repr: _ReprArgType = ..., + cmp: _EqOrderType | None = ..., + hash: bool | None = ..., + init: bool = ..., + metadata: Mapping[Any, Any] | None = ..., + type: None = ..., + converter: None = ..., + factory: None = ..., + kw_only: bool | None = ..., + eq: _EqOrderType | None = ..., + order: _EqOrderType | None = ..., + on_setattr: _OnSetAttrArgType | None = ..., + alias: str | None = ..., +) -> Any: ... + +# This form catches an explicit None or no default and infers the type from the +# other arguments. +@overload +def attrib( + default: None = ..., + validator: _ValidatorArgType[_T] | None = ..., + repr: _ReprArgType = ..., + cmp: _EqOrderType | None = ..., + hash: bool | None = ..., + init: bool = ..., + metadata: Mapping[Any, Any] | None = ..., + type: type[_T] | None = ..., + converter: _ConverterType + | list[_ConverterType] + | tuple[_ConverterType] + | None = ..., + factory: Callable[[], _T] | None = ..., + kw_only: bool | None = ..., + eq: _EqOrderType | None = ..., + order: _EqOrderType | None = ..., + on_setattr: _OnSetAttrArgType | None = ..., + alias: str | None = ..., +) -> _T: ... + +# This form catches an explicit default argument. +@overload +def attrib( + default: _T, + validator: _ValidatorArgType[_T] | None = ..., + repr: _ReprArgType = ..., + cmp: _EqOrderType | None = ..., + hash: bool | None = ..., + init: bool = ..., + metadata: Mapping[Any, Any] | None = ..., + type: type[_T] | None = ..., + converter: _ConverterType + | list[_ConverterType] + | tuple[_ConverterType] + | None = ..., + factory: Callable[[], _T] | None = ..., + kw_only: bool | None = ..., + eq: _EqOrderType | None = ..., + order: _EqOrderType | None = ..., + on_setattr: _OnSetAttrArgType | None = ..., + alias: str | None = ..., +) -> _T: ... + +# This form covers type=non-Type: e.g. forward references (str), Any +@overload +def attrib( + default: _T | None = ..., + validator: _ValidatorArgType[_T] | None = ..., + repr: _ReprArgType = ..., + cmp: _EqOrderType | None = ..., + hash: bool | None = ..., + init: bool = ..., + metadata: Mapping[Any, Any] | None = ..., + type: object = ..., + converter: _ConverterType + | list[_ConverterType] + | tuple[_ConverterType] + | None = ..., + factory: Callable[[], _T] | None = ..., + kw_only: bool | None = ..., + eq: _EqOrderType | None = ..., + order: _EqOrderType | None = ..., + on_setattr: _OnSetAttrArgType | None = ..., + alias: str | None = ..., +) -> Any: ... +@overload +@dataclass_transform(order_default=True, field_specifiers=(attrib, field)) +def attrs( + maybe_cls: _C, + these: dict[str, Any] | None = ..., + repr_ns: str | None = ..., + repr: bool = ..., + cmp: _EqOrderType | None = ..., + hash: bool | None = ..., + init: bool = ..., + slots: bool = ..., + frozen: bool = ..., + weakref_slot: bool = ..., + str: bool = ..., + auto_attribs: bool = ..., + kw_only: bool = ..., + cache_hash: bool = ..., + auto_exc: bool = ..., + eq: _EqOrderType | None = ..., + order: _EqOrderType | None = ..., + auto_detect: bool = ..., + collect_by_mro: bool = ..., + getstate_setstate: bool | None = ..., + on_setattr: _OnSetAttrArgType | None = ..., + field_transformer: _FieldTransformer | None = ..., + match_args: bool = ..., + unsafe_hash: bool | None = ..., +) -> _C: ... +@overload +@dataclass_transform(order_default=True, field_specifiers=(attrib, field)) +def attrs( + maybe_cls: None = ..., + these: dict[str, Any] | None = ..., + repr_ns: str | None = ..., + repr: bool = ..., + cmp: _EqOrderType | None = ..., + hash: bool | None = ..., + init: bool = ..., + slots: bool = ..., + frozen: bool = ..., + weakref_slot: bool = ..., + str: bool = ..., + auto_attribs: bool = ..., + kw_only: bool = ..., + cache_hash: bool = ..., + auto_exc: bool = ..., + eq: _EqOrderType | None = ..., + order: _EqOrderType | None = ..., + auto_detect: bool = ..., + collect_by_mro: bool = ..., + getstate_setstate: bool | None = ..., + on_setattr: _OnSetAttrArgType | None = ..., + field_transformer: _FieldTransformer | None = ..., + match_args: bool = ..., + unsafe_hash: bool | None = ..., +) -> Callable[[_C], _C]: ... +def fields(cls: type[AttrsInstance] | AttrsInstance) -> Any: ... +def fields_dict(cls: type[AttrsInstance]) -> dict[str, Attribute[Any]]: ... +def validate(inst: AttrsInstance) -> None: ... +def resolve_types( + cls: _A, + globalns: dict[str, Any] | None = ..., + localns: dict[str, Any] | None = ..., + attribs: list[Attribute[Any]] | None = ..., + include_extras: bool = ..., +) -> _A: ... + +# TODO: add support for returning a proper attrs class from the mypy plugin +# we use Any instead of _CountingAttr so that e.g. `make_class('Foo', +# [attr.ib()])` is valid +def make_class( + name: str, + attrs: list[str] | tuple[str, ...] | dict[str, Any], + bases: tuple[type, ...] = ..., + class_body: dict[str, Any] | None = ..., + repr_ns: str | None = ..., + repr: bool = ..., + cmp: _EqOrderType | None = ..., + hash: bool | None = ..., + init: bool = ..., + slots: bool = ..., + frozen: bool = ..., + weakref_slot: bool = ..., + str: bool = ..., + auto_attribs: bool = ..., + kw_only: bool = ..., + cache_hash: bool = ..., + auto_exc: bool = ..., + eq: _EqOrderType | None = ..., + order: _EqOrderType | None = ..., + collect_by_mro: bool = ..., + on_setattr: _OnSetAttrArgType | None = ..., + field_transformer: _FieldTransformer | None = ..., +) -> type: ... + +# _funcs -- + +# TODO: add support for returning TypedDict from the mypy plugin +# FIXME: asdict/astuple do not honor their factory args. Waiting on one of +# these: +# https://github.com/python/mypy/issues/4236 +# https://github.com/python/typing/issues/253 +# XXX: remember to fix attrs.asdict/astuple too! +def asdict( + inst: AttrsInstance, + recurse: bool = ..., + filter: _FilterType[Any] | None = ..., + dict_factory: type[Mapping[Any, Any]] = ..., + retain_collection_types: bool = ..., + value_serializer: Callable[[type, Attribute[Any], Any], Any] | None = ..., + tuple_keys: bool | None = ..., +) -> dict[str, Any]: ... + +# TODO: add support for returning NamedTuple from the mypy plugin +def astuple( + inst: AttrsInstance, + recurse: bool = ..., + filter: _FilterType[Any] | None = ..., + tuple_factory: type[Sequence[Any]] = ..., + retain_collection_types: bool = ..., +) -> tuple[Any, ...]: ... +def has(cls: type) -> TypeGuard[type[AttrsInstance]]: ... +def assoc(inst: _T, **changes: Any) -> _T: ... +def evolve(inst: _T, **changes: Any) -> _T: ... + +# _config -- + +def set_run_validators(run: bool) -> None: ... +def get_run_validators() -> bool: ... + +# aliases -- + +s = attributes = attrs +ib = attr = attrib +dataclass = attrs # Technically, partial(attrs, auto_attribs=True) ;) diff --git a/attr/_cmp.py b/attr/_cmp.py new file mode 100644 index 0000000000000000000000000000000000000000..09bab491f83ef4d15129f34b5f5a9e69bb34d63c --- /dev/null +++ b/attr/_cmp.py @@ -0,0 +1,160 @@ +# SPDX-License-Identifier: MIT + + +import functools +import types + +from ._make import __ne__ + + +_operation_names = {"eq": "==", "lt": "<", "le": "<=", "gt": ">", "ge": ">="} + + +def cmp_using( + eq=None, + lt=None, + le=None, + gt=None, + ge=None, + require_same_type=True, + class_name="Comparable", +): + """ + Create a class that can be passed into `attrs.field`'s ``eq``, ``order``, + and ``cmp`` arguments to customize field comparison. + + The resulting class will have a full set of ordering methods if at least + one of ``{lt, le, gt, ge}`` and ``eq`` are provided. + + Args: + eq (typing.Callable | None): + Callable used to evaluate equality of two objects. + + lt (typing.Callable | None): + Callable used to evaluate whether one object is less than another + object. + + le (typing.Callable | None): + Callable used to evaluate whether one object is less than or equal + to another object. + + gt (typing.Callable | None): + Callable used to evaluate whether one object is greater than + another object. + + ge (typing.Callable | None): + Callable used to evaluate whether one object is greater than or + equal to another object. + + require_same_type (bool): + When `True`, equality and ordering methods will return + `NotImplemented` if objects are not of the same type. + + class_name (str | None): Name of class. Defaults to "Comparable". + + See `comparison` for more details. + + .. versionadded:: 21.1.0 + """ + + body = { + "__slots__": ["value"], + "__init__": _make_init(), + "_requirements": [], + "_is_comparable_to": _is_comparable_to, + } + + # Add operations. + num_order_functions = 0 + has_eq_function = False + + if eq is not None: + has_eq_function = True + body["__eq__"] = _make_operator("eq", eq) + body["__ne__"] = __ne__ + + if lt is not None: + num_order_functions += 1 + body["__lt__"] = _make_operator("lt", lt) + + if le is not None: + num_order_functions += 1 + body["__le__"] = _make_operator("le", le) + + if gt is not None: + num_order_functions += 1 + body["__gt__"] = _make_operator("gt", gt) + + if ge is not None: + num_order_functions += 1 + body["__ge__"] = _make_operator("ge", ge) + + type_ = types.new_class( + class_name, (object,), {}, lambda ns: ns.update(body) + ) + + # Add same type requirement. + if require_same_type: + type_._requirements.append(_check_same_type) + + # Add total ordering if at least one operation was defined. + if 0 < num_order_functions < 4: + if not has_eq_function: + # functools.total_ordering requires __eq__ to be defined, + # so raise early error here to keep a nice stack. + msg = "eq must be define is order to complete ordering from lt, le, gt, ge." + raise ValueError(msg) + type_ = functools.total_ordering(type_) + + return type_ + + +def _make_init(): + """ + Create __init__ method. + """ + + def __init__(self, value): + """ + Initialize object with *value*. + """ + self.value = value + + return __init__ + + +def _make_operator(name, func): + """ + Create operator method. + """ + + def method(self, other): + if not self._is_comparable_to(other): + return NotImplemented + + result = func(self.value, other.value) + if result is NotImplemented: + return NotImplemented + + return result + + method.__name__ = f"__{name}__" + method.__doc__ = ( + f"Return a {_operation_names[name]} b. Computed by attrs." + ) + + return method + + +def _is_comparable_to(self, other): + """ + Check whether `other` is comparable to `self`. + """ + return all(func(self, other) for func in self._requirements) + + +def _check_same_type(self, other): + """ + Return True if *self* and *other* are of the same type, False otherwise. + """ + return other.value.__class__ is self.value.__class__ diff --git a/attr/_cmp.pyi b/attr/_cmp.pyi new file mode 100644 index 0000000000000000000000000000000000000000..cc7893b04520afa719b1412c7646c3c1b39bf94b --- /dev/null +++ b/attr/_cmp.pyi @@ -0,0 +1,13 @@ +from typing import Any, Callable + +_CompareWithType = Callable[[Any, Any], bool] + +def cmp_using( + eq: _CompareWithType | None = ..., + lt: _CompareWithType | None = ..., + le: _CompareWithType | None = ..., + gt: _CompareWithType | None = ..., + ge: _CompareWithType | None = ..., + require_same_type: bool = ..., + class_name: str = ..., +) -> type: ... diff --git a/attr/_compat.py b/attr/_compat.py new file mode 100644 index 0000000000000000000000000000000000000000..bc68ed9eaf9853bcc6065e7691209a787bf2eccc --- /dev/null +++ b/attr/_compat.py @@ -0,0 +1,99 @@ +# SPDX-License-Identifier: MIT + +import inspect +import platform +import sys +import threading + +from collections.abc import Mapping, Sequence # noqa: F401 +from typing import _GenericAlias + + +PYPY = platform.python_implementation() == "PyPy" +PY_3_10_PLUS = sys.version_info[:2] >= (3, 10) +PY_3_11_PLUS = sys.version_info[:2] >= (3, 11) +PY_3_12_PLUS = sys.version_info[:2] >= (3, 12) +PY_3_13_PLUS = sys.version_info[:2] >= (3, 13) +PY_3_14_PLUS = sys.version_info[:2] >= (3, 14) + + +if PY_3_14_PLUS: + import annotationlib + + # We request forward-ref annotations to not break in the presence of + # forward references. + + def _get_annotations(cls): + return annotationlib.get_annotations( + cls, format=annotationlib.Format.FORWARDREF + ) + +else: + + def _get_annotations(cls): + """ + Get annotations for *cls*. + """ + return cls.__dict__.get("__annotations__", {}) + + +class _AnnotationExtractor: + """ + Extract type annotations from a callable, returning None whenever there + is none. + """ + + __slots__ = ["sig"] + + def __init__(self, callable): + try: + self.sig = inspect.signature(callable) + except (ValueError, TypeError): # inspect failed + self.sig = None + + def get_first_param_type(self): + """ + Return the type annotation of the first argument if it's not empty. + """ + if not self.sig: + return None + + params = list(self.sig.parameters.values()) + if params and params[0].annotation is not inspect.Parameter.empty: + return params[0].annotation + + return None + + def get_return_type(self): + """ + Return the return type if it's not empty. + """ + if ( + self.sig + and self.sig.return_annotation is not inspect.Signature.empty + ): + return self.sig.return_annotation + + return None + + +# Thread-local global to track attrs instances which are already being repr'd. +# This is needed because there is no other (thread-safe) way to pass info +# about the instances that are already being repr'd through the call stack +# in order to ensure we don't perform infinite recursion. +# +# For instance, if an instance contains a dict which contains that instance, +# we need to know that we're already repr'ing the outside instance from within +# the dict's repr() call. +# +# This lives here rather than in _make.py so that the functions in _make.py +# don't have a direct reference to the thread-local in their globals dict. +# If they have such a reference, it breaks cloudpickle. +repr_context = threading.local() + + +def get_generic_base(cl): + """If this is a generic class (A[str]), return the generic base for it.""" + if cl.__class__ is _GenericAlias: + return cl.__origin__ + return None diff --git a/attr/_config.py b/attr/_config.py new file mode 100644 index 0000000000000000000000000000000000000000..4b257726fb1e8b95583ecc3eee8d153336dc4089 --- /dev/null +++ b/attr/_config.py @@ -0,0 +1,31 @@ +# SPDX-License-Identifier: MIT + +__all__ = ["get_run_validators", "set_run_validators"] + +_run_validators = True + + +def set_run_validators(run): + """ + Set whether or not validators are run. By default, they are run. + + .. deprecated:: 21.3.0 It will not be removed, but it also will not be + moved to new ``attrs`` namespace. Use `attrs.validators.set_disabled()` + instead. + """ + if not isinstance(run, bool): + msg = "'run' must be bool." + raise TypeError(msg) + global _run_validators + _run_validators = run + + +def get_run_validators(): + """ + Return whether or not validators are run. + + .. deprecated:: 21.3.0 It will not be removed, but it also will not be + moved to new ``attrs`` namespace. Use `attrs.validators.get_disabled()` + instead. + """ + return _run_validators diff --git a/attr/_funcs.py b/attr/_funcs.py new file mode 100644 index 0000000000000000000000000000000000000000..1adb50021373d9c09fcb9db0641bbc03248d54a3 --- /dev/null +++ b/attr/_funcs.py @@ -0,0 +1,497 @@ +# SPDX-License-Identifier: MIT + + +import copy + +from ._compat import get_generic_base +from ._make import _OBJ_SETATTR, NOTHING, fields +from .exceptions import AttrsAttributeNotFoundError + + +_ATOMIC_TYPES = frozenset( + { + type(None), + bool, + int, + float, + str, + complex, + bytes, + type(...), + type, + range, + property, + } +) + + +def asdict( + inst, + recurse=True, + filter=None, + dict_factory=dict, + retain_collection_types=False, + value_serializer=None, +): + """ + Return the *attrs* attribute values of *inst* as a dict. + + Optionally recurse into other *attrs*-decorated classes. + + Args: + inst: Instance of an *attrs*-decorated class. + + recurse (bool): Recurse into classes that are also *attrs*-decorated. + + filter (~typing.Callable): + A callable whose return code determines whether an attribute or + element is included (`True`) or dropped (`False`). Is called with + the `attrs.Attribute` as the first argument and the value as the + second argument. + + dict_factory (~typing.Callable): + A callable to produce dictionaries from. For example, to produce + ordered dictionaries instead of normal Python dictionaries, pass in + ``collections.OrderedDict``. + + retain_collection_types (bool): + Do not convert to `list` when encountering an attribute whose type + is `tuple` or `set`. Only meaningful if *recurse* is `True`. + + value_serializer (typing.Callable | None): + A hook that is called for every attribute or dict key/value. It + receives the current instance, field and value and must return the + (updated) value. The hook is run *after* the optional *filter* has + been applied. + + Returns: + Return type of *dict_factory*. + + Raises: + attrs.exceptions.NotAnAttrsClassError: + If *cls* is not an *attrs* class. + + .. versionadded:: 16.0.0 *dict_factory* + .. versionadded:: 16.1.0 *retain_collection_types* + .. versionadded:: 20.3.0 *value_serializer* + .. versionadded:: 21.3.0 + If a dict has a collection for a key, it is serialized as a tuple. + """ + attrs = fields(inst.__class__) + rv = dict_factory() + for a in attrs: + v = getattr(inst, a.name) + if filter is not None and not filter(a, v): + continue + + if value_serializer is not None: + v = value_serializer(inst, a, v) + + if recurse is True: + value_type = type(v) + if value_type in _ATOMIC_TYPES: + rv[a.name] = v + elif has(value_type): + rv[a.name] = asdict( + v, + recurse=True, + filter=filter, + dict_factory=dict_factory, + retain_collection_types=retain_collection_types, + value_serializer=value_serializer, + ) + elif issubclass(value_type, (tuple, list, set, frozenset)): + cf = value_type if retain_collection_types is True else list + items = [ + _asdict_anything( + i, + is_key=False, + filter=filter, + dict_factory=dict_factory, + retain_collection_types=retain_collection_types, + value_serializer=value_serializer, + ) + for i in v + ] + try: + rv[a.name] = cf(items) + except TypeError: + if not issubclass(cf, tuple): + raise + # Workaround for TypeError: cf.__new__() missing 1 required + # positional argument (which appears, for a namedturle) + rv[a.name] = cf(*items) + elif issubclass(value_type, dict): + df = dict_factory + rv[a.name] = df( + ( + _asdict_anything( + kk, + is_key=True, + filter=filter, + dict_factory=df, + retain_collection_types=retain_collection_types, + value_serializer=value_serializer, + ), + _asdict_anything( + vv, + is_key=False, + filter=filter, + dict_factory=df, + retain_collection_types=retain_collection_types, + value_serializer=value_serializer, + ), + ) + for kk, vv in v.items() + ) + else: + rv[a.name] = v + else: + rv[a.name] = v + return rv + + +def _asdict_anything( + val, + is_key, + filter, + dict_factory, + retain_collection_types, + value_serializer, +): + """ + ``asdict`` only works on attrs instances, this works on anything. + """ + val_type = type(val) + if val_type in _ATOMIC_TYPES: + rv = val + if value_serializer is not None: + rv = value_serializer(None, None, rv) + elif getattr(val_type, "__attrs_attrs__", None) is not None: + # Attrs class. + rv = asdict( + val, + recurse=True, + filter=filter, + dict_factory=dict_factory, + retain_collection_types=retain_collection_types, + value_serializer=value_serializer, + ) + elif issubclass(val_type, (tuple, list, set, frozenset)): + if retain_collection_types is True: + cf = val.__class__ + elif is_key: + cf = tuple + else: + cf = list + + rv = cf( + [ + _asdict_anything( + i, + is_key=False, + filter=filter, + dict_factory=dict_factory, + retain_collection_types=retain_collection_types, + value_serializer=value_serializer, + ) + for i in val + ] + ) + elif issubclass(val_type, dict): + df = dict_factory + rv = df( + ( + _asdict_anything( + kk, + is_key=True, + filter=filter, + dict_factory=df, + retain_collection_types=retain_collection_types, + value_serializer=value_serializer, + ), + _asdict_anything( + vv, + is_key=False, + filter=filter, + dict_factory=df, + retain_collection_types=retain_collection_types, + value_serializer=value_serializer, + ), + ) + for kk, vv in val.items() + ) + else: + rv = val + if value_serializer is not None: + rv = value_serializer(None, None, rv) + + return rv + + +def astuple( + inst, + recurse=True, + filter=None, + tuple_factory=tuple, + retain_collection_types=False, +): + """ + Return the *attrs* attribute values of *inst* as a tuple. + + Optionally recurse into other *attrs*-decorated classes. + + Args: + inst: Instance of an *attrs*-decorated class. + + recurse (bool): + Recurse into classes that are also *attrs*-decorated. + + filter (~typing.Callable): + A callable whose return code determines whether an attribute or + element is included (`True`) or dropped (`False`). Is called with + the `attrs.Attribute` as the first argument and the value as the + second argument. + + tuple_factory (~typing.Callable): + A callable to produce tuples from. For example, to produce lists + instead of tuples. + + retain_collection_types (bool): + Do not convert to `list` or `dict` when encountering an attribute + which type is `tuple`, `dict` or `set`. Only meaningful if + *recurse* is `True`. + + Returns: + Return type of *tuple_factory* + + Raises: + attrs.exceptions.NotAnAttrsClassError: + If *cls* is not an *attrs* class. + + .. versionadded:: 16.2.0 + """ + attrs = fields(inst.__class__) + rv = [] + retain = retain_collection_types # Very long. :/ + for a in attrs: + v = getattr(inst, a.name) + if filter is not None and not filter(a, v): + continue + value_type = type(v) + if recurse is True: + if value_type in _ATOMIC_TYPES: + rv.append(v) + elif has(value_type): + rv.append( + astuple( + v, + recurse=True, + filter=filter, + tuple_factory=tuple_factory, + retain_collection_types=retain, + ) + ) + elif issubclass(value_type, (tuple, list, set, frozenset)): + cf = v.__class__ if retain is True else list + items = [ + ( + astuple( + j, + recurse=True, + filter=filter, + tuple_factory=tuple_factory, + retain_collection_types=retain, + ) + if has(j.__class__) + else j + ) + for j in v + ] + try: + rv.append(cf(items)) + except TypeError: + if not issubclass(cf, tuple): + raise + # Workaround for TypeError: cf.__new__() missing 1 required + # positional argument (which appears, for a namedturle) + rv.append(cf(*items)) + elif issubclass(value_type, dict): + df = value_type if retain is True else dict + rv.append( + df( + ( + ( + astuple( + kk, + tuple_factory=tuple_factory, + retain_collection_types=retain, + ) + if has(kk.__class__) + else kk + ), + ( + astuple( + vv, + tuple_factory=tuple_factory, + retain_collection_types=retain, + ) + if has(vv.__class__) + else vv + ), + ) + for kk, vv in v.items() + ) + ) + else: + rv.append(v) + else: + rv.append(v) + + return rv if tuple_factory is list else tuple_factory(rv) + + +def has(cls): + """ + Check whether *cls* is a class with *attrs* attributes. + + Args: + cls (type): Class to introspect. + + Raises: + TypeError: If *cls* is not a class. + + Returns: + bool: + """ + attrs = getattr(cls, "__attrs_attrs__", None) + if attrs is not None: + return True + + # No attrs, maybe it's a specialized generic (A[str])? + generic_base = get_generic_base(cls) + if generic_base is not None: + generic_attrs = getattr(generic_base, "__attrs_attrs__", None) + if generic_attrs is not None: + # Stick it on here for speed next time. + cls.__attrs_attrs__ = generic_attrs + return generic_attrs is not None + return False + + +def assoc(inst, **changes): + """ + Copy *inst* and apply *changes*. + + This is different from `evolve` that applies the changes to the arguments + that create the new instance. + + `evolve`'s behavior is preferable, but there are `edge cases`_ where it + doesn't work. Therefore `assoc` is deprecated, but will not be removed. + + .. _`edge cases`: https://github.com/python-attrs/attrs/issues/251 + + Args: + inst: Instance of a class with *attrs* attributes. + + changes: Keyword changes in the new copy. + + Returns: + A copy of inst with *changes* incorporated. + + Raises: + attrs.exceptions.AttrsAttributeNotFoundError: + If *attr_name* couldn't be found on *cls*. + + attrs.exceptions.NotAnAttrsClassError: + If *cls* is not an *attrs* class. + + .. deprecated:: 17.1.0 + Use `attrs.evolve` instead if you can. This function will not be + removed du to the slightly different approach compared to + `attrs.evolve`, though. + """ + new = copy.copy(inst) + attrs = fields(inst.__class__) + for k, v in changes.items(): + a = getattr(attrs, k, NOTHING) + if a is NOTHING: + msg = f"{k} is not an attrs attribute on {new.__class__}." + raise AttrsAttributeNotFoundError(msg) + _OBJ_SETATTR(new, k, v) + return new + + +def resolve_types( + cls, globalns=None, localns=None, attribs=None, include_extras=True +): + """ + Resolve any strings and forward annotations in type annotations. + + This is only required if you need concrete types in :class:`Attribute`'s + *type* field. In other words, you don't need to resolve your types if you + only use them for static type checking. + + With no arguments, names will be looked up in the module in which the class + was created. If this is not what you want, for example, if the name only + exists inside a method, you may pass *globalns* or *localns* to specify + other dictionaries in which to look up these names. See the docs of + `typing.get_type_hints` for more details. + + Args: + cls (type): Class to resolve. + + globalns (dict | None): Dictionary containing global variables. + + localns (dict | None): Dictionary containing local variables. + + attribs (list | None): + List of attribs for the given class. This is necessary when calling + from inside a ``field_transformer`` since *cls* is not an *attrs* + class yet. + + include_extras (bool): + Resolve more accurately, if possible. Pass ``include_extras`` to + ``typing.get_hints``, if supported by the typing module. On + supported Python versions (3.9+), this resolves the types more + accurately. + + Raises: + TypeError: If *cls* is not a class. + + attrs.exceptions.NotAnAttrsClassError: + If *cls* is not an *attrs* class and you didn't pass any attribs. + + NameError: If types cannot be resolved because of missing variables. + + Returns: + *cls* so you can use this function also as a class decorator. Please + note that you have to apply it **after** `attrs.define`. That means the + decorator has to come in the line **before** `attrs.define`. + + .. versionadded:: 20.1.0 + .. versionadded:: 21.1.0 *attribs* + .. versionadded:: 23.1.0 *include_extras* + """ + # Since calling get_type_hints is expensive we cache whether we've + # done it already. + if getattr(cls, "__attrs_types_resolved__", None) != cls: + import typing + + kwargs = { + "globalns": globalns, + "localns": localns, + "include_extras": include_extras, + } + + hints = typing.get_type_hints(cls, **kwargs) + for field in fields(cls) if attribs is None else attribs: + if field.name in hints: + # Since fields have been frozen we must work around it. + _OBJ_SETATTR(field, "type", hints[field.name]) + # We store the class we resolved so that subclasses know they haven't + # been resolved. + cls.__attrs_types_resolved__ = cls + + # Return the class so you can use it as a decorator too. + return cls diff --git a/attr/_make.py b/attr/_make.py new file mode 100644 index 0000000000000000000000000000000000000000..4b32d6a71b0d91f3c4eb9ae615771aa46cae00eb --- /dev/null +++ b/attr/_make.py @@ -0,0 +1,3406 @@ +# SPDX-License-Identifier: MIT + +from __future__ import annotations + +import abc +import contextlib +import copy +import enum +import inspect +import itertools +import linecache +import sys +import types +import unicodedata +import weakref + +from collections.abc import Callable, Mapping +from functools import cached_property +from typing import Any, NamedTuple, TypeVar + +# We need to import _compat itself in addition to the _compat members to avoid +# having the thread-local in the globals here. +from . import _compat, _config, setters +from ._compat import ( + PY_3_10_PLUS, + PY_3_11_PLUS, + PY_3_13_PLUS, + _AnnotationExtractor, + _get_annotations, + get_generic_base, +) +from .exceptions import ( + DefaultAlreadySetError, + FrozenInstanceError, + NotAnAttrsClassError, + UnannotatedAttributeError, +) + + +# This is used at least twice, so cache it here. +_OBJ_SETATTR = object.__setattr__ +_INIT_FACTORY_PAT = "__attr_factory_%s" +_CLASSVAR_PREFIXES = ( + "typing.ClassVar", + "t.ClassVar", + "ClassVar", + "typing_extensions.ClassVar", +) +# we don't use a double-underscore prefix because that triggers +# name mangling when trying to create a slot for the field +# (when slots=True) +_HASH_CACHE_FIELD = "_attrs_cached_hash" + +_EMPTY_METADATA_SINGLETON = types.MappingProxyType({}) + +# Unique object for unequivocal getattr() defaults. +_SENTINEL = object() + +_DEFAULT_ON_SETATTR = setters.pipe(setters.convert, setters.validate) + + +class _Nothing(enum.Enum): + """ + Sentinel to indicate the lack of a value when `None` is ambiguous. + + If extending attrs, you can use ``typing.Literal[NOTHING]`` to show + that a value may be ``NOTHING``. + + .. versionchanged:: 21.1.0 ``bool(NOTHING)`` is now False. + .. versionchanged:: 22.2.0 ``NOTHING`` is now an ``enum.Enum`` variant. + """ + + NOTHING = enum.auto() + + def __repr__(self): + return "NOTHING" + + def __bool__(self): + return False + + +NOTHING = _Nothing.NOTHING +""" +Sentinel to indicate the lack of a value when `None` is ambiguous. + +When using in 3rd party code, use `attrs.NothingType` for type annotations. +""" + + +class _CacheHashWrapper(int): + """ + An integer subclass that pickles / copies as None + + This is used for non-slots classes with ``cache_hash=True``, to avoid + serializing a potentially (even likely) invalid hash value. Since `None` + is the default value for uncalculated hashes, whenever this is copied, + the copy's value for the hash should automatically reset. + + See GH #613 for more details. + """ + + def __reduce__(self, _none_constructor=type(None), _args=()): # noqa: B008 + return _none_constructor, _args + + +def attrib( + default=NOTHING, + validator=None, + repr=True, + cmp=None, + hash=None, + init=True, + metadata=None, + type=None, + converter=None, + factory=None, + kw_only=None, + eq=None, + order=None, + on_setattr=None, + alias=None, +): + """ + Create a new field / attribute on a class. + + Identical to `attrs.field`, except it's not keyword-only. + + Consider using `attrs.field` in new code (``attr.ib`` will *never* go away, + though). + + .. warning:: + + Does **nothing** unless the class is also decorated with + `attr.s` (or similar)! + + + .. versionadded:: 15.2.0 *convert* + .. versionadded:: 16.3.0 *metadata* + .. versionchanged:: 17.1.0 *validator* can be a ``list`` now. + .. versionchanged:: 17.1.0 + *hash* is `None` and therefore mirrors *eq* by default. + .. versionadded:: 17.3.0 *type* + .. deprecated:: 17.4.0 *convert* + .. versionadded:: 17.4.0 + *converter* as a replacement for the deprecated *convert* to achieve + consistency with other noun-based arguments. + .. versionadded:: 18.1.0 + ``factory=f`` is syntactic sugar for ``default=attr.Factory(f)``. + .. versionadded:: 18.2.0 *kw_only* + .. versionchanged:: 19.2.0 *convert* keyword argument removed. + .. versionchanged:: 19.2.0 *repr* also accepts a custom callable. + .. deprecated:: 19.2.0 *cmp* Removal on or after 2021-06-01. + .. versionadded:: 19.2.0 *eq* and *order* + .. versionadded:: 20.1.0 *on_setattr* + .. versionchanged:: 20.3.0 *kw_only* backported to Python 2 + .. versionchanged:: 21.1.0 + *eq*, *order*, and *cmp* also accept a custom callable + .. versionchanged:: 21.1.0 *cmp* undeprecated + .. versionadded:: 22.2.0 *alias* + .. versionchanged:: 25.4.0 + *kw_only* can now be None, and its default is also changed from False to + None. + """ + eq, eq_key, order, order_key = _determine_attrib_eq_order( + cmp, eq, order, True + ) + + if hash is not None and hash is not True and hash is not False: + msg = "Invalid value for hash. Must be True, False, or None." + raise TypeError(msg) + + if factory is not None: + if default is not NOTHING: + msg = ( + "The `default` and `factory` arguments are mutually exclusive." + ) + raise ValueError(msg) + if not callable(factory): + msg = "The `factory` argument must be a callable." + raise ValueError(msg) + default = Factory(factory) + + if metadata is None: + metadata = {} + + # Apply syntactic sugar by auto-wrapping. + if isinstance(on_setattr, (list, tuple)): + on_setattr = setters.pipe(*on_setattr) + + if validator and isinstance(validator, (list, tuple)): + validator = and_(*validator) + + if converter and isinstance(converter, (list, tuple)): + converter = pipe(*converter) + + return _CountingAttr( + default=default, + validator=validator, + repr=repr, + cmp=None, + hash=hash, + init=init, + converter=converter, + metadata=metadata, + type=type, + kw_only=kw_only, + eq=eq, + eq_key=eq_key, + order=order, + order_key=order_key, + on_setattr=on_setattr, + alias=alias, + ) + + +def _compile_and_eval( + script: str, + globs: dict[str, Any] | None, + locs: Mapping[str, object] | None = None, + filename: str = "", +) -> None: + """ + Evaluate the script with the given global (globs) and local (locs) + variables. + """ + bytecode = compile(script, filename, "exec") + eval(bytecode, globs, locs) + + +def _linecache_and_compile( + script: str, + filename: str, + globs: dict[str, Any] | None, + locals: Mapping[str, object] | None = None, +) -> dict[str, Any]: + """ + Cache the script with _linecache_, compile it and return the _locals_. + """ + + locs = {} if locals is None else locals + + # In order of debuggers like PDB being able to step through the code, + # we add a fake linecache entry. + count = 1 + base_filename = filename + while True: + linecache_tuple = ( + len(script), + None, + script.splitlines(True), + filename, + ) + old_val = linecache.cache.setdefault(filename, linecache_tuple) + if old_val == linecache_tuple: + break + + filename = f"{base_filename[:-1]}-{count}>" + count += 1 + + _compile_and_eval(script, globs, locs, filename) + + return locs + + +def _make_attr_tuple_class(cls_name: str, attr_names: list[str]) -> type: + """ + Create a tuple subclass to hold `Attribute`s for an `attrs` class. + + The subclass is a bare tuple with properties for names. + + class MyClassAttributes(tuple): + __slots__ = () + x = property(itemgetter(0)) + """ + attr_class_name = f"{cls_name}Attributes" + body = {} + for i, attr_name in enumerate(attr_names): + + def getter(self, i=i): + return self[i] + + body[attr_name] = property(getter) + return type(attr_class_name, (tuple,), body) + + +# Tuple class for extracted attributes from a class definition. +# `base_attrs` is a subset of `attrs`. +class _Attributes(NamedTuple): + attrs: type + base_attrs: list[Attribute] + base_attrs_map: dict[str, type] + + +def _is_class_var(annot): + """ + Check whether *annot* is a typing.ClassVar. + + The string comparison hack is used to avoid evaluating all string + annotations which would put attrs-based classes at a performance + disadvantage compared to plain old classes. + """ + annot = str(annot) + + # Annotation can be quoted. + if annot.startswith(("'", '"')) and annot.endswith(("'", '"')): + annot = annot[1:-1] + + return annot.startswith(_CLASSVAR_PREFIXES) + + +def _has_own_attribute(cls, attrib_name): + """ + Check whether *cls* defines *attrib_name* (and doesn't just inherit it). + """ + return attrib_name in cls.__dict__ + + +def _collect_base_attrs( + cls, taken_attr_names +) -> tuple[list[Attribute], dict[str, type]]: + """ + Collect attr.ibs from base classes of *cls*, except *taken_attr_names*. + """ + base_attrs = [] + base_attr_map = {} # A dictionary of base attrs to their classes. + + # Traverse the MRO and collect attributes. + for base_cls in reversed(cls.__mro__[1:-1]): + for a in getattr(base_cls, "__attrs_attrs__", []): + if a.inherited or a.name in taken_attr_names: + continue + + a = a.evolve(inherited=True) # noqa: PLW2901 + base_attrs.append(a) + base_attr_map[a.name] = base_cls + + # For each name, only keep the freshest definition i.e. the furthest at the + # back. base_attr_map is fine because it gets overwritten with every new + # instance. + filtered = [] + seen = set() + for a in reversed(base_attrs): + if a.name in seen: + continue + filtered.insert(0, a) + seen.add(a.name) + + return filtered, base_attr_map + + +def _collect_base_attrs_broken(cls, taken_attr_names): + """ + Collect attr.ibs from base classes of *cls*, except *taken_attr_names*. + + N.B. *taken_attr_names* will be mutated. + + Adhere to the old incorrect behavior. + + Notably it collects from the front and considers inherited attributes which + leads to the buggy behavior reported in #428. + """ + base_attrs = [] + base_attr_map = {} # A dictionary of base attrs to their classes. + + # Traverse the MRO and collect attributes. + for base_cls in cls.__mro__[1:-1]: + for a in getattr(base_cls, "__attrs_attrs__", []): + if a.name in taken_attr_names: + continue + + a = a.evolve(inherited=True) # noqa: PLW2901 + taken_attr_names.add(a.name) + base_attrs.append(a) + base_attr_map[a.name] = base_cls + + return base_attrs, base_attr_map + + +def _transform_attrs( + cls, + these, + auto_attribs, + kw_only, + collect_by_mro, + field_transformer, +) -> _Attributes: + """ + Transform all `_CountingAttr`s on a class into `Attribute`s. + + If *these* is passed, use that and don't look for them on the class. + + If *collect_by_mro* is True, collect them in the correct MRO order, + otherwise use the old -- incorrect -- order. See #428. + + Return an `_Attributes`. + """ + cd = cls.__dict__ + anns = _get_annotations(cls) + + if these is not None: + ca_list = list(these.items()) + elif auto_attribs is True: + ca_names = { + name + for name, attr in cd.items() + if attr.__class__ is _CountingAttr + } + ca_list = [] + annot_names = set() + for attr_name, type in anns.items(): + if _is_class_var(type): + continue + annot_names.add(attr_name) + a = cd.get(attr_name, NOTHING) + + if a.__class__ is not _CountingAttr: + a = attrib(a) + ca_list.append((attr_name, a)) + + unannotated = ca_names - annot_names + if unannotated: + raise UnannotatedAttributeError( + "The following `attr.ib`s lack a type annotation: " + + ", ".join( + sorted(unannotated, key=lambda n: cd.get(n).counter) + ) + + "." + ) + else: + ca_list = sorted( + ( + (name, attr) + for name, attr in cd.items() + if attr.__class__ is _CountingAttr + ), + key=lambda e: e[1].counter, + ) + + fca = Attribute.from_counting_attr + no = ClassProps.KeywordOnly.NO + own_attrs = [ + fca( + attr_name, + ca, + kw_only is not no, + anns.get(attr_name), + ) + for attr_name, ca in ca_list + ] + + if collect_by_mro: + base_attrs, base_attr_map = _collect_base_attrs( + cls, {a.name for a in own_attrs} + ) + else: + base_attrs, base_attr_map = _collect_base_attrs_broken( + cls, {a.name for a in own_attrs} + ) + + if kw_only is ClassProps.KeywordOnly.FORCE: + own_attrs = [a.evolve(kw_only=True) for a in own_attrs] + base_attrs = [a.evolve(kw_only=True) for a in base_attrs] + + attrs = base_attrs + own_attrs + + # Resolve default field alias before executing field_transformer, so that + # the transformer receives fully populated Attribute objects with usable + # alias values. + for a in attrs: + if not a.alias: + # Evolve is very slow, so we hold our nose and do it dirty. + _OBJ_SETATTR.__get__(a)("alias", _default_init_alias_for(a.name)) + _OBJ_SETATTR.__get__(a)("alias_is_default", True) + + if field_transformer is not None: + attrs = tuple(field_transformer(cls, attrs)) + + # Check attr order after executing the field_transformer. + # Mandatory vs non-mandatory attr order only matters when they are part of + # the __init__ signature and when they aren't kw_only (which are moved to + # the end and can be mandatory or non-mandatory in any order, as they will + # be specified as keyword args anyway). Check the order of those attrs: + had_default = False + for a in (a for a in attrs if a.init is not False and a.kw_only is False): + if had_default is True and a.default is NOTHING: + msg = f"No mandatory attributes allowed after an attribute with a default value or factory. Attribute in question: {a!r}" + raise ValueError(msg) + + if had_default is False and a.default is not NOTHING: + had_default = True + + # Resolve default field alias for any new attributes that the + # field_transformer may have added without setting an alias. + for a in attrs: + if not a.alias: + _OBJ_SETATTR.__get__(a)("alias", _default_init_alias_for(a.name)) + _OBJ_SETATTR.__get__(a)("alias_is_default", True) + + # Create AttrsClass *after* applying the field_transformer since it may + # add or remove attributes! + attr_names = [a.name for a in attrs] + AttrsClass = _make_attr_tuple_class(cls.__name__, attr_names) + + return _Attributes(AttrsClass(attrs), base_attrs, base_attr_map) + + +def _make_cached_property_getattr(cached_properties, original_getattr, cls): + lines = [ + # Wrapped to get `__class__` into closure cell for super() + # (It will be replaced with the newly constructed class after construction). + "def wrapper(_cls):", + " __class__ = _cls", + " def __getattr__(self, item, cached_properties=cached_properties, original_getattr=original_getattr, _cached_setattr_get=_cached_setattr_get):", + " func = cached_properties.get(item)", + " if func is not None:", + " result = func(self)", + " _setter = _cached_setattr_get(self)", + " _setter(item, result)", + " return result", + ] + if original_getattr is not None: + lines.append( + " return original_getattr(self, item)", + ) + else: + lines.extend( + [ + " try:", + " return super().__getattribute__(item)", + " except AttributeError:", + " if not hasattr(super(), '__getattr__'):", + " raise", + " return super().__getattr__(item)", + " original_error = f\"'{self.__class__.__name__}' object has no attribute '{item}'\"", + " raise AttributeError(original_error)", + ] + ) + + lines.extend( + [ + " return __getattr__", + "__getattr__ = wrapper(_cls)", + ] + ) + + unique_filename = _generate_unique_filename(cls, "getattr") + + glob = { + "cached_properties": cached_properties, + "_cached_setattr_get": _OBJ_SETATTR.__get__, + "original_getattr": original_getattr, + } + + return _linecache_and_compile( + "\n".join(lines), unique_filename, glob, locals={"_cls": cls} + )["__getattr__"] + + +def _frozen_setattrs(self, name, value): + """ + Attached to frozen classes as __setattr__. + """ + if isinstance(self, BaseException) and name in ( + "__cause__", + "__context__", + "__traceback__", + "__suppress_context__", + "__notes__", + ): + BaseException.__setattr__(self, name, value) + return + + raise FrozenInstanceError + + +def _frozen_delattrs(self, name): + """ + Attached to frozen classes as __delattr__. + """ + if isinstance(self, BaseException) and name == "__notes__": + BaseException.__delattr__(self, name) + return + + raise FrozenInstanceError + + +def evolve(*args, **changes): + """ + Create a new instance, based on the first positional argument with + *changes* applied. + + .. tip:: + + On Python 3.13 and later, you can also use `copy.replace` instead. + + Args: + + inst: + Instance of a class with *attrs* attributes. *inst* must be passed + as a positional argument. + + changes: + Keyword changes in the new copy. + + Returns: + A copy of inst with *changes* incorporated. + + Raises: + TypeError: + If *attr_name* couldn't be found in the class ``__init__``. + + attrs.exceptions.NotAnAttrsClassError: + If *cls* is not an *attrs* class. + + .. versionadded:: 17.1.0 + .. deprecated:: 23.1.0 + It is now deprecated to pass the instance using the keyword argument + *inst*. It will raise a warning until at least April 2024, after which + it will become an error. Always pass the instance as a positional + argument. + .. versionchanged:: 24.1.0 + *inst* can't be passed as a keyword argument anymore. + """ + try: + (inst,) = args + except ValueError: + msg = ( + f"evolve() takes 1 positional argument, but {len(args)} were given" + ) + raise TypeError(msg) from None + + cls = inst.__class__ + attrs = fields(cls) + for a in attrs: + if not a.init: + continue + attr_name = a.name # To deal with private attributes. + init_name = a.alias + if init_name not in changes: + changes[init_name] = getattr(inst, attr_name) + + return cls(**changes) + + +class _ClassBuilder: + """ + Iteratively build *one* class. + """ + + __slots__ = ( + "_add_method_dunders", + "_attr_names", + "_attrs", + "_base_attr_map", + "_base_names", + "_cache_hash", + "_cls", + "_cls_dict", + "_delete_attribs", + "_frozen", + "_has_custom_setattr", + "_has_post_init", + "_has_pre_init", + "_is_exc", + "_on_setattr", + "_pre_init_has_args", + "_repr_added", + "_script_snippets", + "_slots", + "_weakref_slot", + "_wrote_own_setattr", + ) + + def __init__( + self, + cls: type, + these, + auto_attribs: bool, + props: ClassProps, + has_custom_setattr: bool, + ): + attrs, base_attrs, base_map = _transform_attrs( + cls, + these, + auto_attribs, + props.kw_only, + props.collected_fields_by_mro, + props.field_transformer, + ) + + self._cls = cls + self._cls_dict = dict(cls.__dict__) if props.is_slotted else {} + self._attrs = attrs + self._base_names = {a.name for a in base_attrs} + self._base_attr_map = base_map + self._attr_names = tuple(a.name for a in attrs) + self._slots = props.is_slotted + self._frozen = props.is_frozen + self._weakref_slot = props.has_weakref_slot + self._cache_hash = ( + props.hashability is ClassProps.Hashability.HASHABLE_CACHED + ) + self._has_pre_init = bool(getattr(cls, "__attrs_pre_init__", False)) + self._pre_init_has_args = False + if self._has_pre_init: + # Check if the pre init method has more arguments than just `self` + # We want to pass arguments if pre init expects arguments + pre_init_func = cls.__attrs_pre_init__ + pre_init_signature = inspect.signature(pre_init_func) + self._pre_init_has_args = len(pre_init_signature.parameters) > 1 + self._has_post_init = bool(getattr(cls, "__attrs_post_init__", False)) + self._delete_attribs = not bool(these) + self._is_exc = props.is_exception + self._on_setattr = props.on_setattr_hook + + self._has_custom_setattr = has_custom_setattr + self._wrote_own_setattr = False + + self._cls_dict["__attrs_attrs__"] = self._attrs + self._cls_dict["__attrs_props__"] = props + + if props.is_frozen: + self._cls_dict["__setattr__"] = _frozen_setattrs + self._cls_dict["__delattr__"] = _frozen_delattrs + + self._wrote_own_setattr = True + elif self._on_setattr in ( + _DEFAULT_ON_SETATTR, + setters.validate, + setters.convert, + ): + has_validator = has_converter = False + for a in attrs: + if a.validator is not None: + has_validator = True + if a.converter is not None: + has_converter = True + + if has_validator and has_converter: + break + if ( + ( + self._on_setattr == _DEFAULT_ON_SETATTR + and not (has_validator or has_converter) + ) + or (self._on_setattr == setters.validate and not has_validator) + or (self._on_setattr == setters.convert and not has_converter) + ): + # If class-level on_setattr is set to convert + validate, but + # there's no field to convert or validate, pretend like there's + # no on_setattr. + self._on_setattr = None + + if props.added_pickling: + ( + self._cls_dict["__getstate__"], + self._cls_dict["__setstate__"], + ) = self._make_getstate_setstate() + + # tuples of script, globs, hook + self._script_snippets: list[ + tuple[str, dict, Callable[[dict, dict], Any]] + ] = [] + self._repr_added = False + + # We want to only do this check once; in 99.9% of cases these + # exist. + if not hasattr(self._cls, "__module__") or not hasattr( + self._cls, "__qualname__" + ): + self._add_method_dunders = self._add_method_dunders_safe + else: + self._add_method_dunders = self._add_method_dunders_unsafe + + def __repr__(self): + return f"<_ClassBuilder(cls={self._cls.__name__})>" + + def _eval_snippets(self) -> None: + """ + Evaluate any registered snippets in one go. + """ + script = "\n".join([snippet[0] for snippet in self._script_snippets]) + globs = {} + for _, snippet_globs, _ in self._script_snippets: + globs.update(snippet_globs) + + locs = _linecache_and_compile( + script, + _generate_unique_filename(self._cls, "methods"), + globs, + ) + + for _, _, hook in self._script_snippets: + hook(self._cls_dict, locs) + + def build_class(self): + """ + Finalize class based on the accumulated configuration. + + Builder cannot be used after calling this method. + """ + self._eval_snippets() + if self._slots is True: + cls = self._create_slots_class() + self._cls.__attrs_base_of_slotted__ = weakref.ref(cls) + else: + cls = self._patch_original_class() + if PY_3_10_PLUS: + cls = abc.update_abstractmethods(cls) + + # The method gets only called if it's not inherited from a base class. + # _has_own_attribute does NOT work properly for classmethods. + if ( + getattr(cls, "__attrs_init_subclass__", None) + and "__attrs_init_subclass__" not in cls.__dict__ + ): + cls.__attrs_init_subclass__() + + return cls + + def _patch_original_class(self): + """ + Apply accumulated methods and return the class. + """ + cls = self._cls + base_names = self._base_names + + # Clean class of attribute definitions (`attr.ib()`s). + if self._delete_attribs: + for name in self._attr_names: + if ( + name not in base_names + and getattr(cls, name, _SENTINEL) is not _SENTINEL + ): + # An AttributeError can happen if a base class defines a + # class variable and we want to set an attribute with the + # same name by using only a type annotation. + with contextlib.suppress(AttributeError): + delattr(cls, name) + + # Attach our dunder methods. + for name, value in self._cls_dict.items(): + setattr(cls, name, value) + + # If we've inherited an attrs __setattr__ and don't write our own, + # reset it to object's. + if not self._wrote_own_setattr and getattr( + cls, "__attrs_own_setattr__", False + ): + cls.__attrs_own_setattr__ = False + + if not self._has_custom_setattr: + cls.__setattr__ = _OBJ_SETATTR + + return cls + + def _create_slots_class(self): + """ + Build and return a new class with a `__slots__` attribute. + """ + cd = { + k: v + for k, v in self._cls_dict.items() + if k not in (*tuple(self._attr_names), "__dict__", "__weakref__") + } + + # 3.14.0rc2+ + if hasattr(sys, "_clear_type_descriptors"): + sys._clear_type_descriptors(self._cls) + + # If our class doesn't have its own implementation of __setattr__ + # (either from the user or by us), check the bases, if one of them has + # an attrs-made __setattr__, that needs to be reset. We don't walk the + # MRO because we only care about our immediate base classes. + # XXX: This can be confused by subclassing a slotted attrs class with + # XXX: a non-attrs class and subclass the resulting class with an attrs + # XXX: class. See `test_slotted_confused` for details. For now that's + # XXX: OK with us. + if not self._wrote_own_setattr: + cd["__attrs_own_setattr__"] = False + + if not self._has_custom_setattr: + for base_cls in self._cls.__bases__: + if base_cls.__dict__.get("__attrs_own_setattr__", False): + cd["__setattr__"] = _OBJ_SETATTR + break + + # Traverse the MRO to collect existing slots + # and check for an existing __weakref__. + existing_slots = {} + weakref_inherited = False + for base_cls in self._cls.__mro__[1:-1]: + if base_cls.__dict__.get("__weakref__", None) is not None: + weakref_inherited = True + existing_slots.update( + { + name: getattr(base_cls, name) + for name in getattr(base_cls, "__slots__", []) + } + ) + + base_names = set(self._base_names) + + names = self._attr_names + if ( + self._weakref_slot + and "__weakref__" not in getattr(self._cls, "__slots__", ()) + and "__weakref__" not in names + and not weakref_inherited + ): + names += ("__weakref__",) + + cached_properties = { + name: cached_prop.func + for name, cached_prop in cd.items() + if isinstance(cached_prop, cached_property) + } + + # Collect methods with a `__class__` reference that are shadowed in the new class. + # To know to update them. + additional_closure_functions_to_update = [] + if cached_properties: + class_annotations = _get_annotations(self._cls) + for name, func in cached_properties.items(): + # Add cached properties to names for slotting. + names += (name,) + # Clear out function from class to avoid clashing. + del cd[name] + additional_closure_functions_to_update.append(func) + annotation = inspect.signature(func).return_annotation + if annotation is not inspect.Parameter.empty: + class_annotations[name] = annotation + + original_getattr = cd.get("__getattr__") + if original_getattr is not None: + additional_closure_functions_to_update.append(original_getattr) + + cd["__getattr__"] = _make_cached_property_getattr( + cached_properties, original_getattr, self._cls + ) + + # We only add the names of attributes that aren't inherited. + # Setting __slots__ to inherited attributes wastes memory. + slot_names = [name for name in names if name not in base_names] + + # There are slots for attributes from current class + # that are defined in parent classes. + # As their descriptors may be overridden by a child class, + # we collect them here and update the class dict + reused_slots = { + slot: slot_descriptor + for slot, slot_descriptor in existing_slots.items() + if slot in slot_names + } + slot_names = [name for name in slot_names if name not in reused_slots] + cd.update(reused_slots) + if self._cache_hash: + slot_names.append(_HASH_CACHE_FIELD) + + cd["__slots__"] = tuple(slot_names) + + cd["__qualname__"] = self._cls.__qualname__ + + # Create new class based on old class and our methods. + cls = type(self._cls)(self._cls.__name__, self._cls.__bases__, cd) + + # The following is a fix for + # . + # If a method mentions `__class__` or uses the no-arg super(), the + # compiler will bake a reference to the class in the method itself + # as `method.__closure__`. Since we replace the class with a + # clone, we rewrite these references so it keeps working. + for item in itertools.chain( + cls.__dict__.values(), additional_closure_functions_to_update + ): + if isinstance(item, (classmethod, staticmethod)): + # Class- and staticmethods hide their functions inside. + # These might need to be rewritten as well. + closure_cells = getattr(item.__func__, "__closure__", None) + elif isinstance(item, property): + # Workaround for property `super()` shortcut (PY3-only). + # There is no universal way for other descriptors. + closure_cells = getattr(item.fget, "__closure__", None) + else: + closure_cells = getattr(item, "__closure__", None) + + if not closure_cells: # Catch None or the empty list. + continue + for cell in closure_cells: + try: + match = cell.cell_contents is self._cls + except ValueError: # noqa: PERF203 + # ValueError: Cell is empty + pass + else: + if match: + cell.cell_contents = cls + return cls + + def add_repr(self, ns): + script, globs = _make_repr_script(self._attrs, ns) + + def _attach_repr(cls_dict, globs): + cls_dict["__repr__"] = self._add_method_dunders(globs["__repr__"]) + + self._script_snippets.append((script, globs, _attach_repr)) + self._repr_added = True + return self + + def add_str(self): + if not self._repr_added: + msg = "__str__ can only be generated if a __repr__ exists." + raise ValueError(msg) + + def __str__(self): + return self.__repr__() + + self._cls_dict["__str__"] = self._add_method_dunders(__str__) + return self + + def _make_getstate_setstate(self): + """ + Create custom __setstate__ and __getstate__ methods. + """ + # __weakref__ is not writable. + state_attr_names = tuple( + an for an in self._attr_names if an != "__weakref__" + ) + + def slots_getstate(self): + """ + Automatically created by attrs. + """ + return {name: getattr(self, name) for name in state_attr_names} + + hash_caching_enabled = self._cache_hash + + def slots_setstate(self, state): + """ + Automatically created by attrs. + """ + __bound_setattr = _OBJ_SETATTR.__get__(self) + if isinstance(state, tuple): + # Backward compatibility with attrs instances pickled with + # attrs versions before v22.2.0 which stored tuples. + for name, value in zip(state_attr_names, state): + __bound_setattr(name, value) + else: + for name in state_attr_names: + if name in state: + __bound_setattr(name, state[name]) + + # The hash code cache is not included when the object is + # serialized, but it still needs to be initialized to None to + # indicate that the first call to __hash__ should be a cache + # miss. + if hash_caching_enabled: + __bound_setattr(_HASH_CACHE_FIELD, None) + + return slots_getstate, slots_setstate + + def make_unhashable(self): + self._cls_dict["__hash__"] = None + return self + + def add_hash(self): + script, globs = _make_hash_script( + self._cls, + self._attrs, + frozen=self._frozen, + cache_hash=self._cache_hash, + ) + + def attach_hash(cls_dict: dict, locs: dict) -> None: + cls_dict["__hash__"] = self._add_method_dunders(locs["__hash__"]) + + self._script_snippets.append((script, globs, attach_hash)) + + return self + + def add_init(self): + script, globs, annotations = _make_init_script( + self._cls, + self._attrs, + self._has_pre_init, + self._pre_init_has_args, + self._has_post_init, + self._frozen, + self._slots, + self._cache_hash, + self._base_attr_map, + self._is_exc, + self._on_setattr, + attrs_init=False, + ) + + def _attach_init(cls_dict, globs): + init = globs["__init__"] + init.__annotations__ = annotations + cls_dict["__init__"] = self._add_method_dunders(init) + + self._script_snippets.append((script, globs, _attach_init)) + + return self + + def add_replace(self): + self._cls_dict["__replace__"] = self._add_method_dunders(evolve) + return self + + def add_match_args(self): + self._cls_dict["__match_args__"] = tuple( + field.name + for field in self._attrs + if field.init and not field.kw_only + ) + + def add_attrs_init(self): + script, globs, annotations = _make_init_script( + self._cls, + self._attrs, + self._has_pre_init, + self._pre_init_has_args, + self._has_post_init, + self._frozen, + self._slots, + self._cache_hash, + self._base_attr_map, + self._is_exc, + self._on_setattr, + attrs_init=True, + ) + + def _attach_attrs_init(cls_dict, globs): + init = globs["__attrs_init__"] + init.__annotations__ = annotations + cls_dict["__attrs_init__"] = self._add_method_dunders(init) + + self._script_snippets.append((script, globs, _attach_attrs_init)) + + return self + + def add_eq(self): + cd = self._cls_dict + + script, globs = _make_eq_script(self._attrs) + + def _attach_eq(cls_dict, globs): + cls_dict["__eq__"] = self._add_method_dunders(globs["__eq__"]) + + self._script_snippets.append((script, globs, _attach_eq)) + + cd["__ne__"] = __ne__ + + return self + + def add_order(self): + cd = self._cls_dict + + cd["__lt__"], cd["__le__"], cd["__gt__"], cd["__ge__"] = ( + self._add_method_dunders(meth) + for meth in _make_order(self._cls, self._attrs) + ) + + return self + + def add_setattr(self): + sa_attrs = {} + for a in self._attrs: + on_setattr = a.on_setattr or self._on_setattr + if on_setattr and on_setattr is not setters.NO_OP: + sa_attrs[a.name] = a, on_setattr + + if not sa_attrs: + return self + + if self._has_custom_setattr: + # We need to write a __setattr__ but there already is one! + msg = "Can't combine custom __setattr__ with on_setattr hooks." + raise ValueError(msg) + + # docstring comes from _add_method_dunders + def __setattr__(self, name, val): + try: + a, hook = sa_attrs[name] + except KeyError: + nval = val + else: + nval = hook(self, a, val) + + _OBJ_SETATTR(self, name, nval) + + self._cls_dict["__attrs_own_setattr__"] = True + self._cls_dict["__setattr__"] = self._add_method_dunders(__setattr__) + self._wrote_own_setattr = True + + return self + + def _add_method_dunders_unsafe(self, method: Callable) -> Callable: + """ + Add __module__ and __qualname__ to a *method*. + """ + method.__module__ = self._cls.__module__ + + method.__qualname__ = f"{self._cls.__qualname__}.{method.__name__}" + + method.__doc__ = ( + f"Method generated by attrs for class {self._cls.__qualname__}." + ) + + return method + + def _add_method_dunders_safe(self, method: Callable) -> Callable: + """ + Add __module__ and __qualname__ to a *method* if possible. + """ + with contextlib.suppress(AttributeError): + method.__module__ = self._cls.__module__ + + with contextlib.suppress(AttributeError): + method.__qualname__ = f"{self._cls.__qualname__}.{method.__name__}" + + with contextlib.suppress(AttributeError): + method.__doc__ = f"Method generated by attrs for class {self._cls.__qualname__}." + + return method + + +def _determine_attrs_eq_order(cmp, eq, order, default_eq): + """ + Validate the combination of *cmp*, *eq*, and *order*. Derive the effective + values of eq and order. If *eq* is None, set it to *default_eq*. + """ + if cmp is not None and any((eq is not None, order is not None)): + msg = "Don't mix `cmp` with `eq' and `order`." + raise ValueError(msg) + + # cmp takes precedence due to bw-compatibility. + if cmp is not None: + return cmp, cmp + + # If left None, equality is set to the specified default and ordering + # mirrors equality. + if eq is None: + eq = default_eq + + if order is None: + order = eq + + if eq is False and order is True: + msg = "`order` can only be True if `eq` is True too." + raise ValueError(msg) + + return eq, order + + +def _determine_attrib_eq_order(cmp, eq, order, default_eq): + """ + Validate the combination of *cmp*, *eq*, and *order*. Derive the effective + values of eq and order. If *eq* is None, set it to *default_eq*. + """ + if cmp is not None and any((eq is not None, order is not None)): + msg = "Don't mix `cmp` with `eq' and `order`." + raise ValueError(msg) + + def decide_callable_or_boolean(value): + """ + Decide whether a key function is used. + """ + if callable(value): + value, key = True, value + else: + key = None + return value, key + + # cmp takes precedence due to bw-compatibility. + if cmp is not None: + cmp, cmp_key = decide_callable_or_boolean(cmp) + return cmp, cmp_key, cmp, cmp_key + + # If left None, equality is set to the specified default and ordering + # mirrors equality. + if eq is None: + eq, eq_key = default_eq, None + else: + eq, eq_key = decide_callable_or_boolean(eq) + + if order is None: + order, order_key = eq, eq_key + else: + order, order_key = decide_callable_or_boolean(order) + + if eq is False and order is True: + msg = "`order` can only be True if `eq` is True too." + raise ValueError(msg) + + return eq, eq_key, order, order_key + + +def _determine_whether_to_implement( + cls, flag, auto_detect, dunders, default=True +): + """ + Check whether we should implement a set of methods for *cls*. + + *flag* is the argument passed into @attr.s like 'init', *auto_detect* the + same as passed into @attr.s and *dunders* is a tuple of attribute names + whose presence signal that the user has implemented it themselves. + + Return *default* if no reason for either for or against is found. + """ + if flag is True or flag is False: + return flag + + if flag is None and auto_detect is False: + return default + + # Logically, flag is None and auto_detect is True here. + for dunder in dunders: + if _has_own_attribute(cls, dunder): + return False + + return default + + +def attrs( + maybe_cls=None, + these=None, + repr_ns=None, + repr=None, + cmp=None, + hash=None, + init=None, + slots=False, + frozen=False, + weakref_slot=True, + str=False, + auto_attribs=False, + kw_only=False, + cache_hash=False, + auto_exc=False, + eq=None, + order=None, + auto_detect=False, + collect_by_mro=False, + getstate_setstate=None, + on_setattr=None, + field_transformer=None, + match_args=True, + unsafe_hash=None, + force_kw_only=True, +): + r""" + A class decorator that adds :term:`dunder methods` according to the + specified attributes using `attr.ib` or the *these* argument. + + Consider using `attrs.define` / `attrs.frozen` in new code (``attr.s`` will + *never* go away, though). + + Args: + repr_ns (str): + When using nested classes, there was no way in Python 2 to + automatically detect that. This argument allows to set a custom + name for a more meaningful ``repr`` output. This argument is + pointless in Python 3 and is therefore deprecated. + + .. caution:: + Refer to `attrs.define` for the rest of the parameters, but note that they + can have different defaults. + + Notably, leaving *on_setattr* as `None` will **not** add any hooks. + + .. versionadded:: 16.0.0 *slots* + .. versionadded:: 16.1.0 *frozen* + .. versionadded:: 16.3.0 *str* + .. versionadded:: 16.3.0 Support for ``__attrs_post_init__``. + .. versionchanged:: 17.1.0 + *hash* supports `None` as value which is also the default now. + .. versionadded:: 17.3.0 *auto_attribs* + .. versionchanged:: 18.1.0 + If *these* is passed, no attributes are deleted from the class body. + .. versionchanged:: 18.1.0 If *these* is ordered, the order is retained. + .. versionadded:: 18.2.0 *weakref_slot* + .. deprecated:: 18.2.0 + ``__lt__``, ``__le__``, ``__gt__``, and ``__ge__`` now raise a + `DeprecationWarning` if the classes compared are subclasses of + each other. ``__eq`` and ``__ne__`` never tried to compared subclasses + to each other. + .. versionchanged:: 19.2.0 + ``__lt__``, ``__le__``, ``__gt__``, and ``__ge__`` now do not consider + subclasses comparable anymore. + .. versionadded:: 18.2.0 *kw_only* + .. versionadded:: 18.2.0 *cache_hash* + .. versionadded:: 19.1.0 *auto_exc* + .. deprecated:: 19.2.0 *cmp* Removal on or after 2021-06-01. + .. versionadded:: 19.2.0 *eq* and *order* + .. versionadded:: 20.1.0 *auto_detect* + .. versionadded:: 20.1.0 *collect_by_mro* + .. versionadded:: 20.1.0 *getstate_setstate* + .. versionadded:: 20.1.0 *on_setattr* + .. versionadded:: 20.3.0 *field_transformer* + .. versionchanged:: 21.1.0 + ``init=False`` injects ``__attrs_init__`` + .. versionchanged:: 21.1.0 Support for ``__attrs_pre_init__`` + .. versionchanged:: 21.1.0 *cmp* undeprecated + .. versionadded:: 21.3.0 *match_args* + .. versionadded:: 22.2.0 + *unsafe_hash* as an alias for *hash* (for :pep:`681` compliance). + .. deprecated:: 24.1.0 *repr_ns* + .. versionchanged:: 24.1.0 + Instances are not compared as tuples of attributes anymore, but using a + big ``and`` condition. This is faster and has more correct behavior for + uncomparable values like `math.nan`. + .. versionadded:: 24.1.0 + If a class has an *inherited* classmethod called + ``__attrs_init_subclass__``, it is executed after the class is created. + .. deprecated:: 24.1.0 *hash* is deprecated in favor of *unsafe_hash*. + .. versionchanged:: 25.4.0 + *kw_only* now only applies to attributes defined in the current class, + and respects attribute-level ``kw_only=False`` settings. + .. versionadded:: 25.4.0 *force_kw_only* + """ + if repr_ns is not None: + import warnings + + warnings.warn( + DeprecationWarning( + "The `repr_ns` argument is deprecated and will be removed in or after August 2025." + ), + stacklevel=2, + ) + + eq_, order_ = _determine_attrs_eq_order(cmp, eq, order, None) + + # unsafe_hash takes precedence due to PEP 681. + if unsafe_hash is not None: + hash = unsafe_hash + + if isinstance(on_setattr, (list, tuple)): + on_setattr = setters.pipe(*on_setattr) + + def wrap(cls): + nonlocal hash + is_frozen = frozen or _has_frozen_base_class(cls) + is_exc = auto_exc is True and issubclass(cls, BaseException) + has_own_setattr = auto_detect and _has_own_attribute( + cls, "__setattr__" + ) + + if has_own_setattr and is_frozen: + msg = "Can't freeze a class with a custom __setattr__." + raise ValueError(msg) + + eq = not is_exc and _determine_whether_to_implement( + cls, eq_, auto_detect, ("__eq__", "__ne__") + ) + + Hashability = ClassProps.Hashability + + if is_exc: + hashability = Hashability.LEAVE_ALONE + elif hash is True: + hashability = ( + Hashability.HASHABLE_CACHED + if cache_hash + else Hashability.HASHABLE + ) + elif hash is False: + hashability = Hashability.LEAVE_ALONE + elif hash is None: + if auto_detect is True and _has_own_attribute(cls, "__hash__"): + hashability = Hashability.LEAVE_ALONE + elif eq is True and is_frozen is True: + hashability = ( + Hashability.HASHABLE_CACHED + if cache_hash + else Hashability.HASHABLE + ) + elif eq is False: + hashability = Hashability.LEAVE_ALONE + else: + hashability = Hashability.UNHASHABLE + else: + msg = "Invalid value for hash. Must be True, False, or None." + raise TypeError(msg) + + KeywordOnly = ClassProps.KeywordOnly + if kw_only: + kwo = KeywordOnly.FORCE if force_kw_only else KeywordOnly.YES + else: + kwo = KeywordOnly.NO + + props = ClassProps( + is_exception=is_exc, + is_frozen=is_frozen, + is_slotted=slots, + collected_fields_by_mro=collect_by_mro, + added_init=_determine_whether_to_implement( + cls, init, auto_detect, ("__init__",) + ), + added_repr=_determine_whether_to_implement( + cls, repr, auto_detect, ("__repr__",) + ), + added_eq=eq, + added_ordering=not is_exc + and _determine_whether_to_implement( + cls, + order_, + auto_detect, + ("__lt__", "__le__", "__gt__", "__ge__"), + ), + hashability=hashability, + added_match_args=match_args, + kw_only=kwo, + has_weakref_slot=weakref_slot, + added_str=str, + added_pickling=_determine_whether_to_implement( + cls, + getstate_setstate, + auto_detect, + ("__getstate__", "__setstate__"), + default=slots, + ), + on_setattr_hook=on_setattr, + field_transformer=field_transformer, + ) + + if not props.is_hashable and cache_hash: + msg = "Invalid value for cache_hash. To use hash caching, hashing must be either explicitly or implicitly enabled." + raise TypeError(msg) + + builder = _ClassBuilder( + cls, + these, + auto_attribs=auto_attribs, + props=props, + has_custom_setattr=has_own_setattr, + ) + + if props.added_repr: + builder.add_repr(repr_ns) + + if props.added_str: + builder.add_str() + + if props.added_eq: + builder.add_eq() + if props.added_ordering: + builder.add_order() + + if not frozen: + builder.add_setattr() + + if props.is_hashable: + builder.add_hash() + elif props.hashability is Hashability.UNHASHABLE: + builder.make_unhashable() + + if props.added_init: + builder.add_init() + else: + builder.add_attrs_init() + if cache_hash: + msg = "Invalid value for cache_hash. To use hash caching, init must be True." + raise TypeError(msg) + + if PY_3_13_PLUS and not _has_own_attribute(cls, "__replace__"): + builder.add_replace() + + if ( + PY_3_10_PLUS + and match_args + and not _has_own_attribute(cls, "__match_args__") + ): + builder.add_match_args() + + return builder.build_class() + + # maybe_cls's type depends on the usage of the decorator. It's a class + # if it's used as `@attrs` but `None` if used as `@attrs()`. + if maybe_cls is None: + return wrap + + return wrap(maybe_cls) + + +_attrs = attrs +""" +Internal alias so we can use it in functions that take an argument called +*attrs*. +""" + + +def _has_frozen_base_class(cls): + """ + Check whether *cls* has a frozen ancestor by looking at its + __setattr__. + """ + return cls.__setattr__ is _frozen_setattrs + + +def _generate_unique_filename(cls: type, func_name: str) -> str: + """ + Create a "filename" suitable for a function being generated. + """ + return ( + f"" + ) + + +def _make_hash_script( + cls: type, attrs: list[Attribute], frozen: bool, cache_hash: bool +) -> tuple[str, dict]: + attrs = tuple( + a for a in attrs if a.hash is True or (a.hash is None and a.eq is True) + ) + + tab = " " + + type_hash = hash(_generate_unique_filename(cls, "hash")) + # If eq is custom generated, we need to include the functions in globs + globs = {} + + hash_def = "def __hash__(self" + hash_func = "hash((" + closing_braces = "))" + if not cache_hash: + hash_def += "):" + else: + hash_def += ", *" + + hash_def += ", _cache_wrapper=__import__('attr._make')._make._CacheHashWrapper):" + hash_func = "_cache_wrapper(" + hash_func + closing_braces += ")" + + method_lines = [hash_def] + + def append_hash_computation_lines(prefix, indent): + """ + Generate the code for actually computing the hash code. + Below this will either be returned directly or used to compute + a value which is then cached, depending on the value of cache_hash + """ + + method_lines.extend( + [ + indent + prefix + hash_func, + indent + f" {type_hash},", + ] + ) + + for a in attrs: + if a.eq_key: + cmp_name = f"_{a.name}_key" + globs[cmp_name] = a.eq_key + method_lines.append( + indent + f" {cmp_name}(self.{a.name})," + ) + else: + method_lines.append(indent + f" self.{a.name},") + + method_lines.append(indent + " " + closing_braces) + + if cache_hash: + method_lines.append(tab + f"if self.{_HASH_CACHE_FIELD} is None:") + if frozen: + append_hash_computation_lines( + f"object.__setattr__(self, '{_HASH_CACHE_FIELD}', ", tab * 2 + ) + method_lines.append(tab * 2 + ")") # close __setattr__ + else: + append_hash_computation_lines( + f"self.{_HASH_CACHE_FIELD} = ", tab * 2 + ) + method_lines.append(tab + f"return self.{_HASH_CACHE_FIELD}") + else: + append_hash_computation_lines("return ", tab) + + script = "\n".join(method_lines) + return script, globs + + +def _add_hash(cls: type, attrs: list[Attribute]): + """ + Add a hash method to *cls*. + """ + script, globs = _make_hash_script( + cls, attrs, frozen=False, cache_hash=False + ) + _compile_and_eval( + script, globs, filename=_generate_unique_filename(cls, "__hash__") + ) + cls.__hash__ = globs["__hash__"] + return cls + + +def __ne__(self, other): + """ + Check equality and either forward a NotImplemented or + return the result negated. + """ + result = self.__eq__(other) + if result is NotImplemented: + return NotImplemented + + return not result + + +def _make_eq_script(attrs: list) -> tuple[str, dict]: + """ + Create __eq__ method for *cls* with *attrs*. + """ + attrs = [a for a in attrs if a.eq] + + lines = [ + "def __eq__(self, other):", + " if other.__class__ is not self.__class__:", + " return NotImplemented", + ] + + globs = {} + if attrs: + lines.append(" return (") + for a in attrs: + if a.eq_key: + cmp_name = f"_{a.name}_key" + # Add the key function to the global namespace + # of the evaluated function. + globs[cmp_name] = a.eq_key + lines.append( + f" {cmp_name}(self.{a.name}) == {cmp_name}(other.{a.name})" + ) + else: + lines.append(f" self.{a.name} == other.{a.name}") + if a is not attrs[-1]: + lines[-1] = f"{lines[-1]} and" + lines.append(" )") + else: + lines.append(" return True") + + script = "\n".join(lines) + + return script, globs + + +def _make_order(cls, attrs): + """ + Create ordering methods for *cls* with *attrs*. + """ + attrs = [a for a in attrs if a.order] + + def attrs_to_tuple(obj): + """ + Save us some typing. + """ + return tuple( + key(value) if key else value + for value, key in ( + (getattr(obj, a.name), a.order_key) for a in attrs + ) + ) + + def __lt__(self, other): + """ + Automatically created by attrs. + """ + if other.__class__ is self.__class__: + return attrs_to_tuple(self) < attrs_to_tuple(other) + + return NotImplemented + + def __le__(self, other): + """ + Automatically created by attrs. + """ + if other.__class__ is self.__class__: + return attrs_to_tuple(self) <= attrs_to_tuple(other) + + return NotImplemented + + def __gt__(self, other): + """ + Automatically created by attrs. + """ + if other.__class__ is self.__class__: + return attrs_to_tuple(self) > attrs_to_tuple(other) + + return NotImplemented + + def __ge__(self, other): + """ + Automatically created by attrs. + """ + if other.__class__ is self.__class__: + return attrs_to_tuple(self) >= attrs_to_tuple(other) + + return NotImplemented + + return __lt__, __le__, __gt__, __ge__ + + +def _add_eq(cls, attrs=None): + """ + Add equality methods to *cls* with *attrs*. + """ + if attrs is None: + attrs = cls.__attrs_attrs__ + + script, globs = _make_eq_script(attrs) + _compile_and_eval( + script, globs, filename=_generate_unique_filename(cls, "__eq__") + ) + cls.__eq__ = globs["__eq__"] + cls.__ne__ = __ne__ + + return cls + + +def _make_repr_script(attrs, ns) -> tuple[str, dict]: + """ + Create the source and globs for a __repr__ and return it. + """ + # Figure out which attributes to include, and which function to use to + # format them. The a.repr value can be either bool or a custom + # callable. + attr_names_with_reprs = tuple( + (a.name, (repr if a.repr is True else a.repr), a.init) + for a in attrs + if a.repr is not False + ) + globs = { + name + "_repr": r for name, r, _ in attr_names_with_reprs if r != repr + } + globs["_compat"] = _compat + globs["AttributeError"] = AttributeError + globs["NOTHING"] = NOTHING + attribute_fragments = [] + for name, r, i in attr_names_with_reprs: + accessor = ( + "self." + name if i else 'getattr(self, "' + name + '", NOTHING)' + ) + fragment = ( + "%s={%s!r}" % (name, accessor) + if r == repr + else "%s={%s_repr(%s)}" % (name, name, accessor) + ) + attribute_fragments.append(fragment) + repr_fragment = ", ".join(attribute_fragments) + + if ns is None: + cls_name_fragment = '{self.__class__.__qualname__.rsplit(">.", 1)[-1]}' + else: + cls_name_fragment = ns + ".{self.__class__.__name__}" + + lines = [ + "def __repr__(self):", + " try:", + " already_repring = _compat.repr_context.already_repring", + " except AttributeError:", + " already_repring = {id(self),}", + " _compat.repr_context.already_repring = already_repring", + " else:", + " if id(self) in already_repring:", + " return '...'", + " else:", + " already_repring.add(id(self))", + " try:", + f" return f'{cls_name_fragment}({repr_fragment})'", + " finally:", + " already_repring.remove(id(self))", + ] + + return "\n".join(lines), globs + + +def _add_repr(cls, ns=None, attrs=None): + """ + Add a repr method to *cls*. + """ + if attrs is None: + attrs = cls.__attrs_attrs__ + + script, globs = _make_repr_script(attrs, ns) + _compile_and_eval( + script, globs, filename=_generate_unique_filename(cls, "__repr__") + ) + cls.__repr__ = globs["__repr__"] + return cls + + +def fields(cls): + """ + Return the tuple of *attrs* attributes for a class or instance. + + The tuple also allows accessing the fields by their names (see below for + examples). + + Args: + cls (type): Class or instance to introspect. + + Raises: + TypeError: If *cls* is neither a class nor an *attrs* instance. + + attrs.exceptions.NotAnAttrsClassError: + If *cls* is not an *attrs* class. + + Returns: + tuple (with name accessors) of `attrs.Attribute` + + .. versionchanged:: 16.2.0 Returned tuple allows accessing the fields + by name. + .. versionchanged:: 23.1.0 Add support for generic classes. + .. versionchanged:: 26.1.0 Add support for instances. + """ + generic_base = get_generic_base(cls) + + if generic_base is None and not isinstance(cls, type): + type_ = type(cls) + if getattr(type_, "__attrs_attrs__", None) is None: + msg = "Passed object must be a class or attrs instance." + raise TypeError(msg) + + return fields(type_) + + attrs = getattr(cls, "__attrs_attrs__", None) + + if attrs is None: + if generic_base is not None: + attrs = getattr(generic_base, "__attrs_attrs__", None) + if attrs is not None: + # Even though this is global state, stick it on here to speed + # it up. We rely on `cls` being cached for this to be + # efficient. + cls.__attrs_attrs__ = attrs + return attrs + msg = f"{cls!r} is not an attrs-decorated class." + raise NotAnAttrsClassError(msg) + + return attrs + + +def fields_dict(cls): + """ + Return an ordered dictionary of *attrs* attributes for a class, whose keys + are the attribute names. + + Args: + cls (type): Class to introspect. + + Raises: + TypeError: If *cls* is not a class. + + attrs.exceptions.NotAnAttrsClassError: + If *cls* is not an *attrs* class. + + Returns: + dict[str, attrs.Attribute]: Dict of attribute name to definition + + .. versionadded:: 18.1.0 + """ + if not isinstance(cls, type): + msg = "Passed object must be a class." + raise TypeError(msg) + attrs = getattr(cls, "__attrs_attrs__", None) + if attrs is None: + msg = f"{cls!r} is not an attrs-decorated class." + raise NotAnAttrsClassError(msg) + return {a.name: a for a in attrs} + + +def validate(inst): + """ + Validate all attributes on *inst* that have a validator. + + Leaves all exceptions through. + + Args: + inst: Instance of a class with *attrs* attributes. + """ + if _config._run_validators is False: + return + + for a in fields(inst.__class__): + v = a.validator + if v is not None: + v(inst, a, getattr(inst, a.name)) + + +def _is_slot_attr(a_name, base_attr_map): + """ + Check if the attribute name comes from a slot class. + """ + cls = base_attr_map.get(a_name) + return cls and "__slots__" in cls.__dict__ + + +def _make_init_script( + cls, + attrs, + pre_init, + pre_init_has_args, + post_init, + frozen, + slots, + cache_hash, + base_attr_map, + is_exc, + cls_on_setattr, + attrs_init, +) -> tuple[str, dict, dict]: + has_cls_on_setattr = ( + cls_on_setattr is not None and cls_on_setattr is not setters.NO_OP + ) + + if frozen and has_cls_on_setattr: + msg = "Frozen classes can't use on_setattr." + raise ValueError(msg) + + needs_cached_setattr = cache_hash or frozen + filtered_attrs = [] + attr_dict = {} + for a in attrs: + if not a.init and a.default is NOTHING: + continue + + filtered_attrs.append(a) + attr_dict[a.name] = a + + if a.on_setattr is not None: + if frozen is True and a.on_setattr is not setters.NO_OP: + msg = "Frozen classes can't use on_setattr." + raise ValueError(msg) + + needs_cached_setattr = True + elif has_cls_on_setattr and a.on_setattr is not setters.NO_OP: + needs_cached_setattr = True + + script, globs, annotations = _attrs_to_init_script( + filtered_attrs, + frozen, + slots, + pre_init, + pre_init_has_args, + post_init, + cache_hash, + base_attr_map, + is_exc, + needs_cached_setattr, + has_cls_on_setattr, + "__attrs_init__" if attrs_init else "__init__", + ) + if cls.__module__ in sys.modules: + # This makes typing.get_type_hints(CLS.__init__) resolve string types. + globs.update(sys.modules[cls.__module__].__dict__) + + globs.update({"NOTHING": NOTHING, "attr_dict": attr_dict}) + + if needs_cached_setattr: + # Save the lookup overhead in __init__ if we need to circumvent + # setattr hooks. + globs["_cached_setattr_get"] = _OBJ_SETATTR.__get__ + + return script, globs, annotations + + +def _setattr(attr_name: str, value_var: str, has_on_setattr: bool) -> str: + """ + Use the cached object.setattr to set *attr_name* to *value_var*. + """ + return f"_setattr('{attr_name}', {value_var})" + + +def _setattr_with_converter( + attr_name: str, value_var: str, has_on_setattr: bool, converter: Converter +) -> str: + """ + Use the cached object.setattr to set *attr_name* to *value_var*, but run + its converter first. + """ + return f"_setattr('{attr_name}', {converter._fmt_converter_call(attr_name, value_var)})" + + +def _assign(attr_name: str, value: str, has_on_setattr: bool) -> str: + """ + Unless *attr_name* has an on_setattr hook, use normal assignment. Otherwise + relegate to _setattr. + """ + if has_on_setattr: + return _setattr(attr_name, value, True) + + return f"self.{attr_name} = {value}" + + +def _assign_with_converter( + attr_name: str, value_var: str, has_on_setattr: bool, converter: Converter +) -> str: + """ + Unless *attr_name* has an on_setattr hook, use normal assignment after + conversion. Otherwise relegate to _setattr_with_converter. + """ + if has_on_setattr: + return _setattr_with_converter(attr_name, value_var, True, converter) + + return f"self.{attr_name} = {converter._fmt_converter_call(attr_name, value_var)}" + + +def _determine_setters( + frozen: bool, slots: bool, base_attr_map: dict[str, type] +): + """ + Determine the correct setter functions based on whether a class is frozen + and/or slotted. + """ + if frozen is True: + if slots is True: + return (), _setattr, _setattr_with_converter + + # Dict frozen classes assign directly to __dict__. + # But only if the attribute doesn't come from an ancestor slot + # class. + # Note _inst_dict will be used again below if cache_hash is True + + def fmt_setter( + attr_name: str, value_var: str, has_on_setattr: bool + ) -> str: + if _is_slot_attr(attr_name, base_attr_map): + return _setattr(attr_name, value_var, has_on_setattr) + + return f"_inst_dict['{attr_name}'] = {value_var}" + + def fmt_setter_with_converter( + attr_name: str, + value_var: str, + has_on_setattr: bool, + converter: Converter, + ) -> str: + if has_on_setattr or _is_slot_attr(attr_name, base_attr_map): + return _setattr_with_converter( + attr_name, value_var, has_on_setattr, converter + ) + + return f"_inst_dict['{attr_name}'] = {converter._fmt_converter_call(attr_name, value_var)}" + + return ( + ("_inst_dict = self.__dict__",), + fmt_setter, + fmt_setter_with_converter, + ) + + # Not frozen -- we can just assign directly. + return (), _assign, _assign_with_converter + + +def _attrs_to_init_script( + attrs: list[Attribute], + is_frozen: bool, + is_slotted: bool, + call_pre_init: bool, + pre_init_has_args: bool, + call_post_init: bool, + does_cache_hash: bool, + base_attr_map: dict[str, type], + is_exc: bool, + needs_cached_setattr: bool, + has_cls_on_setattr: bool, + method_name: str, +) -> tuple[str, dict, dict]: + """ + Return a script of an initializer for *attrs*, a dict of globals, and + annotations for the initializer. + + The globals are required by the generated script. + """ + lines = ["self.__attrs_pre_init__()"] if call_pre_init else [] + + if needs_cached_setattr: + lines.append( + # Circumvent the __setattr__ descriptor to save one lookup per + # assignment. Note _setattr will be used again below if + # does_cache_hash is True. + "_setattr = _cached_setattr_get(self)" + ) + + extra_lines, fmt_setter, fmt_setter_with_converter = _determine_setters( + is_frozen, is_slotted, base_attr_map + ) + lines.extend(extra_lines) + + args = [] # Parameters in the definition of __init__ + pre_init_args = [] # Parameters in the call to __attrs_pre_init__ + kw_only_args = [] # Used for both 'args' and 'pre_init_args' above + attrs_to_validate = [] + + # This is a dictionary of names to validator and converter callables. + # Injecting this into __init__ globals lets us avoid lookups. + names_for_globals = {} + annotations = {"return": None} + + for a in attrs: + if a.validator: + attrs_to_validate.append(a) + + attr_name = a.name + has_on_setattr = a.on_setattr is not None or ( + a.on_setattr is not setters.NO_OP and has_cls_on_setattr + ) + # a.alias is set to maybe-mangled attr_name in _ClassBuilder if not + # explicitly provided + arg_name = a.alias + + has_factory = isinstance(a.default, Factory) + maybe_self = "self" if has_factory and a.default.takes_self else "" + + if a.converter is not None and not isinstance(a.converter, Converter): + converter = Converter(a.converter) + else: + converter = a.converter + + if a.init is False: + if has_factory: + init_factory_name = _INIT_FACTORY_PAT % (a.name,) + if converter is not None: + lines.append( + fmt_setter_with_converter( + attr_name, + init_factory_name + f"({maybe_self})", + has_on_setattr, + converter, + ) + ) + names_for_globals[converter._get_global_name(a.name)] = ( + converter.converter + ) + else: + lines.append( + fmt_setter( + attr_name, + init_factory_name + f"({maybe_self})", + has_on_setattr, + ) + ) + names_for_globals[init_factory_name] = a.default.factory + elif converter is not None: + lines.append( + fmt_setter_with_converter( + attr_name, + f"attr_dict['{attr_name}'].default", + has_on_setattr, + converter, + ) + ) + names_for_globals[converter._get_global_name(a.name)] = ( + converter.converter + ) + else: + lines.append( + fmt_setter( + attr_name, + f"attr_dict['{attr_name}'].default", + has_on_setattr, + ) + ) + elif a.default is not NOTHING and not has_factory: + arg = f"{arg_name}=attr_dict['{attr_name}'].default" + if a.kw_only: + kw_only_args.append(arg) + else: + args.append(arg) + pre_init_args.append(arg_name) + + if converter is not None: + lines.append( + fmt_setter_with_converter( + attr_name, arg_name, has_on_setattr, converter + ) + ) + names_for_globals[converter._get_global_name(a.name)] = ( + converter.converter + ) + else: + lines.append(fmt_setter(attr_name, arg_name, has_on_setattr)) + + elif has_factory: + arg = f"{arg_name}=NOTHING" + if a.kw_only: + kw_only_args.append(arg) + else: + args.append(arg) + pre_init_args.append(arg_name) + lines.append(f"if {arg_name} is not NOTHING:") + + init_factory_name = _INIT_FACTORY_PAT % (a.name,) + if converter is not None: + lines.append( + " " + + fmt_setter_with_converter( + attr_name, arg_name, has_on_setattr, converter + ) + ) + lines.append("else:") + lines.append( + " " + + fmt_setter_with_converter( + attr_name, + init_factory_name + "(" + maybe_self + ")", + has_on_setattr, + converter, + ) + ) + names_for_globals[converter._get_global_name(a.name)] = ( + converter.converter + ) + else: + lines.append( + " " + fmt_setter(attr_name, arg_name, has_on_setattr) + ) + lines.append("else:") + lines.append( + " " + + fmt_setter( + attr_name, + init_factory_name + "(" + maybe_self + ")", + has_on_setattr, + ) + ) + names_for_globals[init_factory_name] = a.default.factory + else: + if a.kw_only: + kw_only_args.append(arg_name) + else: + args.append(arg_name) + pre_init_args.append(arg_name) + + if converter is not None: + lines.append( + fmt_setter_with_converter( + attr_name, arg_name, has_on_setattr, converter + ) + ) + names_for_globals[converter._get_global_name(a.name)] = ( + converter.converter + ) + else: + lines.append(fmt_setter(attr_name, arg_name, has_on_setattr)) + + if a.init is True: + if a.type is not None and converter is None: + annotations[arg_name] = a.type + elif converter is not None and converter._first_param_type: + # Use the type from the converter if present. + annotations[arg_name] = converter._first_param_type + + if attrs_to_validate: # we can skip this if there are no validators. + names_for_globals["_config"] = _config + lines.append("if _config._run_validators is True:") + for a in attrs_to_validate: + val_name = "__attr_validator_" + a.name + attr_name = "__attr_" + a.name + lines.append(f" {val_name}(self, {attr_name}, self.{a.name})") + names_for_globals[val_name] = a.validator + names_for_globals[attr_name] = a + + if call_post_init: + lines.append("self.__attrs_post_init__()") + + # Because this is set only after __attrs_post_init__ is called, a crash + # will result if post-init tries to access the hash code. This seemed + # preferable to setting this beforehand, in which case alteration to field + # values during post-init combined with post-init accessing the hash code + # would result in silent bugs. + if does_cache_hash: + if is_frozen: + if is_slotted: + init_hash_cache = f"_setattr('{_HASH_CACHE_FIELD}', None)" + else: + init_hash_cache = f"_inst_dict['{_HASH_CACHE_FIELD}'] = None" + else: + init_hash_cache = f"self.{_HASH_CACHE_FIELD} = None" + lines.append(init_hash_cache) + + # For exceptions we rely on BaseException.__init__ for proper + # initialization. + if is_exc: + vals = ",".join(f"self.{a.name}" for a in attrs if a.init) + + lines.append(f"BaseException.__init__(self, {vals})") + + args = ", ".join(args) + pre_init_args = ", ".join(pre_init_args) + if kw_only_args: + # leading comma & kw_only args + args += f"{', ' if args else ''}*, {', '.join(kw_only_args)}" + pre_init_kw_only_args = ", ".join( + [ + f"{kw_arg_name}={kw_arg_name}" + # We need to remove the defaults from the kw_only_args. + for kw_arg_name in (kwa.split("=")[0] for kwa in kw_only_args) + ] + ) + pre_init_args += ", " if pre_init_args else "" + pre_init_args += pre_init_kw_only_args + + if call_pre_init and pre_init_has_args: + # If pre init method has arguments, pass the values given to __init__. + lines[0] = f"self.__attrs_pre_init__({pre_init_args})" + + # Python <3.12 doesn't allow backslashes in f-strings. + NL = "\n " + return ( + f"""def {method_name}(self, {args}): + {NL.join(lines) if lines else "pass"} +""", + names_for_globals, + annotations, + ) + + +def _default_init_alias_for(name: str) -> str: + """ + The default __init__ parameter name for a field. + + This performs private-name adjustment via leading-unscore stripping, + and is the default value of Attribute.alias if not provided. + """ + + return name.lstrip("_") + + +class Attribute: + """ + *Read-only* representation of an attribute. + + .. warning:: + + You should never instantiate this class yourself. + + The class has *all* arguments of `attr.ib` (except for ``factory`` which is + only syntactic sugar for ``default=Factory(...)`` plus the following: + + - ``name`` (`str`): The name of the attribute. + - ``alias`` (`str`): The __init__ parameter name of the attribute, after + any explicit overrides and default private-attribute-name handling. + - ``alias_is_default`` (`bool`): Whether the ``alias`` was automatically + generated (``True``) or explicitly provided by the user (``False``). + - ``inherited`` (`bool`): Whether or not that attribute has been inherited + from a base class. + - ``eq_key`` and ``order_key`` (`typing.Callable` or `None`): The + callables that are used for comparing and ordering objects by this + attribute, respectively. These are set by passing a callable to + `attr.ib`'s ``eq``, ``order``, or ``cmp`` arguments. See also + :ref:`comparison customization `. + + Instances of this class are frequently used for introspection purposes + like: + + - `fields` returns a tuple of them. + - Validators get them passed as the first argument. + - The :ref:`field transformer ` hook receives a list of + them. + - The ``alias`` property exposes the __init__ parameter name of the field, + with any overrides and default private-attribute handling applied. + + + .. versionadded:: 20.1.0 *inherited* + .. versionadded:: 20.1.0 *on_setattr* + .. versionchanged:: 20.2.0 *inherited* is not taken into account for + equality checks and hashing anymore. + .. versionadded:: 21.1.0 *eq_key* and *order_key* + .. versionadded:: 22.2.0 *alias* + .. versionadded:: 26.1.0 *alias_is_default* + + For the full version history of the fields, see `attr.ib`. + """ + + # These slots must NOT be reordered because we use them later for + # instantiation. + __slots__ = ( # noqa: RUF023 + "name", + "default", + "validator", + "repr", + "eq", + "eq_key", + "order", + "order_key", + "hash", + "init", + "metadata", + "type", + "converter", + "kw_only", + "inherited", + "on_setattr", + "alias", + "alias_is_default", + ) + + def __init__( + self, + name, + default, + validator, + repr, + cmp, # XXX: unused, remove along with other cmp code. + hash, + init, + inherited, + metadata=None, + type=None, + converter=None, + kw_only=False, + eq=None, + eq_key=None, + order=None, + order_key=None, + on_setattr=None, + alias=None, + alias_is_default=None, + ): + eq, eq_key, order, order_key = _determine_attrib_eq_order( + cmp, eq_key or eq, order_key or order, True + ) + + # Cache this descriptor here to speed things up later. + bound_setattr = _OBJ_SETATTR.__get__(self) + + # Despite the big red warning, people *do* instantiate `Attribute` + # themselves. + bound_setattr("name", name) + bound_setattr("default", default) + bound_setattr("validator", validator) + bound_setattr("repr", repr) + bound_setattr("eq", eq) + bound_setattr("eq_key", eq_key) + bound_setattr("order", order) + bound_setattr("order_key", order_key) + bound_setattr("hash", hash) + bound_setattr("init", init) + bound_setattr("converter", converter) + bound_setattr( + "metadata", + ( + types.MappingProxyType(dict(metadata)) # Shallow copy + if metadata + else _EMPTY_METADATA_SINGLETON + ), + ) + bound_setattr("type", type) + bound_setattr("kw_only", kw_only) + bound_setattr("inherited", inherited) + bound_setattr("on_setattr", on_setattr) + bound_setattr("alias", alias) + bound_setattr( + "alias_is_default", + alias is None if alias_is_default is None else alias_is_default, + ) + + def __setattr__(self, name, value): + raise FrozenInstanceError + + @classmethod + def from_counting_attr( + cls, name: str, ca: _CountingAttr, kw_only: bool, type=None + ): + # The 'kw_only' argument is the class-level setting, and is used if the + # attribute itself does not explicitly set 'kw_only'. + # type holds the annotated value. deal with conflicts: + if type is None: + type = ca.type + elif ca.type is not None: + msg = f"Type annotation and type argument cannot both be present for '{name}'." + raise ValueError(msg) + return cls( + name, + ca._default, + ca._validator, + ca.repr, + None, + ca.hash, + ca.init, + False, + ca.metadata, + type, + ca.converter, + kw_only if ca.kw_only is None else ca.kw_only, + ca.eq, + ca.eq_key, + ca.order, + ca.order_key, + ca.on_setattr, + ca.alias, + ca.alias is None, + ) + + # Don't use attrs.evolve since fields(Attribute) doesn't work + def evolve(self, **changes): + """ + Copy *self* and apply *changes*. + + This works similarly to `attrs.evolve` but that function does not work + with :class:`attrs.Attribute`. + + It is mainly meant to be used for `transform-fields`. + + .. versionadded:: 20.3.0 + """ + new = copy.copy(self) + + new._setattrs(changes.items()) + + if "alias" in changes and "alias_is_default" not in changes: + # Explicit alias provided -- no longer the default. + _OBJ_SETATTR.__get__(new)("alias_is_default", False) + elif ( + "name" in changes + and "alias" not in changes + # Don't auto-generate alias if the user picked picked the old one. + and self.alias_is_default + ): + # Name changed, alias was auto-generated -- update it. + _OBJ_SETATTR.__get__(new)( + "alias", _default_init_alias_for(new.name) + ) + + return new + + # Don't use _add_pickle since fields(Attribute) doesn't work + def __getstate__(self): + """ + Play nice with pickle. + """ + return tuple( + getattr(self, name) if name != "metadata" else dict(self.metadata) + for name in self.__slots__ + ) + + def __setstate__(self, state): + """ + Play nice with pickle. + """ + if len(state) < len(self.__slots__): + # Pre-26.1.0 pickle without alias_is_default -- infer it + # heuristically. + state_dict = dict(zip(self.__slots__, state)) + alias_is_default = state_dict.get( + "alias" + ) is None or state_dict.get("alias") == _default_init_alias_for( + state_dict["name"] + ) + state = (*state, alias_is_default) + + self._setattrs(zip(self.__slots__, state)) + + def _setattrs(self, name_values_pairs): + bound_setattr = _OBJ_SETATTR.__get__(self) + for name, value in name_values_pairs: + if name != "metadata": + bound_setattr(name, value) + else: + bound_setattr( + name, + ( + types.MappingProxyType(dict(value)) + if value + else _EMPTY_METADATA_SINGLETON + ), + ) + + +_a = [ + Attribute( + name=name, + default=NOTHING, + validator=None, + repr=(name != "alias_is_default"), + cmp=None, + eq=True, + order=False, + hash=(name != "metadata"), + init=True, + inherited=False, + alias=_default_init_alias_for(name), + ) + for name in Attribute.__slots__ +] + +Attribute = _add_hash( + _add_eq( + _add_repr(Attribute, attrs=_a), + attrs=[a for a in _a if a.name != "inherited"], + ), + attrs=[a for a in _a if a.hash and a.name != "inherited"], +) + + +class _CountingAttr: + """ + Intermediate representation of attributes that uses a counter to preserve + the order in which the attributes have been defined. + + *Internal* data structure of the attrs library. Running into is most + likely the result of a bug like a forgotten `@attr.s` decorator. + """ + + __slots__ = ( + "_default", + "_validator", + "alias", + "converter", + "counter", + "eq", + "eq_key", + "hash", + "init", + "kw_only", + "metadata", + "on_setattr", + "order", + "order_key", + "repr", + "type", + ) + __attrs_attrs__ = ( + *tuple( + Attribute( + name=name, + alias=_default_init_alias_for(name), + default=NOTHING, + validator=None, + repr=True, + cmp=None, + hash=True, + init=True, + kw_only=False, + eq=True, + eq_key=None, + order=False, + order_key=None, + inherited=False, + on_setattr=None, + ) + for name in ( + "counter", + "_default", + "repr", + "eq", + "order", + "hash", + "init", + "on_setattr", + "alias", + ) + ), + Attribute( + name="metadata", + alias="metadata", + default=None, + validator=None, + repr=True, + cmp=None, + hash=False, + init=True, + kw_only=False, + eq=True, + eq_key=None, + order=False, + order_key=None, + inherited=False, + on_setattr=None, + ), + ) + cls_counter = 0 + + def __init__( + self, + default, + validator, + repr, + cmp, + hash, + init, + converter, + metadata, + type, + kw_only, + eq, + eq_key, + order, + order_key, + on_setattr, + alias, + ): + _CountingAttr.cls_counter += 1 + self.counter = _CountingAttr.cls_counter + self._default = default + self._validator = validator + self.converter = converter + self.repr = repr + self.eq = eq + self.eq_key = eq_key + self.order = order + self.order_key = order_key + self.hash = hash + self.init = init + self.metadata = metadata + self.type = type + self.kw_only = kw_only + self.on_setattr = on_setattr + self.alias = alias + + def validator(self, meth): + """ + Decorator that adds *meth* to the list of validators. + + Returns *meth* unchanged. + + .. versionadded:: 17.1.0 + """ + if self._validator is None: + self._validator = meth + else: + self._validator = and_(self._validator, meth) + return meth + + def default(self, meth): + """ + Decorator that allows to set the default for an attribute. + + Returns *meth* unchanged. + + Raises: + DefaultAlreadySetError: If default has been set before. + + .. versionadded:: 17.1.0 + """ + if self._default is not NOTHING: + raise DefaultAlreadySetError + + self._default = Factory(meth, takes_self=True) + + return meth + + +_CountingAttr = _add_eq(_add_repr(_CountingAttr)) + + +class ClassProps: + """ + Effective class properties as derived from parameters to `attr.s()` or + `define()` decorators. + + This is the same data structure that *attrs* uses internally to decide how + to construct the final class. + + Warning: + + This feature is currently **experimental** and is not covered by our + strict backwards-compatibility guarantees. + + + Attributes: + is_exception (bool): + Whether the class is treated as an exception class. + + is_slotted (bool): + Whether the class is `slotted `. + + has_weakref_slot (bool): + Whether the class has a slot for weak references. + + is_frozen (bool): + Whether the class is frozen. + + kw_only (KeywordOnly): + Whether / how the class enforces keyword-only arguments on the + ``__init__`` method. + + collected_fields_by_mro (bool): + Whether the class fields were collected by method resolution order. + That is, correctly but unlike `dataclasses`. + + added_init (bool): + Whether the class has an *attrs*-generated ``__init__`` method. + + added_repr (bool): + Whether the class has an *attrs*-generated ``__repr__`` method. + + added_eq (bool): + Whether the class has *attrs*-generated equality methods. + + added_ordering (bool): + Whether the class has *attrs*-generated ordering methods. + + hashability (Hashability): How `hashable ` the class is. + + added_match_args (bool): + Whether the class supports positional `match ` over its + fields. + + added_str (bool): + Whether the class has an *attrs*-generated ``__str__`` method. + + added_pickling (bool): + Whether the class has *attrs*-generated ``__getstate__`` and + ``__setstate__`` methods for `pickle`. + + on_setattr_hook (Callable[[Any, Attribute[Any], Any], Any] | None): + The class's ``__setattr__`` hook. + + field_transformer (Callable[[Attribute[Any]], Attribute[Any]] | None): + The class's `field transformers `. + + .. versionadded:: 25.4.0 + """ + + class Hashability(enum.Enum): + """ + The hashability of a class. + + .. versionadded:: 25.4.0 + """ + + HASHABLE = "hashable" + """Write a ``__hash__``.""" + HASHABLE_CACHED = "hashable_cache" + """Write a ``__hash__`` and cache the hash.""" + UNHASHABLE = "unhashable" + """Set ``__hash__`` to ``None``.""" + LEAVE_ALONE = "leave_alone" + """Don't touch ``__hash__``.""" + + class KeywordOnly(enum.Enum): + """ + How attributes should be treated regarding keyword-only parameters. + + .. versionadded:: 25.4.0 + """ + + NO = "no" + """Attributes are not keyword-only.""" + YES = "yes" + """Attributes in current class without kw_only=False are keyword-only.""" + FORCE = "force" + """All attributes are keyword-only.""" + + __slots__ = ( # noqa: RUF023 -- order matters for __init__ + "is_exception", + "is_slotted", + "has_weakref_slot", + "is_frozen", + "kw_only", + "collected_fields_by_mro", + "added_init", + "added_repr", + "added_eq", + "added_ordering", + "hashability", + "added_match_args", + "added_str", + "added_pickling", + "on_setattr_hook", + "field_transformer", + ) + + def __init__( + self, + is_exception, + is_slotted, + has_weakref_slot, + is_frozen, + kw_only, + collected_fields_by_mro, + added_init, + added_repr, + added_eq, + added_ordering, + hashability, + added_match_args, + added_str, + added_pickling, + on_setattr_hook, + field_transformer, + ): + self.is_exception = is_exception + self.is_slotted = is_slotted + self.has_weakref_slot = has_weakref_slot + self.is_frozen = is_frozen + self.kw_only = kw_only + self.collected_fields_by_mro = collected_fields_by_mro + self.added_init = added_init + self.added_repr = added_repr + self.added_eq = added_eq + self.added_ordering = added_ordering + self.hashability = hashability + self.added_match_args = added_match_args + self.added_str = added_str + self.added_pickling = added_pickling + self.on_setattr_hook = on_setattr_hook + self.field_transformer = field_transformer + + @property + def is_hashable(self): + return ( + self.hashability is ClassProps.Hashability.HASHABLE + or self.hashability is ClassProps.Hashability.HASHABLE_CACHED + ) + + +_cas = [ + Attribute( + name=name, + default=NOTHING, + validator=None, + repr=True, + cmp=None, + eq=True, + order=False, + hash=True, + init=True, + inherited=False, + alias=_default_init_alias_for(name), + ) + for name in ClassProps.__slots__ +] + +ClassProps = _add_eq(_add_repr(ClassProps, attrs=_cas), attrs=_cas) + + +class Factory: + """ + Stores a factory callable. + + If passed as the default value to `attrs.field`, the factory is used to + generate a new value. + + Args: + factory (typing.Callable): + A callable that takes either none or exactly one mandatory + positional argument depending on *takes_self*. + + takes_self (bool): + Pass the partially initialized instance that is being initialized + as a positional argument. + + .. versionadded:: 17.1.0 *takes_self* + """ + + __slots__ = ("factory", "takes_self") + + def __init__(self, factory, takes_self=False): + self.factory = factory + self.takes_self = takes_self + + def __getstate__(self): + """ + Play nice with pickle. + """ + return tuple(getattr(self, name) for name in self.__slots__) + + def __setstate__(self, state): + """ + Play nice with pickle. + """ + for name, value in zip(self.__slots__, state): + setattr(self, name, value) + + +_f = [ + Attribute( + name=name, + default=NOTHING, + validator=None, + repr=True, + cmp=None, + eq=True, + order=False, + hash=True, + init=True, + inherited=False, + ) + for name in Factory.__slots__ +] + +Factory = _add_hash(_add_eq(_add_repr(Factory, attrs=_f), attrs=_f), attrs=_f) + + +class Converter: + """ + Stores a converter callable. + + Allows for the wrapped converter to take additional arguments. The + arguments are passed in the order they are documented. + + Args: + converter (Callable): A callable that converts the passed value. + + takes_self (bool): + Pass the partially initialized instance that is being initialized + as a positional argument. (default: `False`) + + takes_field (bool): + Pass the field definition (an :class:`Attribute`) into the + converter as a positional argument. (default: `False`) + + .. versionadded:: 24.1.0 + """ + + __slots__ = ( + "__call__", + "_first_param_type", + "_global_name", + "converter", + "takes_field", + "takes_self", + ) + + def __init__(self, converter, *, takes_self=False, takes_field=False): + self.converter = converter + self.takes_self = takes_self + self.takes_field = takes_field + + ex = _AnnotationExtractor(converter) + self._first_param_type = ex.get_first_param_type() + + if not (self.takes_self or self.takes_field): + self.__call__ = lambda value, _, __: self.converter(value) + elif self.takes_self and not self.takes_field: + self.__call__ = lambda value, instance, __: self.converter( + value, instance + ) + elif not self.takes_self and self.takes_field: + self.__call__ = lambda value, __, field: self.converter( + value, field + ) + else: + self.__call__ = self.converter + + rt = ex.get_return_type() + if rt is not None: + self.__call__.__annotations__["return"] = rt + + @staticmethod + def _get_global_name(attr_name: str) -> str: + """ + Return the name that a converter for an attribute name *attr_name* + would have. + """ + return f"__attr_converter_{attr_name}" + + def _fmt_converter_call(self, attr_name: str, value_var: str) -> str: + """ + Return a string that calls the converter for an attribute name + *attr_name* and the value in variable named *value_var* according to + `self.takes_self` and `self.takes_field`. + """ + if not (self.takes_self or self.takes_field): + return f"{self._get_global_name(attr_name)}({value_var})" + + if self.takes_self and self.takes_field: + return f"{self._get_global_name(attr_name)}({value_var}, self, attr_dict['{attr_name}'])" + + if self.takes_self: + return f"{self._get_global_name(attr_name)}({value_var}, self)" + + return f"{self._get_global_name(attr_name)}({value_var}, attr_dict['{attr_name}'])" + + def __getstate__(self): + """ + Return a dict containing only converter and takes_self -- the rest gets + computed when loading. + """ + return { + "converter": self.converter, + "takes_self": self.takes_self, + "takes_field": self.takes_field, + } + + def __setstate__(self, state): + """ + Load instance from state. + """ + self.__init__(**state) + + +_f = [ + Attribute( + name=name, + default=NOTHING, + validator=None, + repr=True, + cmp=None, + eq=True, + order=False, + hash=True, + init=True, + inherited=False, + ) + for name in ("converter", "takes_self", "takes_field") +] + +Converter = _add_hash( + _add_eq(_add_repr(Converter, attrs=_f), attrs=_f), attrs=_f +) + + +def make_class( + name, attrs, bases=(object,), class_body=None, **attributes_arguments +): + r""" + A quick way to create a new class called *name* with *attrs*. + + .. note:: + + ``make_class()`` is a thin wrapper around `attr.s`, not `attrs.define` + which means that it doesn't come with some of the improved defaults. + + For example, if you want the same ``on_setattr`` behavior as in + `attrs.define`, you have to pass the hooks yourself: ``make_class(..., + on_setattr=setters.pipe(setters.convert, setters.validate)`` + + .. warning:: + + It is *your* duty to ensure that the class name and the attribute names + are valid identifiers. ``make_class()`` will *not* validate them for + you. + + Args: + name (str): The name for the new class. + + attrs (list | dict): + A list of names or a dictionary of mappings of names to `attr.ib`\ + s / `attrs.field`\ s. + + The order is deduced from the order of the names or attributes + inside *attrs*. Otherwise the order of the definition of the + attributes is used. + + bases (tuple[type, ...]): Classes that the new class will subclass. + + class_body (dict): + An optional dictionary of class attributes for the new class. + + attributes_arguments: Passed unmodified to `attr.s`. + + Returns: + type: A new class with *attrs*. + + .. versionadded:: 17.1.0 *bases* + .. versionchanged:: 18.1.0 If *attrs* is ordered, the order is retained. + .. versionchanged:: 23.2.0 *class_body* + .. versionchanged:: 25.2.0 Class names can now be unicode. + """ + # Class identifiers are converted into the normal form NFKC while parsing + name = unicodedata.normalize("NFKC", name) + + if isinstance(attrs, dict): + cls_dict = attrs + elif isinstance(attrs, (list, tuple)): + cls_dict = {a: attrib() for a in attrs} + else: + msg = "attrs argument must be a dict or a list." + raise TypeError(msg) + + pre_init = cls_dict.pop("__attrs_pre_init__", None) + post_init = cls_dict.pop("__attrs_post_init__", None) + user_init = cls_dict.pop("__init__", None) + + body = {} + if class_body is not None: + body.update(class_body) + if pre_init is not None: + body["__attrs_pre_init__"] = pre_init + if post_init is not None: + body["__attrs_post_init__"] = post_init + if user_init is not None: + body["__init__"] = user_init + + type_ = types.new_class(name, bases, {}, lambda ns: ns.update(body)) + + # For pickling to work, the __module__ variable needs to be set to the + # frame where the class is created. Bypass this step in environments where + # sys._getframe is not defined (Jython for example) or sys._getframe is not + # defined for arguments greater than 0 (IronPython). + with contextlib.suppress(AttributeError, ValueError): + type_.__module__ = sys._getframe(1).f_globals.get( + "__name__", "__main__" + ) + + # We do it here for proper warnings with meaningful stacklevel. + cmp = attributes_arguments.pop("cmp", None) + ( + attributes_arguments["eq"], + attributes_arguments["order"], + ) = _determine_attrs_eq_order( + cmp, + attributes_arguments.get("eq"), + attributes_arguments.get("order"), + True, + ) + + cls = _attrs(these=cls_dict, **attributes_arguments)(type_) + # Only add type annotations now or "_attrs()" will complain: + cls.__annotations__ = { + k: v.type for k, v in cls_dict.items() if v.type is not None + } + return cls + + +# These are required by within this module so we define them here and merely +# import into .validators / .converters. + + +@attrs(slots=True, unsafe_hash=True) +class _AndValidator: + """ + Compose many validators to a single one. + """ + + _validators = attrib() + + def __call__(self, inst, attr, value): + for v in self._validators: + v(inst, attr, value) + + +def and_(*validators): + """ + A validator that composes multiple validators into one. + + When called on a value, it runs all wrapped validators. + + Args: + validators (~collections.abc.Iterable[typing.Callable]): + Arbitrary number of validators. + + .. versionadded:: 17.1.0 + """ + vals = [] + for validator in validators: + vals.extend( + validator._validators + if isinstance(validator, _AndValidator) + else [validator] + ) + + return _AndValidator(tuple(vals)) + + +def pipe(*converters): + """ + A converter that composes multiple converters into one. + + When called on a value, it runs all wrapped converters, returning the + *last* value. + + Type annotations will be inferred from the wrapped converters', if they + have any. + + converters (~collections.abc.Iterable[typing.Callable]): + Arbitrary number of converters. + + .. versionadded:: 20.1.0 + """ + + return_instance = any(isinstance(c, Converter) for c in converters) + + if return_instance: + + def pipe_converter(val, inst, field): + for c in converters: + val = ( + c(val, inst, field) if isinstance(c, Converter) else c(val) + ) + + return val + + else: + + def pipe_converter(val): + for c in converters: + val = c(val) + + return val + + if not converters: + # If the converter list is empty, pipe_converter is the identity. + A = TypeVar("A") + pipe_converter.__annotations__.update({"val": A, "return": A}) + else: + # Get parameter type from first converter. + t = _AnnotationExtractor(converters[0]).get_first_param_type() + if t: + pipe_converter.__annotations__["val"] = t + + last = converters[-1] + if not PY_3_11_PLUS and isinstance(last, Converter): + last = last.__call__ + + # Get return type from last converter. + rt = _AnnotationExtractor(last).get_return_type() + if rt: + pipe_converter.__annotations__["return"] = rt + + if return_instance: + return Converter(pipe_converter, takes_self=True, takes_field=True) + return pipe_converter diff --git a/attr/_next_gen.py b/attr/_next_gen.py new file mode 100644 index 0000000000000000000000000000000000000000..4ccd0da2446dc126ce936b054581a527e247cabc --- /dev/null +++ b/attr/_next_gen.py @@ -0,0 +1,674 @@ +# SPDX-License-Identifier: MIT + +""" +These are keyword-only APIs that call `attr.s` and `attr.ib` with different +default values. +""" + +from functools import partial + +from . import setters +from ._funcs import asdict as _asdict +from ._funcs import astuple as _astuple +from ._make import ( + _DEFAULT_ON_SETATTR, + NOTHING, + _frozen_setattrs, + attrib, + attrs, +) +from .exceptions import NotAnAttrsClassError, UnannotatedAttributeError + + +def define( + maybe_cls=None, + *, + these=None, + repr=None, + unsafe_hash=None, + hash=None, + init=None, + slots=True, + frozen=False, + weakref_slot=True, + str=False, + auto_attribs=None, + kw_only=False, + cache_hash=False, + auto_exc=True, + eq=None, + order=False, + auto_detect=True, + getstate_setstate=None, + on_setattr=None, + field_transformer=None, + match_args=True, + force_kw_only=False, +): + r""" + A class decorator that adds :term:`dunder methods` according to + :term:`fields ` specified using :doc:`type annotations `, + `field()` calls, or the *these* argument. + + Since *attrs* patches or replaces an existing class, you cannot use + `object.__init_subclass__` with *attrs* classes, because it runs too early. + As a replacement, you can define ``__attrs_init_subclass__`` on your class. + It will be called by *attrs* classes that subclass it after they're + created. See also :ref:`init-subclass`. + + Args: + slots (bool): + Create a :term:`slotted class ` that's more + memory-efficient. Slotted classes are generally superior to the + default dict classes, but have some gotchas you should know about, + so we encourage you to read the :term:`glossary entry `. + + auto_detect (bool): + Instead of setting the *init*, *repr*, *eq*, and *hash* arguments + explicitly, assume they are set to True **unless any** of the + involved methods for one of the arguments is implemented in the + *current* class (meaning, it is *not* inherited from some base + class). + + So, for example by implementing ``__eq__`` on a class yourself, + *attrs* will deduce ``eq=False`` and will create *neither* + ``__eq__`` *nor* ``__ne__`` (but Python classes come with a + sensible ``__ne__`` by default, so it *should* be enough to only + implement ``__eq__`` in most cases). + + Passing :data:`True` or :data:`False` to *init*, *repr*, *eq*, or *hash* + overrides whatever *auto_detect* would determine. + + auto_exc (bool): + If the class subclasses `BaseException` (which implicitly includes + any subclass of any exception), the following happens to behave + like a well-behaved Python exception class: + + - the values for *eq*, *order*, and *hash* are ignored and the + instances compare and hash by the instance's ids [#]_ , + - all attributes that are either passed into ``__init__`` or have a + default value are additionally available as a tuple in the + ``args`` attribute, + - the value of *str* is ignored leaving ``__str__`` to base + classes. + + .. [#] + Note that *attrs* will *not* remove existing implementations of + ``__hash__`` or the equality methods. It just won't add own + ones. + + on_setattr (~typing.Callable | list[~typing.Callable] | None | ~typing.Literal[attrs.setters.NO_OP]): + A callable that is run whenever the user attempts to set an + attribute (either by assignment like ``i.x = 42`` or by using + `setattr` like ``setattr(i, "x", 42)``). It receives the same + arguments as validators: the instance, the attribute that is being + modified, and the new value. + + If no exception is raised, the attribute is set to the return value + of the callable. + + If a list of callables is passed, they're automatically wrapped in + an `attrs.setters.pipe`. + + If left None, the default behavior is to run converters and + validators whenever an attribute is set. + + init (bool): + Create a ``__init__`` method that initializes the *attrs* + attributes. Leading underscores are stripped for the argument name, + unless an alias is set on the attribute. + + .. seealso:: + `init` shows advanced ways to customize the generated + ``__init__`` method, including executing code before and after. + + repr(bool): + Create a ``__repr__`` method with a human readable representation + of *attrs* attributes. + + str (bool): + Create a ``__str__`` method that is identical to ``__repr__``. This + is usually not necessary except for `Exception`\ s. + + eq (bool | None): + If True or None (default), add ``__eq__`` and ``__ne__`` methods + that check two instances for equality. + + .. seealso:: + `comparison` describes how to customize the comparison behavior + going as far comparing NumPy arrays. + + order (bool | None): + If True, add ``__lt__``, ``__le__``, ``__gt__``, and ``__ge__`` + methods that behave like *eq* above and allow instances to be + ordered. + + They compare the instances as if they were tuples of their *attrs* + attributes if and only if the types of both classes are + *identical*. + + If `None` mirror value of *eq*. + + .. seealso:: `comparison` + + unsafe_hash (bool | None): + If None (default), the ``__hash__`` method is generated according + how *eq* and *frozen* are set. + + 1. If *both* are True, *attrs* will generate a ``__hash__`` for + you. + 2. If *eq* is True and *frozen* is False, ``__hash__`` will be set + to None, marking it unhashable (which it is). + 3. If *eq* is False, ``__hash__`` will be left untouched meaning + the ``__hash__`` method of the base class will be used. If the + base class is `object`, this means it will fall back to id-based + hashing. + + Although not recommended, you can decide for yourself and force + *attrs* to create one (for example, if the class is immutable even + though you didn't freeze it programmatically) by passing True or + not. Both of these cases are rather special and should be used + carefully. + + .. seealso:: + + - Our documentation on `hashing`, + - Python's documentation on `object.__hash__`, + - and the `GitHub issue that led to the default \ behavior + `_ for more + details. + + hash (bool | None): + Deprecated alias for *unsafe_hash*. *unsafe_hash* takes precedence. + + cache_hash (bool): + Ensure that the object's hash code is computed only once and stored + on the object. If this is set to True, hashing must be either + explicitly or implicitly enabled for this class. If the hash code + is cached, avoid any reassignments of fields involved in hash code + computation or mutations of the objects those fields point to after + object creation. If such changes occur, the behavior of the + object's hash code is undefined. + + frozen (bool): + Make instances immutable after initialization. If someone attempts + to modify a frozen instance, `attrs.exceptions.FrozenInstanceError` + is raised. + + .. note:: + + 1. This is achieved by installing a custom ``__setattr__`` + method on your class, so you can't implement your own. + + 2. True immutability is impossible in Python. + + 3. This *does* have a minor a runtime performance `impact + ` when initializing new instances. In other + words: ``__init__`` is slightly slower with ``frozen=True``. + + 4. If a class is frozen, you cannot modify ``self`` in + ``__attrs_post_init__`` or a self-written ``__init__``. You + can circumvent that limitation by using + ``object.__setattr__(self, "attribute_name", value)``. + + 5. Subclasses of a frozen class are frozen too. + + kw_only (bool): + Make attributes keyword-only in the generated ``__init__`` (if + *init* is False, this parameter is ignored). Attributes that + explicitly set ``kw_only=False`` are not affected; base class + attributes are also not affected. + + Also see *force_kw_only*. + + weakref_slot (bool): + Make instances weak-referenceable. This has no effect unless + *slots* is True. + + field_transformer (~typing.Callable | None): + A function that is called with the original class object and all + fields right before *attrs* finalizes the class. You can use this, + for example, to automatically add converters or validators to + fields based on their types. + + .. seealso:: `transform-fields` + + match_args (bool): + If True (default), set ``__match_args__`` on the class to support + :pep:`634` (*Structural Pattern Matching*). It is a tuple of all + non-keyword-only ``__init__`` parameter names on Python 3.10 and + later. Ignored on older Python versions. + + collect_by_mro (bool): + If True, *attrs* collects attributes from base classes correctly + according to the `method resolution order + `_. If False, *attrs* + will mimic the (wrong) behavior of `dataclasses` and :pep:`681`. + + See also `issue #428 + `_. + + force_kw_only (bool): + A back-compat flag for restoring pre-25.4.0 behavior. If True and + ``kw_only=True``, all attributes are made keyword-only, including + base class attributes, and those set to ``kw_only=False`` at the + attribute level. Defaults to False. + + See also `issue #980 + `_. + + getstate_setstate (bool | None): + .. note:: + + This is usually only interesting for slotted classes and you + should probably just set *auto_detect* to True. + + If True, ``__getstate__`` and ``__setstate__`` are generated and + attached to the class. This is necessary for slotted classes to be + pickleable. If left None, it's True by default for slotted classes + and False for dict classes. + + If *auto_detect* is True, and *getstate_setstate* is left None, and + **either** ``__getstate__`` or ``__setstate__`` is detected + directly on the class (meaning: not inherited), it is set to False + (this is usually what you want). + + auto_attribs (bool | None): + If True, look at type annotations to determine which attributes to + use, like `dataclasses`. If False, it will only look for explicit + :func:`field` class attributes, like classic *attrs*. + + If left None, it will guess: + + 1. If any attributes are annotated and no unannotated + `attrs.field`\ s are found, it assumes *auto_attribs=True*. + 2. Otherwise it assumes *auto_attribs=False* and tries to collect + `attrs.field`\ s. + + If *attrs* decides to look at type annotations, **all** fields + **must** be annotated. If *attrs* encounters a field that is set to + a :func:`field` / `attr.ib` but lacks a type annotation, an + `attrs.exceptions.UnannotatedAttributeError` is raised. Use + ``field_name: typing.Any = field(...)`` if you don't want to set a + type. + + .. warning:: + + For features that use the attribute name to create decorators + (for example, :ref:`validators `), you still *must* + assign :func:`field` / `attr.ib` to them. Otherwise Python will + either not find the name or try to use the default value to + call, for example, ``validator`` on it. + + Attributes annotated as `typing.ClassVar`, and attributes that are + neither annotated nor set to an `field()` are **ignored**. + + these (dict[str, object]): + A dictionary of name to the (private) return value of `field()` + mappings. This is useful to avoid the definition of your attributes + within the class body because you can't (for example, if you want + to add ``__repr__`` methods to Django models) or don't want to. + + If *these* is not `None`, *attrs* will *not* search the class body + for attributes and will *not* remove any attributes from it. + + The order is deduced from the order of the attributes inside + *these*. + + Arguably, this is a rather obscure feature. + + .. versionadded:: 20.1.0 + .. versionchanged:: 21.3.0 Converters are also run ``on_setattr``. + .. versionadded:: 22.2.0 + *unsafe_hash* as an alias for *hash* (for :pep:`681` compliance). + .. versionchanged:: 24.1.0 + Instances are not compared as tuples of attributes anymore, but using a + big ``and`` condition. This is faster and has more correct behavior for + uncomparable values like `math.nan`. + .. versionadded:: 24.1.0 + If a class has an *inherited* classmethod called + ``__attrs_init_subclass__``, it is executed after the class is created. + .. deprecated:: 24.1.0 *hash* is deprecated in favor of *unsafe_hash*. + .. versionadded:: 24.3.0 + Unless already present, a ``__replace__`` method is automatically + created for `copy.replace` (Python 3.13+ only). + .. versionchanged:: 25.4.0 + *kw_only* now only applies to attributes defined in the current class, + and respects attribute-level ``kw_only=False`` settings. + .. versionadded:: 25.4.0 + Added *force_kw_only* to go back to the previous *kw_only* behavior. + + .. note:: + + The main differences to the classic `attr.s` are: + + - Automatically detect whether or not *auto_attribs* should be `True` + (c.f. *auto_attribs* parameter). + - Converters and validators run when attributes are set by default -- + if *frozen* is `False`. + - *slots=True* + + Usually, this has only upsides and few visible effects in everyday + programming. But it *can* lead to some surprising behaviors, so + please make sure to read :term:`slotted classes`. + + - *auto_exc=True* + - *auto_detect=True* + - *order=False* + - *force_kw_only=False* + - Some options that were only relevant on Python 2 or were kept around + for backwards-compatibility have been removed. + + """ + + def do_it(cls, auto_attribs): + return attrs( + maybe_cls=cls, + these=these, + repr=repr, + hash=hash, + unsafe_hash=unsafe_hash, + init=init, + slots=slots, + frozen=frozen, + weakref_slot=weakref_slot, + str=str, + auto_attribs=auto_attribs, + kw_only=kw_only, + cache_hash=cache_hash, + auto_exc=auto_exc, + eq=eq, + order=order, + auto_detect=auto_detect, + collect_by_mro=True, + getstate_setstate=getstate_setstate, + on_setattr=on_setattr, + field_transformer=field_transformer, + match_args=match_args, + force_kw_only=force_kw_only, + ) + + def wrap(cls): + """ + Making this a wrapper ensures this code runs during class creation. + + We also ensure that frozen-ness of classes is inherited. + """ + nonlocal frozen, on_setattr + + had_on_setattr = on_setattr not in (None, setters.NO_OP) + + # By default, mutable classes convert & validate on setattr. + if frozen is False and on_setattr is None: + on_setattr = _DEFAULT_ON_SETATTR + + # However, if we subclass a frozen class, we inherit the immutability + # and disable on_setattr. + for base_cls in cls.__bases__: + if base_cls.__setattr__ is _frozen_setattrs: + if had_on_setattr: + msg = "Frozen classes can't use on_setattr (frozen-ness was inherited)." + raise ValueError(msg) + + on_setattr = setters.NO_OP + break + + if auto_attribs is not None: + return do_it(cls, auto_attribs) + + try: + return do_it(cls, True) + except UnannotatedAttributeError: + return do_it(cls, False) + + # maybe_cls's type depends on the usage of the decorator. It's a class + # if it's used as `@attrs` but `None` if used as `@attrs()`. + if maybe_cls is None: + return wrap + + return wrap(maybe_cls) + + +mutable = define +frozen = partial(define, frozen=True, on_setattr=None) + + +def field( + *, + default=NOTHING, + validator=None, + repr=True, + hash=None, + init=True, + metadata=None, + type=None, + converter=None, + factory=None, + kw_only=None, + eq=None, + order=None, + on_setattr=None, + alias=None, +): + """ + Create a new :term:`field` / :term:`attribute` on a class. + + .. warning:: + + Does **nothing** unless the class is also decorated with + `attrs.define` (or similar)! + + Args: + default: + A value that is used if an *attrs*-generated ``__init__`` is used + and no value is passed while instantiating or the attribute is + excluded using ``init=False``. + + If the value is an instance of `attrs.Factory`, its callable will + be used to construct a new value (useful for mutable data types + like lists or dicts). + + If a default is not set (or set manually to `attrs.NOTHING`), a + value *must* be supplied when instantiating; otherwise a + `TypeError` will be raised. + + .. seealso:: `defaults` + + factory (~typing.Callable): + Syntactic sugar for ``default=attr.Factory(factory)``. + + validator (~typing.Callable | list[~typing.Callable]): + Callable that is called by *attrs*-generated ``__init__`` methods + after the instance has been initialized. They receive the + initialized instance, the :func:`~attrs.Attribute`, and the passed + value. + + The return value is *not* inspected so the validator has to throw + an exception itself. + + If a `list` is passed, its items are treated as validators and must + all pass. + + Validators can be globally disabled and re-enabled using + `attrs.validators.get_disabled` / `attrs.validators.set_disabled`. + + The validator can also be set using decorator notation as shown + below. + + .. seealso:: :ref:`validators` + + repr (bool | ~typing.Callable): + Include this attribute in the generated ``__repr__`` method. If + True, include the attribute; if False, omit it. By default, the + built-in ``repr()`` function is used. To override how the attribute + value is formatted, pass a ``callable`` that takes a single value + and returns a string. Note that the resulting string is used as-is, + which means it will be used directly *instead* of calling + ``repr()`` (the default). + + eq (bool | ~typing.Callable): + If True (default), include this attribute in the generated + ``__eq__`` and ``__ne__`` methods that check two instances for + equality. To override how the attribute value is compared, pass a + callable that takes a single value and returns the value to be + compared. + + .. seealso:: `comparison` + + order (bool | ~typing.Callable): + If True (default), include this attributes in the generated + ``__lt__``, ``__le__``, ``__gt__`` and ``__ge__`` methods. To + override how the attribute value is ordered, pass a callable that + takes a single value and returns the value to be ordered. + + .. seealso:: `comparison` + + hash (bool | None): + Include this attribute in the generated ``__hash__`` method. If + None (default), mirror *eq*'s value. This is the correct behavior + according the Python spec. Setting this value to anything else + than None is *discouraged*. + + .. seealso:: `hashing` + + init (bool): + Include this attribute in the generated ``__init__`` method. + + It is possible to set this to False and set a default value. In + that case this attributed is unconditionally initialized with the + specified default value or factory. + + .. seealso:: `init` + + converter (typing.Callable | Converter): + A callable that is called by *attrs*-generated ``__init__`` methods + to convert attribute's value to the desired format. + + If a vanilla callable is passed, it is given the passed-in value as + the only positional argument. It is possible to receive additional + arguments by wrapping the callable in a `Converter`. + + Either way, the returned value will be used as the new value of the + attribute. The value is converted before being passed to the + validator, if any. + + .. seealso:: :ref:`converters` + + metadata (dict | None): + An arbitrary mapping, to be used by third-party code. + + .. seealso:: `extending-metadata`. + + type (type): + The type of the attribute. Nowadays, the preferred method to + specify the type is using a variable annotation (see :pep:`526`). + This argument is provided for backwards-compatibility and for usage + with `make_class`. Regardless of the approach used, the type will + be stored on ``Attribute.type``. + + Please note that *attrs* doesn't do anything with this metadata by + itself. You can use it as part of your own code or for `static type + checking `. + + kw_only (bool | None): + Make this attribute keyword-only in the generated ``__init__`` (if + *init* is False, this parameter is ignored). If None (default), + mirror the setting from `attrs.define`. + + on_setattr (~typing.Callable | list[~typing.Callable] | None | ~typing.Literal[attrs.setters.NO_OP]): + Allows to overwrite the *on_setattr* setting from `attr.s`. If left + None, the *on_setattr* value from `attr.s` is used. Set to + `attrs.setters.NO_OP` to run **no** `setattr` hooks for this + attribute -- regardless of the setting in `define()`. + + alias (str | None): + Override this attribute's parameter name in the generated + ``__init__`` method. If left None, default to ``name`` stripped + of leading underscores. See `private-attributes`. + + .. versionadded:: 20.1.0 + .. versionchanged:: 21.1.0 + *eq*, *order*, and *cmp* also accept a custom callable + .. versionadded:: 22.2.0 *alias* + .. versionadded:: 23.1.0 + The *type* parameter has been re-added; mostly for `attrs.make_class`. + Please note that type checkers ignore this metadata. + .. versionchanged:: 25.4.0 + *kw_only* can now be None, and its default is also changed from False to + None. + + .. seealso:: + + `attr.ib` + """ + return attrib( + default=default, + validator=validator, + repr=repr, + hash=hash, + init=init, + metadata=metadata, + type=type, + converter=converter, + factory=factory, + kw_only=kw_only, + eq=eq, + order=order, + on_setattr=on_setattr, + alias=alias, + ) + + +def asdict(inst, *, recurse=True, filter=None, value_serializer=None): + """ + Same as `attr.asdict`, except that collections types are always retained + and dict is always used as *dict_factory*. + + .. versionadded:: 21.3.0 + """ + return _asdict( + inst=inst, + recurse=recurse, + filter=filter, + value_serializer=value_serializer, + retain_collection_types=True, + ) + + +def astuple(inst, *, recurse=True, filter=None): + """ + Same as `attr.astuple`, except that collections types are always retained + and `tuple` is always used as the *tuple_factory*. + + .. versionadded:: 21.3.0 + """ + return _astuple( + inst=inst, recurse=recurse, filter=filter, retain_collection_types=True + ) + + +def inspect(cls): + """ + Inspect the class and return its effective build parameters. + + Warning: + This feature is currently **experimental** and is not covered by our + strict backwards-compatibility guarantees. + + Args: + cls: The *attrs*-decorated class to inspect. + + Returns: + The effective build parameters of the class. + + Raises: + NotAnAttrsClassError: If the class is not an *attrs*-decorated class. + + .. versionadded:: 25.4.0 + """ + try: + return cls.__dict__["__attrs_props__"] + except KeyError: + msg = f"{cls!r} is not an attrs-decorated class." + raise NotAnAttrsClassError(msg) from None diff --git a/attr/_typing_compat.pyi b/attr/_typing_compat.pyi new file mode 100644 index 0000000000000000000000000000000000000000..ca7b71e906a28f88726bbd342fdfe636af0281e7 --- /dev/null +++ b/attr/_typing_compat.pyi @@ -0,0 +1,15 @@ +from typing import Any, ClassVar, Protocol + +# MYPY is a special constant in mypy which works the same way as `TYPE_CHECKING`. +MYPY = False + +if MYPY: + # A protocol to be able to statically accept an attrs class. + class AttrsInstance_(Protocol): + __attrs_attrs__: ClassVar[Any] + +else: + # For type checkers without plug-in support use an empty protocol that + # will (hopefully) be combined into a union. + class AttrsInstance_(Protocol): + pass diff --git a/attr/_version_info.py b/attr/_version_info.py new file mode 100644 index 0000000000000000000000000000000000000000..27f18884ad4d7a42f338e31a8ea19bc5d19999cd --- /dev/null +++ b/attr/_version_info.py @@ -0,0 +1,89 @@ +# SPDX-License-Identifier: MIT + + +from functools import total_ordering + +from ._funcs import astuple +from ._make import attrib, attrs + + +@total_ordering +@attrs(eq=False, order=False, slots=True, frozen=True) +class VersionInfo: + """ + A version object that can be compared to tuple of length 1--4: + + >>> attr.VersionInfo(19, 1, 0, "final") <= (19, 2) + True + >>> attr.VersionInfo(19, 1, 0, "final") < (19, 1, 1) + True + >>> vi = attr.VersionInfo(19, 2, 0, "final") + >>> vi < (19, 1, 1) + False + >>> vi < (19,) + False + >>> vi == (19, 2,) + True + >>> vi == (19, 2, 1) + False + + .. versionadded:: 19.2 + """ + + year = attrib(type=int) + minor = attrib(type=int) + micro = attrib(type=int) + releaselevel = attrib(type=str) + + @classmethod + def _from_version_string(cls, s): + """ + Parse *s* and return a _VersionInfo. + """ + v = s.split(".") + if len(v) == 3: + v.append("final") + + return cls( + year=int(v[0]), minor=int(v[1]), micro=int(v[2]), releaselevel=v[3] + ) + + def _ensure_tuple(self, other): + """ + Ensure *other* is a tuple of a valid length. + + Returns a possibly transformed *other* and ourselves as a tuple of + the same length as *other*. + """ + + if self.__class__ is other.__class__: + other = astuple(other) + + if not isinstance(other, tuple): + raise NotImplementedError + + if not (1 <= len(other) <= 4): + raise NotImplementedError + + return astuple(self)[: len(other)], other + + def __eq__(self, other): + try: + us, them = self._ensure_tuple(other) + except NotImplementedError: + return NotImplemented + + return us == them + + def __lt__(self, other): + try: + us, them = self._ensure_tuple(other) + except NotImplementedError: + return NotImplemented + + # Since alphabetically "dev0" < "final" < "post1" < "post2", we don't + # have to do anything special with releaselevel for now. + return us < them + + def __hash__(self): + return hash((self.year, self.minor, self.micro, self.releaselevel)) diff --git a/attr/_version_info.pyi b/attr/_version_info.pyi new file mode 100644 index 0000000000000000000000000000000000000000..45ced086337783c4b73b26cd17d2c1c260e24029 --- /dev/null +++ b/attr/_version_info.pyi @@ -0,0 +1,9 @@ +class VersionInfo: + @property + def year(self) -> int: ... + @property + def minor(self) -> int: ... + @property + def micro(self) -> int: ... + @property + def releaselevel(self) -> str: ... diff --git a/attr/converters.py b/attr/converters.py new file mode 100644 index 0000000000000000000000000000000000000000..0a79deef04282fb33a42f6aca59563d49e70d4cb --- /dev/null +++ b/attr/converters.py @@ -0,0 +1,162 @@ +# SPDX-License-Identifier: MIT + +""" +Commonly useful converters. +""" + +import typing + +from ._compat import _AnnotationExtractor +from ._make import NOTHING, Converter, Factory, pipe + + +__all__ = [ + "default_if_none", + "optional", + "pipe", + "to_bool", +] + + +def optional(converter): + """ + A converter that allows an attribute to be optional. An optional attribute + is one which can be set to `None`. + + Type annotations will be inferred from the wrapped converter's, if it has + any. + + Args: + converter (typing.Callable): + the converter that is used for non-`None` values. + + .. versionadded:: 17.1.0 + """ + + if isinstance(converter, Converter): + + def optional_converter(val, inst, field): + if val is None: + return None + return converter(val, inst, field) + + else: + + def optional_converter(val): + if val is None: + return None + return converter(val) + + xtr = _AnnotationExtractor(converter) + + t = xtr.get_first_param_type() + if t: + optional_converter.__annotations__["val"] = typing.Optional[t] + + rt = xtr.get_return_type() + if rt: + optional_converter.__annotations__["return"] = typing.Optional[rt] + + if isinstance(converter, Converter): + return Converter(optional_converter, takes_self=True, takes_field=True) + + return optional_converter + + +def default_if_none(default=NOTHING, factory=None): + """ + A converter that allows to replace `None` values by *default* or the result + of *factory*. + + Args: + default: + Value to be used if `None` is passed. Passing an instance of + `attrs.Factory` is supported, however the ``takes_self`` option is + *not*. + + factory (typing.Callable): + A callable that takes no parameters whose result is used if `None` + is passed. + + Raises: + TypeError: If **neither** *default* or *factory* is passed. + + TypeError: If **both** *default* and *factory* are passed. + + ValueError: + If an instance of `attrs.Factory` is passed with + ``takes_self=True``. + + .. versionadded:: 18.2.0 + """ + if default is NOTHING and factory is None: + msg = "Must pass either `default` or `factory`." + raise TypeError(msg) + + if default is not NOTHING and factory is not None: + msg = "Must pass either `default` or `factory` but not both." + raise TypeError(msg) + + if factory is not None: + default = Factory(factory) + + if isinstance(default, Factory): + if default.takes_self: + msg = "`takes_self` is not supported by default_if_none." + raise ValueError(msg) + + def default_if_none_converter(val): + if val is not None: + return val + + return default.factory() + + else: + + def default_if_none_converter(val): + if val is not None: + return val + + return default + + return default_if_none_converter + + +def to_bool(val): + """ + Convert "boolean" strings (for example, from environment variables) to real + booleans. + + Values mapping to `True`: + + - ``True`` + - ``"true"`` / ``"t"`` + - ``"yes"`` / ``"y"`` + - ``"on"`` + - ``"1"`` + - ``1`` + + Values mapping to `False`: + + - ``False`` + - ``"false"`` / ``"f"`` + - ``"no"`` / ``"n"`` + - ``"off"`` + - ``"0"`` + - ``0`` + + Raises: + ValueError: For any other value. + + .. versionadded:: 21.3.0 + """ + if isinstance(val, str): + val = val.lower() + + if val in (True, "true", "t", "yes", "y", "on", "1", 1): + return True + if val in (False, "false", "f", "no", "n", "off", "0", 0): + return False + + msg = f"Cannot convert value to bool: {val!r}" + raise ValueError(msg) diff --git a/attr/converters.pyi b/attr/converters.pyi new file mode 100644 index 0000000000000000000000000000000000000000..12bd0c4f17bdc60fb8904598af0a3d56d5874a9e --- /dev/null +++ b/attr/converters.pyi @@ -0,0 +1,19 @@ +from typing import Callable, Any, overload + +from attrs import _ConverterType, _CallableConverterType + +@overload +def pipe(*validators: _CallableConverterType) -> _CallableConverterType: ... +@overload +def pipe(*validators: _ConverterType) -> _ConverterType: ... +@overload +def optional(converter: _CallableConverterType) -> _CallableConverterType: ... +@overload +def optional(converter: _ConverterType) -> _ConverterType: ... +@overload +def default_if_none(default: Any) -> _CallableConverterType: ... +@overload +def default_if_none( + *, factory: Callable[[], Any] +) -> _CallableConverterType: ... +def to_bool(val: str | int | bool) -> bool: ... diff --git a/attr/exceptions.py b/attr/exceptions.py new file mode 100644 index 0000000000000000000000000000000000000000..a207df4028f7800f964c2917383ad26be61b665e --- /dev/null +++ b/attr/exceptions.py @@ -0,0 +1,95 @@ +# SPDX-License-Identifier: MIT + +from __future__ import annotations + + +class FrozenError(AttributeError): + """ + A frozen/immutable instance or attribute have been attempted to be + modified. + + It mirrors the behavior of ``namedtuples`` by using the same error message + and subclassing `AttributeError`. + + .. versionadded:: 20.1.0 + """ + + def __init__(self): + msg = "can't set attribute" + super().__init__(msg) + self.msg = msg + + +class FrozenInstanceError(FrozenError): + """ + A frozen instance has been attempted to be modified. + + .. versionadded:: 16.1.0 + """ + + +class FrozenAttributeError(FrozenError): + """ + A frozen attribute has been attempted to be modified. + + .. versionadded:: 20.1.0 + """ + + +class AttrsAttributeNotFoundError(ValueError): + """ + An *attrs* function couldn't find an attribute that the user asked for. + + .. versionadded:: 16.2.0 + """ + + +class NotAnAttrsClassError(ValueError): + """ + A non-*attrs* class has been passed into an *attrs* function. + + .. versionadded:: 16.2.0 + """ + + +class DefaultAlreadySetError(RuntimeError): + """ + A default has been set when defining the field and is attempted to be reset + using the decorator. + + .. versionadded:: 17.1.0 + """ + + +class UnannotatedAttributeError(RuntimeError): + """ + A class with ``auto_attribs=True`` has a field without a type annotation. + + .. versionadded:: 17.3.0 + """ + + +class PythonTooOldError(RuntimeError): + """ + It was attempted to use an *attrs* feature that requires a newer Python + version. + + .. versionadded:: 18.2.0 + """ + + +class NotCallableError(TypeError): + """ + A field requiring a callable has been set with a value that is not + callable. + + .. versionadded:: 19.2.0 + """ + + def __init__(self, msg, value): + super(TypeError, self).__init__(msg, value) + self.msg = msg + self.value = value + + def __str__(self): + return str(self.msg) diff --git a/attr/exceptions.pyi b/attr/exceptions.pyi new file mode 100644 index 0000000000000000000000000000000000000000..f2680118b404db8f5227d04d27e8439331341c4d --- /dev/null +++ b/attr/exceptions.pyi @@ -0,0 +1,17 @@ +from typing import Any + +class FrozenError(AttributeError): + msg: str = ... + +class FrozenInstanceError(FrozenError): ... +class FrozenAttributeError(FrozenError): ... +class AttrsAttributeNotFoundError(ValueError): ... +class NotAnAttrsClassError(ValueError): ... +class DefaultAlreadySetError(RuntimeError): ... +class UnannotatedAttributeError(RuntimeError): ... +class PythonTooOldError(RuntimeError): ... + +class NotCallableError(TypeError): + msg: str = ... + value: Any = ... + def __init__(self, msg: str, value: Any) -> None: ... diff --git a/attr/filters.py b/attr/filters.py new file mode 100644 index 0000000000000000000000000000000000000000..689b1705a60ff110d6077bab996f8b4588e55b82 --- /dev/null +++ b/attr/filters.py @@ -0,0 +1,72 @@ +# SPDX-License-Identifier: MIT + +""" +Commonly useful filters for `attrs.asdict` and `attrs.astuple`. +""" + +from ._make import Attribute + + +def _split_what(what): + """ + Returns a tuple of `frozenset`s of classes and attributes. + """ + return ( + frozenset(cls for cls in what if isinstance(cls, type)), + frozenset(cls for cls in what if isinstance(cls, str)), + frozenset(cls for cls in what if isinstance(cls, Attribute)), + ) + + +def include(*what): + """ + Create a filter that only allows *what*. + + Args: + what (list[type, str, attrs.Attribute]): + What to include. Can be a type, a name, or an attribute. + + Returns: + Callable: + A callable that can be passed to `attrs.asdict`'s and + `attrs.astuple`'s *filter* argument. + + .. versionchanged:: 23.1.0 Accept strings with field names. + """ + cls, names, attrs = _split_what(what) + + def include_(attribute, value): + return ( + value.__class__ in cls + or attribute.name in names + or attribute in attrs + ) + + return include_ + + +def exclude(*what): + """ + Create a filter that does **not** allow *what*. + + Args: + what (list[type, str, attrs.Attribute]): + What to exclude. Can be a type, a name, or an attribute. + + Returns: + Callable: + A callable that can be passed to `attrs.asdict`'s and + `attrs.astuple`'s *filter* argument. + + .. versionchanged:: 23.3.0 Accept field name string as input argument + """ + cls, names, attrs = _split_what(what) + + def exclude_(attribute, value): + return not ( + value.__class__ in cls + or attribute.name in names + or attribute in attrs + ) + + return exclude_ diff --git a/attr/filters.pyi b/attr/filters.pyi new file mode 100644 index 0000000000000000000000000000000000000000..974abdcdb51152393d9c9e460c21aa025c45880c --- /dev/null +++ b/attr/filters.pyi @@ -0,0 +1,6 @@ +from typing import Any + +from . import Attribute, _FilterType + +def include(*what: type | str | Attribute[Any]) -> _FilterType[Any]: ... +def exclude(*what: type | str | Attribute[Any]) -> _FilterType[Any]: ... diff --git a/attr/py.typed b/attr/py.typed new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/attr/setters.py b/attr/setters.py new file mode 100644 index 0000000000000000000000000000000000000000..78b08398a6713fc5fa827c2dc853e0d05de743c4 --- /dev/null +++ b/attr/setters.py @@ -0,0 +1,79 @@ +# SPDX-License-Identifier: MIT + +""" +Commonly used hooks for on_setattr. +""" + +from . import _config +from .exceptions import FrozenAttributeError + + +def pipe(*setters): + """ + Run all *setters* and return the return value of the last one. + + .. versionadded:: 20.1.0 + """ + + def wrapped_pipe(instance, attrib, new_value): + rv = new_value + + for setter in setters: + rv = setter(instance, attrib, rv) + + return rv + + return wrapped_pipe + + +def frozen(_, __, ___): + """ + Prevent an attribute to be modified. + + .. versionadded:: 20.1.0 + """ + raise FrozenAttributeError + + +def validate(instance, attrib, new_value): + """ + Run *attrib*'s validator on *new_value* if it has one. + + .. versionadded:: 20.1.0 + """ + if _config._run_validators is False: + return new_value + + v = attrib.validator + if not v: + return new_value + + v(instance, attrib, new_value) + + return new_value + + +def convert(instance, attrib, new_value): + """ + Run *attrib*'s converter -- if it has one -- on *new_value* and return the + result. + + .. versionadded:: 20.1.0 + """ + c = attrib.converter + if c: + # This can be removed once we drop 3.8 and use attrs.Converter instead. + from ._make import Converter + + if not isinstance(c, Converter): + return c(new_value) + + return c(new_value, instance, attrib) + + return new_value + + +# Sentinel for disabling class-wide *on_setattr* hooks for certain attributes. +# Sphinx's autodata stopped working, so the docstring is inlined in the API +# docs. +NO_OP = object() diff --git a/attr/setters.pyi b/attr/setters.pyi new file mode 100644 index 0000000000000000000000000000000000000000..73abf36e7d5b0f5f56e7fddeee716824c1c60d58 --- /dev/null +++ b/attr/setters.pyi @@ -0,0 +1,20 @@ +from typing import Any, NewType, NoReturn, TypeVar + +from . import Attribute +from attrs import _OnSetAttrType + +_T = TypeVar("_T") + +def frozen( + instance: Any, attribute: Attribute[Any], new_value: Any +) -> NoReturn: ... +def pipe(*setters: _OnSetAttrType) -> _OnSetAttrType: ... +def validate(instance: Any, attribute: Attribute[_T], new_value: _T) -> _T: ... + +# convert is allowed to return Any, because they can be chained using pipe. +def convert( + instance: Any, attribute: Attribute[Any], new_value: Any +) -> Any: ... + +_NoOpType = NewType("_NoOpType", object) +NO_OP: _NoOpType diff --git a/attr/validators.py b/attr/validators.py new file mode 100644 index 0000000000000000000000000000000000000000..0b1a294432d294c4f154be2d9439d825c3ec0781 --- /dev/null +++ b/attr/validators.py @@ -0,0 +1,750 @@ +# SPDX-License-Identifier: MIT + +""" +Commonly useful validators. +""" + +import operator +import re + +from contextlib import contextmanager +from re import Pattern + +from ._config import get_run_validators, set_run_validators +from ._make import _AndValidator, and_, attrib, attrs +from .converters import default_if_none +from .exceptions import NotCallableError + + +__all__ = [ + "and_", + "deep_iterable", + "deep_mapping", + "disabled", + "ge", + "get_disabled", + "gt", + "in_", + "instance_of", + "is_callable", + "le", + "lt", + "matches_re", + "max_len", + "min_len", + "not_", + "optional", + "or_", + "set_disabled", +] + + +def set_disabled(disabled): + """ + Globally disable or enable running validators. + + By default, they are run. + + Args: + disabled (bool): If `True`, disable running all validators. + + .. warning:: + + This function is not thread-safe! + + .. versionadded:: 21.3.0 + """ + set_run_validators(not disabled) + + +def get_disabled(): + """ + Return a bool indicating whether validators are currently disabled or not. + + Returns: + bool:`True` if validators are currently disabled. + + .. versionadded:: 21.3.0 + """ + return not get_run_validators() + + +@contextmanager +def disabled(): + """ + Context manager that disables running validators within its context. + + .. warning:: + + This context manager is not thread-safe! + + .. versionadded:: 21.3.0 + .. versionchanged:: 26.1.0 The contextmanager is nestable. + """ + prev = get_run_validators() + set_run_validators(False) + try: + yield + finally: + set_run_validators(prev) + + +@attrs(repr=False, slots=True, unsafe_hash=True) +class _InstanceOfValidator: + type = attrib() + + def __call__(self, inst, attr, value): + """ + We use a callable class to be able to change the ``__repr__``. + """ + if not isinstance(value, self.type): + msg = f"'{attr.name}' must be {self.type!r} (got {value!r} that is a {value.__class__!r})." + raise TypeError( + msg, + attr, + self.type, + value, + ) + + def __repr__(self): + return f"" + + +def instance_of(type): + """ + A validator that raises a `TypeError` if the initializer is called with a + wrong type for this particular attribute (checks are performed using + `isinstance` therefore it's also valid to pass a tuple of types). + + Args: + type (type | tuple[type]): The type to check for. + + Raises: + TypeError: + With a human readable error message, the attribute (of type + `attrs.Attribute`), the expected type, and the value it got. + """ + return _InstanceOfValidator(type) + + +@attrs(repr=False, frozen=True, slots=True) +class _MatchesReValidator: + pattern = attrib() + match_func = attrib() + + def __call__(self, inst, attr, value): + """ + We use a callable class to be able to change the ``__repr__``. + """ + if not self.match_func(value): + msg = f"'{attr.name}' must match regex {self.pattern.pattern!r} ({value!r} doesn't)" + raise ValueError( + msg, + attr, + self.pattern, + value, + ) + + def __repr__(self): + return f"" + + +def matches_re(regex, flags=0, func=None): + r""" + A validator that raises `ValueError` if the initializer is called with a + string that doesn't match *regex*. + + Args: + regex (str, re.Pattern): + A regex string or precompiled pattern to match against + + flags (int): + Flags that will be passed to the underlying re function (default 0) + + func (typing.Callable): + Which underlying `re` function to call. Valid options are + `re.fullmatch`, `re.search`, and `re.match`; the default `None` + means `re.fullmatch`. For performance reasons, the pattern is + always precompiled using `re.compile`. + + .. versionadded:: 19.2.0 + .. versionchanged:: 21.3.0 *regex* can be a pre-compiled pattern. + """ + valid_funcs = (re.fullmatch, None, re.search, re.match) + if func not in valid_funcs: + msg = "'func' must be one of {}.".format( + ", ".join( + sorted((e and e.__name__) or "None" for e in set(valid_funcs)) + ) + ) + raise ValueError(msg) + + if isinstance(regex, Pattern): + if flags: + msg = "'flags' can only be used with a string pattern; pass flags to re.compile() instead" + raise TypeError(msg) + pattern = regex + else: + pattern = re.compile(regex, flags) + + if func is re.match: + match_func = pattern.match + elif func is re.search: + match_func = pattern.search + else: + match_func = pattern.fullmatch + + return _MatchesReValidator(pattern, match_func) + + +@attrs(repr=False, slots=True, unsafe_hash=True) +class _OptionalValidator: + validator = attrib() + + def __call__(self, inst, attr, value): + if value is None: + return + + self.validator(inst, attr, value) + + def __repr__(self): + return f"" + + +def optional(validator): + """ + A validator that makes an attribute optional. An optional attribute is one + which can be set to `None` in addition to satisfying the requirements of + the sub-validator. + + Args: + validator + (typing.Callable | tuple[typing.Callable] | list[typing.Callable]): + A validator (or validators) that is used for non-`None` values. + + .. versionadded:: 15.1.0 + .. versionchanged:: 17.1.0 *validator* can be a list of validators. + .. versionchanged:: 23.1.0 *validator* can also be a tuple of validators. + """ + if isinstance(validator, (list, tuple)): + return _OptionalValidator(_AndValidator(validator)) + + return _OptionalValidator(validator) + + +@attrs(repr=False, slots=True, unsafe_hash=True) +class _InValidator: + options = attrib() + _original_options = attrib(hash=False) + + def __call__(self, inst, attr, value): + try: + in_options = value in self.options + except TypeError: # e.g. `1 in "abc"` + in_options = False + + if not in_options: + msg = f"'{attr.name}' must be in {self._original_options!r} (got {value!r})" + raise ValueError( + msg, + attr, + self._original_options, + value, + ) + + def __repr__(self): + return f"" + + +def in_(options): + """ + A validator that raises a `ValueError` if the initializer is called with a + value that does not belong in the *options* provided. + + The check is performed using ``value in options``, so *options* has to + support that operation. + + To keep the validator hashable, dicts, lists, and sets are transparently + transformed into a `tuple`. + + Args: + options: Allowed options. + + Raises: + ValueError: + With a human readable error message, the attribute (of type + `attrs.Attribute`), the expected options, and the value it got. + + .. versionadded:: 17.1.0 + .. versionchanged:: 22.1.0 + The ValueError was incomplete until now and only contained the human + readable error message. Now it contains all the information that has + been promised since 17.1.0. + .. versionchanged:: 24.1.0 + *options* that are a list, dict, or a set are now transformed into a + tuple to keep the validator hashable. + """ + repr_options = options + if isinstance(options, (list, dict, set)): + options = tuple(options) + + return _InValidator(options, repr_options) + + +@attrs(repr=False, slots=False, unsafe_hash=True) +class _IsCallableValidator: + def __call__(self, inst, attr, value): + """ + We use a callable class to be able to change the ``__repr__``. + """ + if not callable(value): + message = ( + "'{name}' must be callable " + "(got {value!r} that is a {actual!r})." + ) + raise NotCallableError( + msg=message.format( + name=attr.name, value=value, actual=value.__class__ + ), + value=value, + ) + + def __repr__(self): + return "" + + +def is_callable(): + """ + A validator that raises a `attrs.exceptions.NotCallableError` if the + initializer is called with a value for this particular attribute that is + not callable. + + .. versionadded:: 19.1.0 + + Raises: + attrs.exceptions.NotCallableError: + With a human readable error message containing the attribute + (`attrs.Attribute`) name, and the value it got. + """ + return _IsCallableValidator() + + +@attrs(repr=False, slots=True, unsafe_hash=True) +class _DeepIterable: + member_validator = attrib(validator=is_callable()) + iterable_validator = attrib( + default=None, validator=optional(is_callable()) + ) + + def __call__(self, inst, attr, value): + """ + We use a callable class to be able to change the ``__repr__``. + """ + if self.iterable_validator is not None: + self.iterable_validator(inst, attr, value) + + for member in value: + self.member_validator(inst, attr, member) + + def __repr__(self): + iterable_identifier = ( + "" + if self.iterable_validator is None + else f" {self.iterable_validator!r}" + ) + return ( + f"" + ) + + +def deep_iterable(member_validator, iterable_validator=None): + """ + A validator that performs deep validation of an iterable. + + Args: + member_validator: Validator(s) to apply to iterable members. + + iterable_validator: + Validator(s) to apply to iterable itself (optional). + + Raises + TypeError: if any sub-validators fail + + .. versionadded:: 19.1.0 + + .. versionchanged:: 25.4.0 + *member_validator* and *iterable_validator* can now be a list or tuple + of validators. + """ + if isinstance(member_validator, (list, tuple)): + member_validator = and_(*member_validator) + if isinstance(iterable_validator, (list, tuple)): + iterable_validator = and_(*iterable_validator) + return _DeepIterable(member_validator, iterable_validator) + + +@attrs(repr=False, slots=True, unsafe_hash=True) +class _DeepMapping: + key_validator = attrib(validator=optional(is_callable())) + value_validator = attrib(validator=optional(is_callable())) + mapping_validator = attrib(validator=optional(is_callable())) + + def __call__(self, inst, attr, value): + """ + We use a callable class to be able to change the ``__repr__``. + """ + if self.mapping_validator is not None: + self.mapping_validator(inst, attr, value) + + for key in value: + if self.key_validator is not None: + self.key_validator(inst, attr, key) + if self.value_validator is not None: + self.value_validator(inst, attr, value[key]) + + def __repr__(self): + return f"" + + +def deep_mapping( + key_validator=None, value_validator=None, mapping_validator=None +): + """ + A validator that performs deep validation of a dictionary. + + All validators are optional, but at least one of *key_validator* or + *value_validator* must be provided. + + Args: + key_validator: Validator(s) to apply to dictionary keys. + + value_validator: Validator(s) to apply to dictionary values. + + mapping_validator: + Validator(s) to apply to top-level mapping attribute. + + .. versionadded:: 19.1.0 + + .. versionchanged:: 25.4.0 + *key_validator* and *value_validator* are now optional, but at least one + of them must be provided. + + .. versionchanged:: 25.4.0 + *key_validator*, *value_validator*, and *mapping_validator* can now be a + list or tuple of validators. + + Raises: + TypeError: If any sub-validator fails on validation. + + ValueError: + If neither *key_validator* nor *value_validator* is provided on + instantiation. + """ + if key_validator is None and value_validator is None: + msg = ( + "At least one of key_validator or value_validator must be provided" + ) + raise ValueError(msg) + + if isinstance(key_validator, (list, tuple)): + key_validator = and_(*key_validator) + if isinstance(value_validator, (list, tuple)): + value_validator = and_(*value_validator) + if isinstance(mapping_validator, (list, tuple)): + mapping_validator = and_(*mapping_validator) + + return _DeepMapping(key_validator, value_validator, mapping_validator) + + +@attrs(repr=False, frozen=True, slots=True) +class _NumberValidator: + bound = attrib() + compare_op = attrib() + compare_func = attrib() + + def __call__(self, inst, attr, value): + """ + We use a callable class to be able to change the ``__repr__``. + """ + if not self.compare_func(value, self.bound): + msg = f"'{attr.name}' must be {self.compare_op} {self.bound}: {value}" + raise ValueError(msg) + + def __repr__(self): + return f"" + + +def lt(val): + """ + A validator that raises `ValueError` if the initializer is called with a + number larger or equal to *val*. + + The validator uses `operator.lt` to compare the values. + + Args: + val: Exclusive upper bound for values. + + .. versionadded:: 21.3.0 + """ + return _NumberValidator(val, "<", operator.lt) + + +def le(val): + """ + A validator that raises `ValueError` if the initializer is called with a + number greater than *val*. + + The validator uses `operator.le` to compare the values. + + Args: + val: Inclusive upper bound for values. + + .. versionadded:: 21.3.0 + """ + return _NumberValidator(val, "<=", operator.le) + + +def ge(val): + """ + A validator that raises `ValueError` if the initializer is called with a + number smaller than *val*. + + The validator uses `operator.ge` to compare the values. + + Args: + val: Inclusive lower bound for values + + .. versionadded:: 21.3.0 + """ + return _NumberValidator(val, ">=", operator.ge) + + +def gt(val): + """ + A validator that raises `ValueError` if the initializer is called with a + number smaller or equal to *val*. + + The validator uses `operator.gt` to compare the values. + + Args: + val: Exclusive lower bound for values + + .. versionadded:: 21.3.0 + """ + return _NumberValidator(val, ">", operator.gt) + + +@attrs(repr=False, frozen=True, slots=True) +class _MaxLengthValidator: + max_length = attrib() + + def __call__(self, inst, attr, value): + """ + We use a callable class to be able to change the ``__repr__``. + """ + if len(value) > self.max_length: + msg = f"Length of '{attr.name}' must be <= {self.max_length}: {len(value)}" + raise ValueError(msg) + + def __repr__(self): + return f"" + + +def max_len(length): + """ + A validator that raises `ValueError` if the initializer is called + with a string or iterable that is longer than *length*. + + Args: + length (int): Maximum length of the string or iterable + + .. versionadded:: 21.3.0 + """ + return _MaxLengthValidator(length) + + +@attrs(repr=False, frozen=True, slots=True) +class _MinLengthValidator: + min_length = attrib() + + def __call__(self, inst, attr, value): + """ + We use a callable class to be able to change the ``__repr__``. + """ + if len(value) < self.min_length: + msg = f"Length of '{attr.name}' must be >= {self.min_length}: {len(value)}" + raise ValueError(msg) + + def __repr__(self): + return f"" + + +def min_len(length): + """ + A validator that raises `ValueError` if the initializer is called + with a string or iterable that is shorter than *length*. + + Args: + length (int): Minimum length of the string or iterable + + .. versionadded:: 22.1.0 + """ + return _MinLengthValidator(length) + + +@attrs(repr=False, slots=True, unsafe_hash=True) +class _SubclassOfValidator: + type = attrib() + + def __call__(self, inst, attr, value): + """ + We use a callable class to be able to change the ``__repr__``. + """ + if not issubclass(value, self.type): + msg = f"'{attr.name}' must be a subclass of {self.type!r} (got {value!r})." + raise TypeError( + msg, + attr, + self.type, + value, + ) + + def __repr__(self): + return f"" + + +def _subclass_of(type): + """ + A validator that raises a `TypeError` if the initializer is called with a + wrong type for this particular attribute (checks are performed using + `issubclass` therefore it's also valid to pass a tuple of types). + + Args: + type (type | tuple[type, ...]): The type(s) to check for. + + Raises: + TypeError: + With a human readable error message, the attribute (of type + `attrs.Attribute`), the expected type, and the value it got. + """ + return _SubclassOfValidator(type) + + +@attrs(repr=False, slots=True, unsafe_hash=True) +class _NotValidator: + validator = attrib() + msg = attrib( + converter=default_if_none( + "not_ validator child '{validator!r}' " + "did not raise a captured error" + ) + ) + exc_types = attrib( + validator=deep_iterable( + member_validator=_subclass_of(Exception), + iterable_validator=instance_of(tuple), + ), + ) + + def __call__(self, inst, attr, value): + try: + self.validator(inst, attr, value) + except self.exc_types: + pass # suppress error to invert validity + else: + raise ValueError( + self.msg.format( + validator=self.validator, + exc_types=self.exc_types, + ), + attr, + self.validator, + value, + self.exc_types, + ) + + def __repr__(self): + return f"" + + +def not_(validator, *, msg=None, exc_types=(ValueError, TypeError)): + """ + A validator that wraps and logically 'inverts' the validator passed to it. + It will raise a `ValueError` if the provided validator *doesn't* raise a + `ValueError` or `TypeError` (by default), and will suppress the exception + if the provided validator *does*. + + Intended to be used with existing validators to compose logic without + needing to create inverted variants, for example, ``not_(in_(...))``. + + Args: + validator: A validator to be logically inverted. + + msg (str): + Message to raise if validator fails. Formatted with keys + ``exc_types`` and ``validator``. + + exc_types (tuple[type, ...]): + Exception type(s) to capture. Other types raised by child + validators will not be intercepted and pass through. + + Raises: + ValueError: + With a human readable error message, the attribute (of type + `attrs.Attribute`), the validator that failed to raise an + exception, the value it got, and the expected exception types. + + .. versionadded:: 22.2.0 + """ + try: + exc_types = tuple(exc_types) + except TypeError: + exc_types = (exc_types,) + return _NotValidator(validator, msg, exc_types) + + +@attrs(repr=False, slots=True, unsafe_hash=True) +class _OrValidator: + validators = attrib() + + def __call__(self, inst, attr, value): + for v in self.validators: + try: + v(inst, attr, value) + except Exception: # noqa: BLE001, PERF203, S112 + continue + else: + return + + msg = f"None of {self.validators!r} satisfied for value {value!r}" + raise ValueError(msg) + + def __repr__(self): + return f"" + + +def or_(*validators): + """ + A validator that composes multiple validators into one. + + When called on a value, it runs all wrapped validators until one of them is + satisfied. + + Args: + validators (~collections.abc.Iterable[typing.Callable]): + Arbitrary number of validators. + + Raises: + ValueError: + If no validator is satisfied. Raised with a human-readable error + message listing all the wrapped validators and the value that + failed all of them. + + .. versionadded:: 24.1.0 + """ + vals = [] + for v in validators: + vals.extend(v.validators if isinstance(v, _OrValidator) else [v]) + + return _OrValidator(tuple(vals)) diff --git a/attr/validators.pyi b/attr/validators.pyi new file mode 100644 index 0000000000000000000000000000000000000000..18fb112c89562c2b9625645e0babe1207a02675f --- /dev/null +++ b/attr/validators.pyi @@ -0,0 +1,140 @@ +from types import UnionType +from typing import ( + Any, + AnyStr, + Callable, + Container, + ContextManager, + Iterable, + Mapping, + Match, + Pattern, + TypeVar, + overload, +) + +from attrs import _ValidatorType +from attrs import _ValidatorArgType + +_T = TypeVar("_T") +_T1 = TypeVar("_T1") +_T2 = TypeVar("_T2") +_T3 = TypeVar("_T3") +_T4 = TypeVar("_T4") +_T5 = TypeVar("_T5") +_T6 = TypeVar("_T6") +_I = TypeVar("_I", bound=Iterable) +_K = TypeVar("_K") +_V = TypeVar("_V") +_M = TypeVar("_M", bound=Mapping) + +def set_disabled(run: bool) -> None: ... +def get_disabled() -> bool: ... +def disabled() -> ContextManager[None]: ... + +# To be more precise on instance_of use some overloads. +# If there are more than 3 items in the tuple then we fall back to Any +@overload +def instance_of(type: type[_T]) -> _ValidatorType[_T]: ... +@overload +def instance_of(type: tuple[type[_T]]) -> _ValidatorType[_T]: ... +@overload +def instance_of( + type: tuple[type[_T1], type[_T2]], +) -> _ValidatorType[_T1 | _T2]: ... +@overload +def instance_of( + type: tuple[type[_T1], type[_T2], type[_T3]], +) -> _ValidatorType[_T1 | _T2 | _T3]: ... +@overload +def instance_of(type: tuple[type, ...]) -> _ValidatorType[Any]: ... +@overload +def instance_of(type: UnionType) -> _ValidatorType[Any]: ... +def optional( + validator: ( + _ValidatorType[_T] + | list[_ValidatorType[_T]] + | tuple[_ValidatorType[_T], ...] + ), +) -> _ValidatorType[_T | None]: ... +def in_(options: Container[_T]) -> _ValidatorType[_T]: ... +def and_(*validators: _ValidatorType[_T]) -> _ValidatorType[_T]: ... +def matches_re( + regex: Pattern[AnyStr] | AnyStr, + flags: int = ..., + func: Callable[[AnyStr, AnyStr, int], Match[AnyStr] | None] | None = ..., +) -> _ValidatorType[AnyStr]: ... +def deep_iterable( + member_validator: _ValidatorArgType[_T], + iterable_validator: _ValidatorArgType[_I] | None = ..., +) -> _ValidatorType[_I]: ... +@overload +def deep_mapping( + key_validator: _ValidatorArgType[_K], + value_validator: _ValidatorArgType[_V] | None = ..., + mapping_validator: _ValidatorArgType[_M] | None = ..., +) -> _ValidatorType[_M]: ... +@overload +def deep_mapping( + key_validator: _ValidatorArgType[_K] | None = ..., + value_validator: _ValidatorArgType[_V] = ..., + mapping_validator: _ValidatorArgType[_M] | None = ..., +) -> _ValidatorType[_M]: ... +def is_callable() -> _ValidatorType[_T]: ... +def lt(val: _T) -> _ValidatorType[_T]: ... +def le(val: _T) -> _ValidatorType[_T]: ... +def ge(val: _T) -> _ValidatorType[_T]: ... +def gt(val: _T) -> _ValidatorType[_T]: ... +def max_len(length: int) -> _ValidatorType[_T]: ... +def min_len(length: int) -> _ValidatorType[_T]: ... +def not_( + validator: _ValidatorType[_T], + *, + msg: str | None = None, + exc_types: type[Exception] | Iterable[type[Exception]] = ..., +) -> _ValidatorType[_T]: ... +@overload +def or_( + __v1: _ValidatorType[_T1], + __v2: _ValidatorType[_T2], +) -> _ValidatorType[_T1 | _T2]: ... +@overload +def or_( + __v1: _ValidatorType[_T1], + __v2: _ValidatorType[_T2], + __v3: _ValidatorType[_T3], +) -> _ValidatorType[_T1 | _T2 | _T3]: ... +@overload +def or_( + __v1: _ValidatorType[_T1], + __v2: _ValidatorType[_T2], + __v3: _ValidatorType[_T3], + __v4: _ValidatorType[_T4], +) -> _ValidatorType[_T1 | _T2 | _T3 | _T4]: ... +@overload +def or_( + __v1: _ValidatorType[_T1], + __v2: _ValidatorType[_T2], + __v3: _ValidatorType[_T3], + __v4: _ValidatorType[_T4], + __v5: _ValidatorType[_T5], +) -> _ValidatorType[_T1 | _T2 | _T3 | _T4 | _T5]: ... +@overload +def or_( + __v1: _ValidatorType[_T1], + __v2: _ValidatorType[_T2], + __v3: _ValidatorType[_T3], + __v4: _ValidatorType[_T4], + __v5: _ValidatorType[_T5], + __v6: _ValidatorType[_T6], +) -> _ValidatorType[_T1 | _T2 | _T3 | _T4 | _T5 | _T6]: ... +@overload +def or_( + __v1: _ValidatorType[Any], + __v2: _ValidatorType[Any], + __v3: _ValidatorType[Any], + __v4: _ValidatorType[Any], + __v5: _ValidatorType[Any], + __v6: _ValidatorType[Any], + *validators: _ValidatorType[Any], +) -> _ValidatorType[Any]: ... diff --git a/certifi/__init__.py b/certifi/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..16c0c7c268f3d28336595254df687d2f5f48b574 --- /dev/null +++ b/certifi/__init__.py @@ -0,0 +1,4 @@ +from .core import contents, where + +__all__ = ["contents", "where"] +__version__ = "2026.02.25" diff --git a/certifi/__main__.py b/certifi/__main__.py new file mode 100644 index 0000000000000000000000000000000000000000..8945b5da857f4a7dec2b84f1225f012f6098418c --- /dev/null +++ b/certifi/__main__.py @@ -0,0 +1,12 @@ +import argparse + +from certifi import contents, where + +parser = argparse.ArgumentParser() +parser.add_argument("-c", "--contents", action="store_true") +args = parser.parse_args() + +if args.contents: + print(contents()) +else: + print(where()) diff --git a/certifi/cacert.pem b/certifi/cacert.pem new file mode 100644 index 0000000000000000000000000000000000000000..5ec1afe02d4d859082d132cf74f4c56954e3d6be --- /dev/null +++ b/certifi/cacert.pem @@ -0,0 +1,4494 @@ + +# Issuer: CN=QuoVadis Root CA 2 O=QuoVadis Limited +# Subject: CN=QuoVadis Root CA 2 O=QuoVadis Limited +# Label: "QuoVadis Root CA 2" +# Serial: 1289 +# MD5 Fingerprint: 5e:39:7b:dd:f8:ba:ec:82:e9:ac:62:ba:0c:54:00:2b +# SHA1 Fingerprint: ca:3a:fb:cf:12:40:36:4b:44:b2:16:20:88:80:48:39:19:93:7c:f7 +# SHA256 Fingerprint: 85:a0:dd:7d:d7:20:ad:b7:ff:05:f8:3d:54:2b:20:9d:c7:ff:45:28:f7:d6:77:b1:83:89:fe:a5:e5:c4:9e:86 +-----BEGIN CERTIFICATE----- +MIIFtzCCA5+gAwIBAgICBQkwDQYJKoZIhvcNAQEFBQAwRTELMAkGA1UEBhMCQk0x +GTAXBgNVBAoTEFF1b1ZhZGlzIExpbWl0ZWQxGzAZBgNVBAMTElF1b1ZhZGlzIFJv +b3QgQ0EgMjAeFw0wNjExMjQxODI3MDBaFw0zMTExMjQxODIzMzNaMEUxCzAJBgNV +BAYTAkJNMRkwFwYDVQQKExBRdW9WYWRpcyBMaW1pdGVkMRswGQYDVQQDExJRdW9W +YWRpcyBSb290IENBIDIwggIiMA0GCSqGSIb3DQEBAQUAA4ICDwAwggIKAoICAQCa +GMpLlA0ALa8DKYrwD4HIrkwZhR0In6spRIXzL4GtMh6QRr+jhiYaHv5+HBg6XJxg +Fyo6dIMzMH1hVBHL7avg5tKifvVrbxi3Cgst/ek+7wrGsxDp3MJGF/hd/aTa/55J +WpzmM+Yklvc/ulsrHHo1wtZn/qtmUIttKGAr79dgw8eTvI02kfN/+NsRE8Scd3bB +rrcCaoF6qUWD4gXmuVbBlDePSHFjIuwXZQeVikvfj8ZaCuWw419eaxGrDPmF60Tp ++ARz8un+XJiM9XOva7R+zdRcAitMOeGylZUtQofX1bOQQ7dsE/He3fbE+Ik/0XX1 +ksOR1YqI0JDs3G3eicJlcZaLDQP9nL9bFqyS2+r+eXyt66/3FsvbzSUr5R/7mp/i +Ucw6UwxI5g69ybR2BlLmEROFcmMDBOAENisgGQLodKcftslWZvB1JdxnwQ5hYIiz +PtGo/KPaHbDRsSNU30R2be1B2MGyIrZTHN81Hdyhdyox5C315eXbyOD/5YDXC2Og 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Inc OU=www.digicert.com +# Subject: CN=DigiCert Global Root CA O=DigiCert Inc OU=www.digicert.com +# Label: "DigiCert Global Root CA" +# Serial: 10944719598952040374951832963794454346 +# MD5 Fingerprint: 79:e4:a9:84:0d:7d:3a:96:d7:c0:4f:e2:43:4c:89:2e +# SHA1 Fingerprint: a8:98:5d:3a:65:e5:e5:c4:b2:d7:d6:6d:40:c6:dd:2f:b1:9c:54:36 +# SHA256 Fingerprint: 43:48:a0:e9:44:4c:78:cb:26:5e:05:8d:5e:89:44:b4:d8:4f:96:62:bd:26:db:25:7f:89:34:a4:43:c7:01:61 +-----BEGIN CERTIFICATE----- +MIIDrzCCApegAwIBAgIQCDvgVpBCRrGhdWrJWZHHSjANBgkqhkiG9w0BAQUFADBh +MQswCQYDVQQGEwJVUzEVMBMGA1UEChMMRGlnaUNlcnQgSW5jMRkwFwYDVQQLExB3 +d3cuZGlnaWNlcnQuY29tMSAwHgYDVQQDExdEaWdpQ2VydCBHbG9iYWwgUm9vdCBD +QTAeFw0wNjExMTAwMDAwMDBaFw0zMTExMTAwMDAwMDBaMGExCzAJBgNVBAYTAlVT +MRUwEwYDVQQKEwxEaWdpQ2VydCBJbmMxGTAXBgNVBAsTEHd3dy5kaWdpY2VydC5j +b20xIDAeBgNVBAMTF0RpZ2lDZXJ0IEdsb2JhbCBSb290IENBMIIBIjANBgkqhkiG +9w0BAQEFAAOCAQ8AMIIBCgKCAQEA4jvhEXLeqKTTo1eqUKKPC3eQyaKl7hLOllsB 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Root CA O=DigiCert Inc OU=www.digicert.com +# Label: "DigiCert High Assurance EV Root CA" +# Serial: 3553400076410547919724730734378100087 +# MD5 Fingerprint: d4:74:de:57:5c:39:b2:d3:9c:85:83:c5:c0:65:49:8a +# SHA1 Fingerprint: 5f:b7:ee:06:33:e2:59:db:ad:0c:4c:9a:e6:d3:8f:1a:61:c7:dc:25 +# SHA256 Fingerprint: 74:31:e5:f4:c3:c1:ce:46:90:77:4f:0b:61:e0:54:40:88:3b:a9:a0:1e:d0:0b:a6:ab:d7:80:6e:d3:b1:18:cf +-----BEGIN CERTIFICATE----- +MIIDxTCCAq2gAwIBAgIQAqxcJmoLQJuPC3nyrkYldzANBgkqhkiG9w0BAQUFADBs +MQswCQYDVQQGEwJVUzEVMBMGA1UEChMMRGlnaUNlcnQgSW5jMRkwFwYDVQQLExB3 +d3cuZGlnaWNlcnQuY29tMSswKQYDVQQDEyJEaWdpQ2VydCBIaWdoIEFzc3VyYW5j +ZSBFViBSb290IENBMB4XDTA2MTExMDAwMDAwMFoXDTMxMTExMDAwMDAwMFowbDEL +MAkGA1UEBhMCVVMxFTATBgNVBAoTDERpZ2lDZXJ0IEluYzEZMBcGA1UECxMQd3d3 +LmRpZ2ljZXJ0LmNvbTErMCkGA1UEAxMiRGlnaUNlcnQgSGlnaCBBc3N1cmFuY2Ug +RVYgUm9vdCBDQTCCASIwDQYJKoZIhvcNAQEBBQADggEPADCCAQoCggEBAMbM5XPm ++9S75S0tMqbf5YE/yc0lSbZxKsPVlDRnogocsF9ppkCxxLeyj9CYpKlBWTrT3JTW 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13492815561806991280 +# MD5 Fingerprint: 24:77:d9:a8:91:d1:3b:fa:88:2d:c2:ff:f8:cd:33:93 +# SHA1 Fingerprint: d8:c5:38:8a:b7:30:1b:1b:6e:d4:7a:e6:45:25:3a:6f:9f:1a:27:61 +# SHA256 Fingerprint: 62:dd:0b:e9:b9:f5:0a:16:3e:a0:f8:e7:5c:05:3b:1e:ca:57:ea:55:c8:68:8f:64:7c:68:81:f2:c8:35:7b:95 +-----BEGIN CERTIFICATE----- +MIIFujCCA6KgAwIBAgIJALtAHEP1Xk+wMA0GCSqGSIb3DQEBBQUAMEUxCzAJBgNV +BAYTAkNIMRUwEwYDVQQKEwxTd2lzc1NpZ24gQUcxHzAdBgNVBAMTFlN3aXNzU2ln +biBHb2xkIENBIC0gRzIwHhcNMDYxMDI1MDgzMDM1WhcNMzYxMDI1MDgzMDM1WjBF +MQswCQYDVQQGEwJDSDEVMBMGA1UEChMMU3dpc3NTaWduIEFHMR8wHQYDVQQDExZT +d2lzc1NpZ24gR29sZCBDQSAtIEcyMIICIjANBgkqhkiG9w0BAQEFAAOCAg8AMIIC +CgKCAgEAr+TufoskDhJuqVAtFkQ7kpJcyrhdhJJCEyq8ZVeCQD5XJM1QiyUqt2/8 +76LQwB8CJEoTlo8jE+YoWACjR8cGp4QjK7u9lit/VcyLwVcfDmJlD909Vopz2q5+ +bbqBHH5CjCA12UNNhPqE21Is8w4ndwtrvxEvcnifLtg+5hg3Wipy+dpikJKVyh+c +6bM8K8vzARO/Ws/BtQpgvd21mWRTuKCWs2/iJneRjOBiEAKfNA+k1ZIzUd6+jbqE +emA8atufK+ze3gE/bk3lUIbLtK/tREDFylqM2tIrfKjuvqblCqoOpd8FUrdVxyJd 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b1:2e:13:63:45:86:a4:6f:1a:b2:60:68:37:58:2d:c4:ac:fd:94:97 +# SHA256 Fingerprint: e3:b6:a2:db:2e:d7:ce:48:84:2f:7a:c5:32:41:c7:b7:1d:54:14:4b:fb:40:c1:1f:3f:1d:0b:42:f5:ee:a1:2d +-----BEGIN CERTIFICATE----- +MIIDqDCCApCgAwIBAgIJAP7c4wEPyUj/MA0GCSqGSIb3DQEBBQUAMDQxCzAJBgNV +BAYTAkZSMRIwEAYDVQQKDAlEaGlteW90aXMxETAPBgNVBAMMCENlcnRpZ25hMB4X +DTA3MDYyOTE1MTMwNVoXDTI3MDYyOTE1MTMwNVowNDELMAkGA1UEBhMCRlIxEjAQ +BgNVBAoMCURoaW15b3RpczERMA8GA1UEAwwIQ2VydGlnbmEwggEiMA0GCSqGSIb3 +DQEBAQUAA4IBDwAwggEKAoIBAQDIaPHJ1tazNHUmgh7stL7qXOEm7RFHYeGifBZ4 +QCHkYJ5ayGPhxLGWkv8YbWkj4Sti993iNi+RB7lIzw7sebYs5zRLcAglozyHGxny +gQcPOJAZ0xH+hrTy0V4eHpbNgGzOOzGTtvKg0KmVEn2lmsxryIRWijOp5yIVUxbw +zBfsV1/pogqYCd7jX5xv3EjjhQsVWqa6n6xI4wmy9/Qy3l40vhx4XUJbzg4ij02Q +130yGLMLLGq/jj8UEYkgDncUtT2UCIf3JR7VsmAA7G8qKCVuKj4YYxclPz5EIBb2 +JsglrgVKtOdjLPOMFlN+XPsRGgjBRmKfIrjxwo1p3Po6WAbfAgMBAAGjgbwwgbkw +DwYDVR0TAQH/BAUwAwEB/zAdBgNVHQ4EFgQUGu3+QTmQtCRZvgHyUtVF9lo53BEw +ZAYDVR0jBF0wW4AUGu3+QTmQtCRZvgHyUtVF9lo53BGhOKQ2MDQxCzAJBgNVBAYT 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OU=ePKI Root Certification Authority +# Subject: O=Chunghwa Telecom Co., Ltd. OU=ePKI Root Certification Authority +# Label: "ePKI Root Certification Authority" +# Serial: 28956088682735189655030529057352760477 +# MD5 Fingerprint: 1b:2e:00:ca:26:06:90:3d:ad:fe:6f:15:68:d3:6b:b3 +# SHA1 Fingerprint: 67:65:0d:f1:7e:8e:7e:5b:82:40:a4:f4:56:4b:cf:e2:3d:69:c6:f0 +# SHA256 Fingerprint: c0:a6:f4:dc:63:a2:4b:fd:cf:54:ef:2a:6a:08:2a:0a:72:de:35:80:3e:2f:f5:ff:52:7a:e5:d8:72:06:df:d5 +-----BEGIN CERTIFICATE----- +MIIFsDCCA5igAwIBAgIQFci9ZUdcr7iXAF7kBtK8nTANBgkqhkiG9w0BAQUFADBe +MQswCQYDVQQGEwJUVzEjMCEGA1UECgwaQ2h1bmdod2EgVGVsZWNvbSBDby4sIEx0 +ZC4xKjAoBgNVBAsMIWVQS0kgUm9vdCBDZXJ0aWZpY2F0aW9uIEF1dGhvcml0eTAe +Fw0wNDEyMjAwMjMxMjdaFw0zNDEyMjAwMjMxMjdaMF4xCzAJBgNVBAYTAlRXMSMw +IQYDVQQKDBpDaHVuZ2h3YSBUZWxlY29tIENvLiwgTHRkLjEqMCgGA1UECwwhZVBL +SSBSb290IENlcnRpZmljYXRpb24gQXV0aG9yaXR5MIICIjANBgkqhkiG9w0BAQEF +AAOCAg8AMIICCgKCAgEA4SUP7o3biDN1Z82tH306Tm2d0y8U82N0ywEhajfqhFAH +SyZbCUNsIZ5qyNUD9WBpj8zwIuQf5/dqIjG3LBXy4P4AakP/h2XGtRrBp0xtInAh +ijHyl3SJCRImHJ7K2RKilTza6We/CKBk49ZCt0Xvl/T29de1ShUCWH2YWEtgvM3X +DZoTM1PRYfl61dd4s5oz9wCGzh1NlDivqOx4UXCKXBCDUSH3ET00hl7lSM2XgYI1 +TBnsZfZrxQWh7kcT1rMhJ5QQCtkkO7q+RBNGMD+XPNjX12ruOzjjK9SXDrkb5wdJ +fzcq+Xd4z1TtW0ado4AOkUPB1ltfFLqfpo0kR0BZv3I4sjZsN/+Z0V0OWQqraffA +sgRFelQArr5T9rXn4fg8ozHSqf4hUmTFpmfwdQcGlBSBVcYn5AGPF8Fqcde+S/uU +WH1+ETOxQvdibBjWzwloPn9s9h6PYq2lY9sJpx8iQkEeb5mKPtf5P0B6ebClAZLS +nT0IFaUQAS2zMnaolQ2zepr7BxB4EW/hj8e6DyUadCrlHJhBmd8hh+iVBmoKs2pH +dmX2Os+PYhcZewoozRrSgx4hxyy/vv9haLdnG7t4TY3OZ+XkwY63I2binZB1NJip +NiuKmpS5nezMirH4JYlcWrYvjB9teSSnUmjDhDXiZo1jDiVN1Rmy5nk3pyKdVDEC +AwEAAaNqMGgwHQYDVR0OBBYEFB4M97Zn8uGSJglFwFU5Lnc/QkqiMAwGA1UdEwQF +MAMBAf8wOQYEZyoHAAQxMC8wLQIBADAJBgUrDgMCGgUAMAcGBWcqAwAABBRFsMLH +ClZ87lt4DJX5GFPBphzYEDANBgkqhkiG9w0BAQUFAAOCAgEACbODU1kBPpVJufGB +uvl2ICO1J2B01GqZNF5sAFPZn/KmsSQHRGoqxqWOeBLoR9lYGxMqXnmbnwoqZ6Yl +PwZpVnPDimZI+ymBV3QGypzqKOg4ZyYr8dW1P2WT+DZdjo2NQCCHGervJ8A9tDkP +JXtoUHRVnAxZfVo9QZQlUgjgRywVMRnVvwdVxrsStZf0X4OFunHB2WyBEXYKCrC/ +gpf36j36+uwtqSiUO1bd0lEursC9CBWMd1I0ltabrNMdjmEPNXubrjlpC2JgQCA2 +j6/7Nu4tCEoduL+bXPjqpRugc6bY+G7gMwRfaKonh+3ZwZCc7b3jajWvY9+rGNm6 +5ulK6lCKD2GTHuItGeIwlDWSXQ62B68ZgI9HkFFLLk3dheLSClIKF5r8GrBQAuUB +o2M3IUxExJtRmREOc5wGj1QupyheRDmHVi03vYVElOEMSyycw5KFNGHLD7ibSkNS +/jQ6fbjpKdx2qcgw+BRxgMYeNkh0IkFch4LoGHGLQYlE535YW6i4jRPpp2zDR+2z +Gp1iro2C6pSe3VkQw63d4k3jMdXH7OjysP6SHhYKGvzZ8/gntsm+HbRsZJB/9OTE +W9c3rkIO3aQab3yIVMUWbuF6aC74Or8NpDyJO3inTmODBCEIZ43ygknQW/2xzQ+D +hNQ+IIX3Sj0rnP0qCglN6oH4EZw= +-----END CERTIFICATE----- + +# Issuer: O=certSIGN OU=certSIGN ROOT CA +# Subject: O=certSIGN OU=certSIGN ROOT CA +# Label: "certSIGN ROOT CA" +# Serial: 35210227249154 +# MD5 Fingerprint: 18:98:c0:d6:e9:3a:fc:f9:b0:f5:0c:f7:4b:01:44:17 +# SHA1 Fingerprint: fa:b7:ee:36:97:26:62:fb:2d:b0:2a:f6:bf:03:fd:e8:7c:4b:2f:9b +# SHA256 Fingerprint: ea:a9:62:c4:fa:4a:6b:af:eb:e4:15:19:6d:35:1c:cd:88:8d:4f:53:f3:fa:8a:e6:d7:c4:66:a9:4e:60:42:bb +-----BEGIN CERTIFICATE----- +MIIDODCCAiCgAwIBAgIGIAYFFnACMA0GCSqGSIb3DQEBBQUAMDsxCzAJBgNVBAYT +AlJPMREwDwYDVQQKEwhjZXJ0U0lHTjEZMBcGA1UECxMQY2VydFNJR04gUk9PVCBD +QTAeFw0wNjA3MDQxNzIwMDRaFw0zMTA3MDQxNzIwMDRaMDsxCzAJBgNVBAYTAlJP +MREwDwYDVQQKEwhjZXJ0U0lHTjEZMBcGA1UECxMQY2VydFNJR04gUk9PVCBDQTCC +ASIwDQYJKoZIhvcNAQEBBQADggEPADCCAQoCggEBALczuX7IJUqOtdu0KBuqV5Do +0SLTZLrTk+jUrIZhQGpgV2hUhE28alQCBf/fm5oqrl0Hj0rDKH/v+yv6efHHrfAQ +UySQi2bJqIirr1qjAOm+ukbuW3N7LBeCgV5iLKECZbO9xSsAfsT8AzNXDe3i+s5d +RdY4zTW2ssHQnIFKquSyAVwdj1+ZxLGt24gh65AIgoDzMKND5pCCrlUoSe1b16kQ +OA7+j0xbm0bqQfWwCHTD0IgztnzXdN/chNFDDnU5oSVAKOp4yw4sLjmdjItuFhwv +JoIQ4uNllAoEwF73XVv4EOLQunpL+943AAAaWyjj0pxzPjKHmKHJUS/X3qwzs08C +AwEAAaNCMEAwDwYDVR0TAQH/BAUwAwEB/zAOBgNVHQ8BAf8EBAMCAcYwHQYDVR0O +BBYEFOCMm9slSbPxfIbWskKHC9BroNnkMA0GCSqGSIb3DQEBBQUAA4IBAQA+0hyJ +LjX8+HXd5n9liPRyTMks1zJO890ZeUe9jjtbkw9QSSQTaxQGcu8J06Gh40CEyecY +MnQ8SG4Pn0vU9x7Tk4ZkVJdjclDVVc/6IJMCopvDI5NOFlV2oHB5bc0hH88vLbwZ +44gx+FkagQnIl6Z0x2DEW8xXjrJ1/RsCCdtZb3KTafcxQdaIOL+Hsr0Wefmq5L6I +Jd1hJyMctTEHBDa0GpC9oHRxUIltvBTjD4au8as+x6AJzKNI0eDbZOeStc+vckNw +i/nDhDwTqn6Sm1dTk/pwwpEOMfmbZ13pljheX7NzTogVZ96edhBiIL5VaZVDADlN +9u6wWk5JRFRYX0KD +-----END CERTIFICATE----- + +# Issuer: CN=NetLock Arany (Class Gold) F\u0151tan\xfas\xedtv\xe1ny O=NetLock Kft. OU=Tan\xfas\xedtv\xe1nykiad\xf3k (Certification Services) +# Subject: CN=NetLock Arany (Class Gold) F\u0151tan\xfas\xedtv\xe1ny O=NetLock Kft. OU=Tan\xfas\xedtv\xe1nykiad\xf3k (Certification Services) +# Label: "NetLock Arany (Class Gold) F\u0151tan\xfas\xedtv\xe1ny" +# Serial: 80544274841616 +# MD5 Fingerprint: c5:a1:b7:ff:73:dd:d6:d7:34:32:18:df:fc:3c:ad:88 +# SHA1 Fingerprint: 06:08:3f:59:3f:15:a1:04:a0:69:a4:6b:a9:03:d0:06:b7:97:09:91 +# SHA256 Fingerprint: 6c:61:da:c3:a2:de:f0:31:50:6b:e0:36:d2:a6:fe:40:19:94:fb:d1:3d:f9:c8:d4:66:59:92:74:c4:46:ec:98 +-----BEGIN CERTIFICATE----- +MIIEFTCCAv2gAwIBAgIGSUEs5AAQMA0GCSqGSIb3DQEBCwUAMIGnMQswCQYDVQQG +EwJIVTERMA8GA1UEBwwIQnVkYXBlc3QxFTATBgNVBAoMDE5ldExvY2sgS2Z0LjE3 +MDUGA1UECwwuVGFuw7pzw610dsOhbnlraWFkw7NrIChDZXJ0aWZpY2F0aW9uIFNl +cnZpY2VzKTE1MDMGA1UEAwwsTmV0TG9jayBBcmFueSAoQ2xhc3MgR29sZCkgRsWR +dGFuw7pzw610dsOhbnkwHhcNMDgxMjExMTUwODIxWhcNMjgxMjA2MTUwODIxWjCB +pzELMAkGA1UEBhMCSFUxETAPBgNVBAcMCEJ1ZGFwZXN0MRUwEwYDVQQKDAxOZXRM +b2NrIEtmdC4xNzA1BgNVBAsMLlRhbsO6c8OtdHbDoW55a2lhZMOzayAoQ2VydGlm +aWNhdGlvbiBTZXJ2aWNlcykxNTAzBgNVBAMMLE5ldExvY2sgQXJhbnkgKENsYXNz +IEdvbGQpIEbFkXRhbsO6c8OtdHbDoW55MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8A +MIIBCgKCAQEAxCRec75LbRTDofTjl5Bu0jBFHjzuZ9lk4BqKf8owyoPjIMHj9DrT +lF8afFttvzBPhCf2nx9JvMaZCpDyD/V/Q4Q3Y1GLeqVw/HpYzY6b7cNGbIRwXdrz +AZAj/E4wqX7hJ2Pn7WQ8oLjJM2P+FpD/sLj916jAwJRDC7bVWaaeVtAkH3B5r9s5 +VA1lddkVQZQBr17s9o3x/61k/iCa11zr/qYfCGSji3ZVrR47KGAuhyXoqq8fxmRG +ILdwfzzeSNuWU7c5d+Qa4scWhHaXWy+7GRWF+GmF9ZmnqfI0p6m2pgP8b4Y9VHx2 +BJtr+UBdADTHLpl1neWIA6pN+APSQnbAGwIDAKiLo0UwQzASBgNVHRMBAf8ECDAG +AQH/AgEEMA4GA1UdDwEB/wQEAwIBBjAdBgNVHQ4EFgQUzPpnk/C2uNClwB7zU/2M +U9+D15YwDQYJKoZIhvcNAQELBQADggEBAKt/7hwWqZw8UQCgwBEIBaeZ5m8BiFRh +bvG5GK1Krf6BQCOUL/t1fC8oS2IkgYIL9WHxHG64YTjrgfpioTtaYtOUZcTh5m2C ++C8lcLIhJsFyUR+MLMOEkMNaj7rP9KdlpeuY0fsFskZ1FSNqb4VjMIDw1Z4fKRzC +bLBQWV2QWzuoDTDPv31/zvGdg73JRm4gpvlhUbohL3u+pRVjodSVh/GeufOJ8z2F +uLjbvrW5KfnaNwUASZQDhETnv0Mxz3WLJdH0pmT1kvarBes96aULNmLazAZfNou2 +XjG4Kvte9nHfRCaexOYNkbQudZWAUWpLMKawYqGT8ZvYzsRjdT9ZR7E= +-----END CERTIFICATE----- + +# Issuer: CN=Microsec e-Szigno Root CA 2009 O=Microsec Ltd. +# Subject: CN=Microsec e-Szigno Root CA 2009 O=Microsec Ltd. +# Label: "Microsec e-Szigno Root CA 2009" +# Serial: 14014712776195784473 +# MD5 Fingerprint: f8:49:f4:03:bc:44:2d:83:be:48:69:7d:29:64:fc:b1 +# SHA1 Fingerprint: 89:df:74:fe:5c:f4:0f:4a:80:f9:e3:37:7d:54:da:91:e1:01:31:8e +# SHA256 Fingerprint: 3c:5f:81:fe:a5:fa:b8:2c:64:bf:a2:ea:ec:af:cd:e8:e0:77:fc:86:20:a7:ca:e5:37:16:3d:f3:6e:db:f3:78 +-----BEGIN CERTIFICATE----- +MIIECjCCAvKgAwIBAgIJAMJ+QwRORz8ZMA0GCSqGSIb3DQEBCwUAMIGCMQswCQYD +VQQGEwJIVTERMA8GA1UEBwwIQnVkYXBlc3QxFjAUBgNVBAoMDU1pY3Jvc2VjIEx0 +ZC4xJzAlBgNVBAMMHk1pY3Jvc2VjIGUtU3ppZ25vIFJvb3QgQ0EgMjAwOTEfMB0G +CSqGSIb3DQEJARYQaW5mb0BlLXN6aWduby5odTAeFw0wOTA2MTYxMTMwMThaFw0y +OTEyMzAxMTMwMThaMIGCMQswCQYDVQQGEwJIVTERMA8GA1UEBwwIQnVkYXBlc3Qx +FjAUBgNVBAoMDU1pY3Jvc2VjIEx0ZC4xJzAlBgNVBAMMHk1pY3Jvc2VjIGUtU3pp +Z25vIFJvb3QgQ0EgMjAwOTEfMB0GCSqGSIb3DQEJARYQaW5mb0BlLXN6aWduby5o +dTCCASIwDQYJKoZIhvcNAQEBBQADggEPADCCAQoCggEBAOn4j/NjrdqG2KfgQvvP +kd6mJviZpWNwrZuuyjNAfW2WbqEORO7hE52UQlKavXWFdCyoDh2Tthi3jCyoz/tc +cbna7P7ofo/kLx2yqHWH2Leh5TvPmUpG0IMZfcChEhyVbUr02MelTTMuhTlAdX4U +fIASmFDHQWe4oIBhVKZsTh/gnQ4H6cm6M+f+wFUoLAKApxn1ntxVUwOXewdI/5n7 +N4okxFnMUBBjjqqpGrCEGob5X7uxUG6k0QrM1XF+H6cbfPVTbiJfyyvm1HxdrtbC +xkzlBQHZ7Vf8wSN5/PrIJIOV87VqUQHQd9bpEqH5GoP7ghu5sJf0dgYzQ0mg/wu1 ++rUCAwEAAaOBgDB+MA8GA1UdEwEB/wQFMAMBAf8wDgYDVR0PAQH/BAQDAgEGMB0G +A1UdDgQWBBTLD8bfQkPMPcu1SCOhGnqmKrs0aDAfBgNVHSMEGDAWgBTLD8bfQkPM +Pcu1SCOhGnqmKrs0aDAbBgNVHREEFDASgRBpbmZvQGUtc3ppZ25vLmh1MA0GCSqG +SIb3DQEBCwUAA4IBAQDJ0Q5eLtXMs3w+y/w9/w0olZMEyL/azXm4Q5DwpL7v8u8h +mLzU1F0G9u5C7DBsoKqpyvGvivo/C3NqPuouQH4frlRheesuCDfXI/OMn74dseGk +ddug4lQUsbocKaQY9hK6ohQU4zE1yED/t+AFdlfBHFny+L/k7SViXITwfn4fs775 +tyERzAMBVnCnEJIeGzSBHq2cGsMEPO0CYdYeBvNfOofyK/FFh+U9rNHHV4S9a67c +2Pm2G2JwCz02yULyMtd6YebS2z3PyKnJm9zbWETXbzivf3jTo60adbocwTZ8jx5t +HMN1Rq41Bab2XD0h7lbwyYIiLXpUq3DDfSJlgnCW +-----END CERTIFICATE----- + +# Issuer: CN=GlobalSign O=GlobalSign OU=GlobalSign Root CA - R3 +# Subject: CN=GlobalSign O=GlobalSign OU=GlobalSign Root CA - R3 +# Label: "GlobalSign Root CA - R3" +# Serial: 4835703278459759426209954 +# MD5 Fingerprint: c5:df:b8:49:ca:05:13:55:ee:2d:ba:1a:c3:3e:b0:28 +# SHA1 Fingerprint: d6:9b:56:11:48:f0:1c:77:c5:45:78:c1:09:26:df:5b:85:69:76:ad +# SHA256 Fingerprint: cb:b5:22:d7:b7:f1:27:ad:6a:01:13:86:5b:df:1c:d4:10:2e:7d:07:59:af:63:5a:7c:f4:72:0d:c9:63:c5:3b +-----BEGIN CERTIFICATE----- +MIIDXzCCAkegAwIBAgILBAAAAAABIVhTCKIwDQYJKoZIhvcNAQELBQAwTDEgMB4G +A1UECxMXR2xvYmFsU2lnbiBSb290IENBIC0gUjMxEzARBgNVBAoTCkdsb2JhbFNp +Z24xEzARBgNVBAMTCkdsb2JhbFNpZ24wHhcNMDkwMzE4MTAwMDAwWhcNMjkwMzE4 +MTAwMDAwWjBMMSAwHgYDVQQLExdHbG9iYWxTaWduIFJvb3QgQ0EgLSBSMzETMBEG +A1UEChMKR2xvYmFsU2lnbjETMBEGA1UEAxMKR2xvYmFsU2lnbjCCASIwDQYJKoZI +hvcNAQEBBQADggEPADCCAQoCggEBAMwldpB5BngiFvXAg7aEyiie/QV2EcWtiHL8 +RgJDx7KKnQRfJMsuS+FggkbhUqsMgUdwbN1k0ev1LKMPgj0MK66X17YUhhB5uzsT +gHeMCOFJ0mpiLx9e+pZo34knlTifBtc+ycsmWQ1z3rDI6SYOgxXG71uL0gRgykmm +KPZpO/bLyCiR5Z2KYVc3rHQU3HTgOu5yLy6c+9C7v/U9AOEGM+iCK65TpjoWc4zd +QQ4gOsC0p6Hpsk+QLjJg6VfLuQSSaGjlOCZgdbKfd/+RFO+uIEn8rUAVSNECMWEZ +XriX7613t2Saer9fwRPvm2L7DWzgVGkWqQPabumDk3F2xmmFghcCAwEAAaNCMEAw +DgYDVR0PAQH/BAQDAgEGMA8GA1UdEwEB/wQFMAMBAf8wHQYDVR0OBBYEFI/wS3+o +LkUkrk1Q+mOai97i3Ru8MA0GCSqGSIb3DQEBCwUAA4IBAQBLQNvAUKr+yAzv95ZU +RUm7lgAJQayzE4aGKAczymvmdLm6AC2upArT9fHxD4q/c2dKg8dEe3jgr25sbwMp +jjM5RcOO5LlXbKr8EpbsU8Yt5CRsuZRj+9xTaGdWPoO4zzUhw8lo/s7awlOqzJCK +6fBdRoyV3XpYKBovHd7NADdBj+1EbddTKJd+82cEHhXXipa0095MJ6RMG3NzdvQX +mcIfeg7jLQitChws/zyrVQ4PkX4268NXSb7hLi18YIvDQVETI53O9zJrlAGomecs +Mx86OyXShkDOOyyGeMlhLxS67ttVb9+E7gUJTb0o2HLO02JQZR7rkpeDMdmztcpH +WD9f +-----END CERTIFICATE----- + +# Issuer: CN=Izenpe.com O=IZENPE S.A. +# Subject: CN=Izenpe.com O=IZENPE S.A. +# Label: "Izenpe.com" +# Serial: 917563065490389241595536686991402621 +# MD5 Fingerprint: a6:b0:cd:85:80:da:5c:50:34:a3:39:90:2f:55:67:73 +# SHA1 Fingerprint: 2f:78:3d:25:52:18:a7:4a:65:39:71:b5:2c:a2:9c:45:15:6f:e9:19 +# SHA256 Fingerprint: 25:30:cc:8e:98:32:15:02:ba:d9:6f:9b:1f:ba:1b:09:9e:2d:29:9e:0f:45:48:bb:91:4f:36:3b:c0:d4:53:1f +-----BEGIN CERTIFICATE----- +MIIF8TCCA9mgAwIBAgIQALC3WhZIX7/hy/WL1xnmfTANBgkqhkiG9w0BAQsFADA4 +MQswCQYDVQQGEwJFUzEUMBIGA1UECgwLSVpFTlBFIFMuQS4xEzARBgNVBAMMCkl6 +ZW5wZS5jb20wHhcNMDcxMjEzMTMwODI4WhcNMzcxMjEzMDgyNzI1WjA4MQswCQYD +VQQGEwJFUzEUMBIGA1UECgwLSVpFTlBFIFMuQS4xEzARBgNVBAMMCkl6ZW5wZS5j +b20wggIiMA0GCSqGSIb3DQEBAQUAA4ICDwAwggIKAoICAQDJ03rKDx6sp4boFmVq +scIbRTJxldn+EFvMr+eleQGPicPK8lVx93e+d5TzcqQsRNiekpsUOqHnJJAKClaO +xdgmlOHZSOEtPtoKct2jmRXagaKH9HtuJneJWK3W6wyyQXpzbm3benhB6QiIEn6H +LmYRY2xU+zydcsC8Lv/Ct90NduM61/e0aL6i9eOBbsFGb12N4E3GVFWJGjMxCrFX +uaOKmMPsOzTFlUFpfnXCPCDFYbpRR6AgkJOhkEvzTnyFRVSa0QUmQbC1TR0zvsQD +yCV8wXDbO/QJLVQnSKwv4cSsPsjLkkxTOTcj7NMB+eAJRE1NZMDhDVqHIrytG6P+ +JrUV86f8hBnp7KGItERphIPzidF0BqnMC9bC3ieFUCbKF7jJeodWLBoBHmy+E60Q +rLUk9TiRodZL2vG70t5HtfG8gfZZa88ZU+mNFctKy6lvROUbQc/hhqfK0GqfvEyN +BjNaooXlkDWgYlwWTvDjovoDGrQscbNYLN57C9saD+veIR8GdwYDsMnvmfzAuU8L +hij+0rnq49qlw0dpEuDb8PYZi+17cNcC1u2HGCgsBCRMd+RIihrGO5rUD8r6ddIB +QFqNeb+Lz0vPqhbBleStTIo+F5HUsWLlguWABKQDfo2/2n+iD5dPDNMN+9fR5XJ+ +HMh3/1uaD7euBUbl8agW7EekFwIDAQABo4H2MIHzMIGwBgNVHREEgagwgaWBD2lu +Zm9AaXplbnBlLmNvbaSBkTCBjjFHMEUGA1UECgw+SVpFTlBFIFMuQS4gLSBDSUYg +QTAxMzM3MjYwLVJNZXJjLlZpdG9yaWEtR2FzdGVpeiBUMTA1NSBGNjIgUzgxQzBB +BgNVBAkMOkF2ZGEgZGVsIE1lZGl0ZXJyYW5lbyBFdG9yYmlkZWEgMTQgLSAwMTAx +MCBWaXRvcmlhLUdhc3RlaXowDwYDVR0TAQH/BAUwAwEB/zAOBgNVHQ8BAf8EBAMC +AQYwHQYDVR0OBBYEFB0cZQ6o8iV7tJHP5LGx5r1VdGwFMA0GCSqGSIb3DQEBCwUA +A4ICAQB4pgwWSp9MiDrAyw6lFn2fuUhfGI8NYjb2zRlrrKvV9pF9rnHzP7MOeIWb +laQnIUdCSnxIOvVFfLMMjlF4rJUT3sb9fbgakEyrkgPH7UIBzg/YsfqikuFgba56 +awmqxinuaElnMIAkejEWOVt+8Rwu3WwJrfIxwYJOubv5vr8qhT/AQKM6WfxZSzwo +JNu0FXWuDYi6LnPAvViH5ULy617uHjAimcs30cQhbIHsvm0m5hzkQiCeR7Csg1lw +LDXWrzY0tM07+DKo7+N4ifuNRSzanLh+QBxh5z6ikixL8s36mLYp//Pye6kfLqCT +VyvehQP5aTfLnnhqBbTFMXiJ7HqnheG5ezzevh55hM6fcA5ZwjUukCox2eRFekGk +LhObNA5me0mrZJfQRsN5nXJQY6aYWwa9SG3YOYNw6DXwBdGqvOPbyALqfP2C2sJb +UjWumDqtujWTI6cfSN01RpiyEGjkpTHCClguGYEQyVB1/OpaFs4R1+7vUIgtYf8/ +QnMFlEPVjjxOAToZpR9GTnfQXeWBIiGH/pR9hNiTrdZoQ0iy2+tzJOeRf1SktoA+ +naM8THLCV8Sg1Mw4J87VBp6iSNnpn86CcDaTmjvfliHjWbcM2pE38P1ZWrOZyGls +QyYBNWNgVYkDOnXYukrZVP/u3oDYLdE41V4tC5h9Pmzb/CaIxw== +-----END CERTIFICATE----- + +# Issuer: CN=Go Daddy Root Certificate Authority - G2 O=GoDaddy.com, Inc. +# Subject: CN=Go Daddy Root Certificate Authority - G2 O=GoDaddy.com, Inc. +# Label: "Go Daddy Root Certificate Authority - G2" +# Serial: 0 +# MD5 Fingerprint: 80:3a:bc:22:c1:e6:fb:8d:9b:3b:27:4a:32:1b:9a:01 +# SHA1 Fingerprint: 47:be:ab:c9:22:ea:e8:0e:78:78:34:62:a7:9f:45:c2:54:fd:e6:8b +# SHA256 Fingerprint: 45:14:0b:32:47:eb:9c:c8:c5:b4:f0:d7:b5:30:91:f7:32:92:08:9e:6e:5a:63:e2:74:9d:d3:ac:a9:19:8e:da +-----BEGIN CERTIFICATE----- +MIIDxTCCAq2gAwIBAgIBADANBgkqhkiG9w0BAQsFADCBgzELMAkGA1UEBhMCVVMx +EDAOBgNVBAgTB0FyaXpvbmExEzARBgNVBAcTClNjb3R0c2RhbGUxGjAYBgNVBAoT +EUdvRGFkZHkuY29tLCBJbmMuMTEwLwYDVQQDEyhHbyBEYWRkeSBSb290IENlcnRp +ZmljYXRlIEF1dGhvcml0eSAtIEcyMB4XDTA5MDkwMTAwMDAwMFoXDTM3MTIzMTIz +NTk1OVowgYMxCzAJBgNVBAYTAlVTMRAwDgYDVQQIEwdBcml6b25hMRMwEQYDVQQH +EwpTY290dHNkYWxlMRowGAYDVQQKExFHb0RhZGR5LmNvbSwgSW5jLjExMC8GA1UE +AxMoR28gRGFkZHkgUm9vdCBDZXJ0aWZpY2F0ZSBBdXRob3JpdHkgLSBHMjCCASIw +DQYJKoZIhvcNAQEBBQADggEPADCCAQoCggEBAL9xYgjx+lk09xvJGKP3gElY6SKD +E6bFIEMBO4Tx5oVJnyfq9oQbTqC023CYxzIBsQU+B07u9PpPL1kwIuerGVZr4oAH +/PMWdYA5UXvl+TW2dE6pjYIT5LY/qQOD+qK+ihVqf94Lw7YZFAXK6sOoBJQ7Rnwy +DfMAZiLIjWltNowRGLfTshxgtDj6AozO091GB94KPutdfMh8+7ArU6SSYmlRJQVh +GkSBjCypQ5Yj36w6gZoOKcUcqeldHraenjAKOc7xiID7S13MMuyFYkMlNAJWJwGR +tDtwKj9useiciAF9n9T521NtYJ2/LOdYq7hfRvzOxBsDPAnrSTFcaUaz4EcCAwEA +AaNCMEAwDwYDVR0TAQH/BAUwAwEB/zAOBgNVHQ8BAf8EBAMCAQYwHQYDVR0OBBYE +FDqahQcQZyi27/a9BUFuIMGU2g/eMA0GCSqGSIb3DQEBCwUAA4IBAQCZ21151fmX +WWcDYfF+OwYxdS2hII5PZYe096acvNjpL9DbWu7PdIxztDhC2gV7+AJ1uP2lsdeu +9tfeE8tTEH6KRtGX+rcuKxGrkLAngPnon1rpN5+r5N9ss4UXnT3ZJE95kTXWXwTr +gIOrmgIttRD02JDHBHNA7XIloKmf7J6raBKZV8aPEjoJpL1E/QYVN8Gb5DKj7Tjo +2GTzLH4U/ALqn83/B2gX2yKQOC16jdFU8WnjXzPKej17CuPKf1855eJ1usV2GDPO +LPAvTK33sefOT6jEm0pUBsV/fdUID+Ic/n4XuKxe9tQWskMJDE32p2u0mYRlynqI +4uJEvlz36hz1 +-----END CERTIFICATE----- + +# Issuer: CN=Starfield Root Certificate Authority - G2 O=Starfield Technologies, Inc. +# Subject: CN=Starfield Root Certificate Authority - G2 O=Starfield Technologies, Inc. +# Label: "Starfield Root Certificate Authority - G2" +# Serial: 0 +# MD5 Fingerprint: d6:39:81:c6:52:7e:96:69:fc:fc:ca:66:ed:05:f2:96 +# SHA1 Fingerprint: b5:1c:06:7c:ee:2b:0c:3d:f8:55:ab:2d:92:f4:fe:39:d4:e7:0f:0e +# SHA256 Fingerprint: 2c:e1:cb:0b:f9:d2:f9:e1:02:99:3f:be:21:51:52:c3:b2:dd:0c:ab:de:1c:68:e5:31:9b:83:91:54:db:b7:f5 +-----BEGIN CERTIFICATE----- +MIID3TCCAsWgAwIBAgIBADANBgkqhkiG9w0BAQsFADCBjzELMAkGA1UEBhMCVVMx +EDAOBgNVBAgTB0FyaXpvbmExEzARBgNVBAcTClNjb3R0c2RhbGUxJTAjBgNVBAoT +HFN0YXJmaWVsZCBUZWNobm9sb2dpZXMsIEluYy4xMjAwBgNVBAMTKVN0YXJmaWVs +ZCBSb290IENlcnRpZmljYXRlIEF1dGhvcml0eSAtIEcyMB4XDTA5MDkwMTAwMDAw +MFoXDTM3MTIzMTIzNTk1OVowgY8xCzAJBgNVBAYTAlVTMRAwDgYDVQQIEwdBcml6 +b25hMRMwEQYDVQQHEwpTY290dHNkYWxlMSUwIwYDVQQKExxTdGFyZmllbGQgVGVj +aG5vbG9naWVzLCBJbmMuMTIwMAYDVQQDEylTdGFyZmllbGQgUm9vdCBDZXJ0aWZp +Y2F0ZSBBdXRob3JpdHkgLSBHMjCCASIwDQYJKoZIhvcNAQEBBQADggEPADCCAQoC +ggEBAL3twQP89o/8ArFvW59I2Z154qK3A2FWGMNHttfKPTUuiUP3oWmb3ooa/RMg +nLRJdzIpVv257IzdIvpy3Cdhl+72WoTsbhm5iSzchFvVdPtrX8WJpRBSiUZV9Lh1 +HOZ/5FSuS/hVclcCGfgXcVnrHigHdMWdSL5stPSksPNkN3mSwOxGXn/hbVNMYq/N +Hwtjuzqd+/x5AJhhdM8mgkBj87JyahkNmcrUDnXMN/uLicFZ8WJ/X7NfZTD4p7dN +dloedl40wOiWVpmKs/B/pM293DIxfJHP4F8R+GuqSVzRmZTRouNjWwl2tVZi4Ut0 +HZbUJtQIBFnQmA4O5t78w+wfkPECAwEAAaNCMEAwDwYDVR0TAQH/BAUwAwEB/zAO +BgNVHQ8BAf8EBAMCAQYwHQYDVR0OBBYEFHwMMh+n2TB/xH1oo2Kooc6rB1snMA0G +CSqGSIb3DQEBCwUAA4IBAQARWfolTwNvlJk7mh+ChTnUdgWUXuEok21iXQnCoKjU +sHU48TRqneSfioYmUeYs0cYtbpUgSpIB7LiKZ3sx4mcujJUDJi5DnUox9g61DLu3 +4jd/IroAow57UvtruzvE03lRTs2Q9GcHGcg8RnoNAX3FWOdt5oUwF5okxBDgBPfg +8n/Uqgr/Qh037ZTlZFkSIHc40zI+OIF1lnP6aI+xy84fxez6nH7PfrHxBy22/L/K +pL/QlwVKvOoYKAKQvVR4CSFx09F9HdkWsKlhPdAKACL8x3vLCWRFCztAgfd9fDL1 +mMpYjn0q7pBZc2T5NnReJaH1ZgUufzkVqSr7UIuOhWn0 +-----END CERTIFICATE----- + +# Issuer: CN=Starfield Services Root Certificate Authority - G2 O=Starfield Technologies, Inc. +# Subject: CN=Starfield Services Root Certificate Authority - G2 O=Starfield Technologies, Inc. +# Label: "Starfield Services Root Certificate Authority - G2" +# Serial: 0 +# MD5 Fingerprint: 17:35:74:af:7b:61:1c:eb:f4:f9:3c:e2:ee:40:f9:a2 +# SHA1 Fingerprint: 92:5a:8f:8d:2c:6d:04:e0:66:5f:59:6a:ff:22:d8:63:e8:25:6f:3f +# SHA256 Fingerprint: 56:8d:69:05:a2:c8:87:08:a4:b3:02:51:90:ed:cf:ed:b1:97:4a:60:6a:13:c6:e5:29:0f:cb:2a:e6:3e:da:b5 +-----BEGIN CERTIFICATE----- +MIID7zCCAtegAwIBAgIBADANBgkqhkiG9w0BAQsFADCBmDELMAkGA1UEBhMCVVMx +EDAOBgNVBAgTB0FyaXpvbmExEzARBgNVBAcTClNjb3R0c2RhbGUxJTAjBgNVBAoT +HFN0YXJmaWVsZCBUZWNobm9sb2dpZXMsIEluYy4xOzA5BgNVBAMTMlN0YXJmaWVs +ZCBTZXJ2aWNlcyBSb290IENlcnRpZmljYXRlIEF1dGhvcml0eSAtIEcyMB4XDTA5 +MDkwMTAwMDAwMFoXDTM3MTIzMTIzNTk1OVowgZgxCzAJBgNVBAYTAlVTMRAwDgYD +VQQIEwdBcml6b25hMRMwEQYDVQQHEwpTY290dHNkYWxlMSUwIwYDVQQKExxTdGFy +ZmllbGQgVGVjaG5vbG9naWVzLCBJbmMuMTswOQYDVQQDEzJTdGFyZmllbGQgU2Vy +dmljZXMgUm9vdCBDZXJ0aWZpY2F0ZSBBdXRob3JpdHkgLSBHMjCCASIwDQYJKoZI +hvcNAQEBBQADggEPADCCAQoCggEBANUMOsQq+U7i9b4Zl1+OiFOxHz/Lz58gE20p +OsgPfTz3a3Y4Y9k2YKibXlwAgLIvWX/2h/klQ4bnaRtSmpDhcePYLQ1Ob/bISdm2 +8xpWriu2dBTrz/sm4xq6HZYuajtYlIlHVv8loJNwU4PahHQUw2eeBGg6345AWh1K +Ts9DkTvnVtYAcMtS7nt9rjrnvDH5RfbCYM8TWQIrgMw0R9+53pBlbQLPLJGmpufe +hRhJfGZOozptqbXuNC66DQO4M99H67FrjSXZm86B0UVGMpZwh94CDklDhbZsc7tk +6mFBrMnUVN+HL8cisibMn1lUaJ/8viovxFUcdUBgF4UCVTmLfwUCAwEAAaNCMEAw +DwYDVR0TAQH/BAUwAwEB/zAOBgNVHQ8BAf8EBAMCAQYwHQYDVR0OBBYEFJxfAN+q +AdcwKziIorhtSpzyEZGDMA0GCSqGSIb3DQEBCwUAA4IBAQBLNqaEd2ndOxmfZyMI +bw5hyf2E3F/YNoHN2BtBLZ9g3ccaaNnRbobhiCPPE95Dz+I0swSdHynVv/heyNXB +ve6SbzJ08pGCL72CQnqtKrcgfU28elUSwhXqvfdqlS5sdJ/PHLTyxQGjhdByPq1z +qwubdQxtRbeOlKyWN7Wg0I8VRw7j6IPdj/3vQQF3zCepYoUz8jcI73HPdwbeyBkd +iEDPfUYd/x7H4c7/I9vG+o1VTqkC50cRRj70/b17KSa7qWFiNyi2LSr2EIZkyXCn +0q23KXB56jzaYyWf/Wi3MOxw+3WKt21gZ7IeyLnp2KhvAotnDU0mV3HaIPzBSlCN +sSi6 +-----END CERTIFICATE----- + +# Issuer: CN=Certum Trusted Network CA O=Unizeto Technologies S.A. OU=Certum Certification Authority +# Subject: CN=Certum Trusted Network CA O=Unizeto Technologies S.A. OU=Certum Certification Authority +# Label: "Certum Trusted Network CA" +# Serial: 279744 +# MD5 Fingerprint: d5:e9:81:40:c5:18:69:fc:46:2c:89:75:62:0f:aa:78 +# SHA1 Fingerprint: 07:e0:32:e0:20:b7:2c:3f:19:2f:06:28:a2:59:3a:19:a7:0f:06:9e +# SHA256 Fingerprint: 5c:58:46:8d:55:f5:8e:49:7e:74:39:82:d2:b5:00:10:b6:d1:65:37:4a:cf:83:a7:d4:a3:2d:b7:68:c4:40:8e +-----BEGIN CERTIFICATE----- +MIIDuzCCAqOgAwIBAgIDBETAMA0GCSqGSIb3DQEBBQUAMH4xCzAJBgNVBAYTAlBM +MSIwIAYDVQQKExlVbml6ZXRvIFRlY2hub2xvZ2llcyBTLkEuMScwJQYDVQQLEx5D +ZXJ0dW0gQ2VydGlmaWNhdGlvbiBBdXRob3JpdHkxIjAgBgNVBAMTGUNlcnR1bSBU +cnVzdGVkIE5ldHdvcmsgQ0EwHhcNMDgxMDIyMTIwNzM3WhcNMjkxMjMxMTIwNzM3 +WjB+MQswCQYDVQQGEwJQTDEiMCAGA1UEChMZVW5pemV0byBUZWNobm9sb2dpZXMg +Uy5BLjEnMCUGA1UECxMeQ2VydHVtIENlcnRpZmljYXRpb24gQXV0aG9yaXR5MSIw +IAYDVQQDExlDZXJ0dW0gVHJ1c3RlZCBOZXR3b3JrIENBMIIBIjANBgkqhkiG9w0B +AQEFAAOCAQ8AMIIBCgKCAQEA4/t9o3K6wvDJFIf1awFO4W5AB7ptJ11/91sts1rH +UV+rpDKmYYe2bg+G0jACl/jXaVehGDldamR5xgFZrDwxSjh80gTSSyjoIF87B6LM +TXPb865Px1bVWqeWifrzq2jUI4ZZJ88JJ7ysbnKDHDBy3+Ci6dLhdHUZvSqeexVU +BBvXQzmtVSjF4hq79MDkrjhJM8x2hZ85RdKknvISjFH4fOQtf/WsX+sWn7Et0brM +kUJ3TCXJkDhv2/DM+44el1k+1WBO5gUo7Ul5E0u6SNsv+XLTOcr+H9g0cvW0QM8x +AcPs3hEtF10fuFDRXhmnad4HMyjKUJX5p1TLVIZQRan5SQIDAQABo0IwQDAPBgNV +HRMBAf8EBTADAQH/MB0GA1UdDgQWBBQIds3LB/8k9sXN7buQvOKEN0Z19zAOBgNV +HQ8BAf8EBAMCAQYwDQYJKoZIhvcNAQEFBQADggEBAKaorSLOAT2mo/9i0Eidi15y +sHhE49wcrwn9I0j6vSrEuVUEtRCjjSfeC4Jj0O7eDDd5QVsisrCaQVymcODU0HfL +I9MA4GxWL+FpDQ3Zqr8hgVDZBqWo/5U30Kr+4rP1mS1FhIrlQgnXdAIv94nYmem8 +J9RHjboNRhx3zxSkHLmkMcScKHQDNP8zGSal6Q10tz6XxnboJ5ajZt3hrvJBW8qY +VoNzcOSGGtIxQbovvi0TWnZvTuhOgQ4/WwMioBK+ZlgRSssDxLQqKi2WF+A5VLxI +03YnnZotBqbJ7DnSq9ufmgsnAjUpsUCV5/nonFWIGUbWtzT1fs45mtk48VH3Tyw= +-----END CERTIFICATE----- + +# Issuer: CN=TWCA Root Certification Authority O=TAIWAN-CA OU=Root CA +# Subject: CN=TWCA Root Certification Authority O=TAIWAN-CA OU=Root CA +# Label: "TWCA Root Certification Authority" +# Serial: 1 +# MD5 Fingerprint: aa:08:8f:f6:f9:7b:b7:f2:b1:a7:1e:9b:ea:ea:bd:79 +# SHA1 Fingerprint: cf:9e:87:6d:d3:eb:fc:42:26:97:a3:b5:a3:7a:a0:76:a9:06:23:48 +# SHA256 Fingerprint: bf:d8:8f:e1:10:1c:41:ae:3e:80:1b:f8:be:56:35:0e:e9:ba:d1:a6:b9:bd:51:5e:dc:5c:6d:5b:87:11:ac:44 +-----BEGIN CERTIFICATE----- +MIIDezCCAmOgAwIBAgIBATANBgkqhkiG9w0BAQUFADBfMQswCQYDVQQGEwJUVzES +MBAGA1UECgwJVEFJV0FOLUNBMRAwDgYDVQQLDAdSb290IENBMSowKAYDVQQDDCFU +V0NBIFJvb3QgQ2VydGlmaWNhdGlvbiBBdXRob3JpdHkwHhcNMDgwODI4MDcyNDMz +WhcNMzAxMjMxMTU1OTU5WjBfMQswCQYDVQQGEwJUVzESMBAGA1UECgwJVEFJV0FO +LUNBMRAwDgYDVQQLDAdSb290IENBMSowKAYDVQQDDCFUV0NBIFJvb3QgQ2VydGlm +aWNhdGlvbiBBdXRob3JpdHkwggEiMA0GCSqGSIb3DQEBAQUAA4IBDwAwggEKAoIB +AQCwfnK4pAOU5qfeCTiRShFAh6d8WWQUe7UREN3+v9XAu1bihSX0NXIP+FPQQeFE +AcK0HMMxQhZHhTMidrIKbw/lJVBPhYa+v5guEGcevhEFhgWQxFnQfHgQsIBct+HH +K3XLfJ+utdGdIzdjp9xCoi2SBBtQwXu4PhvJVgSLL1KbralW6cH/ralYhzC2gfeX +RfwZVzsrb+RH9JlF/h3x+JejiB03HFyP4HYlmlD4oFT/RJB2I9IyxsOrBr/8+7/z +rX2SYgJbKdM1o5OaQ2RgXbL6Mv87BK9NQGr5x+PvI/1ry+UPizgN7gr8/g+YnzAx +3WxSZfmLgb4i4RxYA7qRG4kHAgMBAAGjQjBAMA4GA1UdDwEB/wQEAwIBBjAPBgNV +HRMBAf8EBTADAQH/MB0GA1UdDgQWBBRqOFsmjd6LWvJPelSDGRjjCDWmujANBgkq +hkiG9w0BAQUFAAOCAQEAPNV3PdrfibqHDAhUaiBQkr6wQT25JmSDCi/oQMCXKCeC +MErJk/9q56YAf4lCmtYR5VPOL8zy2gXE/uJQxDqGfczafhAJO5I1KlOy/usrBdls +XebQ79NqZp4VKIV66IIArB6nCWlWQtNoURi+VJq/REG6Sb4gumlc7rh3zc5sH62D +lhh9DrUUOYTxKOkto557HnpyWoOzeW/vtPzQCqVYT0bf+215WfKEIlKuD8z7fDvn +aspHYcN6+NOSBB+4IIThNlQWx0DeO4pz3N/GCUzf7Nr/1FNCocnyYh0igzyXxfkZ +YiesZSLX0zzG5Y6yU8xJzrww/nsOM5D77dIUkR8Hrw== +-----END CERTIFICATE----- + +# Issuer: O=SECOM Trust Systems CO.,LTD. OU=Security Communication RootCA2 +# Subject: O=SECOM Trust Systems CO.,LTD. OU=Security Communication RootCA2 +# Label: "Security Communication RootCA2" +# Serial: 0 +# MD5 Fingerprint: 6c:39:7d:a4:0e:55:59:b2:3f:d6:41:b1:12:50:de:43 +# SHA1 Fingerprint: 5f:3b:8c:f2:f8:10:b3:7d:78:b4:ce:ec:19:19:c3:73:34:b9:c7:74 +# SHA256 Fingerprint: 51:3b:2c:ec:b8:10:d4:cd:e5:dd:85:39:1a:df:c6:c2:dd:60:d8:7b:b7:36:d2:b5:21:48:4a:a4:7a:0e:be:f6 +-----BEGIN CERTIFICATE----- +MIIDdzCCAl+gAwIBAgIBADANBgkqhkiG9w0BAQsFADBdMQswCQYDVQQGEwJKUDEl +MCMGA1UEChMcU0VDT00gVHJ1c3QgU3lzdGVtcyBDTy4sTFRELjEnMCUGA1UECxMe +U2VjdXJpdHkgQ29tbXVuaWNhdGlvbiBSb290Q0EyMB4XDTA5MDUyOTA1MDAzOVoX +DTI5MDUyOTA1MDAzOVowXTELMAkGA1UEBhMCSlAxJTAjBgNVBAoTHFNFQ09NIFRy +dXN0IFN5c3RlbXMgQ08uLExURC4xJzAlBgNVBAsTHlNlY3VyaXR5IENvbW11bmlj +YXRpb24gUm9vdENBMjCCASIwDQYJKoZIhvcNAQEBBQADggEPADCCAQoCggEBANAV +OVKxUrO6xVmCxF1SrjpDZYBLx/KWvNs2l9amZIyoXvDjChz335c9S672XewhtUGr +zbl+dp+++T42NKA7wfYxEUV0kz1XgMX5iZnK5atq1LXaQZAQwdbWQonCv/Q4EpVM +VAX3NuRFg3sUZdbcDE3R3n4MqzvEFb46VqZab3ZpUql6ucjrappdUtAtCms1FgkQ 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2b:9b:9e:e4:7b:6c:1f:00:72:1a:cc:c1:77:79:df:6a +# SHA1 Fingerprint: 59:0d:2d:7d:88:4f:40:2e:61:7e:a5:62:32:17:65:cf:17:d8:94:e9 +# SHA256 Fingerprint: 91:e2:f5:78:8d:58:10:eb:a7:ba:58:73:7d:e1:54:8a:8e:ca:cd:01:45:98:bc:0b:14:3e:04:1b:17:05:25:52 +-----BEGIN CERTIFICATE----- +MIIDwzCCAqugAwIBAgIBATANBgkqhkiG9w0BAQsFADCBgjELMAkGA1UEBhMCREUx +KzApBgNVBAoMIlQtU3lzdGVtcyBFbnRlcnByaXNlIFNlcnZpY2VzIEdtYkgxHzAd +BgNVBAsMFlQtU3lzdGVtcyBUcnVzdCBDZW50ZXIxJTAjBgNVBAMMHFQtVGVsZVNl +YyBHbG9iYWxSb290IENsYXNzIDIwHhcNMDgxMDAxMTA0MDE0WhcNMzMxMDAxMjM1 +OTU5WjCBgjELMAkGA1UEBhMCREUxKzApBgNVBAoMIlQtU3lzdGVtcyBFbnRlcnBy +aXNlIFNlcnZpY2VzIEdtYkgxHzAdBgNVBAsMFlQtU3lzdGVtcyBUcnVzdCBDZW50 +ZXIxJTAjBgNVBAMMHFQtVGVsZVNlYyBHbG9iYWxSb290IENsYXNzIDIwggEiMA0G +CSqGSIb3DQEBAQUAA4IBDwAwggEKAoIBAQCqX9obX+hzkeXaXPSi5kfl82hVYAUd +AqSzm1nzHoqvNK38DcLZSBnuaY/JIPwhqgcZ7bBcrGXHX+0CfHt8LRvWurmAwhiC +FoT6ZrAIxlQjgeTNuUk/9k9uN0goOA/FvudocP05l03Sx5iRUKrERLMjfTlH6VJi 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Subject: CN=QuoVadis Root CA 2 G3 O=QuoVadis Limited +# Label: "QuoVadis Root CA 2 G3" +# Serial: 390156079458959257446133169266079962026824725800 +# MD5 Fingerprint: af:0c:86:6e:bf:40:2d:7f:0b:3e:12:50:ba:12:3d:06 +# SHA1 Fingerprint: 09:3c:61:f3:8b:8b:dc:7d:55:df:75:38:02:05:00:e1:25:f5:c8:36 +# SHA256 Fingerprint: 8f:e4:fb:0a:f9:3a:4d:0d:67:db:0b:eb:b2:3e:37:c7:1b:f3:25:dc:bc:dd:24:0e:a0:4d:af:58:b4:7e:18:40 +-----BEGIN CERTIFICATE----- +MIIFYDCCA0igAwIBAgIURFc0JFuBiZs18s64KztbpybwdSgwDQYJKoZIhvcNAQEL +BQAwSDELMAkGA1UEBhMCQk0xGTAXBgNVBAoTEFF1b1ZhZGlzIExpbWl0ZWQxHjAc +BgNVBAMTFVF1b1ZhZGlzIFJvb3QgQ0EgMiBHMzAeFw0xMjAxMTIxODU5MzJaFw00 +MjAxMTIxODU5MzJaMEgxCzAJBgNVBAYTAkJNMRkwFwYDVQQKExBRdW9WYWRpcyBM +aW1pdGVkMR4wHAYDVQQDExVRdW9WYWRpcyBSb290IENBIDIgRzMwggIiMA0GCSqG +SIb3DQEBAQUAA4ICDwAwggIKAoICAQChriWyARjcV4g/Ruv5r+LrI3HimtFhZiFf +qq8nUeVuGxbULX1QsFN3vXg6YOJkApt8hpvWGo6t/x8Vf9WVHhLL5hSEBMHfNrMW +n4rjyduYNM7YMxcoRvynyfDStNVNCXJJ+fKH46nafaF9a7I6JaltUkSs+L5u+9ym 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O=DigiCert Inc OU=www.digicert.com +# Label: "DigiCert Assured ID Root G2" +# Serial: 15385348160840213938643033620894905419 +# MD5 Fingerprint: 92:38:b9:f8:63:24:82:65:2c:57:33:e6:fe:81:8f:9d +# SHA1 Fingerprint: a1:4b:48:d9:43:ee:0a:0e:40:90:4f:3c:e0:a4:c0:91:93:51:5d:3f +# SHA256 Fingerprint: 7d:05:eb:b6:82:33:9f:8c:94:51:ee:09:4e:eb:fe:fa:79:53:a1:14:ed:b2:f4:49:49:45:2f:ab:7d:2f:c1:85 +-----BEGIN CERTIFICATE----- +MIIDljCCAn6gAwIBAgIQC5McOtY5Z+pnI7/Dr5r0SzANBgkqhkiG9w0BAQsFADBl +MQswCQYDVQQGEwJVUzEVMBMGA1UEChMMRGlnaUNlcnQgSW5jMRkwFwYDVQQLExB3 +d3cuZGlnaWNlcnQuY29tMSQwIgYDVQQDExtEaWdpQ2VydCBBc3N1cmVkIElEIFJv +b3QgRzIwHhcNMTMwODAxMTIwMDAwWhcNMzgwMTE1MTIwMDAwWjBlMQswCQYDVQQG +EwJVUzEVMBMGA1UEChMMRGlnaUNlcnQgSW5jMRkwFwYDVQQLExB3d3cuZGlnaWNl +cnQuY29tMSQwIgYDVQQDExtEaWdpQ2VydCBBc3N1cmVkIElEIFJvb3QgRzIwggEi +MA0GCSqGSIb3DQEBAQUAA4IBDwAwggEKAoIBAQDZ5ygvUj82ckmIkzTz+GoeMVSA +n61UQbVH35ao1K+ALbkKz3X9iaV9JPrjIgwrvJUXCzO/GU1BBpAAvQxNEP4Htecc 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15459312981008553731928384953135426796 +# MD5 Fingerprint: 7c:7f:65:31:0c:81:df:8d:ba:3e:99:e2:5c:ad:6e:fb +# SHA1 Fingerprint: f5:17:a2:4f:9a:48:c6:c9:f8:a2:00:26:9f:dc:0f:48:2c:ab:30:89 +# SHA256 Fingerprint: 7e:37:cb:8b:4c:47:09:0c:ab:36:55:1b:a6:f4:5d:b8:40:68:0f:ba:16:6a:95:2d:b1:00:71:7f:43:05:3f:c2 +-----BEGIN CERTIFICATE----- +MIICRjCCAc2gAwIBAgIQC6Fa+h3foLVJRK/NJKBs7DAKBggqhkjOPQQDAzBlMQsw +CQYDVQQGEwJVUzEVMBMGA1UEChMMRGlnaUNlcnQgSW5jMRkwFwYDVQQLExB3d3cu +ZGlnaWNlcnQuY29tMSQwIgYDVQQDExtEaWdpQ2VydCBBc3N1cmVkIElEIFJvb3Qg +RzMwHhcNMTMwODAxMTIwMDAwWhcNMzgwMTE1MTIwMDAwWjBlMQswCQYDVQQGEwJV +UzEVMBMGA1UEChMMRGlnaUNlcnQgSW5jMRkwFwYDVQQLExB3d3cuZGlnaWNlcnQu +Y29tMSQwIgYDVQQDExtEaWdpQ2VydCBBc3N1cmVkIElEIFJvb3QgRzMwdjAQBgcq +hkjOPQIBBgUrgQQAIgNiAAQZ57ysRGXtzbg/WPuNsVepRC0FFfLvC/8QdJ+1YlJf +Zn4f5dwbRXkLzMZTCp2NXQLZqVneAlr2lSoOjThKiknGvMYDOAdfVdp+CW7if17Q +RSAPWXYQ1qAk8C3eNvJsKTmjQjBAMA8GA1UdEwEB/wQFMAMBAf8wDgYDVR0PAQH/ +BAQDAgGGMB0GA1UdDgQWBBTL0L2p4ZgFUaFNN6KDec6NHSrkhDAKBggqhkjOPQQD 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+-----END CERTIFICATE----- + +# Issuer: CN=DigiCert Global Root G3 O=DigiCert Inc OU=www.digicert.com +# Subject: CN=DigiCert Global Root G3 O=DigiCert Inc OU=www.digicert.com +# Label: "DigiCert Global Root G3" +# Serial: 7089244469030293291760083333884364146 +# MD5 Fingerprint: f5:5d:a4:50:a5:fb:28:7e:1e:0f:0d:cc:96:57:56:ca +# SHA1 Fingerprint: 7e:04:de:89:6a:3e:66:6d:00:e6:87:d3:3f:fa:d9:3b:e8:3d:34:9e +# SHA256 Fingerprint: 31:ad:66:48:f8:10:41:38:c7:38:f3:9e:a4:32:01:33:39:3e:3a:18:cc:02:29:6e:f9:7c:2a:c9:ef:67:31:d0 +-----BEGIN CERTIFICATE----- +MIICPzCCAcWgAwIBAgIQBVVWvPJepDU1w6QP1atFcjAKBggqhkjOPQQDAzBhMQsw +CQYDVQQGEwJVUzEVMBMGA1UEChMMRGlnaUNlcnQgSW5jMRkwFwYDVQQLExB3d3cu +ZGlnaWNlcnQuY29tMSAwHgYDVQQDExdEaWdpQ2VydCBHbG9iYWwgUm9vdCBHMzAe +Fw0xMzA4MDExMjAwMDBaFw0zODAxMTUxMjAwMDBaMGExCzAJBgNVBAYTAlVTMRUw +EwYDVQQKEwxEaWdpQ2VydCBJbmMxGTAXBgNVBAsTEHd3dy5kaWdpY2VydC5jb20x +IDAeBgNVBAMTF0RpZ2lDZXJ0IEdsb2JhbCBSb290IEczMHYwEAYHKoZIzj0CAQYF 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+ +# Issuer: CN=COMODO RSA Certification Authority O=COMODO CA Limited +# Subject: CN=COMODO RSA Certification Authority O=COMODO CA Limited +# Label: "COMODO RSA Certification Authority" +# Serial: 101909084537582093308941363524873193117 +# MD5 Fingerprint: 1b:31:b0:71:40:36:cc:14:36:91:ad:c4:3e:fd:ec:18 +# SHA1 Fingerprint: af:e5:d2:44:a8:d1:19:42:30:ff:47:9f:e2:f8:97:bb:cd:7a:8c:b4 +# SHA256 Fingerprint: 52:f0:e1:c4:e5:8e:c6:29:29:1b:60:31:7f:07:46:71:b8:5d:7e:a8:0d:5b:07:27:34:63:53:4b:32:b4:02:34 +-----BEGIN CERTIFICATE----- +MIIF2DCCA8CgAwIBAgIQTKr5yttjb+Af907YWwOGnTANBgkqhkiG9w0BAQwFADCB +hTELMAkGA1UEBhMCR0IxGzAZBgNVBAgTEkdyZWF0ZXIgTWFuY2hlc3RlcjEQMA4G +A1UEBxMHU2FsZm9yZDEaMBgGA1UEChMRQ09NT0RPIENBIExpbWl0ZWQxKzApBgNV +BAMTIkNPTU9ETyBSU0EgQ2VydGlmaWNhdGlvbiBBdXRob3JpdHkwHhcNMTAwMTE5 +MDAwMDAwWhcNMzgwMTE4MjM1OTU5WjCBhTELMAkGA1UEBhMCR0IxGzAZBgNVBAgT +EkdyZWF0ZXIgTWFuY2hlc3RlcjEQMA4GA1UEBxMHU2FsZm9yZDEaMBgGA1UEChMR +Q09NT0RPIENBIExpbWl0ZWQxKzApBgNVBAMTIkNPTU9ETyBSU0EgQ2VydGlmaWNh 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2b:8f:1b:57:33:0d:bb:a2:d0:7a:6c:51:f7:0e:e9:0d:da:b9:ad:8e +# SHA256 Fingerprint: e7:93:c9:b0:2f:d8:aa:13:e2:1c:31:22:8a:cc:b0:81:19:64:3b:74:9c:89:89:64:b1:74:6d:46:c3:d4:cb:d2 +-----BEGIN CERTIFICATE----- +MIIF3jCCA8agAwIBAgIQAf1tMPyjylGoG7xkDjUDLTANBgkqhkiG9w0BAQwFADCB +iDELMAkGA1UEBhMCVVMxEzARBgNVBAgTCk5ldyBKZXJzZXkxFDASBgNVBAcTC0pl +cnNleSBDaXR5MR4wHAYDVQQKExVUaGUgVVNFUlRSVVNUIE5ldHdvcmsxLjAsBgNV +BAMTJVVTRVJUcnVzdCBSU0EgQ2VydGlmaWNhdGlvbiBBdXRob3JpdHkwHhcNMTAw +MjAxMDAwMDAwWhcNMzgwMTE4MjM1OTU5WjCBiDELMAkGA1UEBhMCVVMxEzARBgNV +BAgTCk5ldyBKZXJzZXkxFDASBgNVBAcTC0plcnNleSBDaXR5MR4wHAYDVQQKExVU +aGUgVVNFUlRSVVNUIE5ldHdvcmsxLjAsBgNVBAMTJVVTRVJUcnVzdCBSU0EgQ2Vy +dGlmaWNhdGlvbiBBdXRob3JpdHkwggIiMA0GCSqGSIb3DQEBAQUAA4ICDwAwggIK +AoICAQCAEmUXNg7D2wiz0KxXDXbtzSfTTK1Qg2HiqiBNCS1kCdzOiZ/MPans9s/B +3PHTsdZ7NygRK0faOca8Ohm0X6a9fZ2jY0K2dvKpOyuR+OJv0OwWIJAJPuLodMkY +tJHUYmTbf6MG8YgYapAiPLz+E/CHFHv25B+O1ORRxhFnRghRy4YUVD+8M/5+bJz/ +Fp0YvVGONaanZshyZ9shZrHUm3gDwFA66Mzw3LyeTP6vBZY1H1dat//O+T23LLb2 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Root CA - R5 +# Label: "GlobalSign ECC Root CA - R5" +# Serial: 32785792099990507226680698011560947931244 +# MD5 Fingerprint: 9f:ad:3b:1c:02:1e:8a:ba:17:74:38:81:0c:a2:bc:08 +# SHA1 Fingerprint: 1f:24:c6:30:cd:a4:18:ef:20:69:ff:ad:4f:dd:5f:46:3a:1b:69:aa +# SHA256 Fingerprint: 17:9f:bc:14:8a:3d:d0:0f:d2:4e:a1:34:58:cc:43:bf:a7:f5:9c:81:82:d7:83:a5:13:f6:eb:ec:10:0c:89:24 +-----BEGIN CERTIFICATE----- +MIICHjCCAaSgAwIBAgIRYFlJ4CYuu1X5CneKcflK2GwwCgYIKoZIzj0EAwMwUDEk +MCIGA1UECxMbR2xvYmFsU2lnbiBFQ0MgUm9vdCBDQSAtIFI1MRMwEQYDVQQKEwpH +bG9iYWxTaWduMRMwEQYDVQQDEwpHbG9iYWxTaWduMB4XDTEyMTExMzAwMDAwMFoX +DTM4MDExOTAzMTQwN1owUDEkMCIGA1UECxMbR2xvYmFsU2lnbiBFQ0MgUm9vdCBD +QSAtIFI1MRMwEQYDVQQKEwpHbG9iYWxTaWduMRMwEQYDVQQDEwpHbG9iYWxTaWdu +MHYwEAYHKoZIzj0CAQYFK4EEACIDYgAER0UOlvt9Xb/pOdEh+J8LttV7HpI6SFkc +8GIxLcB6KP4ap1yztsyX50XUWPrRd21DosCHZTQKH3rd6zwzocWdTaRvQZU4f8ke +hOvRnkmSh5SHDDqFSmafnVmTTZdhBoZKo0IwQDAOBgNVHQ8BAf8EBAMCAQYwDwYD +VR0TAQH/BAUwAwEB/zAdBgNVHQ4EFgQUPeYpSJvqB8ohREom3m7e0oPQn1kwCgYI 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e3:5d:28:41:9e:d0:20:25:cf:a6:90:38:cd:62:39:62:45:8d:a5:c6:95:fb:de:a3:c2:2b:0b:fb:25:89:70:92 +-----BEGIN CERTIFICATE----- +MIIB8jCCAXigAwIBAgITBmyf18G7EEwpQ+Vxe3ssyBrBDjAKBggqhkjOPQQDAzA5 +MQswCQYDVQQGEwJVUzEPMA0GA1UEChMGQW1hem9uMRkwFwYDVQQDExBBbWF6b24g +Um9vdCBDQSA0MB4XDTE1MDUyNjAwMDAwMFoXDTQwMDUyNjAwMDAwMFowOTELMAkG +A1UEBhMCVVMxDzANBgNVBAoTBkFtYXpvbjEZMBcGA1UEAxMQQW1hem9uIFJvb3Qg +Q0EgNDB2MBAGByqGSM49AgEGBSuBBAAiA2IABNKrijdPo1MN/sGKe0uoe0ZLY7Bi +9i0b2whxIdIA6GO9mif78DluXeo9pcmBqqNbIJhFXRbb/egQbeOc4OO9X4Ri83Bk +M6DLJC9wuoihKqB1+IGuYgbEgds5bimwHvouXKNCMEAwDwYDVR0TAQH/BAUwAwEB +/zAOBgNVHQ8BAf8EBAMCAYYwHQYDVR0OBBYEFNPsxzplbszh2naaVvuc84ZtV+WB +MAoGCCqGSM49BAMDA2gAMGUCMDqLIfG9fhGt0O9Yli/W651+kI0rz2ZVwyzjKKlw +CkcO8DdZEv8tmZQoTipPNU0zWgIxAOp1AE47xDqUEpHJWEadIRNyp4iciuRMStuW +1KyLa2tJElMzrdfkviT8tQp21KW8EA== +-----END CERTIFICATE----- + +# Issuer: CN=TUBITAK Kamu SM SSL Kok Sertifikasi - Surum 1 O=Turkiye Bilimsel ve Teknolojik Arastirma Kurumu - TUBITAK OU=Kamu Sertifikasyon Merkezi - Kamu SM +# Subject: CN=TUBITAK Kamu SM SSL Kok Sertifikasi - Surum 1 O=Turkiye Bilimsel ve Teknolojik Arastirma Kurumu - TUBITAK OU=Kamu Sertifikasyon Merkezi - Kamu SM +# Label: "TUBITAK Kamu SM SSL Kok Sertifikasi - Surum 1" +# Serial: 1 +# MD5 Fingerprint: dc:00:81:dc:69:2f:3e:2f:b0:3b:f6:3d:5a:91:8e:49 +# SHA1 Fingerprint: 31:43:64:9b:ec:ce:27:ec:ed:3a:3f:0b:8f:0d:e4:e8:91:dd:ee:ca +# SHA256 Fingerprint: 46:ed:c3:68:90:46:d5:3a:45:3f:b3:10:4a:b8:0d:ca:ec:65:8b:26:60:ea:16:29:dd:7e:86:79:90:64:87:16 +-----BEGIN CERTIFICATE----- +MIIEYzCCA0ugAwIBAgIBATANBgkqhkiG9w0BAQsFADCB0jELMAkGA1UEBhMCVFIx +GDAWBgNVBAcTD0dlYnplIC0gS29jYWVsaTFCMEAGA1UEChM5VHVya2l5ZSBCaWxp +bXNlbCB2ZSBUZWtub2xvamlrIEFyYXN0aXJtYSBLdXJ1bXUgLSBUVUJJVEFLMS0w +KwYDVQQLEyRLYW11IFNlcnRpZmlrYXN5b24gTWVya2V6aSAtIEthbXUgU00xNjA0 +BgNVBAMTLVRVQklUQUsgS2FtdSBTTSBTU0wgS29rIFNlcnRpZmlrYXNpIC0gU3Vy +dW0gMTAeFw0xMzExMjUwODI1NTVaFw00MzEwMjUwODI1NTVaMIHSMQswCQYDVQQG +EwJUUjEYMBYGA1UEBxMPR2ViemUgLSBLb2NhZWxpMUIwQAYDVQQKEzlUdXJraXll 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b7:ab:33:08:d1:ea:44:77:ba:14:80:12:5a:6f:bd:a9:36:49:0c:bb +# SHA256 Fingerprint: 85:66:6a:56:2e:e0:be:5c:e9:25:c1:d8:89:0a:6f:76:a8:7e:c1:6d:4d:7d:5f:29:ea:74:19:cf:20:12:3b:69 +-----BEGIN CERTIFICATE----- +MIIF3TCCA8WgAwIBAgIIeyyb0xaAMpkwDQYJKoZIhvcNAQELBQAwfDELMAkGA1UE +BhMCVVMxDjAMBgNVBAgMBVRleGFzMRAwDgYDVQQHDAdIb3VzdG9uMRgwFgYDVQQK +DA9TU0wgQ29ycG9yYXRpb24xMTAvBgNVBAMMKFNTTC5jb20gUm9vdCBDZXJ0aWZp +Y2F0aW9uIEF1dGhvcml0eSBSU0EwHhcNMTYwMjEyMTczOTM5WhcNNDEwMjEyMTcz +OTM5WjB8MQswCQYDVQQGEwJVUzEOMAwGA1UECAwFVGV4YXMxEDAOBgNVBAcMB0hv +dXN0b24xGDAWBgNVBAoMD1NTTCBDb3Jwb3JhdGlvbjExMC8GA1UEAwwoU1NMLmNv +bSBSb290IENlcnRpZmljYXRpb24gQXV0aG9yaXR5IFJTQTCCAiIwDQYJKoZIhvcN +AQEBBQADggIPADCCAgoCggIBAPkP3aMrfcvQKv7sZ4Wm5y4bunfh4/WvpOz6Sl2R +xFdHaxh3a3by/ZPkPQ/CFp4LZsNWlJ4Xg4XOVu/yFv0AYvUiCVToZRdOQbngT0aX +qhvIuG5iXmmxX9sqAn78bMrzQdjt0Oj8P2FI7bADFB0QDksZ4LtO7IZl/zbzXmcC +C52GVWH9ejjt/uIZALdvoVBidXQ8oPrIJZK0bnoix/geoeOy3ZExqysdBP+lSgQ3 +6YWkMyv94tZVNHwZpEpox7Ko07fKoZOI68GXvIz5HdkihCR0xwQ9aqkpk8zruFvh 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Authority RSA R2" +# Serial: 6248227494352943350 +# MD5 Fingerprint: e1:1e:31:58:1a:ae:54:53:02:f6:17:6a:11:7b:4d:95 +# SHA1 Fingerprint: 74:3a:f0:52:9b:d0:32:a0:f4:4a:83:cd:d4:ba:a9:7b:7c:2e:c4:9a +# SHA256 Fingerprint: 2e:7b:f1:6c:c2:24:85:a7:bb:e2:aa:86:96:75:07:61:b0:ae:39:be:3b:2f:e9:d0:cc:6d:4e:f7:34:91:42:5c +-----BEGIN CERTIFICATE----- +MIIF6zCCA9OgAwIBAgIIVrYpzTS8ePYwDQYJKoZIhvcNAQELBQAwgYIxCzAJBgNV +BAYTAlVTMQ4wDAYDVQQIDAVUZXhhczEQMA4GA1UEBwwHSG91c3RvbjEYMBYGA1UE +CgwPU1NMIENvcnBvcmF0aW9uMTcwNQYDVQQDDC5TU0wuY29tIEVWIFJvb3QgQ2Vy +dGlmaWNhdGlvbiBBdXRob3JpdHkgUlNBIFIyMB4XDTE3MDUzMTE4MTQzN1oXDTQy +MDUzMDE4MTQzN1owgYIxCzAJBgNVBAYTAlVTMQ4wDAYDVQQIDAVUZXhhczEQMA4G +A1UEBwwHSG91c3RvbjEYMBYGA1UECgwPU1NMIENvcnBvcmF0aW9uMTcwNQYDVQQD +DC5TU0wuY29tIEVWIFJvb3QgQ2VydGlmaWNhdGlvbiBBdXRob3JpdHkgUlNBIFIy +MIICIjANBgkqhkiG9w0BAQEFAAOCAg8AMIICCgKCAgEAjzZlQOHWTcDXtOlG2mvq +M0fNTPl9fb69LT3w23jhhqXZuglXaO1XPqDQCEGD5yhBJB/jchXQARr7XnAjssuf 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22:a2:c1:f7:bd:ed:70:4c:c1:e7:01:b5:f4:08:c3:10:88:0f:e9:56:b5:de:2a:4a:44:f9:9c:87:3a:25:a7:c8 +-----BEGIN CERTIFICATE----- +MIIClDCCAhqgAwIBAgIILCmcWxbtBZUwCgYIKoZIzj0EAwIwfzELMAkGA1UEBhMC +VVMxDjAMBgNVBAgMBVRleGFzMRAwDgYDVQQHDAdIb3VzdG9uMRgwFgYDVQQKDA9T +U0wgQ29ycG9yYXRpb24xNDAyBgNVBAMMK1NTTC5jb20gRVYgUm9vdCBDZXJ0aWZp +Y2F0aW9uIEF1dGhvcml0eSBFQ0MwHhcNMTYwMjEyMTgxNTIzWhcNNDEwMjEyMTgx +NTIzWjB/MQswCQYDVQQGEwJVUzEOMAwGA1UECAwFVGV4YXMxEDAOBgNVBAcMB0hv +dXN0b24xGDAWBgNVBAoMD1NTTCBDb3Jwb3JhdGlvbjE0MDIGA1UEAwwrU1NMLmNv +bSBFViBSb290IENlcnRpZmljYXRpb24gQXV0aG9yaXR5IEVDQzB2MBAGByqGSM49 +AgEGBSuBBAAiA2IABKoSR5CYG/vvw0AHgyBO8TCCogbR8pKGYfL2IWjKAMTH6kMA +VIbc/R/fALhBYlzccBYy3h+Z1MzFB8gIH2EWB1E9fVwHU+M1OIzfzZ/ZLg1Kthku +WnBaBu2+8KGwytAJKaNjMGEwHQYDVR0OBBYEFFvKXuXe0oGqzagtZFG22XKbl+ZP +MA8GA1UdEwEB/wQFMAMBAf8wHwYDVR0jBBgwFoAUW8pe5d7SgarNqC1kUbbZcpuX +5k8wDgYDVR0PAQH/BAQDAgGGMAoGCCqGSM49BAMCA2gAMGUCMQCK5kCJN+vp1RPZ +ytRrJPOwPYdGWBrssd9v+1a6cGvHOMzosYxPD/fxZ3YOg9AeUY8CMD32IygmTMZg 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e0:11:84:5e:34:de:be:88:81:b9:9c:f6:16:26:d1:96:1f:c3:b9:31 +# SHA256 Fingerprint: 85:60:f9:1c:36:24:da:ba:95:70:b5:fe:a0:db:e3:6f:f1:1a:83:23:be:94:86:85:4f:b3:f3:4a:55:71:19:8d +-----BEGIN CERTIFICATE----- +MIICaTCCAe+gAwIBAgIQISpWDK7aDKtARb8roi066jAKBggqhkjOPQQDAzBtMQsw +CQYDVQQGEwJDSDEQMA4GA1UEChMHV0lTZUtleTEiMCAGA1UECxMZT0lTVEUgRm91 +bmRhdGlvbiBFbmRvcnNlZDEoMCYGA1UEAxMfT0lTVEUgV0lTZUtleSBHbG9iYWwg +Um9vdCBHQyBDQTAeFw0xNzA1MDkwOTQ4MzRaFw00MjA1MDkwOTU4MzNaMG0xCzAJ +BgNVBAYTAkNIMRAwDgYDVQQKEwdXSVNlS2V5MSIwIAYDVQQLExlPSVNURSBGb3Vu +ZGF0aW9uIEVuZG9yc2VkMSgwJgYDVQQDEx9PSVNURSBXSVNlS2V5IEdsb2JhbCBS +b290IEdDIENBMHYwEAYHKoZIzj0CAQYFK4EEACIDYgAETOlQwMYPchi82PG6s4ni +eUqjFqdrVCTbUf/q9Akkwwsin8tqJ4KBDdLArzHkdIJuyiXZjHWd8dvQmqJLIX4W +p2OQ0jnUsYd4XxiWD1AbNTcPasbc2RNNpI6QN+a9WzGRo1QwUjAOBgNVHQ8BAf8E +BAMCAQYwDwYDVR0TAQH/BAUwAwEB/zAdBgNVHQ4EFgQUSIcUrOPDnpBgOtfKie7T +rYy0UGYwEAYJKwYBBAGCNxUBBAMCAQAwCgYIKoZIzj0EAwMDaAAwZQIwJsdpW9zV +57LnyAyMjMPdeYwbY9XJUpROTYJKcx6ygISpJcBMWm1JKWB4E+J+SOtkAjEA2zQg 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CERTIFICATE----- +MIIFWjCCA0KgAwIBAgIQT9Irj/VkyDOeTzRYZiNwYDANBgkqhkiG9w0BAQsFADBH +MQswCQYDVQQGEwJDTjERMA8GA1UECgwIVW5pVHJ1c3QxJTAjBgNVBAMMHFVDQSBF +eHRlbmRlZCBWYWxpZGF0aW9uIFJvb3QwHhcNMTUwMzEzMDAwMDAwWhcNMzgxMjMx +MDAwMDAwWjBHMQswCQYDVQQGEwJDTjERMA8GA1UECgwIVW5pVHJ1c3QxJTAjBgNV +BAMMHFVDQSBFeHRlbmRlZCBWYWxpZGF0aW9uIFJvb3QwggIiMA0GCSqGSIb3DQEB +AQUAA4ICDwAwggIKAoICAQCpCQcoEwKwmeBkqh5DFnpzsZGgdT6o+uM4AHrsiWog +D4vFsJszA1qGxliG1cGFu0/GnEBNyr7uaZa4rYEwmnySBesFK5pI0Lh2PpbIILvS +sPGP2KxFRv+qZ2C0d35qHzwaUnoEPQc8hQ2E0B92CvdqFN9y4zR8V05WAT558aop +O2z6+I9tTcg1367r3CTueUWnhbYFiN6IXSV8l2RnCdm/WhUFhvMJHuxYMjMR83dk +sHYf5BA1FxvyDrFspCqjc/wJHx4yGVMR59mzLC52LqGj3n5qiAno8geK+LLNEOfi +c0CTuwjRP+H8C5SzJe98ptfRr5//lpr1kXuYC3fUfugH0mK1lTnj8/FtDw5lhIpj +VMWAtuCeS31HJqcBCF3RiJ7XwzJE+oJKCmhUfzhTA8ykADNkUVkLo4KRel7sFsLz +KuZi2irbWWIQJUoqgQtHB0MGcIfS+pMRKXpITeuUx3BNr2fVUbGAIAEBtHoIppB/ +TuDvB0GHr2qlXov7z1CymlSvw4m6WC31MJixNnI5fkkE/SmnTHnkBVfblLkWU41G 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Issuer: CN=Certigna Root CA O=Dhimyotis OU=0002 48146308100036 +# Subject: CN=Certigna Root CA O=Dhimyotis OU=0002 48146308100036 +# Label: "Certigna Root CA" +# Serial: 269714418870597844693661054334862075617 +# MD5 Fingerprint: 0e:5c:30:62:27:eb:5b:bc:d7:ae:62:ba:e9:d5:df:77 +# SHA1 Fingerprint: 2d:0d:52:14:ff:9e:ad:99:24:01:74:20:47:6e:6c:85:27:27:f5:43 +# SHA256 Fingerprint: d4:8d:3d:23:ee:db:50:a4:59:e5:51:97:60:1c:27:77:4b:9d:7b:18:c9:4d:5a:05:95:11:a1:02:50:b9:31:68 +-----BEGIN CERTIFICATE----- +MIIGWzCCBEOgAwIBAgIRAMrpG4nxVQMNo+ZBbcTjpuEwDQYJKoZIhvcNAQELBQAw +WjELMAkGA1UEBhMCRlIxEjAQBgNVBAoMCURoaW15b3RpczEcMBoGA1UECwwTMDAw +MiA0ODE0NjMwODEwMDAzNjEZMBcGA1UEAwwQQ2VydGlnbmEgUm9vdCBDQTAeFw0x +MzEwMDEwODMyMjdaFw0zMzEwMDEwODMyMjdaMFoxCzAJBgNVBAYTAkZSMRIwEAYD +VQQKDAlEaGlteW90aXMxHDAaBgNVBAsMEzAwMDIgNDgxNDYzMDgxMDAwMzYxGTAX +BgNVBAMMEENlcnRpZ25hIFJvb3QgQ0EwggIiMA0GCSqGSIb3DQEBAQUAA4ICDwAw +ggIKAoICAQDNGDllGlmx6mQWDoyUJJV8g9PFOSbcDO8WV43X2KyjQn+Cyu3NW9sO 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Root CA - G1" +# Serial: 235931866688319308814040 +# MD5 Fingerprint: 9c:42:84:57:dd:cb:0b:a7:2e:95:ad:b6:f3:da:bc:ac +# SHA1 Fingerprint: 8a:c7:ad:8f:73:ac:4e:c1:b5:75:4d:a5:40:f4:fc:cf:7c:b5:8e:8c +# SHA256 Fingerprint: 40:f6:af:03:46:a9:9a:a1:cd:1d:55:5a:4e:9c:ce:62:c7:f9:63:46:03:ee:40:66:15:83:3d:c8:c8:d0:03:67 +-----BEGIN CERTIFICATE----- +MIIDlDCCAnygAwIBAgIKMfXkYgxsWO3W2DANBgkqhkiG9w0BAQsFADBnMQswCQYD +VQQGEwJJTjETMBEGA1UECxMKZW1TaWduIFBLSTElMCMGA1UEChMcZU11ZGhyYSBU +ZWNobm9sb2dpZXMgTGltaXRlZDEcMBoGA1UEAxMTZW1TaWduIFJvb3QgQ0EgLSBH +MTAeFw0xODAyMTgxODMwMDBaFw00MzAyMTgxODMwMDBaMGcxCzAJBgNVBAYTAklO +MRMwEQYDVQQLEwplbVNpZ24gUEtJMSUwIwYDVQQKExxlTXVkaHJhIFRlY2hub2xv +Z2llcyBMaW1pdGVkMRwwGgYDVQQDExNlbVNpZ24gUm9vdCBDQSAtIEcxMIIBIjAN +BgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAk0u76WaK7p1b1TST0Bsew+eeuGQz +f2N4aLTNLnF115sgxk0pvLZoYIr3IZpWNVrzdr3YzZr/k1ZLpVkGoZM0Kd0WNHVO +8oG0x5ZOrRkVUkr+PHB1cM2vK6sVmjM8qrOLqs1D/fXqcP/tzxE7lM5OMhbTI0Aq 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ce:0b:72:d1:9f:88:8e:d0:50:03:e8:e3:b8:8b:67:40 +# SHA1 Fingerprint: 30:43:fa:4f:f2:57:dc:a0:c3:80:ee:2e:58:ea:78:b2:3f:e6:bb:c1 +# SHA256 Fingerprint: 86:a1:ec:ba:08:9c:4a:8d:3b:be:27:34:c6:12:ba:34:1d:81:3e:04:3c:f9:e8:a8:62:cd:5c:57:a3:6b:be:6b +-----BEGIN CERTIFICATE----- +MIICTjCCAdOgAwIBAgIKPPYHqWhwDtqLhDAKBggqhkjOPQQDAzBrMQswCQYDVQQG +EwJJTjETMBEGA1UECxMKZW1TaWduIFBLSTElMCMGA1UEChMcZU11ZGhyYSBUZWNo +bm9sb2dpZXMgTGltaXRlZDEgMB4GA1UEAxMXZW1TaWduIEVDQyBSb290IENBIC0g +RzMwHhcNMTgwMjE4MTgzMDAwWhcNNDMwMjE4MTgzMDAwWjBrMQswCQYDVQQGEwJJ +TjETMBEGA1UECxMKZW1TaWduIFBLSTElMCMGA1UEChMcZU11ZGhyYSBUZWNobm9s +b2dpZXMgTGltaXRlZDEgMB4GA1UEAxMXZW1TaWduIEVDQyBSb290IENBIC0gRzMw +djAQBgcqhkjOPQIBBgUrgQQAIgNiAAQjpQy4LRL1KPOxst3iAhKAnjlfSU2fySU0 +WXTsuwYc58Byr+iuL+FBVIcUqEqy6HyC5ltqtdyzdc6LBtCGI79G1Y4PPwT01xyS +fvalY8L1X44uT6EYGQIrMgqCZH0Wk9GjQjBAMB0GA1UdDgQWBBR8XQKEE9TMipuB +zhccLikenEhjQjAOBgNVHQ8BAf8EBAMCAQYwDwYDVR0TAQH/BAUwAwEB/zAKBggq 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CN=emSign ECC Root CA - C3 O=eMudhra Inc OU=emSign PKI +# Subject: CN=emSign ECC Root CA - C3 O=eMudhra Inc OU=emSign PKI +# Label: "emSign ECC Root CA - C3" +# Serial: 582948710642506000014504 +# MD5 Fingerprint: 3e:53:b3:a3:81:ee:d7:10:f8:d3:b0:1d:17:92:f5:d5 +# SHA1 Fingerprint: b6:af:43:c2:9b:81:53:7d:f6:ef:6b:c3:1f:1f:60:15:0c:ee:48:66 +# SHA256 Fingerprint: bc:4d:80:9b:15:18:9d:78:db:3e:1d:8c:f4:f9:72:6a:79:5d:a1:64:3c:a5:f1:35:8e:1d:db:0e:dc:0d:7e:b3 +-----BEGIN CERTIFICATE----- +MIICKzCCAbGgAwIBAgIKe3G2gla4EnycqDAKBggqhkjOPQQDAzBaMQswCQYDVQQG +EwJVUzETMBEGA1UECxMKZW1TaWduIFBLSTEUMBIGA1UEChMLZU11ZGhyYSBJbmMx +IDAeBgNVBAMTF2VtU2lnbiBFQ0MgUm9vdCBDQSAtIEMzMB4XDTE4MDIxODE4MzAw +MFoXDTQzMDIxODE4MzAwMFowWjELMAkGA1UEBhMCVVMxEzARBgNVBAsTCmVtU2ln +biBQS0kxFDASBgNVBAoTC2VNdWRocmEgSW5jMSAwHgYDVQQDExdlbVNpZ24gRUND +IFJvb3QgQ0EgLSBDMzB2MBAGByqGSM49AgEGBSuBBAAiA2IABP2lYa57JhAd6bci +MK4G9IGzsUJxlTm801Ljr6/58pc1kjZGDoeVjbk5Wum739D+yAdBPLtVb4Ojavti 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Certificate Authority 2017 O=Microsoft Corporation +# Subject: CN=Microsoft ECC Root Certificate Authority 2017 O=Microsoft Corporation +# Label: "Microsoft ECC Root Certificate Authority 2017" +# Serial: 136839042543790627607696632466672567020 +# MD5 Fingerprint: dd:a1:03:e6:4a:93:10:d1:bf:f0:19:42:cb:fe:ed:67 +# SHA1 Fingerprint: 99:9a:64:c3:7f:f4:7d:9f:ab:95:f1:47:69:89:14:60:ee:c4:c3:c5 +# SHA256 Fingerprint: 35:8d:f3:9d:76:4a:f9:e1:b7:66:e9:c9:72:df:35:2e:e1:5c:fa:c2:27:af:6a:d1:d7:0e:8e:4a:6e:dc:ba:02 +-----BEGIN CERTIFICATE----- +MIICWTCCAd+gAwIBAgIQZvI9r4fei7FK6gxXMQHC7DAKBggqhkjOPQQDAzBlMQsw +CQYDVQQGEwJVUzEeMBwGA1UEChMVTWljcm9zb2Z0IENvcnBvcmF0aW9uMTYwNAYD +VQQDEy1NaWNyb3NvZnQgRUNDIFJvb3QgQ2VydGlmaWNhdGUgQXV0aG9yaXR5IDIw +MTcwHhcNMTkxMjE4MjMwNjQ1WhcNNDIwNzE4MjMxNjA0WjBlMQswCQYDVQQGEwJV +UzEeMBwGA1UEChMVTWljcm9zb2Z0IENvcnBvcmF0aW9uMTYwNAYDVQQDEy1NaWNy +b3NvZnQgRUNDIFJvb3QgQ2VydGlmaWNhdGUgQXV0aG9yaXR5IDIwMTcwdjAQBgcq 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c7:41:f7:0f:4b:2a:8d:88:bf:2e:71:c1:41:22:ef:53:ef:10:eb:a0:cf:a5:e6:4c:fa:20:f4:18:85:30:73:e0 +-----BEGIN CERTIFICATE----- +MIIFqDCCA5CgAwIBAgIQHtOXCV/YtLNHcB6qvn9FszANBgkqhkiG9w0BAQwFADBl +MQswCQYDVQQGEwJVUzEeMBwGA1UEChMVTWljcm9zb2Z0IENvcnBvcmF0aW9uMTYw +NAYDVQQDEy1NaWNyb3NvZnQgUlNBIFJvb3QgQ2VydGlmaWNhdGUgQXV0aG9yaXR5 +IDIwMTcwHhcNMTkxMjE4MjI1MTIyWhcNNDIwNzE4MjMwMDIzWjBlMQswCQYDVQQG +EwJVUzEeMBwGA1UEChMVTWljcm9zb2Z0IENvcnBvcmF0aW9uMTYwNAYDVQQDEy1N +aWNyb3NvZnQgUlNBIFJvb3QgQ2VydGlmaWNhdGUgQXV0aG9yaXR5IDIwMTcwggIi +MA0GCSqGSIb3DQEBAQUAA4ICDwAwggIKAoICAQDKW76UM4wplZEWCpW9R2LBifOZ +Nt9GkMml7Xhqb0eRaPgnZ1AzHaGm++DlQ6OEAlcBXZxIQIJTELy/xztokLaCLeX0 +ZdDMbRnMlfl7rEqUrQ7eS0MdhweSE5CAg2Q1OQT85elss7YfUJQ4ZVBcF0a5toW1 +HLUX6NZFndiyJrDKxHBKrmCk3bPZ7Pw71VdyvD/IybLeS2v4I2wDwAW9lcfNcztm +gGTjGqwu+UcF8ga2m3P1eDNbx6H7JyqhtJqRjJHTOoI+dkC0zVJhUXAoP8XFWvLJ +jEm7FFtNyP9nTUwSlq31/niol4fX/V4ggNyhSyL71Imtus5Hl0dVe49FyGcohJUc +aDDv70ngNXtk55iwlNpNhTs+VcQor1fznhPbRiefHqJeRIOkpcrVE7NLP8TjwuaG 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CN=Trustwave Global Certification Authority O=Trustwave Holdings, Inc. +# Label: "Trustwave Global Certification Authority" +# Serial: 1846098327275375458322922162 +# MD5 Fingerprint: f8:1c:18:2d:2f:ba:5f:6d:a1:6c:bc:c7:ab:91:c7:0e +# SHA1 Fingerprint: 2f:8f:36:4f:e1:58:97:44:21:59:87:a5:2a:9a:d0:69:95:26:7f:b5 +# SHA256 Fingerprint: 97:55:20:15:f5:dd:fc:3c:87:88:c0:06:94:45:55:40:88:94:45:00:84:f1:00:86:70:86:bc:1a:2b:b5:8d:c8 +-----BEGIN CERTIFICATE----- +MIIF2jCCA8KgAwIBAgIMBfcOhtpJ80Y1LrqyMA0GCSqGSIb3DQEBCwUAMIGIMQsw +CQYDVQQGEwJVUzERMA8GA1UECAwISWxsaW5vaXMxEDAOBgNVBAcMB0NoaWNhZ28x +ITAfBgNVBAoMGFRydXN0d2F2ZSBIb2xkaW5ncywgSW5jLjExMC8GA1UEAwwoVHJ1 +c3R3YXZlIEdsb2JhbCBDZXJ0aWZpY2F0aW9uIEF1dGhvcml0eTAeFw0xNzA4MjMx +OTM0MTJaFw00MjA4MjMxOTM0MTJaMIGIMQswCQYDVQQGEwJVUzERMA8GA1UECAwI +SWxsaW5vaXMxEDAOBgNVBAcMB0NoaWNhZ28xITAfBgNVBAoMGFRydXN0d2F2ZSBI +b2xkaW5ncywgSW5jLjExMC8GA1UEAwwoVHJ1c3R3YXZlIEdsb2JhbCBDZXJ0aWZp +Y2F0aW9uIEF1dGhvcml0eTCCAiIwDQYJKoZIhvcNAQEBBQADggIPADCCAgoCggIB 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Fingerprint: 8f:6b:f2:a9:27:4a:da:14:a0:c4:f4:8e:61:27:f9:c0:1e:78:5d:d1 +# SHA256 Fingerprint: 88:f4:38:dc:f8:ff:d1:fa:8f:42:91:15:ff:e5:f8:2a:e1:e0:6e:0c:70:c3:75:fa:ad:71:7b:34:a4:9e:72:65 +-----BEGIN CERTIFICATE----- +MIIFojCCA4qgAwIBAgIUAZQwHqIL3fXFMyqxQ0Rx+NZQTQ0wDQYJKoZIhvcNAQEM +BQAwaTELMAkGA1UEBhMCS1IxJjAkBgNVBAoMHU5BVkVSIEJVU0lORVNTIFBMQVRG +T1JNIENvcnAuMTIwMAYDVQQDDClOQVZFUiBHbG9iYWwgUm9vdCBDZXJ0aWZpY2F0 +aW9uIEF1dGhvcml0eTAeFw0xNzA4MTgwODU4NDJaFw0zNzA4MTgyMzU5NTlaMGkx +CzAJBgNVBAYTAktSMSYwJAYDVQQKDB1OQVZFUiBCVVNJTkVTUyBQTEFURk9STSBD +b3JwLjEyMDAGA1UEAwwpTkFWRVIgR2xvYmFsIFJvb3QgQ2VydGlmaWNhdGlvbiBB +dXRob3JpdHkwggIiMA0GCSqGSIb3DQEBAQUAA4ICDwAwggIKAoICAQC21PGTXLVA +iQqrDZBbUGOukJR0F0Vy1ntlWilLp1agS7gvQnXp2XskWjFlqxcX0TM62RHcQDaH +38dq6SZeWYp34+hInDEW+j6RscrJo+KfziFTowI2MMtSAuXaMl3Dxeb57hHHi8lE +HoSTGEq0n+USZGnQJoViAbbJAh2+g1G7XNr4rRVqmfeSVPc0W+m/6imBEtRTkZaz +kVrd/pBzKPswRrXKCAfHcXLJZtM0l/aM9BhK4dA9WkW2aacp+yPOiNgSnABIqKYP 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c4:14:30:e4:fa:66:43:94:2a:6a:1b:24:5f:19:d0:ef +# SHA1 Fingerprint: 53:a2:b0:4b:ca:6b:d6:45:e6:39:8a:8e:c4:0d:d2:bf:77:c3:a2:90 +# SHA256 Fingerprint: 4f:a3:12:6d:8d:3a:11:d1:c4:85:5a:4f:80:7c:ba:d6:cf:91:9d:3a:5a:88:b0:3b:ea:2c:63:72:d9:3c:40:c9 +-----BEGIN CERTIFICATE----- +MIIFWjCCA0KgAwIBAgISEdK7udcjGJ5AXwqdLdDfJWfRMA0GCSqGSIb3DQEBDAUA +MEYxCzAJBgNVBAYTAkJFMRkwFwYDVQQKExBHbG9iYWxTaWduIG52LXNhMRwwGgYD +VQQDExNHbG9iYWxTaWduIFJvb3QgUjQ2MB4XDTE5MDMyMDAwMDAwMFoXDTQ2MDMy +MDAwMDAwMFowRjELMAkGA1UEBhMCQkUxGTAXBgNVBAoTEEdsb2JhbFNpZ24gbnYt +c2ExHDAaBgNVBAMTE0dsb2JhbFNpZ24gUm9vdCBSNDYwggIiMA0GCSqGSIb3DQEB +AQUAA4ICDwAwggIKAoICAQCsrHQy6LNl5brtQyYdpokNRbopiLKkHWPd08EsCVeJ +OaFV6Wc0dwxu5FUdUiXSE2te4R2pt32JMl8Nnp8semNgQB+msLZ4j5lUlghYruQG +vGIFAha/r6gjA7aUD7xubMLL1aa7DOn2wQL7Id5m3RerdELv8HQvJfTqa1VbkNud +316HCkD7rRlr+/fKYIje2sGP1q7Vf9Q8g+7XFkyDRTNrJ9CG0Bwta/OrffGFqfUo +0q3v84RLHIf8E6M6cqJaESvWJ3En7YEtbWaBkoe0G1h6zD8K+kZPTXhc+CtI4wSE 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OU=Certum Certification Authority +# Subject: CN=Certum EC-384 CA O=Asseco Data Systems S.A. OU=Certum Certification Authority +# Label: "Certum EC-384 CA" +# Serial: 160250656287871593594747141429395092468 +# MD5 Fingerprint: b6:65:b3:96:60:97:12:a1:ec:4e:e1:3d:a3:c6:c9:f1 +# SHA1 Fingerprint: f3:3e:78:3c:ac:df:f4:a2:cc:ac:67:55:69:56:d7:e5:16:3c:e1:ed +# SHA256 Fingerprint: 6b:32:80:85:62:53:18:aa:50:d1:73:c9:8d:8b:da:09:d5:7e:27:41:3d:11:4c:f7:87:a0:f5:d0:6c:03:0c:f6 +-----BEGIN CERTIFICATE----- +MIICZTCCAeugAwIBAgIQeI8nXIESUiClBNAt3bpz9DAKBggqhkjOPQQDAzB0MQsw +CQYDVQQGEwJQTDEhMB8GA1UEChMYQXNzZWNvIERhdGEgU3lzdGVtcyBTLkEuMScw +JQYDVQQLEx5DZXJ0dW0gQ2VydGlmaWNhdGlvbiBBdXRob3JpdHkxGTAXBgNVBAMT +EENlcnR1bSBFQy0zODQgQ0EwHhcNMTgwMzI2MDcyNDU0WhcNNDMwMzI2MDcyNDU0 +WjB0MQswCQYDVQQGEwJQTDEhMB8GA1UEChMYQXNzZWNvIERhdGEgU3lzdGVtcyBT +LkEuMScwJQYDVQQLEx5DZXJ0dW0gQ2VydGlmaWNhdGlvbiBBdXRob3JpdHkxGTAX +BgNVBAMTEENlcnR1bSBFQy0zODQgQ0EwdjAQBgcqhkjOPQIBBgUrgQQAIgNiAATE +KI6rGFtqvm5kN2PkzeyrOvfMobgOgknXhimfoZTy42B4mIF4Bk3y7JoOV2CDn7Tm +Fy8as10CW4kjPMIRBSqniBMY81CE1700LCeJVf/OTOffph8oxPBUw7l8t1Ot68Kj +QjBAMA8GA1UdEwEB/wQFMAMBAf8wHQYDVR0OBBYEFI0GZnQkdjrzife81r1HfS+8 +EF9LMA4GA1UdDwEB/wQEAwIBBjAKBggqhkjOPQQDAwNoADBlAjADVS2m5hjEfO/J +UG7BJw+ch69u1RsIGL2SKcHvlJF40jocVYli5RsJHrpka/F2tNQCMQC0QoSZ/6vn +nvuRlydd3LBbMHHOXjgaatkl5+r3YZJW+OraNsKHZZYuciUvf9/DE8k= +-----END CERTIFICATE----- + +# Issuer: CN=Certum Trusted Root CA O=Asseco Data Systems S.A. OU=Certum Certification Authority +# Subject: CN=Certum Trusted Root CA O=Asseco Data Systems S.A. OU=Certum Certification Authority +# Label: "Certum Trusted Root CA" +# Serial: 40870380103424195783807378461123655149 +# MD5 Fingerprint: 51:e1:c2:e7:fe:4c:84:af:59:0e:2f:f4:54:6f:ea:29 +# SHA1 Fingerprint: c8:83:44:c0:18:ae:9f:cc:f1:87:b7:8f:22:d1:c5:d7:45:84:ba:e5 +# SHA256 Fingerprint: fe:76:96:57:38:55:77:3e:37:a9:5e:7a:d4:d9:cc:96:c3:01:57:c1:5d:31:76:5b:a9:b1:57:04:e1:ae:78:fd +-----BEGIN CERTIFICATE----- +MIIFwDCCA6igAwIBAgIQHr9ZULjJgDdMBvfrVU+17TANBgkqhkiG9w0BAQ0FADB6 +MQswCQYDVQQGEwJQTDEhMB8GA1UEChMYQXNzZWNvIERhdGEgU3lzdGVtcyBTLkEu +MScwJQYDVQQLEx5DZXJ0dW0gQ2VydGlmaWNhdGlvbiBBdXRob3JpdHkxHzAdBgNV +BAMTFkNlcnR1bSBUcnVzdGVkIFJvb3QgQ0EwHhcNMTgwMzE2MTIxMDEzWhcNNDMw +MzE2MTIxMDEzWjB6MQswCQYDVQQGEwJQTDEhMB8GA1UEChMYQXNzZWNvIERhdGEg +U3lzdGVtcyBTLkEuMScwJQYDVQQLEx5DZXJ0dW0gQ2VydGlmaWNhdGlvbiBBdXRo +b3JpdHkxHzAdBgNVBAMTFkNlcnR1bSBUcnVzdGVkIFJvb3QgQ0EwggIiMA0GCSqG +SIb3DQEBAQUAA4ICDwAwggIKAoICAQDRLY67tzbqbTeRn06TpwXkKQMlzhyC93yZ 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Research Institutions CA +# Label: "HARICA TLS ECC Root CA 2021" +# Serial: 137515985548005187474074462014555733966 +# MD5 Fingerprint: ae:f7:4c:e5:66:35:d1:b7:9b:8c:22:93:74:d3:4b:b0 +# SHA1 Fingerprint: bc:b0:c1:9d:e9:98:92:70:19:38:57:e9:8d:a7:b4:5d:6e:ee:01:48 +# SHA256 Fingerprint: 3f:99:cc:47:4a:cf:ce:4d:fe:d5:87:94:66:5e:47:8d:15:47:73:9f:2e:78:0f:1b:b4:ca:9b:13:30:97:d4:01 +-----BEGIN CERTIFICATE----- +MIICVDCCAdugAwIBAgIQZ3SdjXfYO2rbIvT/WeK/zjAKBggqhkjOPQQDAzBsMQsw +CQYDVQQGEwJHUjE3MDUGA1UECgwuSGVsbGVuaWMgQWNhZGVtaWMgYW5kIFJlc2Vh +cmNoIEluc3RpdHV0aW9ucyBDQTEkMCIGA1UEAwwbSEFSSUNBIFRMUyBFQ0MgUm9v +dCBDQSAyMDIxMB4XDTIxMDIxOTExMDExMFoXDTQ1MDIxMzExMDEwOVowbDELMAkG +A1UEBhMCR1IxNzA1BgNVBAoMLkhlbGxlbmljIEFjYWRlbWljIGFuZCBSZXNlYXJj +aCBJbnN0aXR1dGlvbnMgQ0ExJDAiBgNVBAMMG0hBUklDQSBUTFMgRUNDIFJvb3Qg +Q0EgMjAyMTB2MBAGByqGSM49AgEGBSuBBAAiA2IABDgI/rGgltJ6rK9JOtDA4MM7 +KKrxcm1lAEeIhPyaJmuqS7psBAqIXhfyVYf8MLA04jRYVxqEU+kw2anylnTDUR9Y 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Services LLC +# Subject: CN=GTS Root R4 O=Google Trust Services LLC +# Label: "GTS Root R4" +# Serial: 159662532700760215368942768210 +# MD5 Fingerprint: 43:96:83:77:19:4d:76:b3:9d:65:52:e4:1d:22:a5:e8 +# SHA1 Fingerprint: 77:d3:03:67:b5:e0:0c:15:f6:0c:38:61:df:7c:e1:3b:92:46:4d:47 +# SHA256 Fingerprint: 34:9d:fa:40:58:c5:e2:63:12:3b:39:8a:e7:95:57:3c:4e:13:13:c8:3f:e6:8f:93:55:6c:d5:e8:03:1b:3c:7d +-----BEGIN CERTIFICATE----- +MIICCTCCAY6gAwIBAgINAgPlwGjvYxqccpBQUjAKBggqhkjOPQQDAzBHMQswCQYD +VQQGEwJVUzEiMCAGA1UEChMZR29vZ2xlIFRydXN0IFNlcnZpY2VzIExMQzEUMBIG +A1UEAxMLR1RTIFJvb3QgUjQwHhcNMTYwNjIyMDAwMDAwWhcNMzYwNjIyMDAwMDAw +WjBHMQswCQYDVQQGEwJVUzEiMCAGA1UEChMZR29vZ2xlIFRydXN0IFNlcnZpY2Vz +IExMQzEUMBIGA1UEAxMLR1RTIFJvb3QgUjQwdjAQBgcqhkjOPQIBBgUrgQQAIgNi +AATzdHOnaItgrkO4NcWBMHtLSZ37wWHO5t5GvWvVYRg1rkDdc/eJkTBa6zzuhXyi +QHY7qca4R9gq55KRanPpsXI5nymfopjTX15YhmUPoYRlBtHci8nHc8iMai/lxKvR +HYqjQjBAMA4GA1UdDwEB/wQEAwIBhjAPBgNVHRMBAf8EBTADAQH/MB0GA1UdDgQW 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Root G5" +# Serial: 13129116028163249804115411775095713523 +# MD5 Fingerprint: d3:71:04:6a:43:1c:db:a6:59:e1:a8:a3:aa:c5:71:ed +# SHA1 Fingerprint: 17:f3:de:5e:9f:0f:19:e9:8e:f6:1f:32:26:6e:20:c4:07:ae:30:ee +# SHA256 Fingerprint: 01:8e:13:f0:77:25:32:cf:80:9b:d1:b1:72:81:86:72:83:fc:48:c6:e1:3b:e9:c6:98:12:85:4a:49:0c:1b:05 +-----BEGIN CERTIFICATE----- +MIICGTCCAZ+gAwIBAgIQCeCTZaz32ci5PhwLBCou8zAKBggqhkjOPQQDAzBOMQsw +CQYDVQQGEwJVUzEXMBUGA1UEChMORGlnaUNlcnQsIEluYy4xJjAkBgNVBAMTHURp +Z2lDZXJ0IFRMUyBFQ0MgUDM4NCBSb290IEc1MB4XDTIxMDExNTAwMDAwMFoXDTQ2 +MDExNDIzNTk1OVowTjELMAkGA1UEBhMCVVMxFzAVBgNVBAoTDkRpZ2lDZXJ0LCBJ +bmMuMSYwJAYDVQQDEx1EaWdpQ2VydCBUTFMgRUNDIFAzODQgUm9vdCBHNTB2MBAG +ByqGSM49AgEGBSuBBAAiA2IABMFEoc8Rl1Ca3iOCNQfN0MsYndLxf3c1TzvdlHJS +7cI7+Oz6e2tYIOyZrsn8aLN1udsJ7MgT9U7GCh1mMEy7H0cKPGEQQil8pQgO4CLp +0zVozptjn4S1mU1YoI71VOeVyaNCMEAwHQYDVR0OBBYEFMFRRVBZqz7nLFr6ICIS +B4CIfBFqMA4GA1UdDwEB/wQEAwIBhjAPBgNVHRMBAf8EBTADAQH/MAoGCCqGSM49 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8f:af:7d:2e:2c:b4:70:9b:b8:e0:b3:36:66:bf:75:a5:dd:45:b5:de:48:0f:8e:a8:d4:bf:e6:be:bc:17:f2:ed +-----BEGIN CERTIFICATE----- +MIIFiTCCA3GgAwIBAgIQb77arXO9CEDii02+1PdbkTANBgkqhkiG9w0BAQsFADBO +MQswCQYDVQQGEwJVUzEYMBYGA1UECgwPU1NMIENvcnBvcmF0aW9uMSUwIwYDVQQD +DBxTU0wuY29tIFRMUyBSU0EgUm9vdCBDQSAyMDIyMB4XDTIyMDgyNTE2MzQyMloX +DTQ2MDgxOTE2MzQyMVowTjELMAkGA1UEBhMCVVMxGDAWBgNVBAoMD1NTTCBDb3Jw +b3JhdGlvbjElMCMGA1UEAwwcU1NMLmNvbSBUTFMgUlNBIFJvb3QgQ0EgMjAyMjCC +AiIwDQYJKoZIhvcNAQEBBQADggIPADCCAgoCggIBANCkCXJPQIgSYT41I57u9nTP +L3tYPc48DRAokC+X94xI2KDYJbFMsBFMF3NQ0CJKY7uB0ylu1bUJPiYYf7ISf5OY +t6/wNr/y7hienDtSxUcZXXTzZGbVXcdotL8bHAajvI9AI7YexoS9UcQbOcGV0ins +S657Lb85/bRi3pZ7QcacoOAGcvvwB5cJOYF0r/c0WRFXCsJbwST0MXMwgsadugL3 +PnxEX4MN8/HdIGkWCVDi1FW24IBydm5MR7d1VVm0U3TZlMZBrViKMWYPHqIbKUBO +L9975hYsLfy/7PO0+r4Y9ptJ1O4Fbtk085zx7AGL0SDGD6C1vBdOSHtRwvzpXGk3 +R2azaPgVKPC506QVzFpPulJwoxJF3ca6TvvC0PeoUidtbnm1jPx7jMEWTO6Af77w +dr5BUxIzrlo4QqvXDz5BjXYHMtWrifZOZ9mxQnUjbvPNQrL8VfVThxc7wDNY8VLS 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CERTIFICATE----- +MIICFTCCAZugAwIBAgIQPZg7pmY9kGP3fiZXOATvADAKBggqhkjOPQQDAzBMMS4w +LAYDVQQDDCVBdG9zIFRydXN0ZWRSb290IFJvb3QgQ0EgRUNDIFRMUyAyMDIxMQ0w +CwYDVQQKDARBdG9zMQswCQYDVQQGEwJERTAeFw0yMTA0MjIwOTI2MjNaFw00MTA0 +MTcwOTI2MjJaMEwxLjAsBgNVBAMMJUF0b3MgVHJ1c3RlZFJvb3QgUm9vdCBDQSBF +Q0MgVExTIDIwMjExDTALBgNVBAoMBEF0b3MxCzAJBgNVBAYTAkRFMHYwEAYHKoZI +zj0CAQYFK4EEACIDYgAEloZYKDcKZ9Cg3iQZGeHkBQcfl+3oZIK59sRxUM6KDP/X +tXa7oWyTbIOiaG6l2b4siJVBzV3dscqDY4PMwL502eCdpO5KTlbgmClBk1IQ1SQ4 +AjJn8ZQSb+/Xxd4u/RmAo0IwQDAPBgNVHRMBAf8EBTADAQH/MB0GA1UdDgQWBBR2 +KCXWfeBmmnoJsmo7jjPXNtNPojAOBgNVHQ8BAf8EBAMCAYYwCgYIKoZIzj0EAwMD +aAAwZQIwW5kp85wxtolrbNa9d+F851F+uDrNozZffPc8dz7kUK2o59JZDCaOMDtu +CCrCp1rIAjEAmeMM56PDr9NJLkaCI2ZdyQAUEv049OGYa3cpetskz2VAv9LcjBHo +9H1/IISpQuQo +-----END CERTIFICATE----- + +# Issuer: CN=Atos TrustedRoot Root CA RSA TLS 2021 O=Atos +# Subject: CN=Atos TrustedRoot Root CA RSA TLS 2021 O=Atos +# Label: "Atos TrustedRoot Root CA RSA TLS 2021" +# Serial: 111436099570196163832749341232207667876 +# MD5 Fingerprint: d4:d3:46:b8:9a:c0:9c:76:5d:9e:3a:c3:b9:99:31:d2 +# SHA1 Fingerprint: 18:52:3b:0d:06:37:e4:d6:3a:df:23:e4:98:fb:5b:16:fb:86:74:48 +# SHA256 Fingerprint: 81:a9:08:8e:a5:9f:b3:64:c5:48:a6:f8:55:59:09:9b:6f:04:05:ef:bf:18:e5:32:4e:c9:f4:57:ba:00:11:2f +-----BEGIN CERTIFICATE----- +MIIFZDCCA0ygAwIBAgIQU9XP5hmTC/srBRLYwiqipDANBgkqhkiG9w0BAQwFADBM +MS4wLAYDVQQDDCVBdG9zIFRydXN0ZWRSb290IFJvb3QgQ0EgUlNBIFRMUyAyMDIx +MQ0wCwYDVQQKDARBdG9zMQswCQYDVQQGEwJERTAeFw0yMTA0MjIwOTIxMTBaFw00 +MTA0MTcwOTIxMDlaMEwxLjAsBgNVBAMMJUF0b3MgVHJ1c3RlZFJvb3QgUm9vdCBD +QSBSU0EgVExTIDIwMjExDTALBgNVBAoMBEF0b3MxCzAJBgNVBAYTAkRFMIICIjAN +BgkqhkiG9w0BAQEFAAOCAg8AMIICCgKCAgEAtoAOxHm9BYx9sKOdTSJNy/BBl01Z +4NH+VoyX8te9j2y3I49f1cTYQcvyAh5x5en2XssIKl4w8i1mx4QbZFc4nXUtVsYv +Ye+W/CBGvevUez8/fEc4BKkbqlLfEzfTFRVOvV98r61jx3ncCHvVoOX3W3WsgFWZ +kmGbzSoXfduP9LVq6hdKZChmFSlsAvFr1bqjM9xaZ6cF4r9lthawEO3NUDPJcFDs +GY6wx/J0W2tExn2WuZgIWWbeKQGb9Cpt0xU6kGpn8bRrZtkh68rZYnxGEFzedUln 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Issuer: CN=D-TRUST BR Root CA 2 2023 O=D-Trust GmbH +# Subject: CN=D-TRUST BR Root CA 2 2023 O=D-Trust GmbH +# Label: "D-TRUST BR Root CA 2 2023" +# Serial: 153168538924886464690566649552453098598 +# MD5 Fingerprint: e1:09:ed:d3:60:d4:56:1b:47:1f:b7:0c:5f:1b:5f:85 +# SHA1 Fingerprint: 2d:b0:70:ee:71:94:af:69:68:17:db:79:ce:58:9f:a0:6b:96:f7:87 +# SHA256 Fingerprint: 05:52:e6:f8:3f:df:65:e8:fa:96:70:e6:66:df:28:a4:e2:13:40:b5:10:cb:e5:25:66:f9:7c:4f:b9:4b:2b:d1 +-----BEGIN CERTIFICATE----- +MIIFqTCCA5GgAwIBAgIQczswBEhb2U14LnNLyaHcZjANBgkqhkiG9w0BAQ0FADBI +MQswCQYDVQQGEwJERTEVMBMGA1UEChMMRC1UcnVzdCBHbWJIMSIwIAYDVQQDExlE +LVRSVVNUIEJSIFJvb3QgQ0EgMiAyMDIzMB4XDTIzMDUwOTA4NTYzMVoXDTM4MDUw +OTA4NTYzMFowSDELMAkGA1UEBhMCREUxFTATBgNVBAoTDEQtVHJ1c3QgR21iSDEi +MCAGA1UEAxMZRC1UUlVTVCBCUiBSb290IENBIDIgMjAyMzCCAiIwDQYJKoZIhvcN +AQEBBQADggIPADCCAgoCggIBAK7/CVmRgApKaOYkP7in5Mg6CjoWzckjYaCTcfKr +i3OPoGdlYNJUa2NRb0kz4HIHE304zQaSBylSa053bATTlfrdTIzZXcFhfUvnKLNE 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Inc. +# Subject: CN=TrustAsia TLS RSA Root CA O=TrustAsia Technologies, Inc. +# Label: "TrustAsia TLS RSA Root CA" +# Serial: 160405846464868906657516898462547310235378010780 +# MD5 Fingerprint: 3b:9e:c3:86:0f:34:3c:6b:c5:46:c4:8e:1d:e7:19:12 +# SHA1 Fingerprint: a5:46:50:c5:62:ea:95:9a:1a:a7:04:6f:17:58:c7:29:53:3d:03:fa +# SHA256 Fingerprint: 06:c0:8d:7d:af:d8:76:97:1e:b1:12:4f:e6:7f:84:7e:c0:c7:a1:58:d3:ea:53:cb:e9:40:e2:ea:97:91:f4:c3 +-----BEGIN CERTIFICATE----- +MIIFgDCCA2igAwIBAgIUHBjYz+VTPyI1RlNUJDxsR9FcSpwwDQYJKoZIhvcNAQEM +BQAwWDELMAkGA1UEBhMCQ04xJTAjBgNVBAoTHFRydXN0QXNpYSBUZWNobm9sb2dp +ZXMsIEluYy4xIjAgBgNVBAMTGVRydXN0QXNpYSBUTFMgUlNBIFJvb3QgQ0EwHhcN +MjQwNTE1MDU0MTU3WhcNNDQwNTE1MDU0MTU2WjBYMQswCQYDVQQGEwJDTjElMCMG +A1UEChMcVHJ1c3RBc2lhIFRlY2hub2xvZ2llcywgSW5jLjEiMCAGA1UEAxMZVHJ1 +c3RBc2lhIFRMUyBSU0EgUm9vdCBDQTCCAiIwDQYJKoZIhvcNAQEBBQADggIPADCC +AgoCggIBAMMWuBtqpERz5dZO9LnPWwvB0ZqB9WOwj0PBuwhaGnrhB3YmH49pVr7+ +NmDQDIPNlOrnxS1cLwUWAp4KqC/lYCZUlviYQB2srp10Zy9U+5RjmOMmSoPGlbYJ 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+MIIFqTCCA5GgAwIBAgIQaSYJfoBLTKCnjHhiU19abzANBgkqhkiG9w0BAQ0FADBI +MQswCQYDVQQGEwJERTEVMBMGA1UEChMMRC1UcnVzdCBHbWJIMSIwIAYDVQQDExlE +LVRSVVNUIEVWIFJvb3QgQ0EgMiAyMDIzMB4XDTIzMDUwOTA5MTAzM1oXDTM4MDUw +OTA5MTAzMlowSDELMAkGA1UEBhMCREUxFTATBgNVBAoTDEQtVHJ1c3QgR21iSDEi +MCAGA1UEAxMZRC1UUlVTVCBFViBSb290IENBIDIgMjAyMzCCAiIwDQYJKoZIhvcN +AQEBBQADggIPADCCAgoCggIBANiOo4mAC7JXUtypU0w3uX9jFxPvp1sjW2l1sJkK +F8GLxNuo4MwxusLyzV3pt/gdr2rElYfXR8mV2IIEUD2BCP/kPbOx1sWy/YgJ25yE +7CUXFId/MHibaljJtnMoPDT3mfd/06b4HEV8rSyMlD/YZxBTfiLNTiVR8CUkNRFe +EMbsh2aJgWi6zCudR3Mfvc2RpHJqnKIbGKBv7FD0fUDCqDDPvXPIEysQEx6Lmqg6 +lHPTGGkKSv/BAQP/eX+1SH977ugpbzZMlWGG2Pmic4ruri+W7mjNPU0oQvlFKzIb +RlUWaqZLKfm7lVa/Rh3sHZMdwGWyH6FDrlaeoLGPaxK3YG14C8qKXO0elg6DpkiV +jTujIcSuWMYAsoS0I6SWhjW42J7YrDRJmGOVxcttSEfi8i4YHtAxq9107PncjLgc +jmgjutDzUNzPZY9zOjLHfP7KgiJPvo5iR2blzYfi6NUPGJ/lBHJLRjwQ8kTCZFZx +TnXonMkmdMV9WdEKWw9t/p51HBjGGjp82A0EzM23RWV6sY+4roRIPrN6TagD4uJ+ +ARZZaBhDM7DS3LAaQzXupdqpRlyuhoFBAUp0JuyfBr/CBTdkdXgpaP3F9ev+R/nk 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+XBxvWHZks/wCuPWdCg== +-----END CERTIFICATE----- + +# Issuer: CN=SwissSign RSA TLS Root CA 2022 - 1 O=SwissSign AG +# Subject: CN=SwissSign RSA TLS Root CA 2022 - 1 O=SwissSign AG +# Label: "SwissSign RSA TLS Root CA 2022 - 1" +# Serial: 388078645722908516278762308316089881486363258315 +# MD5 Fingerprint: 16:2e:e4:19:76:81:85:ba:8e:91:58:f1:15:ef:72:39 +# SHA1 Fingerprint: 81:34:0a:be:4c:cd:ce:cc:e7:7d:cc:8a:d4:57:e2:45:a0:77:5d:ce +# SHA256 Fingerprint: 19:31:44:f4:31:e0:fd:db:74:07:17:d4:de:92:6a:57:11:33:88:4b:43:60:d3:0e:27:29:13:cb:e6:60:ce:41 +-----BEGIN CERTIFICATE----- +MIIFkzCCA3ugAwIBAgIUQ/oMX04bgBhE79G0TzUfRPSA7cswDQYJKoZIhvcNAQEL +BQAwUTELMAkGA1UEBhMCQ0gxFTATBgNVBAoTDFN3aXNzU2lnbiBBRzErMCkGA1UE +AxMiU3dpc3NTaWduIFJTQSBUTFMgUm9vdCBDQSAyMDIyIC0gMTAeFw0yMjA2MDgx +MTA4MjJaFw00NzA2MDgxMTA4MjJaMFExCzAJBgNVBAYTAkNIMRUwEwYDVQQKEwxT +d2lzc1NpZ24gQUcxKzApBgNVBAMTIlN3aXNzU2lnbiBSU0EgVExTIFJvb3QgQ0Eg +MjAyMiAtIDEwggIiMA0GCSqGSIb3DQEBAQUAA4ICDwAwggIKAoICAQDLKmjiC8NX 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ee:c9:97:c0:c3:0f:21:6f:7e:3b:8b:30:7d:2b:ae:42:41:2d:75:3f:c8:21:9d:af:d1:52:0b:25:72:85:0f:49 +-----BEGIN CERTIFICATE----- +MIICNTCCAbqgAwIBAgIQI/nD1jWvjyhLH/BU6n6XnTAKBggqhkjOPQQDAzBLMQsw +CQYDVQQGEwJDSDEZMBcGA1UECgwQT0lTVEUgRm91bmRhdGlvbjEhMB8GA1UEAwwY +T0lTVEUgU2VydmVyIFJvb3QgRUNDIEcxMB4XDTIzMDUzMTE0NDIyOFoXDTQ4MDUy +NDE0NDIyN1owSzELMAkGA1UEBhMCQ0gxGTAXBgNVBAoMEE9JU1RFIEZvdW5kYXRp +b24xITAfBgNVBAMMGE9JU1RFIFNlcnZlciBSb290IEVDQyBHMTB2MBAGByqGSM49 +AgEGBSuBBAAiA2IABBcv+hK8rBjzCvRE1nZCnrPoH7d5qVi2+GXROiFPqOujvqQy +cvO2Ackr/XeFblPdreqqLiWStukhEaivtUwL85Zgmjvn6hp4LrQ95SjeHIC6XG4N +2xml4z+cKrhAS93mT6NjMGEwDwYDVR0TAQH/BAUwAwEB/zAfBgNVHSMEGDAWgBQ3 +TYhlz/w9itWj8UnATgwQb0K0nDAdBgNVHQ4EFgQUN02IZc/8PYrVo/FJwE4MEG9C +tJwwDgYDVR0PAQH/BAQDAgGGMAoGCCqGSM49BAMDA2kAMGYCMQCpKjAd0MKfkFFR +QD6VVCHNFmb3U2wIFjnQEnx/Yxvf4zgAOdktUyBFCxxgZzFDJe0CMQCSia7pXGKD +YmH5LVerVrkR3SW+ak5KGoJr3M/TvEqzPNcum9v4KGm8ay3sMaE641c= +-----END CERTIFICATE----- + +# Issuer: CN=OISTE Server Root RSA G1 O=OISTE Foundation +# Subject: CN=OISTE Server Root RSA G1 O=OISTE Foundation +# Label: "OISTE Server Root RSA G1" +# Serial: 113845518112613905024960613408179309848 +# MD5 Fingerprint: 23:a7:9e:d4:70:b8:b9:14:57:41:8a:7e:44:59:e2:68 +# SHA1 Fingerprint: f7:00:34:25:94:88:68:31:e4:34:87:3f:70:fe:86:b3:86:9f:f0:6e +# SHA256 Fingerprint: 9a:e3:62:32:a5:18:9f:fd:db:35:3d:fd:26:52:0c:01:53:95:d2:27:77:da:c5:9d:b5:7b:98:c0:89:a6:51:e6 +-----BEGIN CERTIFICATE----- +MIIFgzCCA2ugAwIBAgIQVaXZZ5Qoxu0M+ifdWwFNGDANBgkqhkiG9w0BAQwFADBL +MQswCQYDVQQGEwJDSDEZMBcGA1UECgwQT0lTVEUgRm91bmRhdGlvbjEhMB8GA1UE +AwwYT0lTVEUgU2VydmVyIFJvb3QgUlNBIEcxMB4XDTIzMDUzMTE0MzcxNloXDTQ4 +MDUyNDE0MzcxNVowSzELMAkGA1UEBhMCQ0gxGTAXBgNVBAoMEE9JU1RFIEZvdW5k +YXRpb24xITAfBgNVBAMMGE9JU1RFIFNlcnZlciBSb290IFJTQSBHMTCCAiIwDQYJ +KoZIhvcNAQEBBQADggIPADCCAgoCggIBAKqu9KuCz/vlNwvn1ZatkOhLKdxVYOPM +vLO8LZK55KN68YG0nnJyQ98/qwsmtO57Gmn7KNByXEptaZnwYx4M0rH/1ow00O7b +rEi56rAUjtgHqSSY3ekJvqgiG1k50SeH3BzN+Puz6+mTeO0Pzjd8JnduodgsIUzk 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+gSe7BYhW3SCl95gtkRlpMV+bMPKZrXJAlszYd2abtNUOshD+FKrDgHGdPY3ofRRs +YWSGRqbXVMW215AWRqWFyp464+YTFrYVI8ypKVL9AMb2kI5Wj4kI3Zaq5tNqqYY1 +9tVFeEJKRvwDyF7YZvZFZSS0vod7VSCd9521Kvy5YhnLbDuv0204bKt7ph6N/Ome +/msVuduCmsuY33OhkKCgxeDoAaijFJzIwZqsFVAzje18KotzlUBDJvyBpCpfOZC3 +J8tRd/iWkx7P8nd9H0aTolkelUTFLXVksNb54Dxp6gS1HAviRkRNQzuXSXERvSS2 +wq1yVAb+axj5d9spLFKebXd7Yv0PTY6YMjAwcRLWJTXjn/hvnLXrahut6hDTlhZy +BiElxky8j3C7DOReIoMt0r7+hVu05L0= +-----END CERTIFICATE----- + +# Issuer: CN=e-Szigno TLS Root CA 2023 O=Microsec Ltd. +# Subject: CN=e-Szigno TLS Root CA 2023 O=Microsec Ltd. +# Label: "e-Szigno TLS Root CA 2023" +# Serial: 71934828665710877219916191754 +# MD5 Fingerprint: 6a:e9:99:74:a5:da:5e:f1:d9:2e:f2:c8:d1:86:8b:71 +# SHA1 Fingerprint: 6f:9a:d5:d5:df:e8:2c:eb:be:37:07:ee:4f:4f:52:58:29:41:d1:fe +# SHA256 Fingerprint: b4:91:41:50:2d:00:66:3d:74:0f:2e:7e:c3:40:c5:28:00:96:26:66:12:1a:36:d0:9c:f7:dd:2b:90:38:4f:b4 +-----BEGIN CERTIFICATE----- +MIICzzCCAjGgAwIBAgINAOhvGHvWOWuYSkmYCjAKBggqhkjOPQQDBDB1MQswCQYD +VQQGEwJIVTERMA8GA1UEBwwIQnVkYXBlc3QxFjAUBgNVBAoMDU1pY3Jvc2VjIEx0 +ZC4xFzAVBgNVBGEMDlZBVEhVLTIzNTg0NDk3MSIwIAYDVQQDDBllLVN6aWdubyBU +TFMgUm9vdCBDQSAyMDIzMB4XDTIzMDcxNzE0MDAwMFoXDTM4MDcxNzE0MDAwMFow +dTELMAkGA1UEBhMCSFUxETAPBgNVBAcMCEJ1ZGFwZXN0MRYwFAYDVQQKDA1NaWNy +b3NlYyBMdGQuMRcwFQYDVQRhDA5WQVRIVS0yMzU4NDQ5NzEiMCAGA1UEAwwZZS1T +emlnbm8gVExTIFJvb3QgQ0EgMjAyMzCBmzAQBgcqhkjOPQIBBgUrgQQAIwOBhgAE +AGgP36J8PKp0iGEKjcJMpQEiFNT3YHdCnAo4YKGMZz6zY+n6kbCLS+Y53wLCMAFS +AL/fjO1ZrTJlqwlZULUZwmgcAOAFX9pQJhzDrAQixTpN7+lXWDajwRlTEArRzT/v +SzUaQ49CE0y5LBqcvjC2xN7cS53kpDzLLtmt3999Cd8ukv+ho2MwYTAPBgNVHRMB +Af8EBTADAQH/MA4GA1UdDwEB/wQEAwIBBjAdBgNVHQ4EFgQUWYQCYlpGePVd3I8K +ECgj3NXW+0UwHwYDVR0jBBgwFoAUWYQCYlpGePVd3I8KECgj3NXW+0UwCgYIKoZI +zj0EAwQDgYsAMIGHAkIBLdqu9S54tma4n7Zwf2Z0z+yOfP7AAXmazlIC58PRDHpt +y7Ve7hekm9sEdu4pKeiv+62sUvTXK9Z3hBC9xdIoaDQCQTV2WnXzkoYI9bIeCvZl +C9p2x1L/Cx6AcCIwwzPbGO2E14vs7dOoY4G1VnxHx1YwlGhza9IuqbnZLBwpvQy6 +uWWL +-----END CERTIFICATE----- diff --git a/certifi/core.py b/certifi/core.py new file mode 100644 index 0000000000000000000000000000000000000000..1c9661cc7c2f6917c2506a30b2710002f81ab23a --- /dev/null +++ b/certifi/core.py @@ -0,0 +1,83 @@ +""" +certifi.py +~~~~~~~~~~ + +This module returns the installation location of cacert.pem or its contents. +""" +import sys +import atexit + +def exit_cacert_ctx() -> None: + _CACERT_CTX.__exit__(None, None, None) # type: ignore[union-attr] + + +if sys.version_info >= (3, 11): + + from importlib.resources import as_file, files + + _CACERT_CTX = None + _CACERT_PATH = None + + def where() -> str: + # This is slightly terrible, but we want to delay extracting the file + # in cases where we're inside of a zipimport situation until someone + # actually calls where(), but we don't want to re-extract the file + # on every call of where(), so we'll do it once then store it in a + # global variable. + global _CACERT_CTX + global _CACERT_PATH + if _CACERT_PATH is None: + # This is slightly janky, the importlib.resources API wants you to + # manage the cleanup of this file, so it doesn't actually return a + # path, it returns a context manager that will give you the path + # when you enter it and will do any cleanup when you leave it. In + # the common case of not needing a temporary file, it will just + # return the file system location and the __exit__() is a no-op. + # + # We also have to hold onto the actual context manager, because + # it will do the cleanup whenever it gets garbage collected, so + # we will also store that at the global level as well. + _CACERT_CTX = as_file(files("certifi").joinpath("cacert.pem")) + _CACERT_PATH = str(_CACERT_CTX.__enter__()) + atexit.register(exit_cacert_ctx) + + return _CACERT_PATH + + def contents() -> str: + return files("certifi").joinpath("cacert.pem").read_text(encoding="ascii") + +else: + + from importlib.resources import path as get_path, read_text + + _CACERT_CTX = None + _CACERT_PATH = None + + def where() -> str: + # This is slightly terrible, but we want to delay extracting the + # file in cases where we're inside of a zipimport situation until + # someone actually calls where(), but we don't want to re-extract + # the file on every call of where(), so we'll do it once then store + # it in a global variable. + global _CACERT_CTX + global _CACERT_PATH + if _CACERT_PATH is None: + # This is slightly janky, the importlib.resources API wants you + # to manage the cleanup of this file, so it doesn't actually + # return a path, it returns a context manager that will give + # you the path when you enter it and will do any cleanup when + # you leave it. In the common case of not needing a temporary + # file, it will just return the file system location and the + # __exit__() is a no-op. + # + # We also have to hold onto the actual context manager, because + # it will do the cleanup whenever it gets garbage collected, so + # we will also store that at the global level as well. + _CACERT_CTX = get_path("certifi", "cacert.pem") + _CACERT_PATH = str(_CACERT_CTX.__enter__()) + atexit.register(exit_cacert_ctx) + + return _CACERT_PATH + + def contents() -> str: + return read_text("certifi", "cacert.pem", encoding="ascii") diff --git a/certifi/py.typed b/certifi/py.typed new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/charset_normalizer/__init__.py b/charset_normalizer/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..0d3a37990145e94ad85406166dbaf52f4c311e5e --- /dev/null +++ b/charset_normalizer/__init__.py @@ -0,0 +1,48 @@ +""" +Charset-Normalizer +~~~~~~~~~~~~~~ +The Real First Universal Charset Detector. +A library that helps you read text from an unknown charset encoding. +Motivated by chardet, This package is trying to resolve the issue by taking a new approach. +All IANA character set names for which the Python core library provides codecs are supported. + +Basic usage: + >>> from charset_normalizer import from_bytes + >>> results = from_bytes('Bсеки човек има право на образование. Oбразованието!'.encode('utf_8')) + >>> best_guess = results.best() + >>> str(best_guess) + 'Bсеки човек има право на образование. Oбразованието!' + +Others methods and usages are available - see the full documentation +at . +:copyright: (c) 2021 by Ahmed TAHRI +:license: MIT, see LICENSE for more details. +""" + +from __future__ import annotations + +import logging + +from .api import from_bytes, from_fp, from_path, is_binary +from .legacy import detect +from .models import CharsetMatch, CharsetMatches +from .utils import set_logging_handler +from .version import VERSION, __version__ + +__all__ = ( + "from_fp", + "from_path", + "from_bytes", + "is_binary", + "detect", + "CharsetMatch", + "CharsetMatches", + "__version__", + "VERSION", + "set_logging_handler", +) + +# Attach a NullHandler to the top level logger by default +# https://docs.python.org/3.3/howto/logging.html#configuring-logging-for-a-library + +logging.getLogger("charset_normalizer").addHandler(logging.NullHandler()) diff --git a/charset_normalizer/__main__.py b/charset_normalizer/__main__.py new file mode 100644 index 0000000000000000000000000000000000000000..e0e76f7bfbb411d4424d3a1834b0ea803d80ea7e --- /dev/null +++ b/charset_normalizer/__main__.py @@ -0,0 +1,6 @@ +from __future__ import annotations + +from .cli import cli_detect + +if __name__ == "__main__": + cli_detect() diff --git a/charset_normalizer/api.py b/charset_normalizer/api.py new file mode 100644 index 0000000000000000000000000000000000000000..1f32091f229ea698da564c1a40e4f14dec440323 --- /dev/null +++ b/charset_normalizer/api.py @@ -0,0 +1,974 @@ +from __future__ import annotations + +import logging +from os import PathLike +from typing import BinaryIO + +from .cd import ( + coherence_ratio, + encoding_languages, + mb_encoding_languages, + merge_coherence_ratios, +) +from .constant import ( + IANA_SUPPORTED, + IANA_SUPPORTED_SIMILAR, + TOO_BIG_SEQUENCE, + TOO_SMALL_SEQUENCE, + TRACE, +) +from .md import mess_ratio +from .models import CharsetMatch, CharsetMatches +from .utils import ( + any_specified_encoding, + cut_sequence_chunks, + iana_name, + identify_sig_or_bom, + is_multi_byte_encoding, + should_strip_sig_or_bom, +) + +logger = logging.getLogger("charset_normalizer") +explain_handler = logging.StreamHandler() +explain_handler.setFormatter( + logging.Formatter("%(asctime)s | %(levelname)s | %(message)s") +) + +# Pre-compute a reordered encoding list: multibyte first, then single-byte. +# This allows the mb_definitive_match optimization to fire earlier, skipping +# all single-byte encodings for genuine CJK content. Multibyte codecs +# hard-fail (UnicodeDecodeError) on single-byte data almost instantly, so +# testing them first costs negligible time for non-CJK files. +_mb_supported: list[str] = [] +_sb_supported: list[str] = [] + +for _supported_enc in IANA_SUPPORTED: + try: + if is_multi_byte_encoding(_supported_enc): + _mb_supported.append(_supported_enc) + else: + _sb_supported.append(_supported_enc) + except ImportError: + _sb_supported.append(_supported_enc) + +IANA_SUPPORTED_MB_FIRST: list[str] = _mb_supported + _sb_supported + + +def from_bytes( + sequences: bytes | bytearray, + steps: int = 5, + chunk_size: int = 512, + threshold: float = 0.2, + cp_isolation: list[str] | None = None, + cp_exclusion: list[str] | None = None, + preemptive_behaviour: bool = True, + explain: bool = False, + language_threshold: float = 0.1, + enable_fallback: bool = True, +) -> CharsetMatches: + """ + Given a raw bytes sequence, return the best possibles charset usable to render str objects. + If there is no results, it is a strong indicator that the source is binary/not text. + By default, the process will extract 5 blocks of 512o each to assess the mess and coherence of a given sequence. + And will give up a particular code page after 20% of measured mess. Those criteria are customizable at will. + + The preemptive behavior DOES NOT replace the traditional detection workflow, it prioritize a particular code page + but never take it for granted. Can improve the performance. + + You may want to focus your attention to some code page or/and not others, use cp_isolation and cp_exclusion for that + purpose. + + This function will strip the SIG in the payload/sequence every time except on UTF-16, UTF-32. + By default the library does not setup any handler other than the NullHandler, if you choose to set the 'explain' + toggle to True it will alter the logger configuration to add a StreamHandler that is suitable for debugging. + Custom logging format and handler can be set manually. + """ + + if not isinstance(sequences, (bytearray, bytes)): + raise TypeError( + "Expected object of type bytes or bytearray, got: {}".format( + type(sequences) + ) + ) + + if explain: + previous_logger_level: int = logger.level + logger.addHandler(explain_handler) + logger.setLevel(TRACE) + + length: int = len(sequences) + + if length == 0: + logger.debug("Encoding detection on empty bytes, assuming utf_8 intention.") + if explain: # Defensive: ensure exit path clean handler + logger.removeHandler(explain_handler) + logger.setLevel(previous_logger_level) + return CharsetMatches([CharsetMatch(sequences, "utf_8", 0.0, False, [], "")]) + + if cp_isolation is not None: + logger.log( + TRACE, + "cp_isolation is set. use this flag for debugging purpose. " + "limited list of encoding allowed : %s.", + ", ".join(cp_isolation), + ) + cp_isolation = [iana_name(cp, False) for cp in cp_isolation] + else: + cp_isolation = [] + + if cp_exclusion is not None: + logger.log( + TRACE, + "cp_exclusion is set. use this flag for debugging purpose. " + "limited list of encoding excluded : %s.", + ", ".join(cp_exclusion), + ) + cp_exclusion = [iana_name(cp, False) for cp in cp_exclusion] + else: + cp_exclusion = [] + + if length <= (chunk_size * steps): + logger.log( + TRACE, + "override steps (%i) and chunk_size (%i) as content does not fit (%i byte(s) given) parameters.", + steps, + chunk_size, + length, + ) + steps = 1 + chunk_size = length + + if steps > 1 and length / steps < chunk_size: + chunk_size = int(length / steps) + + is_too_small_sequence: bool = len(sequences) < TOO_SMALL_SEQUENCE + is_too_large_sequence: bool = len(sequences) >= TOO_BIG_SEQUENCE + + if is_too_small_sequence: + logger.log( + TRACE, + "Trying to detect encoding from a tiny portion of ({}) byte(s).".format( + length + ), + ) + elif is_too_large_sequence: + logger.log( + TRACE, + "Using lazy str decoding because the payload is quite large, ({}) byte(s).".format( + length + ), + ) + + prioritized_encodings: list[str] = [] + + specified_encoding: str | None = ( + any_specified_encoding(sequences) if preemptive_behaviour else None + ) + + if specified_encoding is not None: + prioritized_encodings.append(specified_encoding) + logger.log( + TRACE, + "Detected declarative mark in sequence. Priority +1 given for %s.", + specified_encoding, + ) + + tested: set[str] = set() + tested_but_hard_failure: list[str] = [] + tested_but_soft_failure: list[str] = [] + soft_failure_skip: set[str] = set() + success_fast_tracked: set[str] = set() + + # Cache for decoded payload deduplication: hash(decoded_payload) -> (mean_mess_ratio, cd_ratios_merged, passed) + # When multiple encodings decode to the exact same string, we can skip the expensive + # mess_ratio and coherence_ratio analysis and reuse the results from the first encoding. + payload_result_cache: dict[int, tuple[float, list[tuple[str, float]], bool]] = {} + + # When a definitive result (chaos=0.0 and good coherence) is found after testing + # the prioritized encodings (ascii, utf_8), we can significantly reduce the remaining + # work. Encodings that target completely different language families (e.g., Cyrillic + # when the definitive match is Latin) are skipped entirely. + # Additionally, for same-family encodings that pass chaos probing, we reuse the + # definitive match's coherence ratios instead of recomputing them — a major savings + # since coherence_ratio accounts for ~30% of total time on slow Latin files. + definitive_match_found: bool = False + definitive_target_languages: set[str] = set() + # After the definitive match fires, we cap the number of additional same-family + # single-byte encodings that pass chaos probing. Once we've accumulated enough + # good candidates (N), further same-family SB encodings are unlikely to produce + # a better best() result and just waste mess_ratio + coherence_ratio time. + # The first encoding to trigger the definitive match is NOT counted (it's already in). + post_definitive_sb_success_count: int = 0 + POST_DEFINITIVE_SB_CAP: int = 7 + + # When a non-UTF multibyte encoding passes chaos probing with significant multibyte + # content (decoded length < 98% of raw length), skip all remaining single-byte encodings. + # Rationale: multi-byte decoders (CJK) have strict byte-sequence validation — if they + # decode without error AND pass chaos probing with substantial multibyte content, the + # data is genuinely multibyte encoded. Single-byte encodings will always decode (every + # byte maps to something) but waste time on mess_ratio before failing. + # The 98% threshold prevents false triggers on files that happen to have a few valid + # multibyte pairs (e.g., cp424/_ude_1.txt where big5 decodes with 99% ratio). + mb_definitive_match_found: bool = False + + fallback_ascii: CharsetMatch | None = None + fallback_u8: CharsetMatch | None = None + fallback_specified: CharsetMatch | None = None + + results: CharsetMatches = CharsetMatches() + + early_stop_results: CharsetMatches = CharsetMatches() + + sig_encoding, sig_payload = identify_sig_or_bom(sequences) + + if sig_encoding is not None: + prioritized_encodings.append(sig_encoding) + logger.log( + TRACE, + "Detected a SIG or BOM mark on first %i byte(s). Priority +1 given for %s.", + len(sig_payload), + sig_encoding, + ) + + prioritized_encodings.append("ascii") + + if "utf_8" not in prioritized_encodings: + prioritized_encodings.append("utf_8") + + for encoding_iana in prioritized_encodings + IANA_SUPPORTED_MB_FIRST: + if cp_isolation and encoding_iana not in cp_isolation: + continue + + if cp_exclusion and encoding_iana in cp_exclusion: + continue + + if encoding_iana in tested: + continue + + tested.add(encoding_iana) + + decoded_payload: str | None = None + bom_or_sig_available: bool = sig_encoding == encoding_iana + strip_sig_or_bom: bool = bom_or_sig_available and should_strip_sig_or_bom( + encoding_iana + ) + + if encoding_iana in {"utf_16", "utf_32"} and not bom_or_sig_available: + logger.log( + TRACE, + "Encoding %s won't be tested as-is because it require a BOM. Will try some sub-encoder LE/BE.", + encoding_iana, + ) + continue + if encoding_iana in {"utf_7"} and not bom_or_sig_available: + logger.log( + TRACE, + "Encoding %s won't be tested as-is because detection is unreliable without BOM/SIG.", + encoding_iana, + ) + continue + + # Skip encodings similar to ones that already soft-failed (high mess ratio). + # Checked BEFORE the expensive decode attempt. + if encoding_iana in soft_failure_skip: + logger.log( + TRACE, + "%s is deemed too similar to a code page that was already considered unsuited. Continuing!", + encoding_iana, + ) + continue + + # Skip encodings that were already fast-tracked from a similar successful encoding. + if encoding_iana in success_fast_tracked: + logger.log( + TRACE, + "Skipping %s: already fast-tracked from a similar successful encoding.", + encoding_iana, + ) + continue + + try: + is_multi_byte_decoder: bool = is_multi_byte_encoding(encoding_iana) + except (ModuleNotFoundError, ImportError): # Defensive: + logger.log( + TRACE, + "Encoding %s does not provide an IncrementalDecoder", + encoding_iana, + ) + continue + + # When we've already found a definitive match (chaos=0.0 with good coherence) + # after testing the prioritized encodings, skip encodings that target + # completely different language families. This avoids running expensive + # mess_ratio + coherence_ratio on clearly unrelated candidates (e.g., Cyrillic + # when the definitive match is Latin-based). + if definitive_match_found: + if not is_multi_byte_decoder: + enc_languages = set(encoding_languages(encoding_iana)) + else: + enc_languages = set(mb_encoding_languages(encoding_iana)) + if not enc_languages.intersection(definitive_target_languages): + logger.log( + TRACE, + "Skipping %s: definitive match already found, this encoding targets different languages (%s vs %s).", + encoding_iana, + enc_languages, + definitive_target_languages, + ) + continue + + # After the definitive match, cap the number of additional same-family + # single-byte encodings that pass chaos probing. This avoids testing the + # tail of rare, low-value same-family encodings (mac_iceland, cp860, etc.) + # that almost never change best() but each cost ~1-2ms of mess_ratio + coherence. + if ( + definitive_match_found + and not is_multi_byte_decoder + and post_definitive_sb_success_count >= POST_DEFINITIVE_SB_CAP + ): + logger.log( + TRACE, + "Skipping %s: already accumulated %d same-family results after definitive match (cap=%d).", + encoding_iana, + post_definitive_sb_success_count, + POST_DEFINITIVE_SB_CAP, + ) + continue + + # When a multibyte encoding with significant multibyte content has already + # passed chaos probing, skip all single-byte encodings. They will either fail + # chaos probing (wasting mess_ratio time) or produce inferior results. + if mb_definitive_match_found and not is_multi_byte_decoder: + logger.log( + TRACE, + "Skipping single-byte %s: multi-byte definitive match already found.", + encoding_iana, + ) + continue + + try: + if is_too_large_sequence and is_multi_byte_decoder is False: + str( + ( + sequences[: int(50e4)] + if strip_sig_or_bom is False + else sequences[len(sig_payload) : int(50e4)] + ), + encoding=encoding_iana, + ) + else: + decoded_payload = str( + ( + sequences + if strip_sig_or_bom is False + else sequences[len(sig_payload) :] + ), + encoding=encoding_iana, + ) + except (UnicodeDecodeError, LookupError) as e: + if not isinstance(e, LookupError): + logger.log( + TRACE, + "Code page %s does not fit given bytes sequence at ALL. %s", + encoding_iana, + str(e), + ) + tested_but_hard_failure.append(encoding_iana) + continue + + r_ = range( + 0 if not bom_or_sig_available else len(sig_payload), + length, + int(length / steps), + ) + + multi_byte_bonus: bool = ( + is_multi_byte_decoder + and decoded_payload is not None + and len(decoded_payload) < length + ) + + if multi_byte_bonus: + logger.log( + TRACE, + "Code page %s is a multi byte encoding table and it appear that at least one character " + "was encoded using n-bytes.", + encoding_iana, + ) + + # Payload-hash deduplication: if another encoding already decoded to the + # exact same string, reuse its mess_ratio and coherence results entirely. + # This is strictly more general than the old IANA_SUPPORTED_SIMILAR approach + # because it catches ALL identical decoding, not just pre-mapped ones. + if decoded_payload is not None and not is_multi_byte_decoder: + payload_hash: int = hash(decoded_payload) + cached = payload_result_cache.get(payload_hash) + if cached is not None: + cached_mess, cached_cd, cached_passed = cached + if cached_passed: + # The previous encoding with identical output passed chaos probing. + fast_match = CharsetMatch( + sequences, + encoding_iana, + cached_mess, + bom_or_sig_available, + cached_cd, + ( + decoded_payload + if ( + is_too_large_sequence is False + or encoding_iana + in [specified_encoding, "ascii", "utf_8"] + ) + else None + ), + preemptive_declaration=specified_encoding, + ) + results.append(fast_match) + success_fast_tracked.add(encoding_iana) + logger.log( + TRACE, + "%s fast-tracked (identical decoded payload to a prior encoding, chaos=%f %%).", + encoding_iana, + round(cached_mess * 100, ndigits=3), + ) + + if ( + encoding_iana in [specified_encoding, "ascii", "utf_8"] + and cached_mess < 0.1 + ): + if cached_mess == 0.0: + logger.debug( + "Encoding detection: %s is most likely the one.", + fast_match.encoding, + ) + if explain: + logger.removeHandler(explain_handler) + logger.setLevel(previous_logger_level) + return CharsetMatches([fast_match]) + early_stop_results.append(fast_match) + + if ( + len(early_stop_results) + and (specified_encoding is None or specified_encoding in tested) + and "ascii" in tested + and "utf_8" in tested + ): + probable_result: CharsetMatch = early_stop_results.best() # type: ignore[assignment] + logger.debug( + "Encoding detection: %s is most likely the one.", + probable_result.encoding, + ) + if explain: + logger.removeHandler(explain_handler) + logger.setLevel(previous_logger_level) + return CharsetMatches([probable_result]) + + continue + else: + # The previous encoding with identical output failed chaos probing. + tested_but_soft_failure.append(encoding_iana) + logger.log( + TRACE, + "%s fast-skipped (identical decoded payload to a prior encoding that failed chaos probing).", + encoding_iana, + ) + # Prepare fallbacks for special encodings even when skipped. + if enable_fallback and encoding_iana in [ + "ascii", + "utf_8", + specified_encoding, + "utf_16", + "utf_32", + ]: + fallback_entry = CharsetMatch( + sequences, + encoding_iana, + threshold, + bom_or_sig_available, + [], + decoded_payload, + preemptive_declaration=specified_encoding, + ) + if encoding_iana == specified_encoding: + fallback_specified = fallback_entry + elif encoding_iana == "ascii": + fallback_ascii = fallback_entry + else: + fallback_u8 = fallback_entry + continue + + max_chunk_gave_up: int = int(len(r_) / 4) + + max_chunk_gave_up = max(max_chunk_gave_up, 2) + early_stop_count: int = 0 + lazy_str_hard_failure = False + + md_chunks: list[str] = [] + md_ratios = [] + + try: + for chunk in cut_sequence_chunks( + sequences, + encoding_iana, + r_, + chunk_size, + bom_or_sig_available, + strip_sig_or_bom, + sig_payload, + is_multi_byte_decoder, + decoded_payload, + ): + md_chunks.append(chunk) + + md_ratios.append( + mess_ratio( + chunk, + threshold, + explain is True and 1 <= len(cp_isolation) <= 2, + ) + ) + + if md_ratios[-1] >= threshold: + early_stop_count += 1 + + if (early_stop_count >= max_chunk_gave_up) or ( + bom_or_sig_available and strip_sig_or_bom is False + ): + break + except ( + UnicodeDecodeError + ) as e: # Lazy str loading may have missed something there + logger.log( + TRACE, + "LazyStr Loading: After MD chunk decode, code page %s does not fit given bytes sequence at ALL. %s", + encoding_iana, + str(e), + ) + early_stop_count = max_chunk_gave_up + lazy_str_hard_failure = True + + # We might want to check the sequence again with the whole content + # Only if initial MD tests passes + if ( + not lazy_str_hard_failure + and is_too_large_sequence + and not is_multi_byte_decoder + ): + try: + sequences[int(50e3) :].decode(encoding_iana, errors="strict") + except UnicodeDecodeError as e: + logger.log( + TRACE, + "LazyStr Loading: After final lookup, code page %s does not fit given bytes sequence at ALL. %s", + encoding_iana, + str(e), + ) + tested_but_hard_failure.append(encoding_iana) + continue + + mean_mess_ratio: float = sum(md_ratios) / len(md_ratios) if md_ratios else 0.0 + if mean_mess_ratio >= threshold or early_stop_count >= max_chunk_gave_up: + tested_but_soft_failure.append(encoding_iana) + if encoding_iana in IANA_SUPPORTED_SIMILAR: + soft_failure_skip.update(IANA_SUPPORTED_SIMILAR[encoding_iana]) + # Cache this soft-failure so identical decoding from other encodings + # can be skipped immediately. + if decoded_payload is not None and not is_multi_byte_decoder: + payload_result_cache.setdefault( + hash(decoded_payload), (mean_mess_ratio, [], False) + ) + logger.log( + TRACE, + "%s was excluded because of initial chaos probing. Gave up %i time(s). " + "Computed mean chaos is %f %%.", + encoding_iana, + early_stop_count, + round(mean_mess_ratio * 100, ndigits=3), + ) + # Preparing those fallbacks in case we got nothing. + if ( + enable_fallback + and encoding_iana + in ["ascii", "utf_8", specified_encoding, "utf_16", "utf_32"] + and not lazy_str_hard_failure + ): + fallback_entry = CharsetMatch( + sequences, + encoding_iana, + threshold, + bom_or_sig_available, + [], + decoded_payload, + preemptive_declaration=specified_encoding, + ) + if encoding_iana == specified_encoding: + fallback_specified = fallback_entry + elif encoding_iana == "ascii": + fallback_ascii = fallback_entry + else: + fallback_u8 = fallback_entry + continue + + logger.log( + TRACE, + "%s passed initial chaos probing. Mean measured chaos is %f %%", + encoding_iana, + round(mean_mess_ratio * 100, ndigits=3), + ) + + if not is_multi_byte_decoder: + target_languages: list[str] = encoding_languages(encoding_iana) + else: + target_languages = mb_encoding_languages(encoding_iana) + + if target_languages: + logger.log( + TRACE, + "{} should target any language(s) of {}".format( + encoding_iana, str(target_languages) + ), + ) + + cd_ratios = [] + + # Run coherence detection on all chunks. We previously tried limiting to + # 1-2 chunks for post-definitive encodings to save time, but this caused + # coverage regressions by producing unrepresentative coherence scores. + # The SB cap and language-family skip optimizations provide sufficient + # speedup without sacrificing coherence accuracy. + if encoding_iana != "ascii": + # We shall skip the CD when its about ASCII + # Most of the time its not relevant to run "language-detection" on it. + for chunk in md_chunks: + chunk_languages = coherence_ratio( + chunk, + language_threshold, + ",".join(target_languages) if target_languages else None, + ) + + cd_ratios.append(chunk_languages) + cd_ratios_merged = merge_coherence_ratios(cd_ratios) + else: + cd_ratios_merged = merge_coherence_ratios(cd_ratios) + + if cd_ratios_merged: + logger.log( + TRACE, + "We detected language {} using {}".format( + cd_ratios_merged, encoding_iana + ), + ) + + current_match = CharsetMatch( + sequences, + encoding_iana, + mean_mess_ratio, + bom_or_sig_available, + cd_ratios_merged, + ( + decoded_payload + if ( + is_too_large_sequence is False + or encoding_iana in [specified_encoding, "ascii", "utf_8"] + ) + else None + ), + preemptive_declaration=specified_encoding, + ) + + results.append(current_match) + + # Cache the successful result for payload-hash deduplication. + if decoded_payload is not None and not is_multi_byte_decoder: + payload_result_cache.setdefault( + hash(decoded_payload), + (mean_mess_ratio, cd_ratios_merged, True), + ) + + # Count post-definitive same-family SB successes for the early termination cap. + # Only count low-mess encodings (< 2%) toward the cap. High-mess encodings are + # marginal results that shouldn't prevent better-quality candidates from being + # tested. For example, iso8859_4 (mess=0%) should not be skipped just because + # 7 high-mess Latin encodings (cp1252 at 8%, etc.) were tried first. + if ( + definitive_match_found + and not is_multi_byte_decoder + and mean_mess_ratio < 0.02 + ): + post_definitive_sb_success_count += 1 + + if ( + encoding_iana in [specified_encoding, "ascii", "utf_8"] + and mean_mess_ratio < 0.1 + ): + # If md says nothing to worry about, then... stop immediately! + if mean_mess_ratio == 0.0: + logger.debug( + "Encoding detection: %s is most likely the one.", + current_match.encoding, + ) + if explain: # Defensive: ensure exit path clean handler + logger.removeHandler(explain_handler) + logger.setLevel(previous_logger_level) + return CharsetMatches([current_match]) + + early_stop_results.append(current_match) + + if ( + len(early_stop_results) + and (specified_encoding is None or specified_encoding in tested) + and "ascii" in tested + and "utf_8" in tested + ): + probable_result = early_stop_results.best() # type: ignore[assignment] + logger.debug( + "Encoding detection: %s is most likely the one.", + probable_result.encoding, # type: ignore[union-attr] + ) + if explain: # Defensive: ensure exit path clean handler + logger.removeHandler(explain_handler) + logger.setLevel(previous_logger_level) + + return CharsetMatches([probable_result]) + + # Once we find a result with good coherence (>= 0.5) after testing the + # prioritized encodings (ascii, utf_8), activate "definitive mode": skip + # encodings that target completely different language families. This avoids + # running expensive mess_ratio + coherence_ratio on clearly unrelated + # candidates (e.g., Cyrillic encodings when the match is Latin-based). + # We require coherence >= 0.5 to avoid false positives (e.g., cp1251 decoding + # Hebrew text with 0.0 chaos but wrong language detection at coherence 0.33). + if not definitive_match_found and not is_multi_byte_decoder: + best_coherence = ( + max((v for _, v in cd_ratios_merged), default=0.0) + if cd_ratios_merged + else 0.0 + ) + if best_coherence >= 0.5 and "ascii" in tested and "utf_8" in tested: + definitive_match_found = True + definitive_target_languages.update(target_languages) + logger.log( + TRACE, + "Definitive match found: %s (chaos=%.3f, coherence=%.2f). Encodings targeting different language families will be skipped.", + encoding_iana, + mean_mess_ratio, + best_coherence, + ) + + # When a non-UTF multibyte encoding passes chaos probing with significant + # multibyte content (decoded < 98% of raw), activate mb_definitive_match. + # This skips all remaining single-byte encodings which would either soft-fail + # (running expensive mess_ratio for nothing) or produce inferior results. + if ( + not mb_definitive_match_found + and is_multi_byte_decoder + and multi_byte_bonus + and decoded_payload is not None + and len(decoded_payload) < length * 0.98 + and encoding_iana + not in { + "utf_8", + "utf_8_sig", + "utf_16", + "utf_16_be", + "utf_16_le", + "utf_32", + "utf_32_be", + "utf_32_le", + "utf_7", + } + and "ascii" in tested + and "utf_8" in tested + ): + mb_definitive_match_found = True + logger.log( + TRACE, + "Multi-byte definitive match: %s (chaos=%.3f, decoded=%d/%d=%.1f%%). Single-byte encodings will be skipped.", + encoding_iana, + mean_mess_ratio, + len(decoded_payload), + length, + len(decoded_payload) / length * 100, + ) + + if encoding_iana == sig_encoding: + logger.debug( + "Encoding detection: %s is most likely the one as we detected a BOM or SIG within " + "the beginning of the sequence.", + encoding_iana, + ) + if explain: # Defensive: ensure exit path clean handler + logger.removeHandler(explain_handler) + logger.setLevel(previous_logger_level) + return CharsetMatches([results[encoding_iana]]) + + if len(results) == 0: + if fallback_u8 or fallback_ascii or fallback_specified: + logger.log( + TRACE, + "Nothing got out of the detection process. Using ASCII/UTF-8/Specified fallback.", + ) + + if fallback_specified: + logger.debug( + "Encoding detection: %s will be used as a fallback match", + fallback_specified.encoding, + ) + results.append(fallback_specified) + elif ( + (fallback_u8 and fallback_ascii is None) + or ( + fallback_u8 + and fallback_ascii + and fallback_u8.fingerprint != fallback_ascii.fingerprint + ) + or (fallback_u8 is not None) + ): + logger.debug("Encoding detection: utf_8 will be used as a fallback match") + results.append(fallback_u8) + elif fallback_ascii: + logger.debug("Encoding detection: ascii will be used as a fallback match") + results.append(fallback_ascii) + + if results: + logger.debug( + "Encoding detection: Found %s as plausible (best-candidate) for content. With %i alternatives.", + results.best().encoding, # type: ignore + len(results) - 1, + ) + else: + logger.debug("Encoding detection: Unable to determine any suitable charset.") + + if explain: + logger.removeHandler(explain_handler) + logger.setLevel(previous_logger_level) + + return results + + +def from_fp( + fp: BinaryIO, + steps: int = 5, + chunk_size: int = 512, + threshold: float = 0.20, + cp_isolation: list[str] | None = None, + cp_exclusion: list[str] | None = None, + preemptive_behaviour: bool = True, + explain: bool = False, + language_threshold: float = 0.1, + enable_fallback: bool = True, +) -> CharsetMatches: + """ + Same thing than the function from_bytes but using a file pointer that is already ready. + Will not close the file pointer. + """ + return from_bytes( + fp.read(), + steps, + chunk_size, + threshold, + cp_isolation, + cp_exclusion, + preemptive_behaviour, + explain, + language_threshold, + enable_fallback, + ) + + +def from_path( + path: str | bytes | PathLike, # type: ignore[type-arg] + steps: int = 5, + chunk_size: int = 512, + threshold: float = 0.20, + cp_isolation: list[str] | None = None, + cp_exclusion: list[str] | None = None, + preemptive_behaviour: bool = True, + explain: bool = False, + language_threshold: float = 0.1, + enable_fallback: bool = True, +) -> CharsetMatches: + """ + Same thing than the function from_bytes but with one extra step. Opening and reading given file path in binary mode. + Can raise IOError. + """ + with open(path, "rb") as fp: + return from_fp( + fp, + steps, + chunk_size, + threshold, + cp_isolation, + cp_exclusion, + preemptive_behaviour, + explain, + language_threshold, + enable_fallback, + ) + + +def is_binary( + fp_or_path_or_payload: PathLike | str | BinaryIO | bytes, # type: ignore[type-arg] + steps: int = 5, + chunk_size: int = 512, + threshold: float = 0.20, + cp_isolation: list[str] | None = None, + cp_exclusion: list[str] | None = None, + preemptive_behaviour: bool = True, + explain: bool = False, + language_threshold: float = 0.1, + enable_fallback: bool = False, +) -> bool: + """ + Detect if the given input (file, bytes, or path) points to a binary file. aka. not a string. + Based on the same main heuristic algorithms and default kwargs at the sole exception that fallbacks match + are disabled to be stricter around ASCII-compatible but unlikely to be a string. + """ + if isinstance(fp_or_path_or_payload, (str, PathLike)): + guesses = from_path( + fp_or_path_or_payload, + steps=steps, + chunk_size=chunk_size, + threshold=threshold, + cp_isolation=cp_isolation, + cp_exclusion=cp_exclusion, + preemptive_behaviour=preemptive_behaviour, + explain=explain, + language_threshold=language_threshold, + enable_fallback=enable_fallback, + ) + elif isinstance( + fp_or_path_or_payload, + ( + bytes, + bytearray, + ), + ): + guesses = from_bytes( + fp_or_path_or_payload, + steps=steps, + chunk_size=chunk_size, + threshold=threshold, + cp_isolation=cp_isolation, + cp_exclusion=cp_exclusion, + preemptive_behaviour=preemptive_behaviour, + explain=explain, + language_threshold=language_threshold, + enable_fallback=enable_fallback, + ) + else: + guesses = from_fp( + fp_or_path_or_payload, + steps=steps, + chunk_size=chunk_size, + threshold=threshold, + cp_isolation=cp_isolation, + cp_exclusion=cp_exclusion, + preemptive_behaviour=preemptive_behaviour, + explain=explain, + language_threshold=language_threshold, + enable_fallback=enable_fallback, + ) + + return not guesses diff --git a/charset_normalizer/cd.cpython-312-x86_64-linux-gnu.so b/charset_normalizer/cd.cpython-312-x86_64-linux-gnu.so new file mode 100644 index 0000000000000000000000000000000000000000..cbb712352fc574c36b9cd639aae8cef358e45c06 Binary files /dev/null and b/charset_normalizer/cd.cpython-312-x86_64-linux-gnu.so differ diff --git a/charset_normalizer/cd.py b/charset_normalizer/cd.py new file mode 100644 index 0000000000000000000000000000000000000000..9545d35d1ec3f0c170dc6243325955db3856033b --- /dev/null +++ b/charset_normalizer/cd.py @@ -0,0 +1,454 @@ +from __future__ import annotations + +import importlib +from codecs import IncrementalDecoder +from collections import Counter +from functools import lru_cache +from typing import Counter as TypeCounter + +from .constant import ( + FREQUENCIES, + KO_NAMES, + LANGUAGE_SUPPORTED_COUNT, + TOO_SMALL_SEQUENCE, + ZH_NAMES, + _FREQUENCIES_SET, + _FREQUENCIES_RANK, +) +from .md import is_suspiciously_successive_range +from .models import CoherenceMatches +from .utils import ( + is_accentuated, + is_latin, + is_multi_byte_encoding, + is_unicode_range_secondary, + unicode_range, +) + + +def encoding_unicode_range(iana_name: str) -> list[str]: + """ + Return associated unicode ranges in a single byte code page. + """ + if is_multi_byte_encoding(iana_name): + raise OSError( # Defensive: + "Function not supported on multi-byte code page" + ) + + decoder = importlib.import_module(f"encodings.{iana_name}").IncrementalDecoder + + p: IncrementalDecoder = decoder(errors="ignore") + seen_ranges: dict[str, int] = {} + character_count: int = 0 + + for i in range(0x40, 0xFF): + chunk: str = p.decode(bytes([i])) + + if chunk: + character_range: str | None = unicode_range(chunk) + + if character_range is None: + continue + + if is_unicode_range_secondary(character_range) is False: + if character_range not in seen_ranges: + seen_ranges[character_range] = 0 + seen_ranges[character_range] += 1 + character_count += 1 + + return sorted( + [ + character_range + for character_range in seen_ranges + if seen_ranges[character_range] / character_count >= 0.15 + ] + ) + + +def unicode_range_languages(primary_range: str) -> list[str]: + """ + Return inferred languages used with a unicode range. + """ + languages: list[str] = [] + + for language, characters in FREQUENCIES.items(): + for character in characters: + if unicode_range(character) == primary_range: + languages.append(language) + break + + return languages + + +@lru_cache() +def encoding_languages(iana_name: str) -> list[str]: + """ + Single-byte encoding language association. Some code page are heavily linked to particular language(s). + This function does the correspondence. + """ + unicode_ranges: list[str] = encoding_unicode_range(iana_name) + primary_range: str | None = None + + for specified_range in unicode_ranges: + if "Latin" not in specified_range: + primary_range = specified_range + break + + if primary_range is None: + return ["Latin Based"] + + return unicode_range_languages(primary_range) + + +@lru_cache() +def mb_encoding_languages(iana_name: str) -> list[str]: + """ + Multi-byte encoding language association. Some code page are heavily linked to particular language(s). + This function does the correspondence. + """ + if ( + iana_name.startswith("shift_") + or iana_name.startswith("iso2022_jp") + or iana_name.startswith("euc_j") + or iana_name == "cp932" + ): + return ["Japanese"] + if iana_name.startswith("gb") or iana_name in ZH_NAMES: + return ["Chinese"] + if iana_name.startswith("iso2022_kr") or iana_name in KO_NAMES: + return ["Korean"] + + return [] + + +@lru_cache(maxsize=LANGUAGE_SUPPORTED_COUNT) +def get_target_features(language: str) -> tuple[bool, bool]: + """ + Determine main aspects from a supported language if it contains accents and if is pure Latin. + """ + target_have_accents: bool = False + target_pure_latin: bool = True + + for character in FREQUENCIES[language]: + if not target_have_accents and is_accentuated(character): + target_have_accents = True + if target_pure_latin and is_latin(character) is False: + target_pure_latin = False + + return target_have_accents, target_pure_latin + + +def alphabet_languages( + characters: list[str], ignore_non_latin: bool = False +) -> list[str]: + """ + Return associated languages associated to given characters. + """ + languages: list[tuple[str, float]] = [] + + characters_set: frozenset[str] = frozenset(characters) + source_have_accents = any(is_accentuated(character) for character in characters) + + for language, language_characters in FREQUENCIES.items(): + target_have_accents, target_pure_latin = get_target_features(language) + + if ignore_non_latin and target_pure_latin is False: + continue + + if target_have_accents is False and source_have_accents: + continue + + character_count: int = len(language_characters) + + character_match_count: int = len(_FREQUENCIES_SET[language] & characters_set) + + ratio: float = character_match_count / character_count + + if ratio >= 0.2: + languages.append((language, ratio)) + + languages = sorted(languages, key=lambda x: x[1], reverse=True) + + return [compatible_language[0] for compatible_language in languages] + + +def characters_popularity_compare( + language: str, ordered_characters: list[str] +) -> float: + """ + Determine if a ordered characters list (by occurrence from most appearance to rarest) match a particular language. + The result is a ratio between 0. (absolutely no correspondence) and 1. (near perfect fit). + Beware that is function is not strict on the match in order to ease the detection. (Meaning close match is 1.) + """ + if language not in FREQUENCIES: + raise ValueError(f"{language} not available") # Defensive: + + character_approved_count: int = 0 + frequencies_language_set: frozenset[str] = _FREQUENCIES_SET[language] + lang_rank: dict[str, int] = _FREQUENCIES_RANK[language] + + ordered_characters_count: int = len(ordered_characters) + target_language_characters_count: int = len(FREQUENCIES[language]) + + large_alphabet: bool = target_language_characters_count > 26 + + expected_projection_ratio: float = ( + target_language_characters_count / ordered_characters_count + ) + + # Pre-built rank dict for ordered_characters (avoids repeated list slicing). + ordered_rank: dict[str, int] = { + char: rank for rank, char in enumerate(ordered_characters) + } + + # Pre-compute characters common to both orderings. + # Avoids repeated `c in ordered_rank` dict lookups in the inner counts. + common_chars: list[tuple[int, int]] = [ + (lr, ordered_rank[c]) for c, lr in lang_rank.items() if c in ordered_rank + ] + + # Pre-extract lr and orr arrays for faster iteration in the inner loop. + # Plain integer loops with local arrays are much faster under mypyc than + # generator expression sums over a list of tuples. + common_count: int = len(common_chars) + common_lr: list[int] = [p[0] for p in common_chars] + common_orr: list[int] = [p[1] for p in common_chars] + + for character, character_rank in zip( + ordered_characters, range(0, ordered_characters_count) + ): + if character not in frequencies_language_set: + continue + + character_rank_in_language: int = lang_rank[character] + character_rank_projection: int = int(character_rank * expected_projection_ratio) + + if ( + large_alphabet is False + and abs(character_rank_projection - character_rank_in_language) > 4 + ): + continue + + if ( + large_alphabet is True + and abs(character_rank_projection - character_rank_in_language) + < target_language_characters_count / 3 + ): + character_approved_count += 1 + continue + + # Count how many characters appear "before" in both orderings, + # and how many appear "at or after" in both orderings. + # Single pass over pre-extracted arrays — much faster under mypyc + # than two generator expression sums. + before_match_count: int = 0 + after_match_count: int = 0 + for i in range(common_count): + lr_i: int = common_lr[i] + orr_i: int = common_orr[i] + if lr_i < character_rank_in_language: + if orr_i < character_rank: + before_match_count += 1 + else: + if orr_i >= character_rank: + after_match_count += 1 + + after_len: int = target_language_characters_count - character_rank_in_language + + if character_rank_in_language == 0 and before_match_count <= 4: + character_approved_count += 1 + continue + + if after_len == 0 and after_match_count <= 4: + character_approved_count += 1 + continue + + if ( + character_rank_in_language > 0 + and before_match_count / character_rank_in_language >= 0.4 + ) or (after_len > 0 and after_match_count / after_len >= 0.4): + character_approved_count += 1 + continue + + return character_approved_count / len(ordered_characters) + + +def alpha_unicode_split(decoded_sequence: str) -> list[str]: + """ + Given a decoded text sequence, return a list of str. Unicode range / alphabet separation. + Ex. a text containing English/Latin with a bit a Hebrew will return two items in the resulting list; + One containing the latin letters and the other hebrew. + """ + layers: dict[str, list[str]] = {} + + # Fast path: track single-layer key to skip dict iteration for single-script text. + single_layer_key: str | None = None + multi_layer: bool = False + + # Cache the last character_range and its resolved layer to avoid repeated + # is_suspiciously_successive_range calls for consecutive same-range chars. + prev_character_range: str | None = None + prev_layer_target: str | None = None + + for character in decoded_sequence: + if character.isalpha() is False: + continue + + # ASCII fast-path: a-z and A-Z are always "Basic Latin". + # Avoids unicode_range() function call overhead for the most common case. + character_ord: int = ord(character) + if character_ord < 128: + character_range: str | None = "Basic Latin" + else: + character_range = unicode_range(character) + + if character_range is None: + continue + + # Fast path: same range as previous character → reuse cached layer target. + if character_range == prev_character_range: + if prev_layer_target is not None: + layers[prev_layer_target].append(character) + continue + + layer_target_range: str | None = None + + if multi_layer: + for discovered_range in layers: + if ( + is_suspiciously_successive_range(discovered_range, character_range) + is False + ): + layer_target_range = discovered_range + break + elif single_layer_key is not None: + if ( + is_suspiciously_successive_range(single_layer_key, character_range) + is False + ): + layer_target_range = single_layer_key + + if layer_target_range is None: + layer_target_range = character_range + + if layer_target_range not in layers: + layers[layer_target_range] = [] + if single_layer_key is None: + single_layer_key = layer_target_range + else: + multi_layer = True + + layers[layer_target_range].append(character) + + # Cache for next iteration + prev_character_range = character_range + prev_layer_target = layer_target_range + + return ["".join(chars).lower() for chars in layers.values()] + + +def merge_coherence_ratios(results: list[CoherenceMatches]) -> CoherenceMatches: + """ + This function merge results previously given by the function coherence_ratio. + The return type is the same as coherence_ratio. + """ + per_language_ratios: dict[str, list[float]] = {} + for result in results: + for sub_result in result: + language, ratio = sub_result + if language not in per_language_ratios: + per_language_ratios[language] = [ratio] + continue + per_language_ratios[language].append(ratio) + + merge = [ + ( + language, + round( + sum(per_language_ratios[language]) / len(per_language_ratios[language]), + 4, + ), + ) + for language in per_language_ratios + ] + + return sorted(merge, key=lambda x: x[1], reverse=True) + + +def filter_alt_coherence_matches(results: CoherenceMatches) -> CoherenceMatches: + """ + We shall NOT return "English—" in CoherenceMatches because it is an alternative + of "English". This function only keeps the best match and remove the em-dash in it. + """ + index_results: dict[str, list[float]] = dict() + + for result in results: + language, ratio = result + no_em_name: str = language.replace("—", "") + + if no_em_name not in index_results: + index_results[no_em_name] = [] + + index_results[no_em_name].append(ratio) + + if any(len(index_results[e]) > 1 for e in index_results): + filtered_results: CoherenceMatches = [] + + for language in index_results: + filtered_results.append((language, max(index_results[language]))) + + return filtered_results + + return results + + +@lru_cache(maxsize=2048) +def coherence_ratio( + decoded_sequence: str, threshold: float = 0.1, lg_inclusion: str | None = None +) -> CoherenceMatches: + """ + Detect ANY language that can be identified in given sequence. The sequence will be analysed by layers. + A layer = Character extraction by alphabets/ranges. + """ + + results: list[tuple[str, float]] = [] + ignore_non_latin: bool = False + + sufficient_match_count: int = 0 + + lg_inclusion_list = lg_inclusion.split(",") if lg_inclusion is not None else [] + if "Latin Based" in lg_inclusion_list: + ignore_non_latin = True + lg_inclusion_list.remove("Latin Based") + + for layer in alpha_unicode_split(decoded_sequence): + sequence_frequencies: TypeCounter[str] = Counter(layer) + most_common = sequence_frequencies.most_common() + + character_count: int = len(layer) + + if character_count <= TOO_SMALL_SEQUENCE: + continue + + popular_character_ordered: list[str] = [c for c, o in most_common] + + for language in lg_inclusion_list or alphabet_languages( + popular_character_ordered, ignore_non_latin + ): + ratio: float = characters_popularity_compare( + language, popular_character_ordered + ) + + if ratio < threshold: + continue + elif ratio >= 0.8: + sufficient_match_count += 1 + + results.append((language, round(ratio, 4))) + + if sufficient_match_count >= 3: + break + + return sorted( + filter_alt_coherence_matches(results), key=lambda x: x[1], reverse=True + ) diff --git a/charset_normalizer/constant.py b/charset_normalizer/constant.py new file mode 100644 index 0000000000000000000000000000000000000000..6ed7795675050fb80ebb33dbe503b323a3a1912b --- /dev/null +++ b/charset_normalizer/constant.py @@ -0,0 +1,2050 @@ +from __future__ import annotations + +from codecs import BOM_UTF8, BOM_UTF16_BE, BOM_UTF16_LE, BOM_UTF32_BE, BOM_UTF32_LE +from encodings.aliases import aliases +from re import IGNORECASE +from re import compile as re_compile + +# Contain for each eligible encoding a list of/item bytes SIG/BOM +ENCODING_MARKS: dict[str, bytes | list[bytes]] = { + "utf_8": BOM_UTF8, + "utf_7": [ + b"\x2b\x2f\x76\x38", + b"\x2b\x2f\x76\x39", + b"\x2b\x2f\x76\x2b", + b"\x2b\x2f\x76\x2f", + b"\x2b\x2f\x76\x38\x2d", + ], + "gb18030": b"\x84\x31\x95\x33", + "utf_32": [BOM_UTF32_BE, BOM_UTF32_LE], + "utf_16": [BOM_UTF16_BE, BOM_UTF16_LE], +} + +TOO_SMALL_SEQUENCE: int = 32 +TOO_BIG_SEQUENCE: int = int(10e6) + +UTF8_MAXIMAL_ALLOCATION: int = 1_112_064 + +# Up-to-date Unicode ucd/17.0.0 +UNICODE_RANGES_COMBINED: dict[str, range] = { + "Control character": range(32), + "Basic Latin": range(32, 128), + "Latin-1 Supplement": range(128, 256), + "Latin Extended-A": range(256, 384), + "Latin Extended-B": range(384, 592), + "IPA Extensions": range(592, 688), + "Spacing Modifier Letters": range(688, 768), + "Combining Diacritical Marks": range(768, 880), + "Greek and Coptic": range(880, 1024), + "Cyrillic": range(1024, 1280), + "Cyrillic Supplement": range(1280, 1328), + "Armenian": range(1328, 1424), + "Hebrew": range(1424, 1536), + "Arabic": range(1536, 1792), + "Syriac": range(1792, 1872), + "Arabic Supplement": range(1872, 1920), + "Thaana": range(1920, 1984), + "NKo": range(1984, 2048), + "Samaritan": range(2048, 2112), + "Mandaic": range(2112, 2144), + "Syriac Supplement": range(2144, 2160), + "Arabic Extended-B": range(2160, 2208), + "Arabic Extended-A": range(2208, 2304), + "Devanagari": range(2304, 2432), + "Bengali": range(2432, 2560), + "Gurmukhi": range(2560, 2688), + "Gujarati": range(2688, 2816), + "Oriya": range(2816, 2944), + "Tamil": range(2944, 3072), + "Telugu": range(3072, 3200), + "Kannada": range(3200, 3328), + "Malayalam": range(3328, 3456), + "Sinhala": range(3456, 3584), + "Thai": range(3584, 3712), + "Lao": range(3712, 3840), + "Tibetan": range(3840, 4096), + "Myanmar": range(4096, 4256), + "Georgian": range(4256, 4352), + "Hangul Jamo": range(4352, 4608), + "Ethiopic": range(4608, 4992), + "Ethiopic Supplement": range(4992, 5024), + "Cherokee": range(5024, 5120), + "Unified Canadian Aboriginal Syllabics": range(5120, 5760), + "Ogham": range(5760, 5792), + "Runic": range(5792, 5888), + "Tagalog": range(5888, 5920), + "Hanunoo": range(5920, 5952), + "Buhid": range(5952, 5984), + "Tagbanwa": range(5984, 6016), + "Khmer": range(6016, 6144), + "Mongolian": range(6144, 6320), + "Unified Canadian Aboriginal Syllabics Extended": range(6320, 6400), + "Limbu": range(6400, 6480), + "Tai Le": range(6480, 6528), + "New Tai Lue": range(6528, 6624), + "Khmer Symbols": range(6624, 6656), + "Buginese": range(6656, 6688), + "Tai Tham": range(6688, 6832), + "Combining Diacritical Marks Extended": range(6832, 6912), + "Balinese": range(6912, 7040), + "Sundanese": range(7040, 7104), + "Batak": range(7104, 7168), + "Lepcha": range(7168, 7248), + "Ol Chiki": range(7248, 7296), + "Cyrillic Extended-C": range(7296, 7312), + "Georgian Extended": range(7312, 7360), + "Sundanese Supplement": range(7360, 7376), + "Vedic Extensions": range(7376, 7424), + "Phonetic Extensions": range(7424, 7552), + "Phonetic Extensions Supplement": range(7552, 7616), + "Combining Diacritical Marks Supplement": range(7616, 7680), + "Latin Extended Additional": range(7680, 7936), + "Greek Extended": range(7936, 8192), + "General Punctuation": range(8192, 8304), + "Superscripts and Subscripts": range(8304, 8352), + "Currency Symbols": range(8352, 8400), + "Combining Diacritical Marks for Symbols": range(8400, 8448), + "Letterlike Symbols": range(8448, 8528), + "Number Forms": range(8528, 8592), + "Arrows": range(8592, 8704), + "Mathematical Operators": range(8704, 8960), + "Miscellaneous Technical": range(8960, 9216), + "Control Pictures": range(9216, 9280), + "Optical Character Recognition": range(9280, 9312), + "Enclosed Alphanumerics": range(9312, 9472), + "Box Drawing": range(9472, 9600), + "Block Elements": range(9600, 9632), + "Geometric Shapes": range(9632, 9728), + "Miscellaneous Symbols": range(9728, 9984), + "Dingbats": range(9984, 10176), + "Miscellaneous Mathematical Symbols-A": range(10176, 10224), + "Supplemental Arrows-A": range(10224, 10240), + "Braille Patterns": range(10240, 10496), + "Supplemental Arrows-B": range(10496, 10624), + "Miscellaneous Mathematical Symbols-B": range(10624, 10752), + "Supplemental Mathematical Operators": range(10752, 11008), + "Miscellaneous Symbols and Arrows": range(11008, 11264), + "Glagolitic": range(11264, 11360), + "Latin Extended-C": range(11360, 11392), + "Coptic": range(11392, 11520), + "Georgian Supplement": range(11520, 11568), + "Tifinagh": range(11568, 11648), + "Ethiopic Extended": range(11648, 11744), + "Cyrillic Extended-A": range(11744, 11776), + "Supplemental Punctuation": range(11776, 11904), + "CJK Radicals Supplement": range(11904, 12032), + "Kangxi Radicals": range(12032, 12256), + "Ideographic Description Characters": range(12272, 12288), + "CJK Symbols and Punctuation": range(12288, 12352), + "Hiragana": range(12352, 12448), + "Katakana": range(12448, 12544), + "Bopomofo": range(12544, 12592), + "Hangul Compatibility Jamo": range(12592, 12688), + "Kanbun": range(12688, 12704), + "Bopomofo Extended": range(12704, 12736), + "CJK Strokes": range(12736, 12784), + "Katakana Phonetic Extensions": range(12784, 12800), + "Enclosed CJK Letters and Months": range(12800, 13056), + "CJK Compatibility": range(13056, 13312), + "CJK Unified Ideographs Extension A": range(13312, 19904), + "Yijing Hexagram Symbols": range(19904, 19968), + "CJK Unified Ideographs": range(19968, 40960), + "Yi Syllables": range(40960, 42128), + "Yi Radicals": range(42128, 42192), + "Lisu": range(42192, 42240), + "Vai": range(42240, 42560), + "Cyrillic Extended-B": range(42560, 42656), + "Bamum": range(42656, 42752), + "Modifier Tone Letters": range(42752, 42784), + "Latin Extended-D": range(42784, 43008), + "Syloti Nagri": range(43008, 43056), + "Common Indic Number Forms": range(43056, 43072), + "Phags-pa": range(43072, 43136), + "Saurashtra": range(43136, 43232), + "Devanagari Extended": range(43232, 43264), + "Kayah Li": range(43264, 43312), + "Rejang": range(43312, 43360), + "Hangul Jamo Extended-A": range(43360, 43392), + "Javanese": range(43392, 43488), + "Myanmar Extended-B": range(43488, 43520), + "Cham": range(43520, 43616), + "Myanmar Extended-A": range(43616, 43648), + "Tai Viet": range(43648, 43744), + "Meetei Mayek Extensions": range(43744, 43776), + "Ethiopic Extended-A": range(43776, 43824), + "Latin Extended-E": range(43824, 43888), + "Cherokee Supplement": range(43888, 43968), + "Meetei Mayek": range(43968, 44032), + "Hangul Syllables": range(44032, 55216), + "Hangul Jamo Extended-B": range(55216, 55296), + "High Surrogates": range(55296, 56192), + "High Private Use Surrogates": range(56192, 56320), + "Low Surrogates": range(56320, 57344), + "Private Use Area": range(57344, 63744), + "CJK Compatibility Ideographs": range(63744, 64256), + "Alphabetic Presentation Forms": range(64256, 64336), + "Arabic Presentation Forms-A": range(64336, 65024), + "Variation Selectors": range(65024, 65040), + "Vertical Forms": range(65040, 65056), + "Combining Half Marks": range(65056, 65072), + "CJK Compatibility Forms": range(65072, 65104), + "Small Form Variants": range(65104, 65136), + "Arabic Presentation Forms-B": range(65136, 65280), + "Halfwidth and Fullwidth Forms": range(65280, 65520), + "Specials": range(65520, 65536), + "Linear B Syllabary": range(65536, 65664), + "Linear B Ideograms": range(65664, 65792), + "Aegean Numbers": range(65792, 65856), + "Ancient Greek Numbers": range(65856, 65936), + "Ancient Symbols": range(65936, 66000), + "Phaistos Disc": range(66000, 66048), + "Lycian": range(66176, 66208), + "Carian": range(66208, 66272), + "Coptic Epact Numbers": range(66272, 66304), + "Old Italic": range(66304, 66352), + "Gothic": range(66352, 66384), + "Old Permic": range(66384, 66432), + "Ugaritic": range(66432, 66464), + "Old Persian": range(66464, 66528), + "Deseret": range(66560, 66640), + "Shavian": range(66640, 66688), + "Osmanya": range(66688, 66736), + "Osage": range(66736, 66816), + "Elbasan": range(66816, 66864), + "Caucasian Albanian": range(66864, 66928), + "Vithkuqi": range(66928, 67008), + "Todhri": range(67008, 67072), + "Linear A": range(67072, 67456), + "Latin Extended-F": range(67456, 67520), + "Cypriot Syllabary": range(67584, 67648), + "Imperial Aramaic": range(67648, 67680), + "Palmyrene": range(67680, 67712), + "Nabataean": range(67712, 67760), + "Hatran": range(67808, 67840), + "Phoenician": range(67840, 67872), + "Lydian": range(67872, 67904), + "Sidetic": range(67904, 67936), + "Meroitic Hieroglyphs": range(67968, 68000), + "Meroitic Cursive": range(68000, 68096), + "Kharoshthi": range(68096, 68192), + "Old South Arabian": range(68192, 68224), + "Old North Arabian": range(68224, 68256), + "Manichaean": range(68288, 68352), + "Avestan": range(68352, 68416), + "Inscriptional Parthian": range(68416, 68448), + "Inscriptional Pahlavi": range(68448, 68480), + "Psalter Pahlavi": range(68480, 68528), + "Old Turkic": range(68608, 68688), + "Old Hungarian": range(68736, 68864), + "Hanifi Rohingya": range(68864, 68928), + "Garay": range(68928, 69008), + "Rumi Numeral Symbols": range(69216, 69248), + "Yezidi": range(69248, 69312), + "Arabic Extended-C": range(69312, 69376), + "Old Sogdian": range(69376, 69424), + "Sogdian": range(69424, 69488), + "Old Uyghur": range(69488, 69552), + "Chorasmian": range(69552, 69600), + "Elymaic": range(69600, 69632), + "Brahmi": range(69632, 69760), + "Kaithi": range(69760, 69840), + "Sora Sompeng": range(69840, 69888), + "Chakma": range(69888, 69968), + "Mahajani": range(69968, 70016), + "Sharada": range(70016, 70112), + "Sinhala Archaic Numbers": range(70112, 70144), + "Khojki": range(70144, 70224), + "Multani": range(70272, 70320), + "Khudawadi": range(70320, 70400), + "Grantha": range(70400, 70528), + "Tulu-Tigalari": range(70528, 70656), + "Newa": range(70656, 70784), + "Tirhuta": range(70784, 70880), + "Siddham": range(71040, 71168), + "Modi": range(71168, 71264), + "Mongolian Supplement": range(71264, 71296), + "Takri": range(71296, 71376), + "Myanmar Extended-C": range(71376, 71424), + "Ahom": range(71424, 71504), + "Dogra": range(71680, 71760), + "Warang Citi": range(71840, 71936), + "Dives Akuru": range(71936, 72032), + "Nandinagari": range(72096, 72192), + "Zanabazar Square": range(72192, 72272), + "Soyombo": range(72272, 72368), + "Unified Canadian Aboriginal Syllabics Extended-A": range(72368, 72384), + "Pau Cin Hau": range(72384, 72448), + "Devanagari Extended-A": range(72448, 72544), + "Sharada Supplement": range(72544, 72576), + "Sunuwar": range(72640, 72704), + "Bhaiksuki": range(72704, 72816), + "Marchen": range(72816, 72896), + "Masaram Gondi": range(72960, 73056), + "Gunjala Gondi": range(73056, 73136), + "Tolong Siki": range(73136, 73200), + "Makasar": range(73440, 73472), + "Kawi": range(73472, 73568), + "Lisu Supplement": range(73648, 73664), + "Tamil Supplement": range(73664, 73728), + "Cuneiform": range(73728, 74752), + "Cuneiform Numbers and Punctuation": range(74752, 74880), + "Early Dynastic Cuneiform": range(74880, 75088), + "Cypro-Minoan": range(77712, 77824), + "Egyptian Hieroglyphs": range(77824, 78896), + "Egyptian Hieroglyph Format Controls": range(78896, 78944), + "Egyptian Hieroglyphs Extended-A": range(78944, 82944), + "Anatolian Hieroglyphs": range(82944, 83584), + "Gurung Khema": range(90368, 90432), + "Bamum Supplement": range(92160, 92736), + "Mro": range(92736, 92784), + "Tangsa": range(92784, 92880), + "Bassa Vah": range(92880, 92928), + "Pahawh Hmong": range(92928, 93072), + "Kirat Rai": range(93504, 93568), + "Medefaidrin": range(93760, 93856), + "Beria Erfe": range(93856, 93920), + "Miao": range(93952, 94112), + "Ideographic Symbols and Punctuation": range(94176, 94208), + "Tangut": range(94208, 100352), + "Tangut Components": range(100352, 101120), + "Khitan Small Script": range(101120, 101632), + "Tangut Supplement": range(101632, 101760), + "Tangut Components Supplement": range(101760, 101888), + "Kana Extended-B": range(110576, 110592), + "Kana Supplement": range(110592, 110848), + "Kana Extended-A": range(110848, 110896), + "Small Kana Extension": range(110896, 110960), + "Nushu": range(110960, 111360), + "Duployan": range(113664, 113824), + "Shorthand Format Controls": range(113824, 113840), + "Symbols for Legacy Computing Supplement": range(117760, 118464), + "Miscellaneous Symbols Supplement": range(118464, 118528), + "Znamenny Musical Notation": range(118528, 118736), + "Byzantine Musical Symbols": range(118784, 119040), + "Musical Symbols": range(119040, 119296), + "Ancient Greek Musical Notation": range(119296, 119376), + "Kaktovik Numerals": range(119488, 119520), + "Mayan Numerals": range(119520, 119552), + "Tai Xuan Jing Symbols": range(119552, 119648), + "Counting Rod Numerals": range(119648, 119680), + "Mathematical Alphanumeric Symbols": range(119808, 120832), + "Sutton SignWriting": range(120832, 121520), + "Latin Extended-G": range(122624, 122880), + "Glagolitic Supplement": range(122880, 122928), + "Cyrillic Extended-D": range(122928, 123024), + "Nyiakeng Puachue Hmong": range(123136, 123216), + "Toto": range(123536, 123584), + "Wancho": range(123584, 123648), + "Nag Mundari": range(124112, 124160), + "Ol Onal": range(124368, 124416), + "Tai Yo": range(124608, 124672), + "Ethiopic Extended-B": range(124896, 124928), + "Mende Kikakui": range(124928, 125152), + "Adlam": range(125184, 125280), + "Indic Siyaq Numbers": range(126064, 126144), + "Ottoman Siyaq Numbers": range(126208, 126288), + "Arabic Mathematical Alphabetic Symbols": range(126464, 126720), + "Mahjong Tiles": range(126976, 127024), + "Domino Tiles": range(127024, 127136), + "Playing Cards": range(127136, 127232), + "Enclosed Alphanumeric Supplement": range(127232, 127488), + "Enclosed Ideographic Supplement": range(127488, 127744), + "Miscellaneous Symbols and Pictographs": range(127744, 128512), + "Emoticons": range(128512, 128592), + "Ornamental Dingbats": range(128592, 128640), + "Transport and Map Symbols": range(128640, 128768), + "Alchemical Symbols": range(128768, 128896), + "Geometric Shapes Extended": range(128896, 129024), + "Supplemental Arrows-C": range(129024, 129280), + "Supplemental Symbols and Pictographs": range(129280, 129536), + "Chess Symbols": range(129536, 129648), + "Symbols and Pictographs Extended-A": range(129648, 129792), + "Symbols for Legacy Computing": range(129792, 130048), + "CJK Unified Ideographs Extension B": range(131072, 173792), + "CJK Unified Ideographs Extension C": range(173824, 177984), + "CJK Unified Ideographs Extension D": range(177984, 178208), + "CJK Unified Ideographs Extension E": range(178208, 183984), + "CJK Unified Ideographs Extension F": range(183984, 191472), + "CJK Unified Ideographs Extension I": range(191472, 192096), + "CJK Compatibility Ideographs Supplement": range(194560, 195104), + "CJK Unified Ideographs Extension G": range(196608, 201552), + "CJK Unified Ideographs Extension H": range(201552, 205744), + "CJK Unified Ideographs Extension J": range(205744, 210048), + "Tags": range(917504, 917632), + "Variation Selectors Supplement": range(917760, 918000), + "Supplementary Private Use Area-A": range(983040, 1048576), + "Supplementary Private Use Area-B": range(1048576, 1114112), +} + + +UNICODE_SECONDARY_RANGE_KEYWORD: list[str] = [ + "Supplement", + "Extended", + "Extensions", + "Modifier", + "Marks", + "Punctuation", + "Symbols", + "Forms", + "Operators", + "Miscellaneous", + "Drawing", + "Block", + "Shapes", + "Supplemental", + "Tags", +] + +RE_POSSIBLE_ENCODING_INDICATION = re_compile( + r"(?:(?:encoding)|(?:charset)|(?:coding))(?:[\:= ]{1,10})(?:[\"\']?)([a-zA-Z0-9\-_]+)(?:[\"\']?)", + IGNORECASE, +) + +IANA_NO_ALIASES = [ + "cp720", + "cp737", + "cp856", + "cp874", + "cp875", + "cp1006", + "koi8_r", + "koi8_t", + "koi8_u", +] + +IANA_SUPPORTED: list[str] = sorted( + filter( + lambda x: x.endswith("_codec") is False + and x not in {"rot_13", "tactis", "mbcs"}, + list(set(aliases.values())) + IANA_NO_ALIASES, + ) +) + +IANA_SUPPORTED_COUNT: int = len(IANA_SUPPORTED) + +# pre-computed code page that are similar using the function cp_similarity. +IANA_SUPPORTED_SIMILAR: dict[str, list[str]] = { + "cp037": ["cp1026", "cp1140", "cp273", "cp500"], + "cp1026": ["cp037", "cp1140", "cp273", "cp500"], + "cp1125": ["cp866"], + "cp1140": ["cp037", "cp1026", "cp273", "cp500"], + "cp1250": ["iso8859_2"], + "cp1251": ["kz1048", "ptcp154"], + "cp1252": ["iso8859_15", "iso8859_9", "latin_1"], + "cp1253": ["iso8859_7"], + "cp1254": ["iso8859_15", "iso8859_9", "latin_1"], + "cp1257": ["iso8859_13"], + "cp273": ["cp037", "cp1026", "cp1140", "cp500"], + "cp437": ["cp850", "cp858", "cp860", "cp861", "cp862", "cp863", "cp865"], + "cp500": ["cp037", "cp1026", "cp1140", "cp273"], + "cp850": ["cp437", "cp857", "cp858", "cp865"], + "cp857": ["cp850", "cp858", "cp865"], + "cp858": ["cp437", "cp850", "cp857", "cp865"], + "cp860": ["cp437", "cp861", "cp862", "cp863", "cp865"], + "cp861": ["cp437", "cp860", "cp862", "cp863", "cp865"], + "cp862": ["cp437", "cp860", "cp861", "cp863", "cp865"], + "cp863": ["cp437", "cp860", "cp861", "cp862", "cp865"], + "cp865": ["cp437", "cp850", "cp857", "cp858", "cp860", "cp861", "cp862", "cp863"], + "cp866": ["cp1125"], + "iso8859_10": ["iso8859_14", "iso8859_15", "iso8859_4", "iso8859_9", "latin_1"], + "iso8859_11": ["tis_620"], + "iso8859_13": ["cp1257"], + "iso8859_14": [ + "iso8859_10", + "iso8859_15", + "iso8859_16", + "iso8859_3", + "iso8859_9", + "latin_1", + ], + "iso8859_15": [ + "cp1252", + "cp1254", + "iso8859_10", + "iso8859_14", + "iso8859_16", + "iso8859_3", + "iso8859_9", + "latin_1", + ], + "iso8859_16": [ + "iso8859_14", + "iso8859_15", + "iso8859_2", + "iso8859_3", + "iso8859_9", + "latin_1", + ], + "iso8859_2": ["cp1250", "iso8859_16", "iso8859_4"], + "iso8859_3": ["iso8859_14", "iso8859_15", "iso8859_16", "iso8859_9", "latin_1"], + "iso8859_4": ["iso8859_10", "iso8859_2", "iso8859_9", "latin_1"], + "iso8859_7": ["cp1253"], + "iso8859_9": [ + "cp1252", + "cp1254", + "cp1258", + "iso8859_10", + "iso8859_14", + "iso8859_15", + "iso8859_16", + "iso8859_3", + "iso8859_4", + "latin_1", + ], + "kz1048": ["cp1251", "ptcp154"], + "latin_1": [ + "cp1252", + "cp1254", + "cp1258", + "iso8859_10", + "iso8859_14", + "iso8859_15", + "iso8859_16", + "iso8859_3", + "iso8859_4", + "iso8859_9", + ], + "mac_iceland": ["mac_roman", "mac_turkish"], + "mac_roman": ["mac_iceland", "mac_turkish"], + "mac_turkish": ["mac_iceland", "mac_roman"], + "ptcp154": ["cp1251", "kz1048"], + "tis_620": ["iso8859_11"], +} + + +CHARDET_CORRESPONDENCE: dict[str, str] = { + "iso2022_kr": "ISO-2022-KR", + "iso2022_jp": "ISO-2022-JP", + "euc_kr": "EUC-KR", + "tis_620": "TIS-620", + "utf_32": "UTF-32", + "euc_jp": "EUC-JP", + "koi8_r": "KOI8-R", + "iso8859_1": "ISO-8859-1", + "iso8859_2": "ISO-8859-2", + "iso8859_5": "ISO-8859-5", + "iso8859_6": "ISO-8859-6", + "iso8859_7": "ISO-8859-7", + "iso8859_8": "ISO-8859-8", + "utf_16": "UTF-16", + "cp855": "IBM855", + "mac_cyrillic": "MacCyrillic", + "gb2312": "GB2312", + "gb18030": "GB18030", + "cp932": "CP932", + "cp866": "IBM866", + "utf_8": "utf-8", + "utf_8_sig": "UTF-8-SIG", + "shift_jis": "SHIFT_JIS", + "big5": "Big5", + "cp1250": "windows-1250", + "cp1251": "windows-1251", + "cp1252": "Windows-1252", + "cp1253": "windows-1253", + "cp1255": "windows-1255", + "cp1256": "windows-1256", + "cp1254": "Windows-1254", + "cp949": "CP949", +} + + +COMMON_SAFE_ASCII_CHARACTERS: frozenset[str] = frozenset( + { + "<", + ">", + "=", + ":", + "/", + "&", + ";", + "{", + "}", + "[", + "]", + ",", + "|", + '"', + "-", + "(", + ")", + } +) + +# Sample character sets — replace with full lists if needed +COMMON_CHINESE_CHARACTERS = "的一是在不了有和人这中大为上个国我以要他时来用们生到作地于出就分对成会可主发年动同工也能下过子说产种面而方后多定行学法所民得经十三之进着等部度家电力里如水化高自二理起小物现实加量都两体制机当使点从业本去把性好应开它合还因由其些然前外天政四日那社义事平形相全表间样与关各重新线内数正心反你明看原又么利比或但质气第向道命此变条只没结解问意建月公无系军很情者最立代想已通并提直题党程展五果料象员革位入常文总次品式活设及管特件长求老头基资边流路级少图山统接知较将组见计别她手角期根论运农指几九区强放决西被干做必战先回则任取据处队南给色光门即保治北造百规热领七海口东导器压志世金增争济阶油思术极交受联什认六共权收证改清己美再采转更单风切打白教速花带安场身车例真务具万每目至达走积示议声报斗完类八离华名确才科张信马节话米整空元况今集温传土许步群广石记需段研界拉林律叫且究观越织装影算低持音众书布复容儿须际商非验连断深难近矿千周委素技备半办青省列习响约支般史感劳便团往酸历市克何除消构府太准精值号率族维划选标写存候毛亲快效斯院查江型眼王按格养易置派层片始却专状育厂京识适属圆包火住调满县局照参红细引听该铁价严龙飞" + +COMMON_JAPANESE_CHARACTERS = "日一国年大十二本中長出三時行見月分後前生五間上東四今金九入学高円子外八六下来気小七山話女北午百書先名川千水半男西電校語土木聞食車何南万毎白天母火右読友左休父雨" + +COMMON_KOREAN_CHARACTERS = "一二三四五六七八九十百千萬上下左右中人女子大小山川日月火水木金土父母天地國名年時文校學生" + +# Combine all into a frozenset +COMMON_CJK_CHARACTERS = frozenset( + "".join( + [ + COMMON_CHINESE_CHARACTERS, + COMMON_JAPANESE_CHARACTERS, + COMMON_KOREAN_CHARACTERS, + ] + ) +) + +KO_NAMES: frozenset[str] = frozenset({"johab", "cp949", "euc_kr"}) +ZH_NAMES: frozenset[str] = frozenset({"big5", "cp950", "big5hkscs", "hz"}) + +# Logging LEVEL below DEBUG +TRACE: int = 5 + + +# Language label that contain the em dash "—" +# character are to be considered alternative seq to origin +FREQUENCIES: dict[str, list[str]] = { + "English": [ + "e", + "a", + "t", + "i", + "o", + "n", + "s", + "r", + "h", + "l", + "d", + "c", + "u", + "m", + "f", + "p", + "g", + "w", + "y", + "b", + "v", + "k", + "x", + "j", + "z", + "q", + ], + "English—": [ + "e", + "a", + "t", + "i", + "o", + "n", + "s", + "r", + "h", + "l", + "d", + "c", + "m", + "u", + "f", + "p", + "g", + "w", + "b", + "y", + "v", + "k", + "j", + "x", + "z", + "q", + ], + "German": [ + "e", + "n", + "i", + "r", + "s", + "t", + "a", + "d", + "h", + "u", + "l", + "g", + "o", + "c", + "m", + "b", + "f", + "k", + "w", + "z", + "p", + "v", + "ü", + "ä", + "ö", + "j", + ], + "French": [ + "e", + "a", + "s", + "n", + "i", + "t", + "r", + "l", + "u", + "o", + "d", + "c", + "p", + "m", + "é", + "v", + "g", + "f", + "b", + "h", + "q", + "à", + "x", + "è", + "y", + "j", + ], + "Dutch": [ + "e", + "n", + "a", + "i", + "r", + "t", + "o", + "d", + "s", + "l", + "g", + "h", + "v", + "m", + "u", + "k", + "c", + "p", + "b", + "w", + "j", + "z", + "f", + "y", + "x", + "ë", + ], + "Italian": [ + "e", + "i", + "a", + "o", + "n", + "l", + "t", + "r", + "s", + "c", + "d", + "u", + "p", + "m", + "g", + "v", + "f", + "b", + "z", + "h", + "q", + "è", + "à", + "k", + "y", + "ò", + ], + "Polish": [ + "a", + "i", + "o", + "e", + "n", + "r", + "z", + "w", + "s", + "c", + "t", + "k", + "y", + "d", + "p", + "m", + "u", + "l", + "j", + "ł", + "g", + "b", + "h", + "ą", + "ę", + "ó", + ], + "Spanish": [ + "e", + "a", + "o", + "n", + "s", + "r", + "i", + "l", + "d", + "t", + "c", + "u", + "m", + "p", + "b", + "g", + "v", + "f", + "y", + "ó", + "h", + "q", + "í", + "j", + "z", + "á", + ], + "Russian": [ + "о", + "е", + "а", + "и", + "н", + "т", + "с", + "р", + "в", + "л", + "к", + "м", + "д", + "п", + "у", + "г", + "я", + "ы", + "з", + "б", + "й", + "ь", + "ч", + "х", + "ж", + "ц", + ], + # Jap-Kanji + "Japanese": [ + "日", + "一", + "人", + "年", + "大", + "十", + "二", + "本", + "中", + "長", + "出", + "三", + "時", + "行", + "見", + "月", + "分", + "後", + "前", + "生", + "五", + "間", + "上", + "東", + "四", + "今", + "金", + "九", + "入", + "学", + "高", + "円", + "子", + "外", + "八", + "六", + "下", + "来", + "気", + "小", + "七", + "山", + "話", + "女", + "北", + "午", + "百", + "書", + "先", + "名", + "川", + "千", + "水", + "半", + "男", + "西", + "電", + "校", + "語", + "土", + "木", + "聞", + "食", + "車", + "何", + "南", + "万", + "毎", + "白", + "天", + "母", + "火", + "右", + "読", + "友", + "左", + "休", + "父", + "雨", + ], + # Jap-Katakana + "Japanese—": [ + "ー", + "ン", + "ス", + "・", + "ル", + "ト", + "リ", + "イ", + "ア", + "ラ", + "ッ", + "ク", + "ド", + "シ", + "レ", + "ジ", + "タ", + "フ", + "ロ", + "カ", + "テ", + "マ", + "ィ", + "グ", + "バ", + "ム", + "プ", + "オ", + "コ", + "デ", + "ニ", + "ウ", + "メ", + "サ", + "ビ", + "ナ", + "ブ", + "ャ", + "エ", + "ュ", + "チ", + "キ", + "ズ", + "ダ", + "パ", + "ミ", + "ェ", + "ョ", + "ハ", + "セ", + "ベ", + "ガ", + "モ", + "ツ", + "ネ", + "ボ", + "ソ", + "ノ", + "ァ", + "ヴ", + "ワ", + "ポ", + "ペ", + "ピ", + "ケ", + "ゴ", + "ギ", + "ザ", + "ホ", + "ゲ", + "ォ", + "ヤ", + "ヒ", + "ユ", + "ヨ", + "ヘ", + "ゼ", + "ヌ", + "ゥ", + "ゾ", + "ヶ", + "ヂ", + "ヲ", + "ヅ", + "ヵ", + "ヱ", + "ヰ", + "ヮ", + "ヽ", + "゠", + "ヾ", + "ヷ", + "ヿ", + "ヸ", + "ヹ", + "ヺ", + ], + # Jap-Hiragana + "Japanese——": [ + "の", + "に", + "る", + "た", + "と", + "は", + "し", + "い", + "を", + "で", + "て", + "が", + "な", + "れ", + "か", + "ら", + "さ", + "っ", + "り", + "す", + "あ", + "も", + "こ", + "ま", + "う", + "く", + "よ", + "き", + "ん", + "め", + "お", + "け", + "そ", + "つ", + "だ", + "や", + "え", + "ど", + "わ", + "ち", + "み", + "せ", + "じ", + "ば", + "へ", + "び", + "ず", + "ろ", + "ほ", + "げ", + "む", + "べ", + "ひ", + "ょ", + "ゆ", + "ぶ", + "ご", + "ゃ", + "ね", + "ふ", + "ぐ", + "ぎ", + "ぼ", + "ゅ", + "づ", + "ざ", + "ぞ", + "ぬ", + "ぜ", + "ぱ", + "ぽ", + "ぷ", + "ぴ", + "ぃ", + "ぁ", + "ぇ", + "ぺ", + "ゞ", + "ぢ", + "ぉ", + "ぅ", + "ゐ", + "ゝ", + "ゑ", + "゛", + "゜", + "ゎ", + "ゔ", + "゚", + "ゟ", + "゙", + "ゕ", + "ゖ", + ], + "Portuguese": [ + "a", + "e", + "o", + "s", + "i", + "r", + "d", + "n", + "t", + "m", + "u", + "c", + "l", + "p", + "g", + "v", + "b", + "f", + "h", + "ã", + "q", + "é", + "ç", + "á", + "z", + "í", + ], + "Swedish": [ + "e", + "a", + "n", + "r", + "t", + "s", + "i", + "l", + "d", + "o", + "m", + "k", + "g", + "v", + "h", + "f", + "u", + "p", + "ä", + "c", + "b", + "ö", + "å", + "y", + "j", + "x", + ], + "Chinese": [ + "的", + "一", + "是", + "不", + "了", + "在", + "人", + "有", + "我", + "他", + "这", + "个", + "们", + "中", + "来", + "上", + "大", + "为", + "和", + "国", + "地", + "到", + "以", + "说", + "时", + "要", + "就", + "出", + "会", + "可", + "也", + "你", + "对", + "生", + "能", + "而", + "子", + "那", + "得", + "于", + "着", + "下", + "自", + "之", + "年", + "过", + "发", + "后", + "作", + "里", + "用", + "道", + "行", + "所", + "然", + "家", + "种", + "事", + "成", + "方", + "多", + "经", + "么", + "去", + "法", + "学", + "如", + "都", + "同", + "现", + "当", + "没", + "动", + "面", + "起", + "看", + "定", + "天", + "分", + "还", + "进", + "好", + "小", + "部", + "其", + "些", + "主", + "样", + "理", + "心", + "她", + "本", + "前", + "开", + "但", + "因", + "只", + "从", + "想", + "实", + ], + "Ukrainian": [ + "о", + "а", + "н", + "і", + "и", + "р", + "в", + "т", + "е", + "с", + "к", + "л", + "у", + "д", + "м", + "п", + "з", + "я", + "ь", + "б", + "г", + "й", + "ч", + "х", + "ц", + "ї", + ], + "Norwegian": [ + "e", + "r", + "n", + "t", + "a", + "s", + "i", + "o", + "l", + "d", + "g", + "k", + "m", + "v", + "f", + "p", + "u", + "b", + "h", + "å", + "y", + "j", + "ø", + "c", + "æ", + "w", + ], + "Finnish": [ + "a", + "i", + "n", + "t", + "e", + "s", + "l", + "o", + "u", + "k", + "ä", + "m", + "r", + "v", + "j", + "h", + "p", + "y", + "d", + "ö", + "g", + "c", + "b", + "f", + "w", + "z", + ], + "Vietnamese": [ + "n", + "h", + "t", + "i", + "c", + "g", + "a", + "o", + "u", + "m", + "l", + "r", + "à", + "đ", + "s", + "e", + "v", + "p", + "b", + "y", + "ư", + "d", + "á", + "k", + "ộ", + "ế", + ], + "Czech": [ + "o", + "e", + "a", + "n", + "t", + "s", + "i", + "l", + "v", + "r", + "k", + "d", + "u", + "m", + "p", + "í", + "c", + "h", + "z", + "á", + "y", + "j", + "b", + "ě", + "é", + "ř", + ], + "Hungarian": [ + "e", + "a", + "t", + "l", + "s", + "n", + "k", + "r", + "i", + "o", + "z", + "á", + "é", + "g", + "m", + "b", + "y", + "v", + "d", + "h", + "u", + "p", + "j", + "ö", + "f", + "c", + ], + "Korean": [ + "이", + "다", + "에", + "의", + "는", + "로", + "하", + "을", + "가", + "고", + "지", + "서", + "한", + "은", + "기", + "으", + "년", + "대", + "사", + "시", + "를", + "리", + "도", + "인", + "스", + "일", + ], + "Indonesian": [ + "a", + "n", + "e", + "i", + "r", + "t", + "u", + "s", + "d", + "k", + "m", + "l", + "g", + "p", + "b", + "o", + "h", + "y", + "j", + "c", + "w", + "f", + "v", + "z", + "x", + "q", + ], + "Turkish": [ + "a", + "e", + "i", + "n", + "r", + "l", + "ı", + "k", + "d", + "t", + "s", + "m", + "y", + "u", + "o", + "b", + "ü", + "ş", + "v", + "g", + "z", + "h", + "c", + "p", + "ç", + "ğ", + ], + "Romanian": [ + "e", + "i", + "a", + "r", + "n", + "t", + "u", + "l", + "o", + "c", + "s", + "d", + "p", + "m", + "ă", + "f", + "v", + "î", + "g", + "b", + "ș", + "ț", + "z", + "h", + "â", + "j", + ], + "Farsi": [ + "ا", + "ی", + "ر", + "د", + "ن", + "ه", + "و", + "م", + "ت", + "ب", + "س", + "ل", + "ک", + "ش", + "ز", + "ف", + "گ", + "ع", + "خ", + "ق", + "ج", + "آ", + "پ", + "ح", + "ط", + "ص", + ], + "Arabic": [ + "ا", + "ل", + "ي", + "م", + "و", + "ن", + "ر", + "ت", + "ب", + "ة", + "ع", + "د", + "س", + "ف", + "ه", + "ك", + "ق", + "أ", + "ح", + "ج", + "ش", + "ط", + "ص", + "ى", + "خ", + "إ", + ], + "Danish": [ + "e", + "r", + "n", + "t", + "a", + "i", + "s", + "d", + "l", + "o", + "g", + "m", + "k", + "f", + "v", + "u", + "b", + "h", + "p", + "å", + "y", + "ø", + "æ", + "c", + "j", + "w", + ], + "Serbian": [ + "а", + "и", + "о", + "е", + "н", + "р", + "с", + "у", + "т", + "к", + "ј", + "в", + "д", + "м", + "п", + "л", + "г", + "з", + "б", + "a", + "i", + "e", + "o", + "n", + "ц", + "ш", + ], + "Lithuanian": [ + "i", + "a", + "s", + "o", + "r", + "e", + "t", + "n", + "u", + "k", + "m", + "l", + "p", + "v", + "d", + "j", + "g", + "ė", + "b", + "y", + "ų", + "š", + "ž", + "c", + "ą", + "į", + ], + "Slovene": [ + "e", + "a", + "i", + "o", + "n", + "r", + "s", + "l", + "t", + "j", + "v", + "k", + "d", + "p", + "m", + "u", + "z", + "b", + "g", + "h", + "č", + "c", + "š", + "ž", + "f", + "y", + ], + "Slovak": [ + "o", + "a", + "e", + "n", + "i", + "r", + "v", + "t", + "s", + "l", + "k", + "d", + "m", + "p", + "u", + "c", + "h", + "j", + "b", + "z", + "á", + "y", + "ý", + "í", + "č", + "é", + ], + "Hebrew": [ + "י", + "ו", + "ה", + "ל", + "ר", + "ב", + "ת", + "מ", + "א", + "ש", + "נ", + "ע", + "ם", + "ד", + "ק", + "ח", + "פ", + "ס", + "כ", + "ג", + "ט", + "צ", + "ן", + "ז", + "ך", + ], + "Bulgarian": [ + "а", + "и", + "о", + "е", + "н", + "т", + "р", + "с", + "в", + "л", + "к", + "д", + "п", + "м", + "з", + "г", + "я", + "ъ", + "у", + "б", + "ч", + "ц", + "й", + "ж", + "щ", + "х", + ], + "Croatian": [ + "a", + "i", + "o", + "e", + "n", + "r", + "j", + "s", + "t", + "u", + "k", + "l", + "v", + "d", + "m", + "p", + "g", + "z", + "b", + "c", + "č", + "h", + "š", + "ž", + "ć", + "f", + ], + "Hindi": [ + "क", + "र", + "स", + "न", + "त", + "म", + "ह", + "प", + "य", + "ल", + "व", + "ज", + "द", + "ग", + "ब", + "श", + "ट", + "अ", + "ए", + "थ", + "भ", + "ड", + "च", + "ध", + "ष", + "इ", + ], + "Estonian": [ + "a", + "i", + "e", + "s", + "t", + "l", + "u", + "n", + "o", + "k", + "r", + "d", + "m", + "v", + "g", + "p", + "j", + "h", + "ä", + "b", + "õ", + "ü", + "f", + "c", + "ö", + "y", + ], + "Thai": [ + "า", + "น", + "ร", + "อ", + "ก", + "เ", + "ง", + "ม", + "ย", + "ล", + "ว", + "ด", + "ท", + "ส", + "ต", + "ะ", + "ป", + "บ", + "ค", + "ห", + "แ", + "จ", + "พ", + "ช", + "ข", + "ใ", + ], + "Greek": [ + "α", + "τ", + "ο", + "ι", + "ε", + "ν", + "ρ", + "σ", + "κ", + "η", + "π", + "ς", + "υ", + "μ", + "λ", + "ί", + "ό", + "ά", + "γ", + "έ", + "δ", + "ή", + "ω", + "χ", + "θ", + "ύ", + ], + "Tamil": [ + "க", + "த", + "ப", + "ட", + "ர", + "ம", + "ல", + "ன", + "வ", + "ற", + "ய", + "ள", + "ச", + "ந", + "இ", + "ண", + "அ", + "ஆ", + "ழ", + "ங", + "எ", + "உ", + "ஒ", + "ஸ", + ], + "Kazakh": [ + "а", + "ы", + "е", + "н", + "т", + "р", + "л", + "і", + "д", + "с", + "м", + "қ", + "к", + "о", + "б", + "и", + "у", + "ғ", + "ж", + "ң", + "з", + "ш", + "й", + "п", + "г", + "ө", + ], +} + +LANGUAGE_SUPPORTED_COUNT: int = len(FREQUENCIES) + +# Bit flags for unified character classification. +# A single unicodedata.name() call sets all relevant flags at once. +_LATIN: int = 1 +_ACCENTUATED: int = 1 << 1 +_CJK: int = 1 << 2 +_HANGUL: int = 1 << 3 +_KATAKANA: int = 1 << 4 +_HIRAGANA: int = 1 << 5 +_THAI: int = 1 << 6 +_ARABIC: int = 1 << 7 +_ARABIC_ISOLATED_FORM: int = 1 << 8 + +_ACCENT_KEYWORDS: tuple[str, ...] = ( + "WITH GRAVE", + "WITH ACUTE", + "WITH CEDILLA", + "WITH DIAERESIS", + "WITH CIRCUMFLEX", + "WITH TILDE", + "WITH MACRON", + "WITH RING ABOVE", +) + +# Pre-built lookup structures for FREQUENCIES (computed once at import time). +# character -> rank mapping per language (replaces list .index() calls). +_FREQUENCIES_RANK: dict[str, dict[str, int]] = { + lang: {char: rank for rank, char in enumerate(chars)} + for lang, chars in FREQUENCIES.items() +} + +# frozenset per language (avoids rebuilding set() per call). +_FREQUENCIES_SET: dict[str, frozenset[str]] = { + lang: frozenset(chars) for lang, chars in FREQUENCIES.items() +} diff --git a/charset_normalizer/legacy.py b/charset_normalizer/legacy.py new file mode 100644 index 0000000000000000000000000000000000000000..293c1efaf045559ea088e7991b318571a4ff71a8 --- /dev/null +++ b/charset_normalizer/legacy.py @@ -0,0 +1,79 @@ +from __future__ import annotations + +from typing import TYPE_CHECKING, Any +from warnings import warn + +from .api import from_bytes +from .constant import CHARDET_CORRESPONDENCE, TOO_SMALL_SEQUENCE + +if TYPE_CHECKING: + from typing import TypedDict + + class ResultDict(TypedDict): + encoding: str | None + language: str + confidence: float | None + + +def detect( + byte_str: bytes, should_rename_legacy: bool = False, **kwargs: Any +) -> ResultDict: + """ + chardet legacy method + Detect the encoding of the given byte string. It should be mostly backward-compatible. + Encoding name will match Chardet own writing whenever possible. (Not on encoding name unsupported by it) + This function is deprecated and should be used to migrate your project easily, consult the documentation for + further information. Not planned for removal. + + :param byte_str: The byte sequence to examine. + :param should_rename_legacy: Should we rename legacy encodings + to their more modern equivalents? + """ + if len(kwargs): + warn( + f"charset-normalizer disregard arguments '{','.join(list(kwargs.keys()))}' in legacy function detect()" + ) + + if not isinstance(byte_str, (bytearray, bytes)): + raise TypeError( # pragma: nocover + f"Expected object of type bytes or bytearray, got: {type(byte_str)}" + ) + + if isinstance(byte_str, bytearray): + byte_str = bytes(byte_str) + + r = from_bytes(byte_str).best() + + encoding = r.encoding if r is not None else None + language = r.language if r is not None and r.language != "Unknown" else "" + confidence = 1.0 - r.chaos if r is not None else None + + # automatically lower confidence + # on small bytes samples. + # https://github.com/jawah/charset_normalizer/issues/391 + if ( + confidence is not None + and confidence >= 0.9 + and encoding + not in { + "utf_8", + "ascii", + } + and r.bom is False # type: ignore[union-attr] + and len(byte_str) < TOO_SMALL_SEQUENCE + ): + confidence -= 0.2 + + # Note: CharsetNormalizer does not return 'UTF-8-SIG' as the sig get stripped in the detection/normalization process + # but chardet does return 'utf-8-sig' and it is a valid codec name. + if r is not None and encoding == "utf_8" and r.bom: + encoding += "_sig" + + if should_rename_legacy is False and encoding in CHARDET_CORRESPONDENCE: + encoding = CHARDET_CORRESPONDENCE[encoding] + + return { + "encoding": encoding, + "language": language, + "confidence": confidence, + } diff --git a/charset_normalizer/md.cpython-312-x86_64-linux-gnu.so b/charset_normalizer/md.cpython-312-x86_64-linux-gnu.so new file mode 100644 index 0000000000000000000000000000000000000000..8fb2c57503ef9cd144ae966361dfad8beaa92cff Binary files /dev/null and b/charset_normalizer/md.cpython-312-x86_64-linux-gnu.so differ diff --git a/charset_normalizer/md.py b/charset_normalizer/md.py new file mode 100644 index 0000000000000000000000000000000000000000..b41d9cfc575d5ea2dd0dab5b0e4350b8485bd70b --- /dev/null +++ b/charset_normalizer/md.py @@ -0,0 +1,936 @@ +from __future__ import annotations + +import sys +from functools import lru_cache +from logging import getLogger + +if sys.version_info >= (3, 8): + from typing import final +else: + try: + from typing_extensions import final + except ImportError: + + def final(cls): # type: ignore[misc,no-untyped-def] + return cls + + +from .constant import ( + COMMON_CJK_CHARACTERS, + COMMON_SAFE_ASCII_CHARACTERS, + TRACE, + UNICODE_SECONDARY_RANGE_KEYWORD, + _ACCENTUATED, + _ARABIC, + _ARABIC_ISOLATED_FORM, + _CJK, + _HANGUL, + _HIRAGANA, + _KATAKANA, + _LATIN, + _THAI, +) +from .utils import ( + _character_flags, + is_emoticon, + is_punctuation, + is_separator, + is_symbol, + remove_accent, + unicode_range, +) + +# Combined bitmask for CJK/Hangul/Katakana/Hiragana/Thai glyph detection. +_GLYPH_MASK: int = _CJK | _HANGUL | _KATAKANA | _HIRAGANA | _THAI + + +@final +class CharInfo: + """Pre-computed character properties shared across all detectors. + + Instantiated once and reused via :meth:`update` on every character + in the hot loop so that redundant calls to str methods + (``isalpha``, ``isupper``, …) and cached utility functions + (``_character_flags``, ``is_punctuation``, …) are avoided when + several plugins need the same information. + """ + + __slots__ = ( + "character", + "printable", + "alpha", + "upper", + "lower", + "space", + "digit", + "is_ascii", + "case_variable", + "flags", + "accentuated", + "latin", + "is_cjk", + "is_arabic", + "is_glyph", + "punct", + "sym", + ) + + def __init__(self) -> None: + self.character: str = "" + self.printable: bool = False + self.alpha: bool = False + self.upper: bool = False + self.lower: bool = False + self.space: bool = False + self.digit: bool = False + self.is_ascii: bool = False + self.case_variable: bool = False + self.flags: int = 0 + self.accentuated: bool = False + self.latin: bool = False + self.is_cjk: bool = False + self.is_arabic: bool = False + self.is_glyph: bool = False + self.punct: bool = False + self.sym: bool = False + + def update(self, character: str) -> None: + """Update all properties for *character* (called once per character).""" + self.character = character + + # ASCII fast-path: for characters with ord < 128, we can skip + # _character_flags() entirely and derive most properties from ord. + o: int = ord(character) + if o < 128: + self.is_ascii = True + self.accentuated = False + self.is_cjk = False + self.is_arabic = False + self.is_glyph = False + # ASCII alpha: a-z (97-122) or A-Z (65-90) + if 65 <= o <= 90: + # Uppercase ASCII letter + self.alpha = True + self.upper = True + self.lower = False + self.space = False + self.digit = False + self.printable = True + self.case_variable = True + self.flags = _LATIN + self.latin = True + self.punct = False + self.sym = False + elif 97 <= o <= 122: + # Lowercase ASCII letter + self.alpha = True + self.upper = False + self.lower = True + self.space = False + self.digit = False + self.printable = True + self.case_variable = True + self.flags = _LATIN + self.latin = True + self.punct = False + self.sym = False + elif 48 <= o <= 57: + # ASCII digit 0-9 + self.alpha = False + self.upper = False + self.lower = False + self.space = False + self.digit = True + self.printable = True + self.case_variable = False + self.flags = 0 + self.latin = False + self.punct = False + self.sym = False + elif o == 32 or (9 <= o <= 13): + # Space, tab, newline, etc. + self.alpha = False + self.upper = False + self.lower = False + self.space = True + self.digit = False + self.printable = o == 32 + self.case_variable = False + self.flags = 0 + self.latin = False + self.punct = False + self.sym = False + else: + # Other ASCII (punctuation, symbols, control chars) + self.printable = character.isprintable() + self.alpha = False + self.upper = False + self.lower = False + self.space = False + self.digit = False + self.case_variable = False + self.flags = 0 + self.latin = False + self.punct = is_punctuation(character) if self.printable else False + self.sym = is_symbol(character) if self.printable else False + else: + # Non-ASCII path + self.is_ascii = False + self.printable = character.isprintable() + self.alpha = character.isalpha() + self.upper = character.isupper() + self.lower = character.islower() + self.space = character.isspace() + self.digit = character.isdigit() + self.case_variable = self.lower != self.upper + + # Flag-based classification (single unicodedata.name() call, lru-cached) + flags: int + if self.alpha: + flags = _character_flags(character) + else: + flags = 0 + self.flags = flags + self.accentuated = bool(flags & _ACCENTUATED) + self.latin = bool(flags & _LATIN) + self.is_cjk = bool(flags & _CJK) + self.is_arabic = bool(flags & _ARABIC) + self.is_glyph = bool(flags & _GLYPH_MASK) + + # Eagerly compute punct and sym (avoids property dispatch overhead + # on 300K+ accesses in the hot loop). + self.punct = is_punctuation(character) if self.printable else False + self.sym = is_symbol(character) if self.printable else False + + +class MessDetectorPlugin: + """ + Base abstract class used for mess detection plugins. + All detectors MUST extend and implement given methods. + """ + + __slots__ = () + + def feed_info(self, character: str, info: CharInfo) -> None: + """ + The main routine to be executed upon character. + Insert the logic in witch the text would be considered chaotic. + """ + raise NotImplementedError # Defensive: + + def reset(self) -> None: # Defensive: + """ + Permit to reset the plugin to the initial state. + """ + raise NotImplementedError + + @property + def ratio(self) -> float: + """ + Compute the chaos ratio based on what your feed() has seen. + Must NOT be lower than 0.; No restriction gt 0. + """ + raise NotImplementedError # Defensive: + + +@final +class TooManySymbolOrPunctuationPlugin(MessDetectorPlugin): + __slots__ = ( + "_punctuation_count", + "_symbol_count", + "_character_count", + "_last_printable_char", + "_frenzy_symbol_in_word", + ) + + def __init__(self) -> None: + self._punctuation_count: int = 0 + self._symbol_count: int = 0 + self._character_count: int = 0 + + self._last_printable_char: str | None = None + self._frenzy_symbol_in_word: bool = False + + def feed_info(self, character: str, info: CharInfo) -> None: + """Optimized feed using pre-computed character info.""" + self._character_count += 1 + + if ( + character != self._last_printable_char + and character not in COMMON_SAFE_ASCII_CHARACTERS + ): + if info.punct: + self._punctuation_count += 1 + elif not info.digit and info.sym and not is_emoticon(character): + self._symbol_count += 2 + + self._last_printable_char = character + + def reset(self) -> None: # Abstract + self._punctuation_count = 0 + self._character_count = 0 + self._symbol_count = 0 + + @property + def ratio(self) -> float: + if self._character_count == 0: + return 0.0 + + ratio_of_punctuation: float = ( + self._punctuation_count + self._symbol_count + ) / self._character_count + + return ratio_of_punctuation if ratio_of_punctuation >= 0.3 else 0.0 + + +@final +class TooManyAccentuatedPlugin(MessDetectorPlugin): + __slots__ = ("_character_count", "_accentuated_count") + + def __init__(self) -> None: + self._character_count: int = 0 + self._accentuated_count: int = 0 + + def feed_info(self, character: str, info: CharInfo) -> None: + """Optimized feed using pre-computed character info.""" + self._character_count += 1 + + if info.accentuated: + self._accentuated_count += 1 + + def reset(self) -> None: # Abstract + self._character_count = 0 + self._accentuated_count = 0 + + @property + def ratio(self) -> float: + if self._character_count < 8: + return 0.0 + + ratio_of_accentuation: float = self._accentuated_count / self._character_count + return ratio_of_accentuation if ratio_of_accentuation >= 0.35 else 0.0 + + +@final +class UnprintablePlugin(MessDetectorPlugin): + __slots__ = ("_unprintable_count", "_character_count") + + def __init__(self) -> None: + self._unprintable_count: int = 0 + self._character_count: int = 0 + + def feed_info(self, character: str, info: CharInfo) -> None: + """Optimized feed using pre-computed character info.""" + if ( + not info.space + and not info.printable + and character != "\x1a" + and character != "\ufeff" + ): + self._unprintable_count += 1 + self._character_count += 1 + + def reset(self) -> None: # Abstract + self._unprintable_count = 0 + + @property + def ratio(self) -> float: + if self._character_count == 0: # Defensive: + return 0.0 + + return (self._unprintable_count * 8) / self._character_count + + +@final +class SuspiciousDuplicateAccentPlugin(MessDetectorPlugin): + __slots__ = ( + "_successive_count", + "_character_count", + "_last_latin_character", + "_last_was_accentuated", + ) + + def __init__(self) -> None: + self._successive_count: int = 0 + self._character_count: int = 0 + + self._last_latin_character: str | None = None + self._last_was_accentuated: bool = False + + def feed_info(self, character: str, info: CharInfo) -> None: + """Optimized feed using pre-computed character info.""" + self._character_count += 1 + if ( + self._last_latin_character is not None + and info.accentuated + and self._last_was_accentuated + ): + if info.upper and self._last_latin_character.isupper(): + self._successive_count += 1 + if remove_accent(character) == remove_accent(self._last_latin_character): + self._successive_count += 1 + self._last_latin_character = character + self._last_was_accentuated = info.accentuated + + def reset(self) -> None: # Abstract + self._successive_count = 0 + self._character_count = 0 + self._last_latin_character = None + self._last_was_accentuated = False + + @property + def ratio(self) -> float: + if self._character_count == 0: + return 0.0 + + return (self._successive_count * 2) / self._character_count + + +@final +class SuspiciousRange(MessDetectorPlugin): + __slots__ = ( + "_suspicious_successive_range_count", + "_character_count", + "_last_printable_seen", + "_last_printable_range", + ) + + def __init__(self) -> None: + self._suspicious_successive_range_count: int = 0 + self._character_count: int = 0 + self._last_printable_seen: str | None = None + self._last_printable_range: str | None = None + + def feed_info(self, character: str, info: CharInfo) -> None: + """Optimized feed using pre-computed character info.""" + self._character_count += 1 + + if info.space or info.punct or character in COMMON_SAFE_ASCII_CHARACTERS: + self._last_printable_seen = None + self._last_printable_range = None + return + + if self._last_printable_seen is None: + self._last_printable_seen = character + self._last_printable_range = unicode_range(character) + return + + unicode_range_a: str | None = self._last_printable_range + unicode_range_b: str | None = unicode_range(character) + + if is_suspiciously_successive_range(unicode_range_a, unicode_range_b): + self._suspicious_successive_range_count += 1 + + self._last_printable_seen = character + self._last_printable_range = unicode_range_b + + def reset(self) -> None: # Abstract + self._character_count = 0 + self._suspicious_successive_range_count = 0 + self._last_printable_seen = None + self._last_printable_range = None + + @property + def ratio(self) -> float: + if self._character_count <= 13: + return 0.0 + + ratio_of_suspicious_range_usage: float = ( + self._suspicious_successive_range_count * 2 + ) / self._character_count + + return ratio_of_suspicious_range_usage + + +@final +class SuperWeirdWordPlugin(MessDetectorPlugin): + __slots__ = ( + "_word_count", + "_bad_word_count", + "_foreign_long_count", + "_is_current_word_bad", + "_foreign_long_watch", + "_character_count", + "_bad_character_count", + "_buffer_length", + "_buffer_last_char", + "_buffer_last_char_accentuated", + "_buffer_accent_count", + "_buffer_glyph_count", + "_buffer_upper_count", + ) + + def __init__(self) -> None: + self._word_count: int = 0 + self._bad_word_count: int = 0 + self._foreign_long_count: int = 0 + + self._is_current_word_bad: bool = False + self._foreign_long_watch: bool = False + + self._character_count: int = 0 + self._bad_character_count: int = 0 + + self._buffer_length: int = 0 + self._buffer_last_char: str | None = None + self._buffer_last_char_accentuated: bool = False + self._buffer_accent_count: int = 0 + self._buffer_glyph_count: int = 0 + self._buffer_upper_count: int = 0 + + def feed_info(self, character: str, info: CharInfo) -> None: + """Optimized feed using pre-computed character info.""" + if info.alpha: + self._buffer_length += 1 + self._buffer_last_char = character + + if info.upper: + self._buffer_upper_count += 1 + + self._buffer_last_char_accentuated = info.accentuated + + if info.accentuated: + self._buffer_accent_count += 1 + if ( + not self._foreign_long_watch + and (not info.latin or info.accentuated) + and not info.is_glyph + ): + self._foreign_long_watch = True + if info.is_glyph: + self._buffer_glyph_count += 1 + return + if not self._buffer_length: + return + if info.space or info.punct or is_separator(character): + self._word_count += 1 + buffer_length: int = self._buffer_length + + self._character_count += buffer_length + + if buffer_length >= 4: + if self._buffer_accent_count / buffer_length >= 0.5: + self._is_current_word_bad = True + elif ( + self._buffer_last_char_accentuated + and self._buffer_last_char.isupper() # type: ignore[union-attr] + and self._buffer_upper_count != buffer_length + ): + self._foreign_long_count += 1 + self._is_current_word_bad = True + elif self._buffer_glyph_count == 1: + self._is_current_word_bad = True + self._foreign_long_count += 1 + if buffer_length >= 24 and self._foreign_long_watch: + probable_camel_cased: bool = ( + self._buffer_upper_count > 0 + and self._buffer_upper_count / buffer_length <= 0.3 + ) + + if not probable_camel_cased: + self._foreign_long_count += 1 + self._is_current_word_bad = True + + if self._is_current_word_bad: + self._bad_word_count += 1 + self._bad_character_count += buffer_length + self._is_current_word_bad = False + + self._foreign_long_watch = False + self._buffer_length = 0 + self._buffer_last_char = None + self._buffer_last_char_accentuated = False + self._buffer_accent_count = 0 + self._buffer_glyph_count = 0 + self._buffer_upper_count = 0 + elif ( + character not in {"<", ">", "-", "=", "~", "|", "_"} + and not info.digit + and info.sym + ): + self._is_current_word_bad = True + self._buffer_length += 1 + self._buffer_last_char = character + self._buffer_last_char_accentuated = False + + def reset(self) -> None: # Abstract + self._buffer_length = 0 + self._buffer_last_char = None + self._buffer_last_char_accentuated = False + self._is_current_word_bad = False + self._foreign_long_watch = False + self._bad_word_count = 0 + self._word_count = 0 + self._character_count = 0 + self._bad_character_count = 0 + self._foreign_long_count = 0 + self._buffer_accent_count = 0 + self._buffer_glyph_count = 0 + self._buffer_upper_count = 0 + + @property + def ratio(self) -> float: + if self._word_count <= 10 and self._foreign_long_count == 0: + return 0.0 + + return self._bad_character_count / self._character_count + + +@final +class CjkUncommonPlugin(MessDetectorPlugin): + """ + Detect messy CJK text that probably means nothing. + """ + + __slots__ = ("_character_count", "_uncommon_count") + + def __init__(self) -> None: + self._character_count: int = 0 + self._uncommon_count: int = 0 + + def feed_info(self, character: str, info: CharInfo) -> None: + """Optimized feed using pre-computed character info.""" + self._character_count += 1 + + if character not in COMMON_CJK_CHARACTERS: + self._uncommon_count += 1 + + def reset(self) -> None: # Abstract + self._character_count = 0 + self._uncommon_count = 0 + + @property + def ratio(self) -> float: + if self._character_count < 8: + return 0.0 + + uncommon_form_usage: float = self._uncommon_count / self._character_count + + # we can be pretty sure it's garbage when uncommon characters are widely + # used. otherwise it could just be traditional chinese for example. + return uncommon_form_usage / 10 if uncommon_form_usage > 0.5 else 0.0 + + +@final +class ArchaicUpperLowerPlugin(MessDetectorPlugin): + __slots__ = ( + "_buf", + "_character_count_since_last_sep", + "_successive_upper_lower_count", + "_successive_upper_lower_count_final", + "_character_count", + "_last_alpha_seen", + "_last_alpha_seen_upper", + "_last_alpha_seen_lower", + "_current_ascii_only", + ) + + def __init__(self) -> None: + self._buf: bool = False + + self._character_count_since_last_sep: int = 0 + + self._successive_upper_lower_count: int = 0 + self._successive_upper_lower_count_final: int = 0 + + self._character_count: int = 0 + + self._last_alpha_seen: str | None = None + self._last_alpha_seen_upper: bool = False + self._last_alpha_seen_lower: bool = False + self._current_ascii_only: bool = True + + def feed_info(self, character: str, info: CharInfo) -> None: + """Optimized feed using pre-computed character info.""" + is_concerned: bool = info.alpha and info.case_variable + chunk_sep: bool = not is_concerned + + if chunk_sep and self._character_count_since_last_sep > 0: + if ( + self._character_count_since_last_sep <= 64 + and not info.digit + and not self._current_ascii_only + ): + self._successive_upper_lower_count_final += ( + self._successive_upper_lower_count + ) + + self._successive_upper_lower_count = 0 + self._character_count_since_last_sep = 0 + self._last_alpha_seen = None + self._buf = False + self._character_count += 1 + self._current_ascii_only = True + + return + + if self._current_ascii_only and not info.is_ascii: + self._current_ascii_only = False + + if self._last_alpha_seen is not None: + if (info.upper and self._last_alpha_seen_lower) or ( + info.lower and self._last_alpha_seen_upper + ): + if self._buf: + self._successive_upper_lower_count += 2 + self._buf = False + else: + self._buf = True + else: + self._buf = False + + self._character_count += 1 + self._character_count_since_last_sep += 1 + self._last_alpha_seen = character + self._last_alpha_seen_upper = info.upper + self._last_alpha_seen_lower = info.lower + + def reset(self) -> None: # Abstract + self._character_count = 0 + self._character_count_since_last_sep = 0 + self._successive_upper_lower_count = 0 + self._successive_upper_lower_count_final = 0 + self._last_alpha_seen = None + self._last_alpha_seen_upper = False + self._last_alpha_seen_lower = False + self._buf = False + self._current_ascii_only = True + + @property + def ratio(self) -> float: + if self._character_count == 0: # Defensive: + return 0.0 + + return self._successive_upper_lower_count_final / self._character_count + + +@final +class ArabicIsolatedFormPlugin(MessDetectorPlugin): + __slots__ = ("_character_count", "_isolated_form_count") + + def __init__(self) -> None: + self._character_count: int = 0 + self._isolated_form_count: int = 0 + + def reset(self) -> None: # Abstract + self._character_count = 0 + self._isolated_form_count = 0 + + def feed_info(self, character: str, info: CharInfo) -> None: + """Optimized feed using pre-computed character info.""" + self._character_count += 1 + + if info.flags & _ARABIC_ISOLATED_FORM: + self._isolated_form_count += 1 + + @property + def ratio(self) -> float: + if self._character_count < 8: + return 0.0 + + isolated_form_usage: float = self._isolated_form_count / self._character_count + + return isolated_form_usage + + +@lru_cache(maxsize=1024) +def is_suspiciously_successive_range( + unicode_range_a: str | None, unicode_range_b: str | None +) -> bool: + """ + Determine if two Unicode range seen next to each other can be considered as suspicious. + """ + if unicode_range_a is None or unicode_range_b is None: + return True + + if unicode_range_a == unicode_range_b: + return False + + if "Latin" in unicode_range_a and "Latin" in unicode_range_b: + return False + + if "Emoticons" in unicode_range_a or "Emoticons" in unicode_range_b: + return False + + # Latin characters can be accompanied with a combining diacritical mark + # eg. Vietnamese. + if ("Latin" in unicode_range_a or "Latin" in unicode_range_b) and ( + "Combining" in unicode_range_a or "Combining" in unicode_range_b + ): + return False + + keywords_range_a, keywords_range_b = ( + unicode_range_a.split(" "), + unicode_range_b.split(" "), + ) + + for el in keywords_range_a: + if el in UNICODE_SECONDARY_RANGE_KEYWORD: + continue + if el in keywords_range_b: + return False + + # Japanese Exception + range_a_jp_chars, range_b_jp_chars = ( + unicode_range_a + in ( + "Hiragana", + "Katakana", + ), + unicode_range_b in ("Hiragana", "Katakana"), + ) + if (range_a_jp_chars or range_b_jp_chars) and ( + "CJK" in unicode_range_a or "CJK" in unicode_range_b + ): + return False + if range_a_jp_chars and range_b_jp_chars: + return False + + if "Hangul" in unicode_range_a or "Hangul" in unicode_range_b: + if "CJK" in unicode_range_a or "CJK" in unicode_range_b: + return False + if unicode_range_a == "Basic Latin" or unicode_range_b == "Basic Latin": + return False + + # Chinese/Japanese use dedicated range for punctuation and/or separators. + if ("CJK" in unicode_range_a or "CJK" in unicode_range_b) or ( + unicode_range_a in ["Katakana", "Hiragana"] + and unicode_range_b in ["Katakana", "Hiragana"] + ): + if "Punctuation" in unicode_range_a or "Punctuation" in unicode_range_b: + return False + if "Forms" in unicode_range_a or "Forms" in unicode_range_b: + return False + if unicode_range_a == "Basic Latin" or unicode_range_b == "Basic Latin": + return False + + return True + + +@lru_cache(maxsize=2048) +def mess_ratio( + decoded_sequence: str, maximum_threshold: float = 0.2, debug: bool = False +) -> float: + """ + Compute a mess ratio given a decoded bytes sequence. The maximum threshold does stop the computation earlier. + """ + + seq_len: int = len(decoded_sequence) + + if seq_len < 511: + step: int = 32 + elif seq_len < 1024: + step = 64 + else: + step = 128 + + # Create each detector as a named local variable (unrolled from the generic loop). + # This eliminates per-character iteration over the detector list and + # per-character eligible() virtual dispatch, while keeping every plugin class + # intact and fully readable. + d_sp: TooManySymbolOrPunctuationPlugin = TooManySymbolOrPunctuationPlugin() + d_ta: TooManyAccentuatedPlugin = TooManyAccentuatedPlugin() + d_up: UnprintablePlugin = UnprintablePlugin() + d_sda: SuspiciousDuplicateAccentPlugin = SuspiciousDuplicateAccentPlugin() + d_sr: SuspiciousRange = SuspiciousRange() + d_sw: SuperWeirdWordPlugin = SuperWeirdWordPlugin() + d_cu: CjkUncommonPlugin = CjkUncommonPlugin() + d_au: ArchaicUpperLowerPlugin = ArchaicUpperLowerPlugin() + d_ai: ArabicIsolatedFormPlugin = ArabicIsolatedFormPlugin() + + # Local references for feed_info methods called in the hot loop. + d_sp_feed = d_sp.feed_info + d_ta_feed = d_ta.feed_info + d_up_feed = d_up.feed_info + d_sda_feed = d_sda.feed_info + d_sr_feed = d_sr.feed_info + d_sw_feed = d_sw.feed_info + d_cu_feed = d_cu.feed_info + d_au_feed = d_au.feed_info + d_ai_feed = d_ai.feed_info + + # Single reusable CharInfo object (avoids per-character allocation). + info: CharInfo = CharInfo() + info_update = info.update + + mean_mess_ratio: float + + for block_start in range(0, seq_len, step): + for character in decoded_sequence[block_start : block_start + step]: + # Pre-compute all character properties once (shared across all plugins). + info_update(character) + + # Detectors with eligible() == always True + d_up_feed(character, info) + d_sw_feed(character, info) + d_au_feed(character, info) + + # Detectors with eligible() == isprintable + if info.printable: + d_sp_feed(character, info) + d_sr_feed(character, info) + + # Detectors with eligible() == isalpha + if info.alpha: + d_ta_feed(character, info) + # SuspiciousDuplicateAccent: isalpha() and is_latin() + if info.latin: + d_sda_feed(character, info) + # CjkUncommon: is_cjk() + if info.is_cjk: + d_cu_feed(character, info) + # ArabicIsolatedForm: is_arabic() + if info.is_arabic: + d_ai_feed(character, info) + + mean_mess_ratio = ( + d_sp.ratio + + d_ta.ratio + + d_up.ratio + + d_sda.ratio + + d_sr.ratio + + d_sw.ratio + + d_cu.ratio + + d_au.ratio + + d_ai.ratio + ) + + if mean_mess_ratio >= maximum_threshold: + break + else: + # Flush last word buffer in SuperWeirdWordPlugin via trailing newline. + info_update("\n") + d_sw_feed("\n", info) + d_au_feed("\n", info) + d_up_feed("\n", info) + + mean_mess_ratio = ( + d_sp.ratio + + d_ta.ratio + + d_up.ratio + + d_sda.ratio + + d_sr.ratio + + d_sw.ratio + + d_cu.ratio + + d_au.ratio + + d_ai.ratio + ) + + if debug: # Defensive: + logger = getLogger("charset_normalizer") + + logger.log( + TRACE, + "Mess-detector extended-analysis start. " + f"intermediary_mean_mess_ratio_calc={step} mean_mess_ratio={mean_mess_ratio} " + f"maximum_threshold={maximum_threshold}", + ) + + if seq_len > 16: + logger.log(TRACE, f"Starting with: {decoded_sequence[:16]}") + logger.log(TRACE, f"Ending with: {decoded_sequence[-16::]}") + + for dt in [d_sp, d_ta, d_up, d_sda, d_sr, d_sw, d_cu, d_au, d_ai]: + logger.log(TRACE, f"{dt.__class__}: {dt.ratio}") + + return round(mean_mess_ratio, 3) diff --git a/charset_normalizer/models.py b/charset_normalizer/models.py new file mode 100644 index 0000000000000000000000000000000000000000..30e8a163e2ef7b801a2ce013f0aee41e75701783 --- /dev/null +++ b/charset_normalizer/models.py @@ -0,0 +1,359 @@ +from __future__ import annotations + +from encodings.aliases import aliases +from json import dumps +from re import sub +from typing import Any, Iterator, List, Tuple + +from .constant import RE_POSSIBLE_ENCODING_INDICATION, TOO_BIG_SEQUENCE +from .utils import iana_name, is_multi_byte_encoding, unicode_range + + +class CharsetMatch: + def __init__( + self, + payload: bytes | bytearray, + guessed_encoding: str, + mean_mess_ratio: float, + has_sig_or_bom: bool, + languages: CoherenceMatches, + decoded_payload: str | None = None, + preemptive_declaration: str | None = None, + ): + self._payload: bytes | bytearray = payload + + self._encoding: str = guessed_encoding + self._mean_mess_ratio: float = mean_mess_ratio + self._languages: CoherenceMatches = languages + self._has_sig_or_bom: bool = has_sig_or_bom + self._unicode_ranges: list[str] | None = None + + self._leaves: list[CharsetMatch] = [] + self._mean_coherence_ratio: float = 0.0 + + self._output_payload: bytes | None = None + self._output_encoding: str | None = None + + self._string: str | None = decoded_payload + + self._preemptive_declaration: str | None = preemptive_declaration + + def __eq__(self, other: object) -> bool: + if not isinstance(other, CharsetMatch): + if isinstance(other, str): + return iana_name(other) == self.encoding + return False + return self.encoding == other.encoding and self.fingerprint == other.fingerprint + + def __lt__(self, other: object) -> bool: + """ + Implemented to make sorted available upon CharsetMatches items. + """ + if not isinstance(other, CharsetMatch): + raise ValueError + + chaos_difference: float = abs(self.chaos - other.chaos) + coherence_difference: float = abs(self.coherence - other.coherence) + + # Below 0.5% difference --> Use Coherence + if chaos_difference < 0.005 and coherence_difference > 0.02: + return self.coherence > other.coherence + elif chaos_difference < 0.005 and coherence_difference <= 0.02: + # When having a difficult decision, use the result that decoded as many multi-byte as possible. + # preserve RAM usage! + if len(self._payload) >= TOO_BIG_SEQUENCE: + return self.chaos < other.chaos + return self.multi_byte_usage > other.multi_byte_usage + + return self.chaos < other.chaos + + @property + def multi_byte_usage(self) -> float: + return 1.0 - (len(str(self)) / len(self.raw)) + + def __str__(self) -> str: + # Lazy Str Loading + if self._string is None: + self._string = str(self._payload, self._encoding, "strict") + return self._string + + def __repr__(self) -> str: + return f"" + + def add_submatch(self, other: CharsetMatch) -> None: + if not isinstance(other, CharsetMatch) or other == self: + raise ValueError( + "Unable to add instance <{}> as a submatch of a CharsetMatch".format( + other.__class__ + ) + ) + + other._string = None # Unload RAM usage; dirty trick. + self._leaves.append(other) + + @property + def encoding(self) -> str: + return self._encoding + + @property + def encoding_aliases(self) -> list[str]: + """ + Encoding name are known by many name, using this could help when searching for IBM855 when it's listed as CP855. + """ + also_known_as: list[str] = [] + for u, p in aliases.items(): + if self.encoding == u: + also_known_as.append(p) + elif self.encoding == p: + also_known_as.append(u) + return also_known_as + + @property + def bom(self) -> bool: + return self._has_sig_or_bom + + @property + def byte_order_mark(self) -> bool: + return self._has_sig_or_bom + + @property + def languages(self) -> list[str]: + """ + Return the complete list of possible languages found in decoded sequence. + Usually not really useful. Returned list may be empty even if 'language' property return something != 'Unknown'. + """ + return [e[0] for e in self._languages] + + @property + def language(self) -> str: + """ + Most probable language found in decoded sequence. If none were detected or inferred, the property will return + "Unknown". + """ + if not self._languages: + # Trying to infer the language based on the given encoding + # Its either English or we should not pronounce ourselves in certain cases. + if "ascii" in self.could_be_from_charset: + return "English" + + # doing it there to avoid circular import + from charset_normalizer.cd import encoding_languages, mb_encoding_languages + + languages = ( + mb_encoding_languages(self.encoding) + if is_multi_byte_encoding(self.encoding) + else encoding_languages(self.encoding) + ) + + if len(languages) == 0 or "Latin Based" in languages: + return "Unknown" + + return languages[0] + + return self._languages[0][0] + + @property + def chaos(self) -> float: + return self._mean_mess_ratio + + @property + def coherence(self) -> float: + if not self._languages: + return 0.0 + return self._languages[0][1] + + @property + def percent_chaos(self) -> float: + return round(self.chaos * 100, ndigits=3) + + @property + def percent_coherence(self) -> float: + return round(self.coherence * 100, ndigits=3) + + @property + def raw(self) -> bytes | bytearray: + """ + Original untouched bytes. + """ + return self._payload + + @property + def submatch(self) -> list[CharsetMatch]: + return self._leaves + + @property + def has_submatch(self) -> bool: + return len(self._leaves) > 0 + + @property + def alphabets(self) -> list[str]: + if self._unicode_ranges is not None: + return self._unicode_ranges + # list detected ranges + detected_ranges: list[str | None] = [unicode_range(char) for char in str(self)] + # filter and sort + self._unicode_ranges = sorted(list({r for r in detected_ranges if r})) + return self._unicode_ranges + + @property + def could_be_from_charset(self) -> list[str]: + """ + The complete list of encoding that output the exact SAME str result and therefore could be the originating + encoding. + This list does include the encoding available in property 'encoding'. + """ + return [self._encoding] + [m.encoding for m in self._leaves] + + def output(self, encoding: str = "utf_8") -> bytes: + """ + Method to get re-encoded bytes payload using given target encoding. Default to UTF-8. + Any errors will be simply ignored by the encoder NOT replaced. + """ + if self._output_encoding is None or self._output_encoding != encoding: + self._output_encoding = encoding + decoded_string = str(self) + if ( + self._preemptive_declaration is not None + and self._preemptive_declaration.lower() + not in ["utf-8", "utf8", "utf_8"] + ): + patched_header = sub( + RE_POSSIBLE_ENCODING_INDICATION, + lambda m: m.string[m.span()[0] : m.span()[1]].replace( + m.groups()[0], + iana_name(self._output_encoding).replace("_", "-"), # type: ignore[arg-type] + ), + decoded_string[:8192], + count=1, + ) + + decoded_string = patched_header + decoded_string[8192:] + + self._output_payload = decoded_string.encode(encoding, "replace") + + return self._output_payload # type: ignore + + @property + def fingerprint(self) -> int: + """ + Retrieve a hash fingerprint of the decoded payload, used for deduplication. + """ + return hash(str(self)) + + +class CharsetMatches: + """ + Container with every CharsetMatch items ordered by default from most probable to the less one. + Act like a list(iterable) but does not implements all related methods. + """ + + def __init__(self, results: list[CharsetMatch] | None = None): + self._results: list[CharsetMatch] = sorted(results) if results else [] + + def __iter__(self) -> Iterator[CharsetMatch]: + yield from self._results + + def __getitem__(self, item: int | str) -> CharsetMatch: + """ + Retrieve a single item either by its position or encoding name (alias may be used here). + Raise KeyError upon invalid index or encoding not present in results. + """ + if isinstance(item, int): + return self._results[item] + if isinstance(item, str): + item = iana_name(item, False) + for result in self._results: + if item in result.could_be_from_charset: + return result + raise KeyError + + def __len__(self) -> int: + return len(self._results) + + def __bool__(self) -> bool: + return len(self._results) > 0 + + def append(self, item: CharsetMatch) -> None: + """ + Insert a single match. Will be inserted accordingly to preserve sort. + Can be inserted as a submatch. + """ + if not isinstance(item, CharsetMatch): + raise ValueError( + "Cannot append instance '{}' to CharsetMatches".format( + str(item.__class__) + ) + ) + # We should disable the submatch factoring when the input file is too heavy (conserve RAM usage) + if len(item.raw) < TOO_BIG_SEQUENCE: + for match in self._results: + if match.fingerprint == item.fingerprint and match.chaos == item.chaos: + match.add_submatch(item) + return + self._results.append(item) + self._results = sorted(self._results) + + def best(self) -> CharsetMatch | None: + """ + Simply return the first match. Strict equivalent to matches[0]. + """ + if not self._results: + return None + return self._results[0] + + def first(self) -> CharsetMatch | None: + """ + Redundant method, call the method best(). Kept for BC reasons. + """ + return self.best() + + +CoherenceMatch = Tuple[str, float] +CoherenceMatches = List[CoherenceMatch] + + +class CliDetectionResult: + def __init__( + self, + path: str, + encoding: str | None, + encoding_aliases: list[str], + alternative_encodings: list[str], + language: str, + alphabets: list[str], + has_sig_or_bom: bool, + chaos: float, + coherence: float, + unicode_path: str | None, + is_preferred: bool, + ): + self.path: str = path + self.unicode_path: str | None = unicode_path + self.encoding: str | None = encoding + self.encoding_aliases: list[str] = encoding_aliases + self.alternative_encodings: list[str] = alternative_encodings + self.language: str = language + self.alphabets: list[str] = alphabets + self.has_sig_or_bom: bool = has_sig_or_bom + self.chaos: float = chaos + self.coherence: float = coherence + self.is_preferred: bool = is_preferred + + @property + def __dict__(self) -> dict[str, Any]: # type: ignore + return { + "path": self.path, + "encoding": self.encoding, + "encoding_aliases": self.encoding_aliases, + "alternative_encodings": self.alternative_encodings, + "language": self.language, + "alphabets": self.alphabets, + "has_sig_or_bom": self.has_sig_or_bom, + "chaos": self.chaos, + "coherence": self.coherence, + "unicode_path": self.unicode_path, + "is_preferred": self.is_preferred, + } + + def to_json(self) -> str: + return dumps(self.__dict__, ensure_ascii=True, indent=4) diff --git a/charset_normalizer/py.typed b/charset_normalizer/py.typed new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/charset_normalizer/utils.py b/charset_normalizer/utils.py new file mode 100644 index 0000000000000000000000000000000000000000..0f529b59cfdf6f2b4f6aca39b439b2e35dd93d00 --- /dev/null +++ b/charset_normalizer/utils.py @@ -0,0 +1,422 @@ +from __future__ import annotations + +import importlib +import logging +import unicodedata +from bisect import bisect_right +from codecs import IncrementalDecoder +from encodings.aliases import aliases +from functools import lru_cache +from re import findall +from typing import Generator + +from _multibytecodec import ( # type: ignore[import-not-found,import] + MultibyteIncrementalDecoder, +) + +from .constant import ( + ENCODING_MARKS, + IANA_SUPPORTED_SIMILAR, + RE_POSSIBLE_ENCODING_INDICATION, + UNICODE_RANGES_COMBINED, + UNICODE_SECONDARY_RANGE_KEYWORD, + UTF8_MAXIMAL_ALLOCATION, + COMMON_CJK_CHARACTERS, + _LATIN, + _CJK, + _HANGUL, + _KATAKANA, + _HIRAGANA, + _THAI, + _ARABIC, + _ARABIC_ISOLATED_FORM, + _ACCENT_KEYWORDS, + _ACCENTUATED, +) + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def _character_flags(character: str) -> int: + """Compute all name-based classification flags with a single unicodedata.name() call.""" + try: + desc: str = unicodedata.name(character) + except ValueError: + return 0 + + flags: int = 0 + + if "LATIN" in desc: + flags |= _LATIN + if "CJK" in desc: + flags |= _CJK + if "HANGUL" in desc: + flags |= _HANGUL + if "KATAKANA" in desc: + flags |= _KATAKANA + if "HIRAGANA" in desc: + flags |= _HIRAGANA + if "THAI" in desc: + flags |= _THAI + if "ARABIC" in desc: + flags |= _ARABIC + if "ISOLATED FORM" in desc: + flags |= _ARABIC_ISOLATED_FORM + + for kw in _ACCENT_KEYWORDS: + if kw in desc: + flags |= _ACCENTUATED + break + + return flags + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_accentuated(character: str) -> bool: + return bool(_character_flags(character) & _ACCENTUATED) + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def remove_accent(character: str) -> str: + decomposed: str = unicodedata.decomposition(character) + if not decomposed: + return character + + codes: list[str] = decomposed.split(" ") + + return chr(int(codes[0], 16)) + + +# Pre-built sorted lookup table for O(log n) binary search in unicode_range(). +# Each entry is (range_start, range_end_exclusive, range_name). +_UNICODE_RANGES_SORTED: list[tuple[int, int, str]] = sorted( + (ord_range.start, ord_range.stop, name) + for name, ord_range in UNICODE_RANGES_COMBINED.items() +) +_UNICODE_RANGE_STARTS: list[int] = [e[0] for e in _UNICODE_RANGES_SORTED] + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def unicode_range(character: str) -> str | None: + """ + Retrieve the Unicode range official name from a single character. + """ + character_ord: int = ord(character) + + # Binary search: find the rightmost range whose start <= character_ord + idx = bisect_right(_UNICODE_RANGE_STARTS, character_ord) - 1 + if idx >= 0: + start, stop, name = _UNICODE_RANGES_SORTED[idx] + if character_ord < stop: + return name + + return None + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_latin(character: str) -> bool: + return bool(_character_flags(character) & _LATIN) + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_punctuation(character: str) -> bool: + character_category: str = unicodedata.category(character) + + if "P" in character_category: + return True + + character_range: str | None = unicode_range(character) + + if character_range is None: + return False + + return "Punctuation" in character_range + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_symbol(character: str) -> bool: + character_category: str = unicodedata.category(character) + + if "S" in character_category or "N" in character_category: + return True + + character_range: str | None = unicode_range(character) + + if character_range is None: + return False + + return "Forms" in character_range and character_category != "Lo" + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_emoticon(character: str) -> bool: + character_range: str | None = unicode_range(character) + + if character_range is None: + return False + + return "Emoticons" in character_range or "Pictographs" in character_range + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_separator(character: str) -> bool: + if character.isspace() or character in {"｜", "+", "<", ">"}: + return True + + character_category: str = unicodedata.category(character) + + return "Z" in character_category or character_category in {"Po", "Pd", "Pc"} + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_case_variable(character: str) -> bool: + return character.islower() != character.isupper() + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_cjk(character: str) -> bool: + return bool(_character_flags(character) & _CJK) + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_hiragana(character: str) -> bool: + return bool(_character_flags(character) & _HIRAGANA) + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_katakana(character: str) -> bool: + return bool(_character_flags(character) & _KATAKANA) + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_hangul(character: str) -> bool: + return bool(_character_flags(character) & _HANGUL) + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_thai(character: str) -> bool: + return bool(_character_flags(character) & _THAI) + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_arabic(character: str) -> bool: + return bool(_character_flags(character) & _ARABIC) + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_arabic_isolated_form(character: str) -> bool: + return bool(_character_flags(character) & _ARABIC_ISOLATED_FORM) + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_cjk_uncommon(character: str) -> bool: + return character not in COMMON_CJK_CHARACTERS + + +@lru_cache(maxsize=len(UNICODE_RANGES_COMBINED)) +def is_unicode_range_secondary(range_name: str) -> bool: + return any(keyword in range_name for keyword in UNICODE_SECONDARY_RANGE_KEYWORD) + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_unprintable(character: str) -> bool: + return ( + character.isspace() is False # includes \n \t \r \v + and character.isprintable() is False + and character != "\x1a" # Why? Its the ASCII substitute character. + and character != "\ufeff" # bug discovered in Python, + # Zero Width No-Break Space located in Arabic Presentation Forms-B, Unicode 1.1 not acknowledged as space. + ) + + +def any_specified_encoding( + sequence: bytes | bytearray, search_zone: int = 8192 +) -> str | None: + """ + Extract using ASCII-only decoder any specified encoding in the first n-bytes. + """ + if not isinstance(sequence, (bytes, bytearray)): + raise TypeError + + seq_len: int = len(sequence) + + results: list[str] = findall( + RE_POSSIBLE_ENCODING_INDICATION, + sequence[: min(seq_len, search_zone)].decode("ascii", errors="ignore"), + ) + + if len(results) == 0: + return None + + for specified_encoding in results: + specified_encoding = specified_encoding.lower().replace("-", "_") + + encoding_alias: str + encoding_iana: str + + for encoding_alias, encoding_iana in aliases.items(): + if encoding_alias == specified_encoding: + return encoding_iana + if encoding_iana == specified_encoding: + return encoding_iana + + return None + + +@lru_cache(maxsize=128) +def is_multi_byte_encoding(name: str) -> bool: + """ + Verify is a specific encoding is a multi byte one based on it IANA name + """ + return name in { + "utf_8", + "utf_8_sig", + "utf_16", + "utf_16_be", + "utf_16_le", + "utf_32", + "utf_32_le", + "utf_32_be", + "utf_7", + } or issubclass( + importlib.import_module(f"encodings.{name}").IncrementalDecoder, + MultibyteIncrementalDecoder, + ) + + +def identify_sig_or_bom(sequence: bytes | bytearray) -> tuple[str | None, bytes]: + """ + Identify and extract SIG/BOM in given sequence. + """ + + for iana_encoding in ENCODING_MARKS: + marks: bytes | list[bytes] = ENCODING_MARKS[iana_encoding] + + if isinstance(marks, bytes): + marks = [marks] + + for mark in marks: + if sequence.startswith(mark): + return iana_encoding, mark + + return None, b"" + + +def should_strip_sig_or_bom(iana_encoding: str) -> bool: + return iana_encoding not in {"utf_16", "utf_32"} + + +def iana_name(cp_name: str, strict: bool = True) -> str: + """Returns the Python normalized encoding name (Not the IANA official name).""" + cp_name = cp_name.lower().replace("-", "_") + + encoding_alias: str + encoding_iana: str + + for encoding_alias, encoding_iana in aliases.items(): + if cp_name in [encoding_alias, encoding_iana]: + return encoding_iana + + if strict: + raise ValueError(f"Unable to retrieve IANA for '{cp_name}'") + + return cp_name + + +def cp_similarity(iana_name_a: str, iana_name_b: str) -> float: + if is_multi_byte_encoding(iana_name_a) or is_multi_byte_encoding(iana_name_b): + return 0.0 + + decoder_a = importlib.import_module(f"encodings.{iana_name_a}").IncrementalDecoder + decoder_b = importlib.import_module(f"encodings.{iana_name_b}").IncrementalDecoder + + id_a: IncrementalDecoder = decoder_a(errors="ignore") + id_b: IncrementalDecoder = decoder_b(errors="ignore") + + character_match_count: int = 0 + + for i in range(256): + to_be_decoded: bytes = bytes([i]) + if id_a.decode(to_be_decoded) == id_b.decode(to_be_decoded): + character_match_count += 1 + + return character_match_count / 256 + + +def is_cp_similar(iana_name_a: str, iana_name_b: str) -> bool: + """ + Determine if two code page are at least 80% similar. IANA_SUPPORTED_SIMILAR dict was generated using + the function cp_similarity. + """ + return ( + iana_name_a in IANA_SUPPORTED_SIMILAR + and iana_name_b in IANA_SUPPORTED_SIMILAR[iana_name_a] + ) + + +def set_logging_handler( + name: str = "charset_normalizer", + level: int = logging.INFO, + format_string: str = "%(asctime)s | %(levelname)s | %(message)s", +) -> None: + logger = logging.getLogger(name) + logger.setLevel(level) + + handler = logging.StreamHandler() + handler.setFormatter(logging.Formatter(format_string)) + logger.addHandler(handler) + + +def cut_sequence_chunks( + sequences: bytes | bytearray, + encoding_iana: str, + offsets: range, + chunk_size: int, + bom_or_sig_available: bool, + strip_sig_or_bom: bool, + sig_payload: bytes, + is_multi_byte_decoder: bool, + decoded_payload: str | None = None, +) -> Generator[str, None, None]: + if decoded_payload and is_multi_byte_decoder is False: + for i in offsets: + chunk = decoded_payload[i : i + chunk_size] + if not chunk: + break + yield chunk + else: + for i in offsets: + chunk_end = i + chunk_size + if chunk_end > len(sequences) + 8: + continue + + cut_sequence = sequences[i : i + chunk_size] + + if bom_or_sig_available and strip_sig_or_bom is False: + cut_sequence = sig_payload + cut_sequence + + chunk = cut_sequence.decode( + encoding_iana, + errors="ignore" if is_multi_byte_decoder else "strict", + ) + + # multi-byte bad cutting detector and adjustment + # not the cleanest way to perform that fix but clever enough for now. + if is_multi_byte_decoder and i > 0: + chunk_partial_size_chk: int = min(chunk_size, 16) + + if ( + decoded_payload + and chunk[:chunk_partial_size_chk] not in decoded_payload + ): + for j in range(i, i - 4, -1): + cut_sequence = sequences[j:chunk_end] + + if bom_or_sig_available and strip_sig_or_bom is False: + cut_sequence = sig_payload + cut_sequence + + chunk = cut_sequence.decode(encoding_iana, errors="ignore") + + if chunk[:chunk_partial_size_chk] in decoded_payload: + break + + yield chunk diff --git a/charset_normalizer/version.py b/charset_normalizer/version.py new file mode 100644 index 0000000000000000000000000000000000000000..a80346fc7ef899107a55de8550da98085fb4b122 --- /dev/null +++ b/charset_normalizer/version.py @@ -0,0 +1,8 @@ +""" +Expose version +""" + +from __future__ import annotations + +__version__ = "3.4.6" +VERSION = __version__.split(".") diff --git a/cut_cross_entropy-25.1.1.dist-info/INSTALLER b/cut_cross_entropy-25.1.1.dist-info/INSTALLER new file mode 100644 index 0000000000000000000000000000000000000000..5c69047b2eb8235994febeeae1da4a82365a240a --- /dev/null +++ b/cut_cross_entropy-25.1.1.dist-info/INSTALLER @@ -0,0 +1 @@ +uv \ No newline at end of file diff --git a/cut_cross_entropy-25.1.1.dist-info/LICENSE b/cut_cross_entropy-25.1.1.dist-info/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..4c5d7933fc92f85a1dcb32666f7270ec27804f10 --- /dev/null +++ b/cut_cross_entropy-25.1.1.dist-info/LICENSE @@ -0,0 +1,47 @@ +Copyright (C) 2024 Apple Inc. All Rights Reserved. + +IMPORTANT: This Apple software is supplied to you by Apple +Inc. ("Apple") in consideration of your agreement to the following +terms, and your use, installation, modification or redistribution of +this Apple software constitutes acceptance of these terms. If you do +not agree with these terms, please do not use, install, modify or +redistribute this Apple software. + +In consideration of your agreement to abide by the following terms, and +subject to these terms, Apple grants you a personal, non-exclusive +license, under Apple's copyrights in this original Apple software (the +"Apple Software"), to use, reproduce, modify and redistribute the Apple +Software, with or without modifications, in source and/or binary forms; +provided that if you redistribute the Apple Software in its entirety and +without modifications, you must retain this notice and the following +text and disclaimers in all such redistributions of the Apple Software. +Neither the name, trademarks, service marks or logos of Apple Inc. may +be used to endorse or promote products derived from the Apple Software +without specific prior written permission from Apple. Except as +expressly stated in this notice, no other rights or licenses, express or +implied, are granted by Apple herein, including but not limited to any +patent rights that may be infringed by your derivative works or by other +works in which the Apple Software may be incorporated. + +The Apple Software is provided by Apple on an "AS IS" basis. APPLE +MAKES NO WARRANTIES, EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION +THE IMPLIED WARRANTIES OF NON-INFRINGEMENT, MERCHANTABILITY AND FITNESS +FOR A PARTICULAR PURPOSE, REGARDING THE APPLE SOFTWARE OR ITS USE AND +OPERATION ALONE OR IN COMBINATION WITH YOUR PRODUCTS. + +IN NO EVENT SHALL APPLE BE LIABLE FOR ANY SPECIAL, INDIRECT, INCIDENTAL +OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF +SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS +INTERRUPTION) ARISING IN ANY WAY OUT OF THE USE, REPRODUCTION, +MODIFICATION AND/OR DISTRIBUTION OF THE APPLE SOFTWARE, HOWEVER CAUSED +AND WHETHER UNDER THEORY OF CONTRACT, TORT (INCLUDING NEGLIGENCE), +STRICT LIABILITY OR OTHERWISE, EVEN IF APPLE HAS BEEN ADVISED OF THE +POSSIBILITY OF SUCH DAMAGE. + + +------------------------------------------------------------------------------- +SOFTWARE DISTRIBUTED WITH CUT CROSS ENTROPY: + +The Cut Cross Entropy software includes a number of subcomponents with separate +copyright notices and license terms - please see the file ACKNOWLEDGEMENTS.md. +------------------------------------------------------------------------------- diff --git a/cut_cross_entropy-25.1.1.dist-info/METADATA b/cut_cross_entropy-25.1.1.dist-info/METADATA new file mode 100644 index 0000000000000000000000000000000000000000..c401d3aa9364f22a7adc95d9b40e9f2eb17ca9ad --- /dev/null +++ b/cut_cross_entropy-25.1.1.dist-info/METADATA @@ -0,0 +1,244 @@ +Metadata-Version: 2.1 +Name: cut-cross-entropy +Version: 25.1.1 +Summary: Code for cut cross entropy, a memory efficient implementation of linear-cross-entropy loss. +Requires-Python: >=3.10 +Description-Content-Type: text/markdown +License-File: LICENSE +Requires-Dist: torch +Requires-Dist: triton; platform_system == "Linux" +Provides-Extra: test +Requires-Dist: pytest; extra == "test" +Provides-Extra: transformers +Requires-Dist: transformers>=4.44.2; extra == "transformers" +Provides-Extra: all +Requires-Dist: cut-cross-entropy[transformers]; extra == "all" +Requires-Dist: deepspeed>=0.15.1; platform_system != "Darwin" and extra == "all" +Requires-Dist: accelerate>=0.34.2; extra == "all" +Requires-Dist: datasets>=3.1.0; extra == "all" +Requires-Dist: huggingface_hub>=0.26.2; extra == "all" +Requires-Dist: pandas; extra == "all" +Requires-Dist: fire; extra == "all" +Requires-Dist: tqdm; extra == "all" +Provides-Extra: dev +Requires-Dist: cut-cross-entropy[all,test]; extra == "dev" +Requires-Dist: build; extra == "dev" +Requires-Dist: twine; extra == "dev" +Requires-Dist: pre-commit; extra == "dev" + +## Cut Your Losses in Large-Vocabulary Language Models + +This software project accompanies the research paper: +**[Cut Your Losses in Large-Vocabulary Language Models](https://arxiv.org/abs/2411.09009)**, +*Erik Wijmans, Brody Huval, Alexander Hertzberg, Vladlen Koltun, and Philipp Krähenbühl*. + +![](assets/cce_figure.png) + +As language models grow ever larger, so do their vocabularies. This has shifted the memory footprint of LLMs during training disproportionately to one single layer: the cross-entropy in the loss computation. Cross-entropy builds up a logit matrix with entries for each pair of input tokens and vocabulary items and, for small models, consumes an order of magnitude more memory than the rest of the LLM combined. We propose Cut Cross-Entropy (CCE), a method that computes the cross-entropy loss without materializing the logits for all tokens into global memory. Rather, CCE only computes the logit for the correct token and evaluates the log-sum-exp over all logits on the fly. We implement a custom kernel that performs the matrix multiplications and the log-sum-exp reduction over the vocabulary in flash memory, making global memory consumption for the cross-entropy computation negligible. This has a dramatic effect. Taking the Gemma 2 (2B) model as an example, CCE reduces the memory footprint of the loss computation from 24 GB to 1 MB, and the total training-time memory consumption of the classifier head from 28 GB to 1 GB. To improve the throughput of CCE, we leverage the inherent sparsity of softmax and propose to skip elements of the gradient computation that have a negligible (i.e., below numerical precision) contribution to the gradient. Experiments demonstrate that the dramatic reduction in memory consumption is accomplished without sacrificing training speed or convergence. + +## Getting started + +**Requirements** + +1. Python 3.10+ +2. PyTorch 2.4+ +3. Triton 3.0+ +4. Ampere (or newer) GPU + + +**Note:** For operating systems that are not supported by Triton (e.g., MacOS), we include a highly optimized version of +linear-cross-entropy using `torch.compile`. This implementation will be set to the default on MacOS. + +### Basic usage + +**Installation** +```bash +pip install "cut-cross-entropy @ git+https://github.com/apple/ml-cross-entropy.git" +``` + +**Usage** + +```python +from cut_cross_entropy import linear_cross_entropy + +embeddings = model.compute_embedding(inputs) +classifier = model.get_classifier_weights() + +loss = linear_cross_entropy(embeddings, classifier, labels) +``` + +In causal language modeling, it is common that the model embeddings and labels need to be shifted +such that the model predicts the next token. + +```python +from cut_cross_entropy import linear_cross_entropy + +embeddings = model.compute_embedding(inputs) +classifier = model.get_classifier_weights() + +shift_embeddings = embeddings[..., :-1, :].flatten(0, -2) +shift_labels = labels[..., 1:] + +manual_shift_loss = linear_cross_entropy(shift_embeddings, classifier, shift_labels) +``` + +Instead, pass `shift=True` to perform this computation without allocating the shift_embeddings matrix. +```python +from cut_cross_entropy import linear_cross_entropy + +embeddings = model.compute_embedding(inputs) +classifier = model.get_classifier_weights() + +# This is the same as manual_shift_loss above +auto_shift_loss = linear_cross_entropy(embeddings, classifier, labels, shift=True) +``` + +We also provide a highly optimized implementation of linear-cross-entropy loss using `torch.compile`. +This is a good option +for scenarios where speed is the primary goal and the model has a relatively small vocabulary compared to its +hidden dimension (when |V| >> D, `cce` will both save memory _and_ be faster). +This option also works on the CPU and older GPUs, making it useful for testing. + +```python +from cut_cross_entropy import linear_cross_entropy + +embeddings = model.compute_embedding(inputs) +classifier = model.get_classifier_weights() + +loss = linear_cross_entropy(embeddings, classifier, labels, ..., impl="torch_compile") +``` + +### Transformers Integration + +**Installation** + +Install cut-cross-entropy with transformers dependencies +```bash +pip install "cut-cross-entropy[transformers] @ git+https://github.com/apple/ml-cross-entropy.git" +``` + +**Usage** + +If you are using transformers, you can patch transformers to use CCE directly. Note that +logits will no longer be returned (`None` will be returned instead). +```python +from cut_cross_entropy.transformers import cce_patch + +cce_patch("llama") + +# or + +model = ... +model = cce_patch(model) +``` + +We currently support the Llama, Phi3, Mistral, and Gemma2 families of models. + +`cce_patch` takes two options. The first is the linear-cross-entropy implementation to use. Currently `"cce"` or `"torch_compile"`. + +The second +is the loss reduction. We support `"mean"`, `"sum"`, and `"none"`, that mirror their PyTorch counterpart. +`"mean"` is the default and what the transformers trainer API expects. +However, +`"none"` in particular can enable for efficient computation of quantities based on the loss. + +For example, the following efficiently computes the perplexity of a batch of sequences: +```python +import transformers + +from cut_cross_entropy.transformers import cce_patch + + +model = transformers.AutoModelForCausalLM.from_pretrained(...) + +model = cce_patch(model, reduction="none") + +labels = input_ids.clone() +labels[~attention_mask] = -100 # -100 is the ignore index for PyTorch and CCE. + +outputs = model(input_ids, attention_mask, labels=labels) + +loss = outputs[0] # A (B, T - 1) tensor because reduction="none". T - 1 because the first input token has +# no loss. + +ppl = torch.exp( + # [:, 1:] because the first token has no loss + loss.sum(1) / (labels[:, 1:] != -100).count_nonzero(dim=1) +).mean() # Average perplexity over the batch +``` + + + +### Training and reproducing the benchmark results + +We provide a training in `training/train.py`. + +**Installation** +```bash +pip install "cut-cross-entropy[all] @ git+https://github.com/apple/ml-cross-entropy.git" +``` + +**Training** + +Use `scripts/train.sh` to train a full model. + +**Benchmarking** + +The benchmark script can be run via `python -m benchmark`. + +Expected output with A100 SMX4, PyTorch 2.4.1, and CUDA 12.4. + +``` + method kind runtime_ms op_mem_mb test_data +0 cce loss-fw 46.4 1.1 gemma2 +1 torch_compile loss-fw 49.9 4000.1 gemma2 +2 baseline loss-fw 81.9 24000.0 gemma2 +3 cce loss-bw 89.3 1163.0 gemma2 +4 torch_compile loss-bw 92.3 12000.0 gemma2 +5 baseline loss-bw 122.4 16000.0 gemma2 +6 cce loss-fw-bw 134.8 1164.0 gemma2 +7 torch_compile loss-fw-bw 144.0 16000.1 gemma2 +8 baseline loss-fw-bw 208.8 28000.0 gemma2 +``` + +### Development + +If dependencies are installed locally, `cut-cross-entropy` will work without a pip install as long as `python` is executed in the root path of the github repo. + +To install directly from the github repo, either use an (editable) install or manipulate PYTHONPATH, e.g. + +```bash +pip install -e ".[dev]" + +# or +pip install ".[dev]" + +# or +export PYTHONPATH=/path/to/ml-cross-entropy:${PYTHONPATH} +``` + +## Citation + +``` +@article{wijmans2024cut, + author = {Erik Wijmans and + Brody Huval and + Alexander Hertzberg and + Vladlen Koltun and + Philipp Kr\"ahenb\"uhl}, + title = {Cut Your Losses in Large-Vocabulary Language Models}, + journal = {arXiv}, + year = {2024}, + url = {https://arxiv.org/abs/2411.09009}, +} +``` + + +## License +This sample code is released under the [LICENSE](LICENSE) terms. + +## Acknowledgements + +Our codebase is built using multiple opensource contributions, please see [Acknowledgements](ACKNOWLEDGEMENTS.md) for more details. + +Please check the paper for a complete list of references and datasets used in this work. diff --git a/cut_cross_entropy-25.1.1.dist-info/RECORD b/cut_cross_entropy-25.1.1.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..56dafe2dc778ba6fbe945e07e5c232a00e7b66c1 --- /dev/null +++ b/cut_cross_entropy-25.1.1.dist-info/RECORD @@ -0,0 +1,19 @@ +cut_cross_entropy-25.1.1.dist-info/INSTALLER,sha256=5hhM4Q4mYTT9z6QB6PGpUAW81PGNFrYrdXMj4oM_6ak,2 +cut_cross_entropy-25.1.1.dist-info/LICENSE,sha256=yTPASVpJQ4IDvXmZGERUjmxoUyBRB_lcZowxeiwgIVU,2731 +cut_cross_entropy-25.1.1.dist-info/METADATA,sha256=l_RYRfXvAIXZ8knBG_BPe8HP32Qwvv7_qqr9Ar_k3Mg,9325 +cut_cross_entropy-25.1.1.dist-info/RECORD,, +cut_cross_entropy-25.1.1.dist-info/REQUESTED,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0 +cut_cross_entropy-25.1.1.dist-info/WHEEL,sha256=A3WOREP4zgxI0fKrHUG8DC8013e3dK3n7a6HDbcEIwE,91 +cut_cross_entropy-25.1.1.dist-info/top_level.txt,sha256=dSZLLiYIfH2pCB4rvFQkuZqtFgxQFJvUhRCctLcJUYE,18 +cut_cross_entropy/__init__.py,sha256=LVqos5i3MrSloU1c3bkHptCTq6AaMvy6_Is6m3-7qrI,325 +cut_cross_entropy/cce.py,sha256=tCqocDb5BEtSP0RlWINNt0vI0tD7skBL0FfJemHtIGg,5339 +cut_cross_entropy/cce_backward.py,sha256=RN_MpStTJNaX_kOcFcFbcu8WR_AKWMNBGrlFwUgbYrg,9803 +cut_cross_entropy/cce_lse_forward.py,sha256=8yVyuAa2_cOIRiYHbfWxRuZU2gR4nIOrPgOWH_f9yTA,6316 +cut_cross_entropy/constants.py,sha256=LcLPytUgFUR98ED3WwKEE8nivhVESJ5wkWLrUXKeysc,80 +cut_cross_entropy/doc.py,sha256=_H4o7CMrPj0aVOUo4Rk-cQZfaExxOhaKXgAXfM6bLMs,1626 +cut_cross_entropy/indexed_dot.py,sha256=NmyTNVmu7mtAfbUl2pkCgsLvqBsmKY935aGhbE_9lFg,3740 +cut_cross_entropy/linear_cross_entropy.py,sha256=mSllz6S2DCR1Id5_imqGFBKi_KRGiCIeKLMvQ4ZMG94,3319 +cut_cross_entropy/tl_autotune.py,sha256=9rQwBNgvFyR6mWv1IQCTMB7jH2_coaQRIRCq9aiXUSM,15151 +cut_cross_entropy/tl_utils.py,sha256=F9ukF0zkf4iyv2DfYmVq802lVUZQMNgD-v8votVyc_M,1312 +cut_cross_entropy/torch_compile.py,sha256=J0JKocvE2WO0TNffGBMJI8tTGV8556OG13kKan4EC1M,1961 +cut_cross_entropy/utils.py,sha256=smOz4gRcsFnfa2R73UNQduWdiSkRfYuyGV2hXXHyrGg,1881 diff --git a/cut_cross_entropy-25.1.1.dist-info/REQUESTED b/cut_cross_entropy-25.1.1.dist-info/REQUESTED new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/cut_cross_entropy-25.1.1.dist-info/WHEEL b/cut_cross_entropy-25.1.1.dist-info/WHEEL new file mode 100644 index 0000000000000000000000000000000000000000..1e3dcb16c30886471a686180684c9274bf795aad --- /dev/null +++ b/cut_cross_entropy-25.1.1.dist-info/WHEEL @@ -0,0 +1,5 @@ +Wheel-Version: 1.0 +Generator: setuptools (75.7.0) +Root-Is-Purelib: true +Tag: py3-none-any + diff --git a/cut_cross_entropy-25.1.1.dist-info/top_level.txt b/cut_cross_entropy-25.1.1.dist-info/top_level.txt new file mode 100644 index 0000000000000000000000000000000000000000..c69bb5ad6f450659b2c04fe0a9d34c69aef7b580 --- /dev/null +++ b/cut_cross_entropy-25.1.1.dist-info/top_level.txt @@ -0,0 +1 @@ +cut_cross_entropy diff --git a/cut_cross_entropy/__init__.py b/cut_cross_entropy/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..3fa89fb65ac3534dca3fa810b0947b14eaf7eaa7 --- /dev/null +++ b/cut_cross_entropy/__init__.py @@ -0,0 +1,15 @@ +# Copyright (C) 2024 Apple Inc. All Rights Reserved. +from cut_cross_entropy.linear_cross_entropy import ( + LinearCrossEntropy, + LinearCrossEntropyImpl, + linear_cross_entropy, +) + +__all__ = [ + "LinearCrossEntropy", + "LinearCrossEntropyImpl", + "linear_cross_entropy", +] + + +__version__ = "25.1.1" diff --git a/cut_cross_entropy/cce.py b/cut_cross_entropy/cce.py new file mode 100644 index 0000000000000000000000000000000000000000..318047503e50a74ee1c6908db8de0787ddc4846c --- /dev/null +++ b/cut_cross_entropy/cce.py @@ -0,0 +1,180 @@ +# Copyright (C) 2024 Apple Inc. All Rights Reserved. +from dataclasses import dataclass +from typing import cast + +import torch + +from cut_cross_entropy.cce_backward import cce_backward_kernel +from cut_cross_entropy.cce_lse_forward import cce_lse_forward_kernel +from cut_cross_entropy.constants import IGNORE_INDEX +from cut_cross_entropy.doc import LINEAR_CROSS_ENTROPY_DOC, add_doc_start +from cut_cross_entropy.indexed_dot import indexed_neg_dot_forward_kernel +from cut_cross_entropy.utils import ( + _build_flat_valids, + _handle_eps, + handle_reduction_none, +) + + +@dataclass +class CCEParams: + targets: torch.Tensor + valids: torch.Tensor | None + softcap: float | None + reduction: str + filter_eps: float | None + shift: bool + batch_shape: torch.Size + + +@torch.compile(fullgraph=True, dynamic=True) +def sort_logit_avg(logit_avg: torch.Tensor) -> torch.Tensor: + return torch.argsort(logit_avg).to(torch.int32) + + +class LinearCrossEntropyFunction(torch.autograd.Function): + @staticmethod + def forward( + ctx, + e: torch.Tensor, + c: torch.Tensor, + params: CCEParams, + ) -> torch.Tensor: + needs_grad = e.requires_grad or c.requires_grad + return_logit_avg = needs_grad and params.filter_eps is not None + + ret = cce_lse_forward_kernel( + e, + c, + params.valids, + softcap=params.softcap, + return_logit_avg=return_logit_avg, + ) + if return_logit_avg: + assert isinstance(ret, tuple) + lse, logit_avg = ret + else: + assert isinstance(ret, torch.Tensor) + lse = ret + logit_avg = None + + neg_dot = indexed_neg_dot_forward_kernel( + e, c, params.targets, params.shift, params.valids, params.softcap, lse.dtype + ) + + nll = neg_dot.add_(lse) + + reduction = params.reduction + if reduction == "mean": + loss = nll.mean() + elif reduction == "sum": + loss = nll.sum() + elif reduction == "none": + loss = handle_reduction_none(params.batch_shape, params.valids, params.shift, nll) + else: + raise ValueError(f"Unknown reduction {reduction}") + + ctx.save_for_backward(e, c, lse, params.targets, params.valids, logit_avg) + ctx.params = params + + return loss + + @staticmethod + def backward(ctx, grad_out: torch.Tensor) -> tuple[torch.Tensor, torch.Tensor, None]: + h, w, lse, targets, valids, logit_avg = ctx.saved_tensors + + if logit_avg is not None: + vocab_ordering = sort_logit_avg(logit_avg) + else: + vocab_ordering = None + + params = cast(CCEParams, ctx.params) + reduction = params.reduction + if reduction == "mean": + grad_scale = 1 / lse.numel() + elif reduction == "sum": + grad_scale = 1.0 + elif reduction == "none": + grad_scale = 1.0 + grad_out = grad_out.view(-1) + else: + raise ValueError(f"Unknown reduction {reduction}") + + de, dc = cce_backward_kernel( + grad_out, + h, + w, + lse, + valids, + params.softcap, + params.filter_eps, + targets=targets, + shift=params.shift, + vocab_ordering=vocab_ordering, + grad_scale=grad_scale, + ) + + return de, dc, None + + +def linear_cross_entropy_apply( + e: torch.Tensor, + c: torch.Tensor, + params: CCEParams, +) -> torch.Tensor: + loss = LinearCrossEntropyFunction.apply(e, c, params) + assert isinstance(loss, torch.Tensor) + + if params.shift and params.reduction == "none": + loss = loss[..., 1:] + + return loss + + +@add_doc_start(LINEAR_CROSS_ENTROPY_DOC) +def cce_linear_cross_entropy( + e: torch.Tensor, + c: torch.Tensor, + targets: torch.Tensor, + ignore_index: int = IGNORE_INDEX, + softcap: float | None = None, + reduction: str = "mean", + shift: bool = False, + filter_eps: float | str | None = "auto", +) -> torch.Tensor: + """ + :param filter_eps: The threshold value used to determine which locations can be safely ignored + in gradient computation. The default value of "auto" will automatically choose a value + based on the input dtype. + """ + assert e.size()[0:-1] == targets.size() + assert e.size(-1) == c.size(1) + # if not torch.cuda.is_bf16_supported(): + # raise RuntimeError( + # "Cut Cross Entropy requires an ampere GPU or newer. " + # "Consider using torch_compile_linear_cross_entropy for scenarios where one is not available." + # ) + + batch_shape = targets.size() + + e = e.contiguous() + targets = targets.contiguous() + + valids = _build_flat_valids(targets, ignore_index, shift) + + e = e.flatten(0, -2) + targets = targets.flatten() + + return linear_cross_entropy_apply( + e, + c, + CCEParams( + targets, + valids, + softcap, + reduction, + _handle_eps(filter_eps, e.dtype), + shift, + batch_shape, + ), + ) diff --git a/cut_cross_entropy/cce_backward.py b/cut_cross_entropy/cce_backward.py new file mode 100644 index 0000000000000000000000000000000000000000..3bdf44cbf80376c111b02932f8e2989984d58b52 --- /dev/null +++ b/cut_cross_entropy/cce_backward.py @@ -0,0 +1,338 @@ +# Copyright (C) 2024 Apple Inc. All Rights Reserved. +import torch +import triton +import triton.language as tl + +from cut_cross_entropy.tl_autotune import cce_backward_autotune +from cut_cross_entropy.tl_utils import ( + b_bin_fn, + tl_and_reduce_fn, + tl_lock_add, + tl_softcapping, + tl_softcapping_grad, +) + + +@triton.jit +def _mm_backward( + do, + da_ptrs, + partial_mask_a, + da_lock_ptr, + n_locks, + b_ptrs, + partial_mask_b, + stride_ad, + stride_bd, + D, + BLOCK_D: tl.constexpr, + EVEN_D: tl.constexpr, +): + d_inds = tl.arange(0, BLOCK_D)[None, :] + + da_ptrs = da_ptrs + d_inds * stride_ad + b_ptrs = b_ptrs + d_inds * stride_bd + + for d in range(0, tl.cdiv(D, BLOCK_D)): + if EVEN_D: + mask = partial_mask_b + else: + mask = partial_mask_b & (d_inds < (D - d * BLOCK_D)) + + b = tl.load(b_ptrs, mask=mask, other=0.0).to(do.dtype) + + da_i = tl.dot(do, b).to(da_ptrs.dtype.element_ty) + + if EVEN_D: + mask = partial_mask_a + else: + mask = partial_mask_a & (d_inds < (D - d * BLOCK_D)) + + lock_offset = d // tl.cdiv(D, BLOCK_D * n_locks) + this_da_lock_ptr = da_lock_ptr + lock_offset + + tl_lock_add(da_ptrs, da_i, mask, this_da_lock_ptr) + + b_ptrs += BLOCK_D * stride_bd + da_ptrs += BLOCK_D * stride_ad + + +@triton.jit +def _block_is_filtered(check_val: tl.tensor, filter_eps: tl.tensor) -> tl.tensor: + return tl.reduce(check_val < filter_eps, None, tl_and_reduce_fn) + + +def _cce_backward_kernel( + E, + C, + LSE, + dOut, + grad_scale, + Valids, + VocabOrdering, + softcap, + Targets, + dE, + dELocks, + dC, + dCLocks, + B, + D, + V, + n_de_locks_0, + n_de_locks_1, + n_dc_locks_0, + n_dc_locks_1, + stride_eb, + stride_ed, + stride_cv, + stride_cd, + stride_vb, + filter_eps, + B_BIN, + BLOCK_B: tl.constexpr, + BLOCK_V: tl.constexpr, + BLOCK_D: tl.constexpr, + MM_BACK_BLOCK_D: tl.constexpr, + GROUP_B: tl.constexpr, + EVEN_D: tl.constexpr, + MM_BACK_EVEN_D: tl.constexpr, + ITEM_DO: tl.constexpr, + HAS_VALIDS: tl.constexpr, + HAS_VOCAB_ORDERING: tl.constexpr, + FILTER_GRAD: tl.constexpr, + HAS_TARGETS: tl.constexpr, + HAS_SOFTCAP: tl.constexpr, + SHIFT: tl.constexpr, + REQUIRES_GRAD: tl.constexpr, +): + pid = tl.program_id(axis=0) + num_b_chunks = tl.cdiv(B, BLOCK_B) + num_v_chunks = tl.cdiv(V, BLOCK_V) + num_v_in_group = GROUP_B * num_v_chunks + group_id = pid // num_v_in_group + first_pid_b = group_id * GROUP_B + group_size_b = min(num_b_chunks - first_pid_b, GROUP_B) + pid_b = first_pid_b + ((pid % num_v_in_group) % group_size_b) + pid_v = (pid % num_v_in_group) // group_size_b + + offs_b = (pid_b * BLOCK_B + tl.arange(0, BLOCK_B)) % B + if HAS_VALIDS: + offs_b = tl.load(Valids + stride_vb * offs_b) + + offs_v = (pid_v * BLOCK_V + tl.arange(0, BLOCK_V)) % V + if HAS_VOCAB_ORDERING: + offs_v = tl.load(VocabOrdering + offs_v) + + offs_d = tl.arange(0, BLOCK_D) + e_ptrs = E + (offs_b[:, None] * stride_eb + offs_d[None, :] * stride_ed) + c_ptrs = C + (offs_v[None, :] * stride_cv + offs_d[:, None] * stride_cd) + + accum = tl.zeros((BLOCK_B, BLOCK_V), dtype=tl.float32) + for d in range(0, tl.cdiv(D, BLOCK_D)): + if EVEN_D: + e = tl.load(e_ptrs) + c = tl.load(c_ptrs).to(e.dtype) + else: + e = tl.load(e_ptrs, mask=offs_d[None, :] < D - d * BLOCK_D, other=0.0) + c = tl.load(c_ptrs, mask=offs_d[:, None] < D - d * BLOCK_D, other=0.0).to(e.dtype) + + accum = tl.dot(e, c, accum, input_precision = "ieee") + + e_ptrs += BLOCK_D * stride_ed + c_ptrs += BLOCK_D * stride_cd + + if HAS_SOFTCAP: + accum = tl_softcapping(accum, softcap) + + if HAS_VALIDS: + lse = tl.load(LSE + (pid_b * BLOCK_B + tl.arange(0, BLOCK_B)) % B) + else: + lse = tl.load(LSE + offs_b) + + d_accum = tl.exp(accum - lse[:, None]) + + if HAS_TARGETS: + targets = tl.load(Targets + ((offs_b + 1) if SHIFT else offs_b)) + is_target = targets[:, None] == offs_v[None, :] + d_accum += tl.where(is_target, -1.0, 0.0) + else: + is_target = None + + accum_valid_mask = ((pid_b * BLOCK_B + tl.arange(0, BLOCK_B))[:, None] < B) & ( + (pid_v * BLOCK_V + tl.arange(0, BLOCK_V))[None, :] < V + ) + d_accum = tl.where(accum_valid_mask, d_accum, 0.0) + + if FILTER_GRAD: + if _block_is_filtered(tl.abs(d_accum), filter_eps): + return + + if HAS_SOFTCAP: + d_accum = tl_softcapping_grad(d_accum, accum, softcap) + + if ITEM_DO: + d_out = tl.load(dOut) + else: + d_out = tl.load(dOut + ((offs_b + 1) if SHIFT else offs_b))[:, None] + + d_out = grad_scale * d_out + + d_accum = (d_accum * d_out).to(e_ptrs.dtype.element_ty) + + b_mask = (pid_b * BLOCK_B + tl.arange(0, BLOCK_B)[:, None]) < B + v_mask = (pid_v * BLOCK_V + tl.arange(0, BLOCK_V)[:, None]) < V + + lock_offset = (pid_b // tl.cdiv(B, BLOCK_B * n_de_locks_0)) * n_de_locks_1 + dELocks += lock_offset + + _mm_backward( + d_accum, + dE + (offs_b[:, None] * stride_eb), + b_mask, + dELocks, + n_de_locks_1, + C + offs_v[:, None] * stride_cv, + v_mask, + stride_ed, + stride_cd, + D, + MM_BACK_BLOCK_D, + MM_BACK_EVEN_D, + ) + + lock_offset = (pid_v // tl.cdiv(V, BLOCK_V * n_dc_locks_0)) * n_dc_locks_1 + dCLocks += lock_offset + + if REQUIRES_GRAD: + _mm_backward( + tl.trans(d_accum), + dC + (offs_v[:, None] * stride_cv), + v_mask, + dCLocks, + n_dc_locks_1, + E + (offs_b[:, None] * stride_eb), + b_mask, + stride_cd, + stride_ed, + D, + MM_BACK_BLOCK_D, + MM_BACK_EVEN_D, + ) + + +_cce_backward_kernel = triton.jit(_cce_backward_kernel) +_cce_backward_kernel = triton.heuristics( # type: ignore + { + "EVEN_D": lambda args: (args["D"] % args["BLOCK_D"]) == 0, + "MM_BACK_BLOCK_D": lambda args: args["BLOCK_D"] * 2, + "MM_BACK_EVEN_D": lambda args: (args["D"] % (args["BLOCK_D"] * 2)) == 0, + "HAS_VALIDS": lambda args: args["Valids"] is not None, + "HAS_VOCAB_ORDERING": lambda args: args["VocabOrdering"] is not None, + "FILTER_GRAD": lambda args: args["filter_eps"] is not None, + "HAS_TARGETS": lambda args: args["Targets"] is not None, + "HAS_SOFTCAP": lambda args: args["softcap"] is not None, + "ITEM_DO": lambda args: args["dOut"].numel() == 1, + "GROUP_B": lambda args: 8, + "REQUIRES_GRAD" : lambda args: args["REQUIRES_GRAD"], + } +)(_cce_backward_kernel) +_cce_backward_kernel = cce_backward_autotune()(_cce_backward_kernel) # type: ignore + + +def cce_backward_kernel( + do: torch.Tensor, + e: torch.Tensor, + c: torch.Tensor, + lse: torch.Tensor, + valids: torch.Tensor | None, + softcap: float | None, + filter_eps: float | None, + targets: torch.Tensor | None = None, + shift: bool = False, + vocab_ordering: torch.Tensor | None = None, + grad_scale: float = 1.0, +) -> tuple[torch.Tensor, torch.Tensor]: + assert do.numel() in (e.size(0), 1) + assert c.size(1) == e.size(1) + assert lse.size(0) == e.size(0) or (valids is not None and lse.size(0) == valids.size(0)) + assert e.dtype in ( + torch.float16, + torch.bfloat16, + ), "Backwards requires embeddings to be bf16 or fp16" + assert c.dtype in ( + torch.float16, + torch.bfloat16, + torch.float32, + ), "Backwards requires classifier to be bf16 or fp16 or fp32" + + do = do.contiguous() + lse = lse.contiguous() + + de = torch.zeros_like(e) + assert de.stride() == e.stride() + + if c.requires_grad: + dc = torch.zeros_like(c, dtype = e.dtype) + assert dc.stride() == c.stride() + REQUIRES_GRAD = True + else: + dc = c + REQUIRES_GRAD = False + + if valids is not None: + assert valids.ndim == 1 + B = valids.size(0) + else: + B = e.size(0) + + if do.numel() > 1: + do = do.contiguous() + lse = lse.contiguous() + assert do.stride(0) == lse.stride(0), f"{do.stride()=}, {lse.stride()=}" + + def grid(META): + return (triton.cdiv(B, META["BLOCK_B"]) * triton.cdiv(c.size(0), META["BLOCK_V"]),) + + if vocab_ordering is not None: + assert vocab_ordering.ndim == 1 + assert vocab_ordering.numel() == dc.size(0) + assert vocab_ordering.stride(0) == 1 + + nd_locks = triton.cdiv(c.size(1), 64) + de_locks = e.new_zeros((triton.cdiv(B, nd_locks), nd_locks), dtype=torch.int32) + dc_locks = c.new_zeros((triton.cdiv(c.size(0), nd_locks), nd_locks), dtype=torch.int32) + + _cce_backward_kernel[grid]( + e, + c, + lse, + do, + grad_scale, + valids, + vocab_ordering, + softcap, + targets, + de, + de_locks, + dc, + dc_locks, + B, + e.size(1), + c.size(0), + de_locks.size(0), + de_locks.size(1), + dc_locks.size(0), + dc_locks.size(1), + e.stride(0), + e.stride(1), + c.stride(0), + c.stride(1), + 1 if valids is None else valids.stride(0), + filter_eps, + B_BIN=b_bin_fn(B), + SHIFT=shift, + REQUIRES_GRAD = REQUIRES_GRAD, + ) + + return de, dc.to(c.dtype) if REQUIRES_GRAD else None diff --git a/cut_cross_entropy/cce_lse_forward.py b/cut_cross_entropy/cce_lse_forward.py new file mode 100644 index 0000000000000000000000000000000000000000..20fce797f617c4b433260df88fbef40037f1a8de --- /dev/null +++ b/cut_cross_entropy/cce_lse_forward.py @@ -0,0 +1,209 @@ +# Copyright (C) 2024 Apple Inc. All Rights Reserved. +from typing import Literal, overload + +import torch +import triton +import triton.language as tl + +from cut_cross_entropy.tl_autotune import cce_forward_autotune +from cut_cross_entropy.tl_utils import b_bin_fn, tl_logaddexp, tl_softcapping + + +def _cce_lse_forward_kernel( + E, + C, + LSE, + LA, + Locks, + Valids, + softcap, + B, + V, + D, + stride_eb, + stride_ed, + stride_cv, + stride_cd, + stride_lse_b, + stride_vb, + num_locks, + # Meta-parameters + B_BIN, + HAS_VALIDS: tl.constexpr, + BLOCK_B: tl.constexpr, + BLOCK_V: tl.constexpr, + BLOCK_D: tl.constexpr, # + GROUP_B: tl.constexpr, # + EVEN_D: tl.constexpr, + HAS_SOFTCAP: tl.constexpr, + HAS_LA: tl.constexpr, + DOT_PRECISION: tl.constexpr, +): + pid = tl.program_id(axis=0) + num_pid_b = tl.cdiv(B, BLOCK_B) + num_pid_v = tl.cdiv(V, BLOCK_V) + num_pid_in_group = GROUP_B * num_pid_v + group_id = pid // num_pid_in_group + first_pid_b = group_id * GROUP_B + group_size_b = min(num_pid_b - first_pid_b, GROUP_B) + pid_b = first_pid_b + ((pid % num_pid_in_group) % group_size_b) + pid_v = (pid % num_pid_in_group) // group_size_b + + offs_b = (pid_b * BLOCK_B + tl.arange(0, BLOCK_B)) % B + if HAS_VALIDS: + offs_b = tl.load(Valids + stride_vb * offs_b) + + offs_v = (pid_v * BLOCK_V + tl.arange(0, BLOCK_V)) % V + offs_d = tl.arange(0, BLOCK_D) + e_ptrs = E + (offs_b[:, None] * stride_eb + offs_d[None, :] * stride_ed) + c_ptrs = C + (offs_v[None, :] * stride_cv + offs_d[:, None] * stride_cd) + + accum = tl.zeros((BLOCK_B, BLOCK_V), dtype=tl.float32) + for d in range(0, tl.cdiv(D, BLOCK_D)): + # Load the next block of A and B, generate a mask by checking the K dimension. + # If it is out of bounds, set it to 0. + if EVEN_D: + e = tl.load(e_ptrs) + c = tl.load(c_ptrs).to(e.dtype) + else: + e = tl.load(e_ptrs, mask=offs_d[None, :] < D - d * BLOCK_D, other=0.0) + c = tl.load(c_ptrs, mask=offs_d[:, None] < D - d * BLOCK_D, other=0.0).to(e.dtype) + accum = tl.dot(e, c, accum, input_precision=DOT_PRECISION) + e_ptrs += BLOCK_D * stride_ed + c_ptrs += BLOCK_D * stride_cd + + v_mask = (pid_v * BLOCK_V + tl.arange(0, BLOCK_V)) < V + logits = tl.where(v_mask[None, :], accum, -float("inf")) + if HAS_SOFTCAP: + logits = tl_softcapping(logits, softcap) + + off_b = pid_b * BLOCK_B + tl.arange(0, BLOCK_B) + o_mask = off_b < B + if HAS_LA: + logits = tl.where(o_mask[:, None], logits, 0.0) + this_avg_logit = tl.sum(logits, 0) / B + tl.atomic_add(LA + offs_v, this_avg_logit, mask=v_mask) + + this_mx = tl.max(logits, axis=1) + e = tl.exp(logits - this_mx[:, None]) + this_lse = this_mx + tl.log(tl.sum(e, axis=1)) + + lse_ptrs = LSE + (stride_lse_b * off_b) + + this_locks = Locks + (pid_b // tl.cdiv(B, BLOCK_B * num_locks)) + while tl.atomic_cas(this_locks, 0, 1) == 1: + pass + + lse = tl.load(lse_ptrs, mask=o_mask, other=0.0, eviction_policy="evict_last") + lse = tl_logaddexp(lse, this_lse) + tl.store(lse_ptrs, lse, mask=o_mask, eviction_policy="evict_last") + + tl.atomic_xchg(this_locks, 0) + + +_cce_lse_forward_kernel = triton.jit(_cce_lse_forward_kernel) +_cce_lse_forward_kernel = triton.heuristics( # type: ignore + { + "EVEN_D": lambda args: args["D"] % args["BLOCK_D"] == 0, + "HAS_VALIDS": lambda args: args["Valids"] is not None, + "HAS_SOFTCAP": lambda args: args["softcap"] is not None, + "HAS_LA": lambda args: args["LA"] is not None, + "GROUP_B": lambda args: 8, + "DOT_PRECISION": lambda args: "tf32" + if torch.get_float32_matmul_precision() == "high" + else "ieee", # [TODO] Use tf32x3 + } +)(_cce_lse_forward_kernel) +_cce_lse_forward_kernel = cce_forward_autotune()(_cce_lse_forward_kernel) # type: ignore + + +@overload +def cce_lse_forward_kernel( + e, + c, + valids: torch.Tensor | None = None, + softcap: float | None = None, + return_logit_avg: Literal[False] = False, +) -> torch.Tensor: ... + + +@overload +def cce_lse_forward_kernel( + e, + c, + valids: torch.Tensor | None = None, + softcap: float | None = None, + return_logit_avg: Literal[True] = True, +) -> tuple[torch.Tensor, torch.Tensor]: ... + + +@overload +def cce_lse_forward_kernel( + e, + c, + valids: torch.Tensor | None = None, + softcap: float | None = None, + return_logit_avg: bool = False, +) -> tuple[torch.Tensor, torch.Tensor] | torch.Tensor: ... + + +def cce_lse_forward_kernel( + e: torch.Tensor, + c: torch.Tensor, + valids: torch.Tensor | None = None, + softcap: float | None = None, + return_logit_avg: bool = False, +) -> tuple[torch.Tensor, torch.Tensor] | torch.Tensor: + # Check constraints. + assert e.shape[1] == c.shape[1], "Incompatible dimensions" + assert e.is_contiguous(), "Matrix A must be contiguous" + if valids is not None: + assert valids.ndim == 1 + B = valids.numel() + else: + B, _ = e.shape + + V, D = c.shape + # Allocates output. + lse = e.new_full((B,), -float("inf"), dtype=torch.float32) + locks = e.new_full( + (triton.cdiv(B, 128),), + 0, + dtype=torch.uint32, + ) + + if return_logit_avg: + logit_avg = e.new_full((V,), 0.0, dtype=torch.float32) + else: + logit_avg = None + + # 1D launch kernel where each block gets its own program. + def grid(META) -> tuple[int]: + return (triton.cdiv(B, META["BLOCK_B"]) * triton.cdiv(V, META["BLOCK_V"]),) + + _cce_lse_forward_kernel[grid]( + e, + c, + lse, # + logit_avg, + locks, + valids, + softcap, + B, + V, + D, # + e.stride(0), + e.stride(1), # + c.stride(0), + c.stride(1), # + lse.stride(0), + 1 if valids is None else valids.stride(0), + num_locks=locks.size(0), + B_BIN=b_bin_fn(B), + ) + + if return_logit_avg: + assert logit_avg is not None + return lse, logit_avg + else: + return lse diff --git a/cut_cross_entropy/constants.py b/cut_cross_entropy/constants.py new file mode 100644 index 0000000000000000000000000000000000000000..efcadac3345802149e5b96afee91e6af23510e1b --- /dev/null +++ b/cut_cross_entropy/constants.py @@ -0,0 +1,2 @@ +# Copyright (C) 2024 Apple Inc. All Rights Reserved. +IGNORE_INDEX: int = -100 diff --git a/cut_cross_entropy/doc.py b/cut_cross_entropy/doc.py new file mode 100644 index 0000000000000000000000000000000000000000..8e086acd104e2ef1c6fe8c82f6fa9b838e65932e --- /dev/null +++ b/cut_cross_entropy/doc.py @@ -0,0 +1,43 @@ +# Copyright (C) 2024 Apple Inc. All Rights Reserved. +LINEAR_CROSS_ENTROPY_DOC = """Computes cross-entropy loss using the logits generated by performing + the matrix multiplication between the embeddings (e) and classifier (c). + + This method saves GPU memory by not materializing the logits into GPU + main memory. + + + Specifically, this computes + + ```python + + loss = F.cross_entropy((e @ c.T).float(), targets) + ``` + + without allocating the intermediary (e @ c.T).float() matrix. + + :param e: Embedding of the inputs used to compute the logits. Shape (..., D) + :param c: Classifier matrix. Shape (NumClasses, D) + :param targets: The target class for each input. Values must be in [0, NumClasses). Shape (...) + :param ignore_index: If an input as a target of this value, it is ignored in the loss computation. + :param softcap: The value for logit softcapping. + :param reduction: The reduction to perform over the loss. Supports "mean", "sum", and "none". + :param shift: If true, the embedding and targets are assumed to require a shift along the + temporal axis to perform next token prediction. Specifically, setting this to true + will efficiently compute + + ```python + shift_e = e[..., :-1, :].flatten(0, -2) + shift_targets = targets[..., 1:].flatten() + + loss = F.cross_entropy((shift_e @ c.T), targets) + ``` +""" + + +def add_doc_start(*docstr: str): + def add_doc(fn): + fn.__doc__ = "".join(docstr) + (fn.__doc__ if fn.__doc__ is not None else "") + + return fn + + return add_doc diff --git a/cut_cross_entropy/indexed_dot.py b/cut_cross_entropy/indexed_dot.py new file mode 100644 index 0000000000000000000000000000000000000000..6c07185d90c7dee9787454026f096e7bcc48db0b --- /dev/null +++ b/cut_cross_entropy/indexed_dot.py @@ -0,0 +1,132 @@ +# Copyright (C) 2024 Apple Inc. All Rights Reserved. +import torch +import triton +import triton.language as tl + +from cut_cross_entropy.tl_autotune import indexed_dot_autotune +from cut_cross_entropy.tl_utils import b_bin_fn +from cut_cross_entropy.utils import softcapping + + +def _indexed_neg_dot_forward_kernel( + E, + C, + Inds, + Valids, + Out, + B, + D, + stride_eb, + stride_ed, + stride_cv, + stride_cd, + stride_ib, + stride_vb, + B_BIN, + BLOCK_B: tl.constexpr, + BLOCK_D: tl.constexpr, + GROUP_B: tl.constexpr, + HAS_VALIDS: tl.constexpr, + EVEN_D: tl.constexpr, + SHIFT: tl.constexpr, +): + pid = tl.program_id(axis=0) + num_b_chunks = tl.cdiv(B, BLOCK_B) + num_d_chunks = tl.cdiv(D, BLOCK_D) + num_d_in_group = GROUP_B * num_d_chunks + group_id = pid // num_d_in_group + first_pid_b = group_id * GROUP_B + group_size_b = min(num_b_chunks - first_pid_b, GROUP_B) + pid_b = first_pid_b + ((pid % num_d_in_group) % group_size_b) + pid_d = (pid % num_d_in_group) // group_size_b + + offs_b = (tl.arange(0, BLOCK_B) + pid_b * BLOCK_B) % B + if HAS_VALIDS: + offs_b = tl.load(Valids + stride_vb * offs_b) + + offs_d = tl.arange(0, BLOCK_D) + pid_d * BLOCK_D + e_ptrs = E + (stride_eb * offs_b[:, None] + stride_ed * offs_d[None, :]) + if EVEN_D: + e = tl.load(e_ptrs) + else: + e = tl.load(e_ptrs, mask=offs_d[None, :] < D, other=0.0) + + inds = tl.load(Inds + stride_ib * ((offs_b + 1) if SHIFT else offs_b)) + + c_ptrs = C + (inds[:, None] * stride_cv + offs_d[None, :] * stride_cd) + if EVEN_D: + c = tl.load(c_ptrs) + else: + c = tl.load(c_ptrs, mask=offs_d[None, :] < D, other=0.0) + + offs_b = tl.arange(0, BLOCK_B) + pid_b * BLOCK_B + out_ptrs = Out + offs_b + dot = (e * c).to(tl.float32) + neg_dot = -tl.sum(dot, 1).to(out_ptrs.dtype.element_ty) + tl.atomic_add(out_ptrs, neg_dot, mask=offs_b < B) + + +_indexed_neg_dot_forward_kernel = triton.jit(_indexed_neg_dot_forward_kernel) +_indexed_neg_dot_forward_kernel = triton.heuristics( # type: ignore + { + "EVEN_D": lambda args: args["D"] % args["BLOCK_D"] == 0, + "HAS_VALIDS": lambda args: args["Valids"] is not None, + "GROUP_B": lambda args: 8, + } +)(_indexed_neg_dot_forward_kernel) +_indexed_neg_dot_forward_kernel = indexed_dot_autotune()(_indexed_neg_dot_forward_kernel) # type: ignore + + +def indexed_neg_dot_forward_kernel( + e: torch.Tensor, + c: torch.Tensor, + inds: torch.Tensor, + shift: bool = False, + valids: torch.Tensor | None = None, + softcap: float | None = None, + out_dtype: torch.dtype | None = None, +) -> torch.Tensor: + assert inds.ndim == 1 + assert e.ndim == 2 + assert c.ndim == 2 + assert inds.size(0) == e.size(0) + assert c.size(1) == e.size(1) + + if valids is not None: + assert valids.ndim == 1 + B = valids.size(0) + else: + B = e.size(0) + + out = e.new_zeros((B,), dtype=torch.float32) + + def grid(META) -> tuple[int]: + return (triton.cdiv(B, META["BLOCK_B"]) * triton.cdiv(e.size(1), META["BLOCK_D"]),) + + _indexed_neg_dot_forward_kernel[grid]( + e, + c, + inds, + valids, + out, + B, + e.size(1), + e.stride(0), + e.stride(1), + c.stride(0), + c.stride(1), + inds.stride(0), + 1 if valids is None else valids.stride(0), + B_BIN=b_bin_fn(B), + SHIFT=shift, + ) + + if softcap is not None: + out = softcapping(out, softcap) + + if out_dtype is None: + out_dtype = e.dtype + + out = out.to(out_dtype) + + return out diff --git a/cut_cross_entropy/linear_cross_entropy.py b/cut_cross_entropy/linear_cross_entropy.py new file mode 100644 index 0000000000000000000000000000000000000000..f9fe1a567c82fd1961f526b24efd5323afea9e40 --- /dev/null +++ b/cut_cross_entropy/linear_cross_entropy.py @@ -0,0 +1,99 @@ +# Copyright (C) 2024 Apple Inc. All Rights Reserved. +import enum +import platform +from enum import auto + +import torch +import torch.nn as nn + +from cut_cross_entropy.constants import IGNORE_INDEX +from cut_cross_entropy.doc import LINEAR_CROSS_ENTROPY_DOC, add_doc_start +from cut_cross_entropy.torch_compile import torch_compile_linear_cross_entropy + + +class LinearCrossEntropyImpl(enum.IntEnum): + CCE = auto() + TORCH_COMPILE = auto() + +PLATFORM_SYSTEM = platform.system() +if PLATFORM_SYSTEM != "Darwin": + from cut_cross_entropy.cce import cce_linear_cross_entropy + + LCE_IMPL_DEFAULT = LinearCrossEntropyImpl.CCE +else: + cce_linear_cross_entropy = None + LCE_IMPL_DEFAULT = LinearCrossEntropyImpl.TORCH_COMPILE + + +@add_doc_start(LINEAR_CROSS_ENTROPY_DOC) +def linear_cross_entropy( + e: torch.Tensor, + c: torch.Tensor, + targets: torch.Tensor, + ignore_index: int = IGNORE_INDEX, + softcap: float | None = None, + reduction: str = "mean", + shift: bool = False, + filter_eps: float | str | None = "high", + impl: str | LinearCrossEntropyImpl = LCE_IMPL_DEFAULT, +) -> torch.Tensor: + """ + :param filter_eps: The threshold value used to determine which locations can be safely ignored + in gradient computation. The default value of "auto" will automatically choose a value + based on the input dtype. Only valid for the CCE implementation. + :param impl: The linear cross entropy implementation to use. Currently supports cce and torch_compile. + """ + + if isinstance(impl, LinearCrossEntropyImpl): + impl = impl.name.lower() + + match impl: + case "cce": + if PLATFORM_SYSTEM == "Darwin": + raise RuntimeError( + "CCE does not support MacOS. Please use torch_compile when running on MacOS instead." + ) + + assert cce_linear_cross_entropy is not None + return cce_linear_cross_entropy( + e, c, targets, ignore_index, softcap, reduction, shift, filter_eps + ) + case "torch_compile": + return torch_compile_linear_cross_entropy( + e, c, targets, ignore_index, softcap, reduction, shift + ) + case _: + raise NotImplementedError(f"{impl} is not implemented.") + + +class LinearCrossEntropy(nn.Module): + def __init__( + self, + ignore_index: int = IGNORE_INDEX, + softcap: float | None = None, + reduction: str = "mean", + filter_eps: float | str | None = "high", + shift: bool = False, + impl: str | LinearCrossEntropyImpl = LCE_IMPL_DEFAULT, + ): + super().__init__() + self.ignore_index = ignore_index + self.softcap = softcap + self.reduction = reduction + self.filter_eps = filter_eps + self.shift = shift + + self.impl = impl + + def forward(self, e: torch.Tensor, c: torch.Tensor, targets: torch.Tensor) -> torch.Tensor: + return linear_cross_entropy( + e, + c, + targets, + self.ignore_index, + self.softcap, + reduction=self.reduction, + filter_eps=self.filter_eps, + shift=self.shift, + impl=self.impl, + ) diff --git a/cut_cross_entropy/tl_autotune.py b/cut_cross_entropy/tl_autotune.py new file mode 100644 index 0000000000000000000000000000000000000000..4e676cc3294ac5ad7f1961f78a09735b5b663651 --- /dev/null +++ b/cut_cross_entropy/tl_autotune.py @@ -0,0 +1,482 @@ +# Copyright (C) 2024 Apple Inc. All Rights Reserved. +import functools +import heapq +import os +from typing import Callable + +import torch +import triton +from triton import Config, cdiv +from triton.runtime import autotuner, driver +from triton.testing import ( + get_dram_gbps, + get_max_simd_tflops, + get_max_tensorcore_tflops, + nvsmi, +) + +_AUTOTUNE: bool = os.getenv("CCE_AUTOTUNE", "0") != "0" + + +@functools.lru_cache() +def get_clock_rate_in_khz(): + try: + return nvsmi(["clocks.max.sm"])[0] * 1e3 + except FileNotFoundError: + import pynvml + + pynvml.nvmlInit() + handle = pynvml.nvmlDeviceGetHandleByIndex(0) + return pynvml.nvmlDeviceGetMaxClockInfo(handle, pynvml.NVML_CLOCK_SM) * 1e3 + + +def get_tensorcore_tflops(device, num_ctas, num_warps, dtype): + """return compute throughput in TOPS""" + total_warps = num_ctas * min(num_warps, 4) + num_subcores = ( + driver.active.utils.get_device_properties(device)["multiprocessor_count"] * 4 + ) # on recent GPUs + tflops = ( + min(num_subcores, total_warps) + / num_subcores + * get_max_tensorcore_tflops(dtype, get_clock_rate_in_khz(), device) + ) + return tflops + + +def get_simd_tflops(device, num_ctas, num_warps, dtype): + """return compute throughput in TOPS""" + total_warps = num_ctas * min(num_warps, 4) + num_subcores = ( + driver.active.utils.get_device_properties(device)["multiprocessor_count"] * 4 + ) # on recent GPUs + tflops = ( + min(num_subcores, total_warps) + / num_subcores + * get_max_simd_tflops(dtype, get_clock_rate_in_khz(), device) + ) + return tflops + + +def get_tflops(device, num_ctas, num_warps, dtype): + capability = torch.cuda.get_device_capability(device) + if capability[0] < 8 and dtype == torch.float32: + return get_simd_tflops(device, num_ctas, num_warps, dtype) + return get_tensorcore_tflops(device, num_ctas, num_warps, dtype) + + +def early_config_prune( + configs, + named_args, + *, + shared_memory_factor: float = 1.0, + max_num_warps: int | None = None, + **kwargs, +): + device = torch.cuda.current_device() + capability = torch.cuda.get_device_capability() + # BLOCK_B, BLOCK_V, BLOCK_D, SPLIT_K, num_warps, num_stages + dtsize = named_args["E"].element_size() + + if max_num_warps is not None: + configs = [config for config in configs if config.num_warps <= max_num_warps] + + # 1. make sure we have enough smem + pruned_configs = [] + for config in configs: + kw = config.kwargs + BLOCK_B, BLOCK_V, BLOCK_D, num_stages = ( + kw["BLOCK_B"], + kw["BLOCK_V"], + kw["BLOCK_D"], + config.num_stages, + ) + + max_shared_memory = driver.active.utils.get_device_properties(device)["max_shared_mem"] + required_shared_memory = ( + shared_memory_factor * (BLOCK_B + BLOCK_V) * BLOCK_D * num_stages * dtsize + ) + if required_shared_memory > max_shared_memory: + continue + + pruned_configs.append(config) + + configs = pruned_configs + + # group configs by (BLOCK_B,_N,_K, num_warps) + configs_map = {} + for config in configs: + kw = config.kwargs + BLOCK_B, BLOCK_V, BLOCK_D, num_warps, num_stages = ( + kw["BLOCK_B"], + kw["BLOCK_V"], + kw["BLOCK_D"], + config.num_warps, + config.num_stages, + ) + + key = (BLOCK_B, BLOCK_V, BLOCK_D, num_warps) + if key in configs_map: + configs_map[key].append((config, num_stages)) + else: + configs_map[key] = [(config, num_stages)] + + pruned_configs = [] + for k, v in configs_map.items(): + BLOCK_B, BLOCK_V, BLOCK_D, num_warps = k + if capability[0] >= 8: + # compute cycles (only works for ampere GPUs) + mmas = BLOCK_B * BLOCK_V * BLOCK_D / (16 * 8 * 16) + mma_cycles = mmas / min(4, num_warps) * 8 + + ldgsts_latency = 300 # Does this matter? + optimal_num_stages = ldgsts_latency / mma_cycles + + # nearest stages, prefer large #stages + nearest = heapq.nsmallest( + 2, + v, + key=lambda x: 10 + abs(x[1] - optimal_num_stages) + if (x[1] - optimal_num_stages) < 0 + else x[1] - optimal_num_stages, + ) + + for n in nearest: + pruned_configs.append(n[0]) + else: # Volta & Turing only supports num_stages <= 2 + random_config = v[0][0] + random_config.num_stages = 2 + pruned_configs.append(random_config) + return pruned_configs + + +def _total_ops_fn(B, V, D) -> float: + return 2 * B * V * D + 10 * B * V + + +def _total_store_fn(B, V, D, dtsize, num_cta_b, num_cta_v): + return B * dtsize + + +def estimate_matmul_time( + # backend, device, + num_warps, + num_stages, # + E, + B, + V, + D, # + BLOCK_B, + BLOCK_V, + BLOCK_D, + debug=False, + total_ops_fn=_total_ops_fn, + total_store_fn=_total_store_fn, + **kwargs, # +): + """return estimated running time in ms + = max(compute, loading) + store""" + device = torch.cuda.current_device() + dtype = E.dtype + dtsize = E.element_size() + + num_cta_b = cdiv(B, BLOCK_B) + num_cta_v = cdiv(V, BLOCK_V) + num_ctas = num_cta_b * num_cta_v + + # If the input is smaller than the block size + B, V = max(B, BLOCK_B), max(V, BLOCK_V) + + # time to compute + total_ops = total_ops_fn(B, V, D) + total_ops = total_ops / (1024 * 1024 * 1024) # GOPS + tput = get_tflops(device, num_ctas, num_warps, dtype) + compute_ms = total_ops / tput + + # time to load data + num_sm = driver.active.utils.get_device_properties(device)["multiprocessor_count"] + active_cta_ratio = min(1, num_ctas / num_sm) + active_cta_ratio_bw1 = min(1, num_ctas / 32) # 32 active ctas are enough to saturate + active_cta_ratio_bw2 = max(min(1, (num_ctas - 32) / (108 - 32)), 0) # 32-108, remaining 5% + dram_bw = get_dram_gbps(device) * ( + active_cta_ratio_bw1 * 0.95 + active_cta_ratio_bw2 * 0.05 + ) # in GB/s + l2_bw = dram_bw * 4 # rough estimation (should be 4.7 for A100?) + # assume 80% of (following) loads are in L2 cache + load_a_dram = B * D * dtsize * (1 + 0.2 * (num_cta_v - 1)) + load_a_l2 = B * D * dtsize * 0.8 * (num_cta_v - 1) + load_b_dram = V * D * dtsize * (1 + 0.2 * (num_cta_b - 1)) + load_b_l2 = V * D * dtsize * 0.8 * (num_cta_b - 1) + # total + total_dram = (load_a_dram + load_b_dram) / (1024 * 1024) # MB + total_l2 = (load_a_l2 + load_b_l2) / (1024 * 1024) + # loading time in ms + load_ms = total_dram / dram_bw + total_l2 / l2_bw + + # estimate storing time + store_bw = dram_bw * 0.4 # :o + store_dram = total_store_fn(B, V, D, dtsize, num_cta_b, num_cta_v) / (1024 * 1024) + store_ms = store_dram / store_bw + + total_time_ms = max(compute_ms, load_ms) + store_ms + if debug: + print( + f"{BLOCK_B=}, {BLOCK_V=}, {BLOCK_D=}, {num_warps=}, {num_stages=}, " + f"Total time: {total_time_ms}ms, compute time: {compute_ms}ms, " + f"loading time: {load_ms}ms, store time: {store_ms}ms, " + f"Activate CTAs: {active_cta_ratio*100}%" + ) + return total_time_ms + + +def get_configs_io_bound(): + configs = [] + for num_stages in [2, 3, 4, 5, 6]: + for block_m in [16, 32]: + for block_k in [32, 64]: + for block_n in [32, 64, 128, 256]: + num_warps = 2 if block_n <= 64 else 4 + configs.append( + Config( + { + "BLOCK_B": block_m, + "BLOCK_V": block_n, + "BLOCK_D": block_k, + }, + num_stages=num_stages, + num_warps=num_warps, + ) + ) + return configs + + +def get_autotune_config(): + return [ + # basic configs for compute-bound matmuls + Config( + {"BLOCK_B": 128, "BLOCK_V": 128, "BLOCK_D": 128}, + num_stages=2, + num_warps=4, + ), + Config( + {"BLOCK_B": 128, "BLOCK_V": 256, "BLOCK_D": 32}, + num_stages=3, + num_warps=8, + ), + Config( + {"BLOCK_B": 256, "BLOCK_V": 128, "BLOCK_D": 32}, + num_stages=3, + num_warps=8, + ), + Config( + {"BLOCK_B": 256, "BLOCK_V": 64, "BLOCK_D": 32}, + num_stages=4, + num_warps=4, + ), + Config( + {"BLOCK_B": 64, "BLOCK_V": 256, "BLOCK_D": 32}, + num_stages=4, + num_warps=4, + ), + Config( + {"BLOCK_B": 128, "BLOCK_V": 128, "BLOCK_D": 32}, + num_stages=4, + num_warps=4, + ), + Config( + {"BLOCK_B": 128, "BLOCK_V": 128, "BLOCK_D": 32}, + num_stages=3, + num_warps=8, + ), + Config( + {"BLOCK_B": 128, "BLOCK_V": 128, "BLOCK_D": 32}, + num_stages=4, + num_warps=8, + ), + Config( + {"BLOCK_B": 128, "BLOCK_V": 64, "BLOCK_D": 32}, + num_stages=4, + num_warps=4, + ), + Config( + {"BLOCK_B": 64, "BLOCK_V": 128, "BLOCK_D": 32}, + num_stages=4, + num_warps=4, + ), + Config( + {"BLOCK_B": 128, "BLOCK_V": 32, "BLOCK_D": 32}, + num_stages=4, + num_warps=4, + ), + Config({"BLOCK_B": 64, "BLOCK_V": 32, "BLOCK_D": 32}, num_stages=5, num_warps=2), + # good for int8 + Config( + {"BLOCK_B": 128, "BLOCK_V": 256, "BLOCK_D": 128}, + num_stages=3, + num_warps=8, + ), + Config( + {"BLOCK_B": 128, "BLOCK_V": 256, "BLOCK_D": 128}, + num_stages=3, + num_warps=16, + ), + Config( + {"BLOCK_B": 256, "BLOCK_V": 128, "BLOCK_D": 128}, + num_stages=3, + num_warps=8, + ), + Config( + {"BLOCK_B": 256, "BLOCK_V": 128, "BLOCK_D": 128}, + num_stages=3, + num_warps=16, + ), + Config( + {"BLOCK_B": 256, "BLOCK_V": 64, "BLOCK_D": 128}, + num_stages=4, + num_warps=4, + ), + Config( + {"BLOCK_B": 64, "BLOCK_V": 256, "BLOCK_D": 128}, + num_stages=4, + num_warps=4, + ), + Config( + {"BLOCK_B": 128, "BLOCK_V": 128, "BLOCK_D": 128}, + num_stages=4, + num_warps=4, + ), + Config( + {"BLOCK_B": 128, "BLOCK_V": 64, "BLOCK_D": 64}, + num_stages=4, + num_warps=4, + ), + Config( + {"BLOCK_B": 64, "BLOCK_V": 128, "BLOCK_D": 64}, + num_stages=4, + num_warps=4, + ), + Config( + {"BLOCK_B": 128, "BLOCK_V": 32, "BLOCK_D": 64}, + num_stages=4, + num_warps=4, + ), + Config({"BLOCK_B": 64, "BLOCK_V": 32, "BLOCK_D": 64}, num_stages=5, num_warps=2), + ] + get_configs_io_bound() + + +def _heuristics_from_config(config: Config) -> Callable[..., autotuner.Heuristics]: + return triton.heuristics({k: (lambda args, _v=v: _v) for k, v in config.all_kwargs().items()}) + + +def _cce_forward_best_config() -> Config: + return Config(dict(BLOCK_B=256, BLOCK_V=128, BLOCK_D=32), num_warps=8, num_stages=3) + + +def cce_forward_autotune() -> Callable[..., autotuner.Autotuner | autotuner.Heuristics]: + if _AUTOTUNE: + return triton.autotune( + configs=get_autotune_config(), + key=["V", "D", "B_BIN"], + prune_configs_by={ + "early_config_prune": early_config_prune, + "perf_model": estimate_matmul_time, + "top_k": 10, + }, + restore_value=["LSE"], + ) + else: + return _heuristics_from_config(_cce_forward_best_config()) + + +def _bw_total_ops_fn(B, V, D) -> float: + return 2 * B * V * D + 6 * B * V + 0.2 * (2 * B * V * D + 2 * B * V * D) + + +def _bw_total_store_fn(B, V, D, dtsize, num_cta_b, num_cta_v): + return 0.2 * (num_cta_v * B * D * dtsize + num_cta_b * D * V * dtsize) + + +def _cce_backward_best_config() -> Config: + return Config(dict(BLOCK_B=128, BLOCK_V=128, BLOCK_D=32), num_warps=4, num_stages=4) + + +def cce_backward_autotune() -> Callable[..., autotuner.Autotuner | autotuner.Heuristics]: + if _AUTOTUNE: + return triton.autotune( + configs=get_autotune_config(), + key=["V", "D", "B_BIN"], + prune_configs_by={ + "early_config_prune": functools.partial( + early_config_prune, shared_memory_factor=2.0 + ), + "perf_model": functools.partial( + estimate_matmul_time, + total_ops_fn=_bw_total_ops_fn, + total_store_fn=_bw_total_store_fn, + ), + "top_k": 5, + }, + reset_to_zero=["dE", "dC"], + ) + else: + return _heuristics_from_config(_cce_backward_best_config()) + + +def _indexed_dot_best_config() -> Config: + return Config(dict(BLOCK_B=128, BLOCK_D=256), num_warps=16, num_stages=4) + + +def _indexed_dot_all_configs() -> list[Config]: + return [ + Config( + dict( + BLOCK_B=128, + BLOCK_D=128, + ), + num_warps=4, + num_stages=4, + ), + Config( + dict( + BLOCK_B=128, + BLOCK_D=128, + ), + num_warps=8, + num_stages=4, + ), + Config( + dict( + BLOCK_B=256, + BLOCK_D=256, + ), + num_warps=16, + num_stages=4, + ), + Config( + dict( + BLOCK_B=256, + BLOCK_D=128, + ), + num_warps=16, + num_stages=4, + ), + Config( + dict( + BLOCK_B=128, + BLOCK_D=256, + ), + num_warps=16, + num_stages=4, + ), + ] + + +def indexed_dot_autotune() -> Callable[..., autotuner.Autotuner | autotuner.Heuristics]: + if _AUTOTUNE: + return triton.autotune( + configs=_indexed_dot_all_configs(), + key=["D", "B_BIN"], + reset_to_zero=["Out"], + ) + else: + return _heuristics_from_config(_indexed_dot_best_config()) diff --git a/cut_cross_entropy/tl_utils.py b/cut_cross_entropy/tl_utils.py new file mode 100644 index 0000000000000000000000000000000000000000..adc1d8e9b0c6cb746983589d7da6bc8b3fdb230f --- /dev/null +++ b/cut_cross_entropy/tl_utils.py @@ -0,0 +1,58 @@ +# Copyright (C) 2024 Apple Inc. All Rights Reserved. +import triton +import triton.language as tl +from triton.language.extra import libdevice as tl_libdevice + + +@triton.jit +def tl_and_reduce_fn(a, b): + return a & b + + +@triton.jit +def tl_tanh(a: tl.tensor) -> tl.tensor: + return tl_libdevice.tanh(a) + + +@triton.jit +def tl_log1p(a: tl.tensor) -> tl.tensor: + return tl_libdevice.log1p(a) + + +@triton.jit +def tl_softcapping(v: tl.tensor, softcap: float) -> tl.tensor: + return tl_tanh(v / softcap) * softcap + + +@triton.jit +def tl_softcapping_grad(dv: tl.tensor, v: tl.tensor, softcap: float) -> tl.tensor: + v = v / softcap + return dv * (1 - v * v) + + +@triton.jit +def tl_logaddexp(a, b) -> tl.tensor: + minx = tl.minimum(a, b) + mx = tl.maximum(a, b) + return tl_log1p(tl.exp(minx - mx)) + mx + + +@triton.jit +def tl_lock_add(ptrs, v, mask, lock_ptr): + while tl.atomic_cas(lock_ptr, 0, 1) == 1: + pass + + cur_v = tl.load(ptrs, mask=mask, other=0.0, eviction_policy="evict_last") + new_v = v + cur_v + tl.store(ptrs, new_v, mask=mask, eviction_policy="evict_last") + + tl.atomic_xchg(lock_ptr, 0) + + +def b_bin_fn(b: int) -> int: + if b >= 1024: + return 1024 + elif b <= 128: + return 128 + else: + return 512 diff --git a/cut_cross_entropy/torch_compile.py b/cut_cross_entropy/torch_compile.py new file mode 100644 index 0000000000000000000000000000000000000000..0a65f942360fe5648fd835cd2d9c315b01c0effc --- /dev/null +++ b/cut_cross_entropy/torch_compile.py @@ -0,0 +1,75 @@ +# Copyright (C) 2024 Apple Inc. All Rights Reserved. +import torch +import torch.nn.functional as F + +from cut_cross_entropy.constants import IGNORE_INDEX +from cut_cross_entropy.doc import LINEAR_CROSS_ENTROPY_DOC, add_doc_start +from cut_cross_entropy.utils import ( + _build_flat_valids, + handle_reduction_none, + softcapping, +) + + +@torch.compile(fullgraph=True, dynamic=True) +def torch_compile_linear_cross_entropy_apply( + e: torch.Tensor, + c: torch.Tensor, + targets: torch.Tensor, + softcap: float | None = None, + *, + ignore_index: int = IGNORE_INDEX, + reduction: str = "mean", +) -> torch.Tensor: + logits = e @ c.T + + if softcap is not None: + logits = softcapping(logits, softcap) + + loss = F.cross_entropy(logits.float(), targets, ignore_index=ignore_index, reduction=reduction) + + return loss + + +@add_doc_start(LINEAR_CROSS_ENTROPY_DOC) +def torch_compile_linear_cross_entropy( + e: torch.Tensor, + c: torch.Tensor, + targets: torch.Tensor, + ignore_index: int = IGNORE_INDEX, + softcap: float | None = None, + reduction: str = "mean", + shift: bool = False, +) -> torch.Tensor: + assert e.size()[0:-1] == targets.size() + assert e.size(-1) == c.size(1) + + orig_b_size = targets.size() + e = e.contiguous() + targets = targets.contiguous() + + valids = _build_flat_valids(targets, ignore_index, shift) + + e = e.flatten(0, -2) + targets = targets.flatten() + + if valids is not None: + e = e[valids] + targets = targets[(valids + 1) if shift else valids] + + loss = torch_compile_linear_cross_entropy_apply( + e, + c, + targets, + softcap, + ignore_index=ignore_index, + reduction=reduction, + ) + + if reduction == "none": + loss = handle_reduction_none(orig_b_size, valids, shift, loss) + + if shift: + loss = loss[..., 1:] + + return loss diff --git a/cut_cross_entropy/utils.py b/cut_cross_entropy/utils.py new file mode 100644 index 0000000000000000000000000000000000000000..aff4c27a3b19537d08584b2c26a720bac81fcf90 --- /dev/null +++ b/cut_cross_entropy/utils.py @@ -0,0 +1,61 @@ +# Copyright (C) 2024 Apple Inc. All Rights Reserved. +import torch + + +@torch.compile(fullgraph=True, dynamic=True) +def softcapping(logits: torch.Tensor, softcap: float) -> torch.Tensor: + return torch.tanh(logits / softcap) * softcap + + +def _handle_eps(filter_eps: float | str | None, dtype: torch.dtype) -> float | None: + match filter_eps: + case None: + return None + case float(): + return filter_eps + case "auto": + # bfloat16 eps = 0.0078125 / 32 = 0.000244140625 + # float16 eps = 0.0009765625 / 32 = 0.000030517578125 + return torch.finfo(dtype).eps / 32 + case "high": + # bfloat16 eps = 0.0078125 / 32 = 0.000244140625 + # float16 eps = 0.0009765625 / 32 = 0.000030517578125 + return torch.finfo(dtype).eps / 32 + case _: + raise RuntimeError(f"Unknown eps {filter_eps}") + + +def _build_flat_valids( + targets: torch.Tensor, + ignore_index: int, + shift: bool, +) -> torch.Tensor | None: + if shift: + targets = targets[..., 1:] + else: + targets = targets.flatten() + + valids = (targets != ignore_index).nonzero().to(torch.int32) + + if not shift: + assert valids.size(1) == 1 + return valids.squeeze(1) if valids.numel() != targets.numel() else None + + for i in range(targets.ndim - 1): + valids[:, i] *= targets.stride(i) + + assert targets.stride(-1) == 1 + + return valids.sum(1) + + +def handle_reduction_none( + batch_shape: torch.Size, valids: torch.Tensor | None, shift: bool, loss: torch.Tensor +) -> torch.Tensor: + if valids is None: + return loss.view(batch_shape) + + full_loss = loss.new_zeros((batch_shape.numel(),)) + full_loss[(valids + 1) if shift else valids] = loss + + return full_loss.view(batch_shape) diff --git a/dill/__diff.py b/dill/__diff.py new file mode 100644 index 0000000000000000000000000000000000000000..63e81826dabf1e62287295417051d7baf39d74d1 --- /dev/null +++ b/dill/__diff.py @@ -0,0 +1,234 @@ +#!/usr/bin/env python +# +# Author: Mike McKerns (mmckerns @caltech and @uqfoundation) +# Copyright (c) 2008-2016 California Institute of Technology. +# Copyright (c) 2016-2025 The Uncertainty Quantification Foundation. +# License: 3-clause BSD. The full license text is available at: +# - https://github.com/uqfoundation/dill/blob/master/LICENSE + +""" +Module to show if an object has changed since it was memorised +""" + +import builtins +import os +import sys +import types +try: + import numpy.ma + HAS_NUMPY = True +except ImportError: + HAS_NUMPY = False + +# pypy doesn't use reference counting +getrefcount = getattr(sys, 'getrefcount', lambda x:0) + +# memo of objects indexed by id to a tuple (attributes, sequence items) +# attributes is a dict indexed by attribute name to attribute id +# sequence items is either a list of ids, of a dictionary of keys to ids +memo = {} +id_to_obj = {} +# types that cannot have changing attributes +builtins_types = set((str, list, dict, set, frozenset, int)) +dont_memo = set(id(i) for i in (memo, sys.modules, sys.path_importer_cache, + os.environ, id_to_obj)) + + +def get_attrs(obj): + """ + Gets all the attributes of an object though its __dict__ or return None + """ + if type(obj) in builtins_types \ + or type(obj) is type and obj in builtins_types: + return + return getattr(obj, '__dict__', None) + + +def get_seq(obj, cache={str: False, frozenset: False, list: True, set: True, + dict: True, tuple: True, type: False, + types.ModuleType: False, types.FunctionType: False, + types.BuiltinFunctionType: False}): + """ + Gets all the items in a sequence or return None + """ + try: + o_type = obj.__class__ + except AttributeError: + o_type = type(obj) + hsattr = hasattr + if o_type in cache: + if cache[o_type]: + if hsattr(obj, "copy"): + return obj.copy() + return obj + elif HAS_NUMPY and o_type in (numpy.ndarray, numpy.ma.core.MaskedConstant): + if obj.shape and obj.size: + return obj + else: + return [] + elif hsattr(obj, "__contains__") and hsattr(obj, "__iter__") \ + and hsattr(obj, "__len__") and hsattr(o_type, "__contains__") \ + and hsattr(o_type, "__iter__") and hsattr(o_type, "__len__"): + cache[o_type] = True + if hsattr(obj, "copy"): + return obj.copy() + return obj + else: + cache[o_type] = False + return None + + +def memorise(obj, force=False): + """ + Adds an object to the memo, and recursively adds all the objects + attributes, and if it is a container, its items. Use force=True to update + an object already in the memo. Updating is not recursively done. + """ + obj_id = id(obj) + if obj_id in memo and not force or obj_id in dont_memo: + return + id_ = id + g = get_attrs(obj) + if g is None: + attrs_id = None + else: + attrs_id = dict((key,id_(value)) for key, value in g.items()) + + s = get_seq(obj) + if s is None: + seq_id = None + elif hasattr(s, "items"): + seq_id = dict((id_(key),id_(value)) for key, value in s.items()) + elif not hasattr(s, "__len__"): #XXX: avoid TypeError from unexpected case + seq_id = None + else: + seq_id = [id_(i) for i in s] + + memo[obj_id] = attrs_id, seq_id + id_to_obj[obj_id] = obj + mem = memorise + if g is not None: + [mem(value) for key, value in g.items()] + + if s is not None: + if hasattr(s, "items"): + [(mem(key), mem(item)) + for key, item in s.items()] + else: + if hasattr(s, '__len__'): + [mem(item) for item in s] + else: mem(s) + + +def release_gone(): + itop, mp, src = id_to_obj.pop, memo.pop, getrefcount + [(itop(id_), mp(id_)) for id_, obj in list(id_to_obj.items()) + if src(obj) < 4] #XXX: correct for pypy? + + +def whats_changed(obj, seen=None, simple=False, first=True): + """ + Check an object against the memo. Returns a list in the form + (attribute changes, container changed). Attribute changes is a dict of + attribute name to attribute value. container changed is a boolean. + If simple is true, just returns a boolean. None for either item means + that it has not been checked yet + """ + # Special cases + if first: + # ignore the _ variable, which only appears in interactive sessions + if "_" in builtins.__dict__: + del builtins._ + if seen is None: + seen = {} + + obj_id = id(obj) + + if obj_id in seen: + if simple: + return any(seen[obj_id]) + return seen[obj_id] + + # Safety checks + if obj_id in dont_memo: + seen[obj_id] = [{}, False] + if simple: + return False + return seen[obj_id] + elif obj_id not in memo: + if simple: + return True + else: + raise RuntimeError("Object not memorised " + str(obj)) + + seen[obj_id] = ({}, False) + + chngd = whats_changed + id_ = id + + # compare attributes + attrs = get_attrs(obj) + if attrs is None: + changed = {} + else: + obj_attrs = memo[obj_id][0] + obj_get = obj_attrs.get + changed = dict((key,None) for key in obj_attrs if key not in attrs) + for key, o in attrs.items(): + if id_(o) != obj_get(key, None) or chngd(o, seen, True, False): + changed[key] = o + + # compare sequence + items = get_seq(obj) + seq_diff = False + if (items is not None) and (hasattr(items, '__len__')): + obj_seq = memo[obj_id][1] + if (len(items) != len(obj_seq)): + seq_diff = True + elif hasattr(obj, "items"): # dict type obj + obj_get = obj_seq.get + for key, item in items.items(): + if id_(item) != obj_get(id_(key)) \ + or chngd(key, seen, True, False) \ + or chngd(item, seen, True, False): + seq_diff = True + break + else: + for i, j in zip(items, obj_seq): # list type obj + if id_(i) != j or chngd(i, seen, True, False): + seq_diff = True + break + seen[obj_id] = changed, seq_diff + if simple: + return changed or seq_diff + return changed, seq_diff + + +def has_changed(*args, **kwds): + kwds['simple'] = True # ignore simple if passed in + return whats_changed(*args, **kwds) + +__import__ = __import__ + + +def _imp(*args, **kwds): + """ + Replaces the default __import__, to allow a module to be memorised + before the user can change it + """ + before = set(sys.modules.keys()) + mod = __import__(*args, **kwds) + after = set(sys.modules.keys()).difference(before) + for m in after: + memorise(sys.modules[m]) + return mod + +builtins.__import__ = _imp +if hasattr(builtins, "_"): + del builtins._ + +# memorise all already imported modules. This implies that this must be +# imported first for any changes to be recorded +for mod in list(sys.modules.values()): + memorise(mod) +release_gone() diff --git a/dill/__info__.py b/dill/__info__.py new file mode 100644 index 0000000000000000000000000000000000000000..e71bdfa31b6dcc0ae13f9c77282f5bb6d04be2d2 --- /dev/null +++ b/dill/__info__.py @@ -0,0 +1,291 @@ +#!/usr/bin/env python +# +# Author: Mike McKerns (mmckerns @caltech and @uqfoundation) +# Copyright (c) 2025 The Uncertainty Quantification Foundation. +# License: 3-clause BSD. The full license text is available at: +# - https://github.com/uqfoundation/dill/blob/master/LICENSE +''' +----------------------------- +dill: serialize all of Python +----------------------------- + +About Dill +========== + +``dill`` extends Python's ``pickle`` module for serializing and de-serializing +Python objects to the majority of the built-in Python types. Serialization +is the process of converting an object to a byte stream, and the inverse +of which is converting a byte stream back to a Python object hierarchy. + +``dill`` provides the user the same interface as the ``pickle`` module, and +also includes some additional features. In addition to pickling Python +objects, ``dill`` provides the ability to save the state of an interpreter +session in a single command. Hence, it would be feasible to save an +interpreter session, close the interpreter, ship the pickled file to +another computer, open a new interpreter, unpickle the session and +thus continue from the 'saved' state of the original interpreter +session. + +``dill`` can be used to store Python objects to a file, but the primary +usage is to send Python objects across the network as a byte stream. +``dill`` is quite flexible, and allows arbitrary user defined classes +and functions to be serialized. Thus ``dill`` is not intended to be +secure against erroneously or maliciously constructed data. It is +left to the user to decide whether the data they unpickle is from +a trustworthy source. + +``dill`` is part of ``pathos``, a Python framework for heterogeneous computing. +``dill`` is in active development, so any user feedback, bug reports, comments, +or suggestions are highly appreciated. A list of issues is located at +https://github.com/uqfoundation/dill/issues, with a legacy list maintained at +https://uqfoundation.github.io/project/pathos/query. + + +Major Features +============== + +``dill`` can pickle the following standard types: + + - none, type, bool, int, float, complex, bytes, str, + - tuple, list, dict, file, buffer, builtin, + - Python classes, namedtuples, dataclasses, metaclasses, + - instances of classes, + - set, frozenset, array, functions, exceptions + +``dill`` can also pickle more 'exotic' standard types: + + - functions with yields, nested functions, lambdas, + - cell, method, unboundmethod, module, code, methodwrapper, + - methoddescriptor, getsetdescriptor, memberdescriptor, wrapperdescriptor, + - dictproxy, slice, notimplemented, ellipsis, quit + +``dill`` cannot yet pickle these standard types: + + - frame, generator, traceback + +``dill`` also provides the capability to: + + - save and load Python interpreter sessions + - save and extract the source code from functions and classes + - interactively diagnose pickling errors + + +Current Release +=============== + +The latest released version of ``dill`` is available from: + + https://pypi.org/project/dill + +``dill`` is distributed under a 3-clause BSD license. + + +Development Version +=================== + +You can get the latest development version with all the shiny new features at: + + https://github.com/uqfoundation + +If you have a new contribution, please submit a pull request. + + +Installation +============ + +``dill`` can be installed with ``pip``:: + + $ pip install dill + +To optionally include the ``objgraph`` diagnostic tool in the install:: + + $ pip install dill[graph] + +To optionally include the ``gprof2dot`` diagnostic tool in the install:: + + $ pip install dill[profile] + +For windows users, to optionally install session history tools:: + + $ pip install dill[readline] + + +Requirements +============ + +``dill`` requires: + + - ``python`` (or ``pypy``), **>=3.8** + - ``setuptools``, **>=42** + +Optional requirements: + + - ``objgraph``, **>=1.7.2** + - ``gprof2dot``, **>=2022.7.29** + - ``pyreadline``, **>=1.7.1** (on windows) + + +Basic Usage +=========== + +``dill`` is a drop-in replacement for ``pickle``. Existing code can be +updated to allow complete pickling using:: + + >>> import dill as pickle + +or:: + + >>> from dill import dumps, loads + +``dumps`` converts the object to a unique byte string, and ``loads`` performs +the inverse operation:: + + >>> squared = lambda x: x**2 + >>> loads(dumps(squared))(3) + 9 + +There are a number of options to control serialization which are provided +as keyword arguments to several ``dill`` functions: + +* with *protocol*, the pickle protocol level can be set. This uses the + same value as the ``pickle`` module, *DEFAULT_PROTOCOL*. +* with *byref=True*, ``dill`` to behave a lot more like pickle with + certain objects (like modules) pickled by reference as opposed to + attempting to pickle the object itself. +* with *recurse=True*, objects referred to in the global dictionary are + recursively traced and pickled, instead of the default behavior of + attempting to store the entire global dictionary. +* with *fmode*, the contents of the file can be pickled along with the file + handle, which is useful if the object is being sent over the wire to a + remote system which does not have the original file on disk. Options are + *HANDLE_FMODE* for just the handle, *CONTENTS_FMODE* for the file content + and *FILE_FMODE* for content and handle. +* with *ignore=False*, objects reconstructed with types defined in the + top-level script environment use the existing type in the environment + rather than a possibly different reconstructed type. + +The default serialization can also be set globally in *dill.settings*. +Thus, we can modify how ``dill`` handles references to the global dictionary +locally or globally:: + + >>> import dill.settings + >>> dumps(absolute) == dumps(absolute, recurse=True) + False + >>> dill.settings['recurse'] = True + >>> dumps(absolute) == dumps(absolute, recurse=True) + True + +``dill`` also includes source code inspection, as an alternate to pickling:: + + >>> import dill.source + >>> print(dill.source.getsource(squared)) + squared = lambda x:x**2 + +To aid in debugging pickling issues, use *dill.detect* which provides +tools like pickle tracing:: + + >>> import dill.detect + >>> with dill.detect.trace(): + >>> dumps(squared) + ┬ F1: at 0x7fe074f8c280> + ├┬ F2: + │└ # F2 [34 B] + ├┬ Co: at 0x7fe07501eb30, file "", line 1> + │├┬ F2: + ││└ # F2 [19 B] + │└ # Co [87 B] + ├┬ D1: + │└ # D1 [22 B] + ├┬ D2: + │└ # D2 [2 B] + ├┬ D2: + │├┬ D2: + ││└ # D2 [2 B] + │└ # D2 [23 B] + └ # F1 [180 B] + +With trace, we see how ``dill`` stored the lambda (``F1``) by first storing +``_create_function``, the underlying code object (``Co``) and ``_create_code`` +(which is used to handle code objects), then we handle the reference to +the global dict (``D2``) plus other dictionaries (``D1`` and ``D2``) that +save the lambda object's state. A ``#`` marks when the object is actually stored. + + +More Information +================ + +Probably the best way to get started is to look at the documentation at +http://dill.rtfd.io. Also see ``dill.tests`` for a set of scripts that +demonstrate how ``dill`` can serialize different Python objects. You can +run the test suite with ``python -m dill.tests``. The contents of any +pickle file can be examined with ``undill``. As ``dill`` conforms to +the ``pickle`` interface, the examples and documentation found at +http://docs.python.org/library/pickle.html also apply to ``dill`` +if one will ``import dill as pickle``. The source code is also generally +well documented, so further questions may be resolved by inspecting the +code itself. Please feel free to submit a ticket on github, or ask a +question on stackoverflow (**@Mike McKerns**). +If you would like to share how you use ``dill`` in your work, please send +an email (to **mmckerns at uqfoundation dot org**). + + +Citation +======== + +If you use ``dill`` to do research that leads to publication, we ask that you +acknowledge use of ``dill`` by citing the following in your publication:: + + M.M. McKerns, L. Strand, T. Sullivan, A. Fang, M.A.G. Aivazis, + "Building a framework for predictive science", Proceedings of + the 10th Python in Science Conference, 2011; + http://arxiv.org/pdf/1202.1056 + + Michael McKerns and Michael Aivazis, + "pathos: a framework for heterogeneous computing", 2010- ; + https://uqfoundation.github.io/project/pathos + +Please see https://uqfoundation.github.io/project/pathos or +http://arxiv.org/pdf/1202.1056 for further information. + +''' + +__version__ = '0.4.0' +__author__ = 'Mike McKerns' + +__license__ = ''' +Copyright (c) 2004-2016 California Institute of Technology. +Copyright (c) 2016-2025 The Uncertainty Quantification Foundation. +All rights reserved. + +This software is available subject to the conditions and terms laid +out below. By downloading and using this software you are agreeing +to the following conditions. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions +are met: + + - Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + + - Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + + - Neither the names of the copyright holders nor the names of any of + the contributors may be used to endorse or promote products derived + from this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS +"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED +TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR +PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR +CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, +EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, +PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; +OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, +WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR +OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF +ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + +''' diff --git a/dill/__init__.py b/dill/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..7fc930c1383232a06779d82a30146b5d12d6281a --- /dev/null +++ b/dill/__init__.py @@ -0,0 +1,119 @@ +#!/usr/bin/env python +# +# Author: Mike McKerns (mmckerns @caltech and @uqfoundation) +# Copyright (c) 2008-2016 California Institute of Technology. +# Copyright (c) 2016-2025 The Uncertainty Quantification Foundation. +# License: 3-clause BSD. The full license text is available at: +# - https://github.com/uqfoundation/dill/blob/master/LICENSE + +# author, version, license, and long description +try: # the package is installed + from .__info__ import __version__, __author__, __doc__, __license__ +except: # pragma: no cover + import os + import sys + parent = os.path.dirname(os.path.abspath(os.path.dirname(__file__))) + sys.path.append(parent) + # get distribution meta info + from version import (__version__, __author__, + get_license_text, get_readme_as_rst) + __license__ = get_license_text(os.path.join(parent, 'LICENSE')) + __license__ = "\n%s" % __license__ + __doc__ = get_readme_as_rst(os.path.join(parent, 'README.md')) + del os, sys, parent, get_license_text, get_readme_as_rst + + +from ._dill import ( + dump, dumps, load, loads, copy, + Pickler, Unpickler, register, pickle, pickles, check, + DEFAULT_PROTOCOL, HIGHEST_PROTOCOL, HANDLE_FMODE, CONTENTS_FMODE, FILE_FMODE, + PickleError, PickleWarning, PicklingError, PicklingWarning, UnpicklingError, + UnpicklingWarning, +) +from .session import ( + dump_module, load_module, load_module_asdict, + dump_session, load_session # backward compatibility +) +from . import detect, logger, session, source, temp + +# get global settings +from .settings import settings + +# make sure "trace" is turned off +logger.trace(False) + +objects = {} +# local import of dill._objects +#from . import _objects +#objects.update(_objects.succeeds) +#del _objects + +# local import of dill.objtypes +from . import objtypes as types + +def load_types(pickleable=True, unpickleable=True): + """load pickleable and/or unpickleable types to ``dill.types`` + + ``dill.types`` is meant to mimic the ``types`` module, providing a + registry of object types. By default, the module is empty (for import + speed purposes). Use the ``load_types`` function to load selected object + types to the ``dill.types`` module. + + Args: + pickleable (bool, default=True): if True, load pickleable types. + unpickleable (bool, default=True): if True, load unpickleable types. + + Returns: + None + """ + from importlib import reload + # local import of dill.objects + from . import _objects + if pickleable: + objects.update(_objects.succeeds) + else: + [objects.pop(obj,None) for obj in _objects.succeeds] + if unpickleable: + objects.update(_objects.failures) + else: + [objects.pop(obj,None) for obj in _objects.failures] + objects.update(_objects.registered) + del _objects + # reset contents of types to 'empty' + [types.__dict__.pop(obj) for obj in list(types.__dict__.keys()) \ + if obj.find('Type') != -1] + # add corresponding types from objects to types + reload(types) + +def extend(use_dill=True): + '''add (or remove) dill types to/from the pickle registry + + by default, ``dill`` populates its types to ``pickle.Pickler.dispatch``. + Thus, all ``dill`` types are available upon calling ``'import pickle'``. + To drop all ``dill`` types from the ``pickle`` dispatch, *use_dill=False*. + + Args: + use_dill (bool, default=True): if True, extend the dispatch table. + + Returns: + None + ''' + from ._dill import _revert_extension, _extend + if use_dill: _extend() + else: _revert_extension() + return + +extend() + + +def license(): + """print license""" + print (__license__) + return + +def citation(): + """print citation""" + print (__doc__[-491:-118]) + return + +# end of file diff --git a/dill/_dill.py b/dill/_dill.py new file mode 100644 index 0000000000000000000000000000000000000000..aec297c49a9b97cba26a8072cae81ec0318f4a11 --- /dev/null +++ b/dill/_dill.py @@ -0,0 +1,2255 @@ +# -*- coding: utf-8 -*- +# +# Author: Mike McKerns (mmckerns @caltech and @uqfoundation) +# Copyright (c) 2008-2015 California Institute of Technology. +# Copyright (c) 2016-2025 The Uncertainty Quantification Foundation. +# License: 3-clause BSD. The full license text is available at: +# - https://github.com/uqfoundation/dill/blob/master/LICENSE +""" +dill: a utility for serialization of python objects + +The primary functions in `dill` are :func:`dump` and +:func:`dumps` for serialization ("pickling") to a +file or to a string, respectively, and :func:`load` +and :func:`loads` for deserialization ("unpickling"), +similarly, from a file or from a string. Other notable +functions are :func:`~dill.dump_module` and +:func:`~dill.load_module`, which are used to save and +restore module objects, including an intepreter session. + +Based on code written by Oren Tirosh and Armin Ronacher. +Extended to a (near) full set of the builtin types (in types module), +and coded to the pickle interface, by . +Initial port to python3 by Jonathan Dobson, continued by mmckerns. +Tested against "all" python types (Std. Lib. CH 1-15 @ 2.7) by mmckerns. +Tested against CH16+ Std. Lib. ... TBD. +""" + +from __future__ import annotations + +__all__ = [ + 'dump','dumps','load','loads','copy', + 'Pickler','Unpickler','register','pickle','pickles','check', + 'DEFAULT_PROTOCOL','HIGHEST_PROTOCOL','HANDLE_FMODE','CONTENTS_FMODE','FILE_FMODE', + 'PickleError','PickleWarning','PicklingError','PicklingWarning','UnpicklingError', + 'UnpicklingWarning', +] + +__module__ = 'dill' + +import warnings +from .logger import adapter as logger +from .logger import trace as _trace +log = logger # backward compatibility (see issue #582) + +import os +import sys +diff = None +_use_diff = False +OLD38 = (sys.hexversion < 0x3080000) +OLD39 = (sys.hexversion < 0x3090000) +OLD310 = (sys.hexversion < 0x30a0000) +OLD312a7 = (sys.hexversion < 0x30c00a7) +#XXX: get types from .objtypes ? +import builtins as __builtin__ +from pickle import _Pickler as StockPickler, Unpickler as StockUnpickler +from pickle import GLOBAL, POP +from _thread import LockType +from _thread import RLock as RLockType +try: + from _thread import _ExceptHookArgs as ExceptHookArgsType +except ImportError: + ExceptHookArgsType = None +try: + from _thread import _ThreadHandle as ThreadHandleType +except ImportError: + ThreadHandleType = None +#from io import IOBase +from types import CodeType, FunctionType, MethodType, GeneratorType, \ + TracebackType, FrameType, ModuleType, BuiltinMethodType +BufferType = memoryview #XXX: unregistered +ClassType = type # no 'old-style' classes +EllipsisType = type(Ellipsis) +#FileType = IOBase +NotImplementedType = type(NotImplemented) +SliceType = slice +TypeType = type # 'new-style' classes #XXX: unregistered +XRangeType = range +from types import MappingProxyType as DictProxyType, new_class +from pickle import DEFAULT_PROTOCOL, HIGHEST_PROTOCOL, PickleError, PicklingError, UnpicklingError +import __main__ as _main_module +import marshal +import gc +# import zlib +import abc +import dataclasses +from weakref import ReferenceType, ProxyType, CallableProxyType +from collections import OrderedDict +from enum import Enum, EnumMeta +from functools import partial +from operator import itemgetter, attrgetter +GENERATOR_FAIL = False +import importlib.machinery +EXTENSION_SUFFIXES = tuple(importlib.machinery.EXTENSION_SUFFIXES) +try: + import ctypes + HAS_CTYPES = True + # if using `pypy`, pythonapi is not found + IS_PYPY = not hasattr(ctypes, 'pythonapi') +except ImportError: + HAS_CTYPES = False + IS_PYPY = False +NumpyUfuncType = None +NumpyDType = None +NumpyArrayType = None +try: + if not importlib.machinery.PathFinder().find_spec('numpy'): + raise ImportError("No module named 'numpy'") + NumpyUfuncType = True + NumpyDType = True + NumpyArrayType = True +except ImportError: + pass +def __hook__(): + global NumpyArrayType, NumpyDType, NumpyUfuncType + from numpy import ufunc as NumpyUfuncType + from numpy import ndarray as NumpyArrayType + from numpy import dtype as NumpyDType + return True +if NumpyArrayType: # then has numpy + def ndarraysubclassinstance(obj_type): + if all((c.__module__, c.__name__) != ('numpy', 'ndarray') for c in obj_type.__mro__): + return False + # anything below here is a numpy array (or subclass) instance + __hook__() # import numpy (so the following works!!!) + # verify that __reduce__ has not been overridden + if obj_type.__reduce_ex__ is not NumpyArrayType.__reduce_ex__ \ + or obj_type.__reduce__ is not NumpyArrayType.__reduce__: + return False + return True + def numpyufunc(obj_type): + return any((c.__module__, c.__name__) == ('numpy', 'ufunc') for c in obj_type.__mro__) + def numpydtype(obj_type): + if all((c.__module__, c.__name__) != ('numpy', 'dtype') for c in obj_type.__mro__): + return False + # anything below here is a numpy dtype + __hook__() # import numpy (so the following works!!!) + return obj_type is type(NumpyDType) # handles subclasses +else: + def ndarraysubclassinstance(obj): return False + def numpyufunc(obj): return False + def numpydtype(obj): return False + +from types import GetSetDescriptorType, ClassMethodDescriptorType, \ + WrapperDescriptorType, MethodDescriptorType, MemberDescriptorType, \ + MethodWrapperType #XXX: unused + +# make sure to add these 'hand-built' types to _typemap +CellType = type((lambda x: lambda y: x)(0).__closure__[0]) +PartialType = type(partial(int, base=2)) +SuperType = type(super(Exception, TypeError())) +ItemGetterType = type(itemgetter(0)) +AttrGetterType = type(attrgetter('__repr__')) + +try: + from functools import _lru_cache_wrapper as LRUCacheType +except ImportError: + LRUCacheType = None + +if not isinstance(LRUCacheType, type): + LRUCacheType = None + +def get_file_type(*args, **kwargs): + open = kwargs.pop("open", __builtin__.open) + f = open(os.devnull, *args, **kwargs) + t = type(f) + f.close() + return t + +IS_PYODIDE = sys.platform == 'emscripten' + +FileType = get_file_type('rb', buffering=0) +TextWrapperType = get_file_type('r', buffering=-1) +BufferedRandomType = None if IS_PYODIDE else get_file_type('r+b', buffering=-1) +BufferedReaderType = get_file_type('rb', buffering=-1) +BufferedWriterType = get_file_type('wb', buffering=-1) +try: + from _pyio import open as _open + PyTextWrapperType = get_file_type('r', buffering=-1, open=_open) + PyBufferedRandomType = None if IS_PYODIDE else get_file_type('r+b', buffering=-1, open=_open) + PyBufferedReaderType = get_file_type('rb', buffering=-1, open=_open) + PyBufferedWriterType = get_file_type('wb', buffering=-1, open=_open) +except ImportError: + PyTextWrapperType = PyBufferedRandomType = PyBufferedReaderType = PyBufferedWriterType = None +from io import BytesIO as StringIO +InputType = OutputType = None +from socket import socket as SocketType +#FIXME: additionally calls ForkingPickler.register several times +from multiprocessing.reduction import _reduce_socket as reduce_socket +try: #pragma: no cover + IS_IPYTHON = __IPYTHON__ # is True + ExitType = None # IPython.core.autocall.ExitAutocall + IPYTHON_SINGLETONS = ('exit', 'quit', 'get_ipython') +except NameError: + IS_IPYTHON = False + try: ExitType = type(exit) # apparently 'exit' can be removed + except NameError: ExitType = None + IPYTHON_SINGLETONS = () + +import inspect +import typing + + +### Shims for different versions of Python and dill +class Sentinel(object): + """ + Create a unique sentinel object that is pickled as a constant. + """ + def __init__(self, name, module_name=None): + self.name = name + if module_name is None: + # Use the calling frame's module + self.__module__ = inspect.currentframe().f_back.f_globals['__name__'] + else: + self.__module__ = module_name # pragma: no cover + def __repr__(self): + return self.__module__ + '.' + self.name # pragma: no cover + def __copy__(self): + return self # pragma: no cover + def __deepcopy__(self, memo): + return self # pragma: no cover + def __reduce__(self): + return self.name + def __reduce_ex__(self, protocol): + return self.name + +from . import _shims +from ._shims import Reduce, Getattr + +### File modes +#: Pickles the file handle, preserving mode. The position of the unpickled +#: object is as for a new file handle. +HANDLE_FMODE = 0 +#: Pickles the file contents, creating a new file if on load the file does +#: not exist. The position = min(pickled position, EOF) and mode is chosen +#: as such that "best" preserves behavior of the original file. +CONTENTS_FMODE = 1 +#: Pickles the entire file (handle and contents), preserving mode and position. +FILE_FMODE = 2 + +### Shorthands (modified from python2.5/lib/pickle.py) +def copy(obj, *args, **kwds): + """ + Use pickling to 'copy' an object (i.e. `loads(dumps(obj))`). + + See :func:`dumps` and :func:`loads` for keyword arguments. + """ + ignore = kwds.pop('ignore', Unpickler.settings['ignore']) + return loads(dumps(obj, *args, **kwds), ignore=ignore) + +def dump(obj, file, protocol=None, byref=None, fmode=None, recurse=None, **kwds):#, strictio=None): + """ + Pickle an object to a file. + + See :func:`dumps` for keyword arguments. + """ + from .settings import settings + protocol = settings['protocol'] if protocol is None else int(protocol) + _kwds = kwds.copy() + _kwds.update(dict(byref=byref, fmode=fmode, recurse=recurse)) + Pickler(file, protocol, **_kwds).dump(obj) + return + +def dumps(obj, protocol=None, byref=None, fmode=None, recurse=None, **kwds):#, strictio=None): + """ + Pickle an object to a string. + + *protocol* is the pickler protocol, as defined for Python *pickle*. + + If *byref=True*, then dill behaves a lot more like pickle as certain + objects (like modules) are pickled by reference as opposed to attempting + to pickle the object itself. + + If *recurse=True*, then objects referred to in the global dictionary + are recursively traced and pickled, instead of the default behavior + of attempting to store the entire global dictionary. This is needed for + functions defined via *exec()*. + + *fmode* (:const:`HANDLE_FMODE`, :const:`CONTENTS_FMODE`, + or :const:`FILE_FMODE`) indicates how file handles will be pickled. + For example, when pickling a data file handle for transfer to a remote + compute service, *FILE_FMODE* will include the file contents in the + pickle and cursor position so that a remote method can operate + transparently on an object with an open file handle. + + Default values for keyword arguments can be set in :mod:`dill.settings`. + """ + file = StringIO() + dump(obj, file, protocol, byref, fmode, recurse, **kwds)#, strictio) + return file.getvalue() + +def load(file, ignore=None, **kwds): + """ + Unpickle an object from a file. + + See :func:`loads` for keyword arguments. + """ + return Unpickler(file, ignore=ignore, **kwds).load() + +def loads(str, ignore=None, **kwds): + """ + Unpickle an object from a string. + + If *ignore=False* then objects whose class is defined in the module + *__main__* are updated to reference the existing class in *__main__*, + otherwise they are left to refer to the reconstructed type, which may + be different. + + Default values for keyword arguments can be set in :mod:`dill.settings`. + """ + file = StringIO(str) + return load(file, ignore, **kwds) + +# def dumpzs(obj, protocol=None): +# """pickle an object to a compressed string""" +# return zlib.compress(dumps(obj, protocol)) + +# def loadzs(str): +# """unpickle an object from a compressed string""" +# return loads(zlib.decompress(str)) + +### End: Shorthands ### + +class MetaCatchingDict(dict): + def get(self, key, default=None): + try: + return self[key] + except KeyError: + return default + + def __missing__(self, key): + if issubclass(key, type): + return save_type + else: + raise KeyError() + +class PickleWarning(Warning, PickleError): + pass + +class PicklingWarning(PickleWarning, PicklingError): + pass + +class UnpicklingWarning(PickleWarning, UnpicklingError): + pass + +### Extend the Picklers +class Pickler(StockPickler): + """python's Pickler extended to interpreter sessions""" + dispatch: typing.Dict[type, typing.Callable[[Pickler, typing.Any], None]] \ + = MetaCatchingDict(StockPickler.dispatch.copy()) + """The dispatch table, a dictionary of serializing functions used + by Pickler to save objects of specific types. Use :func:`pickle` + or :func:`register` to associate types to custom functions. + + :meta hide-value: + """ + _session = False + from .settings import settings + + def __init__(self, file, *args, **kwds): + settings = Pickler.settings + _byref = kwds.pop('byref', None) + #_strictio = kwds.pop('strictio', None) + _fmode = kwds.pop('fmode', None) + _recurse = kwds.pop('recurse', None) + StockPickler.__init__(self, file, *args, **kwds) + self._main = _main_module + self._diff_cache = {} + self._byref = settings['byref'] if _byref is None else _byref + self._strictio = False #_strictio + self._fmode = settings['fmode'] if _fmode is None else _fmode + self._recurse = settings['recurse'] if _recurse is None else _recurse + self._postproc = OrderedDict() + self._file = file + + def save(self, obj, save_persistent_id=True): + # numpy hack + obj_type = type(obj) + if NumpyArrayType and not (obj_type is type or obj_type in Pickler.dispatch): + # register if the object is a numpy ufunc + # thanks to Paul Kienzle for pointing out ufuncs didn't pickle + if numpyufunc(obj_type): + @register(obj_type) + def save_numpy_ufunc(pickler, obj): + logger.trace(pickler, "Nu: %s", obj) + name = getattr(obj, '__qualname__', getattr(obj, '__name__', None)) + StockPickler.save_global(pickler, obj, name=name) + logger.trace(pickler, "# Nu") + return + # NOTE: the above 'save' performs like: + # import copy_reg + # def udump(f): return f.__name__ + # def uload(name): return getattr(numpy, name) + # copy_reg.pickle(NumpyUfuncType, udump, uload) + # register if the object is a numpy dtype + if numpydtype(obj_type): + @register(obj_type) + def save_numpy_dtype(pickler, obj): + logger.trace(pickler, "Dt: %s", obj) + pickler.save_reduce(_create_dtypemeta, (obj.type,), obj=obj) + logger.trace(pickler, "# Dt") + return + # NOTE: the above 'save' performs like: + # import copy_reg + # def uload(name): return type(NumpyDType(name)) + # def udump(f): return uload, (f.type,) + # copy_reg.pickle(NumpyDTypeType, udump, uload) + # register if the object is a subclassed numpy array instance + if ndarraysubclassinstance(obj_type): + @register(obj_type) + def save_numpy_array(pickler, obj): + logger.trace(pickler, "Nu: (%s, %s)", obj.shape, obj.dtype) + npdict = getattr(obj, '__dict__', None) + f, args, state = obj.__reduce__() + pickler.save_reduce(_create_array, (f,args,state,npdict), obj=obj) + logger.trace(pickler, "# Nu") + return + # end numpy hack + + if GENERATOR_FAIL and obj_type is GeneratorType: + msg = "Can't pickle %s: attribute lookup builtins.generator failed" % GeneratorType + raise PicklingError(msg) + StockPickler.save(self, obj, save_persistent_id) + + save.__doc__ = StockPickler.save.__doc__ + + def dump(self, obj): #NOTE: if settings change, need to update attributes + logger.trace_setup(self) + StockPickler.dump(self, obj) + dump.__doc__ = StockPickler.dump.__doc__ + +class Unpickler(StockUnpickler): + """python's Unpickler extended to interpreter sessions and more types""" + from .settings import settings + _session = False + + def find_class(self, module, name): + if (module, name) == ('__builtin__', '__main__'): + return self._main.__dict__ #XXX: above set w/save_module_dict + elif (module, name) == ('__builtin__', 'NoneType'): + return type(None) #XXX: special case: NoneType missing + if module == 'dill.dill': module = 'dill._dill' + return StockUnpickler.find_class(self, module, name) + + def __init__(self, *args, **kwds): + settings = Pickler.settings + _ignore = kwds.pop('ignore', None) + StockUnpickler.__init__(self, *args, **kwds) + self._main = _main_module + self._ignore = settings['ignore'] if _ignore is None else _ignore + + def load(self): #NOTE: if settings change, need to update attributes + obj = StockUnpickler.load(self) + if type(obj).__module__ == getattr(_main_module, '__name__', '__main__'): + if not self._ignore: + # point obj class to main + try: obj.__class__ = getattr(self._main, type(obj).__name__) + except (AttributeError,TypeError): pass # defined in a file + #_main_module.__dict__.update(obj.__dict__) #XXX: should update globals ? + return obj + load.__doc__ = StockUnpickler.load.__doc__ + pass + +''' +def dispatch_table(): + """get the dispatch table of registered types""" + return Pickler.dispatch +''' + +pickle_dispatch_copy = StockPickler.dispatch.copy() + +def pickle(t, func): + """expose :attr:`~Pickler.dispatch` table for user-created extensions""" + Pickler.dispatch[t] = func + return + +def register(t): + """decorator to register types to Pickler's :attr:`~Pickler.dispatch` table""" + def proxy(func): + Pickler.dispatch[t] = func + return func + return proxy + +def _revert_extension(): + """drop dill-registered types from pickle's dispatch table""" + for type, func in list(StockPickler.dispatch.items()): + if func.__module__ == __name__: + del StockPickler.dispatch[type] + if type in pickle_dispatch_copy: + StockPickler.dispatch[type] = pickle_dispatch_copy[type] + +def use_diff(on=True): + """ + Reduces size of pickles by only including object which have changed. + + Decreases pickle size but increases CPU time needed. + Also helps avoid some unpickleable objects. + MUST be called at start of script, otherwise changes will not be recorded. + """ + global _use_diff, diff + _use_diff = on + if _use_diff and diff is None: + try: + from . import diff as d + except ImportError: + import diff as d + diff = d + +def _create_typemap(): + import types + d = dict(list(__builtin__.__dict__.items()) + \ + list(types.__dict__.items())).items() + for key, value in d: + if getattr(value, '__module__', None) == 'builtins' \ + and type(value) is type: + yield key, value + return +_reverse_typemap = dict(_create_typemap()) +_reverse_typemap.update({ + 'PartialType': PartialType, + 'SuperType': SuperType, + 'ItemGetterType': ItemGetterType, + 'AttrGetterType': AttrGetterType, +}) +if sys.hexversion < 0x30800a2: + _reverse_typemap.update({ + 'CellType': CellType, + }) + +# "Incidental" implementation specific types. Unpickling these types in another +# implementation of Python (PyPy -> CPython) is not guaranteed to work + +# This dictionary should contain all types that appear in Python implementations +# but are not defined in https://docs.python.org/3/library/types.html#standard-interpreter-types +x=OrderedDict() +_incedental_reverse_typemap = { + 'FileType': FileType, + 'BufferedRandomType': BufferedRandomType, + 'BufferedReaderType': BufferedReaderType, + 'BufferedWriterType': BufferedWriterType, + 'TextWrapperType': TextWrapperType, + 'PyBufferedRandomType': PyBufferedRandomType, + 'PyBufferedReaderType': PyBufferedReaderType, + 'PyBufferedWriterType': PyBufferedWriterType, + 'PyTextWrapperType': PyTextWrapperType, +} + +_incedental_reverse_typemap.update({ + "DictKeysType": type({}.keys()), + "DictValuesType": type({}.values()), + "DictItemsType": type({}.items()), + + "OdictKeysType": type(x.keys()), + "OdictValuesType": type(x.values()), + "OdictItemsType": type(x.items()), +}) + +if ExitType: + _incedental_reverse_typemap['ExitType'] = ExitType +if InputType: + _incedental_reverse_typemap['InputType'] = InputType + _incedental_reverse_typemap['OutputType'] = OutputType + +''' +try: + import symtable + _incedental_reverse_typemap["SymtableEntryType"] = type(symtable.symtable("", "string", "exec")._table) +except: #FIXME: fails to pickle + pass + +if sys.hexversion >= 0x30a00a0: + _incedental_reverse_typemap['LineIteratorType'] = type(compile('3', '', 'eval').co_lines()) +''' + +if sys.hexversion >= 0x30b00b0 and not IS_PYPY: + from types import GenericAlias + _incedental_reverse_typemap["GenericAliasIteratorType"] = type(iter(GenericAlias(list, (int,)))) + ''' + _incedental_reverse_typemap['PositionsIteratorType'] = type(compile('3', '', 'eval').co_positions()) + ''' + +try: + import winreg + _incedental_reverse_typemap["HKEYType"] = winreg.HKEYType +except ImportError: + pass + +_reverse_typemap.update(_incedental_reverse_typemap) +_incedental_types = set(_incedental_reverse_typemap.values()) + +del x + +_typemap = dict((v, k) for k, v in _reverse_typemap.items()) + +def _unmarshal(string): + return marshal.loads(string) + +def _load_type(name): + return _reverse_typemap[name] + +def _create_type(typeobj, *args): + return typeobj(*args) + +def _create_function(fcode, fglobals, fname=None, fdefaults=None, + fclosure=None, fdict=None, fkwdefaults=None): + # same as FunctionType, but enable passing __dict__ to new function, + # __dict__ is the storehouse for attributes added after function creation + func = FunctionType(fcode, fglobals or dict(), fname, fdefaults, fclosure) + if fdict is not None: + func.__dict__.update(fdict) #XXX: better copy? option to copy? + if fkwdefaults is not None: + func.__kwdefaults__ = fkwdefaults + # 'recurse' only stores referenced modules/objects in fglobals, + # thus we need to make sure that we have __builtins__ as well + if "__builtins__" not in func.__globals__: + func.__globals__["__builtins__"] = globals()["__builtins__"] + # assert id(fglobals) == id(func.__globals__) + return func + +class match: + """ + Make avaialable a limited structural pattern matching-like syntax for Python < 3.10 + + Patterns can be only tuples (without types) currently. + Inspired by the package pattern-matching-PEP634. + + Usage: + >>> with match(args) as m: + >>> if m.case(('x', 'y')): + >>> # use m.x and m.y + >>> elif m.case(('x', 'y', 'z')): + >>> # use m.x, m.y and m.z + + Equivalent native code for Python >= 3.10: + >>> match args: + >>> case (x, y): + >>> # use x and y + >>> case (x, y, z): + >>> # use x, y and z + """ + def __init__(self, value): + self.value = value + self._fields = None + def __enter__(self): + return self + def __exit__(self, *exc_info): + return False + def case(self, args): # *args, **kwargs): + """just handles tuple patterns""" + if len(self.value) != len(args): # + len(kwargs): + return False + #if not all(isinstance(arg, pat) for arg, pat in zip(self.value[len(args):], kwargs.values())): + # return False + self.args = args # (*args, *kwargs) + return True + @property + def fields(self): + # Only bind names to values if necessary. + if self._fields is None: + self._fields = dict(zip(self.args, self.value)) + return self._fields + def __getattr__(self, item): + return self.fields[item] + +ALL_CODE_PARAMS = [ + # Version New attribute CodeType parameters + ((3,11,'a'), 'co_endlinetable', 'argcount posonlyargcount kwonlyargcount nlocals stacksize flags code consts names varnames filename name qualname firstlineno linetable endlinetable columntable exceptiontable freevars cellvars'), + ((3,11), 'co_exceptiontable', 'argcount posonlyargcount kwonlyargcount nlocals stacksize flags code consts names varnames filename name qualname firstlineno linetable exceptiontable freevars cellvars'), + ((3,11,'p'), 'co_qualname', 'argcount posonlyargcount kwonlyargcount nlocals stacksize flags code consts names varnames filename name qualname firstlineno linetable freevars cellvars'), + ((3,10), 'co_linetable', 'argcount posonlyargcount kwonlyargcount nlocals stacksize flags code consts names varnames filename name firstlineno linetable freevars cellvars'), + ((3,8), 'co_posonlyargcount', 'argcount posonlyargcount kwonlyargcount nlocals stacksize flags code consts names varnames filename name firstlineno lnotab freevars cellvars'), + ((3,7), 'co_kwonlyargcount', 'argcount kwonlyargcount nlocals stacksize flags code consts names varnames filename name firstlineno lnotab freevars cellvars'), + ] +for version, new_attr, params in ALL_CODE_PARAMS: + if hasattr(CodeType, new_attr): + CODE_VERSION = version + CODE_PARAMS = params.split() + break +ENCODE_PARAMS = set(CODE_PARAMS).intersection( + ['code', 'lnotab', 'linetable', 'endlinetable', 'columntable', 'exceptiontable']) + +def _create_code(*args): + if not isinstance(args[0], int): # co_lnotab stored from >= 3.10 + LNOTAB, *args = args + else: # from < 3.10 (or pre-LNOTAB storage) + LNOTAB = b'' + + with match(args) as m: + # Python 3.11/3.12a (18 members) + if m.case(( + 'argcount', 'posonlyargcount', 'kwonlyargcount', 'nlocals', 'stacksize', 'flags', # args[0:6] + 'code', 'consts', 'names', 'varnames', 'filename', 'name', 'qualname', 'firstlineno', # args[6:14] + 'linetable', 'exceptiontable', 'freevars', 'cellvars' # args[14:] + )): + if CODE_VERSION == (3,11): + return CodeType( + *args[:6], + args[6].encode() if hasattr(args[6], 'encode') else args[6], # code + *args[7:14], + args[14].encode() if hasattr(args[14], 'encode') else args[14], # linetable + args[15].encode() if hasattr(args[15], 'encode') else args[15], # exceptiontable + args[16], + args[17], + ) + fields = m.fields + # PyPy 3.11 7.3.19+ (17 members) + elif m.case(( + 'argcount', 'posonlyargcount', 'kwonlyargcount', 'nlocals', 'stacksize', 'flags', # args[0:6] + 'code', 'consts', 'names', 'varnames', 'filename', 'name', 'qualname', # args[6:13] + 'firstlineno', 'linetable', 'freevars', 'cellvars' # args[13:] + )): + if CODE_VERSION == (3,11,'p'): + return CodeType( + *args[:6], + args[6].encode() if hasattr(args[6], 'encode') else args[6], # code + *args[7:14], + args[14].encode() if hasattr(args[14], 'encode') else args[14], # linetable + args[15], + args[16], + ) + fields = m.fields + # Python 3.10 or 3.8/3.9 (16 members) + elif m.case(( + 'argcount', 'posonlyargcount', 'kwonlyargcount', 'nlocals', 'stacksize', 'flags', # args[0:6] + 'code', 'consts', 'names', 'varnames', 'filename', 'name', 'firstlineno', # args[6:13] + 'LNOTAB_OR_LINETABLE', 'freevars', 'cellvars' # args[13:] + )): + if CODE_VERSION == (3,10) or CODE_VERSION == (3,8): + return CodeType( + *args[:6], + args[6].encode() if hasattr(args[6], 'encode') else args[6], # code + *args[7:13], + args[13].encode() if hasattr(args[13], 'encode') else args[13], # lnotab/linetable + args[14], + args[15], + ) + fields = m.fields + if CODE_VERSION >= (3,10): + fields['linetable'] = m.LNOTAB_OR_LINETABLE + else: + fields['lnotab'] = LNOTAB if LNOTAB else m.LNOTAB_OR_LINETABLE + # Python 3.7 (15 args) + elif m.case(( + 'argcount', 'kwonlyargcount', 'nlocals', 'stacksize', 'flags', # args[0:5] + 'code', 'consts', 'names', 'varnames', 'filename', 'name', 'firstlineno', # args[5:12] + 'lnotab', 'freevars', 'cellvars' # args[12:] + )): + if CODE_VERSION == (3,7): + return CodeType( + *args[:5], + args[5].encode() if hasattr(args[5], 'encode') else args[5], # code + *args[6:12], + args[12].encode() if hasattr(args[12], 'encode') else args[12], # lnotab + args[13], + args[14], + ) + fields = m.fields + # Python 3.11a (20 members) + elif m.case(( + 'argcount', 'posonlyargcount', 'kwonlyargcount', 'nlocals', 'stacksize', 'flags', # args[0:6] + 'code', 'consts', 'names', 'varnames', 'filename', 'name', 'qualname', 'firstlineno', # args[6:14] + 'linetable', 'endlinetable', 'columntable', 'exceptiontable', 'freevars', 'cellvars' # args[14:] + )): + if CODE_VERSION == (3,11,'a'): + return CodeType( + *args[:6], + args[6].encode() if hasattr(args[6], 'encode') else args[6], # code + *args[7:14], + *(a.encode() if hasattr(a, 'encode') else a for a in args[14:18]), # linetable-exceptiontable + args[18], + args[19], + ) + fields = m.fields + else: + raise UnpicklingError("pattern match for code object failed") + + # The args format doesn't match this version. + fields.setdefault('posonlyargcount', 0) # from python <= 3.7 + fields.setdefault('lnotab', LNOTAB) # from python >= 3.10 + fields.setdefault('linetable', b'') # from python <= 3.9 + fields.setdefault('qualname', fields['name']) # from python <= 3.10 + fields.setdefault('exceptiontable', b'') # from python <= 3.10 + fields.setdefault('endlinetable', None) # from python != 3.11a + fields.setdefault('columntable', None) # from python != 3.11a + + args = (fields[k].encode() if k in ENCODE_PARAMS and hasattr(fields[k], 'encode') else fields[k] + for k in CODE_PARAMS) + return CodeType(*args) + +def _create_ftype(ftypeobj, func, args, kwds): + if kwds is None: + kwds = {} + if args is None: + args = () + return ftypeobj(func, *args, **kwds) + +def _create_typing_tuple(argz, *args): #NOTE: workaround python/cpython#94245 + if not argz: + return typing.Tuple[()].copy_with(()) + if argz == ((),): + return typing.Tuple[()] + return typing.Tuple[argz] + +if ThreadHandleType: + def _create_thread_handle(ident, done, *args): #XXX: ignores 'blocking' + from threading import _make_thread_handle + handle = _make_thread_handle(ident) + if done: + handle._set_done() + return handle + +def _create_lock(locked, *args): #XXX: ignores 'blocking' + from threading import Lock + lock = Lock() + if locked: + if not lock.acquire(False): + raise UnpicklingError("Cannot acquire lock") + return lock + +def _create_rlock(count, owner, *args): #XXX: ignores 'blocking' + lock = RLockType() + if owner is not None: + lock._acquire_restore((count, owner)) + if owner and not lock._is_owned(): + raise UnpicklingError("Cannot acquire lock") + return lock + +# thanks to matsjoyce for adding all the different file modes +def _create_filehandle(name, mode, position, closed, open, strictio, fmode, fdata): # buffering=0 + # only pickles the handle, not the file contents... good? or StringIO(data)? + # (for file contents see: http://effbot.org/librarybook/copy-reg.htm) + # NOTE: handle special cases first (are there more special cases?) + names = {'':sys.__stdin__, '':sys.__stdout__, + '':sys.__stderr__} #XXX: better fileno=(0,1,2) ? + if name in list(names.keys()): + f = names[name] #XXX: safer "f=sys.stdin" + elif name == '': + f = os.tmpfile() + elif name == '': + import tempfile + f = tempfile.TemporaryFile(mode) + else: + try: + exists = os.path.exists(name) + except Exception: + exists = False + if not exists: + if strictio: + raise FileNotFoundError("[Errno 2] No such file or directory: '%s'" % name) + elif "r" in mode and fmode != FILE_FMODE: + name = '' # or os.devnull? + current_size = 0 # or maintain position? + else: + current_size = os.path.getsize(name) + + if position > current_size: + if strictio: + raise ValueError("invalid buffer size") + elif fmode == CONTENTS_FMODE: + position = current_size + # try to open the file by name + # NOTE: has different fileno + try: + #FIXME: missing: *buffering*, encoding, softspace + if fmode == FILE_FMODE: + f = open(name, mode if "w" in mode else "w") + f.write(fdata) + if "w" not in mode: + f.close() + f = open(name, mode) + elif name == '': # file did not exist + import tempfile + f = tempfile.TemporaryFile(mode) + # treat x mode as w mode + elif fmode == CONTENTS_FMODE \ + and ("w" in mode or "x" in mode): + # stop truncation when opening + flags = os.O_CREAT + if "+" in mode: + flags |= os.O_RDWR + else: + flags |= os.O_WRONLY + f = os.fdopen(os.open(name, flags), mode) + # set name to the correct value + r = getattr(f, "buffer", f) + r = getattr(r, "raw", r) + r.name = name + assert f.name == name + else: + f = open(name, mode) + except (IOError, FileNotFoundError): + err = sys.exc_info()[1] + raise UnpicklingError(err) + if closed: + f.close() + elif position >= 0 and fmode != HANDLE_FMODE: + f.seek(position) + return f + +def _create_stringi(value, position, closed): + f = StringIO(value) + if closed: f.close() + else: f.seek(position) + return f + +def _create_stringo(value, position, closed): + f = StringIO() + if closed: f.close() + else: + f.write(value) + f.seek(position) + return f + +class _itemgetter_helper(object): + def __init__(self): + self.items = [] + def __getitem__(self, item): + self.items.append(item) + return + +class _attrgetter_helper(object): + def __init__(self, attrs, index=None): + self.attrs = attrs + self.index = index + def __getattribute__(self, attr): + attrs = object.__getattribute__(self, "attrs") + index = object.__getattribute__(self, "index") + if index is None: + index = len(attrs) + attrs.append(attr) + else: + attrs[index] = ".".join([attrs[index], attr]) + return type(self)(attrs, index) + +class _dictproxy_helper(dict): + def __ror__(self, a): + return a + +_dictproxy_helper_instance = _dictproxy_helper() + +__d = {} +try: + # In CPython 3.9 and later, this trick can be used to exploit the + # implementation of the __or__ function of MappingProxyType to get the true + # mapping referenced by the proxy. It may work for other implementations, + # but is not guaranteed. + MAPPING_PROXY_TRICK = __d is (DictProxyType(__d) | _dictproxy_helper_instance) +except Exception: + MAPPING_PROXY_TRICK = False +del __d + +# _CELL_REF and _CELL_EMPTY are used to stay compatible with versions of dill +# whose _create_cell functions do not have a default value. +# _CELL_REF can be safely removed entirely (replaced by empty tuples for calls +# to _create_cell) once breaking changes are allowed. +_CELL_REF = None +_CELL_EMPTY = Sentinel('_CELL_EMPTY') + +def _create_cell(contents=None): + if contents is not _CELL_EMPTY: + value = contents + return (lambda: value).__closure__[0] + +def _create_weakref(obj, *args): + from weakref import ref + if obj is None: # it's dead + from collections import UserDict + return ref(UserDict(), *args) + return ref(obj, *args) + +def _create_weakproxy(obj, callable=False, *args): + from weakref import proxy + if obj is None: # it's dead + if callable: return proxy(lambda x:x, *args) + from collections import UserDict + return proxy(UserDict(), *args) + return proxy(obj, *args) + +def _eval_repr(repr_str): + return eval(repr_str) + +def _create_array(f, args, state, npdict=None): + #array = numpy.core.multiarray._reconstruct(*args) + array = f(*args) + array.__setstate__(state) + if npdict is not None: # we also have saved state in __dict__ + array.__dict__.update(npdict) + return array + +def _create_dtypemeta(scalar_type): + if NumpyDType is True: __hook__() # a bit hacky I think + if scalar_type is None: + return NumpyDType + return type(NumpyDType(scalar_type)) + +def _create_namedtuple(name, fieldnames, modulename, defaults=None): + class_ = _import_module(modulename + '.' + name, safe=True) + if class_ is not None: + return class_ + import collections + t = collections.namedtuple(name, fieldnames, defaults=defaults, module=modulename) + return t + +def _create_capsule(pointer, name, context, destructor): + attr_found = False + try: + # based on https://github.com/python/cpython/blob/f4095e53ab708d95e019c909d5928502775ba68f/Objects/capsule.c#L209-L231 + uname = name.decode('utf8') + for i in range(1, uname.count('.')+1): + names = uname.rsplit('.', i) + try: + module = __import__(names[0]) + except ImportError: + pass + obj = module + for attr in names[1:]: + obj = getattr(obj, attr) + capsule = obj + attr_found = True + break + except Exception: + pass + + if attr_found: + if _PyCapsule_IsValid(capsule, name): + return capsule + raise UnpicklingError("%s object exists at %s but a PyCapsule object was expected." % (type(capsule), name)) + else: + #warnings.warn('Creating a new PyCapsule %s for a C data structure that may not be present in memory. Segmentation faults or other memory errors are possible.' % (name,), UnpicklingWarning) + capsule = _PyCapsule_New(pointer, name, destructor) + _PyCapsule_SetContext(capsule, context) + return capsule + +def _getattr(objclass, name, repr_str): + # hack to grab the reference directly + try: #XXX: works only for __builtin__ ? + attr = repr_str.split("'")[3] + return eval(attr+'.__dict__["'+name+'"]') + except Exception: + try: + attr = objclass.__dict__ + if type(attr) is DictProxyType: + attr = attr[name] + else: + attr = getattr(objclass,name) + except (AttributeError, KeyError): + attr = getattr(objclass,name) + return attr + +def _get_attr(self, name): + # stop recursive pickling + return getattr(self, name, None) or getattr(__builtin__, name) + +def _import_module(import_name, safe=False): + try: + if import_name.startswith('__runtime__.'): + return sys.modules[import_name] + elif '.' in import_name: + items = import_name.split('.') + module = '.'.join(items[:-1]) + obj = items[-1] + submodule = getattr(__import__(module, None, None, [obj]), obj) + if isinstance(submodule, (ModuleType, type)): + return submodule + return __import__(import_name, None, None, [obj]) + else: + return __import__(import_name) + except (ImportError, AttributeError, KeyError): + if safe: + return None + raise + +# https://github.com/python/cpython/blob/a8912a0f8d9eba6d502c37d522221f9933e976db/Lib/pickle.py#L322-L333 +def _getattribute(obj, name): + for subpath in name.split('.'): + if subpath == '': + raise AttributeError("Can't get local attribute {!r} on {!r}" + .format(name, obj)) + try: + parent = obj + obj = getattr(obj, subpath) + except AttributeError: + raise AttributeError("Can't get attribute {!r} on {!r}" + .format(name, obj)) + return obj, parent + +def _locate_function(obj, pickler=None): + module_name = getattr(obj, '__module__', None) + if module_name in ['__main__', None] or \ + pickler and is_dill(pickler, child=False) and pickler._session and module_name == pickler._main.__name__: + return False + if hasattr(obj, '__qualname__'): + module = _import_module(module_name, safe=True) + try: + found, _ = _getattribute(module, obj.__qualname__) + return found is obj + except AttributeError: + return False + else: + found = _import_module(module_name + '.' + obj.__name__, safe=True) + return found is obj + + +def _setitems(dest, source): + for k, v in source.items(): + dest[k] = v + + +def _save_with_postproc(pickler, reduction, is_pickler_dill=None, obj=Getattr.NO_DEFAULT, postproc_list=None): + if obj is Getattr.NO_DEFAULT: + obj = Reduce(reduction) # pragma: no cover + + if is_pickler_dill is None: + is_pickler_dill = is_dill(pickler, child=True) + if is_pickler_dill: + # assert id(obj) not in pickler._postproc, str(obj) + ' already pushed on stack!' + # if not hasattr(pickler, 'x'): pickler.x = 0 + # print(pickler.x*' ', 'push', obj, id(obj), pickler._recurse) + # pickler.x += 1 + if postproc_list is None: + postproc_list = [] + + # Recursive object not supported. Default to a global instead. + if id(obj) in pickler._postproc: + name = '%s.%s ' % (obj.__module__, getattr(obj, '__qualname__', obj.__name__)) if hasattr(obj, '__module__') else '' + warnings.warn('Cannot pickle %r: %shas recursive self-references that trigger a RecursionError.' % (obj, name), PicklingWarning) + pickler.save_global(obj) + return + pickler._postproc[id(obj)] = postproc_list + + # TODO: Use state_setter in Python 3.8 to allow for faster cPickle implementations + pickler.save_reduce(*reduction, obj=obj) + + if is_pickler_dill: + # pickler.x -= 1 + # print(pickler.x*' ', 'pop', obj, id(obj)) + postproc = pickler._postproc.pop(id(obj)) + # assert postproc_list == postproc, 'Stack tampered!' + for reduction in reversed(postproc): + if reduction[0] is _setitems: + # use the internal machinery of pickle.py to speedup when + # updating a dictionary in postproc + dest, source = reduction[1] + if source: + pickler.write(pickler.get(pickler.memo[id(dest)][0])) + if sys.hexversion < 0x30e00a1: + pickler._batch_setitems(iter(source.items())) + else: + pickler._batch_setitems(iter(source.items()), obj=obj) + else: + # Updating with an empty dictionary. Same as doing nothing. + continue + else: + pickler.save_reduce(*reduction) + # pop None created by calling preprocessing step off stack + pickler.write(POP) + +#@register(CodeType) +#def save_code(pickler, obj): +# logger.trace(pickler, "Co: %s", obj) +# pickler.save_reduce(_unmarshal, (marshal.dumps(obj),), obj=obj) +# logger.trace(pickler, "# Co") +# return + +# The following function is based on 'save_codeobject' from 'cloudpickle' +# Copyright (c) 2012, Regents of the University of California. +# Copyright (c) 2009 `PiCloud, Inc. `_. +# License: https://github.com/cloudpipe/cloudpickle/blob/master/LICENSE +@register(CodeType) +def save_code(pickler, obj): + logger.trace(pickler, "Co: %s", obj) + if hasattr(obj, "co_endlinetable"): # python 3.11a (20 args) + args = ( + obj.co_lnotab, # for < python 3.10 [not counted in args] + obj.co_argcount, obj.co_posonlyargcount, + obj.co_kwonlyargcount, obj.co_nlocals, obj.co_stacksize, + obj.co_flags, obj.co_code, obj.co_consts, obj.co_names, + obj.co_varnames, obj.co_filename, obj.co_name, obj.co_qualname, + obj.co_firstlineno, obj.co_linetable, obj.co_endlinetable, + obj.co_columntable, obj.co_exceptiontable, obj.co_freevars, + obj.co_cellvars + ) + elif hasattr(obj, "co_exceptiontable"): # python 3.11 (18 args) + with warnings.catch_warnings(): + if not OLD312a7: # issue 597 + warnings.filterwarnings('ignore', category=DeprecationWarning) + args = ( + obj.co_lnotab, # for < python 3.10 [not counted in args] + obj.co_argcount, obj.co_posonlyargcount, + obj.co_kwonlyargcount, obj.co_nlocals, obj.co_stacksize, + obj.co_flags, obj.co_code, obj.co_consts, obj.co_names, + obj.co_varnames, obj.co_filename, obj.co_name, obj.co_qualname, + obj.co_firstlineno, obj.co_linetable, obj.co_exceptiontable, + obj.co_freevars, obj.co_cellvars + ) + elif hasattr(obj, "co_qualname"): # pypy 3.11 7.3.19+ (17 args) + args = ( + obj.co_lnotab, obj.co_argcount, obj.co_posonlyargcount, + obj.co_kwonlyargcount, obj.co_nlocals, obj.co_stacksize, + obj.co_flags, obj.co_code, obj.co_consts, obj.co_names, + obj.co_varnames, obj.co_filename, obj.co_name, obj.co_qualname, + obj.co_firstlineno, obj.co_linetable, obj.co_freevars, + obj.co_cellvars + ) + elif hasattr(obj, "co_linetable"): # python 3.10 (16 args) + args = ( + obj.co_lnotab, # for < python 3.10 [not counted in args] + obj.co_argcount, obj.co_posonlyargcount, + obj.co_kwonlyargcount, obj.co_nlocals, obj.co_stacksize, + obj.co_flags, obj.co_code, obj.co_consts, obj.co_names, + obj.co_varnames, obj.co_filename, obj.co_name, + obj.co_firstlineno, obj.co_linetable, obj.co_freevars, + obj.co_cellvars + ) + elif hasattr(obj, "co_posonlyargcount"): # python 3.8 (16 args) + args = ( + obj.co_argcount, obj.co_posonlyargcount, + obj.co_kwonlyargcount, obj.co_nlocals, obj.co_stacksize, + obj.co_flags, obj.co_code, obj.co_consts, obj.co_names, + obj.co_varnames, obj.co_filename, obj.co_name, + obj.co_firstlineno, obj.co_lnotab, obj.co_freevars, + obj.co_cellvars + ) + else: # python 3.7 (15 args) + args = ( + obj.co_argcount, obj.co_kwonlyargcount, obj.co_nlocals, + obj.co_stacksize, obj.co_flags, obj.co_code, obj.co_consts, + obj.co_names, obj.co_varnames, obj.co_filename, + obj.co_name, obj.co_firstlineno, obj.co_lnotab, + obj.co_freevars, obj.co_cellvars + ) + + pickler.save_reduce(_create_code, args, obj=obj) + logger.trace(pickler, "# Co") + return + +def _repr_dict(obj): + """Make a short string representation of a dictionary.""" + return "<%s object at %#012x>" % (type(obj).__name__, id(obj)) + +@register(dict) +def save_module_dict(pickler, obj): + if is_dill(pickler, child=False) and obj == pickler._main.__dict__ and \ + not (pickler._session and pickler._first_pass): + logger.trace(pickler, "D1: %s", _repr_dict(obj)) # obj + pickler.write(bytes('c__builtin__\n__main__\n', 'UTF-8')) + logger.trace(pickler, "# D1") + elif (not is_dill(pickler, child=False)) and (obj == _main_module.__dict__): + logger.trace(pickler, "D3: %s", _repr_dict(obj)) # obj + pickler.write(bytes('c__main__\n__dict__\n', 'UTF-8')) #XXX: works in general? + logger.trace(pickler, "# D3") + elif '__name__' in obj and obj != _main_module.__dict__ \ + and type(obj['__name__']) is str \ + and obj is getattr(_import_module(obj['__name__'],True), '__dict__', None): + logger.trace(pickler, "D4: %s", _repr_dict(obj)) # obj + pickler.write(bytes('c%s\n__dict__\n' % obj['__name__'], 'UTF-8')) + logger.trace(pickler, "# D4") + else: + logger.trace(pickler, "D2: %s", _repr_dict(obj)) # obj + if is_dill(pickler, child=False) and pickler._session: + # we only care about session the first pass thru + pickler._first_pass = False + StockPickler.save_dict(pickler, obj) + logger.trace(pickler, "# D2") + return + + +if not OLD310 and MAPPING_PROXY_TRICK: + def save_dict_view(dicttype): + def save_dict_view_for_function(func): + def _save_dict_view(pickler, obj): + logger.trace(pickler, "Dkvi: <%s>", obj) + mapping = obj.mapping | _dictproxy_helper_instance + pickler.save_reduce(func, (mapping,), obj=obj) + logger.trace(pickler, "# Dkvi") + return _save_dict_view + return [ + (funcname, save_dict_view_for_function(getattr(dicttype, funcname))) + for funcname in ('keys', 'values', 'items') + ] +else: + # The following functions are based on 'cloudpickle' + # https://github.com/cloudpipe/cloudpickle/blob/5d89947288a18029672596a4d719093cc6d5a412/cloudpickle/cloudpickle.py#L922-L940 + # Copyright (c) 2012, Regents of the University of California. + # Copyright (c) 2009 `PiCloud, Inc. `_. + # License: https://github.com/cloudpipe/cloudpickle/blob/master/LICENSE + def save_dict_view(dicttype): + def save_dict_keys(pickler, obj): + logger.trace(pickler, "Dk: <%s>", obj) + dict_constructor = _shims.Reduce(dicttype.fromkeys, (list(obj),)) + pickler.save_reduce(dicttype.keys, (dict_constructor,), obj=obj) + logger.trace(pickler, "# Dk") + + def save_dict_values(pickler, obj): + logger.trace(pickler, "Dv: <%s>", obj) + dict_constructor = _shims.Reduce(dicttype, (enumerate(obj),)) + pickler.save_reduce(dicttype.values, (dict_constructor,), obj=obj) + logger.trace(pickler, "# Dv") + + def save_dict_items(pickler, obj): + logger.trace(pickler, "Di: <%s>", obj) + pickler.save_reduce(dicttype.items, (dicttype(obj),), obj=obj) + logger.trace(pickler, "# Di") + + return ( + ('keys', save_dict_keys), + ('values', save_dict_values), + ('items', save_dict_items) + ) + +for __dicttype in ( + dict, + OrderedDict +): + __obj = __dicttype() + for __funcname, __savefunc in save_dict_view(__dicttype): + __tview = type(getattr(__obj, __funcname)()) + if __tview not in Pickler.dispatch: + Pickler.dispatch[__tview] = __savefunc +del __dicttype, __obj, __funcname, __tview, __savefunc + + +@register(ClassType) +def save_classobj(pickler, obj): #FIXME: enable pickler._byref + if not _locate_function(obj, pickler): + logger.trace(pickler, "C1: %s", obj) + pickler.save_reduce(ClassType, (obj.__name__, obj.__bases__, + obj.__dict__), obj=obj) + #XXX: or obj.__dict__.copy()), obj=obj) ? + logger.trace(pickler, "# C1") + else: + logger.trace(pickler, "C2: %s", obj) + name = getattr(obj, '__qualname__', getattr(obj, '__name__', None)) + StockPickler.save_global(pickler, obj, name=name) + logger.trace(pickler, "# C2") + return + +@register(typing._GenericAlias) +def save_generic_alias(pickler, obj): + args = obj.__args__ + if type(obj.__reduce__()) is str: + logger.trace(pickler, "Ga0: %s", obj) + StockPickler.save_global(pickler, obj, name=obj.__reduce__()) + logger.trace(pickler, "# Ga0") + elif obj.__origin__ is tuple and (not args or args == ((),)): + logger.trace(pickler, "Ga1: %s", obj) + pickler.save_reduce(_create_typing_tuple, (args,), obj=obj) + logger.trace(pickler, "# Ga1") + else: + logger.trace(pickler, "Ga2: %s", obj) + StockPickler.save_reduce(pickler, *obj.__reduce__(), obj=obj) + logger.trace(pickler, "# Ga2") + return + +if ThreadHandleType: + @register(ThreadHandleType) + def save_thread_handle(pickler, obj): + logger.trace(pickler, "Th: %s", obj) + pickler.save_reduce(_create_thread_handle, (obj.ident, obj.is_done()), obj=obj) + logger.trace(pickler, "# Th") + return + +@register(LockType) #XXX: copied Thread will have new Event (due to new Lock) +def save_lock(pickler, obj): + logger.trace(pickler, "Lo: %s", obj) + pickler.save_reduce(_create_lock, (obj.locked(),), obj=obj) + logger.trace(pickler, "# Lo") + return + +@register(RLockType) +def save_rlock(pickler, obj): + logger.trace(pickler, "RL: %s", obj) + r = obj.__repr__() # don't use _release_save as it unlocks the lock + count = int(r.split('count=')[1].split()[0].rstrip('>')) + owner = int(r.split('owner=')[1].split()[0]) + pickler.save_reduce(_create_rlock, (count,owner,), obj=obj) + logger.trace(pickler, "# RL") + return + +#@register(SocketType) #FIXME: causes multiprocess test_pickling FAIL +def save_socket(pickler, obj): + logger.trace(pickler, "So: %s", obj) + pickler.save_reduce(*reduce_socket(obj)) + logger.trace(pickler, "# So") + return + +def _save_file(pickler, obj, open_): + if obj.closed: + position = 0 + else: + obj.flush() + if obj in (sys.__stdout__, sys.__stderr__, sys.__stdin__): + position = -1 + else: + position = obj.tell() + if is_dill(pickler, child=True) and pickler._fmode == FILE_FMODE: + f = open_(obj.name, "r") + fdata = f.read() + f.close() + else: + fdata = "" + if is_dill(pickler, child=True): + strictio = pickler._strictio + fmode = pickler._fmode + else: + strictio = False + fmode = 0 # HANDLE_FMODE + pickler.save_reduce(_create_filehandle, (obj.name, obj.mode, position, + obj.closed, open_, strictio, + fmode, fdata), obj=obj) + return + + +@register(FileType) #XXX: in 3.x has buffer=0, needs different _create? +@register(BufferedReaderType) +@register(BufferedWriterType) +@register(TextWrapperType) +def save_file(pickler, obj): + logger.trace(pickler, "Fi: %s", obj) + f = _save_file(pickler, obj, open) + logger.trace(pickler, "# Fi") + return f + +if BufferedRandomType: + @register(BufferedRandomType) + def save_file(pickler, obj): + logger.trace(pickler, "Fi: %s", obj) + f = _save_file(pickler, obj, open) + logger.trace(pickler, "# Fi") + return f + +if PyTextWrapperType: + @register(PyBufferedReaderType) + @register(PyBufferedWriterType) + @register(PyTextWrapperType) + def save_file(pickler, obj): + logger.trace(pickler, "Fi: %s", obj) + f = _save_file(pickler, obj, _open) + logger.trace(pickler, "# Fi") + return f + + if PyBufferedRandomType: + @register(PyBufferedRandomType) + def save_file(pickler, obj): + logger.trace(pickler, "Fi: %s", obj) + f = _save_file(pickler, obj, _open) + logger.trace(pickler, "# Fi") + return f + + +# The following two functions are based on 'saveCStringIoInput' +# and 'saveCStringIoOutput' from spickle +# Copyright (c) 2011 by science+computing ag +# License: http://www.apache.org/licenses/LICENSE-2.0 +if InputType: + @register(InputType) + def save_stringi(pickler, obj): + logger.trace(pickler, "Io: %s", obj) + if obj.closed: + value = ''; position = 0 + else: + value = obj.getvalue(); position = obj.tell() + pickler.save_reduce(_create_stringi, (value, position, \ + obj.closed), obj=obj) + logger.trace(pickler, "# Io") + return + + @register(OutputType) + def save_stringo(pickler, obj): + logger.trace(pickler, "Io: %s", obj) + if obj.closed: + value = ''; position = 0 + else: + value = obj.getvalue(); position = obj.tell() + pickler.save_reduce(_create_stringo, (value, position, \ + obj.closed), obj=obj) + logger.trace(pickler, "# Io") + return + +if LRUCacheType is not None: + from functools import lru_cache + @register(LRUCacheType) + def save_lru_cache(pickler, obj): + logger.trace(pickler, "LRU: %s", obj) + if OLD39: + kwargs = obj.cache_info() + args = (kwargs.maxsize,) + else: + kwargs = obj.cache_parameters() + args = (kwargs['maxsize'], kwargs['typed']) + if args != lru_cache.__defaults__: + wrapper = Reduce(lru_cache, args, is_callable=True) + else: + wrapper = lru_cache + pickler.save_reduce(wrapper, (obj.__wrapped__,), obj=obj) + logger.trace(pickler, "# LRU") + return + +@register(SuperType) +def save_super(pickler, obj): + logger.trace(pickler, "Su: %s", obj) + pickler.save_reduce(super, (obj.__thisclass__, obj.__self__), obj=obj) + logger.trace(pickler, "# Su") + return + +if IS_PYPY: + @register(MethodType) + def save_instancemethod0(pickler, obj): + code = getattr(obj.__func__, '__code__', None) + if code is not None and type(code) is not CodeType \ + and getattr(obj.__self__, obj.__name__) == obj: + # Some PyPy builtin functions have no module name + logger.trace(pickler, "Me2: %s", obj) + # TODO: verify that this works for all PyPy builtin methods + pickler.save_reduce(getattr, (obj.__self__, obj.__name__), obj=obj) + logger.trace(pickler, "# Me2") + return + + logger.trace(pickler, "Me1: %s", obj) + pickler.save_reduce(MethodType, (obj.__func__, obj.__self__), obj=obj) + logger.trace(pickler, "# Me1") + return +else: + @register(MethodType) + def save_instancemethod0(pickler, obj): + logger.trace(pickler, "Me1: %s", obj) + pickler.save_reduce(MethodType, (obj.__func__, obj.__self__), obj=obj) + logger.trace(pickler, "# Me1") + return + +if not IS_PYPY: + @register(MemberDescriptorType) + @register(GetSetDescriptorType) + @register(MethodDescriptorType) + @register(WrapperDescriptorType) + @register(ClassMethodDescriptorType) + def save_wrapper_descriptor(pickler, obj): + logger.trace(pickler, "Wr: %s", obj) + pickler.save_reduce(_getattr, (obj.__objclass__, obj.__name__, + obj.__repr__()), obj=obj) + logger.trace(pickler, "# Wr") + return +else: + @register(MemberDescriptorType) + @register(GetSetDescriptorType) + def save_wrapper_descriptor(pickler, obj): + logger.trace(pickler, "Wr: %s", obj) + pickler.save_reduce(_getattr, (obj.__objclass__, obj.__name__, + obj.__repr__()), obj=obj) + logger.trace(pickler, "# Wr") + return + +@register(CellType) +def save_cell(pickler, obj): + try: + f = obj.cell_contents + except ValueError: # cell is empty + logger.trace(pickler, "Ce3: %s", obj) + # _shims._CELL_EMPTY is defined in _shims.py to support PyPy 2.7. + # It unpickles to a sentinel object _dill._CELL_EMPTY, also created in + # _shims.py. This object is not present in Python 3 because the cell's + # contents can be deleted in newer versions of Python. The reduce object + # will instead unpickle to None if unpickled in Python 3. + + # When breaking changes are made to dill, (_shims._CELL_EMPTY,) can + # be replaced by () OR the delattr function can be removed repending on + # whichever is more convienient. + pickler.save_reduce(_create_cell, (_shims._CELL_EMPTY,), obj=obj) + # Call the function _delattr on the cell's cell_contents attribute + # The result of this function call will be None + pickler.save_reduce(_shims._delattr, (obj, 'cell_contents')) + # pop None created by calling _delattr off stack + pickler.write(POP) + logger.trace(pickler, "# Ce3") + return + if is_dill(pickler, child=True): + if id(f) in pickler._postproc: + # Already seen. Add to its postprocessing. + postproc = pickler._postproc[id(f)] + else: + # Haven't seen it. Add to the highest possible object and set its + # value as late as possible to prevent cycle. + postproc = next(iter(pickler._postproc.values()), None) + if postproc is not None: + logger.trace(pickler, "Ce2: %s", obj) + # _CELL_REF is defined in _shims.py to support older versions of + # dill. When breaking changes are made to dill, (_CELL_REF,) can + # be replaced by () + pickler.save_reduce(_create_cell, (_CELL_REF,), obj=obj) + postproc.append((_shims._setattr, (obj, 'cell_contents', f))) + logger.trace(pickler, "# Ce2") + return + logger.trace(pickler, "Ce1: %s", obj) + pickler.save_reduce(_create_cell, (f,), obj=obj) + logger.trace(pickler, "# Ce1") + return + +if MAPPING_PROXY_TRICK: + @register(DictProxyType) + def save_dictproxy(pickler, obj): + logger.trace(pickler, "Mp: %s", _repr_dict(obj)) # obj + mapping = obj | _dictproxy_helper_instance + pickler.save_reduce(DictProxyType, (mapping,), obj=obj) + logger.trace(pickler, "# Mp") + return +else: + @register(DictProxyType) + def save_dictproxy(pickler, obj): + logger.trace(pickler, "Mp: %s", _repr_dict(obj)) # obj + pickler.save_reduce(DictProxyType, (obj.copy(),), obj=obj) + logger.trace(pickler, "# Mp") + return + +@register(SliceType) +def save_slice(pickler, obj): + logger.trace(pickler, "Sl: %s", obj) + pickler.save_reduce(slice, (obj.start, obj.stop, obj.step), obj=obj) + logger.trace(pickler, "# Sl") + return + +@register(XRangeType) +@register(EllipsisType) +@register(NotImplementedType) +def save_singleton(pickler, obj): + logger.trace(pickler, "Si: %s", obj) + pickler.save_reduce(_eval_repr, (obj.__repr__(),), obj=obj) + logger.trace(pickler, "# Si") + return + +def _proxy_helper(obj): # a dead proxy returns a reference to None + """get memory address of proxy's reference object""" + _repr = repr(obj) + try: _str = str(obj) + except ReferenceError: # it's a dead proxy + return id(None) + if _str == _repr: return id(obj) # it's a repr + try: # either way, it's a proxy from here + address = int(_str.rstrip('>').split(' at ')[-1], base=16) + except ValueError: # special case: proxy of a 'type' + if not IS_PYPY: + address = int(_repr.rstrip('>').split(' at ')[-1], base=16) + else: + objects = iter(gc.get_objects()) + for _obj in objects: + if repr(_obj) == _str: return id(_obj) + # all bad below... nothing found so throw ReferenceError + msg = "Cannot reference object for proxy at '%s'" % id(obj) + raise ReferenceError(msg) + return address + +def _locate_object(address, module=None): + """get object located at the given memory address (inverse of id(obj))""" + special = [None, True, False] #XXX: more...? + for obj in special: + if address == id(obj): return obj + if module: + objects = iter(module.__dict__.values()) + else: objects = iter(gc.get_objects()) + for obj in objects: + if address == id(obj): return obj + # all bad below... nothing found so throw ReferenceError or TypeError + try: address = hex(address) + except TypeError: + raise TypeError("'%s' is not a valid memory address" % str(address)) + raise ReferenceError("Cannot reference object at '%s'" % address) + +@register(ReferenceType) +def save_weakref(pickler, obj): + refobj = obj() + logger.trace(pickler, "R1: %s", obj) + #refobj = ctypes.pythonapi.PyWeakref_GetObject(obj) # dead returns "None" + pickler.save_reduce(_create_weakref, (refobj,), obj=obj) + logger.trace(pickler, "# R1") + return + +@register(ProxyType) +@register(CallableProxyType) +def save_weakproxy(pickler, obj): + # Must do string substitution here and use %r to avoid ReferenceError. + logger.trace(pickler, "R2: %r" % obj) + refobj = _locate_object(_proxy_helper(obj)) + pickler.save_reduce(_create_weakproxy, (refobj, callable(obj)), obj=obj) + logger.trace(pickler, "# R2") + return + +def _is_builtin_module(module): + if not hasattr(module, "__file__"): return True + if module.__file__ is None: return False + # If a module file name starts with prefix, it should be a builtin + # module, so should always be pickled as a reference. + names = ["base_prefix", "base_exec_prefix", "exec_prefix", "prefix", "real_prefix"] + rp = os.path.realpath + # See https://github.com/uqfoundation/dill/issues/566 + return ( + any( + module.__file__.startswith(getattr(sys, name)) + or rp(module.__file__).startswith(rp(getattr(sys, name))) + for name in names + if hasattr(sys, name) + ) + or module.__file__.endswith(EXTENSION_SUFFIXES) + or 'site-packages' in module.__file__ + ) + +def _is_imported_module(module): + return getattr(module, '__loader__', None) is not None or module in sys.modules.values() + +@register(ModuleType) +def save_module(pickler, obj): + if False: #_use_diff: + if obj.__name__.split('.', 1)[0] != "dill": + try: + changed = diff.whats_changed(obj, seen=pickler._diff_cache)[0] + except RuntimeError: # not memorised module, probably part of dill + pass + else: + logger.trace(pickler, "M2: %s with diff", obj) + logger.info("Diff: %s", changed.keys()) + pickler.save_reduce(_import_module, (obj.__name__,), obj=obj, + state=changed) + logger.trace(pickler, "# M2") + return + + logger.trace(pickler, "M1: %s", obj) + pickler.save_reduce(_import_module, (obj.__name__,), obj=obj) + logger.trace(pickler, "# M1") + else: + builtin_mod = _is_builtin_module(obj) + is_session_main = is_dill(pickler, child=True) and obj is pickler._main + if (obj.__name__ not in ("builtins", "dill", "dill._dill") and not builtin_mod + or is_session_main): + logger.trace(pickler, "M1: %s", obj) + # Hack for handling module-type objects in load_module(). + mod_name = obj.__name__ if _is_imported_module(obj) else '__runtime__.%s' % obj.__name__ + # Second references are saved as __builtin__.__main__ in save_module_dict(). + main_dict = obj.__dict__.copy() + for item in ('__builtins__', '__loader__'): + main_dict.pop(item, None) + for item in IPYTHON_SINGLETONS: #pragma: no cover + if getattr(main_dict.get(item), '__module__', '').startswith('IPython'): + del main_dict[item] + pickler.save_reduce(_import_module, (mod_name,), obj=obj, state=main_dict) + logger.trace(pickler, "# M1") + elif obj.__name__ == "dill._dill": + logger.trace(pickler, "M2: %s", obj) + pickler.save_global(obj, name="_dill") + logger.trace(pickler, "# M2") + else: + logger.trace(pickler, "M2: %s", obj) + pickler.save_reduce(_import_module, (obj.__name__,), obj=obj) + logger.trace(pickler, "# M2") + return + +# The following function is based on '_extract_class_dict' from 'cloudpickle' +# Copyright (c) 2012, Regents of the University of California. +# Copyright (c) 2009 `PiCloud, Inc. `_. +# License: https://github.com/cloudpipe/cloudpickle/blob/master/LICENSE +def _get_typedict_type(cls, clsdict, attrs, postproc_list): + """Retrieve a copy of the dict of a class without the inherited methods""" + if len(cls.__bases__) == 1: + inherited_dict = cls.__bases__[0].__dict__ + else: + inherited_dict = {} + for base in reversed(cls.__bases__): + inherited_dict.update(base.__dict__) + to_remove = [] + for name, value in dict.items(clsdict): + try: + base_value = inherited_dict[name] + if value is base_value and hasattr(value, '__qualname__'): + to_remove.append(name) + except KeyError: + pass + for name in to_remove: + dict.pop(clsdict, name) + + if issubclass(type(cls), type): + clsdict.pop('__dict__', None) + clsdict.pop('__weakref__', None) + # clsdict.pop('__prepare__', None) + return clsdict, attrs + +def _get_typedict_abc(obj, _dict, attrs, postproc_list): + if hasattr(abc, '_get_dump'): + (registry, _, _, _) = abc._get_dump(obj) + register = obj.register + postproc_list.extend((register, (reg(),)) for reg in registry) + elif hasattr(obj, '_abc_registry'): + registry = obj._abc_registry + register = obj.register + postproc_list.extend((register, (reg,)) for reg in registry) + else: + raise PicklingError("Cannot find registry of ABC %s", obj) + + if '_abc_registry' in _dict: + _dict.pop('_abc_registry', None) + _dict.pop('_abc_cache', None) + _dict.pop('_abc_negative_cache', None) + # _dict.pop('_abc_negative_cache_version', None) + else: + _dict.pop('_abc_impl', None) + return _dict, attrs + +@register(TypeType) +def save_type(pickler, obj, postproc_list=None): + if obj in _typemap: + logger.trace(pickler, "T1: %s", obj) + # if obj in _incedental_types: + # warnings.warn('Type %r may only exist on this implementation of Python and cannot be unpickled in other implementations.' % (obj,), PicklingWarning) + pickler.save_reduce(_load_type, (_typemap[obj],), obj=obj) + logger.trace(pickler, "# T1") + elif obj.__bases__ == (tuple,) and all([hasattr(obj, attr) for attr in ('_fields','_asdict','_make','_replace')]): + # special case: namedtuples + logger.trace(pickler, "T6: %s", obj) + + obj_name = getattr(obj, '__qualname__', getattr(obj, '__name__', None)) + if obj.__name__ != obj_name: + if postproc_list is None: + postproc_list = [] + postproc_list.append((setattr, (obj, '__qualname__', obj_name))) + + if not obj._field_defaults: + _save_with_postproc(pickler, (_create_namedtuple, (obj.__name__, obj._fields, obj.__module__)), obj=obj, postproc_list=postproc_list) + else: + defaults = [obj._field_defaults[field] for field in obj._fields if field in obj._field_defaults] + _save_with_postproc(pickler, (_create_namedtuple, (obj.__name__, obj._fields, obj.__module__, defaults)), obj=obj, postproc_list=postproc_list) + logger.trace(pickler, "# T6") + return + + # special caes: NoneType, NotImplementedType, EllipsisType, EnumMeta, etc + elif obj is type(None): + logger.trace(pickler, "T7: %s", obj) + #XXX: pickler.save_reduce(type, (None,), obj=obj) + pickler.write(GLOBAL + b'__builtin__\nNoneType\n') + logger.trace(pickler, "# T7") + elif obj is NotImplementedType: + logger.trace(pickler, "T7: %s", obj) + pickler.save_reduce(type, (NotImplemented,), obj=obj) + logger.trace(pickler, "# T7") + elif obj is EllipsisType: + logger.trace(pickler, "T7: %s", obj) + pickler.save_reduce(type, (Ellipsis,), obj=obj) + logger.trace(pickler, "# T7") + elif obj is EnumMeta: + logger.trace(pickler, "T7: %s", obj) + pickler.write(GLOBAL + b'enum\nEnumMeta\n') + logger.trace(pickler, "# T7") + elif obj is ExceptHookArgsType: #NOTE: must be after NoneType for pypy + logger.trace(pickler, "T7: %s", obj) + pickler.write(GLOBAL + b'threading\nExceptHookArgs\n') + logger.trace(pickler, "# T7") + + else: + _byref = getattr(pickler, '_byref', None) + obj_recursive = id(obj) in getattr(pickler, '_postproc', ()) + incorrectly_named = not _locate_function(obj, pickler) + if not _byref and not obj_recursive and incorrectly_named: # not a function, but the name was held over + if postproc_list is None: + postproc_list = [] + + # thanks to Tom Stepleton pointing out pickler._session unneeded + logger.trace(pickler, "T2: %s", obj) + _dict, attrs = _get_typedict_type(obj, obj.__dict__.copy(), None, postproc_list) # copy dict proxy to a dict + + #print (_dict) + #print ("%s\n%s" % (type(obj), obj.__name__)) + #print ("%s\n%s" % (obj.__bases__, obj.__dict__)) + slots = _dict.get('__slots__', ()) + if type(slots) == str: + # __slots__ accepts a single string + slots = (slots,) + + for name in slots: + _dict.pop(name, None) + + if isinstance(obj, abc.ABCMeta): + logger.trace(pickler, "ABC: %s", obj) + _dict, attrs = _get_typedict_abc(obj, _dict, attrs, postproc_list) + logger.trace(pickler, "# ABC") + + qualname = getattr(obj, '__qualname__', None) + if attrs is not None: + for k, v in attrs.items(): + postproc_list.append((setattr, (obj, k, v))) + # TODO: Consider using the state argument to save_reduce? + if qualname is not None: + postproc_list.append((setattr, (obj, '__qualname__', qualname))) + + if not hasattr(obj, '__orig_bases__'): + _save_with_postproc(pickler, (_create_type, ( + type(obj), obj.__name__, obj.__bases__, _dict + )), obj=obj, postproc_list=postproc_list) + else: + # This case will always work, but might be overkill. + _metadict = { + 'metaclass': type(obj) + } + + if _dict: + _dict_update = PartialType(_setitems, source=_dict) + else: + _dict_update = None + + _save_with_postproc(pickler, (new_class, ( + obj.__name__, obj.__orig_bases__, _metadict, _dict_update + )), obj=obj, postproc_list=postproc_list) + logger.trace(pickler, "# T2") + else: + obj_name = getattr(obj, '__qualname__', getattr(obj, '__name__', None)) + logger.trace(pickler, "T4: %s", obj) + if incorrectly_named: + warnings.warn( + "Cannot locate reference to %r." % (obj,), + PicklingWarning, + stacklevel=3, + ) + if obj_recursive: + warnings.warn( + "Cannot pickle %r: %s.%s has recursive self-references that " + "trigger a RecursionError." % (obj, obj.__module__, obj_name), + PicklingWarning, + stacklevel=3, + ) + #print (obj.__dict__) + #print ("%s\n%s" % (type(obj), obj.__name__)) + #print ("%s\n%s" % (obj.__bases__, obj.__dict__)) + StockPickler.save_global(pickler, obj, name=obj_name) + logger.trace(pickler, "# T4") + return + +@register(property) +@register(abc.abstractproperty) +def save_property(pickler, obj): + logger.trace(pickler, "Pr: %s", obj) + pickler.save_reduce(type(obj), (obj.fget, obj.fset, obj.fdel, obj.__doc__), + obj=obj) + logger.trace(pickler, "# Pr") + +@register(staticmethod) +@register(classmethod) +@register(abc.abstractstaticmethod) +@register(abc.abstractclassmethod) +def save_classmethod(pickler, obj): + logger.trace(pickler, "Cm: %s", obj) + orig_func = obj.__func__ + + # if type(obj.__dict__) is dict: + # if obj.__dict__: + # state = obj.__dict__ + # else: + # state = None + # else: + # state = (None, {'__dict__', obj.__dict__}) + + pickler.save_reduce(type(obj), (orig_func,), obj=obj) + logger.trace(pickler, "# Cm") + +@register(FunctionType) +def save_function(pickler, obj): + if not _locate_function(obj, pickler): + if type(obj.__code__) is not CodeType: + # Some PyPy builtin functions have no module name, and thus are not + # able to be located + module_name = getattr(obj, '__module__', None) + if module_name is None: + module_name = __builtin__.__name__ + module = _import_module(module_name, safe=True) + _pypy_builtin = False + try: + found, _ = _getattribute(module, obj.__qualname__) + if getattr(found, '__func__', None) is obj: + _pypy_builtin = True + except AttributeError: + pass + + if _pypy_builtin: + logger.trace(pickler, "F3: %s", obj) + pickler.save_reduce(getattr, (found, '__func__'), obj=obj) + logger.trace(pickler, "# F3") + return + + logger.trace(pickler, "F1: %s", obj) + _recurse = getattr(pickler, '_recurse', None) + _postproc = getattr(pickler, '_postproc', None) + _main_modified = getattr(pickler, '_main_modified', None) + _original_main = getattr(pickler, '_original_main', __builtin__)#'None' + postproc_list = [] + if _recurse: + # recurse to get all globals referred to by obj + from .detect import globalvars + globs_copy = globalvars(obj, recurse=True, builtin=True) + + # Add the name of the module to the globs dictionary to prevent + # the duplication of the dictionary. Pickle the unpopulated + # globals dictionary and set the remaining items after the function + # is created to correctly handle recursion. + globs = {'__name__': obj.__module__} + else: + globs_copy = obj.__globals__ + + # If the globals is the __dict__ from the module being saved as a + # session, substitute it by the dictionary being actually saved. + if _main_modified and globs_copy is _original_main.__dict__: + globs_copy = getattr(pickler, '_main', _original_main).__dict__ + globs = globs_copy + # If the globals is a module __dict__, do not save it in the pickle. + elif globs_copy is not None and obj.__module__ is not None and \ + getattr(_import_module(obj.__module__, True), '__dict__', None) is globs_copy: + globs = globs_copy + else: + globs = {'__name__': obj.__module__} + + if globs_copy is not None and globs is not globs_copy: + # In the case that the globals are copied, we need to ensure that + # the globals dictionary is updated when all objects in the + # dictionary are already created. + glob_ids = {id(g) for g in globs_copy.values()} + for stack_element in _postproc: + if stack_element in glob_ids: + _postproc[stack_element].append((_setitems, (globs, globs_copy))) + break + else: + postproc_list.append((_setitems, (globs, globs_copy))) + + closure = obj.__closure__ + state_dict = {} + for fattrname in ('__doc__', '__kwdefaults__', '__annotations__'): + fattr = getattr(obj, fattrname, None) + if fattr is not None: + state_dict[fattrname] = fattr + if obj.__qualname__ != obj.__name__: + state_dict['__qualname__'] = obj.__qualname__ + if '__name__' not in globs or obj.__module__ != globs['__name__']: + state_dict['__module__'] = obj.__module__ + + state = obj.__dict__ + if type(state) is not dict: + state_dict['__dict__'] = state + state = None + if state_dict: + state = state, state_dict + + _save_with_postproc(pickler, (_create_function, ( + obj.__code__, globs, obj.__name__, obj.__defaults__, + closure + ), state), obj=obj, postproc_list=postproc_list) + + # Lift closure cell update to earliest function (#458) + if _postproc: + topmost_postproc = next(iter(_postproc.values()), None) + if closure and topmost_postproc: + for cell in closure: + possible_postproc = (setattr, (cell, 'cell_contents', obj)) + try: + topmost_postproc.remove(possible_postproc) + except ValueError: + continue + + # Change the value of the cell + pickler.save_reduce(*possible_postproc) + # pop None created by calling preprocessing step off stack + pickler.write(POP) + + logger.trace(pickler, "# F1") + else: + logger.trace(pickler, "F2: %s", obj) + name = getattr(obj, '__qualname__', getattr(obj, '__name__', None)) + StockPickler.save_global(pickler, obj, name=name) + logger.trace(pickler, "# F2") + return + +if HAS_CTYPES and hasattr(ctypes, 'pythonapi'): + _PyCapsule_New = ctypes.pythonapi.PyCapsule_New + _PyCapsule_New.argtypes = (ctypes.c_void_p, ctypes.c_char_p, ctypes.c_void_p) + _PyCapsule_New.restype = ctypes.py_object + _PyCapsule_GetPointer = ctypes.pythonapi.PyCapsule_GetPointer + _PyCapsule_GetPointer.argtypes = (ctypes.py_object, ctypes.c_char_p) + _PyCapsule_GetPointer.restype = ctypes.c_void_p + _PyCapsule_GetDestructor = ctypes.pythonapi.PyCapsule_GetDestructor + _PyCapsule_GetDestructor.argtypes = (ctypes.py_object,) + _PyCapsule_GetDestructor.restype = ctypes.c_void_p + _PyCapsule_GetContext = ctypes.pythonapi.PyCapsule_GetContext + _PyCapsule_GetContext.argtypes = (ctypes.py_object,) + _PyCapsule_GetContext.restype = ctypes.c_void_p + _PyCapsule_GetName = ctypes.pythonapi.PyCapsule_GetName + _PyCapsule_GetName.argtypes = (ctypes.py_object,) + _PyCapsule_GetName.restype = ctypes.c_char_p + _PyCapsule_IsValid = ctypes.pythonapi.PyCapsule_IsValid + _PyCapsule_IsValid.argtypes = (ctypes.py_object, ctypes.c_char_p) + _PyCapsule_IsValid.restype = ctypes.c_bool + _PyCapsule_SetContext = ctypes.pythonapi.PyCapsule_SetContext + _PyCapsule_SetContext.argtypes = (ctypes.py_object, ctypes.c_void_p) + _PyCapsule_SetDestructor = ctypes.pythonapi.PyCapsule_SetDestructor + _PyCapsule_SetDestructor.argtypes = (ctypes.py_object, ctypes.c_void_p) + _PyCapsule_SetName = ctypes.pythonapi.PyCapsule_SetName + _PyCapsule_SetName.argtypes = (ctypes.py_object, ctypes.c_char_p) + _PyCapsule_SetPointer = ctypes.pythonapi.PyCapsule_SetPointer + _PyCapsule_SetPointer.argtypes = (ctypes.py_object, ctypes.c_void_p) + #from _socket import CAPI as _testcapsule + _testcapsule_name = b'dill._dill._testcapsule' + _testcapsule = _PyCapsule_New( + ctypes.cast(_PyCapsule_New, ctypes.c_void_p), + ctypes.c_char_p(_testcapsule_name), + None + ) + PyCapsuleType = type(_testcapsule) + @register(PyCapsuleType) + def save_capsule(pickler, obj): + logger.trace(pickler, "Cap: %s", obj) + name = _PyCapsule_GetName(obj) + #warnings.warn('Pickling a PyCapsule (%s) does not pickle any C data structures and could cause segmentation faults or other memory errors when unpickling.' % (name,), PicklingWarning) + pointer = _PyCapsule_GetPointer(obj, name) + context = _PyCapsule_GetContext(obj) + destructor = _PyCapsule_GetDestructor(obj) + pickler.save_reduce(_create_capsule, (pointer, name, context, destructor), obj=obj) + logger.trace(pickler, "# Cap") + _incedental_reverse_typemap['PyCapsuleType'] = PyCapsuleType + _reverse_typemap['PyCapsuleType'] = PyCapsuleType + _incedental_types.add(PyCapsuleType) +else: + _testcapsule = None + + +############################# +# A quick fix for issue #500 +# This should be removed when a better solution is found. + +if hasattr(dataclasses, "_HAS_DEFAULT_FACTORY_CLASS"): + @register(dataclasses._HAS_DEFAULT_FACTORY_CLASS) + def save_dataclasses_HAS_DEFAULT_FACTORY_CLASS(pickler, obj): + logger.trace(pickler, "DcHDF: %s", obj) + pickler.write(GLOBAL + b"dataclasses\n_HAS_DEFAULT_FACTORY\n") + logger.trace(pickler, "# DcHDF") + +if hasattr(dataclasses, "MISSING"): + @register(type(dataclasses.MISSING)) + def save_dataclasses_MISSING_TYPE(pickler, obj): + logger.trace(pickler, "DcM: %s", obj) + pickler.write(GLOBAL + b"dataclasses\nMISSING\n") + logger.trace(pickler, "# DcM") + +if hasattr(dataclasses, "KW_ONLY"): + @register(type(dataclasses.KW_ONLY)) + def save_dataclasses_KW_ONLY_TYPE(pickler, obj): + logger.trace(pickler, "DcKWO: %s", obj) + pickler.write(GLOBAL + b"dataclasses\nKW_ONLY\n") + logger.trace(pickler, "# DcKWO") + +if hasattr(dataclasses, "_FIELD_BASE"): + @register(dataclasses._FIELD_BASE) + def save_dataclasses_FIELD_BASE(pickler, obj): + logger.trace(pickler, "DcFB: %s", obj) + pickler.write(GLOBAL + b"dataclasses\n" + obj.name.encode() + b"\n") + logger.trace(pickler, "# DcFB") + +############################# + +# quick sanity checking +def pickles(obj,exact=False,safe=False,**kwds): + """ + Quick check if object pickles with dill. + + If *exact=True* then an equality test is done to check if the reconstructed + object matches the original object. + + If *safe=True* then any exception will raised in copy signal that the + object is not picklable, otherwise only pickling errors will be trapped. + + Additional keyword arguments are as :func:`dumps` and :func:`loads`. + """ + if safe: exceptions = (Exception,) # RuntimeError, ValueError + else: + exceptions = (TypeError, AssertionError, NotImplementedError, PicklingError, UnpicklingError) + try: + pik = copy(obj, **kwds) + #FIXME: should check types match first, then check content if "exact" + try: + #FIXME: should be "(pik == obj).all()" for numpy comparison, though that'll fail if shapes differ + result = bool(pik.all() == obj.all()) + except (AttributeError, TypeError): + warnings.filterwarnings('ignore') #FIXME: be specific + result = pik == obj + if warnings.filters: del warnings.filters[0] + if hasattr(result, 'toarray'): # for unusual types like sparse matrix + result = result.toarray().all() + if result: return True + if not exact: + result = type(pik) == type(obj) + if result: return result + # class instances might have been dumped with byref=False + return repr(type(pik)) == repr(type(obj)) #XXX: InstanceType? + return False + except exceptions: + return False + +def check(obj, *args, **kwds): + """ + Check pickling of an object across another process. + + *python* is the path to the python interpreter (defaults to sys.executable) + + Set *verbose=True* to print the unpickled object in the other process. + + Additional keyword arguments are as :func:`dumps` and :func:`loads`. + """ + # == undocumented == + # python -- the string path or executable name of the selected python + # verbose -- if True, be verbose about printing warning messages + # all other args and kwds are passed to dill.dumps #FIXME: ignore on load + verbose = kwds.pop('verbose', False) + python = kwds.pop('python', None) + if python is None: + import sys + python = sys.executable + # type check + isinstance(python, str) + import subprocess + fail = True + try: + _obj = dumps(obj, *args, **kwds) + fail = False + finally: + if fail and verbose: + print("DUMP FAILED") + #FIXME: fails if python interpreter path contains spaces + # Use the following instead (which also processes the 'ignore' keyword): + # ignore = kwds.pop('ignore', None) + # unpickle = "dill.loads(%s, ignore=%s)"%(repr(_obj), repr(ignore)) + # cmd = [python, "-c", "import dill; print(%s)"%unpickle] + # msg = "SUCCESS" if not subprocess.call(cmd) else "LOAD FAILED" + msg = "%s -c import dill; print(dill.loads(%s))" % (python, repr(_obj)) + msg = "SUCCESS" if not subprocess.call(msg.split(None,2)) else "LOAD FAILED" + if verbose: + print(msg) + return + +# use to protect against missing attributes +def is_dill(pickler, child=None): + "check the dill-ness of your pickler" + if child is False or not hasattr(pickler.__class__, 'mro'): + return 'dill' in pickler.__module__ + return Pickler in pickler.__class__.mro() + +def _extend(): + """extend pickle with all of dill's registered types""" + # need to have pickle not choke on _main_module? use is_dill(pickler) + for t,func in Pickler.dispatch.items(): + try: + StockPickler.dispatch[t] = func + except Exception: #TypeError, PicklingError, UnpicklingError + logger.trace(pickler, "skip: %s", t) + return + +del diff, _use_diff, use_diff + +# EOF diff --git a/dill/_objects.py b/dill/_objects.py new file mode 100644 index 0000000000000000000000000000000000000000..a37cd79bc33c73e69d44c11ada78912bf67c7c5a --- /dev/null +++ b/dill/_objects.py @@ -0,0 +1,541 @@ +#!/usr/bin/env python +# +# Author: Mike McKerns (mmckerns @caltech and @uqfoundation) +# Copyright (c) 2008-2016 California Institute of Technology. +# Copyright (c) 2016-2025 The Uncertainty Quantification Foundation. +# License: 3-clause BSD. The full license text is available at: +# - https://github.com/uqfoundation/dill/blob/master/LICENSE +""" +all Python Standard Library objects (currently: CH 1-15 @ 2.7) +and some other common objects (i.e. numpy.ndarray) +""" + +__all__ = ['registered','failures','succeeds'] + +# helper imports +import warnings; warnings.filterwarnings("ignore", category=DeprecationWarning) +import sys +import queue as Queue +#import dbm as anydbm #XXX: delete foo +from io import BytesIO as StringIO +import re +import array +import collections +import codecs +import struct +import dataclasses +import datetime +import calendar +import weakref +import pprint +import decimal +import numbers +import functools +import itertools +import operator +import tempfile +import shelve +import zlib +import gzip +import zipfile +import tarfile +import csv +import hashlib +import hmac +import os +import logging +import logging.handlers +import optparse +#import __hello__ +import threading +import socket +import contextlib +try: + import bz2 + import sqlite3 + import dbm.ndbm as dbm + HAS_ALL = True +except ImportError: # Ubuntu + HAS_ALL = False +try: + #import curses + #from curses import textpad, panel + HAS_CURSES = True +except ImportError: # Windows + HAS_CURSES = False +try: + import ctypes + HAS_CTYPES = True + # if using `pypy`, pythonapi is not found + IS_PYPY = not hasattr(ctypes, 'pythonapi') +except ImportError: # MacPorts + HAS_CTYPES = False + IS_PYPY = False + +IS_PYODIDE = sys.platform == 'emscripten' + +# helper objects +class _class: + def _method(self): + pass +# @classmethod +# def _clsmethod(cls): #XXX: test me +# pass +# @staticmethod +# def _static(self): #XXX: test me +# pass +class _class2: + def __call__(self): + pass +_instance2 = _class2() +class _newclass(object): + def _method(self): + pass +# @classmethod +# def _clsmethod(cls): #XXX: test me +# pass +# @staticmethod +# def _static(self): #XXX: test me +# pass +class _newclass2(object): + __slots__ = ['descriptor'] +def _function(x): yield x +def _function2(): + try: raise + except Exception: + from sys import exc_info + e, er, tb = exc_info() + return er, tb +if HAS_CTYPES: + class _Struct(ctypes.Structure): + pass + _Struct._fields_ = [("_field", ctypes.c_int),("next", ctypes.POINTER(_Struct))] +_filedescrip, _tempfile = tempfile.mkstemp('r') # deleted in cleanup +if sys.hexversion < 0x30d00a1: + _tmpf = tempfile.TemporaryFile('w') # emits OSError 9 in python 3.13 +else: + _tmpf = tempfile.NamedTemporaryFile('w').file # for > python 3.9 + +# objects used by dill for type declaration +registered = d = {} +# objects dill fails to pickle +failures = x = {} +# all other type objects +succeeds = a = {} + +# types module (part of CH 8) +a['BooleanType'] = bool(1) +a['BuiltinFunctionType'] = len +a['BuiltinMethodType'] = a['BuiltinFunctionType'] +a['BytesType'] = _bytes = codecs.latin_1_encode('\x00')[0] # bytes(1) +a['ClassType'] = _class +a['ComplexType'] = complex(1) +a['DictType'] = _dict = {} +a['DictionaryType'] = a['DictType'] +a['FloatType'] = float(1) +a['FunctionType'] = _function +a['InstanceType'] = _instance = _class() +a['IntType'] = _int = int(1) +a['ListType'] = _list = [] +a['NoneType'] = None +a['ObjectType'] = object() +a['StringType'] = _str = str(1) +a['TupleType'] = _tuple = () +a['TypeType'] = type +a['LongType'] = _int +a['UnicodeType'] = _str +# built-in constants (CH 4) +a['CopyrightType'] = copyright +# built-in types (CH 5) +a['ClassObjectType'] = _newclass # +a['ClassInstanceType'] = _newclass() # +a['SetType'] = _set = set() +a['FrozenSetType'] = frozenset() +# built-in exceptions (CH 6) +a['ExceptionType'] = _exception = _function2()[0] +# string services (CH 7) +a['SREPatternType'] = _srepattern = re.compile('') +# data types (CH 8) +a['ArrayType'] = array.array("f") +a['DequeType'] = collections.deque([0]) +a['DefaultDictType'] = collections.defaultdict(_function, _dict) +a['TZInfoType'] = datetime.tzinfo() +a['DateTimeType'] = datetime.datetime.today() +a['CalendarType'] = calendar.Calendar() +# numeric and mathematical types (CH 9) +a['DecimalType'] = decimal.Decimal(1) +# data compression and archiving (CH 12) +a['TarInfoType'] = tarfile.TarInfo() +# generic operating system services (CH 15) +a['LoggerType'] = _logger = logging.getLogger() +a['FormatterType'] = logging.Formatter() # pickle ok +a['FilterType'] = logging.Filter() # pickle ok +a['LogRecordType'] = logging.makeLogRecord(_dict) # pickle ok +a['OptionParserType'] = _oparser = optparse.OptionParser() # pickle ok +a['OptionGroupType'] = optparse.OptionGroup(_oparser,"foo") # pickle ok +a['OptionType'] = optparse.Option('--foo') # pickle ok +if HAS_CTYPES: + z = x if IS_PYPY else a + z['CCharType'] = _cchar = ctypes.c_char() + z['CWCharType'] = ctypes.c_wchar() # fail == 2.6 + z['CByteType'] = ctypes.c_byte() + z['CUByteType'] = ctypes.c_ubyte() + z['CShortType'] = ctypes.c_short() + z['CUShortType'] = ctypes.c_ushort() + z['CIntType'] = ctypes.c_int() + z['CUIntType'] = ctypes.c_uint() + z['CLongType'] = ctypes.c_long() + z['CULongType'] = ctypes.c_ulong() + z['CLongLongType'] = ctypes.c_longlong() + z['CULongLongType'] = ctypes.c_ulonglong() + z['CFloatType'] = ctypes.c_float() + z['CDoubleType'] = ctypes.c_double() + z['CSizeTType'] = ctypes.c_size_t() + del z + a['CLibraryLoaderType'] = ctypes.cdll + a['StructureType'] = _Struct + # if not IS_PYPY: + # a['BigEndianStructureType'] = ctypes.BigEndianStructure() +#NOTE: also LittleEndianStructureType and UnionType... abstract classes +#NOTE: remember for ctypesobj.contents creates a new python object +#NOTE: ctypes.c_int._objects is memberdescriptor for object's __dict__ +#NOTE: base class of all ctypes data types is non-public _CData + +import fractions +import io +from io import StringIO as TextIO +# built-in functions (CH 2) +a['ByteArrayType'] = bytearray([1]) +# numeric and mathematical types (CH 9) +a['FractionType'] = fractions.Fraction() +a['NumberType'] = numbers.Number() +# generic operating system services (CH 15) +a['IOBaseType'] = io.IOBase() +a['RawIOBaseType'] = io.RawIOBase() +a['TextIOBaseType'] = io.TextIOBase() +a['BufferedIOBaseType'] = io.BufferedIOBase() +a['UnicodeIOType'] = TextIO() # the new StringIO +a['LoggerAdapterType'] = logging.LoggerAdapter(_logger,_dict) # pickle ok +if HAS_CTYPES: + z = x if IS_PYPY else a + z['CBoolType'] = ctypes.c_bool(1) + z['CLongDoubleType'] = ctypes.c_longdouble() + del z +import argparse +# data types (CH 8) +a['OrderedDictType'] = collections.OrderedDict(_dict) +a['CounterType'] = collections.Counter(_dict) +if HAS_CTYPES: + z = x if IS_PYPY else a + z['CSSizeTType'] = ctypes.c_ssize_t() + del z +# generic operating system services (CH 15) +a['NullHandlerType'] = logging.NullHandler() # pickle ok # new 2.7 +a['ArgParseFileType'] = argparse.FileType() # pickle ok + +# -- pickle fails on all below here ----------------------------------------- +# types module (part of CH 8) +a['CodeType'] = compile('','','exec') +a['DictProxyType'] = type.__dict__ +a['DictProxyType2'] = _newclass.__dict__ +a['EllipsisType'] = Ellipsis +a['ClosedFileType'] = open(os.devnull, 'wb', buffering=0).close() +a['GetSetDescriptorType'] = array.array.typecode +a['LambdaType'] = _lambda = lambda x: lambda y: x #XXX: works when not imported! +a['MemberDescriptorType'] = _newclass2.descriptor +if not IS_PYPY: + a['MemberDescriptorType2'] = datetime.timedelta.days +a['MethodType'] = _method = _class()._method #XXX: works when not imported! +a['ModuleType'] = datetime +a['NotImplementedType'] = NotImplemented +a['SliceType'] = slice(1) +a['UnboundMethodType'] = _class._method #XXX: works when not imported! +d['TextWrapperType'] = open(os.devnull, 'r') # same as mode='w','w+','r+' +if not IS_PYODIDE: + d['BufferedRandomType'] = open(os.devnull, 'r+b') # same as mode='w+b' +d['BufferedReaderType'] = open(os.devnull, 'rb') # (default: buffering=-1) +d['BufferedWriterType'] = open(os.devnull, 'wb') +try: # oddities: deprecated + from _pyio import open as _open + d['PyTextWrapperType'] = _open(os.devnull, 'r', buffering=-1) + if not IS_PYODIDE: + d['PyBufferedRandomType'] = _open(os.devnull, 'r+b', buffering=-1) + d['PyBufferedReaderType'] = _open(os.devnull, 'rb', buffering=-1) + d['PyBufferedWriterType'] = _open(os.devnull, 'wb', buffering=-1) +except ImportError: + pass +# other (concrete) object types +z = d if sys.hexversion < 0x30800a2 else a +z['CellType'] = (_lambda)(0).__closure__[0] +del z +a['XRangeType'] = _xrange = range(1) +a['MethodDescriptorType'] = type.__dict__['mro'] +a['WrapperDescriptorType'] = type.__repr__ +#a['WrapperDescriptorType2'] = type.__dict__['__module__']#XXX: GetSetDescriptor +a['ClassMethodDescriptorType'] = type.__dict__['__prepare__'] +# built-in functions (CH 2) +_methodwrap = (1).__lt__ +a['MethodWrapperType'] = _methodwrap +a['StaticMethodType'] = staticmethod(_method) +a['ClassMethodType'] = classmethod(_method) +a['PropertyType'] = property() +d['SuperType'] = super(Exception, _exception) +# string services (CH 7) +_in = _bytes +a['InputType'] = _cstrI = StringIO(_in) +a['OutputType'] = _cstrO = StringIO() +# data types (CH 8) +a['WeakKeyDictionaryType'] = weakref.WeakKeyDictionary() +a['WeakValueDictionaryType'] = weakref.WeakValueDictionary() +a['ReferenceType'] = weakref.ref(_instance) +a['DeadReferenceType'] = weakref.ref(_class()) +a['ProxyType'] = weakref.proxy(_instance) +a['DeadProxyType'] = weakref.proxy(_class()) +a['CallableProxyType'] = weakref.proxy(_instance2) +a['DeadCallableProxyType'] = weakref.proxy(_class2()) +a['QueueType'] = Queue.Queue() +# numeric and mathematical types (CH 9) +d['PartialType'] = functools.partial(int,base=2) +a['IzipType'] = zip('0','1') +d['ItemGetterType'] = operator.itemgetter(0) +d['AttrGetterType'] = operator.attrgetter('__repr__') +# file and directory access (CH 10) +_fileW = _cstrO +# data persistence (CH 11) +if HAS_ALL: + x['ConnectionType'] = _conn = sqlite3.connect(':memory:') + x['CursorType'] = _conn.cursor() +a['ShelveType'] = shelve.Shelf({}) +# data compression and archiving (CH 12) +if HAS_ALL: + x['BZ2FileType'] = bz2.BZ2File(os.devnull) + x['BZ2CompressorType'] = bz2.BZ2Compressor() + x['BZ2DecompressorType'] = bz2.BZ2Decompressor() +#x['ZipFileType'] = _zip = zipfile.ZipFile(os.devnull,'w') +#_zip.write(_tempfile,'x') [causes annoying warning/error printed on import] +#a['ZipInfoType'] = _zip.getinfo('x') +a['TarFileType'] = tarfile.open(fileobj=_fileW,mode='w') +# file formats (CH 13) +x['DialectType'] = csv.get_dialect('excel') +if sys.hexversion < 0x30d00a1: + import xdrlib + a['PackerType'] = xdrlib.Packer() +# optional operating system services (CH 16) +a['LockType'] = threading.Lock() +a['RLockType'] = threading.RLock() +# generic operating system services (CH 15) # also closed/open and r/w/etc... +a['NamedLoggerType'] = _logger = logging.getLogger(__name__) +#a['FrozenModuleType'] = __hello__ #FIXME: prints "Hello world..." +# interprocess communication (CH 17) +x['SocketType'] = _socket = socket.socket() +x['SocketPairType'] = socket.socketpair()[0] +# python runtime services (CH 27) +a['GeneratorContextManagerType'] = contextlib.contextmanager(max)([1]) + +try: # ipython + __IPYTHON__ is True # is ipython +except NameError: + # built-in constants (CH 4) + a['QuitterType'] = quit + d['ExitType'] = a['QuitterType'] +try: # numpy #FIXME: slow... 0.05 to 0.1 sec to import numpy + from numpy import ufunc as _numpy_ufunc + from numpy import array as _numpy_array + from numpy import int32 as _numpy_int32 + a['NumpyUfuncType'] = _numpy_ufunc + a['NumpyArrayType'] = _numpy_array + a['NumpyInt32Type'] = _numpy_int32 +except ImportError: + pass +# generic operating system services (CH 15) +a['FileHandlerType'] = logging.FileHandler(os.devnull) +a['RotatingFileHandlerType'] = logging.handlers.RotatingFileHandler(os.devnull) +a['SocketHandlerType'] = logging.handlers.SocketHandler('localhost',514) +a['MemoryHandlerType'] = logging.handlers.MemoryHandler(1) +# data types (CH 8) +a['WeakSetType'] = weakref.WeakSet() # 2.7 +# generic operating system services (CH 15) [errors when dill is imported] +#a['ArgumentParserType'] = _parser = argparse.ArgumentParser('PROG') +#a['NamespaceType'] = _parser.parse_args() # pickle ok +#a['SubParsersActionType'] = _parser.add_subparsers() +#a['MutuallyExclusiveGroupType'] = _parser.add_mutually_exclusive_group() +#a['ArgumentGroupType'] = _parser.add_argument_group() + +# -- dill fails in some versions below here --------------------------------- +# types module (part of CH 8) +d['FileType'] = open(os.devnull, 'rb', buffering=0) # same 'wb','wb+','rb+' +# built-in functions (CH 2) +# Iterators: +a['ListIteratorType'] = iter(_list) # empty vs non-empty +a['SetIteratorType'] = iter(_set) #XXX: empty vs non-empty #FIXME: list_iterator +a['TupleIteratorType']= iter(_tuple) # empty vs non-empty +a['XRangeIteratorType'] = iter(_xrange) # empty vs non-empty +a["BytesIteratorType"] = iter(b'') +a["BytearrayIteratorType"] = iter(bytearray(b'')) +z = x if IS_PYPY else a +z["CallableIteratorType"] = iter(iter, None) +del z +x["MemoryIteratorType"] = iter(memoryview(b'')) +a["ListReverseiteratorType"] = reversed([]) +X = a['OrderedDictType'] +d["OdictKeysType"] = X.keys() +d["OdictValuesType"] = X.values() +d["OdictItemsType"] = X.items() +a["OdictIteratorType"] = iter(X.keys()) #FIXME: list_iterator +del X +#FIXME: list_iterator +a['DictionaryItemIteratorType'] = iter(type.__dict__.items()) +a['DictionaryKeyIteratorType'] = iter(type.__dict__.keys()) +a['DictionaryValueIteratorType'] = iter(type.__dict__.values()) +if sys.hexversion >= 0x30800a0: + a["DictReversekeyiteratorType"] = reversed({}.keys()) + a["DictReversevalueiteratorType"] = reversed({}.values()) + a["DictReverseitemiteratorType"] = reversed({}.items()) + +try: + import symtable + #FIXME: fails to pickle + x["SymtableEntryType"] = symtable.symtable("", "string", "exec")._table +except ImportError: + pass + +if sys.hexversion >= 0x30a00a0 and not IS_PYPY: + x['LineIteratorType'] = compile('3', '', 'eval').co_lines() + +if sys.hexversion >= 0x30b00b0 and not IS_PYPY: + from types import GenericAlias + d["GenericAliasIteratorType"] = iter(GenericAlias(list, (int,))) + x['PositionsIteratorType'] = compile('3', '', 'eval').co_positions() + +# data types (CH 8) +a['PrettyPrinterType'] = pprint.PrettyPrinter() +# file and directory access (CH 10) +a['TemporaryFileType'] = _tmpf +# data compression and archiving (CH 12) +x['GzipFileType'] = gzip.GzipFile(fileobj=_fileW) +# generic operating system services (CH 15) +a['StreamHandlerType'] = logging.StreamHandler() +# numeric and mathematical types (CH 9) +z = a if sys.hexversion < 0x30e00a1 else x +z['CountType'] = itertools.count(0) #FIXME: __reduce__ removed in 3.14.0a1 +z['ChainType'] = itertools.chain('0','1') +z['ProductType'] = itertools.product('0','1') +z['CycleType'] = itertools.cycle('0') +z['PermutationsType'] = itertools.permutations('0') +z['CombinationsType'] = itertools.combinations('0',1) +z['RepeatType'] = itertools.repeat(0) +z['CompressType'] = itertools.compress('0',[1]) +del z +#XXX: ...and etc + +# -- dill fails on all below here ------------------------------------------- +# types module (part of CH 8) +x['GeneratorType'] = _generator = _function(1) #XXX: priority +x['FrameType'] = _generator.gi_frame #XXX: inspect.currentframe() +x['TracebackType'] = _function2()[1] #(see: inspect.getouterframes,getframeinfo) +# other (concrete) object types +# (also: Capsule / CObject ?) +# built-in functions (CH 2) +# built-in types (CH 5) +# string services (CH 7) +x['StructType'] = struct.Struct('c') +x['CallableIteratorType'] = _srepattern.finditer('') +x['SREMatchType'] = _srepattern.match('') +x['SREScannerType'] = _srepattern.scanner('') +x['StreamReader'] = codecs.StreamReader(_cstrI) #XXX: ... and etc +# python object persistence (CH 11) +# x['DbShelveType'] = shelve.open('foo','n')#,protocol=2) #XXX: delete foo +if HAS_ALL: + z = a if IS_PYPY else x + z['DbmType'] = dbm.open(_tempfile,'n') + del z +# x['DbCursorType'] = _dbcursor = anydbm.open('foo','n') #XXX: delete foo +# x['DbType'] = _dbcursor.db +# data compression and archiving (CH 12) +x['ZlibCompressType'] = zlib.compressobj() +x['ZlibDecompressType'] = zlib.decompressobj() +# file formats (CH 13) +x['CSVReaderType'] = csv.reader(_cstrI) +x['CSVWriterType'] = csv.writer(_cstrO) +x['CSVDictReaderType'] = csv.DictReader(_cstrI) +x['CSVDictWriterType'] = csv.DictWriter(_cstrO,{}) +# cryptographic services (CH 14) +x['HashType'] = hashlib.md5() +if (sys.hexversion < 0x30800a1): + x['HMACType'] = hmac.new(_in) +else: + x['HMACType'] = hmac.new(_in, digestmod='md5') +# generic operating system services (CH 15) +if HAS_CURSES: pass + #x['CursesWindowType'] = _curwin = curses.initscr() #FIXME: messes up tty + #x['CursesTextPadType'] = textpad.Textbox(_curwin) + #x['CursesPanelType'] = panel.new_panel(_curwin) +if HAS_CTYPES: + x['CCharPType'] = ctypes.c_char_p() + x['CWCharPType'] = ctypes.c_wchar_p() + x['CVoidPType'] = ctypes.c_void_p() + if sys.platform[:3] == 'win': + x['CDLLType'] = _cdll = ctypes.cdll.msvcrt + else: + x['CDLLType'] = _cdll = ctypes.CDLL(None) + if not IS_PYPY: + x['PyDLLType'] = _pydll = ctypes.pythonapi + x['FuncPtrType'] = _cdll._FuncPtr() + x['CCharArrayType'] = ctypes.create_string_buffer(1) + x['CWCharArrayType'] = ctypes.create_unicode_buffer(1) + x['CParamType'] = ctypes.byref(_cchar) + x['LPCCharType'] = ctypes.pointer(_cchar) + x['LPCCharObjType'] = _lpchar = ctypes.POINTER(ctypes.c_char) + x['NullPtrType'] = _lpchar() + x['NullPyObjectType'] = ctypes.py_object() + x['PyObjectType'] = ctypes.py_object(lambda :None) + z = a if IS_PYPY else x + z['FieldType'] = _field = _Struct._field + z['CFUNCTYPEType'] = _cfunc = ctypes.CFUNCTYPE(ctypes.c_char) + if sys.hexversion < 0x30c00b3: + x['CFunctionType'] = _cfunc(str) + del z +# numeric and mathematical types (CH 9) +a['MethodCallerType'] = operator.methodcaller('mro') # 2.6 +# built-in types (CH 5) +x['MemoryType'] = memoryview(_in) # 2.7 +x['MemoryType2'] = memoryview(bytearray(_in)) # 2.7 +d['DictItemsType'] = _dict.items() # 2.7 +d['DictKeysType'] = _dict.keys() # 2.7 +d['DictValuesType'] = _dict.values() # 2.7 +# generic operating system services (CH 15) +a['RawTextHelpFormatterType'] = argparse.RawTextHelpFormatter('PROG') +a['RawDescriptionHelpFormatterType'] = argparse.RawDescriptionHelpFormatter('PROG') +a['ArgDefaultsHelpFormatterType'] = argparse.ArgumentDefaultsHelpFormatter('PROG') +z = a if IS_PYPY else x +z['CmpKeyType'] = _cmpkey = functools.cmp_to_key(_methodwrap) # 2.7, >=3.2 +z['CmpKeyObjType'] = _cmpkey('0') #2.7, >=3.2 +del z +# oddities: removed, etc +x['BufferType'] = x['MemoryType'] + +from dill._dill import _testcapsule +if _testcapsule is not None: + d['PyCapsuleType'] = _testcapsule +del _testcapsule + +if hasattr(dataclasses, '_HAS_DEFAULT_FACTORY'): + a['DataclassesHasDefaultFactoryType'] = dataclasses._HAS_DEFAULT_FACTORY + +if hasattr(dataclasses, 'MISSING'): + a['DataclassesMissingType'] = dataclasses.MISSING + +if hasattr(dataclasses, 'KW_ONLY'): + a['DataclassesKWOnlyType'] = dataclasses.KW_ONLY + +if hasattr(dataclasses, '_FIELD_BASE'): + a['DataclassesFieldBaseType'] = dataclasses._FIELD + +# -- cleanup ---------------------------------------------------------------- +a.update(d) # registered also succeed +if sys.platform[:3] == 'win': + os.close(_filedescrip) # required on win32 +os.remove(_tempfile) + + +# EOF diff --git a/dill/_shims.py b/dill/_shims.py new file mode 100644 index 0000000000000000000000000000000000000000..bb0a9dcdfa4ec424ec99f805ff39996346f58ee9 --- /dev/null +++ b/dill/_shims.py @@ -0,0 +1,193 @@ +#!/usr/bin/env python +# +# Author: Mike McKerns (mmckerns @caltech and @uqfoundation) +# Author: Anirudh Vegesana (avegesan@cs.stanford.edu) +# Copyright (c) 2021-2025 The Uncertainty Quantification Foundation. +# License: 3-clause BSD. The full license text is available at: +# - https://github.com/uqfoundation/dill/blob/master/LICENSE +""" +Provides shims for compatibility between versions of dill and Python. + +Compatibility shims should be provided in this file. Here are two simple example +use cases. + +Deprecation of constructor function: +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +Assume that we were transitioning _import_module in _dill.py to +the builtin function importlib.import_module when present. + +@move_to(_dill) +def _import_module(import_name): + ... # code already in _dill.py + +_import_module = Getattr(importlib, 'import_module', Getattr(_dill, '_import_module', None)) + +The code will attempt to find import_module in the importlib module. If not +present, it will use the _import_module function in _dill. + +Emulate new Python behavior in older Python versions: +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +CellType.cell_contents behaves differently in Python 3.6 and 3.7. It is +read-only in Python 3.6 and writable and deletable in 3.7. + +if _dill.OLD37 and _dill.HAS_CTYPES and ...: + @move_to(_dill) + def _setattr(object, name, value): + if type(object) is _dill.CellType and name == 'cell_contents': + _PyCell_Set.argtypes = (ctypes.py_object, ctypes.py_object) + _PyCell_Set(object, value) + else: + setattr(object, name, value) +... # more cases below + +_setattr = Getattr(_dill, '_setattr', setattr) + +_dill._setattr will be used when present to emulate Python 3.7 functionality in +older versions of Python while defaulting to the standard setattr in 3.7+. + +See this PR for the discussion that lead to this system: +https://github.com/uqfoundation/dill/pull/443 +""" + +import inspect +import sys + +_dill = sys.modules['dill._dill'] + + +class Reduce(object): + """ + Reduce objects are wrappers used for compatibility enforcement during + unpickle-time. They should only be used in calls to pickler.save and + other Reduce objects. They are only evaluated within unpickler.load. + + Pickling a Reduce object makes the two implementations equivalent: + + pickler.save(Reduce(*reduction)) + + pickler.save_reduce(*reduction, obj=reduction) + """ + __slots__ = ['reduction'] + def __new__(cls, *reduction, **kwargs): + """ + Args: + *reduction: a tuple that matches the format given here: + https://docs.python.org/3/library/pickle.html#object.__reduce__ + is_callable: a bool to indicate that the object created by + unpickling `reduction` is callable. If true, the current Reduce + is allowed to be used as the function in further save_reduce calls + or Reduce objects. + """ + is_callable = kwargs.get('is_callable', False) # Pleases Py2. Can be removed later + if is_callable: + self = object.__new__(_CallableReduce) + else: + self = object.__new__(Reduce) + self.reduction = reduction + return self + def __repr__(self): + return 'Reduce%s' % (self.reduction,) + def __copy__(self): + return self # pragma: no cover + def __deepcopy__(self, memo): + return self # pragma: no cover + def __reduce__(self): + return self.reduction + def __reduce_ex__(self, protocol): + return self.__reduce__() + +class _CallableReduce(Reduce): + # A version of Reduce for functions. Used to trick pickler.save_reduce into + # thinking that Reduce objects of functions are themselves meaningful functions. + def __call__(self, *args, **kwargs): + reduction = self.__reduce__() + func = reduction[0] + f_args = reduction[1] + obj = func(*f_args) + return obj(*args, **kwargs) + +__NO_DEFAULT = _dill.Sentinel('Getattr.NO_DEFAULT') + +def Getattr(object, name, default=__NO_DEFAULT): + """ + A Reduce object that represents the getattr operation. When unpickled, the + Getattr will access an attribute 'name' of 'object' and return the value + stored there. If the attribute doesn't exist, the default value will be + returned if present. + + The following statements are equivalent: + + Getattr(collections, 'OrderedDict') + Getattr(collections, 'spam', None) + Getattr(*args) + + Reduce(getattr, (collections, 'OrderedDict')) + Reduce(getattr, (collections, 'spam', None)) + Reduce(getattr, args) + + During unpickling, the first two will result in collections.OrderedDict and + None respectively because the first attribute exists and the second one does + not, forcing it to use the default value given in the third argument. + """ + + if default is Getattr.NO_DEFAULT: + reduction = (getattr, (object, name)) + else: + reduction = (getattr, (object, name, default)) + + return Reduce(*reduction, is_callable=callable(default)) + +Getattr.NO_DEFAULT = __NO_DEFAULT +del __NO_DEFAULT + +def move_to(module, name=None): + def decorator(func): + if name is None: + fname = func.__name__ + else: + fname = name + module.__dict__[fname] = func + func.__module__ = module.__name__ + return func + return decorator + +def register_shim(name, default): + """ + A easier to understand and more compact way of "softly" defining a function. + These two pieces of code are equivalent: + + if _dill.OLD3X: + def _create_class(): + ... + _create_class = register_shim('_create_class', types.new_class) + + if _dill.OLD3X: + @move_to(_dill) + def _create_class(): + ... + _create_class = Getattr(_dill, '_create_class', types.new_class) + + Intuitively, it creates a function or object in the versions of dill/python + that require special reimplementations, and use a core library or default + implementation if that function or object does not exist. + """ + func = globals().get(name) + if func is not None: + _dill.__dict__[name] = func + func.__module__ = _dill.__name__ + + if default is Getattr.NO_DEFAULT: + reduction = (getattr, (_dill, name)) + else: + reduction = (getattr, (_dill, name, default)) + + return Reduce(*reduction, is_callable=callable(default)) + +###################### +## Compatibility Shims are defined below +###################### + +_CELL_EMPTY = register_shim('_CELL_EMPTY', None) + +_setattr = register_shim('_setattr', setattr) +_delattr = register_shim('_delattr', delattr) diff --git a/dill/detect.py b/dill/detect.py new file mode 100644 index 0000000000000000000000000000000000000000..2f0bea1c7e9e8ab40fea50a8576506d7d2e4a3fc --- /dev/null +++ b/dill/detect.py @@ -0,0 +1,287 @@ +#!/usr/bin/env python +# +# Author: Mike McKerns (mmckerns @caltech and @uqfoundation) +# Copyright (c) 2008-2016 California Institute of Technology. +# Copyright (c) 2016-2025 The Uncertainty Quantification Foundation. +# License: 3-clause BSD. The full license text is available at: +# - https://github.com/uqfoundation/dill/blob/master/LICENSE +""" +Methods for detecting objects leading to pickling failures. +""" + +import dis +from inspect import ismethod, isfunction, istraceback, isframe, iscode + +from .pointers import parent, reference, at, parents, children +from .logger import trace + +__all__ = ['baditems','badobjects','badtypes','code','errors','freevars', + 'getmodule','globalvars','nestedcode','nestedglobals','outermost', + 'referredglobals','referrednested','trace','varnames'] + +def getmodule(object, _filename=None, force=False): + """get the module of the object""" + from inspect import getmodule as getmod + module = getmod(object, _filename) + if module or not force: return module + import builtins + from .source import getname + name = getname(object, force=True) + return builtins if name in vars(builtins).keys() else None + +def outermost(func): # is analogous to getsource(func,enclosing=True) + """get outermost enclosing object (i.e. the outer function in a closure) + + NOTE: this is the object-equivalent of getsource(func, enclosing=True) + """ + if ismethod(func): + _globals = func.__func__.__globals__ or {} + elif isfunction(func): + _globals = func.__globals__ or {} + else: + return #XXX: or raise? no matches + _globals = _globals.items() + # get the enclosing source + from .source import getsourcelines + try: lines,lnum = getsourcelines(func, enclosing=True) + except Exception: #TypeError, IOError + lines,lnum = [],None + code = ''.join(lines) + # get all possible names,objects that are named in the enclosing source + _locals = ((name,obj) for (name,obj) in _globals if name in code) + # now only save the objects that generate the enclosing block + for name,obj in _locals: #XXX: don't really need 'name' + try: + if getsourcelines(obj) == (lines,lnum): return obj + except Exception: #TypeError, IOError + pass + return #XXX: or raise? no matches + +def nestedcode(func, recurse=True): #XXX: or return dict of {co_name: co} ? + """get the code objects for any nested functions (e.g. in a closure)""" + func = code(func) + if not iscode(func): return [] #XXX: or raise? no matches + nested = set() + for co in func.co_consts: + if co is None: continue + co = code(co) + if co: + nested.add(co) + if recurse: nested |= set(nestedcode(co, recurse=True)) + return list(nested) + +def code(func): + """get the code object for the given function or method + + NOTE: use dill.source.getsource(CODEOBJ) to get the source code + """ + if ismethod(func): func = func.__func__ + if isfunction(func): func = func.__code__ + if istraceback(func): func = func.tb_frame + if isframe(func): func = func.f_code + if iscode(func): return func + return + +#XXX: ugly: parse dis.dis for name after " len(referrednested(func)), try calling func(). + If possible, python builds code objects, but delays building functions + until func() is called. + """ + import gc + funcs = set() + # get the code objects, and try to track down by referrence + for co in nestedcode(func, recurse): + # look for function objects that refer to the code object + for obj in gc.get_referrers(co): + # get methods + _ = getattr(obj, '__func__', None) # ismethod + if getattr(_, '__code__', None) is co: funcs.add(obj) + # get functions + elif getattr(obj, '__code__', None) is co: funcs.add(obj) + # get frame objects + elif getattr(obj, 'f_code', None) is co: funcs.add(obj) + # get code objects + elif hasattr(obj, 'co_code') and obj is co: funcs.add(obj) +# frameobjs => func.__code__.co_varnames not in func.__code__.co_cellvars +# funcobjs => func.__code__.co_cellvars not in func.__code__.co_varnames +# frameobjs are not found, however funcobjs are... +# (see: test_mixins.quad ... and test_mixins.wtf) +# after execution, code objects get compiled, and then may be found by gc + return list(funcs) + + +def freevars(func): + """get objects defined in enclosing code that are referred to by func + + returns a dict of {name:object}""" + if ismethod(func): func = func.__func__ + if isfunction(func): + closures = func.__closure__ or () + func = func.__code__.co_freevars # get freevars + else: + return {} + + def get_cell_contents(): + for name, c in zip(func, closures): + try: + cell_contents = c.cell_contents + except ValueError: # cell is empty + continue + yield name, c.cell_contents + + return dict(get_cell_contents()) + +# thanks to Davies Liu for recursion of globals +def nestedglobals(func, recurse=True): + """get the names of any globals found within func""" + func = code(func) + if func is None: return list() + import sys + from .temp import capture + CAN_NULL = sys.hexversion >= 0x30b00a7 # NULL may be prepended >= 3.11a7 + names = set() + with capture('stdout') as out: + try: + dis.dis(func) #XXX: dis.dis(None) disassembles last traceback + except IndexError: + pass #FIXME: HACK for IS_PYPY (3.11) + for line in out.getvalue().splitlines(): + if '_GLOBAL' in line: + name = line.split('(')[-1].split(')')[0] + if CAN_NULL: + names.add(name.replace('NULL + ', '').replace(' + NULL', '')) + else: + names.add(name) + for co in getattr(func, 'co_consts', tuple()): + if co and recurse and iscode(co): + names.update(nestedglobals(co, recurse=True)) + return list(names) + +def referredglobals(func, recurse=True, builtin=False): + """get the names of objects in the global scope referred to by func""" + return globalvars(func, recurse, builtin).keys() + +def globalvars(func, recurse=True, builtin=False): + """get objects defined in global scope that are referred to by func + + return a dict of {name:object}""" + if ismethod(func): func = func.__func__ + if isfunction(func): + globs = vars(getmodule(sum)).copy() if builtin else {} + # get references from within closure + orig_func, func = func, set() + for obj in orig_func.__closure__ or {}: + try: + cell_contents = obj.cell_contents + except ValueError: # cell is empty + pass + else: + _vars = globalvars(cell_contents, recurse, builtin) or {} + func.update(_vars) #XXX: (above) be wary of infinte recursion? + globs.update(_vars) + # get globals + globs.update(orig_func.__globals__ or {}) + # get names of references + if not recurse: + func.update(orig_func.__code__.co_names) + else: + func.update(nestedglobals(orig_func.__code__)) + # find globals for all entries of func + for key in func.copy(): #XXX: unnecessary...? + nested_func = globs.get(key) + if nested_func is orig_func: + #func.remove(key) if key in func else None + continue #XXX: globalvars(func, False)? + func.update(globalvars(nested_func, True, builtin)) + elif iscode(func): + globs = vars(getmodule(sum)).copy() if builtin else {} + #globs.update(globals()) + if not recurse: + func = func.co_names # get names + else: + orig_func = func.co_name # to stop infinite recursion + func = set(nestedglobals(func)) + # find globals for all entries of func + for key in func.copy(): #XXX: unnecessary...? + if key is orig_func: + #func.remove(key) if key in func else None + continue #XXX: globalvars(func, False)? + nested_func = globs.get(key) + func.update(globalvars(nested_func, True, builtin)) + else: + return {} + #NOTE: if name not in __globals__, then we skip it... + return dict((name,globs[name]) for name in func if name in globs) + + +def varnames(func): + """get names of variables defined by func + + returns a tuple (local vars, local vars referrenced by nested functions)""" + func = code(func) + if not iscode(func): + return () #XXX: better ((),())? or None? + return func.co_varnames, func.co_cellvars + + +def baditems(obj, exact=False, safe=False): #XXX: obj=globals() ? + """get items in object that fail to pickle""" + if not hasattr(obj,'__iter__'): # is not iterable + return [j for j in (badobjects(obj,0,exact,safe),) if j is not None] + obj = obj.values() if getattr(obj,'values',None) else obj + _obj = [] # can't use a set, as items may be unhashable + [_obj.append(badobjects(i,0,exact,safe)) for i in obj if i not in _obj] + return [j for j in _obj if j is not None] + + +def badobjects(obj, depth=0, exact=False, safe=False): + """get objects that fail to pickle""" + from dill import pickles + if not depth: + if pickles(obj,exact,safe): return None + return obj + return dict(((attr, badobjects(getattr(obj,attr),depth-1,exact,safe)) \ + for attr in dir(obj) if not pickles(getattr(obj,attr),exact,safe))) + +def badtypes(obj, depth=0, exact=False, safe=False): + """get types for objects that fail to pickle""" + from dill import pickles + if not depth: + if pickles(obj,exact,safe): return None + return type(obj) + return dict(((attr, badtypes(getattr(obj,attr),depth-1,exact,safe)) \ + for attr in dir(obj) if not pickles(getattr(obj,attr),exact,safe))) + +def errors(obj, depth=0, exact=False, safe=False): + """get errors for objects that fail to pickle""" + from dill import pickles, copy + if not depth: + try: + pik = copy(obj) + if exact: + assert pik == obj, \ + "Unpickling produces %s instead of %s" % (pik,obj) + assert type(pik) == type(obj), \ + "Unpickling produces %s instead of %s" % (type(pik),type(obj)) + return None + except Exception: + import sys + return sys.exc_info()[1] + _dict = {} + for attr in dir(obj): + try: + _attr = getattr(obj,attr) + except Exception: + import sys + _dict[attr] = sys.exc_info()[1] + continue + if not pickles(_attr,exact,safe): + _dict[attr] = errors(_attr,depth-1,exact,safe) + return _dict + + +# EOF diff --git a/dill/logger.py b/dill/logger.py new file mode 100644 index 0000000000000000000000000000000000000000..435f82b0ea2b420d00f2bc1736531b955088c6ba --- /dev/null +++ b/dill/logger.py @@ -0,0 +1,285 @@ +#!/usr/bin/env python +# -*- coding: utf-8 -*- +# +# Author: Leonardo Gama (@leogama) +# Copyright (c) 2022-2025 The Uncertainty Quantification Foundation. +# License: 3-clause BSD. The full license text is available at: +# - https://github.com/uqfoundation/dill/blob/master/LICENSE +""" +Logging utilities for dill. + +The 'logger' object is dill's top-level logger. + +The 'adapter' object wraps the logger and implements a 'trace()' method that +generates a detailed tree-style trace for the pickling call at log level INFO. + +The 'trace()' function sets and resets dill's logger log level, enabling and +disabling the pickling trace. + +The trace shows a tree structure depicting the depth of each object serialized +*with dill save functions*, but not the ones that use save functions from +'pickle._Pickler.dispatch'. If the information is available, it also displays +the size in bytes that the object contributed to the pickle stream (including +its child objects). Sample trace output: + + >>> import dill, dill.tests + >>> dill.detect.trace(True) + >>> dill.dump_session(main=dill.tests) + ┬ M1: + ├┬ F2: + │└ # F2 [32 B] + ├┬ D2: + │├┬ T4: + ││└ # T4 [35 B] + │├┬ D2: + ││├┬ T4: + │││└ # T4 [50 B] + ││├┬ D2: + │││└ # D2 [84 B] + ││└ # D2 [413 B] + │└ # D2 [763 B] + └ # M1 [813 B] +""" + +__all__ = ['adapter', 'logger', 'trace'] + +import codecs +import contextlib +import locale +import logging +import math +import os +from functools import partial +from typing import TextIO, Union + +import dill + +# Tree drawing characters: Unicode to ASCII map. +ASCII_MAP = str.maketrans({"│": "|", "├": "|", "┬": "+", "└": "`"}) + +## Notes about the design choices ## + +# Here is some domumentation of the Standard Library's logging internals that +# can't be found completely in the official documentation. dill's logger is +# obtained by calling logging.getLogger('dill') and therefore is an instance of +# logging.getLoggerClass() at the call time. As this is controlled by the user, +# in order to add some functionality to it it's necessary to use a LoggerAdapter +# to wrap it, overriding some of the adapter's methods and creating new ones. +# +# Basic calling sequence +# ====================== +# +# Python's logging functionality can be conceptually divided into five steps: +# 0. Check logging level -> abort if call level is greater than logger level +# 1. Gather information -> construct a LogRecord from passed arguments and context +# 2. Filter (optional) -> discard message if the record matches a filter +# 3. Format -> format message with args, then format output string with message plus record +# 4. Handle -> write the formatted string to output as defined in the handler +# +# dill.logging.logger.log -> # or logger.info, etc. +# Logger.log -> \ +# Logger._log -> }- accept 'extra' parameter for custom record entries +# Logger.makeRecord -> / +# LogRecord.__init__ +# Logger.handle -> +# Logger.callHandlers -> +# Handler.handle -> +# Filterer.filter -> +# Filter.filter +# StreamHandler.emit -> +# Handler.format -> +# Formatter.format -> +# LogRecord.getMessage # does: record.message = msg % args +# Formatter.formatMessage -> +# PercentStyle.format # does: self._fmt % vars(record) +# +# NOTE: All methods from the second line on are from logging.__init__.py + +class TraceAdapter(logging.LoggerAdapter): + """ + Tracks object tree depth and calculates pickled object size. + + A single instance of this wraps the module's logger, as the logging API + doesn't allow setting it directly with a custom Logger subclass. The added + 'trace()' method receives a pickle instance as the first argument and + creates extra values to be added in the LogRecord from it, then calls + 'info()'. + + Usage of logger with 'trace()' method: + + >>> from dill.logger import adapter as logger #NOTE: not dill.logger.logger + >>> ... + >>> def save_atype(pickler, obj): + >>> logger.trace(pickler, "Message with %s and %r etc. placeholders", 'text', obj) + >>> ... + """ + def __init__(self, logger): + self.logger = logger + def addHandler(self, handler): + formatter = TraceFormatter("%(prefix)s%(message)s%(suffix)s", handler=handler) + handler.setFormatter(formatter) + self.logger.addHandler(handler) + def removeHandler(self, handler): + self.logger.removeHandler(handler) + def process(self, msg, kwargs): + # A no-op override, as we don't have self.extra. + return msg, kwargs + def trace_setup(self, pickler): + # Called by Pickler.dump(). + if not dill._dill.is_dill(pickler, child=False): + return + if self.isEnabledFor(logging.INFO): + pickler._trace_depth = 1 + pickler._size_stack = [] + else: + pickler._trace_depth = None + def trace(self, pickler, msg, *args, **kwargs): + if not hasattr(pickler, '_trace_depth'): + logger.info(msg, *args, **kwargs) + return + if pickler._trace_depth is None: + return + extra = kwargs.get('extra', {}) + pushed_obj = msg.startswith('#') + size = None + try: + # Streams are not required to be tellable. + size = pickler._file.tell() + frame = pickler.framer.current_frame + try: + size += frame.tell() + except AttributeError: + # PyPy may use a BytesBuilder as frame + size += len(frame) + except (AttributeError, TypeError): + pass + if size is not None: + if not pushed_obj: + pickler._size_stack.append(size) + else: + size -= pickler._size_stack.pop() + extra['size'] = size + if pushed_obj: + pickler._trace_depth -= 1 + extra['depth'] = pickler._trace_depth + kwargs['extra'] = extra + self.info(msg, *args, **kwargs) + if not pushed_obj: + pickler._trace_depth += 1 + +class TraceFormatter(logging.Formatter): + """ + Generates message prefix and suffix from record. + + This Formatter adds prefix and suffix strings to the log message in trace + mode (an also provides empty string defaults for normal logs). + """ + def __init__(self, *args, handler=None, **kwargs): + super().__init__(*args, **kwargs) + try: + encoding = handler.stream.encoding + if encoding is None: + raise AttributeError + except AttributeError: + encoding = locale.getpreferredencoding() + try: + encoding = codecs.lookup(encoding).name + except LookupError: + self.is_utf8 = False + else: + self.is_utf8 = (encoding == codecs.lookup('utf-8').name) + def format(self, record): + fields = {'prefix': "", 'suffix': ""} + if getattr(record, 'depth', 0) > 0: + if record.msg.startswith("#"): + prefix = (record.depth - 1)*"│" + "└" + elif record.depth == 1: + prefix = "┬" + else: + prefix = (record.depth - 2)*"│" + "├┬" + if not self.is_utf8: + prefix = prefix.translate(ASCII_MAP) + "-" + fields['prefix'] = prefix + " " + if hasattr(record, 'size') and record.size is not None and record.size >= 1: + # Show object size in human-readable form. + power = int(math.log(record.size, 2)) // 10 + size = record.size >> power*10 + fields['suffix'] = " [%d %sB]" % (size, "KMGTP"[power] + "i" if power else "") + vars(record).update(fields) + return super().format(record) + +logger = logging.getLogger('dill') +logger.propagate = False +adapter = TraceAdapter(logger) +stderr_handler = logging._StderrHandler() +adapter.addHandler(stderr_handler) + +def trace(arg: Union[bool, TextIO, str, os.PathLike] = None, *, mode: str = 'a') -> None: + """print a trace through the stack when pickling; useful for debugging + + With a single boolean argument, enable or disable the tracing. + + Example usage: + + >>> import dill + >>> dill.detect.trace(True) + >>> dill.dump_session() + + Alternatively, ``trace()`` can be used as a context manager. With no + arguments, it just takes care of restoring the tracing state on exit. + Either a file handle, or a file name and (optionally) a file mode may be + specitfied to redirect the tracing output in the ``with`` block context. A + log function is yielded by the manager so the user can write extra + information to the file. + + Example usage: + + >>> from dill import detect + >>> D = {'a': 42, 'b': {'x': None}} + >>> with detect.trace(): + >>> dumps(D) + ┬ D2: + ├┬ D2: + │└ # D2 [8 B] + └ # D2 [22 B] + >>> squared = lambda x: x**2 + >>> with detect.trace('output.txt', mode='w') as log: + >>> log("> D = %r", D) + >>> dumps(D) + >>> log("> squared = %r", squared) + >>> dumps(squared) + + Arguments: + arg: a boolean value, or an optional file-like or path-like object for the context manager + mode: mode string for ``open()`` if a file name is passed as the first argument + """ + if repr(arg) not in ('False', 'True'): + return TraceManager(file=arg, mode=mode) + logger.setLevel(logging.INFO if arg else logging.WARNING) + +class TraceManager(contextlib.AbstractContextManager): + """context manager version of trace(); can redirect the trace to a file""" + def __init__(self, file, mode): + self.file = file + self.mode = mode + self.redirect = file is not None + self.file_is_stream = hasattr(file, 'write') + def __enter__(self): + if self.redirect: + stderr_handler.flush() + if self.file_is_stream: + self.handler = logging.StreamHandler(self.file) + else: + self.handler = logging.FileHandler(self.file, self.mode) + adapter.removeHandler(stderr_handler) + adapter.addHandler(self.handler) + self.old_level = adapter.getEffectiveLevel() + adapter.setLevel(logging.INFO) + return adapter.info + def __exit__(self, *exc_info): + adapter.setLevel(self.old_level) + if self.redirect: + adapter.removeHandler(self.handler) + adapter.addHandler(stderr_handler) + if not self.file_is_stream: + self.handler.close() diff --git a/dill/objtypes.py b/dill/objtypes.py new file mode 100644 index 0000000000000000000000000000000000000000..0453fe3cac1c7fdf6a642ebe8de74e9e14ecfae8 --- /dev/null +++ b/dill/objtypes.py @@ -0,0 +1,24 @@ +#!/usr/bin/env python +# +# Author: Mike McKerns (mmckerns @caltech and @uqfoundation) +# Copyright (c) 2008-2016 California Institute of Technology. +# Copyright (c) 2016-2025 The Uncertainty Quantification Foundation. +# License: 3-clause BSD. The full license text is available at: +# - https://github.com/uqfoundation/dill/blob/master/LICENSE +""" +all Python Standard Library object types (currently: CH 1-15 @ 2.7) +and some other common object types (i.e. numpy.ndarray) + +to load more objects and types, use dill.load_types() +""" + +# non-local import of dill.objects +from dill import objects +for _type in objects.keys(): + exec("%s = type(objects['%s'])" % (_type,_type)) + +del objects +try: + del _type +except NameError: + pass diff --git a/dill/pointers.py b/dill/pointers.py new file mode 100644 index 0000000000000000000000000000000000000000..d3e2e31faa81b6226f991ff0b15930ce3e0f8934 --- /dev/null +++ b/dill/pointers.py @@ -0,0 +1,122 @@ +#!/usr/bin/env python +# +# Author: Mike McKerns (mmckerns @caltech and @uqfoundation) +# Copyright (c) 2008-2016 California Institute of Technology. +# Copyright (c) 2016-2025 The Uncertainty Quantification Foundation. +# License: 3-clause BSD. The full license text is available at: +# - https://github.com/uqfoundation/dill/blob/master/LICENSE + +__all__ = ['parent', 'reference', 'at', 'parents', 'children'] + +import gc +import sys + +from ._dill import _proxy_helper as reference +from ._dill import _locate_object as at + +def parent(obj, objtype, ignore=()): + """ +>>> listiter = iter([4,5,6,7]) +>>> obj = parent(listiter, list) +>>> obj == [4,5,6,7] # actually 'is', but don't have handle any longer +True + +NOTE: objtype can be a single type (e.g. int or list) or a tuple of types. + +WARNING: if obj is a sequence (e.g. list), may produce unexpected results. +Parent finds *one* parent (e.g. the last member of the sequence). + """ + depth = 1 #XXX: always looking for the parent (only, right?) + chain = parents(obj, objtype, depth, ignore) + parent = chain.pop() + if parent is obj: + return None + return parent + + +def parents(obj, objtype, depth=1, ignore=()): #XXX: objtype=object ? + """Find the chain of referents for obj. Chain will end with obj. + + objtype: an object type or tuple of types to search for + depth: search depth (e.g. depth=2 is 'grandparents') + ignore: an object or tuple of objects to ignore in the search + """ + edge_func = gc.get_referents # looking for refs, not back_refs + predicate = lambda x: isinstance(x, objtype) # looking for parent type + #if objtype is None: predicate = lambda x: True #XXX: in obj.mro() ? + ignore = (ignore,) if not hasattr(ignore, '__len__') else ignore + ignore = (id(obj) for obj in ignore) + chain = find_chain(obj, predicate, edge_func, depth)[::-1] + #XXX: should pop off obj... ? + return chain + + +def children(obj, objtype, depth=1, ignore=()): #XXX: objtype=object ? + """Find the chain of referrers for obj. Chain will start with obj. + + objtype: an object type or tuple of types to search for + depth: search depth (e.g. depth=2 is 'grandchildren') + ignore: an object or tuple of objects to ignore in the search + + NOTE: a common thing to ignore is all globals, 'ignore=(globals(),)' + + NOTE: repeated calls may yield different results, as python stores + the last value in the special variable '_'; thus, it is often good + to execute something to replace '_' (e.g. >>> 1+1). + """ + edge_func = gc.get_referrers # looking for back_refs, not refs + predicate = lambda x: isinstance(x, objtype) # looking for child type + #if objtype is None: predicate = lambda x: True #XXX: in obj.mro() ? + ignore = (ignore,) if not hasattr(ignore, '__len__') else ignore + ignore = (id(obj) for obj in ignore) + chain = find_chain(obj, predicate, edge_func, depth, ignore) + #XXX: should pop off obj... ? + return chain + + +# more generic helper function (cut-n-paste from objgraph) +# Source at http://mg.pov.lt/objgraph/ +# Copyright (c) 2008-2010 Marius Gedminas +# Copyright (c) 2010 Stefano Rivera +# Released under the MIT licence (see objgraph/objgrah.py) + +def find_chain(obj, predicate, edge_func, max_depth=20, extra_ignore=()): + queue = [obj] + depth = {id(obj): 0} + parent = {id(obj): None} + ignore = set(extra_ignore) + ignore.add(id(extra_ignore)) + ignore.add(id(queue)) + ignore.add(id(depth)) + ignore.add(id(parent)) + ignore.add(id(ignore)) + ignore.add(id(sys._getframe())) # this function + ignore.add(id(sys._getframe(1))) # find_chain/find_backref_chain, likely + gc.collect() + while queue: + target = queue.pop(0) + if predicate(target): + chain = [target] + while parent[id(target)] is not None: + target = parent[id(target)] + chain.append(target) + return chain + tdepth = depth[id(target)] + if tdepth < max_depth: + referrers = edge_func(target) + ignore.add(id(referrers)) + for source in referrers: + if id(source) in ignore: + continue + if id(source) not in depth: + depth[id(source)] = tdepth + 1 + parent[id(source)] = target + queue.append(source) + return [obj] # not found + + +# backward compatibility +refobject = at + + +# EOF diff --git a/dill/session.py b/dill/session.py new file mode 100644 index 0000000000000000000000000000000000000000..8278ccdd1784fb68172cf81308673c22ab60e55e --- /dev/null +++ b/dill/session.py @@ -0,0 +1,612 @@ +#!/usr/bin/env python +# +# Author: Mike McKerns (mmckerns @caltech and @uqfoundation) +# Author: Leonardo Gama (@leogama) +# Copyright (c) 2008-2015 California Institute of Technology. +# Copyright (c) 2016-2025 The Uncertainty Quantification Foundation. +# License: 3-clause BSD. The full license text is available at: +# - https://github.com/uqfoundation/dill/blob/master/LICENSE +""" +Pickle and restore the intepreter session. +""" + +__all__ = [ + 'dump_module', 'load_module', 'load_module_asdict', + 'dump_session', 'load_session' # backward compatibility +] + +import re +import os +import sys +import warnings +import pathlib +import tempfile + +TEMPDIR = pathlib.PurePath(tempfile.gettempdir()) + +# Type hints. +from typing import Optional, Union + +from dill import _dill, Pickler, Unpickler +from ._dill import ( + BuiltinMethodType, FunctionType, MethodType, ModuleType, TypeType, + _import_module, _is_builtin_module, _is_imported_module, _main_module, + _reverse_typemap, __builtin__, UnpicklingError, +) + +def _module_map(): + """get map of imported modules""" + from collections import defaultdict + from types import SimpleNamespace + modmap = SimpleNamespace( + by_name=defaultdict(list), + by_id=defaultdict(list), + top_level={}, + ) + for modname, module in sys.modules.items(): + if modname in ('__main__', '__mp_main__') or not isinstance(module, ModuleType): + continue + if '.' not in modname: + modmap.top_level[id(module)] = modname + for objname, modobj in module.__dict__.items(): + modmap.by_name[objname].append((modobj, modname)) + modmap.by_id[id(modobj)].append((modobj, objname, modname)) + return modmap + +IMPORTED_AS_TYPES = (ModuleType, TypeType, FunctionType, MethodType, BuiltinMethodType) +if 'PyCapsuleType' in _reverse_typemap: + IMPORTED_AS_TYPES += (_reverse_typemap['PyCapsuleType'],) +IMPORTED_AS_MODULES = ('ctypes', 'typing', 'subprocess', 'threading', + r'concurrent\.futures(\.\w+)?', r'multiprocessing(\.\w+)?') +IMPORTED_AS_MODULES = tuple(re.compile(x) for x in IMPORTED_AS_MODULES) + +def _lookup_module(modmap, name, obj, main_module): + """lookup name or id of obj if module is imported""" + for modobj, modname in modmap.by_name[name]: + if modobj is obj and sys.modules[modname] is not main_module: + return modname, name + __module__ = getattr(obj, '__module__', None) + if isinstance(obj, IMPORTED_AS_TYPES) or (__module__ is not None + and any(regex.fullmatch(__module__) for regex in IMPORTED_AS_MODULES)): + for modobj, objname, modname in modmap.by_id[id(obj)]: + if sys.modules[modname] is not main_module: + return modname, objname + return None, None + +def _stash_modules(main_module): + modmap = _module_map() + newmod = ModuleType(main_module.__name__) + + imported = [] + imported_as = [] + imported_top_level = [] # keep separated for backward compatibility + original = {} + for name, obj in main_module.__dict__.items(): + if obj is main_module: + original[name] = newmod # self-reference + elif obj is main_module.__dict__: + original[name] = newmod.__dict__ + # Avoid incorrectly matching a singleton value in another package (ex.: __doc__). + elif any(obj is singleton for singleton in (None, False, True)) \ + or isinstance(obj, ModuleType) and _is_builtin_module(obj): # always saved by ref + original[name] = obj + else: + source_module, objname = _lookup_module(modmap, name, obj, main_module) + if source_module is not None: + if objname == name: + imported.append((source_module, name)) + else: + imported_as.append((source_module, objname, name)) + else: + try: + imported_top_level.append((modmap.top_level[id(obj)], name)) + except KeyError: + original[name] = obj + + if len(original) < len(main_module.__dict__): + newmod.__dict__.update(original) + newmod.__dill_imported = imported + newmod.__dill_imported_as = imported_as + newmod.__dill_imported_top_level = imported_top_level + if getattr(newmod, '__loader__', None) is None and _is_imported_module(main_module): + # Trick _is_imported_module() to force saving as an imported module. + newmod.__loader__ = True # will be discarded by save_module() + return newmod + else: + return main_module + +def _restore_modules(unpickler, main_module): + try: + for modname, name in main_module.__dict__.pop('__dill_imported'): + main_module.__dict__[name] = unpickler.find_class(modname, name) + for modname, objname, name in main_module.__dict__.pop('__dill_imported_as'): + main_module.__dict__[name] = unpickler.find_class(modname, objname) + for modname, name in main_module.__dict__.pop('__dill_imported_top_level'): + main_module.__dict__[name] = __import__(modname) + except KeyError: + pass + +#NOTE: 06/03/15 renamed main_module to main +def dump_module( + filename: Union[str, os.PathLike] = None, + module: Optional[Union[ModuleType, str]] = None, + refimported: bool = False, + **kwds +) -> None: + """Pickle the current state of :py:mod:`__main__` or another module to a file. + + Save the contents of :py:mod:`__main__` (e.g. from an interactive + interpreter session), an imported module, or a module-type object (e.g. + built with :py:class:`~types.ModuleType`), to a file. The pickled + module can then be restored with the function :py:func:`load_module`. + + Args: + filename: a path-like object or a writable stream. If `None` + (the default), write to a named file in a temporary directory. + module: a module object or the name of an importable module. If `None` + (the default), :py:mod:`__main__` is saved. + refimported: if `True`, all objects identified as having been imported + into the module's namespace are saved by reference. *Note:* this is + similar but independent from ``dill.settings[`byref`]``, as + ``refimported`` refers to virtually all imported objects, while + ``byref`` only affects select objects. + **kwds: extra keyword arguments passed to :py:class:`Pickler()`. + + Raises: + :py:exc:`PicklingError`: if pickling fails. + + Examples: + + - Save current interpreter session state: + + >>> import dill + >>> squared = lambda x: x*x + >>> dill.dump_module() # save state of __main__ to /tmp/session.pkl + + - Save the state of an imported/importable module: + + >>> import dill + >>> import pox + >>> pox.plus_one = lambda x: x+1 + >>> dill.dump_module('pox_session.pkl', module=pox) + + - Save the state of a non-importable, module-type object: + + >>> import dill + >>> from types import ModuleType + >>> foo = ModuleType('foo') + >>> foo.values = [1,2,3] + >>> import math + >>> foo.sin = math.sin + >>> dill.dump_module('foo_session.pkl', module=foo, refimported=True) + + - Restore the state of the saved modules: + + >>> import dill + >>> dill.load_module() + >>> squared(2) + 4 + >>> pox = dill.load_module('pox_session.pkl') + >>> pox.plus_one(1) + 2 + >>> foo = dill.load_module('foo_session.pkl') + >>> [foo.sin(x) for x in foo.values] + [0.8414709848078965, 0.9092974268256817, 0.1411200080598672] + + - Use `refimported` to save imported objects by reference: + + >>> import dill + >>> from html.entities import html5 + >>> type(html5), len(html5) + (dict, 2231) + >>> import io + >>> buf = io.BytesIO() + >>> dill.dump_module(buf) # saves __main__, with html5 saved by value + >>> len(buf.getvalue()) # pickle size in bytes + 71665 + >>> buf = io.BytesIO() + >>> dill.dump_module(buf, refimported=True) # html5 saved by reference + >>> len(buf.getvalue()) + 438 + + *Changed in version 0.3.6:* Function ``dump_session()`` was renamed to + ``dump_module()``. Parameters ``main`` and ``byref`` were renamed to + ``module`` and ``refimported``, respectively. + + Note: + Currently, ``dill.settings['byref']`` and ``dill.settings['recurse']`` + don't apply to this function. + """ + for old_par, par in [('main', 'module'), ('byref', 'refimported')]: + if old_par in kwds: + message = "The argument %r has been renamed %r" % (old_par, par) + if old_par == 'byref': + message += " to distinguish it from dill.settings['byref']" + warnings.warn(message + ".", PendingDeprecationWarning) + if locals()[par]: # the defaults are None and False + raise TypeError("both %r and %r arguments were used" % (par, old_par)) + refimported = kwds.pop('byref', refimported) + module = kwds.pop('main', module) + + from .settings import settings + protocol = settings['protocol'] + main = module + if main is None: + main = _main_module + elif isinstance(main, str): + main = _import_module(main) + if not isinstance(main, ModuleType): + raise TypeError("%r is not a module" % main) + if hasattr(filename, 'write'): + file = filename + else: + if filename is None: + filename = str(TEMPDIR/'session.pkl') + file = open(filename, 'wb') + try: + pickler = Pickler(file, protocol, **kwds) + pickler._original_main = main + if refimported: + main = _stash_modules(main) + pickler._main = main #FIXME: dill.settings are disabled + pickler._byref = False # disable pickling by name reference + pickler._recurse = False # disable pickling recursion for globals + pickler._session = True # is best indicator of when pickling a session + pickler._first_pass = True + pickler._main_modified = main is not pickler._original_main + pickler.dump(main) + finally: + if file is not filename: # if newly opened file + file.close() + return + +# Backward compatibility. +def dump_session(filename=None, main=None, byref=False, **kwds): + warnings.warn("dump_session() has been renamed dump_module()", PendingDeprecationWarning) + dump_module(filename, module=main, refimported=byref, **kwds) +dump_session.__doc__ = dump_module.__doc__ + +class _PeekableReader: + """lightweight stream wrapper that implements peek()""" + def __init__(self, stream): + self.stream = stream + def read(self, n): + return self.stream.read(n) + def readline(self): + return self.stream.readline() + def tell(self): + return self.stream.tell() + def close(self): + return self.stream.close() + def peek(self, n): + stream = self.stream + try: + if hasattr(stream, 'flush'): stream.flush() + position = stream.tell() + stream.seek(position) # assert seek() works before reading + chunk = stream.read(n) + stream.seek(position) + return chunk + except (AttributeError, OSError): + raise NotImplementedError("stream is not peekable: %r", stream) from None + +def _make_peekable(stream): + """return stream as an object with a peek() method""" + import io + if hasattr(stream, 'peek'): + return stream + if not (hasattr(stream, 'tell') and hasattr(stream, 'seek')): + try: + return io.BufferedReader(stream) + except Exception: + pass + return _PeekableReader(stream) + +def _identify_module(file, main=None): + """identify the name of the module stored in the given file-type object""" + from pickletools import genops + UNICODE = {'UNICODE', 'BINUNICODE', 'SHORT_BINUNICODE'} + found_import = False + try: + for opcode, arg, pos in genops(file.peek(256)): + if not found_import: + if opcode.name in ('GLOBAL', 'SHORT_BINUNICODE') and \ + arg.endswith('_import_module'): + found_import = True + else: + if opcode.name in UNICODE: + return arg + else: + raise UnpicklingError("reached STOP without finding main module") + except (NotImplementedError, ValueError) as error: + # ValueError occours when the end of the chunk is reached (without a STOP). + if isinstance(error, NotImplementedError) and main is not None: + # file is not peekable, but we have main. + return None + raise UnpicklingError("unable to identify main module") from error + +def load_module( + filename: Union[str, os.PathLike] = None, + module: Optional[Union[ModuleType, str]] = None, + **kwds +) -> Optional[ModuleType]: + """Update the selected module (default is :py:mod:`__main__`) with + the state saved at ``filename``. + + Restore a module to the state saved with :py:func:`dump_module`. The + saved module can be :py:mod:`__main__` (e.g. an interpreter session), + an imported module, or a module-type object (e.g. created with + :py:class:`~types.ModuleType`). + + When restoring the state of a non-importable module-type object, the + current instance of this module may be passed as the argument ``main``. + Otherwise, a new instance is created with :py:class:`~types.ModuleType` + and returned. + + Args: + filename: a path-like object or a readable stream. If `None` + (the default), read from a named file in a temporary directory. + module: a module object or the name of an importable module; + the module name and kind (i.e. imported or non-imported) must + match the name and kind of the module stored at ``filename``. + **kwds: extra keyword arguments passed to :py:class:`Unpickler()`. + + Raises: + :py:exc:`UnpicklingError`: if unpickling fails. + :py:exc:`ValueError`: if the argument ``main`` and module saved + at ``filename`` are incompatible. + + Returns: + A module object, if the saved module is not :py:mod:`__main__` or + a module instance wasn't provided with the argument ``main``. + + Examples: + + - Save the state of some modules: + + >>> import dill + >>> squared = lambda x: x*x + >>> dill.dump_module() # save state of __main__ to /tmp/session.pkl + >>> + >>> import pox # an imported module + >>> pox.plus_one = lambda x: x+1 + >>> dill.dump_module('pox_session.pkl', module=pox) + >>> + >>> from types import ModuleType + >>> foo = ModuleType('foo') # a module-type object + >>> foo.values = [1,2,3] + >>> import math + >>> foo.sin = math.sin + >>> dill.dump_module('foo_session.pkl', module=foo, refimported=True) + + - Restore the state of the interpreter: + + >>> import dill + >>> dill.load_module() # updates __main__ from /tmp/session.pkl + >>> squared(2) + 4 + + - Load the saved state of an importable module: + + >>> import dill + >>> pox = dill.load_module('pox_session.pkl') + >>> pox.plus_one(1) + 2 + >>> import sys + >>> pox in sys.modules.values() + True + + - Load the saved state of a non-importable module-type object: + + >>> import dill + >>> foo = dill.load_module('foo_session.pkl') + >>> [foo.sin(x) for x in foo.values] + [0.8414709848078965, 0.9092974268256817, 0.1411200080598672] + >>> import math + >>> foo.sin is math.sin # foo.sin was saved by reference + True + >>> import sys + >>> foo in sys.modules.values() + False + + - Update the state of a non-importable module-type object: + + >>> import dill + >>> from types import ModuleType + >>> foo = ModuleType('foo') + >>> foo.values = ['a','b'] + >>> foo.sin = lambda x: x*x + >>> dill.load_module('foo_session.pkl', module=foo) + >>> [foo.sin(x) for x in foo.values] + [0.8414709848078965, 0.9092974268256817, 0.1411200080598672] + + *Changed in version 0.3.6:* Function ``load_session()`` was renamed to + ``load_module()``. Parameter ``main`` was renamed to ``module``. + + See also: + :py:func:`load_module_asdict` to load the contents of module saved + with :py:func:`dump_module` into a dictionary. + """ + if 'main' in kwds: + warnings.warn( + "The argument 'main' has been renamed 'module'.", + PendingDeprecationWarning + ) + if module is not None: + raise TypeError("both 'module' and 'main' arguments were used") + module = kwds.pop('main') + main = module + if hasattr(filename, 'read'): + file = filename + else: + if filename is None: + filename = str(TEMPDIR/'session.pkl') + file = open(filename, 'rb') + try: + file = _make_peekable(file) + #FIXME: dill.settings are disabled + unpickler = Unpickler(file, **kwds) + unpickler._session = True + + # Resolve unpickler._main + pickle_main = _identify_module(file, main) + if main is None and pickle_main is not None: + main = pickle_main + if isinstance(main, str): + if main.startswith('__runtime__.'): + # Create runtime module to load the session into. + main = ModuleType(main.partition('.')[-1]) + else: + main = _import_module(main) + if main is not None: + if not isinstance(main, ModuleType): + raise TypeError("%r is not a module" % main) + unpickler._main = main + else: + main = unpickler._main + + # Check against the pickle's main. + is_main_imported = _is_imported_module(main) + if pickle_main is not None: + is_runtime_mod = pickle_main.startswith('__runtime__.') + if is_runtime_mod: + pickle_main = pickle_main.partition('.')[-1] + error_msg = "can't update{} module{} %r with the saved state of{} module{} %r" + if is_runtime_mod and is_main_imported: + raise ValueError( + error_msg.format(" imported", "", "", "-type object") + % (main.__name__, pickle_main) + ) + if not is_runtime_mod and not is_main_imported: + raise ValueError( + error_msg.format("", "-type object", " imported", "") + % (pickle_main, main.__name__) + ) + if main.__name__ != pickle_main: + raise ValueError(error_msg.format("", "", "", "") % (main.__name__, pickle_main)) + + # This is for find_class() to be able to locate it. + if not is_main_imported: + runtime_main = '__runtime__.%s' % main.__name__ + sys.modules[runtime_main] = main + + loaded = unpickler.load() + finally: + if not hasattr(filename, 'read'): # if newly opened file + file.close() + try: + del sys.modules[runtime_main] + except (KeyError, NameError): + pass + assert loaded is main + _restore_modules(unpickler, main) + if main is _main_module or main is module: + return None + else: + return main + +# Backward compatibility. +def load_session(filename=None, main=None, **kwds): + warnings.warn("load_session() has been renamed load_module().", PendingDeprecationWarning) + load_module(filename, module=main, **kwds) +load_session.__doc__ = load_module.__doc__ + +def load_module_asdict( + filename: Union[str, os.PathLike] = None, + update: bool = False, + **kwds +) -> dict: + """ + Load the contents of a saved module into a dictionary. + + ``load_module_asdict()`` is the near-equivalent of:: + + lambda filename: vars(dill.load_module(filename)).copy() + + however, does not alter the original module. Also, the path of + the loaded module is stored in the ``__session__`` attribute. + + Args: + filename: a path-like object or a readable stream. If `None` + (the default), read from a named file in a temporary directory. + update: if `True`, initialize the dictionary with the current state + of the module prior to loading the state stored at filename. + **kwds: extra keyword arguments passed to :py:class:`Unpickler()` + + Raises: + :py:exc:`UnpicklingError`: if unpickling fails + + Returns: + A copy of the restored module's dictionary. + + Note: + If ``update`` is True, the corresponding module may first be imported + into the current namespace before the saved state is loaded from + filename to the dictionary. Note that any module that is imported into + the current namespace as a side-effect of using ``update`` will not be + modified by loading the saved module in filename to a dictionary. + + Example: + >>> import dill + >>> alist = [1, 2, 3] + >>> anum = 42 + >>> dill.dump_module() + >>> anum = 0 + >>> new_var = 'spam' + >>> main = dill.load_module_asdict() + >>> main['__name__'], main['__session__'] + ('__main__', '/tmp/session.pkl') + >>> main is globals() # loaded objects don't reference globals + False + >>> main['alist'] == alist + True + >>> main['alist'] is alist # was saved by value + False + >>> main['anum'] == anum # changed after the session was saved + False + >>> new_var in main # would be True if the option 'update' was set + False + """ + if 'module' in kwds: + raise TypeError("'module' is an invalid keyword argument for load_module_asdict()") + if hasattr(filename, 'read'): + file = filename + else: + if filename is None: + filename = str(TEMPDIR/'session.pkl') + file = open(filename, 'rb') + try: + file = _make_peekable(file) + main_name = _identify_module(file) + old_main = sys.modules.get(main_name) + main = ModuleType(main_name) + if update: + if old_main is None: + old_main = _import_module(main_name) + main.__dict__.update(old_main.__dict__) + else: + main.__builtins__ = __builtin__ + sys.modules[main_name] = main + load_module(file, **kwds) + finally: + if not hasattr(filename, 'read'): # if newly opened file + file.close() + try: + if old_main is None: + del sys.modules[main_name] + else: + sys.modules[main_name] = old_main + except NameError: # failed before setting old_main + pass + main.__session__ = str(filename) + return main.__dict__ + + +# Internal exports for backward compatibility with dill v0.3.5.1 +# Can't be placed in dill._dill because of circular import problems. +for name in ( + '_lookup_module', '_module_map', '_restore_modules', '_stash_modules', + 'dump_session', 'load_session' # backward compatibility functions +): + setattr(_dill, name, globals()[name]) +del name diff --git a/dill/settings.py b/dill/settings.py new file mode 100644 index 0000000000000000000000000000000000000000..bba1ab984bdd4377e0f05fcc274d4bd4562302c1 --- /dev/null +++ b/dill/settings.py @@ -0,0 +1,25 @@ +#!/usr/bin/env python +# +# Author: Mike McKerns (mmckerns @caltech and @uqfoundation) +# Copyright (c) 2008-2016 California Institute of Technology. +# Copyright (c) 2016-2025 The Uncertainty Quantification Foundation. +# License: 3-clause BSD. The full license text is available at: +# - https://github.com/uqfoundation/dill/blob/master/LICENSE +""" +global settings for Pickler +""" + +from pickle import DEFAULT_PROTOCOL + +settings = { + #'main' : None, + 'protocol' : DEFAULT_PROTOCOL, + 'byref' : False, + #'strictio' : False, + 'fmode' : 0, #HANDLE_FMODE + 'recurse' : False, + 'ignore' : False, +} + +del DEFAULT_PROTOCOL + diff --git a/dill/source.py b/dill/source.py new file mode 100644 index 0000000000000000000000000000000000000000..4b538fa65daebf32702ed046ec9b9a253d4cf869 --- /dev/null +++ b/dill/source.py @@ -0,0 +1,1023 @@ +#!/usr/bin/env python +# +# Author: Mike McKerns (mmckerns @caltech and @uqfoundation) +# Copyright (c) 2008-2016 California Institute of Technology. +# Copyright (c) 2016-2025 The Uncertainty Quantification Foundation. +# License: 3-clause BSD. The full license text is available at: +# - https://github.com/uqfoundation/dill/blob/master/LICENSE +# +# inspired by inspect.py from Python-2.7.6 +# inspect.py author: 'Ka-Ping Yee ' +# inspect.py merged into original dill.source by Mike McKerns 4/13/14 +""" +Extensions to python's 'inspect' module, which can be used +to retrieve information from live python objects. The methods +defined in this module are augmented to facilitate access to +source code of interactively defined functions and classes, +as well as provide access to source code for objects defined +in a file. +""" + +__all__ = ['findsource', 'getsourcelines', 'getsource', 'indent', 'outdent', \ + '_wrap', 'dumpsource', 'getname', '_namespace', 'getimport', \ + '_importable', 'importable','isdynamic', 'isfrommain'] + +import linecache +import re +from inspect import (getblock, getfile, getmodule, getsourcefile, indentsize, + isbuiltin, isclass, iscode, isframe, isfunction, ismethod, + ismodule, istraceback) +from tokenize import TokenError + +from ._dill import IS_IPYTHON + + +def isfrommain(obj): + "check if object was built in __main__" + module = getmodule(obj) + if module and module.__name__ == '__main__': + return True + return False + + +def isdynamic(obj): + "check if object was built in the interpreter" + try: file = getfile(obj) + except TypeError: file = None + if file == '' and isfrommain(obj): + return True + return False + + +def _matchlambda(func, line): + """check if lambda object 'func' matches raw line of code 'line'""" + from .detect import code as getcode + from .detect import freevars, globalvars, varnames + dummy = lambda : '__this_is_a_big_dummy_function__' + # process the line (removing leading whitespace, etc) + lhs,rhs = line.split('lambda ',1)[-1].split(":", 1) #FIXME: if !1 inputs + try: #FIXME: unsafe + _ = eval("lambda %s : %s" % (lhs,rhs), globals(),locals()) + except Exception: _ = dummy + # get code objects, for comparison + _, code = getcode(_).co_code, getcode(func).co_code + # check if func is in closure + _f = [line.count(i) for i in freevars(func).keys()] + if not _f: # not in closure + # check if code matches + if _ == code: return True + return False + # weak check on freevars + if not all(_f): return False #XXX: VERY WEAK + # weak check on varnames and globalvars + _f = varnames(func) + _f = [line.count(i) for i in _f[0]+_f[1]] + if _f and not all(_f): return False #XXX: VERY WEAK + _f = [line.count(i) for i in globalvars(func).keys()] + if _f and not all(_f): return False #XXX: VERY WEAK + # check if func is a double lambda + if (line.count('lambda ') > 1) and (lhs in freevars(func).keys()): + _lhs,_rhs = rhs.split('lambda ',1)[-1].split(":",1) #FIXME: if !1 inputs + try: #FIXME: unsafe + _f = eval("lambda %s : %s" % (_lhs,_rhs), globals(),locals()) + except Exception: _f = dummy + # get code objects, for comparison + _, code = getcode(_f).co_code, getcode(func).co_code + if len(_) != len(code): return False + #NOTE: should be same code same order, but except for 't' and '\x88' + _ = set((i,j) for (i,j) in zip(_,code) if i != j) + if len(_) != 1: return False #('t','\x88') + return True + # check indentsize + if not indentsize(line): return False #FIXME: is this a good check??? + # check if code 'pattern' matches + #XXX: or pattern match against dis.dis(code)? (or use uncompyle2?) + _ = _.split(_[0]) # 't' #XXX: remove matching values if starts the same? + _f = code.split(code[0]) # '\x88' + #NOTE: should be same code different order, with different first element + _ = dict(re.match(r'([\W\D\S])(.*)', _[i]).groups() for i in range(1,len(_))) + _f = dict(re.match(r'([\W\D\S])(.*)', _f[i]).groups() for i in range(1,len(_f))) + if (_.keys() == _f.keys()) and (sorted(_.values()) == sorted(_f.values())): + return True + return False + + +def findsource(object): + """Return the entire source file and starting line number for an object. + For interactively-defined objects, the 'file' is the interpreter's history. + + The argument may be a module, class, method, function, traceback, frame, + or code object. The source code is returned as a list of all the lines + in the file and the line number indexes a line in that list. An IOError + is raised if the source code cannot be retrieved, while a TypeError is + raised for objects where the source code is unavailable (e.g. builtins).""" + + module = getmodule(object) + try: file = getfile(module) + except TypeError: file = None + is_module_main = (module and module.__name__ == '__main__' and not file) + if IS_IPYTHON and is_module_main: + #FIXME: quick fix for functions and classes in IPython interpreter + try: + file = getfile(object) + sourcefile = getsourcefile(object) + except TypeError: + if isclass(object): + for object_method in filter(isfunction, object.__dict__.values()): + # look for a method of the class + file_candidate = getfile(object_method) + if not file_candidate.startswith('': pat1 = r'(.*(?': + pat1 = r'(.*(?' + if stdin: + lnum = len(lines) - 1 # can't get lnum easily, so leverage pat + if not pat1: pat1 = r'^(\s*def\s)|(.*(? 0: #XXX: won't find decorators in ? + line = lines[lnum] + if pat1.match(line): + if not stdin: break # co_firstlineno does the job + if name == '': # hackery needed to confirm a match + if _matchlambda(obj, line): break + else: # not a lambda, just look for the name + if name in line: # need to check for decorator... + hats = 0 + for _lnum in range(lnum-1,-1,-1): + if pat2.match(lines[_lnum]): hats += 1 + else: break + lnum = lnum - hats + break + lnum = lnum - 1 + return lines, lnum + + try: # turn instances into classes + if not isclass(object) and isclass(type(object)): # __class__ + object = object.__class__ #XXX: sometimes type(class) is better? + #XXX: we don't find how the instance was built + except AttributeError: pass + if isclass(object): + name = object.__name__ + pat = re.compile(r'^(\s*)class\s*' + name + r'\b') + # make some effort to find the best matching class definition: + # use the one with the least indentation, which is the one + # that's most probably not inside a function definition. + candidates = [] + for i in range(len(lines)-1,-1,-1): + match = pat.match(lines[i]) + if match: + # if it's at toplevel, it's already the best one + if lines[i][0] == 'c': + return lines, i + # else add whitespace to candidate list + candidates.append((match.group(1), i)) + if candidates: + # this will sort by whitespace, and by line number, + # less whitespace first #XXX: should sort high lnum before low + candidates.sort() + return lines, candidates[0][1] + else: + raise IOError('could not find class definition') + raise IOError('could not find code object') + + +def getblocks(object, lstrip=False, enclosing=False, locate=False): + """Return a list of source lines and starting line number for an object. + Interactively-defined objects refer to lines in the interpreter's history. + + If enclosing=True, then also return any enclosing code. + If lstrip=True, ensure there is no indentation in the first line of code. + If locate=True, then also return the line number for the block of code. + + DEPRECATED: use 'getsourcelines' instead + """ + lines, lnum = findsource(object) + + if ismodule(object): + if lstrip: lines = _outdent(lines) + return ([lines], [0]) if locate is True else [lines] + + #XXX: 'enclosing' means: closures only? or classes and files? + indent = indentsize(lines[lnum]) + block = getblock(lines[lnum:]) #XXX: catch any TokenError here? + + if not enclosing or not indent: + if lstrip: block = _outdent(block) + return ([block], [lnum]) if locate is True else [block] + + pat1 = r'^(\s*def\s)|(.*(? indent: #XXX: should be >= ? + line += len(code) - skip + elif target in ''.join(code): + blocks.append(code) # save code block as the potential winner + _lnum.append(line - skip) # save the line number for the match + line += len(code) - skip + else: + line += 1 + skip = 0 + # find skip: the number of consecutive decorators + elif pat2.match(lines[line]): + try: code = getblock(lines[line:]) + except TokenError: code = [lines[line]] + skip = 1 + for _line in code[1:]: # skip lines that are decorators + if not pat2.match(_line): break + skip += 1 + line += skip + # no match: reset skip and go to the next line + else: + line +=1 + skip = 0 + + if not blocks: + blocks = [block] + _lnum = [lnum] + if lstrip: blocks = [_outdent(block) for block in blocks] + # return last match + return (blocks, _lnum) if locate is True else blocks + + +def getsourcelines(object, lstrip=False, enclosing=False): + """Return a list of source lines and starting line number for an object. + Interactively-defined objects refer to lines in the interpreter's history. + + The argument may be a module, class, method, function, traceback, frame, + or code object. The source code is returned as a list of the lines + corresponding to the object and the line number indicates where in the + original source file the first line of code was found. An IOError is + raised if the source code cannot be retrieved, while a TypeError is + raised for objects where the source code is unavailable (e.g. builtins). + + If lstrip=True, ensure there is no indentation in the first line of code. + If enclosing=True, then also return any enclosing code.""" + code, n = getblocks(object, lstrip=lstrip, enclosing=enclosing, locate=True) + return code[-1], n[-1] + + +#NOTE: broke backward compatibility 4/16/14 (was lstrip=True, force=True) +def getsource(object, alias='', lstrip=False, enclosing=False, \ + force=False, builtin=False): + """Return the text of the source code for an object. The source code for + interactively-defined objects are extracted from the interpreter's history. + + The argument may be a module, class, method, function, traceback, frame, + or code object. The source code is returned as a single string. An + IOError is raised if the source code cannot be retrieved, while a + TypeError is raised for objects where the source code is unavailable + (e.g. builtins). + + If alias is provided, then add a line of code that renames the object. + If lstrip=True, ensure there is no indentation in the first line of code. + If enclosing=True, then also return any enclosing code. + If force=True, catch (TypeError,IOError) and try to use import hooks. + If builtin=True, force an import for any builtins + """ + # hascode denotes a callable + hascode = _hascode(object) + # is a class instance type (and not in builtins) + instance = _isinstance(object) + + # get source lines; if fail, try to 'force' an import + try: # fails for builtins, and other assorted object types + lines, lnum = getsourcelines(object, enclosing=enclosing) + except (TypeError, IOError): # failed to get source, resort to import hooks + if not force: # don't try to get types that findsource can't get + raise + if not getmodule(object): # get things like 'None' and '1' + if not instance: return getimport(object, alias, builtin=builtin) + # special handling (numpy arrays, ...) + _import = getimport(object, builtin=builtin) + name = getname(object, force=True) + _alias = "%s = " % alias if alias else "" + if alias == name: _alias = "" + return _import+_alias+"%s\n" % name + else: #FIXME: could use a good bit of cleanup, since using getimport... + if not instance: return getimport(object, alias, builtin=builtin) + # now we are dealing with an instance... + name = object.__class__.__name__ + module = object.__module__ + if module in ['builtins','__builtin__']: + return getimport(object, alias, builtin=builtin) + else: #FIXME: leverage getimport? use 'from module import name'? + lines, lnum = ["%s = __import__('%s', fromlist=['%s']).%s\n" % (name,module,name,name)], 0 + obj = eval(lines[0].lstrip(name + ' = ')) + lines, lnum = getsourcelines(obj, enclosing=enclosing) + + # strip leading indent (helps ensure can be imported) + if lstrip or alias: + lines = _outdent(lines) + + # instantiate, if there's a nice repr #XXX: BAD IDEA??? + if instance: #and force: #XXX: move into findsource or getsourcelines ? + if '(' in repr(object): lines.append('%r\n' % object) + #else: #XXX: better to somehow to leverage __reduce__ ? + # reconstructor,args = object.__reduce__() + # _ = reconstructor(*args) + else: # fall back to serialization #XXX: bad idea? + #XXX: better not duplicate work? #XXX: better new/enclose=True? + lines = dumpsource(object, alias='', new=force, enclose=False) + lines, lnum = [line+'\n' for line in lines.split('\n')][:-1], 0 + #else: object.__code__ # raise AttributeError + + # add an alias to the source code + if alias: + if hascode: + skip = 0 + for line in lines: # skip lines that are decorators + if not line.startswith('@'): break + skip += 1 + #XXX: use regex from findsource / getsourcelines ? + if lines[skip].lstrip().startswith('def '): # we have a function + if alias != object.__name__: + lines.append('\n%s = %s\n' % (alias, object.__name__)) + elif 'lambda ' in lines[skip]: # we have a lambda + if alias != lines[skip].split('=')[0].strip(): + lines[skip] = '%s = %s' % (alias, lines[skip]) + else: # ...try to use the object's name + if alias != object.__name__: + lines.append('\n%s = %s\n' % (alias, object.__name__)) + else: # class or class instance + if instance: + if alias != lines[-1].split('=')[0].strip(): + lines[-1] = ('%s = ' % alias) + lines[-1] + else: + name = getname(object, force=True) or object.__name__ + if alias != name: + lines.append('\n%s = %s\n' % (alias, name)) + return ''.join(lines) + + +def _hascode(object): + '''True if object has an attribute that stores it's __code__''' + return getattr(object,'__code__',None) or getattr(object,'func_code',None) + +def _isinstance(object): + '''True if object is a class instance type (and is not a builtin)''' + if _hascode(object) or isclass(object) or ismodule(object): + return False + if istraceback(object) or isframe(object) or iscode(object): + return False + # special handling (numpy arrays, ...) + if not getmodule(object) and getmodule(type(object)).__name__ in ['numpy']: + return True +# # check if is instance of a builtin +# if not getmodule(object) and getmodule(type(object)).__name__ in ['__builtin__','builtins']: +# return False + _types = ('") + if not repr(type(object)).startswith(_types): #FIXME: weak hack + return False + if not getmodule(object) or object.__module__ in ['builtins','__builtin__'] or getname(object, force=True) in ['array']: + return False + return True # by process of elimination... it's what we want + + +def _intypes(object): + '''check if object is in the 'types' module''' + import types + # allow user to pass in object or object.__name__ + if type(object) is not type(''): + object = getname(object, force=True) + if object == 'ellipsis': object = 'EllipsisType' + return True if hasattr(types, object) else False + + +def _isstring(object): #XXX: isstringlike better? + '''check if object is a string-like type''' + return isinstance(object, (str, bytes)) + + +def indent(code, spaces=4): + '''indent a block of code with whitespace (default is 4 spaces)''' + indent = indentsize(code) + from numbers import Integral + if isinstance(spaces, Integral): spaces = ' '*spaces + # if '\t' is provided, will indent with a tab + nspaces = indentsize(spaces) + # blank lines (etc) need to be ignored + lines = code.split('\n') +## stq = "'''"; dtq = '"""' +## in_stq = in_dtq = False + for i in range(len(lines)): + #FIXME: works... but shouldn't indent 2nd+ lines of multiline doc + _indent = indentsize(lines[i]) + if indent > _indent: continue + lines[i] = spaces+lines[i] +## #FIXME: may fail when stq and dtq in same line (depends on ordering) +## nstq, ndtq = lines[i].count(stq), lines[i].count(dtq) +## if not in_dtq and not in_stq: +## lines[i] = spaces+lines[i] # we indent +## # entering a comment block +## if nstq%2: in_stq = not in_stq +## if ndtq%2: in_dtq = not in_dtq +## # leaving a comment block +## elif in_dtq and ndtq%2: in_dtq = not in_dtq +## elif in_stq and nstq%2: in_stq = not in_stq +## else: pass + if lines[-1].strip() == '': lines[-1] = '' + return '\n'.join(lines) + + +def _outdent(lines, spaces=None, all=True): + '''outdent lines of code, accounting for docs and line continuations''' + indent = indentsize(lines[0]) + if spaces is None or spaces > indent or spaces < 0: spaces = indent + for i in range(len(lines) if all else 1): + #FIXME: works... but shouldn't outdent 2nd+ lines of multiline doc + _indent = indentsize(lines[i]) + if spaces > _indent: _spaces = _indent + else: _spaces = spaces + lines[i] = lines[i][_spaces:] + return lines + +def outdent(code, spaces=None, all=True): + '''outdent a block of code (default is to strip all leading whitespace)''' + indent = indentsize(code) + if spaces is None or spaces > indent or spaces < 0: spaces = indent + #XXX: will this delete '\n' in some cases? + if not all: return code[spaces:] + return '\n'.join(_outdent(code.split('\n'), spaces=spaces, all=all)) + + +# _wrap provides an wrapper to correctly exec and load into locals +__globals__ = globals() +__locals__ = locals() +def _wrap(f): + """ encapsulate a function and it's __import__ """ + def func(*args, **kwds): + try: + # _ = eval(getsource(f, force=True)) #XXX: safer but less robust + exec(getimportable(f, alias='_'), __globals__, __locals__) + except Exception: + raise ImportError('cannot import name ' + f.__name__) + return _(*args, **kwds) + func.__name__ = f.__name__ + func.__doc__ = f.__doc__ + return func + + +def _enclose(object, alias=''): #FIXME: needs alias to hold returned object + """create a function enclosure around the source of some object""" + #XXX: dummy and stub should append a random string + dummy = '__this_is_a_big_dummy_enclosing_function__' + stub = '__this_is_a_stub_variable__' + code = 'def %s():\n' % dummy + code += indent(getsource(object, alias=stub, lstrip=True, force=True)) + code += indent('return %s\n' % stub) + if alias: code += '%s = ' % alias + code += '%s(); del %s\n' % (dummy, dummy) + #code += "globals().pop('%s',lambda :None)()\n" % dummy + return code + + +def dumpsource(object, alias='', new=False, enclose=True): + """'dump to source', where the code includes a pickled object. + + If new=True and object is a class instance, then create a new + instance using the unpacked class source code. If enclose, then + create the object inside a function enclosure (thus minimizing + any global namespace pollution). + """ + from dill import dumps + pik = repr(dumps(object)) + code = 'import dill\n' + if enclose: + stub = '__this_is_a_stub_variable__' #XXX: *must* be same _enclose.stub + pre = '%s = ' % stub + new = False #FIXME: new=True doesn't work with enclose=True + else: + stub = alias + pre = '%s = ' % stub if alias else alias + + # if a 'new' instance is not needed, then just dump and load + if not new or not _isinstance(object): + code += pre + 'dill.loads(%s)\n' % pik + else: #XXX: other cases where source code is needed??? + code += getsource(object.__class__, alias='', lstrip=True, force=True) + mod = repr(object.__module__) # should have a module (no builtins here) + code += pre + 'dill.loads(%s.replace(b%s,bytes(__name__,"UTF-8")))\n' % (pik,mod) + #code += 'del %s' % object.__class__.__name__ #NOTE: kills any existing! + + if enclose: + # generation of the 'enclosure' + dummy = '__this_is_a_big_dummy_object__' + dummy = _enclose(dummy, alias=alias) + # hack to replace the 'dummy' with the 'real' code + dummy = dummy.split('\n') + code = dummy[0]+'\n' + indent(code) + '\n'.join(dummy[-3:]) + + return code #XXX: better 'dumpsourcelines', returning list of lines? + + +def getname(obj, force=False, fqn=False): #XXX: throw(?) to raise error on fail? + """get the name of the object. for lambdas, get the name of the pointer """ + if fqn: return '.'.join(_namespace(obj)) #NOTE: returns 'type' + module = getmodule(obj) + if not module: # things like "None" and "1" + if not force: return None #NOTE: returns 'instance' NOT 'type' #FIXME? + # handle some special cases + if hasattr(obj, 'dtype') and not obj.shape: + return getname(obj.__class__) + "(" + repr(obj.tolist()) + ")" + return repr(obj) + try: + #XXX: 'wrong' for decorators and curried functions ? + # if obj.func_closure: ...use logic from getimportable, etc ? + name = obj.__name__ + if name == '': + return getsource(obj).split('=',1)[0].strip() + # handle some special cases + if module.__name__ in ['builtins','__builtin__']: + if name == 'ellipsis': name = 'EllipsisType' + return name + except AttributeError: #XXX: better to just throw AttributeError ? + if not force: return None + name = repr(obj) + if name.startswith('<'): # or name.split('('): + return None + return name + + +def _namespace(obj): + """_namespace(obj); return namespace hierarchy (as a list of names) + for the given object. For an instance, find the class hierarchy. + + For example: + + >>> from functools import partial + >>> p = partial(int, base=2) + >>> _namespace(p) + [\'functools\', \'partial\'] + """ + # mostly for functions and modules and such + #FIXME: 'wrong' for decorators and curried functions + try: #XXX: needs some work and testing on different types + module = qual = str(getmodule(obj)).split()[1].strip('>').strip('"').strip("'") + qual = qual.split('.') + if ismodule(obj): + return qual + # get name of a lambda, function, etc + name = getname(obj) or obj.__name__ # failing, raise AttributeError + # check special cases (NoneType, ...) + if module in ['builtins','__builtin__']: # BuiltinFunctionType + if _intypes(name): return ['types'] + [name] + return qual + [name] #XXX: can be wrong for some aliased objects + except Exception: pass + # special case: numpy.inf and numpy.nan (we don't want them as floats) + if str(obj) in ['inf','nan','Inf','NaN']: # is more, but are they needed? + return ['numpy'] + [str(obj)] + # mostly for classes and class instances and such + module = getattr(obj.__class__, '__module__', None) + qual = str(obj.__class__) + try: qual = qual[qual.index("'")+1:-2] + except ValueError: pass # str(obj.__class__) made the 'try' unnecessary + qual = qual.split(".") + if module in ['builtins','__builtin__']: + # check special cases (NoneType, Ellipsis, ...) + if qual[-1] == 'ellipsis': qual[-1] = 'EllipsisType' + if _intypes(qual[-1]): module = 'types' #XXX: BuiltinFunctionType + qual = [module] + qual + return qual + + +#NOTE: 05/25/14 broke backward compatibility: added 'alias' as 3rd argument +def _getimport(head, tail, alias='', verify=True, builtin=False): + """helper to build a likely import string from head and tail of namespace. + ('head','tail') are used in the following context: "from head import tail" + + If verify=True, then test the import string before returning it. + If builtin=True, then force an import for builtins where possible. + If alias is provided, then rename the object on import. + """ + # special handling for a few common types + if tail in ['Ellipsis', 'NotImplemented'] and head in ['types']: + head = len.__module__ + elif tail in ['None'] and head in ['types']: + _alias = '%s = ' % alias if alias else '' + if alias == tail: _alias = '' + return _alias+'%s\n' % tail + # we don't need to import from builtins, so return '' +# elif tail in ['NoneType','int','float','long','complex']: return '' #XXX: ? + if head in ['builtins','__builtin__']: + # special cases (NoneType, Ellipsis, ...) #XXX: BuiltinFunctionType + if tail == 'ellipsis': tail = 'EllipsisType' + if _intypes(tail): head = 'types' + elif not builtin: + _alias = '%s = ' % alias if alias else '' + if alias == tail: _alias = '' + return _alias+'%s\n' % tail + else: pass # handle builtins below + # get likely import string + if not head: _str = "import %s" % tail + else: _str = "from %s import %s" % (head, tail) + _alias = " as %s\n" % alias if alias else "\n" + if alias == tail: _alias = "\n" + _str += _alias + # FIXME: fails on most decorators, currying, and such... + # (could look for magic __wrapped__ or __func__ attr) + # (could fix in 'namespace' to check obj for closure) + if verify and not head.startswith('dill.'):# weird behavior for dill + #print(_str) + try: exec(_str) #XXX: check if == obj? (name collision) + except ImportError: #XXX: better top-down or bottom-up recursion? + _head = head.rsplit(".",1)[0] #(or get all, then compare == obj?) + if not _head: raise + if _head != head: + _str = _getimport(_head, tail, alias, verify) + return _str + + +#XXX: rename builtin to force? vice versa? verify to force? (as in getsource) +#NOTE: 05/25/14 broke backward compatibility: added 'alias' as 2nd argument +def getimport(obj, alias='', verify=True, builtin=False, enclosing=False): + """get the likely import string for the given object + + obj is the object to inspect + If verify=True, then test the import string before returning it. + If builtin=True, then force an import for builtins where possible. + If enclosing=True, get the import for the outermost enclosing callable. + If alias is provided, then rename the object on import. + """ + if enclosing: + from .detect import outermost + _obj = outermost(obj) + obj = _obj if _obj else obj + # get the namespace + qual = _namespace(obj) + head = '.'.join(qual[:-1]) + tail = qual[-1] + # for named things... with a nice repr #XXX: move into _namespace? + try: # look for '<...>' and be mindful it might be in lists, dicts, etc... + name = repr(obj).split('<',1)[1].split('>',1)[1] + name = None # we have a 'object'-style repr + except Exception: # it's probably something 'importable' + if head in ['builtins','__builtin__']: + name = repr(obj) #XXX: catch [1,2], (1,2), set([1,2])... others? + elif _isinstance(obj): + name = getname(obj, force=True).split('(')[0] + else: + name = repr(obj).split('(')[0] + #if not repr(obj).startswith('<'): name = repr(obj).split('(')[0] + #else: name = None + if name: # try using name instead of tail + try: return _getimport(head, name, alias, verify, builtin) + except ImportError: pass + except SyntaxError: + if head in ['builtins','__builtin__']: + _alias = '%s = ' % alias if alias else '' + if alias == name: _alias = '' + return _alias+'%s\n' % name + else: pass + try: + #if type(obj) is type(abs): _builtin = builtin # BuiltinFunctionType + #else: _builtin = False + return _getimport(head, tail, alias, verify, builtin) + except ImportError: + raise # could do some checking against obj + except SyntaxError: + if head in ['builtins','__builtin__']: + _alias = '%s = ' % alias if alias else '' + if alias == tail: _alias = '' + return _alias+'%s\n' % tail + raise # could do some checking against obj + + +def _importable(obj, alias='', source=None, enclosing=False, force=True, \ + builtin=True, lstrip=True): + """get an import string (or the source code) for the given object + + This function will attempt to discover the name of the object, or the repr + of the object, or the source code for the object. To attempt to force + discovery of the source code, use source=True, to attempt to force the + use of an import, use source=False; otherwise an import will be sought + for objects not defined in __main__. The intent is to build a string + that can be imported from a python file. obj is the object to inspect. + If alias is provided, then rename the object with the given alias. + + If source=True, use these options: + If enclosing=True, then also return any enclosing code. + If force=True, catch (TypeError,IOError) and try to use import hooks. + If lstrip=True, ensure there is no indentation in the first line of code. + + If source=False, use these options: + If enclosing=True, get the import for the outermost enclosing callable. + If force=True, then don't test the import string before returning it. + If builtin=True, then force an import for builtins where possible. + """ + if source is None: + source = True if isfrommain(obj) else False + if source: # first try to get the source + try: + return getsource(obj, alias, enclosing=enclosing, \ + force=force, lstrip=lstrip, builtin=builtin) + except Exception: pass + try: + if not _isinstance(obj): + return getimport(obj, alias, enclosing=enclosing, \ + verify=(not force), builtin=builtin) + # first 'get the import', then 'get the instance' + _import = getimport(obj, enclosing=enclosing, \ + verify=(not force), builtin=builtin) + name = getname(obj, force=True) + if not name: + raise AttributeError("object has no atribute '__name__'") + _alias = "%s = " % alias if alias else "" + if alias == name: _alias = "" + return _import+_alias+"%s\n" % name + + except Exception: pass + if not source: # try getsource, only if it hasn't been tried yet + try: + return getsource(obj, alias, enclosing=enclosing, \ + force=force, lstrip=lstrip, builtin=builtin) + except Exception: pass + # get the name (of functions, lambdas, and classes) + # or hope that obj can be built from the __repr__ + #XXX: what to do about class instances and such? + obj = getname(obj, force=force) + # we either have __repr__ or __name__ (or None) + if not obj or obj.startswith('<'): + raise AttributeError("object has no atribute '__name__'") + _alias = '%s = ' % alias if alias else '' + if alias == obj: _alias = '' + return _alias+'%s\n' % obj + #XXX: possible failsafe... (for example, for instances when source=False) + # "import dill; result = dill.loads(); # repr()" + +def _closuredimport(func, alias='', builtin=False): + """get import for closured objects; return a dict of 'name' and 'import'""" + import re + from .detect import freevars, outermost + free_vars = freevars(func) + func_vars = {} + # split into 'funcs' and 'non-funcs' + for name,obj in list(free_vars.items()): + if not isfunction(obj): continue + # get import for 'funcs' + fobj = free_vars.pop(name) + src = getsource(fobj) + if src.lstrip().startswith('@'): # we have a decorator + src = getimport(fobj, alias=alias, builtin=builtin) + else: # we have to "hack" a bit... and maybe be lucky + encl = outermost(func) + # pattern: 'func = enclosing(fobj' + pat = r'.*[\w\s]=\s*'+getname(encl)+r'\('+getname(fobj) + mod = getname(getmodule(encl)) + #HACK: get file containing 'outer' function; is func there? + lines,_ = findsource(encl) + candidate = [line for line in lines if getname(encl) in line and \ + re.match(pat, line)] + if not candidate: + mod = getname(getmodule(fobj)) + #HACK: get file containing 'inner' function; is func there? + lines,_ = findsource(fobj) + candidate = [line for line in lines \ + if getname(fobj) in line and re.match(pat, line)] + if not len(candidate): raise TypeError('import could not be found') + candidate = candidate[-1] + name = candidate.split('=',1)[0].split()[-1].strip() + src = _getimport(mod, name, alias=alias, builtin=builtin) + func_vars[name] = src + if not func_vars: + name = outermost(func) + mod = getname(getmodule(name)) + if not mod or name is func: # then it can be handled by getimport + name = getname(func, force=True) #XXX: better key? + src = getimport(func, alias=alias, builtin=builtin) + else: + lines,_ = findsource(name) + # pattern: 'func = enclosing(' + candidate = [line for line in lines if getname(name) in line and \ + re.match(r'.*[\w\s]=\s*'+getname(name)+r'\(', line)] + if not len(candidate): raise TypeError('import could not be found') + candidate = candidate[-1] + name = candidate.split('=',1)[0].split()[-1].strip() + src = _getimport(mod, name, alias=alias, builtin=builtin) + func_vars[name] = src + return func_vars + +#XXX: should be able to use __qualname__ +def _closuredsource(func, alias=''): + """get source code for closured objects; return a dict of 'name' + and 'code blocks'""" + #FIXME: this entire function is a messy messy HACK + # - pollutes global namespace + # - fails if name of freevars are reused + # - can unnecessarily duplicate function code + from .detect import freevars + free_vars = freevars(func) + func_vars = {} + # split into 'funcs' and 'non-funcs' + for name,obj in list(free_vars.items()): + if not isfunction(obj): + # get source for 'non-funcs' + free_vars[name] = getsource(obj, force=True, alias=name) + continue + # get source for 'funcs' + fobj = free_vars.pop(name) + src = getsource(fobj, alias) # DO NOT include dependencies + # if source doesn't start with '@', use name as the alias + if not src.lstrip().startswith('@'): #FIXME: 'enclose' in dummy; + src = importable(fobj,alias=name)# wrong ref 'name' + org = getsource(func, alias, enclosing=False, lstrip=True) + src = (src, org) # undecorated first, then target + else: #NOTE: reproduces the code! + org = getsource(func, enclosing=True, lstrip=False) + src = importable(fobj, alias, source=True) # include dependencies + src = (org, src) # target first, then decorated + func_vars[name] = src + src = ''.join(free_vars.values()) + if not func_vars: #FIXME: 'enclose' in dummy; wrong ref 'name' + org = getsource(func, alias, force=True, enclosing=False, lstrip=True) + src = (src, org) # variables first, then target + else: + src = (src, None) # just variables (better '' instead of None?) + func_vars[None] = src + # FIXME: remove duplicates (however, order is important...) + return func_vars + +def importable(obj, alias='', source=None, builtin=True): + """get an importable string (i.e. source code or the import string) + for the given object, including any required objects from the enclosing + and global scope + + This function will attempt to discover the name of the object, or the repr + of the object, or the source code for the object. To attempt to force + discovery of the source code, use source=True, to attempt to force the + use of an import, use source=False; otherwise an import will be sought + for objects not defined in __main__. The intent is to build a string + that can be imported from a python file. + + obj is the object to inspect. If alias is provided, then rename the + object with the given alias. If builtin=True, then force an import for + builtins where possible. + """ + #NOTE: we always 'force', and 'lstrip' as necessary + #NOTE: for 'enclosing', use importable(outermost(obj)) + if source is None: + source = True if isfrommain(obj) else False + elif builtin and isbuiltin(obj): + source = False + tried_source = tried_import = False + while True: + if not source: # we want an import + try: + if _isinstance(obj): # for instances, punt to _importable + return _importable(obj, alias, source=False, builtin=builtin) + src = _closuredimport(obj, alias=alias, builtin=builtin) + if len(src) == 0: + raise NotImplementedError('not implemented') + if len(src) > 1: + raise NotImplementedError('not implemented') + return list(src.values())[0] + except Exception: + if tried_source: raise + tried_import = True + # we want the source + try: + src = _closuredsource(obj, alias=alias) + if len(src) == 0: + raise NotImplementedError('not implemented') + # groan... an inline code stitcher + def _code_stitcher(block): + "stitch together the strings in tuple 'block'" + if block[0] and block[-1]: block = '\n'.join(block) + elif block[0]: block = block[0] + elif block[-1]: block = block[-1] + else: block = '' + return block + # get free_vars first + _src = _code_stitcher(src.pop(None)) + _src = [_src] if _src else [] + # get func_vars + for xxx in src.values(): + xxx = _code_stitcher(xxx) + if xxx: _src.append(xxx) + # make a single source string + if not len(_src): + src = '' + elif len(_src) == 1: + src = _src[0] + else: + src = '\n'.join(_src) + # get source code of objects referred to by obj in global scope + from .detect import globalvars + obj = globalvars(obj) #XXX: don't worry about alias? recurse? etc? + obj = list(getsource(_obj,name,force=True) for (name,_obj) in obj.items() if not isbuiltin(_obj)) + obj = '\n'.join(obj) if obj else '' + # combine all referred-to source (global then enclosing) + if not obj: return src + if not src: return obj + return obj + src + except Exception: + if tried_import: raise + tried_source = True + source = not source + # should never get here + return + + +# backward compatibility +def getimportable(obj, alias='', byname=True, explicit=False): + return importable(obj,alias,source=(not byname),builtin=explicit) + #return outdent(_importable(obj,alias,source=(not byname),builtin=explicit)) +def likely_import(obj, passive=False, explicit=False): + return getimport(obj, verify=(not passive), builtin=explicit) +def _likely_import(first, last, passive=False, explicit=True): + return _getimport(first, last, verify=(not passive), builtin=explicit) +_get_name = getname +getblocks_from_history = getblocks + + + +# EOF diff --git a/dill/temp.py b/dill/temp.py new file mode 100644 index 0000000000000000000000000000000000000000..c2728770a897cb521ad81c6029872f00e39b3c4d --- /dev/null +++ b/dill/temp.py @@ -0,0 +1,252 @@ +#!/usr/bin/env python +# +# Author: Mike McKerns (mmckerns @caltech and @uqfoundation) +# Copyright (c) 2008-2016 California Institute of Technology. +# Copyright (c) 2016-2025 The Uncertainty Quantification Foundation. +# License: 3-clause BSD. The full license text is available at: +# - https://github.com/uqfoundation/dill/blob/master/LICENSE +""" +Methods for serialized objects (or source code) stored in temporary files +and file-like objects. +""" +#XXX: better instead to have functions write to any given file-like object ? +#XXX: currently, all file-like objects are created by the function... + +__all__ = ['dump_source', 'dump', 'dumpIO_source', 'dumpIO',\ + 'load_source', 'load', 'loadIO_source', 'loadIO',\ + 'capture'] + +import contextlib + + +@contextlib.contextmanager +def capture(stream='stdout'): + """builds a context that temporarily replaces the given stream name + + >>> with capture('stdout') as out: + ... print ("foo!") + ... + >>> print (out.getvalue()) + foo! + + """ + import sys + from io import StringIO + orig = getattr(sys, stream) + setattr(sys, stream, StringIO()) + try: + yield getattr(sys, stream) + finally: + setattr(sys, stream, orig) + + +def b(x): # deal with b'foo' versus 'foo' + import codecs + return codecs.latin_1_encode(x)[0] + +def load_source(file, **kwds): + """load an object that was stored with dill.temp.dump_source + + file: filehandle + alias: string name of stored object + mode: mode to open the file, one of: {'r', 'rb'} + + >>> f = lambda x: x**2 + >>> pyfile = dill.temp.dump_source(f, alias='_f') + >>> _f = dill.temp.load_source(pyfile) + >>> _f(4) + 16 + """ + alias = kwds.pop('alias', None) + mode = kwds.pop('mode', 'r') + fname = getattr(file, 'name', file) # fname=file.name or fname=file (if str) + source = open(fname, mode=mode, **kwds).read() + if not alias: + tag = source.strip().splitlines()[-1].split() + if tag[0] != '#NAME:': + stub = source.splitlines()[0] + raise IOError("unknown name for code: %s" % stub) + alias = tag[-1] + local = {} + exec(source, local) + _ = eval("%s" % alias, local) + return _ + +def dump_source(object, **kwds): + """write object source to a NamedTemporaryFile (instead of dill.dump) +Loads with "import" or "dill.temp.load_source". Returns the filehandle. + + >>> f = lambda x: x**2 + >>> pyfile = dill.temp.dump_source(f, alias='_f') + >>> _f = dill.temp.load_source(pyfile) + >>> _f(4) + 16 + + >>> f = lambda x: x**2 + >>> pyfile = dill.temp.dump_source(f, dir='.') + >>> modulename = os.path.basename(pyfile.name).split('.py')[0] + >>> exec('from %s import f as _f' % modulename) + >>> _f(4) + 16 + +Optional kwds: + If 'alias' is specified, the object will be renamed to the given string. + + If 'prefix' is specified, the file name will begin with that prefix, + otherwise a default prefix is used. + + If 'dir' is specified, the file will be created in that directory, + otherwise a default directory is used. + + If 'text' is specified and true, the file is opened in text + mode. Else (the default) the file is opened in binary mode. On + some operating systems, this makes no difference. + +NOTE: Keep the return value for as long as you want your file to exist ! + """ #XXX: write a "load_source"? + from .source import importable, getname + import tempfile + kwds.setdefault('delete', True) + kwds.pop('suffix', '') # this is *always* '.py' + alias = kwds.pop('alias', '') #XXX: include an alias so a name is known + name = str(alias) or getname(object) + name = "\n#NAME: %s\n" % name + #XXX: assumes kwds['dir'] is writable and on $PYTHONPATH + file = tempfile.NamedTemporaryFile(suffix='.py', **kwds) + file.write(b(''.join([importable(object, alias=alias),name]))) + file.flush() + return file + +def load(file, **kwds): + """load an object that was stored with dill.temp.dump + + file: filehandle + mode: mode to open the file, one of: {'r', 'rb'} + + >>> dumpfile = dill.temp.dump([1, 2, 3, 4, 5]) + >>> dill.temp.load(dumpfile) + [1, 2, 3, 4, 5] + """ + import dill as pickle + mode = kwds.pop('mode', 'rb') + name = getattr(file, 'name', file) # name=file.name or name=file (if str) + return pickle.load(open(name, mode=mode, **kwds)) + +def dump(object, **kwds): + """dill.dump of object to a NamedTemporaryFile. +Loads with "dill.temp.load". Returns the filehandle. + + >>> dumpfile = dill.temp.dump([1, 2, 3, 4, 5]) + >>> dill.temp.load(dumpfile) + [1, 2, 3, 4, 5] + +Optional kwds: + If 'suffix' is specified, the file name will end with that suffix, + otherwise there will be no suffix. + + If 'prefix' is specified, the file name will begin with that prefix, + otherwise a default prefix is used. + + If 'dir' is specified, the file will be created in that directory, + otherwise a default directory is used. + + If 'text' is specified and true, the file is opened in text + mode. Else (the default) the file is opened in binary mode. On + some operating systems, this makes no difference. + +NOTE: Keep the return value for as long as you want your file to exist ! + """ + import dill as pickle + import tempfile + kwds.setdefault('delete', True) + file = tempfile.NamedTemporaryFile(**kwds) + pickle.dump(object, file) + file.flush() + return file + +def loadIO(buffer, **kwds): + """load an object that was stored with dill.temp.dumpIO + + buffer: buffer object + + >>> dumpfile = dill.temp.dumpIO([1, 2, 3, 4, 5]) + >>> dill.temp.loadIO(dumpfile) + [1, 2, 3, 4, 5] + """ + import dill as pickle + from io import BytesIO as StringIO + value = getattr(buffer, 'getvalue', buffer) # value or buffer.getvalue + if value != buffer: value = value() # buffer.getvalue() + return pickle.load(StringIO(value)) + +def dumpIO(object, **kwds): + """dill.dump of object to a buffer. +Loads with "dill.temp.loadIO". Returns the buffer object. + + >>> dumpfile = dill.temp.dumpIO([1, 2, 3, 4, 5]) + >>> dill.temp.loadIO(dumpfile) + [1, 2, 3, 4, 5] + """ + import dill as pickle + from io import BytesIO as StringIO + file = StringIO() + pickle.dump(object, file) + file.flush() + return file + +def loadIO_source(buffer, **kwds): + """load an object that was stored with dill.temp.dumpIO_source + + buffer: buffer object + alias: string name of stored object + + >>> f = lambda x:x**2 + >>> pyfile = dill.temp.dumpIO_source(f, alias='_f') + >>> _f = dill.temp.loadIO_source(pyfile) + >>> _f(4) + 16 + """ + alias = kwds.pop('alias', None) + source = getattr(buffer, 'getvalue', buffer) # source or buffer.getvalue + if source != buffer: source = source() # buffer.getvalue() + source = source.decode() # buffer to string + if not alias: + tag = source.strip().splitlines()[-1].split() + if tag[0] != '#NAME:': + stub = source.splitlines()[0] + raise IOError("unknown name for code: %s" % stub) + alias = tag[-1] + local = {} + exec(source, local) + _ = eval("%s" % alias, local) + return _ + +def dumpIO_source(object, **kwds): + """write object source to a buffer (instead of dill.dump) +Loads by with dill.temp.loadIO_source. Returns the buffer object. + + >>> f = lambda x:x**2 + >>> pyfile = dill.temp.dumpIO_source(f, alias='_f') + >>> _f = dill.temp.loadIO_source(pyfile) + >>> _f(4) + 16 + +Optional kwds: + If 'alias' is specified, the object will be renamed to the given string. + """ + from .source import importable, getname + from io import BytesIO as StringIO + alias = kwds.pop('alias', '') #XXX: include an alias so a name is known + name = str(alias) or getname(object) + name = "\n#NAME: %s\n" % name + #XXX: assumes kwds['dir'] is writable and on $PYTHONPATH + file = StringIO() + file.write(b(''.join([importable(object, alias=alias),name]))) + file.flush() + return file + + +del contextlib + + +# EOF diff --git a/frozenlist-1.8.0.dist-info/INSTALLER b/frozenlist-1.8.0.dist-info/INSTALLER new file mode 100644 index 0000000000000000000000000000000000000000..5c69047b2eb8235994febeeae1da4a82365a240a --- /dev/null +++ b/frozenlist-1.8.0.dist-info/INSTALLER @@ -0,0 +1 @@ +uv \ No newline at end of file diff --git a/frozenlist-1.8.0.dist-info/METADATA b/frozenlist-1.8.0.dist-info/METADATA new file mode 100644 index 0000000000000000000000000000000000000000..30d66530bc93801fc3385006ce179e72b42644df --- /dev/null +++ b/frozenlist-1.8.0.dist-info/METADATA @@ -0,0 +1,672 @@ +Metadata-Version: 2.4 +Name: frozenlist +Version: 1.8.0 +Summary: A list-like structure which implements collections.abc.MutableSequence +Home-page: https://github.com/aio-libs/frozenlist +Maintainer: aiohttp team +Maintainer-email: team@aiohttp.org +License: Apache-2.0 +Project-URL: Chat: Matrix, https://matrix.to/#/#aio-libs:matrix.org +Project-URL: Chat: Matrix Space, https://matrix.to/#/#aio-libs-space:matrix.org +Project-URL: CI: Github Actions, https://github.com/aio-libs/frozenlist/actions +Project-URL: Code of Conduct, https://github.com/aio-libs/.github/blob/master/CODE_OF_CONDUCT.md +Project-URL: Coverage: codecov, https://codecov.io/github/aio-libs/frozenlist +Project-URL: Docs: Changelog, https://github.com/aio-libs/frozenlist/blob/master/CHANGES.rst#changelog +Project-URL: Docs: RTD, https://frozenlist.aio-libs.org +Project-URL: GitHub: issues, https://github.com/aio-libs/frozenlist/issues +Project-URL: GitHub: repo, https://github.com/aio-libs/frozenlist +Classifier: Development Status :: 5 - Production/Stable +Classifier: Intended Audience :: Developers +Classifier: Operating System :: POSIX +Classifier: Operating System :: MacOS :: MacOS X +Classifier: Operating System :: Microsoft :: Windows +Classifier: Programming Language :: Cython +Classifier: Programming Language :: Python +Classifier: Programming Language :: Python :: 3 +Classifier: Programming Language :: Python :: 3.9 +Classifier: Programming Language :: Python :: 3.10 +Classifier: Programming Language :: Python :: 3.11 +Classifier: Programming Language :: Python :: 3.12 +Classifier: Programming Language :: Python :: 3.13 +Classifier: Programming Language :: Python :: 3.14 +Classifier: Programming Language :: Python :: Implementation :: CPython +Classifier: Programming Language :: Python :: Implementation :: PyPy +Requires-Python: >=3.9 +Description-Content-Type: text/x-rst +License-File: LICENSE +Dynamic: license-file + +frozenlist +========== + +.. image:: https://github.com/aio-libs/frozenlist/workflows/CI/badge.svg + :target: https://github.com/aio-libs/frozenlist/actions + :alt: GitHub status for master branch + +.. image:: https://codecov.io/gh/aio-libs/frozenlist/branch/master/graph/badge.svg?flag=pytest + :target: https://codecov.io/gh/aio-libs/frozenlist?flags[]=pytest + :alt: codecov.io status for master branch + +.. image:: https://img.shields.io/pypi/v/frozenlist.svg?logo=Python&logoColor=white + :target: https://pypi.org/project/frozenlist + :alt: frozenlist @ PyPI + +.. image:: https://readthedocs.org/projects/frozenlist/badge/?version=latest + :target: https://frozenlist.aio-libs.org + :alt: Read The Docs build status badge + +.. image:: https://img.shields.io/matrix/aio-libs:matrix.org?label=Discuss%20on%20Matrix%20at%20%23aio-libs%3Amatrix.org&logo=matrix&server_fqdn=matrix.org&style=flat + :target: https://matrix.to/#/%23aio-libs:matrix.org + :alt: Matrix Room — #aio-libs:matrix.org + +.. image:: https://img.shields.io/matrix/aio-libs-space:matrix.org?label=Discuss%20on%20Matrix%20at%20%23aio-libs-space%3Amatrix.org&logo=matrix&server_fqdn=matrix.org&style=flat + :target: https://matrix.to/#/%23aio-libs-space:matrix.org + :alt: Matrix Space — #aio-libs-space:matrix.org + +Introduction +------------ + +``frozenlist.FrozenList`` is a list-like structure which implements +``collections.abc.MutableSequence``. The list is *mutable* until ``FrozenList.freeze`` +is called, after which list modifications raise ``RuntimeError``: + + +>>> from frozenlist import FrozenList +>>> fl = FrozenList([17, 42]) +>>> fl.append('spam') +>>> fl.append('Vikings') +>>> fl + +>>> fl.freeze() +>>> fl + +>>> fl.frozen +True +>>> fl.append("Monty") +Traceback (most recent call last): + File "", line 1, in + File "frozenlist/_frozenlist.pyx", line 97, in frozenlist._frozenlist.FrozenList.append + self._check_frozen() + File "frozenlist/_frozenlist.pyx", line 19, in frozenlist._frozenlist.FrozenList._check_frozen + raise RuntimeError("Cannot modify frozen list.") +RuntimeError: Cannot modify frozen list. + + +FrozenList is also hashable, but only when frozen. Otherwise it also throws a RuntimeError: + + +>>> fl = FrozenList([17, 42, 'spam']) +>>> hash(fl) +Traceback (most recent call last): + File "", line 1, in + File "frozenlist/_frozenlist.pyx", line 111, in frozenlist._frozenlist.FrozenList.__hash__ + raise RuntimeError("Cannot hash unfrozen list.") +RuntimeError: Cannot hash unfrozen list. +>>> fl.freeze() +>>> hash(fl) +3713081631934410656 +>>> dictionary = {fl: 'Vikings'} # frozen fl can be a dict key +>>> dictionary +{: 'Vikings'} + + +Installation +------------ + +:: + + $ pip install frozenlist + + +Documentation +------------- + +https://frozenlist.aio-libs.org + +Communication channels +---------------------- + +We have a *Matrix Space* `#aio-libs-space:matrix.org +`_ which is +also accessible via Gitter. + +License +------- + +``frozenlist`` is offered under the Apache 2 license. + +Source code +----------- + +The project is hosted on GitHub_ + +Please file an issue in the `bug tracker +`_ if you have found a bug +or have some suggestions to improve the library. + +.. _GitHub: https://github.com/aio-libs/frozenlist + +========= +Changelog +========= + +.. + You should *NOT* be adding new change log entries to this file, this + file is managed by towncrier. You *may* edit previous change logs to + fix problems like typo corrections or such. + To add a new change log entry, please see + https://pip.pypa.io/en/latest/development/contributing/#news-entries + we named the news folder "changes". + + WARNING: Don't drop the next directive! + +.. towncrier release notes start + +v1.8.0 +====== + +*(2025-10-05)* + + +Contributor-facing changes +-------------------------- + +- The ``reusable-cibuildwheel.yml`` workflow has been refactored to + be more generic and ``ci-cd.yml`` now holds all the configuration + toggles -- by `@webknjaz `__. + + *Related issues and pull requests on GitHub:* + `#668 `__. + +- When building wheels, the source distribution is now passed directly + to the ``cibuildwheel`` invocation -- by `@webknjaz `__. + + *Related issues and pull requests on GitHub:* + `#669 `__. + +- Builds and tests have been added to + ``ci-cd.yml`` for arm64 Windows wheels -- by `@finnagin `__. + + *Related issues and pull requests on GitHub:* + `#677 `__. + +- Started building wheels for CPython 3.14 -- by `@kumaraditya303 `__. + + *Related issues and pull requests on GitHub:* + `#681 `__, `#682 `__. + +- Removed ``--config-settings=pure-python=false`` from ``requirements/dev.txt``. + Developers on CPython still get accelerated builds by default. To explicitly build + a pure Python wheel, use ``pip install -e . --config-settings=pure-python=true`` + -- by `@bdraco `__. + + *Related issues and pull requests on GitHub:* + `#687 `__. + + +---- + + +v1.7.0 +====== + +*(2025-06-09)* + + +Features +-------- + +- Added deepcopy support to FrozenList -- by `@bdraco `__. + + *Related issues and pull requests on GitHub:* + `#659 `__. + + +Packaging updates and notes for downstreams +------------------------------------------- + +- Fixed an issue where ``frozenlist`` binary wheels would be built with debugging symbols and line tracing enabled, which significantly impacted performance. Line tracing is now disabled by default and can only be enabled explicitly -- by `@bdraco `__. + + This change ensures that production builds are optimized for performance. Developers who need line tracing for debugging purposes can still enable it by: + + 1. Setting the ``FROZENLIST_CYTHON_TRACING`` environment variable + 2. Using the ``--config-setting=with-cython-tracing=true`` option with pip + + *Related issues and pull requests on GitHub:* + `#660 `__. + +- Enabled ``PIP_CONSTRAINT`` environment variable in the build configuration to ensure the pinned Cython version from ``requirements/cython.txt`` is used during wheel builds. + + *Related issues and pull requests on GitHub:* + `#661 `__. + + +---- + + +v1.6.2 +====== + +*(2025-06-03)* + + +No significant changes. + + +---- + + +v1.6.1 +====== + +*(2025-06-02)* + + +Bug fixes +--------- + +- Correctly use ``cimport`` for including ``PyBool_FromLong`` -- by `@lysnikolaou `__. + + *Related issues and pull requests on GitHub:* + `#653 `__. + + +Packaging updates and notes for downstreams +------------------------------------------- + +- Exclude ``_frozenlist.cpp`` from bdists/wheels -- by `@musicinmybrain `__. + + *Related issues and pull requests on GitHub:* + `#649 `__. + +- Updated to use Cython 3.1 universally across the build path -- by `@lysnikolaou `__. + + *Related issues and pull requests on GitHub:* + `#654 `__. + + +---- + + +v1.6.0 +====== + +*(2025-04-17)* + + +Bug fixes +--------- + +- Stopped implicitly allowing the use of Cython pre-release versions when + building the distribution package -- by `@ajsanchezsanz `__ and + `@markgreene74 `__. + + *Related commits on GitHub:* + `41591f2 `__. + + +Features +-------- + +- Implemented support for the free-threaded build of CPython 3.13 -- by `@lysnikolaou `__. + + *Related issues and pull requests on GitHub:* + `#618 `__. + +- Started building armv7l wheels -- by `@bdraco `__. + + *Related issues and pull requests on GitHub:* + `#642 `__. + + +Packaging updates and notes for downstreams +------------------------------------------- + +- Stopped implicitly allowing the use of Cython pre-release versions when + building the distribution package -- by `@ajsanchezsanz `__ and + `@markgreene74 `__. + + *Related commits on GitHub:* + `41591f2 `__. + +- Started building wheels for the free-threaded build of CPython 3.13 -- by `@lysnikolaou `__. + + *Related issues and pull requests on GitHub:* + `#618 `__. + +- The packaging metadata switched to including an SPDX license identifier introduced in `PEP 639 `__ -- by `@cdce8p `__. + + *Related issues and pull requests on GitHub:* + `#639 `__. + + +Contributor-facing changes +-------------------------- + +- GitHub Actions CI/CD is now configured to manage caching pip-ecosystem + dependencies using `re-actors/cache-python-deps`_ -- an action by + `@webknjaz `__ that takes into account ABI stability and the exact + version of Python runtime. + + .. _`re-actors/cache-python-deps`: + https://github.com/marketplace/actions/cache-python-deps + + *Related issues and pull requests on GitHub:* + `#633 `__. + +- Organized dependencies into test and lint dependencies so that no + unnecessary ones are installed during CI runs -- by `@lysnikolaou `__. + + *Related issues and pull requests on GitHub:* + `#636 `__. + + +---- + + +1.5.0 (2024-10-22) +================== + +Bug fixes +--------- + +- An incorrect signature of the ``__class_getitem__`` class method + has been fixed, adding a missing ``class_item`` argument under + Python 3.8 and older. + + This change also improves the code coverage of this method that + was previously missing -- by `@webknjaz `__. + + + *Related issues and pull requests on GitHub:* + `#567 `__, `#571 `__. + + +Improved documentation +---------------------- + +- Rendered issue, PR, and commit links now lead to + ``frozenlist``'s repo instead of ``yarl``'s repo. + + + *Related issues and pull requests on GitHub:* + `#573 `__. + +- On the ``Contributing docs`` page, + a link to the ``Towncrier philosophy`` has been fixed. + + + *Related issues and pull requests on GitHub:* + `#574 `__. + + +Packaging updates and notes for downstreams +------------------------------------------- + +- A name of a temporary building directory now reflects + that it's related to ``frozenlist``, not ``yarl``. + + + *Related issues and pull requests on GitHub:* + `#573 `__. + +- Declared Python 3.13 supported officially in the distribution package metadata. + + + *Related issues and pull requests on GitHub:* + `#595 `__. + + +---- + + +1.4.1 (2023-12-15) +================== + +Packaging updates and notes for downstreams +------------------------------------------- + +- Declared Python 3.12 and PyPy 3.8-3.10 supported officially + in the distribution package metadata. + + + *Related issues and pull requests on GitHub:* + `#553 `__. + +- Replaced the packaging is replaced from an old-fashioned ``setup.py`` to an + in-tree `PEP 517 `__ build backend -- by `@webknjaz `__. + + Whenever the end-users or downstream packagers need to build ``frozenlist`` + from source (a Git checkout or an sdist), they may pass a ``config_settings`` + flag ``pure-python``. If this flag is not set, a C-extension will be built + and included into the distribution. + + Here is how this can be done with ``pip``: + + .. code-block:: console + + $ python3 -m pip install . --config-settings=pure-python= + + This will also work with ``-e | --editable``. + + The same can be achieved via ``pypa/build``: + + .. code-block:: console + + $ python3 -m build --config-setting=pure-python= + + Adding ``-w | --wheel`` can force ``pypa/build`` produce a wheel from source + directly, as opposed to building an ``sdist`` and then building from it. + + + *Related issues and pull requests on GitHub:* + `#560 `__. + + +Contributor-facing changes +-------------------------- + +- It is now possible to request line tracing in Cython builds using the + ``with-cython-tracing`` `PEP 517 `__ config setting + -- `@webknjaz `__. + + This can be used in CI and development environment to measure coverage + on Cython modules, but is not normally useful to the end-users or + downstream packagers. + + Here's a usage example: + + .. code-block:: console + + $ python3 -Im pip install . --config-settings=with-cython-tracing=true + + For editable installs, this setting is on by default. Otherwise, it's + off unless requested explicitly. + + The following produces C-files required for the Cython coverage + plugin to map the measurements back to the PYX-files: + + .. code-block:: console + + $ python -Im pip install -e . + + Alternatively, the ``FROZENLIST_CYTHON_TRACING=1`` environment variable + can be set to do the same as the `PEP 517 `__ config setting. + + + *Related issues and pull requests on GitHub:* + `#560 `__. + +- Coverage collection has been implemented for the Cython modules + -- by `@webknjaz `__. + + It will also be reported to Codecov from any non-release CI jobs. + + + *Related issues and pull requests on GitHub:* + `#561 `__. + +- A step-by-step ``Release Guide`` guide has + been added, describing how to release *frozenlist* -- by `@webknjaz `__. + + This is primarily targeting the maintainers. + + + *Related issues and pull requests on GitHub:* + `#563 `__. + +- Detailed ``Contributing Guidelines`` on + authoring the changelog fragments have been published in the + documentation -- by `@webknjaz `__. + + + *Related issues and pull requests on GitHub:* + `#564 `__. + + +---- + + +1.4.0 (2023-07-12) +================== + +The published source distribution package became buildable +under Python 3.12. + + +---- + + +Bugfixes +-------- + +- Removed an unused ``typing.Tuple`` import + `#411 `_ + + +Deprecations and Removals +------------------------- + +- Dropped Python 3.7 support. + `#413 `_ + + +Misc +---- + +- `#410 `_, `#433 `_ + + +---- + + +1.3.3 (2022-11-08) +================== + +- Fixed CI runs when creating a new release, where new towncrier versions + fail when the current version section is already present. + + +---- + + +1.3.2 (2022-11-08) +================== + +Misc +---- + +- Updated the CI runs to better check for test results and to avoid deprecated syntax. `#327 `_ + + +---- + + +1.3.1 (2022-08-02) +================== + +The published source distribution package became buildable +under Python 3.11. + + +---- + + +1.3.0 (2022-01-18) +================== + +Bugfixes +-------- + +- Do not install C sources with binary distributions. + `#250 `_ + + +Deprecations and Removals +------------------------- + +- Dropped Python 3.6 support + `#274 `_ + + +---- + + +1.2.0 (2021-10-16) +================== + +Features +-------- + +- ``FrozenList`` now supports being used as a generic type as per PEP 585, e.g. ``frozen_int_list: FrozenList[int]`` (requires Python 3.9 or newer). + `#172 `_ +- Added support for Python 3.10. + `#227 `_ +- Started shipping platform-specific wheels with the ``musl`` tag targeting typical Alpine Linux runtimes. + `#227 `_ +- Started shipping platform-specific arm64 wheels for Apple Silicon. + `#227 `_ + + +---- + + +1.1.1 (2020-11-14) +================== + +Bugfixes +-------- + +- Provide x86 Windows wheels. + `#169 `_ + + +---- + + +1.1.0 (2020-10-13) +================== + +Features +-------- + +- Add support for hashing of a frozen list. + `#136 `_ + +- Support Python 3.8 and 3.9. + +- Provide wheels for ``aarch64``, ``i686``, ``ppc64le``, ``s390x`` architectures on + Linux as well as ``x86_64``. + + +---- + + +1.0.0 (2019-11-09) +================== + +Deprecations and Removals +------------------------- + +- Dropped support for Python 3.5; 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extra == 'abfs' +Provides-Extra: adl +Requires-Dist: adlfs; extra == 'adl' +Provides-Extra: arrow +Requires-Dist: pyarrow>=1; extra == 'arrow' +Provides-Extra: dask +Requires-Dist: dask; extra == 'dask' +Requires-Dist: distributed; extra == 'dask' +Provides-Extra: dev +Requires-Dist: pre-commit; extra == 'dev' +Requires-Dist: ruff>=0.5; extra == 'dev' +Provides-Extra: doc +Requires-Dist: numpydoc; extra == 'doc' +Requires-Dist: sphinx; extra == 'doc' +Requires-Dist: sphinx-design; extra == 'doc' +Requires-Dist: sphinx-rtd-theme; extra == 'doc' +Requires-Dist: yarl; extra == 'doc' +Provides-Extra: dropbox +Requires-Dist: dropbox; extra == 'dropbox' +Requires-Dist: dropboxdrivefs; extra == 'dropbox' +Requires-Dist: requests; extra == 'dropbox' +Provides-Extra: entrypoints +Provides-Extra: full +Requires-Dist: adlfs; extra == 'full' +Requires-Dist: aiohttp!=4.0.0a0,!=4.0.0a1; extra == 'full' +Requires-Dist: dask; extra == 'full' +Requires-Dist: distributed; extra == 'full' +Requires-Dist: dropbox; extra == 'full' +Requires-Dist: dropboxdrivefs; extra == 'full' +Requires-Dist: fusepy; extra == 'full' +Requires-Dist: gcsfs; extra == 'full' +Requires-Dist: libarchive-c; extra == 'full' +Requires-Dist: ocifs; extra == 'full' +Requires-Dist: panel; extra == 'full' +Requires-Dist: paramiko; extra == 'full' +Requires-Dist: pyarrow>=1; extra == 'full' +Requires-Dist: pygit2; extra == 'full' +Requires-Dist: requests; extra == 'full' +Requires-Dist: s3fs; extra == 'full' +Requires-Dist: smbprotocol; extra == 'full' +Requires-Dist: tqdm; extra == 'full' +Provides-Extra: fuse +Requires-Dist: fusepy; extra == 'fuse' +Provides-Extra: gcs +Requires-Dist: gcsfs; extra == 'gcs' +Provides-Extra: git +Requires-Dist: pygit2; extra == 'git' +Provides-Extra: github +Requires-Dist: requests; extra == 'github' +Provides-Extra: gs +Requires-Dist: gcsfs; extra == 'gs' +Provides-Extra: gui +Requires-Dist: panel; extra == 'gui' +Provides-Extra: hdfs +Requires-Dist: pyarrow>=1; extra == 'hdfs' +Provides-Extra: http +Requires-Dist: aiohttp!=4.0.0a0,!=4.0.0a1; extra == 'http' +Provides-Extra: libarchive +Requires-Dist: libarchive-c; extra == 'libarchive' +Provides-Extra: oci +Requires-Dist: ocifs; extra == 'oci' +Provides-Extra: s3 +Requires-Dist: s3fs; extra == 's3' +Provides-Extra: sftp +Requires-Dist: paramiko; extra == 'sftp' +Provides-Extra: smb +Requires-Dist: smbprotocol; extra == 'smb' +Provides-Extra: ssh +Requires-Dist: paramiko; extra == 'ssh' +Provides-Extra: test +Requires-Dist: aiohttp!=4.0.0a0,!=4.0.0a1; extra == 'test' +Requires-Dist: numpy; extra == 'test' +Requires-Dist: pytest; extra == 'test' +Requires-Dist: pytest-asyncio!=0.22.0; extra == 'test' +Requires-Dist: pytest-benchmark; extra == 'test' +Requires-Dist: pytest-cov; extra == 'test' +Requires-Dist: pytest-mock; extra == 'test' +Requires-Dist: pytest-recording; extra == 'test' +Requires-Dist: pytest-rerunfailures; extra == 'test' +Requires-Dist: requests; extra == 'test' +Provides-Extra: test-downstream +Requires-Dist: aiobotocore<3.0.0,>=2.5.4; extra == 'test-downstream' +Requires-Dist: dask[dataframe,test]; extra == 'test-downstream' +Requires-Dist: moto[server]<5,>4; extra == 'test-downstream' +Requires-Dist: pytest-timeout; extra == 'test-downstream' +Requires-Dist: xarray; extra == 'test-downstream' +Provides-Extra: test-full +Requires-Dist: adlfs; extra == 'test-full' +Requires-Dist: aiohttp!=4.0.0a0,!=4.0.0a1; extra == 'test-full' +Requires-Dist: cloudpickle; extra == 'test-full' +Requires-Dist: dask; extra == 'test-full' +Requires-Dist: distributed; extra == 'test-full' +Requires-Dist: dropbox; extra == 'test-full' +Requires-Dist: dropboxdrivefs; extra == 'test-full' +Requires-Dist: fastparquet; extra == 'test-full' +Requires-Dist: fusepy; extra == 'test-full' +Requires-Dist: gcsfs; extra == 'test-full' +Requires-Dist: jinja2; extra == 'test-full' +Requires-Dist: kerchunk; extra == 'test-full' +Requires-Dist: libarchive-c; extra == 'test-full' +Requires-Dist: lz4; extra == 'test-full' +Requires-Dist: notebook; extra == 'test-full' +Requires-Dist: numpy; extra == 'test-full' +Requires-Dist: ocifs; extra == 'test-full' +Requires-Dist: pandas; extra == 'test-full' +Requires-Dist: panel; extra == 'test-full' +Requires-Dist: paramiko; extra == 'test-full' +Requires-Dist: pyarrow; extra == 'test-full' +Requires-Dist: pyarrow>=1; extra == 'test-full' +Requires-Dist: pyftpdlib; extra == 'test-full' +Requires-Dist: pygit2; extra == 'test-full' +Requires-Dist: pytest; extra == 'test-full' +Requires-Dist: pytest-asyncio!=0.22.0; extra == 'test-full' +Requires-Dist: pytest-benchmark; extra == 'test-full' +Requires-Dist: pytest-cov; extra == 'test-full' +Requires-Dist: pytest-mock; extra == 'test-full' +Requires-Dist: pytest-recording; extra == 'test-full' +Requires-Dist: pytest-rerunfailures; extra == 'test-full' +Requires-Dist: python-snappy; extra == 'test-full' +Requires-Dist: requests; extra == 'test-full' +Requires-Dist: smbprotocol; extra == 'test-full' +Requires-Dist: tqdm; extra == 'test-full' +Requires-Dist: urllib3; extra == 'test-full' +Requires-Dist: zarr; extra == 'test-full' +Requires-Dist: zstandard; (python_version < '3.14') and extra == 'test-full' +Provides-Extra: tqdm +Requires-Dist: tqdm; extra == 'tqdm' +Description-Content-Type: text/markdown + +# filesystem_spec + +[![PyPI version](https://badge.fury.io/py/fsspec.svg)](https://pypi.python.org/pypi/fsspec/) +[![Anaconda-Server Badge](https://anaconda.org/conda-forge/fsspec/badges/version.svg)](https://anaconda.org/conda-forge/fsspec) +![Build](https://github.com/fsspec/filesystem_spec/workflows/CI/badge.svg) +[![Docs](https://readthedocs.org/projects/filesystem-spec/badge/?version=latest)](https://filesystem-spec.readthedocs.io/en/latest/?badge=latest) + +A specification for pythonic filesystems. + +## Install + +```bash +pip install fsspec +``` + +would install the base fsspec. Various optionally supported features might require specification of custom +extra require, e.g. `pip install fsspec[ssh]` will install dependencies for `ssh` backends support. +Use `pip install fsspec[full]` for installation of all known extra dependencies. + +Up-to-date package also provided through conda-forge distribution: + +```bash +conda install -c conda-forge fsspec +``` + + +## Purpose + +To produce a template or specification for a file-system interface, that specific implementations should follow, +so that applications making use of them can rely on a common behaviour and not have to worry about the specific +internal implementation decisions with any given backend. Many such implementations are included in this package, +or in sister projects such as `s3fs` and `gcsfs`. + +In addition, if this is well-designed, then additional functionality, such as a key-value store or FUSE +mounting of the file-system implementation may be available for all implementations "for free". + +## Documentation + +Please refer to [RTD](https://filesystem-spec.readthedocs.io/en/latest/?badge=latest) + +## Develop + +fsspec uses GitHub Actions for CI. Environment files can be found +in the "ci/" directory. Note that the main environment is called "py38", +but it is expected that the version of python installed be adjustable at +CI runtime. For local use, pick a version suitable for you. + +```bash +# For a new environment (mamba / conda). +mamba create -n fsspec -c conda-forge python=3.9 -y +conda activate fsspec + +# Standard dev install with docs and tests. +pip install -e ".[dev,doc,test]" + +# Full tests except for downstream +pip install s3fs +pip uninstall s3fs +pip install -e .[dev,doc,test_full] +pip install s3fs --no-deps +pytest -v + +# Downstream tests. +sh install_s3fs.sh +# Windows powershell. +install_s3fs.sh +``` + +### Testing + +Tests can be run in the dev environment, if activated, via ``pytest fsspec``. + +The full fsspec suite requires a system-level docker, docker-compose, and fuse +installation. If only making changes to one backend implementation, it is +not generally necessary to run all tests locally. + +It is expected that contributors ensure that any change to fsspec does not +cause issues or regressions for either other fsspec-related packages such +as gcsfs and s3fs, nor for downstream users of fsspec. The "downstream" CI +run and corresponding environment file run a set of tests from the dask +test suite, and very minimal tests against pandas and zarr from the +test_downstream.py module in this repo. + +### Code Formatting + +fsspec uses [Black](https://black.readthedocs.io/en/stable) to ensure +a consistent code format throughout the project. +Run ``black fsspec`` from the root of the filesystem_spec repository to +auto-format your code. Additionally, many editors have plugins that will apply +``black`` as you edit files. ``black`` is included in the ``tox`` environments. + +Optionally, you may wish to setup [pre-commit hooks](https://pre-commit.com) to +automatically run ``black`` when you make a git commit. +Run ``pre-commit install --install-hooks`` from the root of the +filesystem_spec repository to setup pre-commit hooks. ``black`` will now be run +before you commit, reformatting any changed files. You can format without +committing via ``pre-commit run`` or skip these checks with ``git commit +--no-verify``. + +## Support + +Work on this repository is supported in part by: + +"Anaconda, Inc. - Advancing AI through open source." + +anaconda logo diff --git a/fsspec-2025.9.0.dist-info/RECORD b/fsspec-2025.9.0.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..332a9e835e4fe62cb09ab4a85d2aaf9f0facf98e --- /dev/null +++ b/fsspec-2025.9.0.dist-info/RECORD @@ -0,0 +1,62 @@ +fsspec-2025.9.0.dist-info/INSTALLER,sha256=5hhM4Q4mYTT9z6QB6PGpUAW81PGNFrYrdXMj4oM_6ak,2 +fsspec-2025.9.0.dist-info/METADATA,sha256=VmMoGluoRhQXlQigYs9kzwlXfPIg1KBkRL7V2F5O2B0,10397 +fsspec-2025.9.0.dist-info/RECORD,, +fsspec-2025.9.0.dist-info/REQUESTED,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0 +fsspec-2025.9.0.dist-info/WHEEL,sha256=qtCwoSJWgHk21S1Kb4ihdzI2rlJ1ZKaIurTj_ngOhyQ,87 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+fsspec/utils.py,sha256=HC8RFbb7KpEDedsYxExvWvsTObEuUcuuWxd0B_MyGpo,22995 diff --git a/fsspec-2025.9.0.dist-info/REQUESTED b/fsspec-2025.9.0.dist-info/REQUESTED new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/fsspec-2025.9.0.dist-info/WHEEL b/fsspec-2025.9.0.dist-info/WHEEL new file mode 100644 index 0000000000000000000000000000000000000000..12228d414b6cfed7c39d3781c85c63256a1d7fb5 --- /dev/null +++ b/fsspec-2025.9.0.dist-info/WHEEL @@ -0,0 +1,4 @@ +Wheel-Version: 1.0 +Generator: hatchling 1.27.0 +Root-Is-Purelib: true +Tag: py3-none-any diff --git a/functorch/__init__.py b/functorch/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..0aef38c8a9bb84a9833c4c2c9c34ad528d564b32 --- /dev/null +++ b/functorch/__init__.py @@ -0,0 +1,39 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# All rights reserved. +# +# This source code is licensed under the BSD-style license found in the +# LICENSE file in the root directory of this source tree. +import torch +from torch._functorch.deprecated import ( + combine_state_for_ensemble, + functionalize, + grad, + grad_and_value, + hessian, + jacfwd, + jacrev, + jvp, + make_functional, + make_functional_with_buffers, + vjp, + vmap, +) + +# utilities. Maybe these should go in their own namespace in the future? +from torch._functorch.make_functional import ( + FunctionalModule, + FunctionalModuleWithBuffers, +) + +# Was never documented +from torch._functorch.python_key import make_fx + + +# Top-level APIs. Please think carefully before adding something to the +# top-level namespace: +# - private helper functions should go into torch._functorch +# - very experimental things should go into functorch.experimental +# - compilation related things should go into functorch.compile + + +__version__ = torch.__version__ diff --git a/hf_transfer-0.1.9.dist-info/INSTALLER b/hf_transfer-0.1.9.dist-info/INSTALLER new file mode 100644 index 0000000000000000000000000000000000000000..5c69047b2eb8235994febeeae1da4a82365a240a --- /dev/null +++ b/hf_transfer-0.1.9.dist-info/INSTALLER @@ -0,0 +1 @@ +uv \ No newline at end of file diff --git a/hf_transfer-0.1.9.dist-info/METADATA b/hf_transfer-0.1.9.dist-info/METADATA new file mode 100644 index 0000000000000000000000000000000000000000..f6ddf4f0e77a8a767d533125c4c7f37fba08c896 --- /dev/null +++ b/hf_transfer-0.1.9.dist-info/METADATA @@ -0,0 +1,64 @@ +Metadata-Version: 2.4 +Name: hf_transfer +Version: 0.1.9 +Classifier: Programming Language :: Rust +Classifier: Programming Language :: Python :: Implementation :: CPython +Classifier: Programming Language :: Python :: Implementation :: PyPy +License-File: LICENSE +Summary: Speed up file transfers with the Hugging Face Hub. +Requires-Python: >=3.7 +Description-Content-Type: text/markdown; charset=UTF-8; variant=GFM +Project-URL: Issues, https://github.com/huggingface/hf_transfer/issues +Project-URL: Repository, https://github.com/huggingface/hf_transfer.git + +# HF Transfer + +Speed up file transfers with the Hub. + +# DISCLAIMER + +This library is a power user tool, to go beyond `~500MB/s` on very high bandwidth +network, where Python cannot cap out the available bandwidth. + +This is *not* meant to be a general usability tool. +It purposefully lacks progressbars and comes generally as-is. + +Please file issues *only* if there's an issue on the underlying downloaded file. + +## Contributing + +```sh +python3 -m venv ~/.venv/hf_transfer +source ~/.venv/hf_transfer/bin/activate +pip install maturin +maturin develop +``` + +### `huggingface_hub` + +If you are working on changes with `huggingface_hub` + +```sh +git clone git@github.com:huggingface/huggingface_hub.git +# git clone https://github.com/huggingface/huggingface_hub.git + +cd huggingface_hub +python3 -m pip install -e ".[quality]" +``` + +You can use the following test script: + +```py +import os + +# os.environ["HF_ENDPOINT"] = "http://localhost:5564" +os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "1" + +from huggingface_hub import HfApi, logging + +logging.set_verbosity_debug() +hf = HfApi() +hf.upload_file(path_or_fileobj="/path/to/my/repo/some_file", path_in_repo="some_file", repo_id="my/repo", repo_type="model") +``` + + diff --git a/hf_transfer-0.1.9.dist-info/RECORD b/hf_transfer-0.1.9.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..baca72f3c596587a2f05ce79bc7d5bbf2e41d920 --- /dev/null +++ b/hf_transfer-0.1.9.dist-info/RECORD @@ -0,0 +1,8 @@ +hf_transfer-0.1.9.dist-info/INSTALLER,sha256=5hhM4Q4mYTT9z6QB6PGpUAW81PGNFrYrdXMj4oM_6ak,2 +hf_transfer-0.1.9.dist-info/METADATA,sha256=cISfuZ8iKrpsZCWkxI-IFRcC3htDBOCMXXT-liJ9FJA,1747 +hf_transfer-0.1.9.dist-info/RECORD,, +hf_transfer-0.1.9.dist-info/REQUESTED,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0 +hf_transfer-0.1.9.dist-info/WHEEL,sha256=473T-iBDPc6DHc-9q66Gpnn0HSHmHhv_27uSTUVy86w,127 +hf_transfer-0.1.9.dist-info/licenses/LICENSE,sha256=8dFfk5jBdKElwqtcWTyhfvBqN7VD_-J4bwXLJC-rszk,11346 +hf_transfer/__init__.py,sha256=0OjYn5WBWp_eK3hJKyYtyMWxAStjTCTRjSh_eXoOldE,127 +hf_transfer/hf_transfer.abi3.so,sha256=ZQGGGzyeqivKo3-kIKYQQ7m-wW0WILRHX8AW-Q3x1bU,9653960 diff --git a/hf_transfer-0.1.9.dist-info/REQUESTED b/hf_transfer-0.1.9.dist-info/REQUESTED new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/hf_transfer-0.1.9.dist-info/WHEEL b/hf_transfer-0.1.9.dist-info/WHEEL new file mode 100644 index 0000000000000000000000000000000000000000..4a2f9abc544203bc4e582b0d692e0ddbf94eed91 --- /dev/null +++ b/hf_transfer-0.1.9.dist-info/WHEEL @@ -0,0 +1,4 @@ +Wheel-Version: 1.0 +Generator: maturin (1.8.1) +Root-Is-Purelib: false +Tag: cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64 diff --git a/hf_transfer/__init__.py b/hf_transfer/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..ec78d8378ffa59f297d250095503af8f11a6f0db --- /dev/null +++ b/hf_transfer/__init__.py @@ -0,0 +1,5 @@ +from .hf_transfer import * + +__doc__ = hf_transfer.__doc__ +if hasattr(hf_transfer, "__all__"): + __all__ = hf_transfer.__all__ \ No newline at end of file diff --git a/huggingface_hub-1.7.1.dist-info/METADATA b/huggingface_hub-1.7.1.dist-info/METADATA new file mode 100644 index 0000000000000000000000000000000000000000..9499c22e8bbb6208f272402eeea59c729e8ffc17 --- /dev/null +++ b/huggingface_hub-1.7.1.dist-info/METADATA @@ -0,0 +1,322 @@ +Metadata-Version: 2.4 +Name: huggingface_hub +Version: 1.7.1 +Summary: Client library to download and publish models, datasets and other repos on the huggingface.co hub +Home-page: https://github.com/huggingface/huggingface_hub +Author: Hugging Face, Inc. +Author-email: julien@huggingface.co +License: Apache-2.0 +Keywords: model-hub machine-learning models natural-language-processing deep-learning pytorch pretrained-models +Classifier: Intended Audience :: Developers +Classifier: Intended Audience :: Education +Classifier: Intended Audience :: Science/Research +Classifier: License :: OSI Approved :: Apache Software License +Classifier: Operating System :: OS Independent +Classifier: Programming Language :: Python :: 3 +Classifier: Programming Language :: Python :: 3 :: Only +Classifier: Programming Language :: Python :: 3.9 +Classifier: Programming Language :: Python :: 3.10 +Classifier: Programming Language :: Python :: 3.11 +Classifier: Programming Language :: Python :: 3.12 +Classifier: Programming Language :: Python :: 3.13 +Classifier: Programming Language :: Python :: 3.14 +Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence +Requires-Python: >=3.9.0 +Description-Content-Type: text/markdown +License-File: LICENSE +Requires-Dist: filelock>=3.10.0 +Requires-Dist: fsspec>=2023.5.0 +Requires-Dist: hf-xet<2.0.0,>=1.4.2; 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extra == "dev" +Dynamic: author +Dynamic: author-email +Dynamic: classifier +Dynamic: description +Dynamic: description-content-type +Dynamic: home-page +Dynamic: keywords +Dynamic: license +Dynamic: license-file +Dynamic: provides-extra +Dynamic: requires-dist +Dynamic: requires-python +Dynamic: summary + +

+ + + + huggingface_hub library logo + +
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+ +

+ The official Python client for the Huggingface Hub. +

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+ +--- + +**Documentation**: https://hf.co/docs/huggingface_hub + +**Source Code**: https://github.com/huggingface/huggingface_hub + +--- + +## Welcome to the huggingface_hub library + +The `huggingface_hub` library allows you to interact with the [Hugging Face Hub](https://huggingface.co/), a platform democratizing open-source Machine Learning for creators and collaborators. Discover pre-trained models and datasets for your projects or play with the thousands of machine learning apps hosted on the Hub. You can also create and share your own models, datasets and demos with the community. The `huggingface_hub` library provides a simple way to do all these things with Python. + +## Key features + +- [Download files](https://huggingface.co/docs/huggingface_hub/en/guides/download) from the Hub. +- [Upload files](https://huggingface.co/docs/huggingface_hub/en/guides/upload) to the Hub. +- [Manage your repositories](https://huggingface.co/docs/huggingface_hub/en/guides/repository). +- [Run Inference](https://huggingface.co/docs/huggingface_hub/en/guides/inference) on deployed models. +- [Search](https://huggingface.co/docs/huggingface_hub/en/guides/search) for models, datasets and Spaces. +- [Share Model Cards](https://huggingface.co/docs/huggingface_hub/en/guides/model-cards) to document your models. +- [Engage with the community](https://huggingface.co/docs/huggingface_hub/en/guides/community) through PRs and comments. + +## Installation + +Install the `huggingface_hub` package with [pip](https://pypi.org/project/huggingface-hub/): + +```bash +pip install huggingface_hub +``` + +If you prefer, you can also install it with [conda](https://huggingface.co/docs/huggingface_hub/en/installation#install-with-conda). + +In order to keep the package minimal by default, `huggingface_hub` comes with optional dependencies useful for some use cases. For example, if you want to use the MCP module, run: + +```bash +pip install "huggingface_hub[mcp]" +``` + +To learn more installation and optional dependencies, check out the [installation guide](https://huggingface.co/docs/huggingface_hub/en/installation). + +## Quick start + +### Download files + +Download a single file + +```py +from huggingface_hub import hf_hub_download + +hf_hub_download(repo_id="tiiuae/falcon-7b-instruct", filename="config.json") +``` + +Or an entire repository + +```py +from huggingface_hub import snapshot_download + +snapshot_download("stabilityai/stable-diffusion-2-1") +``` + +Files will be downloaded in a local cache folder. More details in [this guide](https://huggingface.co/docs/huggingface_hub/en/guides/manage-cache). + +### Login + +The Hugging Face Hub uses tokens to authenticate applications (see [docs](https://huggingface.co/docs/hub/security-tokens)). To log in your machine, run the following CLI: + +```bash +hf auth login +# or using an environment variable +hf auth login --token $HUGGINGFACE_TOKEN +``` + +### Create a repository + +```py +from huggingface_hub import create_repo + +create_repo(repo_id="super-cool-model") +``` + +### Upload files + +Upload a single file + +```py +from huggingface_hub import upload_file + +upload_file( + path_or_fileobj="/home/lysandre/dummy-test/README.md", + path_in_repo="README.md", + repo_id="lysandre/test-model", +) +``` + +Or an entire folder + +```py +from huggingface_hub import upload_folder + +upload_folder( + folder_path="/path/to/local/space", + repo_id="username/my-cool-space", + repo_type="space", +) +``` + +For details in the [upload guide](https://huggingface.co/docs/huggingface_hub/en/guides/upload). + +## Integrating to the Hub. + +We're partnering with cool open source ML libraries to provide free model hosting and versioning. You can find the existing integrations [here](https://huggingface.co/docs/hub/libraries). + +The advantages are: + +- Free model or dataset hosting for libraries and their users. +- Built-in file versioning, even with very large files, thanks to a git-based approach. +- In-browser widgets to play with the uploaded models. +- Anyone can upload a new model for your library, they just need to add the corresponding tag for the model to be discoverable. +- Fast downloads! We use Cloudfront (a CDN) to geo-replicate downloads so they're blazing fast from anywhere on the globe. +- Usage stats and more features to come. + +If you would like to integrate your library, feel free to open an issue to begin the discussion. We wrote a [step-by-step guide](https://huggingface.co/docs/hub/adding-a-library) with ❤️ showing how to do this integration. + +## Contributions (feature requests, bugs, etc.) are super welcome 💙💚💛💜🧡❤️ + +Everyone is welcome to contribute, and we value everybody's contribution. Code is not the only way to help the community. +Answering questions, helping others, reaching out and improving the documentations are immensely valuable to the community. +We wrote a [contribution guide](https://github.com/huggingface/huggingface_hub/blob/main/CONTRIBUTING.md) to summarize +how to get started to contribute to this repository. diff --git a/joblib-1.5.3.dist-info/INSTALLER b/joblib-1.5.3.dist-info/INSTALLER new file mode 100644 index 0000000000000000000000000000000000000000..5c69047b2eb8235994febeeae1da4a82365a240a --- /dev/null +++ b/joblib-1.5.3.dist-info/INSTALLER @@ -0,0 +1 @@ +uv \ No newline at end of file diff --git a/joblib-1.5.3.dist-info/METADATA b/joblib-1.5.3.dist-info/METADATA new file mode 100644 index 0000000000000000000000000000000000000000..070cab5406c516a471462e445a2af0f0d99470da --- /dev/null +++ b/joblib-1.5.3.dist-info/METADATA @@ -0,0 +1,172 @@ +Metadata-Version: 2.4 +Name: joblib +Version: 1.5.3 +Summary: Lightweight pipelining with Python functions +Author-email: Gael Varoquaux +License-Expression: BSD-3-Clause +Project-URL: Homepage, https://joblib.readthedocs.io +Project-URL: Source, https://github.com/joblib/joblib +Platform: any +Classifier: Development Status :: 5 - Production/Stable +Classifier: Environment :: Console +Classifier: Intended Audience :: Developers +Classifier: Intended Audience :: Science/Research +Classifier: Intended Audience :: Education +Classifier: Operating System :: OS Independent +Classifier: Programming Language :: Python :: 3 +Classifier: Programming Language :: Python :: 3.9 +Classifier: Programming Language :: Python :: 3.10 +Classifier: Programming Language :: Python :: 3.11 +Classifier: Programming Language :: Python :: 3.12 +Classifier: Programming Language :: Python :: 3.13 +Classifier: Topic :: Scientific/Engineering +Classifier: Topic :: Utilities +Classifier: Topic :: Software Development :: Libraries +Requires-Python: >=3.9 +Description-Content-Type: text/x-rst +License-File: LICENSE.txt +Dynamic: license-file + +|PyPi| |CIStatus| |ReadTheDocs| |Codecov| + +.. |PyPi| image:: https://badge.fury.io/py/joblib.svg + :target: https://badge.fury.io/py/joblib + :alt: Joblib version + +.. |CIStatus| image:: https://github.com/joblib/joblib/actions/workflows/test.yml/badge.svg + :target: https://github.com/joblib/joblib/actions/workflows/test.yml?query=branch%3Amain + :alt: CI status + +.. |ReadTheDocs| image:: https://readthedocs.org/projects/joblib/badge/?version=latest + :target: https://joblib.readthedocs.io/en/latest/?badge=latest + :alt: Documentation Status + +.. |Codecov| image:: https://codecov.io/gh/joblib/joblib/branch/main/graph/badge.svg + :target: https://codecov.io/gh/joblib/joblib + :alt: Codecov coverage + + +The homepage of joblib with user documentation is located on: + +https://joblib.readthedocs.io + +Getting the latest code +======================= + +To get the latest code using git, simply type:: + + git clone https://github.com/joblib/joblib.git + +If you don't have git installed, you can download a zip +of the latest code: https://github.com/joblib/joblib/archive/refs/heads/main.zip + +Installing +========== + +You can use `pip` to install joblib from any directory:: + + pip install joblib + +or install it in editable mode from the source directory:: + + pip install -e . + +Dependencies +============ + +- Joblib has no mandatory dependencies besides Python (supported versions are + 3.9+). +- Joblib has an optional dependency on Numpy (at least version 1.6.1) for array + manipulation. +- Joblib includes its own vendored copy of + `loky `_ for process management. +- Joblib can efficiently dump and load numpy arrays but does not require numpy + to be installed. +- Joblib has an optional dependency on + `python-lz4 `_ as a faster alternative to + zlib and gzip for compressed serialization. +- Joblib has an optional dependency on psutil to mitigate memory leaks in + parallel worker processes. +- Some examples require external dependencies such as pandas. See the + instructions in the `Building the docs`_ section for details. + +Workflow to contribute +====================== + +To contribute to joblib, first create an account on `github +`_. Once this is done, fork the `joblib repository +`_ to have your own repository, +clone it using ``git clone``. Make your changes in a branch of your clone, push +them to your github account, test them locally, and when you are happy with +them, send a pull request to the main repository. + +You can use `pre-commit `_ to run code style checks +before each commit:: + + pip install pre-commit + pre-commit install + +pre-commit checks can be disabled for a single commit with:: + + git commit -n + +Running the test suite +====================== + +To run the test suite, you need the pytest (version >= 3) and coverage modules. +Run the test suite using:: + + pytest joblib + +from the root of the project. + +Building the docs +================= + +To build the docs you need to have sphinx (>=1.4) and some dependencies +installed:: + + pip install -U -r .readthedocs-requirements.txt + +The docs can then be built with the following command:: + + make doc + +The html docs are located in the ``doc/_build/html`` directory. + + +Making a source tarball +======================= + +To create a source tarball, eg for packaging or distributing, run the +following command:: + + pip install build + python -m build --sdist + +The tarball will be created in the `dist` directory. This command will create +the resulting tarball that can be installed with no extra dependencies than the +Python standard library. + +Making a release and uploading it to PyPI +========================================= + +This command is only run by project manager, to make a release, and +upload in to PyPI:: + + pip install build + python -m build --sdist --wheel + twine upload dist/* + + +Note that the documentation should automatically get updated at each git +push. If that is not the case, try building th doc locally and resolve +any doc build error (in particular when running the examples). + +Updating the changelog +====================== + +Changes are listed in the CHANGES.rst file. They must be manually updated +but, the following git command may be used to generate the lines:: + + git log --abbrev-commit --date=short --no-merges --sparse diff --git a/joblib-1.5.3.dist-info/RECORD b/joblib-1.5.3.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..14c54f6f7b2893791e8b5fb0dbf2c8c0470ec8ea --- /dev/null +++ b/joblib-1.5.3.dist-info/RECORD @@ -0,0 +1,145 @@ +joblib-1.5.3.dist-info/INSTALLER,sha256=5hhM4Q4mYTT9z6QB6PGpUAW81PGNFrYrdXMj4oM_6ak,2 +joblib-1.5.3.dist-info/METADATA,sha256=zunGCJauTnqWWoQPveUNER0vgBj2EgHR7S6fw91Ig-Y,5542 +joblib-1.5.3.dist-info/RECORD,, +joblib-1.5.3.dist-info/REQUESTED,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0 +joblib-1.5.3.dist-info/WHEEL,sha256=_zCd3N1l69ArxyTb8rzEoP9TpbYXkqRFSNOD5OuxnTs,91 +joblib-1.5.3.dist-info/licenses/LICENSE.txt,sha256=QmEpEcGHLF5LQ_auDo7llGfNNQMyJBz3LOkGQCZPrmo,1527 +joblib-1.5.3.dist-info/top_level.txt,sha256=P0LsoZ45gBL7ckL4lqQt7tdbrHD4xlVYhffmhHeeT_U,7 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a/joblib-1.5.3.dist-info/REQUESTED b/joblib-1.5.3.dist-info/REQUESTED new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/joblib-1.5.3.dist-info/WHEEL b/joblib-1.5.3.dist-info/WHEEL new file mode 100644 index 0000000000000000000000000000000000000000..e7fa31b6f3f78deb1022c1f7927f07d4d16da822 --- /dev/null +++ b/joblib-1.5.3.dist-info/WHEEL @@ -0,0 +1,5 @@ +Wheel-Version: 1.0 +Generator: setuptools (80.9.0) +Root-Is-Purelib: true +Tag: py3-none-any + diff --git a/joblib-1.5.3.dist-info/top_level.txt b/joblib-1.5.3.dist-info/top_level.txt new file mode 100644 index 0000000000000000000000000000000000000000..ca4af27e2b6e9917d9600060588a18cc9e3cc78c --- /dev/null +++ b/joblib-1.5.3.dist-info/top_level.txt @@ -0,0 +1 @@ +joblib diff --git a/joblib/_memmapping_reducer.py b/joblib/_memmapping_reducer.py new file mode 100644 index 0000000000000000000000000000000000000000..d11ec581de8d997162397c92690ef080ace2bb33 --- /dev/null +++ b/joblib/_memmapping_reducer.py @@ -0,0 +1,715 @@ +""" +Reducer using memory mapping for numpy arrays +""" +# Author: Thomas Moreau +# Copyright: 2017, Thomas Moreau +# License: BSD 3 clause + +import atexit +import errno +import os +import stat +import tempfile +import threading +import time +import warnings +import weakref +from mmap import mmap +from multiprocessing import util +from pickle import HIGHEST_PROTOCOL, PicklingError, dumps, loads, whichmodule +from uuid import uuid4 + +try: + WindowsError +except NameError: + WindowsError = type(None) + +try: + import numpy as np + from numpy.lib.stride_tricks import as_strided +except ImportError: + np = None + +from .backports import make_memmap +from .disk import delete_folder +from .externals.loky.backend import resource_tracker +from .numpy_pickle import dump, load, load_temporary_memmap + +# Some system have a ramdisk mounted by default, we can use it instead of /tmp +# as the default folder to dump big arrays to share with subprocesses. +SYSTEM_SHARED_MEM_FS = "/dev/shm" + +# Minimal number of bytes available on SYSTEM_SHARED_MEM_FS to consider using +# it as the default folder to dump big arrays to share with subprocesses. +SYSTEM_SHARED_MEM_FS_MIN_SIZE = int(2e9) + +# Folder and file permissions to chmod temporary files generated by the +# memmapping pool. Only the owner of the Python process can access the +# temporary files and folder. +FOLDER_PERMISSIONS = stat.S_IRUSR | stat.S_IWUSR | stat.S_IXUSR +FILE_PERMISSIONS = stat.S_IRUSR | stat.S_IWUSR + +# Set used in joblib workers, referencing the filenames of temporary memmaps +# created by joblib to speed up data communication. In child processes, we add +# a finalizer to these memmaps that sends a maybe_unlink call to the +# resource_tracker, in order to free main memory as fast as possible. +JOBLIB_MMAPS = set() + + +def _log_and_unlink(filename): + from .externals.loky.backend.resource_tracker import _resource_tracker + + util.debug( + "[FINALIZER CALL] object mapping to {} about to be deleted," + " decrementing the refcount of the file (pid: {})".format( + os.path.basename(filename), os.getpid() + ) + ) + _resource_tracker.maybe_unlink(filename, "file") + + +def add_maybe_unlink_finalizer(memmap): + util.debug( + "[FINALIZER ADD] adding finalizer to {} (id {}, filename {}, pid {})".format( + type(memmap), id(memmap), os.path.basename(memmap.filename), os.getpid() + ) + ) + weakref.finalize(memmap, _log_and_unlink, memmap.filename) + + +def unlink_file(filename): + """Wrapper around os.unlink with a retry mechanism. + + The retry mechanism has been implemented primarily to overcome a race + condition happening during the finalizer of a np.memmap: when a process + holding the last reference to a mmap-backed np.memmap/np.array is about to + delete this array (and close the reference), it sends a maybe_unlink + request to the resource_tracker. This request can be processed faster than + it takes for the last reference of the memmap to be closed, yielding (on + Windows) a PermissionError in the resource_tracker loop. + """ + NUM_RETRIES = 10 + for retry_no in range(1, NUM_RETRIES + 1): + try: + os.unlink(filename) + break + except PermissionError: + util.debug( + "[ResourceTracker] tried to unlink {}, got PermissionError".format( + filename + ) + ) + if retry_no == NUM_RETRIES: + raise + else: + time.sleep(0.2) + except FileNotFoundError: + # In case of a race condition when deleting the temporary folder, + # avoid noisy FileNotFoundError exception in the resource tracker. + pass + + +resource_tracker._CLEANUP_FUNCS["file"] = unlink_file + + +class _WeakArrayKeyMap: + """A variant of weakref.WeakKeyDictionary for unhashable numpy arrays. + + This datastructure will be used with numpy arrays as obj keys, therefore we + do not use the __get__ / __set__ methods to avoid any conflict with the + numpy fancy indexing syntax. + """ + + def __init__(self): + self._data = {} + + def get(self, obj): + ref, val = self._data[id(obj)] + if ref() is not obj: + # In case of race condition with on_destroy: could never be + # triggered by the joblib tests with CPython. + raise KeyError(obj) + return val + + def set(self, obj, value): + key = id(obj) + try: + ref, _ = self._data[key] + if ref() is not obj: + # In case of race condition with on_destroy: could never be + # triggered by the joblib tests with CPython. + raise KeyError(obj) + except KeyError: + # Insert the new entry in the mapping along with a weakref + # callback to automatically delete the entry from the mapping + # as soon as the object used as key is garbage collected. + def on_destroy(_): + del self._data[key] + + ref = weakref.ref(obj, on_destroy) + self._data[key] = ref, value + + def __getstate__(self): + raise PicklingError("_WeakArrayKeyMap is not pickleable") + + +############################################################################### +# Support for efficient transient pickling of numpy data structures + + +def _get_backing_memmap(a): + """Recursively look up the original np.memmap instance base if any.""" + b = getattr(a, "base", None) + if b is None: + # TODO: check scipy sparse datastructure if scipy is installed + # a nor its descendants do not have a memmap base + return None + + elif isinstance(b, mmap): + # a is already a real memmap instance. + return a + + else: + # Recursive exploration of the base ancestry + return _get_backing_memmap(b) + + +def _get_temp_dir(pool_folder_name, temp_folder=None): + """Get the full path to a subfolder inside the temporary folder. + + Parameters + ---------- + pool_folder_name : str + Sub-folder name used for the serialization of a pool instance. + + temp_folder: str, optional + Folder to be used by the pool for memmapping large arrays + for sharing memory with worker processes. If None, this will try in + order: + + - a folder pointed by the JOBLIB_TEMP_FOLDER environment + variable, + - /dev/shm if the folder exists and is writable: this is a + RAMdisk filesystem available by default on modern Linux + distributions, + - the default system temporary folder that can be + overridden with TMP, TMPDIR or TEMP environment + variables, typically /tmp under Unix operating systems. + + Returns + ------- + pool_folder : str + full path to the temporary folder + use_shared_mem : bool + whether the temporary folder is written to the system shared memory + folder or some other temporary folder. + """ + use_shared_mem = False + if temp_folder is None: + temp_folder = os.environ.get("JOBLIB_TEMP_FOLDER", None) + if temp_folder is None: + if os.path.exists(SYSTEM_SHARED_MEM_FS) and hasattr(os, "statvfs"): + try: + shm_stats = os.statvfs(SYSTEM_SHARED_MEM_FS) + available_nbytes = shm_stats.f_bsize * shm_stats.f_bavail + if available_nbytes > SYSTEM_SHARED_MEM_FS_MIN_SIZE: + # Try to see if we have write access to the shared mem + # folder only if it is reasonably large (that is 2GB or + # more). + temp_folder = SYSTEM_SHARED_MEM_FS + pool_folder = os.path.join(temp_folder, pool_folder_name) + if not os.path.exists(pool_folder): + os.makedirs(pool_folder) + use_shared_mem = True + except (IOError, OSError): + # Missing rights in the /dev/shm partition, fallback to regular + # temp folder. + temp_folder = None + if temp_folder is None: + # Fallback to the default tmp folder, typically /tmp + temp_folder = tempfile.gettempdir() + temp_folder = os.path.abspath(os.path.expanduser(temp_folder)) + pool_folder = os.path.join(temp_folder, pool_folder_name) + return pool_folder, use_shared_mem + + +def has_shareable_memory(a): + """Return True if a is backed by some mmap buffer directly or not.""" + return _get_backing_memmap(a) is not None + + +def _strided_from_memmap( + filename, + dtype, + mode, + offset, + order, + shape, + strides, + total_buffer_len, + unlink_on_gc_collect, +): + """Reconstruct an array view on a memory mapped file.""" + if mode == "w+": + # Do not zero the original data when unpickling + mode = "r+" + + if strides is None: + # Simple, contiguous memmap + return make_memmap( + filename, + dtype=dtype, + shape=shape, + mode=mode, + offset=offset, + order=order, + unlink_on_gc_collect=unlink_on_gc_collect, + ) + else: + # For non-contiguous data, memmap the total enclosing buffer and then + # extract the non-contiguous view with the stride-tricks API + base = make_memmap( + filename, + dtype=dtype, + shape=total_buffer_len, + offset=offset, + mode=mode, + order=order, + unlink_on_gc_collect=unlink_on_gc_collect, + ) + return as_strided(base, shape=shape, strides=strides) + + +def _reduce_memmap_backed(a, m): + """Pickling reduction for memmap backed arrays. + + a is expected to be an instance of np.ndarray (or np.memmap) + m is expected to be an instance of np.memmap on the top of the ``base`` + attribute ancestry of a. ``m.base`` should be the real python mmap object. + """ + # offset that comes from the striding differences between a and m + util.debug( + "[MEMMAP REDUCE] reducing a memmap-backed array (shape, {}, pid: {})".format( + a.shape, os.getpid() + ) + ) + try: + from numpy.lib.array_utils import byte_bounds + except (ModuleNotFoundError, ImportError): + # Backward-compat for numpy < 2.0 + from numpy import byte_bounds + a_start, a_end = byte_bounds(a) + m_start = byte_bounds(m)[0] + offset = a_start - m_start + + # offset from the backing memmap + offset += m.offset + + # 1D arrays are both F and C contiguous, so only set the flag in + # higher dimensions. See https://github.com/joblib/joblib/pull/1704. + if m.ndim > 1 and m.flags["F_CONTIGUOUS"]: + order = "F" + else: + # The backing memmap buffer is necessarily contiguous hence C if not + # Fortran + order = "C" + + if a.flags["F_CONTIGUOUS"] or a.flags["C_CONTIGUOUS"]: + # If the array is a contiguous view, no need to pass the strides + strides = None + total_buffer_len = None + else: + # Compute the total number of items to map from which the strided + # view will be extracted. + strides = a.strides + total_buffer_len = (a_end - a_start) // a.itemsize + + return ( + _strided_from_memmap, + ( + m.filename, + a.dtype, + m.mode, + offset, + order, + a.shape, + strides, + total_buffer_len, + False, + ), + ) + + +def reduce_array_memmap_backward(a): + """reduce a np.array or a np.memmap from a child process""" + m = _get_backing_memmap(a) + if isinstance(m, np.memmap) and m.filename not in JOBLIB_MMAPS: + # if a is backed by a memmaped file, reconstruct a using the + # memmaped file. + return _reduce_memmap_backed(a, m) + else: + # a is either a regular (not memmap-backed) numpy array, or an array + # backed by a shared temporary file created by joblib. In the latter + # case, in order to limit the lifespan of these temporary files, we + # serialize the memmap as a regular numpy array, and decref the + # file backing the memmap (done implicitly in a previously registered + # finalizer, see ``unlink_on_gc_collect`` for more details) + return (loads, (dumps(np.asarray(a), protocol=HIGHEST_PROTOCOL),)) + + +class ArrayMemmapForwardReducer(object): + """Reducer callable to dump large arrays to memmap files. + + Parameters + ---------- + max_nbytes: int + Threshold to trigger memmapping of large arrays to files created + a folder. + temp_folder_resolver: callable + An callable in charge of resolving a temporary folder name where files + for backing memmapped arrays are created. + mmap_mode: 'r', 'r+' or 'c' + Mode for the created memmap datastructure. See the documentation of + numpy.memmap for more details. Note: 'w+' is coerced to 'r+' + automatically to avoid zeroing the data on unpickling. + verbose: int, optional, 0 by default + If verbose > 0, memmap creations are logged. + If verbose > 1, both memmap creations, reuse and array pickling are + logged. + prewarm: bool, optional, False by default. + Force a read on newly memmapped array to make sure that OS pre-cache it + memory. This can be useful to avoid concurrent disk access when the + same data array is passed to different worker processes. + """ + + def __init__( + self, + max_nbytes, + temp_folder_resolver, + mmap_mode, + unlink_on_gc_collect, + verbose=0, + prewarm=True, + ): + self._max_nbytes = max_nbytes + self._temp_folder_resolver = temp_folder_resolver + self._mmap_mode = mmap_mode + self.verbose = int(verbose) + if prewarm == "auto": + self._prewarm = not self._temp_folder.startswith(SYSTEM_SHARED_MEM_FS) + else: + self._prewarm = prewarm + self._prewarm = prewarm + self._memmaped_arrays = _WeakArrayKeyMap() + self._temporary_memmaped_filenames = set() + self._unlink_on_gc_collect = unlink_on_gc_collect + + @property + def _temp_folder(self): + return self._temp_folder_resolver() + + def __reduce__(self): + # The ArrayMemmapForwardReducer is passed to the children processes: it + # needs to be pickled but the _WeakArrayKeyMap need to be skipped as + # it's only guaranteed to be consistent with the parent process memory + # garbage collection. + # Although this reducer is pickled, it is not needed in its destination + # process (child processes), as we only use this reducer to send + # memmaps from the parent process to the children processes. For this + # reason, we can afford skipping the resolver, (which would otherwise + # be unpicklable), and pass it as None instead. + args = (self._max_nbytes, None, self._mmap_mode, self._unlink_on_gc_collect) + kwargs = { + "verbose": self.verbose, + "prewarm": self._prewarm, + } + return ArrayMemmapForwardReducer, args, kwargs + + def __call__(self, a): + m = _get_backing_memmap(a) + if m is not None and isinstance(m, np.memmap): + # a is already backed by a memmap file, let's reuse it directly + return _reduce_memmap_backed(a, m) + + if ( + not a.dtype.hasobject + and self._max_nbytes is not None + and a.nbytes > self._max_nbytes + ): + # check that the folder exists (lazily create the pool temp folder + # if required) + try: + os.makedirs(self._temp_folder) + os.chmod(self._temp_folder, FOLDER_PERMISSIONS) + except OSError as e: + if e.errno != errno.EEXIST: + raise e + + try: + basename = self._memmaped_arrays.get(a) + except KeyError: + # Generate a new unique random filename. The process and thread + # ids are only useful for debugging purpose and to make it + # easier to cleanup orphaned files in case of hard process + # kill (e.g. by "kill -9" or segfault). + basename = "{}-{}-{}.pkl".format( + os.getpid(), id(threading.current_thread()), uuid4().hex + ) + self._memmaped_arrays.set(a, basename) + filename = os.path.join(self._temp_folder, basename) + + # In case the same array with the same content is passed several + # times to the pool subprocess children, serialize it only once + + is_new_memmap = filename not in self._temporary_memmaped_filenames + + # add the memmap to the list of temporary memmaps created by joblib + self._temporary_memmaped_filenames.add(filename) + + if self._unlink_on_gc_collect: + # Bump reference count of the memmap by 1 to account for + # shared usage of the memmap by a child process. The + # corresponding decref call will be executed upon calling + # resource_tracker.maybe_unlink, registered as a finalizer in + # the child. + # the incref/decref calls here are only possible when the child + # and the parent share the same resource_tracker. It is not the + # case for the multiprocessing backend, but it does not matter + # because unlinking a memmap from a child process is only + # useful to control the memory usage of long-lasting child + # processes, while the multiprocessing-based pools terminate + # their workers at the end of a map() call. + resource_tracker.register(filename, "file") + + if is_new_memmap: + # Incref each temporary memmap created by joblib one extra + # time. This means that these memmaps will only be deleted + # once an extra maybe_unlink() is called, which is done once + # all the jobs have completed (or been canceled) in the + # Parallel._terminate_backend() method. + resource_tracker.register(filename, "file") + + if not os.path.exists(filename): + util.debug( + "[ARRAY DUMP] Pickling new array (shape={}, dtype={}) " + "creating a new memmap at {}".format(a.shape, a.dtype, filename) + ) + for dumped_filename in dump(a, filename): + os.chmod(dumped_filename, FILE_PERMISSIONS) + + if self._prewarm: + # Warm up the data by accessing it. This operation ensures + # that the disk access required to create the memmapping + # file are performed in the reducing process and avoids + # concurrent memmap creation in multiple children + # processes. + load(filename, mmap_mode=self._mmap_mode).max() + + else: + util.debug( + "[ARRAY DUMP] Pickling known array (shape={}, dtype={}) " + "reusing memmap file: {}".format( + a.shape, a.dtype, os.path.basename(filename) + ) + ) + + # The worker process will use joblib.load to memmap the data + return ( + load_temporary_memmap, + (filename, self._mmap_mode, self._unlink_on_gc_collect), + ) + else: + # do not convert a into memmap, let pickler do its usual copy with + # the default system pickler + util.debug( + "[ARRAY DUMP] Pickling array (NO MEMMAPPING) (shape={}, " + " dtype={}).".format(a.shape, a.dtype) + ) + return (loads, (dumps(a, protocol=HIGHEST_PROTOCOL),)) + + +def get_memmapping_reducers( + forward_reducers=None, + backward_reducers=None, + temp_folder_resolver=None, + max_nbytes=1e6, + mmap_mode="r", + verbose=0, + prewarm=False, + unlink_on_gc_collect=True, + **kwargs, +): + """Construct a pair of memmapping reducer linked to a tmpdir. + + This function manage the creation and the clean up of the temporary folders + underlying the memory maps and should be use to get the reducers necessary + to construct joblib pool or executor. + """ + if forward_reducers is None: + forward_reducers = dict() + if backward_reducers is None: + backward_reducers = dict() + + if np is not None: + # Register smart numpy.ndarray reducers that detects memmap backed + # arrays and that is also able to dump to memmap large in-memory + # arrays over the max_nbytes threshold + forward_reduce_ndarray = ArrayMemmapForwardReducer( + max_nbytes, + temp_folder_resolver, + mmap_mode, + unlink_on_gc_collect, + verbose, + prewarm=prewarm, + ) + forward_reducers[np.ndarray] = forward_reduce_ndarray + forward_reducers[np.memmap] = forward_reduce_ndarray + + # Communication from child process to the parent process always + # pickles in-memory numpy.ndarray without dumping them as memmap + # to avoid confusing the caller and make it tricky to collect the + # temporary folder + backward_reducers[np.ndarray] = reduce_array_memmap_backward + backward_reducers[np.memmap] = reduce_array_memmap_backward + + return forward_reducers, backward_reducers + + +class TemporaryResourcesManager(object): + """Stateful object able to manage temporary folder and pickles + + It exposes: + - a per-context folder name resolving API that memmap-based reducers will + rely on to know where to pickle the temporary memmaps + - a temporary file/folder management API that internally uses the + resource_tracker. + """ + + def __init__(self, temp_folder_root=None, context_id=None): + self._current_temp_folder = None + self._temp_folder_root = temp_folder_root + self._use_shared_mem = None + self._cached_temp_folders = dict() + self._id = uuid4().hex + self._finalizers = {} + if context_id is None: + # It would be safer to not assign a default context id (less silent + # bugs), but doing this while maintaining backward compatibility + # with the previous, context-unaware version get_memmaping_executor + # exposes too many low-level details. + context_id = uuid4().hex + self.set_current_context(context_id) + + def set_current_context(self, context_id): + self._current_context_id = context_id + self.register_new_context(context_id) + + def register_new_context(self, context_id): + # Prepare a sub-folder name specific to a context (usually a unique id + # generated by each instance of the Parallel class). Do not create in + # advance to spare FS write access if no array is to be dumped). + if context_id in self._cached_temp_folders: + return + else: + # During its lifecycle, one Parallel object can have several + # executors associated to it (for instance, if a loky worker raises + # an exception, joblib shutdowns the executor and instantly + # recreates a new one before raising the error - see + # ``ensure_ready``. Because we don't want two executors tied to + # the same Parallel object (and thus the same context id) to + # register/use/delete the same folder, we also add an id specific + # to the current Manager (and thus specific to its associated + # executor) to the folder name. + new_folder_name = "joblib_memmapping_folder_{}_{}_{}".format( + os.getpid(), self._id, context_id + ) + new_folder_path, _ = _get_temp_dir(new_folder_name, self._temp_folder_root) + self.register_folder_finalizer(new_folder_path, context_id) + self._cached_temp_folders[context_id] = new_folder_path + + def resolve_temp_folder_name(self): + """Return a folder name specific to the currently activated context""" + return self._cached_temp_folders[self._current_context_id] + + # resource management API + + def register_folder_finalizer(self, pool_subfolder, context_id): + # Register the garbage collector at program exit in case caller forgets + # to call terminate explicitly: note we do not pass any reference to + # ensure that this callback won't prevent garbage collection of + # parallel instance and related file handler resources such as POSIX + # semaphores and pipes + pool_module_name = whichmodule(delete_folder, "delete_folder") + resource_tracker.register(pool_subfolder, "folder") + + def _cleanup(): + # In some cases the Python runtime seems to set delete_folder to + # None just before exiting when accessing the delete_folder + # function from the closure namespace. So instead we reimport + # the delete_folder function explicitly. + # https://github.com/joblib/joblib/issues/328 + # We cannot just use from 'joblib.pool import delete_folder' + # because joblib should only use relative imports to allow + # easy vendoring. + delete_folder = __import__( + pool_module_name, fromlist=["delete_folder"] + ).delete_folder + try: + delete_folder(pool_subfolder, allow_non_empty=True) + resource_tracker.unregister(pool_subfolder, "folder") + except OSError: + warnings.warn( + "Failed to delete temporary folder: {}".format(pool_subfolder) + ) + + self._finalizers[context_id] = atexit.register(_cleanup) + + def _clean_temporary_resources( + self, context_id=None, force=False, allow_non_empty=False + ): + """Clean temporary resources created by a process-based pool""" + if context_id is None: + # Iterates over a copy of the cache keys to avoid Error due to + # iterating over a changing size dictionary. + for context_id in list(self._cached_temp_folders): + self._clean_temporary_resources( + context_id, force=force, allow_non_empty=allow_non_empty + ) + else: + temp_folder = self._cached_temp_folders.get(context_id) + if temp_folder and os.path.exists(temp_folder): + for filename in os.listdir(temp_folder): + if force: + # Some workers have failed and the ref counted might + # be off. The workers should have shut down by this + # time so forcefully clean up the files. + resource_tracker.unregister( + os.path.join(temp_folder, filename), "file" + ) + else: + resource_tracker.maybe_unlink( + os.path.join(temp_folder, filename), "file" + ) + + # When forcing clean-up, try to delete the folder even if some + # files are still in it. Otherwise, try to delete the folder + allow_non_empty |= force + + # Clean up the folder if possible, either if it is empty or + # if none of the files in it are in used and allow_non_empty. + try: + delete_folder(temp_folder, allow_non_empty=allow_non_empty) + # Forget the folder once it has been deleted + self._cached_temp_folders.pop(context_id, None) + resource_tracker.unregister(temp_folder, "folder") + + # Also cancel the finalizers that gets triggered at gc. + finalizer = self._finalizers.pop(context_id, None) + if finalizer is not None: + atexit.unregister(finalizer) + + except OSError: + # Temporary folder cannot be deleted right now. + # This folder will be cleaned up by an atexit + # finalizer registered by the memmapping_reducer. + pass diff --git a/joblib/_parallel_backends.py b/joblib/_parallel_backends.py new file mode 100644 index 0000000000000000000000000000000000000000..53114a8512fcbcd320f2d62cebe06f1cb9102fa8 --- /dev/null +++ b/joblib/_parallel_backends.py @@ -0,0 +1,753 @@ +""" +Backends for embarrassingly parallel code. +""" + +import contextlib +import gc +import os +import threading +import warnings +from abc import ABCMeta, abstractmethod + +from ._multiprocessing_helpers import mp +from ._utils import ( + _retrieve_traceback_capturing_wrapped_call, + _TracebackCapturingWrapper, +) + +if mp is not None: + from multiprocessing.pool import ThreadPool + + from .executor import get_memmapping_executor + + # Import loky only if multiprocessing is present + from .externals.loky import cpu_count, process_executor + from .externals.loky.process_executor import ShutdownExecutorError + from .pool import MemmappingPool + + +class ParallelBackendBase(metaclass=ABCMeta): + """Helper abc which defines all methods a ParallelBackend must implement""" + + default_n_jobs = 1 + + supports_inner_max_num_threads = False + + # This flag was introduced for backward compatibility reasons. + # New backends should always set it to True and implement the + # `retrieve_result_callback` method. + supports_retrieve_callback = False + + @property + def supports_return_generator(self): + return self.supports_retrieve_callback + + @property + def supports_timeout(self): + return self.supports_retrieve_callback + + nesting_level = None + + def __init__( + self, nesting_level=None, inner_max_num_threads=None, **backend_kwargs + ): + super().__init__() + self.nesting_level = nesting_level + self.inner_max_num_threads = inner_max_num_threads + self.backend_kwargs = backend_kwargs + + MAX_NUM_THREADS_VARS = [ + "OMP_NUM_THREADS", + "OPENBLAS_NUM_THREADS", + "MKL_NUM_THREADS", + "BLIS_NUM_THREADS", + "VECLIB_MAXIMUM_THREADS", + "NUMBA_NUM_THREADS", + "NUMEXPR_NUM_THREADS", + ] + + TBB_ENABLE_IPC_VAR = "ENABLE_IPC" + + @abstractmethod + def effective_n_jobs(self, n_jobs): + """Determine the number of jobs that can actually run in parallel + + n_jobs is the number of workers requested by the callers. Passing + n_jobs=-1 means requesting all available workers for instance matching + the number of CPU cores on the worker host(s). + + This method should return a guesstimate of the number of workers that + can actually perform work concurrently. The primary use case is to make + it possible for the caller to know in how many chunks to slice the + work. + + In general working on larger data chunks is more efficient (less + scheduling overhead and better use of CPU cache prefetching heuristics) + as long as all the workers have enough work to do. + """ + + def apply_async(self, func, callback=None): + """Deprecated: implement `submit` instead.""" + raise NotImplementedError("Implement `submit` instead.") + + def submit(self, func, callback=None): + """Schedule a function to be run and return a future-like object. + + This method should return a future-like object that allow tracking + the progress of the task. + + If ``supports_retrieve_callback`` is False, the return value of this + method is passed to ``retrieve_result`` instead of calling + ``retrieve_result_callback``. + + Parameters + ---------- + func: callable + The function to be run in parallel. + + callback: callable + A callable that will be called when the task is completed. This callable + is a wrapper around ``retrieve_result_callback``. This should be added + to the future-like object returned by this method, so that the callback + is called when the task is completed. + + For future-like backends, this can be achieved with something like + ``future.add_done_callback(callback)``. + + Returns + ------- + future: future-like + A future-like object to track the execution of the submitted function. + """ + warnings.warn( + "`apply_async` is deprecated, implement and use `submit` instead.", + DeprecationWarning, + ) + return self.apply_async(func, callback) + + def retrieve_result_callback(self, out): + """Called within the callback function passed to `submit`. + + This method can customise how the result of the function is retrieved + from the future-like object. + + Parameters + ---------- + future: future-like + The future-like object returned by the `submit` method. + + Returns + ------- + result: object + The result of the function executed in parallel. + """ + + def retrieve_result(self, out, timeout=None): + """Hook to retrieve the result when support_retrieve_callback=False. + + The argument `out` is the result of the `submit` call. This method + should return the result of the computation or raise an exception if + the computation failed. + """ + if self.supports_timeout: + return out.get(timeout=timeout) + else: + return out.get() + + def configure( + self, n_jobs=1, parallel=None, prefer=None, require=None, **backend_kwargs + ): + """Reconfigure the backend and return the number of workers. + + This makes it possible to reuse an existing backend instance for + successive independent calls to Parallel with different parameters. + """ + self.parallel = parallel + return self.effective_n_jobs(n_jobs) + + def start_call(self): + """Call-back method called at the beginning of a Parallel call""" + + def stop_call(self): + """Call-back method called at the end of a Parallel call""" + + def terminate(self): + """Shutdown the workers and free the shared memory.""" + + def compute_batch_size(self): + """Determine the optimal batch size""" + return 1 + + def batch_completed(self, batch_size, duration): + """Callback indicate how long it took to run a batch""" + + def abort_everything(self, ensure_ready=True): + """Abort any running tasks + + This is called when an exception has been raised when executing a task + and all the remaining tasks will be ignored and can therefore be + aborted to spare computation resources. + + If ensure_ready is True, the backend should be left in an operating + state as future tasks might be re-submitted via that same backend + instance. + + If ensure_ready is False, the implementer of this method can decide + to leave the backend in a closed / terminated state as no new task + are expected to be submitted to this backend. + + Setting ensure_ready to False is an optimization that can be leveraged + when aborting tasks via killing processes from a local process pool + managed by the backend it-self: if we expect no new tasks, there is no + point in re-creating new workers. + """ + # Does nothing by default: to be overridden in subclasses when + # canceling tasks is possible. + pass + + def get_nested_backend(self): + """Backend instance to be used by nested Parallel calls. + + By default a thread-based backend is used for the first level of + nesting. Beyond, switch to sequential backend to avoid spawning too + many threads on the host. + """ + nesting_level = getattr(self, "nesting_level", 0) + 1 + if nesting_level > 1: + return SequentialBackend(nesting_level=nesting_level), None + else: + return ThreadingBackend(nesting_level=nesting_level), None + + def _prepare_worker_env(self, n_jobs): + """Return environment variables limiting threadpools in external libs. + + This function return a dict containing environment variables to pass + when creating a pool of process. These environment variables limit the + number of threads to `n_threads` for OpenMP, MKL, Accelerated and + OpenBLAS libraries in the child processes. + """ + explicit_n_threads = self.inner_max_num_threads + default_n_threads = max(cpu_count() // n_jobs, 1) + + # Set the inner environment variables to self.inner_max_num_threads if + # it is given. Else, default to cpu_count // n_jobs unless the variable + # is already present in the parent process environment. + env = {} + for var in self.MAX_NUM_THREADS_VARS: + if explicit_n_threads is None: + var_value = os.environ.get(var, default_n_threads) + else: + var_value = explicit_n_threads + + env[var] = str(var_value) + + if self.TBB_ENABLE_IPC_VAR not in os.environ: + # To avoid over-subscription when using TBB, let the TBB schedulers + # use Inter Process Communication to coordinate: + env[self.TBB_ENABLE_IPC_VAR] = "1" + return env + + @contextlib.contextmanager + def retrieval_context(self): + """Context manager to manage an execution context. + + Calls to Parallel.retrieve will be made inside this context. + + By default, this does nothing. It may be useful for subclasses to + handle nested parallelism. In particular, it may be required to avoid + deadlocks if a backend manages a fixed number of workers, when those + workers may be asked to do nested Parallel calls. Without + 'retrieval_context' this could lead to deadlock, as all the workers + managed by the backend may be "busy" waiting for the nested parallel + calls to finish, but the backend has no free workers to execute those + tasks. + """ + yield + + @staticmethod + def in_main_thread(): + return isinstance(threading.current_thread(), threading._MainThread) + + +class SequentialBackend(ParallelBackendBase): + """A ParallelBackend which will execute all batches sequentially. + + Does not use/create any threading objects, and hence has minimal + overhead. Used when n_jobs == 1. + """ + + uses_threads = True + supports_timeout = False + supports_retrieve_callback = False + supports_sharedmem = True + + def effective_n_jobs(self, n_jobs): + """Determine the number of jobs which are going to run in parallel""" + if n_jobs == 0: + raise ValueError("n_jobs == 0 in Parallel has no meaning") + return 1 + + def submit(self, func, callback=None): + """Schedule a func to be run""" + raise RuntimeError("Should never be called for SequentialBackend.") + + def retrieve_result_callback(self, out): + raise RuntimeError("Should never be called for SequentialBackend.") + + def get_nested_backend(self): + # import is not top level to avoid cyclic import errors. + from .parallel import get_active_backend + + # SequentialBackend should neither change the nesting level, the + # default backend or the number of jobs. Just return the current one. + return get_active_backend() + + +class PoolManagerMixin(object): + """A helper class for managing pool of workers.""" + + _pool = None + + def effective_n_jobs(self, n_jobs): + """Determine the number of jobs which are going to run in parallel""" + if n_jobs == 0: + raise ValueError("n_jobs == 0 in Parallel has no meaning") + elif mp is None or n_jobs is None: + # multiprocessing is not available or disabled, fallback + # to sequential mode + return 1 + elif n_jobs < 0: + n_jobs = max(cpu_count() + 1 + n_jobs, 1) + return n_jobs + + def terminate(self): + """Shutdown the process or thread pool""" + if self._pool is not None: + self._pool.close() + self._pool.terminate() # terminate does a join() + self._pool = None + + def _get_pool(self): + """Used by `submit` to make it possible to implement lazy init""" + return self._pool + + def submit(self, func, callback=None): + """Schedule a func to be run""" + # Here, we need a wrapper to avoid crashes on KeyboardInterruptErrors. + # We also call the callback on error, to make sure the pool does not + # wait on crashed jobs. + return self._get_pool().apply_async( + _TracebackCapturingWrapper(func), + (), + callback=callback, + error_callback=callback, + ) + + def retrieve_result_callback(self, result): + """Mimic concurrent.futures results, raising an error if needed.""" + # In the multiprocessing Pool API, the callback are called with the + # result value as an argument so `result`(`out`) is the output of + # job.get(). It's either the result or the exception raised while + # collecting the result. + return _retrieve_traceback_capturing_wrapped_call(result) + + def abort_everything(self, ensure_ready=True): + """Shutdown the pool and restart a new one with the same parameters""" + self.terminate() + if ensure_ready: + self.configure( + n_jobs=self.parallel.n_jobs, + parallel=self.parallel, + **self.parallel._backend_kwargs, + ) + + +class AutoBatchingMixin(object): + """A helper class for automagically batching jobs.""" + + # In seconds, should be big enough to hide multiprocessing dispatching + # overhead. + # This settings was found by running benchmarks/bench_auto_batching.py + # with various parameters on various platforms. + MIN_IDEAL_BATCH_DURATION = 0.2 + + # Should not be too high to avoid stragglers: long jobs running alone + # on a single worker while other workers have no work to process any more. + MAX_IDEAL_BATCH_DURATION = 2 + + # Batching counters default values + _DEFAULT_EFFECTIVE_BATCH_SIZE = 1 + _DEFAULT_SMOOTHED_BATCH_DURATION = 0.0 + + def __init__(self, **kwargs): + super().__init__(**kwargs) + self._effective_batch_size = self._DEFAULT_EFFECTIVE_BATCH_SIZE + self._smoothed_batch_duration = self._DEFAULT_SMOOTHED_BATCH_DURATION + + def compute_batch_size(self): + """Determine the optimal batch size""" + old_batch_size = self._effective_batch_size + batch_duration = self._smoothed_batch_duration + if batch_duration > 0 and batch_duration < self.MIN_IDEAL_BATCH_DURATION: + # The current batch size is too small: the duration of the + # processing of a batch of task is not large enough to hide + # the scheduling overhead. + ideal_batch_size = int( + old_batch_size * self.MIN_IDEAL_BATCH_DURATION / batch_duration + ) + # Multiply by two to limit oscilations between min and max. + ideal_batch_size *= 2 + + # dont increase the batch size too fast to limit huge batch sizes + # potentially leading to starving worker + batch_size = min(2 * old_batch_size, ideal_batch_size) + + batch_size = max(batch_size, 1) + + self._effective_batch_size = batch_size + if self.parallel.verbose >= 10: + self.parallel._print( + f"Batch computation too fast ({batch_duration}s.) " + f"Setting batch_size={batch_size}." + ) + elif batch_duration > self.MAX_IDEAL_BATCH_DURATION and old_batch_size >= 2: + # The current batch size is too big. If we schedule overly long + # running batches some CPUs might wait with nothing left to do + # while a couple of CPUs a left processing a few long running + # batches. Better reduce the batch size a bit to limit the + # likelihood of scheduling such stragglers. + + # decrease the batch size quickly to limit potential starving + ideal_batch_size = int( + old_batch_size * self.MIN_IDEAL_BATCH_DURATION / batch_duration + ) + # Multiply by two to limit oscilations between min and max. + batch_size = max(2 * ideal_batch_size, 1) + self._effective_batch_size = batch_size + if self.parallel.verbose >= 10: + self.parallel._print( + f"Batch computation too slow ({batch_duration}s.) " + f"Setting batch_size={batch_size}." + ) + else: + # No batch size adjustment + batch_size = old_batch_size + + if batch_size != old_batch_size: + # Reset estimation of the smoothed mean batch duration: this + # estimate is updated in the multiprocessing apply_async + # CallBack as long as the batch_size is constant. Therefore + # we need to reset the estimate whenever we re-tune the batch + # size. + self._smoothed_batch_duration = self._DEFAULT_SMOOTHED_BATCH_DURATION + + return batch_size + + def batch_completed(self, batch_size, duration): + """Callback indicate how long it took to run a batch""" + if batch_size == self._effective_batch_size: + # Update the smoothed streaming estimate of the duration of a batch + # from dispatch to completion + old_duration = self._smoothed_batch_duration + if old_duration == self._DEFAULT_SMOOTHED_BATCH_DURATION: + # First record of duration for this batch size after the last + # reset. + new_duration = duration + else: + # Update the exponentially weighted average of the duration of + # batch for the current effective size. + new_duration = 0.8 * old_duration + 0.2 * duration + self._smoothed_batch_duration = new_duration + + def reset_batch_stats(self): + """Reset batch statistics to default values. + + This avoids interferences with future jobs. + """ + self._effective_batch_size = self._DEFAULT_EFFECTIVE_BATCH_SIZE + self._smoothed_batch_duration = self._DEFAULT_SMOOTHED_BATCH_DURATION + + +class ThreadingBackend(PoolManagerMixin, ParallelBackendBase): + """A ParallelBackend which will use a thread pool to execute batches in. + + This is a low-overhead backend but it suffers from the Python Global + Interpreter Lock if the called function relies a lot on Python objects. + Mostly useful when the execution bottleneck is a compiled extension that + explicitly releases the GIL (for instance a Cython loop wrapped in a "with + nogil" block or an expensive call to a library such as NumPy). + + The actual thread pool is lazily initialized: the actual thread pool + construction is delayed to the first call to apply_async. + + ThreadingBackend is used as the default backend for nested calls. + """ + + supports_retrieve_callback = True + uses_threads = True + supports_sharedmem = True + + def configure(self, n_jobs=1, parallel=None, **backend_kwargs): + """Build a process or thread pool and return the number of workers""" + n_jobs = self.effective_n_jobs(n_jobs) + if n_jobs == 1: + # Avoid unnecessary overhead and use sequential backend instead. + raise FallbackToBackend(SequentialBackend(nesting_level=self.nesting_level)) + self.parallel = parallel + self._n_jobs = n_jobs + return n_jobs + + def _get_pool(self): + """Lazily initialize the thread pool + + The actual pool of worker threads is only initialized at the first + call to apply_async. + """ + if self._pool is None: + self._pool = ThreadPool(self._n_jobs) + return self._pool + + +class MultiprocessingBackend(PoolManagerMixin, AutoBatchingMixin, ParallelBackendBase): + """A ParallelBackend which will use a multiprocessing.Pool. + + Will introduce some communication and memory overhead when exchanging + input and output data with the with the worker Python processes. + However, does not suffer from the Python Global Interpreter Lock. + """ + + supports_retrieve_callback = True + supports_return_generator = False + + def effective_n_jobs(self, n_jobs): + """Determine the number of jobs which are going to run in parallel. + + This also checks if we are attempting to create a nested parallel + loop. + """ + if mp is None: + return 1 + + if mp.current_process().daemon: + # Daemonic processes cannot have children + if n_jobs != 1: + if inside_dask_worker(): + msg = ( + "Inside a Dask worker with daemon=True, " + "setting n_jobs=1.\nPossible work-arounds:\n" + "- dask.config.set(" + "{'distributed.worker.daemon': False})" + "- set the environment variable " + "DASK_DISTRIBUTED__WORKER__DAEMON=False\n" + "before creating your Dask cluster." + ) + else: + msg = ( + "Multiprocessing-backed parallel loops " + "cannot be nested, setting n_jobs=1" + ) + warnings.warn(msg, stacklevel=3) + return 1 + + if process_executor._CURRENT_DEPTH > 0: + # Mixing loky and multiprocessing in nested loop is not supported + if n_jobs != 1: + warnings.warn( + "Multiprocessing-backed parallel loops cannot be nested," + " below loky, setting n_jobs=1", + stacklevel=3, + ) + return 1 + + elif not (self.in_main_thread() or self.nesting_level == 0): + # Prevent posix fork inside in non-main posix threads + if n_jobs != 1: + warnings.warn( + "Multiprocessing-backed parallel loops cannot be nested" + " below threads, setting n_jobs=1", + stacklevel=3, + ) + return 1 + + return super(MultiprocessingBackend, self).effective_n_jobs(n_jobs) + + def configure( + self, + n_jobs=1, + parallel=None, + prefer=None, + require=None, + **memmapping_pool_kwargs, + ): + """Build a process or thread pool and return the number of workers""" + n_jobs = self.effective_n_jobs(n_jobs) + if n_jobs == 1: + raise FallbackToBackend(SequentialBackend(nesting_level=self.nesting_level)) + + memmapping_pool_kwargs = { + **self.backend_kwargs, + **memmapping_pool_kwargs, + } + + # Make sure to free as much memory as possible before forking + gc.collect() + self._pool = MemmappingPool(n_jobs, **memmapping_pool_kwargs) + self.parallel = parallel + return n_jobs + + def terminate(self): + """Shutdown the process or thread pool""" + super(MultiprocessingBackend, self).terminate() + self.reset_batch_stats() + + +class LokyBackend(AutoBatchingMixin, ParallelBackendBase): + """Managing pool of workers with loky instead of multiprocessing.""" + + supports_retrieve_callback = True + supports_inner_max_num_threads = True + + def configure( + self, + n_jobs=1, + parallel=None, + prefer=None, + require=None, + idle_worker_timeout=None, + **memmapping_executor_kwargs, + ): + """Build a process executor and return the number of workers""" + n_jobs = self.effective_n_jobs(n_jobs) + if n_jobs == 1: + raise FallbackToBackend(SequentialBackend(nesting_level=self.nesting_level)) + + memmapping_executor_kwargs = { + **self.backend_kwargs, + **memmapping_executor_kwargs, + } + + # Prohibit the use of 'timeout' in the LokyBackend, as 'idle_worker_timeout' + # better describes the backend's behavior. + if "timeout" in memmapping_executor_kwargs: + raise ValueError( + "The 'timeout' parameter is not supported by the LokyBackend. " + "Please use the `idle_worker_timeout` parameter instead." + ) + if idle_worker_timeout is None: + idle_worker_timeout = self.backend_kwargs.get("idle_worker_timeout", 300) + + self._workers = get_memmapping_executor( + n_jobs, + timeout=idle_worker_timeout, + env=self._prepare_worker_env(n_jobs=n_jobs), + context_id=parallel._id, + **memmapping_executor_kwargs, + ) + self.parallel = parallel + return n_jobs + + def effective_n_jobs(self, n_jobs): + """Determine the number of jobs which are going to run in parallel""" + if n_jobs == 0: + raise ValueError("n_jobs == 0 in Parallel has no meaning") + elif mp is None or n_jobs is None: + # multiprocessing is not available or disabled, fallback + # to sequential mode + return 1 + elif mp.current_process().daemon: + # Daemonic processes cannot have children + if n_jobs != 1: + if inside_dask_worker(): + msg = ( + "Inside a Dask worker with daemon=True, " + "setting n_jobs=1.\nPossible work-arounds:\n" + "- dask.config.set(" + "{'distributed.worker.daemon': False})\n" + "- set the environment variable " + "DASK_DISTRIBUTED__WORKER__DAEMON=False\n" + "before creating your Dask cluster." + ) + else: + msg = ( + "Loky-backed parallel loops cannot be called in a" + " multiprocessing, setting n_jobs=1" + ) + warnings.warn(msg, stacklevel=3) + + return 1 + elif not (self.in_main_thread() or self.nesting_level == 0): + # Prevent posix fork inside in non-main posix threads + if n_jobs != 1: + warnings.warn( + "Loky-backed parallel loops cannot be nested below " + "threads, setting n_jobs=1", + stacklevel=3, + ) + return 1 + elif n_jobs < 0: + n_jobs = max(cpu_count() + 1 + n_jobs, 1) + return n_jobs + + def submit(self, func, callback=None): + """Schedule a func to be run""" + future = self._workers.submit(func) + if callback is not None: + future.add_done_callback(callback) + return future + + def retrieve_result_callback(self, future): + """Retrieve the result, here out is the future given by submit""" + try: + return future.result() + except ShutdownExecutorError: + raise RuntimeError( + "The executor underlying Parallel has been shutdown. " + "This is likely due to the garbage collection of a previous " + "generator from a call to Parallel with return_as='generator'." + " Make sure the generator is not garbage collected when " + "submitting a new job or that it is first properly exhausted." + ) + + def terminate(self): + if self._workers is not None: + # Don't terminate the workers as we want to reuse them in later + # calls, but cleanup the temporary resources that the Parallel call + # created. This 'hack' requires a private, low-level operation. + self._workers._temp_folder_manager._clean_temporary_resources( + context_id=self.parallel._id, force=False + ) + self._workers = None + + self.reset_batch_stats() + + def abort_everything(self, ensure_ready=True): + """Shutdown the workers and restart a new one with the same parameters""" + self._workers.terminate(kill_workers=True) + self._workers = None + + if ensure_ready: + self.configure(n_jobs=self.parallel.n_jobs, parallel=self.parallel) + + +class FallbackToBackend(Exception): + """Raised when configuration should fallback to another backend""" + + def __init__(self, backend): + self.backend = backend + + +def inside_dask_worker(): + """Check whether the current function is executed inside a Dask worker.""" + # This function can not be in joblib._dask because there would be a + # circular import: + # _dask imports _parallel_backend that imports _dask ... + try: + from distributed import get_worker + except ImportError: + return False + + try: + get_worker() + return True + except ValueError: + return False diff --git a/joblib/_utils.py b/joblib/_utils.py new file mode 100644 index 0000000000000000000000000000000000000000..5e82173e7de40598b4dae37d42d25d977af4e1a9 --- /dev/null +++ b/joblib/_utils.py @@ -0,0 +1,120 @@ +# Adapted from https://stackoverflow.com/a/9558001/2536294 + +import ast +import functools +import operator as op +from dataclasses import dataclass + +from ._multiprocessing_helpers import mp + +if mp is not None: + from .externals.loky.process_executor import _ExceptionWithTraceback + + +# supported operators +operators = { + ast.Add: op.add, + ast.Sub: op.sub, + ast.Mult: op.mul, + ast.Div: op.truediv, + ast.FloorDiv: op.floordiv, + ast.Mod: op.mod, + ast.Pow: op.pow, + ast.USub: op.neg, +} + + +def eval_expr(expr): + """Somewhat safely evaluate an arithmetic expression. + + >>> eval_expr('2*6') + 12 + >>> eval_expr('2**6') + 64 + >>> eval_expr('1 + 2*3**(4) / (6 + -7)') + -161.0 + + Raises ValueError if the expression is invalid, too long + or its computation involves too large values. + """ + # Restrict the length of the expression to avoid potential Python crashes + # as per the documentation of ast.parse. + max_length = 30 + if len(expr) > max_length: + raise ValueError( + f"Expression {expr[:max_length]!r}... is too long. " + f"Max length is {max_length}, got {len(expr)}." + ) + try: + return eval_(ast.parse(expr, mode="eval").body) + except (TypeError, SyntaxError, OverflowError, KeyError) as e: + raise ValueError( + f"{expr!r} is not a valid or supported arithmetic expression." + ) from e + + +def limit(max_=None): + """Return decorator that limits allowed returned values.""" + + def decorator(func): + @functools.wraps(func) + def wrapper(*args, **kwargs): + ret = func(*args, **kwargs) + try: + mag = abs(ret) + except TypeError: + pass # not applicable + else: + if mag > max_: + raise ValueError( + f"Numeric literal {ret} is too large, max is {max_}." + ) + return ret + + return wrapper + + return decorator + + +@limit(max_=10**6) +def eval_(node): + if isinstance(node, ast.Constant) and isinstance(node.value, (int, float)): + return node.value + elif isinstance(node, ast.BinOp): # + return operators[type(node.op)](eval_(node.left), eval_(node.right)) + elif isinstance(node, ast.UnaryOp): # e.g., -1 + return operators[type(node.op)](eval_(node.operand)) + else: + raise TypeError(node) + + +@dataclass(frozen=True) +class _Sentinel: + """A sentinel to mark a parameter as not explicitly set""" + + default_value: object + + def __repr__(self): + return f"default({self.default_value!r})" + + +class _TracebackCapturingWrapper: + """Protect function call and return error with traceback.""" + + def __init__(self, func): + self.func = func + + def __call__(self, **kwargs): + try: + return self.func(**kwargs) + except BaseException as e: + return _ExceptionWithTraceback(e) + + +def _retrieve_traceback_capturing_wrapped_call(out): + if isinstance(out, _ExceptionWithTraceback): + rebuild, args = out.__reduce__() + out = rebuild(*args) + if isinstance(out, BaseException): + raise out + return out diff --git a/joblib/backports.py b/joblib/backports.py new file mode 100644 index 0000000000000000000000000000000000000000..495e2acb8b38e6676dd4cb0a219d9f3bb7c4bff5 --- /dev/null +++ b/joblib/backports.py @@ -0,0 +1,195 @@ +""" +Backports of fixes for joblib dependencies +""" + +import os +import re +import time +from multiprocessing import util +from os.path import basename + + +class Version: + """Backport from deprecated distutils + + We maintain this backport to avoid introducing a new dependency on + `packaging`. + + We might rexplore this choice in the future if all major Python projects + introduce a dependency on packaging anyway. + """ + + def __init__(self, vstring=None): + if vstring: + self.parse(vstring) + + def __repr__(self): + return "%s ('%s')" % (self.__class__.__name__, str(self)) + + def __eq__(self, other): + c = self._cmp(other) + if c is NotImplemented: + return c + return c == 0 + + def __lt__(self, other): + c = self._cmp(other) + if c is NotImplemented: + return c + return c < 0 + + def __le__(self, other): + c = self._cmp(other) + if c is NotImplemented: + return c + return c <= 0 + + def __gt__(self, other): + c = self._cmp(other) + if c is NotImplemented: + return c + return c > 0 + + def __ge__(self, other): + c = self._cmp(other) + if c is NotImplemented: + return c + return c >= 0 + + +class LooseVersion(Version): + """Backport from deprecated distutils + + We maintain this backport to avoid introducing a new dependency on + `packaging`. + + We might rexplore this choice in the future if all major Python projects + introduce a dependency on packaging anyway. + """ + + component_re = re.compile(r"(\d+ | [a-z]+ | \.)", re.VERBOSE) + + def __init__(self, vstring=None): + if vstring: + self.parse(vstring) + + def parse(self, vstring): + # I've given up on thinking I can reconstruct the version string + # from the parsed tuple -- so I just store the string here for + # use by __str__ + self.vstring = vstring + components = [x for x in self.component_re.split(vstring) if x and x != "."] + for i, obj in enumerate(components): + try: + components[i] = int(obj) + except ValueError: + pass + + self.version = components + + def __str__(self): + return self.vstring + + def __repr__(self): + return "LooseVersion ('%s')" % str(self) + + def _cmp(self, other): + if isinstance(other, str): + other = LooseVersion(other) + elif not isinstance(other, LooseVersion): + return NotImplemented + + if self.version == other.version: + return 0 + if self.version < other.version: + return -1 + if self.version > other.version: + return 1 + + +try: + import numpy as np + + def make_memmap( + filename, + dtype="uint8", + mode="r+", + offset=0, + shape=None, + order="C", + unlink_on_gc_collect=False, + ): + """Custom memmap constructor compatible with numpy.memmap. + + This function: + - is a backport the numpy memmap offset fix (See + https://github.com/numpy/numpy/pull/8443 for more details. + The numpy fix is available starting numpy 1.13) + - adds ``unlink_on_gc_collect``, which specifies explicitly whether + the process re-constructing the memmap owns a reference to the + underlying file. If set to True, it adds a finalizer to the + newly-created memmap that sends a maybe_unlink request for the + memmaped file to resource_tracker. + """ + util.debug( + "[MEMMAP READ] creating a memmap (shape {}, filename {}, pid {})".format( + shape, basename(filename), os.getpid() + ) + ) + + mm = np.memmap( + filename, dtype=dtype, mode=mode, offset=offset, shape=shape, order=order + ) + if LooseVersion(np.__version__) < "1.13": + mm.offset = offset + if unlink_on_gc_collect: + from ._memmapping_reducer import add_maybe_unlink_finalizer + + add_maybe_unlink_finalizer(mm) + return mm +except ImportError: + + def make_memmap( + filename, + dtype="uint8", + mode="r+", + offset=0, + shape=None, + order="C", + unlink_on_gc_collect=False, + ): + raise NotImplementedError( + "'joblib.backports.make_memmap' should not be used " + "if numpy is not installed." + ) + + +if os.name == "nt": + # https://github.com/joblib/joblib/issues/540 + access_denied_errors = (5, 13) + from os import replace + + def concurrency_safe_rename(src, dst): + """Renames ``src`` into ``dst`` overwriting ``dst`` if it exists. + + On Windows os.replace can yield permission errors if executed by two + different processes. + """ + max_sleep_time = 1 + total_sleep_time = 0 + sleep_time = 0.001 + while total_sleep_time < max_sleep_time: + try: + replace(src, dst) + break + except Exception as exc: + if getattr(exc, "winerror", None) in access_denied_errors: + time.sleep(sleep_time) + total_sleep_time += sleep_time + sleep_time *= 2 + else: + raise + else: + raise +else: + from os import replace as concurrency_safe_rename # noqa diff --git a/joblib/compressor.py b/joblib/compressor.py new file mode 100644 index 0000000000000000000000000000000000000000..55bc86c4855574e9b0eec8fad29a2cdde614fbdd --- /dev/null +++ b/joblib/compressor.py @@ -0,0 +1,572 @@ +"""Classes and functions for managing compressors.""" + +import io +import zlib + +from joblib.backports import LooseVersion + +try: + from threading import RLock +except ImportError: + from dummy_threading import RLock + +try: + import bz2 +except ImportError: + bz2 = None + +try: + import lz4 + from lz4.frame import LZ4FrameFile +except ImportError: + lz4 = None + +try: + import lzma +except ImportError: + lzma = None + + +LZ4_NOT_INSTALLED_ERROR = ( + "LZ4 is not installed. Install it with pip: https://python-lz4.readthedocs.io/" +) + +# Registered compressors +_COMPRESSORS = {} + +# Magic numbers of supported compression file formats. +_ZFILE_PREFIX = b"ZF" # used with pickle files created before 0.9.3. +_ZLIB_PREFIX = b"\x78" +_GZIP_PREFIX = b"\x1f\x8b" +_BZ2_PREFIX = b"BZ" +_XZ_PREFIX = b"\xfd\x37\x7a\x58\x5a" +_LZMA_PREFIX = b"\x5d\x00" +_LZ4_PREFIX = b"\x04\x22\x4d\x18" + + +def register_compressor(compressor_name, compressor, force=False): + """Register a new compressor. + + Parameters + ---------- + compressor_name: str. + The name of the compressor. + compressor: CompressorWrapper + An instance of a 'CompressorWrapper'. + """ + global _COMPRESSORS + if not isinstance(compressor_name, str): + raise ValueError( + "Compressor name should be a string, '{}' given.".format(compressor_name) + ) + + if not isinstance(compressor, CompressorWrapper): + raise ValueError( + "Compressor should implement the CompressorWrapper " + "interface, '{}' given.".format(compressor) + ) + + if compressor.fileobj_factory is not None and ( + not hasattr(compressor.fileobj_factory, "read") + or not hasattr(compressor.fileobj_factory, "write") + or not hasattr(compressor.fileobj_factory, "seek") + or not hasattr(compressor.fileobj_factory, "tell") + ): + raise ValueError( + "Compressor 'fileobj_factory' attribute should " + "implement the file object interface, '{}' given.".format( + compressor.fileobj_factory + ) + ) + + if compressor_name in _COMPRESSORS and not force: + raise ValueError("Compressor '{}' already registered.".format(compressor_name)) + + _COMPRESSORS[compressor_name] = compressor + + +class CompressorWrapper: + """A wrapper around a compressor file object. + + Attributes + ---------- + obj: a file-like object + The object must implement the buffer interface and will be used + internally to compress/decompress the data. + prefix: bytestring + A bytestring corresponding to the magic number that identifies the + file format associated to the compressor. + extension: str + The file extension used to automatically select this compressor during + a dump to a file. + """ + + def __init__(self, obj, prefix=b"", extension=""): + self.fileobj_factory = obj + self.prefix = prefix + self.extension = extension + + def compressor_file(self, fileobj, compresslevel=None): + """Returns an instance of a compressor file object.""" + if compresslevel is None: + return self.fileobj_factory(fileobj, "wb") + else: + return self.fileobj_factory(fileobj, "wb", compresslevel=compresslevel) + + def decompressor_file(self, fileobj): + """Returns an instance of a decompressor file object.""" + return self.fileobj_factory(fileobj, "rb") + + +class BZ2CompressorWrapper(CompressorWrapper): + prefix = _BZ2_PREFIX + extension = ".bz2" + + def __init__(self): + if bz2 is not None: + self.fileobj_factory = bz2.BZ2File + else: + self.fileobj_factory = None + + def _check_versions(self): + if bz2 is None: + raise ValueError( + "bz2 module is not compiled on your python standard library." + ) + + def compressor_file(self, fileobj, compresslevel=None): + """Returns an instance of a compressor file object.""" + self._check_versions() + if compresslevel is None: + return self.fileobj_factory(fileobj, "wb") + else: + return self.fileobj_factory(fileobj, "wb", compresslevel=compresslevel) + + def decompressor_file(self, fileobj): + """Returns an instance of a decompressor file object.""" + self._check_versions() + fileobj = self.fileobj_factory(fileobj, "rb") + return fileobj + + +class LZMACompressorWrapper(CompressorWrapper): + prefix = _LZMA_PREFIX + extension = ".lzma" + _lzma_format_name = "FORMAT_ALONE" + + def __init__(self): + if lzma is not None: + self.fileobj_factory = lzma.LZMAFile + self._lzma_format = getattr(lzma, self._lzma_format_name) + else: + self.fileobj_factory = None + + def _check_versions(self): + if lzma is None: + raise ValueError( + "lzma module is not compiled on your python standard library." + ) + + def compressor_file(self, fileobj, compresslevel=None): + """Returns an instance of a compressor file object.""" + if compresslevel is None: + return self.fileobj_factory(fileobj, "wb", format=self._lzma_format) + else: + return self.fileobj_factory( + fileobj, "wb", format=self._lzma_format, preset=compresslevel + ) + + def decompressor_file(self, fileobj): + """Returns an instance of a decompressor file object.""" + return lzma.LZMAFile(fileobj, "rb") + + +class XZCompressorWrapper(LZMACompressorWrapper): + prefix = _XZ_PREFIX + extension = ".xz" + _lzma_format_name = "FORMAT_XZ" + + +class LZ4CompressorWrapper(CompressorWrapper): + prefix = _LZ4_PREFIX + extension = ".lz4" + + def __init__(self): + if lz4 is not None: + self.fileobj_factory = LZ4FrameFile + else: + self.fileobj_factory = None + + def _check_versions(self): + if lz4 is None: + raise ValueError(LZ4_NOT_INSTALLED_ERROR) + lz4_version = lz4.__version__ + if lz4_version.startswith("v"): + lz4_version = lz4_version[1:] + if LooseVersion(lz4_version) < LooseVersion("0.19"): + raise ValueError(LZ4_NOT_INSTALLED_ERROR) + + def compressor_file(self, fileobj, compresslevel=None): + """Returns an instance of a compressor file object.""" + self._check_versions() + if compresslevel is None: + return self.fileobj_factory(fileobj, "wb") + else: + return self.fileobj_factory(fileobj, "wb", compression_level=compresslevel) + + def decompressor_file(self, fileobj): + """Returns an instance of a decompressor file object.""" + self._check_versions() + return self.fileobj_factory(fileobj, "rb") + + +############################################################################### +# base file compression/decompression object definition +_MODE_CLOSED = 0 +_MODE_READ = 1 +_MODE_READ_EOF = 2 +_MODE_WRITE = 3 +_BUFFER_SIZE = 8192 + + +class BinaryZlibFile(io.BufferedIOBase): + """A file object providing transparent zlib (de)compression. + + TODO python2_drop: is it still needed since we dropped Python 2 support A + BinaryZlibFile can act as a wrapper for an existing file object, or refer + directly to a named file on disk. + + Note that BinaryZlibFile provides only a *binary* file interface: data read + is returned as bytes, and data to be written should be given as bytes. + + This object is an adaptation of the BZ2File object and is compatible with + versions of python >= 2.7. + + If filename is a str or bytes object, it gives the name + of the file to be opened. Otherwise, it should be a file object, + which will be used to read or write the compressed data. + + mode can be 'rb' for reading (default) or 'wb' for (over)writing + + If mode is 'wb', compresslevel can be a number between 1 + and 9 specifying the level of compression: 1 produces the least + compression, and 9 produces the most compression. 3 is the default. + """ + + wbits = zlib.MAX_WBITS + + def __init__(self, filename, mode="rb", compresslevel=3): + # This lock must be recursive, so that BufferedIOBase's + # readline(), readlines() and writelines() don't deadlock. + self._lock = RLock() + self._fp = None + self._closefp = False + self._mode = _MODE_CLOSED + self._pos = 0 + self._size = -1 + self.compresslevel = compresslevel + + if not isinstance(compresslevel, int) or not (1 <= compresslevel <= 9): + raise ValueError( + "'compresslevel' must be an integer " + "between 1 and 9. You provided 'compresslevel={}'".format(compresslevel) + ) + + if mode == "rb": + self._mode = _MODE_READ + self._decompressor = zlib.decompressobj(self.wbits) + self._buffer = b"" + self._buffer_offset = 0 + elif mode == "wb": + self._mode = _MODE_WRITE + self._compressor = zlib.compressobj( + self.compresslevel, zlib.DEFLATED, self.wbits, zlib.DEF_MEM_LEVEL, 0 + ) + else: + raise ValueError("Invalid mode: %r" % (mode,)) + + if isinstance(filename, str): + self._fp = io.open(filename, mode) + self._closefp = True + elif hasattr(filename, "read") or hasattr(filename, "write"): + self._fp = filename + else: + raise TypeError("filename must be a str or bytes object, or a file") + + def close(self): + """Flush and close the file. + + May be called more than once without error. Once the file is + closed, any other operation on it will raise a ValueError. + """ + with self._lock: + if self._mode == _MODE_CLOSED: + return + try: + if self._mode in (_MODE_READ, _MODE_READ_EOF): + self._decompressor = None + elif self._mode == _MODE_WRITE: + self._fp.write(self._compressor.flush()) + self._compressor = None + finally: + try: + if self._closefp: + self._fp.close() + finally: + self._fp = None + self._closefp = False + self._mode = _MODE_CLOSED + self._buffer = b"" + self._buffer_offset = 0 + + @property + def closed(self): + """True if this file is closed.""" + return self._mode == _MODE_CLOSED + + def fileno(self): + """Return the file descriptor for the underlying file.""" + self._check_not_closed() + return self._fp.fileno() + + def seekable(self): + """Return whether the file supports seeking.""" + return self.readable() and self._fp.seekable() + + def readable(self): + """Return whether the file was opened for reading.""" + self._check_not_closed() + return self._mode in (_MODE_READ, _MODE_READ_EOF) + + def writable(self): + """Return whether the file was opened for writing.""" + self._check_not_closed() + return self._mode == _MODE_WRITE + + # Mode-checking helper functions. + + def _check_not_closed(self): + if self.closed: + fname = getattr(self._fp, "name", None) + msg = "I/O operation on closed file" + if fname is not None: + msg += " {}".format(fname) + msg += "." + raise ValueError(msg) + + def _check_can_read(self): + if self._mode not in (_MODE_READ, _MODE_READ_EOF): + self._check_not_closed() + raise io.UnsupportedOperation("File not open for reading") + + def _check_can_write(self): + if self._mode != _MODE_WRITE: + self._check_not_closed() + raise io.UnsupportedOperation("File not open for writing") + + def _check_can_seek(self): + if self._mode not in (_MODE_READ, _MODE_READ_EOF): + self._check_not_closed() + raise io.UnsupportedOperation( + "Seeking is only supported on files open for reading" + ) + if not self._fp.seekable(): + raise io.UnsupportedOperation( + "The underlying file object does not support seeking" + ) + + # Fill the readahead buffer if it is empty. Returns False on EOF. + def _fill_buffer(self): + if self._mode == _MODE_READ_EOF: + return False + # Depending on the input data, our call to the decompressor may not + # return any data. In this case, try again after reading another block. + while self._buffer_offset == len(self._buffer): + try: + rawblock = self._decompressor.unused_data or self._fp.read(_BUFFER_SIZE) + if not rawblock: + raise EOFError + except EOFError: + # End-of-stream marker and end of file. We're good. + self._mode = _MODE_READ_EOF + self._size = self._pos + return False + else: + self._buffer = self._decompressor.decompress(rawblock) + self._buffer_offset = 0 + return True + + # Read data until EOF. + # If return_data is false, consume the data without returning it. + def _read_all(self, return_data=True): + # The loop assumes that _buffer_offset is 0. Ensure that this is true. + self._buffer = self._buffer[self._buffer_offset :] + self._buffer_offset = 0 + + blocks = [] + while self._fill_buffer(): + if return_data: + blocks.append(self._buffer) + self._pos += len(self._buffer) + self._buffer = b"" + if return_data: + return b"".join(blocks) + + # Read a block of up to n bytes. + # If return_data is false, consume the data without returning it. + def _read_block(self, n_bytes, return_data=True): + # If we have enough data buffered, return immediately. + end = self._buffer_offset + n_bytes + if end <= len(self._buffer): + data = self._buffer[self._buffer_offset : end] + self._buffer_offset = end + self._pos += len(data) + return data if return_data else None + + # The loop assumes that _buffer_offset is 0. Ensure that this is true. + self._buffer = self._buffer[self._buffer_offset :] + self._buffer_offset = 0 + + blocks = [] + while n_bytes > 0 and self._fill_buffer(): + if n_bytes < len(self._buffer): + data = self._buffer[:n_bytes] + self._buffer_offset = n_bytes + else: + data = self._buffer + self._buffer = b"" + if return_data: + blocks.append(data) + self._pos += len(data) + n_bytes -= len(data) + if return_data: + return b"".join(blocks) + + def read(self, size=-1): + """Read up to size uncompressed bytes from the file. + + If size is negative or omitted, read until EOF is reached. + Returns b'' if the file is already at EOF. + """ + with self._lock: + self._check_can_read() + if size == 0: + return b"" + elif size < 0: + return self._read_all() + else: + return self._read_block(size) + + def readinto(self, b): + """Read up to len(b) bytes into b. + + Returns the number of bytes read (0 for EOF). + """ + with self._lock: + return io.BufferedIOBase.readinto(self, b) + + def write(self, data): + """Write a byte string to the file. + + Returns the number of uncompressed bytes written, which is + always len(data). Note that due to buffering, the file on disk + may not reflect the data written until close() is called. + """ + with self._lock: + self._check_can_write() + # Convert data type if called by io.BufferedWriter. + if isinstance(data, memoryview): + data = data.tobytes() + + compressed = self._compressor.compress(data) + self._fp.write(compressed) + self._pos += len(data) + return len(data) + + # Rewind the file to the beginning of the data stream. + def _rewind(self): + self._fp.seek(0, 0) + self._mode = _MODE_READ + self._pos = 0 + self._decompressor = zlib.decompressobj(self.wbits) + self._buffer = b"" + self._buffer_offset = 0 + + def seek(self, offset, whence=0): + """Change the file position. + + The new position is specified by offset, relative to the + position indicated by whence. Values for whence are: + + 0: start of stream (default); offset must not be negative + 1: current stream position + 2: end of stream; offset must not be positive + + Returns the new file position. + + Note that seeking is emulated, so depending on the parameters, + this operation may be extremely slow. + """ + with self._lock: + self._check_can_seek() + + # Recalculate offset as an absolute file position. + if whence == 0: + pass + elif whence == 1: + offset = self._pos + offset + elif whence == 2: + # Seeking relative to EOF - we need to know the file's size. + if self._size < 0: + self._read_all(return_data=False) + offset = self._size + offset + else: + raise ValueError("Invalid value for whence: %s" % (whence,)) + + # Make it so that offset is the number of bytes to skip forward. + if offset < self._pos: + self._rewind() + else: + offset -= self._pos + + # Read and discard data until we reach the desired position. + self._read_block(offset, return_data=False) + + return self._pos + + def tell(self): + """Return the current file position.""" + with self._lock: + self._check_not_closed() + return self._pos + + +class ZlibCompressorWrapper(CompressorWrapper): + def __init__(self): + CompressorWrapper.__init__( + self, obj=BinaryZlibFile, prefix=_ZLIB_PREFIX, extension=".z" + ) + + +class BinaryGzipFile(BinaryZlibFile): + """A file object providing transparent gzip (de)compression. + + If filename is a str or bytes object, it gives the name + of the file to be opened. Otherwise, it should be a file object, + which will be used to read or write the compressed data. + + mode can be 'rb' for reading (default) or 'wb' for (over)writing + + If mode is 'wb', compresslevel can be a number between 1 + and 9 specifying the level of compression: 1 produces the least + compression, and 9 produces the most compression. 3 is the default. + """ + + wbits = 31 # zlib compressor/decompressor wbits value for gzip format. + + +class GzipCompressorWrapper(CompressorWrapper): + def __init__(self): + CompressorWrapper.__init__( + self, obj=BinaryGzipFile, prefix=_GZIP_PREFIX, extension=".gz" + ) diff --git a/joblib/executor.py b/joblib/executor.py new file mode 100644 index 0000000000000000000000000000000000000000..60aae8f7a8ed4d48116addfdeb9bd213152eed27 --- /dev/null +++ b/joblib/executor.py @@ -0,0 +1,131 @@ +"""Utility function to construct a loky.ReusableExecutor with custom pickler. + +This module provides efficient ways of working with data stored in +shared memory with numpy.memmap arrays without inducing any memory +copy between the parent and child processes. +""" +# Author: Thomas Moreau +# Copyright: 2017, Thomas Moreau +# License: BSD 3 clause + +from ._memmapping_reducer import TemporaryResourcesManager, get_memmapping_reducers +from .externals.loky.reusable_executor import _ReusablePoolExecutor + +_executor_args = None + + +def get_memmapping_executor(n_jobs, **kwargs): + return MemmappingExecutor.get_memmapping_executor(n_jobs, **kwargs) + + +class MemmappingExecutor(_ReusablePoolExecutor): + @classmethod + def get_memmapping_executor( + cls, + n_jobs, + timeout=300, + initializer=None, + initargs=(), + env=None, + temp_folder=None, + context_id=None, + **backend_args, + ): + """Factory for ReusableExecutor with automatic memmapping for large + numpy arrays. + """ + global _executor_args + # Check if we can reuse the executor here instead of deferring the test + # to loky as the reducers are objects that changes at each call. + executor_args = backend_args.copy() + executor_args.update(env if env else {}) + executor_args.update( + dict(timeout=timeout, initializer=initializer, initargs=initargs) + ) + reuse = _executor_args is None or _executor_args == executor_args + _executor_args = executor_args + + manager = TemporaryResourcesManager(temp_folder) + + # reducers access the temporary folder in which to store temporary + # pickles through a call to manager.resolve_temp_folder_name. resolving + # the folder name dynamically is useful to use different folders across + # calls of a same reusable executor + job_reducers, result_reducers = get_memmapping_reducers( + unlink_on_gc_collect=True, + temp_folder_resolver=manager.resolve_temp_folder_name, + **backend_args, + ) + _executor, executor_is_reused = super().get_reusable_executor( + n_jobs, + job_reducers=job_reducers, + result_reducers=result_reducers, + reuse=reuse, + timeout=timeout, + initializer=initializer, + initargs=initargs, + env=env, + ) + + if not executor_is_reused: + # Only set a _temp_folder_manager for new executors. Reused + # executors already have a _temporary_folder_manager that must not + # be re-assigned like that because it is referenced in various + # places in the reducing machinery of the executor. + _executor._temp_folder_manager = manager + + if context_id is not None: + # Only register the specified context once we know which manager + # the current executor is using, in order to not register an atexit + # finalizer twice for the same folder. + _executor._temp_folder_manager.register_new_context(context_id) + + return _executor + + def terminate(self, kill_workers=False): + self.shutdown(kill_workers=kill_workers) + + # When workers are killed in a brutal manner, they cannot execute the + # finalizer of their shared memmaps. The refcount of those memmaps may + # be off by an unknown number, so instead of decref'ing them, we force + # delete the whole temporary folder, and unregister them. There is no + # risk of PermissionError at folder deletion because at this + # point, all child processes are dead, so all references to temporary + # memmaps are closed. Otherwise, just try to delete as much as possible + # with allow_non_empty=True but if we can't, it will be clean up later + # on by the resource_tracker. + with self._submit_resize_lock: + self._temp_folder_manager._clean_temporary_resources( + force=kill_workers, allow_non_empty=True + ) + + @property + def _temp_folder(self): + # Legacy property in tests. could be removed if we refactored the + # memmapping tests. SHOULD ONLY BE USED IN TESTS! + # We cache this property because it is called late in the tests - at + # this point, all context have been unregistered, and + # resolve_temp_folder_name raises an error. + if getattr(self, "_cached_temp_folder", None) is not None: + return self._cached_temp_folder + else: + self._cached_temp_folder = ( + self._temp_folder_manager.resolve_temp_folder_name() + ) # noqa + return self._cached_temp_folder + + +class _TestingMemmappingExecutor(MemmappingExecutor): + """Wrapper around ReusableExecutor to ease memmapping testing with Pool + and Executor. This is only for testing purposes. + + """ + + def apply_async(self, func, args): + """Schedule a func to be run""" + future = self.submit(func, *args) + future.get = future.result + return future + + def map(self, f, *args): + return list(super().map(f, *args)) diff --git a/joblib/hashing.py b/joblib/hashing.py new file mode 100644 index 0000000000000000000000000000000000000000..2055acf85cbd50a81a265c02f6d9dada554424fa --- /dev/null +++ b/joblib/hashing.py @@ -0,0 +1,270 @@ +""" +Fast cryptographic hash of Python objects, with a special case for fast +hashing of numpy arrays. +""" + +# Author: Gael Varoquaux +# Copyright (c) 2009 Gael Varoquaux +# License: BSD Style, 3 clauses. + +import decimal +import hashlib +import io +import pickle +import struct +import sys +import types + +Pickler = pickle._Pickler + + +class _ConsistentSet(object): + """Class used to ensure the hash of Sets is preserved + whatever the order of its items. + """ + + def __init__(self, set_sequence): + # Forces order of elements in set to ensure consistent hash. + try: + # Trying first to order the set assuming the type of elements is + # consistent and orderable. + # This fails on python 3 when elements are unorderable + # but we keep it in a try as it's faster. + self._sequence = sorted(set_sequence) + except (TypeError, decimal.InvalidOperation): + # If elements are unorderable, sorting them using their hash. + # This is slower but works in any case. + self._sequence = sorted((hash(e) for e in set_sequence)) + + +class _MyHash(object): + """Class used to hash objects that won't normally pickle""" + + def __init__(self, *args): + self.args = args + + +class Hasher(Pickler): + """A subclass of pickler, to do cryptographic hashing, rather than + pickling. This is used to produce a unique hash of the given + Python object that is not necessarily cryptographically secure. + """ + + def __init__(self, hash_name="md5"): + self.stream = io.BytesIO() + # By default we want a pickle protocol that only changes with + # the major python version and not the minor one + protocol = 3 + Pickler.__init__(self, self.stream, protocol=protocol) + # Initialise the hash obj + self._hash = hashlib.new(hash_name, usedforsecurity=False) + + def hash(self, obj, return_digest=True): + try: + self.dump(obj) + except pickle.PicklingError as e: + e.args += ("PicklingError while hashing %r: %r" % (obj, e),) + raise + dumps = self.stream.getvalue() + self._hash.update(dumps) + if return_digest: + return self._hash.hexdigest() + + def save(self, obj): + if isinstance(obj, (types.MethodType, type({}.pop))): + # the Pickler cannot pickle instance methods; here we decompose + # them into components that make them uniquely identifiable + if hasattr(obj, "__func__"): + func_name = obj.__func__.__name__ + else: + func_name = obj.__name__ + inst = obj.__self__ + if type(inst) is type(pickle): + obj = _MyHash(func_name, inst.__name__) + elif inst is None: + # type(None) or type(module) do not pickle + obj = _MyHash(func_name, inst) + else: + cls = obj.__self__.__class__ + obj = _MyHash(func_name, inst, cls) + Pickler.save(self, obj) + + def memoize(self, obj): + # We want hashing to be sensitive to value instead of reference. + # For example we want ['aa', 'aa'] and ['aa', 'aaZ'[:2]] + # to hash to the same value and that's why we disable memoization + # for strings + if isinstance(obj, (bytes, str)): + return + Pickler.memoize(self, obj) + + # The dispatch table of the pickler is not accessible in Python + # 3, as these lines are only bugware for IPython, we skip them. + def save_global(self, obj, name=None, pack=struct.pack): + # We have to override this method in order to deal with objects + # defined interactively in IPython that are not injected in + # __main__ + kwargs = dict(name=name, pack=pack) + del kwargs["pack"] + try: + Pickler.save_global(self, obj, **kwargs) + except pickle.PicklingError: + Pickler.save_global(self, obj, **kwargs) + module = getattr(obj, "__module__", None) + if module == "__main__": + my_name = name + if my_name is None: + my_name = obj.__name__ + mod = sys.modules[module] + if not hasattr(mod, my_name): + # IPython doesn't inject the variables define + # interactively in __main__ + setattr(mod, my_name, obj) + + dispatch = Pickler.dispatch.copy() + # builtin + dispatch[type(len)] = save_global + # type + dispatch[type(object)] = save_global + # classobj + dispatch[type(Pickler)] = save_global + # function + dispatch[type(pickle.dump)] = save_global + + # We use *args in _batch_setitems signature because _batch_setitems has an + # additional 'obj' argument in Python 3.14 + def _batch_setitems(self, items, *args): + # forces order of keys in dict to ensure consistent hash. + try: + # Trying first to compare dict assuming the type of keys is + # consistent and orderable. + # This fails on python 3 when keys are unorderable + # but we keep it in a try as it's faster. + Pickler._batch_setitems(self, iter(sorted(items)), *args) + except TypeError: + # If keys are unorderable, sorting them using their hash. This is + # slower but works in any case. + Pickler._batch_setitems( + self, iter(sorted((hash(k), v) for k, v in items)), *args + ) + + def save_set(self, set_items): + # forces order of items in Set to ensure consistent hash + Pickler.save(self, _ConsistentSet(set_items)) + + dispatch[type(set())] = save_set + + +class NumpyHasher(Hasher): + """Special case the hasher for when numpy is loaded.""" + + def __init__(self, hash_name="md5", coerce_mmap=False): + """ + Parameters + ---------- + hash_name: string + The hash algorithm to be used + coerce_mmap: boolean + Make no difference between np.memmap and np.ndarray + objects. + """ + self.coerce_mmap = coerce_mmap + Hasher.__init__(self, hash_name=hash_name) + # delayed import of numpy, to avoid tight coupling + import numpy as np + + self.np = np + if hasattr(np, "getbuffer"): + self._getbuffer = np.getbuffer + else: + self._getbuffer = memoryview + + def save(self, obj): + """Subclass the save method, to hash ndarray subclass, rather + than pickling them. Off course, this is a total abuse of + the Pickler class. + """ + if isinstance(obj, self.np.ndarray) and not obj.dtype.hasobject: + # Compute a hash of the object + # The update function of the hash requires a c_contiguous buffer. + if obj.shape == (): + # 0d arrays need to be flattened because viewing them as bytes + # raises a ValueError exception. + obj_c_contiguous = obj.flatten() + elif obj.flags.c_contiguous: + obj_c_contiguous = obj + elif obj.flags.f_contiguous: + obj_c_contiguous = obj.T + else: + # Cater for non-single-segment arrays: this creates a + # copy, and thus alleviates this issue. + # XXX: There might be a more efficient way of doing this + obj_c_contiguous = obj.flatten() + + # memoryview is not supported for some dtypes, e.g. datetime64, see + # https://github.com/numpy/numpy/issues/4983. The + # workaround is to view the array as bytes before + # taking the memoryview. + self._hash.update(self._getbuffer(obj_c_contiguous.view(self.np.uint8))) + + # We store the class, to be able to distinguish between + # Objects with the same binary content, but different + # classes. + if self.coerce_mmap and isinstance(obj, self.np.memmap): + # We don't make the difference between memmap and + # normal ndarrays, to be able to reload previously + # computed results with memmap. + klass = self.np.ndarray + else: + klass = obj.__class__ + # We also return the dtype and the shape, to distinguish + # different views on the same data with different dtypes. + + # The object will be pickled by the pickler hashed at the end. + obj = (klass, ("HASHED", obj.dtype, obj.shape, obj.strides)) + elif isinstance(obj, self.np.dtype): + # numpy.dtype consistent hashing is tricky to get right. This comes + # from the fact that atomic np.dtype objects are interned: + # ``np.dtype('f4') is np.dtype('f4')``. The situation is + # complicated by the fact that this interning does not resist a + # simple pickle.load/dump roundtrip: + # ``pickle.loads(pickle.dumps(np.dtype('f4'))) is not + # np.dtype('f4') Because pickle relies on memoization during + # pickling, it is easy to + # produce different hashes for seemingly identical objects, such as + # ``[np.dtype('f4'), np.dtype('f4')]`` + # and ``[np.dtype('f4'), pickle.loads(pickle.dumps('f4'))]``. + # To prevent memoization from interfering with hashing, we isolate + # the serialization (and thus the pickle memoization) of each dtype + # using each time a different ``pickle.dumps`` call unrelated to + # the current Hasher instance. + self._hash.update("_HASHED_DTYPE".encode("utf-8")) + self._hash.update(pickle.dumps(obj)) + return + Hasher.save(self, obj) + + +def hash(obj, hash_name="md5", coerce_mmap=False): + """Quick calculation of a hash to identify uniquely Python objects + containing numpy arrays. + + Parameters + ---------- + hash_name: 'md5' or 'sha1' + Hashing algorithm used. sha1 is supposedly safer, but md5 is + faster. + coerce_mmap: boolean + Make no difference between np.memmap and np.ndarray + """ + valid_hash_names = ("md5", "sha1") + if hash_name not in valid_hash_names: + raise ValueError( + "Valid options for 'hash_name' are {}. Got hash_name={!r} instead.".format( + valid_hash_names, hash_name + ) + ) + if "numpy" in sys.modules: + hasher = NumpyHasher(hash_name=hash_name, coerce_mmap=coerce_mmap) + else: + hasher = Hasher(hash_name=hash_name) + return hasher.hash(obj) diff --git a/joblib/numpy_pickle.py b/joblib/numpy_pickle.py new file mode 100644 index 0000000000000000000000000000000000000000..169016d818102f9045f71a67d5f9b40b882f031c --- /dev/null +++ b/joblib/numpy_pickle.py @@ -0,0 +1,756 @@ +"""Utilities for fast persistence of big data, with optional compression.""" + +# Author: Gael Varoquaux +# Copyright (c) 2009 Gael Varoquaux +# License: BSD Style, 3 clauses. + +import io +import os +import pickle +import warnings +from pathlib import Path + +from .backports import make_memmap +from .compressor import ( + _COMPRESSORS, + LZ4_NOT_INSTALLED_ERROR, + BinaryZlibFile, + BZ2CompressorWrapper, + GzipCompressorWrapper, + LZ4CompressorWrapper, + LZMACompressorWrapper, + XZCompressorWrapper, + ZlibCompressorWrapper, + lz4, + register_compressor, +) + +# For compatibility with old versions of joblib, we need ZNDArrayWrapper +# to be visible in the current namespace. +from .numpy_pickle_compat import ( + NDArrayWrapper, + ZNDArrayWrapper, # noqa: F401 + load_compatibility, +) +from .numpy_pickle_utils import ( + BUFFER_SIZE, + Pickler, + Unpickler, + _ensure_native_byte_order, + _read_bytes, + _reconstruct, + _validate_fileobject_and_memmap, + _write_fileobject, +) + +# Register supported compressors +register_compressor("zlib", ZlibCompressorWrapper()) +register_compressor("gzip", GzipCompressorWrapper()) +register_compressor("bz2", BZ2CompressorWrapper()) +register_compressor("lzma", LZMACompressorWrapper()) +register_compressor("xz", XZCompressorWrapper()) +register_compressor("lz4", LZ4CompressorWrapper()) + + +############################################################################### +# Utility objects for persistence. + +# For convenience, 16 bytes are used to be sure to cover all the possible +# dtypes' alignments. For reference, see: +# https://numpy.org/devdocs/dev/alignment.html +NUMPY_ARRAY_ALIGNMENT_BYTES = 16 + + +class NumpyArrayWrapper(object): + """An object to be persisted instead of numpy arrays. + + This object is used to hack into the pickle machinery and read numpy + array data from our custom persistence format. + More precisely, this object is used for: + * carrying the information of the persisted array: subclass, shape, order, + dtype. Those ndarray metadata are used to correctly reconstruct the array + with low level numpy functions. + * determining if memmap is allowed on the array. + * reading the array bytes from a file. + * reading the array using memorymap from a file. + * writing the array bytes to a file. + + Attributes + ---------- + subclass: numpy.ndarray subclass + Determine the subclass of the wrapped array. + shape: numpy.ndarray shape + Determine the shape of the wrapped array. + order: {'C', 'F'} + Determine the order of wrapped array data. 'C' is for C order, 'F' is + for fortran order. + dtype: numpy.ndarray dtype + Determine the data type of the wrapped array. + allow_mmap: bool + Determine if memory mapping is allowed on the wrapped array. + Default: False. + """ + + def __init__( + self, + subclass, + shape, + order, + dtype, + allow_mmap=False, + numpy_array_alignment_bytes=NUMPY_ARRAY_ALIGNMENT_BYTES, + ): + """Constructor. Store the useful information for later.""" + self.subclass = subclass + self.shape = shape + self.order = order + self.dtype = dtype + self.allow_mmap = allow_mmap + # We make numpy_array_alignment_bytes an instance attribute to allow us + # to change our mind about the default alignment and still load the old + # pickles (with the previous alignment) correctly + self.numpy_array_alignment_bytes = numpy_array_alignment_bytes + + def safe_get_numpy_array_alignment_bytes(self): + # NumpyArrayWrapper instances loaded from joblib <= 1.1 pickles don't + # have an numpy_array_alignment_bytes attribute + return getattr(self, "numpy_array_alignment_bytes", None) + + def write_array(self, array, pickler): + """Write array bytes to pickler file handle. + + This function is an adaptation of the numpy write_array function + available in version 1.10.1 in numpy/lib/format.py. + """ + # Set buffer size to 16 MiB to hide the Python loop overhead. + buffersize = max(16 * 1024**2 // array.itemsize, 1) + if array.dtype.hasobject: + # We contain Python objects so we cannot write out the data + # directly. Instead, we will pickle it out with version 5 of the + # pickle protocol. + pickle.dump(array, pickler.file_handle, protocol=5) + else: + numpy_array_alignment_bytes = self.safe_get_numpy_array_alignment_bytes() + if numpy_array_alignment_bytes is not None: + current_pos = pickler.file_handle.tell() + pos_after_padding_byte = current_pos + 1 + padding_length = numpy_array_alignment_bytes - ( + pos_after_padding_byte % numpy_array_alignment_bytes + ) + # A single byte is written that contains the padding length in + # bytes + padding_length_byte = int.to_bytes( + padding_length, length=1, byteorder="little" + ) + pickler.file_handle.write(padding_length_byte) + + if padding_length != 0: + padding = b"\xff" * padding_length + pickler.file_handle.write(padding) + + for chunk in pickler.np.nditer( + array, + flags=["external_loop", "buffered", "zerosize_ok"], + buffersize=buffersize, + order=self.order, + ): + pickler.file_handle.write(chunk.tobytes("C")) + + def read_array(self, unpickler, ensure_native_byte_order): + """Read array from unpickler file handle. + + This function is an adaptation of the numpy read_array function + available in version 1.10.1 in numpy/lib/format.py. + """ + if len(self.shape) == 0: + count = 1 + else: + # joblib issue #859: we cast the elements of self.shape to int64 to + # prevent a potential overflow when computing their product. + shape_int64 = [unpickler.np.int64(x) for x in self.shape] + count = unpickler.np.multiply.reduce(shape_int64) + # Now read the actual data. + if self.dtype.hasobject: + # The array contained Python objects. We need to unpickle the data. + array = pickle.load(unpickler.file_handle) + else: + numpy_array_alignment_bytes = self.safe_get_numpy_array_alignment_bytes() + if numpy_array_alignment_bytes is not None: + padding_byte = unpickler.file_handle.read(1) + padding_length = int.from_bytes(padding_byte, byteorder="little") + if padding_length != 0: + unpickler.file_handle.read(padding_length) + + # This is not a real file. We have to read it the + # memory-intensive way. + # crc32 module fails on reads greater than 2 ** 32 bytes, + # breaking large reads from gzip streams. Chunk reads to + # BUFFER_SIZE bytes to avoid issue and reduce memory overhead + # of the read. In non-chunked case count < max_read_count, so + # only one read is performed. + max_read_count = BUFFER_SIZE // min(BUFFER_SIZE, self.dtype.itemsize) + + array = unpickler.np.empty(count, dtype=self.dtype) + for i in range(0, count, max_read_count): + read_count = min(max_read_count, count - i) + read_size = int(read_count * self.dtype.itemsize) + data = _read_bytes(unpickler.file_handle, read_size, "array data") + array[i : i + read_count] = unpickler.np.frombuffer( + data, dtype=self.dtype, count=read_count + ) + del data + + if self.order == "F": + array.shape = self.shape[::-1] + array = array.transpose() + else: + array.shape = self.shape + + if ensure_native_byte_order: + # Detect byte order mismatch and swap as needed. + array = _ensure_native_byte_order(array) + + return array + + def read_mmap(self, unpickler): + """Read an array using numpy memmap.""" + current_pos = unpickler.file_handle.tell() + offset = current_pos + numpy_array_alignment_bytes = self.safe_get_numpy_array_alignment_bytes() + + if numpy_array_alignment_bytes is not None: + padding_byte = unpickler.file_handle.read(1) + padding_length = int.from_bytes(padding_byte, byteorder="little") + # + 1 is for the padding byte + offset += padding_length + 1 + + if unpickler.mmap_mode == "w+": + unpickler.mmap_mode = "r+" + + marray = make_memmap( + unpickler.filename, + dtype=self.dtype, + shape=self.shape, + order=self.order, + mode=unpickler.mmap_mode, + offset=offset, + ) + # update the offset so that it corresponds to the end of the read array + unpickler.file_handle.seek(offset + marray.nbytes) + + if ( + numpy_array_alignment_bytes is None + and current_pos % NUMPY_ARRAY_ALIGNMENT_BYTES != 0 + ): + message = ( + f"The memmapped array {marray} loaded from the file " + f"{unpickler.file_handle.name} is not byte aligned. " + "This may cause segmentation faults if this memmapped array " + "is used in some libraries like BLAS or PyTorch. " + "To get rid of this warning, regenerate your pickle file " + "with joblib >= 1.2.0. " + "See https://github.com/joblib/joblib/issues/563 " + "for more details" + ) + warnings.warn(message) + + return marray + + def read(self, unpickler, ensure_native_byte_order): + """Read the array corresponding to this wrapper. + + Use the unpickler to get all information to correctly read the array. + + Parameters + ---------- + unpickler: NumpyUnpickler + ensure_native_byte_order: bool + If true, coerce the array to use the native endianness of the + host system. + + Returns + ------- + array: numpy.ndarray + + """ + # When requested, only use memmap mode if allowed. + if unpickler.mmap_mode is not None and self.allow_mmap: + assert not ensure_native_byte_order, ( + "Memmaps cannot be coerced to a given byte order, " + "this code path is impossible." + ) + array = self.read_mmap(unpickler) + else: + array = self.read_array(unpickler, ensure_native_byte_order) + + # Manage array subclass case + if hasattr(array, "__array_prepare__") and self.subclass not in ( + unpickler.np.ndarray, + unpickler.np.memmap, + ): + # We need to reconstruct another subclass + new_array = _reconstruct(self.subclass, (0,), "b") + return new_array.__array_prepare__(array) + else: + return array + + +############################################################################### +# Pickler classes + + +class NumpyPickler(Pickler): + """A pickler to persist big data efficiently. + + The main features of this object are: + * persistence of numpy arrays in a single file. + * optional compression with a special care on avoiding memory copies. + + Attributes + ---------- + fp: file + File object handle used for serializing the input object. + protocol: int, optional + Pickle protocol used. Default is pickle.DEFAULT_PROTOCOL. + """ + + dispatch = Pickler.dispatch.copy() + + def __init__(self, fp, protocol=None): + self.file_handle = fp + self.buffered = isinstance(self.file_handle, BinaryZlibFile) + + # By default we want a pickle protocol that only changes with + # the major python version and not the minor one + if protocol is None: + protocol = pickle.DEFAULT_PROTOCOL + + Pickler.__init__(self, self.file_handle, protocol=protocol) + # delayed import of numpy, to avoid tight coupling + try: + import numpy as np + except ImportError: + np = None + self.np = np + + def _create_array_wrapper(self, array): + """Create and returns a numpy array wrapper from a numpy array.""" + order = ( + "F" if (array.flags.f_contiguous and not array.flags.c_contiguous) else "C" + ) + allow_mmap = not self.buffered and not array.dtype.hasobject + + kwargs = {} + try: + self.file_handle.tell() + except io.UnsupportedOperation: + kwargs = {"numpy_array_alignment_bytes": None} + + wrapper = NumpyArrayWrapper( + type(array), + array.shape, + order, + array.dtype, + allow_mmap=allow_mmap, + **kwargs, + ) + + return wrapper + + def save(self, obj): + """Subclass the Pickler `save` method. + + This is a total abuse of the Pickler class in order to use the numpy + persistence function `save` instead of the default pickle + implementation. The numpy array is replaced by a custom wrapper in the + pickle persistence stack and the serialized array is written right + after in the file. Warning: the file produced does not follow the + pickle format. As such it can not be read with `pickle.load`. + """ + if self.np is not None and type(obj) in ( + self.np.ndarray, + self.np.matrix, + self.np.memmap, + ): + if type(obj) is self.np.memmap: + # Pickling doesn't work with memmapped arrays + obj = self.np.asanyarray(obj) + + # The array wrapper is pickled instead of the real array. + wrapper = self._create_array_wrapper(obj) + Pickler.save(self, wrapper) + + # A framer was introduced with pickle protocol 4 and we want to + # ensure the wrapper object is written before the numpy array + # buffer in the pickle file. + # See https://www.python.org/dev/peps/pep-3154/#framing to get + # more information on the framer behavior. + if self.proto >= 4: + self.framer.commit_frame(force=True) + + # And then array bytes are written right after the wrapper. + wrapper.write_array(obj, self) + return + + return Pickler.save(self, obj) + + +class NumpyUnpickler(Unpickler): + """A subclass of the Unpickler to unpickle our numpy pickles. + + Attributes + ---------- + mmap_mode: str + The memorymap mode to use for reading numpy arrays. + file_handle: file_like + File object to unpickle from. + ensure_native_byte_order: bool + If True, coerce the array to use the native endianness of the + host system. + filename: str + Name of the file to unpickle from. It should correspond to file_handle. + This parameter is required when using mmap_mode. + np: module + Reference to numpy module if numpy is installed else None. + + """ + + dispatch = Unpickler.dispatch.copy() + + def __init__(self, filename, file_handle, ensure_native_byte_order, mmap_mode=None): + # The next line is for backward compatibility with pickle generated + # with joblib versions less than 0.10. + self._dirname = os.path.dirname(filename) + + self.mmap_mode = mmap_mode + self.file_handle = file_handle + # filename is required for numpy mmap mode. + self.filename = filename + self.compat_mode = False + self.ensure_native_byte_order = ensure_native_byte_order + Unpickler.__init__(self, self.file_handle) + try: + import numpy as np + except ImportError: + np = None + self.np = np + + def load_build(self): + """Called to set the state of a newly created object. + + We capture it to replace our place-holder objects, NDArrayWrapper or + NumpyArrayWrapper, by the array we are interested in. We + replace them directly in the stack of pickler. + NDArrayWrapper is used for backward compatibility with joblib <= 0.9. + """ + Unpickler.load_build(self) + + # For backward compatibility, we support NDArrayWrapper objects. + if isinstance(self.stack[-1], (NDArrayWrapper, NumpyArrayWrapper)): + if self.np is None: + raise ImportError( + "Trying to unpickle an ndarray, but numpy didn't import correctly" + ) + array_wrapper = self.stack.pop() + # If any NDArrayWrapper is found, we switch to compatibility mode, + # this will be used to raise a DeprecationWarning to the user at + # the end of the unpickling. + if isinstance(array_wrapper, NDArrayWrapper): + self.compat_mode = True + _array_payload = array_wrapper.read(self) + else: + _array_payload = array_wrapper.read(self, self.ensure_native_byte_order) + + self.stack.append(_array_payload) + + # Be careful to register our new method. + dispatch[pickle.BUILD[0]] = load_build + + +############################################################################### +# Utility functions + + +def dump(value, filename, compress=0, protocol=None): + """Persist an arbitrary Python object into one file. + + Read more in the :ref:`User Guide `. + + Parameters + ---------- + value: any Python object + The object to store to disk. + filename: str, pathlib.Path, or file object. + The file object or path of the file in which it is to be stored. + The compression method corresponding to one of the supported filename + extensions ('.z', '.gz', '.bz2', '.xz' or '.lzma') will be used + automatically. + compress: int from 0 to 9 or bool or 2-tuple, optional + Optional compression level for the data. 0 or False is no compression. + Higher value means more compression, but also slower read and + write times. Using a value of 3 is often a good compromise. + See the notes for more details. + If compress is True, the compression level used is 3. + If compress is a 2-tuple, the first element must correspond to a string + between supported compressors (e.g 'zlib', 'gzip', 'bz2', 'lzma' + 'xz'), the second element must be an integer from 0 to 9, corresponding + to the compression level. + protocol: int, optional + Pickle protocol, see pickle.dump documentation for more details. + + Returns + ------- + filenames: list of strings + The list of file names in which the data is stored. If + compress is false, each array is stored in a different file. + + See Also + -------- + joblib.load : corresponding loader + + Notes + ----- + Memmapping on load cannot be used for compressed files. Thus + using compression can significantly slow down loading. In + addition, compressed files take up extra memory during + dump and load. + + """ + + if Path is not None and isinstance(filename, Path): + filename = str(filename) + + is_filename = isinstance(filename, str) + is_fileobj = hasattr(filename, "write") + + compress_method = "zlib" # zlib is the default compression method. + if compress is True: + # By default, if compress is enabled, we want the default compress + # level of the compressor. + compress_level = None + elif isinstance(compress, tuple): + # a 2-tuple was set in compress + if len(compress) != 2: + raise ValueError( + "Compress argument tuple should contain exactly 2 elements: " + "(compress method, compress level), you passed {}".format(compress) + ) + compress_method, compress_level = compress + elif isinstance(compress, str): + compress_method = compress + compress_level = None # Use default compress level + compress = (compress_method, compress_level) + else: + compress_level = compress + + if compress_method == "lz4" and lz4 is None: + raise ValueError(LZ4_NOT_INSTALLED_ERROR) + + if ( + compress_level is not None + and compress_level is not False + and compress_level not in range(10) + ): + # Raising an error if a non valid compress level is given. + raise ValueError( + 'Non valid compress level given: "{}". Possible values are {}.'.format( + compress_level, list(range(10)) + ) + ) + + if compress_method not in _COMPRESSORS: + # Raising an error if an unsupported compression method is given. + raise ValueError( + 'Non valid compression method given: "{}". Possible values are {}.'.format( + compress_method, _COMPRESSORS + ) + ) + + if not is_filename and not is_fileobj: + # People keep inverting arguments, and the resulting error is + # incomprehensible + raise ValueError( + "Second argument should be a filename or a file-like object, " + "%s (type %s) was given." % (filename, type(filename)) + ) + + if is_filename and not isinstance(compress, tuple): + # In case no explicit compression was requested using both compression + # method and level in a tuple and the filename has an explicit + # extension, we select the corresponding compressor. + + # unset the variable to be sure no compression level is set afterwards. + compress_method = None + for name, compressor in _COMPRESSORS.items(): + if filename.endswith(compressor.extension): + compress_method = name + + if compress_method in _COMPRESSORS and compress_level == 0: + # we choose the default compress_level in case it was not given + # as an argument (using compress). + compress_level = None + + if compress_level != 0: + with _write_fileobject( + filename, compress=(compress_method, compress_level) + ) as f: + NumpyPickler(f, protocol=protocol).dump(value) + elif is_filename: + with open(filename, "wb") as f: + NumpyPickler(f, protocol=protocol).dump(value) + else: + NumpyPickler(filename, protocol=protocol).dump(value) + + # If the target container is a file object, nothing is returned. + if is_fileobj: + return + + # For compatibility, the list of created filenames (e.g with one element + # after 0.10.0) is returned by default. + return [filename] + + +def _unpickle(fobj, ensure_native_byte_order, filename="", mmap_mode=None): + """Internal unpickling function.""" + # We are careful to open the file handle early and keep it open to + # avoid race-conditions on renames. + # That said, if data is stored in companion files, which can be + # the case with the old persistence format, moving the directory + # will create a race when joblib tries to access the companion + # files. + unpickler = NumpyUnpickler( + filename, fobj, ensure_native_byte_order, mmap_mode=mmap_mode + ) + obj = None + try: + obj = unpickler.load() + if unpickler.compat_mode: + warnings.warn( + "The file '%s' has been generated with a " + "joblib version less than 0.10. " + "Please regenerate this pickle file." % filename, + DeprecationWarning, + stacklevel=3, + ) + except UnicodeDecodeError as exc: + # More user-friendly error message + new_exc = ValueError( + "You may be trying to read with " + "python 3 a joblib pickle generated with python 2. " + "This feature is not supported by joblib." + ) + new_exc.__cause__ = exc + raise new_exc + return obj + + +def load_temporary_memmap(filename, mmap_mode, unlink_on_gc_collect): + from ._memmapping_reducer import JOBLIB_MMAPS, add_maybe_unlink_finalizer + + with open(filename, "rb") as f: + with _validate_fileobject_and_memmap(f, filename, mmap_mode) as ( + fobj, + validated_mmap_mode, + ): + # Memmap are used for interprocess communication, which should + # keep the objects untouched. We pass `ensure_native_byte_order=False` + # to remain consistent with the loading behavior of non-memmaped arrays + # in workers, where the byte order is preserved. + # Note that we do not implement endianness change for memmaps, as this + # would result in inconsistent behavior. + obj = _unpickle( + fobj, + ensure_native_byte_order=False, + filename=filename, + mmap_mode=validated_mmap_mode, + ) + + JOBLIB_MMAPS.add(obj.filename) + if unlink_on_gc_collect: + add_maybe_unlink_finalizer(obj) + return obj + + +def load(filename, mmap_mode=None, ensure_native_byte_order="auto"): + """Reconstruct a Python object from a file persisted with joblib.dump. + + Read more in the :ref:`User Guide `. + + WARNING: joblib.load relies on the pickle module and can therefore + execute arbitrary Python code. It should therefore never be used + to load files from untrusted sources. + + Parameters + ---------- + filename: str, pathlib.Path, or file object. + The file object or path of the file from which to load the object + mmap_mode: {None, 'r+', 'r', 'w+', 'c'}, optional + If not None, the arrays are memory-mapped from the disk. This + mode has no effect for compressed files. Note that in this + case the reconstructed object might no longer match exactly + the originally pickled object. + ensure_native_byte_order: bool, or 'auto', default=='auto' + If True, ensures that the byte order of the loaded arrays matches the + native byte ordering (or _endianness_) of the host system. This is not + compatible with memory-mapped arrays and using non-null `mmap_mode` + parameter at the same time will raise an error. The default 'auto' + parameter is equivalent to True if `mmap_mode` is None, else False. + + Returns + ------- + result: any Python object + The object stored in the file. + + See Also + -------- + joblib.dump : function to save an object + + Notes + ----- + + This function can load numpy array files saved separately during the + dump. If the mmap_mode argument is given, it is passed to np.load and + arrays are loaded as memmaps. As a consequence, the reconstructed + object might not match the original pickled object. Note that if the + file was saved with compression, the arrays cannot be memmapped. + """ + if ensure_native_byte_order == "auto": + ensure_native_byte_order = mmap_mode is None + + if ensure_native_byte_order and mmap_mode is not None: + raise ValueError( + "Native byte ordering can only be enforced if 'mmap_mode' parameter " + f"is set to None, but got 'mmap_mode={mmap_mode}' instead." + ) + + if Path is not None and isinstance(filename, Path): + filename = str(filename) + + if hasattr(filename, "read"): + fobj = filename + filename = getattr(fobj, "name", "") + with _validate_fileobject_and_memmap(fobj, filename, mmap_mode) as (fobj, _): + obj = _unpickle(fobj, ensure_native_byte_order=ensure_native_byte_order) + else: + with open(filename, "rb") as f: + with _validate_fileobject_and_memmap(f, filename, mmap_mode) as ( + fobj, + validated_mmap_mode, + ): + if isinstance(fobj, str): + # if the returned file object is a string, this means we + # try to load a pickle file generated with an version of + # Joblib so we load it with joblib compatibility function. + return load_compatibility(fobj) + + # A memory-mapped array has to be mapped with the endianness + # it has been written with. Other arrays are coerced to the + # native endianness of the host system. + obj = _unpickle( + fobj, + ensure_native_byte_order=ensure_native_byte_order, + filename=filename, + mmap_mode=validated_mmap_mode, + ) + + return obj diff --git a/joblib/parallel.py b/joblib/parallel.py new file mode 100644 index 0000000000000000000000000000000000000000..452bd3446fb2d590e7a0b7f812f3454f5ee909a0 --- /dev/null +++ b/joblib/parallel.py @@ -0,0 +1,2075 @@ +""" +Helpers for embarrassingly parallel code. +""" +# Author: Gael Varoquaux < gael dot varoquaux at normalesup dot org > +# Copyright: 2010, Gael Varoquaux +# License: BSD 3 clause + +from __future__ import division + +import collections +import functools +import itertools +import os +import queue +import sys +import threading +import time +import warnings +import weakref +from contextlib import nullcontext +from math import floor, log10, sqrt +from multiprocessing import TimeoutError +from numbers import Integral +from uuid import uuid4 + +from ._multiprocessing_helpers import mp + +# Make sure that those two classes are part of the public joblib.parallel API +# so that 3rd party backend implementers can import them from here. +from ._parallel_backends import ( + AutoBatchingMixin, # noqa + FallbackToBackend, + LokyBackend, + MultiprocessingBackend, + ParallelBackendBase, # noqa + SequentialBackend, + ThreadingBackend, +) +from ._utils import _Sentinel, eval_expr +from .disk import memstr_to_bytes +from .logger import Logger, short_format_time + +BACKENDS = { + "threading": ThreadingBackend, + "sequential": SequentialBackend, +} +# name of the backend used by default by Parallel outside of any context +# managed by ``parallel_config`` or ``parallel_backend``. + +# threading is the only backend that is always everywhere +DEFAULT_BACKEND = "threading" +DEFAULT_THREAD_BACKEND = "threading" +DEFAULT_PROCESS_BACKEND = "threading" + +MAYBE_AVAILABLE_BACKENDS = {"multiprocessing", "loky"} + +# if multiprocessing is available, so is loky, we set it as the default +# backend +if mp is not None: + BACKENDS["multiprocessing"] = MultiprocessingBackend + from .externals import loky + + BACKENDS["loky"] = LokyBackend + DEFAULT_BACKEND = "loky" + DEFAULT_PROCESS_BACKEND = "loky" + +# Thread local value that can be overridden by the ``parallel_config`` context +# manager +_backend = threading.local() + + +def _register_dask(): + """Register Dask Backend if called with parallel_config(backend="dask")""" + try: + from ._dask import DaskDistributedBackend + + register_parallel_backend("dask", DaskDistributedBackend) + except ImportError as e: + msg = ( + "To use the dask.distributed backend you must install both " + "the `dask` and distributed modules.\n\n" + "See https://dask.pydata.org/en/latest/install.html for more " + "information." + ) + raise ImportError(msg) from e + + +EXTERNAL_BACKENDS = { + "dask": _register_dask, +} + + +# Sentinels for the default values of the Parallel constructor and +# the parallel_config and parallel_backend context managers +default_parallel_config = { + "backend": _Sentinel(default_value=None), + "n_jobs": _Sentinel(default_value=None), + "verbose": _Sentinel(default_value=0), + "temp_folder": _Sentinel(default_value=None), + "max_nbytes": _Sentinel(default_value="1M"), + "mmap_mode": _Sentinel(default_value="r"), + "prefer": _Sentinel(default_value=None), + "require": _Sentinel(default_value=None), +} + + +VALID_BACKEND_HINTS = ("processes", "threads", None) +VALID_BACKEND_CONSTRAINTS = ("sharedmem", None) + + +def _get_config_param(param, context_config, key): + """Return the value of a parallel config parameter + + Explicitly setting it in Parallel has priority over setting in a + parallel_(config/backend) context manager. + """ + if param is not default_parallel_config[key]: + # param is explicitly set, return it + return param + + if context_config[key] is not default_parallel_config[key]: + # there's a context manager and the key is set, return it + return context_config[key] + + # Otherwise, we are in the default_parallel_config, + # return the default value + return param.default_value + + +def get_active_backend( + prefer=default_parallel_config["prefer"], + require=default_parallel_config["require"], + verbose=default_parallel_config["verbose"], +): + """Return the active default backend""" + backend, config = _get_active_backend(prefer, require, verbose) + n_jobs = _get_config_param(default_parallel_config["n_jobs"], config, "n_jobs") + return backend, n_jobs + + +def _get_active_backend( + prefer=default_parallel_config["prefer"], + require=default_parallel_config["require"], + verbose=default_parallel_config["verbose"], +): + """Return the active default backend""" + + backend_config = getattr(_backend, "config", default_parallel_config) + + backend = _get_config_param( + default_parallel_config["backend"], backend_config, "backend" + ) + + prefer = _get_config_param(prefer, backend_config, "prefer") + require = _get_config_param(require, backend_config, "require") + verbose = _get_config_param(verbose, backend_config, "verbose") + + if prefer not in VALID_BACKEND_HINTS: + raise ValueError( + f"prefer={prefer} is not a valid backend hint, " + f"expected one of {VALID_BACKEND_HINTS}" + ) + if require not in VALID_BACKEND_CONSTRAINTS: + raise ValueError( + f"require={require} is not a valid backend constraint, " + f"expected one of {VALID_BACKEND_CONSTRAINTS}" + ) + if prefer == "processes" and require == "sharedmem": + raise ValueError( + "prefer == 'processes' and require == 'sharedmem' are inconsistent settings" + ) + + explicit_backend = True + if backend is None: + # We are either outside of the scope of any parallel_(config/backend) + # context manager or the context manager did not set a backend. + # create the default backend instance now. + backend = BACKENDS[DEFAULT_BACKEND](nesting_level=0) + explicit_backend = False + + # Try to use the backend set by the user with the context manager. + + nesting_level = backend.nesting_level + uses_threads = getattr(backend, "uses_threads", False) + supports_sharedmem = getattr(backend, "supports_sharedmem", False) + # Force to use thread-based backend if the provided backend does not + # match the shared memory constraint or if the backend is not explicitly + # given and threads are preferred. + force_threads = (require == "sharedmem" and not supports_sharedmem) or ( + not explicit_backend and prefer == "threads" and not uses_threads + ) + force_processes = not explicit_backend and prefer == "processes" and uses_threads + + if force_threads: + # This backend does not match the shared memory constraint: + # fallback to the default thead-based backend. + sharedmem_backend = BACKENDS[DEFAULT_THREAD_BACKEND]( + nesting_level=nesting_level + ) + # Warn the user if we forced the backend to thread-based, while the + # user explicitly specified a non-thread-based backend. + if verbose >= 10 and explicit_backend: + print( + f"Using {sharedmem_backend.__class__.__name__} as " + f"joblib backend instead of {backend.__class__.__name__} " + "as the latter does not provide shared memory semantics." + ) + # Force to n_jobs=1 by default + thread_config = backend_config.copy() + thread_config["n_jobs"] = 1 + return sharedmem_backend, thread_config + + if force_processes: + # This backend does not match the prefer="processes" constraint: + # fallback to the default process-based backend. + process_backend = BACKENDS[DEFAULT_PROCESS_BACKEND](nesting_level=nesting_level) + + return process_backend, backend_config.copy() + + return backend, backend_config + + +class parallel_config: + """Set the default backend or configuration for :class:`~joblib.Parallel`. + + This is an alternative to directly passing keyword arguments to the + :class:`~joblib.Parallel` class constructor. It is particularly useful when + calling into library code that uses joblib internally but does not expose + the various parallel configuration arguments in its own API. + + Parameters + ---------- + backend: str or ParallelBackendBase instance, default=None + If ``backend`` is a string it must match a previously registered + implementation using the :func:`~register_parallel_backend` function. + + By default the following backends are available: + + - 'loky': single-host, process-based parallelism (used by default), + - 'threading': single-host, thread-based parallelism, + - 'multiprocessing': legacy single-host, process-based parallelism. + + 'loky' is recommended to run functions that manipulate Python objects. + 'threading' is a low-overhead alternative that is most efficient for + functions that release the Global Interpreter Lock: e.g. I/O-bound + code or CPU-bound code in a few calls to native code that explicitly + releases the GIL. Note that on some rare systems (such as pyodide), + multiprocessing and loky may not be available, in which case joblib + defaults to threading. + + In addition, if the ``dask`` and ``distributed`` Python packages are + installed, it is possible to use the 'dask' backend for better + scheduling of nested parallel calls without over-subscription and + potentially distribute parallel calls over a networked cluster of + several hosts. + + It is also possible to use the distributed 'ray' backend for + distributing the workload to a cluster of nodes. See more details + in the Examples section below. + + Alternatively the backend can be passed directly as an instance. + + n_jobs: int, default=None + The maximum number of concurrently running jobs, such as the number + of Python worker processes when ``backend="loky"`` or the size of the + thread-pool when ``backend="threading"``. + This argument is converted to an integer, rounded below for float. + If -1 is given, `joblib` tries to use all CPUs. The number of CPUs + ``n_cpus`` is obtained with :func:`~cpu_count`. + For n_jobs below -1, (n_cpus + 1 + n_jobs) are used. For instance, + using ``n_jobs=-2`` will result in all CPUs but one being used. + This argument can also go above ``n_cpus``, which will cause + oversubscription. In some cases, slight oversubscription can be + beneficial, e.g., for tasks with large I/O operations. + If 1 is given, no parallel computing code is used at all, and the + behavior amounts to a simple python `for` loop. This mode is not + compatible with `timeout`. + None is a marker for 'unset' that will be interpreted as n_jobs=1 + unless the call is performed under a :func:`~parallel_config` + context manager that sets another value for ``n_jobs``. + If n_jobs = 0 then a ValueError is raised. + + verbose: int, default=0 + The verbosity level: if non zero, progress messages are + printed. Above 50, the output is sent to stdout. + The frequency of the messages increases with the verbosity level. + If it more than 10, all iterations are reported. + + temp_folder: str or None, default=None + Folder to be used by the pool for memmapping large arrays + for sharing memory with worker processes. If None, this will try in + order: + + - a folder pointed by the ``JOBLIB_TEMP_FOLDER`` environment + variable, + - ``/dev/shm`` if the folder exists and is writable: this is a + RAM disk filesystem available by default on modern Linux + distributions, + - the default system temporary folder that can be + overridden with ``TMP``, ``TMPDIR`` or ``TEMP`` environment + variables, typically ``/tmp`` under Unix operating systems. + + max_nbytes: int, str, or None, optional, default='1M' + Threshold on the size of arrays passed to the workers that + triggers automated memory mapping in temp_folder. Can be an int + in Bytes, or a human-readable string, e.g., '1M' for 1 megabyte. + Use None to disable memmapping of large arrays. + + mmap_mode: {None, 'r+', 'r', 'w+', 'c'}, default='r' + Memmapping mode for numpy arrays passed to workers. None will + disable memmapping, other modes defined in the numpy.memmap doc: + https://numpy.org/doc/stable/reference/generated/numpy.memmap.html + Also, see 'max_nbytes' parameter documentation for more details. + + prefer: str in {'processes', 'threads'} or None, default=None + Soft hint to choose the default backend. + The default process-based backend is 'loky' and the default + thread-based backend is 'threading'. Ignored if the ``backend`` + parameter is specified. + + require: 'sharedmem' or None, default=None + Hard constraint to select the backend. If set to 'sharedmem', + the selected backend will be single-host and thread-based. + + inner_max_num_threads: int, default=None + If not None, overwrites the limit set on the number of threads + usable in some third-party library threadpools like OpenBLAS, + MKL or OpenMP. This is only used with the ``loky`` backend. + + backend_params: dict + Additional parameters to pass to the backend constructor when + backend is a string. + + Notes + ----- + Joblib tries to limit the oversubscription by limiting the number of + threads usable in some third-party library threadpools like OpenBLAS, MKL + or OpenMP. The default limit in each worker is set to + ``max(cpu_count() // effective_n_jobs, 1)`` but this limit can be + overwritten with the ``inner_max_num_threads`` argument which will be used + to set this limit in the child processes. + + .. versionadded:: 1.3 + + Examples + -------- + >>> from operator import neg + >>> with parallel_config(backend='threading'): + ... print(Parallel()(delayed(neg)(i + 1) for i in range(5))) + ... + [-1, -2, -3, -4, -5] + + To use the 'ray' joblib backend add the following lines: + + >>> from ray.util.joblib import register_ray # doctest: +SKIP + >>> register_ray() # doctest: +SKIP + >>> with parallel_config(backend="ray"): # doctest: +SKIP + ... print(Parallel()(delayed(neg)(i + 1) for i in range(5))) + [-1, -2, -3, -4, -5] + + """ + + def __init__( + self, + backend=default_parallel_config["backend"], + *, + n_jobs=default_parallel_config["n_jobs"], + verbose=default_parallel_config["verbose"], + temp_folder=default_parallel_config["temp_folder"], + max_nbytes=default_parallel_config["max_nbytes"], + mmap_mode=default_parallel_config["mmap_mode"], + prefer=default_parallel_config["prefer"], + require=default_parallel_config["require"], + inner_max_num_threads=None, + **backend_params, + ): + # Save the parallel info and set the active parallel config + self.old_parallel_config = getattr(_backend, "config", default_parallel_config) + + backend = self._check_backend(backend, inner_max_num_threads, **backend_params) + + new_config = { + "n_jobs": n_jobs, + "verbose": verbose, + "temp_folder": temp_folder, + "max_nbytes": max_nbytes, + "mmap_mode": mmap_mode, + "prefer": prefer, + "require": require, + "backend": backend, + } + self.parallel_config = self.old_parallel_config.copy() + self.parallel_config.update( + {k: v for k, v in new_config.items() if not isinstance(v, _Sentinel)} + ) + + setattr(_backend, "config", self.parallel_config) + + def _check_backend(self, backend, inner_max_num_threads, **backend_params): + if backend is default_parallel_config["backend"]: + if inner_max_num_threads is not None or len(backend_params) > 0: + raise ValueError( + "inner_max_num_threads and other constructor " + "parameters backend_params are only supported " + "when backend is not None." + ) + return backend + + if isinstance(backend, str): + # Handle non-registered or missing backends + if backend not in BACKENDS: + if backend in EXTERNAL_BACKENDS: + register = EXTERNAL_BACKENDS[backend] + register() + elif backend in MAYBE_AVAILABLE_BACKENDS: + warnings.warn( + f"joblib backend '{backend}' is not available on " + f"your system, falling back to {DEFAULT_BACKEND}.", + UserWarning, + stacklevel=2, + ) + BACKENDS[backend] = BACKENDS[DEFAULT_BACKEND] + else: + raise ValueError( + f"Invalid backend: {backend}, expected one of " + f"{sorted(BACKENDS.keys())}" + ) + + backend = BACKENDS[backend](**backend_params) + else: + if len(backend_params) > 0: + raise ValueError( + "Constructor parameters backend_params are only " + "supported when backend is a string." + ) + + if inner_max_num_threads is not None: + msg = ( + f"{backend.__class__.__name__} does not accept setting the " + "inner_max_num_threads argument." + ) + assert backend.supports_inner_max_num_threads, msg + backend.inner_max_num_threads = inner_max_num_threads + + # If the nesting_level of the backend is not set previously, use the + # nesting level from the previous active_backend to set it + if backend.nesting_level is None: + parent_backend = self.old_parallel_config["backend"] + if parent_backend is default_parallel_config["backend"]: + nesting_level = 0 + else: + nesting_level = parent_backend.nesting_level + backend.nesting_level = nesting_level + + return backend + + def __enter__(self): + return self.parallel_config + + def __exit__(self, type, value, traceback): + self.unregister() + + def unregister(self): + setattr(_backend, "config", self.old_parallel_config) + + +class parallel_backend(parallel_config): + """Change the default backend used by Parallel inside a with block. + + .. warning:: + It is advised to use the :class:`~joblib.parallel_config` context + manager instead, which allows more fine-grained control over the + backend configuration. + + If ``backend`` is a string it must match a previously registered + implementation using the :func:`~register_parallel_backend` function. + + By default the following backends are available: + + - 'loky': single-host, process-based parallelism (used by default), + - 'threading': single-host, thread-based parallelism, + - 'multiprocessing': legacy single-host, process-based parallelism. + + 'loky' is recommended to run functions that manipulate Python objects. + 'threading' is a low-overhead alternative that is most efficient for + functions that release the Global Interpreter Lock: e.g. I/O-bound code or + CPU-bound code in a few calls to native code that explicitly releases the + GIL. Note that on some rare systems (such as Pyodide), + multiprocessing and loky may not be available, in which case joblib + defaults to threading. + + You can also use the `Dask `_ joblib + backend to distribute work across machines. This works well with + scikit-learn estimators with the ``n_jobs`` parameter, for example:: + + >>> import joblib # doctest: +SKIP + >>> from sklearn.model_selection import GridSearchCV # doctest: +SKIP + >>> from dask.distributed import Client, LocalCluster # doctest: +SKIP + + >>> # create a local Dask cluster + >>> cluster = LocalCluster() # doctest: +SKIP + >>> client = Client(cluster) # doctest: +SKIP + >>> grid_search = GridSearchCV(estimator, param_grid, n_jobs=-1) + ... # doctest: +SKIP + >>> with joblib.parallel_backend("dask", scatter=[X, y]): # doctest: +SKIP + ... grid_search.fit(X, y) + + It is also possible to use the distributed 'ray' backend for distributing + the workload to a cluster of nodes. To use the 'ray' joblib backend add + the following lines:: + + >>> from ray.util.joblib import register_ray # doctest: +SKIP + >>> register_ray() # doctest: +SKIP + >>> with parallel_backend("ray"): # doctest: +SKIP + ... print(Parallel()(delayed(neg)(i + 1) for i in range(5))) + [-1, -2, -3, -4, -5] + + Alternatively the backend can be passed directly as an instance. + + By default all available workers will be used (``n_jobs=-1``) unless the + caller passes an explicit value for the ``n_jobs`` parameter. + + This is an alternative to passing a ``backend='backend_name'`` argument to + the :class:`~Parallel` class constructor. It is particularly useful when + calling into library code that uses joblib internally but does not expose + the backend argument in its own API. + + >>> from operator import neg + >>> with parallel_backend('threading'): + ... print(Parallel()(delayed(neg)(i + 1) for i in range(5))) + ... + [-1, -2, -3, -4, -5] + + Joblib also tries to limit the oversubscription by limiting the number of + threads usable in some third-party library threadpools like OpenBLAS, MKL + or OpenMP. The default limit in each worker is set to + ``max(cpu_count() // effective_n_jobs, 1)`` but this limit can be + overwritten with the ``inner_max_num_threads`` argument which will be used + to set this limit in the child processes. + + .. versionadded:: 0.10 + + See Also + -------- + joblib.parallel_config: context manager to change the backend configuration. + """ + + def __init__( + self, backend, n_jobs=-1, inner_max_num_threads=None, **backend_params + ): + super().__init__( + backend=backend, + n_jobs=n_jobs, + inner_max_num_threads=inner_max_num_threads, + **backend_params, + ) + + if self.old_parallel_config is None: + self.old_backend_and_jobs = None + else: + self.old_backend_and_jobs = ( + self.old_parallel_config["backend"], + self.old_parallel_config["n_jobs"], + ) + self.new_backend_and_jobs = ( + self.parallel_config["backend"], + self.parallel_config["n_jobs"], + ) + + def __enter__(self): + return self.new_backend_and_jobs + + +# Under Linux or OS X the default start method of multiprocessing +# can cause third party libraries to crash. Under Python 3.4+ it is possible +# to set an environment variable to switch the default start method from +# 'fork' to 'forkserver' or 'spawn' to avoid this issue albeit at the cost +# of causing semantic changes and some additional pool instantiation overhead. +DEFAULT_MP_CONTEXT = None +if hasattr(mp, "get_context"): + method = os.environ.get("JOBLIB_START_METHOD", "").strip() or None + if method is not None: + DEFAULT_MP_CONTEXT = mp.get_context(method=method) + + +class BatchedCalls(object): + """Wrap a sequence of (func, args, kwargs) tuples as a single callable""" + + def __init__( + self, iterator_slice, backend_and_jobs, reducer_callback=None, pickle_cache=None + ): + self.items = list(iterator_slice) + self._size = len(self.items) + self._reducer_callback = reducer_callback + if isinstance(backend_and_jobs, tuple): + self._backend, self._n_jobs = backend_and_jobs + else: + # this is for backward compatibility purposes. Before 0.12.6, + # nested backends were returned without n_jobs indications. + self._backend, self._n_jobs = backend_and_jobs, None + self._pickle_cache = pickle_cache if pickle_cache is not None else {} + + def __call__(self): + # Set the default nested backend to self._backend but do not set the + # change the default number of processes to -1 + with parallel_config(backend=self._backend, n_jobs=self._n_jobs): + return [func(*args, **kwargs) for func, args, kwargs in self.items] + + def __reduce__(self): + if self._reducer_callback is not None: + self._reducer_callback() + # no need to pickle the callback. + return ( + BatchedCalls, + (self.items, (self._backend, self._n_jobs), None, self._pickle_cache), + ) + + def __len__(self): + return self._size + + +# Possible exit status for a task +TASK_DONE = "Done" +TASK_ERROR = "Error" +TASK_PENDING = "Pending" + + +############################################################################### +# CPU count that works also when multiprocessing has been disabled via +# the JOBLIB_MULTIPROCESSING environment variable +def cpu_count(only_physical_cores=False): + """Return the number of CPUs. + + This delegates to loky.cpu_count that takes into account additional + constraints such as Linux CFS scheduler quotas (typically set by container + runtimes such as docker) and CPU affinity (for instance using the taskset + command on Linux). + + Parameters + ---------- + only_physical_cores : boolean, default=False + If True, does not take hyperthreading / SMT logical cores into account. + + """ + if mp is None: + return 1 + + return loky.cpu_count(only_physical_cores=only_physical_cores) + + +############################################################################### +# For verbosity + + +def _verbosity_filter(index, verbose): + """Returns False for indices increasingly apart, the distance + depending on the value of verbose. + + We use a lag increasing as the square of index + """ + if not verbose: + return True + elif verbose > 10: + return False + if index == 0: + return False + verbose = 0.5 * (11 - verbose) ** 2 + scale = sqrt(index / verbose) + next_scale = sqrt((index + 1) / verbose) + return int(next_scale) == int(scale) + + +############################################################################### +def delayed(function): + """Decorator used to capture the arguments of a function.""" + + def delayed_function(*args, **kwargs): + return function, args, kwargs + + try: + delayed_function = functools.wraps(function)(delayed_function) + except AttributeError: + " functools.wraps fails on some callable objects " + return delayed_function + + +############################################################################### +class BatchCompletionCallBack(object): + """Callback to keep track of completed results and schedule the next tasks. + + This callable is executed by the parent process whenever a worker process + has completed a batch of tasks. + + It is used for progress reporting, to update estimate of the batch + processing duration and to schedule the next batch of tasks to be + processed. + + It is assumed that this callback will always be triggered by the backend + right after the end of a task, in case of success as well as in case of + failure. + """ + + ########################################################################## + # METHODS CALLED BY THE MAIN THREAD # + ########################################################################## + def __init__(self, dispatch_timestamp, batch_size, parallel): + self.dispatch_timestamp = dispatch_timestamp + self.batch_size = batch_size + self.parallel = parallel + self.parallel_call_id = parallel._call_id + self._completion_timeout_counter = None + + # Internals to keep track of the status and outcome of the task. + + # Used to hold a reference to the future-like object returned by the + # backend after launching this task + # This will be set later when calling `register_job`, as it is only + # created once the task has been submitted. + self.job = None + + if not parallel._backend.supports_retrieve_callback: + # The status is only used for asynchronous result retrieval in the + # callback. + self.status = None + else: + # The initial status for the job is TASK_PENDING. + # Once it is done, it will be either TASK_DONE, or TASK_ERROR. + self.status = TASK_PENDING + + def register_job(self, job): + """Register the object returned by `submit`.""" + self.job = job + + def get_result(self, timeout): + """Returns the raw result of the task that was submitted. + + If the task raised an exception rather than returning, this same + exception will be raised instead. + + If the backend supports the retrieval callback, it is assumed that this + method is only called after the result has been registered. It is + ensured by checking that `self.status(timeout)` does not return + TASK_PENDING. In this case, `get_result` directly returns the + registered result (or raise the registered exception). + + For other backends, there are no such assumptions, but `get_result` + still needs to synchronously retrieve the result before it can + return it or raise. It will block at most `self.timeout` seconds + waiting for retrieval to complete, after that it raises a TimeoutError. + """ + + backend = self.parallel._backend + + if backend.supports_retrieve_callback: + # We assume that the result has already been retrieved by the + # callback thread, and is stored internally. It's just waiting to + # be returned. + return self._return_or_raise() + + # For other backends, the main thread needs to run the retrieval step. + try: + result = backend.retrieve_result(self.job, timeout=timeout) + outcome = dict(result=result, status=TASK_DONE) + except BaseException as e: + outcome = dict(result=e, status=TASK_ERROR) + self._register_outcome(outcome) + + return self._return_or_raise() + + def _return_or_raise(self): + try: + if self.status == TASK_ERROR: + raise self._result + return self._result + finally: + del self._result + + def get_status(self, timeout): + """Get the status of the task. + + This function also checks if the timeout has been reached and register + the TimeoutError outcome when it is the case. + """ + if timeout is None or self.status != TASK_PENDING: + return self.status + + # The computation are running and the status is pending. + # Check that we did not wait for this jobs more than `timeout`. + now = time.time() + if self._completion_timeout_counter is None: + self._completion_timeout_counter = now + + if (now - self._completion_timeout_counter) > timeout: + outcome = dict(result=TimeoutError(), status=TASK_ERROR) + self._register_outcome(outcome) + + return self.status + + ########################################################################## + # METHODS CALLED BY CALLBACK THREADS # + ########################################################################## + def __call__(self, *args, **kwargs): + """Function called by the callback thread after a job is completed.""" + + # If the backend doesn't support callback retrievals, the next batch of + # tasks is dispatched regardless. The result will be retrieved by the + # main thread when calling `get_result`. + if not self.parallel._backend.supports_retrieve_callback: + self._dispatch_new() + return + + # If the backend supports retrieving the result in the callback, it + # registers the task outcome (TASK_ERROR or TASK_DONE), and schedules + # the next batch if needed. + with self.parallel._lock: + # Edge case where while the task was processing, the `parallel` + # instance has been reset and a new call has been issued, but the + # worker managed to complete the task and trigger this callback + # call just before being aborted by the reset. + if self.parallel._call_id != self.parallel_call_id: + return + + # When aborting, stop as fast as possible and do not retrieve the + # result as it won't be returned by the Parallel call. + if self.parallel._aborting: + return + + # Retrieves the result of the task in the main process and dispatch + # a new batch if needed. + job_succeeded = self._retrieve_result(*args, **kwargs) + + if job_succeeded: + self._dispatch_new() + + def _dispatch_new(self): + """Schedule the next batch of tasks to be processed.""" + + # This steps ensure that auto-batching works as expected. + this_batch_duration = time.time() - self.dispatch_timestamp + self.parallel._backend.batch_completed(self.batch_size, this_batch_duration) + + # Schedule the next batch of tasks. + with self.parallel._lock: + self.parallel.n_completed_tasks += self.batch_size + self.parallel.print_progress() + if self.parallel._original_iterator is not None: + self.parallel.dispatch_next() + + def _retrieve_result(self, out): + """Fetch and register the outcome of a task. + + Return True if the task succeeded, False otherwise. + This function is only called by backends that support retrieving + the task result in the callback thread. + """ + try: + result = self.parallel._backend.retrieve_result_callback(out) + outcome = dict(status=TASK_DONE, result=result) + except BaseException as e: + # Avoid keeping references to parallel in the error. + e.__traceback__ = None + outcome = dict(result=e, status=TASK_ERROR) + + self._register_outcome(outcome) + return outcome["status"] != TASK_ERROR + + ########################################################################## + # This method can be called either in the main thread # + # or in the callback thread. # + ########################################################################## + def _register_outcome(self, outcome): + """Register the outcome of a task. + + This method can be called only once, future calls will be ignored. + """ + # Covers the edge case where the main thread tries to register a + # `TimeoutError` while the callback thread tries to register a result + # at the same time. + with self.parallel._lock: + if self.status not in (TASK_PENDING, None): + return + self.status = outcome["status"] + + self._result = outcome["result"] + + # Once the result and the status are extracted, the last reference to + # the job can be deleted. + self.job = None + + # As soon as an error as been spotted, early stopping flags are sent to + # the `parallel` instance. + if self.status == TASK_ERROR: + self.parallel._exception = True + self.parallel._aborting = True + + if self.parallel.return_ordered: + return + + with self.parallel._lock: + # For `return_as=generator_unordered`, append the job to the queue + # in the order of completion instead of submission. + self.parallel._jobs.append(self) + + +############################################################################### +def register_parallel_backend(name, factory, make_default=False): + """Register a new Parallel backend factory. + + The new backend can then be selected by passing its name as the backend + argument to the :class:`~Parallel` class. Moreover, the default backend can + be overwritten globally by setting make_default=True. + + The factory can be any callable that takes no argument and return an + instance of ``ParallelBackendBase``. + + Warning: this function is experimental and subject to change in a future + version of joblib. + + .. versionadded:: 0.10 + """ + BACKENDS[name] = factory + if make_default: + global DEFAULT_BACKEND + DEFAULT_BACKEND = name + + +def effective_n_jobs(n_jobs=-1): + """Determine the number of jobs that can actually run in parallel + + n_jobs is the number of workers requested by the callers. Passing n_jobs=-1 + means requesting all available workers for instance matching the number of + CPU cores on the worker host(s). + + This method should return a guesstimate of the number of workers that can + actually perform work concurrently with the currently enabled default + backend. The primary use case is to make it possible for the caller to know + in how many chunks to slice the work. + + In general working on larger data chunks is more efficient (less scheduling + overhead and better use of CPU cache prefetching heuristics) as long as all + the workers have enough work to do. + + Warning: this function is experimental and subject to change in a future + version of joblib. + + .. versionadded:: 0.10 + """ + if n_jobs == 1: + return 1 + + backend, backend_n_jobs = get_active_backend() + if n_jobs is None: + n_jobs = backend_n_jobs + return backend.effective_n_jobs(n_jobs=n_jobs) + + +############################################################################### +class Parallel(Logger): + """Helper class for readable parallel mapping. + + Read more in the :ref:`User Guide `. + + Parameters + ---------- + n_jobs: int, default=None + The maximum number of concurrently running jobs, such as the number + of Python worker processes when ``backend="loky"`` or the size of + the thread-pool when ``backend="threading"``. + This argument is converted to an integer, rounded below for float. + If -1 is given, `joblib` tries to use all CPUs. The number of CPUs + ``n_cpus`` is obtained with :func:`~cpu_count`. + For n_jobs below -1, (n_cpus + 1 + n_jobs) are used. For instance, + using ``n_jobs=-2`` will result in all CPUs but one being used. + This argument can also go above ``n_cpus``, which will cause + oversubscription. In some cases, slight oversubscription can be + beneficial, e.g., for tasks with large I/O operations. + If 1 is given, no parallel computing code is used at all, and the + behavior amounts to a simple python `for` loop. This mode is not + compatible with ``timeout``. + None is a marker for 'unset' that will be interpreted as n_jobs=1 + unless the call is performed under a :func:`~parallel_config` + context manager that sets another value for ``n_jobs``. + If n_jobs = 0 then a ValueError is raised. + backend: str, ParallelBackendBase instance or None, default='loky' + Specify the parallelization backend implementation. + Supported backends are: + + - "loky" used by default, can induce some + communication and memory overhead when exchanging input and + output data with the worker Python processes. On some rare + systems (such as Pyiodide), the loky backend may not be + available. + - "multiprocessing" previous process-based backend based on + `multiprocessing.Pool`. Less robust than `loky`. + - "threading" is a very low-overhead backend but it suffers + from the Python Global Interpreter Lock if the called function + relies a lot on Python objects. "threading" is mostly useful + when the execution bottleneck is a compiled extension that + explicitly releases the GIL (for instance a Cython loop wrapped + in a "with nogil" block or an expensive call to a library such + as NumPy). + - finally, you can register backends by calling + :func:`~register_parallel_backend`. This will allow you to + implement a backend of your liking. + + It is not recommended to hard-code the backend name in a call to + :class:`~Parallel` in a library. Instead it is recommended to set + soft hints (prefer) or hard constraints (require) so as to make it + possible for library users to change the backend from the outside + using the :func:`~parallel_config` context manager. + return_as: str in {'list', 'generator', 'generator_unordered'}, default='list' + If 'list', calls to this instance will return a list, only when + all results have been processed and retrieved. + If 'generator', it will return a generator that yields the results + as soon as they are available, in the order the tasks have been + submitted with. + If 'generator_unordered', the generator will immediately yield + available results independently of the submission order. The output + order is not deterministic in this case because it depends on the + concurrency of the workers. + prefer: str in {'processes', 'threads'} or None, default=None + Soft hint to choose the default backend if no specific backend + was selected with the :func:`~parallel_config` context manager. + The default process-based backend is 'loky' and the default + thread-based backend is 'threading'. Ignored if the ``backend`` + parameter is specified. + require: 'sharedmem' or None, default=None + Hard constraint to select the backend. If set to 'sharedmem', + the selected backend will be single-host and thread-based even + if the user asked for a non-thread based backend with + :func:`~joblib.parallel_config`. + verbose: int, default=0 + The verbosity level: if non zero, progress messages are + printed. Above 50, the output is sent to stdout. + The frequency of the messages increases with the verbosity level. + If it more than 10, all iterations are reported. + timeout: float or None, default=None + Timeout limit for each task to complete. If any task takes longer + a TimeOutError will be raised. Only applied when n_jobs != 1 + pre_dispatch: {'all', integer, or expression, as in '3*n_jobs'}, default='2*n_jobs' + The number of batches (of tasks) to be pre-dispatched. + Default is '2*n_jobs'. When batch_size="auto" this is reasonable + default and the workers should never starve. Note that only basic + arithmetic are allowed here and no modules can be used in this + expression. + batch_size: int or 'auto', default='auto' + The number of atomic tasks to dispatch at once to each + worker. When individual evaluations are very fast, dispatching + calls to workers can be slower than sequential computation because + of the overhead. Batching fast computations together can mitigate + this. + The ``'auto'`` strategy keeps track of the time it takes for a + batch to complete, and dynamically adjusts the batch size to keep + the time on the order of half a second, using a heuristic. The + initial batch size is 1. + ``batch_size="auto"`` with ``backend="threading"`` will dispatch + batches of a single task at a time as the threading backend has + very little overhead and using larger batch size has not proved to + bring any gain in that case. + temp_folder: str or None, default=None + Folder to be used by the pool for memmapping large arrays + for sharing memory with worker processes. If None, this will try in + order: + + - a folder pointed by the JOBLIB_TEMP_FOLDER environment + variable, + - /dev/shm if the folder exists and is writable: this is a + RAM disk filesystem available by default on modern Linux + distributions, + - the default system temporary folder that can be + overridden with TMP, TMPDIR or TEMP environment + variables, typically /tmp under Unix operating systems. + + Only active when ``backend="loky"`` or ``"multiprocessing"``. + max_nbytes int, str, or None, optional, default='1M' + Threshold on the size of arrays passed to the workers that + triggers automated memory mapping in temp_folder. Can be an int + in Bytes, or a human-readable string, e.g., '1M' for 1 megabyte. + Use None to disable memmapping of large arrays. + Only active when ``backend="loky"`` or ``"multiprocessing"``. + mmap_mode: {None, 'r+', 'r', 'w+', 'c'}, default='r' + Memmapping mode for numpy arrays passed to workers. None will + disable memmapping, other modes defined in the numpy.memmap doc: + https://numpy.org/doc/stable/reference/generated/numpy.memmap.html + Also, see 'max_nbytes' parameter documentation for more details. + backend_kwargs: dict, optional + Additional parameters to pass to the backend `configure` method. + + Notes + ----- + + This object uses workers to compute in parallel the application of a + function to many different arguments. The main functionality it brings + in addition to using the raw multiprocessing or concurrent.futures API + are (see examples for details): + + * More readable code, in particular since it avoids + constructing list of arguments. + + * Easier debugging: + - informative tracebacks even when the error happens on + the client side + - using 'n_jobs=1' enables to turn off parallel computing + for debugging without changing the codepath + - early capture of pickling errors + + * An optional progress meter. + + * Interruption of multiprocesses jobs with 'Ctrl-C' + + * Flexible pickling control for the communication to and from + the worker processes. + + * Ability to use shared memory efficiently with worker + processes for large numpy-based datastructures. + + Note that the intended usage is to run one call at a time. Multiple + calls to the same Parallel object will result in a ``RuntimeError`` + + Examples + -------- + + A simple example: + + >>> from math import sqrt + >>> from joblib import Parallel, delayed + >>> Parallel(n_jobs=1)(delayed(sqrt)(i**2) for i in range(10)) + [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0] + + Reshaping the output when the function has several return + values: + + >>> from math import modf + >>> from joblib import Parallel, delayed + >>> r = Parallel(n_jobs=1)(delayed(modf)(i/2.) for i in range(10)) + >>> res, i = zip(*r) + >>> res + (0.0, 0.5, 0.0, 0.5, 0.0, 0.5, 0.0, 0.5, 0.0, 0.5) + >>> i + (0.0, 0.0, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 4.0, 4.0) + + The progress meter: the higher the value of `verbose`, the more + messages: + + >>> from time import sleep + >>> from joblib import Parallel, delayed + >>> r = Parallel(n_jobs=2, verbose=10)( + ... delayed(sleep)(.2) for _ in range(10)) #doctest: +SKIP + [Parallel(n_jobs=2)]: Done 1 tasks | elapsed: 0.6s + [Parallel(n_jobs=2)]: Done 4 tasks | elapsed: 0.8s + [Parallel(n_jobs=2)]: Done 10 out of 10 | elapsed: 1.4s finished + + Traceback example, note how the line of the error is indicated + as well as the values of the parameter passed to the function that + triggered the exception, even though the traceback happens in the + child process: + + >>> from heapq import nlargest + >>> from joblib import Parallel, delayed + >>> Parallel(n_jobs=2)( + ... delayed(nlargest)(2, n) for n in (range(4), 'abcde', 3)) + ... # doctest: +SKIP + ----------------------------------------------------------------------- + Sub-process traceback: + ----------------------------------------------------------------------- + TypeError Mon Nov 12 11:37:46 2012 + PID: 12934 Python 2.7.3: /usr/bin/python + ........................................................................ + /usr/lib/python2.7/heapq.pyc in nlargest(n=2, iterable=3, key=None) + 419 if n >= size: + 420 return sorted(iterable, key=key, reverse=True)[:n] + 421 + 422 # When key is none, use simpler decoration + 423 if key is None: + --> 424 it = izip(iterable, count(0,-1)) # decorate + 425 result = _nlargest(n, it) + 426 return map(itemgetter(0), result) # undecorate + 427 + 428 # General case, slowest method + TypeError: izip argument #1 must support iteration + _______________________________________________________________________ + + + Using pre_dispatch in a producer/consumer situation, where the + data is generated on the fly. Note how the producer is first + called 3 times before the parallel loop is initiated, and then + called to generate new data on the fly: + + >>> from math import sqrt + >>> from joblib import Parallel, delayed + >>> def producer(): + ... for i in range(6): + ... print('Produced %s' % i) + ... yield i + >>> out = Parallel(n_jobs=2, verbose=100, pre_dispatch='1.5*n_jobs')( + ... delayed(sqrt)(i) for i in producer()) #doctest: +SKIP + Produced 0 + Produced 1 + Produced 2 + [Parallel(n_jobs=2)]: Done 1 jobs | elapsed: 0.0s + Produced 3 + [Parallel(n_jobs=2)]: Done 2 jobs | elapsed: 0.0s + Produced 4 + [Parallel(n_jobs=2)]: Done 3 jobs | elapsed: 0.0s + Produced 5 + [Parallel(n_jobs=2)]: Done 4 jobs | elapsed: 0.0s + [Parallel(n_jobs=2)]: Done 6 out of 6 | elapsed: 0.0s remaining: 0.0s + [Parallel(n_jobs=2)]: Done 6 out of 6 | elapsed: 0.0s finished + + """ # noqa: E501 + + def __init__( + self, + n_jobs=default_parallel_config["n_jobs"], + backend=default_parallel_config["backend"], + return_as="list", + verbose=default_parallel_config["verbose"], + timeout=None, + pre_dispatch="2 * n_jobs", + batch_size="auto", + temp_folder=default_parallel_config["temp_folder"], + max_nbytes=default_parallel_config["max_nbytes"], + mmap_mode=default_parallel_config["mmap_mode"], + prefer=default_parallel_config["prefer"], + require=default_parallel_config["require"], + **backend_kwargs, + ): + # Initiate parent Logger class state + super().__init__() + + # Interpret n_jobs=None as 'unset' + if n_jobs is None: + n_jobs = default_parallel_config["n_jobs"] + + active_backend, context_config = _get_active_backend( + prefer=prefer, require=require, verbose=verbose + ) + + nesting_level = active_backend.nesting_level + + self.verbose = _get_config_param(verbose, context_config, "verbose") + self.timeout = timeout + self.pre_dispatch = pre_dispatch + + if return_as not in {"list", "generator", "generator_unordered"}: + raise ValueError( + 'Expected `return_as` parameter to be a string equal to "list"' + f',"generator" or "generator_unordered", but got {return_as} ' + "instead." + ) + self.return_as = return_as + self.return_generator = return_as != "list" + self.return_ordered = return_as != "generator_unordered" + + # Check if we are under a parallel_config or parallel_backend + # context manager and use the config from the context manager + # for arguments that are not explicitly set. + self._backend_kwargs = { + **backend_kwargs, + **{ + k: _get_config_param(param, context_config, k) + for param, k in [ + (max_nbytes, "max_nbytes"), + (temp_folder, "temp_folder"), + (mmap_mode, "mmap_mode"), + (prefer, "prefer"), + (require, "require"), + (verbose, "verbose"), + ] + }, + } + + if isinstance(self._backend_kwargs["max_nbytes"], str): + self._backend_kwargs["max_nbytes"] = memstr_to_bytes( + self._backend_kwargs["max_nbytes"] + ) + self._backend_kwargs["verbose"] = max(0, self._backend_kwargs["verbose"] - 50) + + if DEFAULT_MP_CONTEXT is not None: + self._backend_kwargs["context"] = DEFAULT_MP_CONTEXT + elif hasattr(mp, "get_context"): + self._backend_kwargs["context"] = mp.get_context() + + if backend is default_parallel_config["backend"] or backend is None: + backend = active_backend + + elif isinstance(backend, ParallelBackendBase): + # Use provided backend as is, with the current nesting_level if it + # is not set yet. + if backend.nesting_level is None: + backend.nesting_level = nesting_level + + elif hasattr(backend, "Pool") and hasattr(backend, "Lock"): + # Make it possible to pass a custom multiprocessing context as + # backend to change the start method to forkserver or spawn or + # preload modules on the forkserver helper process. + self._backend_kwargs["context"] = backend + backend = MultiprocessingBackend(nesting_level=nesting_level) + + elif backend not in BACKENDS and backend in MAYBE_AVAILABLE_BACKENDS: + warnings.warn( + f"joblib backend '{backend}' is not available on " + f"your system, falling back to {DEFAULT_BACKEND}.", + UserWarning, + stacklevel=2, + ) + BACKENDS[backend] = BACKENDS[DEFAULT_BACKEND] + backend = BACKENDS[DEFAULT_BACKEND](nesting_level=nesting_level) + + else: + try: + backend_factory = BACKENDS[backend] + except KeyError as e: + raise ValueError( + "Invalid backend: %s, expected one of %r" + % (backend, sorted(BACKENDS.keys())) + ) from e + backend = backend_factory(nesting_level=nesting_level) + + n_jobs = _get_config_param(n_jobs, context_config, "n_jobs") + if n_jobs is None: + # No specific context override and no specific value request: + # default to the default of the backend. + n_jobs = backend.default_n_jobs + try: + n_jobs = int(n_jobs) + except ValueError: + raise ValueError("n_jobs could not be converted to int") + self.n_jobs = n_jobs + + if require == "sharedmem" and not getattr(backend, "supports_sharedmem", False): + raise ValueError("Backend %s does not support shared memory" % backend) + + if batch_size == "auto" or isinstance(batch_size, Integral) and batch_size > 0: + self.batch_size = batch_size + else: + raise ValueError( + "batch_size must be 'auto' or a positive integer, got: %r" % batch_size + ) + + if not isinstance(backend, SequentialBackend): + if self.return_generator and not backend.supports_return_generator: + raise ValueError( + "Backend {} does not support return_as={}".format( + backend, return_as + ) + ) + # This lock is used to coordinate the main thread of this process + # with the async callback thread of our the pool. + self._lock = threading.RLock() + self._jobs = collections.deque() + self._jobs_set = set() + self._pending_outputs = list() + self._ready_batches = queue.Queue() + self._reducer_callback = None + + # Internal variables + self._backend = backend + self._running = False + self._managed_backend = False + self._id = uuid4().hex + self._call_ref = None + + def __enter__(self): + self._managed_backend = True + self._calling = False + self._initialize_backend() + return self + + def __exit__(self, exc_type, exc_value, traceback): + self._managed_backend = False + if self.return_generator and self._calling: + self._abort() + self._terminate_and_reset() + + def _initialize_backend(self): + """Build a process or thread pool and return the number of workers""" + try: + n_jobs = self._backend.configure( + n_jobs=self.n_jobs, parallel=self, **self._backend_kwargs + ) + if self.timeout is not None and not self._backend.supports_timeout: + warnings.warn( + "The backend class {!r} does not support timeout. " + "You have set 'timeout={}' in Parallel but " + "the 'timeout' parameter will not be used.".format( + self._backend.__class__.__name__, self.timeout + ) + ) + + except FallbackToBackend as e: + # Recursively initialize the backend in case of requested fallback. + self._backend = e.backend + n_jobs = self._initialize_backend() + + return n_jobs + + def _effective_n_jobs(self): + if self._backend: + return self._backend.effective_n_jobs(self.n_jobs) + return 1 + + def _terminate_and_reset(self): + if hasattr(self._backend, "stop_call") and self._calling: + self._backend.stop_call() + self._calling = False + if not self._managed_backend: + self._backend.terminate() + + def _dispatch(self, batch): + """Queue the batch for computing, with or without multiprocessing + + WARNING: this method is not thread-safe: it should be only called + indirectly via dispatch_one_batch. + + """ + # If job.get() catches an exception, it closes the queue: + if self._aborting: + return + + batch_size = len(batch) + + self.n_dispatched_tasks += batch_size + self.n_dispatched_batches += 1 + + dispatch_timestamp = time.time() + + batch_tracker = BatchCompletionCallBack(dispatch_timestamp, batch_size, self) + + self._register_new_job(batch_tracker) + + # If return_ordered is False, the batch_tracker is not stored in the + # jobs queue at the time of submission. Instead, it will be appended to + # the queue by itself as soon as the callback is triggered to be able + # to return the results in the order of completion. + + job = self._backend.submit(batch, callback=batch_tracker) + batch_tracker.register_job(job) + + def _register_new_job(self, batch_tracker): + if self.return_ordered: + self._jobs.append(batch_tracker) + else: + self._jobs_set.add(batch_tracker) + + def dispatch_next(self): + """Dispatch more data for parallel processing + + This method is meant to be called concurrently by the multiprocessing + callback. We rely on the thread-safety of dispatch_one_batch to protect + against concurrent consumption of the unprotected iterator. + """ + if not self.dispatch_one_batch(self._original_iterator): + self._iterating = False + self._original_iterator = None + + def dispatch_one_batch(self, iterator): + """Prefetch the tasks for the next batch and dispatch them. + + The effective size of the batch is computed here. + If there are no more jobs to dispatch, return False, else return True. + + The iterator consumption and dispatching is protected by the same + lock so calling this function should be thread safe. + + """ + + if self._aborting: + return False + + batch_size = self._get_batch_size() + + with self._lock: + # to ensure an even distribution of the workload between workers, + # we look ahead in the original iterators more than batch_size + # tasks - However, we keep consuming only one batch at each + # dispatch_one_batch call. The extra tasks are stored in a local + # queue, _ready_batches, that is looked-up prior to re-consuming + # tasks from the origal iterator. + try: + tasks = self._ready_batches.get(block=False) + except queue.Empty: + # slice the iterator n_jobs * batchsize items at a time. If the + # slice returns less than that, then the current batchsize puts + # too much weight on a subset of workers, while other may end + # up starving. So in this case, re-scale the batch size + # accordingly to distribute evenly the last items between all + # workers. + n_jobs = self._cached_effective_n_jobs + big_batch_size = batch_size * n_jobs + + try: + islice = list(itertools.islice(iterator, big_batch_size)) + except Exception as e: + # Handle the fact that the generator of task raised an + # exception. As this part of the code can be executed in + # a thread internal to the backend, register a task with + # an error that will be raised in the user's thread. + if isinstance(e.__context__, queue.Empty): + # Suppress the cause of the exception if it is + # queue.Empty to avoid cluttered traceback. Only do it + # if the __context__ is really empty to avoid messing + # with causes of the original error. + e.__cause__ = None + batch_tracker = BatchCompletionCallBack(0, batch_size, self) + self._register_new_job(batch_tracker) + batch_tracker._register_outcome(dict(result=e, status=TASK_ERROR)) + return True + + if len(islice) == 0: + return False + elif ( + iterator is self._original_iterator and len(islice) < big_batch_size + ): + # We reached the end of the original iterator (unless + # iterator is the ``pre_dispatch``-long initial slice of + # the original iterator) -- decrease the batch size to + # account for potential variance in the batches running + # time. + final_batch_size = max(1, len(islice) // (10 * n_jobs)) + else: + final_batch_size = max(1, len(islice) // n_jobs) + + # enqueue n_jobs batches in a local queue + for i in range(0, len(islice), final_batch_size): + tasks = BatchedCalls( + islice[i : i + final_batch_size], + self._backend.get_nested_backend(), + self._reducer_callback, + self._pickle_cache, + ) + self._ready_batches.put(tasks) + + # finally, get one task. + tasks = self._ready_batches.get(block=False) + if len(tasks) == 0: + # No more tasks available in the iterator: tell caller to stop. + return False + else: + self._dispatch(tasks) + return True + + def _get_batch_size(self): + """Returns the effective batch size for dispatch""" + if self.batch_size == "auto": + return self._backend.compute_batch_size() + else: + # Fixed batch size strategy + return self.batch_size + + def _print(self, msg): + """Display the message on stout or stderr depending on verbosity""" + # XXX: Not using the logger framework: need to + # learn to use logger better. + if not self.verbose: + return + if self.verbose < 50: + writer = sys.stderr.write + else: + writer = sys.stdout.write + writer(f"[{self}]: {msg}\n") + + def _is_completed(self): + """Check if all tasks have been completed""" + return self.n_completed_tasks == self.n_dispatched_tasks and not ( + self._iterating or self._aborting + ) + + def print_progress(self): + """Display the process of the parallel execution only a fraction + of time, controlled by self.verbose. + """ + + if not self.verbose: + return + + if self.n_tasks is not None and self.n_tasks > 0: + width = floor(log10(self.n_tasks)) + 1 + else: + width = 3 + elapsed_time = time.time() - self._start_time + + if self._is_completed(): + # Make sure that we get a last message telling us we are done + self._print( + f"Done {self.n_completed_tasks:{width}d} out of " + f"{self.n_completed_tasks:{width}d} | elapsed: " + f"{short_format_time(elapsed_time)} finished" + ) + return + + # Original job iterator becomes None once it has been fully + # consumed: at this point we know the total number of jobs and we are + # able to display an estimation of the remaining time based on already + # completed jobs. Otherwise, we simply display the number of completed + # tasks. + elif self._original_iterator is not None: + if _verbosity_filter(self.n_dispatched_batches, self.verbose): + return + fmt_time = f"| elapsed: {short_format_time(elapsed_time)}" + index = self.n_completed_tasks + if self.n_tasks is not None: + self._print( + f"Done {index:{width}d} out of {self.n_tasks:{width}d} {fmt_time}" + ) + else: + pad = " " * (len("out of ") + width - len("tasks")) + self._print(f"Done {index:{width}d} tasks {pad}{fmt_time}") + else: + index = self.n_completed_tasks + # We are finished dispatching + total_tasks = self.n_dispatched_tasks + # We always display the first loop + if index != 0: + # Display depending on the number of remaining items + # A message as soon as we finish dispatching, cursor is 0 + cursor = total_tasks - index + 1 - self._pre_dispatch_amount + frequency = (total_tasks // self.verbose) + 1 + is_last_item = index + 1 == total_tasks + if is_last_item or cursor % frequency: + return + remaining_time = (elapsed_time / max(index, 1)) * ( + self.n_dispatched_tasks - index + ) + # only display status if remaining time is greater or equal to 0 + self._print( + f"Done {index:{width}d} out of {total_tasks:{width}d} " + f"| elapsed: {short_format_time(elapsed_time)} remaining: " + f"{short_format_time(remaining_time)}" + ) + + def _abort(self): + # Stop dispatching new jobs in the async callback thread + self._aborting = True + + # If the backend allows it, cancel or kill remaining running + # tasks without waiting for the results as we will raise + # the exception we got back to the caller instead of returning + # any result. + backend = self._backend + if not self._aborted and hasattr(backend, "abort_everything"): + # If the backend is managed externally we need to make sure + # to leave it in a working state to allow for future jobs + # scheduling. + ensure_ready = self._managed_backend + backend.abort_everything(ensure_ready=ensure_ready) + self._aborted = True + + def _start(self, iterator, pre_dispatch): + # Only set self._iterating to True if at least a batch + # was dispatched. In particular this covers the edge + # case of Parallel used with an exhausted iterator. If + # self._original_iterator is None, then this means either + # that pre_dispatch == "all", n_jobs == 1 or that the first batch + # was very quick and its callback already dispatched all the + # remaining jobs. + self._iterating = False + if self.dispatch_one_batch(iterator): + self._iterating = self._original_iterator is not None + + while self.dispatch_one_batch(iterator): + pass + + if pre_dispatch == "all": + # The iterable was consumed all at once by the above for loop. + # No need to wait for async callbacks to trigger to + # consumption. + self._iterating = False + + def _get_outputs(self, iterator, pre_dispatch): + """Iterator returning the tasks' output as soon as they are ready.""" + dispatch_thread_id = threading.get_ident() + detach_generator_exit = False + try: + self._start(iterator, pre_dispatch) + # first yield returns None, for internal use only. This ensures + # that we enter the try/except block and start dispatching the + # tasks. + yield + + with self._backend.retrieval_context(): + yield from self._retrieve() + + except GeneratorExit: + # The generator has been garbage collected before being fully + # consumed. This aborts the remaining tasks if possible and warn + # the user if necessary. + self._exception = True + + # In some interpreters such as PyPy, GeneratorExit can be raised in + # a different thread than the one used to start the dispatch of the + # parallel tasks. This can lead to hang when a thread attempts to + # join itself. As workaround, we detach the execution of the + # aborting code to a dedicated thread. We then need to make sure + # the rest of the function does not call `_terminate_and_reset` + # in finally. + if dispatch_thread_id != threading.get_ident(): + warnings.warn( + "A generator produced by joblib.Parallel has been " + "gc'ed in an unexpected thread. This behavior should " + "not cause major -issues but to make sure, please " + "report this warning and your use case at " + "https://github.com/joblib/joblib/issues so it can " + "be investigated." + ) + + detach_generator_exit = True + _parallel = self + + class _GeneratorExitThread(threading.Thread): + def run(self): + _parallel._abort() + if _parallel.return_generator: + _parallel._warn_exit_early() + _parallel._terminate_and_reset() + + _GeneratorExitThread(name="GeneratorExitThread").start() + return + + # Otherwise, we are in the thread that started the dispatch: we can + # safely abort the execution and warn the user. + self._abort() + if self.return_generator: + self._warn_exit_early() + + raise + + # Note: we catch any BaseException instead of just Exception instances + # to also include KeyboardInterrupt + except BaseException: + self._exception = True + self._abort() + raise + finally: + # Store the unconsumed tasks and terminate the workers if necessary + _remaining_outputs = [] if self._exception else self._jobs + self._jobs = collections.deque() + self._jobs_set = set() + self._running = False + if not detach_generator_exit: + self._terminate_and_reset() + + while len(_remaining_outputs) > 0: + batched_results = _remaining_outputs.popleft() + batched_results = batched_results.get_result(self.timeout) + for result in batched_results: + yield result + + def _wait_retrieval(self): + """Return True if we need to continue retrieving some tasks.""" + + # If the input load is still being iterated over, it means that tasks + # are still on the dispatch waitlist and their results will need to + # be retrieved later on. + if self._iterating: + return True + + # If some of the dispatched tasks are still being processed by the + # workers, wait for the compute to finish before starting retrieval + if self.n_completed_tasks < self.n_dispatched_tasks: + return True + + # For backends that does not support retrieving asynchronously the + # result to the main process, all results must be carefully retrieved + # in the _retrieve loop in the main thread while the backend is alive. + # For other backends, the actual retrieval is done asynchronously in + # the callback thread, and we can terminate the backend before the + # `self._jobs` result list has been emptied. The remaining results + # will be collected in the `finally` step of the generator. + if not self._backend.supports_retrieve_callback: + if len(self._jobs) > 0: + return True + + return False + + def _retrieve(self): + timeout_control_job = None + while self._wait_retrieval(): + # If the callback thread of a worker has signaled that its task + # triggered an exception, or if the retrieval loop has raised an + # exception (e.g. `GeneratorExit`), exit the loop and surface the + # worker traceback. + if self._aborting: + self._raise_error_fast() + break + + nb_jobs = len(self._jobs) + # Now wait for a job to be ready for retrieval. + if self.return_ordered: + # Case ordered: wait for completion (or error) of the next job + # that have been dispatched and not retrieved yet. If no job + # have been dispatched yet, wait for dispatch. + # We assume that the time to wait for the next job to be + # dispatched is always low, so that the timeout + # control only have to be done on the amount of time the next + # dispatched job is pending. + if (nb_jobs == 0) or ( + self._jobs[0].get_status(timeout=self.timeout) == TASK_PENDING + ): + time.sleep(0.01) + continue + + elif nb_jobs == 0: + # Case unordered: jobs are added to the list of jobs to + # retrieve `self._jobs` only once completed or in error, which + # is too late to enable timeout control in the same way than in + # the previous case. + # Instead, if no job is ready to be retrieved yet, we + # arbitrarily pick a dispatched job, and the timeout control is + # done such that an error is raised if this control job + # timeouts before any other dispatched job has completed and + # been added to `self._jobs` to be retrieved. + if timeout_control_job is None: + timeout_control_job = next(iter(self._jobs_set), None) + + # NB: it can be None if no job has been dispatched yet. + if timeout_control_job is not None: + timeout_control_job.get_status(timeout=self.timeout) + + time.sleep(0.01) + continue + + elif timeout_control_job is not None: + # Case unordered, when `nb_jobs > 0`: + # It means that a job is ready to be retrieved, so no timeout + # will occur during this iteration. + # Before proceeding to retrieval of the next ready job, reset + # the timeout control state to prepare the next iteration. + timeout_control_job._completion_timeout_counter = None + timeout_control_job = None + + # We need to be careful: the job list can be filling up as + # we empty it and Python list are not thread-safe by + # default hence the use of the lock + with self._lock: + batched_results = self._jobs.popleft() + if not self.return_ordered: + self._jobs_set.remove(batched_results) + + # Flatten the batched results to output one output at a time + batched_results = batched_results.get_result(self.timeout) + for result in batched_results: + self._nb_consumed += 1 + yield result + + def _raise_error_fast(self): + """If we are aborting, raise if a job caused an error.""" + + # Find the first job whose status is TASK_ERROR if it exists. + with self._lock: + error_job = next( + (job for job in self._jobs if job.status == TASK_ERROR), None + ) + + # If this error job exists, immediately raise the error by + # calling get_result. This job might not exists if abort has been + # called directly or if the generator is gc'ed. + if error_job is not None: + error_job.get_result(self.timeout) + + def _warn_exit_early(self): + """Warn the user if the generator is gc'ed before being consumned.""" + ready_outputs = self.n_completed_tasks - self._nb_consumed + is_completed = self._is_completed() + msg = "" + if ready_outputs: + msg += ( + f"{ready_outputs} tasks have been successfully executed but not used." + ) + if not is_completed: + msg += " Additionally, " + + if not is_completed: + msg += ( + f"{self.n_dispatched_tasks - self.n_completed_tasks} tasks " + "which were still being processed by the workers have been " + "cancelled." + ) + + if msg: + msg += ( + " You could benefit from adjusting the input task " + "iterator to limit unnecessary computation time." + ) + + warnings.warn(msg) + + def _get_sequential_output(self, iterable): + """Separate loop for sequential output. + + This simplifies the traceback in case of errors and reduces the + overhead of calling sequential tasks with `joblib`. + """ + try: + self._iterating = True + self._original_iterator = iterable + batch_size = self._get_batch_size() + + if batch_size != 1: + it = iter(iterable) + iterable_batched = iter( + lambda: tuple(itertools.islice(it, batch_size)), () + ) + iterable = (task for batch in iterable_batched for task in batch) + + # first yield returns None, for internal use only. This ensures + # that we enter the try/except block and setup the generator. + yield None + + # Sequentially call the tasks and yield the results. + for func, args, kwargs in iterable: + self.n_dispatched_batches += 1 + self.n_dispatched_tasks += 1 + res = func(*args, **kwargs) + self.n_completed_tasks += 1 + self.print_progress() + yield res + self._nb_consumed += 1 + except BaseException: + self._exception = True + self._aborting = True + self._aborted = True + raise + finally: + self._running = False + self._iterating = False + self._original_iterator = None + self.print_progress() + + def _reset_run_tracking(self): + """Reset the counters and flags used to track the execution.""" + + # Makes sur the parallel instance was not previously running in a + # thread-safe way. + with getattr(self, "_lock", nullcontext()): + if self._running: + msg = "This Parallel instance is already running !" + if self.return_generator is True: + msg += ( + " Before submitting new tasks, you must wait for the " + "completion of all the previous tasks, or clean all " + "references to the output generator." + ) + raise RuntimeError(msg) + self._running = True + + # Counter to keep track of the task dispatched and completed. + self.n_dispatched_batches = 0 + self.n_dispatched_tasks = 0 + self.n_completed_tasks = 0 + + # Following count is incremented by one each time the user iterates + # on the output generator, it is used to prepare an informative + # warning message in case the generator is deleted before all the + # dispatched tasks have been consumed. + self._nb_consumed = 0 + + # Following flags are used to synchronize the threads in case one of + # the tasks error-out to ensure that all workers abort fast and that + # the backend terminates properly. + + # Set to True as soon as a worker signals that a task errors-out + self._exception = False + # Set to True in case of early termination following an incident + self._aborting = False + # Set to True after abortion is complete + self._aborted = False + + def __call__(self, iterable): + """Main function to dispatch parallel tasks.""" + + self._reset_run_tracking() + self.n_tasks = len(iterable) if hasattr(iterable, "__len__") else None + self._start_time = time.time() + + if not self._managed_backend: + n_jobs = self._initialize_backend() + else: + n_jobs = self._effective_n_jobs() + + if n_jobs == 1: + # If n_jobs==1, run the computation sequentially and return + # immediately to avoid overheads. + output = self._get_sequential_output(iterable) + next(output) + return output if self.return_generator else list(output) + + # Let's create an ID that uniquely identifies the current call. If the + # call is interrupted early and that the same instance is immediately + # reused, this id will be used to prevent workers that were + # concurrently finalizing a task from the previous call to run the + # callback. + with self._lock: + self._call_id = uuid4().hex + + # self._effective_n_jobs should be called in the Parallel.__call__ + # thread only -- store its value in an attribute for further queries. + self._cached_effective_n_jobs = n_jobs + + if isinstance(self._backend, LokyBackend): + # For the loky backend, we add a callback executed when reducing + # BatchCalls, that makes the loky executor use a temporary folder + # specific to this Parallel object when pickling temporary memmaps. + # This callback is necessary to ensure that several Parallel + # objects using the same reusable executor don't use the same + # temporary resources. + + def _batched_calls_reducer_callback(): + # Relevant implementation detail: the following lines, called + # when reducing BatchedCalls, are called in a thread-safe + # situation, meaning that the context of the temporary folder + # manager will not be changed in between the callback execution + # and the end of the BatchedCalls pickling. The reason is that + # pickling (the only place where set_current_context is used) + # is done from a single thread (the queue_feeder_thread). + self._backend._workers._temp_folder_manager.set_current_context( # noqa + self._id + ) + + self._reducer_callback = _batched_calls_reducer_callback + + # self._effective_n_jobs should be called in the Parallel.__call__ + # thread only -- store its value in an attribute for further queries. + self._cached_effective_n_jobs = n_jobs + + backend_name = self._backend.__class__.__name__ + if n_jobs == 0: + raise RuntimeError("%s has no active worker." % backend_name) + + self._print(f"Using backend {backend_name} with {n_jobs} concurrent workers.") + if hasattr(self._backend, "start_call"): + self._backend.start_call() + + # Following flag prevents double calls to `backend.stop_call`. + self._calling = True + + iterator = iter(iterable) + pre_dispatch = self.pre_dispatch + + if pre_dispatch == "all": + # prevent further dispatch via multiprocessing callback thread + self._original_iterator = None + self._pre_dispatch_amount = 0 + else: + self._original_iterator = iterator + if hasattr(pre_dispatch, "endswith"): + pre_dispatch = eval_expr(pre_dispatch.replace("n_jobs", str(n_jobs))) + self._pre_dispatch_amount = pre_dispatch = int(pre_dispatch) + + # The main thread will consume the first pre_dispatch items and + # the remaining items will later be lazily dispatched by async + # callbacks upon task completions. + + # TODO: this iterator should be batch_size * n_jobs + iterator = itertools.islice(iterator, self._pre_dispatch_amount) + + # Use a caching dict for callables that are pickled with cloudpickle to + # improve performances. This cache is used only in the case of + # functions that are defined in the __main__ module, functions that + # are defined locally (inside another function) and lambda expressions. + self._pickle_cache = dict() + + output = self._get_outputs(iterator, pre_dispatch) + self._call_ref = weakref.ref(output) + + # The first item from the output is blank, but it makes the interpreter + # progress until it enters the Try/Except block of the generator and + # reaches the first `yield` statement. This starts the asynchronous + # dispatch of the tasks to the workers. + next(output) + + return output if self.return_generator else list(output) + + def __repr__(self): + return "%s(n_jobs=%s)" % (self.__class__.__name__, self.n_jobs) diff --git a/joblib/pool.py b/joblib/pool.py new file mode 100644 index 0000000000000000000000000000000000000000..6e961080703cd29dfbe441417aaeff37944a7118 --- /dev/null +++ b/joblib/pool.py @@ -0,0 +1,362 @@ +"""Custom implementation of multiprocessing.Pool with custom pickler. + +This module provides efficient ways of working with data stored in +shared memory with numpy.memmap arrays without inducing any memory +copy between the parent and child processes. + +This module should not be imported if multiprocessing is not +available as it implements subclasses of multiprocessing Pool +that uses a custom alternative to SimpleQueue. + +""" +# Author: Olivier Grisel +# Copyright: 2012, Olivier Grisel +# License: BSD 3 clause + +import copyreg +import sys +import warnings +from time import sleep + +try: + WindowsError +except NameError: + WindowsError = type(None) + +from io import BytesIO + +# We need the class definition to derive from it, not the multiprocessing.Pool +# factory function +from multiprocessing.pool import Pool +from pickle import HIGHEST_PROTOCOL, Pickler + +from ._memmapping_reducer import TemporaryResourcesManager, get_memmapping_reducers +from ._multiprocessing_helpers import assert_spawning, mp + +try: + import numpy as np +except ImportError: + np = None + + +############################################################################### +# Enable custom pickling in Pool queues + + +class CustomizablePickler(Pickler): + """Pickler that accepts custom reducers. + + TODO python2_drop : can this be simplified ? + + HIGHEST_PROTOCOL is selected by default as this pickler is used + to pickle ephemeral datastructures for interprocess communication + hence no backward compatibility is required. + + `reducers` is expected to be a dictionary with key/values + being `(type, callable)` pairs where `callable` is a function that + give an instance of `type` will return a tuple `(constructor, + tuple_of_objects)` to rebuild an instance out of the pickled + `tuple_of_objects` as would return a `__reduce__` method. See the + standard library documentation on pickling for more details. + + """ + + # We override the pure Python pickler as its the only way to be able to + # customize the dispatch table without side effects in Python 2.7 + # to 3.2. For Python 3.3+ leverage the new dispatch_table + # feature from https://bugs.python.org/issue14166 that makes it possible + # to use the C implementation of the Pickler which is faster. + + def __init__(self, writer, reducers=None, protocol=HIGHEST_PROTOCOL): + Pickler.__init__(self, writer, protocol=protocol) + if reducers is None: + reducers = {} + if hasattr(Pickler, "dispatch"): + # Make the dispatch registry an instance level attribute instead of + # a reference to the class dictionary under Python 2 + self.dispatch = Pickler.dispatch.copy() + else: + # Under Python 3 initialize the dispatch table with a copy of the + # default registry + self.dispatch_table = copyreg.dispatch_table.copy() + for type, reduce_func in reducers.items(): + self.register(type, reduce_func) + + def register(self, type, reduce_func): + """Attach a reducer function to a given type in the dispatch table.""" + if hasattr(Pickler, "dispatch"): + # Python 2 pickler dispatching is not explicitly customizable. + # Let us use a closure to workaround this limitation. + def dispatcher(self, obj): + reduced = reduce_func(obj) + self.save_reduce(obj=obj, *reduced) + + self.dispatch[type] = dispatcher + else: + self.dispatch_table[type] = reduce_func + + +class CustomizablePicklingQueue(object): + """Locked Pipe implementation that uses a customizable pickler. + + This class is an alternative to the multiprocessing implementation + of SimpleQueue in order to make it possible to pass custom + pickling reducers, for instance to avoid memory copy when passing + memory mapped datastructures. + + `reducers` is expected to be a dict with key / values being + `(type, callable)` pairs where `callable` is a function that, given an + instance of `type`, will return a tuple `(constructor, tuple_of_objects)` + to rebuild an instance out of the pickled `tuple_of_objects` as would + return a `__reduce__` method. + + See the standard library documentation on pickling for more details. + """ + + def __init__(self, context, reducers=None): + self._reducers = reducers + self._reader, self._writer = context.Pipe(duplex=False) + self._rlock = context.Lock() + if sys.platform == "win32": + self._wlock = None + else: + self._wlock = context.Lock() + self._make_methods() + + def __getstate__(self): + assert_spawning(self) + return (self._reader, self._writer, self._rlock, self._wlock, self._reducers) + + def __setstate__(self, state): + (self._reader, self._writer, self._rlock, self._wlock, self._reducers) = state + self._make_methods() + + def empty(self): + return not self._reader.poll() + + def _make_methods(self): + self._recv = recv = self._reader.recv + racquire, rrelease = self._rlock.acquire, self._rlock.release + + def get(): + racquire() + try: + return recv() + finally: + rrelease() + + self.get = get + + if self._reducers: + + def send(obj): + buffer = BytesIO() + CustomizablePickler(buffer, self._reducers).dump(obj) + self._writer.send_bytes(buffer.getvalue()) + + self._send = send + else: + self._send = send = self._writer.send + if self._wlock is None: + # writes to a message oriented win32 pipe are atomic + self.put = send + else: + wlock_acquire, wlock_release = (self._wlock.acquire, self._wlock.release) + + def put(obj): + wlock_acquire() + try: + return send(obj) + finally: + wlock_release() + + self.put = put + + +class PicklingPool(Pool): + """Pool implementation with customizable pickling reducers. + + This is useful to control how data is shipped between processes + and makes it possible to use shared memory without useless + copies induces by the default pickling methods of the original + objects passed as arguments to dispatch. + + `forward_reducers` and `backward_reducers` are expected to be + dictionaries with key/values being `(type, callable)` pairs where + `callable` is a function that, given an instance of `type`, will return a + tuple `(constructor, tuple_of_objects)` to rebuild an instance out of the + pickled `tuple_of_objects` as would return a `__reduce__` method. + See the standard library documentation about pickling for more details. + + """ + + def __init__( + self, processes=None, forward_reducers=None, backward_reducers=None, **kwargs + ): + if forward_reducers is None: + forward_reducers = dict() + if backward_reducers is None: + backward_reducers = dict() + self._forward_reducers = forward_reducers + self._backward_reducers = backward_reducers + poolargs = dict(processes=processes) + poolargs.update(kwargs) + super(PicklingPool, self).__init__(**poolargs) + + def _setup_queues(self): + context = getattr(self, "_ctx", mp) + self._inqueue = CustomizablePicklingQueue(context, self._forward_reducers) + self._outqueue = CustomizablePicklingQueue(context, self._backward_reducers) + self._quick_put = self._inqueue._send + self._quick_get = self._outqueue._recv + + +class MemmappingPool(PicklingPool): + """Process pool that shares large arrays to avoid memory copy. + + This drop-in replacement for `multiprocessing.pool.Pool` makes + it possible to work efficiently with shared memory in a numpy + context. + + Existing instances of numpy.memmap are preserved: the child + suprocesses will have access to the same shared memory in the + original mode except for the 'w+' mode that is automatically + transformed as 'r+' to avoid zeroing the original data upon + instantiation. + + Furthermore large arrays from the parent process are automatically + dumped to a temporary folder on the filesystem such as child + processes to access their content via memmapping (file system + backed shared memory). + + Note: it is important to call the terminate method to collect + the temporary folder used by the pool. + + Parameters + ---------- + processes: int, optional + Number of worker processes running concurrently in the pool. + initializer: callable, optional + Callable executed on worker process creation. + initargs: tuple, optional + Arguments passed to the initializer callable. + temp_folder: (str, callable) optional + If str: + Folder to be used by the pool for memmapping large arrays + for sharing memory with worker processes. If None, this will try in + order: + - a folder pointed by the JOBLIB_TEMP_FOLDER environment variable, + - /dev/shm if the folder exists and is writable: this is a RAMdisk + filesystem available by default on modern Linux distributions, + - the default system temporary folder that can be overridden + with TMP, TMPDIR or TEMP environment variables, typically /tmp + under Unix operating systems. + if callable: + An callable in charge of dynamically resolving a temporary folder + for memmapping large arrays. + max_nbytes int or None, optional, 1e6 by default + Threshold on the size of arrays passed to the workers that + triggers automated memory mapping in temp_folder. + Use None to disable memmapping of large arrays. + mmap_mode: {'r+', 'r', 'w+', 'c'} + Memmapping mode for numpy arrays passed to workers. + See 'max_nbytes' parameter documentation for more details. + forward_reducers: dictionary, optional + Reducers used to pickle objects passed from main process to worker + processes: see below. + backward_reducers: dictionary, optional + Reducers used to pickle return values from workers back to the + main process. + verbose: int, optional + Make it possible to monitor how the communication of numpy arrays + with the subprocess is handled (pickling or memmapping) + prewarm: bool or str, optional, "auto" by default. + If True, force a read on newly memmapped array to make sure that OS + pre-cache it in memory. This can be useful to avoid concurrent disk + access when the same data array is passed to different worker + processes. If "auto" (by default), prewarm is set to True, unless the + Linux shared memory partition /dev/shm is available and used as temp + folder. + + `forward_reducers` and `backward_reducers` are expected to be + dictionaries with key/values being `(type, callable)` pairs where + `callable` is a function that give an instance of `type` will return + a tuple `(constructor, tuple_of_objects)` to rebuild an instance out + of the pickled `tuple_of_objects` as would return a `__reduce__` + method. See the standard library documentation on pickling for more + details. + + """ + + def __init__( + self, + processes=None, + temp_folder=None, + max_nbytes=1e6, + mmap_mode="r", + forward_reducers=None, + backward_reducers=None, + verbose=0, + prewarm=False, + **kwargs, + ): + manager = TemporaryResourcesManager(temp_folder) + self._temp_folder_manager = manager + + # The usage of a temp_folder_resolver over a simple temp_folder is + # superfluous for multiprocessing pools, as they don't get reused, see + # get_memmapping_executor for more details. We still use it for code + # simplicity. + forward_reducers, backward_reducers = get_memmapping_reducers( + temp_folder_resolver=manager.resolve_temp_folder_name, + max_nbytes=max_nbytes, + mmap_mode=mmap_mode, + forward_reducers=forward_reducers, + backward_reducers=backward_reducers, + verbose=verbose, + unlink_on_gc_collect=False, + prewarm=prewarm, + ) + + poolargs = dict( + processes=processes, + forward_reducers=forward_reducers, + backward_reducers=backward_reducers, + ) + poolargs.update(kwargs) + super(MemmappingPool, self).__init__(**poolargs) + + def terminate(self): + n_retries = 10 + for i in range(n_retries): + try: + super(MemmappingPool, self).terminate() + break + except OSError as e: + if isinstance(e, WindowsError): + # Workaround occasional "[Error 5] Access is denied" issue + # when trying to terminate a process under windows. + sleep(0.1) + if i + 1 == n_retries: + warnings.warn( + "Failed to terminate worker processes in" + " multiprocessing pool: %r" % e + ) + + # Clean up the temporary resources as the workers should now be off. + self._temp_folder_manager._clean_temporary_resources() + + @property + def _temp_folder(self): + # Legacy property in tests. could be removed if we refactored the + # memmapping tests. SHOULD ONLY BE USED IN TESTS! + # We cache this property because it is called late in the tests - at + # this point, all context have been unregistered, and + # resolve_temp_folder_name raises an error. + if getattr(self, "_cached_temp_folder", None) is not None: + return self._cached_temp_folder + else: + self._cached_temp_folder = ( + self._temp_folder_manager.resolve_temp_folder_name() + ) # noqa + return self._cached_temp_folder diff --git a/joblib/testing.py b/joblib/testing.py new file mode 100644 index 0000000000000000000000000000000000000000..3ac3e7027c7931ddc3f72482cd86ef5fa87cfdf8 --- /dev/null +++ b/joblib/testing.py @@ -0,0 +1,96 @@ +""" +Helper for testing. +""" + +import os.path +import re +import subprocess +import sys +import threading +import warnings + +import _pytest +import pytest + +raises = pytest.raises +warns = pytest.warns +SkipTest = _pytest.runner.Skipped +skipif = pytest.mark.skipif +fixture = pytest.fixture +parametrize = pytest.mark.parametrize +timeout = pytest.mark.timeout +xfail = pytest.mark.xfail +param = pytest.param + + +def warnings_to_stdout(): + """Redirect all warnings to stdout.""" + showwarning_orig = warnings.showwarning + + def showwarning(msg, cat, fname, lno, file=None, line=0): + showwarning_orig(msg, cat, os.path.basename(fname), line, sys.stdout) + + warnings.showwarning = showwarning + # warnings.simplefilter('always') + + +def check_subprocess_call(cmd, timeout=5, stdout_regex=None, stderr_regex=None): + """Runs a command in a subprocess with timeout in seconds. + + A SIGTERM is sent after `timeout` and if it does not terminate, a + SIGKILL is sent after `2 * timeout`. + + Also checks returncode is zero, stdout if stdout_regex is set, and + stderr if stderr_regex is set. + """ + proc = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE) + + def terminate_process(): # pragma: no cover + """ + Attempt to terminate a leftover process spawned during test execution: + ideally this should not be needed but can help avoid clogging the CI + workers in case of deadlocks. + """ + warnings.warn(f"Timeout running {cmd}") + proc.terminate() + + def kill_process(): # pragma: no cover + """ + Kill a leftover process spawned during test execution: ideally this + should not be needed but can help avoid clogging the CI workers in + case of deadlocks. + """ + warnings.warn(f"Timeout running {cmd}") + proc.kill() + + try: + if timeout is not None: + terminate_timer = threading.Timer(timeout, terminate_process) + terminate_timer.start() + kill_timer = threading.Timer(2 * timeout, kill_process) + kill_timer.start() + stdout, stderr = proc.communicate() + stdout, stderr = stdout.decode(), stderr.decode() + if proc.returncode != 0: + message = ("Non-zero return code: {}.\nStdout:\n{}\nStderr:\n{}").format( + proc.returncode, stdout, stderr + ) + raise ValueError(message) + + if stdout_regex is not None and not re.search(stdout_regex, stdout): + raise ValueError( + "Unexpected stdout: {!r} does not match:\n{!r}".format( + stdout_regex, stdout + ) + ) + if stderr_regex is not None and not re.search(stderr_regex, stderr): + raise ValueError( + "Unexpected stderr: {!r} does not match:\n{!r}".format( + stderr_regex, stderr + ) + ) + + finally: + if timeout is not None: + terminate_timer.cancel() + kill_timer.cancel() diff --git a/mamba_ssm-2.3.1.dist-info/AUTHORS b/mamba_ssm-2.3.1.dist-info/AUTHORS new file mode 100644 index 0000000000000000000000000000000000000000..38557a872f8d603ed963a05c211de7032de5926b --- /dev/null +++ b/mamba_ssm-2.3.1.dist-info/AUTHORS @@ -0,0 +1,2 @@ +Tri Dao, tri@tridao.me +Albert Gu, agu@andrew.cmu.edu diff --git a/mamba_ssm-2.3.1.dist-info/INSTALLER b/mamba_ssm-2.3.1.dist-info/INSTALLER new file mode 100644 index 0000000000000000000000000000000000000000..5c69047b2eb8235994febeeae1da4a82365a240a --- /dev/null +++ b/mamba_ssm-2.3.1.dist-info/INSTALLER @@ -0,0 +1 @@ +uv \ No newline at end of file diff --git a/mamba_ssm-2.3.1.dist-info/LICENSE b/mamba_ssm-2.3.1.dist-info/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..f4abe24eb520fbb077753ae4f34bfaa43cb3b83f --- /dev/null +++ b/mamba_ssm-2.3.1.dist-info/LICENSE @@ -0,0 +1,201 @@ + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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However, in accepting such obligations, You may act only + on Your own behalf and on Your sole responsibility, not on behalf + of any other Contributor, and only if You agree to indemnify, + defend, and hold each Contributor harmless for any liability + incurred by, or claims asserted against, such Contributor by reason + of your accepting any such warranty or additional liability. + + END OF TERMS AND CONDITIONS + + APPENDIX: How to apply the Apache License to your work. + + To apply the Apache License to your work, attach the following + boilerplate notice, with the fields enclosed by brackets "[]" + replaced with your own identifying information. (Don't include + the brackets!) The text should be enclosed in the appropriate + comment syntax for the file format. We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright 2023 Tri Dao, Albert Gu + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. + +Project-URL: Repository, https://github.com/state-spaces/mamba +Keywords: cuda,pytorch,state-space model +Classifier: Programming Language :: Python :: 3 +Classifier: License :: OSI Approved :: Apache Software License +Classifier: Operating System :: Unix +Requires-Python: >=3.9 +Description-Content-Type: text/markdown +License-File: LICENSE +License-File: AUTHORS +Requires-Dist: torch +Requires-Dist: triton +Requires-Dist: ninja +Requires-Dist: einops +Requires-Dist: transformers +Requires-Dist: packaging +Requires-Dist: setuptools>=61.0.0 +Provides-Extra: causal-conv1d +Requires-Dist: causal-conv1d>=1.2.0; extra == "causal-conv1d" +Provides-Extra: dev +Requires-Dist: pytest; extra == "dev" + +# Mamba + +![Mamba](assets/selection.png "Selective State Space") +> **Mamba: Linear-Time Sequence Modeling with Selective State Spaces**\ +> Albert Gu*, Tri Dao*\ +> Paper: https://arxiv.org/abs/2312.00752 + +![Mamba-2](assets/ssd_algorithm.png "State Space Dual Model") +> **Transformers are SSMs: Generalized Models and Efficient Algorithms**\ +> **Through Structured State Space Duality**\ +> Tri Dao*, Albert Gu*\ +> Paper: https://arxiv.org/abs/2405.21060 + +## About + +Mamba is a new state space model architecture showing promising performance on information-dense data such as language modeling, where previous subquadratic models fall short of Transformers. +It is based on the line of progress on [structured state space models](https://github.com/state-spaces/s4), +with an efficient hardware-aware design and implementation in the spirit of [FlashAttention](https://github.com/Dao-AILab/flash-attention). + +## Installation + +- [Option] `pip install causal-conv1d>=1.4.0`: an efficient implementation of a simple causal Conv1d layer used inside the Mamba block. +- `pip install mamba-ssm`: the core Mamba package. +- `pip install mamba-ssm[causal-conv1d]`: To install core Mamba package and causal-conv1d. +- `pip install mamba-ssm[dev]`: To install core Mamba package and dev depdencies. + +It can also be built from source with `pip install .` from this repository. + +Try passing `--no-build-isolation` to `pip` if installation encounters difficulties either when building from source or installing from PyPi. Common `pip` complaints that can be resolved in this way include PyTorch versions, but other cases exist as well. + +Other requirements: +- Linux +- NVIDIA GPU +- PyTorch 1.12+ +- CUDA 11.6+ + +For AMD cards, see additional prerequisites below. + +## Usage + +We expose several levels of interface with the Mamba model. + +### Selective SSM + +Mamba is based on a selective SSM layer, which is the focus of the paper (Section 3; Algorithm 2). + +Source: [ops/selective_scan_interface.py](mamba_ssm/ops/selective_scan_interface.py). + +### Mamba Block + +The main module of this repository is the Mamba architecture block wrapping the selective SSM. + +Source: [modules/mamba_simple.py](mamba_ssm/modules/mamba_simple.py). + +Usage: +``` python +import torch +from mamba_ssm import Mamba + +batch, length, dim = 2, 64, 16 +x = torch.randn(batch, length, dim).to("cuda") +model = Mamba( + # This module uses roughly 3 * expand * d_model^2 parameters + d_model=dim, # Model dimension d_model + d_state=16, # SSM state expansion factor + d_conv=4, # Local convolution width + expand=2, # Block expansion factor +).to("cuda") +y = model(x) +assert y.shape == x.shape +``` + +### Mamba-2 + +The Mamba-2 block is implemented at [modules/mamba2.py](mamba_ssm/modules/mamba2.py). + +A simpler version is at [modules/mamba2_simple.py](mamba_ssm/modules/mamba2_simple.py) + +The usage is similar to Mamba(-1): +``` python +from mamba_ssm import Mamba2 +model = Mamba2( + # This module uses roughly 3 * expand * d_model^2 parameters + d_model=dim, # Model dimension d_model + d_state=64, # SSM state expansion factor, typically 64 or 128 + d_conv=4, # Local convolution width + expand=2, # Block expansion factor +).to("cuda") +y = model(x) +assert y.shape == x.shape +``` + +#### SSD + +A minimal version of the inner SSD module (Listing 1 from the Mamba-2 paper) with conversion between "discrete" and "continuous" SSM versions +is at [modules/ssd_minimal.py](mamba_ssm/modules/ssd_minimal.py). + +### Mamba Language Model + +Finally, we provide an example of a complete language model: a deep sequence model backbone (with repeating Mamba blocks) + language model head. + +Source: [models/mixer_seq_simple.py](mamba_ssm/models/mixer_seq_simple.py). + +This is an example of how to integrate Mamba into an end-to-end neural network. +This example is used in the generation scripts below. + + +## Pretrained Models + +Pretrained models are uploaded to +[Hugging Face](https://huggingface.co/state-spaces): `mamba-130m`, `mamba-370m`, +`mamba-790m`, `mamba-1.4b`, `mamba-2.8b`, `mamba2-130m`, `mamba2-370m`, +`mamba2-780m`, `mamba2-1.3b`, `mamba2-2.7b`, `transformerpp-2.7b`, `mamba2attn-2.7b`, trained on 300B tokens on the Pile, as well as `mamba-2.8b-slimpj` +(trained on 600B tokens on the SlimPajama dataset). + + +The models will be autodownloaded by the generation script below. + +These models were trained on the [Pile](https://huggingface.co/datasets/EleutherAI/pile), and follow the standard model dimensions described by GPT-3 and followed by many open source models: + +| Parameters | Layers | Model dim. | +|------------|--------|------------| +| 130M | 24 | 768 | +| 370M | 48 | 1024 | +| 790M | 48 | 1536 | +| 1.4B | 48 | 2048 | +| 2.8B | 64 | 2560 | + +(The layer count of Mamba doubles that of a Transformer with similar size, as two Mamba blocks are needed for each "layer" (MHA block + MLP block) of a Transformer.) + +Note: these are base models trained only for 300B tokens, without any form of downstream modification (instruction tuning, etc.). +Performance is expected to be comparable or better than other architectures trained on similar data, but not to match larger or fine-tuned models. + + +## Evaluations + +To run zero-shot evaluations of models (corresponding to Table 3 of the paper), +we use the +[lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness) +library. + +1. Install `lm-evaluation-harness` by `pip install lm-eval==0.4.2`. +2. Run evaluation with (more documentation at the [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness/tree/big-refactor) repo): +``` sh +lm_eval --model mamba_ssm --model_args pretrained=state-spaces/mamba-130m --tasks lambada_openai,hellaswag,piqa,arc_easy,arc_challenge,winogrande,openbookqa --device cuda --batch_size 256 +python evals/lm_harness_eval.py --model hf --model_args pretrained=EleutherAI/pythia-160m --tasks lambada_openai,hellaswag,piqa,arc_easy,arc_challenge,winogrande --device cuda --batch_size 64 +``` + +To reproduce the results on the `mamba-2.8b-slimpj` model reported in the blogposts: +``` sh +lm_eval --model mamba_ssm --model_args pretrained=state-spaces/mamba-2.8b-slimpj --tasks boolq,piqa,hellaswag,winogrande,arc_easy,arc_challenge,openbookqa,race,truthfulqa_mc2 --device cuda --batch_size 256 +lm_eval --model mamba_ssm --model_args pretrained=state-spaces/mamba-2.8b-slimpj --tasks mmlu --num_fewshot 5 --device cuda --batch_size 256 +``` + +To run evaluations on Mamba-2 models, simply replace the model names: +``` sh +lm_eval --model mamba_ssm --model_args pretrained=state-spaces/mamba2-2.7b --tasks lambada_openai,hellaswag,piqa,arc_easy,arc_challenge,winogrande,openbookqa --device cuda --batch_size 256 +lm_eval --model mamba_ssm --model_args pretrained=state-spaces/transformerpp-2.7b --tasks lambada_openai,hellaswag,piqa,arc_easy,arc_challenge,winogrande,openbookqa --device cuda --batch_size 256 +lm_eval --model mamba_ssm --model_args pretrained=state-spaces/mamba2attn-2.7b --tasks lambada_openai,hellaswag,piqa,arc_easy,arc_challenge,winogrande,openbookqa --device cuda --batch_size 256 +``` + +Note that the result of each task might differ from reported values by 0.1-0.3 due to noise in the evaluation process. + +## Inference + +The script [benchmarks/benchmark_generation_mamba_simple.py](benchmarks/benchmark_generation_mamba_simple.py) +1. autoloads a model from the Hugging Face Hub, +2. generates completions of a user-specified prompt, +3. benchmarks the inference speed of this generation. + +Other configurable options include the top-p (nucleus sampling) probability, and the softmax temperature. + +### Examples + +To test generation latency (e.g. batch size = 1) with different sampling strategies: + +``` sh +python benchmarks/benchmark_generation_mamba_simple.py --model-name "state-spaces/mamba-2.8b" --prompt "My cat wrote all this CUDA code for a new language model and" --topp 0.9 --temperature 0.7 --repetition-penalty 1.2 +python benchmarks/benchmark_generation_mamba_simple.py --model-name "EleutherAI/pythia-2.8b" --prompt "My cat wrote all this CUDA code for a new language model and" --topp 0.9 --temperature 0.7 --repetition-penalty 1.2 +python benchmarks/benchmark_generation_mamba_simple.py --model-name "state-spaces/mamba-2.8b" --prompt "My cat wrote all this CUDA code for a new language model and" --minp 0.05 --topk 0 --temperature 0.7 --repetition-penalty 1.2 +``` + +To test generation throughput with random prompts (e.g. large batch size): +``` sh +python benchmarks/benchmark_generation_mamba_simple.py --model-name "state-spaces/mamba-2.8b" --batch 64 +python benchmarks/benchmark_generation_mamba_simple.py --model-name "EleutherAI/pythia-2.8b" --batch 64 +``` + +With Mamba-2, you just need to change the model name: +``` sh +python benchmarks/benchmark_generation_mamba_simple.py --model-name "state-spaces/mamba2-2.7b" --prompt "My cat wrote all this CUDA code for a new language model and" --topp 0.9 --temperature 0.7 --repetition-penalty 1.2 +``` + + +## Troubleshooting + +### Precision +Our models were trained using PyTorch [AMP](https://pytorch.org/docs/stable/amp.html) for mixed precision. AMP keeps model parameters in float32 and casts to half precision when necessary. +On the other hand, other frameworks like DeepSpeed store parameters in float16 and upcasts when necessary (e.g. for optimizer accumulation). + +We've observed that higher precision for the main model parameters may be necessary, because SSMs are sensitive to their recurrent dynamics. If you are experiencing instabilities, +as a first step please try a framework storing parameters in fp32 (such as AMP). + +### Initialization +Some parts of the model have initializations inherited from prior work on S4 models. +For [example](https://github.com/state-spaces/mamba/blob/f0affcf69f06d1d06cef018ff640bf080a11c421/mamba_ssm/modules/mamba_simple.py#L102), the $\Delta$ parameter has a targeted range by initializing the bias of its linear projection. +However, some frameworks may have post-initialization hooks (e.g. setting all bias terms in `nn.Linear` modules to zero). +If this is the case, you may have to add custom logic (e.g. this [line](https://github.com/state-spaces/mamba/blob/f0affcf69f06d1d06cef018ff640bf080a11c421/mamba_ssm/modules/mamba_simple.py#L104) turns off re-initializing in our trainer, but would be a no-op in any other framework) +that is specific to the training framework. + +## Additional Prerequisites for AMD cards + +### Patching ROCm + +If you are on ROCm 6.0, run the following steps to avoid errors during compilation. This is not required for ROCm 6.1 onwards. + +1. Locate your ROCm installation directory. This is typically found at `/opt/rocm/`, but may vary depending on your installation. + +2. Apply the Patch. Run with `sudo` in case you encounter permission issues. + ```bash + patch /opt/rocm/include/hip/amd_detail/amd_hip_bf16.h < rocm_patch/rocm6_0.patch + ``` + + +## Citation + +If you use this codebase, or otherwise find our work valuable, please cite Mamba: +``` +@article{mamba, + title={Mamba: Linear-Time Sequence Modeling with Selective State Spaces}, + author={Gu, Albert and Dao, Tri}, + journal={arXiv preprint arXiv:2312.00752}, + year={2023} +} + +@inproceedings{mamba2, + title={Transformers are {SSM}s: Generalized Models and Efficient Algorithms Through Structured State Space Duality}, + author={Dao, Tri and Gu, Albert}, + booktitle={International Conference on Machine Learning (ICML)}, + year={2024} +} + +``` diff --git a/mamba_ssm-2.3.1.dist-info/RECORD b/mamba_ssm-2.3.1.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..17843870237afd744fbe2aaef51bbc37ea02d651 --- /dev/null +++ b/mamba_ssm-2.3.1.dist-info/RECORD @@ -0,0 +1,43 @@ 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markdown-it. Markdown parsing, done right! +Keywords: markdown,lexer,parser,commonmark,markdown-it +Author-email: Chris Sewell +Requires-Python: >=3.10 +Description-Content-Type: text/markdown +Classifier: Development Status :: 5 - Production/Stable +Classifier: Intended Audience :: Developers +Classifier: License :: OSI Approved :: MIT License +Classifier: Programming Language :: Python :: 3 +Classifier: Programming Language :: Python :: 3.10 +Classifier: Programming Language :: Python :: 3.11 +Classifier: Programming Language :: Python :: 3.12 +Classifier: Programming Language :: Python :: 3.13 +Classifier: Programming Language :: Python :: Implementation :: CPython +Classifier: Programming Language :: Python :: Implementation :: PyPy +Classifier: Topic :: Software Development :: Libraries :: Python Modules +Classifier: Topic :: Text Processing :: Markup +License-File: LICENSE +License-File: LICENSE.markdown-it +Requires-Dist: mdurl~=0.1 +Requires-Dist: psutil ; extra == "benchmarking" +Requires-Dist: pytest ; extra == "benchmarking" +Requires-Dist: pytest-benchmark ; extra == "benchmarking" +Requires-Dist: commonmark~=0.9 ; extra == "compare" +Requires-Dist: markdown~=3.4 ; extra == "compare" +Requires-Dist: mistletoe~=1.0 ; extra == "compare" +Requires-Dist: mistune~=3.0 ; extra == "compare" +Requires-Dist: panflute~=2.3 ; extra == "compare" +Requires-Dist: markdown-it-pyrs ; extra == "compare" +Requires-Dist: linkify-it-py>=1,<3 ; extra == "linkify" +Requires-Dist: mdit-py-plugins>=0.5.0 ; extra == "plugins" +Requires-Dist: gprof2dot ; extra == "profiling" +Requires-Dist: mdit-py-plugins>=0.5.0 ; extra == "rtd" +Requires-Dist: myst-parser ; extra == "rtd" +Requires-Dist: pyyaml ; extra == "rtd" +Requires-Dist: sphinx ; extra == "rtd" +Requires-Dist: sphinx-copybutton ; extra == "rtd" +Requires-Dist: sphinx-design ; extra == "rtd" +Requires-Dist: sphinx-book-theme~=1.0 ; extra == "rtd" +Requires-Dist: jupyter_sphinx ; extra == "rtd" +Requires-Dist: ipykernel ; extra == "rtd" +Requires-Dist: coverage ; extra == "testing" +Requires-Dist: pytest ; extra == "testing" +Requires-Dist: pytest-cov ; extra == "testing" +Requires-Dist: pytest-regressions ; extra == "testing" +Requires-Dist: requests ; extra == "testing" +Project-URL: Documentation, https://markdown-it-py.readthedocs.io +Project-URL: Homepage, https://github.com/executablebooks/markdown-it-py +Provides-Extra: benchmarking +Provides-Extra: compare +Provides-Extra: linkify +Provides-Extra: plugins +Provides-Extra: profiling +Provides-Extra: rtd +Provides-Extra: testing + +# markdown-it-py + +[![Github-CI][github-ci]][github-link] +[![Coverage Status][codecov-badge]][codecov-link] +[![PyPI][pypi-badge]][pypi-link] +[![Conda][conda-badge]][conda-link] +[![PyPI - Downloads][install-badge]][install-link] + +

+ markdown-it-py icon +

+ +> Markdown parser done right. + +- Follows the __[CommonMark spec](http://spec.commonmark.org/)__ for baseline parsing +- Configurable syntax: you can add new rules and even replace existing ones. +- Pluggable: Adds syntax extensions to extend the parser (see the [plugin list][md-plugins]). +- High speed (see our [benchmarking tests][md-performance]) +- Easy to configure for [security][md-security] +- Member of [Google's Assured Open Source Software](https://cloud.google.com/assured-open-source-software/docs/supported-packages) + +This is a Python port of [markdown-it], and some of its associated plugins. +For more details see: . + +For details on [markdown-it] itself, see: + +- The __[Live demo](https://markdown-it.github.io)__ +- [The markdown-it README][markdown-it-readme] + +**See also:** [markdown-it-pyrs](https://github.com/chrisjsewell/markdown-it-pyrs) for an experimental Rust binding, +for even more speed! + +## Installation + +### PIP + +```bash +pip install markdown-it-py[plugins] +``` + +or with extras + +```bash +pip install markdown-it-py[linkify,plugins] +``` + +### Conda + +```bash +conda install -c conda-forge markdown-it-py +``` + +or with extras + +```bash +conda install -c conda-forge markdown-it-py linkify-it-py mdit-py-plugins +``` + +## Usage + +### Python API Usage + +Render markdown to HTML with markdown-it-py and a custom configuration +with and without plugins and features: + +```python +from markdown_it import MarkdownIt +from mdit_py_plugins.front_matter import front_matter_plugin +from mdit_py_plugins.footnote import footnote_plugin + +md = ( + MarkdownIt('commonmark', {'breaks':True,'html':True}) + .use(front_matter_plugin) + .use(footnote_plugin) + .enable('table') +) +text = (""" +--- +a: 1 +--- + +a | b +- | - +1 | 2 + +A footnote [^1] + +[^1]: some details +""") +tokens = md.parse(text) +html_text = md.render(text) + +## To export the html to a file, uncomment the lines below: +# from pathlib import Path +# Path("output.html").write_text(html_text) +``` + +### Command-line Usage + +Render markdown to HTML with markdown-it-py from the +command-line: + +```console +usage: markdown-it [-h] [-v] [filenames [filenames ...]] + +Parse one or more markdown files, convert each to HTML, and print to stdout + +positional arguments: + filenames specify an optional list of files to convert + +optional arguments: + -h, --help show this help message and exit + -v, --version show program's version number and exit + +Interactive: + + $ markdown-it + markdown-it-py [version 0.0.0] (interactive) + Type Ctrl-D to complete input, or Ctrl-C to exit. + >>> # Example + ... > markdown *input* + ... +

Example

+
+

markdown input

+
+ +Batch: + + $ markdown-it README.md README.footer.md > index.html + +``` + +## References / Thanks + +Big thanks to the authors of [markdown-it]: + +- Alex Kocharin [github/rlidwka](https://github.com/rlidwka) +- Vitaly Puzrin [github/puzrin](https://github.com/puzrin) + +Also [John MacFarlane](https://github.com/jgm) for his work on the CommonMark spec and reference implementations. + +[github-ci]: https://github.com/executablebooks/markdown-it-py/actions/workflows/tests.yml/badge.svg?branch=master +[github-link]: https://github.com/executablebooks/markdown-it-py +[pypi-badge]: https://img.shields.io/pypi/v/markdown-it-py.svg +[pypi-link]: https://pypi.org/project/markdown-it-py +[conda-badge]: https://anaconda.org/conda-forge/markdown-it-py/badges/version.svg +[conda-link]: https://anaconda.org/conda-forge/markdown-it-py +[codecov-badge]: https://codecov.io/gh/executablebooks/markdown-it-py/branch/master/graph/badge.svg +[codecov-link]: https://codecov.io/gh/executablebooks/markdown-it-py +[install-badge]: https://img.shields.io/pypi/dw/markdown-it-py?label=pypi%20installs +[install-link]: https://pypistats.org/packages/markdown-it-py + +[CommonMark spec]: http://spec.commonmark.org/ +[markdown-it]: https://github.com/markdown-it/markdown-it +[markdown-it-readme]: https://github.com/markdown-it/markdown-it/blob/master/README.md +[md-security]: https://markdown-it-py.readthedocs.io/en/latest/security.html +[md-performance]: https://markdown-it-py.readthedocs.io/en/latest/performance.html +[md-plugins]: https://markdown-it-py.readthedocs.io/en/latest/plugins.html + diff --git a/markdown_it_py-4.0.0.dist-info/RECORD b/markdown_it_py-4.0.0.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..8156a48f0bf171c53878b16f7fcf1830fc11e75f --- /dev/null +++ b/markdown_it_py-4.0.0.dist-info/RECORD @@ -0,0 +1,77 @@ +bin/markdown-it,sha256=sPT7OZak_aikSyl8n1l5uISN-ipg5dfdpZJe4h3G7h4,335 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0000000000000000000000000000000000000000..7d829cd792a5d754844f433c6a8dd499564fdcbf --- /dev/null +++ b/markdown_it_py-4.0.0.dist-info/entry_points.txt @@ -0,0 +1,3 @@ +[console_scripts] +markdown-it=markdown_it.cli.parse:main + diff --git a/mdurl-0.1.2.dist-info/INSTALLER b/mdurl-0.1.2.dist-info/INSTALLER new file mode 100644 index 0000000000000000000000000000000000000000..5c69047b2eb8235994febeeae1da4a82365a240a --- /dev/null +++ b/mdurl-0.1.2.dist-info/INSTALLER @@ -0,0 +1 @@ +uv \ No newline at end of file diff --git a/mdurl-0.1.2.dist-info/LICENSE b/mdurl-0.1.2.dist-info/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..2a920c59d8abdd485a774087915986448495fd7c --- /dev/null +++ b/mdurl-0.1.2.dist-info/LICENSE @@ -0,0 +1,46 @@ +Copyright (c) 2015 Vitaly Puzrin, Alex Kocharin. +Copyright (c) 2021 Taneli Hukkinen + +Permission is hereby granted, free of charge, to any person +obtaining a copy of this software and associated documentation +files (the "Software"), to deal in the Software without +restriction, including without limitation the rights to use, +copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the +Software is furnished to do so, subject to the following +conditions: + +The above copyright notice and this permission notice shall be +included in all copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES +OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND +NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT +HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, +WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING +FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR +OTHER DEALINGS IN THE SOFTWARE. + +-------------------------------------------------------------------------------- + +.parse() is based on Joyent's node.js `url` code: + +Copyright Joyent, Inc. and other Node contributors. All rights reserved. +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to +deal in the Software without restriction, including without limitation the +rights to use, copy, modify, merge, publish, distribute, sublicense, and/or +sell copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in +all copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING +FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS +IN THE SOFTWARE. diff --git a/mdurl-0.1.2.dist-info/METADATA b/mdurl-0.1.2.dist-info/METADATA new file mode 100644 index 0000000000000000000000000000000000000000..b4670e86b6dc207c944c55c5d3b84911fb41157a --- /dev/null +++ b/mdurl-0.1.2.dist-info/METADATA @@ -0,0 +1,32 @@ +Metadata-Version: 2.1 +Name: mdurl +Version: 0.1.2 +Summary: Markdown URL utilities +Keywords: markdown,commonmark +Author-email: Taneli Hukkinen +Requires-Python: >=3.7 +Description-Content-Type: text/markdown +Classifier: License :: OSI Approved :: MIT License +Classifier: Operating System :: MacOS +Classifier: Operating System :: Microsoft :: Windows +Classifier: Operating System :: POSIX :: Linux +Classifier: Programming Language :: Python :: 3 :: Only +Classifier: Programming Language :: Python :: 3.7 +Classifier: Programming Language :: Python :: 3.8 +Classifier: Programming Language :: Python :: 3.9 +Classifier: Programming Language :: Python :: 3.10 +Classifier: Programming Language :: Python :: Implementation :: CPython +Classifier: Programming Language :: Python :: Implementation :: PyPy +Classifier: Topic :: Software Development :: Libraries :: Python Modules +Classifier: Typing :: Typed +Project-URL: Homepage, https://github.com/executablebooks/mdurl + +# mdurl + +[![Build Status](https://github.com/executablebooks/mdurl/workflows/Tests/badge.svg?branch=master)](https://github.com/executablebooks/mdurl/actions?query=workflow%3ATests+branch%3Amaster+event%3Apush) +[![codecov.io](https://codecov.io/gh/executablebooks/mdurl/branch/master/graph/badge.svg)](https://codecov.io/gh/executablebooks/mdurl) +[![PyPI version](https://img.shields.io/pypi/v/mdurl)](https://pypi.org/project/mdurl) + +This is a Python port of the JavaScript [mdurl](https://www.npmjs.com/package/mdurl) package. +See the [upstream README.md file](https://github.com/markdown-it/mdurl/blob/master/README.md) for API documentation. + diff --git a/mdurl-0.1.2.dist-info/RECORD b/mdurl-0.1.2.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..74d4c2950c1b50f01a1cc2b871bb993e0641107b --- /dev/null +++ b/mdurl-0.1.2.dist-info/RECORD @@ -0,0 +1,13 @@ +mdurl-0.1.2.dist-info/INSTALLER,sha256=5hhM4Q4mYTT9z6QB6PGpUAW81PGNFrYrdXMj4oM_6ak,2 +mdurl-0.1.2.dist-info/LICENSE,sha256=fGBd9uKGZ6lgMRjpgnT2SknOPu0NJvzM6VNKNF4O-VU,2338 +mdurl-0.1.2.dist-info/METADATA,sha256=tTsp1I9Jk2cFP9o8gefOJ9JVg4Drv4PmYCOwLrfd0l0,1638 +mdurl-0.1.2.dist-info/RECORD,, +mdurl-0.1.2.dist-info/REQUESTED,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0 +mdurl-0.1.2.dist-info/WHEEL,sha256=4TfKIB_xu-04bc2iKz6_zFt-gEFEEDU_31HGhqzOCE8,81 +mdurl/__init__.py,sha256=1vpE89NyXniIRZNC_4f6BPm3Ub4bPntjfyyhLRR7opU,547 +mdurl/_decode.py,sha256=3Q_gDQqU__TvDbu7x-b9LjbVl4QWy5g_qFwljcuvN_Y,3004 +mdurl/_encode.py,sha256=goJLUFt1h4rVZNqqm9t15Nw2W-bFXYQEy3aR01ImWvs,2602 +mdurl/_format.py,sha256=xZct0mdePXA0H3kAqxjGtlB5O86G35DAYMGkA44CmB4,626 +mdurl/_parse.py,sha256=ezZSkM2_4NQ2Zx047sEdcJG7NYQRFHiZK7Y8INHFzwY,11374 +mdurl/_url.py,sha256=5kQnRQN2A_G4svLnRzZcG0bfoD9AbBrYDXousDHZ3z0,284 +mdurl/py.typed,sha256=8PjyZ1aVoQpRVvt71muvuq5qE-jTFZkK-GLHkhdebmc,26 diff --git a/mdurl-0.1.2.dist-info/REQUESTED b/mdurl-0.1.2.dist-info/REQUESTED new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/mdurl-0.1.2.dist-info/WHEEL b/mdurl-0.1.2.dist-info/WHEEL new file mode 100644 index 0000000000000000000000000000000000000000..668ba4d0151c5c76ed6e758061daa8c1b0bf5d21 --- /dev/null +++ b/mdurl-0.1.2.dist-info/WHEEL @@ -0,0 +1,4 @@ +Wheel-Version: 1.0 +Generator: flit 3.7.1 +Root-Is-Purelib: true +Tag: py3-none-any diff --git a/mpmath-1.3.0.dist-info/INSTALLER b/mpmath-1.3.0.dist-info/INSTALLER new file mode 100644 index 0000000000000000000000000000000000000000..5c69047b2eb8235994febeeae1da4a82365a240a --- /dev/null +++ b/mpmath-1.3.0.dist-info/INSTALLER @@ -0,0 +1 @@ +uv \ No newline at end of file diff --git a/mpmath-1.3.0.dist-info/LICENSE b/mpmath-1.3.0.dist-info/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..9ecdc7586d08805bc984539f6672476e86e538b6 --- /dev/null +++ b/mpmath-1.3.0.dist-info/LICENSE @@ -0,0 +1,27 @@ +Copyright (c) 2005-2021 Fredrik Johansson and mpmath contributors + +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are met: + + a. Redistributions of source code must retain the above copyright notice, + this list of conditions and the following disclaimer. + b. Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + c. Neither the name of the copyright holder nor the names of its + contributors may be used to endorse or promote products derived + from this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE +ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR +ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL +DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR +SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER +CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT +LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY +OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH +DAMAGE. diff --git a/mpmath-1.3.0.dist-info/METADATA b/mpmath-1.3.0.dist-info/METADATA new file mode 100644 index 0000000000000000000000000000000000000000..994b48acdba5cd0fdfb28cd1fbb0a84ebf81cba5 --- /dev/null +++ b/mpmath-1.3.0.dist-info/METADATA @@ -0,0 +1,233 @@ +Metadata-Version: 2.1 +Name: mpmath +Version: 1.3.0 +Summary: Python library for arbitrary-precision floating-point arithmetic +Home-page: http://mpmath.org/ +Author: Fredrik Johansson +Author-email: fredrik.johansson@gmail.com +License: BSD +Project-URL: Source, https://github.com/fredrik-johansson/mpmath +Project-URL: Tracker, https://github.com/fredrik-johansson/mpmath/issues +Project-URL: Documentation, http://mpmath.org/doc/current/ +Classifier: License :: OSI Approved :: BSD License +Classifier: Topic :: Scientific/Engineering :: Mathematics +Classifier: Topic :: Software Development :: Libraries :: Python Modules +Classifier: Programming Language :: Python +Classifier: Programming Language :: Python :: 2 +Classifier: Programming Language :: Python :: 2.7 +Classifier: Programming Language :: Python :: 3 +Classifier: Programming Language :: Python :: 3.5 +Classifier: Programming Language :: Python :: 3.6 +Classifier: Programming Language :: Python :: 3.7 +Classifier: Programming Language :: Python :: 3.8 +Classifier: Programming Language :: Python :: 3.9 +Classifier: Programming Language :: Python :: Implementation :: CPython +Classifier: Programming Language :: Python :: Implementation :: PyPy +License-File: LICENSE +Provides-Extra: develop +Requires-Dist: pytest (>=4.6) ; extra == 'develop' +Requires-Dist: pycodestyle ; extra == 'develop' +Requires-Dist: pytest-cov ; extra == 'develop' +Requires-Dist: codecov ; extra == 'develop' +Requires-Dist: wheel ; extra == 'develop' +Provides-Extra: docs +Requires-Dist: sphinx ; extra == 'docs' +Provides-Extra: gmpy +Requires-Dist: gmpy2 (>=2.1.0a4) ; (platform_python_implementation != "PyPy") and extra == 'gmpy' +Provides-Extra: tests +Requires-Dist: pytest (>=4.6) ; extra == 'tests' + +mpmath +====== + +|pypi version| |Build status| |Code coverage status| |Zenodo Badge| + +.. |pypi version| image:: https://img.shields.io/pypi/v/mpmath.svg + :target: https://pypi.python.org/pypi/mpmath +.. |Build status| image:: https://github.com/fredrik-johansson/mpmath/workflows/test/badge.svg + :target: https://github.com/fredrik-johansson/mpmath/actions?workflow=test +.. |Code coverage status| image:: https://codecov.io/gh/fredrik-johansson/mpmath/branch/master/graph/badge.svg + :target: https://codecov.io/gh/fredrik-johansson/mpmath +.. |Zenodo Badge| image:: https://zenodo.org/badge/2934512.svg + :target: https://zenodo.org/badge/latestdoi/2934512 + +A Python library for arbitrary-precision floating-point arithmetic. + +Website: http://mpmath.org/ +Main author: Fredrik Johansson + +Mpmath is free software released under the New BSD License (see the +LICENSE file for details) + +0. History and credits +---------------------- + +The following people (among others) have contributed major patches +or new features to mpmath: + +* Pearu Peterson +* Mario Pernici +* Ondrej Certik +* Vinzent Steinberg +* Nimish Telang +* Mike Taschuk +* Case Van Horsen +* Jorn Baayen +* Chris Smith +* Juan Arias de Reyna +* Ioannis Tziakos +* Aaron Meurer +* Stefan Krastanov +* Ken Allen +* Timo Hartmann +* Sergey B Kirpichev +* Kris Kuhlman +* Paul Masson +* Michael Kagalenko +* Jonathan Warner +* Max Gaukler +* Guillermo Navas-Palencia +* Nike Dattani + +Numerous other people have contributed by reporting bugs, +requesting new features, or suggesting improvements to the +documentation. + +For a detailed changelog, including individual contributions, +see the CHANGES file. + +Fredrik's work on mpmath during summer 2008 was sponsored by Google +as part of the Google Summer of Code program. + +Fredrik's work on mpmath during summer 2009 was sponsored by the +American Institute of Mathematics under the support of the National Science +Foundation Grant No. 0757627 (FRG: L-functions and Modular Forms). + +Any opinions, findings, and conclusions or recommendations expressed in this +material are those of the author(s) and do not necessarily reflect the +views of the sponsors. + +Credit also goes to: + +* The authors of the GMP library and the Python wrapper + gmpy, enabling mpmath to become much faster at + high precision +* The authors of MPFR, pari/gp, MPFUN, and other arbitrary- + precision libraries, whose documentation has been helpful + for implementing many of the algorithms in mpmath +* Wikipedia contributors; Abramowitz & Stegun; Gradshteyn & Ryzhik; + Wolfram Research for MathWorld and the Wolfram Functions site. + These are the main references used for special functions + implementations. +* George Brandl for developing the Sphinx documentation tool + used to build mpmath's documentation + +Release history: + +* Version 1.3.0 released on March 7, 2023 +* Version 1.2.0 released on February 1, 2021 +* Version 1.1.0 released on December 11, 2018 +* Version 1.0.0 released on September 27, 2017 +* Version 0.19 released on June 10, 2014 +* Version 0.18 released on December 31, 2013 +* Version 0.17 released on February 1, 2011 +* Version 0.16 released on September 24, 2010 +* Version 0.15 released on June 6, 2010 +* Version 0.14 released on February 5, 2010 +* Version 0.13 released on August 13, 2009 +* Version 0.12 released on June 9, 2009 +* Version 0.11 released on January 26, 2009 +* Version 0.10 released on October 15, 2008 +* Version 0.9 released on August 23, 2008 +* Version 0.8 released on April 20, 2008 +* Version 0.7 released on March 12, 2008 +* Version 0.6 released on January 13, 2008 +* Version 0.5 released on November 24, 2007 +* Version 0.4 released on November 3, 2007 +* Version 0.3 released on October 5, 2007 +* Version 0.2 released on October 2, 2007 +* Version 0.1 released on September 27, 2007 + +1. Download & installation +-------------------------- + +Mpmath requires Python 2.7 or 3.5 (or later versions). It has been tested +with CPython 2.7, 3.5 through 3.7 and for PyPy. + +The latest release of mpmath can be downloaded from the mpmath +website and from https://github.com/fredrik-johansson/mpmath/releases + +It should also be available in the Python Package Index at +https://pypi.python.org/pypi/mpmath + +To install latest release of Mpmath with pip, simply run + +``pip install mpmath`` + +Or unpack the mpmath archive and run + +``python setup.py install`` + +Mpmath can also be installed using + +``python -m easy_install mpmath`` + +The latest development code is available from +https://github.com/fredrik-johansson/mpmath + +See the main documentation for more detailed instructions. + +2. Running tests +---------------- + +The unit tests in mpmath/tests/ can be run via the script +runtests.py, but it is recommended to run them with py.test +(https://pytest.org/), especially +to generate more useful reports in case there are failures. + +You may also want to check out the demo scripts in the demo +directory. + +The master branch is automatically tested by Travis CI. + +3. Documentation +---------------- + +Documentation in reStructuredText format is available in the +doc directory included with the source package. These files +are human-readable, but can be compiled to prettier HTML using +the build.py script (requires Sphinx, http://sphinx.pocoo.org/). + +See setup.txt in the documentation for more information. + +The most recent documentation is also available in HTML format: + +http://mpmath.org/doc/current/ + +4. Known problems +----------------- + +Mpmath is a work in progress. Major issues include: + +* Some functions may return incorrect values when given extremely + large arguments or arguments very close to singularities. + +* Directed rounding works for arithmetic operations. It is implemented + heuristically for other operations, and their results may be off by one + or two units in the last place (even if otherwise accurate). + +* Some IEEE 754 features are not available. Inifinities and NaN are + partially supported; denormal rounding is currently not available + at all. + +* The interface for switching precision and rounding is not finalized. + The current method is not threadsafe. + +5. Help and bug reports +----------------------- + +General questions and comments can be sent to the mpmath mailinglist, +mpmath@googlegroups.com + +You can also report bugs and send patches to the mpmath issue tracker, +https://github.com/fredrik-johansson/mpmath/issues diff --git a/mpmath-1.3.0.dist-info/RECORD b/mpmath-1.3.0.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..45e6fb5270fece6b354c40b8f57c1cfa617e890a --- /dev/null +++ b/mpmath-1.3.0.dist-info/RECORD @@ -0,0 +1,94 @@ +mpmath-1.3.0.dist-info/INSTALLER,sha256=5hhM4Q4mYTT9z6QB6PGpUAW81PGNFrYrdXMj4oM_6ak,2 +mpmath-1.3.0.dist-info/LICENSE,sha256=wmyugdpFCOXiSZhXd6M4IfGDIj67dNf4z7-Q_n7vL7c,1537 +mpmath-1.3.0.dist-info/METADATA,sha256=RLZupES5wNGa6UgV01a_BHrmtoDBkmi1wmVofNaoFAY,8630 +mpmath-1.3.0.dist-info/RECORD,, +mpmath-1.3.0.dist-info/REQUESTED,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0 +mpmath-1.3.0.dist-info/WHEEL,sha256=2wepM1nk4DS4eFpYrW1TTqPcoGNfHhhO_i5m4cOimbo,92 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b/mpmath-1.3.0.dist-info/WHEEL new file mode 100644 index 0000000000000000000000000000000000000000..57e3d840d59a650ac5bccbad5baeec47d155f0ad --- /dev/null +++ b/mpmath-1.3.0.dist-info/WHEEL @@ -0,0 +1,5 @@ +Wheel-Version: 1.0 +Generator: bdist_wheel (0.38.4) +Root-Is-Purelib: true +Tag: py3-none-any + diff --git a/mpmath-1.3.0.dist-info/top_level.txt b/mpmath-1.3.0.dist-info/top_level.txt new file mode 100644 index 0000000000000000000000000000000000000000..dda7c273a8dd1c6adffa9d2d9901e0ce6876f4ac --- /dev/null +++ b/mpmath-1.3.0.dist-info/top_level.txt @@ -0,0 +1 @@ +mpmath diff --git a/multiprocess-0.70.16.dist-info/COPYING b/multiprocess-0.70.16.dist-info/COPYING new file mode 100644 index 0000000000000000000000000000000000000000..17f34bc3d8ae0889ae327ae0c16bf78870c41527 --- /dev/null +++ b/multiprocess-0.70.16.dist-info/COPYING @@ -0,0 +1,28 @@ +Copyright (c) 2006-2008, R Oudkerk + +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions +are met: + +1. Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. +2. Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. +3. Neither the name of author nor the names of any contributors may be + used to endorse or promote products derived from this software + without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE AUTHOR AND CONTRIBUTORS "AS IS" AND +ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE +ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR OR CONTRIBUTORS BE LIABLE +FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL +DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS +OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) +HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT +LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY +OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF +SUCH DAMAGE. diff --git a/multiprocess-0.70.16.dist-info/INSTALLER b/multiprocess-0.70.16.dist-info/INSTALLER new file mode 100644 index 0000000000000000000000000000000000000000..5c69047b2eb8235994febeeae1da4a82365a240a --- /dev/null +++ b/multiprocess-0.70.16.dist-info/INSTALLER @@ -0,0 +1 @@ +uv \ No newline at end of file diff --git a/multiprocess-0.70.16.dist-info/LICENSE b/multiprocess-0.70.16.dist-info/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..0f46bc0edd00d1950d98fec0f78e4366691391d5 --- /dev/null +++ b/multiprocess-0.70.16.dist-info/LICENSE @@ -0,0 +1,38 @@ +Copyright (c) 2008-2016 California Institute of Technology. +Copyright (c) 2016-2024 The Uncertainty Quantification Foundation. +All rights reserved. + +This software forks the python package "multiprocessing". Licence and +copyright information for multiprocessing can be found in "COPYING". + +This software is available subject to the conditions and terms laid +out below. By downloading and using this software you are agreeing +to the following conditions. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions +are met: + + - Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + + - Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + + - Neither the names of the copyright holders nor the names of any of + the contributors may be used to endorse or promote products derived + from this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS +"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED +TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR +PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR +CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, +EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, +PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; +OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, +WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR +OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF +ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + diff --git a/multiprocess-0.70.16.dist-info/METADATA b/multiprocess-0.70.16.dist-info/METADATA new file mode 100644 index 0000000000000000000000000000000000000000..1e8d30dd497e6ac867b1f7f11f79ac2704525be0 --- /dev/null +++ b/multiprocess-0.70.16.dist-info/METADATA @@ -0,0 +1,203 @@ +Metadata-Version: 2.1 +Name: multiprocess +Version: 0.70.16 +Summary: better multiprocessing and multithreading in Python +Home-page: https://github.com/uqfoundation/multiprocess +Download-URL: https://pypi.org/project/multiprocess/#files +Author: Mike McKerns +Author-email: mmckerns@uqfoundation.org +Maintainer: Mike McKerns +Maintainer-email: mmckerns@uqfoundation.org +License: BSD-3-Clause +Project-URL: Documentation, http://multiprocess.rtfd.io +Project-URL: Source Code, https://github.com/uqfoundation/multiprocess +Project-URL: Bug Tracker, https://github.com/uqfoundation/multiprocess/issues +Platform: Linux +Platform: Windows +Platform: Mac +Classifier: Development Status :: 5 - Production/Stable +Classifier: Intended Audience :: Developers +Classifier: Intended Audience :: Science/Research +Classifier: License :: OSI Approved :: BSD License +Classifier: Programming Language :: Python :: 3 +Classifier: Programming Language :: Python :: 3.8 +Classifier: Programming Language :: Python :: 3.9 +Classifier: Programming Language :: Python :: 3.10 +Classifier: Programming Language :: Python :: 3.11 +Classifier: Programming Language :: Python :: 3.12 +Classifier: Programming Language :: Python :: Implementation :: CPython +Classifier: Programming Language :: Python :: Implementation :: PyPy +Classifier: Topic :: Scientific/Engineering +Classifier: Topic :: Software Development +Requires-Python: >=3.8 +License-File: LICENSE +License-File: COPYING +Requires-Dist: dill (>=0.3.8) + +----------------------------------------------------------------- +multiprocess: better multiprocessing and multithreading in Python +----------------------------------------------------------------- + +About Multiprocess +================== + +``multiprocess`` is a fork of ``multiprocessing``. ``multiprocess`` extends ``multiprocessing`` to provide enhanced serialization, using `dill`. ``multiprocess`` leverages ``multiprocessing`` to support the spawning of processes using the API of the Python standard library's ``threading`` module. ``multiprocessing`` has been distributed as part of the standard library since Python 2.6. + +``multiprocess`` is part of ``pathos``, a Python framework for heterogeneous computing. +``multiprocess`` is in active development, so any user feedback, bug reports, comments, +or suggestions are highly appreciated. A list of issues is located at https://github.com/uqfoundation/multiprocess/issues, with a legacy list maintained at https://uqfoundation.github.io/project/pathos/query. + + +Major Features +============== + +``multiprocess`` enables: + + - objects to be transferred between processes using pipes or multi-producer/multi-consumer queues + - objects to be shared between processes using a server process or (for simple data) shared memory + +``multiprocess`` provides: + + - equivalents of all the synchronization primitives in ``threading`` + - a ``Pool`` class to facilitate submitting tasks to worker processes + - enhanced serialization, using ``dill`` + + +Current Release +=============== + +The latest released version of ``multiprocess`` is available from: + + https://pypi.org/project/multiprocess + +``multiprocess`` is distributed under a 3-clause BSD license, and is a fork of ``multiprocessing``. + + +Development Version +=================== + +You can get the latest development version with all the shiny new features at: + + https://github.com/uqfoundation + +If you have a new contribution, please submit a pull request. + + +Installation +============ + +``multiprocess`` can be installed with ``pip``:: + + $ pip install multiprocess + +For Python 2, a C compiler is required to build the included extension module from source. Python 3 and binary installs do not require a C compiler. + + +Requirements +============ + +``multiprocess`` requires: + + - ``python`` (or ``pypy``), **>=3.8** + - ``setuptools``, **>=42** + - ``dill``, **>=0.3.8** + + +Basic Usage +=========== + +The ``multiprocess.Process`` class follows the API of ``threading.Thread``. +For example :: + + from multiprocess import Process, Queue + + def f(q): + q.put('hello world') + + if __name__ == '__main__': + q = Queue() + p = Process(target=f, args=[q]) + p.start() + print (q.get()) + p.join() + +Synchronization primitives like locks, semaphores and conditions are +available, for example :: + + >>> from multiprocess import Condition + >>> c = Condition() + >>> print (c) + ), 0> + >>> c.acquire() + True + >>> print (c) + ), 0> + +One can also use a manager to create shared objects either in shared +memory or in a server process, for example :: + + >>> from multiprocess import Manager + >>> manager = Manager() + >>> l = manager.list(range(10)) + >>> l.reverse() + >>> print (l) + [9, 8, 7, 6, 5, 4, 3, 2, 1, 0] + >>> print (repr(l)) + + +Tasks can be offloaded to a pool of worker processes in various ways, +for example :: + + >>> from multiprocess import Pool + >>> def f(x): return x*x + ... + >>> p = Pool(4) + >>> result = p.map_async(f, range(10)) + >>> print (result.get(timeout=1)) + [0, 1, 4, 9, 16, 25, 36, 49, 64, 81] + +When ``dill`` is installed, serialization is extended to most objects, +for example :: + + >>> from multiprocess import Pool + >>> p = Pool(4) + >>> print (p.map(lambda x: (lambda y:y**2)(x) + x, xrange(10))) + [0, 2, 6, 12, 20, 30, 42, 56, 72, 90] + + +More Information +================ + +Probably the best way to get started is to look at the documentation at +http://multiprocess.rtfd.io. Also see ``multiprocess.tests`` for scripts that +demonstrate how ``multiprocess`` can be used to leverge multiple processes +to execute Python in parallel. You can run the test suite with +``python -m multiprocess.tests``. As ``multiprocess`` conforms to the +``multiprocessing`` interface, the examples and documentation found at +http://docs.python.org/library/multiprocessing.html also apply to +``multiprocess`` if one will ``import multiprocessing as multiprocess``. +See https://github.com/uqfoundation/multiprocess/tree/master/py3.12/examples +for a set of examples that demonstrate some basic use cases and benchmarking +for running Python code in parallel. Please feel free to submit a ticket on +github, or ask a question on stackoverflow (**@Mike McKerns**). If you would +like to share how you use ``multiprocess`` in your work, please send an email +(to **mmckerns at uqfoundation dot org**). + + +Citation +======== + +If you use ``multiprocess`` to do research that leads to publication, we ask that you +acknowledge use of ``multiprocess`` by citing the following in your publication:: + + M.M. McKerns, L. Strand, T. Sullivan, A. Fang, M.A.G. Aivazis, + "Building a framework for predictive science", Proceedings of + the 10th Python in Science Conference, 2011; + http://arxiv.org/pdf/1202.1056 + + Michael McKerns and Michael Aivazis, + "pathos: a framework for heterogeneous computing", 2010- ; + https://uqfoundation.github.io/project/pathos + +Please see https://uqfoundation.github.io/project/pathos or +http://arxiv.org/pdf/1202.1056 for further information. diff --git a/multiprocess-0.70.16.dist-info/RECORD b/multiprocess-0.70.16.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..c4d4fb70abb6e03712ab20bf56b119ba5cea4176 --- /dev/null +++ b/multiprocess-0.70.16.dist-info/RECORD @@ -0,0 +1,53 @@ +_multiprocess/__init__.py,sha256=zX5_h36TGSL0brHRtBvCL5E59ccW7yjL79i-Y399ODM,321 +multiprocess-0.70.16.dist-info/COPYING,sha256=n3_yfLkw0sMgLuB-PS1hRvTeZ20GmjPaMWbJjNuoOpU,1493 +multiprocess-0.70.16.dist-info/INSTALLER,sha256=5hhM4Q4mYTT9z6QB6PGpUAW81PGNFrYrdXMj4oM_6ak,2 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License +Classifier: Operating System :: OS Independent +Classifier: Programming Language :: C +Classifier: Programming Language :: C++ +Classifier: Programming Language :: Fortran +Classifier: Programming Language :: Python +Classifier: Topic :: Software Development :: Build Tools +Classifier: Typing :: Typed +Project-URL: Bug Tracker, https://github.com/scikit-build/ninja-python-distributions/issues +Project-URL: Documentation, https://github.com/scikit-build/ninja-python-distributions#readme +Project-URL: Download, https://github.com/ninja-build/ninja/releases +Project-URL: Homepage, http://ninja-build.org/ +Project-URL: Mailing list, https://groups.google.com/forum/#!forum/scikit-build +Project-URL: Source Code, https://github.com/scikit-build/ninja-python-distributions +Requires-Python: >=3.8 +Description-Content-Type: text/x-rst + +========================== +Ninja Python Distributions +========================== + +`Ninja `_ is a small build system with a focus on speed. + +The latest Ninja python wheels provide `ninja 1.13.0.gd74ef.kitware.jobserver-pipe-1 `_ executable +and `ninja_syntax.py` for generating `.ninja` files. + +.. image:: https://raw.githubusercontent.com/scikit-build/ninja-python-distributions/master/ninja-python-distributions-logo.png + +Latest Release +-------------- + +.. table:: + + +----------------------------------------------------------------------+---------------------------------------------------------------------------+ + | Versions | Downloads | + +======================================================================+===========================================================================+ + | .. image:: https://img.shields.io/pypi/v/ninja.svg | .. image:: https://img.shields.io/badge/downloads-2535k%20total-green.svg | + | :target: https://pypi.python.org/pypi/ninja | :target: https://pypi.python.org/pypi/ninja | + +----------------------------------------------------------------------+---------------------------------------------------------------------------+ + +Build Status +------------ + +.. table:: + + +---------------+-------------------------------------------------------------------------------------------------------------+ + | | GitHub Actions (Windows, macOS, Linux) | + +===============+=============================================================================================================+ + | PyPI | .. image:: https://github.com/scikit-build/ninja-python-distributions/actions/workflows/build.yml/badge.svg | + | | :target: https://github.com/scikit-build/ninja-python-distributions/actions/workflows/build.yml | + +---------------+-------------------------------------------------------------------------------------------------------------+ + +Maintainers +----------- + +* `How to update ninja version ? `_ + +* `How to make a release ? `_ + + +Miscellaneous +------------- + +* Documentation: https://github.com/scikit-build/ninja-python-distributions#readme +* Source code: https://github.com/scikit-build/ninja-python-distributions +* Mailing list: https://groups.google.com/forum/#!forum/scikit-build + +Python Version Support +---------------------- + +Versions after 1.11.1.1 no longer support Python 2-3.6, and require manylinux2010+ on linux. +Versions after 1.13 no longer support Python 3.7, and require manylinux2014+/musllinux_1_2+ on linux. + +License +------- + +This project is maintained by Jean-Christophe Fillion-Robin from Kitware Inc. +It is covered by the `Apache License, Version 2.0 `_. + +Ninja is also distributed under the `Apache License, Version 2.0 `_. +For more information about Ninja, visit https://ninja-build.org + +Logo was originally created by Libby Rose from Kitware Inc. +It is covered by `CC BY 4.0 `_. + + +History +------- + +ninja-python-distributions was initially developed in November 2016 by +Jean-Christophe Fillion-Robin to facilitate the distribution of project using +`scikit-build `_ and depending on CMake +and Ninja. diff --git a/ninja-1.13.0.dist-info/RECORD b/ninja-1.13.0.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..74c719f0d3e4383c43bf2eafbb9094f4d7479f91 --- /dev/null +++ b/ninja-1.13.0.dist-info/RECORD @@ -0,0 +1,15 @@ +bin/ninja,sha256=aW-WKKednOUDFM-VVtfNGh0exSuP1Sgo9vnbFxlWW2c,372384 +ninja-1.13.0.dist-info/INSTALLER,sha256=5hhM4Q4mYTT9z6QB6PGpUAW81PGNFrYrdXMj4oM_6ak,2 +ninja-1.13.0.dist-info/METADATA,sha256=jXb8Tjgs7c0ivK6qdIrzmz-nkxtyRCOW0VyxgWWdCk4,5148 +ninja-1.13.0.dist-info/RECORD,, +ninja-1.13.0.dist-info/REQUESTED,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0 +ninja-1.13.0.dist-info/WHEEL,sha256=zzOwTeuxXsHOT9QV_vcZk1hX9KJAUdqJD7e-2jGJxLA,150 +ninja-1.13.0.dist-info/licenses/AUTHORS.rst,sha256=bGE1t_Lhm2ir8S7n_jbLDohP84fpJ5sNCuxvDVsKNQg,142 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0000000000000000000000000000000000000000..0a6a9a310a0d2edd46721b7b00182339807a1e25 --- /dev/null +++ b/ninja-1.13.0.dist-info/WHEEL @@ -0,0 +1,6 @@ +Wheel-Version: 1.0 +Generator: scikit-build-core 0.11.5 +Root-Is-Purelib: false +Tag: py3-none-manylinux_2_17_x86_64 +Tag: py3-none-manylinux2014_x86_64 + diff --git a/ninja/__init__.py b/ninja/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..252a4b8337015af7d975e3813f2d90071caa58bf --- /dev/null +++ b/ninja/__init__.py @@ -0,0 +1,60 @@ +from __future__ import annotations + +import os +import subprocess +import sys +import sysconfig +from collections.abc import Iterable +from typing import NoReturn + +from ._version import version as __version__ +from .ninja_syntax import Writer, escape, expand + +__all__ = ["BIN_DIR", "DATA", "Writer", "__version__", "escape", "expand", "ninja"] + + +def __dir__() -> list[str]: + return __all__ + + +def _get_ninja_dir() -> str: + ninja_exe = "ninja" + sysconfig.get_config_var("EXE") + + # Default path + path = os.path.join(sysconfig.get_path("scripts"), ninja_exe) + if os.path.isfile(path): + return os.path.dirname(path) + + # User path + if sys.version_info >= (3, 10): + user_scheme = sysconfig.get_preferred_scheme("user") + elif os.name == "nt": + user_scheme = "nt_user" + elif sys.platform.startswith("darwin") and getattr(sys, "_framework", None): + user_scheme = "osx_framework_user" + else: + user_scheme = "posix_user" + + path = sysconfig.get_path("scripts", scheme=user_scheme) + + if os.path.isfile(os.path.join(path, ninja_exe)): + return path + + # Fallback to python location + path = os.path.dirname(sys.executable) + if os.path.isfile(os.path.join(path, ninja_exe)): + return path + + return "" + + +BIN_DIR = _get_ninja_dir() + + +def _program(name: str, args: Iterable[str]) -> int: + cmd = os.path.join(BIN_DIR, name) + return subprocess.call([cmd, *args], close_fds=False) + + +def ninja() -> NoReturn: + raise SystemExit(_program('ninja', sys.argv[1:])) diff --git a/ninja/__main__.py b/ninja/__main__.py new file mode 100644 index 0000000000000000000000000000000000000000..87772abf7bee12bc06c887a199e791989b8ccdbc --- /dev/null +++ b/ninja/__main__.py @@ -0,0 +1,6 @@ +from __future__ import annotations + +from ninja import ninja + +if __name__ == '__main__': + ninja() diff --git a/ninja/_version.py b/ninja/_version.py new file mode 100644 index 0000000000000000000000000000000000000000..667df30e26167da3017fb177fcf95c652a4040b9 --- /dev/null +++ b/ninja/_version.py @@ -0,0 +1 @@ +version = "1.13.0" diff --git a/ninja/_version.pyi b/ninja/_version.pyi new file mode 100644 index 0000000000000000000000000000000000000000..91744f98344db40b12025cf4e48d9e6320225968 --- /dev/null +++ b/ninja/_version.pyi @@ -0,0 +1,4 @@ +from __future__ import annotations + +version: str +version_tuple: tuple[int, int, int] | tuple[int, int, int, str, str] diff --git a/ninja/ninja_syntax.py b/ninja/ninja_syntax.py new file mode 100644 index 0000000000000000000000000000000000000000..2aa8456e9dbaf802ae8de7c83594ea1206e293e6 --- /dev/null +++ b/ninja/ninja_syntax.py @@ -0,0 +1,231 @@ +#!/usr/bin/python + +# Copyright 2011 Google Inc. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Python module for generating .ninja files. + +Note that this is emphatically not a required piece of Ninja; it's +just a helpful utility for build-file-generation systems that already +use Python. +""" + +import re +import textwrap +from io import TextIOWrapper +from typing import Dict, List, Match, Optional, Tuple, Union + +def escape_path(word: str) -> str: + return word.replace('$ ', '$$ ').replace(' ', '$ ').replace(':', '$:') + +class Writer(object): + def __init__(self, output: TextIOWrapper, width: int = 78) -> None: + self.output = output + self.width = width + + def newline(self) -> None: + self.output.write('\n') + + def comment(self, text: str) -> None: + for line in textwrap.wrap(text, self.width - 2, break_long_words=False, + break_on_hyphens=False): + self.output.write('# ' + line + '\n') + + def variable( + self, + key: str, + value: Optional[Union[bool, int, float, str, List[str]]], + indent: int = 0, + ) -> None: + if value is None: + return + if isinstance(value, list): + value = ' '.join(filter(None, value)) # Filter out empty strings. + self._line('%s = %s' % (key, value), indent) + + def pool(self, name: str, depth: int) -> None: + self._line('pool %s' % name) + self.variable('depth', depth, indent=1) + + def rule( + self, + name: str, + command: str, + description: Optional[str] = None, + depfile: Optional[str] = None, + generator: bool = False, + pool: Optional[str] = None, + restat: bool = False, + rspfile: Optional[str] = None, + rspfile_content: Optional[str] = None, + deps: Optional[Union[str, List[str]]] = None, + ) -> None: + self._line('rule %s' % name) + self.variable('command', command, indent=1) + if description: + self.variable('description', description, indent=1) + if depfile: + self.variable('depfile', depfile, indent=1) + if generator: + self.variable('generator', '1', indent=1) + if pool: + self.variable('pool', pool, indent=1) + if restat: + self.variable('restat', '1', indent=1) + if rspfile: + self.variable('rspfile', rspfile, indent=1) + if rspfile_content: + self.variable('rspfile_content', rspfile_content, indent=1) + if deps: + self.variable('deps', deps, indent=1) + + def build( + self, + outputs: Union[str, List[str]], + rule: str, + inputs: Optional[Union[str, List[str]]] = None, + implicit: Optional[Union[str, List[str]]] = None, + order_only: Optional[Union[str, List[str]]] = None, + variables: Optional[ + Union[ + List[Tuple[str, Optional[Union[str, List[str]]]]], + Dict[str, Optional[Union[str, List[str]]]], + ] + ] = None, + implicit_outputs: Optional[Union[str, List[str]]] = None, + pool: Optional[str] = None, + dyndep: Optional[str] = None, + ) -> List[str]: + outputs = as_list(outputs) + out_outputs = [escape_path(x) for x in outputs] + all_inputs = [escape_path(x) for x in as_list(inputs)] + + if implicit: + implicit = [escape_path(x) for x in as_list(implicit)] + all_inputs.append('|') + all_inputs.extend(implicit) + if order_only: + order_only = [escape_path(x) for x in as_list(order_only)] + all_inputs.append('||') + all_inputs.extend(order_only) + if implicit_outputs: + implicit_outputs = [escape_path(x) + for x in as_list(implicit_outputs)] + out_outputs.append('|') + out_outputs.extend(implicit_outputs) + + self._line('build %s: %s' % (' '.join(out_outputs), + ' '.join([rule] + all_inputs))) + if pool is not None: + self._line(' pool = %s' % pool) + if dyndep is not None: + self._line(' dyndep = %s' % dyndep) + + if variables: + if isinstance(variables, dict): + iterator = iter(variables.items()) + else: + iterator = iter(variables) + + for key, val in iterator: + self.variable(key, val, indent=1) + + return outputs + + def include(self, path: str) -> None: + self._line('include %s' % path) + + def subninja(self, path: str) -> None: + self._line('subninja %s' % path) + + def default(self, paths: Union[str, List[str]]) -> None: + self._line('default %s' % ' '.join(as_list(paths))) + + def _count_dollars_before_index(self, s: str, i: int) -> int: + """Returns the number of '$' characters right in front of s[i].""" + dollar_count = 0 + dollar_index = i - 1 + while dollar_index > 0 and s[dollar_index] == '$': + dollar_count += 1 + dollar_index -= 1 + return dollar_count + + def _line(self, text: str, indent: int = 0) -> None: + """Write 'text' word-wrapped at self.width characters.""" + leading_space = ' ' * indent + while len(leading_space) + len(text) > self.width: + # The text is too wide; wrap if possible. + + # Find the rightmost space that would obey our width constraint and + # that's not an escaped space. + available_space = self.width - len(leading_space) - len(' $') + space = available_space + while True: + space = text.rfind(' ', 0, space) + if (space < 0 or + self._count_dollars_before_index(text, space) % 2 == 0): + break + + if space < 0: + # No such space; just use the first unescaped space we can find. + space = available_space - 1 + while True: + space = text.find(' ', space + 1) + if (space < 0 or + self._count_dollars_before_index(text, space) % 2 == 0): + break + if space < 0: + # Give up on breaking. + break + + self.output.write(leading_space + text[0:space] + ' $\n') + text = text[space+1:] + + # Subsequent lines are continuations, so indent them. + leading_space = ' ' * (indent+2) + + self.output.write(leading_space + text + '\n') + + def close(self) -> None: + self.output.close() + + +def as_list(input: Optional[Union[str, List[str]]]) -> List[str]: + if input is None: + return [] + if isinstance(input, list): + return input + return [input] + + +def escape(string: str) -> str: + """Escape a string such that it can be embedded into a Ninja file without + further interpretation.""" + assert '\n' not in string, 'Ninja syntax does not allow newlines' + # We only have one special metacharacter: '$'. + return string.replace('$', '$$') + + +def expand(string: str, vars: Dict[str, str], local_vars: Dict[str, str] = {}) -> str: + """Expand a string containing $vars as Ninja would. + + Note: doesn't handle the full Ninja variable syntax, but it's enough + to make configure.py's use of it work. + """ + def exp(m: Match[str]) -> str: + var = m.group(1) + if var == '$': + return '$' + return local_vars.get(var, vars.get(var, '')) + return re.sub(r'\$(\$|\w*)', exp, string) diff --git a/ninja/ninja_syntax.pyi b/ninja/ninja_syntax.pyi new file mode 100644 index 0000000000000000000000000000000000000000..8f84bf75bd33a50ab34103342abb227c2d177adc --- /dev/null +++ b/ninja/ninja_syntax.pyi @@ -0,0 +1,37 @@ +from collections.abc import Mapping, Sequence +from os import PathLike + +def escape_path(word: str) -> str: ... + +class Writer: + output: str + width: int + + def __init__(self, output: str, width: int = ...): ... + def newline(self) -> None: ... + def comment(self, text: str) -> None: ... + def variable(self, key: str, value: list[str] | str, indent: int = ...) -> None: ... + def pool(self, name: str, depth: int) -> None: ... + def rule(self, name: str, command: str, description: str | None = None, + depfile: str | None = None, generator: bool = False, + pool: str | None = None, restat: bool = False, + rspfile: str | None = None, rspfile_content: str | None = None, + deps: str | None = None) -> None: + ... + + def build(self, outputs: list[str], rule: str, inputs: list[str] | None = None, + implicit: list[str] | None = None, order_only: list[str] | None = None, + variables: dict[str, str] | None = None, + implicit_outputs: list[str] | None = None, + pool: str | None = None, dyndep: str | None = None) -> None: + ... + def include(self, path: str | PathLike[str]) -> None: ... + def subninja(self, path: str | PathLike[str]) -> None: ... + def default(self, paths: Sequence[str | PathLike[str]]) -> None: ... + def close(self) -> None: ... + +def as_list(input: None | list[str] | str) -> list[str]: ... + +def escape(string: str) -> str: ... + +def expand(string: str, vars: Mapping[str, str], local_vars: Mapping[str, str]=...) -> str: ... diff --git a/ninja/py.typed b/ninja/py.typed new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/numpy/__config__.py b/numpy/__config__.py new file mode 100644 index 0000000000000000000000000000000000000000..361cf053ddf1cf04a73f117f6bcffc7f928f6349 --- /dev/null +++ b/numpy/__config__.py @@ -0,0 +1,162 @@ +# This file is generated by numpy's build process +# It contains system_info results at the time of building this package. +from enum import Enum +from numpy.core._multiarray_umath import ( + __cpu_features__, + __cpu_baseline__, + __cpu_dispatch__, +) + +__all__ = ["show"] +_built_with_meson = True + + +class DisplayModes(Enum): + stdout = "stdout" + dicts = "dicts" + + +def _cleanup(d): + """ + Removes empty values in a `dict` recursively + This ensures we remove values that Meson could not provide to CONFIG + """ + if isinstance(d, dict): + return {k: _cleanup(v) for k, v in d.items() if v and _cleanup(v)} + else: + return d + + +CONFIG = _cleanup( + { + "Compilers": { + "c": { + "name": "gcc", + "linker": r"ld.bfd", + "version": "10.2.1", + "commands": r"cc", + "args": r"-fno-strict-aliasing", + "linker args": r"-Wl,--strip-debug, -fno-strict-aliasing", + }, + "cython": { + "name": "cython", + "linker": r"cython", + "version": "3.0.8", + "commands": r"cython", + "args": r"", + "linker args": r"", + }, + "c++": { + "name": "gcc", + "linker": r"ld.bfd", + "version": "10.2.1", + "commands": r"c++", + "args": r"", + "linker args": r"-Wl,--strip-debug", + }, + }, + "Machine Information": { + "host": { + "cpu": "x86_64", + "family": "x86_64", + "endian": "little", + "system": "linux", + }, + "build": { + "cpu": "x86_64", + "family": "x86_64", + "endian": "little", + "system": "linux", + }, + "cross-compiled": bool("False".lower().replace("false", "")), + }, + "Build Dependencies": { + "blas": { + "name": "openblas64", + "found": bool("True".lower().replace("false", "")), + "version": "0.3.23.dev", + "detection method": "pkgconfig", + "include directory": r"/usr/local/include", + "lib directory": r"/usr/local/lib", + "openblas configuration": r"USE_64BITINT=1 DYNAMIC_ARCH=1 DYNAMIC_OLDER= NO_CBLAS= NO_LAPACK= NO_LAPACKE= NO_AFFINITY=1 USE_OPENMP= HASWELL MAX_THREADS=2", + "pc file directory": r"/usr/local/lib/pkgconfig", + }, + "lapack": { + "name": "dep140551260102944", + "found": bool("True".lower().replace("false", "")), + "version": "1.26.4", + "detection method": "internal", + "include directory": r"unknown", + "lib directory": r"unknown", + "openblas configuration": r"unknown", + "pc file directory": r"unknown", + }, + }, + "Python Information": { + "path": r"/opt/python/cp312-cp312/bin/python", + "version": "3.12", + }, + "SIMD Extensions": { + "baseline": __cpu_baseline__, + "found": [ + feature for feature in __cpu_dispatch__ if __cpu_features__[feature] + ], + "not found": [ + feature for feature in __cpu_dispatch__ if not __cpu_features__[feature] + ], + }, + } +) + + +def _check_pyyaml(): + import yaml + + return yaml + + +def show(mode=DisplayModes.stdout.value): + """ + Show libraries and system information on which NumPy was built + and is being used + + Parameters + ---------- + mode : {`'stdout'`, `'dicts'`}, optional. + Indicates how to display the config information. + `'stdout'` prints to console, `'dicts'` returns a dictionary + of the configuration. + + Returns + ------- + out : {`dict`, `None`} + If mode is `'dicts'`, a dict is returned, else None + + See Also + -------- + get_include : Returns the directory containing NumPy C + header files. + + Notes + ----- + 1. The `'stdout'` mode will give more readable + output if ``pyyaml`` is installed + + """ + if mode == DisplayModes.stdout.value: + try: # Non-standard library, check import + yaml = _check_pyyaml() + + print(yaml.dump(CONFIG)) + except ModuleNotFoundError: + import warnings + import json + + warnings.warn("Install `pyyaml` for better output", stacklevel=1) + print(json.dumps(CONFIG, indent=2)) + elif mode == DisplayModes.dicts.value: + return CONFIG + else: + raise AttributeError( + f"Invalid `mode`, use one of: {', '.join([e.value for e in DisplayModes])}" + ) diff --git a/numpy/__init__.cython-30.pxd b/numpy/__init__.cython-30.pxd new file mode 100644 index 0000000000000000000000000000000000000000..1409514f7a845501a7787f6acb3a5570502d330d --- /dev/null +++ b/numpy/__init__.cython-30.pxd @@ -0,0 +1,1050 @@ +# NumPy static imports for Cython >= 3.0 +# +# If any of the PyArray_* functions are called, import_array must be +# called first. This is done automatically by Cython 3.0+ if a call +# is not detected inside of the module. +# +# Author: Dag Sverre Seljebotn +# + +from cpython.ref cimport Py_INCREF +from cpython.object cimport PyObject, PyTypeObject, PyObject_TypeCheck +cimport libc.stdio as stdio + + +cdef extern from *: + # Leave a marker that the NumPy declarations came from NumPy itself and not from Cython. + # See https://github.com/cython/cython/issues/3573 + """ + /* Using NumPy API declarations from "numpy/__init__.cython-30.pxd" */ + """ + + +cdef extern from "Python.h": + ctypedef int Py_intptr_t + +cdef extern from "numpy/arrayobject.h": + ctypedef Py_intptr_t npy_intp + ctypedef size_t npy_uintp + + cdef enum NPY_TYPES: + NPY_BOOL + NPY_BYTE + NPY_UBYTE + NPY_SHORT + NPY_USHORT + NPY_INT + NPY_UINT + NPY_LONG + NPY_ULONG + NPY_LONGLONG + NPY_ULONGLONG + NPY_FLOAT + NPY_DOUBLE + NPY_LONGDOUBLE + NPY_CFLOAT + NPY_CDOUBLE + NPY_CLONGDOUBLE + NPY_OBJECT + NPY_STRING + NPY_UNICODE + NPY_VOID + NPY_DATETIME + NPY_TIMEDELTA + NPY_NTYPES + NPY_NOTYPE + + NPY_INT8 + NPY_INT16 + NPY_INT32 + NPY_INT64 + NPY_INT128 + NPY_INT256 + NPY_UINT8 + NPY_UINT16 + NPY_UINT32 + NPY_UINT64 + NPY_UINT128 + NPY_UINT256 + NPY_FLOAT16 + NPY_FLOAT32 + NPY_FLOAT64 + NPY_FLOAT80 + NPY_FLOAT96 + NPY_FLOAT128 + NPY_FLOAT256 + NPY_COMPLEX32 + NPY_COMPLEX64 + NPY_COMPLEX128 + NPY_COMPLEX160 + NPY_COMPLEX192 + NPY_COMPLEX256 + NPY_COMPLEX512 + + NPY_INTP + + ctypedef enum NPY_ORDER: + NPY_ANYORDER + NPY_CORDER + NPY_FORTRANORDER + NPY_KEEPORDER + + ctypedef enum NPY_CASTING: + NPY_NO_CASTING + NPY_EQUIV_CASTING + NPY_SAFE_CASTING + NPY_SAME_KIND_CASTING + NPY_UNSAFE_CASTING + + ctypedef enum NPY_CLIPMODE: + NPY_CLIP + NPY_WRAP + NPY_RAISE + + ctypedef enum NPY_SCALARKIND: + NPY_NOSCALAR, + NPY_BOOL_SCALAR, + NPY_INTPOS_SCALAR, + NPY_INTNEG_SCALAR, + NPY_FLOAT_SCALAR, + NPY_COMPLEX_SCALAR, + NPY_OBJECT_SCALAR + + ctypedef enum NPY_SORTKIND: + NPY_QUICKSORT + NPY_HEAPSORT + NPY_MERGESORT + + ctypedef enum NPY_SEARCHSIDE: + NPY_SEARCHLEFT + NPY_SEARCHRIGHT + + enum: + # DEPRECATED since NumPy 1.7 ! Do not use in new code! + NPY_C_CONTIGUOUS + NPY_F_CONTIGUOUS + NPY_CONTIGUOUS + NPY_FORTRAN + NPY_OWNDATA + NPY_FORCECAST + NPY_ENSURECOPY + NPY_ENSUREARRAY + NPY_ELEMENTSTRIDES + NPY_ALIGNED + NPY_NOTSWAPPED + NPY_WRITEABLE + NPY_ARR_HAS_DESCR + + NPY_BEHAVED + NPY_BEHAVED_NS + NPY_CARRAY + NPY_CARRAY_RO + NPY_FARRAY + NPY_FARRAY_RO + NPY_DEFAULT + + NPY_IN_ARRAY + NPY_OUT_ARRAY + NPY_INOUT_ARRAY + NPY_IN_FARRAY + NPY_OUT_FARRAY + NPY_INOUT_FARRAY + + NPY_UPDATE_ALL + + enum: + # Added in NumPy 1.7 to replace the deprecated enums above. + NPY_ARRAY_C_CONTIGUOUS + NPY_ARRAY_F_CONTIGUOUS + NPY_ARRAY_OWNDATA + NPY_ARRAY_FORCECAST + NPY_ARRAY_ENSURECOPY + NPY_ARRAY_ENSUREARRAY + NPY_ARRAY_ELEMENTSTRIDES + NPY_ARRAY_ALIGNED + NPY_ARRAY_NOTSWAPPED + NPY_ARRAY_WRITEABLE + NPY_ARRAY_WRITEBACKIFCOPY + + NPY_ARRAY_BEHAVED + NPY_ARRAY_BEHAVED_NS + NPY_ARRAY_CARRAY + NPY_ARRAY_CARRAY_RO + NPY_ARRAY_FARRAY + NPY_ARRAY_FARRAY_RO + NPY_ARRAY_DEFAULT + + NPY_ARRAY_IN_ARRAY + NPY_ARRAY_OUT_ARRAY + NPY_ARRAY_INOUT_ARRAY + NPY_ARRAY_IN_FARRAY + NPY_ARRAY_OUT_FARRAY + NPY_ARRAY_INOUT_FARRAY + + NPY_ARRAY_UPDATE_ALL + + cdef enum: + NPY_MAXDIMS + + npy_intp NPY_MAX_ELSIZE + + ctypedef void (*PyArray_VectorUnaryFunc)(void *, void *, npy_intp, void *, void *) + + ctypedef struct PyArray_ArrayDescr: + # shape is a tuple, but Cython doesn't support "tuple shape" + # inside a non-PyObject declaration, so we have to declare it + # as just a PyObject*. + PyObject* shape + + ctypedef struct PyArray_Descr: + pass + + ctypedef class numpy.dtype [object PyArray_Descr, check_size ignore]: + # Use PyDataType_* macros when possible, however there are no macros + # for accessing some of the fields, so some are defined. + cdef PyTypeObject* typeobj + cdef char kind + cdef char type + # Numpy sometimes mutates this without warning (e.g. it'll + # sometimes change "|" to "<" in shared dtype objects on + # little-endian machines). If this matters to you, use + # PyArray_IsNativeByteOrder(dtype.byteorder) instead of + # directly accessing this field. + cdef char byteorder + cdef char flags + cdef int type_num + cdef int itemsize "elsize" + cdef int alignment + cdef object fields + cdef tuple names + # Use PyDataType_HASSUBARRAY to test whether this field is + # valid (the pointer can be NULL). Most users should access + # this field via the inline helper method PyDataType_SHAPE. + cdef PyArray_ArrayDescr* subarray + + ctypedef class numpy.flatiter [object PyArrayIterObject, check_size ignore]: + # Use through macros + pass + + ctypedef class numpy.broadcast [object PyArrayMultiIterObject, check_size ignore]: + # Use through macros + pass + + ctypedef struct PyArrayObject: + # For use in situations where ndarray can't replace PyArrayObject*, + # like PyArrayObject**. + pass + + ctypedef class numpy.ndarray [object PyArrayObject, check_size ignore]: + cdef __cythonbufferdefaults__ = {"mode": "strided"} + + # NOTE: no field declarations since direct access is deprecated since NumPy 1.7 + # Instead, we use properties that map to the corresponding C-API functions. + + @property + cdef inline PyObject* base(self) nogil: + """Returns a borrowed reference to the object owning the data/memory. + """ + return PyArray_BASE(self) + + @property + cdef inline dtype descr(self): + """Returns an owned reference to the dtype of the array. + """ + return PyArray_DESCR(self) + + @property + cdef inline int ndim(self) nogil: + """Returns the number of dimensions in the array. + """ + return PyArray_NDIM(self) + + @property + cdef inline npy_intp *shape(self) nogil: + """Returns a pointer to the dimensions/shape of the array. + The number of elements matches the number of dimensions of the array (ndim). + Can return NULL for 0-dimensional arrays. + """ + return PyArray_DIMS(self) + + @property + cdef inline npy_intp *strides(self) nogil: + """Returns a pointer to the strides of the array. + The number of elements matches the number of dimensions of the array (ndim). + """ + return PyArray_STRIDES(self) + + @property + cdef inline npy_intp size(self) nogil: + """Returns the total size (in number of elements) of the array. + """ + return PyArray_SIZE(self) + + @property + cdef inline char* data(self) nogil: + """The pointer to the data buffer as a char*. + This is provided for legacy reasons to avoid direct struct field access. + For new code that needs this access, you probably want to cast the result + of `PyArray_DATA()` instead, which returns a 'void*'. + """ + return PyArray_BYTES(self) + + ctypedef unsigned char npy_bool + + ctypedef signed char npy_byte + ctypedef signed short npy_short + ctypedef signed int npy_int + ctypedef signed long npy_long + ctypedef signed long long npy_longlong + + ctypedef unsigned char npy_ubyte + ctypedef unsigned short npy_ushort + ctypedef unsigned int npy_uint + ctypedef unsigned long npy_ulong + ctypedef unsigned long long npy_ulonglong + + ctypedef float npy_float + ctypedef double npy_double + ctypedef long double npy_longdouble + + ctypedef signed char npy_int8 + ctypedef signed short npy_int16 + ctypedef signed int npy_int32 + ctypedef signed long long npy_int64 + ctypedef signed long long npy_int96 + ctypedef signed long long npy_int128 + + ctypedef unsigned char npy_uint8 + ctypedef unsigned short npy_uint16 + ctypedef unsigned int npy_uint32 + ctypedef unsigned long long npy_uint64 + ctypedef unsigned long long npy_uint96 + ctypedef unsigned long long npy_uint128 + + ctypedef float npy_float32 + ctypedef double npy_float64 + ctypedef long double npy_float80 + ctypedef long double npy_float96 + ctypedef long double npy_float128 + + ctypedef struct npy_cfloat: + float real + float imag + + ctypedef struct npy_cdouble: + double real + double imag + + ctypedef struct npy_clongdouble: + long double real + long double imag + + ctypedef struct npy_complex64: + float real + float imag + + ctypedef struct npy_complex128: + double real + double imag + + ctypedef struct npy_complex160: + long double real + long double imag + + ctypedef struct npy_complex192: + long double real + long double imag + + ctypedef struct npy_complex256: + long double real + long double imag + + ctypedef struct PyArray_Dims: + npy_intp *ptr + int len + + int _import_array() except -1 + # A second definition so _import_array isn't marked as used when we use it here. + # Do not use - subject to change any time. + int __pyx_import_array "_import_array"() except -1 + + # + # Macros from ndarrayobject.h + # + bint PyArray_CHKFLAGS(ndarray m, int flags) nogil + bint PyArray_IS_C_CONTIGUOUS(ndarray arr) nogil + bint PyArray_IS_F_CONTIGUOUS(ndarray arr) nogil + bint PyArray_ISCONTIGUOUS(ndarray m) nogil + bint PyArray_ISWRITEABLE(ndarray m) nogil + bint PyArray_ISALIGNED(ndarray m) nogil + + int PyArray_NDIM(ndarray) nogil + bint PyArray_ISONESEGMENT(ndarray) nogil + bint PyArray_ISFORTRAN(ndarray) nogil + int PyArray_FORTRANIF(ndarray) nogil + + void* PyArray_DATA(ndarray) nogil + char* PyArray_BYTES(ndarray) nogil + + npy_intp* PyArray_DIMS(ndarray) nogil + npy_intp* PyArray_STRIDES(ndarray) nogil + npy_intp PyArray_DIM(ndarray, size_t) nogil + npy_intp PyArray_STRIDE(ndarray, size_t) nogil + + PyObject *PyArray_BASE(ndarray) nogil # returns borrowed reference! + PyArray_Descr *PyArray_DESCR(ndarray) nogil # returns borrowed reference to dtype! + PyArray_Descr *PyArray_DTYPE(ndarray) nogil # returns borrowed reference to dtype! NP 1.7+ alias for descr. + int PyArray_FLAGS(ndarray) nogil + void PyArray_CLEARFLAGS(ndarray, int flags) nogil # Added in NumPy 1.7 + void PyArray_ENABLEFLAGS(ndarray, int flags) nogil # Added in NumPy 1.7 + npy_intp PyArray_ITEMSIZE(ndarray) nogil + int PyArray_TYPE(ndarray arr) nogil + + object PyArray_GETITEM(ndarray arr, void *itemptr) + int PyArray_SETITEM(ndarray arr, void *itemptr, object obj) except -1 + + bint PyTypeNum_ISBOOL(int) nogil + bint PyTypeNum_ISUNSIGNED(int) nogil + bint PyTypeNum_ISSIGNED(int) nogil + bint PyTypeNum_ISINTEGER(int) nogil + bint PyTypeNum_ISFLOAT(int) nogil + bint PyTypeNum_ISNUMBER(int) nogil + bint PyTypeNum_ISSTRING(int) nogil + bint PyTypeNum_ISCOMPLEX(int) nogil + bint PyTypeNum_ISPYTHON(int) nogil + bint PyTypeNum_ISFLEXIBLE(int) nogil + bint PyTypeNum_ISUSERDEF(int) nogil + bint PyTypeNum_ISEXTENDED(int) nogil + bint PyTypeNum_ISOBJECT(int) nogil + + bint PyDataType_ISBOOL(dtype) nogil + bint PyDataType_ISUNSIGNED(dtype) nogil + bint PyDataType_ISSIGNED(dtype) nogil + bint PyDataType_ISINTEGER(dtype) nogil + bint PyDataType_ISFLOAT(dtype) nogil + bint PyDataType_ISNUMBER(dtype) nogil + bint PyDataType_ISSTRING(dtype) nogil + bint PyDataType_ISCOMPLEX(dtype) nogil + bint PyDataType_ISPYTHON(dtype) nogil + bint PyDataType_ISFLEXIBLE(dtype) nogil + bint PyDataType_ISUSERDEF(dtype) nogil + bint PyDataType_ISEXTENDED(dtype) nogil + bint PyDataType_ISOBJECT(dtype) nogil + bint PyDataType_HASFIELDS(dtype) nogil + bint PyDataType_HASSUBARRAY(dtype) nogil + + bint PyArray_ISBOOL(ndarray) nogil + bint PyArray_ISUNSIGNED(ndarray) nogil + bint PyArray_ISSIGNED(ndarray) nogil + bint PyArray_ISINTEGER(ndarray) nogil + bint PyArray_ISFLOAT(ndarray) nogil + bint PyArray_ISNUMBER(ndarray) nogil + bint PyArray_ISSTRING(ndarray) nogil + bint PyArray_ISCOMPLEX(ndarray) nogil + bint PyArray_ISPYTHON(ndarray) nogil + bint PyArray_ISFLEXIBLE(ndarray) nogil + bint PyArray_ISUSERDEF(ndarray) nogil + bint PyArray_ISEXTENDED(ndarray) nogil + bint PyArray_ISOBJECT(ndarray) nogil + bint PyArray_HASFIELDS(ndarray) nogil + + bint PyArray_ISVARIABLE(ndarray) nogil + + bint PyArray_SAFEALIGNEDCOPY(ndarray) nogil + bint PyArray_ISNBO(char) nogil # works on ndarray.byteorder + bint PyArray_IsNativeByteOrder(char) nogil # works on ndarray.byteorder + bint PyArray_ISNOTSWAPPED(ndarray) nogil + bint PyArray_ISBYTESWAPPED(ndarray) nogil + + bint PyArray_FLAGSWAP(ndarray, int) nogil + + bint PyArray_ISCARRAY(ndarray) nogil + bint PyArray_ISCARRAY_RO(ndarray) nogil + bint PyArray_ISFARRAY(ndarray) nogil + bint PyArray_ISFARRAY_RO(ndarray) nogil + bint PyArray_ISBEHAVED(ndarray) nogil + bint PyArray_ISBEHAVED_RO(ndarray) nogil + + + bint PyDataType_ISNOTSWAPPED(dtype) nogil + bint PyDataType_ISBYTESWAPPED(dtype) nogil + + bint PyArray_DescrCheck(object) + + bint PyArray_Check(object) + bint PyArray_CheckExact(object) + + # Cannot be supported due to out arg: + # bint PyArray_HasArrayInterfaceType(object, dtype, object, object&) + # bint PyArray_HasArrayInterface(op, out) + + + bint PyArray_IsZeroDim(object) + # Cannot be supported due to ## ## in macro: + # bint PyArray_IsScalar(object, verbatim work) + bint PyArray_CheckScalar(object) + bint PyArray_IsPythonNumber(object) + bint PyArray_IsPythonScalar(object) + bint PyArray_IsAnyScalar(object) + bint PyArray_CheckAnyScalar(object) + + ndarray PyArray_GETCONTIGUOUS(ndarray) + bint PyArray_SAMESHAPE(ndarray, ndarray) nogil + npy_intp PyArray_SIZE(ndarray) nogil + npy_intp PyArray_NBYTES(ndarray) nogil + + object PyArray_FROM_O(object) + object PyArray_FROM_OF(object m, int flags) + object PyArray_FROM_OT(object m, int type) + object PyArray_FROM_OTF(object m, int type, int flags) + object PyArray_FROMANY(object m, int type, int min, int max, int flags) + object PyArray_ZEROS(int nd, npy_intp* dims, int type, int fortran) + object PyArray_EMPTY(int nd, npy_intp* dims, int type, int fortran) + void PyArray_FILLWBYTE(object, int val) + npy_intp PyArray_REFCOUNT(object) + object PyArray_ContiguousFromAny(op, int, int min_depth, int max_depth) + unsigned char PyArray_EquivArrTypes(ndarray a1, ndarray a2) + bint PyArray_EquivByteorders(int b1, int b2) nogil + object PyArray_SimpleNew(int nd, npy_intp* dims, int typenum) + object PyArray_SimpleNewFromData(int nd, npy_intp* dims, int typenum, void* data) + #object PyArray_SimpleNewFromDescr(int nd, npy_intp* dims, dtype descr) + object PyArray_ToScalar(void* data, ndarray arr) + + void* PyArray_GETPTR1(ndarray m, npy_intp i) nogil + void* PyArray_GETPTR2(ndarray m, npy_intp i, npy_intp j) nogil + void* PyArray_GETPTR3(ndarray m, npy_intp i, npy_intp j, npy_intp k) nogil + void* PyArray_GETPTR4(ndarray m, npy_intp i, npy_intp j, npy_intp k, npy_intp l) nogil + + # Cannot be supported due to out arg + # void PyArray_DESCR_REPLACE(descr) + + + object PyArray_Copy(ndarray) + object PyArray_FromObject(object op, int type, int min_depth, int max_depth) + object PyArray_ContiguousFromObject(object op, int type, int min_depth, int max_depth) + object PyArray_CopyFromObject(object op, int type, int min_depth, int max_depth) + + object PyArray_Cast(ndarray mp, int type_num) + object PyArray_Take(ndarray ap, object items, int axis) + object PyArray_Put(ndarray ap, object items, object values) + + void PyArray_ITER_RESET(flatiter it) nogil + void PyArray_ITER_NEXT(flatiter it) nogil + void PyArray_ITER_GOTO(flatiter it, npy_intp* destination) nogil + void PyArray_ITER_GOTO1D(flatiter it, npy_intp ind) nogil + void* PyArray_ITER_DATA(flatiter it) nogil + bint PyArray_ITER_NOTDONE(flatiter it) nogil + + void PyArray_MultiIter_RESET(broadcast multi) nogil + void PyArray_MultiIter_NEXT(broadcast multi) nogil + void PyArray_MultiIter_GOTO(broadcast multi, npy_intp dest) nogil + void PyArray_MultiIter_GOTO1D(broadcast multi, npy_intp ind) nogil + void* PyArray_MultiIter_DATA(broadcast multi, npy_intp i) nogil + void PyArray_MultiIter_NEXTi(broadcast multi, npy_intp i) nogil + bint PyArray_MultiIter_NOTDONE(broadcast multi) nogil + + # Functions from __multiarray_api.h + + # Functions taking dtype and returning object/ndarray are disabled + # for now as they steal dtype references. I'm conservative and disable + # more than is probably needed until it can be checked further. + int PyArray_SetNumericOps (object) except -1 + object PyArray_GetNumericOps () + int PyArray_INCREF (ndarray) except * # uses PyArray_Item_INCREF... + int PyArray_XDECREF (ndarray) except * # uses PyArray_Item_DECREF... + void PyArray_SetStringFunction (object, int) + dtype PyArray_DescrFromType (int) + object PyArray_TypeObjectFromType (int) + char * PyArray_Zero (ndarray) + char * PyArray_One (ndarray) + #object PyArray_CastToType (ndarray, dtype, int) + int PyArray_CastTo (ndarray, ndarray) except -1 + int PyArray_CastAnyTo (ndarray, ndarray) except -1 + int PyArray_CanCastSafely (int, int) # writes errors + npy_bool PyArray_CanCastTo (dtype, dtype) # writes errors + int PyArray_ObjectType (object, int) except 0 + dtype PyArray_DescrFromObject (object, dtype) + #ndarray* PyArray_ConvertToCommonType (object, int *) + dtype PyArray_DescrFromScalar (object) + dtype PyArray_DescrFromTypeObject (object) + npy_intp PyArray_Size (object) + #object PyArray_Scalar (void *, dtype, object) + #object PyArray_FromScalar (object, dtype) + void PyArray_ScalarAsCtype (object, void *) + #int PyArray_CastScalarToCtype (object, void *, dtype) + #int PyArray_CastScalarDirect (object, dtype, void *, int) + object PyArray_ScalarFromObject (object) + #PyArray_VectorUnaryFunc * PyArray_GetCastFunc (dtype, int) + object PyArray_FromDims (int, int *, int) + #object PyArray_FromDimsAndDataAndDescr (int, int *, dtype, char *) + #object PyArray_FromAny (object, dtype, int, int, int, object) + object PyArray_EnsureArray (object) + object PyArray_EnsureAnyArray (object) + #object PyArray_FromFile (stdio.FILE *, dtype, npy_intp, char *) + #object PyArray_FromString (char *, npy_intp, dtype, npy_intp, char *) + #object PyArray_FromBuffer (object, dtype, npy_intp, npy_intp) + #object PyArray_FromIter (object, dtype, npy_intp) + object PyArray_Return (ndarray) + #object PyArray_GetField (ndarray, dtype, int) + #int PyArray_SetField (ndarray, dtype, int, object) except -1 + object PyArray_Byteswap (ndarray, npy_bool) + object PyArray_Resize (ndarray, PyArray_Dims *, int, NPY_ORDER) + int PyArray_MoveInto (ndarray, ndarray) except -1 + int PyArray_CopyInto (ndarray, ndarray) except -1 + int PyArray_CopyAnyInto (ndarray, ndarray) except -1 + int PyArray_CopyObject (ndarray, object) except -1 + object PyArray_NewCopy (ndarray, NPY_ORDER) + object PyArray_ToList (ndarray) + object PyArray_ToString (ndarray, NPY_ORDER) + int PyArray_ToFile (ndarray, stdio.FILE *, char *, char *) except -1 + int PyArray_Dump (object, object, int) except -1 + object PyArray_Dumps (object, int) + int PyArray_ValidType (int) # Cannot error + void PyArray_UpdateFlags (ndarray, int) + object PyArray_New (type, int, npy_intp *, int, npy_intp *, void *, int, int, object) + #object PyArray_NewFromDescr (type, dtype, int, npy_intp *, npy_intp *, void *, int, object) + #dtype PyArray_DescrNew (dtype) + dtype PyArray_DescrNewFromType (int) + double PyArray_GetPriority (object, double) # clears errors as of 1.25 + object PyArray_IterNew (object) + object PyArray_MultiIterNew (int, ...) + + int PyArray_PyIntAsInt (object) except? -1 + npy_intp PyArray_PyIntAsIntp (object) + int PyArray_Broadcast (broadcast) except -1 + void PyArray_FillObjectArray (ndarray, object) except * + int PyArray_FillWithScalar (ndarray, object) except -1 + npy_bool PyArray_CheckStrides (int, int, npy_intp, npy_intp, npy_intp *, npy_intp *) + dtype PyArray_DescrNewByteorder (dtype, char) + object PyArray_IterAllButAxis (object, int *) + #object PyArray_CheckFromAny (object, dtype, int, int, int, object) + #object PyArray_FromArray (ndarray, dtype, int) + object PyArray_FromInterface (object) + object PyArray_FromStructInterface (object) + #object PyArray_FromArrayAttr (object, dtype, object) + #NPY_SCALARKIND PyArray_ScalarKind (int, ndarray*) + int PyArray_CanCoerceScalar (int, int, NPY_SCALARKIND) + object PyArray_NewFlagsObject (object) + npy_bool PyArray_CanCastScalar (type, type) + #int PyArray_CompareUCS4 (npy_ucs4 *, npy_ucs4 *, register size_t) + int PyArray_RemoveSmallest (broadcast) except -1 + int PyArray_ElementStrides (object) + void PyArray_Item_INCREF (char *, dtype) except * + void PyArray_Item_XDECREF (char *, dtype) except * + object PyArray_FieldNames (object) + object PyArray_Transpose (ndarray, PyArray_Dims *) + object PyArray_TakeFrom (ndarray, object, int, ndarray, NPY_CLIPMODE) + object PyArray_PutTo (ndarray, object, object, NPY_CLIPMODE) + object PyArray_PutMask (ndarray, object, object) + object PyArray_Repeat (ndarray, object, int) + object PyArray_Choose (ndarray, object, ndarray, NPY_CLIPMODE) + int PyArray_Sort (ndarray, int, NPY_SORTKIND) except -1 + object PyArray_ArgSort (ndarray, int, NPY_SORTKIND) + object PyArray_SearchSorted (ndarray, object, NPY_SEARCHSIDE, PyObject *) + object PyArray_ArgMax (ndarray, int, ndarray) + object PyArray_ArgMin (ndarray, int, ndarray) + object PyArray_Reshape (ndarray, object) + object PyArray_Newshape (ndarray, PyArray_Dims *, NPY_ORDER) + object PyArray_Squeeze (ndarray) + #object PyArray_View (ndarray, dtype, type) + object PyArray_SwapAxes (ndarray, int, int) + object PyArray_Max (ndarray, int, ndarray) + object PyArray_Min (ndarray, int, ndarray) + object PyArray_Ptp (ndarray, int, ndarray) + object PyArray_Mean (ndarray, int, int, ndarray) + object PyArray_Trace (ndarray, int, int, int, int, ndarray) + object PyArray_Diagonal (ndarray, int, int, int) + object PyArray_Clip (ndarray, object, object, ndarray) + object PyArray_Conjugate (ndarray, ndarray) + object PyArray_Nonzero (ndarray) + object PyArray_Std (ndarray, int, int, ndarray, int) + object PyArray_Sum (ndarray, int, int, ndarray) + object PyArray_CumSum (ndarray, int, int, ndarray) + object PyArray_Prod (ndarray, int, int, ndarray) + object PyArray_CumProd (ndarray, int, int, ndarray) + object PyArray_All (ndarray, int, ndarray) + object PyArray_Any (ndarray, int, ndarray) + object PyArray_Compress (ndarray, object, int, ndarray) + object PyArray_Flatten (ndarray, NPY_ORDER) + object PyArray_Ravel (ndarray, NPY_ORDER) + npy_intp PyArray_MultiplyList (npy_intp *, int) + int PyArray_MultiplyIntList (int *, int) + void * PyArray_GetPtr (ndarray, npy_intp*) + int PyArray_CompareLists (npy_intp *, npy_intp *, int) + #int PyArray_AsCArray (object*, void *, npy_intp *, int, dtype) + #int PyArray_As1D (object*, char **, int *, int) + #int PyArray_As2D (object*, char ***, int *, int *, int) + int PyArray_Free (object, void *) + #int PyArray_Converter (object, object*) + int PyArray_IntpFromSequence (object, npy_intp *, int) except -1 + object PyArray_Concatenate (object, int) + object PyArray_InnerProduct (object, object) + object PyArray_MatrixProduct (object, object) + object PyArray_CopyAndTranspose (object) + object PyArray_Correlate (object, object, int) + int PyArray_TypestrConvert (int, int) + #int PyArray_DescrConverter (object, dtype*) except 0 + #int PyArray_DescrConverter2 (object, dtype*) except 0 + int PyArray_IntpConverter (object, PyArray_Dims *) except 0 + #int PyArray_BufferConverter (object, chunk) except 0 + int PyArray_AxisConverter (object, int *) except 0 + int PyArray_BoolConverter (object, npy_bool *) except 0 + int PyArray_ByteorderConverter (object, char *) except 0 + int PyArray_OrderConverter (object, NPY_ORDER *) except 0 + unsigned char PyArray_EquivTypes (dtype, dtype) # clears errors + #object PyArray_Zeros (int, npy_intp *, dtype, int) + #object PyArray_Empty (int, npy_intp *, dtype, int) + object PyArray_Where (object, object, object) + object PyArray_Arange (double, double, double, int) + #object PyArray_ArangeObj (object, object, object, dtype) + int PyArray_SortkindConverter (object, NPY_SORTKIND *) except 0 + object PyArray_LexSort (object, int) + object PyArray_Round (ndarray, int, ndarray) + unsigned char PyArray_EquivTypenums (int, int) + int PyArray_RegisterDataType (dtype) except -1 + int PyArray_RegisterCastFunc (dtype, int, PyArray_VectorUnaryFunc *) except -1 + int PyArray_RegisterCanCast (dtype, int, NPY_SCALARKIND) except -1 + #void PyArray_InitArrFuncs (PyArray_ArrFuncs *) + object PyArray_IntTupleFromIntp (int, npy_intp *) + int PyArray_TypeNumFromName (char *) + int PyArray_ClipmodeConverter (object, NPY_CLIPMODE *) except 0 + #int PyArray_OutputConverter (object, ndarray*) except 0 + object PyArray_BroadcastToShape (object, npy_intp *, int) + void _PyArray_SigintHandler (int) + void* _PyArray_GetSigintBuf () + #int PyArray_DescrAlignConverter (object, dtype*) except 0 + #int PyArray_DescrAlignConverter2 (object, dtype*) except 0 + int PyArray_SearchsideConverter (object, void *) except 0 + object PyArray_CheckAxis (ndarray, int *, int) + npy_intp PyArray_OverflowMultiplyList (npy_intp *, int) + int PyArray_CompareString (char *, char *, size_t) + int PyArray_SetBaseObject(ndarray, base) except -1 # NOTE: steals a reference to base! Use "set_array_base()" instead. + + +# Typedefs that matches the runtime dtype objects in +# the numpy module. + +# The ones that are commented out needs an IFDEF function +# in Cython to enable them only on the right systems. + +ctypedef npy_int8 int8_t +ctypedef npy_int16 int16_t +ctypedef npy_int32 int32_t +ctypedef npy_int64 int64_t +#ctypedef npy_int96 int96_t +#ctypedef npy_int128 int128_t + +ctypedef npy_uint8 uint8_t +ctypedef npy_uint16 uint16_t +ctypedef npy_uint32 uint32_t +ctypedef npy_uint64 uint64_t +#ctypedef npy_uint96 uint96_t +#ctypedef npy_uint128 uint128_t + +ctypedef npy_float32 float32_t +ctypedef npy_float64 float64_t +#ctypedef npy_float80 float80_t +#ctypedef npy_float128 float128_t + +ctypedef float complex complex64_t +ctypedef double complex complex128_t + +# The int types are mapped a bit surprising -- +# numpy.int corresponds to 'l' and numpy.long to 'q' +ctypedef npy_long int_t +ctypedef npy_longlong longlong_t + +ctypedef npy_ulong uint_t +ctypedef npy_ulonglong ulonglong_t + +ctypedef npy_intp intp_t +ctypedef npy_uintp uintp_t + +ctypedef npy_double float_t +ctypedef npy_double double_t +ctypedef npy_longdouble longdouble_t + +ctypedef npy_cfloat cfloat_t +ctypedef npy_cdouble cdouble_t +ctypedef npy_clongdouble clongdouble_t + +ctypedef npy_cdouble complex_t + +cdef inline object PyArray_MultiIterNew1(a): + return PyArray_MultiIterNew(1, a) + +cdef inline object PyArray_MultiIterNew2(a, b): + return PyArray_MultiIterNew(2, a, b) + +cdef inline object PyArray_MultiIterNew3(a, b, c): + return PyArray_MultiIterNew(3, a, b, c) + +cdef inline object PyArray_MultiIterNew4(a, b, c, d): + return PyArray_MultiIterNew(4, a, b, c, d) + +cdef inline object PyArray_MultiIterNew5(a, b, c, d, e): + return PyArray_MultiIterNew(5, a, b, c, d, e) + +cdef inline tuple PyDataType_SHAPE(dtype d): + if PyDataType_HASSUBARRAY(d): + return d.subarray.shape + else: + return () + + +cdef extern from "numpy/ndarrayobject.h": + PyTypeObject PyTimedeltaArrType_Type + PyTypeObject PyDatetimeArrType_Type + ctypedef int64_t npy_timedelta + ctypedef int64_t npy_datetime + +cdef extern from "numpy/ndarraytypes.h": + ctypedef struct PyArray_DatetimeMetaData: + NPY_DATETIMEUNIT base + int64_t num + +cdef extern from "numpy/arrayscalars.h": + + # abstract types + ctypedef class numpy.generic [object PyObject]: + pass + ctypedef class numpy.number [object PyObject]: + pass + ctypedef class numpy.integer [object PyObject]: + pass + ctypedef class numpy.signedinteger [object PyObject]: + pass + ctypedef class numpy.unsignedinteger [object PyObject]: + pass + ctypedef class numpy.inexact [object PyObject]: + pass + ctypedef class numpy.floating [object PyObject]: + pass + ctypedef class numpy.complexfloating [object PyObject]: + pass + ctypedef class numpy.flexible [object PyObject]: + pass + ctypedef class numpy.character [object PyObject]: + pass + + ctypedef struct PyDatetimeScalarObject: + # PyObject_HEAD + npy_datetime obval + PyArray_DatetimeMetaData obmeta + + ctypedef struct PyTimedeltaScalarObject: + # PyObject_HEAD + npy_timedelta obval + PyArray_DatetimeMetaData obmeta + + ctypedef enum NPY_DATETIMEUNIT: + NPY_FR_Y + NPY_FR_M + NPY_FR_W + NPY_FR_D + NPY_FR_B + NPY_FR_h + NPY_FR_m + NPY_FR_s + NPY_FR_ms + NPY_FR_us + NPY_FR_ns + NPY_FR_ps + NPY_FR_fs + NPY_FR_as + NPY_FR_GENERIC + + +# +# ufunc API +# + +cdef extern from "numpy/ufuncobject.h": + + ctypedef void (*PyUFuncGenericFunction) (char **, npy_intp *, npy_intp *, void *) + + ctypedef class numpy.ufunc [object PyUFuncObject, check_size ignore]: + cdef: + int nin, nout, nargs + int identity + PyUFuncGenericFunction *functions + void **data + int ntypes + int check_return + char *name + char *types + char *doc + void *ptr + PyObject *obj + PyObject *userloops + + cdef enum: + PyUFunc_Zero + PyUFunc_One + PyUFunc_None + UFUNC_ERR_IGNORE + UFUNC_ERR_WARN + UFUNC_ERR_RAISE + UFUNC_ERR_CALL + UFUNC_ERR_PRINT + UFUNC_ERR_LOG + UFUNC_MASK_DIVIDEBYZERO + UFUNC_MASK_OVERFLOW + UFUNC_MASK_UNDERFLOW + UFUNC_MASK_INVALID + UFUNC_SHIFT_DIVIDEBYZERO + UFUNC_SHIFT_OVERFLOW + UFUNC_SHIFT_UNDERFLOW + UFUNC_SHIFT_INVALID + UFUNC_FPE_DIVIDEBYZERO + UFUNC_FPE_OVERFLOW + UFUNC_FPE_UNDERFLOW + UFUNC_FPE_INVALID + UFUNC_ERR_DEFAULT + UFUNC_ERR_DEFAULT2 + + object PyUFunc_FromFuncAndData(PyUFuncGenericFunction *, + void **, char *, int, int, int, int, char *, char *, int) + int PyUFunc_RegisterLoopForType(ufunc, int, + PyUFuncGenericFunction, int *, void *) except -1 + void PyUFunc_f_f_As_d_d \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_d_d \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_f_f \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_g_g \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_F_F_As_D_D \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_F_F \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_D_D \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_G_G \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_O_O \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_ff_f_As_dd_d \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_ff_f \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_dd_d \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_gg_g \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_FF_F_As_DD_D \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_DD_D \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_FF_F \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_GG_G \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_OO_O \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_O_O_method \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_OO_O_method \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_On_Om \ + (char **, npy_intp *, npy_intp *, void *) + int PyUFunc_GetPyValues \ + (char *, int *, int *, PyObject **) + int PyUFunc_checkfperr \ + (int, PyObject *, int *) + void PyUFunc_clearfperr() + int PyUFunc_getfperr() + int PyUFunc_handlefperr \ + (int, PyObject *, int, int *) except -1 + int PyUFunc_ReplaceLoopBySignature \ + (ufunc, PyUFuncGenericFunction, int *, PyUFuncGenericFunction *) + object PyUFunc_FromFuncAndDataAndSignature \ + (PyUFuncGenericFunction *, void **, char *, int, int, int, + int, char *, char *, int, char *) + + int _import_umath() except -1 + +cdef inline void set_array_base(ndarray arr, object base): + Py_INCREF(base) # important to do this before stealing the reference below! + PyArray_SetBaseObject(arr, base) + +cdef inline object get_array_base(ndarray arr): + base = PyArray_BASE(arr) + if base is NULL: + return None + return base + +# Versions of the import_* functions which are more suitable for +# Cython code. +cdef inline int import_array() except -1: + try: + __pyx_import_array() + except Exception: + raise ImportError("numpy.core.multiarray failed to import") + +cdef inline int import_umath() except -1: + try: + _import_umath() + except Exception: + raise ImportError("numpy.core.umath failed to import") + +cdef inline int import_ufunc() except -1: + try: + _import_umath() + except Exception: + raise ImportError("numpy.core.umath failed to import") + + +cdef inline bint is_timedelta64_object(object obj): + """ + Cython equivalent of `isinstance(obj, np.timedelta64)` + + Parameters + ---------- + obj : object + + Returns + ------- + bool + """ + return PyObject_TypeCheck(obj, &PyTimedeltaArrType_Type) + + +cdef inline bint is_datetime64_object(object obj): + """ + Cython equivalent of `isinstance(obj, np.datetime64)` + + Parameters + ---------- + obj : object + + Returns + ------- + bool + """ + return PyObject_TypeCheck(obj, &PyDatetimeArrType_Type) + + +cdef inline npy_datetime get_datetime64_value(object obj) nogil: + """ + returns the int64 value underlying scalar numpy datetime64 object + + Note that to interpret this as a datetime, the corresponding unit is + also needed. That can be found using `get_datetime64_unit`. + """ + return (obj).obval + + +cdef inline npy_timedelta get_timedelta64_value(object obj) nogil: + """ + returns the int64 value underlying scalar numpy timedelta64 object + """ + return (obj).obval + + +cdef inline NPY_DATETIMEUNIT get_datetime64_unit(object obj) nogil: + """ + returns the unit part of the dtype for a numpy datetime64 object. + """ + return (obj).obmeta.base diff --git a/numpy/__init__.pxd b/numpy/__init__.pxd new file mode 100644 index 0000000000000000000000000000000000000000..ca0a3a6c5288ac5ee384636fff3574ed257e49e4 --- /dev/null +++ b/numpy/__init__.pxd @@ -0,0 +1,1015 @@ +# NumPy static imports for Cython < 3.0 +# +# If any of the PyArray_* functions are called, import_array must be +# called first. +# +# Author: Dag Sverre Seljebotn +# + +DEF _buffer_format_string_len = 255 + +cimport cpython.buffer as pybuf +from cpython.ref cimport Py_INCREF +from cpython.mem cimport PyObject_Malloc, PyObject_Free +from cpython.object cimport PyObject, PyTypeObject +from cpython.buffer cimport PyObject_GetBuffer +from cpython.type cimport type +cimport libc.stdio as stdio + +cdef extern from "Python.h": + ctypedef int Py_intptr_t + bint PyObject_TypeCheck(object obj, PyTypeObject* type) + +cdef extern from "numpy/arrayobject.h": + ctypedef Py_intptr_t npy_intp + ctypedef size_t npy_uintp + + cdef enum NPY_TYPES: + NPY_BOOL + NPY_BYTE + NPY_UBYTE + NPY_SHORT + NPY_USHORT + NPY_INT + NPY_UINT + NPY_LONG + NPY_ULONG + NPY_LONGLONG + NPY_ULONGLONG + NPY_FLOAT + NPY_DOUBLE + NPY_LONGDOUBLE + NPY_CFLOAT + NPY_CDOUBLE + NPY_CLONGDOUBLE + NPY_OBJECT + NPY_STRING + NPY_UNICODE + NPY_VOID + NPY_DATETIME + NPY_TIMEDELTA + NPY_NTYPES + NPY_NOTYPE + + NPY_INT8 + NPY_INT16 + NPY_INT32 + NPY_INT64 + NPY_INT128 + NPY_INT256 + NPY_UINT8 + NPY_UINT16 + NPY_UINT32 + NPY_UINT64 + NPY_UINT128 + NPY_UINT256 + NPY_FLOAT16 + NPY_FLOAT32 + NPY_FLOAT64 + NPY_FLOAT80 + NPY_FLOAT96 + NPY_FLOAT128 + NPY_FLOAT256 + NPY_COMPLEX32 + NPY_COMPLEX64 + NPY_COMPLEX128 + NPY_COMPLEX160 + NPY_COMPLEX192 + NPY_COMPLEX256 + NPY_COMPLEX512 + + NPY_INTP + + ctypedef enum NPY_ORDER: + NPY_ANYORDER + NPY_CORDER + NPY_FORTRANORDER + NPY_KEEPORDER + + ctypedef enum NPY_CASTING: + NPY_NO_CASTING + NPY_EQUIV_CASTING + NPY_SAFE_CASTING + NPY_SAME_KIND_CASTING + NPY_UNSAFE_CASTING + + ctypedef enum NPY_CLIPMODE: + NPY_CLIP + NPY_WRAP + NPY_RAISE + + ctypedef enum NPY_SCALARKIND: + NPY_NOSCALAR, + NPY_BOOL_SCALAR, + NPY_INTPOS_SCALAR, + NPY_INTNEG_SCALAR, + NPY_FLOAT_SCALAR, + NPY_COMPLEX_SCALAR, + NPY_OBJECT_SCALAR + + ctypedef enum NPY_SORTKIND: + NPY_QUICKSORT + NPY_HEAPSORT + NPY_MERGESORT + + ctypedef enum NPY_SEARCHSIDE: + NPY_SEARCHLEFT + NPY_SEARCHRIGHT + + enum: + # DEPRECATED since NumPy 1.7 ! Do not use in new code! + NPY_C_CONTIGUOUS + NPY_F_CONTIGUOUS + NPY_CONTIGUOUS + NPY_FORTRAN + NPY_OWNDATA + NPY_FORCECAST + NPY_ENSURECOPY + NPY_ENSUREARRAY + NPY_ELEMENTSTRIDES + NPY_ALIGNED + NPY_NOTSWAPPED + NPY_WRITEABLE + NPY_ARR_HAS_DESCR + + NPY_BEHAVED + NPY_BEHAVED_NS + NPY_CARRAY + NPY_CARRAY_RO + NPY_FARRAY + NPY_FARRAY_RO + NPY_DEFAULT + + NPY_IN_ARRAY + NPY_OUT_ARRAY + NPY_INOUT_ARRAY + NPY_IN_FARRAY + NPY_OUT_FARRAY + NPY_INOUT_FARRAY + + NPY_UPDATE_ALL + + enum: + # Added in NumPy 1.7 to replace the deprecated enums above. + NPY_ARRAY_C_CONTIGUOUS + NPY_ARRAY_F_CONTIGUOUS + NPY_ARRAY_OWNDATA + NPY_ARRAY_FORCECAST + NPY_ARRAY_ENSURECOPY + NPY_ARRAY_ENSUREARRAY + NPY_ARRAY_ELEMENTSTRIDES + NPY_ARRAY_ALIGNED + NPY_ARRAY_NOTSWAPPED + NPY_ARRAY_WRITEABLE + NPY_ARRAY_WRITEBACKIFCOPY + + NPY_ARRAY_BEHAVED + NPY_ARRAY_BEHAVED_NS + NPY_ARRAY_CARRAY + NPY_ARRAY_CARRAY_RO + NPY_ARRAY_FARRAY + NPY_ARRAY_FARRAY_RO + NPY_ARRAY_DEFAULT + + NPY_ARRAY_IN_ARRAY + NPY_ARRAY_OUT_ARRAY + NPY_ARRAY_INOUT_ARRAY + NPY_ARRAY_IN_FARRAY + NPY_ARRAY_OUT_FARRAY + NPY_ARRAY_INOUT_FARRAY + + NPY_ARRAY_UPDATE_ALL + + cdef enum: + NPY_MAXDIMS + + npy_intp NPY_MAX_ELSIZE + + ctypedef void (*PyArray_VectorUnaryFunc)(void *, void *, npy_intp, void *, void *) + + ctypedef struct PyArray_ArrayDescr: + # shape is a tuple, but Cython doesn't support "tuple shape" + # inside a non-PyObject declaration, so we have to declare it + # as just a PyObject*. + PyObject* shape + + ctypedef struct PyArray_Descr: + pass + + ctypedef class numpy.dtype [object PyArray_Descr, check_size ignore]: + # Use PyDataType_* macros when possible, however there are no macros + # for accessing some of the fields, so some are defined. + cdef PyTypeObject* typeobj + cdef char kind + cdef char type + # Numpy sometimes mutates this without warning (e.g. it'll + # sometimes change "|" to "<" in shared dtype objects on + # little-endian machines). If this matters to you, use + # PyArray_IsNativeByteOrder(dtype.byteorder) instead of + # directly accessing this field. + cdef char byteorder + cdef char flags + cdef int type_num + cdef int itemsize "elsize" + cdef int alignment + cdef object fields + cdef tuple names + # Use PyDataType_HASSUBARRAY to test whether this field is + # valid (the pointer can be NULL). Most users should access + # this field via the inline helper method PyDataType_SHAPE. + cdef PyArray_ArrayDescr* subarray + + ctypedef class numpy.flatiter [object PyArrayIterObject, check_size ignore]: + # Use through macros + pass + + ctypedef class numpy.broadcast [object PyArrayMultiIterObject, check_size ignore]: + cdef int numiter + cdef npy_intp size, index + cdef int nd + cdef npy_intp *dimensions + cdef void **iters + + ctypedef struct PyArrayObject: + # For use in situations where ndarray can't replace PyArrayObject*, + # like PyArrayObject**. + pass + + ctypedef class numpy.ndarray [object PyArrayObject, check_size ignore]: + cdef __cythonbufferdefaults__ = {"mode": "strided"} + + cdef: + # Only taking a few of the most commonly used and stable fields. + # One should use PyArray_* macros instead to access the C fields. + char *data + int ndim "nd" + npy_intp *shape "dimensions" + npy_intp *strides + dtype descr # deprecated since NumPy 1.7 ! + PyObject* base # NOT PUBLIC, DO NOT USE ! + + + + ctypedef unsigned char npy_bool + + ctypedef signed char npy_byte + ctypedef signed short npy_short + ctypedef signed int npy_int + ctypedef signed long npy_long + ctypedef signed long long npy_longlong + + ctypedef unsigned char npy_ubyte + ctypedef unsigned short npy_ushort + ctypedef unsigned int npy_uint + ctypedef unsigned long npy_ulong + ctypedef unsigned long long npy_ulonglong + + ctypedef float npy_float + ctypedef double npy_double + ctypedef long double npy_longdouble + + ctypedef signed char npy_int8 + ctypedef signed short npy_int16 + ctypedef signed int npy_int32 + ctypedef signed long long npy_int64 + ctypedef signed long long npy_int96 + ctypedef signed long long npy_int128 + + ctypedef unsigned char npy_uint8 + ctypedef unsigned short npy_uint16 + ctypedef unsigned int npy_uint32 + ctypedef unsigned long long npy_uint64 + ctypedef unsigned long long npy_uint96 + ctypedef unsigned long long npy_uint128 + + ctypedef float npy_float32 + ctypedef double npy_float64 + ctypedef long double npy_float80 + ctypedef long double npy_float96 + ctypedef long double npy_float128 + + ctypedef struct npy_cfloat: + float real + float imag + + ctypedef struct npy_cdouble: + double real + double imag + + ctypedef struct npy_clongdouble: + long double real + long double imag + + ctypedef struct npy_complex64: + float real + float imag + + ctypedef struct npy_complex128: + double real + double imag + + ctypedef struct npy_complex160: + long double real + long double imag + + ctypedef struct npy_complex192: + long double real + long double imag + + ctypedef struct npy_complex256: + long double real + long double imag + + ctypedef struct PyArray_Dims: + npy_intp *ptr + int len + + int _import_array() except -1 + # A second definition so _import_array isn't marked as used when we use it here. + # Do not use - subject to change any time. + int __pyx_import_array "_import_array"() except -1 + + # + # Macros from ndarrayobject.h + # + bint PyArray_CHKFLAGS(ndarray m, int flags) nogil + bint PyArray_IS_C_CONTIGUOUS(ndarray arr) nogil + bint PyArray_IS_F_CONTIGUOUS(ndarray arr) nogil + bint PyArray_ISCONTIGUOUS(ndarray m) nogil + bint PyArray_ISWRITEABLE(ndarray m) nogil + bint PyArray_ISALIGNED(ndarray m) nogil + + int PyArray_NDIM(ndarray) nogil + bint PyArray_ISONESEGMENT(ndarray) nogil + bint PyArray_ISFORTRAN(ndarray) nogil + int PyArray_FORTRANIF(ndarray) nogil + + void* PyArray_DATA(ndarray) nogil + char* PyArray_BYTES(ndarray) nogil + + npy_intp* PyArray_DIMS(ndarray) nogil + npy_intp* PyArray_STRIDES(ndarray) nogil + npy_intp PyArray_DIM(ndarray, size_t) nogil + npy_intp PyArray_STRIDE(ndarray, size_t) nogil + + PyObject *PyArray_BASE(ndarray) nogil # returns borrowed reference! + PyArray_Descr *PyArray_DESCR(ndarray) nogil # returns borrowed reference to dtype! + int PyArray_FLAGS(ndarray) nogil + npy_intp PyArray_ITEMSIZE(ndarray) nogil + int PyArray_TYPE(ndarray arr) nogil + + object PyArray_GETITEM(ndarray arr, void *itemptr) + int PyArray_SETITEM(ndarray arr, void *itemptr, object obj) except -1 + + bint PyTypeNum_ISBOOL(int) nogil + bint PyTypeNum_ISUNSIGNED(int) nogil + bint PyTypeNum_ISSIGNED(int) nogil + bint PyTypeNum_ISINTEGER(int) nogil + bint PyTypeNum_ISFLOAT(int) nogil + bint PyTypeNum_ISNUMBER(int) nogil + bint PyTypeNum_ISSTRING(int) nogil + bint PyTypeNum_ISCOMPLEX(int) nogil + bint PyTypeNum_ISPYTHON(int) nogil + bint PyTypeNum_ISFLEXIBLE(int) nogil + bint PyTypeNum_ISUSERDEF(int) nogil + bint PyTypeNum_ISEXTENDED(int) nogil + bint PyTypeNum_ISOBJECT(int) nogil + + bint PyDataType_ISBOOL(dtype) nogil + bint PyDataType_ISUNSIGNED(dtype) nogil + bint PyDataType_ISSIGNED(dtype) nogil + bint PyDataType_ISINTEGER(dtype) nogil + bint PyDataType_ISFLOAT(dtype) nogil + bint PyDataType_ISNUMBER(dtype) nogil + bint PyDataType_ISSTRING(dtype) nogil + bint PyDataType_ISCOMPLEX(dtype) nogil + bint PyDataType_ISPYTHON(dtype) nogil + bint PyDataType_ISFLEXIBLE(dtype) nogil + bint PyDataType_ISUSERDEF(dtype) nogil + bint PyDataType_ISEXTENDED(dtype) nogil + bint PyDataType_ISOBJECT(dtype) nogil + bint PyDataType_HASFIELDS(dtype) nogil + bint PyDataType_HASSUBARRAY(dtype) nogil + + bint PyArray_ISBOOL(ndarray) nogil + bint PyArray_ISUNSIGNED(ndarray) nogil + bint PyArray_ISSIGNED(ndarray) nogil + bint PyArray_ISINTEGER(ndarray) nogil + bint PyArray_ISFLOAT(ndarray) nogil + bint PyArray_ISNUMBER(ndarray) nogil + bint PyArray_ISSTRING(ndarray) nogil + bint PyArray_ISCOMPLEX(ndarray) nogil + bint PyArray_ISPYTHON(ndarray) nogil + bint PyArray_ISFLEXIBLE(ndarray) nogil + bint PyArray_ISUSERDEF(ndarray) nogil + bint PyArray_ISEXTENDED(ndarray) nogil + bint PyArray_ISOBJECT(ndarray) nogil + bint PyArray_HASFIELDS(ndarray) nogil + + bint PyArray_ISVARIABLE(ndarray) nogil + + bint PyArray_SAFEALIGNEDCOPY(ndarray) nogil + bint PyArray_ISNBO(char) nogil # works on ndarray.byteorder + bint PyArray_IsNativeByteOrder(char) nogil # works on ndarray.byteorder + bint PyArray_ISNOTSWAPPED(ndarray) nogil + bint PyArray_ISBYTESWAPPED(ndarray) nogil + + bint PyArray_FLAGSWAP(ndarray, int) nogil + + bint PyArray_ISCARRAY(ndarray) nogil + bint PyArray_ISCARRAY_RO(ndarray) nogil + bint PyArray_ISFARRAY(ndarray) nogil + bint PyArray_ISFARRAY_RO(ndarray) nogil + bint PyArray_ISBEHAVED(ndarray) nogil + bint PyArray_ISBEHAVED_RO(ndarray) nogil + + + bint PyDataType_ISNOTSWAPPED(dtype) nogil + bint PyDataType_ISBYTESWAPPED(dtype) nogil + + bint PyArray_DescrCheck(object) + + bint PyArray_Check(object) + bint PyArray_CheckExact(object) + + # Cannot be supported due to out arg: + # bint PyArray_HasArrayInterfaceType(object, dtype, object, object&) + # bint PyArray_HasArrayInterface(op, out) + + + bint PyArray_IsZeroDim(object) + # Cannot be supported due to ## ## in macro: + # bint PyArray_IsScalar(object, verbatim work) + bint PyArray_CheckScalar(object) + bint PyArray_IsPythonNumber(object) + bint PyArray_IsPythonScalar(object) + bint PyArray_IsAnyScalar(object) + bint PyArray_CheckAnyScalar(object) + + ndarray PyArray_GETCONTIGUOUS(ndarray) + bint PyArray_SAMESHAPE(ndarray, ndarray) nogil + npy_intp PyArray_SIZE(ndarray) nogil + npy_intp PyArray_NBYTES(ndarray) nogil + + object PyArray_FROM_O(object) + object PyArray_FROM_OF(object m, int flags) + object PyArray_FROM_OT(object m, int type) + object PyArray_FROM_OTF(object m, int type, int flags) + object PyArray_FROMANY(object m, int type, int min, int max, int flags) + object PyArray_ZEROS(int nd, npy_intp* dims, int type, int fortran) + object PyArray_EMPTY(int nd, npy_intp* dims, int type, int fortran) + void PyArray_FILLWBYTE(object, int val) + npy_intp PyArray_REFCOUNT(object) + object PyArray_ContiguousFromAny(op, int, int min_depth, int max_depth) + unsigned char PyArray_EquivArrTypes(ndarray a1, ndarray a2) + bint PyArray_EquivByteorders(int b1, int b2) nogil + object PyArray_SimpleNew(int nd, npy_intp* dims, int typenum) + object PyArray_SimpleNewFromData(int nd, npy_intp* dims, int typenum, void* data) + #object PyArray_SimpleNewFromDescr(int nd, npy_intp* dims, dtype descr) + object PyArray_ToScalar(void* data, ndarray arr) + + void* PyArray_GETPTR1(ndarray m, npy_intp i) nogil + void* PyArray_GETPTR2(ndarray m, npy_intp i, npy_intp j) nogil + void* PyArray_GETPTR3(ndarray m, npy_intp i, npy_intp j, npy_intp k) nogil + void* PyArray_GETPTR4(ndarray m, npy_intp i, npy_intp j, npy_intp k, npy_intp l) nogil + + # Cannot be supported due to out arg + # void PyArray_DESCR_REPLACE(descr) + + + object PyArray_Copy(ndarray) + object PyArray_FromObject(object op, int type, int min_depth, int max_depth) + object PyArray_ContiguousFromObject(object op, int type, int min_depth, int max_depth) + object PyArray_CopyFromObject(object op, int type, int min_depth, int max_depth) + + object PyArray_Cast(ndarray mp, int type_num) + object PyArray_Take(ndarray ap, object items, int axis) + object PyArray_Put(ndarray ap, object items, object values) + + void PyArray_ITER_RESET(flatiter it) nogil + void PyArray_ITER_NEXT(flatiter it) nogil + void PyArray_ITER_GOTO(flatiter it, npy_intp* destination) nogil + void PyArray_ITER_GOTO1D(flatiter it, npy_intp ind) nogil + void* PyArray_ITER_DATA(flatiter it) nogil + bint PyArray_ITER_NOTDONE(flatiter it) nogil + + void PyArray_MultiIter_RESET(broadcast multi) nogil + void PyArray_MultiIter_NEXT(broadcast multi) nogil + void PyArray_MultiIter_GOTO(broadcast multi, npy_intp dest) nogil + void PyArray_MultiIter_GOTO1D(broadcast multi, npy_intp ind) nogil + void* PyArray_MultiIter_DATA(broadcast multi, npy_intp i) nogil + void PyArray_MultiIter_NEXTi(broadcast multi, npy_intp i) nogil + bint PyArray_MultiIter_NOTDONE(broadcast multi) nogil + + # Functions from __multiarray_api.h + + # Functions taking dtype and returning object/ndarray are disabled + # for now as they steal dtype references. I'm conservative and disable + # more than is probably needed until it can be checked further. + int PyArray_SetNumericOps (object) except -1 + object PyArray_GetNumericOps () + int PyArray_INCREF (ndarray) except * # uses PyArray_Item_INCREF... + int PyArray_XDECREF (ndarray) except * # uses PyArray_Item_DECREF... + void PyArray_SetStringFunction (object, int) + dtype PyArray_DescrFromType (int) + object PyArray_TypeObjectFromType (int) + char * PyArray_Zero (ndarray) + char * PyArray_One (ndarray) + #object PyArray_CastToType (ndarray, dtype, int) + int PyArray_CastTo (ndarray, ndarray) except -1 + int PyArray_CastAnyTo (ndarray, ndarray) except -1 + int PyArray_CanCastSafely (int, int) # writes errors + npy_bool PyArray_CanCastTo (dtype, dtype) # writes errors + int PyArray_ObjectType (object, int) except 0 + dtype PyArray_DescrFromObject (object, dtype) + #ndarray* PyArray_ConvertToCommonType (object, int *) + dtype PyArray_DescrFromScalar (object) + dtype PyArray_DescrFromTypeObject (object) + npy_intp PyArray_Size (object) + #object PyArray_Scalar (void *, dtype, object) + #object PyArray_FromScalar (object, dtype) + void PyArray_ScalarAsCtype (object, void *) + #int PyArray_CastScalarToCtype (object, void *, dtype) + #int PyArray_CastScalarDirect (object, dtype, void *, int) + object PyArray_ScalarFromObject (object) + #PyArray_VectorUnaryFunc * PyArray_GetCastFunc (dtype, int) + object PyArray_FromDims (int, int *, int) + #object PyArray_FromDimsAndDataAndDescr (int, int *, dtype, char *) + #object PyArray_FromAny (object, dtype, int, int, int, object) + object PyArray_EnsureArray (object) + object PyArray_EnsureAnyArray (object) + #object PyArray_FromFile (stdio.FILE *, dtype, npy_intp, char *) + #object PyArray_FromString (char *, npy_intp, dtype, npy_intp, char *) + #object PyArray_FromBuffer (object, dtype, npy_intp, npy_intp) + #object PyArray_FromIter (object, dtype, npy_intp) + object PyArray_Return (ndarray) + #object PyArray_GetField (ndarray, dtype, int) + #int PyArray_SetField (ndarray, dtype, int, object) except -1 + object PyArray_Byteswap (ndarray, npy_bool) + object PyArray_Resize (ndarray, PyArray_Dims *, int, NPY_ORDER) + int PyArray_MoveInto (ndarray, ndarray) except -1 + int PyArray_CopyInto (ndarray, ndarray) except -1 + int PyArray_CopyAnyInto (ndarray, ndarray) except -1 + int PyArray_CopyObject (ndarray, object) except -1 + object PyArray_NewCopy (ndarray, NPY_ORDER) + object PyArray_ToList (ndarray) + object PyArray_ToString (ndarray, NPY_ORDER) + int PyArray_ToFile (ndarray, stdio.FILE *, char *, char *) except -1 + int PyArray_Dump (object, object, int) except -1 + object PyArray_Dumps (object, int) + int PyArray_ValidType (int) # Cannot error + void PyArray_UpdateFlags (ndarray, int) + object PyArray_New (type, int, npy_intp *, int, npy_intp *, void *, int, int, object) + #object PyArray_NewFromDescr (type, dtype, int, npy_intp *, npy_intp *, void *, int, object) + #dtype PyArray_DescrNew (dtype) + dtype PyArray_DescrNewFromType (int) + double PyArray_GetPriority (object, double) # clears errors as of 1.25 + object PyArray_IterNew (object) + object PyArray_MultiIterNew (int, ...) + + int PyArray_PyIntAsInt (object) except? -1 + npy_intp PyArray_PyIntAsIntp (object) + int PyArray_Broadcast (broadcast) except -1 + void PyArray_FillObjectArray (ndarray, object) except * + int PyArray_FillWithScalar (ndarray, object) except -1 + npy_bool PyArray_CheckStrides (int, int, npy_intp, npy_intp, npy_intp *, npy_intp *) + dtype PyArray_DescrNewByteorder (dtype, char) + object PyArray_IterAllButAxis (object, int *) + #object PyArray_CheckFromAny (object, dtype, int, int, int, object) + #object PyArray_FromArray (ndarray, dtype, int) + object PyArray_FromInterface (object) + object PyArray_FromStructInterface (object) + #object PyArray_FromArrayAttr (object, dtype, object) + #NPY_SCALARKIND PyArray_ScalarKind (int, ndarray*) + int PyArray_CanCoerceScalar (int, int, NPY_SCALARKIND) + object PyArray_NewFlagsObject (object) + npy_bool PyArray_CanCastScalar (type, type) + #int PyArray_CompareUCS4 (npy_ucs4 *, npy_ucs4 *, register size_t) + int PyArray_RemoveSmallest (broadcast) except -1 + int PyArray_ElementStrides (object) + void PyArray_Item_INCREF (char *, dtype) except * + void PyArray_Item_XDECREF (char *, dtype) except * + object PyArray_FieldNames (object) + object PyArray_Transpose (ndarray, PyArray_Dims *) + object PyArray_TakeFrom (ndarray, object, int, ndarray, NPY_CLIPMODE) + object PyArray_PutTo (ndarray, object, object, NPY_CLIPMODE) + object PyArray_PutMask (ndarray, object, object) + object PyArray_Repeat (ndarray, object, int) + object PyArray_Choose (ndarray, object, ndarray, NPY_CLIPMODE) + int PyArray_Sort (ndarray, int, NPY_SORTKIND) except -1 + object PyArray_ArgSort (ndarray, int, NPY_SORTKIND) + object PyArray_SearchSorted (ndarray, object, NPY_SEARCHSIDE, PyObject *) + object PyArray_ArgMax (ndarray, int, ndarray) + object PyArray_ArgMin (ndarray, int, ndarray) + object PyArray_Reshape (ndarray, object) + object PyArray_Newshape (ndarray, PyArray_Dims *, NPY_ORDER) + object PyArray_Squeeze (ndarray) + #object PyArray_View (ndarray, dtype, type) + object PyArray_SwapAxes (ndarray, int, int) + object PyArray_Max (ndarray, int, ndarray) + object PyArray_Min (ndarray, int, ndarray) + object PyArray_Ptp (ndarray, int, ndarray) + object PyArray_Mean (ndarray, int, int, ndarray) + object PyArray_Trace (ndarray, int, int, int, int, ndarray) + object PyArray_Diagonal (ndarray, int, int, int) + object PyArray_Clip (ndarray, object, object, ndarray) + object PyArray_Conjugate (ndarray, ndarray) + object PyArray_Nonzero (ndarray) + object PyArray_Std (ndarray, int, int, ndarray, int) + object PyArray_Sum (ndarray, int, int, ndarray) + object PyArray_CumSum (ndarray, int, int, ndarray) + object PyArray_Prod (ndarray, int, int, ndarray) + object PyArray_CumProd (ndarray, int, int, ndarray) + object PyArray_All (ndarray, int, ndarray) + object PyArray_Any (ndarray, int, ndarray) + object PyArray_Compress (ndarray, object, int, ndarray) + object PyArray_Flatten (ndarray, NPY_ORDER) + object PyArray_Ravel (ndarray, NPY_ORDER) + npy_intp PyArray_MultiplyList (npy_intp *, int) + int PyArray_MultiplyIntList (int *, int) + void * PyArray_GetPtr (ndarray, npy_intp*) + int PyArray_CompareLists (npy_intp *, npy_intp *, int) + #int PyArray_AsCArray (object*, void *, npy_intp *, int, dtype) + #int PyArray_As1D (object*, char **, int *, int) + #int PyArray_As2D (object*, char ***, int *, int *, int) + int PyArray_Free (object, void *) + #int PyArray_Converter (object, object*) + int PyArray_IntpFromSequence (object, npy_intp *, int) except -1 + object PyArray_Concatenate (object, int) + object PyArray_InnerProduct (object, object) + object PyArray_MatrixProduct (object, object) + object PyArray_CopyAndTranspose (object) + object PyArray_Correlate (object, object, int) + int PyArray_TypestrConvert (int, int) + #int PyArray_DescrConverter (object, dtype*) except 0 + #int PyArray_DescrConverter2 (object, dtype*) except 0 + int PyArray_IntpConverter (object, PyArray_Dims *) except 0 + #int PyArray_BufferConverter (object, chunk) except 0 + int PyArray_AxisConverter (object, int *) except 0 + int PyArray_BoolConverter (object, npy_bool *) except 0 + int PyArray_ByteorderConverter (object, char *) except 0 + int PyArray_OrderConverter (object, NPY_ORDER *) except 0 + unsigned char PyArray_EquivTypes (dtype, dtype) # clears errors + #object PyArray_Zeros (int, npy_intp *, dtype, int) + #object PyArray_Empty (int, npy_intp *, dtype, int) + object PyArray_Where (object, object, object) + object PyArray_Arange (double, double, double, int) + #object PyArray_ArangeObj (object, object, object, dtype) + int PyArray_SortkindConverter (object, NPY_SORTKIND *) except 0 + object PyArray_LexSort (object, int) + object PyArray_Round (ndarray, int, ndarray) + unsigned char PyArray_EquivTypenums (int, int) + int PyArray_RegisterDataType (dtype) except -1 + int PyArray_RegisterCastFunc (dtype, int, PyArray_VectorUnaryFunc *) except -1 + int PyArray_RegisterCanCast (dtype, int, NPY_SCALARKIND) except -1 + #void PyArray_InitArrFuncs (PyArray_ArrFuncs *) + object PyArray_IntTupleFromIntp (int, npy_intp *) + int PyArray_TypeNumFromName (char *) + int PyArray_ClipmodeConverter (object, NPY_CLIPMODE *) except 0 + #int PyArray_OutputConverter (object, ndarray*) except 0 + object PyArray_BroadcastToShape (object, npy_intp *, int) + void _PyArray_SigintHandler (int) + void* _PyArray_GetSigintBuf () + #int PyArray_DescrAlignConverter (object, dtype*) except 0 + #int PyArray_DescrAlignConverter2 (object, dtype*) except 0 + int PyArray_SearchsideConverter (object, void *) except 0 + object PyArray_CheckAxis (ndarray, int *, int) + npy_intp PyArray_OverflowMultiplyList (npy_intp *, int) + int PyArray_CompareString (char *, char *, size_t) + int PyArray_SetBaseObject(ndarray, base) except -1 # NOTE: steals a reference to base! Use "set_array_base()" instead. + + +# Typedefs that matches the runtime dtype objects in +# the numpy module. + +# The ones that are commented out needs an IFDEF function +# in Cython to enable them only on the right systems. + +ctypedef npy_int8 int8_t +ctypedef npy_int16 int16_t +ctypedef npy_int32 int32_t +ctypedef npy_int64 int64_t +#ctypedef npy_int96 int96_t +#ctypedef npy_int128 int128_t + +ctypedef npy_uint8 uint8_t +ctypedef npy_uint16 uint16_t +ctypedef npy_uint32 uint32_t +ctypedef npy_uint64 uint64_t +#ctypedef npy_uint96 uint96_t +#ctypedef npy_uint128 uint128_t + +ctypedef npy_float32 float32_t +ctypedef npy_float64 float64_t +#ctypedef npy_float80 float80_t +#ctypedef npy_float128 float128_t + +ctypedef float complex complex64_t +ctypedef double complex complex128_t + +# The int types are mapped a bit surprising -- +# numpy.int corresponds to 'l' and numpy.long to 'q' +ctypedef npy_long int_t +ctypedef npy_longlong longlong_t + +ctypedef npy_ulong uint_t +ctypedef npy_ulonglong ulonglong_t + +ctypedef npy_intp intp_t +ctypedef npy_uintp uintp_t + +ctypedef npy_double float_t +ctypedef npy_double double_t +ctypedef npy_longdouble longdouble_t + +ctypedef npy_cfloat cfloat_t +ctypedef npy_cdouble cdouble_t +ctypedef npy_clongdouble clongdouble_t + +ctypedef npy_cdouble complex_t + +cdef inline object PyArray_MultiIterNew1(a): + return PyArray_MultiIterNew(1, a) + +cdef inline object PyArray_MultiIterNew2(a, b): + return PyArray_MultiIterNew(2, a, b) + +cdef inline object PyArray_MultiIterNew3(a, b, c): + return PyArray_MultiIterNew(3, a, b, c) + +cdef inline object PyArray_MultiIterNew4(a, b, c, d): + return PyArray_MultiIterNew(4, a, b, c, d) + +cdef inline object PyArray_MultiIterNew5(a, b, c, d, e): + return PyArray_MultiIterNew(5, a, b, c, d, e) + +cdef inline tuple PyDataType_SHAPE(dtype d): + if PyDataType_HASSUBARRAY(d): + return d.subarray.shape + else: + return () + + +cdef extern from "numpy/ndarrayobject.h": + PyTypeObject PyTimedeltaArrType_Type + PyTypeObject PyDatetimeArrType_Type + ctypedef int64_t npy_timedelta + ctypedef int64_t npy_datetime + +cdef extern from "numpy/ndarraytypes.h": + ctypedef struct PyArray_DatetimeMetaData: + NPY_DATETIMEUNIT base + int64_t num + +cdef extern from "numpy/arrayscalars.h": + + # abstract types + ctypedef class numpy.generic [object PyObject]: + pass + ctypedef class numpy.number [object PyObject]: + pass + ctypedef class numpy.integer [object PyObject]: + pass + ctypedef class numpy.signedinteger [object PyObject]: + pass + ctypedef class numpy.unsignedinteger [object PyObject]: + pass + ctypedef class numpy.inexact [object PyObject]: + pass + ctypedef class numpy.floating [object PyObject]: + pass + ctypedef class numpy.complexfloating [object PyObject]: + pass + ctypedef class numpy.flexible [object PyObject]: + pass + ctypedef class numpy.character [object PyObject]: + pass + + ctypedef struct PyDatetimeScalarObject: + # PyObject_HEAD + npy_datetime obval + PyArray_DatetimeMetaData obmeta + + ctypedef struct PyTimedeltaScalarObject: + # PyObject_HEAD + npy_timedelta obval + PyArray_DatetimeMetaData obmeta + + ctypedef enum NPY_DATETIMEUNIT: + NPY_FR_Y + NPY_FR_M + NPY_FR_W + NPY_FR_D + NPY_FR_B + NPY_FR_h + NPY_FR_m + NPY_FR_s + NPY_FR_ms + NPY_FR_us + NPY_FR_ns + NPY_FR_ps + NPY_FR_fs + NPY_FR_as + NPY_FR_GENERIC + + +# +# ufunc API +# + +cdef extern from "numpy/ufuncobject.h": + + ctypedef void (*PyUFuncGenericFunction) (char **, npy_intp *, npy_intp *, void *) + + ctypedef class numpy.ufunc [object PyUFuncObject, check_size ignore]: + cdef: + int nin, nout, nargs + int identity + PyUFuncGenericFunction *functions + void **data + int ntypes + int check_return + char *name + char *types + char *doc + void *ptr + PyObject *obj + PyObject *userloops + + cdef enum: + PyUFunc_Zero + PyUFunc_One + PyUFunc_None + UFUNC_ERR_IGNORE + UFUNC_ERR_WARN + UFUNC_ERR_RAISE + UFUNC_ERR_CALL + UFUNC_ERR_PRINT + UFUNC_ERR_LOG + UFUNC_MASK_DIVIDEBYZERO + UFUNC_MASK_OVERFLOW + UFUNC_MASK_UNDERFLOW + UFUNC_MASK_INVALID + UFUNC_SHIFT_DIVIDEBYZERO + UFUNC_SHIFT_OVERFLOW + UFUNC_SHIFT_UNDERFLOW + UFUNC_SHIFT_INVALID + UFUNC_FPE_DIVIDEBYZERO + UFUNC_FPE_OVERFLOW + UFUNC_FPE_UNDERFLOW + UFUNC_FPE_INVALID + UFUNC_ERR_DEFAULT + UFUNC_ERR_DEFAULT2 + + object PyUFunc_FromFuncAndData(PyUFuncGenericFunction *, + void **, char *, int, int, int, int, char *, char *, int) + int PyUFunc_RegisterLoopForType(ufunc, int, + PyUFuncGenericFunction, int *, void *) except -1 + void PyUFunc_f_f_As_d_d \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_d_d \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_f_f \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_g_g \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_F_F_As_D_D \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_F_F \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_D_D \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_G_G \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_O_O \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_ff_f_As_dd_d \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_ff_f \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_dd_d \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_gg_g \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_FF_F_As_DD_D \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_DD_D \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_FF_F \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_GG_G \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_OO_O \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_O_O_method \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_OO_O_method \ + (char **, npy_intp *, npy_intp *, void *) + void PyUFunc_On_Om \ + (char **, npy_intp *, npy_intp *, void *) + int PyUFunc_GetPyValues \ + (char *, int *, int *, PyObject **) + int PyUFunc_checkfperr \ + (int, PyObject *, int *) + void PyUFunc_clearfperr() + int PyUFunc_getfperr() + int PyUFunc_handlefperr \ + (int, PyObject *, int, int *) except -1 + int PyUFunc_ReplaceLoopBySignature \ + (ufunc, PyUFuncGenericFunction, int *, PyUFuncGenericFunction *) + object PyUFunc_FromFuncAndDataAndSignature \ + (PyUFuncGenericFunction *, void **, char *, int, int, int, + int, char *, char *, int, char *) + + int _import_umath() except -1 + +cdef inline void set_array_base(ndarray arr, object base): + Py_INCREF(base) # important to do this before stealing the reference below! + PyArray_SetBaseObject(arr, base) + +cdef inline object get_array_base(ndarray arr): + base = PyArray_BASE(arr) + if base is NULL: + return None + return base + +# Versions of the import_* functions which are more suitable for +# Cython code. +cdef inline int import_array() except -1: + try: + __pyx_import_array() + except Exception: + raise ImportError("numpy.core.multiarray failed to import") + +cdef inline int import_umath() except -1: + try: + _import_umath() + except Exception: + raise ImportError("numpy.core.umath failed to import") + +cdef inline int import_ufunc() except -1: + try: + _import_umath() + except Exception: + raise ImportError("numpy.core.umath failed to import") + +cdef extern from *: + # Leave a marker that the NumPy declarations came from this file + # See https://github.com/cython/cython/issues/3573 + """ + /* NumPy API declarations from "numpy/__init__.pxd" */ + """ + + +cdef inline bint is_timedelta64_object(object obj): + """ + Cython equivalent of `isinstance(obj, np.timedelta64)` + + Parameters + ---------- + obj : object + + Returns + ------- + bool + """ + return PyObject_TypeCheck(obj, &PyTimedeltaArrType_Type) + + +cdef inline bint is_datetime64_object(object obj): + """ + Cython equivalent of `isinstance(obj, np.datetime64)` + + Parameters + ---------- + obj : object + + Returns + ------- + bool + """ + return PyObject_TypeCheck(obj, &PyDatetimeArrType_Type) + + +cdef inline npy_datetime get_datetime64_value(object obj) nogil: + """ + returns the int64 value underlying scalar numpy datetime64 object + + Note that to interpret this as a datetime, the corresponding unit is + also needed. That can be found using `get_datetime64_unit`. + """ + return (obj).obval + + +cdef inline npy_timedelta get_timedelta64_value(object obj) nogil: + """ + returns the int64 value underlying scalar numpy timedelta64 object + """ + return (obj).obval + + +cdef inline NPY_DATETIMEUNIT get_datetime64_unit(object obj) nogil: + """ + returns the unit part of the dtype for a numpy datetime64 object. + """ + return (obj).obmeta.base diff --git a/numpy/__init__.py b/numpy/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..91da496a95271f8e3eb4f4ea2cbaec925325a1f5 --- /dev/null +++ b/numpy/__init__.py @@ -0,0 +1,461 @@ +""" +NumPy +===== + +Provides + 1. An array object of arbitrary homogeneous items + 2. Fast mathematical operations over arrays + 3. Linear Algebra, Fourier Transforms, Random Number Generation + +How to use the documentation +---------------------------- +Documentation is available in two forms: docstrings provided +with the code, and a loose standing reference guide, available from +`the NumPy homepage `_. + +We recommend exploring the docstrings using +`IPython `_, an advanced Python shell with +TAB-completion and introspection capabilities. See below for further +instructions. + +The docstring examples assume that `numpy` has been imported as ``np``:: + + >>> import numpy as np + +Code snippets are indicated by three greater-than signs:: + + >>> x = 42 + >>> x = x + 1 + +Use the built-in ``help`` function to view a function's docstring:: + + >>> help(np.sort) + ... # doctest: +SKIP + +For some objects, ``np.info(obj)`` may provide additional help. This is +particularly true if you see the line "Help on ufunc object:" at the top +of the help() page. Ufuncs are implemented in C, not Python, for speed. +The native Python help() does not know how to view their help, but our +np.info() function does. + +To search for documents containing a keyword, do:: + + >>> np.lookfor('keyword') + ... # doctest: +SKIP + +General-purpose documents like a glossary and help on the basic concepts +of numpy are available under the ``doc`` sub-module:: + + >>> from numpy import doc + >>> help(doc) + ... # doctest: +SKIP + +Available subpackages +--------------------- +lib + Basic functions used by several sub-packages. +random + Core Random Tools +linalg + Core Linear Algebra Tools +fft + Core FFT routines +polynomial + Polynomial tools +testing + NumPy testing tools +distutils + Enhancements to distutils with support for + Fortran compilers support and more (for Python <= 3.11). + +Utilities +--------- +test + Run numpy unittests +show_config + Show numpy build configuration +matlib + Make everything matrices. +__version__ + NumPy version string + +Viewing documentation using IPython +----------------------------------- + +Start IPython and import `numpy` usually under the alias ``np``: `import +numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste +examples into the shell. To see which functions are available in `numpy`, +type ``np.`` (where ```` refers to the TAB key), or use +``np.*cos*?`` (where ```` refers to the ENTER key) to narrow +down the list. To view the docstring for a function, use +``np.cos?`` (to view the docstring) and ``np.cos??`` (to view +the source code). + +Copies vs. in-place operation +----------------------------- +Most of the functions in `numpy` return a copy of the array argument +(e.g., `np.sort`). In-place versions of these functions are often +available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. +Exceptions to this rule are documented. + +""" +import sys +import warnings + +from ._globals import _NoValue, _CopyMode +# These exceptions were moved in 1.25 and are hidden from __dir__() +from .exceptions import ( + ComplexWarning, ModuleDeprecationWarning, VisibleDeprecationWarning, + TooHardError, AxisError) + + +# If a version with git hash was stored, use that instead +from . import version +from .version import __version__ + +# We first need to detect if we're being called as part of the numpy setup +# procedure itself in a reliable manner. +try: + __NUMPY_SETUP__ +except NameError: + __NUMPY_SETUP__ = False + +if __NUMPY_SETUP__: + sys.stderr.write('Running from numpy source directory.\n') +else: + # Allow distributors to run custom init code before importing numpy.core + from . import _distributor_init + + try: + from numpy.__config__ import show as show_config + except ImportError as e: + msg = """Error importing numpy: you should not try to import numpy from + its source directory; please exit the numpy source tree, and relaunch + your python interpreter from there.""" + raise ImportError(msg) from e + + __all__ = [ + 'exceptions', 'ModuleDeprecationWarning', 'VisibleDeprecationWarning', + 'ComplexWarning', 'TooHardError', 'AxisError'] + + # mapping of {name: (value, deprecation_msg)} + __deprecated_attrs__ = {} + + from . import core + from .core import * + from . import compat + from . import exceptions + from . import dtypes + from . import lib + # NOTE: to be revisited following future namespace cleanup. + # See gh-14454 and gh-15672 for discussion. + from .lib import * + + from . import linalg + from . import fft + from . import polynomial + from . import random + from . import ctypeslib + from . import ma + from . import matrixlib as _mat + from .matrixlib import * + + # Deprecations introduced in NumPy 1.20.0, 2020-06-06 + import builtins as _builtins + + _msg = ( + "module 'numpy' has no attribute '{n}'.\n" + "`np.{n}` was a deprecated alias for the builtin `{n}`. " + "To avoid this error in existing code, use `{n}` by itself. " + "Doing this will not modify any behavior and is safe. {extended_msg}\n" + "The aliases was originally deprecated in NumPy 1.20; for more " + "details and guidance see the original release note at:\n" + " https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations") + + _specific_msg = ( + "If you specifically wanted the numpy scalar type, use `np.{}` here.") + + _int_extended_msg = ( + "When replacing `np.{}`, you may wish to use e.g. `np.int64` " + "or `np.int32` to specify the precision. If you wish to review " + "your current use, check the release note link for " + "additional information.") + + _type_info = [ + ("object", ""), # The NumPy scalar only exists by name. + ("bool", _specific_msg.format("bool_")), + ("float", _specific_msg.format("float64")), + ("complex", _specific_msg.format("complex128")), + ("str", _specific_msg.format("str_")), + ("int", _int_extended_msg.format("int"))] + + __former_attrs__ = { + n: _msg.format(n=n, extended_msg=extended_msg) + for n, extended_msg in _type_info + } + + # Future warning introduced in NumPy 1.24.0, 2022-11-17 + _msg = ( + "`np.{n}` is a deprecated alias for `{an}`. (Deprecated NumPy 1.24)") + + # Some of these are awkward (since `np.str` may be preferable in the long + # term), but overall the names ending in 0 seem undesirable + _type_info = [ + ("bool8", bool_, "np.bool_"), + ("int0", intp, "np.intp"), + ("uint0", uintp, "np.uintp"), + ("str0", str_, "np.str_"), + ("bytes0", bytes_, "np.bytes_"), + ("void0", void, "np.void"), + ("object0", object_, + "`np.object0` is a deprecated alias for `np.object_`. " + "`object` can be used instead. (Deprecated NumPy 1.24)")] + + # Some of these could be defined right away, but most were aliases to + # the Python objects and only removed in NumPy 1.24. Defining them should + # probably wait for NumPy 1.26 or 2.0. + # When defined, these should possibly not be added to `__all__` to avoid + # import with `from numpy import *`. + __future_scalars__ = {"bool", "long", "ulong", "str", "bytes", "object"} + + __deprecated_attrs__.update({ + n: (alias, _msg.format(n=n, an=an)) for n, alias, an in _type_info}) + + import math + + __deprecated_attrs__['math'] = (math, + "`np.math` is a deprecated alias for the standard library `math` " + "module (Deprecated Numpy 1.25). Replace usages of `np.math` with " + "`math`") + + del math, _msg, _type_info + + from .core import abs + # now that numpy modules are imported, can initialize limits + core.getlimits._register_known_types() + + __all__.extend(['__version__', 'show_config']) + __all__.extend(core.__all__) + __all__.extend(_mat.__all__) + __all__.extend(lib.__all__) + __all__.extend(['linalg', 'fft', 'random', 'ctypeslib', 'ma']) + + # Remove min and max from __all__ to avoid `from numpy import *` override + # the builtins min/max. Temporary fix for 1.25.x/1.26.x, see gh-24229. + __all__.remove('min') + __all__.remove('max') + __all__.remove('round') + + # Remove one of the two occurrences of `issubdtype`, which is exposed as + # both `numpy.core.issubdtype` and `numpy.lib.issubdtype`. + __all__.remove('issubdtype') + + # These are exported by np.core, but are replaced by the builtins below + # remove them to ensure that we don't end up with `np.long == np.int_`, + # which would be a breaking change. + del long, unicode + __all__.remove('long') + __all__.remove('unicode') + + # Remove things that are in the numpy.lib but not in the numpy namespace + # Note that there is a test (numpy/tests/test_public_api.py:test_numpy_namespace) + # that prevents adding more things to the main namespace by accident. + # The list below will grow until the `from .lib import *` fixme above is + # taken care of + __all__.remove('Arrayterator') + del Arrayterator + + # These names were removed in NumPy 1.20. For at least one release, + # attempts to access these names in the numpy namespace will trigger + # a warning, and calling the function will raise an exception. + _financial_names = ['fv', 'ipmt', 'irr', 'mirr', 'nper', 'npv', 'pmt', + 'ppmt', 'pv', 'rate'] + __expired_functions__ = { + name: (f'In accordance with NEP 32, the function {name} was removed ' + 'from NumPy version 1.20. A replacement for this function ' + 'is available in the numpy_financial library: ' + 'https://pypi.org/project/numpy-financial') + for name in _financial_names} + + # Filter out Cython harmless warnings + warnings.filterwarnings("ignore", message="numpy.dtype size changed") + warnings.filterwarnings("ignore", message="numpy.ufunc size changed") + warnings.filterwarnings("ignore", message="numpy.ndarray size changed") + + # oldnumeric and numarray were removed in 1.9. In case some packages import + # but do not use them, we define them here for backward compatibility. + oldnumeric = 'removed' + numarray = 'removed' + + def __getattr__(attr): + # Warn for expired attributes, and return a dummy function + # that always raises an exception. + import warnings + import math + try: + msg = __expired_functions__[attr] + except KeyError: + pass + else: + warnings.warn(msg, DeprecationWarning, stacklevel=2) + + def _expired(*args, **kwds): + raise RuntimeError(msg) + + return _expired + + # Emit warnings for deprecated attributes + try: + val, msg = __deprecated_attrs__[attr] + except KeyError: + pass + else: + warnings.warn(msg, DeprecationWarning, stacklevel=2) + return val + + if attr in __future_scalars__: + # And future warnings for those that will change, but also give + # the AttributeError + warnings.warn( + f"In the future `np.{attr}` will be defined as the " + "corresponding NumPy scalar.", FutureWarning, stacklevel=2) + + if attr in __former_attrs__: + raise AttributeError(__former_attrs__[attr]) + + if attr == 'testing': + import numpy.testing as testing + return testing + elif attr == 'Tester': + "Removed in NumPy 1.25.0" + raise RuntimeError("Tester was removed in NumPy 1.25.") + + raise AttributeError("module {!r} has no attribute " + "{!r}".format(__name__, attr)) + + def __dir__(): + public_symbols = globals().keys() | {'testing'} + public_symbols -= { + "core", "matrixlib", + # These were moved in 1.25 and may be deprecated eventually: + "ModuleDeprecationWarning", "VisibleDeprecationWarning", + "ComplexWarning", "TooHardError", "AxisError" + } + return list(public_symbols) + + # Pytest testing + from numpy._pytesttester import PytestTester + test = PytestTester(__name__) + del PytestTester + + def _sanity_check(): + """ + Quick sanity checks for common bugs caused by environment. + There are some cases e.g. with wrong BLAS ABI that cause wrong + results under specific runtime conditions that are not necessarily + achieved during test suite runs, and it is useful to catch those early. + + See https://github.com/numpy/numpy/issues/8577 and other + similar bug reports. + + """ + try: + x = ones(2, dtype=float32) + if not abs(x.dot(x) - float32(2.0)) < 1e-5: + raise AssertionError() + except AssertionError: + msg = ("The current Numpy installation ({!r}) fails to " + "pass simple sanity checks. This can be caused for example " + "by incorrect BLAS library being linked in, or by mixing " + "package managers (pip, conda, apt, ...). Search closed " + "numpy issues for similar problems.") + raise RuntimeError(msg.format(__file__)) from None + + _sanity_check() + del _sanity_check + + def _mac_os_check(): + """ + Quick Sanity check for Mac OS look for accelerate build bugs. + Testing numpy polyfit calls init_dgelsd(LAPACK) + """ + try: + c = array([3., 2., 1.]) + x = linspace(0, 2, 5) + y = polyval(c, x) + _ = polyfit(x, y, 2, cov=True) + except ValueError: + pass + + if sys.platform == "darwin": + from . import exceptions + with warnings.catch_warnings(record=True) as w: + _mac_os_check() + # Throw runtime error, if the test failed Check for warning and error_message + if len(w) > 0: + for _wn in w: + if _wn.category is exceptions.RankWarning: + # Ignore other warnings, they may not be relevant (see gh-25433). + error_message = f"{_wn.category.__name__}: {str(_wn.message)}" + msg = ( + "Polyfit sanity test emitted a warning, most likely due " + "to using a buggy Accelerate backend." + "\nIf you compiled yourself, more information is available at:" + "\nhttps://numpy.org/devdocs/building/index.html" + "\nOtherwise report this to the vendor " + "that provided NumPy.\n\n{}\n".format(error_message)) + raise RuntimeError(msg) + del _wn + del w + del _mac_os_check + + # We usually use madvise hugepages support, but on some old kernels it + # is slow and thus better avoided. + # Specifically kernel version 4.6 had a bug fix which probably fixed this: + # https://github.com/torvalds/linux/commit/7cf91a98e607c2f935dbcc177d70011e95b8faff + import os + use_hugepage = os.environ.get("NUMPY_MADVISE_HUGEPAGE", None) + if sys.platform == "linux" and use_hugepage is None: + # If there is an issue with parsing the kernel version, + # set use_hugepages to 0. Usage of LooseVersion will handle + # the kernel version parsing better, but avoided since it + # will increase the import time. See: #16679 for related discussion. + try: + use_hugepage = 1 + kernel_version = os.uname().release.split(".")[:2] + kernel_version = tuple(int(v) for v in kernel_version) + if kernel_version < (4, 6): + use_hugepage = 0 + except ValueError: + use_hugepages = 0 + elif use_hugepage is None: + # This is not Linux, so it should not matter, just enable anyway + use_hugepage = 1 + else: + use_hugepage = int(use_hugepage) + + # Note that this will currently only make a difference on Linux + core.multiarray._set_madvise_hugepage(use_hugepage) + del use_hugepage + + # Give a warning if NumPy is reloaded or imported on a sub-interpreter + # We do this from python, since the C-module may not be reloaded and + # it is tidier organized. + core.multiarray._multiarray_umath._reload_guard() + + # default to "weak" promotion for "NumPy 2". + core._set_promotion_state( + os.environ.get("NPY_PROMOTION_STATE", + "weak" if _using_numpy2_behavior() else "legacy")) + + # Tell PyInstaller where to find hook-numpy.py + def _pyinstaller_hooks_dir(): + from pathlib import Path + return [str(Path(__file__).with_name("_pyinstaller").resolve())] + + # Remove symbols imported for internal use + del os + + +# Remove symbols imported for internal use +del sys, warnings diff --git a/numpy/__init__.pyi b/numpy/__init__.pyi new file mode 100644 index 0000000000000000000000000000000000000000..a185bfe754e3d6ba5004f8cca06177e60a7aa13c --- /dev/null +++ b/numpy/__init__.pyi @@ -0,0 +1,4422 @@ +import builtins +import sys +import os +import mmap +import ctypes as ct +import array as _array +import datetime as dt +import enum +from abc import abstractmethod +from types import TracebackType, MappingProxyType, GenericAlias +from contextlib import ContextDecorator +from contextlib import contextmanager + +from numpy._pytesttester import PytestTester +from numpy.core._internal import _ctypes + +from numpy._typing import ( + # Arrays + ArrayLike, + NDArray, + _SupportsArray, + _NestedSequence, + _FiniteNestedSequence, + _SupportsArray, + _ArrayLikeBool_co, + _ArrayLikeUInt_co, + _ArrayLikeInt_co, + _ArrayLikeFloat_co, + _ArrayLikeComplex_co, + _ArrayLikeNumber_co, + _ArrayLikeTD64_co, + _ArrayLikeDT64_co, + _ArrayLikeObject_co, + _ArrayLikeStr_co, + _ArrayLikeBytes_co, + _ArrayLikeUnknown, + _UnknownType, + + # DTypes + DTypeLike, + _DTypeLike, + _DTypeLikeVoid, + _SupportsDType, + _VoidDTypeLike, + + # Shapes + _Shape, + _ShapeLike, + + # Scalars + _CharLike_co, + _BoolLike_co, + _IntLike_co, + _FloatLike_co, + _ComplexLike_co, + _TD64Like_co, + _NumberLike_co, + _ScalarLike_co, + + # `number` precision + NBitBase, + _256Bit, + _128Bit, + _96Bit, + _80Bit, + _64Bit, + _32Bit, + _16Bit, + _8Bit, + _NBitByte, + _NBitShort, + _NBitIntC, + _NBitIntP, + _NBitInt, + _NBitLongLong, + _NBitHalf, + _NBitSingle, + _NBitDouble, + _NBitLongDouble, + + # Character codes + _BoolCodes, + _UInt8Codes, + _UInt16Codes, + _UInt32Codes, + _UInt64Codes, + _Int8Codes, + _Int16Codes, + _Int32Codes, + _Int64Codes, + _Float16Codes, + _Float32Codes, + _Float64Codes, + _Complex64Codes, + _Complex128Codes, + _ByteCodes, + _ShortCodes, + _IntCCodes, + _IntPCodes, + _IntCodes, + _LongLongCodes, + _UByteCodes, + _UShortCodes, + _UIntCCodes, + _UIntPCodes, + _UIntCodes, + _ULongLongCodes, + _HalfCodes, + _SingleCodes, + _DoubleCodes, + _LongDoubleCodes, + _CSingleCodes, + _CDoubleCodes, + _CLongDoubleCodes, + _DT64Codes, + _TD64Codes, + _StrCodes, + _BytesCodes, + _VoidCodes, + _ObjectCodes, + + # Ufuncs + _UFunc_Nin1_Nout1, + _UFunc_Nin2_Nout1, + _UFunc_Nin1_Nout2, + _UFunc_Nin2_Nout2, + _GUFunc_Nin2_Nout1, +) + +from numpy._typing._callable import ( + _BoolOp, + _BoolBitOp, + _BoolSub, + _BoolTrueDiv, + _BoolMod, + _BoolDivMod, + _TD64Div, + _IntTrueDiv, + _UnsignedIntOp, + _UnsignedIntBitOp, + _UnsignedIntMod, + _UnsignedIntDivMod, + _SignedIntOp, + _SignedIntBitOp, + _SignedIntMod, + _SignedIntDivMod, + _FloatOp, + _FloatMod, + _FloatDivMod, + _ComplexOp, + _NumberOp, + _ComparisonOp, +) + +# NOTE: Numpy's mypy plugin is used for removing the types unavailable +# to the specific platform +from numpy._typing._extended_precision import ( + uint128 as uint128, + uint256 as uint256, + int128 as int128, + int256 as int256, + float80 as float80, + float96 as float96, + float128 as float128, + float256 as float256, + complex160 as complex160, + complex192 as complex192, + complex256 as complex256, + complex512 as complex512, +) + +from collections.abc import ( + Callable, + Container, + Iterable, + Iterator, + Mapping, + Sequence, + Sized, +) +from typing import ( + Literal as L, + Any, + Generator, + Generic, + IO, + NoReturn, + overload, + SupportsComplex, + SupportsFloat, + SupportsInt, + TypeVar, + Union, + Protocol, + SupportsIndex, + Final, + final, + ClassVar, +) + +# Ensures that the stubs are picked up +from numpy import ( + ctypeslib as ctypeslib, + exceptions as exceptions, + fft as fft, + lib as lib, + linalg as linalg, + ma as ma, + polynomial as polynomial, + random as random, + testing as testing, + version as version, + exceptions as exceptions, + dtypes as dtypes, +) + +from numpy.core import defchararray, records +char = defchararray +rec = records + +from numpy.core.function_base import ( + linspace as linspace, + logspace as logspace, + geomspace as geomspace, +) + +from numpy.core.fromnumeric import ( + take as take, + reshape as reshape, + choose as choose, + repeat as repeat, + put as put, + swapaxes as swapaxes, + transpose as transpose, + partition as partition, + argpartition as argpartition, + sort as sort, + argsort as argsort, + argmax as argmax, + argmin as argmin, + searchsorted as searchsorted, + resize as resize, + squeeze as squeeze, + diagonal as diagonal, + trace as trace, + ravel as ravel, + nonzero as nonzero, + shape as shape, + compress as compress, + clip as clip, + sum as sum, + all as all, + any as any, + cumsum as cumsum, + ptp as ptp, + max as max, + min as min, + amax as amax, + amin as amin, + prod as prod, + cumprod as cumprod, + ndim as ndim, + size as size, + around as around, + round as round, + mean as mean, + std as std, + var as var, +) + +from numpy.core._asarray import ( + require as require, +) + +from numpy.core._type_aliases import ( + sctypes as sctypes, + sctypeDict as sctypeDict, +) + +from numpy.core._ufunc_config import ( + seterr as seterr, + geterr as geterr, + setbufsize as setbufsize, + getbufsize as getbufsize, + seterrcall as seterrcall, + geterrcall as geterrcall, + _ErrKind, + _ErrFunc, + _ErrDictOptional, +) + +from numpy.core.arrayprint import ( + set_printoptions as set_printoptions, + get_printoptions as get_printoptions, + array2string as array2string, + format_float_scientific as format_float_scientific, + format_float_positional as format_float_positional, + array_repr as array_repr, + array_str as array_str, + set_string_function as set_string_function, + printoptions as printoptions, +) + +from numpy.core.einsumfunc import ( + einsum as einsum, + einsum_path as einsum_path, +) + +from numpy.core.multiarray import ( + ALLOW_THREADS as ALLOW_THREADS, + BUFSIZE as BUFSIZE, + CLIP as CLIP, + MAXDIMS as MAXDIMS, + MAY_SHARE_BOUNDS as MAY_SHARE_BOUNDS, + MAY_SHARE_EXACT as MAY_SHARE_EXACT, + RAISE as RAISE, + WRAP as WRAP, + tracemalloc_domain as tracemalloc_domain, + array as array, + empty_like as empty_like, + empty as empty, + zeros as zeros, + concatenate as concatenate, + inner as inner, + where as where, + lexsort as lexsort, + can_cast as can_cast, + min_scalar_type as min_scalar_type, + result_type as result_type, + dot as dot, + vdot as vdot, + bincount as bincount, + copyto as copyto, + putmask as putmask, + packbits as packbits, + unpackbits as unpackbits, + shares_memory as shares_memory, + may_share_memory as may_share_memory, + asarray as asarray, + asanyarray as asanyarray, + ascontiguousarray as ascontiguousarray, + asfortranarray as asfortranarray, + arange as arange, + busday_count as busday_count, + busday_offset as busday_offset, + compare_chararrays as compare_chararrays, + datetime_as_string as datetime_as_string, + datetime_data as datetime_data, + frombuffer as frombuffer, + fromfile as fromfile, + fromiter as fromiter, + is_busday as is_busday, + promote_types as promote_types, + seterrobj as seterrobj, + geterrobj as geterrobj, + fromstring as fromstring, + frompyfunc as frompyfunc, + nested_iters as nested_iters, + flagsobj, +) + +from numpy.core.numeric import ( + zeros_like as zeros_like, + ones as ones, + ones_like as ones_like, + full as full, + full_like as full_like, + count_nonzero as count_nonzero, + isfortran as isfortran, + argwhere as argwhere, + flatnonzero as flatnonzero, + correlate as correlate, + convolve as convolve, + outer as outer, + tensordot as tensordot, + roll as roll, + rollaxis as rollaxis, + moveaxis as moveaxis, + cross as cross, + indices as indices, + fromfunction as fromfunction, + isscalar as isscalar, + binary_repr as binary_repr, + base_repr as base_repr, + identity as identity, + allclose as allclose, + isclose as isclose, + array_equal as array_equal, + array_equiv as array_equiv, +) + +from numpy.core.numerictypes import ( + maximum_sctype as maximum_sctype, + issctype as issctype, + obj2sctype as obj2sctype, + issubclass_ as issubclass_, + issubsctype as issubsctype, + issubdtype as issubdtype, + sctype2char as sctype2char, + nbytes as nbytes, + cast as cast, + ScalarType as ScalarType, + typecodes as typecodes, +) + +from numpy.core.shape_base import ( + atleast_1d as atleast_1d, + atleast_2d as atleast_2d, + atleast_3d as atleast_3d, + block as block, + hstack as hstack, + stack as stack, + vstack as vstack, +) + +from numpy.exceptions import ( + ComplexWarning as ComplexWarning, + ModuleDeprecationWarning as ModuleDeprecationWarning, + VisibleDeprecationWarning as VisibleDeprecationWarning, + TooHardError as TooHardError, + DTypePromotionError as DTypePromotionError, + AxisError as AxisError, +) + +from numpy.lib import ( + emath as emath, +) + +from numpy.lib.arraypad import ( + pad as pad, +) + +from numpy.lib.arraysetops import ( + ediff1d as ediff1d, + intersect1d as intersect1d, + setxor1d as setxor1d, + union1d as union1d, + setdiff1d as setdiff1d, + unique as unique, + in1d as in1d, + isin as isin, +) + +from numpy.lib.arrayterator import ( + Arrayterator as Arrayterator, +) + +from numpy.lib.function_base import ( + select as select, + piecewise as piecewise, + trim_zeros as trim_zeros, + copy as copy, + iterable as iterable, + percentile as percentile, + diff as diff, + gradient as gradient, + angle as angle, + unwrap as unwrap, + sort_complex as sort_complex, + disp as disp, + flip as flip, + rot90 as rot90, + extract as extract, + place as place, + asarray_chkfinite as asarray_chkfinite, + average as average, + bincount as bincount, + digitize as digitize, + cov as cov, + corrcoef as corrcoef, + median as median, + sinc as sinc, + hamming as hamming, + hanning as hanning, + bartlett as bartlett, + blackman as blackman, + kaiser as kaiser, + trapz as trapz, + i0 as i0, + add_newdoc as add_newdoc, + add_docstring as add_docstring, + meshgrid as meshgrid, + delete as delete, + insert as insert, + append as append, + interp as interp, + add_newdoc_ufunc as add_newdoc_ufunc, + quantile as quantile, +) + +from numpy.lib.histograms import ( + histogram_bin_edges as histogram_bin_edges, + histogram as histogram, + histogramdd as histogramdd, +) + +from numpy.lib.index_tricks import ( + ravel_multi_index as ravel_multi_index, + unravel_index as unravel_index, + mgrid as mgrid, + ogrid as ogrid, + r_ as r_, + c_ as c_, + s_ as s_, + index_exp as index_exp, + ix_ as ix_, + fill_diagonal as fill_diagonal, + diag_indices as diag_indices, + diag_indices_from as diag_indices_from, +) + +from numpy.lib.nanfunctions import ( + nansum as nansum, + nanmax as nanmax, + nanmin as nanmin, + nanargmax as nanargmax, + nanargmin as nanargmin, + nanmean as nanmean, + nanmedian as nanmedian, + nanpercentile as nanpercentile, + nanvar as nanvar, + nanstd as nanstd, + nanprod as nanprod, + nancumsum as nancumsum, + nancumprod as nancumprod, + nanquantile as nanquantile, +) + +from numpy.lib.npyio import ( + savetxt as savetxt, + loadtxt as loadtxt, + genfromtxt as genfromtxt, + recfromtxt as recfromtxt, + recfromcsv as recfromcsv, + load as load, + save as save, + savez as savez, + savez_compressed as savez_compressed, + packbits as packbits, + unpackbits as unpackbits, + fromregex as fromregex, +) + +from numpy.lib.polynomial import ( + poly as poly, + roots as roots, + polyint as polyint, + polyder as polyder, + polyadd as polyadd, + polysub as polysub, + polymul as polymul, + polydiv as polydiv, + polyval as polyval, + polyfit as polyfit, +) + +from numpy.lib.shape_base import ( + column_stack as column_stack, + row_stack as row_stack, + dstack as dstack, + array_split as array_split, + split as split, + hsplit as hsplit, + vsplit as vsplit, + dsplit as dsplit, + apply_over_axes as apply_over_axes, + expand_dims as expand_dims, + apply_along_axis as apply_along_axis, + kron as kron, + tile as tile, + get_array_wrap as get_array_wrap, + take_along_axis as take_along_axis, + put_along_axis as put_along_axis, +) + +from numpy.lib.stride_tricks import ( + broadcast_to as broadcast_to, + broadcast_arrays as broadcast_arrays, + broadcast_shapes as broadcast_shapes, +) + +from numpy.lib.twodim_base import ( + diag as diag, + diagflat as diagflat, + eye as eye, + fliplr as fliplr, + flipud as flipud, + tri as tri, + triu as triu, + tril as tril, + vander as vander, + histogram2d as histogram2d, + mask_indices as mask_indices, + tril_indices as tril_indices, + tril_indices_from as tril_indices_from, + triu_indices as triu_indices, + triu_indices_from as triu_indices_from, +) + +from numpy.lib.type_check import ( + mintypecode as mintypecode, + asfarray as asfarray, + real as real, + imag as imag, + iscomplex as iscomplex, + isreal as isreal, + iscomplexobj as iscomplexobj, + isrealobj as isrealobj, + nan_to_num as nan_to_num, + real_if_close as real_if_close, + typename as typename, + common_type as common_type, +) + +from numpy.lib.ufunclike import ( + fix as fix, + isposinf as isposinf, + isneginf as isneginf, +) + +from numpy.lib.utils import ( + issubclass_ as issubclass_, + issubsctype as issubsctype, + issubdtype as issubdtype, + deprecate as deprecate, + deprecate_with_doc as deprecate_with_doc, + get_include as get_include, + info as info, + source as source, + who as who, + lookfor as lookfor, + byte_bounds as byte_bounds, + safe_eval as safe_eval, + show_runtime as show_runtime, +) + +from numpy.matrixlib import ( + asmatrix as asmatrix, + mat as mat, + bmat as bmat, +) + +_AnyStr_contra = TypeVar("_AnyStr_contra", str, bytes, contravariant=True) + +# Protocol for representing file-like-objects accepted +# by `ndarray.tofile` and `fromfile` +class _IOProtocol(Protocol): + def flush(self) -> object: ... + def fileno(self) -> int: ... + def tell(self) -> SupportsIndex: ... + def seek(self, offset: int, whence: int, /) -> object: ... + +# NOTE: `seek`, `write` and `flush` are technically only required +# for `readwrite`/`write` modes +class _MemMapIOProtocol(Protocol): + def flush(self) -> object: ... + def fileno(self) -> SupportsIndex: ... + def tell(self) -> int: ... + def seek(self, offset: int, whence: int, /) -> object: ... + def write(self, s: bytes, /) -> object: ... + @property + def read(self) -> object: ... + +class _SupportsWrite(Protocol[_AnyStr_contra]): + def write(self, s: _AnyStr_contra, /) -> object: ... + +__all__: list[str] +__path__: list[str] +__version__: str +test: PytestTester + +# TODO: Move placeholders to their respective module once +# their annotations are properly implemented +# +# Placeholders for classes + +def show_config() -> None: ... + +_NdArraySubClass = TypeVar("_NdArraySubClass", bound=ndarray[Any, Any]) +_DTypeScalar_co = TypeVar("_DTypeScalar_co", covariant=True, bound=generic) +_ByteOrder = L["S", "<", ">", "=", "|", "L", "B", "N", "I"] + +@final +class dtype(Generic[_DTypeScalar_co]): + names: None | tuple[builtins.str, ...] + def __hash__(self) -> int: ... + # Overload for subclass of generic + @overload + def __new__( + cls, + dtype: type[_DTypeScalar_co], + align: bool = ..., + copy: bool = ..., + metadata: dict[builtins.str, Any] = ..., + ) -> dtype[_DTypeScalar_co]: ... + # Overloads for string aliases, Python types, and some assorted + # other special cases. Order is sometimes important because of the + # subtype relationships + # + # bool < int < float < complex < object + # + # so we have to make sure the overloads for the narrowest type is + # first. + # Builtin types + @overload + def __new__(cls, dtype: type[bool], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[bool_]: ... + @overload + def __new__(cls, dtype: type[int], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[int_]: ... + @overload + def __new__(cls, dtype: None | type[float], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[float_]: ... + @overload + def __new__(cls, dtype: type[complex], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[complex_]: ... + @overload + def __new__(cls, dtype: type[builtins.str], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[str_]: ... + @overload + def __new__(cls, dtype: type[bytes], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[bytes_]: ... + + # `unsignedinteger` string-based representations and ctypes + @overload + def __new__(cls, dtype: _UInt8Codes | type[ct.c_uint8], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[uint8]: ... + @overload + def __new__(cls, dtype: _UInt16Codes | type[ct.c_uint16], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[uint16]: ... + @overload + def __new__(cls, dtype: _UInt32Codes | type[ct.c_uint32], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[uint32]: ... + @overload + def __new__(cls, dtype: _UInt64Codes | type[ct.c_uint64], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[uint64]: ... + @overload + def __new__(cls, dtype: _UByteCodes | type[ct.c_ubyte], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[ubyte]: ... + @overload + def __new__(cls, dtype: _UShortCodes | type[ct.c_ushort], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[ushort]: ... + @overload + def __new__(cls, dtype: _UIntCCodes | type[ct.c_uint], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[uintc]: ... + + # NOTE: We're assuming here that `uint_ptr_t == size_t`, + # an assumption that does not hold in rare cases (same for `ssize_t`) + @overload + def __new__(cls, dtype: _UIntPCodes | type[ct.c_void_p] | type[ct.c_size_t], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[uintp]: ... + @overload + def __new__(cls, dtype: _UIntCodes | type[ct.c_ulong], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[uint]: ... + @overload + def __new__(cls, dtype: _ULongLongCodes | type[ct.c_ulonglong], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[ulonglong]: ... + + # `signedinteger` string-based representations and ctypes + @overload + def __new__(cls, dtype: _Int8Codes | type[ct.c_int8], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[int8]: ... + @overload + def __new__(cls, dtype: _Int16Codes | type[ct.c_int16], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[int16]: ... + @overload + def __new__(cls, dtype: _Int32Codes | type[ct.c_int32], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[int32]: ... + @overload + def __new__(cls, dtype: _Int64Codes | type[ct.c_int64], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[int64]: ... + @overload + def __new__(cls, dtype: _ByteCodes | type[ct.c_byte], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[byte]: ... + @overload + def __new__(cls, dtype: _ShortCodes | type[ct.c_short], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[short]: ... + @overload + def __new__(cls, dtype: _IntCCodes | type[ct.c_int], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[intc]: ... + @overload + def __new__(cls, dtype: _IntPCodes | type[ct.c_ssize_t], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[intp]: ... + @overload + def __new__(cls, dtype: _IntCodes | type[ct.c_long], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[int_]: ... + @overload + def __new__(cls, dtype: _LongLongCodes | type[ct.c_longlong], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[longlong]: ... + + # `floating` string-based representations and ctypes + @overload + def __new__(cls, dtype: _Float16Codes, align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[float16]: ... + @overload + def __new__(cls, dtype: _Float32Codes, align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[float32]: ... + @overload + def __new__(cls, dtype: _Float64Codes, align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[float64]: ... + @overload + def __new__(cls, dtype: _HalfCodes, align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[half]: ... + @overload + def __new__(cls, dtype: _SingleCodes | type[ct.c_float], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[single]: ... + @overload + def __new__(cls, dtype: _DoubleCodes | type[ct.c_double], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[double]: ... + @overload + def __new__(cls, dtype: _LongDoubleCodes | type[ct.c_longdouble], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[longdouble]: ... + + # `complexfloating` string-based representations + @overload + def __new__(cls, dtype: _Complex64Codes, align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[complex64]: ... + @overload + def __new__(cls, dtype: _Complex128Codes, align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[complex128]: ... + @overload + def __new__(cls, dtype: _CSingleCodes, align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[csingle]: ... + @overload + def __new__(cls, dtype: _CDoubleCodes, align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[cdouble]: ... + @overload + def __new__(cls, dtype: _CLongDoubleCodes, align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[clongdouble]: ... + + # Miscellaneous string-based representations and ctypes + @overload + def __new__(cls, dtype: _BoolCodes | type[ct.c_bool], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[bool_]: ... + @overload + def __new__(cls, dtype: _TD64Codes, align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[timedelta64]: ... + @overload + def __new__(cls, dtype: _DT64Codes, align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[datetime64]: ... + @overload + def __new__(cls, dtype: _StrCodes, align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[str_]: ... + @overload + def __new__(cls, dtype: _BytesCodes | type[ct.c_char], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[bytes_]: ... + @overload + def __new__(cls, dtype: _VoidCodes, align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[void]: ... + @overload + def __new__(cls, dtype: _ObjectCodes | type[ct.py_object[Any]], align: bool = ..., copy: bool = ..., metadata: dict[builtins.str, Any] = ...) -> dtype[object_]: ... + + # dtype of a dtype is the same dtype + @overload + def __new__( + cls, + dtype: dtype[_DTypeScalar_co], + align: bool = ..., + copy: bool = ..., + metadata: dict[builtins.str, Any] = ..., + ) -> dtype[_DTypeScalar_co]: ... + @overload + def __new__( + cls, + dtype: _SupportsDType[dtype[_DTypeScalar_co]], + align: bool = ..., + copy: bool = ..., + metadata: dict[builtins.str, Any] = ..., + ) -> dtype[_DTypeScalar_co]: ... + # Handle strings that can't be expressed as literals; i.e. s1, s2, ... + @overload + def __new__( + cls, + dtype: builtins.str, + align: bool = ..., + copy: bool = ..., + metadata: dict[builtins.str, Any] = ..., + ) -> dtype[Any]: ... + # Catchall overload for void-likes + @overload + def __new__( + cls, + dtype: _VoidDTypeLike, + align: bool = ..., + copy: bool = ..., + metadata: dict[builtins.str, Any] = ..., + ) -> dtype[void]: ... + # Catchall overload for object-likes + @overload + def __new__( + cls, + dtype: type[object], + align: bool = ..., + copy: bool = ..., + metadata: dict[builtins.str, Any] = ..., + ) -> dtype[object_]: ... + + def __class_getitem__(self, item: Any) -> GenericAlias: ... + + @overload + def __getitem__(self: dtype[void], key: list[builtins.str]) -> dtype[void]: ... + @overload + def __getitem__(self: dtype[void], key: builtins.str | SupportsIndex) -> dtype[Any]: ... + + # NOTE: In the future 1-based multiplications will also yield `flexible` dtypes + @overload + def __mul__(self: _DType, value: L[1]) -> _DType: ... + @overload + def __mul__(self: _FlexDType, value: SupportsIndex) -> _FlexDType: ... + @overload + def __mul__(self, value: SupportsIndex) -> dtype[void]: ... + + # NOTE: `__rmul__` seems to be broken when used in combination with + # literals as of mypy 0.902. Set the return-type to `dtype[Any]` for + # now for non-flexible dtypes. + @overload + def __rmul__(self: _FlexDType, value: SupportsIndex) -> _FlexDType: ... + @overload + def __rmul__(self, value: SupportsIndex) -> dtype[Any]: ... + + def __gt__(self, other: DTypeLike) -> bool: ... + def __ge__(self, other: DTypeLike) -> bool: ... + def __lt__(self, other: DTypeLike) -> bool: ... + def __le__(self, other: DTypeLike) -> bool: ... + + # Explicitly defined `__eq__` and `__ne__` to get around mypy's + # `strict_equality` option; even though their signatures are + # identical to their `object`-based counterpart + def __eq__(self, other: Any) -> bool: ... + def __ne__(self, other: Any) -> bool: ... + + @property + def alignment(self) -> int: ... + @property + def base(self) -> dtype[Any]: ... + @property + def byteorder(self) -> builtins.str: ... + @property + def char(self) -> builtins.str: ... + @property + def descr(self) -> list[tuple[builtins.str, builtins.str] | tuple[builtins.str, builtins.str, _Shape]]: ... + @property + def fields( + self, + ) -> None | MappingProxyType[builtins.str, tuple[dtype[Any], int] | tuple[dtype[Any], int, Any]]: ... + @property + def flags(self) -> int: ... + @property + def hasobject(self) -> bool: ... + @property + def isbuiltin(self) -> int: ... + @property + def isnative(self) -> bool: ... + @property + def isalignedstruct(self) -> bool: ... + @property + def itemsize(self) -> int: ... + @property + def kind(self) -> builtins.str: ... + @property + def metadata(self) -> None | MappingProxyType[builtins.str, Any]: ... + @property + def name(self) -> builtins.str: ... + @property + def num(self) -> int: ... + @property + def shape(self) -> _Shape: ... + @property + def ndim(self) -> int: ... + @property + def subdtype(self) -> None | tuple[dtype[Any], _Shape]: ... + def newbyteorder(self: _DType, __new_order: _ByteOrder = ...) -> _DType: ... + @property + def str(self) -> builtins.str: ... + @property + def type(self) -> type[_DTypeScalar_co]: ... + +_ArrayLikeInt = Union[ + int, + integer[Any], + Sequence[Union[int, integer[Any]]], + Sequence[Sequence[Any]], # TODO: wait for support for recursive types + ndarray[Any, Any] +] + +_FlatIterSelf = TypeVar("_FlatIterSelf", bound=flatiter[Any]) + +@final +class flatiter(Generic[_NdArraySubClass]): + __hash__: ClassVar[None] + @property + def base(self) -> _NdArraySubClass: ... + @property + def coords(self) -> _Shape: ... + @property + def index(self) -> int: ... + def copy(self) -> _NdArraySubClass: ... + def __iter__(self: _FlatIterSelf) -> _FlatIterSelf: ... + def __next__(self: flatiter[ndarray[Any, dtype[_ScalarType]]]) -> _ScalarType: ... + def __len__(self) -> int: ... + @overload + def __getitem__( + self: flatiter[ndarray[Any, dtype[_ScalarType]]], + key: int | integer[Any] | tuple[int | integer[Any]], + ) -> _ScalarType: ... + @overload + def __getitem__( + self, + key: _ArrayLikeInt | slice | ellipsis | tuple[_ArrayLikeInt | slice | ellipsis], + ) -> _NdArraySubClass: ... + # TODO: `__setitem__` operates via `unsafe` casting rules, and can + # thus accept any type accepted by the relevant underlying `np.generic` + # constructor. + # This means that `value` must in reality be a supertype of `npt.ArrayLike`. + def __setitem__( + self, + key: _ArrayLikeInt | slice | ellipsis | tuple[_ArrayLikeInt | slice | ellipsis], + value: Any, + ) -> None: ... + @overload + def __array__(self: flatiter[ndarray[Any, _DType]], dtype: None = ..., /) -> ndarray[Any, _DType]: ... + @overload + def __array__(self, dtype: _DType, /) -> ndarray[Any, _DType]: ... + +_OrderKACF = L[None, "K", "A", "C", "F"] +_OrderACF = L[None, "A", "C", "F"] +_OrderCF = L[None, "C", "F"] + +_ModeKind = L["raise", "wrap", "clip"] +_PartitionKind = L["introselect"] +_SortKind = L["quicksort", "mergesort", "heapsort", "stable"] +_SortSide = L["left", "right"] + +_ArraySelf = TypeVar("_ArraySelf", bound=_ArrayOrScalarCommon) + +class _ArrayOrScalarCommon: + @property + def T(self: _ArraySelf) -> _ArraySelf: ... + @property + def data(self) -> memoryview: ... + @property + def flags(self) -> flagsobj: ... + @property + def itemsize(self) -> int: ... + @property + def nbytes(self) -> int: ... + def __bool__(self) -> bool: ... + def __bytes__(self) -> bytes: ... + def __str__(self) -> str: ... + def __repr__(self) -> str: ... + def __copy__(self: _ArraySelf) -> _ArraySelf: ... + def __deepcopy__(self: _ArraySelf, memo: None | dict[int, Any], /) -> _ArraySelf: ... + + # TODO: How to deal with the non-commutative nature of `==` and `!=`? + # xref numpy/numpy#17368 + def __eq__(self, other: Any) -> Any: ... + def __ne__(self, other: Any) -> Any: ... + def copy(self: _ArraySelf, order: _OrderKACF = ...) -> _ArraySelf: ... + def dump(self, file: str | bytes | os.PathLike[str] | os.PathLike[bytes] | _SupportsWrite[bytes]) -> None: ... + def dumps(self) -> bytes: ... + def tobytes(self, order: _OrderKACF = ...) -> bytes: ... + # NOTE: `tostring()` is deprecated and therefore excluded + # def tostring(self, order=...): ... + def tofile( + self, + fid: str | bytes | os.PathLike[str] | os.PathLike[bytes] | _IOProtocol, + sep: str = ..., + format: str = ..., + ) -> None: ... + # generics and 0d arrays return builtin scalars + def tolist(self) -> Any: ... + + @property + def __array_interface__(self) -> dict[str, Any]: ... + @property + def __array_priority__(self) -> float: ... + @property + def __array_struct__(self) -> Any: ... # builtins.PyCapsule + def __setstate__(self, state: tuple[ + SupportsIndex, # version + _ShapeLike, # Shape + _DType_co, # DType + bool, # F-continuous + bytes | list[Any], # Data + ], /) -> None: ... + # a `bool_` is returned when `keepdims=True` and `self` is a 0d array + + @overload + def all( + self, + axis: None = ..., + out: None = ..., + keepdims: L[False] = ..., + *, + where: _ArrayLikeBool_co = ..., + ) -> bool_: ... + @overload + def all( + self, + axis: None | _ShapeLike = ..., + out: None = ..., + keepdims: bool = ..., + *, + where: _ArrayLikeBool_co = ..., + ) -> Any: ... + @overload + def all( + self, + axis: None | _ShapeLike = ..., + out: _NdArraySubClass = ..., + keepdims: bool = ..., + *, + where: _ArrayLikeBool_co = ..., + ) -> _NdArraySubClass: ... + + @overload + def any( + self, + axis: None = ..., + out: None = ..., + keepdims: L[False] = ..., + *, + where: _ArrayLikeBool_co = ..., + ) -> bool_: ... + @overload + def any( + self, + axis: None | _ShapeLike = ..., + out: None = ..., + keepdims: bool = ..., + *, + where: _ArrayLikeBool_co = ..., + ) -> Any: ... + @overload + def any( + self, + axis: None | _ShapeLike = ..., + out: _NdArraySubClass = ..., + keepdims: bool = ..., + *, + where: _ArrayLikeBool_co = ..., + ) -> _NdArraySubClass: ... + + @overload + def argmax( + self, + axis: None = ..., + out: None = ..., + *, + keepdims: L[False] = ..., + ) -> intp: ... + @overload + def argmax( + self, + axis: SupportsIndex = ..., + out: None = ..., + *, + keepdims: bool = ..., + ) -> Any: ... + @overload + def argmax( + self, + axis: None | SupportsIndex = ..., + out: _NdArraySubClass = ..., + *, + keepdims: bool = ..., + ) -> _NdArraySubClass: ... + + @overload + def argmin( + self, + axis: None = ..., + out: None = ..., + *, + keepdims: L[False] = ..., + ) -> intp: ... + @overload + def argmin( + self, + axis: SupportsIndex = ..., + out: None = ..., + *, + keepdims: bool = ..., + ) -> Any: ... + @overload + def argmin( + self, + axis: None | SupportsIndex = ..., + out: _NdArraySubClass = ..., + *, + keepdims: bool = ..., + ) -> _NdArraySubClass: ... + + def argsort( + self, + axis: None | SupportsIndex = ..., + kind: None | _SortKind = ..., + order: None | str | Sequence[str] = ..., + ) -> ndarray[Any, Any]: ... + + @overload + def choose( + self, + choices: ArrayLike, + out: None = ..., + mode: _ModeKind = ..., + ) -> ndarray[Any, Any]: ... + @overload + def choose( + self, + choices: ArrayLike, + out: _NdArraySubClass = ..., + mode: _ModeKind = ..., + ) -> _NdArraySubClass: ... + + @overload + def clip( + self, + min: ArrayLike = ..., + max: None | ArrayLike = ..., + out: None = ..., + **kwargs: Any, + ) -> ndarray[Any, Any]: ... + @overload + def clip( + self, + min: None = ..., + max: ArrayLike = ..., + out: None = ..., + **kwargs: Any, + ) -> ndarray[Any, Any]: ... + @overload + def clip( + self, + min: ArrayLike = ..., + max: None | ArrayLike = ..., + out: _NdArraySubClass = ..., + **kwargs: Any, + ) -> _NdArraySubClass: ... + @overload + def clip( + self, + min: None = ..., + max: ArrayLike = ..., + out: _NdArraySubClass = ..., + **kwargs: Any, + ) -> _NdArraySubClass: ... + + @overload + def compress( + self, + a: ArrayLike, + axis: None | SupportsIndex = ..., + out: None = ..., + ) -> ndarray[Any, Any]: ... + @overload + def compress( + self, + a: ArrayLike, + axis: None | SupportsIndex = ..., + out: _NdArraySubClass = ..., + ) -> _NdArraySubClass: ... + + def conj(self: _ArraySelf) -> _ArraySelf: ... + + def conjugate(self: _ArraySelf) -> _ArraySelf: ... + + @overload + def cumprod( + self, + axis: None | SupportsIndex = ..., + dtype: DTypeLike = ..., + out: None = ..., + ) -> ndarray[Any, Any]: ... + @overload + def cumprod( + self, + axis: None | SupportsIndex = ..., + dtype: DTypeLike = ..., + out: _NdArraySubClass = ..., + ) -> _NdArraySubClass: ... + + @overload + def cumsum( + self, + axis: None | SupportsIndex = ..., + dtype: DTypeLike = ..., + out: None = ..., + ) -> ndarray[Any, Any]: ... + @overload + def cumsum( + self, + axis: None | SupportsIndex = ..., + dtype: DTypeLike = ..., + out: _NdArraySubClass = ..., + ) -> _NdArraySubClass: ... + + @overload + def max( + self, + axis: None | _ShapeLike = ..., + out: None = ..., + keepdims: bool = ..., + initial: _NumberLike_co = ..., + where: _ArrayLikeBool_co = ..., + ) -> Any: ... + @overload + def max( + self, + axis: None | _ShapeLike = ..., + out: _NdArraySubClass = ..., + keepdims: bool = ..., + initial: _NumberLike_co = ..., + where: _ArrayLikeBool_co = ..., + ) -> _NdArraySubClass: ... + + @overload + def mean( + self, + axis: None | _ShapeLike = ..., + dtype: DTypeLike = ..., + out: None = ..., + keepdims: bool = ..., + *, + where: _ArrayLikeBool_co = ..., + ) -> Any: ... + @overload + def mean( + self, + axis: None | _ShapeLike = ..., + dtype: DTypeLike = ..., + out: _NdArraySubClass = ..., + keepdims: bool = ..., + *, + where: _ArrayLikeBool_co = ..., + ) -> _NdArraySubClass: ... + + @overload + def min( + self, + axis: None | _ShapeLike = ..., + out: None = ..., + keepdims: bool = ..., + initial: _NumberLike_co = ..., + where: _ArrayLikeBool_co = ..., + ) -> Any: ... + @overload + def min( + self, + axis: None | _ShapeLike = ..., + out: _NdArraySubClass = ..., + keepdims: bool = ..., + initial: _NumberLike_co = ..., + where: _ArrayLikeBool_co = ..., + ) -> _NdArraySubClass: ... + + def newbyteorder( + self: _ArraySelf, + __new_order: _ByteOrder = ..., + ) -> _ArraySelf: ... + + @overload + def prod( + self, + axis: None | _ShapeLike = ..., + dtype: DTypeLike = ..., + out: None = ..., + keepdims: bool = ..., + initial: _NumberLike_co = ..., + where: _ArrayLikeBool_co = ..., + ) -> Any: ... + @overload + def prod( + self, + axis: None | _ShapeLike = ..., + dtype: DTypeLike = ..., + out: _NdArraySubClass = ..., + keepdims: bool = ..., + initial: _NumberLike_co = ..., + where: _ArrayLikeBool_co = ..., + ) -> _NdArraySubClass: ... + + @overload + def ptp( + self, + axis: None | _ShapeLike = ..., + out: None = ..., + keepdims: bool = ..., + ) -> Any: ... + @overload + def ptp( + self, + axis: None | _ShapeLike = ..., + out: _NdArraySubClass = ..., + keepdims: bool = ..., + ) -> _NdArraySubClass: ... + + @overload + def round( + self: _ArraySelf, + decimals: SupportsIndex = ..., + out: None = ..., + ) -> _ArraySelf: ... + @overload + def round( + self, + decimals: SupportsIndex = ..., + out: _NdArraySubClass = ..., + ) -> _NdArraySubClass: ... + + @overload + def std( + self, + axis: None | _ShapeLike = ..., + dtype: DTypeLike = ..., + out: None = ..., + ddof: float = ..., + keepdims: bool = ..., + *, + where: _ArrayLikeBool_co = ..., + ) -> Any: ... + @overload + def std( + self, + axis: None | _ShapeLike = ..., + dtype: DTypeLike = ..., + out: _NdArraySubClass = ..., + ddof: float = ..., + keepdims: bool = ..., + *, + where: _ArrayLikeBool_co = ..., + ) -> _NdArraySubClass: ... + + @overload + def sum( + self, + axis: None | _ShapeLike = ..., + dtype: DTypeLike = ..., + out: None = ..., + keepdims: bool = ..., + initial: _NumberLike_co = ..., + where: _ArrayLikeBool_co = ..., + ) -> Any: ... + @overload + def sum( + self, + axis: None | _ShapeLike = ..., + dtype: DTypeLike = ..., + out: _NdArraySubClass = ..., + keepdims: bool = ..., + initial: _NumberLike_co = ..., + where: _ArrayLikeBool_co = ..., + ) -> _NdArraySubClass: ... + + @overload + def var( + self, + axis: None | _ShapeLike = ..., + dtype: DTypeLike = ..., + out: None = ..., + ddof: float = ..., + keepdims: bool = ..., + *, + where: _ArrayLikeBool_co = ..., + ) -> Any: ... + @overload + def var( + self, + axis: None | _ShapeLike = ..., + dtype: DTypeLike = ..., + out: _NdArraySubClass = ..., + ddof: float = ..., + keepdims: bool = ..., + *, + where: _ArrayLikeBool_co = ..., + ) -> _NdArraySubClass: ... + +_DType = TypeVar("_DType", bound=dtype[Any]) +_DType_co = TypeVar("_DType_co", covariant=True, bound=dtype[Any]) +_FlexDType = TypeVar("_FlexDType", bound=dtype[flexible]) + +# TODO: Set the `bound` to something more suitable once we +# have proper shape support +_ShapeType = TypeVar("_ShapeType", bound=Any) +_ShapeType2 = TypeVar("_ShapeType2", bound=Any) +_NumberType = TypeVar("_NumberType", bound=number[Any]) + +if sys.version_info >= (3, 12): + from collections.abc import Buffer as _SupportsBuffer +else: + _SupportsBuffer = ( + bytes + | bytearray + | memoryview + | _array.array[Any] + | mmap.mmap + | NDArray[Any] + | generic + ) + +_T = TypeVar("_T") +_T_co = TypeVar("_T_co", covariant=True) +_T_contra = TypeVar("_T_contra", contravariant=True) +_2Tuple = tuple[_T, _T] +_CastingKind = L["no", "equiv", "safe", "same_kind", "unsafe"] + +_ArrayUInt_co = NDArray[Union[bool_, unsignedinteger[Any]]] +_ArrayInt_co = NDArray[Union[bool_, integer[Any]]] +_ArrayFloat_co = NDArray[Union[bool_, integer[Any], floating[Any]]] +_ArrayComplex_co = NDArray[Union[bool_, integer[Any], floating[Any], complexfloating[Any, Any]]] +_ArrayNumber_co = NDArray[Union[bool_, number[Any]]] +_ArrayTD64_co = NDArray[Union[bool_, integer[Any], timedelta64]] + +# Introduce an alias for `dtype` to avoid naming conflicts. +_dtype = dtype + +# `builtins.PyCapsule` unfortunately lacks annotations as of the moment; +# use `Any` as a stopgap measure +_PyCapsule = Any + +class _SupportsItem(Protocol[_T_co]): + def item(self, args: Any, /) -> _T_co: ... + +class _SupportsReal(Protocol[_T_co]): + @property + def real(self) -> _T_co: ... + +class _SupportsImag(Protocol[_T_co]): + @property + def imag(self) -> _T_co: ... + +class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): + __hash__: ClassVar[None] + @property + def base(self) -> None | ndarray[Any, Any]: ... + @property + def ndim(self) -> int: ... + @property + def size(self) -> int: ... + @property + def real( + self: ndarray[_ShapeType, dtype[_SupportsReal[_ScalarType]]], # type: ignore[type-var] + ) -> ndarray[_ShapeType, _dtype[_ScalarType]]: ... + @real.setter + def real(self, value: ArrayLike) -> None: ... + @property + def imag( + self: ndarray[_ShapeType, dtype[_SupportsImag[_ScalarType]]], # type: ignore[type-var] + ) -> ndarray[_ShapeType, _dtype[_ScalarType]]: ... + @imag.setter + def imag(self, value: ArrayLike) -> None: ... + def __new__( + cls: type[_ArraySelf], + shape: _ShapeLike, + dtype: DTypeLike = ..., + buffer: None | _SupportsBuffer = ..., + offset: SupportsIndex = ..., + strides: None | _ShapeLike = ..., + order: _OrderKACF = ..., + ) -> _ArraySelf: ... + + if sys.version_info >= (3, 12): + def __buffer__(self, flags: int, /) -> memoryview: ... + + def __class_getitem__(self, item: Any) -> GenericAlias: ... + + @overload + def __array__(self, dtype: None = ..., /) -> ndarray[Any, _DType_co]: ... + @overload + def __array__(self, dtype: _DType, /) -> ndarray[Any, _DType]: ... + + def __array_ufunc__( + self, + ufunc: ufunc, + method: L["__call__", "reduce", "reduceat", "accumulate", "outer", "inner"], + *inputs: Any, + **kwargs: Any, + ) -> Any: ... + + def __array_function__( + self, + func: Callable[..., Any], + types: Iterable[type], + args: Iterable[Any], + kwargs: Mapping[str, Any], + ) -> Any: ... + + # NOTE: In practice any object is accepted by `obj`, but as `__array_finalize__` + # is a pseudo-abstract method the type has been narrowed down in order to + # grant subclasses a bit more flexibility + def __array_finalize__(self, obj: None | NDArray[Any], /) -> None: ... + + def __array_wrap__( + self, + array: ndarray[_ShapeType2, _DType], + context: None | tuple[ufunc, tuple[Any, ...], int] = ..., + /, + ) -> ndarray[_ShapeType2, _DType]: ... + + def __array_prepare__( + self, + array: ndarray[_ShapeType2, _DType], + context: None | tuple[ufunc, tuple[Any, ...], int] = ..., + /, + ) -> ndarray[_ShapeType2, _DType]: ... + + @overload + def __getitem__(self, key: ( + NDArray[integer[Any]] + | NDArray[bool_] + | tuple[NDArray[integer[Any]] | NDArray[bool_], ...] + )) -> ndarray[Any, _DType_co]: ... + @overload + def __getitem__(self, key: SupportsIndex | tuple[SupportsIndex, ...]) -> Any: ... + @overload + def __getitem__(self, key: ( + None + | slice + | ellipsis + | SupportsIndex + | _ArrayLikeInt_co + | tuple[None | slice | ellipsis | _ArrayLikeInt_co | SupportsIndex, ...] + )) -> ndarray[Any, _DType_co]: ... + @overload + def __getitem__(self: NDArray[void], key: str) -> NDArray[Any]: ... + @overload + def __getitem__(self: NDArray[void], key: list[str]) -> ndarray[_ShapeType, _dtype[void]]: ... + + @property + def ctypes(self) -> _ctypes[int]: ... + @property + def shape(self) -> _Shape: ... + @shape.setter + def shape(self, value: _ShapeLike) -> None: ... + @property + def strides(self) -> _Shape: ... + @strides.setter + def strides(self, value: _ShapeLike) -> None: ... + def byteswap(self: _ArraySelf, inplace: bool = ...) -> _ArraySelf: ... + def fill(self, value: Any) -> None: ... + @property + def flat(self: _NdArraySubClass) -> flatiter[_NdArraySubClass]: ... + + # Use the same output type as that of the underlying `generic` + @overload + def item( + self: ndarray[Any, _dtype[_SupportsItem[_T]]], # type: ignore[type-var] + *args: SupportsIndex, + ) -> _T: ... + @overload + def item( + self: ndarray[Any, _dtype[_SupportsItem[_T]]], # type: ignore[type-var] + args: tuple[SupportsIndex, ...], + /, + ) -> _T: ... + + @overload + def itemset(self, value: Any, /) -> None: ... + @overload + def itemset(self, item: _ShapeLike, value: Any, /) -> None: ... + + @overload + def resize(self, new_shape: _ShapeLike, /, *, refcheck: bool = ...) -> None: ... + @overload + def resize(self, *new_shape: SupportsIndex, refcheck: bool = ...) -> None: ... + + def setflags( + self, write: bool = ..., align: bool = ..., uic: bool = ... + ) -> None: ... + + def squeeze( + self, + axis: None | SupportsIndex | tuple[SupportsIndex, ...] = ..., + ) -> ndarray[Any, _DType_co]: ... + + def swapaxes( + self, + axis1: SupportsIndex, + axis2: SupportsIndex, + ) -> ndarray[Any, _DType_co]: ... + + @overload + def transpose(self: _ArraySelf, axes: None | _ShapeLike, /) -> _ArraySelf: ... + @overload + def transpose(self: _ArraySelf, *axes: SupportsIndex) -> _ArraySelf: ... + + def argpartition( + self, + kth: _ArrayLikeInt_co, + axis: None | SupportsIndex = ..., + kind: _PartitionKind = ..., + order: None | str | Sequence[str] = ..., + ) -> ndarray[Any, _dtype[intp]]: ... + + def diagonal( + self, + offset: SupportsIndex = ..., + axis1: SupportsIndex = ..., + axis2: SupportsIndex = ..., + ) -> ndarray[Any, _DType_co]: ... + + # 1D + 1D returns a scalar; + # all other with at least 1 non-0D array return an ndarray. + @overload + def dot(self, b: _ScalarLike_co, out: None = ...) -> ndarray[Any, Any]: ... + @overload + def dot(self, b: ArrayLike, out: None = ...) -> Any: ... # type: ignore[misc] + @overload + def dot(self, b: ArrayLike, out: _NdArraySubClass) -> _NdArraySubClass: ... + + # `nonzero()` is deprecated for 0d arrays/generics + def nonzero(self) -> tuple[ndarray[Any, _dtype[intp]], ...]: ... + + def partition( + self, + kth: _ArrayLikeInt_co, + axis: SupportsIndex = ..., + kind: _PartitionKind = ..., + order: None | str | Sequence[str] = ..., + ) -> None: ... + + # `put` is technically available to `generic`, + # but is pointless as `generic`s are immutable + def put( + self, + ind: _ArrayLikeInt_co, + v: ArrayLike, + mode: _ModeKind = ..., + ) -> None: ... + + @overload + def searchsorted( # type: ignore[misc] + self, # >= 1D array + v: _ScalarLike_co, # 0D array-like + side: _SortSide = ..., + sorter: None | _ArrayLikeInt_co = ..., + ) -> intp: ... + @overload + def searchsorted( + self, # >= 1D array + v: ArrayLike, + side: _SortSide = ..., + sorter: None | _ArrayLikeInt_co = ..., + ) -> ndarray[Any, _dtype[intp]]: ... + + def setfield( + self, + val: ArrayLike, + dtype: DTypeLike, + offset: SupportsIndex = ..., + ) -> None: ... + + def sort( + self, + axis: SupportsIndex = ..., + kind: None | _SortKind = ..., + order: None | str | Sequence[str] = ..., + ) -> None: ... + + @overload + def trace( + self, # >= 2D array + offset: SupportsIndex = ..., + axis1: SupportsIndex = ..., + axis2: SupportsIndex = ..., + dtype: DTypeLike = ..., + out: None = ..., + ) -> Any: ... + @overload + def trace( + self, # >= 2D array + offset: SupportsIndex = ..., + axis1: SupportsIndex = ..., + axis2: SupportsIndex = ..., + dtype: DTypeLike = ..., + out: _NdArraySubClass = ..., + ) -> _NdArraySubClass: ... + + @overload + def take( # type: ignore[misc] + self: ndarray[Any, _dtype[_ScalarType]], + indices: _IntLike_co, + axis: None | SupportsIndex = ..., + out: None = ..., + mode: _ModeKind = ..., + ) -> _ScalarType: ... + @overload + def take( # type: ignore[misc] + self, + indices: _ArrayLikeInt_co, + axis: None | SupportsIndex = ..., + out: None = ..., + mode: _ModeKind = ..., + ) -> ndarray[Any, _DType_co]: ... + @overload + def take( + self, + indices: _ArrayLikeInt_co, + axis: None | SupportsIndex = ..., + out: _NdArraySubClass = ..., + mode: _ModeKind = ..., + ) -> _NdArraySubClass: ... + + def repeat( + self, + repeats: _ArrayLikeInt_co, + axis: None | SupportsIndex = ..., + ) -> ndarray[Any, _DType_co]: ... + + def flatten( + self, + order: _OrderKACF = ..., + ) -> ndarray[Any, _DType_co]: ... + + def ravel( + self, + order: _OrderKACF = ..., + ) -> ndarray[Any, _DType_co]: ... + + @overload + def reshape( + self, shape: _ShapeLike, /, *, order: _OrderACF = ... + ) -> ndarray[Any, _DType_co]: ... + @overload + def reshape( + self, *shape: SupportsIndex, order: _OrderACF = ... + ) -> ndarray[Any, _DType_co]: ... + + @overload + def astype( + self, + dtype: _DTypeLike[_ScalarType], + order: _OrderKACF = ..., + casting: _CastingKind = ..., + subok: bool = ..., + copy: bool | _CopyMode = ..., + ) -> NDArray[_ScalarType]: ... + @overload + def astype( + self, + dtype: DTypeLike, + order: _OrderKACF = ..., + casting: _CastingKind = ..., + subok: bool = ..., + copy: bool | _CopyMode = ..., + ) -> NDArray[Any]: ... + + @overload + def view(self: _ArraySelf) -> _ArraySelf: ... + @overload + def view(self, type: type[_NdArraySubClass]) -> _NdArraySubClass: ... + @overload + def view(self, dtype: _DTypeLike[_ScalarType]) -> NDArray[_ScalarType]: ... + @overload + def view(self, dtype: DTypeLike) -> NDArray[Any]: ... + @overload + def view( + self, + dtype: DTypeLike, + type: type[_NdArraySubClass], + ) -> _NdArraySubClass: ... + + @overload + def getfield( + self, + dtype: _DTypeLike[_ScalarType], + offset: SupportsIndex = ... + ) -> NDArray[_ScalarType]: ... + @overload + def getfield( + self, + dtype: DTypeLike, + offset: SupportsIndex = ... + ) -> NDArray[Any]: ... + + # Dispatch to the underlying `generic` via protocols + def __int__( + self: ndarray[Any, _dtype[SupportsInt]], # type: ignore[type-var] + ) -> int: ... + + def __float__( + self: ndarray[Any, _dtype[SupportsFloat]], # type: ignore[type-var] + ) -> float: ... + + def __complex__( + self: ndarray[Any, _dtype[SupportsComplex]], # type: ignore[type-var] + ) -> complex: ... + + def __index__( + self: ndarray[Any, _dtype[SupportsIndex]], # type: ignore[type-var] + ) -> int: ... + + def __len__(self) -> int: ... + def __setitem__(self, key, value): ... + def __iter__(self) -> Any: ... + def __contains__(self, key) -> bool: ... + + # The last overload is for catching recursive objects whose + # nesting is too deep. + # The first overload is for catching `bytes` (as they are a subtype of + # `Sequence[int]`) and `str`. As `str` is a recursive sequence of + # strings, it will pass through the final overload otherwise + + @overload + def __lt__(self: _ArrayNumber_co, other: _ArrayLikeNumber_co) -> NDArray[bool_]: ... + @overload + def __lt__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> NDArray[bool_]: ... + @overload + def __lt__(self: NDArray[datetime64], other: _ArrayLikeDT64_co) -> NDArray[bool_]: ... + @overload + def __lt__(self: NDArray[object_], other: Any) -> NDArray[bool_]: ... + @overload + def __lt__(self: NDArray[Any], other: _ArrayLikeObject_co) -> NDArray[bool_]: ... + + @overload + def __le__(self: _ArrayNumber_co, other: _ArrayLikeNumber_co) -> NDArray[bool_]: ... + @overload + def __le__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> NDArray[bool_]: ... + @overload + def __le__(self: NDArray[datetime64], other: _ArrayLikeDT64_co) -> NDArray[bool_]: ... + @overload + def __le__(self: NDArray[object_], other: Any) -> NDArray[bool_]: ... + @overload + def __le__(self: NDArray[Any], other: _ArrayLikeObject_co) -> NDArray[bool_]: ... + + @overload + def __gt__(self: _ArrayNumber_co, other: _ArrayLikeNumber_co) -> NDArray[bool_]: ... + @overload + def __gt__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> NDArray[bool_]: ... + @overload + def __gt__(self: NDArray[datetime64], other: _ArrayLikeDT64_co) -> NDArray[bool_]: ... + @overload + def __gt__(self: NDArray[object_], other: Any) -> NDArray[bool_]: ... + @overload + def __gt__(self: NDArray[Any], other: _ArrayLikeObject_co) -> NDArray[bool_]: ... + + @overload + def __ge__(self: _ArrayNumber_co, other: _ArrayLikeNumber_co) -> NDArray[bool_]: ... + @overload + def __ge__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> NDArray[bool_]: ... + @overload + def __ge__(self: NDArray[datetime64], other: _ArrayLikeDT64_co) -> NDArray[bool_]: ... + @overload + def __ge__(self: NDArray[object_], other: Any) -> NDArray[bool_]: ... + @overload + def __ge__(self: NDArray[Any], other: _ArrayLikeObject_co) -> NDArray[bool_]: ... + + # Unary ops + @overload + def __abs__(self: NDArray[bool_]) -> NDArray[bool_]: ... + @overload + def __abs__(self: NDArray[complexfloating[_NBit1, _NBit1]]) -> NDArray[floating[_NBit1]]: ... + @overload + def __abs__(self: NDArray[_NumberType]) -> NDArray[_NumberType]: ... + @overload + def __abs__(self: NDArray[timedelta64]) -> NDArray[timedelta64]: ... + @overload + def __abs__(self: NDArray[object_]) -> Any: ... + + @overload + def __invert__(self: NDArray[bool_]) -> NDArray[bool_]: ... + @overload + def __invert__(self: NDArray[_IntType]) -> NDArray[_IntType]: ... + @overload + def __invert__(self: NDArray[object_]) -> Any: ... + + @overload + def __pos__(self: NDArray[_NumberType]) -> NDArray[_NumberType]: ... + @overload + def __pos__(self: NDArray[timedelta64]) -> NDArray[timedelta64]: ... + @overload + def __pos__(self: NDArray[object_]) -> Any: ... + + @overload + def __neg__(self: NDArray[_NumberType]) -> NDArray[_NumberType]: ... + @overload + def __neg__(self: NDArray[timedelta64]) -> NDArray[timedelta64]: ... + @overload + def __neg__(self: NDArray[object_]) -> Any: ... + + # Binary ops + @overload + def __matmul__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[bool_]: ... # type: ignore[misc] + @overload + def __matmul__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __matmul__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... # type: ignore[misc] + @overload + def __matmul__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ... # type: ignore[misc] + @overload + def __matmul__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> NDArray[complexfloating[Any, Any]]: ... + @overload + def __matmul__(self: NDArray[number[Any]], other: _ArrayLikeNumber_co) -> NDArray[number[Any]]: ... + @overload + def __matmul__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __matmul__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __rmatmul__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[bool_]: ... # type: ignore[misc] + @overload + def __rmatmul__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __rmatmul__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... # type: ignore[misc] + @overload + def __rmatmul__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ... # type: ignore[misc] + @overload + def __rmatmul__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> NDArray[complexfloating[Any, Any]]: ... + @overload + def __rmatmul__(self: NDArray[number[Any]], other: _ArrayLikeNumber_co) -> NDArray[number[Any]]: ... + @overload + def __rmatmul__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __rmatmul__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __mod__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[int8]: ... # type: ignore[misc] + @overload + def __mod__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __mod__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... # type: ignore[misc] + @overload + def __mod__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ... # type: ignore[misc] + @overload + def __mod__(self: _ArrayTD64_co, other: _SupportsArray[_dtype[timedelta64]] | _NestedSequence[_SupportsArray[_dtype[timedelta64]]]) -> NDArray[timedelta64]: ... + @overload + def __mod__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __mod__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __rmod__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[int8]: ... # type: ignore[misc] + @overload + def __rmod__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __rmod__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... # type: ignore[misc] + @overload + def __rmod__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ... # type: ignore[misc] + @overload + def __rmod__(self: _ArrayTD64_co, other: _SupportsArray[_dtype[timedelta64]] | _NestedSequence[_SupportsArray[_dtype[timedelta64]]]) -> NDArray[timedelta64]: ... + @overload + def __rmod__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __rmod__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __divmod__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> _2Tuple[NDArray[int8]]: ... # type: ignore[misc] + @overload + def __divmod__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _2Tuple[NDArray[unsignedinteger[Any]]]: ... # type: ignore[misc] + @overload + def __divmod__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _2Tuple[NDArray[signedinteger[Any]]]: ... # type: ignore[misc] + @overload + def __divmod__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _2Tuple[NDArray[floating[Any]]]: ... # type: ignore[misc] + @overload + def __divmod__(self: _ArrayTD64_co, other: _SupportsArray[_dtype[timedelta64]] | _NestedSequence[_SupportsArray[_dtype[timedelta64]]]) -> tuple[NDArray[int64], NDArray[timedelta64]]: ... + + @overload + def __rdivmod__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> _2Tuple[NDArray[int8]]: ... # type: ignore[misc] + @overload + def __rdivmod__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _2Tuple[NDArray[unsignedinteger[Any]]]: ... # type: ignore[misc] + @overload + def __rdivmod__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _2Tuple[NDArray[signedinteger[Any]]]: ... # type: ignore[misc] + @overload + def __rdivmod__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _2Tuple[NDArray[floating[Any]]]: ... # type: ignore[misc] + @overload + def __rdivmod__(self: _ArrayTD64_co, other: _SupportsArray[_dtype[timedelta64]] | _NestedSequence[_SupportsArray[_dtype[timedelta64]]]) -> tuple[NDArray[int64], NDArray[timedelta64]]: ... + + @overload + def __add__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[bool_]: ... # type: ignore[misc] + @overload + def __add__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __add__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... # type: ignore[misc] + @overload + def __add__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ... # type: ignore[misc] + @overload + def __add__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> NDArray[complexfloating[Any, Any]]: ... # type: ignore[misc] + @overload + def __add__(self: NDArray[number[Any]], other: _ArrayLikeNumber_co) -> NDArray[number[Any]]: ... + @overload + def __add__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> NDArray[timedelta64]: ... # type: ignore[misc] + @overload + def __add__(self: _ArrayTD64_co, other: _ArrayLikeDT64_co) -> NDArray[datetime64]: ... + @overload + def __add__(self: NDArray[datetime64], other: _ArrayLikeTD64_co) -> NDArray[datetime64]: ... + @overload + def __add__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __add__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __radd__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[bool_]: ... # type: ignore[misc] + @overload + def __radd__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __radd__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... # type: ignore[misc] + @overload + def __radd__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ... # type: ignore[misc] + @overload + def __radd__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> NDArray[complexfloating[Any, Any]]: ... # type: ignore[misc] + @overload + def __radd__(self: NDArray[number[Any]], other: _ArrayLikeNumber_co) -> NDArray[number[Any]]: ... + @overload + def __radd__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> NDArray[timedelta64]: ... # type: ignore[misc] + @overload + def __radd__(self: _ArrayTD64_co, other: _ArrayLikeDT64_co) -> NDArray[datetime64]: ... + @overload + def __radd__(self: NDArray[datetime64], other: _ArrayLikeTD64_co) -> NDArray[datetime64]: ... + @overload + def __radd__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __radd__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __sub__(self: NDArray[_UnknownType], other: _ArrayLikeUnknown) -> NDArray[Any]: ... + @overload + def __sub__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NoReturn: ... + @overload + def __sub__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __sub__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... # type: ignore[misc] + @overload + def __sub__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ... # type: ignore[misc] + @overload + def __sub__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> NDArray[complexfloating[Any, Any]]: ... # type: ignore[misc] + @overload + def __sub__(self: NDArray[number[Any]], other: _ArrayLikeNumber_co) -> NDArray[number[Any]]: ... + @overload + def __sub__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> NDArray[timedelta64]: ... # type: ignore[misc] + @overload + def __sub__(self: NDArray[datetime64], other: _ArrayLikeTD64_co) -> NDArray[datetime64]: ... + @overload + def __sub__(self: NDArray[datetime64], other: _ArrayLikeDT64_co) -> NDArray[timedelta64]: ... + @overload + def __sub__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __sub__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __rsub__(self: NDArray[_UnknownType], other: _ArrayLikeUnknown) -> NDArray[Any]: ... + @overload + def __rsub__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NoReturn: ... + @overload + def __rsub__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __rsub__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... # type: ignore[misc] + @overload + def __rsub__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ... # type: ignore[misc] + @overload + def __rsub__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> NDArray[complexfloating[Any, Any]]: ... # type: ignore[misc] + @overload + def __rsub__(self: NDArray[number[Any]], other: _ArrayLikeNumber_co) -> NDArray[number[Any]]: ... + @overload + def __rsub__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> NDArray[timedelta64]: ... # type: ignore[misc] + @overload + def __rsub__(self: _ArrayTD64_co, other: _ArrayLikeDT64_co) -> NDArray[datetime64]: ... # type: ignore[misc] + @overload + def __rsub__(self: NDArray[datetime64], other: _ArrayLikeDT64_co) -> NDArray[timedelta64]: ... + @overload + def __rsub__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __rsub__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __mul__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[bool_]: ... # type: ignore[misc] + @overload + def __mul__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __mul__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... # type: ignore[misc] + @overload + def __mul__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ... # type: ignore[misc] + @overload + def __mul__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> NDArray[complexfloating[Any, Any]]: ... # type: ignore[misc] + @overload + def __mul__(self: NDArray[number[Any]], other: _ArrayLikeNumber_co) -> NDArray[number[Any]]: ... + @overload + def __mul__(self: _ArrayTD64_co, other: _ArrayLikeFloat_co) -> NDArray[timedelta64]: ... + @overload + def __mul__(self: _ArrayFloat_co, other: _ArrayLikeTD64_co) -> NDArray[timedelta64]: ... + @overload + def __mul__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __mul__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __rmul__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[bool_]: ... # type: ignore[misc] + @overload + def __rmul__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __rmul__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... # type: ignore[misc] + @overload + def __rmul__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ... # type: ignore[misc] + @overload + def __rmul__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> NDArray[complexfloating[Any, Any]]: ... # type: ignore[misc] + @overload + def __rmul__(self: NDArray[number[Any]], other: _ArrayLikeNumber_co) -> NDArray[number[Any]]: ... + @overload + def __rmul__(self: _ArrayTD64_co, other: _ArrayLikeFloat_co) -> NDArray[timedelta64]: ... + @overload + def __rmul__(self: _ArrayFloat_co, other: _ArrayLikeTD64_co) -> NDArray[timedelta64]: ... + @overload + def __rmul__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __rmul__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __floordiv__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[int8]: ... # type: ignore[misc] + @overload + def __floordiv__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __floordiv__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... # type: ignore[misc] + @overload + def __floordiv__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ... # type: ignore[misc] + @overload + def __floordiv__(self: NDArray[timedelta64], other: _SupportsArray[_dtype[timedelta64]] | _NestedSequence[_SupportsArray[_dtype[timedelta64]]]) -> NDArray[int64]: ... + @overload + def __floordiv__(self: NDArray[timedelta64], other: _ArrayLikeBool_co) -> NoReturn: ... + @overload + def __floordiv__(self: NDArray[timedelta64], other: _ArrayLikeFloat_co) -> NDArray[timedelta64]: ... + @overload + def __floordiv__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __floordiv__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __rfloordiv__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[int8]: ... # type: ignore[misc] + @overload + def __rfloordiv__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __rfloordiv__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... # type: ignore[misc] + @overload + def __rfloordiv__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ... # type: ignore[misc] + @overload + def __rfloordiv__(self: NDArray[timedelta64], other: _SupportsArray[_dtype[timedelta64]] | _NestedSequence[_SupportsArray[_dtype[timedelta64]]]) -> NDArray[int64]: ... + @overload + def __rfloordiv__(self: NDArray[bool_], other: _ArrayLikeTD64_co) -> NoReturn: ... + @overload + def __rfloordiv__(self: _ArrayFloat_co, other: _ArrayLikeTD64_co) -> NDArray[timedelta64]: ... + @overload + def __rfloordiv__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __rfloordiv__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __pow__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[int8]: ... # type: ignore[misc] + @overload + def __pow__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __pow__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... # type: ignore[misc] + @overload + def __pow__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ... # type: ignore[misc] + @overload + def __pow__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> NDArray[complexfloating[Any, Any]]: ... + @overload + def __pow__(self: NDArray[number[Any]], other: _ArrayLikeNumber_co) -> NDArray[number[Any]]: ... + @overload + def __pow__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __pow__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __rpow__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[int8]: ... # type: ignore[misc] + @overload + def __rpow__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __rpow__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... # type: ignore[misc] + @overload + def __rpow__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ... # type: ignore[misc] + @overload + def __rpow__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> NDArray[complexfloating[Any, Any]]: ... + @overload + def __rpow__(self: NDArray[number[Any]], other: _ArrayLikeNumber_co) -> NDArray[number[Any]]: ... + @overload + def __rpow__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __rpow__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __truediv__(self: _ArrayInt_co, other: _ArrayInt_co) -> NDArray[float64]: ... # type: ignore[misc] + @overload + def __truediv__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ... # type: ignore[misc] + @overload + def __truediv__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> NDArray[complexfloating[Any, Any]]: ... # type: ignore[misc] + @overload + def __truediv__(self: NDArray[number[Any]], other: _ArrayLikeNumber_co) -> NDArray[number[Any]]: ... + @overload + def __truediv__(self: NDArray[timedelta64], other: _SupportsArray[_dtype[timedelta64]] | _NestedSequence[_SupportsArray[_dtype[timedelta64]]]) -> NDArray[float64]: ... + @overload + def __truediv__(self: NDArray[timedelta64], other: _ArrayLikeBool_co) -> NoReturn: ... + @overload + def __truediv__(self: NDArray[timedelta64], other: _ArrayLikeFloat_co) -> NDArray[timedelta64]: ... + @overload + def __truediv__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __truediv__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __rtruediv__(self: _ArrayInt_co, other: _ArrayInt_co) -> NDArray[float64]: ... # type: ignore[misc] + @overload + def __rtruediv__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ... # type: ignore[misc] + @overload + def __rtruediv__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> NDArray[complexfloating[Any, Any]]: ... # type: ignore[misc] + @overload + def __rtruediv__(self: NDArray[number[Any]], other: _ArrayLikeNumber_co) -> NDArray[number[Any]]: ... + @overload + def __rtruediv__(self: NDArray[timedelta64], other: _SupportsArray[_dtype[timedelta64]] | _NestedSequence[_SupportsArray[_dtype[timedelta64]]]) -> NDArray[float64]: ... + @overload + def __rtruediv__(self: NDArray[bool_], other: _ArrayLikeTD64_co) -> NoReturn: ... + @overload + def __rtruediv__(self: _ArrayFloat_co, other: _ArrayLikeTD64_co) -> NDArray[timedelta64]: ... + @overload + def __rtruediv__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __rtruediv__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __lshift__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[int8]: ... # type: ignore[misc] + @overload + def __lshift__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __lshift__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... + @overload + def __lshift__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __lshift__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __rlshift__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[int8]: ... # type: ignore[misc] + @overload + def __rlshift__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __rlshift__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... + @overload + def __rlshift__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __rlshift__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __rshift__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[int8]: ... # type: ignore[misc] + @overload + def __rshift__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __rshift__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... + @overload + def __rshift__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __rshift__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __rrshift__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[int8]: ... # type: ignore[misc] + @overload + def __rrshift__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __rrshift__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... + @overload + def __rrshift__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __rrshift__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __and__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[bool_]: ... # type: ignore[misc] + @overload + def __and__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __and__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... + @overload + def __and__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __and__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __rand__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[bool_]: ... # type: ignore[misc] + @overload + def __rand__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __rand__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... + @overload + def __rand__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __rand__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __xor__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[bool_]: ... # type: ignore[misc] + @overload + def __xor__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __xor__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... + @overload + def __xor__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __xor__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __rxor__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[bool_]: ... # type: ignore[misc] + @overload + def __rxor__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __rxor__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... + @overload + def __rxor__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __rxor__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __or__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[bool_]: ... # type: ignore[misc] + @overload + def __or__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __or__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... + @overload + def __or__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __or__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + @overload + def __ror__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[bool_]: ... # type: ignore[misc] + @overload + def __ror__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc] + @overload + def __ror__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... + @overload + def __ror__(self: NDArray[object_], other: Any) -> Any: ... + @overload + def __ror__(self: NDArray[Any], other: _ArrayLikeObject_co) -> Any: ... + + # `np.generic` does not support inplace operations + + # NOTE: Inplace ops generally use "same_kind" casting w.r.t. to the left + # operand. An exception to this rule are unsigned integers though, which + # also accepts a signed integer for the right operand as long it is a 0D + # object and its value is >= 0 + @overload + def __iadd__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[bool_]: ... + @overload + def __iadd__(self: NDArray[unsignedinteger[_NBit1]], other: _ArrayLikeUInt_co | _IntLike_co) -> NDArray[unsignedinteger[_NBit1]]: ... + @overload + def __iadd__(self: NDArray[signedinteger[_NBit1]], other: _ArrayLikeInt_co) -> NDArray[signedinteger[_NBit1]]: ... + @overload + def __iadd__(self: NDArray[floating[_NBit1]], other: _ArrayLikeFloat_co) -> NDArray[floating[_NBit1]]: ... + @overload + def __iadd__(self: NDArray[complexfloating[_NBit1, _NBit1]], other: _ArrayLikeComplex_co) -> NDArray[complexfloating[_NBit1, _NBit1]]: ... + @overload + def __iadd__(self: NDArray[timedelta64], other: _ArrayLikeTD64_co) -> NDArray[timedelta64]: ... + @overload + def __iadd__(self: NDArray[datetime64], other: _ArrayLikeTD64_co) -> NDArray[datetime64]: ... + @overload + def __iadd__(self: NDArray[object_], other: Any) -> NDArray[object_]: ... + + @overload + def __isub__(self: NDArray[unsignedinteger[_NBit1]], other: _ArrayLikeUInt_co | _IntLike_co) -> NDArray[unsignedinteger[_NBit1]]: ... + @overload + def __isub__(self: NDArray[signedinteger[_NBit1]], other: _ArrayLikeInt_co) -> NDArray[signedinteger[_NBit1]]: ... + @overload + def __isub__(self: NDArray[floating[_NBit1]], other: _ArrayLikeFloat_co) -> NDArray[floating[_NBit1]]: ... + @overload + def __isub__(self: NDArray[complexfloating[_NBit1, _NBit1]], other: _ArrayLikeComplex_co) -> NDArray[complexfloating[_NBit1, _NBit1]]: ... + @overload + def __isub__(self: NDArray[timedelta64], other: _ArrayLikeTD64_co) -> NDArray[timedelta64]: ... + @overload + def __isub__(self: NDArray[datetime64], other: _ArrayLikeTD64_co) -> NDArray[datetime64]: ... + @overload + def __isub__(self: NDArray[object_], other: Any) -> NDArray[object_]: ... + + @overload + def __imul__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[bool_]: ... + @overload + def __imul__(self: NDArray[unsignedinteger[_NBit1]], other: _ArrayLikeUInt_co | _IntLike_co) -> NDArray[unsignedinteger[_NBit1]]: ... + @overload + def __imul__(self: NDArray[signedinteger[_NBit1]], other: _ArrayLikeInt_co) -> NDArray[signedinteger[_NBit1]]: ... + @overload + def __imul__(self: NDArray[floating[_NBit1]], other: _ArrayLikeFloat_co) -> NDArray[floating[_NBit1]]: ... + @overload + def __imul__(self: NDArray[complexfloating[_NBit1, _NBit1]], other: _ArrayLikeComplex_co) -> NDArray[complexfloating[_NBit1, _NBit1]]: ... + @overload + def __imul__(self: NDArray[timedelta64], other: _ArrayLikeFloat_co) -> NDArray[timedelta64]: ... + @overload + def __imul__(self: NDArray[object_], other: Any) -> NDArray[object_]: ... + + @overload + def __itruediv__(self: NDArray[floating[_NBit1]], other: _ArrayLikeFloat_co) -> NDArray[floating[_NBit1]]: ... + @overload + def __itruediv__(self: NDArray[complexfloating[_NBit1, _NBit1]], other: _ArrayLikeComplex_co) -> NDArray[complexfloating[_NBit1, _NBit1]]: ... + @overload + def __itruediv__(self: NDArray[timedelta64], other: _ArrayLikeBool_co) -> NoReturn: ... + @overload + def __itruediv__(self: NDArray[timedelta64], other: _ArrayLikeInt_co) -> NDArray[timedelta64]: ... + @overload + def __itruediv__(self: NDArray[object_], other: Any) -> NDArray[object_]: ... + + @overload + def __ifloordiv__(self: NDArray[unsignedinteger[_NBit1]], other: _ArrayLikeUInt_co | _IntLike_co) -> NDArray[unsignedinteger[_NBit1]]: ... + @overload + def __ifloordiv__(self: NDArray[signedinteger[_NBit1]], other: _ArrayLikeInt_co) -> NDArray[signedinteger[_NBit1]]: ... + @overload + def __ifloordiv__(self: NDArray[floating[_NBit1]], other: _ArrayLikeFloat_co) -> NDArray[floating[_NBit1]]: ... + @overload + def __ifloordiv__(self: NDArray[complexfloating[_NBit1, _NBit1]], other: _ArrayLikeComplex_co) -> NDArray[complexfloating[_NBit1, _NBit1]]: ... + @overload + def __ifloordiv__(self: NDArray[timedelta64], other: _ArrayLikeBool_co) -> NoReturn: ... + @overload + def __ifloordiv__(self: NDArray[timedelta64], other: _ArrayLikeInt_co) -> NDArray[timedelta64]: ... + @overload + def __ifloordiv__(self: NDArray[object_], other: Any) -> NDArray[object_]: ... + + @overload + def __ipow__(self: NDArray[unsignedinteger[_NBit1]], other: _ArrayLikeUInt_co | _IntLike_co) -> NDArray[unsignedinteger[_NBit1]]: ... + @overload + def __ipow__(self: NDArray[signedinteger[_NBit1]], other: _ArrayLikeInt_co) -> NDArray[signedinteger[_NBit1]]: ... + @overload + def __ipow__(self: NDArray[floating[_NBit1]], other: _ArrayLikeFloat_co) -> NDArray[floating[_NBit1]]: ... + @overload + def __ipow__(self: NDArray[complexfloating[_NBit1, _NBit1]], other: _ArrayLikeComplex_co) -> NDArray[complexfloating[_NBit1, _NBit1]]: ... + @overload + def __ipow__(self: NDArray[object_], other: Any) -> NDArray[object_]: ... + + @overload + def __imod__(self: NDArray[unsignedinteger[_NBit1]], other: _ArrayLikeUInt_co | _IntLike_co) -> NDArray[unsignedinteger[_NBit1]]: ... + @overload + def __imod__(self: NDArray[signedinteger[_NBit1]], other: _ArrayLikeInt_co) -> NDArray[signedinteger[_NBit1]]: ... + @overload + def __imod__(self: NDArray[floating[_NBit1]], other: _ArrayLikeFloat_co) -> NDArray[floating[_NBit1]]: ... + @overload + def __imod__(self: NDArray[timedelta64], other: _SupportsArray[_dtype[timedelta64]] | _NestedSequence[_SupportsArray[_dtype[timedelta64]]]) -> NDArray[timedelta64]: ... + @overload + def __imod__(self: NDArray[object_], other: Any) -> NDArray[object_]: ... + + @overload + def __ilshift__(self: NDArray[unsignedinteger[_NBit1]], other: _ArrayLikeUInt_co | _IntLike_co) -> NDArray[unsignedinteger[_NBit1]]: ... + @overload + def __ilshift__(self: NDArray[signedinteger[_NBit1]], other: _ArrayLikeInt_co) -> NDArray[signedinteger[_NBit1]]: ... + @overload + def __ilshift__(self: NDArray[object_], other: Any) -> NDArray[object_]: ... + + @overload + def __irshift__(self: NDArray[unsignedinteger[_NBit1]], other: _ArrayLikeUInt_co | _IntLike_co) -> NDArray[unsignedinteger[_NBit1]]: ... + @overload + def __irshift__(self: NDArray[signedinteger[_NBit1]], other: _ArrayLikeInt_co) -> NDArray[signedinteger[_NBit1]]: ... + @overload + def __irshift__(self: NDArray[object_], other: Any) -> NDArray[object_]: ... + + @overload + def __iand__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[bool_]: ... + @overload + def __iand__(self: NDArray[unsignedinteger[_NBit1]], other: _ArrayLikeUInt_co | _IntLike_co) -> NDArray[unsignedinteger[_NBit1]]: ... + @overload + def __iand__(self: NDArray[signedinteger[_NBit1]], other: _ArrayLikeInt_co) -> NDArray[signedinteger[_NBit1]]: ... + @overload + def __iand__(self: NDArray[object_], other: Any) -> NDArray[object_]: ... + + @overload + def __ixor__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[bool_]: ... + @overload + def __ixor__(self: NDArray[unsignedinteger[_NBit1]], other: _ArrayLikeUInt_co | _IntLike_co) -> NDArray[unsignedinteger[_NBit1]]: ... + @overload + def __ixor__(self: NDArray[signedinteger[_NBit1]], other: _ArrayLikeInt_co) -> NDArray[signedinteger[_NBit1]]: ... + @overload + def __ixor__(self: NDArray[object_], other: Any) -> NDArray[object_]: ... + + @overload + def __ior__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[bool_]: ... + @overload + def __ior__(self: NDArray[unsignedinteger[_NBit1]], other: _ArrayLikeUInt_co | _IntLike_co) -> NDArray[unsignedinteger[_NBit1]]: ... + @overload + def __ior__(self: NDArray[signedinteger[_NBit1]], other: _ArrayLikeInt_co) -> NDArray[signedinteger[_NBit1]]: ... + @overload + def __ior__(self: NDArray[object_], other: Any) -> NDArray[object_]: ... + + @overload + def __imatmul__(self: NDArray[bool_], other: _ArrayLikeBool_co) -> NDArray[bool_]: ... + @overload + def __imatmul__(self: NDArray[unsignedinteger[_NBit1]], other: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[_NBit1]]: ... + @overload + def __imatmul__(self: NDArray[signedinteger[_NBit1]], other: _ArrayLikeInt_co) -> NDArray[signedinteger[_NBit1]]: ... + @overload + def __imatmul__(self: NDArray[floating[_NBit1]], other: _ArrayLikeFloat_co) -> NDArray[floating[_NBit1]]: ... + @overload + def __imatmul__(self: NDArray[complexfloating[_NBit1, _NBit1]], other: _ArrayLikeComplex_co) -> NDArray[complexfloating[_NBit1, _NBit1]]: ... + @overload + def __imatmul__(self: NDArray[object_], other: Any) -> NDArray[object_]: ... + + def __dlpack__(self: NDArray[number[Any]], *, stream: None = ...) -> _PyCapsule: ... + def __dlpack_device__(self) -> tuple[int, L[0]]: ... + + # Keep `dtype` at the bottom to avoid name conflicts with `np.dtype` + @property + def dtype(self) -> _DType_co: ... + +# NOTE: while `np.generic` is not technically an instance of `ABCMeta`, +# the `@abstractmethod` decorator is herein used to (forcefully) deny +# the creation of `np.generic` instances. +# The `# type: ignore` comments are necessary to silence mypy errors regarding +# the missing `ABCMeta` metaclass. + +# See https://github.com/numpy/numpy-stubs/pull/80 for more details. + +_ScalarType = TypeVar("_ScalarType", bound=generic) +_NBit1 = TypeVar("_NBit1", bound=NBitBase) +_NBit2 = TypeVar("_NBit2", bound=NBitBase) + +class generic(_ArrayOrScalarCommon): + @abstractmethod + def __init__(self, *args: Any, **kwargs: Any) -> None: ... + @overload + def __array__(self: _ScalarType, dtype: None = ..., /) -> ndarray[Any, _dtype[_ScalarType]]: ... + @overload + def __array__(self, dtype: _DType, /) -> ndarray[Any, _DType]: ... + def __hash__(self) -> int: ... + @property + def base(self) -> None: ... + @property + def ndim(self) -> L[0]: ... + @property + def size(self) -> L[1]: ... + @property + def shape(self) -> tuple[()]: ... + @property + def strides(self) -> tuple[()]: ... + def byteswap(self: _ScalarType, inplace: L[False] = ...) -> _ScalarType: ... + @property + def flat(self: _ScalarType) -> flatiter[ndarray[Any, _dtype[_ScalarType]]]: ... + + if sys.version_info >= (3, 12): + def __buffer__(self, flags: int, /) -> memoryview: ... + + @overload + def astype( + self, + dtype: _DTypeLike[_ScalarType], + order: _OrderKACF = ..., + casting: _CastingKind = ..., + subok: bool = ..., + copy: bool | _CopyMode = ..., + ) -> _ScalarType: ... + @overload + def astype( + self, + dtype: DTypeLike, + order: _OrderKACF = ..., + casting: _CastingKind = ..., + subok: bool = ..., + copy: bool | _CopyMode = ..., + ) -> Any: ... + + # NOTE: `view` will perform a 0D->scalar cast, + # thus the array `type` is irrelevant to the output type + @overload + def view( + self: _ScalarType, + type: type[ndarray[Any, Any]] = ..., + ) -> _ScalarType: ... + @overload + def view( + self, + dtype: _DTypeLike[_ScalarType], + type: type[ndarray[Any, Any]] = ..., + ) -> _ScalarType: ... + @overload + def view( + self, + dtype: DTypeLike, + type: type[ndarray[Any, Any]] = ..., + ) -> Any: ... + + @overload + def getfield( + self, + dtype: _DTypeLike[_ScalarType], + offset: SupportsIndex = ... + ) -> _ScalarType: ... + @overload + def getfield( + self, + dtype: DTypeLike, + offset: SupportsIndex = ... + ) -> Any: ... + + def item( + self, args: L[0] | tuple[()] | tuple[L[0]] = ..., /, + ) -> Any: ... + + @overload + def take( # type: ignore[misc] + self: _ScalarType, + indices: _IntLike_co, + axis: None | SupportsIndex = ..., + out: None = ..., + mode: _ModeKind = ..., + ) -> _ScalarType: ... + @overload + def take( # type: ignore[misc] + self: _ScalarType, + indices: _ArrayLikeInt_co, + axis: None | SupportsIndex = ..., + out: None = ..., + mode: _ModeKind = ..., + ) -> ndarray[Any, _dtype[_ScalarType]]: ... + @overload + def take( + self, + indices: _ArrayLikeInt_co, + axis: None | SupportsIndex = ..., + out: _NdArraySubClass = ..., + mode: _ModeKind = ..., + ) -> _NdArraySubClass: ... + + def repeat( + self: _ScalarType, + repeats: _ArrayLikeInt_co, + axis: None | SupportsIndex = ..., + ) -> ndarray[Any, _dtype[_ScalarType]]: ... + + def flatten( + self: _ScalarType, + order: _OrderKACF = ..., + ) -> ndarray[Any, _dtype[_ScalarType]]: ... + + def ravel( + self: _ScalarType, + order: _OrderKACF = ..., + ) -> ndarray[Any, _dtype[_ScalarType]]: ... + + @overload + def reshape( + self: _ScalarType, shape: _ShapeLike, /, *, order: _OrderACF = ... + ) -> ndarray[Any, _dtype[_ScalarType]]: ... + @overload + def reshape( + self: _ScalarType, *shape: SupportsIndex, order: _OrderACF = ... + ) -> ndarray[Any, _dtype[_ScalarType]]: ... + + def squeeze( + self: _ScalarType, axis: None | L[0] | tuple[()] = ... + ) -> _ScalarType: ... + def transpose(self: _ScalarType, axes: None | tuple[()] = ..., /) -> _ScalarType: ... + # Keep `dtype` at the bottom to avoid name conflicts with `np.dtype` + @property + def dtype(self: _ScalarType) -> _dtype[_ScalarType]: ... + +class number(generic, Generic[_NBit1]): # type: ignore + @property + def real(self: _ArraySelf) -> _ArraySelf: ... + @property + def imag(self: _ArraySelf) -> _ArraySelf: ... + def __class_getitem__(self, item: Any) -> GenericAlias: ... + def __int__(self) -> int: ... + def __float__(self) -> float: ... + def __complex__(self) -> complex: ... + def __neg__(self: _ArraySelf) -> _ArraySelf: ... + def __pos__(self: _ArraySelf) -> _ArraySelf: ... + def __abs__(self: _ArraySelf) -> _ArraySelf: ... + # Ensure that objects annotated as `number` support arithmetic operations + __add__: _NumberOp + __radd__: _NumberOp + __sub__: _NumberOp + __rsub__: _NumberOp + __mul__: _NumberOp + __rmul__: _NumberOp + __floordiv__: _NumberOp + __rfloordiv__: _NumberOp + __pow__: _NumberOp + __rpow__: _NumberOp + __truediv__: _NumberOp + __rtruediv__: _NumberOp + __lt__: _ComparisonOp[_NumberLike_co, _ArrayLikeNumber_co] + __le__: _ComparisonOp[_NumberLike_co, _ArrayLikeNumber_co] + __gt__: _ComparisonOp[_NumberLike_co, _ArrayLikeNumber_co] + __ge__: _ComparisonOp[_NumberLike_co, _ArrayLikeNumber_co] + +class bool_(generic): + def __init__(self, value: object = ..., /) -> None: ... + def item( + self, args: L[0] | tuple[()] | tuple[L[0]] = ..., /, + ) -> bool: ... + def tolist(self) -> bool: ... + @property + def real(self: _ArraySelf) -> _ArraySelf: ... + @property + def imag(self: _ArraySelf) -> _ArraySelf: ... + def __int__(self) -> int: ... + def __float__(self) -> float: ... + def __complex__(self) -> complex: ... + def __abs__(self: _ArraySelf) -> _ArraySelf: ... + __add__: _BoolOp[bool_] + __radd__: _BoolOp[bool_] + __sub__: _BoolSub + __rsub__: _BoolSub + __mul__: _BoolOp[bool_] + __rmul__: _BoolOp[bool_] + __floordiv__: _BoolOp[int8] + __rfloordiv__: _BoolOp[int8] + __pow__: _BoolOp[int8] + __rpow__: _BoolOp[int8] + __truediv__: _BoolTrueDiv + __rtruediv__: _BoolTrueDiv + def __invert__(self) -> bool_: ... + __lshift__: _BoolBitOp[int8] + __rlshift__: _BoolBitOp[int8] + __rshift__: _BoolBitOp[int8] + __rrshift__: _BoolBitOp[int8] + __and__: _BoolBitOp[bool_] + __rand__: _BoolBitOp[bool_] + __xor__: _BoolBitOp[bool_] + __rxor__: _BoolBitOp[bool_] + __or__: _BoolBitOp[bool_] + __ror__: _BoolBitOp[bool_] + __mod__: _BoolMod + __rmod__: _BoolMod + __divmod__: _BoolDivMod + __rdivmod__: _BoolDivMod + __lt__: _ComparisonOp[_NumberLike_co, _ArrayLikeNumber_co] + __le__: _ComparisonOp[_NumberLike_co, _ArrayLikeNumber_co] + __gt__: _ComparisonOp[_NumberLike_co, _ArrayLikeNumber_co] + __ge__: _ComparisonOp[_NumberLike_co, _ArrayLikeNumber_co] + +class object_(generic): + def __init__(self, value: object = ..., /) -> None: ... + @property + def real(self: _ArraySelf) -> _ArraySelf: ... + @property + def imag(self: _ArraySelf) -> _ArraySelf: ... + # The 3 protocols below may or may not raise, + # depending on the underlying object + def __int__(self) -> int: ... + def __float__(self) -> float: ... + def __complex__(self) -> complex: ... + + if sys.version_info >= (3, 12): + def __release_buffer__(self, buffer: memoryview, /) -> None: ... + +# The `datetime64` constructors requires an object with the three attributes below, +# and thus supports datetime duck typing +class _DatetimeScalar(Protocol): + @property + def day(self) -> int: ... + @property + def month(self) -> int: ... + @property + def year(self) -> int: ... + +# TODO: `item`/`tolist` returns either `dt.date`, `dt.datetime` or `int` +# depending on the unit +class datetime64(generic): + @overload + def __init__( + self, + value: None | datetime64 | _CharLike_co | _DatetimeScalar = ..., + format: _CharLike_co | tuple[_CharLike_co, _IntLike_co] = ..., + /, + ) -> None: ... + @overload + def __init__( + self, + value: int, + format: _CharLike_co | tuple[_CharLike_co, _IntLike_co], + /, + ) -> None: ... + def __add__(self, other: _TD64Like_co) -> datetime64: ... + def __radd__(self, other: _TD64Like_co) -> datetime64: ... + @overload + def __sub__(self, other: datetime64) -> timedelta64: ... + @overload + def __sub__(self, other: _TD64Like_co) -> datetime64: ... + def __rsub__(self, other: datetime64) -> timedelta64: ... + __lt__: _ComparisonOp[datetime64, _ArrayLikeDT64_co] + __le__: _ComparisonOp[datetime64, _ArrayLikeDT64_co] + __gt__: _ComparisonOp[datetime64, _ArrayLikeDT64_co] + __ge__: _ComparisonOp[datetime64, _ArrayLikeDT64_co] + +_IntValue = Union[SupportsInt, _CharLike_co, SupportsIndex] +_FloatValue = Union[None, _CharLike_co, SupportsFloat, SupportsIndex] +_ComplexValue = Union[ + None, + _CharLike_co, + SupportsFloat, + SupportsComplex, + SupportsIndex, + complex, # `complex` is not a subtype of `SupportsComplex` +] + +class integer(number[_NBit1]): # type: ignore + @property + def numerator(self: _ScalarType) -> _ScalarType: ... + @property + def denominator(self) -> L[1]: ... + @overload + def __round__(self, ndigits: None = ...) -> int: ... + @overload + def __round__(self: _ScalarType, ndigits: SupportsIndex) -> _ScalarType: ... + + # NOTE: `__index__` is technically defined in the bottom-most + # sub-classes (`int64`, `uint32`, etc) + def item( + self, args: L[0] | tuple[()] | tuple[L[0]] = ..., /, + ) -> int: ... + def tolist(self) -> int: ... + def is_integer(self) -> L[True]: ... + def bit_count(self: _ScalarType) -> int: ... + def __index__(self) -> int: ... + __truediv__: _IntTrueDiv[_NBit1] + __rtruediv__: _IntTrueDiv[_NBit1] + def __mod__(self, value: _IntLike_co) -> integer[Any]: ... + def __rmod__(self, value: _IntLike_co) -> integer[Any]: ... + def __invert__(self: _IntType) -> _IntType: ... + # Ensure that objects annotated as `integer` support bit-wise operations + def __lshift__(self, other: _IntLike_co) -> integer[Any]: ... + def __rlshift__(self, other: _IntLike_co) -> integer[Any]: ... + def __rshift__(self, other: _IntLike_co) -> integer[Any]: ... + def __rrshift__(self, other: _IntLike_co) -> integer[Any]: ... + def __and__(self, other: _IntLike_co) -> integer[Any]: ... + def __rand__(self, other: _IntLike_co) -> integer[Any]: ... + def __or__(self, other: _IntLike_co) -> integer[Any]: ... + def __ror__(self, other: _IntLike_co) -> integer[Any]: ... + def __xor__(self, other: _IntLike_co) -> integer[Any]: ... + def __rxor__(self, other: _IntLike_co) -> integer[Any]: ... + +class signedinteger(integer[_NBit1]): + def __init__(self, value: _IntValue = ..., /) -> None: ... + __add__: _SignedIntOp[_NBit1] + __radd__: _SignedIntOp[_NBit1] + __sub__: _SignedIntOp[_NBit1] + __rsub__: _SignedIntOp[_NBit1] + __mul__: _SignedIntOp[_NBit1] + __rmul__: _SignedIntOp[_NBit1] + __floordiv__: _SignedIntOp[_NBit1] + __rfloordiv__: _SignedIntOp[_NBit1] + __pow__: _SignedIntOp[_NBit1] + __rpow__: _SignedIntOp[_NBit1] + __lshift__: _SignedIntBitOp[_NBit1] + __rlshift__: _SignedIntBitOp[_NBit1] + __rshift__: _SignedIntBitOp[_NBit1] + __rrshift__: _SignedIntBitOp[_NBit1] + __and__: _SignedIntBitOp[_NBit1] + __rand__: _SignedIntBitOp[_NBit1] + __xor__: _SignedIntBitOp[_NBit1] + __rxor__: _SignedIntBitOp[_NBit1] + __or__: _SignedIntBitOp[_NBit1] + __ror__: _SignedIntBitOp[_NBit1] + __mod__: _SignedIntMod[_NBit1] + __rmod__: _SignedIntMod[_NBit1] + __divmod__: _SignedIntDivMod[_NBit1] + __rdivmod__: _SignedIntDivMod[_NBit1] + +int8 = signedinteger[_8Bit] +int16 = signedinteger[_16Bit] +int32 = signedinteger[_32Bit] +int64 = signedinteger[_64Bit] + +byte = signedinteger[_NBitByte] +short = signedinteger[_NBitShort] +intc = signedinteger[_NBitIntC] +intp = signedinteger[_NBitIntP] +int_ = signedinteger[_NBitInt] +longlong = signedinteger[_NBitLongLong] + +# TODO: `item`/`tolist` returns either `dt.timedelta` or `int` +# depending on the unit +class timedelta64(generic): + def __init__( + self, + value: None | int | _CharLike_co | dt.timedelta | timedelta64 = ..., + format: _CharLike_co | tuple[_CharLike_co, _IntLike_co] = ..., + /, + ) -> None: ... + @property + def numerator(self: _ScalarType) -> _ScalarType: ... + @property + def denominator(self) -> L[1]: ... + + # NOTE: Only a limited number of units support conversion + # to builtin scalar types: `Y`, `M`, `ns`, `ps`, `fs`, `as` + def __int__(self) -> int: ... + def __float__(self) -> float: ... + def __complex__(self) -> complex: ... + def __neg__(self: _ArraySelf) -> _ArraySelf: ... + def __pos__(self: _ArraySelf) -> _ArraySelf: ... + def __abs__(self: _ArraySelf) -> _ArraySelf: ... + def __add__(self, other: _TD64Like_co) -> timedelta64: ... + def __radd__(self, other: _TD64Like_co) -> timedelta64: ... + def __sub__(self, other: _TD64Like_co) -> timedelta64: ... + def __rsub__(self, other: _TD64Like_co) -> timedelta64: ... + def __mul__(self, other: _FloatLike_co) -> timedelta64: ... + def __rmul__(self, other: _FloatLike_co) -> timedelta64: ... + __truediv__: _TD64Div[float64] + __floordiv__: _TD64Div[int64] + def __rtruediv__(self, other: timedelta64) -> float64: ... + def __rfloordiv__(self, other: timedelta64) -> int64: ... + def __mod__(self, other: timedelta64) -> timedelta64: ... + def __rmod__(self, other: timedelta64) -> timedelta64: ... + def __divmod__(self, other: timedelta64) -> tuple[int64, timedelta64]: ... + def __rdivmod__(self, other: timedelta64) -> tuple[int64, timedelta64]: ... + __lt__: _ComparisonOp[_TD64Like_co, _ArrayLikeTD64_co] + __le__: _ComparisonOp[_TD64Like_co, _ArrayLikeTD64_co] + __gt__: _ComparisonOp[_TD64Like_co, _ArrayLikeTD64_co] + __ge__: _ComparisonOp[_TD64Like_co, _ArrayLikeTD64_co] + +class unsignedinteger(integer[_NBit1]): + # NOTE: `uint64 + signedinteger -> float64` + def __init__(self, value: _IntValue = ..., /) -> None: ... + __add__: _UnsignedIntOp[_NBit1] + __radd__: _UnsignedIntOp[_NBit1] + __sub__: _UnsignedIntOp[_NBit1] + __rsub__: _UnsignedIntOp[_NBit1] + __mul__: _UnsignedIntOp[_NBit1] + __rmul__: _UnsignedIntOp[_NBit1] + __floordiv__: _UnsignedIntOp[_NBit1] + __rfloordiv__: _UnsignedIntOp[_NBit1] + __pow__: _UnsignedIntOp[_NBit1] + __rpow__: _UnsignedIntOp[_NBit1] + __lshift__: _UnsignedIntBitOp[_NBit1] + __rlshift__: _UnsignedIntBitOp[_NBit1] + __rshift__: _UnsignedIntBitOp[_NBit1] + __rrshift__: _UnsignedIntBitOp[_NBit1] + __and__: _UnsignedIntBitOp[_NBit1] + __rand__: _UnsignedIntBitOp[_NBit1] + __xor__: _UnsignedIntBitOp[_NBit1] + __rxor__: _UnsignedIntBitOp[_NBit1] + __or__: _UnsignedIntBitOp[_NBit1] + __ror__: _UnsignedIntBitOp[_NBit1] + __mod__: _UnsignedIntMod[_NBit1] + __rmod__: _UnsignedIntMod[_NBit1] + __divmod__: _UnsignedIntDivMod[_NBit1] + __rdivmod__: _UnsignedIntDivMod[_NBit1] + +uint8 = unsignedinteger[_8Bit] +uint16 = unsignedinteger[_16Bit] +uint32 = unsignedinteger[_32Bit] +uint64 = unsignedinteger[_64Bit] + +ubyte = unsignedinteger[_NBitByte] +ushort = unsignedinteger[_NBitShort] +uintc = unsignedinteger[_NBitIntC] +uintp = unsignedinteger[_NBitIntP] +uint = unsignedinteger[_NBitInt] +ulonglong = unsignedinteger[_NBitLongLong] + +class inexact(number[_NBit1]): # type: ignore + def __getnewargs__(self: inexact[_64Bit]) -> tuple[float, ...]: ... + +_IntType = TypeVar("_IntType", bound=integer[Any]) +_FloatType = TypeVar('_FloatType', bound=floating[Any]) + +class floating(inexact[_NBit1]): + def __init__(self, value: _FloatValue = ..., /) -> None: ... + def item( + self, args: L[0] | tuple[()] | tuple[L[0]] = ..., + /, + ) -> float: ... + def tolist(self) -> float: ... + def is_integer(self) -> bool: ... + def hex(self: float64) -> str: ... + @classmethod + def fromhex(cls: type[float64], string: str, /) -> float64: ... + def as_integer_ratio(self) -> tuple[int, int]: ... + def __ceil__(self: float64) -> int: ... + def __floor__(self: float64) -> int: ... + def __trunc__(self: float64) -> int: ... + def __getnewargs__(self: float64) -> tuple[float]: ... + def __getformat__(self: float64, typestr: L["double", "float"], /) -> str: ... + @overload + def __round__(self, ndigits: None = ...) -> int: ... + @overload + def __round__(self: _ScalarType, ndigits: SupportsIndex) -> _ScalarType: ... + __add__: _FloatOp[_NBit1] + __radd__: _FloatOp[_NBit1] + __sub__: _FloatOp[_NBit1] + __rsub__: _FloatOp[_NBit1] + __mul__: _FloatOp[_NBit1] + __rmul__: _FloatOp[_NBit1] + __truediv__: _FloatOp[_NBit1] + __rtruediv__: _FloatOp[_NBit1] + __floordiv__: _FloatOp[_NBit1] + __rfloordiv__: _FloatOp[_NBit1] + __pow__: _FloatOp[_NBit1] + __rpow__: _FloatOp[_NBit1] + __mod__: _FloatMod[_NBit1] + __rmod__: _FloatMod[_NBit1] + __divmod__: _FloatDivMod[_NBit1] + __rdivmod__: _FloatDivMod[_NBit1] + +float16 = floating[_16Bit] +float32 = floating[_32Bit] +float64 = floating[_64Bit] + +half = floating[_NBitHalf] +single = floating[_NBitSingle] +double = floating[_NBitDouble] +float_ = floating[_NBitDouble] +longdouble = floating[_NBitLongDouble] +longfloat = floating[_NBitLongDouble] + +# The main reason for `complexfloating` having two typevars is cosmetic. +# It is used to clarify why `complex128`s precision is `_64Bit`, the latter +# describing the two 64 bit floats representing its real and imaginary component + +class complexfloating(inexact[_NBit1], Generic[_NBit1, _NBit2]): + def __init__(self, value: _ComplexValue = ..., /) -> None: ... + def item( + self, args: L[0] | tuple[()] | tuple[L[0]] = ..., /, + ) -> complex: ... + def tolist(self) -> complex: ... + @property + def real(self) -> floating[_NBit1]: ... # type: ignore[override] + @property + def imag(self) -> floating[_NBit2]: ... # type: ignore[override] + def __abs__(self) -> floating[_NBit1]: ... # type: ignore[override] + def __getnewargs__(self: complex128) -> tuple[float, float]: ... + # NOTE: Deprecated + # def __round__(self, ndigits=...): ... + __add__: _ComplexOp[_NBit1] + __radd__: _ComplexOp[_NBit1] + __sub__: _ComplexOp[_NBit1] + __rsub__: _ComplexOp[_NBit1] + __mul__: _ComplexOp[_NBit1] + __rmul__: _ComplexOp[_NBit1] + __truediv__: _ComplexOp[_NBit1] + __rtruediv__: _ComplexOp[_NBit1] + __pow__: _ComplexOp[_NBit1] + __rpow__: _ComplexOp[_NBit1] + +complex64 = complexfloating[_32Bit, _32Bit] +complex128 = complexfloating[_64Bit, _64Bit] + +csingle = complexfloating[_NBitSingle, _NBitSingle] +singlecomplex = complexfloating[_NBitSingle, _NBitSingle] +cdouble = complexfloating[_NBitDouble, _NBitDouble] +complex_ = complexfloating[_NBitDouble, _NBitDouble] +cfloat = complexfloating[_NBitDouble, _NBitDouble] +clongdouble = complexfloating[_NBitLongDouble, _NBitLongDouble] +clongfloat = complexfloating[_NBitLongDouble, _NBitLongDouble] +longcomplex = complexfloating[_NBitLongDouble, _NBitLongDouble] + +class flexible(generic): ... # type: ignore + +# TODO: `item`/`tolist` returns either `bytes` or `tuple` +# depending on whether or not it's used as an opaque bytes sequence +# or a structure +class void(flexible): + @overload + def __init__(self, value: _IntLike_co | bytes, /, dtype : None = ...) -> None: ... + @overload + def __init__(self, value: Any, /, dtype: _DTypeLikeVoid) -> None: ... + @property + def real(self: _ArraySelf) -> _ArraySelf: ... + @property + def imag(self: _ArraySelf) -> _ArraySelf: ... + def setfield( + self, val: ArrayLike, dtype: DTypeLike, offset: int = ... + ) -> None: ... + @overload + def __getitem__(self, key: str | SupportsIndex) -> Any: ... + @overload + def __getitem__(self, key: list[str]) -> void: ... + def __setitem__( + self, + key: str | list[str] | SupportsIndex, + value: ArrayLike, + ) -> None: ... + +class character(flexible): # type: ignore + def __int__(self) -> int: ... + def __float__(self) -> float: ... + +# NOTE: Most `np.bytes_` / `np.str_` methods return their +# builtin `bytes` / `str` counterpart + +class bytes_(character, bytes): + @overload + def __init__(self, value: object = ..., /) -> None: ... + @overload + def __init__( + self, value: str, /, encoding: str = ..., errors: str = ... + ) -> None: ... + def item( + self, args: L[0] | tuple[()] | tuple[L[0]] = ..., /, + ) -> bytes: ... + def tolist(self) -> bytes: ... + +string_ = bytes_ + +class str_(character, str): + @overload + def __init__(self, value: object = ..., /) -> None: ... + @overload + def __init__( + self, value: bytes, /, encoding: str = ..., errors: str = ... + ) -> None: ... + def item( + self, args: L[0] | tuple[()] | tuple[L[0]] = ..., /, + ) -> str: ... + def tolist(self) -> str: ... + +unicode_ = str_ + +# +# Constants +# + +Inf: Final[float] +Infinity: Final[float] +NAN: Final[float] +NINF: Final[float] +NZERO: Final[float] +NaN: Final[float] +PINF: Final[float] +PZERO: Final[float] +e: Final[float] +euler_gamma: Final[float] +inf: Final[float] +infty: Final[float] +nan: Final[float] +pi: Final[float] + +ERR_IGNORE: L[0] +ERR_WARN: L[1] +ERR_RAISE: L[2] +ERR_CALL: L[3] +ERR_PRINT: L[4] +ERR_LOG: L[5] +ERR_DEFAULT: L[521] + +SHIFT_DIVIDEBYZERO: L[0] +SHIFT_OVERFLOW: L[3] +SHIFT_UNDERFLOW: L[6] +SHIFT_INVALID: L[9] + +FPE_DIVIDEBYZERO: L[1] +FPE_OVERFLOW: L[2] +FPE_UNDERFLOW: L[4] +FPE_INVALID: L[8] + +FLOATING_POINT_SUPPORT: L[1] +UFUNC_BUFSIZE_DEFAULT = BUFSIZE + +little_endian: Final[bool] +True_: Final[bool_] +False_: Final[bool_] + +UFUNC_PYVALS_NAME: L["UFUNC_PYVALS"] + +newaxis: None + +# See `numpy._typing._ufunc` for more concrete nin-/nout-specific stubs +@final +class ufunc: + @property + def __name__(self) -> str: ... + @property + def __doc__(self) -> str: ... + __call__: Callable[..., Any] + @property + def nin(self) -> int: ... + @property + def nout(self) -> int: ... + @property + def nargs(self) -> int: ... + @property + def ntypes(self) -> int: ... + @property + def types(self) -> list[str]: ... + # Broad return type because it has to encompass things like + # + # >>> np.logical_and.identity is True + # True + # >>> np.add.identity is 0 + # True + # >>> np.sin.identity is None + # True + # + # and any user-defined ufuncs. + @property + def identity(self) -> Any: ... + # This is None for ufuncs and a string for gufuncs. + @property + def signature(self) -> None | str: ... + # The next four methods will always exist, but they will just + # raise a ValueError ufuncs with that don't accept two input + # arguments and return one output argument. Because of that we + # can't type them very precisely. + reduce: Any + accumulate: Any + reduceat: Any + outer: Any + # Similarly at won't be defined for ufuncs that return multiple + # outputs, so we can't type it very precisely. + at: Any + +# Parameters: `__name__`, `ntypes` and `identity` +absolute: _UFunc_Nin1_Nout1[L['absolute'], L[20], None] +add: _UFunc_Nin2_Nout1[L['add'], L[22], L[0]] +arccos: _UFunc_Nin1_Nout1[L['arccos'], L[8], None] +arccosh: _UFunc_Nin1_Nout1[L['arccosh'], L[8], None] +arcsin: _UFunc_Nin1_Nout1[L['arcsin'], L[8], None] +arcsinh: _UFunc_Nin1_Nout1[L['arcsinh'], L[8], None] +arctan2: _UFunc_Nin2_Nout1[L['arctan2'], L[5], None] +arctan: _UFunc_Nin1_Nout1[L['arctan'], L[8], None] +arctanh: _UFunc_Nin1_Nout1[L['arctanh'], L[8], None] +bitwise_and: _UFunc_Nin2_Nout1[L['bitwise_and'], L[12], L[-1]] +bitwise_not: _UFunc_Nin1_Nout1[L['invert'], L[12], None] +bitwise_or: _UFunc_Nin2_Nout1[L['bitwise_or'], L[12], L[0]] +bitwise_xor: _UFunc_Nin2_Nout1[L['bitwise_xor'], L[12], L[0]] +cbrt: _UFunc_Nin1_Nout1[L['cbrt'], L[5], None] +ceil: _UFunc_Nin1_Nout1[L['ceil'], L[7], None] +conj: _UFunc_Nin1_Nout1[L['conjugate'], L[18], None] +conjugate: _UFunc_Nin1_Nout1[L['conjugate'], L[18], None] +copysign: _UFunc_Nin2_Nout1[L['copysign'], L[4], None] +cos: _UFunc_Nin1_Nout1[L['cos'], L[9], None] +cosh: _UFunc_Nin1_Nout1[L['cosh'], L[8], None] +deg2rad: _UFunc_Nin1_Nout1[L['deg2rad'], L[5], None] +degrees: _UFunc_Nin1_Nout1[L['degrees'], L[5], None] +divide: _UFunc_Nin2_Nout1[L['true_divide'], L[11], None] +divmod: _UFunc_Nin2_Nout2[L['divmod'], L[15], None] +equal: _UFunc_Nin2_Nout1[L['equal'], L[23], None] +exp2: _UFunc_Nin1_Nout1[L['exp2'], L[8], None] +exp: _UFunc_Nin1_Nout1[L['exp'], L[10], None] +expm1: _UFunc_Nin1_Nout1[L['expm1'], L[8], None] +fabs: _UFunc_Nin1_Nout1[L['fabs'], L[5], None] +float_power: _UFunc_Nin2_Nout1[L['float_power'], L[4], None] +floor: _UFunc_Nin1_Nout1[L['floor'], L[7], None] +floor_divide: _UFunc_Nin2_Nout1[L['floor_divide'], L[21], None] +fmax: _UFunc_Nin2_Nout1[L['fmax'], L[21], None] +fmin: _UFunc_Nin2_Nout1[L['fmin'], L[21], None] +fmod: _UFunc_Nin2_Nout1[L['fmod'], L[15], None] +frexp: _UFunc_Nin1_Nout2[L['frexp'], L[4], None] +gcd: _UFunc_Nin2_Nout1[L['gcd'], L[11], L[0]] +greater: _UFunc_Nin2_Nout1[L['greater'], L[23], None] +greater_equal: _UFunc_Nin2_Nout1[L['greater_equal'], L[23], None] +heaviside: _UFunc_Nin2_Nout1[L['heaviside'], L[4], None] +hypot: _UFunc_Nin2_Nout1[L['hypot'], L[5], L[0]] +invert: _UFunc_Nin1_Nout1[L['invert'], L[12], None] +isfinite: _UFunc_Nin1_Nout1[L['isfinite'], L[20], None] +isinf: _UFunc_Nin1_Nout1[L['isinf'], L[20], None] +isnan: _UFunc_Nin1_Nout1[L['isnan'], L[20], None] +isnat: _UFunc_Nin1_Nout1[L['isnat'], L[2], None] +lcm: _UFunc_Nin2_Nout1[L['lcm'], L[11], None] +ldexp: _UFunc_Nin2_Nout1[L['ldexp'], L[8], None] +left_shift: _UFunc_Nin2_Nout1[L['left_shift'], L[11], None] +less: _UFunc_Nin2_Nout1[L['less'], L[23], None] +less_equal: _UFunc_Nin2_Nout1[L['less_equal'], L[23], None] +log10: _UFunc_Nin1_Nout1[L['log10'], L[8], None] +log1p: _UFunc_Nin1_Nout1[L['log1p'], L[8], None] +log2: _UFunc_Nin1_Nout1[L['log2'], L[8], None] +log: _UFunc_Nin1_Nout1[L['log'], L[10], None] +logaddexp2: _UFunc_Nin2_Nout1[L['logaddexp2'], L[4], float] +logaddexp: _UFunc_Nin2_Nout1[L['logaddexp'], L[4], float] +logical_and: _UFunc_Nin2_Nout1[L['logical_and'], L[20], L[True]] +logical_not: _UFunc_Nin1_Nout1[L['logical_not'], L[20], None] +logical_or: _UFunc_Nin2_Nout1[L['logical_or'], L[20], L[False]] +logical_xor: _UFunc_Nin2_Nout1[L['logical_xor'], L[19], L[False]] +matmul: _GUFunc_Nin2_Nout1[L['matmul'], L[19], None] +maximum: _UFunc_Nin2_Nout1[L['maximum'], L[21], None] +minimum: _UFunc_Nin2_Nout1[L['minimum'], L[21], None] +mod: _UFunc_Nin2_Nout1[L['remainder'], L[16], None] +modf: _UFunc_Nin1_Nout2[L['modf'], L[4], None] +multiply: _UFunc_Nin2_Nout1[L['multiply'], L[23], L[1]] +negative: _UFunc_Nin1_Nout1[L['negative'], L[19], None] +nextafter: _UFunc_Nin2_Nout1[L['nextafter'], L[4], None] +not_equal: _UFunc_Nin2_Nout1[L['not_equal'], L[23], None] +positive: _UFunc_Nin1_Nout1[L['positive'], L[19], None] +power: _UFunc_Nin2_Nout1[L['power'], L[18], None] +rad2deg: _UFunc_Nin1_Nout1[L['rad2deg'], L[5], None] +radians: _UFunc_Nin1_Nout1[L['radians'], L[5], None] +reciprocal: _UFunc_Nin1_Nout1[L['reciprocal'], L[18], None] +remainder: _UFunc_Nin2_Nout1[L['remainder'], L[16], None] +right_shift: _UFunc_Nin2_Nout1[L['right_shift'], L[11], None] +rint: _UFunc_Nin1_Nout1[L['rint'], L[10], None] +sign: _UFunc_Nin1_Nout1[L['sign'], L[19], None] +signbit: _UFunc_Nin1_Nout1[L['signbit'], L[4], None] +sin: _UFunc_Nin1_Nout1[L['sin'], L[9], None] +sinh: _UFunc_Nin1_Nout1[L['sinh'], L[8], None] +spacing: _UFunc_Nin1_Nout1[L['spacing'], L[4], None] +sqrt: _UFunc_Nin1_Nout1[L['sqrt'], L[10], None] +square: _UFunc_Nin1_Nout1[L['square'], L[18], None] +subtract: _UFunc_Nin2_Nout1[L['subtract'], L[21], None] +tan: _UFunc_Nin1_Nout1[L['tan'], L[8], None] +tanh: _UFunc_Nin1_Nout1[L['tanh'], L[8], None] +true_divide: _UFunc_Nin2_Nout1[L['true_divide'], L[11], None] +trunc: _UFunc_Nin1_Nout1[L['trunc'], L[7], None] + +abs = absolute + +class _CopyMode(enum.Enum): + ALWAYS: L[True] + IF_NEEDED: L[False] + NEVER: L[2] + +# Warnings +class RankWarning(UserWarning): ... + +_CallType = TypeVar("_CallType", bound=_ErrFunc | _SupportsWrite[str]) + +class errstate(Generic[_CallType], ContextDecorator): + call: _CallType + kwargs: _ErrDictOptional + + # Expand `**kwargs` into explicit keyword-only arguments + def __init__( + self, + *, + call: _CallType = ..., + all: None | _ErrKind = ..., + divide: None | _ErrKind = ..., + over: None | _ErrKind = ..., + under: None | _ErrKind = ..., + invalid: None | _ErrKind = ..., + ) -> None: ... + def __enter__(self) -> None: ... + def __exit__( + self, + exc_type: None | type[BaseException], + exc_value: None | BaseException, + traceback: None | TracebackType, + /, + ) -> None: ... + +@contextmanager +def _no_nep50_warning() -> Generator[None, None, None]: ... +def _get_promotion_state() -> str: ... +def _set_promotion_state(state: str, /) -> None: ... + +class ndenumerate(Generic[_ScalarType]): + iter: flatiter[NDArray[_ScalarType]] + @overload + def __new__( + cls, arr: _FiniteNestedSequence[_SupportsArray[dtype[_ScalarType]]], + ) -> ndenumerate[_ScalarType]: ... + @overload + def __new__(cls, arr: str | _NestedSequence[str]) -> ndenumerate[str_]: ... + @overload + def __new__(cls, arr: bytes | _NestedSequence[bytes]) -> ndenumerate[bytes_]: ... + @overload + def __new__(cls, arr: bool | _NestedSequence[bool]) -> ndenumerate[bool_]: ... + @overload + def __new__(cls, arr: int | _NestedSequence[int]) -> ndenumerate[int_]: ... + @overload + def __new__(cls, arr: float | _NestedSequence[float]) -> ndenumerate[float_]: ... + @overload + def __new__(cls, arr: complex | _NestedSequence[complex]) -> ndenumerate[complex_]: ... + def __next__(self: ndenumerate[_ScalarType]) -> tuple[_Shape, _ScalarType]: ... + def __iter__(self: _T) -> _T: ... + +class ndindex: + @overload + def __init__(self, shape: tuple[SupportsIndex, ...], /) -> None: ... + @overload + def __init__(self, *shape: SupportsIndex) -> None: ... + def __iter__(self: _T) -> _T: ... + def __next__(self) -> _Shape: ... + +class DataSource: + def __init__( + self, + destpath: None | str | os.PathLike[str] = ..., + ) -> None: ... + def __del__(self) -> None: ... + def abspath(self, path: str) -> str: ... + def exists(self, path: str) -> bool: ... + + # Whether the file-object is opened in string or bytes mode (by default) + # depends on the file-extension of `path` + def open( + self, + path: str, + mode: str = ..., + encoding: None | str = ..., + newline: None | str = ..., + ) -> IO[Any]: ... + +# TODO: The type of each `__next__` and `iters` return-type depends +# on the length and dtype of `args`; we can't describe this behavior yet +# as we lack variadics (PEP 646). +@final +class broadcast: + def __new__(cls, *args: ArrayLike) -> broadcast: ... + @property + def index(self) -> int: ... + @property + def iters(self) -> tuple[flatiter[Any], ...]: ... + @property + def nd(self) -> int: ... + @property + def ndim(self) -> int: ... + @property + def numiter(self) -> int: ... + @property + def shape(self) -> _Shape: ... + @property + def size(self) -> int: ... + def __next__(self) -> tuple[Any, ...]: ... + def __iter__(self: _T) -> _T: ... + def reset(self) -> None: ... + +@final +class busdaycalendar: + def __new__( + cls, + weekmask: ArrayLike = ..., + holidays: ArrayLike | dt.date | _NestedSequence[dt.date] = ..., + ) -> busdaycalendar: ... + @property + def weekmask(self) -> NDArray[bool_]: ... + @property + def holidays(self) -> NDArray[datetime64]: ... + +class finfo(Generic[_FloatType]): + dtype: dtype[_FloatType] + bits: int + eps: _FloatType + epsneg: _FloatType + iexp: int + machep: int + max: _FloatType + maxexp: int + min: _FloatType + minexp: int + negep: int + nexp: int + nmant: int + precision: int + resolution: _FloatType + smallest_subnormal: _FloatType + @property + def smallest_normal(self) -> _FloatType: ... + @property + def tiny(self) -> _FloatType: ... + @overload + def __new__( + cls, dtype: inexact[_NBit1] | _DTypeLike[inexact[_NBit1]] + ) -> finfo[floating[_NBit1]]: ... + @overload + def __new__( + cls, dtype: complex | float | type[complex] | type[float] + ) -> finfo[float_]: ... + @overload + def __new__( + cls, dtype: str + ) -> finfo[floating[Any]]: ... + +class iinfo(Generic[_IntType]): + dtype: dtype[_IntType] + kind: str + bits: int + key: str + @property + def min(self) -> int: ... + @property + def max(self) -> int: ... + + @overload + def __new__(cls, dtype: _IntType | _DTypeLike[_IntType]) -> iinfo[_IntType]: ... + @overload + def __new__(cls, dtype: int | type[int]) -> iinfo[int_]: ... + @overload + def __new__(cls, dtype: str) -> iinfo[Any]: ... + +class format_parser: + dtype: dtype[void] + def __init__( + self, + formats: DTypeLike, + names: None | str | Sequence[str], + titles: None | str | Sequence[str], + aligned: bool = ..., + byteorder: None | _ByteOrder = ..., + ) -> None: ... + +class recarray(ndarray[_ShapeType, _DType_co]): + # NOTE: While not strictly mandatory, we're demanding here that arguments + # for the `format_parser`- and `dtype`-based dtype constructors are + # mutually exclusive + @overload + def __new__( + subtype, + shape: _ShapeLike, + dtype: None = ..., + buf: None | _SupportsBuffer = ..., + offset: SupportsIndex = ..., + strides: None | _ShapeLike = ..., + *, + formats: DTypeLike, + names: None | str | Sequence[str] = ..., + titles: None | str | Sequence[str] = ..., + byteorder: None | _ByteOrder = ..., + aligned: bool = ..., + order: _OrderKACF = ..., + ) -> recarray[Any, dtype[record]]: ... + @overload + def __new__( + subtype, + shape: _ShapeLike, + dtype: DTypeLike, + buf: None | _SupportsBuffer = ..., + offset: SupportsIndex = ..., + strides: None | _ShapeLike = ..., + formats: None = ..., + names: None = ..., + titles: None = ..., + byteorder: None = ..., + aligned: L[False] = ..., + order: _OrderKACF = ..., + ) -> recarray[Any, dtype[Any]]: ... + def __array_finalize__(self, obj: object) -> None: ... + def __getattribute__(self, attr: str) -> Any: ... + def __setattr__(self, attr: str, val: ArrayLike) -> None: ... + @overload + def __getitem__(self, indx: ( + SupportsIndex + | _ArrayLikeInt_co + | tuple[SupportsIndex | _ArrayLikeInt_co, ...] + )) -> Any: ... + @overload + def __getitem__(self: recarray[Any, dtype[void]], indx: ( + None + | slice + | ellipsis + | SupportsIndex + | _ArrayLikeInt_co + | tuple[None | slice | ellipsis | _ArrayLikeInt_co | SupportsIndex, ...] + )) -> recarray[Any, _DType_co]: ... + @overload + def __getitem__(self, indx: ( + None + | slice + | ellipsis + | SupportsIndex + | _ArrayLikeInt_co + | tuple[None | slice | ellipsis | _ArrayLikeInt_co | SupportsIndex, ...] + )) -> ndarray[Any, _DType_co]: ... + @overload + def __getitem__(self, indx: str) -> NDArray[Any]: ... + @overload + def __getitem__(self, indx: list[str]) -> recarray[_ShapeType, dtype[record]]: ... + @overload + def field(self, attr: int | str, val: None = ...) -> Any: ... + @overload + def field(self, attr: int | str, val: ArrayLike) -> None: ... + +class record(void): + def __getattribute__(self, attr: str) -> Any: ... + def __setattr__(self, attr: str, val: ArrayLike) -> None: ... + def pprint(self) -> str: ... + @overload + def __getitem__(self, key: str | SupportsIndex) -> Any: ... + @overload + def __getitem__(self, key: list[str]) -> record: ... + +_NDIterFlagsKind = L[ + "buffered", + "c_index", + "copy_if_overlap", + "common_dtype", + "delay_bufalloc", + "external_loop", + "f_index", + "grow_inner", "growinner", + "multi_index", + "ranged", + "refs_ok", + "reduce_ok", + "zerosize_ok", +] + +_NDIterOpFlagsKind = L[ + "aligned", + "allocate", + "arraymask", + "copy", + "config", + "nbo", + "no_subtype", + "no_broadcast", + "overlap_assume_elementwise", + "readonly", + "readwrite", + "updateifcopy", + "virtual", + "writeonly", + "writemasked" +] + +@final +class nditer: + def __new__( + cls, + op: ArrayLike | Sequence[ArrayLike], + flags: None | Sequence[_NDIterFlagsKind] = ..., + op_flags: None | Sequence[Sequence[_NDIterOpFlagsKind]] = ..., + op_dtypes: DTypeLike | Sequence[DTypeLike] = ..., + order: _OrderKACF = ..., + casting: _CastingKind = ..., + op_axes: None | Sequence[Sequence[SupportsIndex]] = ..., + itershape: None | _ShapeLike = ..., + buffersize: SupportsIndex = ..., + ) -> nditer: ... + def __enter__(self) -> nditer: ... + def __exit__( + self, + exc_type: None | type[BaseException], + exc_value: None | BaseException, + traceback: None | TracebackType, + ) -> None: ... + def __iter__(self) -> nditer: ... + def __next__(self) -> tuple[NDArray[Any], ...]: ... + def __len__(self) -> int: ... + def __copy__(self) -> nditer: ... + @overload + def __getitem__(self, index: SupportsIndex) -> NDArray[Any]: ... + @overload + def __getitem__(self, index: slice) -> tuple[NDArray[Any], ...]: ... + def __setitem__(self, index: slice | SupportsIndex, value: ArrayLike) -> None: ... + def close(self) -> None: ... + def copy(self) -> nditer: ... + def debug_print(self) -> None: ... + def enable_external_loop(self) -> None: ... + def iternext(self) -> bool: ... + def remove_axis(self, i: SupportsIndex, /) -> None: ... + def remove_multi_index(self) -> None: ... + def reset(self) -> None: ... + @property + def dtypes(self) -> tuple[dtype[Any], ...]: ... + @property + def finished(self) -> bool: ... + @property + def has_delayed_bufalloc(self) -> bool: ... + @property + def has_index(self) -> bool: ... + @property + def has_multi_index(self) -> bool: ... + @property + def index(self) -> int: ... + @property + def iterationneedsapi(self) -> bool: ... + @property + def iterindex(self) -> int: ... + @property + def iterrange(self) -> tuple[int, ...]: ... + @property + def itersize(self) -> int: ... + @property + def itviews(self) -> tuple[NDArray[Any], ...]: ... + @property + def multi_index(self) -> tuple[int, ...]: ... + @property + def ndim(self) -> int: ... + @property + def nop(self) -> int: ... + @property + def operands(self) -> tuple[NDArray[Any], ...]: ... + @property + def shape(self) -> tuple[int, ...]: ... + @property + def value(self) -> tuple[NDArray[Any], ...]: ... + +_MemMapModeKind = L[ + "readonly", "r", + "copyonwrite", "c", + "readwrite", "r+", + "write", "w+", +] + +class memmap(ndarray[_ShapeType, _DType_co]): + __array_priority__: ClassVar[float] + filename: str | None + offset: int + mode: str + @overload + def __new__( + subtype, + filename: str | bytes | os.PathLike[str] | os.PathLike[bytes] | _MemMapIOProtocol, + dtype: type[uint8] = ..., + mode: _MemMapModeKind = ..., + offset: int = ..., + shape: None | int | tuple[int, ...] = ..., + order: _OrderKACF = ..., + ) -> memmap[Any, dtype[uint8]]: ... + @overload + def __new__( + subtype, + filename: str | bytes | os.PathLike[str] | os.PathLike[bytes] | _MemMapIOProtocol, + dtype: _DTypeLike[_ScalarType], + mode: _MemMapModeKind = ..., + offset: int = ..., + shape: None | int | tuple[int, ...] = ..., + order: _OrderKACF = ..., + ) -> memmap[Any, dtype[_ScalarType]]: ... + @overload + def __new__( + subtype, + filename: str | bytes | os.PathLike[str] | os.PathLike[bytes] | _MemMapIOProtocol, + dtype: DTypeLike, + mode: _MemMapModeKind = ..., + offset: int = ..., + shape: None | int | tuple[int, ...] = ..., + order: _OrderKACF = ..., + ) -> memmap[Any, dtype[Any]]: ... + def __array_finalize__(self, obj: object) -> None: ... + def __array_wrap__( + self, + array: memmap[_ShapeType, _DType_co], + context: None | tuple[ufunc, tuple[Any, ...], int] = ..., + ) -> Any: ... + def flush(self) -> None: ... + +# TODO: Add a mypy plugin for managing functions whose output type is dependent +# on the literal value of some sort of signature (e.g. `einsum` and `vectorize`) +class vectorize: + pyfunc: Callable[..., Any] + cache: bool + signature: None | str + otypes: None | str + excluded: set[int | str] + __doc__: None | str + def __init__( + self, + pyfunc: Callable[..., Any], + otypes: None | str | Iterable[DTypeLike] = ..., + doc: None | str = ..., + excluded: None | Iterable[int | str] = ..., + cache: bool = ..., + signature: None | str = ..., + ) -> None: ... + def __call__(self, *args: Any, **kwargs: Any) -> Any: ... + +class poly1d: + @property + def variable(self) -> str: ... + @property + def order(self) -> int: ... + @property + def o(self) -> int: ... + @property + def roots(self) -> NDArray[Any]: ... + @property + def r(self) -> NDArray[Any]: ... + + @property + def coeffs(self) -> NDArray[Any]: ... + @coeffs.setter + def coeffs(self, value: NDArray[Any]) -> None: ... + + @property + def c(self) -> NDArray[Any]: ... + @c.setter + def c(self, value: NDArray[Any]) -> None: ... + + @property + def coef(self) -> NDArray[Any]: ... + @coef.setter + def coef(self, value: NDArray[Any]) -> None: ... + + @property + def coefficients(self) -> NDArray[Any]: ... + @coefficients.setter + def coefficients(self, value: NDArray[Any]) -> None: ... + + __hash__: ClassVar[None] # type: ignore + + @overload + def __array__(self, t: None = ...) -> NDArray[Any]: ... + @overload + def __array__(self, t: _DType) -> ndarray[Any, _DType]: ... + + @overload + def __call__(self, val: _ScalarLike_co) -> Any: ... + @overload + def __call__(self, val: poly1d) -> poly1d: ... + @overload + def __call__(self, val: ArrayLike) -> NDArray[Any]: ... + + def __init__( + self, + c_or_r: ArrayLike, + r: bool = ..., + variable: None | str = ..., + ) -> None: ... + def __len__(self) -> int: ... + def __neg__(self) -> poly1d: ... + def __pos__(self) -> poly1d: ... + def __mul__(self, other: ArrayLike) -> poly1d: ... + def __rmul__(self, other: ArrayLike) -> poly1d: ... + def __add__(self, other: ArrayLike) -> poly1d: ... + def __radd__(self, other: ArrayLike) -> poly1d: ... + def __pow__(self, val: _FloatLike_co) -> poly1d: ... # Integral floats are accepted + def __sub__(self, other: ArrayLike) -> poly1d: ... + def __rsub__(self, other: ArrayLike) -> poly1d: ... + def __div__(self, other: ArrayLike) -> poly1d: ... + def __truediv__(self, other: ArrayLike) -> poly1d: ... + def __rdiv__(self, other: ArrayLike) -> poly1d: ... + def __rtruediv__(self, other: ArrayLike) -> poly1d: ... + def __getitem__(self, val: int) -> Any: ... + def __setitem__(self, key: int, val: Any) -> None: ... + def __iter__(self) -> Iterator[Any]: ... + def deriv(self, m: SupportsInt | SupportsIndex = ...) -> poly1d: ... + def integ( + self, + m: SupportsInt | SupportsIndex = ..., + k: None | _ArrayLikeComplex_co | _ArrayLikeObject_co = ..., + ) -> poly1d: ... + +class matrix(ndarray[_ShapeType, _DType_co]): + __array_priority__: ClassVar[float] + def __new__( + subtype, + data: ArrayLike, + dtype: DTypeLike = ..., + copy: bool = ..., + ) -> matrix[Any, Any]: ... + def __array_finalize__(self, obj: object) -> None: ... + + @overload + def __getitem__(self, key: ( + SupportsIndex + | _ArrayLikeInt_co + | tuple[SupportsIndex | _ArrayLikeInt_co, ...] + )) -> Any: ... + @overload + def __getitem__(self, key: ( + None + | slice + | ellipsis + | SupportsIndex + | _ArrayLikeInt_co + | tuple[None | slice | ellipsis | _ArrayLikeInt_co | SupportsIndex, ...] + )) -> matrix[Any, _DType_co]: ... + @overload + def __getitem__(self: NDArray[void], key: str) -> matrix[Any, dtype[Any]]: ... + @overload + def __getitem__(self: NDArray[void], key: list[str]) -> matrix[_ShapeType, dtype[void]]: ... + + def __mul__(self, other: ArrayLike) -> matrix[Any, Any]: ... + def __rmul__(self, other: ArrayLike) -> matrix[Any, Any]: ... + def __imul__(self, other: ArrayLike) -> matrix[_ShapeType, _DType_co]: ... + def __pow__(self, other: ArrayLike) -> matrix[Any, Any]: ... + def __ipow__(self, other: ArrayLike) -> matrix[_ShapeType, _DType_co]: ... + + @overload + def sum(self, axis: None = ..., dtype: DTypeLike = ..., out: None = ...) -> Any: ... + @overload + def sum(self, axis: _ShapeLike, dtype: DTypeLike = ..., out: None = ...) -> matrix[Any, Any]: ... + @overload + def sum(self, axis: None | _ShapeLike = ..., dtype: DTypeLike = ..., out: _NdArraySubClass = ...) -> _NdArraySubClass: ... + + @overload + def mean(self, axis: None = ..., dtype: DTypeLike = ..., out: None = ...) -> Any: ... + @overload + def mean(self, axis: _ShapeLike, dtype: DTypeLike = ..., out: None = ...) -> matrix[Any, Any]: ... + @overload + def mean(self, axis: None | _ShapeLike = ..., dtype: DTypeLike = ..., out: _NdArraySubClass = ...) -> _NdArraySubClass: ... + + @overload + def std(self, axis: None = ..., dtype: DTypeLike = ..., out: None = ..., ddof: float = ...) -> Any: ... + @overload + def std(self, axis: _ShapeLike, dtype: DTypeLike = ..., out: None = ..., ddof: float = ...) -> matrix[Any, Any]: ... + @overload + def std(self, axis: None | _ShapeLike = ..., dtype: DTypeLike = ..., out: _NdArraySubClass = ..., ddof: float = ...) -> _NdArraySubClass: ... + + @overload + def var(self, axis: None = ..., dtype: DTypeLike = ..., out: None = ..., ddof: float = ...) -> Any: ... + @overload + def var(self, axis: _ShapeLike, dtype: DTypeLike = ..., out: None = ..., ddof: float = ...) -> matrix[Any, Any]: ... + @overload + def var(self, axis: None | _ShapeLike = ..., dtype: DTypeLike = ..., out: _NdArraySubClass = ..., ddof: float = ...) -> _NdArraySubClass: ... + + @overload + def prod(self, axis: None = ..., dtype: DTypeLike = ..., out: None = ...) -> Any: ... + @overload + def prod(self, axis: _ShapeLike, dtype: DTypeLike = ..., out: None = ...) -> matrix[Any, Any]: ... + @overload + def prod(self, axis: None | _ShapeLike = ..., dtype: DTypeLike = ..., out: _NdArraySubClass = ...) -> _NdArraySubClass: ... + + @overload + def any(self, axis: None = ..., out: None = ...) -> bool_: ... + @overload + def any(self, axis: _ShapeLike, out: None = ...) -> matrix[Any, dtype[bool_]]: ... + @overload + def any(self, axis: None | _ShapeLike = ..., out: _NdArraySubClass = ...) -> _NdArraySubClass: ... + + @overload + def all(self, axis: None = ..., out: None = ...) -> bool_: ... + @overload + def all(self, axis: _ShapeLike, out: None = ...) -> matrix[Any, dtype[bool_]]: ... + @overload + def all(self, axis: None | _ShapeLike = ..., out: _NdArraySubClass = ...) -> _NdArraySubClass: ... + + @overload + def max(self: NDArray[_ScalarType], axis: None = ..., out: None = ...) -> _ScalarType: ... + @overload + def max(self, axis: _ShapeLike, out: None = ...) -> matrix[Any, _DType_co]: ... + @overload + def max(self, axis: None | _ShapeLike = ..., out: _NdArraySubClass = ...) -> _NdArraySubClass: ... + + @overload + def min(self: NDArray[_ScalarType], axis: None = ..., out: None = ...) -> _ScalarType: ... + @overload + def min(self, axis: _ShapeLike, out: None = ...) -> matrix[Any, _DType_co]: ... + @overload + def min(self, axis: None | _ShapeLike = ..., out: _NdArraySubClass = ...) -> _NdArraySubClass: ... + + @overload + def argmax(self: NDArray[_ScalarType], axis: None = ..., out: None = ...) -> intp: ... + @overload + def argmax(self, axis: _ShapeLike, out: None = ...) -> matrix[Any, dtype[intp]]: ... + @overload + def argmax(self, axis: None | _ShapeLike = ..., out: _NdArraySubClass = ...) -> _NdArraySubClass: ... + + @overload + def argmin(self: NDArray[_ScalarType], axis: None = ..., out: None = ...) -> intp: ... + @overload + def argmin(self, axis: _ShapeLike, out: None = ...) -> matrix[Any, dtype[intp]]: ... + @overload + def argmin(self, axis: None | _ShapeLike = ..., out: _NdArraySubClass = ...) -> _NdArraySubClass: ... + + @overload + def ptp(self: NDArray[_ScalarType], axis: None = ..., out: None = ...) -> _ScalarType: ... + @overload + def ptp(self, axis: _ShapeLike, out: None = ...) -> matrix[Any, _DType_co]: ... + @overload + def ptp(self, axis: None | _ShapeLike = ..., out: _NdArraySubClass = ...) -> _NdArraySubClass: ... + + def squeeze(self, axis: None | _ShapeLike = ...) -> matrix[Any, _DType_co]: ... + def tolist(self: matrix[Any, dtype[_SupportsItem[_T]]]) -> list[list[_T]]: ... # type: ignore[typevar] + def ravel(self, order: _OrderKACF = ...) -> matrix[Any, _DType_co]: ... + def flatten(self, order: _OrderKACF = ...) -> matrix[Any, _DType_co]: ... + + @property + def T(self) -> matrix[Any, _DType_co]: ... + @property + def I(self) -> matrix[Any, Any]: ... + @property + def A(self) -> ndarray[_ShapeType, _DType_co]: ... + @property + def A1(self) -> ndarray[Any, _DType_co]: ... + @property + def H(self) -> matrix[Any, _DType_co]: ... + def getT(self) -> matrix[Any, _DType_co]: ... + def getI(self) -> matrix[Any, Any]: ... + def getA(self) -> ndarray[_ShapeType, _DType_co]: ... + def getA1(self) -> ndarray[Any, _DType_co]: ... + def getH(self) -> matrix[Any, _DType_co]: ... + +_CharType = TypeVar("_CharType", str_, bytes_) +_CharDType = TypeVar("_CharDType", dtype[str_], dtype[bytes_]) +_CharArray = chararray[Any, dtype[_CharType]] + +class chararray(ndarray[_ShapeType, _CharDType]): + @overload + def __new__( + subtype, + shape: _ShapeLike, + itemsize: SupportsIndex | SupportsInt = ..., + unicode: L[False] = ..., + buffer: _SupportsBuffer = ..., + offset: SupportsIndex = ..., + strides: _ShapeLike = ..., + order: _OrderKACF = ..., + ) -> chararray[Any, dtype[bytes_]]: ... + @overload + def __new__( + subtype, + shape: _ShapeLike, + itemsize: SupportsIndex | SupportsInt = ..., + unicode: L[True] = ..., + buffer: _SupportsBuffer = ..., + offset: SupportsIndex = ..., + strides: _ShapeLike = ..., + order: _OrderKACF = ..., + ) -> chararray[Any, dtype[str_]]: ... + + def __array_finalize__(self, obj: object) -> None: ... + def __mul__(self, other: _ArrayLikeInt_co) -> chararray[Any, _CharDType]: ... + def __rmul__(self, other: _ArrayLikeInt_co) -> chararray[Any, _CharDType]: ... + def __mod__(self, i: Any) -> chararray[Any, _CharDType]: ... + + @overload + def __eq__( + self: _CharArray[str_], + other: _ArrayLikeStr_co, + ) -> NDArray[bool_]: ... + @overload + def __eq__( + self: _CharArray[bytes_], + other: _ArrayLikeBytes_co, + ) -> NDArray[bool_]: ... + + @overload + def __ne__( + self: _CharArray[str_], + other: _ArrayLikeStr_co, + ) -> NDArray[bool_]: ... + @overload + def __ne__( + self: _CharArray[bytes_], + other: _ArrayLikeBytes_co, + ) -> NDArray[bool_]: ... + + @overload + def __ge__( + self: _CharArray[str_], + other: _ArrayLikeStr_co, + ) -> NDArray[bool_]: ... + @overload + def __ge__( + self: _CharArray[bytes_], + other: _ArrayLikeBytes_co, + ) -> NDArray[bool_]: ... + + @overload + def __le__( + self: _CharArray[str_], + other: _ArrayLikeStr_co, + ) -> NDArray[bool_]: ... + @overload + def __le__( + self: _CharArray[bytes_], + other: _ArrayLikeBytes_co, + ) -> NDArray[bool_]: ... + + @overload + def __gt__( + self: _CharArray[str_], + other: _ArrayLikeStr_co, + ) -> NDArray[bool_]: ... + @overload + def __gt__( + self: _CharArray[bytes_], + other: _ArrayLikeBytes_co, + ) -> NDArray[bool_]: ... + + @overload + def __lt__( + self: _CharArray[str_], + other: _ArrayLikeStr_co, + ) -> NDArray[bool_]: ... + @overload + def __lt__( + self: _CharArray[bytes_], + other: _ArrayLikeBytes_co, + ) -> NDArray[bool_]: ... + + @overload + def __add__( + self: _CharArray[str_], + other: _ArrayLikeStr_co, + ) -> _CharArray[str_]: ... + @overload + def __add__( + self: _CharArray[bytes_], + other: _ArrayLikeBytes_co, + ) -> _CharArray[bytes_]: ... + + @overload + def __radd__( + self: _CharArray[str_], + other: _ArrayLikeStr_co, + ) -> _CharArray[str_]: ... + @overload + def __radd__( + self: _CharArray[bytes_], + other: _ArrayLikeBytes_co, + ) -> _CharArray[bytes_]: ... + + @overload + def center( + self: _CharArray[str_], + width: _ArrayLikeInt_co, + fillchar: _ArrayLikeStr_co = ..., + ) -> _CharArray[str_]: ... + @overload + def center( + self: _CharArray[bytes_], + width: _ArrayLikeInt_co, + fillchar: _ArrayLikeBytes_co = ..., + ) -> _CharArray[bytes_]: ... + + @overload + def count( + self: _CharArray[str_], + sub: _ArrayLikeStr_co, + start: _ArrayLikeInt_co = ..., + end: None | _ArrayLikeInt_co = ..., + ) -> NDArray[int_]: ... + @overload + def count( + self: _CharArray[bytes_], + sub: _ArrayLikeBytes_co, + start: _ArrayLikeInt_co = ..., + end: None | _ArrayLikeInt_co = ..., + ) -> NDArray[int_]: ... + + def decode( + self: _CharArray[bytes_], + encoding: None | str = ..., + errors: None | str = ..., + ) -> _CharArray[str_]: ... + + def encode( + self: _CharArray[str_], + encoding: None | str = ..., + errors: None | str = ..., + ) -> _CharArray[bytes_]: ... + + @overload + def endswith( + self: _CharArray[str_], + suffix: _ArrayLikeStr_co, + start: _ArrayLikeInt_co = ..., + end: None | _ArrayLikeInt_co = ..., + ) -> NDArray[bool_]: ... + @overload + def endswith( + self: _CharArray[bytes_], + suffix: _ArrayLikeBytes_co, + start: _ArrayLikeInt_co = ..., + end: None | _ArrayLikeInt_co = ..., + ) -> NDArray[bool_]: ... + + def expandtabs( + self, + tabsize: _ArrayLikeInt_co = ..., + ) -> chararray[Any, _CharDType]: ... + + @overload + def find( + self: _CharArray[str_], + sub: _ArrayLikeStr_co, + start: _ArrayLikeInt_co = ..., + end: None | _ArrayLikeInt_co = ..., + ) -> NDArray[int_]: ... + @overload + def find( + self: _CharArray[bytes_], + sub: _ArrayLikeBytes_co, + start: _ArrayLikeInt_co = ..., + end: None | _ArrayLikeInt_co = ..., + ) -> NDArray[int_]: ... + + @overload + def index( + self: _CharArray[str_], + sub: _ArrayLikeStr_co, + start: _ArrayLikeInt_co = ..., + end: None | _ArrayLikeInt_co = ..., + ) -> NDArray[int_]: ... + @overload + def index( + self: _CharArray[bytes_], + sub: _ArrayLikeBytes_co, + start: _ArrayLikeInt_co = ..., + end: None | _ArrayLikeInt_co = ..., + ) -> NDArray[int_]: ... + + @overload + def join( + self: _CharArray[str_], + seq: _ArrayLikeStr_co, + ) -> _CharArray[str_]: ... + @overload + def join( + self: _CharArray[bytes_], + seq: _ArrayLikeBytes_co, + ) -> _CharArray[bytes_]: ... + + @overload + def ljust( + self: _CharArray[str_], + width: _ArrayLikeInt_co, + fillchar: _ArrayLikeStr_co = ..., + ) -> _CharArray[str_]: ... + @overload + def ljust( + self: _CharArray[bytes_], + width: _ArrayLikeInt_co, + fillchar: _ArrayLikeBytes_co = ..., + ) -> _CharArray[bytes_]: ... + + @overload + def lstrip( + self: _CharArray[str_], + chars: None | _ArrayLikeStr_co = ..., + ) -> _CharArray[str_]: ... + @overload + def lstrip( + self: _CharArray[bytes_], + chars: None | _ArrayLikeBytes_co = ..., + ) -> _CharArray[bytes_]: ... + + @overload + def partition( + self: _CharArray[str_], + sep: _ArrayLikeStr_co, + ) -> _CharArray[str_]: ... + @overload + def partition( + self: _CharArray[bytes_], + sep: _ArrayLikeBytes_co, + ) -> _CharArray[bytes_]: ... + + @overload + def replace( + self: _CharArray[str_], + old: _ArrayLikeStr_co, + new: _ArrayLikeStr_co, + count: None | _ArrayLikeInt_co = ..., + ) -> _CharArray[str_]: ... + @overload + def replace( + self: _CharArray[bytes_], + old: _ArrayLikeBytes_co, + new: _ArrayLikeBytes_co, + count: None | _ArrayLikeInt_co = ..., + ) -> _CharArray[bytes_]: ... + + @overload + def rfind( + self: _CharArray[str_], + sub: _ArrayLikeStr_co, + start: _ArrayLikeInt_co = ..., + end: None | _ArrayLikeInt_co = ..., + ) -> NDArray[int_]: ... + @overload + def rfind( + self: _CharArray[bytes_], + sub: _ArrayLikeBytes_co, + start: _ArrayLikeInt_co = ..., + end: None | _ArrayLikeInt_co = ..., + ) -> NDArray[int_]: ... + + @overload + def rindex( + self: _CharArray[str_], + sub: _ArrayLikeStr_co, + start: _ArrayLikeInt_co = ..., + end: None | _ArrayLikeInt_co = ..., + ) -> NDArray[int_]: ... + @overload + def rindex( + self: _CharArray[bytes_], + sub: _ArrayLikeBytes_co, + start: _ArrayLikeInt_co = ..., + end: None | _ArrayLikeInt_co = ..., + ) -> NDArray[int_]: ... + + @overload + def rjust( + self: _CharArray[str_], + width: _ArrayLikeInt_co, + fillchar: _ArrayLikeStr_co = ..., + ) -> _CharArray[str_]: ... + @overload + def rjust( + self: _CharArray[bytes_], + width: _ArrayLikeInt_co, + fillchar: _ArrayLikeBytes_co = ..., + ) -> _CharArray[bytes_]: ... + + @overload + def rpartition( + self: _CharArray[str_], + sep: _ArrayLikeStr_co, + ) -> _CharArray[str_]: ... + @overload + def rpartition( + self: _CharArray[bytes_], + sep: _ArrayLikeBytes_co, + ) -> _CharArray[bytes_]: ... + + @overload + def rsplit( + self: _CharArray[str_], + sep: None | _ArrayLikeStr_co = ..., + maxsplit: None | _ArrayLikeInt_co = ..., + ) -> NDArray[object_]: ... + @overload + def rsplit( + self: _CharArray[bytes_], + sep: None | _ArrayLikeBytes_co = ..., + maxsplit: None | _ArrayLikeInt_co = ..., + ) -> NDArray[object_]: ... + + @overload + def rstrip( + self: _CharArray[str_], + chars: None | _ArrayLikeStr_co = ..., + ) -> _CharArray[str_]: ... + @overload + def rstrip( + self: _CharArray[bytes_], + chars: None | _ArrayLikeBytes_co = ..., + ) -> _CharArray[bytes_]: ... + + @overload + def split( + self: _CharArray[str_], + sep: None | _ArrayLikeStr_co = ..., + maxsplit: None | _ArrayLikeInt_co = ..., + ) -> NDArray[object_]: ... + @overload + def split( + self: _CharArray[bytes_], + sep: None | _ArrayLikeBytes_co = ..., + maxsplit: None | _ArrayLikeInt_co = ..., + ) -> NDArray[object_]: ... + + def splitlines(self, keepends: None | _ArrayLikeBool_co = ...) -> NDArray[object_]: ... + + @overload + def startswith( + self: _CharArray[str_], + prefix: _ArrayLikeStr_co, + start: _ArrayLikeInt_co = ..., + end: None | _ArrayLikeInt_co = ..., + ) -> NDArray[bool_]: ... + @overload + def startswith( + self: _CharArray[bytes_], + prefix: _ArrayLikeBytes_co, + start: _ArrayLikeInt_co = ..., + end: None | _ArrayLikeInt_co = ..., + ) -> NDArray[bool_]: ... + + @overload + def strip( + self: _CharArray[str_], + chars: None | _ArrayLikeStr_co = ..., + ) -> _CharArray[str_]: ... + @overload + def strip( + self: _CharArray[bytes_], + chars: None | _ArrayLikeBytes_co = ..., + ) -> _CharArray[bytes_]: ... + + @overload + def translate( + self: _CharArray[str_], + table: _ArrayLikeStr_co, + deletechars: None | _ArrayLikeStr_co = ..., + ) -> _CharArray[str_]: ... + @overload + def translate( + self: _CharArray[bytes_], + table: _ArrayLikeBytes_co, + deletechars: None | _ArrayLikeBytes_co = ..., + ) -> _CharArray[bytes_]: ... + + def zfill(self, width: _ArrayLikeInt_co) -> chararray[Any, _CharDType]: ... + def capitalize(self) -> chararray[_ShapeType, _CharDType]: ... + def title(self) -> chararray[_ShapeType, _CharDType]: ... + def swapcase(self) -> chararray[_ShapeType, _CharDType]: ... + def lower(self) -> chararray[_ShapeType, _CharDType]: ... + def upper(self) -> chararray[_ShapeType, _CharDType]: ... + def isalnum(self) -> ndarray[_ShapeType, dtype[bool_]]: ... + def isalpha(self) -> ndarray[_ShapeType, dtype[bool_]]: ... + def isdigit(self) -> ndarray[_ShapeType, dtype[bool_]]: ... + def islower(self) -> ndarray[_ShapeType, dtype[bool_]]: ... + def isspace(self) -> ndarray[_ShapeType, dtype[bool_]]: ... + def istitle(self) -> ndarray[_ShapeType, dtype[bool_]]: ... + def isupper(self) -> ndarray[_ShapeType, dtype[bool_]]: ... + def isnumeric(self) -> ndarray[_ShapeType, dtype[bool_]]: ... + def isdecimal(self) -> ndarray[_ShapeType, dtype[bool_]]: ... + +# NOTE: Deprecated +# class MachAr: ... + +class _SupportsDLPack(Protocol[_T_contra]): + def __dlpack__(self, *, stream: None | _T_contra = ...) -> _PyCapsule: ... + +def from_dlpack(obj: _SupportsDLPack[None], /) -> NDArray[Any]: ... diff --git a/numpy/_distributor_init.py b/numpy/_distributor_init.py new file mode 100644 index 0000000000000000000000000000000000000000..25b0eed79fcabe6d6ad5a7b2bf45e5371f37d4a0 --- /dev/null +++ b/numpy/_distributor_init.py @@ -0,0 +1,15 @@ +""" Distributor init file + +Distributors: you can add custom code here to support particular distributions +of numpy. + +For example, this is a good place to put any BLAS/LAPACK initialization code. + +The numpy standard source distribution will not put code in this file, so you +can safely replace this file with your own version. +""" + +try: + from . import _distributor_init_local +except ImportError: + pass diff --git a/numpy/_globals.py b/numpy/_globals.py new file mode 100644 index 0000000000000000000000000000000000000000..416a20f5e11b14b1da34e2bfb45c7961edc9097c --- /dev/null +++ b/numpy/_globals.py @@ -0,0 +1,95 @@ +""" +Module defining global singleton classes. + +This module raises a RuntimeError if an attempt to reload it is made. In that +way the identities of the classes defined here are fixed and will remain so +even if numpy itself is reloaded. In particular, a function like the following +will still work correctly after numpy is reloaded:: + + def foo(arg=np._NoValue): + if arg is np._NoValue: + ... + +That was not the case when the singleton classes were defined in the numpy +``__init__.py`` file. See gh-7844 for a discussion of the reload problem that +motivated this module. + +""" +import enum + +from ._utils import set_module as _set_module + +__all__ = ['_NoValue', '_CopyMode'] + + +# Disallow reloading this module so as to preserve the identities of the +# classes defined here. +if '_is_loaded' in globals(): + raise RuntimeError('Reloading numpy._globals is not allowed') +_is_loaded = True + + +class _NoValueType: + """Special keyword value. + + The instance of this class may be used as the default value assigned to a + keyword if no other obvious default (e.g., `None`) is suitable, + + Common reasons for using this keyword are: + + - A new keyword is added to a function, and that function forwards its + inputs to another function or method which can be defined outside of + NumPy. For example, ``np.std(x)`` calls ``x.std``, so when a ``keepdims`` + keyword was added that could only be forwarded if the user explicitly + specified ``keepdims``; downstream array libraries may not have added + the same keyword, so adding ``x.std(..., keepdims=keepdims)`` + unconditionally could have broken previously working code. + - A keyword is being deprecated, and a deprecation warning must only be + emitted when the keyword is used. + + """ + __instance = None + def __new__(cls): + # ensure that only one instance exists + if not cls.__instance: + cls.__instance = super().__new__(cls) + return cls.__instance + + def __repr__(self): + return "" + + +_NoValue = _NoValueType() + + +@_set_module("numpy") +class _CopyMode(enum.Enum): + """ + An enumeration for the copy modes supported + by numpy.copy() and numpy.array(). The following three modes are supported, + + - ALWAYS: This means that a deep copy of the input + array will always be taken. + - IF_NEEDED: This means that a deep copy of the input + array will be taken only if necessary. + - NEVER: This means that the deep copy will never be taken. + If a copy cannot be avoided then a `ValueError` will be + raised. + + Note that the buffer-protocol could in theory do copies. NumPy currently + assumes an object exporting the buffer protocol will never do this. + """ + + ALWAYS = True + IF_NEEDED = False + NEVER = 2 + + def __bool__(self): + # For backwards compatibility + if self == _CopyMode.ALWAYS: + return True + + if self == _CopyMode.IF_NEEDED: + return False + + raise ValueError(f"{self} is neither True nor False.") diff --git a/numpy/_pytesttester.py b/numpy/_pytesttester.py new file mode 100644 index 0000000000000000000000000000000000000000..1c38291ae3319a08bb665fe5c86dfa13e1655a4c --- /dev/null +++ b/numpy/_pytesttester.py @@ -0,0 +1,207 @@ +""" +Pytest test running. + +This module implements the ``test()`` function for NumPy modules. The usual +boiler plate for doing that is to put the following in the module +``__init__.py`` file:: + + from numpy._pytesttester import PytestTester + test = PytestTester(__name__) + del PytestTester + + +Warnings filtering and other runtime settings should be dealt with in the +``pytest.ini`` file in the numpy repo root. The behavior of the test depends on +whether or not that file is found as follows: + +* ``pytest.ini`` is present (develop mode) + All warnings except those explicitly filtered out are raised as error. +* ``pytest.ini`` is absent (release mode) + DeprecationWarnings and PendingDeprecationWarnings are ignored, other + warnings are passed through. + +In practice, tests run from the numpy repo are run in develop mode. That +includes the standard ``python runtests.py`` invocation. + +This module is imported by every numpy subpackage, so lies at the top level to +simplify circular import issues. For the same reason, it contains no numpy +imports at module scope, instead importing numpy within function calls. +""" +import sys +import os + +__all__ = ['PytestTester'] + + +def _show_numpy_info(): + import numpy as np + + print("NumPy version %s" % np.__version__) + relaxed_strides = np.ones((10, 1), order="C").flags.f_contiguous + print("NumPy relaxed strides checking option:", relaxed_strides) + info = np.lib.utils._opt_info() + print("NumPy CPU features: ", (info if info else 'nothing enabled')) + + +class PytestTester: + """ + Pytest test runner. + + A test function is typically added to a package's __init__.py like so:: + + from numpy._pytesttester import PytestTester + test = PytestTester(__name__).test + del PytestTester + + Calling this test function finds and runs all tests associated with the + module and all its sub-modules. + + Attributes + ---------- + module_name : str + Full path to the package to test. + + Parameters + ---------- + module_name : module name + The name of the module to test. + + Notes + ----- + Unlike the previous ``nose``-based implementation, this class is not + publicly exposed as it performs some ``numpy``-specific warning + suppression. + + """ + def __init__(self, module_name): + self.module_name = module_name + + def __call__(self, label='fast', verbose=1, extra_argv=None, + doctests=False, coverage=False, durations=-1, tests=None): + """ + Run tests for module using pytest. + + Parameters + ---------- + label : {'fast', 'full'}, optional + Identifies the tests to run. When set to 'fast', tests decorated + with `pytest.mark.slow` are skipped, when 'full', the slow marker + is ignored. + verbose : int, optional + Verbosity value for test outputs, in the range 1-3. Default is 1. + extra_argv : list, optional + List with any extra arguments to pass to pytests. + doctests : bool, optional + .. note:: Not supported + coverage : bool, optional + If True, report coverage of NumPy code. Default is False. + Requires installation of (pip) pytest-cov. + durations : int, optional + If < 0, do nothing, If 0, report time of all tests, if > 0, + report the time of the slowest `timer` tests. Default is -1. + tests : test or list of tests + Tests to be executed with pytest '--pyargs' + + Returns + ------- + result : bool + Return True on success, false otherwise. + + Notes + ----- + Each NumPy module exposes `test` in its namespace to run all tests for + it. For example, to run all tests for numpy.lib: + + >>> np.lib.test() #doctest: +SKIP + + Examples + -------- + >>> result = np.lib.test() #doctest: +SKIP + ... + 1023 passed, 2 skipped, 6 deselected, 1 xfailed in 10.39 seconds + >>> result + True + + """ + import pytest + import warnings + + module = sys.modules[self.module_name] + module_path = os.path.abspath(module.__path__[0]) + + # setup the pytest arguments + pytest_args = ["-l"] + + # offset verbosity. The "-q" cancels a "-v". + pytest_args += ["-q"] + + if sys.version_info < (3, 12): + with warnings.catch_warnings(): + warnings.simplefilter("always") + # Filter out distutils cpu warnings (could be localized to + # distutils tests). ASV has problems with top level import, + # so fetch module for suppression here. + from numpy.distutils import cpuinfo + + with warnings.catch_warnings(record=True): + # Ignore the warning from importing the array_api submodule. This + # warning is done on import, so it would break pytest collection, + # but importing it early here prevents the warning from being + # issued when it imported again. + import numpy.array_api + + # Filter out annoying import messages. Want these in both develop and + # release mode. + pytest_args += [ + "-W ignore:Not importing directory", + "-W ignore:numpy.dtype size changed", + "-W ignore:numpy.ufunc size changed", + "-W ignore::UserWarning:cpuinfo", + ] + + # When testing matrices, ignore their PendingDeprecationWarnings + pytest_args += [ + "-W ignore:the matrix subclass is not", + "-W ignore:Importing from numpy.matlib is", + ] + + if doctests: + pytest_args += ["--doctest-modules"] + + if extra_argv: + pytest_args += list(extra_argv) + + if verbose > 1: + pytest_args += ["-" + "v"*(verbose - 1)] + + if coverage: + pytest_args += ["--cov=" + module_path] + + if label == "fast": + # not importing at the top level to avoid circular import of module + from numpy.testing import IS_PYPY + if IS_PYPY: + pytest_args += ["-m", "not slow and not slow_pypy"] + else: + pytest_args += ["-m", "not slow"] + + elif label != "full": + pytest_args += ["-m", label] + + if durations >= 0: + pytest_args += ["--durations=%s" % durations] + + if tests is None: + tests = [self.module_name] + + pytest_args += ["--pyargs"] + list(tests) + + # run tests. + _show_numpy_info() + + try: + code = pytest.main(pytest_args) + except SystemExit as exc: + code = exc.code + + return code == 0 diff --git a/numpy/_pytesttester.pyi b/numpy/_pytesttester.pyi new file mode 100644 index 0000000000000000000000000000000000000000..67ac87b33de164c710a25110d45545e24a06d42e --- /dev/null +++ b/numpy/_pytesttester.pyi @@ -0,0 +1,18 @@ +from collections.abc import Iterable +from typing import Literal as L + +__all__: list[str] + +class PytestTester: + module_name: str + def __init__(self, module_name: str) -> None: ... + def __call__( + self, + label: L["fast", "full"] = ..., + verbose: int = ..., + extra_argv: None | Iterable[str] = ..., + doctests: L[False] = ..., + coverage: bool = ..., + durations: int = ..., + tests: None | Iterable[str] = ..., + ) -> bool: ... diff --git a/numpy/conftest.py b/numpy/conftest.py new file mode 100644 index 0000000000000000000000000000000000000000..f1a3eda989057713f3576b60580f2d06b664873c --- /dev/null +++ b/numpy/conftest.py @@ -0,0 +1,138 @@ +""" +Pytest configuration and fixtures for the Numpy test suite. +""" +import os +import tempfile + +import hypothesis +import pytest +import numpy + +from numpy.core._multiarray_tests import get_fpu_mode + + +_old_fpu_mode = None +_collect_results = {} + +# Use a known and persistent tmpdir for hypothesis' caches, which +# can be automatically cleared by the OS or user. +hypothesis.configuration.set_hypothesis_home_dir( + os.path.join(tempfile.gettempdir(), ".hypothesis") +) + +# We register two custom profiles for Numpy - for details see +# https://hypothesis.readthedocs.io/en/latest/settings.html +# The first is designed for our own CI runs; the latter also +# forces determinism and is designed for use via np.test() +hypothesis.settings.register_profile( + name="numpy-profile", deadline=None, print_blob=True, +) +hypothesis.settings.register_profile( + name="np.test() profile", + deadline=None, print_blob=True, database=None, derandomize=True, + suppress_health_check=list(hypothesis.HealthCheck), +) +# Note that the default profile is chosen based on the presence +# of pytest.ini, but can be overridden by passing the +# --hypothesis-profile=NAME argument to pytest. +_pytest_ini = os.path.join(os.path.dirname(__file__), "..", "pytest.ini") +hypothesis.settings.load_profile( + "numpy-profile" if os.path.isfile(_pytest_ini) else "np.test() profile" +) + +# The experimentalAPI is used in _umath_tests +os.environ["NUMPY_EXPERIMENTAL_DTYPE_API"] = "1" + +def pytest_configure(config): + config.addinivalue_line("markers", + "valgrind_error: Tests that are known to error under valgrind.") + config.addinivalue_line("markers", + "leaks_references: Tests that are known to leak references.") + config.addinivalue_line("markers", + "slow: Tests that are very slow.") + config.addinivalue_line("markers", + "slow_pypy: Tests that are very slow on pypy.") + + +def pytest_addoption(parser): + parser.addoption("--available-memory", action="store", default=None, + help=("Set amount of memory available for running the " + "test suite. This can result to tests requiring " + "especially large amounts of memory to be skipped. " + "Equivalent to setting environment variable " + "NPY_AVAILABLE_MEM. Default: determined" + "automatically.")) + + +def pytest_sessionstart(session): + available_mem = session.config.getoption('available_memory') + if available_mem is not None: + os.environ['NPY_AVAILABLE_MEM'] = available_mem + + +#FIXME when yield tests are gone. +@pytest.hookimpl() +def pytest_itemcollected(item): + """ + Check FPU precision mode was not changed during test collection. + + The clumsy way we do it here is mainly necessary because numpy + still uses yield tests, which can execute code at test collection + time. + """ + global _old_fpu_mode + + mode = get_fpu_mode() + + if _old_fpu_mode is None: + _old_fpu_mode = mode + elif mode != _old_fpu_mode: + _collect_results[item] = (_old_fpu_mode, mode) + _old_fpu_mode = mode + + +@pytest.fixture(scope="function", autouse=True) +def check_fpu_mode(request): + """ + Check FPU precision mode was not changed during the test. + """ + old_mode = get_fpu_mode() + yield + new_mode = get_fpu_mode() + + if old_mode != new_mode: + raise AssertionError("FPU precision mode changed from {0:#x} to {1:#x}" + " during the test".format(old_mode, new_mode)) + + collect_result = _collect_results.get(request.node) + if collect_result is not None: + old_mode, new_mode = collect_result + raise AssertionError("FPU precision mode changed from {0:#x} to {1:#x}" + " when collecting the test".format(old_mode, + new_mode)) + + +@pytest.fixture(autouse=True) +def add_np(doctest_namespace): + doctest_namespace['np'] = numpy + +@pytest.fixture(autouse=True) +def env_setup(monkeypatch): + monkeypatch.setenv('PYTHONHASHSEED', '0') + + +@pytest.fixture(params=[True, False]) +def weak_promotion(request): + """ + Fixture to ensure "legacy" promotion state or change it to use the new + weak promotion (plus warning). `old_promotion` should be used as a + parameter in the function. + """ + state = numpy._get_promotion_state() + if request.param: + numpy._set_promotion_state("weak_and_warn") + else: + numpy._set_promotion_state("legacy") + + yield request.param + numpy._set_promotion_state(state) diff --git a/numpy/ctypeslib.py b/numpy/ctypeslib.py new file mode 100644 index 0000000000000000000000000000000000000000..d9f64fd9e716830ff33d4d787a0492c65d517603 --- /dev/null +++ b/numpy/ctypeslib.py @@ -0,0 +1,545 @@ +""" +============================ +``ctypes`` Utility Functions +============================ + +See Also +-------- +load_library : Load a C library. +ndpointer : Array restype/argtype with verification. +as_ctypes : Create a ctypes array from an ndarray. +as_array : Create an ndarray from a ctypes array. + +References +---------- +.. [1] "SciPy Cookbook: ctypes", https://scipy-cookbook.readthedocs.io/items/Ctypes.html + +Examples +-------- +Load the C library: + +>>> _lib = np.ctypeslib.load_library('libmystuff', '.') #doctest: +SKIP + +Our result type, an ndarray that must be of type double, be 1-dimensional +and is C-contiguous in memory: + +>>> array_1d_double = np.ctypeslib.ndpointer( +... dtype=np.double, +... ndim=1, flags='CONTIGUOUS') #doctest: +SKIP + +Our C-function typically takes an array and updates its values +in-place. For example:: + + void foo_func(double* x, int length) + { + int i; + for (i = 0; i < length; i++) { + x[i] = i*i; + } + } + +We wrap it using: + +>>> _lib.foo_func.restype = None #doctest: +SKIP +>>> _lib.foo_func.argtypes = [array_1d_double, c_int] #doctest: +SKIP + +Then, we're ready to call ``foo_func``: + +>>> out = np.empty(15, dtype=np.double) +>>> _lib.foo_func(out, len(out)) #doctest: +SKIP + +""" +__all__ = ['load_library', 'ndpointer', 'c_intp', 'as_ctypes', 'as_array', + 'as_ctypes_type'] + +import os +from numpy import ( + integer, ndarray, dtype as _dtype, asarray, frombuffer +) +from numpy.core.multiarray import _flagdict, flagsobj + +try: + import ctypes +except ImportError: + ctypes = None + +if ctypes is None: + def _dummy(*args, **kwds): + """ + Dummy object that raises an ImportError if ctypes is not available. + + Raises + ------ + ImportError + If ctypes is not available. + + """ + raise ImportError("ctypes is not available.") + load_library = _dummy + as_ctypes = _dummy + as_array = _dummy + from numpy import intp as c_intp + _ndptr_base = object +else: + import numpy.core._internal as nic + c_intp = nic._getintp_ctype() + del nic + _ndptr_base = ctypes.c_void_p + + # Adapted from Albert Strasheim + def load_library(libname, loader_path): + """ + It is possible to load a library using + + >>> lib = ctypes.cdll[] # doctest: +SKIP + + But there are cross-platform considerations, such as library file extensions, + plus the fact Windows will just load the first library it finds with that name. + NumPy supplies the load_library function as a convenience. + + .. versionchanged:: 1.20.0 + Allow libname and loader_path to take any + :term:`python:path-like object`. + + Parameters + ---------- + libname : path-like + Name of the library, which can have 'lib' as a prefix, + but without an extension. + loader_path : path-like + Where the library can be found. + + Returns + ------- + ctypes.cdll[libpath] : library object + A ctypes library object + + Raises + ------ + OSError + If there is no library with the expected extension, or the + library is defective and cannot be loaded. + """ + # Convert path-like objects into strings + libname = os.fsdecode(libname) + loader_path = os.fsdecode(loader_path) + + ext = os.path.splitext(libname)[1] + if not ext: + import sys + import sysconfig + # Try to load library with platform-specific name, otherwise + # default to libname.[so|dll|dylib]. Sometimes, these files are + # built erroneously on non-linux platforms. + base_ext = ".so" + if sys.platform.startswith("darwin"): + base_ext = ".dylib" + elif sys.platform.startswith("win"): + base_ext = ".dll" + libname_ext = [libname + base_ext] + so_ext = sysconfig.get_config_var("EXT_SUFFIX") + if not so_ext == base_ext: + libname_ext.insert(0, libname + so_ext) + else: + libname_ext = [libname] + + loader_path = os.path.abspath(loader_path) + if not os.path.isdir(loader_path): + libdir = os.path.dirname(loader_path) + else: + libdir = loader_path + + for ln in libname_ext: + libpath = os.path.join(libdir, ln) + if os.path.exists(libpath): + try: + return ctypes.cdll[libpath] + except OSError: + ## defective lib file + raise + ## if no successful return in the libname_ext loop: + raise OSError("no file with expected extension") + + +def _num_fromflags(flaglist): + num = 0 + for val in flaglist: + num += _flagdict[val] + return num + +_flagnames = ['C_CONTIGUOUS', 'F_CONTIGUOUS', 'ALIGNED', 'WRITEABLE', + 'OWNDATA', 'WRITEBACKIFCOPY'] +def _flags_fromnum(num): + res = [] + for key in _flagnames: + value = _flagdict[key] + if (num & value): + res.append(key) + return res + + +class _ndptr(_ndptr_base): + @classmethod + def from_param(cls, obj): + if not isinstance(obj, ndarray): + raise TypeError("argument must be an ndarray") + if cls._dtype_ is not None \ + and obj.dtype != cls._dtype_: + raise TypeError("array must have data type %s" % cls._dtype_) + if cls._ndim_ is not None \ + and obj.ndim != cls._ndim_: + raise TypeError("array must have %d dimension(s)" % cls._ndim_) + if cls._shape_ is not None \ + and obj.shape != cls._shape_: + raise TypeError("array must have shape %s" % str(cls._shape_)) + if cls._flags_ is not None \ + and ((obj.flags.num & cls._flags_) != cls._flags_): + raise TypeError("array must have flags %s" % + _flags_fromnum(cls._flags_)) + return obj.ctypes + + +class _concrete_ndptr(_ndptr): + """ + Like _ndptr, but with `_shape_` and `_dtype_` specified. + + Notably, this means the pointer has enough information to reconstruct + the array, which is not generally true. + """ + def _check_retval_(self): + """ + This method is called when this class is used as the .restype + attribute for a shared-library function, to automatically wrap the + pointer into an array. + """ + return self.contents + + @property + def contents(self): + """ + Get an ndarray viewing the data pointed to by this pointer. + + This mirrors the `contents` attribute of a normal ctypes pointer + """ + full_dtype = _dtype((self._dtype_, self._shape_)) + full_ctype = ctypes.c_char * full_dtype.itemsize + buffer = ctypes.cast(self, ctypes.POINTER(full_ctype)).contents + return frombuffer(buffer, dtype=full_dtype).squeeze(axis=0) + + +# Factory for an array-checking class with from_param defined for +# use with ctypes argtypes mechanism +_pointer_type_cache = {} +def ndpointer(dtype=None, ndim=None, shape=None, flags=None): + """ + Array-checking restype/argtypes. + + An ndpointer instance is used to describe an ndarray in restypes + and argtypes specifications. This approach is more flexible than + using, for example, ``POINTER(c_double)``, since several restrictions + can be specified, which are verified upon calling the ctypes function. + These include data type, number of dimensions, shape and flags. If a + given array does not satisfy the specified restrictions, + a ``TypeError`` is raised. + + Parameters + ---------- + dtype : data-type, optional + Array data-type. + ndim : int, optional + Number of array dimensions. + shape : tuple of ints, optional + Array shape. + flags : str or tuple of str + Array flags; may be one or more of: + + - C_CONTIGUOUS / C / CONTIGUOUS + - F_CONTIGUOUS / F / FORTRAN + - OWNDATA / O + - WRITEABLE / W + - ALIGNED / A + - WRITEBACKIFCOPY / X + + Returns + ------- + klass : ndpointer type object + A type object, which is an ``_ndtpr`` instance containing + dtype, ndim, shape and flags information. + + Raises + ------ + TypeError + If a given array does not satisfy the specified restrictions. + + Examples + -------- + >>> clib.somefunc.argtypes = [np.ctypeslib.ndpointer(dtype=np.float64, + ... ndim=1, + ... flags='C_CONTIGUOUS')] + ... #doctest: +SKIP + >>> clib.somefunc(np.array([1, 2, 3], dtype=np.float64)) + ... #doctest: +SKIP + + """ + + # normalize dtype to an Optional[dtype] + if dtype is not None: + dtype = _dtype(dtype) + + # normalize flags to an Optional[int] + num = None + if flags is not None: + if isinstance(flags, str): + flags = flags.split(',') + elif isinstance(flags, (int, integer)): + num = flags + flags = _flags_fromnum(num) + elif isinstance(flags, flagsobj): + num = flags.num + flags = _flags_fromnum(num) + if num is None: + try: + flags = [x.strip().upper() for x in flags] + except Exception as e: + raise TypeError("invalid flags specification") from e + num = _num_fromflags(flags) + + # normalize shape to an Optional[tuple] + if shape is not None: + try: + shape = tuple(shape) + except TypeError: + # single integer -> 1-tuple + shape = (shape,) + + cache_key = (dtype, ndim, shape, num) + + try: + return _pointer_type_cache[cache_key] + except KeyError: + pass + + # produce a name for the new type + if dtype is None: + name = 'any' + elif dtype.names is not None: + name = str(id(dtype)) + else: + name = dtype.str + if ndim is not None: + name += "_%dd" % ndim + if shape is not None: + name += "_"+"x".join(str(x) for x in shape) + if flags is not None: + name += "_"+"_".join(flags) + + if dtype is not None and shape is not None: + base = _concrete_ndptr + else: + base = _ndptr + + klass = type("ndpointer_%s"%name, (base,), + {"_dtype_": dtype, + "_shape_" : shape, + "_ndim_" : ndim, + "_flags_" : num}) + _pointer_type_cache[cache_key] = klass + return klass + + +if ctypes is not None: + def _ctype_ndarray(element_type, shape): + """ Create an ndarray of the given element type and shape """ + for dim in shape[::-1]: + element_type = dim * element_type + # prevent the type name include np.ctypeslib + element_type.__module__ = None + return element_type + + + def _get_scalar_type_map(): + """ + Return a dictionary mapping native endian scalar dtype to ctypes types + """ + ct = ctypes + simple_types = [ + ct.c_byte, ct.c_short, ct.c_int, ct.c_long, ct.c_longlong, + ct.c_ubyte, ct.c_ushort, ct.c_uint, ct.c_ulong, ct.c_ulonglong, + ct.c_float, ct.c_double, + ct.c_bool, + ] + return {_dtype(ctype): ctype for ctype in simple_types} + + + _scalar_type_map = _get_scalar_type_map() + + + def _ctype_from_dtype_scalar(dtype): + # swapping twice ensure that `=` is promoted to <, >, or | + dtype_with_endian = dtype.newbyteorder('S').newbyteorder('S') + dtype_native = dtype.newbyteorder('=') + try: + ctype = _scalar_type_map[dtype_native] + except KeyError as e: + raise NotImplementedError( + "Converting {!r} to a ctypes type".format(dtype) + ) from None + + if dtype_with_endian.byteorder == '>': + ctype = ctype.__ctype_be__ + elif dtype_with_endian.byteorder == '<': + ctype = ctype.__ctype_le__ + + return ctype + + + def _ctype_from_dtype_subarray(dtype): + element_dtype, shape = dtype.subdtype + ctype = _ctype_from_dtype(element_dtype) + return _ctype_ndarray(ctype, shape) + + + def _ctype_from_dtype_structured(dtype): + # extract offsets of each field + field_data = [] + for name in dtype.names: + field_dtype, offset = dtype.fields[name][:2] + field_data.append((offset, name, _ctype_from_dtype(field_dtype))) + + # ctypes doesn't care about field order + field_data = sorted(field_data, key=lambda f: f[0]) + + if len(field_data) > 1 and all(offset == 0 for offset, name, ctype in field_data): + # union, if multiple fields all at address 0 + size = 0 + _fields_ = [] + for offset, name, ctype in field_data: + _fields_.append((name, ctype)) + size = max(size, ctypes.sizeof(ctype)) + + # pad to the right size + if dtype.itemsize != size: + _fields_.append(('', ctypes.c_char * dtype.itemsize)) + + # we inserted manual padding, so always `_pack_` + return type('union', (ctypes.Union,), dict( + _fields_=_fields_, + _pack_=1, + __module__=None, + )) + else: + last_offset = 0 + _fields_ = [] + for offset, name, ctype in field_data: + padding = offset - last_offset + if padding < 0: + raise NotImplementedError("Overlapping fields") + if padding > 0: + _fields_.append(('', ctypes.c_char * padding)) + + _fields_.append((name, ctype)) + last_offset = offset + ctypes.sizeof(ctype) + + + padding = dtype.itemsize - last_offset + if padding > 0: + _fields_.append(('', ctypes.c_char * padding)) + + # we inserted manual padding, so always `_pack_` + return type('struct', (ctypes.Structure,), dict( + _fields_=_fields_, + _pack_=1, + __module__=None, + )) + + + def _ctype_from_dtype(dtype): + if dtype.fields is not None: + return _ctype_from_dtype_structured(dtype) + elif dtype.subdtype is not None: + return _ctype_from_dtype_subarray(dtype) + else: + return _ctype_from_dtype_scalar(dtype) + + + def as_ctypes_type(dtype): + r""" + Convert a dtype into a ctypes type. + + Parameters + ---------- + dtype : dtype + The dtype to convert + + Returns + ------- + ctype + A ctype scalar, union, array, or struct + + Raises + ------ + NotImplementedError + If the conversion is not possible + + Notes + ----- + This function does not losslessly round-trip in either direction. + + ``np.dtype(as_ctypes_type(dt))`` will: + + - insert padding fields + - reorder fields to be sorted by offset + - discard field titles + + ``as_ctypes_type(np.dtype(ctype))`` will: + + - discard the class names of `ctypes.Structure`\ s and + `ctypes.Union`\ s + - convert single-element `ctypes.Union`\ s into single-element + `ctypes.Structure`\ s + - insert padding fields + + """ + return _ctype_from_dtype(_dtype(dtype)) + + + def as_array(obj, shape=None): + """ + Create a numpy array from a ctypes array or POINTER. + + The numpy array shares the memory with the ctypes object. + + The shape parameter must be given if converting from a ctypes POINTER. + The shape parameter is ignored if converting from a ctypes array + """ + if isinstance(obj, ctypes._Pointer): + # convert pointers to an array of the desired shape + if shape is None: + raise TypeError( + 'as_array() requires a shape argument when called on a ' + 'pointer') + p_arr_type = ctypes.POINTER(_ctype_ndarray(obj._type_, shape)) + obj = ctypes.cast(obj, p_arr_type).contents + + return asarray(obj) + + + def as_ctypes(obj): + """Create and return a ctypes object from a numpy array. Actually + anything that exposes the __array_interface__ is accepted.""" + ai = obj.__array_interface__ + if ai["strides"]: + raise TypeError("strided arrays not supported") + if ai["version"] != 3: + raise TypeError("only __array_interface__ version 3 supported") + addr, readonly = ai["data"] + if readonly: + raise TypeError("readonly arrays unsupported") + + # can't use `_dtype((ai["typestr"], ai["shape"]))` here, as it overflows + # dtype.itemsize (gh-14214) + ctype_scalar = as_ctypes_type(ai["typestr"]) + result_type = _ctype_ndarray(ctype_scalar, ai["shape"]) + result = result_type.from_address(addr) + result.__keep = obj + return result diff --git a/numpy/ctypeslib.pyi b/numpy/ctypeslib.pyi new file mode 100644 index 0000000000000000000000000000000000000000..3edf98e143cf17e8a14fe585be75f4735b1fa6e7 --- /dev/null +++ b/numpy/ctypeslib.pyi @@ -0,0 +1,251 @@ +# NOTE: Numpy's mypy plugin is used for importing the correct +# platform-specific `ctypes._SimpleCData[int]` sub-type +from ctypes import c_int64 as _c_intp + +import os +import sys +import ctypes +from collections.abc import Iterable, Sequence +from typing import ( + Literal as L, + Any, + Union, + TypeVar, + Generic, + overload, + ClassVar, +) + +from numpy import ( + ndarray, + dtype, + generic, + bool_, + byte, + short, + intc, + int_, + longlong, + ubyte, + ushort, + uintc, + uint, + ulonglong, + single, + double, + longdouble, + void, +) +from numpy.core._internal import _ctypes +from numpy.core.multiarray import flagsobj +from numpy._typing import ( + # Arrays + NDArray, + _ArrayLike, + + # Shapes + _ShapeLike, + + # DTypes + DTypeLike, + _DTypeLike, + _VoidDTypeLike, + _BoolCodes, + _UByteCodes, + _UShortCodes, + _UIntCCodes, + _UIntCodes, + _ULongLongCodes, + _ByteCodes, + _ShortCodes, + _IntCCodes, + _IntCodes, + _LongLongCodes, + _SingleCodes, + _DoubleCodes, + _LongDoubleCodes, +) + +# TODO: Add a proper `_Shape` bound once we've got variadic typevars +_DType = TypeVar("_DType", bound=dtype[Any]) +_DTypeOptional = TypeVar("_DTypeOptional", bound=None | dtype[Any]) +_SCT = TypeVar("_SCT", bound=generic) + +_FlagsKind = L[ + 'C_CONTIGUOUS', 'CONTIGUOUS', 'C', + 'F_CONTIGUOUS', 'FORTRAN', 'F', + 'ALIGNED', 'A', + 'WRITEABLE', 'W', + 'OWNDATA', 'O', + 'WRITEBACKIFCOPY', 'X', +] + +# TODO: Add a shape typevar once we have variadic typevars (PEP 646) +class _ndptr(ctypes.c_void_p, Generic[_DTypeOptional]): + # In practice these 4 classvars are defined in the dynamic class + # returned by `ndpointer` + _dtype_: ClassVar[_DTypeOptional] + _shape_: ClassVar[None] + _ndim_: ClassVar[None | int] + _flags_: ClassVar[None | list[_FlagsKind]] + + @overload + @classmethod + def from_param(cls: type[_ndptr[None]], obj: ndarray[Any, Any]) -> _ctypes[Any]: ... + @overload + @classmethod + def from_param(cls: type[_ndptr[_DType]], obj: ndarray[Any, _DType]) -> _ctypes[Any]: ... + +class _concrete_ndptr(_ndptr[_DType]): + _dtype_: ClassVar[_DType] + _shape_: ClassVar[tuple[int, ...]] + @property + def contents(self) -> ndarray[Any, _DType]: ... + +def load_library( + libname: str | bytes | os.PathLike[str] | os.PathLike[bytes], + loader_path: str | bytes | os.PathLike[str] | os.PathLike[bytes], +) -> ctypes.CDLL: ... + +__all__: list[str] + +c_intp = _c_intp + +@overload +def ndpointer( + dtype: None = ..., + ndim: int = ..., + shape: None | _ShapeLike = ..., + flags: None | _FlagsKind | Iterable[_FlagsKind] | int | flagsobj = ..., +) -> type[_ndptr[None]]: ... +@overload +def ndpointer( + dtype: _DTypeLike[_SCT], + ndim: int = ..., + *, + shape: _ShapeLike, + flags: None | _FlagsKind | Iterable[_FlagsKind] | int | flagsobj = ..., +) -> type[_concrete_ndptr[dtype[_SCT]]]: ... +@overload +def ndpointer( + dtype: DTypeLike, + ndim: int = ..., + *, + shape: _ShapeLike, + flags: None | _FlagsKind | Iterable[_FlagsKind] | int | flagsobj = ..., +) -> type[_concrete_ndptr[dtype[Any]]]: ... +@overload +def ndpointer( + dtype: _DTypeLike[_SCT], + ndim: int = ..., + shape: None = ..., + flags: None | _FlagsKind | Iterable[_FlagsKind] | int | flagsobj = ..., +) -> type[_ndptr[dtype[_SCT]]]: ... +@overload +def ndpointer( + dtype: DTypeLike, + ndim: int = ..., + shape: None = ..., + flags: None | _FlagsKind | Iterable[_FlagsKind] | int | flagsobj = ..., +) -> type[_ndptr[dtype[Any]]]: ... + +@overload +def as_ctypes_type(dtype: _BoolCodes | _DTypeLike[bool_] | type[ctypes.c_bool]) -> type[ctypes.c_bool]: ... +@overload +def as_ctypes_type(dtype: _ByteCodes | _DTypeLike[byte] | type[ctypes.c_byte]) -> type[ctypes.c_byte]: ... +@overload +def as_ctypes_type(dtype: _ShortCodes | _DTypeLike[short] | type[ctypes.c_short]) -> type[ctypes.c_short]: ... +@overload +def as_ctypes_type(dtype: _IntCCodes | _DTypeLike[intc] | type[ctypes.c_int]) -> type[ctypes.c_int]: ... +@overload +def as_ctypes_type(dtype: _IntCodes | _DTypeLike[int_] | type[int | ctypes.c_long]) -> type[ctypes.c_long]: ... +@overload +def as_ctypes_type(dtype: _LongLongCodes | _DTypeLike[longlong] | type[ctypes.c_longlong]) -> type[ctypes.c_longlong]: ... +@overload +def as_ctypes_type(dtype: _UByteCodes | _DTypeLike[ubyte] | type[ctypes.c_ubyte]) -> type[ctypes.c_ubyte]: ... +@overload +def as_ctypes_type(dtype: _UShortCodes | _DTypeLike[ushort] | type[ctypes.c_ushort]) -> type[ctypes.c_ushort]: ... +@overload +def as_ctypes_type(dtype: _UIntCCodes | _DTypeLike[uintc] | type[ctypes.c_uint]) -> type[ctypes.c_uint]: ... +@overload +def as_ctypes_type(dtype: _UIntCodes | _DTypeLike[uint] | type[ctypes.c_ulong]) -> type[ctypes.c_ulong]: ... +@overload +def as_ctypes_type(dtype: _ULongLongCodes | _DTypeLike[ulonglong] | type[ctypes.c_ulonglong]) -> type[ctypes.c_ulonglong]: ... +@overload +def as_ctypes_type(dtype: _SingleCodes | _DTypeLike[single] | type[ctypes.c_float]) -> type[ctypes.c_float]: ... +@overload +def as_ctypes_type(dtype: _DoubleCodes | _DTypeLike[double] | type[float | ctypes.c_double]) -> type[ctypes.c_double]: ... +@overload +def as_ctypes_type(dtype: _LongDoubleCodes | _DTypeLike[longdouble] | type[ctypes.c_longdouble]) -> type[ctypes.c_longdouble]: ... +@overload +def as_ctypes_type(dtype: _VoidDTypeLike) -> type[Any]: ... # `ctypes.Union` or `ctypes.Structure` +@overload +def as_ctypes_type(dtype: str) -> type[Any]: ... + +@overload +def as_array(obj: ctypes._PointerLike, shape: Sequence[int]) -> NDArray[Any]: ... +@overload +def as_array(obj: _ArrayLike[_SCT], shape: None | _ShapeLike = ...) -> NDArray[_SCT]: ... +@overload +def as_array(obj: object, shape: None | _ShapeLike = ...) -> NDArray[Any]: ... + +@overload +def as_ctypes(obj: bool_) -> ctypes.c_bool: ... +@overload +def as_ctypes(obj: byte) -> ctypes.c_byte: ... +@overload +def as_ctypes(obj: short) -> ctypes.c_short: ... +@overload +def as_ctypes(obj: intc) -> ctypes.c_int: ... +@overload +def as_ctypes(obj: int_) -> ctypes.c_long: ... +@overload +def as_ctypes(obj: longlong) -> ctypes.c_longlong: ... +@overload +def as_ctypes(obj: ubyte) -> ctypes.c_ubyte: ... +@overload +def as_ctypes(obj: ushort) -> ctypes.c_ushort: ... +@overload +def as_ctypes(obj: uintc) -> ctypes.c_uint: ... +@overload +def as_ctypes(obj: uint) -> ctypes.c_ulong: ... +@overload +def as_ctypes(obj: ulonglong) -> ctypes.c_ulonglong: ... +@overload +def as_ctypes(obj: single) -> ctypes.c_float: ... +@overload +def as_ctypes(obj: double) -> ctypes.c_double: ... +@overload +def as_ctypes(obj: longdouble) -> ctypes.c_longdouble: ... +@overload +def as_ctypes(obj: void) -> Any: ... # `ctypes.Union` or `ctypes.Structure` +@overload +def as_ctypes(obj: NDArray[bool_]) -> ctypes.Array[ctypes.c_bool]: ... +@overload +def as_ctypes(obj: NDArray[byte]) -> ctypes.Array[ctypes.c_byte]: ... +@overload +def as_ctypes(obj: NDArray[short]) -> ctypes.Array[ctypes.c_short]: ... +@overload +def as_ctypes(obj: NDArray[intc]) -> ctypes.Array[ctypes.c_int]: ... +@overload +def as_ctypes(obj: NDArray[int_]) -> ctypes.Array[ctypes.c_long]: ... +@overload +def as_ctypes(obj: NDArray[longlong]) -> ctypes.Array[ctypes.c_longlong]: ... +@overload +def as_ctypes(obj: NDArray[ubyte]) -> ctypes.Array[ctypes.c_ubyte]: ... +@overload +def as_ctypes(obj: NDArray[ushort]) -> ctypes.Array[ctypes.c_ushort]: ... +@overload +def as_ctypes(obj: NDArray[uintc]) -> ctypes.Array[ctypes.c_uint]: ... +@overload +def as_ctypes(obj: NDArray[uint]) -> ctypes.Array[ctypes.c_ulong]: ... +@overload +def as_ctypes(obj: NDArray[ulonglong]) -> ctypes.Array[ctypes.c_ulonglong]: ... +@overload +def as_ctypes(obj: NDArray[single]) -> ctypes.Array[ctypes.c_float]: ... +@overload +def as_ctypes(obj: NDArray[double]) -> ctypes.Array[ctypes.c_double]: ... +@overload +def as_ctypes(obj: NDArray[longdouble]) -> ctypes.Array[ctypes.c_longdouble]: ... +@overload +def as_ctypes(obj: NDArray[void]) -> ctypes.Array[Any]: ... # `ctypes.Union` or `ctypes.Structure` diff --git a/numpy/dtypes.py b/numpy/dtypes.py new file mode 100644 index 0000000000000000000000000000000000000000..068a6a1a0f5b5382a7d0c4fcc2b6cd33f989fdfa --- /dev/null +++ b/numpy/dtypes.py @@ -0,0 +1,77 @@ +""" +DType classes and utility (:mod:`numpy.dtypes`) +=============================================== + +This module is home to specific dtypes related functionality and their classes. +For more general information about dtypes, also see `numpy.dtype` and +:ref:`arrays.dtypes`. + +Similar to the builtin ``types`` module, this submodule defines types (classes) +that are not widely used directly. + +.. versionadded:: NumPy 1.25 + + The dtypes module is new in NumPy 1.25. Previously DType classes were + only accessible indirectly. + + +DType classes +------------- + +The following are the classes of the corresponding NumPy dtype instances and +NumPy scalar types. The classes can be used in ``isinstance`` checks and can +also be instantiated or used directly. Direct use of these classes is not +typical, since their scalar counterparts (e.g. ``np.float64``) or strings +like ``"float64"`` can be used. + +.. list-table:: + :header-rows: 1 + + * - Group + - DType class + + * - Boolean + - ``BoolDType`` + + * - Bit-sized integers + - ``Int8DType``, ``UInt8DType``, ``Int16DType``, ``UInt16DType``, + ``Int32DType``, ``UInt32DType``, ``Int64DType``, ``UInt64DType`` + + * - C-named integers (may be aliases) + - ``ByteDType``, ``UByteDType``, ``ShortDType``, ``UShortDType``, + ``IntDType``, ``UIntDType``, ``LongDType``, ``ULongDType``, + ``LongLongDType``, ``ULongLongDType`` + + * - Floating point + - ``Float16DType``, ``Float32DType``, ``Float64DType``, + ``LongDoubleDType`` + + * - Complex + - ``Complex64DType``, ``Complex128DType``, ``CLongDoubleDType`` + + * - Strings + - ``BytesDType``, ``BytesDType`` + + * - Times + - ``DateTime64DType``, ``TimeDelta64DType`` + + * - Others + - ``ObjectDType``, ``VoidDType`` + +""" + +__all__ = [] + + +def _add_dtype_helper(DType, alias): + # Function to add DTypes a bit more conveniently without channeling them + # through `numpy.core._multiarray_umath` namespace or similar. + from numpy import dtypes + + setattr(dtypes, DType.__name__, DType) + __all__.append(DType.__name__) + + if alias: + alias = alias.removeprefix("numpy.dtypes.") + setattr(dtypes, alias, DType) + __all__.append(alias) diff --git a/numpy/dtypes.pyi b/numpy/dtypes.pyi new file mode 100644 index 0000000000000000000000000000000000000000..2f7e846f23d4de0dd7caa3198e3eb4fd339ebdbe --- /dev/null +++ b/numpy/dtypes.pyi @@ -0,0 +1,43 @@ +import numpy as np + + +__all__: list[str] + +# Boolean: +BoolDType = np.dtype[np.bool_] +# Sized integers: +Int8DType = np.dtype[np.int8] +UInt8DType = np.dtype[np.uint8] +Int16DType = np.dtype[np.int16] +UInt16DType = np.dtype[np.uint16] +Int32DType = np.dtype[np.int32] +UInt32DType = np.dtype[np.uint32] +Int64DType = np.dtype[np.int64] +UInt64DType = np.dtype[np.uint64] +# Standard C-named version/alias: +ByteDType = np.dtype[np.byte] +UByteDType = np.dtype[np.ubyte] +ShortDType = np.dtype[np.short] +UShortDType = np.dtype[np.ushort] +IntDType = np.dtype[np.intc] +UIntDType = np.dtype[np.uintc] +LongDType = np.dtype[np.int_] # Unfortunately, the correct scalar +ULongDType = np.dtype[np.uint] # Unfortunately, the correct scalar +LongLongDType = np.dtype[np.longlong] +ULongLongDType = np.dtype[np.ulonglong] +# Floats +Float16DType = np.dtype[np.float16] +Float32DType = np.dtype[np.float32] +Float64DType = np.dtype[np.float64] +LongDoubleDType = np.dtype[np.longdouble] +# Complex: +Complex64DType = np.dtype[np.complex64] +Complex128DType = np.dtype[np.complex128] +CLongDoubleDType = np.dtype[np.clongdouble] +# Others: +ObjectDType = np.dtype[np.object_] +BytesDType = np.dtype[np.bytes_] +StrDType = np.dtype[np.str_] +VoidDType = np.dtype[np.void] +DateTime64DType = np.dtype[np.datetime64] +TimeDelta64DType = np.dtype[np.timedelta64] diff --git a/numpy/exceptions.py b/numpy/exceptions.py new file mode 100644 index 0000000000000000000000000000000000000000..2f843810141a7c2d78de9ff75f5a0db9e592c981 --- /dev/null +++ b/numpy/exceptions.py @@ -0,0 +1,231 @@ +""" +Exceptions and Warnings (:mod:`numpy.exceptions`) +================================================= + +General exceptions used by NumPy. Note that some exceptions may be module +specific, such as linear algebra errors. + +.. versionadded:: NumPy 1.25 + + The exceptions module is new in NumPy 1.25. Older exceptions remain + available through the main NumPy namespace for compatibility. + +.. currentmodule:: numpy.exceptions + +Warnings +-------- +.. autosummary:: + :toctree: generated/ + + ComplexWarning Given when converting complex to real. + VisibleDeprecationWarning Same as a DeprecationWarning, but more visible. + +Exceptions +---------- +.. autosummary:: + :toctree: generated/ + + AxisError Given when an axis was invalid. + DTypePromotionError Given when no common dtype could be found. + TooHardError Error specific to `numpy.shares_memory`. + +""" + + +__all__ = [ + "ComplexWarning", "VisibleDeprecationWarning", "ModuleDeprecationWarning", + "TooHardError", "AxisError", "DTypePromotionError"] + + +# Disallow reloading this module so as to preserve the identities of the +# classes defined here. +if '_is_loaded' in globals(): + raise RuntimeError('Reloading numpy._globals is not allowed') +_is_loaded = True + + +class ComplexWarning(RuntimeWarning): + """ + The warning raised when casting a complex dtype to a real dtype. + + As implemented, casting a complex number to a real discards its imaginary + part, but this behavior may not be what the user actually wants. + + """ + pass + + +class ModuleDeprecationWarning(DeprecationWarning): + """Module deprecation warning. + + .. warning:: + + This warning should not be used, since nose testing is not relevant + anymore. + + The nose tester turns ordinary Deprecation warnings into test failures. + That makes it hard to deprecate whole modules, because they get + imported by default. So this is a special Deprecation warning that the + nose tester will let pass without making tests fail. + + """ + + +class VisibleDeprecationWarning(UserWarning): + """Visible deprecation warning. + + By default, python will not show deprecation warnings, so this class + can be used when a very visible warning is helpful, for example because + the usage is most likely a user bug. + + """ + + +# Exception used in shares_memory() +class TooHardError(RuntimeError): + """max_work was exceeded. + + This is raised whenever the maximum number of candidate solutions + to consider specified by the ``max_work`` parameter is exceeded. + Assigning a finite number to max_work may have caused the operation + to fail. + + """ + + pass + + +class AxisError(ValueError, IndexError): + """Axis supplied was invalid. + + This is raised whenever an ``axis`` parameter is specified that is larger + than the number of array dimensions. + For compatibility with code written against older numpy versions, which + raised a mixture of `ValueError` and `IndexError` for this situation, this + exception subclasses both to ensure that ``except ValueError`` and + ``except IndexError`` statements continue to catch `AxisError`. + + .. versionadded:: 1.13 + + Parameters + ---------- + axis : int or str + The out of bounds axis or a custom exception message. + If an axis is provided, then `ndim` should be specified as well. + ndim : int, optional + The number of array dimensions. + msg_prefix : str, optional + A prefix for the exception message. + + Attributes + ---------- + axis : int, optional + The out of bounds axis or ``None`` if a custom exception + message was provided. This should be the axis as passed by + the user, before any normalization to resolve negative indices. + + .. versionadded:: 1.22 + ndim : int, optional + The number of array dimensions or ``None`` if a custom exception + message was provided. + + .. versionadded:: 1.22 + + + Examples + -------- + >>> array_1d = np.arange(10) + >>> np.cumsum(array_1d, axis=1) + Traceback (most recent call last): + ... + numpy.exceptions.AxisError: axis 1 is out of bounds for array of dimension 1 + + Negative axes are preserved: + + >>> np.cumsum(array_1d, axis=-2) + Traceback (most recent call last): + ... + numpy.exceptions.AxisError: axis -2 is out of bounds for array of dimension 1 + + The class constructor generally takes the axis and arrays' + dimensionality as arguments: + + >>> print(np.AxisError(2, 1, msg_prefix='error')) + error: axis 2 is out of bounds for array of dimension 1 + + Alternatively, a custom exception message can be passed: + + >>> print(np.AxisError('Custom error message')) + Custom error message + + """ + + __slots__ = ("axis", "ndim", "_msg") + + def __init__(self, axis, ndim=None, msg_prefix=None): + if ndim is msg_prefix is None: + # single-argument form: directly set the error message + self._msg = axis + self.axis = None + self.ndim = None + else: + self._msg = msg_prefix + self.axis = axis + self.ndim = ndim + + def __str__(self): + axis = self.axis + ndim = self.ndim + + if axis is ndim is None: + return self._msg + else: + msg = f"axis {axis} is out of bounds for array of dimension {ndim}" + if self._msg is not None: + msg = f"{self._msg}: {msg}" + return msg + + +class DTypePromotionError(TypeError): + """Multiple DTypes could not be converted to a common one. + + This exception derives from ``TypeError`` and is raised whenever dtypes + cannot be converted to a single common one. This can be because they + are of a different category/class or incompatible instances of the same + one (see Examples). + + Notes + ----- + Many functions will use promotion to find the correct result and + implementation. For these functions the error will typically be chained + with a more specific error indicating that no implementation was found + for the input dtypes. + + Typically promotion should be considered "invalid" between the dtypes of + two arrays when `arr1 == arr2` can safely return all ``False`` because the + dtypes are fundamentally different. + + Examples + -------- + Datetimes and complex numbers are incompatible classes and cannot be + promoted: + + >>> np.result_type(np.dtype("M8[s]"), np.complex128) + DTypePromotionError: The DType could not + be promoted by . This means that no common + DType exists for the given inputs. For example they cannot be stored in a + single array unless the dtype is `object`. The full list of DTypes is: + (, ) + + For example for structured dtypes, the structure can mismatch and the + same ``DTypePromotionError`` is given when two structured dtypes with + a mismatch in their number of fields is given: + + >>> dtype1 = np.dtype([("field1", np.float64), ("field2", np.int64)]) + >>> dtype2 = np.dtype([("field1", np.float64)]) + >>> np.promote_types(dtype1, dtype2) + DTypePromotionError: field names `('field1', 'field2')` and `('field1',)` + mismatch. + + """ + pass diff --git a/numpy/exceptions.pyi b/numpy/exceptions.pyi new file mode 100644 index 0000000000000000000000000000000000000000..c76a0946b97b088c9f0c431eb559b5a3c86a4f6b --- /dev/null +++ b/numpy/exceptions.pyi @@ -0,0 +1,18 @@ +from typing import overload + +__all__: list[str] + +class ComplexWarning(RuntimeWarning): ... +class ModuleDeprecationWarning(DeprecationWarning): ... +class VisibleDeprecationWarning(UserWarning): ... +class TooHardError(RuntimeError): ... +class DTypePromotionError(TypeError): ... + +class AxisError(ValueError, IndexError): + axis: None | int + ndim: None | int + @overload + def __init__(self, axis: str, ndim: None = ..., msg_prefix: None = ...) -> None: ... + @overload + def __init__(self, axis: int, ndim: int, msg_prefix: None | str = ...) -> None: ... + def __str__(self) -> str: ... diff --git a/numpy/matlib.py b/numpy/matlib.py new file mode 100644 index 0000000000000000000000000000000000000000..e929fd9b1885f208afb6301f19cc21511adc098b --- /dev/null +++ b/numpy/matlib.py @@ -0,0 +1,378 @@ +import warnings + +# 2018-05-29, PendingDeprecationWarning added to matrix.__new__ +# 2020-01-23, numpy 1.19.0 PendingDeprecatonWarning +warnings.warn("Importing from numpy.matlib is deprecated since 1.19.0. " + "The matrix subclass is not the recommended way to represent " + "matrices or deal with linear algebra (see " + "https://docs.scipy.org/doc/numpy/user/numpy-for-matlab-users.html). " + "Please adjust your code to use regular ndarray. ", + PendingDeprecationWarning, stacklevel=2) + +import numpy as np +from numpy.matrixlib.defmatrix import matrix, asmatrix +# Matlib.py contains all functions in the numpy namespace with a few +# replacements. See doc/source/reference/routines.matlib.rst for details. +# Need * as we're copying the numpy namespace. +from numpy import * # noqa: F403 + +__version__ = np.__version__ + +__all__ = np.__all__[:] # copy numpy namespace +__all__ += ['rand', 'randn', 'repmat'] + +def empty(shape, dtype=None, order='C'): + """Return a new matrix of given shape and type, without initializing entries. + + Parameters + ---------- + shape : int or tuple of int + Shape of the empty matrix. + dtype : data-type, optional + Desired output data-type. + order : {'C', 'F'}, optional + Whether to store multi-dimensional data in row-major + (C-style) or column-major (Fortran-style) order in + memory. + + See Also + -------- + empty_like, zeros + + Notes + ----- + `empty`, unlike `zeros`, does not set the matrix values to zero, + and may therefore be marginally faster. On the other hand, it requires + the user to manually set all the values in the array, and should be + used with caution. + + Examples + -------- + >>> import numpy.matlib + >>> np.matlib.empty((2, 2)) # filled with random data + matrix([[ 6.76425276e-320, 9.79033856e-307], # random + [ 7.39337286e-309, 3.22135945e-309]]) + >>> np.matlib.empty((2, 2), dtype=int) + matrix([[ 6600475, 0], # random + [ 6586976, 22740995]]) + + """ + return ndarray.__new__(matrix, shape, dtype, order=order) + +def ones(shape, dtype=None, order='C'): + """ + Matrix of ones. + + Return a matrix of given shape and type, filled with ones. + + Parameters + ---------- + shape : {sequence of ints, int} + Shape of the matrix + dtype : data-type, optional + The desired data-type for the matrix, default is np.float64. + order : {'C', 'F'}, optional + Whether to store matrix in C- or Fortran-contiguous order, + default is 'C'. + + Returns + ------- + out : matrix + Matrix of ones of given shape, dtype, and order. + + See Also + -------- + ones : Array of ones. + matlib.zeros : Zero matrix. + + Notes + ----- + If `shape` has length one i.e. ``(N,)``, or is a scalar ``N``, + `out` becomes a single row matrix of shape ``(1,N)``. + + Examples + -------- + >>> np.matlib.ones((2,3)) + matrix([[1., 1., 1.], + [1., 1., 1.]]) + + >>> np.matlib.ones(2) + matrix([[1., 1.]]) + + """ + a = ndarray.__new__(matrix, shape, dtype, order=order) + a.fill(1) + return a + +def zeros(shape, dtype=None, order='C'): + """ + Return a matrix of given shape and type, filled with zeros. + + Parameters + ---------- + shape : int or sequence of ints + Shape of the matrix + dtype : data-type, optional + The desired data-type for the matrix, default is float. + order : {'C', 'F'}, optional + Whether to store the result in C- or Fortran-contiguous order, + default is 'C'. + + Returns + ------- + out : matrix + Zero matrix of given shape, dtype, and order. + + See Also + -------- + numpy.zeros : Equivalent array function. + matlib.ones : Return a matrix of ones. + + Notes + ----- + If `shape` has length one i.e. ``(N,)``, or is a scalar ``N``, + `out` becomes a single row matrix of shape ``(1,N)``. + + Examples + -------- + >>> import numpy.matlib + >>> np.matlib.zeros((2, 3)) + matrix([[0., 0., 0.], + [0., 0., 0.]]) + + >>> np.matlib.zeros(2) + matrix([[0., 0.]]) + + """ + a = ndarray.__new__(matrix, shape, dtype, order=order) + a.fill(0) + return a + +def identity(n,dtype=None): + """ + Returns the square identity matrix of given size. + + Parameters + ---------- + n : int + Size of the returned identity matrix. + dtype : data-type, optional + Data-type of the output. Defaults to ``float``. + + Returns + ------- + out : matrix + `n` x `n` matrix with its main diagonal set to one, + and all other elements zero. + + See Also + -------- + numpy.identity : Equivalent array function. + matlib.eye : More general matrix identity function. + + Examples + -------- + >>> import numpy.matlib + >>> np.matlib.identity(3, dtype=int) + matrix([[1, 0, 0], + [0, 1, 0], + [0, 0, 1]]) + + """ + a = array([1]+n*[0], dtype=dtype) + b = empty((n, n), dtype=dtype) + b.flat = a + return b + +def eye(n,M=None, k=0, dtype=float, order='C'): + """ + Return a matrix with ones on the diagonal and zeros elsewhere. + + Parameters + ---------- + n : int + Number of rows in the output. + M : int, optional + Number of columns in the output, defaults to `n`. + k : int, optional + Index of the diagonal: 0 refers to the main diagonal, + a positive value refers to an upper diagonal, + and a negative value to a lower diagonal. + dtype : dtype, optional + Data-type of the returned matrix. + order : {'C', 'F'}, optional + Whether the output should be stored in row-major (C-style) or + column-major (Fortran-style) order in memory. + + .. versionadded:: 1.14.0 + + Returns + ------- + I : matrix + A `n` x `M` matrix where all elements are equal to zero, + except for the `k`-th diagonal, whose values are equal to one. + + See Also + -------- + numpy.eye : Equivalent array function. + identity : Square identity matrix. + + Examples + -------- + >>> import numpy.matlib + >>> np.matlib.eye(3, k=1, dtype=float) + matrix([[0., 1., 0.], + [0., 0., 1.], + [0., 0., 0.]]) + + """ + return asmatrix(np.eye(n, M=M, k=k, dtype=dtype, order=order)) + +def rand(*args): + """ + Return a matrix of random values with given shape. + + Create a matrix of the given shape and propagate it with + random samples from a uniform distribution over ``[0, 1)``. + + Parameters + ---------- + \\*args : Arguments + Shape of the output. + If given as N integers, each integer specifies the size of one + dimension. + If given as a tuple, this tuple gives the complete shape. + + Returns + ------- + out : ndarray + The matrix of random values with shape given by `\\*args`. + + See Also + -------- + randn, numpy.random.RandomState.rand + + Examples + -------- + >>> np.random.seed(123) + >>> import numpy.matlib + >>> np.matlib.rand(2, 3) + matrix([[0.69646919, 0.28613933, 0.22685145], + [0.55131477, 0.71946897, 0.42310646]]) + >>> np.matlib.rand((2, 3)) + matrix([[0.9807642 , 0.68482974, 0.4809319 ], + [0.39211752, 0.34317802, 0.72904971]]) + + If the first argument is a tuple, other arguments are ignored: + + >>> np.matlib.rand((2, 3), 4) + matrix([[0.43857224, 0.0596779 , 0.39804426], + [0.73799541, 0.18249173, 0.17545176]]) + + """ + if isinstance(args[0], tuple): + args = args[0] + return asmatrix(np.random.rand(*args)) + +def randn(*args): + """ + Return a random matrix with data from the "standard normal" distribution. + + `randn` generates a matrix filled with random floats sampled from a + univariate "normal" (Gaussian) distribution of mean 0 and variance 1. + + Parameters + ---------- + \\*args : Arguments + Shape of the output. + If given as N integers, each integer specifies the size of one + dimension. If given as a tuple, this tuple gives the complete shape. + + Returns + ------- + Z : matrix of floats + A matrix of floating-point samples drawn from the standard normal + distribution. + + See Also + -------- + rand, numpy.random.RandomState.randn + + Notes + ----- + For random samples from the normal distribution with mean ``mu`` and + standard deviation ``sigma``, use:: + + sigma * np.matlib.randn(...) + mu + + Examples + -------- + >>> np.random.seed(123) + >>> import numpy.matlib + >>> np.matlib.randn(1) + matrix([[-1.0856306]]) + >>> np.matlib.randn(1, 2, 3) + matrix([[ 0.99734545, 0.2829785 , -1.50629471], + [-0.57860025, 1.65143654, -2.42667924]]) + + Two-by-four matrix of samples from the normal distribution with + mean 3 and standard deviation 2.5: + + >>> 2.5 * np.matlib.randn((2, 4)) + 3 + matrix([[1.92771843, 6.16484065, 0.83314899, 1.30278462], + [2.76322758, 6.72847407, 1.40274501, 1.8900451 ]]) + + """ + if isinstance(args[0], tuple): + args = args[0] + return asmatrix(np.random.randn(*args)) + +def repmat(a, m, n): + """ + Repeat a 0-D to 2-D array or matrix MxN times. + + Parameters + ---------- + a : array_like + The array or matrix to be repeated. + m, n : int + The number of times `a` is repeated along the first and second axes. + + Returns + ------- + out : ndarray + The result of repeating `a`. + + Examples + -------- + >>> import numpy.matlib + >>> a0 = np.array(1) + >>> np.matlib.repmat(a0, 2, 3) + array([[1, 1, 1], + [1, 1, 1]]) + + >>> a1 = np.arange(4) + >>> np.matlib.repmat(a1, 2, 2) + array([[0, 1, 2, 3, 0, 1, 2, 3], + [0, 1, 2, 3, 0, 1, 2, 3]]) + + >>> a2 = np.asmatrix(np.arange(6).reshape(2, 3)) + >>> np.matlib.repmat(a2, 2, 3) + matrix([[0, 1, 2, 0, 1, 2, 0, 1, 2], + [3, 4, 5, 3, 4, 5, 3, 4, 5], + [0, 1, 2, 0, 1, 2, 0, 1, 2], + [3, 4, 5, 3, 4, 5, 3, 4, 5]]) + + """ + a = asanyarray(a) + ndim = a.ndim + if ndim == 0: + origrows, origcols = (1, 1) + elif ndim == 1: + origrows, origcols = (1, a.shape[0]) + else: + origrows, origcols = a.shape + rows = origrows * m + cols = origcols * n + c = a.reshape(1, a.size).repeat(m, 0).reshape(rows, origcols).repeat(n, 0) + return c.reshape(rows, cols) diff --git a/numpy/py.typed b/numpy/py.typed new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/numpy/version.py b/numpy/version.py new file mode 100644 index 0000000000000000000000000000000000000000..fb108fcb4742144d1255ea5f3364fb6cb1c1752f --- /dev/null +++ b/numpy/version.py @@ -0,0 +1,8 @@ + +version = "1.26.4" +__version__ = version +full_version = version + +git_revision = "9815c16f449e12915ef35a8255329ba26dacd5c0" +release = 'dev' not in version and '+' not in version +short_version = version.split("+")[0] diff --git a/nvidia/__init__.py b/nvidia/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/nvidia_cuda_runtime_cu12-12.8.90.dist-info/INSTALLER b/nvidia_cuda_runtime_cu12-12.8.90.dist-info/INSTALLER new file mode 100644 index 0000000000000000000000000000000000000000..5c69047b2eb8235994febeeae1da4a82365a240a --- /dev/null +++ b/nvidia_cuda_runtime_cu12-12.8.90.dist-info/INSTALLER @@ -0,0 +1 @@ +uv \ No newline at end of file diff --git a/nvidia_cuda_runtime_cu12-12.8.90.dist-info/License.txt b/nvidia_cuda_runtime_cu12-12.8.90.dist-info/License.txt new file mode 100644 index 0000000000000000000000000000000000000000..b491c70e0aef319022ded661e111ddbd45b8a17f --- /dev/null +++ b/nvidia_cuda_runtime_cu12-12.8.90.dist-info/License.txt @@ -0,0 +1,1568 @@ +End User License Agreement +-------------------------- + + +Preface +------- + +The Software License Agreement in Chapter 1 and the Supplement +in Chapter 2 contain license terms and conditions that govern +the use of NVIDIA software. 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CUDA Toolkit Supplement to Software License Agreement for +NVIDIA Software Development Kits +------------------------------------------------------------ + + +Release date: August 16, 2018 +----------------------------- + +The terms in this supplement govern your use of the NVIDIA +CUDA Toolkit SDK under the terms of your license agreement +(“Agreement”) as modified by this supplement. Capitalized +terms used but not defined below have the meaning assigned to +them in the Agreement. + +This supplement is an exhibit to the Agreement and is +incorporated as an integral part of the Agreement. In the +event of conflict between the terms in this supplement and the +terms in the Agreement, the terms in this supplement govern. + + +2.1. License Scope + +The SDK is licensed for you to develop applications only for +use in systems with NVIDIA GPUs. + + +2.2. Distribution + +The portions of the SDK that are distributable under the +Agreement are listed in Attachment A. + + +2.3. 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NVIDIA does not grant to you +under this Agreement any necessary patent or other rights with +respect to any audio and/or video encoders and decoders. + + +2.5. Licensing + +If the distribution terms in this Agreement are not suitable +for your organization, or for any questions regarding this +Agreement, please contact NVIDIA at +nvidia-compute-license-questions@nvidia.com. + + +2.6. Attachment A + +The following portions of the SDK are distributable under the +Agreement: + +Component + +CUDA Runtime + +Windows + +cudart.dll, cudart_static.lib, cudadevrt.lib + +Mac OSX + +libcudart.dylib, libcudart_static.a, libcudadevrt.a + +Linux + +libcudart.so, libcudart_static.a, libcudadevrt.a + +Android + +libcudart.so, libcudart_static.a, libcudadevrt.a + +Component + +CUDA FFT Library + +Windows + +cufft.dll, cufftw.dll, cufft.lib, cufftw.lib + +Mac OSX + +libcufft.dylib, libcufft_static.a, libcufftw.dylib, +libcufftw_static.a + +Linux + +libcufft.so, libcufft_static.a, libcufftw.so, +libcufftw_static.a + +Android + +libcufft.so, libcufft_static.a, libcufftw.so, +libcufftw_static.a + +Component + +CUDA BLAS Library + +Windows + +cublas.dll, cublasLt.dll + +Mac OSX + +libcublas.dylib, libcublasLt.dylib, libcublas_static.a, +libcublasLt_static.a + +Linux + +libcublas.so, libcublasLt.so, libcublas_static.a, +libcublasLt_static.a + +Android + +libcublas.so, libcublasLt.so, libcublas_static.a, +libcublasLt_static.a + +Component + +NVIDIA "Drop-in" BLAS Library + +Windows + +nvblas.dll + +Mac OSX + +libnvblas.dylib + +Linux + +libnvblas.so + +Component + +CUDA Sparse Matrix Library + +Windows + +cusparse.dll, cusparse.lib + +Mac OSX + +libcusparse.dylib, libcusparse_static.a + +Linux + +libcusparse.so, libcusparse_static.a + +Android + +libcusparse.so, libcusparse_static.a + +Component + +CUDA Linear Solver Library + +Windows + +cusolver.dll, cusolver.lib + +Mac OSX + +libcusolver.dylib, libcusolver_static.a + +Linux + +libcusolver.so, libcusolver_static.a + +Android + +libcusolver.so, libcusolver_static.a + +Component + +CUDA Random Number Generation Library + +Windows + +curand.dll, curand.lib + +Mac OSX + +libcurand.dylib, libcurand_static.a + +Linux + +libcurand.so, libcurand_static.a + +Android + +libcurand.so, libcurand_static.a + +Component + +CUDA Accelerated Graph Library + +Component + +NVIDIA Performance Primitives Library + +Windows + +nppc.dll, nppc.lib, nppial.dll, nppial.lib, nppicc.dll, +nppicc.lib, nppicom.dll, nppicom.lib, nppidei.dll, +nppidei.lib, nppif.dll, nppif.lib, nppig.dll, nppig.lib, +nppim.dll, nppim.lib, nppist.dll, nppist.lib, nppisu.dll, +nppisu.lib, nppitc.dll, nppitc.lib, npps.dll, npps.lib + +Mac OSX + +libnppc.dylib, libnppc_static.a, libnppial.dylib, +libnppial_static.a, libnppicc.dylib, libnppicc_static.a, +libnppicom.dylib, libnppicom_static.a, libnppidei.dylib, +libnppidei_static.a, libnppif.dylib, libnppif_static.a, +libnppig.dylib, libnppig_static.a, libnppim.dylib, +libnppisu_static.a, libnppitc.dylib, libnppitc_static.a, +libnpps.dylib, libnpps_static.a + +Linux + +libnppc.so, libnppc_static.a, libnppial.so, +libnppial_static.a, libnppicc.so, libnppicc_static.a, +libnppicom.so, libnppicom_static.a, libnppidei.so, +libnppidei_static.a, libnppif.so, libnppif_static.a +libnppig.so, libnppig_static.a, libnppim.so, +libnppim_static.a, libnppist.so, libnppist_static.a, +libnppisu.so, libnppisu_static.a, libnppitc.so +libnppitc_static.a, libnpps.so, libnpps_static.a + +Android + +libnppc.so, libnppc_static.a, libnppial.so, +libnppial_static.a, libnppicc.so, libnppicc_static.a, +libnppicom.so, libnppicom_static.a, libnppidei.so, +libnppidei_static.a, libnppif.so, libnppif_static.a +libnppig.so, libnppig_static.a, libnppim.so, +libnppim_static.a, libnppist.so, libnppist_static.a, +libnppisu.so, libnppisu_static.a, libnppitc.so +libnppitc_static.a, libnpps.so, libnpps_static.a + +Component + +NVIDIA JPEG Library + +Linux + +libnvjpeg.so, libnvjpeg_static.a + +Component + +Internal common library required for statically linking to +cuBLAS, cuSPARSE, cuFFT, cuRAND, nvJPEG and NPP + +Mac OSX + +libculibos.a + +Linux + +libculibos.a + +Component + +NVIDIA Runtime Compilation Library and Header + +All + +nvrtc.h + +Windows + +nvrtc.dll, nvrtc-builtins.dll + +Mac OSX + +libnvrtc.dylib, libnvrtc-builtins.dylib + +Linux + +libnvrtc.so, libnvrtc-builtins.so + +Component + +NVIDIA Optimizing Compiler Library + +Windows + +nvvm.dll + +Mac OSX + +libnvvm.dylib + +Linux + +libnvvm.so + +Component + +NVIDIA Common Device Math Functions Library + +Windows + +libdevice.10.bc + +Mac OSX + +libdevice.10.bc + +Linux + +libdevice.10.bc + +Component + +CUDA Occupancy Calculation Header Library + +All + +cuda_occupancy.h + +Component + +CUDA Half Precision Headers + +All + +cuda_fp16.h, cuda_fp16.hpp + +Component + +CUDA Profiling Tools Interface (CUPTI) Library + +Windows + +cupti.dll + +Mac OSX + +libcupti.dylib + +Linux + +libcupti.so + +Component + +NVIDIA Tools Extension Library + +Windows + +nvToolsExt.dll, nvToolsExt.lib + +Mac OSX + +libnvToolsExt.dylib + +Linux + +libnvToolsExt.so + +Component + +NVIDIA CUDA Driver Libraries + +Linux + +libcuda.so, libnvidia-fatbinaryloader.so, +libnvidia-ptxjitcompiler.so + +The NVIDIA CUDA Driver Libraries are only distributable in +applications that meet this criteria: + + 1. The application was developed starting from a NVIDIA CUDA + container obtained from Docker Hub or the NVIDIA GPU + Cloud, and + + 2. The resulting application is packaged as a Docker + container and distributed to users on Docker Hub or the + NVIDIA GPU Cloud only. + + +2.7. Attachment B + + +Additional Licensing Obligations + +The following third party components included in the SOFTWARE +are licensed to Licensee pursuant to the following terms and +conditions: + + 1. Licensee's use of the GDB third party component is + subject to the terms and conditions of GNU GPL v3: + + This product includes copyrighted third-party software licensed + under the terms of the GNU General Public License v3 ("GPL v3"). + All third-party software packages are copyright by their respective + authors. GPL v3 terms and conditions are hereby incorporated into + the Agreement by this reference: http://www.gnu.org/licenses/gpl.txt + + Consistent with these licensing requirements, the software + listed below is provided under the terms of the specified + open source software licenses. To obtain source code for + software provided under licenses that require + redistribution of source code, including the GNU General + Public License (GPL) and GNU Lesser General Public License + (LGPL), contact oss-requests@nvidia.com. This offer is + valid for a period of three (3) years from the date of the + distribution of this product by NVIDIA CORPORATION. + + Component License + CUDA-GDB GPL v3 + + 2. Licensee represents and warrants that any and all third + party licensing and/or royalty payment obligations in + connection with Licensee's use of the H.264 video codecs + are solely the responsibility of Licensee. + + 3. Licensee's use of the Thrust library is subject to the + terms and conditions of the Apache License Version 2.0. + All third-party software packages are copyright by their + respective authors. Apache License Version 2.0 terms and + conditions are hereby incorporated into the Agreement by + this reference. + http://www.apache.org/licenses/LICENSE-2.0.html + + In addition, Licensee acknowledges the following notice: + Thrust includes source code from the Boost Iterator, + Tuple, System, and Random Number libraries. + + Boost Software License - Version 1.0 - August 17th, 2003 + . . . . + + Permission is hereby granted, free of charge, to any person or + organization obtaining a copy of the software and accompanying + documentation covered by this license (the "Software") to use, + reproduce, display, distribute, execute, and transmit the Software, + and to prepare derivative works of the Software, and to permit + third-parties to whom the Software is furnished to do so, all + subject to the following: + + The copyright notices in the Software and this entire statement, + including the above license grant, this restriction and the following + disclaimer, must be included in all copies of the Software, in whole + or in part, and all derivative works of the Software, unless such + copies or derivative works are solely in the form of machine-executable + object code generated by a source language processor. + + THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, + EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF + MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, TITLE AND + NON-INFRINGEMENT. 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Licensee's use of the LLVM third party component is + subject to the following terms and conditions: + + ====================================================== + LLVM Release License + ====================================================== + University of Illinois/NCSA + Open Source License + + Copyright (c) 2003-2010 University of Illinois at Urbana-Champaign. + All rights reserved. + + Developed by: + + LLVM Team + + University of Illinois at Urbana-Champaign + + http://llvm.org + + Permission is hereby granted, free of charge, to any person obtaining a copy + of this software and associated documentation files (the "Software"), to + deal with the Software without restriction, including without limitation the + rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + sell copies of the Software, and to permit persons to whom the Software is + furnished to do so, subject to the following conditions: + + * Redistributions of source code must retain the above copyright notice, + this list of conditions and the following disclaimers. + + * Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimers in the + documentation and/or other materials provided with the distribution. + + * Neither the names of the LLVM Team, University of Illinois at Urbana- + Champaign, nor the names of its contributors may be used to endorse or + promote products derived from this Software without specific prior + written permission. + + THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL + THE CONTRIBUTORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR + OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, + ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER + DEALINGS WITH THE SOFTWARE. + + 5. Licensee's use (e.g. nvprof) of the PCRE third party + component is subject to the following terms and + conditions: + + ------------ + PCRE LICENCE + ------------ + PCRE is a library of functions to support regular expressions whose syntax + and semantics are as close as possible to those of the Perl 5 language. + Release 8 of PCRE is distributed under the terms of the "BSD" licence, as + specified below. The documentation for PCRE, supplied in the "doc" + directory, is distributed under the same terms as the software itself. The + basic library functions are written in C and are freestanding. Also + included in the distribution is a set of C++ wrapper functions, and a just- + in-time compiler that can be used to optimize pattern matching. These are + both optional features that can be omitted when the library is built. + + THE BASIC LIBRARY FUNCTIONS + --------------------------- + Written by: Philip Hazel + Email local part: ph10 + Email domain: cam.ac.uk + University of Cambridge Computing Service, + Cambridge, England. + Copyright (c) 1997-2012 University of Cambridge + All rights reserved. + + PCRE JUST-IN-TIME COMPILATION SUPPORT + ------------------------------------- + Written by: Zoltan Herczeg + Email local part: hzmester + Emain domain: freemail.hu + Copyright(c) 2010-2012 Zoltan Herczeg + All rights reserved. + + STACK-LESS JUST-IN-TIME COMPILER + -------------------------------- + Written by: Zoltan Herczeg + Email local part: hzmester + Emain domain: freemail.hu + Copyright(c) 2009-2012 Zoltan Herczeg + All rights reserved. + + THE C++ WRAPPER FUNCTIONS + ------------------------- + Contributed by: Google Inc. + Copyright (c) 2007-2012, Google Inc. + All rights reserved. + + THE "BSD" LICENCE + ----------------- + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, + this list of conditions and the following disclaimer. + + * Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + + * Neither the name of the University of Cambridge nor the name of Google + Inc. nor the names of their contributors may be used to endorse or + promote products derived from this software without specific prior + written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" + AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE + IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE + ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE + LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR + CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF + SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS + INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN + CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) + ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE + POSSIBILITY OF SUCH DAMAGE. + + 6. Some of the cuBLAS library routines were written by or + derived from code written by Vasily Volkov and are subject + to the Modified Berkeley Software Distribution License as + follows: + + Copyright (c) 2007-2009, Regents of the University of California + + All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are + met: + * Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above + copyright notice, this list of conditions and the following + disclaimer in the documentation and/or other materials provided + with the distribution. + * Neither the name of the University of California, Berkeley nor + the names of its contributors may be used to endorse or promote + products derived from this software without specific prior + written permission. + + THIS SOFTWARE IS PROVIDED BY THE AUTHOR "AS IS" AND ANY EXPRESS OR + IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, + INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR + SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) + HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, + STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING + IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE + POSSIBILITY OF SUCH DAMAGE. + + 7. Some of the cuBLAS library routines were written by or + derived from code written by Davide Barbieri and are + subject to the Modified Berkeley Software Distribution + License as follows: + + Copyright (c) 2008-2009 Davide Barbieri @ University of Rome Tor Vergata. + + All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are + met: + * Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above + copyright notice, this list of conditions and the following + disclaimer in the documentation and/or other materials provided + with the distribution. + * The name of the author may not be used to endorse or promote + products derived from this software without specific prior + written permission. + + THIS SOFTWARE IS PROVIDED BY THE AUTHOR "AS IS" AND ANY EXPRESS OR + IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, + INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR + SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) + HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, + STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING + IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE + POSSIBILITY OF SUCH DAMAGE. + + 8. Some of the cuBLAS library routines were derived from + code developed by the University of Tennessee and are + subject to the Modified Berkeley Software Distribution + License as follows: + + Copyright (c) 2010 The University of Tennessee. + + All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are + met: + * Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above + copyright notice, this list of conditions and the following + disclaimer listed in this license in the documentation and/or + other materials provided with the distribution. + * Neither the name of the copyright holders nor the names of its + contributors may be used to endorse or promote products derived + from this software without specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT + OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, + SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT + LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE + OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + 9. Some of the cuBLAS library routines were written by or + derived from code written by Jonathan Hogg and are subject + to the Modified Berkeley Software Distribution License as + follows: + + Copyright (c) 2012, The Science and Technology Facilities Council (STFC). + + All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are + met: + * Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above + copyright notice, this list of conditions and the following + disclaimer in the documentation and/or other materials provided + with the distribution. + * Neither the name of the STFC nor the names of its contributors + may be used to endorse or promote products derived from this + software without specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE STFC BE + LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR + CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF + SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR + BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, + WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE + OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN + IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + 10. Some of the cuBLAS library routines were written by or + derived from code written by Ahmad M. Abdelfattah, David + Keyes, and Hatem Ltaief, and are subject to the Apache + License, Version 2.0, as follows: + + -- (C) Copyright 2013 King Abdullah University of Science and Technology + Authors: + Ahmad Abdelfattah (ahmad.ahmad@kaust.edu.sa) + David Keyes (david.keyes@kaust.edu.sa) + Hatem Ltaief (hatem.ltaief@kaust.edu.sa) + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions + are met: + + * Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + * Neither the name of the King Abdullah University of Science and + Technology nor the names of its contributors may be used to endorse + or promote products derived from this software without specific prior + written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT + HOLDERS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, + SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT + LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE + OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE + + 11. Some of the cuSPARSE library routines were written by or + derived from code written by Li-Wen Chang and are subject + to the NCSA Open Source License as follows: + + Copyright (c) 2012, University of Illinois. + + All rights reserved. + + Developed by: IMPACT Group, University of Illinois, http://impact.crhc.illinois.edu + + Permission is hereby granted, free of charge, to any person obtaining + a copy of this software and associated documentation files (the + "Software"), to deal with the Software without restriction, including + without limitation the rights to use, copy, modify, merge, publish, + distribute, sublicense, and/or sell copies of the Software, and to + permit persons to whom the Software is furnished to do so, subject to + the following conditions: + * Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above + copyright notice, this list of conditions and the following + disclaimers in the documentation and/or other materials provided + with the distribution. + * Neither the names of IMPACT Group, University of Illinois, nor + the names of its contributors may be used to endorse or promote + products derived from this Software without specific prior + written permission. + + THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, + EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF + MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND + NONINFRINGEMENT. IN NO EVENT SHALL THE CONTRIBUTORS OR COPYRIGHT + HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER + IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR + IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS WITH THE + SOFTWARE. + + 12. Some of the cuRAND library routines were written by or + derived from code written by Mutsuo Saito and Makoto + Matsumoto and are subject to the following license: + + Copyright (c) 2009, 2010 Mutsuo Saito, Makoto Matsumoto and Hiroshima + University. All rights reserved. + + Copyright (c) 2011 Mutsuo Saito, Makoto Matsumoto, Hiroshima + University and University of Tokyo. All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are + met: + * Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above + copyright notice, this list of conditions and the following + disclaimer in the documentation and/or other materials provided + with the distribution. + * Neither the name of the Hiroshima University nor the names of + its contributors may be used to endorse or promote products + derived from this software without specific prior written + permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT + OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, + SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT + LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE + OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + 13. Some of the cuRAND library routines were derived from + code developed by D. E. Shaw Research and are subject to + the following license: + + Copyright 2010-2011, D. E. Shaw Research. + + All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are + met: + * Redistributions of source code must retain the above copyright + notice, this list of conditions, and the following disclaimer. + * Redistributions in binary form must reproduce the above + copyright notice, this list of conditions, and the following + disclaimer in the documentation and/or other materials provided + with the distribution. + * Neither the name of D. E. Shaw Research nor the names of its + contributors may be used to endorse or promote products derived + from this software without specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT + OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, + SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT + LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE + OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + 14. Some of the Math library routines were written by or + derived from code developed by Norbert Juffa and are + subject to the following license: + + Copyright (c) 2015-2017, Norbert Juffa + All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions + are met: + + 1. Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + + 2. Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + A PARTICULAR PURPOSE ARE DISCLAIMED. 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The DX12-CUDA sample uses the d3dx12.h header, which is + subject to the MIT license . + +----------------- diff --git a/nvidia_cuda_runtime_cu12-12.8.90.dist-info/METADATA b/nvidia_cuda_runtime_cu12-12.8.90.dist-info/METADATA new file mode 100644 index 0000000000000000000000000000000000000000..14b471170862b26f1dc2b83800d568d5c38533ec --- /dev/null +++ b/nvidia_cuda_runtime_cu12-12.8.90.dist-info/METADATA @@ -0,0 +1,44 @@ +Metadata-Version: 2.2 +Name: nvidia-cuda-runtime-cu12 +Version: 12.8.90 +Summary: CUDA Runtime native Libraries +Home-page: https://developer.nvidia.com/cuda-zone +Author: Nvidia CUDA Installer Team +Author-email: compute_installer@nvidia.com +License: NVIDIA Proprietary Software +Keywords: cuda,nvidia,runtime,machine learning,deep learning +Classifier: Development Status :: 4 - Beta +Classifier: Intended Audience :: Developers +Classifier: Intended Audience :: Education +Classifier: Intended Audience :: Science/Research +Classifier: License :: Other/Proprietary License +Classifier: Natural Language :: English +Classifier: Programming Language :: Python :: 3 +Classifier: Programming Language :: Python :: 3.5 +Classifier: Programming Language :: Python :: 3.6 +Classifier: Programming Language :: Python :: 3.7 +Classifier: Programming Language :: Python :: 3.8 +Classifier: Programming Language :: Python :: 3.9 +Classifier: Programming Language :: Python :: 3.10 +Classifier: Programming Language :: Python :: 3.11 +Classifier: Programming Language :: Python :: 3 :: Only +Classifier: Topic :: Scientific/Engineering +Classifier: Topic :: Scientific/Engineering :: Mathematics +Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence +Classifier: Topic :: Software Development +Classifier: Topic :: Software Development :: Libraries +Classifier: Operating System :: Microsoft :: Windows +Classifier: Operating System :: POSIX :: Linux +Requires-Python: >=3 +License-File: License.txt +Dynamic: author +Dynamic: author-email +Dynamic: 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Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND +ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED +WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE +DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE +FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL +DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR +SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER +CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, +OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE +OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.A. HISTORY OF THE SOFTWARE +========================== + +Python was created in the early 1990s by Guido van Rossum at Stichting +Mathematisch Centrum (CWI, see https://www.cwi.nl) in the Netherlands +as a successor of a language called ABC. Guido remains Python's +principal author, although it includes many contributions from others. + +In 1995, Guido continued his work on Python at the Corporation for +National Research Initiatives (CNRI, see https://www.cnri.reston.va.us) +in Reston, Virginia where he released several versions of the +software. + +In May 2000, Guido and the Python core development team moved to +BeOpen.com to form the BeOpen PythonLabs team. In October of the same +year, the PythonLabs team moved to Digital Creations, which became +Zope Corporation. In 2001, the Python Software Foundation (PSF, see +https://www.python.org/psf/) was formed, a non-profit organization +created specifically to own Python-related Intellectual Property. +Zope Corporation was a sponsoring member of the PSF. + +All Python releases are Open Source (see https://opensource.org for +the Open Source Definition). Historically, most, but not all, Python +releases have also been GPL-compatible; the table below summarizes +the various releases. + + Release Derived Year Owner GPL- + from compatible? (1) + + 0.9.0 thru 1.2 1991-1995 CWI yes + 1.3 thru 1.5.2 1.2 1995-1999 CNRI yes + 1.6 1.5.2 2000 CNRI no + 2.0 1.6 2000 BeOpen.com no + 1.6.1 1.6 2001 CNRI yes (2) + 2.1 2.0+1.6.1 2001 PSF no + 2.0.1 2.0+1.6.1 2001 PSF yes + 2.1.1 2.1+2.0.1 2001 PSF yes + 2.1.2 2.1.1 2002 PSF yes + 2.1.3 2.1.2 2002 PSF yes + 2.2 and above 2.1.1 2001-now PSF yes + +Footnotes: + +(1) GPL-compatible doesn't mean that we're distributing Python under + the GPL. All Python licenses, unlike the GPL, let you distribute + a modified version without making your changes open source. The + GPL-compatible licenses make it possible to combine Python with + other software that is released under the GPL; the others don't. + +(2) According to Richard Stallman, 1.6.1 is not GPL-compatible, + because its license has a choice of law clause. According to + CNRI, however, Stallman's lawyer has told CNRI's lawyer that 1.6.1 + is "not incompatible" with the GPL. + +Thanks to the many outside volunteers who have worked under Guido's +direction to make these releases possible. + + +B. TERMS AND CONDITIONS FOR ACCESSING OR OTHERWISE USING PYTHON +=============================================================== + +Python software and documentation are licensed under the +Python Software Foundation License Version 2. + +Starting with Python 3.8.6, examples, recipes, and other code in +the documentation are dual licensed under the PSF License Version 2 +and the Zero-Clause BSD license. + +Some software incorporated into Python is under different licenses. +The licenses are listed with code falling under that license. + + +PYTHON SOFTWARE FOUNDATION LICENSE VERSION 2 +-------------------------------------------- + +1. This LICENSE AGREEMENT is between the Python Software Foundation +("PSF"), and the Individual or Organization ("Licensee") accessing and +otherwise using this software ("Python") in source or binary form and +its associated documentation. + +2. Subject to the terms and conditions of this License Agreement, PSF hereby +grants Licensee a nonexclusive, royalty-free, world-wide license to reproduce, +analyze, test, perform and/or display publicly, prepare derivative works, +distribute, and otherwise use Python alone or in any derivative version, +provided, however, that PSF's License Agreement and PSF's notice of copyright, +i.e., "Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, +2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023 Python Software Foundation; +All Rights Reserved" are retained in Python alone or in any derivative version +prepared by Licensee. + +3. In the event Licensee prepares a derivative work that is based on +or incorporates Python or any part thereof, and wants to make +the derivative work available to others as provided herein, then +Licensee hereby agrees to include in any such work a brief summary of +the changes made to Python. + +4. PSF is making Python available to Licensee on an "AS IS" +basis. PSF MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR +IMPLIED. BY WAY OF EXAMPLE, BUT NOT LIMITATION, PSF MAKES NO AND +DISCLAIMS ANY REPRESENTATION OR WARRANTY OF MERCHANTABILITY OR FITNESS +FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF PYTHON WILL NOT +INFRINGE ANY THIRD PARTY RIGHTS. + +5. PSF SHALL NOT BE LIABLE TO LICENSEE OR ANY OTHER USERS OF PYTHON +FOR ANY INCIDENTAL, SPECIAL, OR CONSEQUENTIAL DAMAGES OR LOSS AS +A RESULT OF MODIFYING, DISTRIBUTING, OR OTHERWISE USING PYTHON, +OR ANY DERIVATIVE THEREOF, EVEN IF ADVISED OF THE POSSIBILITY THEREOF. + +6. This License Agreement will automatically terminate upon a material +breach of its terms and conditions. + +7. Nothing in this License Agreement shall be deemed to create any +relationship of agency, partnership, or joint venture between PSF and +Licensee. This License Agreement does not grant permission to use PSF +trademarks or trade name in a trademark sense to endorse or promote +products or services of Licensee, or any third party. + +8. By copying, installing or otherwise using Python, Licensee +agrees to be bound by the terms and conditions of this License +Agreement. + + +BEOPEN.COM LICENSE AGREEMENT FOR PYTHON 2.0 +------------------------------------------- + +BEOPEN PYTHON OPEN SOURCE LICENSE AGREEMENT VERSION 1 + +1. This LICENSE AGREEMENT is between BeOpen.com ("BeOpen"), having an +office at 160 Saratoga Avenue, Santa Clara, CA 95051, and the +Individual or Organization ("Licensee") accessing and otherwise using +this software in source or binary form and its associated +documentation ("the Software"). + +2. 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This License Agreement shall be governed by the federal +intellectual property law of the United States, including without +limitation the federal copyright law, and, to the extent such +U.S. federal law does not apply, by the law of the Commonwealth of +Virginia, excluding Virginia's conflict of law provisions. +Notwithstanding the foregoing, with regard to derivative works based +on Python 1.6.1 that incorporate non-separable material that was +previously distributed under the GNU General Public License (GPL), the +law of the Commonwealth of Virginia shall govern this License +Agreement only as to issues arising under or with respect to +Paragraphs 4, 5, and 7 of this License Agreement. Nothing in this +License Agreement shall be deemed to create any relationship of +agency, partnership, or joint venture between CNRI and Licensee. 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IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +THE SOFTWARE.Copyright (c) 2015-2019 Jared Hobbs + +Permission is hereby granted, free of charge, to any person obtaining a copy of +this software and associated documentation files (the "Software"), to deal in +the Software without restriction, including without limitation the rights to +use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies +of the Software, and to permit persons to whom the Software is furnished to do +so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE.Developed by ESN, an Electronic Arts Inc. studio. +Copyright (c) 2014, Electronic Arts Inc. +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are met: +* Redistributions of source code must retain the above copyright +notice, this list of conditions and the following disclaimer. +* Redistributions in binary form must reproduce the above copyright +notice, this list of conditions and the following disclaimer in the +documentation and/or other materials provided with the distribution. +* Neither the name of ESN, Electronic Arts Inc. nor the +names of its contributors may be used to endorse or promote products +derived from this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND +ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED +WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE +DISCLAIMED. IN NO EVENT SHALL ELECTRONIC ARTS INC. BE LIABLE +FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES +(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; +LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND +ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT +(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS +SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + +---- + +Portions of code from MODP_ASCII - Ascii transformations (upper/lower, etc) +https://github.com/client9/stringencoders + + Copyright 2005, 2006, 2007 + Nick Galbreath -- nickg [at] modp [dot] com + All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are + met: + + Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + + Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + + Neither the name of the modp.com nor the names of its + contributors may be used to endorse or promote products derived from + this software without specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + A PARTICULAR PURPOSE ARE DISCLAIMED. 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Wilcox + Ada Worcester + Alex Dowad + Alex Suykov + Alexander Monakov + Andre McCurdy + Andrew Kelley + Anthony G. Basile + Aric Belsito + Arvid Picciani + Bartosz Brachaczek + Benjamin Peterson + Bobby Bingham + Boris Brezillon + Brent Cook + Chris Spiegel + Clément Vasseur + Daniel Micay + Daniel Sabogal + Daurnimator + David Carlier + David Edelsohn + Denys Vlasenko + Dmitry Ivanov + Dmitry V. Levin + Drew DeVault + Emil Renner Berthing + Fangrui Song + Felix Fietkau + Felix Janda + Gianluca Anzolin + Hauke Mehrtens + He X + Hiltjo Posthuma + Isaac Dunham + Jaydeep Patil + Jens Gustedt + Jeremy Huntwork + Jo-Philipp Wich + Joakim Sindholt + John Spencer + Julien Ramseier + Justin Cormack + Kaarle Ritvanen + Khem Raj + Kylie McClain + Leah Neukirchen + Luca Barbato + Luka Perkov + M Farkas-Dyck (Strake) + Mahesh Bodapati + Markus Wichmann + Masanori Ogino + Michael Clark + Michael Forney + Mikhail Kremnyov + Natanael Copa + Nicholas J. Kain + orc + Pascal Cuoq + Patrick Oppenlander + Petr Hosek + Petr Skocik + Pierre Carrier + Reini Urban + Rich Felker + Richard Pennington + Ryan Fairfax + Samuel Holland + Segev Finer + Shiz + sin + Solar Designer + Stefan Kristiansson + Stefan O'Rear + Szabolcs Nagy + Timo Teräs + Trutz Behn + Valentin Ochs + Will Dietz + William Haddon + William Pitcock + + Portions of this software are derived from third-party works licensed + under terms compatible with the above MIT license: + + The TRE regular expression implementation (src/regex/reg* and + src/regex/tre*) is Copyright © 2001-2008 Ville Laurikari and licensed + under a 2-clause BSD license (license text in the source files). 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HISTORY OF THE SOFTWARE + ========================== + + Python was created in the early 1990s by Guido van Rossum at Stichting + Mathematisch Centrum (CWI, see https://www.cwi.nl) in the Netherlands + as a successor of a language called ABC. Guido remains Python's + principal author, although it includes many contributions from others. + + In 1995, Guido continued his work on Python at the Corporation for + National Research Initiatives (CNRI, see https://www.cnri.reston.va.us) + in Reston, Virginia where he released several versions of the + software. + + In May 2000, Guido and the Python core development team moved to + BeOpen.com to form the BeOpen PythonLabs team. In October of the same + year, the PythonLabs team moved to Digital Creations, which became + Zope Corporation. 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All Python licenses, unlike the GPL, let you distribute + a modified version without making your changes open source. The + GPL-compatible licenses make it possible to combine Python with + other software that is released under the GPL; the others don't. + + (2) According to Richard Stallman, 1.6.1 is not GPL-compatible, + because its license has a choice of law clause. According to + CNRI, however, Stallman's lawyer has told CNRI's lawyer that 1.6.1 + is "not incompatible" with the GPL. + + Thanks to the many outside volunteers who have worked under Guido's + direction to make these releases possible. + + + B. 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BE LIABLE + FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND + ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ---- + + Portions of code from MODP_ASCII - Ascii transformations (upper/lower, etc) + https://github.com/client9/stringencoders + + Copyright 2005, 2006, 2007 + Nick Galbreath -- nickg [at] modp [dot] com + All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are + met: + + Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + + Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + + Neither the name of the modp.com nor the names of its + contributors may be used to endorse or promote products derived from + this software without specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + A PARTICULAR PURPOSE ARE DISCLAIMED. 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Notwithstanding the foregoing, the + authors grant the U.S. Government and others acting in its behalf + permission to use and distribute the software in accordance with the + terms specified in this license. +Classifier: Development Status :: 5 - Production/Stable +Classifier: Environment :: Console +Classifier: Intended Audience :: Science/Research +Classifier: License :: OSI Approved :: BSD License +Classifier: Operating System :: OS Independent +Classifier: Programming Language :: Cython +Classifier: Programming Language :: Python +Classifier: Programming Language :: Python :: 3 +Classifier: Programming Language :: Python :: 3 :: Only +Classifier: Programming Language :: Python :: 3.11 +Classifier: Programming Language :: Python :: 3.12 +Classifier: Programming Language :: Python :: 3.13 +Classifier: Programming Language :: Python :: 3.14 +Classifier: Topic :: Scientific/Engineering +Project-URL: homepage, https://pandas.pydata.org +Project-URL: documentation, https://pandas.pydata.org/docs/ +Project-URL: repository, https://github.com/pandas-dev/pandas +Requires-Python: >=3.11 +Requires-Dist: numpy>=1.26.0; 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extra == "mysql" +Provides-Extra: sql-other +Requires-Dist: SQLAlchemy>=2.0.36; extra == "sql-other" +Requires-Dist: adbc-driver-postgresql>=1.2.0; extra == "sql-other" +Requires-Dist: adbc-driver-sqlite>=1.2.0; extra == "sql-other" +Provides-Extra: html +Requires-Dist: beautifulsoup4>=4.12.3; extra == "html" +Requires-Dist: html5lib>=1.1; extra == "html" +Requires-Dist: lxml>=5.3.0; extra == "html" +Provides-Extra: xml +Requires-Dist: lxml>=5.3.0; extra == "xml" +Provides-Extra: plot +Requires-Dist: matplotlib>=3.9.3; extra == "plot" +Provides-Extra: output-formatting +Requires-Dist: jinja2>=3.1.5; extra == "output-formatting" +Requires-Dist: tabulate>=0.9.0; extra == "output-formatting" +Provides-Extra: clipboard +Requires-Dist: PyQt5>=5.15.9; extra == "clipboard" +Requires-Dist: qtpy>=2.4.2; extra == "clipboard" +Provides-Extra: compression +Requires-Dist: zstandard>=0.23.0; extra == "compression" +Provides-Extra: timezone +Requires-Dist: pytz>=2024.2; extra == "timezone" +Provides-Extra: all +Requires-Dist: adbc-driver-postgresql>=1.2.0; extra == "all" +Requires-Dist: adbc-driver-sqlite>=1.2.0; extra == "all" +Requires-Dist: beautifulsoup4>=4.12.3; extra == "all" +Requires-Dist: bottleneck>=1.4.2; extra == "all" +Requires-Dist: fastparquet>=2024.11.0; extra == "all" +Requires-Dist: fsspec>=2024.10.0; extra == "all" +Requires-Dist: gcsfs>=2024.10.0; extra == "all" +Requires-Dist: html5lib>=1.1; extra == "all" +Requires-Dist: hypothesis>=6.116.0; extra == "all" +Requires-Dist: jinja2>=3.1.5; extra == "all" +Requires-Dist: lxml>=5.3.0; extra == "all" +Requires-Dist: matplotlib>=3.9.3; extra == "all" +Requires-Dist: numba>=0.60.0; extra == "all" +Requires-Dist: numexpr>=2.10.2; extra == "all" +Requires-Dist: odfpy>=1.4.1; extra == "all" +Requires-Dist: openpyxl>=3.1.5; extra == "all" +Requires-Dist: psycopg2>=2.9.10; extra == "all" +Requires-Dist: pyarrow>=13.0.0; extra == "all" +Requires-Dist: pyiceberg>=0.8.1; extra == "all" +Requires-Dist: pymysql>=1.1.1; extra == "all" +Requires-Dist: PyQt5>=5.15.9; extra == "all" +Requires-Dist: pyreadstat>=1.2.8; extra == "all" +Requires-Dist: pytest>=8.3.4; extra == "all" +Requires-Dist: pytest-xdist>=3.6.1; extra == "all" +Requires-Dist: python-calamine>=0.3.0; extra == "all" +Requires-Dist: pytz>=2024.2; extra == "all" +Requires-Dist: pyxlsb>=1.0.10; extra == "all" +Requires-Dist: qtpy>=2.4.2; extra == "all" +Requires-Dist: scipy>=1.14.1; extra == "all" +Requires-Dist: s3fs>=2024.10.0; extra == "all" +Requires-Dist: SQLAlchemy>=2.0.36; extra == "all" +Requires-Dist: tables>=3.10.1; extra == "all" +Requires-Dist: tabulate>=0.9.0; extra == "all" +Requires-Dist: xarray>=2024.10.0; extra == "all" +Requires-Dist: xlrd>=2.0.1; extra == "all" +Requires-Dist: xlsxwriter>=3.2.0; extra == "all" +Requires-Dist: zstandard>=0.23.0; extra == "all" +Description-Content-Type: text/markdown + + + + Pandas Logo + + +----------------- + +# pandas: A Powerful Python Data Analysis Toolkit + +| | | +| --- | --- | +| Testing | [![CI - Test](https://github.com/pandas-dev/pandas/actions/workflows/unit-tests.yml/badge.svg)](https://github.com/pandas-dev/pandas/actions/workflows/unit-tests.yml) [![Coverage](https://codecov.io/github/pandas-dev/pandas/coverage.svg?branch=main)](https://codecov.io/gh/pandas-dev/pandas) | +| Package | [![PyPI Latest Release](https://img.shields.io/pypi/v/pandas.svg)](https://pypi.org/project/pandas/) [![PyPI Downloads](https://img.shields.io/pypi/dm/pandas.svg?label=PyPI%20downloads)](https://pypi.org/project/pandas/) [![Conda Latest Release](https://anaconda.org/conda-forge/pandas/badges/version.svg)](https://anaconda.org/conda-forge/pandas) [![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/pandas.svg?label=Conda%20downloads)](https://anaconda.org/conda-forge/pandas) | +| Meta | [![Powered by NumFOCUS](https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A)](https://numfocus.org) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3509134.svg)](https://doi.org/10.5281/zenodo.3509134) [![License - BSD 3-Clause](https://img.shields.io/pypi/l/pandas.svg)](https://github.com/pandas-dev/pandas/blob/main/LICENSE) [![Slack](https://img.shields.io/badge/join_Slack-information-brightgreen.svg?logo=slack)](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack) [![LFX Health Score](https://insights.linuxfoundation.org/api/badge/health-score?project=pandas-dev-pandas)](https://insights.linuxfoundation.org/project/pandas-dev-pandas) | + + +## What is it? + +**pandas** is a Python package that provides fast, flexible, and expressive data +structures designed to make working with "relational" or "labeled" data both +easy and intuitive. It aims to be the fundamental high-level building block for +doing practical, **real-world** data analysis in Python. Additionally, it has +the broader goal of becoming **the most powerful and flexible open-source data +analysis/manipulation tool available in any language**. It is already well on +its way towards this goal. + +## Table of Contents + +- [Main Features](#main-features) +- [Where to get it](#where-to-get-it) +- [Dependencies](#dependencies) +- [Installation from sources](#installation-from-sources) +- [License](#license) +- [Documentation](#documentation) +- [Background](#background) +- [Getting Help](#getting-help) +- [Discussion and Development](#discussion-and-development) +- [Contributing to pandas](#contributing-to-pandas) + +## Main Features +Here are just a few of the things that pandas does well: + + - Easy handling of [**missing data**][missing-data] (represented as + `NaN`, `NA`, or `NaT`) in floating point as well as non-floating point data + - Size mutability: columns can be [**inserted and + deleted**][insertion-deletion] from DataFrame and higher dimensional + objects + - Automatic and explicit [**data alignment**][alignment]: objects can + be explicitly aligned to a set of labels, or the user can simply + ignore the labels and let `Series`, `DataFrame`, etc. automatically + align the data for you in computations + - Powerful, flexible [**group by**][groupby] functionality to perform + split-apply-combine operations on data sets, for both aggregating + and transforming data + - Make it [**easy to convert**][conversion] ragged, + differently-indexed data in other Python and NumPy data structures + into DataFrame objects + - Intelligent label-based [**slicing**][slicing], [**fancy + indexing**][fancy-indexing], and [**subsetting**][subsetting] of + large data sets + - Intuitive [**merging**][merging] and [**joining**][joining] data + sets + - Flexible [**reshaping**][reshape] and [**pivoting**][pivot-table] of + data sets + - [**Hierarchical**][mi] labeling of axes (possible to have multiple + labels per tick) + - Robust I/O tools for loading data from [**flat files**][flat-files] + (CSV and delimited), [**Excel files**][excel], [**databases**][db], + and saving/loading data from the ultrafast [**HDF5 format**][hdfstore] + - [**Time series**][timeseries]-specific functionality: date range + generation and frequency conversion, moving window statistics, + date shifting and lagging + + + [missing-data]: https://pandas.pydata.org/pandas-docs/stable/user_guide/missing_data.html + [insertion-deletion]: https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html#column-selection-addition-deletion + [alignment]: https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html?highlight=alignment#intro-to-data-structures + [groupby]: https://pandas.pydata.org/pandas-docs/stable/user_guide/groupby.html#group-by-split-apply-combine + [conversion]: https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html#dataframe + [slicing]: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#slicing-ranges + [fancy-indexing]: https://pandas.pydata.org/pandas-docs/stable/user_guide/advanced.html#advanced + [subsetting]: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#boolean-indexing + [merging]: https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html#database-style-dataframe-or-named-series-joining-merging + [joining]: https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html#joining-on-index + [reshape]: https://pandas.pydata.org/pandas-docs/stable/user_guide/reshaping.html + [pivot-table]: https://pandas.pydata.org/pandas-docs/stable/user_guide/reshaping.html + [mi]: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#hierarchical-indexing-multiindex + [flat-files]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#csv-text-files + [excel]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#excel-files + [db]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#sql-queries + [hdfstore]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#hdf5-pytables + [timeseries]: https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#time-series-date-functionality + +## Where to get it +The source code is currently hosted on GitHub at: +https://github.com/pandas-dev/pandas + +Binary installers for the latest released version are available at the [Python +Package Index (PyPI)](https://pypi.org/project/pandas) and on [Conda](https://anaconda.org/conda-forge/pandas). + +```sh +# conda +conda install -c conda-forge pandas +``` + +```sh +# or PyPI +pip install pandas +``` + +The list of changes to pandas between each release can be found +[here](https://pandas.pydata.org/pandas-docs/stable/whatsnew/index.html). For full +details, see the commit logs at https://github.com/pandas-dev/pandas. + +## Dependencies +- [NumPy - Adds support for large, multi-dimensional arrays, matrices and high-level mathematical functions to operate on these arrays](https://www.numpy.org) +- [python-dateutil - Provides powerful extensions to the standard datetime module](https://dateutil.readthedocs.io/en/stable/index.html) +- [tzdata - Provides an IANA time zone database](https://tzdata.readthedocs.io/en/latest/) (Only required on Windows/Emscripten) + +See the [full installation instructions](https://pandas.pydata.org/pandas-docs/stable/install.html#dependencies) for minimum supported versions of required, recommended and optional dependencies. + +## Installation from sources +To install pandas from source you need [Cython](https://cython.org/) in addition to the normal +dependencies above. Cython can be installed from PyPI: + +```sh +pip install cython +``` + +In the `pandas` directory (same one where you found this file after +cloning the git repo), execute: + +```sh +pip install . +``` + +or for installing in [development mode](https://pip.pypa.io/en/latest/cli/pip_install/#install-editable): + + +```sh +python -m pip install -ve . --no-build-isolation --config-settings editable-verbose=true +``` + +See the full instructions for [installing from source](https://pandas.pydata.org/docs/dev/development/contributing_environment.html). + +## License +[BSD 3](LICENSE) + +## Documentation +The official documentation is hosted on [PyData.org](https://pandas.pydata.org/pandas-docs/stable/). + +## Background +Work on ``pandas`` started at [AQR](https://www.aqr.com/) (a quantitative hedge fund) in 2008 and +has been under active development since then. + +## Getting Help + +For usage questions, the best place to go to is [Stack Overflow](https://stackoverflow.com/questions/tagged/pandas). +Further, general questions and discussions can also take place on the [pydata mailing list](https://groups.google.com/forum/?fromgroups#!forum/pydata). + +## Discussion and Development +Most development discussions take place on GitHub in this repo, via the [GitHub issue tracker](https://github.com/pandas-dev/pandas/issues). + +Further, the [pandas-dev mailing list](https://mail.python.org/mailman/listinfo/pandas-dev) can also be used for specialized discussions or design issues, and a [Slack channel](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack) is available for quick development related questions. + +There are also frequent [community meetings](https://pandas.pydata.org/docs/dev/development/community.html#community-meeting) for project maintainers open to the community as well as monthly [new contributor meetings](https://pandas.pydata.org/docs/dev/development/community.html#new-contributor-meeting) to help support new contributors. + +Additional information on the communication channels can be found on the [contributor community](https://pandas.pydata.org/docs/development/community.html) page. + +## Contributing to pandas + +[![Open Source Helpers](https://www.codetriage.com/pandas-dev/pandas/badges/users.svg)](https://www.codetriage.com/pandas-dev/pandas) + +All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome. + +A detailed overview on how to contribute can be found in the **[contributing guide](https://pandas.pydata.org/docs/dev/development/contributing.html)**. + +If you are simply looking to start working with the pandas codebase, navigate to the [GitHub "issues" tab](https://github.com/pandas-dev/pandas/issues) and start looking through interesting issues. There are a number of issues listed under [Docs](https://github.com/pandas-dev/pandas/issues?q=is%3Aissue%20state%3Aopen%20label%3ADocs%20sort%3Aupdated-desc) and [good first issue](https://github.com/pandas-dev/pandas/issues?q=is%3Aissue%20state%3Aopen%20label%3A%22good%20first%20issue%22%20sort%3Aupdated-desc) where you could start out. + +You can also triage issues which may include reproducing bug reports, or asking for vital information such as version numbers or reproduction instructions. If you would like to start triaging issues, one easy way to get started is to [subscribe to pandas on CodeTriage](https://www.codetriage.com/pandas-dev/pandas). + +Or maybe through using pandas you have an idea of your own or are looking for something in the documentation and thinking ‘this can be improved’... you can do something about it! + +Feel free to ask questions on the [mailing list](https://groups.google.com/forum/?fromgroups#!forum/pydata) or on [Slack](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack). + +As contributors and maintainers to this project, you are expected to abide by pandas' code of conduct. More information can be found at: [Contributor Code of Conduct](https://github.com/pandas-dev/.github/blob/master/CODE_OF_CONDUCT.md) + +
+ +[Go to Top](#table-of-contents) diff --git a/pandas-3.0.1.dist-info/RECORD b/pandas-3.0.1.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..18ee341b83cce0d777dece72cc908e750117aed3 --- /dev/null +++ b/pandas-3.0.1.dist-info/RECORD @@ -0,0 +1,1522 @@ +pandas-3.0.1.dist-info/INSTALLER,sha256=5hhM4Q4mYTT9z6QB6PGpUAW81PGNFrYrdXMj4oM_6ak,2 +pandas-3.0.1.dist-info/LICENSE,sha256=XBBS6SHmLTbM2lCmFYXpwERLgMYvObV8Tz8NX7YvUHE,52127 +pandas-3.0.1.dist-info/METADATA,sha256=-XwfUgVClh-PbltkPFwovj82U5n_KLIYulb3lX9R5DM,79468 +pandas-3.0.1.dist-info/RECORD,, +pandas-3.0.1.dist-info/REQUESTED,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0 +pandas-3.0.1.dist-info/WHEEL,sha256=5CT1xAVtUA3SK4LW_XdoM9Kto3PJPVP1rBIfK8BYqcM,138 +pandas-3.0.1.dist-info/entry_points.txt,sha256=OVLKNEPs-Q7IWypWBL6fxv56_zt4sRnEI7zawo6y_0w,69 +pandas/__init__.py,sha256=dC-FwTXuZUv_EgPvzudmS_gvxzBaw5Ev8wSgY_X36jw,8223 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b/pandas-3.0.1.dist-info/WHEEL new file mode 100644 index 0000000000000000000000000000000000000000..c178c31e46ab3001b0a2e21731d772429ca0cfe6 --- /dev/null +++ b/pandas-3.0.1.dist-info/WHEEL @@ -0,0 +1,6 @@ +Wheel-Version: 1.0 +Generator: meson +Root-Is-Purelib: false +Tag: cp312-cp312-manylinux_2_24_x86_64 +Tag: cp312-cp312-manylinux_2_28_x86_64 + diff --git a/pandas-3.0.1.dist-info/entry_points.txt b/pandas-3.0.1.dist-info/entry_points.txt new file mode 100644 index 0000000000000000000000000000000000000000..3c1b523d70758fbd0080e21ca4c7ce6d9c9d9bd5 --- /dev/null +++ b/pandas-3.0.1.dist-info/entry_points.txt @@ -0,0 +1,3 @@ +[pandas_plotting_backends] +matplotlib = pandas:plotting._matplotlib + diff --git a/peft/__init__.py b/peft/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..3c0f1c6b2d9522407822c430c547e0fa28206abe --- /dev/null +++ b/peft/__init__.py @@ -0,0 +1,244 @@ +# Copyright 2023-present the HuggingFace Inc. team. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +__version__ = "0.18.1" + +from .auto import ( + MODEL_TYPE_TO_PEFT_MODEL_MAPPING, + AutoPeftModel, + AutoPeftModelForCausalLM, + AutoPeftModelForFeatureExtraction, + AutoPeftModelForQuestionAnswering, + AutoPeftModelForSeq2SeqLM, + AutoPeftModelForSequenceClassification, + AutoPeftModelForTokenClassification, +) +from .config import PeftConfig, PromptLearningConfig +from .mapping import ( + PEFT_TYPE_TO_CONFIG_MAPPING, + PEFT_TYPE_TO_MIXED_MODEL_MAPPING, + PEFT_TYPE_TO_TUNER_MAPPING, + get_peft_config, + inject_adapter_in_model, +) +from .mapping_func import get_peft_model +from .mixed_model import PeftMixedModel +from .peft_model import ( + PeftModel, + PeftModelForCausalLM, + PeftModelForFeatureExtraction, + PeftModelForQuestionAnswering, + PeftModelForSeq2SeqLM, + PeftModelForSequenceClassification, + PeftModelForTokenClassification, + get_layer_status, + get_model_status, +) +from .tuners import ( + AdaLoraConfig, + AdaLoraModel, + AdaptionPromptConfig, + AdaptionPromptModel, + ArrowConfig, + BOFTConfig, + BOFTModel, + BoneConfig, + BoneModel, + C3AConfig, + C3AModel, + CPTConfig, + CPTEmbedding, + DeloraConfig, + DeloraModel, + EvaConfig, + FourierFTConfig, + FourierFTModel, + HRAConfig, + HRAModel, + IA3Config, + IA3Model, + LNTuningConfig, + LNTuningModel, + LoftQConfig, + LoHaConfig, + LoHaModel, + LoKrConfig, + LoKrModel, + LoraConfig, + LoraModel, + LoraRuntimeConfig, + MissConfig, + MissModel, + MultitaskPromptTuningConfig, + MultitaskPromptTuningInit, + OFTConfig, + OFTModel, + OSFConfig, + OSFModel, + PolyConfig, + PolyModel, + PrefixEncoder, + PrefixTuningConfig, + PromptEmbedding, + PromptEncoder, + PromptEncoderConfig, + PromptEncoderReparameterizationType, + PromptTuningConfig, + PromptTuningInit, + RandLoraConfig, + RandLoraModel, + RoadConfig, + RoadModel, + ShiraConfig, + ShiraModel, + TrainableTokensConfig, + TrainableTokensModel, + VBLoRAConfig, + VBLoRAModel, + VeraConfig, + VeraModel, + WaveFTConfig, + WaveFTModel, + XLoraConfig, + XLoraModel, + create_arrow_model, + get_eva_state_dict, + initialize_lora_eva_weights, +) +from .utils import ( + TRANSFORMERS_MODELS_TO_PREFIX_TUNING_POSTPROCESS_MAPPING, + PeftType, + PeftWarning, + TaskType, + bloom_model_postprocess_past_key_value, + cast_mixed_precision_params, + get_peft_model_state_dict, + load_peft_weights, + prepare_model_for_kbit_training, + replace_lora_weights_loftq, + set_peft_model_state_dict, + shift_tokens_right, +) + + +__all__ = [ + "MODEL_TYPE_TO_PEFT_MODEL_MAPPING", + "PEFT_TYPE_TO_CONFIG_MAPPING", + "PEFT_TYPE_TO_MIXED_MODEL_MAPPING", + "PEFT_TYPE_TO_TUNER_MAPPING", + "TRANSFORMERS_MODELS_TO_PREFIX_TUNING_POSTPROCESS_MAPPING", + "AdaLoraConfig", + "AdaLoraModel", + "AdaptionPromptConfig", + "AdaptionPromptModel", + "ArrowConfig", + "AutoPeftModel", + "AutoPeftModelForCausalLM", + "AutoPeftModelForFeatureExtraction", + "AutoPeftModelForQuestionAnswering", + "AutoPeftModelForSeq2SeqLM", + "AutoPeftModelForSequenceClassification", + "AutoPeftModelForTokenClassification", + "BOFTConfig", + "BOFTModel", + "BoneConfig", + "BoneModel", + "C3AConfig", + "C3AModel", + "CPTConfig", + "CPTEmbedding", + "DeloraConfig", + "DeloraModel", + "EvaConfig", + "FourierFTConfig", + "FourierFTModel", + "HRAConfig", + "HRAModel", + "IA3Config", + "IA3Model", + "LNTuningConfig", + "LNTuningModel", + "LoHaConfig", + "LoHaModel", + "LoKrConfig", + "LoKrModel", + "LoftQConfig", + "LoraConfig", + "LoraModel", + "LoraRuntimeConfig", + "MissConfig", + "MissModel", + "MultitaskPromptTuningConfig", + "MultitaskPromptTuningInit", + "OFTConfig", + "OFTModel", + "OSFConfig", + "OSFModel", + "PeftConfig", + "PeftMixedModel", + "PeftModel", + "PeftModelForCausalLM", + "PeftModelForFeatureExtraction", + "PeftModelForQuestionAnswering", + "PeftModelForSeq2SeqLM", + "PeftModelForSequenceClassification", + "PeftModelForTokenClassification", + "PeftType", + "PeftWarning", + "PolyConfig", + "PolyModel", + "PrefixEncoder", + "PrefixTuningConfig", + "PromptEmbedding", + "PromptEncoder", + "PromptEncoderConfig", + "PromptEncoderReparameterizationType", + "PromptLearningConfig", + "PromptTuningConfig", + "PromptTuningInit", + "RandLoraConfig", + "RandLoraModel", + "RoadConfig", + "RoadModel", + "ShiraConfig", + "ShiraModel", + "TaskType", + "TrainableTokensConfig", + "TrainableTokensModel", + "VBLoRAConfig", + "VBLoRAConfig", + "VBLoRAModel", + "VeraConfig", + "VeraModel", + "WaveFTConfig", + "WaveFTModel", + "XLoraConfig", + "XLoraModel", + "bloom_model_postprocess_past_key_value", + "cast_mixed_precision_params", + "create_arrow_model", + "get_eva_state_dict", + "get_layer_status", + "get_model_status", + "get_peft_config", + "get_peft_model", + "get_peft_model_state_dict", + "initialize_lora_eva_weights", + "inject_adapter_in_model", + "load_peft_weights", + "prepare_model_for_kbit_training", + "replace_lora_weights_loftq", + "set_peft_model_state_dict", + "shift_tokens_right", +] diff --git a/peft/auto.py b/peft/auto.py new file mode 100644 index 0000000000000000000000000000000000000000..613f67c707e344eab1a5281565fb0fdb3d827d01 --- /dev/null +++ b/peft/auto.py @@ -0,0 +1,184 @@ +# Copyright 2023-present the HuggingFace Inc. team. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from __future__ import annotations + +import importlib +import os +from typing import Optional + +from transformers import ( + AutoModel, + AutoModelForCausalLM, + AutoModelForQuestionAnswering, + AutoModelForSeq2SeqLM, + AutoModelForSequenceClassification, + AutoModelForTokenClassification, + AutoTokenizer, +) + +from .config import PeftConfig +from .peft_model import ( + PeftModel, + PeftModelForCausalLM, + PeftModelForFeatureExtraction, + PeftModelForQuestionAnswering, + PeftModelForSeq2SeqLM, + PeftModelForSequenceClassification, + PeftModelForTokenClassification, +) +from .utils.constants import TOKENIZER_CONFIG_NAME +from .utils.other import check_file_exists_on_hf_hub + + +MODEL_TYPE_TO_PEFT_MODEL_MAPPING: dict[str, type[PeftModel]] = { + "SEQ_CLS": PeftModelForSequenceClassification, + "SEQ_2_SEQ_LM": PeftModelForSeq2SeqLM, + "CAUSAL_LM": PeftModelForCausalLM, + "TOKEN_CLS": PeftModelForTokenClassification, + "QUESTION_ANS": PeftModelForQuestionAnswering, + "FEATURE_EXTRACTION": PeftModelForFeatureExtraction, +} + + +class _BaseAutoPeftModel: + _target_class = None + _target_peft_class = None + + def __init__(self, *args, **kwargs): + # For consistency with transformers: https://github.com/huggingface/transformers/blob/91d7df58b6537d385e90578dac40204cb550f706/src/transformers/models/auto/auto_factory.py#L400 + raise EnvironmentError( # noqa: UP024 + f"{self.__class__.__name__} is designed to be instantiated " + f"using the `{self.__class__.__name__}.from_pretrained(pretrained_model_name_or_path)` or " + f"`{self.__class__.__name__}.from_config(config)` methods." + ) + + @classmethod + def from_pretrained( + cls, + pretrained_model_name_or_path, + adapter_name: str = "default", + is_trainable: bool = False, + config: Optional[PeftConfig] = None, + revision: Optional[str] = None, + **kwargs, + ): + r""" + A wrapper around all the preprocessing steps a user needs to perform in order to load a PEFT model. The kwargs + are passed along to `PeftConfig` that automatically takes care of filtering the kwargs of the Hub methods and + the config object init. + """ + peft_config = PeftConfig.from_pretrained(pretrained_model_name_or_path, revision=revision, **kwargs) + base_model_path = peft_config.base_model_name_or_path + base_model_revision = peft_config.revision + + task_type = getattr(peft_config, "task_type", None) + + if cls._target_class is not None: + target_class = cls._target_class + elif cls._target_class is None and task_type is not None: + # this is only in the case where we use `AutoPeftModel` + raise ValueError( + "Cannot use `AutoPeftModel` with a task type, please use a specific class for your task type. (e.g. `AutoPeftModelForCausalLM` for `task_type='CAUSAL_LM'`)" + ) + + if task_type is not None: + expected_target_class = MODEL_TYPE_TO_PEFT_MODEL_MAPPING[task_type] + if cls._target_peft_class.__name__ != expected_target_class.__name__: + raise ValueError( + f"Expected target PEFT class: {expected_target_class.__name__}, but you have asked for: {cls._target_peft_class.__name__}" + " make sure that you are loading the correct model for your task type." + ) + elif task_type is None and getattr(peft_config, "auto_mapping", None) is not None: + auto_mapping = getattr(peft_config, "auto_mapping", None) + base_model_class = auto_mapping["base_model_class"] + parent_library_name = auto_mapping["parent_library"] + + parent_library = importlib.import_module(parent_library_name) + target_class = getattr(parent_library, base_model_class) + else: + raise ValueError( + "Cannot infer the auto class from the config, please make sure that you are loading the correct model for your task type." + ) + + base_model = target_class.from_pretrained(base_model_path, revision=base_model_revision, **kwargs) + + tokenizer_exists = False + if os.path.exists(os.path.join(pretrained_model_name_or_path, TOKENIZER_CONFIG_NAME)): + tokenizer_exists = True + else: + token = kwargs.get("token", None) + if token is None: + token = kwargs.get("use_auth_token", None) + + tokenizer_exists = check_file_exists_on_hf_hub( + repo_id=pretrained_model_name_or_path, + filename=TOKENIZER_CONFIG_NAME, + revision=revision, + repo_type=kwargs.get("repo_type", None), + token=token, + ) + + if tokenizer_exists and hasattr(base_model, "get_input_embeddings"): + tokenizer = AutoTokenizer.from_pretrained( + pretrained_model_name_or_path, trust_remote_code=kwargs.get("trust_remote_code", False) + ) + embedding_size = base_model.get_input_embeddings().weight.shape[0] + if len(tokenizer) > embedding_size: + # only resize if the tokenizer has a larger vocab size than there are embeddings + base_model.resize_token_embeddings(len(tokenizer)) + + return cls._target_peft_class.from_pretrained( + base_model, + pretrained_model_name_or_path, + adapter_name=adapter_name, + is_trainable=is_trainable, + config=config, + **kwargs, + ) + + +class AutoPeftModel(_BaseAutoPeftModel): + _target_class = None + _target_peft_class = PeftModel + + +class AutoPeftModelForCausalLM(_BaseAutoPeftModel): + _target_class = AutoModelForCausalLM + _target_peft_class = PeftModelForCausalLM + + +class AutoPeftModelForSeq2SeqLM(_BaseAutoPeftModel): + _target_class = AutoModelForSeq2SeqLM + _target_peft_class = PeftModelForSeq2SeqLM + + +class AutoPeftModelForSequenceClassification(_BaseAutoPeftModel): + _target_class = AutoModelForSequenceClassification + _target_peft_class = PeftModelForSequenceClassification + + +class AutoPeftModelForTokenClassification(_BaseAutoPeftModel): + _target_class = AutoModelForTokenClassification + _target_peft_class = PeftModelForTokenClassification + + +class AutoPeftModelForQuestionAnswering(_BaseAutoPeftModel): + _target_class = AutoModelForQuestionAnswering + _target_peft_class = PeftModelForQuestionAnswering + + +class AutoPeftModelForFeatureExtraction(_BaseAutoPeftModel): + _target_class = AutoModel + _target_peft_class = PeftModelForFeatureExtraction diff --git a/peft/config.py b/peft/config.py new file mode 100644 index 0000000000000000000000000000000000000000..60a5c20c74bc2b8b97a5e0262e99cc10a79be481 --- /dev/null +++ b/peft/config.py @@ -0,0 +1,408 @@ +# Copyright 2023-present the HuggingFace Inc. team. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from __future__ import annotations + +import importlib.metadata +import inspect +import json +import os +import warnings +from dataclasses import asdict, dataclass, field +from typing import Optional, Union + +import packaging.version +from huggingface_hub import hf_hub_download +from transformers.utils import PushToHubMixin, http_user_agent + +from peft import __version__ + +from .utils import CONFIG_NAME, PeftType, TaskType + + +# we expect at least these keys to be present in a PEFT adapter_config.json +MIN_EXPECTED_CONFIG_KEYS = {"peft_type"} + + +def _check_and_remove_unused_kwargs(cls, kwargs): + """Make PEFT configs forward-compatible by removing unused kwargs that were added in later PEFT versions. + + This assumes that removing the unused kwargs will not affect the default behavior. + + Returns the filtered kwargs and the set of removed keys. + """ + # it's not pretty but eh + signature_parameters = inspect.signature(cls.__init__).parameters + unexpected_kwargs = set(kwargs.keys()) - set(signature_parameters.keys()) + for key in unexpected_kwargs: + del kwargs[key] + return kwargs, unexpected_kwargs + + +def _is_dev_version(version: str) -> bool: + # check if the given version is a dev version + return packaging.version.Version(version).dev is not None + + +def _get_commit_hash(pkg_name: str) -> str | None: + # If PEFT was installed from a specific commit hash, try to get it. This works e.g. when installing PEFT with `pip + # install git+https://github.com/huggingface/peft.git@`. This works not for other means, like editable + # installs. + try: + dist = importlib.metadata.distribution(pkg_name) + except importlib.metadata.PackageNotFoundError: + return None + + # See: https://packaging.python.org/en/latest/specifications/direct-url/ + for path in dist.files or []: + if path.name == "direct_url.json": + direct_url = json.loads((dist.locate_file(path)).read_text()) + vcs_info = direct_url.get("vcs_info") + if vcs_info and "commit_id" in vcs_info: + return vcs_info["commit_id"] + return None + + +@dataclass +class PeftConfigMixin(PushToHubMixin): + r""" + This is the base configuration class for PEFT adapter models. It contains all the methods that are common to all + PEFT adapter models. This class inherits from [`~transformers.utils.PushToHubMixin`] which contains the methods to + push your model to the Hub. The method `save_pretrained` will save the configuration of your adapter model in a + directory. The method `from_pretrained` will load the configuration of your adapter model from a directory. + + Args: + peft_type (Union[[`~peft.utils.config.PeftType`], `str`]): The type of Peft method to use. + """ + + task_type: Optional[TaskType] = field(default=None, metadata={"help": "The type of task."}) + peft_type: Optional[PeftType] = field(default=None, metadata={"help": "The type of PEFT model."}) + auto_mapping: Optional[dict] = field( + default=None, metadata={"help": "An auto mapping dict to help retrieve the base model class if needed."} + ) + peft_version: Optional[str] = field(default=None, metadata={"help": "PEFT version, leave empty to auto-fill."}) + + def __post_init__(self): + # check for invalid task type + if (self.task_type is not None) and (self.task_type not in list(TaskType)): + raise ValueError( + f"Invalid task type: '{self.task_type}'. Must be one of the following task types: {', '.join(TaskType)}." + ) + if self.peft_version is None: + self.peft_version = self._get_peft_version() + + @staticmethod + def _get_peft_version() -> str: + # gets the current peft version; if it's a dev version, try to get the commit hash too, as the dev version is + # ambiguous + version = __version__ + if not _is_dev_version(version): + return version + + try: + git_hash = _get_commit_hash("peft") + if git_hash is None: + git_hash = "UNKNOWN" + except Exception: + # Broad exception: We never want to break user code just because the git_hash could not be determined + warnings.warn( + "A dev version of PEFT is used but there was an error while trying to determine the commit hash. " + "Please open an issue: https://github.com/huggingface/peft/issues" + ) + git_hash = "UNKNOWN" + version = version + f"@{git_hash}" + return version + + def to_dict(self) -> dict: + r""" + Returns the configuration for your adapter model as a dictionary. + """ + return asdict(self) + + def save_pretrained(self, save_directory: str, **kwargs) -> None: + r""" + This method saves the configuration of your adapter model in a directory. + + Args: + save_directory (`str`): + The directory where the configuration will be saved. + kwargs (additional keyword arguments, *optional*): + Additional keyword arguments passed along to the [`~transformers.utils.PushToHubMixin.push_to_hub`] + method. + """ + if os.path.isfile(save_directory): + raise AssertionError(f"Provided path ({save_directory}) should be a directory, not a file") + + os.makedirs(save_directory, exist_ok=True) + auto_mapping_dict = kwargs.pop("auto_mapping_dict", None) + + output_dict = self.to_dict() + # converting set type to list + for key, value in output_dict.items(): + if isinstance(value, set): + output_dict[key] = list(value) + + output_path = os.path.join(save_directory, CONFIG_NAME) + + # Add auto mapping details for custom models. + if auto_mapping_dict is not None: + output_dict["auto_mapping"] = auto_mapping_dict + + # save it + with open(output_path, "w") as writer: + writer.write(json.dumps(output_dict, indent=2, sort_keys=True)) + + @classmethod + def from_peft_type(cls, **kwargs): + r""" + This method loads the configuration of your adapter model from a set of kwargs. + + The appropriate configuration type is determined by the `peft_type` argument. If `peft_type` is not provided, + the calling class type is instantiated. + + Args: + kwargs (configuration keyword arguments): + Keyword arguments passed along to the configuration initialization. + """ + # Avoid circular dependency .. TODO: fix this with a larger refactor + from peft.mapping import PEFT_TYPE_TO_CONFIG_MAPPING + + # TODO: this hack is needed to fix the following issue (on commit 702f937): + # if someone saves a default config and loads it back with `PeftConfig` class it yields to + # not loading the correct config class. + # + # from peft import AdaLoraConfig, PeftConfig + # peft_config = AdaLoraConfig() + # print(peft_config) + # >>> AdaLoraConfig(peft_type=, auto_mapping=None, base_model_name_or_path=None, + # revision=None, task_type=None, inference_mode=False, r=8, target_modules=None, lora_alpha=8, lora_dropout=0.0, ... + # + # peft_config.save_pretrained("./test_config") + # peft_config = PeftConfig.from_pretrained("./test_config") + # print(peft_config) + # >>> PeftConfig(peft_type='ADALORA', auto_mapping=None, base_model_name_or_path=None, revision=None, task_type=None, inference_mode=False) + + if "peft_type" in kwargs: + peft_type = kwargs["peft_type"] + config_cls = PEFT_TYPE_TO_CONFIG_MAPPING[peft_type] + else: + config_cls = cls + + try: + config = config_cls(**kwargs) + except TypeError as exc: + # Here we potentially handle forward compatibility. Sometimes new keywords are added to configs, which makes + # new configs incompatible with older PEFT versions. We catch these and remove them to allow the program to + # continue, but warn the user about it. + + # First check if the error is due to unexpected keyword arguments, we don't want to accidentally catch + # other TypeErrors. + if "got an unexpected keyword argument" not in str(exc): + raise exc + + filtered_kwargs, unexpected_kwargs = _check_and_remove_unused_kwargs(config_cls, kwargs) + if not MIN_EXPECTED_CONFIG_KEYS.issubset(set(filtered_kwargs.keys())): + raise TypeError( + f"The {cls.__name__} config that is trying to be loaded is missing required keys: " + f"{MIN_EXPECTED_CONFIG_KEYS}." + ) + + warnings.warn( + f"Unexpected keyword arguments {sorted(unexpected_kwargs)} for class {config_cls.__name__}, these are " + "ignored. This probably means that you're loading a configuration file that was saved using a " + "higher version of the library and additional parameters have been introduced since. It is " + "highly recommended to upgrade the PEFT version before continuing (e.g. by running `pip install " + "-U peft`)." + ) + config = config_cls.from_peft_type(**filtered_kwargs) + return config + + @classmethod + def from_pretrained(cls, pretrained_model_name_or_path: str, subfolder: Optional[str] = None, **kwargs): + r""" + This method loads the configuration of your adapter model from a directory. + + Args: + pretrained_model_name_or_path (`str`): + The directory or the Hub repository id where the configuration is saved. + kwargs (additional keyword arguments, *optional*): + Additional keyword arguments passed along to the child class initialization. + """ + path = ( + os.path.join(pretrained_model_name_or_path, subfolder) + if subfolder is not None + else pretrained_model_name_or_path + ) + + hf_hub_download_kwargs, class_kwargs, _ = cls._split_kwargs(kwargs) + if "user_agent" not in hf_hub_download_kwargs: + hf_hub_download_kwargs["user_agent"] = http_user_agent() + + if os.path.isfile(os.path.join(path, CONFIG_NAME)): + config_file = os.path.join(path, CONFIG_NAME) + else: + try: + config_file = hf_hub_download( + pretrained_model_name_or_path, CONFIG_NAME, subfolder=subfolder, **hf_hub_download_kwargs + ) + except Exception as exc: + raise ValueError(f"Can't find '{CONFIG_NAME}' at '{pretrained_model_name_or_path}'") from exc + + loaded_attributes = cls.from_json_file(config_file) + kwargs = {**class_kwargs, **loaded_attributes} + kwargs = cls.check_kwargs(**kwargs) + return cls.from_peft_type(**kwargs) + + @classmethod + def from_json_file(cls, path_json_file: str, **kwargs): + r""" + Loads a configuration file from a json file. + + Args: + path_json_file (`str`): + The path to the json file. + """ + with open(path_json_file) as file: + json_object = json.load(file) + + # Sanity check that config does not contain a runtime_config + if "runtime_config" in json_object: + warnings.warn( + "The configuration file contains a `runtime_config` key. This is ignored. Runtime configurations are only valid at runtime." + ) + del json_object["runtime_config"] + + return json_object + + @classmethod + def _split_kwargs(cls, kwargs): + hf_hub_download_kwargs = {} + class_kwargs = {} + other_kwargs = {} + + for key, value in kwargs.items(): + if key in inspect.signature(hf_hub_download).parameters: + hf_hub_download_kwargs[key] = value + elif key in list(cls.__annotations__): + class_kwargs[key] = value + else: + other_kwargs[key] = value + + return hf_hub_download_kwargs, class_kwargs, other_kwargs + + @classmethod + def _get_peft_type( + cls, + model_id: str, + **hf_hub_download_kwargs, + ): + subfolder = hf_hub_download_kwargs.get("subfolder", None) + + path = os.path.join(model_id, subfolder) if subfolder is not None else model_id + + if os.path.isfile(os.path.join(path, CONFIG_NAME)): + config_file = os.path.join(path, CONFIG_NAME) + else: + try: + config_file = hf_hub_download( + model_id, + CONFIG_NAME, + **hf_hub_download_kwargs, + ) + except Exception: + raise ValueError(f"Can't find '{CONFIG_NAME}' at '{model_id}'") + + loaded_attributes = cls.from_json_file(config_file) + return loaded_attributes["peft_type"] + + @classmethod + def check_kwargs(cls, **kwargs): + """Check kwargs before initializing the config instance. + + Subclasses can override this method to add specific checks. + + """ + return kwargs + + @property + def is_prompt_learning(self) -> bool: + r""" + Utility method to check if the configuration is for prompt learning. + """ + return False + + @property + def is_adaption_prompt(self) -> bool: + """Return True if this is an adaption prompt config.""" + return False + + +@dataclass +class PeftConfig(PeftConfigMixin): + """ + This is the base configuration class to store the configuration of a [`PeftModel`]. + + Args: + peft_type (Union[[`~peft.utils.config.PeftType`], `str`]): The type of Peft method to use. + task_type (Union[[`~peft.utils.config.TaskType`], `str`]): The type of task to perform. + inference_mode (`bool`, defaults to `False`): Whether to use the Peft model in inference mode. + """ + + base_model_name_or_path: Optional[str] = field( + default=None, metadata={"help": "The name of the base model to use."} + ) + revision: Optional[str] = field(default=None, metadata={"help": "The specific base model version to use."}) + peft_type: Optional[Union[str, PeftType]] = field(default=None, metadata={"help": "Peft type"}) + task_type: Optional[Union[str, TaskType]] = field(default=None, metadata={"help": "Task type"}) + inference_mode: bool = field(default=False, metadata={"help": "Whether to use inference mode"}) + + +@dataclass +class PromptLearningConfig(PeftConfig): + """ + This is the base configuration class to store the configuration of [`PrefixTuning`], [`PromptEncoder`], or + [`PromptTuning`]. + + Args: + num_virtual_tokens (`int`): The number of virtual tokens to use. + token_dim (`int`): The hidden embedding dimension of the base transformer model. + num_transformer_submodules (`int`): The number of transformer submodules in the base transformer model. + num_attention_heads (`int`): The number of attention heads in the base transformer model. + num_layers (`int`): The number of layers in the base transformer model. + """ + + num_virtual_tokens: int = field(default=None, metadata={"help": "Number of virtual tokens"}) + token_dim: int = field( + default=None, metadata={"help": "The hidden embedding dimension of the base transformer model"} + ) + num_transformer_submodules: Optional[int] = field( + default=None, metadata={"help": "Number of transformer submodules"} + ) + num_attention_heads: Optional[int] = field(default=None, metadata={"help": "Number of attention heads"}) + num_layers: Optional[int] = field(default=None, metadata={"help": "Number of transformer layers"}) + modules_to_save: Optional[list[str]] = field( + default=None, + metadata={ + "help": "List of extra modules to be set as trainable and saved in the final checkpoint. " + "For example, in Sequence Classification or Token Classification tasks, " + "the final layer `classifier/score` are randomly initialized and as such need to be trainable and saved. " + "The module(s) will be fully fine-tuned." + }, + ) + + @property + def is_prompt_learning(self) -> bool: + r""" + Utility method to check if the configuration is for prompt learning. + """ + return True diff --git a/peft/functional.py b/peft/functional.py new file mode 100644 index 0000000000000000000000000000000000000000..60df690cafe1e9a3b5c8ff09d550f82110afe593 --- /dev/null +++ b/peft/functional.py @@ -0,0 +1,34 @@ +# Copyright 2025-present the HuggingFace Inc. team. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" +Functions that are useful for integration with non-PeftModel models, e.g. transformers or diffusers. + +The functions provided here can be considered "public API" of PEFT and hence are safe to be used by packages that +provide PEFT integrations. +""" + +from peft.mapping import inject_adapter_in_model +from peft.tuners.tuners_utils import cast_adapter_dtype, delete_adapter, set_adapter, set_requires_grad +from peft.utils import get_peft_model_state_dict, set_peft_model_state_dict + + +__all__ = [ + "cast_adapter_dtype", + "delete_adapter", + "get_peft_model_state_dict", + "inject_adapter_in_model", + "set_adapter", + "set_peft_model_state_dict", + "set_requires_grad", +] diff --git a/peft/helpers.py b/peft/helpers.py new file mode 100644 index 0000000000000000000000000000000000000000..d748c62e696d57034e4e9fd6458b27febbd9c90c --- /dev/null +++ b/peft/helpers.py @@ -0,0 +1,251 @@ +# Copyright 2023-present the HuggingFace Inc. team. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import inspect +from contextlib import contextmanager +from copy import deepcopy +from functools import update_wrapper +from types import MethodType + +from torch import nn + +from .peft_model import PeftConfig, PeftModel +from .tuners.lora import LoraLayer +from .tuners.tuners_utils import BaseTunerLayer + + +def update_forward_signature(model: PeftModel) -> None: + """ + Updates the forward signature of the PeftModel to include parents class signature + model (`PeftModel`): Peft model to update the forward signature + + Example: + + ```python + >>> from transformers import WhisperForConditionalGeneration + >>> from peft import get_peft_model, LoraConfig, update_forward_signature + + >>> model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny.en") + >>> peft_config = LoraConfig(r=8, lora_alpha=32, lora_dropout=0.1, target_modules=["q_proj", "v_proj"]) + + >>> peft_model = get_peft_model(model, peft_config) + >>> update_forward_signature(peft_model) + ``` + """ + + # Only update signature when the current forward signature only has *args and **kwargs + current_signature = inspect.signature(model.forward) + if ( + len(current_signature.parameters) == 2 + and "args" in current_signature.parameters + and "kwargs" in current_signature.parameters + ): + forward = deepcopy(model.forward.__func__) + update_wrapper( + forward, type(model.get_base_model()).forward, assigned=("__doc__", "__name__", "__annotations__") + ) + model.forward = MethodType(forward, model) + + +def update_generate_signature(model: PeftModel) -> None: + """ + Updates the generate signature of a PeftModel with overriding generate to include parents class signature + model (`PeftModel`): Peft model to update the generate signature + + Example: + + ```python + >>> from transformers import AutoModelForSeq2SeqLM, AutoTokenizer + >>> from peft import get_peft_model, LoraConfig, TaskType, update_generate_signature + + >>> model_name_or_path = "bigscience/mt0-large" + >>> tokenizer = AutoTokenizer.from_pretrained(model_name_or_path) + >>> model = AutoModelForSeq2SeqLM.from_pretrained(model_name_or_path) + + >>> peft_config = LoraConfig( + ... task_type=TaskType.SEQ_2_SEQ_LM, inference_mode=False, r=8, lora_alpha=32, lora_dropout=0.1 + ... ) + >>> peft_model = get_peft_model(model, peft_config) + >>> update_generate_signature(peft_model) + >>> help(peft_model.generate) + ``` + """ + if not hasattr(model, "generate"): + return + current_signature = inspect.signature(model.generate) + if ( + len(current_signature.parameters) == 2 + and "args" in current_signature.parameters + and "kwargs" in current_signature.parameters + ) or (len(current_signature.parameters) == 1 and "kwargs" in current_signature.parameters): + generate = deepcopy(model.generate.__func__) + update_wrapper( + generate, + type(model.get_base_model()).generate, + assigned=("__doc__", "__name__", "__annotations__"), + ) + model.generate = MethodType(generate, model) + + +def update_signature(model: PeftModel, method: str = "all") -> None: + """ + Updates the signature of a PeftModel include parents class signature for forward or generate method + model (`PeftModel`): Peft model to update generate or forward signature method (`str`): method to update + signature choose one of "forward", "generate", "all" + + Example: + ```python + >>> from transformers import AutoModelForSeq2SeqLM, AutoTokenizer + >>> from peft import get_peft_model, LoraConfig, TaskType, update_signature + + >>> model_name_or_path = "bigscience/mt0-large" + >>> tokenizer = AutoTokenizer.from_pretrained(model_name_or_path) + >>> model = AutoModelForSeq2SeqLM.from_pretrained(model_name_or_path) + + >>> peft_config = LoraConfig( + ... task_type=TaskType.SEQ_2_SEQ_LM, inference_mode=False, r=8, lora_alpha=32, lora_dropout=0.1 + ... ) + >>> peft_model = get_peft_model(model, peft_config) + >>> update_signature(peft_model) + >>> help(peft_model.generate) + ``` + """ + if method == "forward": + update_forward_signature(model) + elif method == "generate": + update_generate_signature(model) + elif method == "all": + update_forward_signature(model) + update_generate_signature(model) + else: + raise ValueError(f"method {method} is not supported please choose one of ['forward', 'generate', 'all']") + + +def check_if_peft_model(model_name_or_path: str) -> bool: + """ + Check if the model is a PEFT model. + + Args: + model_name_or_path (`str`): + Model id to check, can be local or on the Hugging Face Hub. + + Returns: + `bool`: True if the model is a PEFT model, False otherwise. + """ + is_peft_model = True + try: + PeftConfig.from_pretrained(model_name_or_path) + except Exception: + # allow broad exceptions so that this works even if new exceptions are added on HF Hub side + is_peft_model = False + + return is_peft_model + + +@contextmanager +def rescale_adapter_scale(model, multiplier): + """ + Context manager to temporarily rescale the scaling of the LoRA adapter in a model. + + The original scaling values are restored when the context manager exits. This context manager works with the + transformers and diffusers models that have directly loaded LoRA adapters. + + For LoRA, applying this context manager with multiplier in [0, 1] is strictly equivalent to applying + [wise-ft](https://huggingface.co/papers/2109.01903) (see [#1940](https://github.com/huggingface/peft/issues/1940) + for details). It can improve the performances of the model if there is a distribution shiftbetween the training + data used for fine-tuning, and the test data used during inference. + + Warning: It has been reported that when using Apple's MPS backend for PyTorch, it is necessary to add a short sleep + time after exiting the context before the scales are fully restored. + + Args: + model: The model containing `LoraLayer` modules whose scaling is to be adjusted. + multiplier (float or int): + The multiplier that rescales the `scaling` attribute. Must be of type float or int. + + Raises: + ValueError: If the model does not contain any `LoraLayer` + instances, indicating that the model does not support scaling. + + Example: + + ```python + >>> model = ModelWithLoraLayer() + >>> multiplier = 0.5 + >>> with rescale_adapter_scale(model, multiplier): + ... outputs = model(**inputs) # Perform operations with the scaled model + >>> outputs = model(**inputs) # The original scaling values are restored here + ``` + """ + # check if multiplier has a valid data type + if not isinstance(multiplier, (float, int)): + raise TypeError(f"Argument multiplier should be of type float, got {type(multiplier)}") + + # iterate on the model's modules and grab the original scaling attribute + # from the lora layers if present + original_scaling = {} + for module in model.modules(): + if isinstance(module, LoraLayer): + original_scaling[module] = module.scaling.copy() + module.scaling = {k: v * multiplier for k, v in module.scaling.items()} + + # check whether scaling is prohibited on model + # the original scaling dictionary should be empty + # if there were no lora layers + if not original_scaling: + raise ValueError("scaling is only supported for models with `LoraLayer`s") + try: + yield + + finally: + # restore original scaling values after exiting the context + for module, scaling in original_scaling.items(): + module.scaling = scaling + + +@contextmanager +def disable_input_dtype_casting(model: nn.Module, active: bool = True): + """ + Context manager disables input dtype casting to the dtype of the weight. + + Parameters: + model (nn.Module): + The model containing PEFT modules whose input dtype casting is to be adjusted. + active (bool): + Whether the context manager is active (default) or inactive. + + """ + # Additional info: Normally, the dtype of the weight and input need to match, which is why the dtype is cast. + # However, in certain circumustances, this is handled by forward hooks, e.g. when using layerwise casting in + # diffusers. In that case, PEFT casting the dtype interferes with the layerwise casting, which is why the option to + # disable it is given. + if not active: + yield + return + + original_values = {} + for name, module in model.named_modules(): + if not isinstance(module, BaseTunerLayer): + continue + original_values[name] = module.cast_input_dtype_enabled + module.cast_input_dtype_enabled = False + + try: + yield + finally: + for name, module in model.named_modules(): + if not isinstance(module, BaseTunerLayer): + continue + if name in original_values: + module.cast_input_dtype_enabled = original_values[name] diff --git a/peft/import_utils.py b/peft/import_utils.py new file mode 100644 index 0000000000000000000000000000000000000000..6aa69a85190bc91bb8bd0649fa80806d7209c584 --- /dev/null +++ b/peft/import_utils.py @@ -0,0 +1,172 @@ +# Copyright 2023-present the HuggingFace Inc. team. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import importlib +import importlib.metadata as importlib_metadata +import platform +from functools import lru_cache + +import packaging.version +import torch + + +@lru_cache +def is_bnb_available() -> bool: + return importlib.util.find_spec("bitsandbytes") is not None + + +@lru_cache +def is_bnb_4bit_available() -> bool: + if not is_bnb_available(): + return False + + import bitsandbytes as bnb + + return hasattr(bnb.nn, "Linear4bit") + + +@lru_cache +def is_auto_gptq_available(): + if importlib.util.find_spec("auto_gptq") is not None: + AUTOGPTQ_MINIMUM_VERSION = packaging.version.parse("0.5.0") + version_autogptq = packaging.version.parse(importlib_metadata.version("auto_gptq")) + if AUTOGPTQ_MINIMUM_VERSION <= version_autogptq: + return True + else: + raise ImportError( + f"Found an incompatible version of auto-gptq. Found version {version_autogptq}, " + f"but only versions above {AUTOGPTQ_MINIMUM_VERSION} are supported" + ) + + +@lru_cache +def is_gptqmodel_available(): + if importlib.util.find_spec("gptqmodel") is not None: + GPTQMODEL_MINIMUM_VERSION = packaging.version.parse("2.0.0") + OPTIMUM_MINIMUM_VERSION = packaging.version.parse("1.24.0") + version_gptqmodel = packaging.version.parse(importlib_metadata.version("gptqmodel")) + if GPTQMODEL_MINIMUM_VERSION <= version_gptqmodel: + if is_optimum_available(): + version_optimum = packaging.version.parse(importlib_metadata.version("optimum")) + if OPTIMUM_MINIMUM_VERSION <= version_optimum: + return True + else: + raise ImportError( + f"gptqmodel requires optimum version `{OPTIMUM_MINIMUM_VERSION}` or higher. Found version `{version_optimum}`, " + f"but only versions above `{OPTIMUM_MINIMUM_VERSION}` are supported" + ) + else: + raise ImportError( + f"gptqmodel requires optimum version `{OPTIMUM_MINIMUM_VERSION}` or higher to be installed." + ) + else: + raise ImportError( + f"Found an incompatible version of gptqmodel. Found version `{version_gptqmodel}`, " + f"but only versions above `{GPTQMODEL_MINIMUM_VERSION}` are supported" + ) + + +@lru_cache +def is_optimum_available() -> bool: + return importlib.util.find_spec("optimum") is not None + + +@lru_cache +def is_torch_tpu_available(check_device=True): + "Checks if `torch_xla` is installed and potentially if a TPU is in the environment" + if importlib.util.find_spec("torch_xla") is not None: + if check_device: + # We need to check if `xla_device` can be found, will raise a RuntimeError if not + try: + import torch_xla.core.xla_model as xm + + _ = xm.xla_device() + return True + except RuntimeError: + return False + return True + return False + + +@lru_cache +def is_aqlm_available(): + return importlib.util.find_spec("aqlm") is not None + + +@lru_cache +def is_auto_awq_available(): + return importlib.util.find_spec("awq") is not None + + +@lru_cache +def is_eetq_available(): + return importlib.util.find_spec("eetq") is not None + + +@lru_cache +def is_hqq_available(): + return importlib.util.find_spec("hqq") is not None + + +@lru_cache +def is_inc_available(): + return importlib.util.find_spec("neural_compressor") is not None + + +@lru_cache +def is_torchao_available(): + if importlib.util.find_spec("torchao") is None: + return False + + TORCHAO_MINIMUM_VERSION = packaging.version.parse("0.4.0") + try: + torchao_version = packaging.version.parse(importlib_metadata.version("torchao")) + except importlib_metadata.PackageNotFoundError: + # Same idea as in diffusers: + # https://github.com/huggingface/diffusers/blob/9f06a0d1a4a998ac6a463c5be728c892f95320a8/src/diffusers/utils/import_utils.py#L351-L357 + # It's not clear under what circumstances `importlib_metadata.version("torchao")` can raise an error even + # though `importlib.util.find_spec("torchao") is not None` but it has been observed, so adding this for + # precaution. + return False + + if torchao_version < TORCHAO_MINIMUM_VERSION: + raise ImportError( + f"Found an incompatible version of torchao. Found version {torchao_version}, " + f"but only versions above {TORCHAO_MINIMUM_VERSION} are supported" + ) + return True + + +@lru_cache +def is_xpu_available(check_device=False): + """ + Checks if XPU acceleration is available and potentially if a XPU is in the environment + """ + + system = platform.system() + if system == "Darwin": + return False + else: + if check_device: + try: + # Will raise a RuntimeError if no XPU is found + _ = torch.xpu.device_count() + return torch.xpu.is_available() + except RuntimeError: + return False + return hasattr(torch, "xpu") and torch.xpu.is_available() + + +@lru_cache +def is_diffusers_available(): + return importlib.util.find_spec("diffusers") is not None diff --git a/peft/mapping.py b/peft/mapping.py new file mode 100644 index 0000000000000000000000000000000000000000..82c6ec1e40bb7b06f505b82346245b8bf00d789c --- /dev/null +++ b/peft/mapping.py @@ -0,0 +1,92 @@ +# Copyright 2023-present the HuggingFace Inc. team. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from __future__ import annotations + +from typing import TYPE_CHECKING, Any, Optional + +import torch + +from .utils import PeftType + + +if TYPE_CHECKING: + from .config import PeftConfig + from .tuners.tuners_utils import BaseTuner + + +# these will be filled by the register_peft_method function +PEFT_TYPE_TO_CONFIG_MAPPING: dict[PeftType, type[PeftConfig]] = {} +PEFT_TYPE_TO_TUNER_MAPPING: dict[PeftType, type[BaseTuner]] = {} +PEFT_TYPE_TO_MIXED_MODEL_MAPPING: dict[PeftType, type[BaseTuner]] = {} +PEFT_TYPE_TO_PREFIX_MAPPING: dict[PeftType, str] = {} + + +def get_peft_config(config_dict: dict[str, Any]) -> PeftConfig: + """ + Returns a Peft config object from a dictionary. + + Args: + config_dict (`Dict[str, Any]`): Dictionary containing the configuration parameters. + """ + + return PEFT_TYPE_TO_CONFIG_MAPPING[config_dict["peft_type"]](**config_dict) + + +def inject_adapter_in_model( + peft_config: PeftConfig, + model: torch.nn.Module, + adapter_name: str = "default", + low_cpu_mem_usage: bool = False, + state_dict: Optional[dict[str, torch.Tensor]] = None, +) -> torch.nn.Module: + r""" + Create PEFT layers and inject them into the model in-place. + + Currently the API does not support prompt learning methods and adaption prompt. + + This function is similar to [`get_peft_model`] but it does not return a [`PeftModel`] instance. Instead, it returns + the original, mutated instance of the passed model. + + Args: + peft_config (`PeftConfig`): + Configuration object containing the parameters of the PEFT model. + model (`torch.nn.Module`): + The input model where the adapter will be injected. + adapter_name (`str`, `optional`, defaults to `"default"`): + The name of the adapter to be injected, if not provided, the default adapter name is used ("default"). + low_cpu_mem_usage (`bool`, `optional`, defaults to `False`): + Create empty adapter weights on meta device. Useful to speed up the loading process. + state_dict (`dict`, *optional*, defaults to `None`) + If a `state_dict` is passed here, the adapters will be injected based on the entries of the state_dict. + This can be useful when the exact `target_modules` of the PEFT method is unknown, for instance because the + checkpoint was created without meta data. Note that the values from the `state_dict` are not used, only the + keys are used to determine the correct layers that should be adapted. + """ + if peft_config.is_prompt_learning or peft_config.is_adaption_prompt: + raise ValueError("`create_and_replace` does not support prompt learning and adaption prompt yet.") + + if peft_config.peft_type not in PEFT_TYPE_TO_TUNER_MAPPING.keys(): + raise ValueError( + f"`inject_adapter_in_model` does not support {peft_config.peft_type} yet. Please use `get_peft_model`." + ) + + tuner_cls = PEFT_TYPE_TO_TUNER_MAPPING[peft_config.peft_type] + + # By instantiating a peft model we are injecting randomly initialized LoRA layers into the model's modules. + peft_model = tuner_cls( + model, peft_config, adapter_name=adapter_name, low_cpu_mem_usage=low_cpu_mem_usage, state_dict=state_dict + ) + + return peft_model.model diff --git a/peft/mapping_func.py b/peft/mapping_func.py new file mode 100644 index 0000000000000000000000000000000000000000..fae671819eb037e3a14f51dd2b94bffaaffaa819 --- /dev/null +++ b/peft/mapping_func.py @@ -0,0 +1,128 @@ +# Copyright 2024-present the HuggingFace Inc. team. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from __future__ import annotations + +import warnings +from typing import Optional + +from transformers import PreTrainedModel + +from .auto import MODEL_TYPE_TO_PEFT_MODEL_MAPPING +from .config import PeftConfig +from .mapping import PEFT_TYPE_TO_CONFIG_MAPPING, PEFT_TYPE_TO_PREFIX_MAPPING +from .mixed_model import PeftMixedModel +from .peft_model import PeftModel +from .tuners.tuners_utils import BaseTuner, BaseTunerLayer + + +def get_peft_model( + model: PreTrainedModel, + peft_config: PeftConfig, + adapter_name: str = "default", + mixed: bool = False, + autocast_adapter_dtype: bool = True, + revision: Optional[str] = None, + low_cpu_mem_usage: bool = False, +) -> PeftModel | PeftMixedModel: + """ + Returns a Peft model object from a model and a config, where the model will be modified in-place. + + Args: + model ([`transformers.PreTrainedModel`]): + Model to be wrapped. + peft_config ([`PeftConfig`]): + Configuration object containing the parameters of the Peft model. + adapter_name (`str`, `optional`, defaults to `"default"`): + The name of the adapter to be injected, if not provided, the default adapter name is used ("default"). + mixed (`bool`, `optional`, defaults to `False`): + Whether to allow mixing different (compatible) adapter types. + autocast_adapter_dtype (`bool`, *optional*): + Whether to autocast the adapter dtype. Defaults to `True`. Right now, this will only cast adapter weights + using float16 or bfloat16 to float32, as this is typically required for stable training, and only affect + select PEFT tuners. + revision (`str`, `optional`, defaults to `main`): + The revision of the base model. If this isn't set, the saved peft model will load the `main` revision for + the base model + low_cpu_mem_usage (`bool`, `optional`, defaults to `False`): + Create empty adapter weights on meta device. Useful to speed up the loading process. Leave this setting as + False if you intend on training the model, unless the adapter weights will be replaced by different weights + before training starts. + """ + model_config = BaseTuner.get_model_config(model) + old_name = peft_config.base_model_name_or_path + new_name = model.__dict__.get("name_or_path", None) + peft_config.base_model_name_or_path = new_name + + # Especially in notebook environments there could be a case that a user wants to experiment with different + # configuration values. However, it is likely that there won't be any changes for new configs on an already + # initialized PEFT model. The best we can do is warn the user about it. + if any(isinstance(module, BaseTunerLayer) for module in model.modules()): + warnings.warn( + "You are trying to modify a model with PEFT for a second time. If you want to reload the model with a " + "different config, make sure to call `.unload()` before." + ) + + if (old_name is not None) and (old_name != new_name): + warnings.warn( + f"The PEFT config's `base_model_name_or_path` was renamed from '{old_name}' to '{new_name}'. " + "Please ensure that the correct base model is loaded when loading this checkpoint." + ) + + if revision is not None: + if peft_config.revision is not None and peft_config.revision != revision: + warnings.warn( + f"peft config has already set base model revision to {peft_config.revision}, overwriting with revision {revision}" + ) + peft_config.revision = revision + + if ( + (isinstance(peft_config, PEFT_TYPE_TO_CONFIG_MAPPING["LORA"])) + and (peft_config.init_lora_weights == "eva") + and not low_cpu_mem_usage + ): + warnings.warn( + "lora with eva initialization used with low_cpu_mem_usage=False. " + "Setting low_cpu_mem_usage=True can improve the maximum batch size possible for eva initialization." + ) + + prefix = PEFT_TYPE_TO_PREFIX_MAPPING.get(peft_config.peft_type) + if prefix and adapter_name in prefix: + warnings.warn( + f"Adapter name '{adapter_name}' should not be contained in the prefix '{prefix}'. " + "This may lead to reinitialization of the adapter weights during loading." + ) + + if mixed: + # note: PeftMixedModel does not support autocast_adapter_dtype, so don't pass it + return PeftMixedModel(model, peft_config, adapter_name=adapter_name) + + # We explicitly exclude prompt learning here since prompt learning is specific to the task and needs special + # handling in the PEFT model's forward method. + if peft_config.task_type not in MODEL_TYPE_TO_PEFT_MODEL_MAPPING.keys() and not peft_config.is_prompt_learning: + return PeftModel( + model, + peft_config, + adapter_name=adapter_name, + autocast_adapter_dtype=autocast_adapter_dtype, + low_cpu_mem_usage=low_cpu_mem_usage, + ) + + return MODEL_TYPE_TO_PEFT_MODEL_MAPPING[peft_config.task_type]( + model, + peft_config, + adapter_name=adapter_name, + autocast_adapter_dtype=autocast_adapter_dtype, + low_cpu_mem_usage=low_cpu_mem_usage, + ) diff --git a/peft/mixed_model.py b/peft/mixed_model.py new file mode 100644 index 0000000000000000000000000000000000000000..c3ad517e7eb65b10b955410eddb2f1962e43e3e1 --- /dev/null +++ b/peft/mixed_model.py @@ -0,0 +1,460 @@ +# Copyright 2023-present the HuggingFace Inc. team. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from __future__ import annotations + +import os +from contextlib import contextmanager +from typing import Any, Optional, Union + +import torch +from accelerate.hooks import remove_hook_from_submodules +from torch import nn +from transformers.utils import PushToHubMixin + +from peft.utils.constants import DUMMY_MODEL_CONFIG + +from .config import PeftConfig +from .peft_model import PeftModel +from .tuners import MixedModel +from .utils import _set_adapter, _set_trainable + + +def _prepare_model_for_gradient_checkpointing(model: nn.Module) -> None: + r""" + Prepares the model for gradient checkpointing if necessary + """ + # Note: same as PeftModel._prepare_model_for_gradient_checkpointing + if not getattr(model, "is_gradient_checkpointing", True): + return model + + if not ( + getattr(model, "is_loaded_in_8bit", False) + or getattr(model, "is_loaded_in_4bit", False) + or getattr(model, "is_quantized", False) + ): + if hasattr(model, "enable_input_require_grads"): + model.enable_input_require_grads() + elif hasattr(model, "get_input_embeddings"): + + def make_inputs_require_grad(module, input, output): + output.requires_grad_(True) + + model.get_input_embeddings().register_forward_hook(make_inputs_require_grad) + + +def _check_config_compatible(peft_config: PeftConfig) -> None: + from .tuners.mixed import COMPATIBLE_TUNER_TYPES + + if peft_config.peft_type not in COMPATIBLE_TUNER_TYPES: + raise ValueError( + f"The provided `peft_type` '{peft_config.peft_type.value}' is not compatible with the `PeftMixedModel`. " + f"Compatible types are: {COMPATIBLE_TUNER_TYPES}" + ) + + +class PeftMixedModel(PushToHubMixin, torch.nn.Module): + """ + PeftMixedModel for loading mixing different types of adapters for inference. + + This class does not support loading/saving, and it shouldn't usually be initialized directly. Instead, use + `get_peft_model` with the argument `mixed=True`. + + > [!TIP] > Read the [Mixed adapter types](https://huggingface.co/docs/peft/en/developer_guides/mixed_models) guide + to learn > more about using different adapter types. + + Example: + + ```py + >>> base_model = ... # load the base model, e.g. from transformers + >>> peft_model = PeftMixedModel.from_pretrained(base_model, path_to_adapter1, "adapter1").eval() + >>> peft_model.load_adapter(path_to_adapter2, "adapter2") + >>> peft_model.set_adapter(["adapter1", "adapter2"]) # activate both adapters + >>> peft_model(data) # forward pass using both adapters + ``` + + Args: + model (`torch.nn.Module`): + The model to be tuned. + config (`PeftConfig`): + The config of the model to be tuned. The adapter type must be compatible. + adapter_name (`str`, `optional`, defaults to `"default"`): + The name of the first adapter. + low_cpu_mem_usage (`bool`, `optional`, defaults to `False`): + Create empty adapter weights on meta device. Useful to speed up the loading process. + """ + + def __init__(self, model: nn.Module, peft_config: PeftConfig, adapter_name: str = "default") -> None: + super().__init__() + _check_config_compatible(peft_config) + _prepare_model_for_gradient_checkpointing(model) + self.modules_to_save = None + self.base_model = MixedModel(model, {adapter_name: peft_config}, adapter_name) + self.set_modules_to_save(peft_config, adapter_name) + + self.config = getattr(model, "config", DUMMY_MODEL_CONFIG) + + # the `pretraining_tp` is set for some models to simulate Tensor Parallelism during inference to avoid + # numerical differences, https://github.com/pytorch/pytorch/issues/76232 - to avoid any unexpected + # behavior we disable that in this line. + if hasattr(self.base_model, "config") and hasattr(self.base_model.config, "pretraining_tp"): + self.base_model.config.pretraining_tp = 1 + + @property + def peft_config(self) -> dict[str, PeftConfig]: + return self.base_model.peft_config + + @property + def active_adapter(self) -> str: + return self.base_model.active_adapter + + @property + def active_adapters(self) -> list[str]: + return self.base_model.active_adapters + + def get_nb_trainable_parameters(self): + r""" + Returns the number of trainable parameters and number of all parameters in the model. + """ + # note: same as PeftModel.get_nb_trainable_parameters + trainable_params = 0 + all_param = 0 + for _, param in self.named_parameters(): + num_params = param.numel() + # if using DS Zero 3 and the weights are initialized empty + if num_params == 0 and hasattr(param, "ds_numel"): + num_params = param.ds_numel + + # Due to the design of 4bit linear layers from bitsandbytes + # one needs to multiply the number of parameters by 2 to get + # the correct number of parameters + if param.__class__.__name__ == "Params4bit": + num_params = num_params * 2 + + all_param += num_params + if param.requires_grad: + trainable_params += num_params + + return trainable_params, all_param + + def print_trainable_parameters(self): + """ + Prints the number of trainable parameters in the model. + + Note: print_trainable_parameters() uses get_nb_trainable_parameters() which is different from + num_parameters(only_trainable=True) from huggingface/transformers. get_nb_trainable_parameters() returns + (trainable parameters, all parameters) of the Peft Model which includes modified backbone transformer model. + For techniques like LoRA, the backbone transformer model is modified in place with LoRA modules. However, for + prompt tuning, the backbone transformer model is unmodified. num_parameters(only_trainable=True) returns number + of trainable parameters of the backbone transformer model which can be different. + """ + # note: same as PeftModel.print_trainable_parameters + trainable_params, all_param = self.get_nb_trainable_parameters() + + print( + f"trainable params: {trainable_params:,d} || " + f"all params: {all_param:,d} || " + f"trainable%: {100 * trainable_params / all_param:.4f}" + ) + + def __getattr__(self, name: str): + """Forward missing attributes to the wrapped module.""" + try: + return super().__getattr__(name) # defer to nn.Module's logic + except AttributeError: + if name == "base_model": # see #1892: prevent infinite recursion if class is not initialized + raise + return getattr(self.base_model, name) + + def forward(self, *args: Any, **kwargs: Any): + """ + Forward pass of the model. + """ + return self.base_model(*args, **kwargs) + + def generate(self, *args: Any, **kwargs: Any): + """ + Generate output. + """ + return self.base_model.generate(*args, **kwargs) + + @contextmanager + def disable_adapter(self): + """ + Disables the adapter module. + """ + try: + self.base_model.disable_adapter_layers() + yield + finally: + self.base_model.enable_adapter_layers() + + def add_adapter(self, adapter_name: str, peft_config: PeftConfig, low_cpu_mem_usage: bool = False) -> None: + """ + Add an adapter to the model based on the passed configuration. + + This adapter is not trained. To load a trained adapter, check out [`PeftModel.load_adapter`]. + + The name for the new adapter should be unique. + + The new adapter is not automatically set as the active adapter. Use [`PeftModel.set_adapter`] to set the active + adapter. + + Args: + adapter_name (`str`): + The name of the adapter to be added. + peft_config ([`PeftConfig`]): + The configuration of the adapter to be added. + low_cpu_mem_usage (`bool`, `optional`, defaults to `False`): + Create empty adapter weights on meta device. Useful to speed up the process when loading saved + adapters. + + > [!TIP] > Don't use `low_cpu_mem_usage=True` when creating a new PEFT adapter for training (training + is untested > and discouraged for PeftMixedModel in general). + """ + _check_config_compatible(peft_config) + + try: + self.peft_config[adapter_name] = peft_config + self.base_model.inject_adapter(self, adapter_name, low_cpu_mem_usage=low_cpu_mem_usage) + except Exception: # something went wrong, roll back + if adapter_name in self.peft_config: + del self.peft_config[adapter_name] + raise + + self.set_modules_to_save(peft_config, adapter_name) + + def set_modules_to_save(self, peft_config: PeftConfig, adapter_name: str) -> None: + if (modules_to_save := getattr(peft_config, "modules_to_save", None)) is None: + return + + if self.modules_to_save is None: + self.modules_to_save = set(modules_to_save) + else: + self.modules_to_save.update(modules_to_save) + _set_trainable( + self, + adapter_name, + module_names=getattr(peft_config, "modules_to_save", None), + inference_mode=peft_config.inference_mode, + ) + + def set_adapter(self, adapter_name: Union[str, list[str]], inference_mode: bool = False) -> None: + """ + Sets the active adapter(s) for the model. + + Note that the order in which the adapters are applied during the forward pass may not be the same as the order + in which they are passed to this function. Instead, the order during the forward pass is determined by the + order in which the adapters were loaded into the model. The active adapters only determine which adapters are + active during the forward pass, but not the order in which they are applied. + + Additionally, this function will set the specified adapter to trainable (i.e., requires_grad=True) unless + inference_mode is True. + + Args: + adapter_name (str, list[str]): + The name(s) of the adapter(s) to set as active + inference_mode (bool, optional): + Whether the activated adapter should be frozen (i.e. `requires_grad=False`). Default is False. + """ + if isinstance(adapter_name, str): + adapter_name = [adapter_name] + + mismatched = set(adapter_name) - set(self.peft_config.keys()) + if mismatched: + raise ValueError( + f"Adapter(s) {sorted(mismatched)} not found, available adapters: {sorted(self.peft_config.keys())}" + ) + + self.base_model.set_adapter(adapter_name, inference_mode=inference_mode) + _set_adapter(self, adapter_name, inference_mode=inference_mode) + + def delete_adapter(self, adapter_name: Union[str, list[str]]) -> None: + if isinstance(adapter_name, str): + adapter_name = [adapter_name] + + mismatched = set(adapter_name) - set(self.peft_config.keys()) + if mismatched: + raise ValueError( + f"Adapter(s) {sorted(mismatched)} not found, available adapters: {sorted(self.peft_config.keys())}" + ) + + self.base_model.delete_adapter(adapter_name) + + def merge_and_unload(self, *args: Any, **kwargs: Any): + r""" + This method merges the adapter layers into the base model. This is needed if someone wants to use the base + model as a standalone model. + + Args: + progressbar (`bool`): + whether to show a progressbar indicating the unload and merge process + safe_merge (`bool`): + whether to activate the safe merging check to check if there is any potential Nan in the adapter + weights + adapter_names (`List[str]`, *optional*): + The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults + to `None`. + """ + return self.base_model.merge_and_unload(*args, **kwargs) + + def unload(self, *args: Any, **kwargs: Any): + """ + Gets back the base model by removing all the adapter modules without merging. This gives back the original base + model. + """ + return self.base_model.unload(*args, **kwargs) + + def get_layer_status(self): + raise TypeError(f"get_layer_status is not supported for {self.__class__.__name__}.") + + def get_model_status(self): + raise TypeError(f"get_model_status is not supported for {self.__class__.__name__}.") + + @classmethod + def _split_kwargs(cls, kwargs: dict[str, Any]): + return PeftModel._split_kwargs(kwargs) + + def _check_new_adapter_config(self, peft_config: PeftConfig, is_trainable: bool) -> None: + return PeftModel._check_new_adapter_config(self, peft_config, is_trainable=is_trainable) + + def load_adapter(self, model_id: str, adapter_name: str, *args: Any, **kwargs: Any): + """ + Load a trained adapter into the model. + + The name for the new adapter should be unique. + + The new adapter is not automatically set as the active adapter. Use [`PeftModel.set_adapter`] to set the active + adapter. + + Args: + adapter_name (`str`): + The name of the adapter to be added. + peft_config ([`PeftConfig`]): + The configuration of the adapter to be added. + is_trainable (`bool`, *optional*, defaults to `False`): + Whether the adapter should be trainable or not. If `False`, the adapter will be frozen and can only be + used for inference. + torch_device (`str`, *optional*, defaults to None): + The device to load the adapter on. If `None`, the device will be inferred. + autocast_adapter_dtype (`bool`, *optional*, defaults to `True`): + Whether to autocast the adapter dtype. Defaults to `True`. Right now, this will only cast adapter + weights using float16 and bfloat16 to float32, as this is typically required for stable training, and + only affect select PEFT tuners. + ephemeral_gpu_offload (`bool`, *optional*, defaults to `False`): + Whether to use ephemeral GPU offloading for partially loaded modules. Defaults to `False`. + low_cpu_mem_usage (`bool`, `optional`, defaults to `False`): + Create empty adapter weights on meta device before loading the saved weights. Useful to speed up the + process. + kwargs: (`optional`): + Additional arguments to modify the way the adapter is loaded, e.g. the token for Hugging Face Hub. + """ + # the low_cpu_mem_usage option is handled through kwargs + output = PeftModel.load_adapter(self, model_id, adapter_name, *args, **kwargs) + # TODO: not quite clear why this is necessary but tests fail without it + self.set_adapter(self.active_adapters) + return output + + def create_or_update_model_card(self, output_dir: str): + raise NotImplementedError(f"Model card creation is not supported for {self.__class__.__name__} (yet).") + + def save_pretrained( + self, + save_directory: str, + safe_serialization: bool = False, + selected_adapters: Optional[list[str]] = None, + **kwargs: Any, + ): + raise NotImplementedError(f"Saving is not supported for {self.__class__.__name__} (yet).") + + @classmethod + def from_pretrained( + cls, + model: nn.Module, + model_id: str | os.PathLike, + adapter_name: str = "default", + is_trainable: bool = False, + config: Optional[PeftConfig] = None, + **kwargs: Any, + ): + r""" + Instantiate a PEFT mixed model from a pretrained model and loaded PEFT weights. + + Note that the passed `model` may be modified inplace. + + Args: + model (`nn.Module`): + The model to be adapted. + model_id (`str` or `os.PathLike`): + The name of the PEFT configuration to use. Can be either: + - A string, the `model id` of a PEFT configuration hosted inside a model repo on the Hugging Face + Hub. + - A path to a directory containing a PEFT configuration file saved using the `save_pretrained` + method (`./my_peft_config_directory/`). + adapter_name (`str`, *optional*, defaults to `"default"`): + The name of the adapter to be loaded. This is useful for loading multiple adapters. + is_trainable (`bool`, *optional*, defaults to `False`): + Whether the adapter should be trainable or not. If `False`, the adapter will be frozen and use for + inference + config ([`~peft.PeftConfig`], *optional*): + The configuration object to use instead of an automatically loaded configuration. This configuration + object is mutually exclusive with `model_id` and `kwargs`. This is useful when configuration is already + loaded before calling `from_pretrained`. + low_cpu_mem_usage (`bool`, `optional`, defaults to `False`): + Create empty adapter weights on meta device before loading the saved weights. Useful to speed up the + process. + kwargs: (`optional`): + Additional keyword arguments passed along to the specific PEFT configuration class. + """ + # note: adapted from PeftModel.from_pretrained + from .mapping import PEFT_TYPE_TO_CONFIG_MAPPING, PEFT_TYPE_TO_MIXED_MODEL_MAPPING + + # load the config + if config is None: + hf_kwargs = { + "subfolder": kwargs.get("subfolder", None), + "revision": kwargs.get("revision", None), + "cache_dir": kwargs.get("cache_dir", None), + "token": kwargs.get("token", None), + } + if use_auth_token := kwargs.get("use_auth_token", None): + hf_kwargs["use_auth_token"] = use_auth_token + config = PEFT_TYPE_TO_CONFIG_MAPPING[PeftConfig._get_peft_type(model_id, **hf_kwargs)].from_pretrained( + model_id, **kwargs + ) + elif isinstance(config, PeftConfig): + config.inference_mode = not is_trainable + else: + raise ValueError(f"The input config must be a PeftConfig, got {config.__class__}") + + # note: this is different from PeftModel.from_pretrained + if config.peft_type not in PEFT_TYPE_TO_MIXED_MODEL_MAPPING: + raise ValueError(f"Adapter of type {config.peft_type} is not supported for mixed models.") + + if (getattr(model, "hf_device_map", None) is not None) and len( + set(model.hf_device_map.values()).intersection({"cpu", "disk"}) + ) > 0: + remove_hook_from_submodules(model) + + if config.is_prompt_learning and is_trainable: + # note: should not be possible to reach, but just in case + raise ValueError("Cannot set a prompt learning adapter to trainable when loading pretrained adapter.") + else: + config.inference_mode = not is_trainable + + # note: this is different from PeftModel.from_pretrained, we always return a PeftMixedModel + model = cls(model, config, adapter_name) + # the low_cpu_mem_usage option is handled through kwargs + model.load_adapter(model_id, adapter_name, is_trainable=is_trainable, **kwargs) + return model diff --git a/peft/peft_model.py b/peft/peft_model.py new file mode 100644 index 0000000000000000000000000000000000000000..47d6f72c8d2887b51b43e09a647ba6222730fa3b --- /dev/null +++ b/peft/peft_model.py @@ -0,0 +1,3330 @@ +# Copyright 2023-present the HuggingFace Inc. team. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from __future__ import annotations + +import collections +import copy +import inspect +import os +import warnings +from collections.abc import Sequence +from contextlib import contextmanager, nullcontext +from copy import deepcopy +from dataclasses import dataclass +from typing import Any, Literal, Optional, Union + +import packaging.version +import torch +import transformers +from accelerate import dispatch_model, infer_auto_device_map +from accelerate.hooks import AlignDevicesHook, add_hook_to_module, remove_hook_from_submodules +from accelerate.utils import get_balanced_memory, named_module_tensors +from huggingface_hub import HfFileSystem, ModelCard, ModelCardData, hf_hub_download +from safetensors import safe_open +from safetensors.torch import save_file as safe_save_file +from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss +from transformers import Cache, DynamicCache, EncoderDecoderCache, PreTrainedModel +from transformers.modeling_outputs import QuestionAnsweringModelOutput, SequenceClassifierOutput, TokenClassifierOutput +from transformers.utils import PushToHubMixin + +from peft.tuners.lora.variants import get_alora_offsets_for_forward, get_alora_offsets_for_generate +from peft.tuners.tuners_utils import BaseTuner, BaseTunerLayer +from peft.utils import AuxiliaryTrainingWrapper +from peft.utils.constants import DUMMY_MODEL_CONFIG +from peft.utils.integrations import init_empty_weights +from peft.utils.other import TrainableTokensWrapper, create_attention_mask, set_additional_trainable_modules + +from . import __version__ +from .config import PeftConfig +from .mapping import PEFT_TYPE_TO_CONFIG_MAPPING, PEFT_TYPE_TO_PREFIX_MAPPING, PEFT_TYPE_TO_TUNER_MAPPING +from .utils import ( + SAFETENSORS_WEIGHTS_NAME, + TRANSFORMERS_MODELS_TO_PREFIX_TUNING_POSTPROCESS_MAPPING, + WEIGHTS_NAME, + PeftType, + TaskType, + _get_batch_size, + _prepare_prompt_learning_config, + _set_adapter, + _set_trainable, + get_peft_model_state_dict, + id_tensor_storage, + infer_device, + load_peft_weights, + map_cache_to_layer_device_map, + set_peft_model_state_dict, + shift_tokens_right, +) + + +class PeftModel(PushToHubMixin, torch.nn.Module): + """ + Base model encompassing various Peft methods. + + Args: + model ([`~transformers.PreTrainedModel`]): The base transformer model used for Peft. + peft_config ([`PeftConfig`]): The configuration of the Peft model. + adapter_name (`str`, *optional*): The name of the adapter, defaults to `"default"`. + autocast_adapter_dtype (`bool`, *optional*): + Whether to autocast the adapter dtype. Defaults to `True`. Right now, this will only cast adapter weights + using float16 and bfloat16 to float32, as this is typically required for stable training, and only affect + select PEFT tuners. + low_cpu_mem_usage (`bool`, `optional`, defaults to `False`): + Create empty adapter weights on meta device. Useful to speed up the loading loading process. + + > [!TIP] > Don't use `low_cpu_mem_usage=True` when creating a new PEFT adapter for training. + + **Attributes**: + - **base_model** ([`torch.nn.Module`]) -- The base transformer model used for Peft. + - **peft_config** ([`PeftConfig`]) -- The configuration of the Peft model. + - **modules_to_save** (`list` of `str`) -- The list of sub-module names to save when + saving the model. + - **prompt_encoder** ([`PromptEncoder`]) -- The prompt encoder used for Peft if + using [`PromptLearningConfig`]. + - **prompt_tokens** (`torch.Tensor`) -- The virtual prompt tokens used for Peft if + using [`PromptLearningConfig`]. + - **transformer_backbone_name** (`str`) -- The name of the transformer + backbone in the base model if using [`PromptLearningConfig`]. + - **word_embeddings** (`torch.nn.Embedding`) -- The word embeddings of the transformer backbone + in the base model if using [`PromptLearningConfig`]. + """ + + def __init__( + self, + model: PreTrainedModel, + peft_config: PeftConfig, + adapter_name: str = "default", + autocast_adapter_dtype: bool = True, + low_cpu_mem_usage: bool = False, + ) -> None: + super().__init__() + self.active_adapter = adapter_name + self.peft_type = peft_config.peft_type + # These args are special PEFT arguments that users can pass. They need to be removed before passing them to + # forward. + self.special_peft_forward_args = {"adapter_names", "alora_offsets"} + + self._is_prompt_learning = peft_config.is_prompt_learning + if self._is_prompt_learning: + self._peft_config = {adapter_name: peft_config} + self.base_model = model + self.add_adapter(adapter_name, peft_config, low_cpu_mem_usage=low_cpu_mem_usage) + else: + self._peft_config = None + cls = PEFT_TYPE_TO_TUNER_MAPPING[peft_config.peft_type] + ctx = init_empty_weights if low_cpu_mem_usage else nullcontext + with ctx(): + self.base_model = cls(model, {adapter_name: peft_config}, adapter_name) + + if hasattr(self.base_model, "_cast_adapter_dtype"): + self.base_model._cast_adapter_dtype( + adapter_name=adapter_name, autocast_adapter_dtype=autocast_adapter_dtype + ) + + if getattr(model, "is_gradient_checkpointing", True): + model = self.prepare_model_for_gradient_checkpointing(model) + + # the `pretraining_tp` is set for some models to simulate Tensor Parallelism during inference to avoid + # numerical differences, https://github.com/pytorch/pytorch/issues/76232 - to avoid any unexpected + # behavior we disable that in this line. + if hasattr(self.base_model, "config") and hasattr(self.base_model.config, "pretraining_tp"): + self.base_model.config.pretraining_tp = 1 + + self._adapters_disabled = False + + @property + def peft_config(self) -> dict[str, PeftConfig]: + if self._is_prompt_learning: + return self._peft_config + return self.base_model.peft_config + + @property + def active_adapters(self) -> list[str]: + try: + adapters = self.base_model.active_adapters + if not isinstance(adapters, list): + # Base model is probably a transformers model, see: + # https://github.com/huggingface/transformers/pull/30790#issuecomment-2253808249 + # Unfortunately, transformers models also have an active_adapters method but it's 1) not a property and + # 2) calling it fails because the base model (usually) has no loaded adapter. The base model can be a + # transformers model for prompt learning, where the base model is not wrapped in a LoraModel or similar. + adapters = self.active_adapter + if isinstance(adapters, str): + adapters = [adapters] + except AttributeError: + adapters = self.active_adapter + if isinstance(adapters, str): + adapters = [adapters] + return adapters + + @property + def has_active_enabled_adapter(self) -> bool: + """Reflects whether the adapters are purposefully disabled (via disable_adapter) or if there + are no active adapters (enabled but inactive). They are two separate mechanisms but sometimes it is helpful to + know whether the model has any active/enabled adapter at all. + """ + if self.peft_config[self.active_adapter].is_prompt_learning: + return not self._adapters_disabled + + return not self._adapters_disabled or not self.active_adapters + + @peft_config.setter + def peft_config(self, value: dict[str, PeftConfig]): + if self._is_prompt_learning: + self._peft_config = value + else: + self.base_model.peft_config = value + + def save_pretrained( + self, + save_directory: str, + safe_serialization: bool = True, + selected_adapters: Optional[list[str]] = None, + save_embedding_layers: Union[str, bool] = "auto", + is_main_process: bool = True, + path_initial_model_for_weight_conversion: Optional[str] = None, + **kwargs: Any, + ) -> None: + r""" + This function saves the adapter model and the adapter configuration files to a directory, so that it can be + reloaded using the [`PeftModel.from_pretrained`] class method, and also used by the [`PeftModel.push_to_hub`] + method. + + Args: + save_directory (`str`): + Directory where the adapter model and configuration files will be saved (will be created if it does not + exist). + safe_serialization (`bool`, *optional*): + Whether to save the adapter files in safetensors format, defaults to `True`. + selected_adapters (`List[str]`, *optional*): + A list of adapters to be saved. If `None`, will default to all adapters. + save_embedding_layers (`Union[bool, str]`, *optional*, defaults to `"auto"`): + If `True`, save the embedding layers in addition to adapter weights. If `auto`, checks the common + embedding layers `peft.utils.other.EMBEDDING_LAYER_NAMES` in config's `target_modules` when available. + and automatically sets the boolean flag. This only works for 🤗 transformers models. + is_main_process (`bool`, *optional*): + Whether the process calling this is the main process or not. Will default to `True`. Will not save the + checkpoint if not on the main process, which is important for multi device setups (e.g. DDP). + path_initial_model_for_weight_conversion (`str, *optional*`): + The path to the initialized adapter, which is obtained after initializing the model with + PiSSA/CorDA/OLoRA and before performing any training. When `path_initial_model_for_weight_conversion` + is not None, the difference in adapter before and after fine-tuning is calculated. This difference can + be represented as the parameters of a standard LoRA adapter. Using this converted adapter does not + require changes to the base model, thus conveniently allowing the use of multiple PiSSA/CorDA/OLoRA + adapters with LoRA adapters, and the activation or deactivation of any adapters. Note that this + conversion is not supported if `rslora` is used in combination with `rank_pattern` or `alpha_pattern`. + kwargs (additional keyword arguments, *optional*): + Additional keyword arguments passed along to the `push_to_hub` method. + + """ + if os.path.isfile(save_directory): + raise ValueError(f"Provided path ({save_directory}) should be a directory, not a file") + + if selected_adapters is None: + selected_adapters = list(self.peft_config.keys()) + else: + if any( + selected_adapter_name not in list(self.peft_config.keys()) + for selected_adapter_name in selected_adapters + ): + raise ValueError( + f"You passed an invalid `selected_adapters` arguments, current supported adapter names are" + f" {list(self.peft_config.keys())} - got {selected_adapters}." + ) + + def save_mutated_as_lora(peft_config, path_initial_model_for_weight_conversion, output_state_dict, kwargs): + if peft_config.use_rslora and (peft_config.rank_pattern or peft_config.alpha_pattern): + msg = ( + "Passing `path_initial_model_for_weight_conversion` to `save_pretrained` is not supported when " + "using `rank_pattern` or `alpha_pattern` at the same time as `use_rslora=True`." + ) + raise ValueError(msg) + + if not any( + str(peft_config.init_lora_weights).lower().startswith(prefix) + for prefix in ["pissa", "corda", "olora", "true"] + ): + warnings.warn( + "`path_initial_model_for_weight_conversion` only works for converting a PiSSA/CorDA/OLoRA adapter to " + "a LoRA adapter" + ) + initial_adapter_name = os.path.basename(path_initial_model_for_weight_conversion) + try: + self.load_adapter( + os.path.dirname(path_initial_model_for_weight_conversion), + subfolder=initial_adapter_name, + adapter_name=initial_adapter_name, + ) + is_pissa = str(self.peft_config[initial_adapter_name].init_lora_weights).lower().startswith("pissa") + is_corda = str(self.peft_config[initial_adapter_name].init_lora_weights).lower() == "corda" + is_olora = str(self.peft_config[initial_adapter_name].init_lora_weights).lower() == "olora" + if is_pissa or is_corda or is_olora: + raise ValueError( + "The `init_lora_weights` parameter of the initial adapter should be set to `True`. " + "Otherwise, `self.load_adapter` will subtract the decomposed values again based on the " + "residual model." + ) + output_state_dict = self.base_model.subtract_mutated_init( + output_state_dict, initial_adapter_name, kwargs + ) + finally: + self.delete_adapter(initial_adapter_name) + return output_state_dict + + if is_main_process: + os.makedirs(save_directory, exist_ok=True) + self.create_or_update_model_card(save_directory) + + for adapter_name in selected_adapters: + peft_config = self.peft_config[adapter_name] + # save only the trainable weights + output_state_dict = get_peft_model_state_dict( + self, + state_dict=kwargs.get("state_dict", None), + adapter_name=adapter_name, + save_embedding_layers=save_embedding_layers, + ) + output_dir = os.path.join(save_directory, adapter_name) if adapter_name != "default" else save_directory + os.makedirs(output_dir, exist_ok=True) + + if is_main_process and safe_serialization: + # Section copied from: https://github.com/huggingface/transformers/blob/main/src/transformers/modeling_utils.py#L2111-L2134 + # Safetensors does not allow tensor aliasing. + # We're going to remove aliases before saving + ptrs = collections.defaultdict(list) + for name, tensor in output_state_dict.items(): + # Sometimes in the state_dict we have non-tensor objects. + # e.g. in bitsandbytes we have some `str` objects in the state_dict + if isinstance(tensor, torch.Tensor): + ptrs[id_tensor_storage(tensor)].append(name) + else: + # In the non-tensor case, fall back to the pointer of the object itself + ptrs[id(tensor)].append(name) + + # These are all the pointers of shared tensors. + shared_ptrs = {ptr: names for ptr, names in ptrs.items() if len(names) > 1} + + for _, names in shared_ptrs.items(): + # Here we just clone the shared tensors to avoid tensor aliasing which is + # not supported in safetensors. + for shared_tensor_name in names[1:]: + output_state_dict[shared_tensor_name] = output_state_dict[shared_tensor_name].clone() + if path_initial_model_for_weight_conversion is not None: + peft_config = copy.deepcopy(peft_config) + peft_config.init_lora_weights = True + peft_config.save_pretrained(path_initial_model_for_weight_conversion) + output_state_dict = save_mutated_as_lora( + peft_config, path_initial_model_for_weight_conversion, output_state_dict, kwargs + ) + safe_save_file( + output_state_dict, + os.path.join(output_dir, SAFETENSORS_WEIGHTS_NAME), + metadata={"format": "pt"}, + ) + elif is_main_process: + if path_initial_model_for_weight_conversion is not None: + peft_config = copy.deepcopy(peft_config) + peft_config.init_lora_weights = True + peft_config.save_pretrained(path_initial_model_for_weight_conversion) + output_state_dict = save_mutated_as_lora( + peft_config, path_initial_model_for_weight_conversion, output_state_dict, kwargs + ) + torch.save(output_state_dict, os.path.join(output_dir, WEIGHTS_NAME)) + + # save the config and change the inference mode to `True` + if peft_config.base_model_name_or_path is None: + peft_config.base_model_name_or_path = ( + self.base_model.__dict__.get("name_or_path", None) + if peft_config.is_prompt_learning + else self.base_model.model.__dict__.get("name_or_path", None) + ) + inference_mode = peft_config.inference_mode + peft_config.inference_mode = True + + if peft_config.task_type is None: + # deal with auto mapping + base_model_class = self._get_base_model_class( + is_prompt_tuning=peft_config.is_prompt_learning, + ) + parent_library = base_model_class.__module__ + + auto_mapping_dict = { + "base_model_class": base_model_class.__name__, + "parent_library": parent_library, + } + else: + auto_mapping_dict = None + + if is_main_process: + if path_initial_model_for_weight_conversion is not None: + peft_config.init_lora_weights = True + peft_config.r *= 2 + if not peft_config.use_rslora: + peft_config.lora_alpha *= 2 + else: + # with rslora, we have scaling = alpha / sqrt(r), we thus adjust alpha to keep the same scaling + peft_config.lora_alpha *= 2**0.5 + + if peft_config.rank_pattern: + peft_config.rank_pattern = {key: 2 * val for key, val in peft_config.rank_pattern.items()} + if peft_config.alpha_pattern: + peft_config.alpha_pattern = {key: 2 * val for key, val in peft_config.alpha_pattern.items()} + + peft_config.save_pretrained(output_dir, auto_mapping_dict=auto_mapping_dict) + peft_config.inference_mode = inference_mode + + @classmethod + def from_pretrained( + cls, + model: torch.nn.Module, + model_id: Union[str, os.PathLike], + adapter_name: str = "default", + is_trainable: bool = False, + config: Optional[PeftConfig] = None, + autocast_adapter_dtype: bool = True, + ephemeral_gpu_offload: bool = False, + low_cpu_mem_usage: bool = False, + key_mapping: Optional[dict[str, str]] = None, + **kwargs: Any, + ) -> PeftModel: + r""" + Instantiate a PEFT model from a pretrained model and loaded PEFT weights. + + Note that the passed `model` may be modified inplace. + + Args: + model ([`torch.nn.Module`]): + The model to be adapted. For 🤗 Transformers models, the model should be initialized with the + [`~transformers.PreTrainedModel.from_pretrained`]. + model_id (`str` or `os.PathLike`): + The name of the PEFT configuration to use. Can be either: + - A string, the `model id` of a PEFT configuration hosted inside a model repo on the Hugging Face + Hub. + - A path to a directory containing a PEFT configuration file saved using the `save_pretrained` + method (`./my_peft_config_directory/`). + adapter_name (`str`, *optional*, defaults to `"default"`): + The name of the adapter to be loaded. This is useful for loading multiple adapters. + is_trainable (`bool`, *optional*, defaults to `False`): + Whether the adapter should be trainable or not. If `False`, the adapter will be frozen and can only be + used for inference. + config ([`~peft.PeftConfig`], *optional*): + The configuration object to use instead of an automatically loaded configuration. This configuration + object is mutually exclusive with `model_id` and `kwargs`. This is useful when configuration is already + loaded before calling `from_pretrained`. + autocast_adapter_dtype (`bool`, *optional*): + Whether to autocast the adapter dtype. Defaults to `True`. Only relevant for specific adapter types. + ephemeral_gpu_offload (`bool`, *optional*): + Whether to use ephemeral GPU offloading for partially loaded modules. Defaults to `False`. This is + useful when parts of the model and/or components (such as adapters) are kept in CPU memory until they + are needed. Rather than perform expensive operations on small data, the data is transferred to the GPU + on-demand, the operation(s) performed, and the results moved back to CPU memory. This brings a slight + momentary VRAM overhead but gives orders of magnitude speedup in certain cases. + low_cpu_mem_usage (`bool`, `optional`, defaults to `False`): + Create empty adapter weights on meta device before loading the saved weights. Useful to speed up the + process. + torch_device (`str`, *optional*, defaults to None): + The device to load the adapter on. If `None`, the device will be inferred. + key_mapping (dict, *optional*, defaults to None) + Extra mapping of PEFT `state_dict` keys applied before loading the `state_dict`. When this mapping is + applied, the PEFT-specific `"base_model.model"` prefix is removed beforehand and the adapter name (e.g. + `"default"`) is not inserted yet. Only pass this argument if you know what you're doing. + kwargs: (`optional`): + Additional keyword arguments passed along to the specific PEFT configuration class. + """ + from .auto import MODEL_TYPE_TO_PEFT_MODEL_MAPPING + from .tuners import XLoraConfig, XLoraModel + + # load the config + if config is None: + hf_kwargs = { + "subfolder": kwargs.get("subfolder", None), + "revision": kwargs.get("revision", None), + "cache_dir": kwargs.get("cache_dir", None), + "token": kwargs.get("token", None), + } + if use_auth_token := kwargs.get("use_auth_token", None): + hf_kwargs["use_auth_token"] = use_auth_token + config = PEFT_TYPE_TO_CONFIG_MAPPING[PeftConfig._get_peft_type(model_id, **hf_kwargs)].from_pretrained( + model_id, **kwargs + ) + elif isinstance(config, PeftConfig): + config.inference_mode = not is_trainable + else: + raise ValueError(f"The input config must be a PeftConfig, got {config.__class__}") + + # See discussion in https://github.com/huggingface/transformers/pull/38627 + # Some transformers models can have a _checkpoint_conversion_mapping dict that is used to map state_dicts + # stemming from updated model architectures so that they still correspond to the initial architecture. When + # loading a PEFT state_dict created with the initial architecture on a model with the new architecture, we need + # to map it too according to the same rules. Note that we skip prompt learning methods. This is because they + # don't have the "base_model.model." prefix, which we need to remove before mapping. Instead just using + # "base_model.". This could be fine, we could only remove "base_model.", However, the subsequent sub-module + # could also be called "model", resulting in what looks like "base_model.model.". To avoid this confusion, we + # skip prompt learning. Since it applies itself directly to the pre-trained model (unlike LoRA et al that target + # sub-modules), skipping should be fine. + if (key_mapping is None) and (not config.is_prompt_learning): + key_mapping = getattr(model, "_checkpoint_conversion_mapping", {}) + + # Runtime configuration, if supported + if hasattr(config, "runtime_config"): + config.runtime_config.ephemeral_gpu_offload = ephemeral_gpu_offload + else: + if ephemeral_gpu_offload: + warnings.warn("Ephemeral GPU offloading is not supported for this model. Ignoring.") + + if hasattr(model, "hf_device_map"): + weight_map = dict(named_module_tensors(model, recurse=True)) + + # recreate the offload_index for disk-offloaded modules: we need to know the location in storage of each weight + # before the offload hook is removed from the model + disk_modules = set() + index = None + for name, module in model.named_modules(): + if hasattr(module, "_hf_hook") and hasattr(module._hf_hook, "original_devices"): + if hasattr(module._hf_hook.weights_map, "dataset"): + index = module._hf_hook.weights_map.dataset.index + for key in module._hf_hook.original_devices.keys(): + if module._hf_hook.original_devices[key] == torch.device("meta"): + disk_modules.add(str(name) + "." + str(key)) + + if disk_modules and not kwargs.get("use_safetensors", True): + raise ValueError("Disk offloading currently only supported for safetensors") + + if index: + offload_index = { + p: { + "safetensors_file": index[p]["safetensors_file"], + "weight_name": p, + "dtype": str(weight_map[p].dtype).replace("torch.", ""), + } + for p in weight_map.keys() + if p in disk_modules + } + kwargs["offload_index"] = offload_index + + if (getattr(model, "hf_device_map", None) is not None) and len( + set(model.hf_device_map.values()).intersection({"cpu", "disk"}) + ) > 0: + remove_hook_from_submodules(model) + + if config.is_prompt_learning and is_trainable: + raise ValueError("Cannot set a prompt learning adapter to trainable when loading pretrained adapter.") + else: + config.inference_mode = not is_trainable + if isinstance(getattr(model, "base_model", None), XLoraModel): + if not isinstance(config, XLoraConfig): + raise TypeError(f"Expected 'XLoraConfig', got '{type(config)}' instead.") + if "adapters" in kwargs: + config.adapters = kwargs["adapters"] + else: + # If the path is on HF hub, then we get the adapter names to create a subfolders list which tells + # `load_adapter` where the adapters are. + if not os.path.exists(model_id): + s = HfFileSystem() + + # The names of the adapters which must be in folders + adapter_names = [ + file["name"][len(model_id) + 1 :] for file in s.ls(model_id) if file["type"] == "directory" + ] + # Prepare a dict of adapter paths, which really just point to the hf id; we will use the subfolders + adapter_paths = {} + for adapter_name in adapter_names: + adapter_paths[adapter_name] = os.path.join(model_id, model_id) + config.adapters = adapter_paths + config._subfolders = adapter_names + else: + if "adapters" not in kwargs: + raise ValueError("If model_id is a local path, then `adapters` must be passed in kwargs.") + + if config.task_type not in MODEL_TYPE_TO_PEFT_MODEL_MAPPING.keys(): + model = cls( + model, + config, + adapter_name, + autocast_adapter_dtype=autocast_adapter_dtype, + low_cpu_mem_usage=low_cpu_mem_usage, + ) + else: + model = MODEL_TYPE_TO_PEFT_MODEL_MAPPING[config.task_type]( + model, + config, + adapter_name, + autocast_adapter_dtype=autocast_adapter_dtype, + low_cpu_mem_usage=low_cpu_mem_usage, + ) + + load_result = model.load_adapter( + model_id, + adapter_name, + is_trainable=is_trainable, + autocast_adapter_dtype=autocast_adapter_dtype, + low_cpu_mem_usage=low_cpu_mem_usage, + key_mapping=key_mapping, + **kwargs, + ) + + # 1. Remove VB-LoRA vector bank, since it's a shared parameter set via the VBLoRAModel + # 2. Remove the prompt encoder, as it does not need to be part of the checkpoint + missing_keys = [ + k for k in load_result.missing_keys if "vblora_vector_bank" not in k and "prompt_encoder" not in k + ] + if missing_keys: + # Let's warn here since (in contrast to load_adapter) we don't return the load result, so it could be quite + # difficult for users to even notice that something might have gone wrong here. As we filter out non PEFT + # keys from the missing keys, this gives no false positives. + + # careful: if the wording of the warning is changed, adjust the unit tests accordingly! + warn_message = f"Found missing adapter keys while loading the checkpoint: {missing_keys}." + + prefix = PEFT_TYPE_TO_PREFIX_MAPPING.get(config.peft_type) + if prefix and adapter_name in prefix: + warn_message = ( + f"Adapter name '{adapter_name}' should not be contained in the prefix '{prefix}'. " + "This could be the potential reason for missing adapter keys. " + ) + warn_message + + warnings.warn(warn_message) + + return model + + def _setup_prompt_encoder(self, adapter_name: str): + config = self.peft_config[adapter_name] + if not hasattr(self, "prompt_encoder"): + self.prompt_encoder = torch.nn.ModuleDict({}) + self.prompt_tokens = {} + transformer_backbone = None + for name, module in self.base_model.named_children(): + for param in module.parameters(): + param.requires_grad = False + if isinstance(module, PreTrainedModel): + # Make sure to freeze Tranformers model + if transformer_backbone is None: + transformer_backbone = module + self.transformer_backbone_name = name + if transformer_backbone is None: + transformer_backbone = self.base_model + + if config.num_transformer_submodules is None: + config.num_transformer_submodules = 2 if config.task_type == TaskType.SEQ_2_SEQ_LM else 1 + + # determine the word embeddings + word_embeddings = None + try: + # First try to find the word embeddings based on the module name, this should work for models like Bert, + # Roberta, Deberta, etc. + word_embeddings = self.base_model.get_submodule("embeddings.word_embeddings") + except AttributeError: + pass + + if word_embeddings is None: + # Word embeddings could not be determined. Next try to guess them by checking which parameter has the size + # of the vocab. + for named_param, value in list(transformer_backbone.named_parameters()): + # for ZeRO-3, the tensor is sharded across accelerators and deepspeed modifies it to a tensor with shape + # [0] the actual unsharded shape is stored in "ds_shape" attribute special handling is needed in case + # the model is initialized in deepspeed.zero.Init() context or HfDeepSpeedConfig has been called before + # For reference refer to issue: https://github.com/huggingface/peft/issues/996 + deepspeed_distributed_tensor_shape = getattr(value, "ds_shape", None) + + # Handle VLM case with separate text and vision configs + if hasattr(self.base_model.config, "get_text_config"): + vocab_size = self.base_model.config.get_text_config().vocab_size + # below: for older transformers versions before get_text_config was added + elif "text_config" in self.base_model.config: + vocab_size = self.base_model.config.text_config.vocab_size + else: + vocab_size = self.base_model.config.vocab_size + + if value.shape[0] == vocab_size or ( + deepspeed_distributed_tensor_shape is not None + and deepspeed_distributed_tensor_shape[0] == vocab_size + ): + word_embeddings = transformer_backbone.get_submodule(named_param.replace(".weight", "")) + break + + self.word_embeddings = word_embeddings + model_cls = PEFT_TYPE_TO_TUNER_MAPPING[config.peft_type] + + if config.peft_type in (PeftType.PROMPT_TUNING, PeftType.MULTITASK_PROMPT_TUNING, PeftType.CPT): + prompt_encoder = model_cls(config, self.word_embeddings) + elif config.peft_type == PeftType.P_TUNING: + prompt_encoder = model_cls(config) + elif config.peft_type == PeftType.PREFIX_TUNING: + # prefix tuning now uses Cache but that won't work with gradient checkpointing + if any(getattr(module, "gradient_checkpointing", False) for module in self.get_base_model().modules()): + raise ValueError("Prefix tuning does not work with gradient checkpointing.") + prompt_encoder = model_cls(config) + else: + raise ValueError("Not supported") + + prompt_encoder = prompt_encoder.to(self.device) + self.prompt_encoder.update(torch.nn.ModuleDict({adapter_name: prompt_encoder})) + self.prompt_tokens[adapter_name] = torch.arange( + config.num_virtual_tokens * config.num_transformer_submodules + ).long() + + def prepare_model_for_gradient_checkpointing(self, model: PreTrainedModel): + r""" + Prepares the model for gradient checkpointing if necessary + """ + self._prepare_model_for_gradient_checkpointing(model) + + def _prepare_model_for_gradient_checkpointing(self, model: PreTrainedModel): + if not ( + getattr(model, "is_loaded_in_8bit", False) + or getattr(model, "is_loaded_in_4bit", False) + or getattr(model, "is_quantized", False) + ): + if hasattr(model, "enable_input_require_grads"): + model.enable_input_require_grads() + elif hasattr(model, "get_input_embeddings"): + + def make_inputs_require_grad(module, input, output): + output.requires_grad_(True) + + model.get_input_embeddings().register_forward_hook(make_inputs_require_grad) + return model + + def get_prompt_embedding_to_save(self, adapter_name: str) -> torch.Tensor: + """ + Returns the prompt embedding to save when saving the model. Only applicable when using a prompt learning + method. + """ + prompt_encoder = self.prompt_encoder[adapter_name] + prompt_tokens = ( + self.prompt_tokens[adapter_name].unsqueeze(0).expand(1, -1).to(prompt_encoder.embedding.weight.device) + ) + peft_type = self.peft_config[adapter_name].peft_type + if self.peft_config[adapter_name].peft_type == PeftType.PREFIX_TUNING: + prompt_tokens = prompt_tokens[:, : self.peft_config[adapter_name].num_virtual_tokens] + + if self.peft_config[adapter_name].peft_type == PeftType.MULTITASK_PROMPT_TUNING: + prompt_embedding_cls = PEFT_TYPE_TO_TUNER_MAPPING[peft_type] + prompt_embeddings = super(prompt_embedding_cls, prompt_encoder).forward(prompt_tokens) + else: + prompt_embeddings = prompt_encoder(prompt_tokens) + + return prompt_embeddings[0].detach().cpu() + + def get_prompt( + self, batch_size: int, task_ids: Optional[torch.Tensor] = None, max_cache_len: Optional[int] = None + ) -> torch.Tensor: + """ + Returns the virtual prompts to use for Peft. Only applicable when using a prompt learning method. + """ + peft_config = self.active_peft_config + prompt_encoder = self.prompt_encoder[self.active_adapter] + prompt_tokens = ( + self.prompt_tokens[self.active_adapter] + .unsqueeze(0) + .expand(batch_size, -1) + .to(prompt_encoder.embedding.weight.device) + ) + if peft_config.peft_type == PeftType.PREFIX_TUNING: + prompt_tokens = prompt_tokens[:, : peft_config.num_virtual_tokens] + if peft_config.inference_mode: + past_key_values = prompt_encoder.embedding.weight.repeat(batch_size, 1, 1) + else: + past_key_values = prompt_encoder(prompt_tokens) + if self.base_model_torch_dtype is not None: + past_key_values = past_key_values.to(self.base_model_torch_dtype) + past_key_values = past_key_values.view( + batch_size, + peft_config.num_virtual_tokens, + peft_config.num_layers * 2, + peft_config.num_attention_heads, + peft_config.token_dim // peft_config.num_attention_heads, + ) + if peft_config.num_transformer_submodules == 2: + past_key_values = torch.cat([past_key_values, past_key_values], dim=2) + + # Transpose: 2 x [num_layers, batch_size, num_heads, num_virtual_tokens, head_dim] + past_key_values = past_key_values.permute([2, 0, 3, 1, 4]).split( + peft_config.num_transformer_submodules * 2 + ) + + base_model = self.get_base_model() + model_config = getattr(base_model, "config", None) + model_type = getattr(model_config, "model_type", "") + if TRANSFORMERS_MODELS_TO_PREFIX_TUNING_POSTPROCESS_MAPPING.get(self.config.model_type, None) is not None: + post_process_fn = TRANSFORMERS_MODELS_TO_PREFIX_TUNING_POSTPROCESS_MAPPING[self.config.model_type] + past_key_values = post_process_fn(past_key_values) + elif ("gemma2" in model_type) or ("gemma3_text" in model_type): + # TODO: remove this logic once transformers < 4.56 is dropped + transformers_lt_4_56 = packaging.version.parse(transformers.__version__) < packaging.version.parse( + "4.56.0.dev0" + ) + # Gemma2 and Gemma3 only support HybridCache (which does not have the from_legacy_cache method) + if transformers_lt_4_56 and ((max_cache_len is None) or (max_cache_len == -1)): + raise ValueError( + "max_cache_len is missing but it should have been passed. Something went wrong, please open an " + "issue on GitHub with a reproducer: https://github.com/huggingface/peft/issues" + ) + base_config = base_model.config + if hasattr(base_config, "get_text_config"): + base_config = base_config.get_text_config() + if transformers_lt_4_56: + # HybridCache is deprecated, and will be removed in 4.60.0 + # see https://github.com/huggingface/transformers/pull/40276 + from transformers import HybridCache + + new_cache = HybridCache( + config=base_config, + max_batch_size=batch_size, + max_cache_len=max_cache_len, + dtype=past_key_values[0].dtype, + device=past_key_values[0].device, + ) + else: + # transformers 4.56+ uses DynamicCache for gemma + new_cache = DynamicCache(config=base_config) + cache_position = torch.arange(peft_config.num_virtual_tokens, device=past_key_values[0].device) + for layer_idx in range(peft_config.num_layers): + key_states, value_states = past_key_values[0][layer_idx], past_key_values[1][layer_idx] + new_cache.update( + key_states, value_states, layer_idx, cache_kwargs={"cache_position": cache_position} + ) + past_key_values = new_cache + elif peft_config.num_transformer_submodules == 1: + # Dont' apply this to encoder-decoder models and not to models requiring special processing. + # TODO: remove from_legacy_cache once transformers < 4.56 is dropped + transformers_lt_4_56 = packaging.version.parse(transformers.__version__) < packaging.version.parse( + "4.56.0.dev0" + ) + if transformers_lt_4_56: + past_key_values = DynamicCache.from_legacy_cache(past_key_values) + else: + past_key_values = DynamicCache(past_key_values) + + elif (peft_config.num_transformer_submodules == 2) and getattr( + self.base_model, "_supports_cache_class", True + ): + # Dont' apply this to encoder-decoder models that don't support new Cache format yet + # If we don't apply this, prefix-tuning fails to update cross-attn cache + # TODO: remove check for _supports_cache_class once transformers 4.53 is no longer supported + # TODO: remove from_legacy_cache once transformers < 4.56 is dropped + transformers_lt_4_56 = packaging.version.parse(transformers.__version__) < packaging.version.parse( + "4.56.0.dev0" + ) + if transformers_lt_4_56: + past_key_values = EncoderDecoderCache.from_legacy_cache(past_key_values) + else: + past_key_values = EncoderDecoderCache(past_key_values) + + past_key_values.cross_attention_cache = DynamicCache() + # invalidate the cross attention cache, since we add virtual tokens to the encoder + for key in past_key_values.is_updated.keys(): + past_key_values.is_updated[key] = False + map_cache_to_layer_device_map(self.get_base_model(), past_key_values) # no-op if not a Cache instance + return past_key_values + else: + if peft_config.peft_type == PeftType.MULTITASK_PROMPT_TUNING: + prompts = prompt_encoder(prompt_tokens, task_ids) + else: + if peft_config.inference_mode: + prompts = prompt_encoder.embedding.weight + else: + # Take only one prompt token sample and expand the output instead of expanding the input, see: + # https://github.com/huggingface/peft/issues/2043#issuecomment-2321522577 + prompt_tokens = prompt_tokens[:1] + prompts = prompt_encoder(prompt_tokens) + prompts = prompts.repeat(batch_size, 1, 1) + return prompts + + def get_nb_trainable_parameters(self) -> tuple[int, int]: + r""" + Returns the number of trainable parameters and the number of all parameters in the model. + """ + trainable_params = 0 + all_param = 0 + for _, param in self.named_parameters(): + num_params = param.numel() + # if using DS Zero 3 and the weights are initialized empty + if num_params == 0 and hasattr(param, "ds_numel"): + num_params = param.ds_numel + + # Due to the design of 4bit linear layers from bitsandbytes + # one needs to multiply the number of parameters by 2 to get + # the correct number of parameters + if param.__class__.__name__ == "Params4bit": + if hasattr(param, "element_size"): + num_bytes = param.element_size() + elif not hasattr(param, "quant_storage"): + num_bytes = 1 + else: + num_bytes = param.quant_storage.itemsize + num_params = num_params * 2 * num_bytes + + all_param += num_params + if param.requires_grad: + trainable_params += num_params + + return trainable_params, all_param + + def print_trainable_parameters(self) -> None: + """ + Prints the number of trainable parameters in the model. + + Note: print_trainable_parameters() uses get_nb_trainable_parameters() which is different from + num_parameters(only_trainable=True) from huggingface/transformers. get_nb_trainable_parameters() returns + (trainable parameters, all parameters) of the Peft Model which includes modified backbone transformer model. + For techniques like LoRA, the backbone transformer model is modified in place with LoRA modules. However, for + prompt tuning, the backbone transformer model is unmodified. num_parameters(only_trainable=True) returns number + of trainable parameters of the backbone transformer model which can be different. + """ + trainable_params, all_param = self.get_nb_trainable_parameters() + + print( + f"trainable params: {trainable_params:,d} || all params: {all_param:,d} || trainable%: {100 * trainable_params / all_param:.4f}" + ) + + def __getattr__(self, name: str): + """Forward missing attributes to the wrapped module.""" + try: + return super().__getattr__(name) # defer to nn.Module's logic + except AttributeError: + if name == "base_model": # see #1892: prevent infinite recursion if class is not initialized + raise + return getattr(self.base_model, name) + + @contextmanager + def _enable_peft_forward_hooks(self, *args, **kwargs): + # If the base model has a method called _enable_peft_forward_hooks, it is invoked as a context. Otherwise, this + # runs without any changes + if hasattr(self.base_model, "_enable_peft_forward_hooks") and self.has_active_enabled_adapter: + with self.base_model._enable_peft_forward_hooks(*args, **kwargs): + yield + return + else: + # nothing to enable + yield + return + + def forward(self, *args: Any, **kwargs: Any): + """ + Forward pass of the model. + """ + with self._enable_peft_forward_hooks(*args, **kwargs): + kwargs = {k: v for k, v in kwargs.items() if k not in self.special_peft_forward_args} + return self.get_base_model()(*args, **kwargs) + + def generate(self, *args, **kwargs): + with self._enable_peft_forward_hooks(*args, **kwargs): + kwargs = {k: v for k, v in kwargs.items() if k not in self.special_peft_forward_args} + return self.get_base_model().generate(*args, **kwargs) + + def _get_base_model_class(self, is_prompt_tuning=False): + """ + Returns the base model class. + """ + if not is_prompt_tuning: + return self.base_model.model.__class__ + return self.base_model.__class__ + + @contextmanager + def disable_adapter(self): + """ + Context manager that disables the adapter module. Use this to run inference on the base model. + + Example: + + ```py + >>> with model.disable_adapter(): + ... model(inputs) + ``` + """ + if self.peft_config[self.active_adapter].is_prompt_learning: + try: + # TODO: consider replacing this patching of methods with a more robust mechanism: setting a flag and + # letting the underlying methods deal with it, same as how LoRA does it. + old_forward = self.forward + self.forward = self.base_model.forward + old_prepare_inputs_for_generation = self.prepare_inputs_for_generation + self.prepare_inputs_for_generation = self.base_model.prepare_inputs_for_generation + self._adapters_disabled = True + yield + finally: + self.forward = old_forward + self.prepare_inputs_for_generation = old_prepare_inputs_for_generation + self._adapters_disabled = False + + elif self.peft_config[self.active_adapter].is_adaption_prompt: + try: + self.base_model.disable_adapter_layers() + self._adapters_disabled = True + yield + finally: + self.base_model.enable_adapter_layers() + self._adapters_disabled = False + + else: # LoRA, LoHa, etc. + model_status = self.get_model_status() + if model_status.enabled == "irregular": + warnings.warn( + "The model contains some adapter layers that are enabled and others that are disabled. " + "This is most likely unintentional. After exiting the disable_adapter context, all adapters " + "will be enabled" + ) + try: + self.base_model.disable_adapter_layers() + self._adapters_disabled = True + yield + finally: + if model_status.enabled is not False: + # model_status.enabled is `True` or `"irregular"` + self.base_model.enable_adapter_layers() + self._adapters_disabled = False + + def get_base_model(self) -> torch.nn.Module: + """ + Returns the base model. + """ + return self.base_model if self.active_peft_config.is_prompt_learning else self.base_model.model + + def add_adapter(self, adapter_name: str, peft_config: PeftConfig, low_cpu_mem_usage: bool = False) -> None: + """ + Add an adapter to the model based on the passed configuration. + + This adapter is not trained. To load a trained adapter, check out [`PeftModel.load_adapter`]. + + The name for the new adapter should be unique. + + The new adapter is not automatically set as the active adapter. Use [`PeftModel.set_adapter`] to set the active + adapter. + + Args: + adapter_name (`str`): + The name of the adapter to be added. + peft_config ([`PeftConfig`]): + The configuration of the adapter to be added. + low_cpu_mem_usage (`bool`, `optional`, defaults to `False`): + Create empty adapter weights on meta device. Useful to speed up the process when loading saved + adapters. Don't use this option when creating a new PEFT adapter for training. + + """ + prefix = PEFT_TYPE_TO_PREFIX_MAPPING.get(peft_config.peft_type) + if prefix and adapter_name in prefix: + warnings.warn( + f"Adapter name '{adapter_name}' should not be contained in the prefix '{prefix}'. " + "This may lead to reinitialization of the adapter weights during loading." + ) + + if peft_config.peft_type != self.peft_type: + raise ValueError( + f"Cannot combine adapters with different peft types. " + f"Found {self.peft_type} and {peft_config.peft_type}." + ) + + try: + if peft_config.is_prompt_learning: + self.peft_config[adapter_name] = peft_config + if hasattr(self.config, "to_dict"): + dict_config = self.config.to_dict() + else: + dict_config = self.config + + peft_config = _prepare_prompt_learning_config(peft_config, dict_config) + self._setup_prompt_encoder(adapter_name) + set_additional_trainable_modules( + model=self.base_model, + peft_config=peft_config, + model_config=BaseTuner.get_model_config(self), + adapter_name=adapter_name, + ) + elif peft_config.is_adaption_prompt: + self.base_model.add_adapter(adapter_name, peft_config) + set_additional_trainable_modules( + model=self.base_model, + peft_config=peft_config, + model_config=BaseTuner.get_model_config(self), + adapter_name=adapter_name, + ) + else: + self.peft_config[adapter_name] = peft_config + self.base_model.inject_adapter( + self.base_model.model, adapter_name, low_cpu_mem_usage=low_cpu_mem_usage + ) + except Exception: # something went wrong, roll back + if adapter_name in self.peft_config: + del self.peft_config[adapter_name] + raise + + def delete_adapter(self, adapter_name: str) -> None: + """ + Deletes an existing adapter. + + Args: + adapter_name (str): Name of the adapter to be deleted. + """ + if adapter_name not in self.peft_config: + raise ValueError(f"Adapter {adapter_name} does not exist") + + self.base_model.delete_adapter(adapter_name=adapter_name) + new_active_adapters = self.active_adapters + num_adapters = len(new_active_adapters) + # Note: PeftModel assumes that there is exactly one active adapter, so we should theoretically raise if + # num_adapters != 1. However, we have allowed this in the past (maybe inadvertently), so we let it slip and + # don't introduce a backwards incompatibility by raising an error. + if num_adapters == 1: + self.active_adapter = new_active_adapters[0] + + @property + def modules_to_save(self) -> Optional[set[str]]: + modules: set[str] = set() + for config in self.peft_config.values(): + if getattr(config, "modules_to_save", None) is not None: + # modules_to_save can only be a sequence of str, not a str + modules.update(config.modules_to_save) + + if not modules: + # for backwards compatibility, as modules_to_save was initialized as None + return None + return modules + + def get_layer_status(self) -> list[TunerLayerStatus]: + """Get the status of each adapter layer in the model. + + This method returns a list of `TunerLayerStatus` dataclass instances, each of which contains the following + attributes: + + - `name` (`str`): + The name of the adapter layer, e.g. `model.encoder.block.0.layer.0.SelfAttention.q`. + - `module_type` (`str`): + The type of the adapter layer, e.g. `lora.Linear`. + - `enabled` (`bool`): + Whether the adapter layer is enabled. + - `active_adapters` (`list[str]`): + The names of the active adapters, if any, e.g. `["default"]`. + - `merged_adapters` (`list[str]`): + The names of the merged adapters, if any, e.g. `["default"]`. + - `available_adapters` (`list[str]`): + The names of the available adapters, e.g. `["default"]`. + + Args: + model ([`~PeftModel`]): + The model to get the adapter layer status from. + + Returns: + list[`peft.peft_model.TunerLayerStatus`]: + A list of dataclasses, each containing the status of the corresponding adapter layer. + + """ + return get_layer_status(self) + + def get_model_status(self) -> TunerModelStatus: + """Get the status of tuners of the model. + + This method returns a `TunerModelStatus` dataclass instance, which contains the following attributes: + + - `base_model_type` (`str`): + The type of the base model, e.g. `T5Model`. + - `adapter_model_type` (`str`): + The type of the adapter model, e.g. `LoraModel`. + - `peft_types` (`dict[str, str]`): + The mapping of adapter name to adapter type, e.g. `{"default": "LORA"}`. + - `trainable_params` (`int`): + The number of trainable parameters in the model. + - `total_params` (`int`): + The total number of parameters in the model. + - `num_adapter_layers` (`int`): + The number of adapter layers in the model. + - `enabled` (`bool`, `Literal["irregular"]`): + Whether all adapter layers are enabled. If some are enabled and some are not, this will be `"irregular"`. + This means that your model is in an inconsistent state and might not work as expected. + - `active_adapters` (`list[str]`, `Literal["irregular"]`): + The names of the active adapters. If the active adapters are not consistent across all layers, this will be + `"irregular"`, which means that your model is in an inconsistent state and might not work as expected. + - `merged_adapters` (`list[str]`, `Literal["irregular"]`): + The names of the merged adapters. If the merged adapters are not consistent across all layers, this will be + `"irregular"`, which means that your model is in an inconsistent state and might not work as expected. + - `available_adapters` (`list[str]`): + The names of the available adapters, e.g. `["default"]`. + + Args: + model ([`~PeftModel`]): + The model to get the adapter layer status from. + + Returns: + `peft.peft_model.TunerModelStatus`: + A dataclass containing the status of the model. + + """ + return get_model_status(self) + + @classmethod + def _split_kwargs(cls, kwargs: dict[str, Any]): + _kwargs_not_in_hf_hub_download_signature = ("use_auth_token",) + hf_hub_download_kwargs = {} + other_kwargs = {} + + for key, value in kwargs.items(): + if key in inspect.signature(hf_hub_download).parameters or key in _kwargs_not_in_hf_hub_download_signature: + hf_hub_download_kwargs[key] = value + else: + other_kwargs[key] = value + + return hf_hub_download_kwargs, other_kwargs + + def _update_offload(self, offload_index: dict[str, dict[str, str]], adapters_weights: dict[str, torch.tensor]): + """ + Update the offload_index and safetensors files for loading and mergine PeftModels with disk-offloaded modules. + + Args: + offload_index (Dict[str: str]): + Dictionary of disk-offloaded modules with their metadata and safetensors filenames + adapters_weights (Dict[str: torch.tensor]): + Dictionary of Peft adapter module names and weights + """ + + if not offload_index: + return offload_index + + prefix = "base_model.model." + # rename offload index weight and model names + adapter_names = list(self.peft_config.keys()) + for adapter_name in adapter_names: + keys = list(offload_index.keys()) + block_id = keys[0].split(".")[0] + "." # for writing safetensors key, + + # replace original offload index keys with PeftModel keys + for key in keys: + suffix_pos = key.rfind(".") + extended_prefix = prefix + key[:suffix_pos] + module = dict(self.named_modules())[extended_prefix] + if isinstance(module, BaseTunerLayer): + new_key = prefix + key[:suffix_pos] + ".base_layer" + key[suffix_pos:] + else: + new_key = prefix + key + offload_index[key]["weight_name"] = new_key + offload_index[new_key] = offload_index[key] + del offload_index[key] + + files_seen = set() + # rename safetensors for dispatch + for new_key in list(offload_index.keys()): + fname = offload_index[new_key]["safetensors_file"] + + # make a new file name + new_fname_list = list(fname.split(os.sep)) + for i, name in enumerate(new_fname_list): + if "--" in name: + new_fname_list[i] += "-peft" + break + new_fname = os.path.join(*new_fname_list) + + if fname in files_seen: + continue + safe_dict = {} + with safe_open(fname, framework="pt") as f: + for safe_key in f.keys(): + safe_tensor = f.get_tensor(safe_key) + metadata = f.metadata() + suffix_pos = safe_key.rfind(".") + extended_prefix = prefix + block_id + safe_key[:suffix_pos] + safe_module = dict(self.named_modules())[extended_prefix] + if isinstance(safe_module, BaseTunerLayer): + final_key = extended_prefix + ".base_layer" + safe_key[suffix_pos:] + lora_dict = {key: val for key, val in adapters_weights.items() if extended_prefix in key} + + # add LoRA keys and values to disk offload + for lora_key, lora_val in lora_dict.items(): + divide = lora_key.rfind(".") + new_key = lora_key[:divide] + f".{adapter_name}" + lora_key[divide:] + safe_dict[new_key] = lora_val + else: + final_key = prefix + block_id + safe_key + safe_dict[final_key] = safe_tensor + files_seen.add(new_fname) + + # avoid overwriting original safetensors + for key in safe_dict.keys(): + offload_index[key] = {"safetensors_file": new_fname, "weight_name": key} + + base_name = os.path.dirname(new_fname) + if not os.path.exists(base_name): + os.makedirs(base_name) + safe_save_file(safe_dict, new_fname, metadata=metadata) + + def _check_new_adapter_config(self, peft_config: PeftConfig, is_trainable: bool) -> None: + """Perform checks on newly added PEFT configs to ensure integrity.""" + if peft_config.is_prompt_learning and is_trainable: + raise ValueError("Cannot set a prompt learning adapter to trainable when loading pretrained adapter.") + + # Since PiSSA/CorDA/OLoRA modifies the base weights, it should not be combined with other adapters. + all_configs = [peft_config] + list(self.peft_config.values()) + if len(all_configs) > 1: + if any(getattr(config, "init_lora_weights", None) == "pissa" for config in all_configs): + msg = ( + "PiSSA changes the base weights of the model and should thus not be used with other adapters. " + "Consider converting the PiSSA adapter into a normal LoRA adapter: " + "https://github.com/huggingface/peft/tree/main/examples/pissa_finetuning#convert-pissa-to-lora" + ) + warnings.warn(msg) + elif any(getattr(config, "init_lora_weights", None) == "corda" for config in all_configs): + msg = ( + "CorDA changes the base weights of the model and should thus not be used with other adapters. " + "Consider converting the CorDA adapter into a normal LoRA adapter: " + "https://github.com/huggingface/peft/tree/main/examples/corda_finetuning#convert-corda-to-lora" + ) + warnings.warn(msg) + elif any(getattr(config, "init_lora_weights", None) == "olora" for config in all_configs): + msg = ( + "OLoRA changes the base weights of the model and should thus not be used with other adapters. " + "Consider converting the OLoRA adapter into a normal LoRA adapter: " + "https://github.com/huggingface/peft/tree/main/examples/olora_finetuning#olora-and-lora" + ) + warnings.warn(msg) + + def load_adapter( + self, + model_id: Union[str, os.PathLike], + adapter_name: str, + is_trainable: bool = False, + torch_device: Optional[str] = None, + autocast_adapter_dtype: bool = True, + ephemeral_gpu_offload: bool = False, + low_cpu_mem_usage: bool = False, + key_mapping: Optional[dict[str, str]] = None, + **kwargs: Any, + ): + """ + Load a trained adapter into the model. + + The name for the new adapter should be unique. + + The new adapter is not automatically set as the active adapter. Use [`PeftModel.set_adapter`] to set the active + adapter. + + Args: + model_id (`str` or `os.PathLike`): + The name of the PEFT configuration to use. Can be either: + - A string, the `model id` of a PEFT configuration hosted inside a model repo on the Hugging Face + Hub. + - A path to a directory containing a PEFT configuration file saved using the `save_pretrained` + method (`./my_peft_config_directory/`). + adapter_name (`str`): + The name of the adapter to be added. + is_trainable (`bool`, *optional*, defaults to `False`): + Whether the adapter should be trainable or not. If `False`, the adapter will be frozen and can only be + used for inference. + torch_device (`str`, *optional*, defaults to None): + The device to load the adapter on. If `None`, the device will be inferred. + autocast_adapter_dtype (`bool`, *optional*, defaults to `True`): + Whether to autocast the adapter dtype. Defaults to `True`. Right now, this will only cast adapter + weights using float16 and bfloat16 to float32, as this is typically required for stable training, and + only affect select PEFT tuners. + ephemeral_gpu_offload (`bool`, *optional*, defaults to `False`): + Whether to use ephemeral GPU offloading for partially loaded modules. Defaults to `False`. + low_cpu_mem_usage (`bool`, `optional`, defaults to `False`): + Create empty adapter weights on meta device before loading the saved weights. Useful to speed up the + process. + key_mapping (dict, *optional*, defaults to None) + Extra mapping of PEFT `state_dict` keys applied before loading the `state_dict`. When this mapping is + applied, the PEFT-specific `"base_model.model"` prefix is removed beforehand and the adapter name (e.g. + `"default"`) is not inserted yet. Only pass this argument if you know what you're doing. + kwargs: (`optional`): + Additional arguments to modify the way the adapter is loaded, e.g. the token for Hugging Face Hub. + """ + from .mapping import PEFT_TYPE_TO_CONFIG_MAPPING + + hf_hub_download_kwargs, kwargs = self._split_kwargs(kwargs) + if torch_device is None: + torch_device = infer_device() + + if adapter_name not in self.peft_config: + # load the config + peft_config = PEFT_TYPE_TO_CONFIG_MAPPING[ + PeftConfig._get_peft_type( + model_id, + **hf_hub_download_kwargs, + ) + ].from_pretrained( + model_id, + ephemeral_gpu_offload=ephemeral_gpu_offload, + **hf_hub_download_kwargs, + ) + self._check_new_adapter_config(peft_config, is_trainable=is_trainable) + peft_config.inference_mode = not is_trainable + self.add_adapter(adapter_name, peft_config, low_cpu_mem_usage=low_cpu_mem_usage) + + adapters_weights = load_peft_weights( + model_id, device=torch_device, key_mapping=key_mapping, **hf_hub_download_kwargs + ) + + # load the weights into the model + ignore_mismatched_sizes = kwargs.get("ignore_mismatched_sizes", False) + load_result = set_peft_model_state_dict( + self, + adapters_weights, + adapter_name=adapter_name, + ignore_mismatched_sizes=ignore_mismatched_sizes, + low_cpu_mem_usage=low_cpu_mem_usage, + ) + + tuner = self.peft_config[adapter_name].peft_type + tuner_prefix = PEFT_TYPE_TO_PREFIX_MAPPING.get(tuner, "") + adapter_missing_keys = [] + + # Filter missing keys specific to the current adapter and tuner prefix. + for key in load_result.missing_keys: + if tuner_prefix in key and adapter_name in key: + adapter_missing_keys.append(key) + + load_result.missing_keys.clear() + load_result.missing_keys.extend(adapter_missing_keys) + + if ( + (getattr(self, "hf_device_map", None) is not None) + and (len(set(self.hf_device_map.values()).intersection({"cpu", "disk"})) > 0) + and len(self.peft_config) == 1 + ): + device_map = kwargs.get("device_map", "auto") + max_memory = kwargs.get("max_memory", None) + offload_folder = kwargs.get("offload_folder", None) + offload_dir = kwargs.get("offload_dir", None) + offload_index = kwargs.get("offload_index", None) + + if offload_dir is not None and offload_folder is not None: + # see https://github.com/huggingface/peft/issues/2541 + raise ValueError("Cannot use `offload_folder` when `offload_dir` is specified.") + elif offload_dir is None: + # to keep backwards compatibility + offload_dir = offload_folder + + dispatch_model_kwargs = {} + # Safety checker for previous `accelerate` versions + # `offload_index` was introduced in https://github.com/huggingface/accelerate/pull/873/ + if "offload_index" in inspect.signature(dispatch_model).parameters: + dispatch_model_kwargs["offload_index"] = offload_index + + no_split_module_classes = self._no_split_modules + + if device_map != "sequential": + max_memory = get_balanced_memory( + self, + max_memory=max_memory, + no_split_module_classes=no_split_module_classes, + low_zero=(device_map == "balanced_low_0"), + ) + + if isinstance(device_map, str): + device_map = infer_auto_device_map( + self, max_memory=max_memory, no_split_module_classes=no_split_module_classes + ) + + self._update_offload(offload_index, adapters_weights) + dispatch_model_kwargs["offload_index"] = offload_index + + dispatch_model( + self, + device_map=device_map, + offload_dir=offload_dir, + **dispatch_model_kwargs, + ) + + hook = AlignDevicesHook(io_same_device=True) + if self.peft_config[adapter_name].is_prompt_learning: + remove_hook_from_submodules(self.prompt_encoder) + add_hook_to_module(self.get_base_model(), hook) + + if hasattr(self.base_model, "_cast_adapter_dtype"): + self.base_model._cast_adapter_dtype( + adapter_name=adapter_name, autocast_adapter_dtype=autocast_adapter_dtype + ) + + # Set model in evaluation mode to deactivate Dropout modules by default + if not is_trainable: + self.eval() + return load_result + + def set_adapter(self, adapter_name: str) -> None: + """ + Sets the active adapter. + + Only one adapter can be active at a time. + + Additionally, this function will set the specified adapter to trainable (i.e., requires_grad=True). If this is + not desired, use the following code. + + ```py + >>> for name, param in model_peft.named_parameters(): + ... if ...: # some check on name (ex. if 'lora' in name) + ... param.requires_grad = False + ``` + + Args: + adapter_name (`str`): + The name of the adapter to be set as active. The adapter must be loaded first. + """ + if adapter_name not in self.peft_config: + raise ValueError(f"Adapter {adapter_name} not found.") + self.active_adapter = adapter_name + if not self.peft_config[adapter_name].is_prompt_learning: + # _set_adapter does not need to be called, since it's called through the BaseTuner class. + self.base_model.set_adapter(adapter_name) + else: + # handle auxiliary modules + _set_adapter(self, adapter_name) + + def set_requires_grad(self, adapter_names: str | Sequence[str], requires_grad: bool = True) -> None: + """ + Enable or disable gradients on the given adapter(s). + + Note: Not supported for prompt learning methods like prompt tuning. + + Args: + adapter_name (`str` or `Sequence[str]`): + The name of the adapter(s) whose gradients should be enabled/disabled. + requires_grad (`bool`, *optional*) + Whether to enable (`True`, default) or disable (`False`). + """ + if self.active_peft_config.is_prompt_learning: + raise TypeError( + "Setting `requires_grad` is not supported for prompt learning methods like " + f"{self.active_peft_config.peft_type.value}." + ) + + self.base_model.set_requires_grad(adapter_names=adapter_names, requires_grad=requires_grad) + + @property + def base_model_torch_dtype(self): + return getattr(self.base_model, "dtype", None) + + @property + def active_peft_config(self): + return self.peft_config[self.active_adapter] + + def _get_peft_specific_model_tags(self): + """Derive tags for the model card from the adapter's config. For example, setting the + base model is important for enabling support for HF inference providers but it also makes models more + searchable on the HF hub. + """ + peft_method = self.active_peft_config.peft_type + if not isinstance(peft_method, str): + peft_method = peft_method.value + + tags = [] + + if hasattr(self.base_model, "model") and isinstance(self.base_model.model, transformers.PreTrainedModel): + tags.append("transformers") + + if peft_method == "LORA": + tags.append("lora") + + if hasattr(self.base_model, "name_or_path"): + tags.append(f"base_model:adapter:{self.base_model.name_or_path}") + + return tags + + def create_or_update_model_card(self, output_dir: str): + """ + Updates or create model card to include information about peft: + 1. Adds `peft` library tag + 2. Adds peft version + 3. Adds base model info + 4. Adds quantization information if it was used + """ + + filename = os.path.join(output_dir, "README.md") + + card = ModelCard.load(filename) if os.path.exists(filename) else ModelCard.from_template(ModelCardData()) + + card.data["library_name"] = "peft" + + tags = set() + base_model = self.get_base_model() + if hasattr(base_model, "model_tags"): + tags = tags.union(base_model.model_tags or []) + + tags = tags.union(self._get_peft_specific_model_tags()) + if tags: + card.data["tags"] = sorted(tags) + + # One of the rare moments where we can select the pipeline tag with certainty, so let's do that. + # Makes it easier to deploy an adapter with auto inference since the user doesn't have to add any tags. + if not card.data.pipeline_tag and isinstance(self, PeftModelForCausalLM): + card.data.pipeline_tag = "text-generation" + + model_config = BaseTuner.get_model_config(self) + model_config = None if model_config == DUMMY_MODEL_CONFIG else model_config + if model_config is not None and "_name_or_path" in model_config: + card.data["base_model"] = model_config["_name_or_path"] + + lines = card.text.splitlines() + + quantization_config = None + if hasattr(model_config, "quantization_config"): + quantization_config = self.config.quantization_config.to_dict() + training_config_text = "" + quantization_prefix = "The following `bitsandbytes` quantization config was used during training:" + # Adds quantization information if it was used + if quantization_config is not None: + training_config_text += f"\n{quantization_prefix}\n" + training_config_text += "\n".join([f"- {name}: {value}" for name, value in quantization_config.items()]) + training_config_text += "\n" + + training_procedure_heading = "## Training procedure" + if quantization_prefix not in lines and bool(training_config_text): + if training_procedure_heading in lines: + lines.insert(lines.index(training_procedure_heading) + 2, training_config_text) + else: + lines.append(f"{training_procedure_heading}\n{training_config_text}") + + # Adds peft version + framework_block_heading = "### Framework versions" + if f"- PEFT {__version__}" not in lines: + if framework_block_heading in lines: + lines.insert(lines.index(framework_block_heading) + 2, f"- PEFT {__version__}") + else: + lines.append(f"{framework_block_heading}\n\n- PEFT {__version__}") + + card.text = "\n".join(lines) + card.save(filename) + + +class PeftModelForSequenceClassification(PeftModel): + """ + Peft model for sequence classification tasks. + + Args: + model ([`~transformers.PreTrainedModel`]): Base transformer model. + peft_config ([`PeftConfig`]): Peft config. + adapter_name (`str`, *optional*): The name of the adapter, defaults to `"default"`. + autocast_adapter_dtype (`bool`, *optional*): + Whether to autocast the adapter dtype. Defaults to `True`. Right now, this will only cast adapter weights + using float16 and bfloat16 to float32, as this is typically required for stable training, and only affect + select PEFT tuners. + + **Attributes**: + - **config** ([`~transformers.PretrainedConfig`]) -- The configuration object of the base model. + - **cls_layer_name** (`str`) -- The name of the classification layer. + + Example: + + ```py + >>> from transformers import AutoModelForSequenceClassification + >>> from peft import PeftModelForSequenceClassification, get_peft_config + + >>> config = { + ... "peft_type": "PREFIX_TUNING", + ... "task_type": "SEQ_CLS", + ... "inference_mode": False, + ... "num_virtual_tokens": 20, + ... "token_dim": 768, + ... "num_transformer_submodules": 1, + ... "num_attention_heads": 12, + ... "num_layers": 12, + ... "encoder_hidden_size": 768, + ... "prefix_projection": False, + ... "postprocess_past_key_value_function": None, + ... } + + >>> peft_config = get_peft_config(config) + >>> model = AutoModelForSequenceClassification.from_pretrained("bert-base-cased") + >>> peft_model = PeftModelForSequenceClassification(model, peft_config) + >>> peft_model.print_trainable_parameters() + trainable params: 370178 || all params: 108680450 || trainable%: 0.3406113979101117 + ``` + """ + + def __init__( + self, model: torch.nn.Module, peft_config: PeftConfig, adapter_name: str = "default", **kwargs + ) -> None: + classifier_module_names = ["classifier", "score"] + + if hasattr(peft_config, "modules_to_save"): + if peft_config.modules_to_save is None: + peft_config.modules_to_save = classifier_module_names[:] + else: + peft_config.modules_to_save.extend(classifier_module_names) + + # The modification of peft_config must happen before the init call as the `modules_to_save` information + # will be used to guard the target layer matching against matching `modules_to_save` layers. Only the + # config is relevant for this, the `modules_to_save` attribute can follow later. + super().__init__(model, peft_config, adapter_name, **kwargs) + + if hasattr(peft_config, "modules_to_save"): + for name, _ in self.base_model.named_children(): + if any(module_name in name for module_name in self.modules_to_save): + self.cls_layer_name = name + break + + # to make sure classifier layer is trainable; this may add a new ModulesToSaveWrapper + _set_trainable( + self, + adapter_name, + module_names=getattr(peft_config, "modules_to_save", None), + inference_mode=peft_config.inference_mode, + ) + + def add_adapter(self, adapter_name: str, peft_config: PeftConfig, low_cpu_mem_usage: bool = False) -> None: + """ + Add an adapter to the model based on the passed configuration. + + This adapter is not trained. To load a trained adapter, check out [`PeftModel.load_adapter`]. + + The name for the new adapter should be unique. + + The new adapter is not automatically set as the active adapter. Use [`PeftModel.set_adapter`] to set the active + adapter. + + Args: + adapter_name (`str`): + The name of the adapter to be added. + peft_config ([`PeftConfig`]): + The configuration of the adapter to be added. + low_cpu_mem_usage (`bool`, `optional`, defaults to `False`): + Create empty adapter weights on meta device. Useful to speed up the process when loading saved + adapters. Don't use this option when creating a new PEFT adapter for training. + + """ + # ensure that additional adapters also add the classifier layer to modules_to_save + if hasattr(peft_config, "modules_to_save"): + classifier_module_names = ["classifier", "score"] + if peft_config.modules_to_save is None: + peft_config.modules_to_save = classifier_module_names[:] + else: + peft_config.modules_to_save.extend(classifier_module_names) + + return super().add_adapter(adapter_name, peft_config, low_cpu_mem_usage=low_cpu_mem_usage) + + def forward( + self, + input_ids=None, + attention_mask=None, + inputs_embeds=None, + labels=None, + output_attentions=None, + output_hidden_states=None, + return_dict=None, + task_ids=None, + **kwargs, + ): + return_dict = return_dict if return_dict is not None else self.config.use_return_dict + peft_config = self.active_peft_config + if not peft_config.is_prompt_learning: + with self._enable_peft_forward_hooks(**kwargs): + kwargs = {k: v for k, v in kwargs.items() if k not in self.special_peft_forward_args} + if peft_config.peft_type == PeftType.POLY: + kwargs["task_ids"] = task_ids + return self.base_model( + input_ids=input_ids, + attention_mask=attention_mask, + inputs_embeds=inputs_embeds, + labels=labels, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + return_dict=return_dict, + **kwargs, + ) + + batch_size = _get_batch_size(input_ids, inputs_embeds) + if attention_mask is not None: + # concat prompt attention mask + prefix_attention_mask = torch.ones(batch_size, peft_config.num_virtual_tokens).to(attention_mask.device) + attention_mask = torch.cat((prefix_attention_mask, attention_mask), dim=1) + if kwargs.get("position_ids", None) is not None: + warnings.warn("Position ids are not supported for parameter efficient tuning. Ignoring position ids.") + kwargs["position_ids"] = None + kwargs.update( + { + "attention_mask": attention_mask, + "labels": labels, + "output_attentions": output_attentions, + "output_hidden_states": output_hidden_states, + "return_dict": return_dict, + } + ) + + if peft_config.peft_type == PeftType.PREFIX_TUNING: + return self._prefix_tuning_forward(input_ids=input_ids, **kwargs) + else: + if kwargs.get("token_type_ids", None) is not None: + kwargs["token_type_ids"] = torch.cat( + ( + torch.zeros(batch_size, peft_config.num_virtual_tokens).to(self.word_embeddings.weight.device), + kwargs["token_type_ids"], + ), + dim=1, + ).long() + if inputs_embeds is None: + inputs_embeds = self.word_embeddings(input_ids) + prompts = self.get_prompt(batch_size=batch_size, task_ids=task_ids) + prompts = prompts.to(inputs_embeds.dtype) + inputs_embeds = torch.cat((prompts, inputs_embeds), dim=1) + return self.base_model(inputs_embeds=inputs_embeds, **kwargs) + + def _prefix_tuning_forward( + self, + input_ids=None, + attention_mask=None, + inputs_embeds=None, + labels=None, + output_attentions=None, + output_hidden_states=None, + return_dict=None, + **kwargs, + ): + batch_size = _get_batch_size(input_ids, inputs_embeds) + past_key_values = self.get_prompt(batch_size) + fwd_params = list(inspect.signature(self.base_model.forward).parameters.keys()) + kwargs.update( + { + "input_ids": input_ids, + "attention_mask": attention_mask, + "inputs_embeds": inputs_embeds, + "output_attentions": output_attentions, + "output_hidden_states": output_hidden_states, + "return_dict": return_dict, + "past_key_values": past_key_values, + } + ) + if "past_key_values" in fwd_params: + return self.base_model(labels=labels, **kwargs) + else: + transformer_backbone_name = self.base_model.get_submodule(self.transformer_backbone_name) + fwd_params = list(inspect.signature(transformer_backbone_name.forward).parameters.keys()) + if "past_key_values" not in fwd_params: + raise ValueError("Model does not support past key values which are required for prefix tuning.") + outputs = transformer_backbone_name(**kwargs) + pooled_output = outputs[1] if len(outputs) > 1 else outputs[0] + if "dropout" in [name for name, _ in list(self.base_model.named_children())]: + pooled_output = self.base_model.dropout(pooled_output) + logits = self.base_model.get_submodule(self.cls_layer_name)(pooled_output) + + loss = None + if labels is not None: + if self.config.problem_type is None: + if self.base_model.num_labels == 1: + self.config.problem_type = "regression" + elif self.base_model.num_labels > 1 and (labels.dtype == torch.long or labels.dtype == torch.int): + self.config.problem_type = "single_label_classification" + else: + self.config.problem_type = "multi_label_classification" + + if self.config.problem_type == "regression": + loss_fct = MSELoss() + if self.base_model.num_labels == 1: + loss = loss_fct(logits.squeeze(), labels.squeeze()) + else: + loss = loss_fct(logits, labels) + elif self.config.problem_type == "single_label_classification": + loss_fct = CrossEntropyLoss() + loss = loss_fct(logits.view(-1, self.base_model.num_labels), labels.view(-1)) + elif self.config.problem_type == "multi_label_classification": + loss_fct = BCEWithLogitsLoss() + loss = loss_fct(logits, labels) + if not return_dict: + output = (logits,) + outputs[2:] + return ((loss,) + output) if loss is not None else output + + return SequenceClassifierOutput( + loss=loss, + logits=logits, + hidden_states=outputs.hidden_states, + attentions=outputs.attentions, + ) + + +class PeftModelForCausalLM(PeftModel): + """ + Peft model for causal language modeling. + + Args: + model ([`~transformers.PreTrainedModel`]): Base transformer model. + peft_config ([`PeftConfig`]): Peft config. + adapter_name (`str`, *optional*): The name of the adapter, defaults to `"default"`. + autocast_adapter_dtype (`bool`, *optional*): + Whether to autocast the adapter dtype. Defaults to `True`. Right now, this will only cast adapter weights + using float16 and bfloat16 to float32, as this is typically required for stable training, and only affect + select PEFT tuners. + + Example: + + ```py + >>> from transformers import AutoModelForCausalLM + >>> from peft import PeftModelForCausalLM, get_peft_config + + >>> config = { + ... "peft_type": "PREFIX_TUNING", + ... "task_type": "CAUSAL_LM", + ... "inference_mode": False, + ... "num_virtual_tokens": 20, + ... "token_dim": 1280, + ... "num_transformer_submodules": 1, + ... "num_attention_heads": 20, + ... "num_layers": 36, + ... "encoder_hidden_size": 1280, + ... "prefix_projection": False, + ... "postprocess_past_key_value_function": None, + ... } + + >>> peft_config = get_peft_config(config) + >>> model = AutoModelForCausalLM.from_pretrained("gpt2-large") + >>> peft_model = PeftModelForCausalLM(model, peft_config) + >>> peft_model.print_trainable_parameters() + trainable params: 1843200 || all params: 775873280 || trainable%: 0.23756456724479544 + ``` + """ + + def __init__( + self, model: torch.nn.Module, peft_config: PeftConfig, adapter_name: str = "default", **kwargs + ) -> None: + super().__init__(model, peft_config, adapter_name, **kwargs) + self.base_model_prepare_inputs_for_generation = self.base_model.prepare_inputs_for_generation + + def forward( + self, + input_ids=None, + attention_mask=None, + inputs_embeds=None, + labels=None, + output_attentions=None, + output_hidden_states=None, + return_dict=None, + task_ids=None, + **kwargs, + ): + peft_config = self.active_peft_config + + if not peft_config.is_prompt_learning: + # Adds alora_offsets to kwargs if relevant. No other modifications. + kwargs = get_alora_offsets_for_forward(self, input_ids, inputs_embeds, **kwargs) + if self.base_model.config.model_type == "mpt": + if inputs_embeds is not None: + raise AssertionError("forward in MPTForCausalLM does not support inputs_embeds") + return self.base_model( + input_ids=input_ids, + attention_mask=attention_mask, + labels=labels, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + return_dict=return_dict, + **kwargs, + ) + + if peft_config.peft_type == PeftType.POLY: + kwargs["task_ids"] = task_ids + + with self._enable_peft_forward_hooks(**kwargs): + kwargs = {k: v for k, v in kwargs.items() if k not in self.special_peft_forward_args} + return self.base_model( + input_ids=input_ids, + attention_mask=attention_mask, + inputs_embeds=inputs_embeds, + labels=labels, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + return_dict=return_dict, + **kwargs, + ) + + batch_size = _get_batch_size(input_ids, inputs_embeds) + if attention_mask is not None: + # concat prompt attention mask + prefix_attention_mask = torch.ones(batch_size, peft_config.num_virtual_tokens).to(attention_mask.device) + attention_mask = torch.cat((prefix_attention_mask, attention_mask), dim=1) + + if kwargs.get("position_ids", None) is not None: + warnings.warn("Position ids are not supported for parameter efficient tuning. Ignoring position ids.") + kwargs["position_ids"] = None + if kwargs.get("token_type_ids", None) is not None: + warnings.warn("Token type ids are not supported for parameter efficient tuning. Ignoring token type ids") + kwargs["token_type_ids"] = None + kwargs.update( + { + "attention_mask": attention_mask, + "labels": labels, + "output_attentions": output_attentions, + "output_hidden_states": output_hidden_states, + "return_dict": return_dict, + } + ) + + if peft_config.peft_type == PeftType.PREFIX_TUNING: + # overwrite past_kv in kwargs + # some archs require max_cache_len to re-initialize the cache + if input_ids is not None: + max_cache_len = input_ids.shape[1] + peft_config.num_virtual_tokens + else: + max_cache_len = inputs_embeds.shape[1] + peft_config.num_virtual_tokens + kwargs["past_key_values"] = self.get_prompt(batch_size, max_cache_len=max_cache_len) + return self.base_model(input_ids=input_ids, inputs_embeds=inputs_embeds, **kwargs) + elif peft_config.peft_type == PeftType.CPT: + return self._cpt_forward(input_ids, inputs_embeds, peft_config, task_ids, batch_size, **kwargs) + else: + if inputs_embeds is None: + inputs_embeds = self.word_embeddings(input_ids) + # concat prompt labels + if labels is not None: + prefix_labels = torch.full((batch_size, peft_config.num_virtual_tokens), -100).to(labels.device) + kwargs["labels"] = torch.cat((prefix_labels, labels), dim=1) + prompts = self.get_prompt(batch_size=batch_size, task_ids=task_ids) + prompts = prompts.to(inputs_embeds.dtype) + inputs_embeds = torch.cat((prompts, inputs_embeds), dim=1) + return self.base_model(inputs_embeds=inputs_embeds, **kwargs) + + def _cpt_forward(self, input_ids, inputs_embeds, peft_config, task_ids, batch_size, **kwargs): + # Extract labels from kwargs + labels = kwargs.pop("labels") + device = [i.device for i in [input_ids, inputs_embeds, labels] if i is not None][0] + # Extract input_type_mask from kwargs and move it to the same device as labels + if "input_type_mask" in kwargs.keys(): + input_type_mask = kwargs.pop("input_type_mask").to(device) + else: + if input_ids is None: + N_tokens = inputs_embeds.shape[1] + else: + N_tokens = input_ids.shape[1] + input_type_mask = torch.ones((batch_size, N_tokens)).to(device) * 4 + + cpt_token_ids = peft_config.cpt_token_ids + cpt_tokens_type_mask = peft_config.cpt_tokens_type_mask + + # Generate embeddings if not provided + if inputs_embeds is None: + inputs_embeds = self.word_embeddings(input_ids) + # Get prompt and concatenate with input embeddings + prompts = self.get_prompt(batch_size=batch_size, task_ids=task_ids) + prompts = prompts.to(inputs_embeds.dtype) + inputs_embeds = torch.cat((prompts, inputs_embeds), dim=1) + # If labels are provided, generate prefix labels and type mask + cpt_labels = None + if labels is not None: + # Generate prefix labels and concatenate with the input labels + prefix_labels = torch.Tensor(cpt_token_ids).long().view(1, -1) + prefix_labels = prefix_labels.repeat(batch_size, 1).to(labels.device) + cpt_labels = torch.cat((prefix_labels, labels), dim=1) + # Generate prefix type mask and shift input type mask values to avoid conflicts + prefix_type_mask = torch.Tensor(cpt_tokens_type_mask).long().view(1, -1) + prefix_type_mask = prefix_type_mask.repeat(batch_size, 1).to(labels.device) + adjusted_input_type_mask = input_type_mask + adjusted_input_type_mask[adjusted_input_type_mask > 0] += prefix_type_mask.max() + # Concatenate prefix and shifted input type masks + cpt_type_mask = torch.cat((prefix_type_mask, adjusted_input_type_mask), dim=1) + # Identify valid label positions and mask invalid ones with -100 + labels_idx = (cpt_type_mask > 0) & (cpt_type_mask % 4 == 0) + cpt_labels[~labels_idx] = -100 + # Update kwargs with the modified labels + + kwargs["labels"] = cpt_labels + # Pass the modified inputs to the base model + base_model_output = self.base_model(inputs_embeds=inputs_embeds, **kwargs) + if labels is None: + return base_model_output + else: + # Calculate the loss using the custom CPT loss function + cpt_embedding = PEFT_TYPE_TO_TUNER_MAPPING[peft_config.peft_type] + base_model_output = cpt_embedding.calculate_loss( + base_model_output, cpt_labels, cpt_type_mask, self.peft_config["default"] + ) + return base_model_output + + def generate(self, *args, **kwargs): + peft_config = self.active_peft_config + self.base_model.prepare_inputs_for_generation = self.prepare_inputs_for_generation + if hasattr(self.base_model, "model"): + self.base_model.model.generation_config = self.generation_config + else: + self.base_model.generation_config = self.generation_config + try: + if not peft_config.is_prompt_learning: + # Adds alora_offsets to kwargs if relevant. No other changes. + kwargs = get_alora_offsets_for_generate(self, *args, **kwargs) + with self._enable_peft_forward_hooks(*args, **kwargs): + kwargs = {k: v for k, v in kwargs.items() if k not in self.special_peft_forward_args} + outputs = self.base_model.generate(*args, **kwargs) + else: + outputs = self.base_model.generate(**kwargs) + except: + self.base_model.prepare_inputs_for_generation = self.base_model_prepare_inputs_for_generation + raise + else: + self.base_model.prepare_inputs_for_generation = self.base_model_prepare_inputs_for_generation + return outputs + + def prepare_inputs_for_generation(self, *args, task_ids: Optional[torch.Tensor] = None, **kwargs): + peft_config = self.active_peft_config + model_kwargs = self.base_model_prepare_inputs_for_generation(*args, **kwargs) + + # https://github.com/huggingface/transformers/pull/26681/ introduced new cache format + # for some architectures which requires a special fix for prompt tuning etc. + # TODO: starting with transformers 4.38, all architectures should support caching. + uses_transformers_4_38 = packaging.version.parse(transformers.__version__) >= packaging.version.parse("4.38.0") + uses_transformers_4_36 = packaging.version.parse(transformers.__version__) >= packaging.version.parse("4.36.0") + transformers_new_cache_archs = ["llama", "mistral", "persimmon", "phi"] + if packaging.version.parse(transformers.__version__) > packaging.version.parse("4.43.3"): + # https://github.com/huggingface/transformers/pull/31445 + transformers_new_cache_archs.append("bloom") + + uses_cache = uses_transformers_4_38 or ( + uses_transformers_4_36 and self.base_model.config.model_type in transformers_new_cache_archs + ) + + # heuristic to determine if we're in 'prefill stage' (when the KV cache is filled with the values from the + # initial input) + is_prefill = (model_kwargs.get("cache_position") is not None) and (model_kwargs["cache_position"][0] == 0) + + if peft_config.peft_type == PeftType.POLY: + model_kwargs["task_ids"] = task_ids + if peft_config.is_prompt_learning: + if uses_cache and (model_kwargs.get("past_key_values", None) is not None): + # change in the logic of `prepare_inputs_for_generation` makes the below code necessary + # In prompt learning methods, past key values are longer when compared to the `input_ids`. + # As such only consider the last input ids in the autogressive generation phase. + past_key_values = model_kwargs["past_key_values"] + if isinstance(past_key_values, (tuple, list)): + seq_len = past_key_values[0][0].shape[-2] + else: # using transformers kv cache + seq_len = past_key_values.get_seq_length() + if seq_len >= model_kwargs["input_ids"].shape[1]: + model_kwargs["input_ids"] = model_kwargs["input_ids"][:, -1:] + + if (attention_mask := model_kwargs.get("attention_mask", None)) is not None: + if isinstance(attention_mask, dict): + # see: https://github.com/huggingface/transformers/pull/37866 + # For now, just deal with the case of a single attention mask + if len(attention_mask) != 1: + raise ValueError( + f"Expected a single attention mask, got {len(attention_mask)} instead, please open an " + "issue (https://github.com/huggingface/peft/issues) and report the error." + ) + attention_mask = list(attention_mask.values())[0] + + size = model_kwargs["input_ids"].shape[0], peft_config.num_virtual_tokens + prefix_attention_mask = torch.ones(size).to(model_kwargs["input_ids"].device) + if attention_mask.dim() == 4: + # Transform the 4d attention mask to 2d, leave it up to the model to deal with it instead of trying + # to create a 4d attention mask here. + # from [batch_size, heads, input_ids_length, total_sequence_length] + # to [batch_size, total_sequence_length] + bs = attention_mask.shape[0] + total_seq_len = prefix_attention_mask.shape[1] + attention_mask.shape[2] + attention_mask_2d = torch.ones((bs, total_seq_len), dtype=attention_mask.dtype) + + if is_prefill and (peft_config.peft_type != PeftType.PREFIX_TUNING): + # if in prefill stage, for prompt learning methods that are not prefix tuning, new tokens + # (embeddings) are inserted, thus set cache_position to correspond to these tokens + cache_position_ = torch.arange(total_seq_len, device=model_kwargs["input_ids"].device) + else: + # prefix tuning acts directly on the cache, no need to upate cache_position + cache_position_ = model_kwargs["cache_position"] + + attention_mask_new = create_attention_mask( + self.get_base_model(), + model_input=None, + attention_mask=attention_mask_2d, + past_key_values=model_kwargs.get("past_key_values"), + cache_position=cache_position_, + batch_size=bs, + sequence_length=total_seq_len, + position_ids=model_kwargs.get("position_ids", None), + ) + model_kwargs["attention_mask"] = attention_mask_new + else: + # 2d attention mask + model_kwargs["attention_mask"] = torch.cat((prefix_attention_mask, attention_mask), dim=1) + + if model_kwargs.get("position_ids", None) is not None: + warnings.warn("Position ids are not supported for parameter efficient tuning. Ignoring position ids.") + model_kwargs["position_ids"] = None + + if kwargs.get("token_type_ids", None) is not None: + warnings.warn( + "Token type ids are not supported for parameter efficient tuning. Ignoring token type ids" + ) + kwargs["token_type_ids"] = None + + cache: transformers.Cache | None = model_kwargs.get("past_key_values", None) + # no past_key_values or past_key_values empty cache + requires_prompt_injection = (cache is None) or ( + isinstance(cache, transformers.Cache) and not cache.get_seq_length() + ) + + if requires_prompt_injection and peft_config.peft_type == PeftType.PREFIX_TUNING: + # some archs require max_cache_len to re-initialize the cache, but DynamicCache has no max len + if isinstance(cache, transformers.Cache) and not isinstance(cache, transformers.DynamicCache): + max_cache_len = cache.max_cache_len + else: + max_cache_len = -1 # -1 means no max length + new_past_key_values = self.get_prompt( + batch_size=model_kwargs["input_ids"].shape[0], + max_cache_len=max_cache_len, + ) + model_kwargs["past_key_values"] = new_past_key_values + elif requires_prompt_injection: + inputs_embeds = self.word_embeddings(model_kwargs["input_ids"]) + prompts = self.get_prompt(batch_size=model_kwargs["input_ids"].shape[0], task_ids=task_ids) + prompts = prompts.to(inputs_embeds.dtype) + model_kwargs["inputs_embeds"] = torch.cat((prompts, inputs_embeds), dim=1) + model_kwargs["input_ids"] = None + + # if we're in the prefill stage + if is_prefill and (peft_config.peft_type == PeftType.PREFIX_TUNING): + # for prefix tuning, the past_key_values have been prefilled + model_kwargs["cache_position"] += peft_config.num_virtual_tokens + elif peft_config.peft_type != PeftType.PREFIX_TUNING: # prefix tuning needs cache_position + # For transformers>=4.38.0 - for some architectures such as Llama, `cache_position` is passed in the forward + # pass to keep track of the position ids of the cache. We have to pop that from `model_kwargs` as + # `cache_position` is properly created by the model, using the passed `inputs_embeds`: + # https://github.com/huggingface/transformers/blob/593230f0a1150ea9c0477b9d859f25daf73c8c33/src/transformers/models/llama/modeling_llama.py#L956 + _ = model_kwargs.pop("cache_position", None) + + return model_kwargs + + +class PeftModelForSeq2SeqLM(PeftModel): + """ + Peft model for sequence-to-sequence language modeling. + + Args: + model ([`~transformers.PreTrainedModel`]): Base transformer model. + peft_config ([`PeftConfig`]): Peft config. + adapter_name (`str`, *optional*): The name of the adapter, defaults to `"default"`. + autocast_adapter_dtype (`bool`, *optional*): + Whether to autocast the adapter dtype. Defaults to `True`. Right now, this will only cast adapter weights + using float16 and bfloat16 to float32, as this is typically required for stable training, and only affect + select PEFT tuners. + + Example: + + ```py + >>> from transformers import AutoModelForSeq2SeqLM + >>> from peft import PeftModelForSeq2SeqLM, get_peft_config + + >>> config = { + ... "peft_type": "LORA", + ... "task_type": "SEQ_2_SEQ_LM", + ... "inference_mode": False, + ... "r": 8, + ... "target_modules": ["q", "v"], + ... "lora_alpha": 32, + ... "lora_dropout": 0.1, + ... "fan_in_fan_out": False, + ... "enable_lora": None, + ... "bias": "none", + ... } + + >>> peft_config = get_peft_config(config) + >>> model = AutoModelForSeq2SeqLM.from_pretrained("t5-base") + >>> peft_model = PeftModelForSeq2SeqLM(model, peft_config) + >>> peft_model.print_trainable_parameters() + trainable params: 884736 || all params: 223843584 || trainable%: 0.3952474242013566 + ``` + """ + + def __init__( + self, model: torch.nn.Module, peft_config: PeftConfig, adapter_name: str = "default", **kwargs + ) -> None: + super().__init__(model, peft_config, adapter_name, **kwargs) + self.base_model_prepare_inputs_for_generation = self.base_model.prepare_inputs_for_generation + self.base_model_prepare_encoder_decoder_kwargs_for_generation = ( + self.base_model._prepare_encoder_decoder_kwargs_for_generation + ) + + def forward( + self, + input_ids=None, + attention_mask=None, + inputs_embeds=None, + decoder_input_ids=None, + decoder_attention_mask=None, + decoder_inputs_embeds=None, + labels=None, + output_attentions=None, + output_hidden_states=None, + return_dict=None, + task_ids=None, + **kwargs, + ): + peft_config = self.active_peft_config + if not peft_config.is_prompt_learning: + if peft_config.peft_type == PeftType.POLY: + kwargs["task_ids"] = task_ids + + with self._enable_peft_forward_hooks(**kwargs): + kwargs = {k: v for k, v in kwargs.items() if k not in self.special_peft_forward_args} + return self.base_model( + input_ids=input_ids, + attention_mask=attention_mask, + inputs_embeds=inputs_embeds, + decoder_input_ids=decoder_input_ids, + decoder_attention_mask=decoder_attention_mask, + decoder_inputs_embeds=decoder_inputs_embeds, + labels=labels, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + return_dict=return_dict, + **kwargs, + ) + + batch_size = _get_batch_size(input_ids, inputs_embeds) + if decoder_attention_mask is not None: + # concat prompt attention mask + prefix_attention_mask = torch.ones(batch_size, peft_config.num_virtual_tokens).to( + decoder_attention_mask.device + ) + if peft_config.peft_type not in [PeftType.PROMPT_TUNING, PeftType.P_TUNING]: + decoder_attention_mask = torch.cat((prefix_attention_mask, decoder_attention_mask), dim=1) + + if kwargs.get("position_ids", None) is not None: + warnings.warn("Position ids are not supported for parameter efficient tuning. Ignoring position ids.") + kwargs["position_ids"] = None + if kwargs.get("token_type_ids", None) is not None: + warnings.warn("Token type ids are not supported for parameter efficient tuning. Ignoring token type ids") + kwargs["token_type_ids"] = None + kwargs.update( + { + "attention_mask": attention_mask, + "decoder_attention_mask": decoder_attention_mask, + "labels": labels, + "output_attentions": output_attentions, + "output_hidden_states": output_hidden_states, + "return_dict": return_dict, + } + ) + + if peft_config.peft_type == PeftType.PREFIX_TUNING: + # overwrite past_kv in kwargs + kwargs["past_key_values"] = self.get_prompt(batch_size) + return self.base_model( + input_ids=input_ids, + decoder_input_ids=decoder_input_ids, + decoder_inputs_embeds=decoder_inputs_embeds, + **kwargs, + ) + elif peft_config.peft_type in [PeftType.PROMPT_TUNING, PeftType.P_TUNING]: + if inputs_embeds is None: + inputs_embeds = self.word_embeddings(input_ids) + + if attention_mask is not None: + # concat prompt attention mask + prefix_attention_mask = torch.ones(batch_size, peft_config.num_virtual_tokens).to( + attention_mask.device + ) + kwargs["attention_mask"] = torch.cat((prefix_attention_mask, attention_mask), dim=1) + + prompts = self.get_prompt(batch_size=batch_size) + prompts = prompts.to(inputs_embeds.dtype) + inputs_embeds = torch.cat((prompts[:, : peft_config.num_virtual_tokens], inputs_embeds), dim=1) + + return self.base_model( + inputs_embeds=inputs_embeds, + decoder_input_ids=decoder_input_ids, + decoder_inputs_embeds=decoder_inputs_embeds, + **kwargs, + ) + else: + if inputs_embeds is None: + inputs_embeds = self.word_embeddings(input_ids) + if decoder_inputs_embeds is None and decoder_input_ids is None: + decoder_input_ids = shift_tokens_right( + labels, self.config.pad_token_id, self.config.decoder_start_token_id + ) + decoder_inputs_embeds = self.word_embeddings(decoder_input_ids) + + if attention_mask is not None: + # concat prompt attention mask + prefix_attention_mask = torch.ones(batch_size, peft_config.num_virtual_tokens).to( + attention_mask.device + ) + kwargs["attention_mask"] = torch.cat((prefix_attention_mask, attention_mask), dim=1) + # concat prompt labels + if labels is not None: + if peft_config.num_transformer_submodules == 1: + kwargs["labels"] = labels + elif peft_config.num_transformer_submodules == 2: + prefix_labels = torch.full((batch_size, peft_config.num_virtual_tokens), -100).to(labels.device) + kwargs["labels"] = torch.cat((prefix_labels, labels), dim=1) + prompts = self.get_prompt(batch_size=batch_size, task_ids=task_ids) + prompts = prompts.to(inputs_embeds.dtype) + inputs_embeds = torch.cat((prompts[:, : peft_config.num_virtual_tokens], inputs_embeds), dim=1) + if peft_config.num_transformer_submodules == 1: + return self.base_model(inputs_embeds=inputs_embeds, **kwargs) + elif peft_config.num_transformer_submodules == 2: + decoder_inputs_embeds = torch.cat( + (prompts[:, peft_config.num_virtual_tokens :], decoder_inputs_embeds), dim=1 + ) + return self.base_model( + inputs_embeds=inputs_embeds, decoder_inputs_embeds=decoder_inputs_embeds, **kwargs + ) + + def generate(self, **kwargs): + peft_config = self.active_peft_config + self.base_model.prepare_inputs_for_generation = self.prepare_inputs_for_generation + self.base_model._prepare_encoder_decoder_kwargs_for_generation = ( + self._prepare_encoder_decoder_kwargs_for_generation + ) + try: + if not peft_config.is_prompt_learning: + with self._enable_peft_forward_hooks(**kwargs): + kwargs = {k: v for k, v in kwargs.items() if k not in self.special_peft_forward_args} + outputs = self.base_model.generate(**kwargs) + else: + if "input_ids" not in kwargs: + raise ValueError("input_ids must be provided for Peft model generation") + if kwargs.get("position_ids", None) is not None: + warnings.warn( + "Position ids are not supported for parameter efficient tuning. Ignoring position ids." + ) + kwargs["position_ids"] = None + if kwargs.get("token_type_ids", None) is not None: + warnings.warn( + "Token type ids are not supported for parameter efficient tuning. Ignoring token type ids" + ) + kwargs["token_type_ids"] = None + + if peft_config.peft_type == PeftType.PREFIX_TUNING: + outputs = self.base_model.generate(**kwargs) + elif peft_config.peft_type in [ + PeftType.PROMPT_TUNING, + PeftType.P_TUNING, + PeftType.MULTITASK_PROMPT_TUNING, + ]: + kwargs = deepcopy(kwargs) + + if "encoder_outputs" in kwargs: + del kwargs["encoder_outputs"] + warnings.warn( + "`encoder_outputs` should not be passed to `generate` when using prompt tuning. Ignoring it." + ) + + input_ids = kwargs.pop("input_ids") + inputs_embeds = self.word_embeddings(input_ids) + batch_size = inputs_embeds.shape[0] + prompts = self.get_prompt(batch_size=batch_size, task_ids=kwargs.pop("task_ids", None)) + prompts = prompts.to(inputs_embeds.dtype) + + inputs_embeds = torch.cat((prompts[:, : peft_config.num_virtual_tokens], inputs_embeds), dim=1) + kwargs["inputs_embeds"] = inputs_embeds + + if "attention_mask" in kwargs: + prefix_attention_mask = torch.ones(batch_size, peft_config.num_virtual_tokens).to( + kwargs["attention_mask"].device + ) + kwargs["attention_mask"] = torch.cat((prefix_attention_mask, kwargs["attention_mask"]), dim=1) + + return self.base_model.generate(**kwargs) + else: + raise NotImplementedError + except: + self.base_model.prepare_inputs_for_generation = self.base_model_prepare_inputs_for_generation + self.base_model._prepare_encoder_decoder_kwargs_for_generation = ( + self.base_model_prepare_encoder_decoder_kwargs_for_generation + ) + raise + else: + self.base_model.prepare_inputs_for_generation = self.base_model_prepare_inputs_for_generation + self.base_model._prepare_encoder_decoder_kwargs_for_generation = ( + self.base_model_prepare_encoder_decoder_kwargs_for_generation + ) + return outputs + + def prepare_inputs_for_generation(self, *args, task_ids: torch.Tensor = None, **kwargs): + peft_config = self.active_peft_config + model_kwargs = self.base_model_prepare_inputs_for_generation(*args, **kwargs) + if peft_config.peft_type == PeftType.POLY: + model_kwargs["task_ids"] = task_ids + elif peft_config.peft_type == PeftType.PREFIX_TUNING: + past_key_values = model_kwargs.get("past_key_values", None) + cache_position = model_kwargs.get("cache_position", [None]) + # check prefill stage + is_prefill_stage = ( + # old cache implementation + (past_key_values is None) + # new cache implementation + or (isinstance(past_key_values, Cache) and (cache_position[0] == 0)) + ) + if is_prefill_stage: + batch_size = model_kwargs["decoder_input_ids"].shape[0] + new_past_key_values = self.get_prompt(batch_size) + model_kwargs["past_key_values"] = new_past_key_values + + return model_kwargs + + +class PeftModelForTokenClassification(PeftModel): + """ + Peft model for token classification tasks. + + Args: + model ([`~transformers.PreTrainedModel`]): Base transformer model. + peft_config ([`PeftConfig`]): Peft config. + adapter_name (`str`, *optional*): The name of the adapter, defaults to `"default"`. + autocast_adapter_dtype (`bool`, *optional*): + Whether to autocast the adapter dtype. Defaults to `True`. Right now, this will only cast adapter weights + using float16 and bfloat16 to float32, as this is typically required for stable training, and only affect + select PEFT tuners. + + **Attributes**: + - **config** ([`~transformers.PretrainedConfig`]) -- The configuration object of the base model. + - **cls_layer_name** (`str`) -- The name of the classification layer. + + Example: + + ```py + >>> from transformers import AutoModelForSequenceClassification + >>> from peft import PeftModelForTokenClassification, get_peft_config + + >>> config = { + ... "peft_type": "PREFIX_TUNING", + ... "task_type": "TOKEN_CLS", + ... "inference_mode": False, + ... "num_virtual_tokens": 20, + ... "token_dim": 768, + ... "num_transformer_submodules": 1, + ... "num_attention_heads": 12, + ... "num_layers": 12, + ... "encoder_hidden_size": 768, + ... "prefix_projection": False, + ... "postprocess_past_key_value_function": None, + ... } + + >>> peft_config = get_peft_config(config) + >>> model = AutoModelForTokenClassification.from_pretrained("bert-base-cased") + >>> peft_model = PeftModelForTokenClassification(model, peft_config) + >>> peft_model.print_trainable_parameters() + trainable params: 370178 || all params: 108680450 || trainable%: 0.3406113979101117 + ``` + """ + + def __init__( + self, model: torch.nn.Module, peft_config: PeftConfig = None, adapter_name: str = "default", **kwargs + ) -> None: + super().__init__(model, peft_config, adapter_name, **kwargs) + + classifier_module_names = ["classifier", "score"] + if hasattr(peft_config, "modules_to_save"): + if peft_config.modules_to_save is None: + peft_config.modules_to_save = classifier_module_names[:] + else: + peft_config.modules_to_save.extend(classifier_module_names) + + for name, _ in self.base_model.named_children(): + if any(module_name in name for module_name in self.modules_to_save): + self.cls_layer_name = name + break + + # to make sure classifier layer is trainable; this may add a new ModulesToSaveWrapper + _set_trainable( + self, + adapter_name, + module_names=getattr(peft_config, "modules_to_save", None), + inference_mode=peft_config.inference_mode, + ) + + def add_adapter(self, adapter_name: str, peft_config: PeftConfig, low_cpu_mem_usage: bool = False) -> None: + """ + Add an adapter to the model based on the passed configuration. + + This adapter is not trained. To load a trained adapter, check out [`PeftModel.load_adapter`]. + + The name for the new adapter should be unique. + + The new adapter is not automatically set as the active adapter. Use [`PeftModel.set_adapter`] to set the active + adapter. + + Args: + adapter_name (`str`): + The name of the adapter to be added. + peft_config ([`PeftConfig`]): + The configuration of the adapter to be added. + low_cpu_mem_usage (`bool`, `optional`, defaults to `False`): + Create empty adapter weights on meta device. Useful to speed up the process when loading saved + adapters. Don't use this option when creating a new PEFT adapter for training. + + """ + # ensure that additional adapters also add the classifier layer to modules_to_save + if hasattr(peft_config, "modules_to_save"): + classifier_module_names = ["classifier", "score"] + if peft_config.modules_to_save is None: + peft_config.modules_to_save = classifier_module_names[:] + else: + peft_config.modules_to_save.extend(classifier_module_names) + + return super().add_adapter(adapter_name, peft_config, low_cpu_mem_usage=low_cpu_mem_usage) + + def forward( + self, + input_ids=None, + attention_mask=None, + inputs_embeds=None, + labels=None, + output_attentions=None, + output_hidden_states=None, + return_dict=None, + task_ids=None, + **kwargs, + ): + peft_config = self.active_peft_config + return_dict = return_dict if return_dict is not None else self.config.use_return_dict + + if not peft_config.is_prompt_learning: + with self._enable_peft_forward_hooks(**kwargs): + kwargs = {k: v for k, v in kwargs.items() if k not in self.special_peft_forward_args} + if peft_config.peft_type == PeftType.POLY: + kwargs["task_ids"] = task_ids + return self.base_model( + input_ids=input_ids, + attention_mask=attention_mask, + inputs_embeds=inputs_embeds, + labels=labels, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + return_dict=return_dict, + **kwargs, + ) + + batch_size = _get_batch_size(input_ids, inputs_embeds) + if attention_mask is not None: + # concat prompt attention mask + prefix_attention_mask = torch.ones(batch_size, peft_config.num_virtual_tokens).to(attention_mask.device) + attention_mask = torch.cat((prefix_attention_mask, attention_mask), dim=1) + if kwargs.get("position_ids", None) is not None: + warnings.warn("Position ids are not supported for parameter efficient tuning. Ignoring position ids.") + kwargs["position_ids"] = None + kwargs.update( + { + "attention_mask": attention_mask, + "labels": labels, + "output_attentions": output_attentions, + "output_hidden_states": output_hidden_states, + "return_dict": return_dict, + } + ) + + if peft_config.peft_type == PeftType.PREFIX_TUNING: + return self._prefix_tuning_forward(input_ids=input_ids, **kwargs) + else: + if kwargs.get("token_type_ids", None) is not None: + kwargs["token_type_ids"] = torch.cat( + ( + torch.zeros(batch_size, peft_config.num_virtual_tokens).to(self.word_embeddings.weight.device), + kwargs["token_type_ids"], + ), + dim=1, + ).long() + if inputs_embeds is None: + inputs_embeds = self.word_embeddings(input_ids) + prompts = self.get_prompt(batch_size=batch_size, task_ids=task_ids) + prompts = prompts.to(inputs_embeds.dtype) + inputs_embeds = torch.cat((prompts, inputs_embeds), dim=1) + return self.base_model(inputs_embeds=inputs_embeds, **kwargs) + + def _prefix_tuning_forward( + self, + input_ids=None, + attention_mask=None, + inputs_embeds=None, + labels=None, + output_attentions=None, + output_hidden_states=None, + return_dict=None, + **kwargs, + ): + batch_size = _get_batch_size(input_ids, inputs_embeds) + past_key_values = self.get_prompt(batch_size) + fwd_params = list(inspect.signature(self.base_model.forward).parameters.keys()) + kwargs.update( + { + "input_ids": input_ids, + "attention_mask": attention_mask, + "inputs_embeds": inputs_embeds, + "output_attentions": output_attentions, + "output_hidden_states": output_hidden_states, + "return_dict": return_dict, + "past_key_values": past_key_values, + } + ) + if "past_key_values" in fwd_params: + return self.base_model(labels=labels, **kwargs) + else: + transformer_backbone_name = self.base_model.get_submodule(self.transformer_backbone_name) + fwd_params = list(inspect.signature(transformer_backbone_name.forward).parameters.keys()) + if "past_key_values" not in fwd_params: + raise ValueError("Model does not support past key values which are required for prefix tuning.") + outputs = transformer_backbone_name(**kwargs) + sequence_output = outputs[0] + if "dropout" in [name for name, _ in list(self.base_model.named_children())]: + sequence_output = self.base_model.dropout(sequence_output) + logits = self.base_model.get_submodule(self.cls_layer_name)(sequence_output) + + loss = None + if labels is not None: + loss_fct = CrossEntropyLoss() + loss = loss_fct(logits.view(-1, self.num_labels), labels.view(-1)) + + if not return_dict: + output = (logits,) + outputs[2:] + return ((loss,) + output) if loss is not None else output + + return TokenClassifierOutput( + loss=loss, + logits=logits, + hidden_states=outputs.hidden_states, + attentions=outputs.attentions, + ) + + +class PeftModelForQuestionAnswering(PeftModel): + """ + Peft model for extractive question answering. + + Args: + model ([`~transformers.PreTrainedModel`]): Base transformer model. + peft_config ([`PeftConfig`]): Peft config. + adapter_name (`str`, *optional*): The name of the adapter, defaults to `"default"`. + autocast_adapter_dtype (`bool`, *optional*): + Whether to autocast the adapter dtype. Defaults to `True`. Right now, this will only cast adapter weights + using float16 and bfloat16 to float32, as this is typically required for stable training, and only affect + select PEFT tuners. + + **Attributes**: + - **config** ([`~transformers.PretrainedConfig`]) -- The configuration object of the base model. + - **cls_layer_name** (`str`) -- The name of the classification layer. + + Example: + + ```py + >>> from transformers import AutoModelForQuestionAnswering + >>> from peft import PeftModelForQuestionAnswering, get_peft_config + + >>> config = { + ... "peft_type": "LORA", + ... "task_type": "QUESTION_ANS", + ... "inference_mode": False, + ... "r": 16, + ... "target_modules": ["query", "value"], + ... "lora_alpha": 32, + ... "lora_dropout": 0.05, + ... "fan_in_fan_out": False, + ... "bias": "none", + ... } + + >>> peft_config = get_peft_config(config) + >>> model = AutoModelForQuestionAnswering.from_pretrained("bert-base-cased") + >>> peft_model = PeftModelForQuestionAnswering(model, peft_config) + >>> peft_model.print_trainable_parameters() + trainable params: 592900 || all params: 108312580 || trainable%: 0.5473971721475013 + ``` + """ + + def __init__( + self, model: torch.nn.Module, peft_config: PeftConfig, adapter_name: str = "default", **kwargs + ) -> None: + super().__init__(model, peft_config, adapter_name, **kwargs) + + qa_module_names = ["qa_outputs"] + if hasattr(peft_config, "modules_to_save"): + if peft_config.modules_to_save is None: + peft_config.modules_to_save = qa_module_names[:] + else: + peft_config.modules_to_save.extend(qa_module_names) + + for name, _ in self.base_model.named_children(): + if any(module_name in name for module_name in self.modules_to_save): + self.cls_layer_name = name + break + + # to make sure classifier layer is trainable; this may add a new ModulesToSaveWrapper + _set_trainable( + self, + adapter_name, + module_names=getattr(peft_config, "modules_to_save", None), + inference_mode=peft_config.inference_mode, + ) + + def add_adapter(self, adapter_name: str, peft_config: PeftConfig, low_cpu_mem_usage: bool = False) -> None: + """ + Add an adapter to the model based on the passed configuration. + + This adapter is not trained. To load a trained adapter, check out [`PeftModel.load_adapter`]. + + The name for the new adapter should be unique. + + The new adapter is not automatically set as the active adapter. Use [`PeftModel.set_adapter`] to set the active + adapter. + + Args: + adapter_name (`str`): + The name of the adapter to be added. + peft_config ([`PeftConfig`]): + The configuration of the adapter to be added. + low_cpu_mem_usage (`bool`, `optional`, defaults to `False`): + Create empty adapter weights on meta device. Useful to speed up the process when loading saved + adapters. Don't use this option when creating a new PEFT adapter for training. + + """ + # ensure that additional adapters also add the classifier layer to modules_to_save + if hasattr(peft_config, "modules_to_save"): + qa_module_names = ["qa_outputs"] + if peft_config.modules_to_save is None: + peft_config.modules_to_save = qa_module_names[:] + else: + peft_config.modules_to_save.extend(qa_module_names) + + return super().add_adapter(adapter_name, peft_config, low_cpu_mem_usage=low_cpu_mem_usage) + + def forward( + self, + input_ids=None, + attention_mask=None, + token_type_ids=None, + position_ids=None, + inputs_embeds=None, + start_positions=None, + end_positions=None, + output_attentions=None, + output_hidden_states=None, + return_dict=None, + task_ids=None, + **kwargs, + ): + peft_config = self.active_peft_config + return_dict = return_dict if return_dict is not None else self.config.use_return_dict + + if not peft_config.is_prompt_learning: + if peft_config.peft_type == PeftType.POLY: + kwargs["task_ids"] = task_ids + + with self._enable_peft_forward_hooks(**kwargs): + kwargs = {k: v for k, v in kwargs.items() if k not in self.special_peft_forward_args} + return self.base_model( + input_ids=input_ids, + attention_mask=attention_mask, + inputs_embeds=inputs_embeds, + start_positions=start_positions, + end_positions=end_positions, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + return_dict=return_dict, + **kwargs, + ) + + batch_size = _get_batch_size(input_ids, inputs_embeds) + if attention_mask is not None: + # concat prompt attention mask + prefix_attention_mask = torch.ones(batch_size, peft_config.num_virtual_tokens).to(attention_mask.device) + attention_mask = torch.cat((prefix_attention_mask, attention_mask), dim=1) + if kwargs.get("position_ids", None) is not None: + warnings.warn("Position ids are not supported for parameter efficient tuning. Ignoring position ids.") + kwargs["position_ids"] = None + kwargs.update( + { + "attention_mask": attention_mask, + "start_positions": start_positions, + "end_positions": end_positions, + "output_attentions": output_attentions, + "output_hidden_states": output_hidden_states, + "return_dict": return_dict, + } + ) + + if peft_config.peft_type == PeftType.PREFIX_TUNING: + return self._prefix_tuning_forward(input_ids=input_ids, **kwargs) + else: + if kwargs.get("token_type_ids", None) is not None: + kwargs["token_type_ids"] = torch.cat( + ( + torch.zeros(batch_size, peft_config.num_virtual_tokens).to(self.word_embeddings.weight.device), + kwargs["token_type_ids"], + ), + dim=1, + ).long() + if inputs_embeds is None: + inputs_embeds = self.word_embeddings(input_ids) + prompts = self.get_prompt(batch_size=batch_size) + prompts = prompts.to(inputs_embeds.dtype) + inputs_embeds = torch.cat((prompts, inputs_embeds), dim=1) + return self.base_model(inputs_embeds=inputs_embeds, **kwargs) + + def _prefix_tuning_forward( + self, + input_ids=None, + attention_mask=None, + inputs_embeds=None, + start_positions=None, + end_positions=None, + output_attentions=None, + output_hidden_states=None, + return_dict=None, + **kwargs, + ): + batch_size = _get_batch_size(input_ids, inputs_embeds) + past_key_values = self.get_prompt(batch_size) + fwd_params = list(inspect.signature(self.base_model.forward).parameters.keys()) + kwargs.update( + { + "input_ids": input_ids, + "attention_mask": attention_mask, + "inputs_embeds": inputs_embeds, + "output_attentions": output_attentions, + "output_hidden_states": output_hidden_states, + "return_dict": return_dict, + "past_key_values": past_key_values, + } + ) + if "past_key_values" in fwd_params: + return self.base_model(start_positions=start_positions, end_positions=end_positions, **kwargs) + else: + transformer_backbone_name = self.base_model.get_submodule(self.transformer_backbone_name) + fwd_params = list(inspect.signature(transformer_backbone_name.forward).parameters.keys()) + if "past_key_values" not in fwd_params: + raise ValueError("Model does not support past key values which are required for prefix tuning.") + outputs = transformer_backbone_name(**kwargs) + sequence_output = outputs[0] + if "dropout" in [name for name, _ in list(self.base_model.named_children())]: + sequence_output = self.base_model.dropout(sequence_output) + logits = self.base_model.get_submodule(self.cls_layer_name)(sequence_output) + start_logits, end_logits = logits.split(1, dim=-1) + start_logits = start_logits.squeeze(-1).contiguous() + end_logits = end_logits.squeeze(-1).contiguous() + + total_loss = None + if start_positions is not None and end_positions is not None: + # If we are on multi-GPU, split add a dimension + if len(start_positions.size()) > 1: + start_positions = start_positions.squeeze(-1) + if len(end_positions.size()) > 1: + end_positions = end_positions.squeeze(-1) + # sometimes the start/end positions are outside our model inputs, we ignore these terms + ignored_index = start_logits.size(1) + start_positions = start_positions.clamp(0, ignored_index) + end_positions = end_positions.clamp(0, ignored_index) + + loss_fct = CrossEntropyLoss(ignore_index=ignored_index) + start_loss = loss_fct(start_logits, start_positions) + end_loss = loss_fct(end_logits, end_positions) + total_loss = (start_loss + end_loss) / 2 + + if not return_dict: + output = (start_logits, end_logits) + outputs[2:] + return ((total_loss,) + output) if total_loss is not None else output + + return QuestionAnsweringModelOutput( + loss=total_loss, + start_logits=start_logits, + end_logits=end_logits, + hidden_states=outputs.hidden_states, + attentions=outputs.attentions, + ) + + +class PeftModelForFeatureExtraction(PeftModel): + """ + Peft model for extracting features/embeddings from transformer models + + Args: + model ([`~transformers.PreTrainedModel`]): Base transformer model. + peft_config ([`PeftConfig`]): Peft config. + adapter_name (`str`, *optional*): The name of the adapter, defaults to `"default"`. + autocast_adapter_dtype (`bool`, *optional*): + Whether to autocast the adapter dtype. Defaults to `True`. Right now, this will only cast adapter weights + using float16 and bfloat16 to float32, as this is typically required for stable training, and only affect + select PEFT tuners. + + **Attributes**: + - **config** ([`~transformers.PretrainedConfig`]) -- The configuration object of the base model. + + Example: + + ```py + >>> from transformers import AutoModel + >>> from peft import PeftModelForFeatureExtraction, get_peft_config + + >>> config = { + ... "peft_type": "LORA", + ... "task_type": "FEATURE_EXTRACTION", + ... "inference_mode": False, + ... "r": 16, + ... "target_modules": ["query", "value"], + ... "lora_alpha": 32, + ... "lora_dropout": 0.05, + ... "fan_in_fan_out": False, + ... "bias": "none", + ... } + >>> peft_config = get_peft_config(config) + >>> model = AutoModel.from_pretrained("bert-base-cased") + >>> peft_model = PeftModelForFeatureExtraction(model, peft_config) + >>> peft_model.print_trainable_parameters() + ``` + """ + + def __init__(self, model: torch.nn.Module, peft_config: PeftConfig, adapter_name: str = "default", **kwargs): + super().__init__(model, peft_config, adapter_name, **kwargs) + + def forward( + self, + input_ids=None, + attention_mask=None, + inputs_embeds=None, + output_attentions=None, + output_hidden_states=None, + return_dict=None, + task_ids=None, + **kwargs, + ): + peft_config = self.active_peft_config + if not peft_config.is_prompt_learning: + if peft_config.peft_type == PeftType.POLY: + kwargs["task_ids"] = task_ids + + with self._enable_peft_forward_hooks(**kwargs): + kwargs = {k: v for k, v in kwargs.items() if k not in self.special_peft_forward_args} + return self.base_model( + input_ids=input_ids, + attention_mask=attention_mask, + inputs_embeds=inputs_embeds, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + return_dict=return_dict, + **kwargs, + ) + + batch_size = _get_batch_size(input_ids, inputs_embeds) + if attention_mask is not None: + # concat prompt attention mask + prefix_attention_mask = torch.ones(batch_size, peft_config.num_virtual_tokens).to(attention_mask.device) + attention_mask = torch.cat((prefix_attention_mask, attention_mask), dim=1) + + if kwargs.get("position_ids", None) is not None: + warnings.warn("Position ids are not supported for parameter efficient tuning. Ignoring position ids.") + kwargs["position_ids"] = None + if kwargs.get("token_type_ids", None) is not None: + warnings.warn("Token type ids are not supported for parameter efficient tuning. Ignoring token type ids") + kwargs["token_type_ids"] = None + kwargs.update( + { + "attention_mask": attention_mask, + "output_attentions": output_attentions, + "output_hidden_states": output_hidden_states, + "return_dict": return_dict, + } + ) + + if peft_config.peft_type == PeftType.PREFIX_TUNING: + # overwrite past_kv in kwargs + kwargs["past_key_values"] = self.get_prompt(batch_size) + return self.base_model(input_ids=input_ids, **kwargs) + else: + if inputs_embeds is None: + inputs_embeds = self.word_embeddings(input_ids) + prompts = self.get_prompt(batch_size=batch_size) + prompts = prompts.to(inputs_embeds.dtype) + inputs_embeds = torch.cat((prompts, inputs_embeds), dim=1) + return self.base_model(inputs_embeds=inputs_embeds, **kwargs) + + +@dataclass +class TunerLayerStatus: + name: str + module_type: str + enabled: bool + active_adapters: list[str] + merged_adapters: list[str] + requires_grad: dict[str, bool | Literal["irregular"]] + available_adapters: list[str] + devices: dict[str, list[str]] + + +def get_layer_status(model: torch.nn.Module) -> list[TunerLayerStatus]: + """Get the status of each adapter layer in the model. + + This function returns a list of `TunerLayerStatus` dataclass instances, each of which contains the following + attributes: + + - `name` (`str`): + The name of the adapter layer, e.g. `model.encoder.block.0.layer.0.SelfAttention.q`. + - `module_type` (`str`): + The type of the adapter layer, e.g. `lora.Linear`. + - `enabled` (`bool`): + Whether the adapter layer is enabled. + - `active_adapters` (`list[str]`): + The names of the active adapters, if any, e.g. `["default"]`. + - `merged_adapters` (`list[str]`): + The names of the merged adapters, if any, e.g. `["default"]`. + - requires_grad : dict[str, bool | Literal["irregular"]] + The requires_grad status of the parameters for each adapter module. Ideally, it should be either `True` or + `False`. If the requires_grad status is not consistent across all parameters, the value will be set to + `"irregular"`. + - `available_adapters` (`list[str]`): + The names of the available adapters, e.g. `["default"]`. + - `devices` (`dict[str, list[str]]`): + The devices where the parameters of the given adapter are stored, e.g. `["cuda"]`. + + Args: + model ([Union[`~PeftModel`, `~transformers.PreTrainedModel`, `nn.Module`]]): + The model to get the adapter layer status from. + + Returns: + list[`peft.peft_model.TunerLayerStatus`]: + A list of dataclasses, each containing the status of the corresponding adapter layer. + + """ + if isinstance(model, PeftModel): + base_model = model.base_model + if not isinstance(base_model, BaseTuner): + raise TypeError( + "get_layer_status() got an invalid PeftModel instance; prefix tuning and adaption prompt are not " + "supported." + ) + else: + base_model = model + + layer_status: list[TunerLayerStatus] = [] + for name, module in base_model.named_modules(): + if not isinstance(module, (BaseTunerLayer, AuxiliaryTrainingWrapper)): + continue + if isinstance(module, TrainableTokensWrapper): + # Skip TrainableTokensWrapper, since it wraps TrainableTokensLayer, which is the actual PEFT layer we're + # interested in. + continue + + # determine if all submodules/parameters if this module require grad or not + mapping_requires_grad_list: dict[str, list[bool]] = collections.defaultdict(list) + for adapter_module_name in module.adapter_layer_names: + adapter_module = getattr(module, adapter_module_name) + if isinstance(adapter_module, torch.nn.ModuleDict): + for key, submodule in adapter_module.items(): + for param in submodule.parameters(): + mapping_requires_grad_list[key].append(param.requires_grad) + elif isinstance(adapter_module, torch.nn.ParameterDict): + for key, param in adapter_module.items(): + mapping_requires_grad_list[key].append(param.requires_grad) + else: + # strange, we don't know how to handle this, ignore for now + pass + + def check_irrgular(vals: list[bool]) -> bool | Literal["irregular"]: + if all(vals): + return True + if not any(vals): + return False + return "irregular" + + requires_grad = {key: check_irrgular(vals) for key, vals in mapping_requires_grad_list.items()} + + devices_dd = collections.defaultdict(list) + for adapter_module_name in module.adapter_layer_names + module.other_param_names: + adapter_module = getattr(module, adapter_module_name) + if isinstance(adapter_module, torch.nn.ModuleDict): + for key, submodule in adapter_module.items(): + devices_dd[key].extend([param.device.type for param in submodule.parameters()]) + elif isinstance(adapter_module, torch.nn.ParameterDict) or ( + adapter_module.__class__.__name__ == "BufferDict" + ): # VeRA + for key, param in adapter_module.items(): + devices_dd[key].append(param.device.type) + devices = {key: sorted(set(val)) for key, val in devices_dd.items()} + + status = TunerLayerStatus( + name=name, + module_type=repr(module).partition("(")[0], + enabled=not module.disable_adapters, + active_adapters=module.active_adapters, + merged_adapters=module.merged_adapters, + requires_grad=requires_grad, + available_adapters=sorted(module._get_available_adapters()), + devices=devices, + ) + layer_status.append(status) + + if not layer_status: + raise ValueError( + "No adapter layers found in the model, please ensure that it's a PEFT model or that you have PEFT adapters " + "injected in the model." + ) + + return layer_status + + +@dataclass +class TunerModelStatus: + base_model_type: str + adapter_model_type: str + peft_types: dict[str, str] + trainable_params: int + total_params: int + num_adapter_layers: int + enabled: bool | Literal["irregular"] + active_adapters: list[str] | Literal["irregular"] + merged_adapters: list[str] | Literal["irregular"] + requires_grad: dict[str, bool | Literal["irregular"]] + available_adapters: list[str] + devices: dict[str, list[str]] + + +def get_model_status(model: torch.nn.Module) -> TunerModelStatus: + """Get the status of tuners of the model. + + This function returns a `TunerModelStatus` dataclass instance, which contains the following attributes: + + - `base_model_type` (`str`): + The type of the base model, e.g. `T5Model`. + - `adapter_model_type` (`str`): + The type of the adapter model, e.g. `LoraModel`. + - `peft_types` (`dict[str, str]`): + The mapping of adapter name to adapter type, e.g. `{"default": "LORA"}`. + - `trainable_params` (`int`): + The number of trainable parameters in the model. + - `total_params` (`int`): + The total number of parameters in the model. + - `num_adapter_layers` (`int`): + The number of adapter layers in the model. + - `enabled` (`bool`, `Literal["irregular"]`): + Whether all adapter layers are enabled. If some are enabled and some are not, this will be `"irregular"`. This + means that your model is in an inconsistent state and might not work as expected. + - `active_adapters` (`list[str]`, `Literal["irregular"]`): + The names of the active adapters. If the active adapters are not consistent across all layers, this will be + `"irregular"`, which means that your model is in an inconsistent state and might not work as expected. + - `merged_adapters` (`list[str]`, `Literal["irregular"]`): + The names of the merged adapters. If the merged adapters are not consistent across all layers, this will be + `"irregular"`, which means that your model is in an inconsistent state and might not work as expected. + - `requires_grad` (`dict[str, bool | Literal["irregular"]]`): + Whether for the given adapter, all adapter layers have `requires_grad` set to `True` or `False`. If there is a + mix, this will be set to `"irregular"`, which means that your model is in an inconsistent state and might not + work as expected. + - `available_adapters` (`list[str]`): + The names of the available adapters, e.g. `["default"]`. + - `devices` (`dict[str, list[str]]`): + The devices where the parameters of the given adapter are stored, e.g. `["cuda"]`. + + Args: + model ([Union[`~PeftModel`, `~transformers.PreTrainedModel`, `nn.Module`]]): + The model to get the adapter layer status from. + + Returns: + `peft.peft_model.TunerModelStatus`: + A dataclass containing the status of the model. + + """ + if isinstance(model, PeftModel): + if not isinstance(model.base_model, BaseTuner): + raise TypeError( + "get_model_status() got an invalid PeftModel instance; prefix tuning and adaption prompt are not " + "supported." + ) + base_model_type = model.get_base_model().__class__.__name__ + trainable_params, total_params = model.get_nb_trainable_parameters() + base_model = model.base_model + peft_types = {key: str(config.peft_type).partition(".")[-1] for key, config in base_model.peft_config.items()} + adapter_model_type = base_model.__class__.__name__ + elif isinstance(model, PreTrainedModel): + base_model_type = model.__class__.__name__ + trainable_params, total_params = PeftModel.get_nb_trainable_parameters(model) + base_model = model + peft_types = {} + adapter_model_type = "None" + else: + base_model_type = "other" + trainable_params, total_params = PeftModel.get_nb_trainable_parameters(model) + base_model = model + peft_types = {} + adapter_model_type = "None" + + layer_status = get_layer_status(model) + num_adapter_layers = len(layer_status) + + enabled_set: set[bool] = {status.enabled for status in layer_status} # must be {True}, {False}, or {True, False} + enabled: bool | Literal["irregular"] + if len(enabled_set) == 1: + enabled = enabled_set.pop() + else: + enabled = "irregular" + + available_adapters: list[str] = sorted(set().union(*(status.available_adapters for status in layer_status))) + + # ideally, active adapters should be consistent across all layers of the model, but we cannot guarantee it + all_active_adapters: set[tuple[str, ...]] = {tuple(status.active_adapters) for status in layer_status} + active_adapters: list[str] | Literal["irregular"] + if not all_active_adapters: + active_adapters = [] + elif len(all_active_adapters) == 1: + active_adapters = list(all_active_adapters.pop()) + else: + active_adapters = "irregular" + + # Here we determine what adapters are merged. This is not trivial because multiple adapters can be merged or not at + # the same time. Some layers may only have adapter A, some only adapter B, so it's not as easy as just checking + # which adapters are merged on each layer. + + # First, determine all adapters that are merged on at least on module. + merged_all: set[str] = set() + for status in layer_status: + merged_all.update(status.merged_adapters) + + # Next, check if on any layer, on of these adapters is not merged. + merged_adapters: list[str] | Literal["irregular"] = sorted(merged_all) + for status in layer_status: + unmerged = set(status.available_adapters) - set(status.merged_adapters) + if unmerged & merged_all: + # there is overlap between unmerged adapters and adapters that should be merged + merged_adapters = "irregular" + break + + # check status of requires_grad + # first, merge the values for all layers + requires_grad_all: dict[str, list[bool | Literal["irregular"]]] = collections.defaultdict(list) + for status in layer_status: + for key, val in status.requires_grad.items(): + requires_grad_all[key].append(val) + + # then, check if the values are consistent + def check_irrgular(vals: list[bool | Literal["irregular"]]) -> bool | Literal["irregular"]: + if all(val is True for val in vals): + return True + if all(val is False for val in vals): + return False + return "irregular" + + requires_grad = {key: check_irrgular(vals) for key, vals in requires_grad_all.items()} + + devices_dd = collections.defaultdict(list) + for status in layer_status: + for key, val in status.devices.items(): + devices_dd[key].extend(val) + devices = {key: sorted(set(val)) for key, val in devices_dd.items()} + + adapter_model_status = TunerModelStatus( + base_model_type=base_model_type, + adapter_model_type=adapter_model_type, + peft_types=peft_types, + trainable_params=trainable_params, + total_params=total_params, + num_adapter_layers=num_adapter_layers, + enabled=enabled, + active_adapters=active_adapters, + merged_adapters=merged_adapters, + requires_grad=requires_grad, + available_adapters=available_adapters, + devices=devices, + ) + return adapter_model_status + + +def __getattr__(name): + if name == "PEFT_TYPE_TO_MODEL_MAPPING": + # This is for backwards compatibility: In #2282, PEFT_TYPE_TO_MODEL_MAPPING was removed as it was redundant with + # PEFT_TYPE_TO_TUNER_MAPPING. However, third party code could still use this mapping, e.g.: + # https://github.com/AutoGPTQ/AutoGPTQ/blob/6689349625de973b9ee3016c28c11f32acf7f02c/auto_gptq/utils/peft_utils.py#L8 + # TODO: Remove after 2026-01 + msg = ( + "PEFT_TYPE_TO_MODEL_MAPPING is deprecated, please use `from peft import PEFT_TYPE_TO_TUNER_MAPPING` instead. " + "The deprecated variable will be removed in 2026." + ) + warnings.warn(msg, category=DeprecationWarning) + return PEFT_TYPE_TO_TUNER_MAPPING + + raise AttributeError(f"module {__name__!r} has no attribute {name!r}") diff --git a/peft/py.typed b/peft/py.typed new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/pillow.libs/libXau-154567c4.so.6.0.0 b/pillow.libs/libXau-154567c4.so.6.0.0 new file mode 100644 index 0000000000000000000000000000000000000000..ff06a58be7b9ff80cee9b8eb45d5e9a28cf67d1b Binary files /dev/null and b/pillow.libs/libXau-154567c4.so.6.0.0 differ diff --git a/pillow.libs/libbrotlidec-b57ddf63.so.1.2.0 b/pillow.libs/libbrotlidec-b57ddf63.so.1.2.0 new file mode 100644 index 0000000000000000000000000000000000000000..90cdef791d0f316d82f887415fd6115a1c68c86c Binary files /dev/null and b/pillow.libs/libbrotlidec-b57ddf63.so.1.2.0 differ diff --git a/pillow.libs/libsharpyuv-95d8a097.so.0.1.2 b/pillow.libs/libsharpyuv-95d8a097.so.0.1.2 new file mode 100644 index 0000000000000000000000000000000000000000..5d17bd4900510a0893df00445053806999c26f32 Binary files /dev/null and b/pillow.libs/libsharpyuv-95d8a097.so.0.1.2 differ diff --git a/pillow.libs/libwebpdemux-747f2b49.so.2.0.17 b/pillow.libs/libwebpdemux-747f2b49.so.2.0.17 new file mode 100644 index 0000000000000000000000000000000000000000..7a4f0eb0adbcbf06c2da4bbcaeb55e47199c4792 Binary files /dev/null and b/pillow.libs/libwebpdemux-747f2b49.so.2.0.17 differ diff --git a/pillow.libs/libwebpmux-7f11e5ce.so.3.1.2 b/pillow.libs/libwebpmux-7f11e5ce.so.3.1.2 new file mode 100644 index 0000000000000000000000000000000000000000..cc0012869e0ca876ebcc853b2349b4469c5b4360 Binary files /dev/null and b/pillow.libs/libwebpmux-7f11e5ce.so.3.1.2 differ diff --git a/pydantic_core-2.41.5.dist-info/INSTALLER b/pydantic_core-2.41.5.dist-info/INSTALLER new file mode 100644 index 0000000000000000000000000000000000000000..5c69047b2eb8235994febeeae1da4a82365a240a --- /dev/null +++ b/pydantic_core-2.41.5.dist-info/INSTALLER @@ -0,0 +1 @@ +uv \ No newline at end of file diff --git a/pydantic_core-2.41.5.dist-info/METADATA b/pydantic_core-2.41.5.dist-info/METADATA new file mode 100644 index 0000000000000000000000000000000000000000..468d2a52e8d80dd4d39d97361c9bf25dbc251f28 --- /dev/null +++ b/pydantic_core-2.41.5.dist-info/METADATA @@ -0,0 +1,180 @@ +Metadata-Version: 2.4 +Name: pydantic_core +Version: 2.41.5 +Classifier: Development Status :: 3 - Alpha +Classifier: Programming Language :: Python +Classifier: Programming Language :: Python :: 3 +Classifier: Programming Language :: Python :: 3 :: Only +Classifier: Programming Language :: Python :: 3.9 +Classifier: Programming Language :: Python :: 3.10 +Classifier: Programming Language :: Python :: 3.11 +Classifier: Programming Language :: Python :: 3.12 +Classifier: Programming Language :: Python :: 3.13 +Classifier: Programming Language :: Python :: 3.14 +Classifier: Programming Language :: Python :: Implementation :: CPython +Classifier: Programming Language :: Python :: Implementation :: PyPy +Classifier: Programming Language :: Python :: Implementation :: GraalPy +Classifier: Programming Language :: Rust +Classifier: Framework :: Pydantic +Classifier: Intended Audience :: Developers +Classifier: Intended Audience :: Information Technology +Classifier: Operating System :: POSIX :: Linux +Classifier: Operating System :: Microsoft :: Windows +Classifier: Operating System :: MacOS +Classifier: Typing :: Typed +Requires-Dist: typing-extensions>=4.14.1 +License-File: LICENSE +Summary: Core functionality for Pydantic validation and serialization +Home-Page: https://github.com/pydantic/pydantic-core +Author-email: Samuel Colvin , Adrian Garcia Badaracco <1755071+adriangb@users.noreply.github.com>, David Montague , David Hewitt , Sydney Runkle , Victorien Plot +License-Expression: MIT +Requires-Python: >=3.9 +Description-Content-Type: text/markdown; charset=UTF-8; variant=GFM +Project-URL: Homepage, https://github.com/pydantic/pydantic-core +Project-URL: Funding, https://github.com/sponsors/samuelcolvin +Project-URL: Source, https://github.com/pydantic/pydantic-core + +# pydantic-core + +[![CI](https://github.com/pydantic/pydantic-core/workflows/ci/badge.svg?event=push)](https://github.com/pydantic/pydantic-core/actions?query=event%3Apush+branch%3Amain+workflow%3Aci) +[![Coverage](https://codecov.io/gh/pydantic/pydantic-core/branch/main/graph/badge.svg)](https://codecov.io/gh/pydantic/pydantic-core) +[![pypi](https://img.shields.io/pypi/v/pydantic-core.svg)](https://pypi.python.org/pypi/pydantic-core) +[![versions](https://img.shields.io/pypi/pyversions/pydantic-core.svg)](https://github.com/pydantic/pydantic-core) +[![license](https://img.shields.io/github/license/pydantic/pydantic-core.svg)](https://github.com/pydantic/pydantic-core/blob/main/LICENSE) + +This package provides the core functionality for [pydantic](https://docs.pydantic.dev) validation and serialization. + +Pydantic-core is currently around 17x faster than pydantic V1. +See [`tests/benchmarks/`](./tests/benchmarks/) for details. + +## Example of direct usage + +_NOTE: You should not need to use pydantic-core directly; instead, use pydantic, which in turn uses pydantic-core._ + +```py +from pydantic_core import SchemaValidator, ValidationError + + +v = SchemaValidator( + { + 'type': 'typed-dict', + 'fields': { + 'name': { + 'type': 'typed-dict-field', + 'schema': { + 'type': 'str', + }, + }, + 'age': { + 'type': 'typed-dict-field', + 'schema': { + 'type': 'int', + 'ge': 18, + }, + }, + 'is_developer': { + 'type': 'typed-dict-field', + 'schema': { + 'type': 'default', + 'schema': {'type': 'bool'}, + 'default': True, + }, + }, + }, + } +) + +r1 = v.validate_python({'name': 'Samuel', 'age': 35}) +assert r1 == {'name': 'Samuel', 'age': 35, 'is_developer': True} + +# pydantic-core can also validate JSON directly +r2 = v.validate_json('{"name": "Samuel", "age": 35}') +assert r1 == r2 + +try: + v.validate_python({'name': 'Samuel', 'age': 11}) +except ValidationError as e: + print(e) + """ + 1 validation error for model + age + Input should be greater than or equal to 18 + [type=greater_than_equal, context={ge: 18}, input_value=11, input_type=int] + """ +``` + +## Getting Started + +### Prerequisites + +You'll need: +1. **[Rust](https://rustup.rs/)** - Rust stable (or nightly for coverage) +2. **[uv](https://docs.astral.sh/uv/getting-started/installation/)** - Fast Python package manager (will install Python 3.9+ automatically) +3. **[git](https://git-scm.com/)** - For version control +4. **[make](https://www.gnu.org/software/make/)** - For running development commands (or use `nmake` on Windows) + +### Quick Start + +```bash +# Clone the repository (or from your fork) +git clone git@github.com:pydantic/pydantic-core.git +cd pydantic-core + +# Install all dependencies using uv, setup pre-commit hooks, and build the development version +make install +``` + +Verify your installation by running: + +```bash +make +``` + +This runs a full development cycle: formatting, building, linting, and testing + +### Development Commands + +Run `make help` to see all available commands, or use these common ones: + +```bash +make build-dev # to build the package during development +make build-prod # to perform an optimised build for benchmarking +make test # to run the tests +make testcov # to run the tests and generate a coverage report +make lint # to run the linter +make format # to format python and rust code +make all # to run to run build-dev + format + lint + test +``` + +### Useful Resources + +* [`python/pydantic_core/_pydantic_core.pyi`](./python/pydantic_core/_pydantic_core.pyi) - Python API types +* [`python/pydantic_core/core_schema.py`](./python/pydantic_core/core_schema.py) - Core schema definitions +* [`tests/`](./tests) - Comprehensive usage examples + +## Profiling + +It's possible to profile the code using the [`flamegraph` utility from `flamegraph-rs`](https://github.com/flamegraph-rs/flamegraph). (Tested on Linux.) You can install this with `cargo install flamegraph`. + +Run `make build-profiling` to install a release build with debugging symbols included (needed for profiling). + +Once that is built, you can profile pytest benchmarks with (e.g.): + +```bash +flamegraph -- pytest tests/benchmarks/test_micro_benchmarks.py -k test_list_of_ints_core_py --benchmark-enable +``` +The `flamegraph` command will produce an interactive SVG at `flamegraph.svg`. + +## Releasing + +1. Bump package version locally. Do not just edit `Cargo.toml` on Github, you need both `Cargo.toml` and `Cargo.lock` to be updated. +2. Make a PR for the version bump and merge it. +3. Go to https://github.com/pydantic/pydantic-core/releases and click "Draft a new release" +4. In the "Choose a tag" dropdown enter the new tag `v` and select "Create new tag on publish" when the option appears. +5. Enter the release title in the form "v " +6. Click Generate release notes button +7. Click Publish release +8. Go to https://github.com/pydantic/pydantic-core/actions and ensure that all build for release are done successfully. +9. Go to https://pypi.org/project/pydantic-core/ and ensure that the latest release is published. +10. Done 🎉 + diff --git a/pydantic_core-2.41.5.dist-info/RECORD b/pydantic_core-2.41.5.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..e70d6ccf82c54aaa27325392508bd60eb46ac27f --- /dev/null +++ b/pydantic_core-2.41.5.dist-info/RECORD @@ -0,0 +1,11 @@ +pydantic_core-2.41.5.dist-info/INSTALLER,sha256=5hhM4Q4mYTT9z6QB6PGpUAW81PGNFrYrdXMj4oM_6ak,2 +pydantic_core-2.41.5.dist-info/METADATA,sha256=Cfg7qjIC7D2piihKVq_fG6aZduSvcXJIiIflsrIFkak,7277 +pydantic_core-2.41.5.dist-info/RECORD,, +pydantic_core-2.41.5.dist-info/REQUESTED,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0 +pydantic_core-2.41.5.dist-info/WHEEL,sha256=AUS7tHOBvWg1bDsPcHg1j3P_rKxqebEdeR--lIGHkyI,129 +pydantic_core-2.41.5.dist-info/licenses/LICENSE,sha256=Kv3TDVS01itvSIprzBVG6E7FBh8T9CCcA9ASNIeDeVo,1080 +pydantic_core/__init__.py,sha256=nK1ikrdSVK9gapcKrpv_blrp8LCAic1jrK-jkbYHlNI,5115 +pydantic_core/_pydantic_core.cpython-312-x86_64-linux-gnu.so,sha256=sfwayXRW_oTj75OQmcampiKiPl-_d6Q5yWOQqXdPcls,4883472 +pydantic_core/_pydantic_core.pyi,sha256=PqHb1BgvCM-TQfJLPFz323egWzU1_-niNSUSejYXoR8,44927 +pydantic_core/core_schema.py,sha256=u9yFC3LWhRM6DiUP7SY7M2kdzfOBNJLzwOMQAePUYAU,154730 +pydantic_core/py.typed,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0 diff --git a/pydantic_core-2.41.5.dist-info/REQUESTED b/pydantic_core-2.41.5.dist-info/REQUESTED new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/pydantic_core-2.41.5.dist-info/WHEEL b/pydantic_core-2.41.5.dist-info/WHEEL new file mode 100644 index 0000000000000000000000000000000000000000..ecc076195c46d7bd21f36f202ceb5977d3100be8 --- /dev/null +++ b/pydantic_core-2.41.5.dist-info/WHEEL @@ -0,0 +1,4 @@ +Wheel-Version: 1.0 +Generator: maturin (1.9.6) +Root-Is-Purelib: false +Tag: cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64 diff --git a/python_dateutil-2.9.0.post0.dist-info/INSTALLER b/python_dateutil-2.9.0.post0.dist-info/INSTALLER new file mode 100644 index 0000000000000000000000000000000000000000..5c69047b2eb8235994febeeae1da4a82365a240a --- /dev/null +++ b/python_dateutil-2.9.0.post0.dist-info/INSTALLER @@ -0,0 +1 @@ +uv \ No newline at end of file diff --git a/python_dateutil-2.9.0.post0.dist-info/LICENSE b/python_dateutil-2.9.0.post0.dist-info/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..1e65815cf0b3132689485874a93034ede7206bf4 --- /dev/null +++ b/python_dateutil-2.9.0.post0.dist-info/LICENSE @@ -0,0 +1,54 @@ +Copyright 2017- Paul Ganssle +Copyright 2017- dateutil contributors (see AUTHORS file) + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. + +The above license applies to all contributions after 2017-12-01, as well as +all contributions that have been re-licensed (see AUTHORS file for the list of +contributors who have re-licensed their code). +-------------------------------------------------------------------------------- +dateutil - Extensions to the standard Python datetime module. + +Copyright (c) 2003-2011 - Gustavo Niemeyer +Copyright (c) 2012-2014 - Tomi Pieviläinen +Copyright (c) 2014-2016 - Yaron de Leeuw +Copyright (c) 2015- - Paul Ganssle +Copyright (c) 2015- - dateutil contributors (see AUTHORS file) + +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, + this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of the copyright holder nor the names of its + contributors may be used to endorse or promote products derived from + this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS +"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT +LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR +A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR +CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, +EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, +PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR +PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF +LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING +NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS +SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + +The above BSD License Applies to all code, even that also covered by Apache 2.0. \ No newline at end of file diff --git a/python_dateutil-2.9.0.post0.dist-info/METADATA b/python_dateutil-2.9.0.post0.dist-info/METADATA new file mode 100644 index 0000000000000000000000000000000000000000..577f2bf2b7749e1b123b8225d610b1b257e430cc --- /dev/null +++ b/python_dateutil-2.9.0.post0.dist-info/METADATA @@ -0,0 +1,204 @@ +Metadata-Version: 2.1 +Name: python-dateutil +Version: 2.9.0.post0 +Summary: Extensions to the standard Python datetime module +Home-page: https://github.com/dateutil/dateutil +Author: Gustavo Niemeyer +Author-email: gustavo@niemeyer.net +Maintainer: Paul Ganssle +Maintainer-email: dateutil@python.org +License: Dual License +Project-URL: Documentation, https://dateutil.readthedocs.io/en/stable/ +Project-URL: Source, https://github.com/dateutil/dateutil +Classifier: Development Status :: 5 - Production/Stable +Classifier: Intended Audience :: Developers +Classifier: License :: OSI Approved :: BSD License +Classifier: License :: OSI Approved :: Apache Software License +Classifier: Programming Language :: Python +Classifier: Programming Language :: Python :: 2 +Classifier: Programming Language :: Python :: 2.7 +Classifier: Programming Language :: Python :: 3 +Classifier: Programming Language :: Python :: 3.3 +Classifier: Programming Language :: Python :: 3.4 +Classifier: Programming Language :: Python :: 3.5 +Classifier: Programming Language :: Python :: 3.6 +Classifier: Programming Language :: Python :: 3.7 +Classifier: Programming Language :: Python :: 3.8 +Classifier: Programming Language :: Python :: 3.9 +Classifier: Programming Language :: Python :: 3.10 +Classifier: Programming Language :: Python :: 3.11 +Classifier: Programming Language :: Python :: 3.12 +Classifier: Topic :: Software Development :: Libraries +Requires-Python: !=3.0.*,!=3.1.*,!=3.2.*,>=2.7 +Description-Content-Type: text/x-rst +License-File: LICENSE +Requires-Dist: six >=1.5 + +dateutil - powerful extensions to datetime +========================================== + +|pypi| |support| |licence| + +|gitter| |readthedocs| + +|travis| |appveyor| |pipelines| |coverage| + +.. |pypi| image:: https://img.shields.io/pypi/v/python-dateutil.svg?style=flat-square + :target: https://pypi.org/project/python-dateutil/ + :alt: pypi version + +.. |support| image:: https://img.shields.io/pypi/pyversions/python-dateutil.svg?style=flat-square + :target: https://pypi.org/project/python-dateutil/ + :alt: supported Python version + +.. |travis| image:: https://img.shields.io/travis/dateutil/dateutil/master.svg?style=flat-square&label=Travis%20Build + :target: https://travis-ci.org/dateutil/dateutil + :alt: travis build status + +.. |appveyor| image:: https://img.shields.io/appveyor/ci/dateutil/dateutil/master.svg?style=flat-square&logo=appveyor + :target: https://ci.appveyor.com/project/dateutil/dateutil + :alt: appveyor build status + +.. |pipelines| image:: https://dev.azure.com/pythondateutilazure/dateutil/_apis/build/status/dateutil.dateutil?branchName=master + :target: https://dev.azure.com/pythondateutilazure/dateutil/_build/latest?definitionId=1&branchName=master + :alt: azure pipelines build status + +.. |coverage| image:: https://codecov.io/gh/dateutil/dateutil/branch/master/graphs/badge.svg?branch=master + :target: https://codecov.io/gh/dateutil/dateutil?branch=master + :alt: Code coverage + +.. |gitter| image:: https://badges.gitter.im/dateutil/dateutil.svg + :alt: Join the chat at https://gitter.im/dateutil/dateutil + :target: https://gitter.im/dateutil/dateutil + +.. |licence| image:: https://img.shields.io/pypi/l/python-dateutil.svg?style=flat-square + :target: https://pypi.org/project/python-dateutil/ + :alt: licence + +.. |readthedocs| image:: https://img.shields.io/readthedocs/dateutil/latest.svg?style=flat-square&label=Read%20the%20Docs + :alt: Read the documentation at https://dateutil.readthedocs.io/en/latest/ + :target: https://dateutil.readthedocs.io/en/latest/ + +The `dateutil` module provides powerful extensions to +the standard `datetime` module, available in Python. + +Installation +============ +`dateutil` can be installed from PyPI using `pip` (note that the package name is +different from the importable name):: + + pip install python-dateutil + +Download +======== +dateutil is available on PyPI +https://pypi.org/project/python-dateutil/ + +The documentation is hosted at: +https://dateutil.readthedocs.io/en/stable/ + +Code +==== +The code and issue tracker are hosted on GitHub: +https://github.com/dateutil/dateutil/ + +Features +======== + +* Computing of relative deltas (next month, next year, + next Monday, last week of month, etc); +* Computing of relative deltas between two given + date and/or datetime objects; +* Computing of dates based on very flexible recurrence rules, + using a superset of the `iCalendar `_ + specification. Parsing of RFC strings is supported as well. +* Generic parsing of dates in almost any string format; +* Timezone (tzinfo) implementations for tzfile(5) format + files (/etc/localtime, /usr/share/zoneinfo, etc), TZ + environment string (in all known formats), iCalendar + format files, given ranges (with help from relative deltas), + local machine timezone, fixed offset timezone, UTC timezone, + and Windows registry-based time zones. +* Internal up-to-date world timezone information based on + Olson's database. +* Computing of Easter Sunday dates for any given year, + using Western, Orthodox or Julian algorithms; +* A comprehensive test suite. + +Quick example +============= +Here's a snapshot, just to give an idea about the power of the +package. For more examples, look at the documentation. + +Suppose you want to know how much time is left, in +years/months/days/etc, before the next easter happening on a +year with a Friday 13th in August, and you want to get today's +date out of the "date" unix system command. Here is the code: + +.. code-block:: python3 + + >>> from dateutil.relativedelta import * + >>> from dateutil.easter import * + >>> from dateutil.rrule import * + >>> from dateutil.parser import * + >>> from datetime import * + >>> now = parse("Sat Oct 11 17:13:46 UTC 2003") + >>> today = now.date() + >>> year = rrule(YEARLY,dtstart=now,bymonth=8,bymonthday=13,byweekday=FR)[0].year + >>> rdelta = relativedelta(easter(year), today) + >>> print("Today is: %s" % today) + Today is: 2003-10-11 + >>> print("Year with next Aug 13th on a Friday is: %s" % year) + Year with next Aug 13th on a Friday is: 2004 + >>> print("How far is the Easter of that year: %s" % rdelta) + How far is the Easter of that year: relativedelta(months=+6) + >>> print("And the Easter of that year is: %s" % (today+rdelta)) + And the Easter of that year is: 2004-04-11 + +Being exactly 6 months ahead was **really** a coincidence :) + +Contributing +============ + +We welcome many types of contributions - bug reports, pull requests (code, infrastructure or documentation fixes). For more information about how to contribute to the project, see the ``CONTRIBUTING.md`` file in the repository. + + +Author +====== +The dateutil module was written by Gustavo Niemeyer +in 2003. + +It is maintained by: + +* Gustavo Niemeyer 2003-2011 +* Tomi Pieviläinen 2012-2014 +* Yaron de Leeuw 2014-2016 +* Paul Ganssle 2015- + +Starting with version 2.4.1 and running until 2.8.2, all source and binary +distributions will be signed by a PGP key that has, at the very least, been +signed by the key which made the previous release. A table of release signing +keys can be found below: + +=========== ============================ +Releases Signing key fingerprint +=========== ============================ +2.4.1-2.8.2 `6B49 ACBA DCF6 BD1C A206 67AB CD54 FCE3 D964 BEFB`_ +=========== ============================ + +New releases *may* have signed tags, but binary and source distributions +uploaded to PyPI will no longer have GPG signatures attached. + +Contact +======= +Our mailing list is available at `dateutil@python.org `_. As it is hosted by the PSF, it is subject to the `PSF code of +conduct `_. + +License +======= + +All contributions after December 1, 2017 released under dual license - either `Apache 2.0 License `_ or the `BSD 3-Clause License `_. Contributions before December 1, 2017 - except those those explicitly relicensed - are released only under the BSD 3-Clause License. + + +.. _6B49 ACBA DCF6 BD1C A206 67AB CD54 FCE3 D964 BEFB: + https://pgp.mit.edu/pks/lookup?op=vindex&search=0xCD54FCE3D964BEFB diff --git a/python_dateutil-2.9.0.post0.dist-info/RECORD b/python_dateutil-2.9.0.post0.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..80cde96581cce34e038232c05925ca054de05960 --- /dev/null +++ b/python_dateutil-2.9.0.post0.dist-info/RECORD @@ -0,0 +1,27 @@ +dateutil/__init__.py,sha256=Mqam67WO9IkTmUFyI66vS6IoSXTp9G388DadH2LCMLY,620 +dateutil/_common.py,sha256=77w0yytkrxlYbSn--lDVPUMabUXRR9I3lBv_vQRUqUY,932 +dateutil/_version.py,sha256=BV031OxDDAmy58neUg5yyqLkLaqIw7ibK9As3jiMib0,166 +dateutil/easter.py,sha256=dyBi-lKvimH1u_k6p7Z0JJK72QhqVtVBsqByvpEPKvc,2678 +dateutil/parser/__init__.py,sha256=wWk6GFuxTpjoggCGtgkceJoti4pVjl4_fHQXpNOaSYg,1766 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Production/Stable +Classifier: Intended Audience :: Developers +Classifier: Operating System :: OS Independent +Classifier: Programming Language :: Python :: 3.10 +Classifier: Programming Language :: Python :: 3.11 +Classifier: Programming Language :: Python :: 3.12 +Classifier: Programming Language :: Python :: 3.13 +Classifier: Programming Language :: Python :: 3.14 +Classifier: Topic :: Scientific/Engineering :: Information Analysis +Classifier: Topic :: Software Development :: Libraries :: Python Modules +Classifier: Topic :: Text Processing +Classifier: Topic :: Text Processing :: General +Requires-Python: >=3.10 +Description-Content-Type: text/x-rst +License-File: LICENSE.txt +Dynamic: license-file + +Introduction +------------ + +This regex implementation is backwards-compatible with the standard 're' module, but offers additional functionality. + +Python 2 +-------- + +Python 2 is no longer supported. The last release that supported Python 2 was 2021.11.10. + +PyPy +---- + +This module is targeted at CPython. It expects that all codepoints are the same width, so it won't behave properly with PyPy outside U+0000..U+007F because PyPy stores strings as UTF-8. + +Multithreading +-------------- + +The regex module releases the GIL during matching on instances of the built-in (immutable) string classes, enabling other Python threads to run concurrently. It is also possible to force the regex module to release the GIL during matching by calling the matching methods with the keyword argument ``concurrent=True``. The behaviour is undefined if the string changes during matching, so use it *only* when it is guaranteed that that won't happen. + +Unicode +------- + +This module supports Unicode 17.0.0. Full Unicode case-folding is supported. + +Flags +----- + +There are 2 kinds of flag: scoped and global. Scoped flags can apply to only part of a pattern and can be turned on or off; global flags apply to the entire pattern and can only be turned on. + +The scoped flags are: ``ASCII (?a)``, ``FULLCASE (?f)``, ``IGNORECASE (?i)``, ``LOCALE (?L)``, ``MULTILINE (?m)``, ``DOTALL (?s)``, ``UNICODE (?u)``, ``VERBOSE (?x)``, ``WORD (?w)``. + +The global flags are: ``BESTMATCH (?b)``, ``ENHANCEMATCH (?e)``, ``POSIX (?p)``, ``REVERSE (?r)``, ``VERSION0 (?V0)``, ``VERSION1 (?V1)``. + +If neither the ``ASCII``, ``LOCALE`` nor ``UNICODE`` flag is specified, it will default to ``UNICODE`` if the regex pattern is a Unicode string and ``ASCII`` if it's a bytestring. + +The ``ENHANCEMATCH`` flag makes fuzzy matching attempt to improve the fit of the next match that it finds. + +The ``BESTMATCH`` flag makes fuzzy matching search for the best match instead of the next match. + +Old vs new behaviour +-------------------- + +In order to be compatible with the re module, this module has 2 behaviours: + +* **Version 0** behaviour (old behaviour, compatible with the re module): + + Please note that the re module's behaviour may change over time, and I'll endeavour to match that behaviour in version 0. + + * Indicated by the ``VERSION0`` flag. + + * Zero-width matches are not handled correctly in the re module before Python 3.7. The behaviour in those earlier versions is: + + * ``.split`` won't split a string at a zero-width match. + + * ``.sub`` will advance by one character after a zero-width match. + + * Inline flags apply to the entire pattern, and they can't be turned off. + + * Only simple sets are supported. + + * Case-insensitive matches in Unicode use simple case-folding by default. + +* **Version 1** behaviour (new behaviour, possibly different from the re module): + + * Indicated by the ``VERSION1`` flag. + + * Zero-width matches are handled correctly. + + * Inline flags apply to the end of the group or pattern, and they can be turned off. + + * Nested sets and set operations are supported. + + * Case-insensitive matches in Unicode use full case-folding by default. + +If no version is specified, the regex module will default to ``regex.DEFAULT_VERSION``. + +Case-insensitive matches in Unicode +----------------------------------- + +The regex module supports both simple and full case-folding for case-insensitive matches in Unicode. Use of full case-folding can be turned on using the ``FULLCASE`` flag. Please note that this flag affects how the ``IGNORECASE`` flag works; the ``FULLCASE`` flag itself does not turn on case-insensitive matching. + +Version 0 behaviour: the flag is off by default. + +Version 1 behaviour: the flag is on by default. + +Nested sets and set operations +------------------------------ + +It's not possible to support both simple sets, as used in the re module, and nested sets at the same time because of a difference in the meaning of an unescaped ``"["`` in a set. + +For example, the pattern ``[[a-z]--[aeiou]]`` is treated in the version 0 behaviour (simple sets, compatible with the re module) as: + +* Set containing "[" and the letters "a" to "z" + +* Literal "--" + +* Set containing letters "a", "e", "i", "o", "u" + +* Literal "]" + +but in the version 1 behaviour (nested sets, enhanced behaviour) as: + +* Set which is: + + * Set containing the letters "a" to "z" + +* but excluding: + + * Set containing the letters "a", "e", "i", "o", "u" + +Version 0 behaviour: only simple sets are supported. + +Version 1 behaviour: nested sets and set operations are supported. + +Notes on named groups +--------------------- + +All groups have a group number, starting from 1. + +Groups with the same group name will have the same group number, and groups with a different group name will have a different group number. + +The same name can be used by more than one group, with later captures 'overwriting' earlier captures. All the captures of the group will be available from the ``captures`` method of the match object. + +Group numbers will be reused across different branches of a branch reset, eg. ``(?|(first)|(second))`` has only group 1. If groups have different group names then they will, of course, have different group numbers, eg. ``(?|(?Pfirst)|(?Psecond))`` has group 1 ("foo") and group 2 ("bar"). + +In the regex ``(\s+)(?|(?P[A-Z]+)|(\w+) (?P[0-9]+)`` there are 2 groups: + +* ``(\s+)`` is group 1. + +* ``(?P[A-Z]+)`` is group 2, also called "foo". + +* ``(\w+)`` is group 2 because of the branch reset. + +* ``(?P[0-9]+)`` is group 2 because it's called "foo". + +If you want to prevent ``(\w+)`` from being group 2, you need to name it (different name, different group number). + +Additional features +------------------- + +The issue numbers relate to the Python bug tracker, except where listed otherwise. + +Added ``\p{Horiz_Space}`` and ``\p{Vert_Space}`` (`GitHub issue 477 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``\p{Horiz_Space}`` or ``\p{H}`` matches horizontal whitespace and ``\p{Vert_Space}`` or ``\p{V}`` matches vertical whitespace. + +Added support for lookaround in conditional pattern (`Hg issue 163 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +The test of a conditional pattern can be a lookaround. + +.. sourcecode:: python + + >>> regex.match(r'(?(?=\d)\d+|\w+)', '123abc') + + >>> regex.match(r'(?(?=\d)\d+|\w+)', 'abc123') + + +This is not quite the same as putting a lookaround in the first branch of a pair of alternatives. + +.. sourcecode:: python + + >>> print(regex.match(r'(?:(?=\d)\d+\b|\w+)', '123abc')) + + >>> print(regex.match(r'(?(?=\d)\d+\b|\w+)', '123abc')) + None + +In the first example, the lookaround matched, but the remainder of the first branch failed to match, and so the second branch was attempted, whereas in the second example, the lookaround matched, and the first branch failed to match, but the second branch was **not** attempted. + +Added POSIX matching (leftmost longest) (`Hg issue 150 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +The POSIX standard for regex is to return the leftmost longest match. This can be turned on using the ``POSIX`` flag. + +.. sourcecode:: python + + >>> # Normal matching. + >>> regex.search(r'Mr|Mrs', 'Mrs') + + >>> regex.search(r'one(self)?(selfsufficient)?', 'oneselfsufficient') + + >>> # POSIX matching. + >>> regex.search(r'(?p)Mr|Mrs', 'Mrs') + + >>> regex.search(r'(?p)one(self)?(selfsufficient)?', 'oneselfsufficient') + + +Note that it will take longer to find matches because when it finds a match at a certain position, it won't return that immediately, but will keep looking to see if there's another longer match there. + +Added ``(?(DEFINE)...)`` (`Hg issue 152 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +If there's no group called "DEFINE", then ... will be ignored except that any groups defined within it can be called and that the normal rules for numbering groups still apply. + +.. sourcecode:: python + + >>> regex.search(r'(?(DEFINE)(?P\d+)(?P\w+))(?&quant) (?&item)', '5 elephants') + + +Added ``(*PRUNE)``, ``(*SKIP)`` and ``(*FAIL)`` (`Hg issue 153 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``(*PRUNE)`` discards the backtracking info up to that point. When used in an atomic group or a lookaround, it won't affect the enclosing pattern. + +``(*SKIP)`` is similar to ``(*PRUNE)``, except that it also sets where in the text the next attempt to match will start. When used in an atomic group or a lookaround, it won't affect the enclosing pattern. + +``(*FAIL)`` causes immediate backtracking. ``(*F)`` is a permitted abbreviation. + +Added ``\K`` (`Hg issue 151 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Keeps the part of the entire match after the position where ``\K`` occurred; the part before it is discarded. + +It does not affect what groups return. + +.. sourcecode:: python + + >>> m = regex.search(r'(\w\w\K\w\w\w)', 'abcdef') + >>> m[0] + 'cde' + >>> m[1] + 'abcde' + >>> + >>> m = regex.search(r'(?r)(\w\w\K\w\w\w)', 'abcdef') + >>> m[0] + 'bc' + >>> m[1] + 'bcdef' + +Added capture subscripting for ``expandf`` and ``subf``/``subfn`` (`Hg issue 133 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +You can use subscripting to get the captures of a repeated group. + +.. sourcecode:: python + + >>> m = regex.match(r"(\w)+", "abc") + >>> m.expandf("{1}") + 'c' + >>> m.expandf("{1[0]} {1[1]} {1[2]}") + 'a b c' + >>> m.expandf("{1[-1]} {1[-2]} {1[-3]}") + 'c b a' + >>> + >>> m = regex.match(r"(?P\w)+", "abc") + >>> m.expandf("{letter}") + 'c' + >>> m.expandf("{letter[0]} {letter[1]} {letter[2]}") + 'a b c' + >>> m.expandf("{letter[-1]} {letter[-2]} {letter[-3]}") + 'c b a' + +Added support for referring to a group by number using ``(?P=...)`` +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +This is in addition to the existing ``\g<...>``. + +Fixed the handling of locale-sensitive regexes +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +The ``LOCALE`` flag is intended for legacy code and has limited support. You're still recommended to use Unicode instead. + +Added partial matches (`Hg issue 102 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +A partial match is one that matches up to the end of string, but that string has been truncated and you want to know whether a complete match could be possible if the string had not been truncated. + +Partial matches are supported by ``match``, ``search``, ``fullmatch`` and ``finditer`` with the ``partial`` keyword argument. + +Match objects have a ``partial`` attribute, which is ``True`` if it's a partial match. + +For example, if you wanted a user to enter a 4-digit number and check it character by character as it was being entered: + +.. sourcecode:: python + + >>> pattern = regex.compile(r'\d{4}') + + >>> # Initially, nothing has been entered: + >>> print(pattern.fullmatch('', partial=True)) + + + >>> # An empty string is OK, but it's only a partial match. + >>> # The user enters a letter: + >>> print(pattern.fullmatch('a', partial=True)) + None + >>> # It'll never match. + + >>> # The user deletes that and enters a digit: + >>> print(pattern.fullmatch('1', partial=True)) + + >>> # It matches this far, but it's only a partial match. + + >>> # The user enters 2 more digits: + >>> print(pattern.fullmatch('123', partial=True)) + + >>> # It matches this far, but it's only a partial match. + + >>> # The user enters another digit: + >>> print(pattern.fullmatch('1234', partial=True)) + + >>> # It's a complete match. + + >>> # If the user enters another digit: + >>> print(pattern.fullmatch('12345', partial=True)) + None + >>> # It's no longer a match. + + >>> # This is a partial match: + >>> pattern.match('123', partial=True).partial + True + + >>> # This is a complete match: + >>> pattern.match('1233', partial=True).partial + False + +``*`` operator not working correctly with sub() (`Hg issue 106 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Sometimes it's not clear how zero-width matches should be handled. For example, should ``.*`` match 0 characters directly after matching >0 characters? + +.. sourcecode:: python + + >>> regex.sub('.*', 'x', 'test') + 'xx' + >>> regex.sub('.*?', '|', 'test') + '|||||||||' + +Added ``capturesdict`` (`Hg issue 86 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``capturesdict`` is a combination of ``groupdict`` and ``captures``: + +``groupdict`` returns a dict of the named groups and the last capture of those groups. + +``captures`` returns a list of all the captures of a group + +``capturesdict`` returns a dict of the named groups and lists of all the captures of those groups. + +.. sourcecode:: python + + >>> m = regex.match(r"(?:(?P\w+) (?P\d+)\n)+", "one 1\ntwo 2\nthree 3\n") + >>> m.groupdict() + {'word': 'three', 'digits': '3'} + >>> m.captures("word") + ['one', 'two', 'three'] + >>> m.captures("digits") + ['1', '2', '3'] + >>> m.capturesdict() + {'word': ['one', 'two', 'three'], 'digits': ['1', '2', '3']} + +Added ``allcaptures`` and ``allspans`` (`Git issue 474 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``allcaptures`` returns a list of all the captures of all the groups. + +``allspans`` returns a list of all the spans of the all captures of all the groups. + +.. sourcecode:: python + + >>> m = regex.match(r"(?:(?P\w+) (?P\d+)\n)+", "one 1\ntwo 2\nthree 3\n") + >>> m.allcaptures() + (['one 1\ntwo 2\nthree 3\n'], ['one', 'two', 'three'], ['1', '2', '3']) + >>> m.allspans() + ([(0, 20)], [(0, 3), (6, 9), (12, 17)], [(4, 5), (10, 11), (18, 19)]) + +Allow duplicate names of groups (`Hg issue 87 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Group names can be duplicated. + +.. sourcecode:: python + + >>> # With optional groups: + >>> + >>> # Both groups capture, the second capture 'overwriting' the first. + >>> m = regex.match(r"(?P\w+)? or (?P\w+)?", "first or second") + >>> m.group("item") + 'second' + >>> m.captures("item") + ['first', 'second'] + >>> # Only the second group captures. + >>> m = regex.match(r"(?P\w+)? or (?P\w+)?", " or second") + >>> m.group("item") + 'second' + >>> m.captures("item") + ['second'] + >>> # Only the first group captures. + >>> m = regex.match(r"(?P\w+)? or (?P\w+)?", "first or ") + >>> m.group("item") + 'first' + >>> m.captures("item") + ['first'] + >>> + >>> # With mandatory groups: + >>> + >>> # Both groups capture, the second capture 'overwriting' the first. + >>> m = regex.match(r"(?P\w*) or (?P\w*)?", "first or second") + >>> m.group("item") + 'second' + >>> m.captures("item") + ['first', 'second'] + >>> # Again, both groups capture, the second capture 'overwriting' the first. + >>> m = regex.match(r"(?P\w*) or (?P\w*)", " or second") + >>> m.group("item") + 'second' + >>> m.captures("item") + ['', 'second'] + >>> # And yet again, both groups capture, the second capture 'overwriting' the first. + >>> m = regex.match(r"(?P\w*) or (?P\w*)", "first or ") + >>> m.group("item") + '' + >>> m.captures("item") + ['first', ''] + +Added ``fullmatch`` (`issue #16203 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``fullmatch`` behaves like ``match``, except that it must match all of the string. + +.. sourcecode:: python + + >>> print(regex.fullmatch(r"abc", "abc").span()) + (0, 3) + >>> print(regex.fullmatch(r"abc", "abcx")) + None + >>> print(regex.fullmatch(r"abc", "abcx", endpos=3).span()) + (0, 3) + >>> print(regex.fullmatch(r"abc", "xabcy", pos=1, endpos=4).span()) + (1, 4) + >>> + >>> regex.match(r"a.*?", "abcd").group(0) + 'a' + >>> regex.fullmatch(r"a.*?", "abcd").group(0) + 'abcd' + +Added ``subf`` and ``subfn`` +^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``subf`` and ``subfn`` are alternatives to ``sub`` and ``subn`` respectively. When passed a replacement string, they treat it as a format string. + +.. sourcecode:: python + + >>> regex.subf(r"(\w+) (\w+)", "{0} => {2} {1}", "foo bar") + 'foo bar => bar foo' + >>> regex.subf(r"(?P\w+) (?P\w+)", "{word2} {word1}", "foo bar") + 'bar foo' + +Added ``expandf`` to match object +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``expandf`` is an alternative to ``expand``. When passed a replacement string, it treats it as a format string. + +.. sourcecode:: python + + >>> m = regex.match(r"(\w+) (\w+)", "foo bar") + >>> m.expandf("{0} => {2} {1}") + 'foo bar => bar foo' + >>> + >>> m = regex.match(r"(?P\w+) (?P\w+)", "foo bar") + >>> m.expandf("{word2} {word1}") + 'bar foo' + +Detach searched string +^^^^^^^^^^^^^^^^^^^^^^ + +A match object contains a reference to the string that was searched, via its ``string`` attribute. The ``detach_string`` method will 'detach' that string, making it available for garbage collection, which might save valuable memory if that string is very large. + +.. sourcecode:: python + + >>> m = regex.search(r"\w+", "Hello world") + >>> print(m.group()) + Hello + >>> print(m.string) + Hello world + >>> m.detach_string() + >>> print(m.group()) + Hello + >>> print(m.string) + None + +Recursive patterns (`Hg issue 27 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Recursive and repeated patterns are supported. + +``(?R)`` or ``(?0)`` tries to match the entire regex recursively. ``(?1)``, ``(?2)``, etc, try to match the relevant group. + +``(?&name)`` tries to match the named group. + +.. sourcecode:: python + + >>> regex.match(r"(Tarzan|Jane) loves (?1)", "Tarzan loves Jane").groups() + ('Tarzan',) + >>> regex.match(r"(Tarzan|Jane) loves (?1)", "Jane loves Tarzan").groups() + ('Jane',) + + >>> m = regex.search(r"(\w)(?:(?R)|(\w?))\1", "kayak") + >>> m.group(0, 1, 2) + ('kayak', 'k', None) + +The first two examples show how the subpattern within the group is reused, but is _not_ itself a group. In other words, ``"(Tarzan|Jane) loves (?1)"`` is equivalent to ``"(Tarzan|Jane) loves (?:Tarzan|Jane)"``. + +It's possible to backtrack into a recursed or repeated group. + +You can't call a group if there is more than one group with that group name or group number (``"ambiguous group reference"``). + +The alternative forms ``(?P>name)`` and ``(?P&name)`` are also supported. + +Full Unicode case-folding is supported +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +In version 1 behaviour, the regex module uses full case-folding when performing case-insensitive matches in Unicode. + +.. sourcecode:: python + + >>> regex.match(r"(?iV1)strasse", "stra\N{LATIN SMALL LETTER SHARP S}e").span() + (0, 6) + >>> regex.match(r"(?iV1)stra\N{LATIN SMALL LETTER SHARP S}e", "STRASSE").span() + (0, 7) + +In version 0 behaviour, it uses simple case-folding for backward compatibility with the re module. + +Approximate "fuzzy" matching (`Hg issue 12 `_, `Hg issue 41 `_, `Hg issue 109 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Regex usually attempts an exact match, but sometimes an approximate, or "fuzzy", match is needed, for those cases where the text being searched may contain errors in the form of inserted, deleted or substituted characters. + +A fuzzy regex specifies which types of errors are permitted, and, optionally, either the minimum and maximum or only the maximum permitted number of each type. (You cannot specify only a minimum.) + +The 3 types of error are: + +* Insertion, indicated by "i" + +* Deletion, indicated by "d" + +* Substitution, indicated by "s" + +In addition, "e" indicates any type of error. + +The fuzziness of a regex item is specified between "{" and "}" after the item. + +Examples: + +* ``foo`` match "foo" exactly + +* ``(?:foo){i}`` match "foo", permitting insertions + +* ``(?:foo){d}`` match "foo", permitting deletions + +* ``(?:foo){s}`` match "foo", permitting substitutions + +* ``(?:foo){i,s}`` match "foo", permitting insertions and substitutions + +* ``(?:foo){e}`` match "foo", permitting errors + +If a certain type of error is specified, then any type not specified will **not** be permitted. + +In the following examples I'll omit the item and write only the fuzziness: + +* ``{d<=3}`` permit at most 3 deletions, but no other types + +* ``{i<=1,s<=2}`` permit at most 1 insertion and at most 2 substitutions, but no deletions + +* ``{1<=e<=3}`` permit at least 1 and at most 3 errors + +* ``{i<=2,d<=2,e<=3}`` permit at most 2 insertions, at most 2 deletions, at most 3 errors in total, but no substitutions + +It's also possible to state the costs of each type of error and the maximum permitted total cost. + +Examples: + +* ``{2i+2d+1s<=4}`` each insertion costs 2, each deletion costs 2, each substitution costs 1, the total cost must not exceed 4 + +* ``{i<=1,d<=1,s<=1,2i+2d+1s<=4}`` at most 1 insertion, at most 1 deletion, at most 1 substitution; each insertion costs 2, each deletion costs 2, each substitution costs 1, the total cost must not exceed 4 + +You can also use "<" instead of "<=" if you want an exclusive minimum or maximum. + +You can add a test to perform on a character that's substituted or inserted. + +Examples: + +* ``{s<=2:[a-z]}`` at most 2 substitutions, which must be in the character set ``[a-z]``. + +* ``{s<=2,i<=3:\d}`` at most 2 substitutions, at most 3 insertions, which must be digits. + +By default, fuzzy matching searches for the first match that meets the given constraints. The ``ENHANCEMATCH`` flag will cause it to attempt to improve the fit (i.e. reduce the number of errors) of the match that it has found. + +The ``BESTMATCH`` flag will make it search for the best match instead. + +Further examples to note: + +* ``regex.search("(dog){e}", "cat and dog")[1]`` returns ``"cat"`` because that matches ``"dog"`` with 3 errors (an unlimited number of errors is permitted). + +* ``regex.search("(dog){e<=1}", "cat and dog")[1]`` returns ``" dog"`` (with a leading space) because that matches ``"dog"`` with 1 error, which is within the limit. + +* ``regex.search("(?e)(dog){e<=1}", "cat and dog")[1]`` returns ``"dog"`` (without a leading space) because the fuzzy search matches ``" dog"`` with 1 error, which is within the limit, and the ``(?e)`` then it attempts a better fit. + +In the first two examples there are perfect matches later in the string, but in neither case is it the first possible match. + +The match object has an attribute ``fuzzy_counts`` which gives the total number of substitutions, insertions and deletions. + +.. sourcecode:: python + + >>> # A 'raw' fuzzy match: + >>> regex.fullmatch(r"(?:cats|cat){e<=1}", "cat").fuzzy_counts + (0, 0, 1) + >>> # 0 substitutions, 0 insertions, 1 deletion. + + >>> # A better match might be possible if the ENHANCEMATCH flag used: + >>> regex.fullmatch(r"(?e)(?:cats|cat){e<=1}", "cat").fuzzy_counts + (0, 0, 0) + >>> # 0 substitutions, 0 insertions, 0 deletions. + +The match object also has an attribute ``fuzzy_changes`` which gives a tuple of the positions of the substitutions, insertions and deletions. + +.. sourcecode:: python + + >>> m = regex.search('(fuu){i<=2,d<=2,e<=5}', 'anaconda foo bar') + >>> m + + >>> m.fuzzy_changes + ([], [7, 8], [10, 11]) + +What this means is that if the matched part of the string had been: + +.. sourcecode:: python + + 'anacondfuuoo bar' + +it would've been an exact match. + +However, there were insertions at positions 7 and 8: + +.. sourcecode:: python + + 'anaconda fuuoo bar' + ^^ + +and deletions at positions 10 and 11: + +.. sourcecode:: python + + 'anaconda f~~oo bar' + ^^ + +So the actual string was: + +.. sourcecode:: python + + 'anaconda foo bar' + +Named lists ``\L`` (`Hg issue 11 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +There are occasions where you may want to include a list (actually, a set) of options in a regex. + +One way is to build the pattern like this: + +.. sourcecode:: python + + >>> p = regex.compile(r"first|second|third|fourth|fifth") + +but if the list is large, parsing the resulting regex can take considerable time, and care must also be taken that the strings are properly escaped and properly ordered, for example, "cats" before "cat". + +The new alternative is to use a named list: + +.. sourcecode:: python + + >>> option_set = ["first", "second", "third", "fourth", "fifth"] + >>> p = regex.compile(r"\L", options=option_set) + +The order of the items is irrelevant, they are treated as a set. The named lists are available as the ``.named_lists`` attribute of the pattern object : + +.. sourcecode:: python + + >>> print(p.named_lists) + {'options': frozenset({'third', 'first', 'fifth', 'fourth', 'second'})} + +If there are any unused keyword arguments, ``ValueError`` will be raised unless you tell it otherwise: + +.. sourcecode:: python + + >>> option_set = ["first", "second", "third", "fourth", "fifth"] + >>> p = regex.compile(r"\L", options=option_set, other_options=[]) + Traceback (most recent call last): + File "", line 1, in + File "C:\Python310\lib\site-packages\regex\regex.py", line 353, in compile + return _compile(pattern, flags, ignore_unused, kwargs, cache_pattern) + File "C:\Python310\lib\site-packages\regex\regex.py", line 500, in _compile + complain_unused_args() + File "C:\Python310\lib\site-packages\regex\regex.py", line 483, in complain_unused_args + raise ValueError('unused keyword argument {!a}'.format(any_one)) + ValueError: unused keyword argument 'other_options' + >>> p = regex.compile(r"\L", options=option_set, other_options=[], ignore_unused=True) + >>> p = regex.compile(r"\L", options=option_set, other_options=[], ignore_unused=False) + Traceback (most recent call last): + File "", line 1, in + File "C:\Python310\lib\site-packages\regex\regex.py", line 353, in compile + return _compile(pattern, flags, ignore_unused, kwargs, cache_pattern) + File "C:\Python310\lib\site-packages\regex\regex.py", line 500, in _compile + complain_unused_args() + File "C:\Python310\lib\site-packages\regex\regex.py", line 483, in complain_unused_args + raise ValueError('unused keyword argument {!a}'.format(any_one)) + ValueError: unused keyword argument 'other_options' + >>> + +Start and end of word +^^^^^^^^^^^^^^^^^^^^^ + +``\m`` matches at the start of a word. + +``\M`` matches at the end of a word. + +Compare with ``\b``, which matches at the start or end of a word. + +Unicode line separators +^^^^^^^^^^^^^^^^^^^^^^^ + +Normally the only line separator is ``\n`` (``\x0A``), but if the ``WORD`` flag is turned on then the line separators are ``\x0D\x0A``, ``\x0A``, ``\x0B``, ``\x0C`` and ``\x0D``, plus ``\x85``, ``\u2028`` and ``\u2029`` when working with Unicode. + +This affects the regex dot ``"."``, which, with the ``DOTALL`` flag turned off, matches any character except a line separator. It also affects the line anchors ``^`` and ``$`` (in multiline mode). + +Set operators +^^^^^^^^^^^^^ + +**Version 1 behaviour only** + +Set operators have been added, and a set ``[...]`` can include nested sets. + +The operators, in order of increasing precedence, are: + +* ``||`` for union ("x||y" means "x or y") + +* ``~~`` (double tilde) for symmetric difference ("x~~y" means "x or y, but not both") + +* ``&&`` for intersection ("x&&y" means "x and y") + +* ``--`` (double dash) for difference ("x--y" means "x but not y") + +Implicit union, ie, simple juxtaposition like in ``[ab]``, has the highest precedence. Thus, ``[ab&&cd]`` is the same as ``[[a||b]&&[c||d]]``. + +Examples: + +* ``[ab]`` # Set containing 'a' and 'b' + +* ``[a-z]`` # Set containing 'a' .. 'z' + +* ``[[a-z]--[qw]]`` # Set containing 'a' .. 'z', but not 'q' or 'w' + +* ``[a-z--qw]`` # Same as above + +* ``[\p{L}--QW]`` # Set containing all letters except 'Q' and 'W' + +* ``[\p{N}--[0-9]]`` # Set containing all numbers except '0' .. '9' + +* ``[\p{ASCII}&&\p{Letter}]`` # Set containing all characters which are ASCII and letter + +regex.escape (`issue #2650 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +regex.escape has an additional keyword parameter ``special_only``. When True, only 'special' regex characters, such as '?', are escaped. + +.. sourcecode:: python + + >>> regex.escape("foo!?", special_only=False) + 'foo\\!\\?' + >>> regex.escape("foo!?", special_only=True) + 'foo!\\?' + +regex.escape (`Hg issue 249 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +regex.escape has an additional keyword parameter ``literal_spaces``. When True, spaces are not escaped. + +.. sourcecode:: python + + >>> regex.escape("foo bar!?", literal_spaces=False) + 'foo\\ bar!\\?' + >>> regex.escape("foo bar!?", literal_spaces=True) + 'foo bar!\\?' + +Repeated captures (`issue #7132 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +A match object has additional methods which return information on all the successful matches of a repeated group. These methods are: + +* ``matchobject.captures([group1, ...])`` + + * Returns a list of the strings matched in a group or groups. Compare with ``matchobject.group([group1, ...])``. + +* ``matchobject.starts([group])`` + + * Returns a list of the start positions. Compare with ``matchobject.start([group])``. + +* ``matchobject.ends([group])`` + + * Returns a list of the end positions. Compare with ``matchobject.end([group])``. + +* ``matchobject.spans([group])`` + + * Returns a list of the spans. Compare with ``matchobject.span([group])``. + +.. sourcecode:: python + + >>> m = regex.search(r"(\w{3})+", "123456789") + >>> m.group(1) + '789' + >>> m.captures(1) + ['123', '456', '789'] + >>> m.start(1) + 6 + >>> m.starts(1) + [0, 3, 6] + >>> m.end(1) + 9 + >>> m.ends(1) + [3, 6, 9] + >>> m.span(1) + (6, 9) + >>> m.spans(1) + [(0, 3), (3, 6), (6, 9)] + +Atomic grouping ``(?>...)`` (`issue #433030 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +If the following pattern subsequently fails, then the subpattern as a whole will fail. + +Possessive quantifiers +^^^^^^^^^^^^^^^^^^^^^^ + +``(?:...)?+`` ; ``(?:...)*+`` ; ``(?:...)++`` ; ``(?:...){min,max}+`` + +The subpattern is matched up to 'max' times. If the following pattern subsequently fails, then all the repeated subpatterns will fail as a whole. For example, ``(?:...)++`` is equivalent to ``(?>(?:...)+)``. + +Scoped flags (`issue #433028 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``(?flags-flags:...)`` + +The flags will apply only to the subpattern. Flags can be turned on or off. + +Definition of 'word' character (`issue #1693050 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +The definition of a 'word' character has been expanded for Unicode. It conforms to the Unicode specification at ``http://www.unicode.org/reports/tr29/``. + +Variable-length lookbehind +^^^^^^^^^^^^^^^^^^^^^^^^^^ + +A lookbehind can match a variable-length string. + +Flags argument for regex.split, regex.sub and regex.subn (`issue #3482 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``regex.split``, ``regex.sub`` and ``regex.subn`` support a 'flags' argument. + +Pos and endpos arguments for regex.sub and regex.subn +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``regex.sub`` and ``regex.subn`` support 'pos' and 'endpos' arguments. + +'Overlapped' argument for regex.findall and regex.finditer +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``regex.findall`` and ``regex.finditer`` support an 'overlapped' flag which permits overlapped matches. + +Splititer +^^^^^^^^^ + +``regex.splititer`` has been added. It's a generator equivalent of ``regex.split``. + +Subscripting match objects for groups +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +A match object accepts access to the groups via subscripting and slicing: + +.. sourcecode:: python + + >>> m = regex.search(r"(?P.*?)(?P\d+)(?P.*)", "pqr123stu") + >>> print(m["before"]) + pqr + >>> print(len(m)) + 4 + >>> print(m[:]) + ('pqr123stu', 'pqr', '123', 'stu') + +Named groups +^^^^^^^^^^^^ + +Groups can be named with ``(?...)`` as well as the existing ``(?P...)``. + +Group references +^^^^^^^^^^^^^^^^ + +Groups can be referenced within a pattern with ``\g``. This also allows there to be more than 99 groups. + +Named characters ``\N{name}`` +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Named characters are supported. Note that only those known by Python's Unicode database will be recognised. + +Unicode codepoint properties, including scripts and blocks +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``\p{property=value}``; ``\P{property=value}``; ``\p{value}`` ; ``\P{value}`` + +Many Unicode properties are supported, including blocks and scripts. ``\p{property=value}`` or ``\p{property:value}`` matches a character whose property ``property`` has value ``value``. The inverse of ``\p{property=value}`` is ``\P{property=value}`` or ``\p{^property=value}``. + +If the short form ``\p{value}`` is used, the properties are checked in the order: ``General_Category``, ``Script``, ``Block``, binary property: + +* ``Latin``, the 'Latin' script (``Script=Latin``). + +* ``BasicLatin``, the 'BasicLatin' block (``Block=BasicLatin``). + +* ``Alphabetic``, the 'Alphabetic' binary property (``Alphabetic=Yes``). + +A short form starting with ``Is`` indicates a script or binary property: + +* ``IsLatin``, the 'Latin' script (``Script=Latin``). + +* ``IsAlphabetic``, the 'Alphabetic' binary property (``Alphabetic=Yes``). + +A short form starting with ``In`` indicates a block property: + +* ``InBasicLatin``, the 'BasicLatin' block (``Block=BasicLatin``). + +POSIX character classes +^^^^^^^^^^^^^^^^^^^^^^^ + +``[[:alpha:]]``; ``[[:^alpha:]]`` + +POSIX character classes are supported. These are normally treated as an alternative form of ``\p{...}``. + +The exceptions are ``alnum``, ``digit``, ``punct`` and ``xdigit``, whose definitions are different from those of Unicode. + +``[[:alnum:]]`` is equivalent to ``\p{posix_alnum}``. + +``[[:digit:]]`` is equivalent to ``\p{posix_digit}``. + +``[[:punct:]]`` is equivalent to ``\p{posix_punct}``. + +``[[:xdigit:]]`` is equivalent to ``\p{posix_xdigit}``. + +Search anchor ``\G`` +^^^^^^^^^^^^^^^^^^^^ + +A search anchor has been added. It matches at the position where each search started/continued and can be used for contiguous matches or in negative variable-length lookbehinds to limit how far back the lookbehind goes: + +.. sourcecode:: python + + >>> regex.findall(r"\w{2}", "abcd ef") + ['ab', 'cd', 'ef'] + >>> regex.findall(r"\G\w{2}", "abcd ef") + ['ab', 'cd'] + +* The search starts at position 0 and matches 'ab'. + +* The search continues at position 2 and matches 'cd'. + +* The search continues at position 4 and fails to match any letters. + +* The anchor stops the search start position from being advanced, so there are no more results. + +Reverse searching +^^^^^^^^^^^^^^^^^ + +Searches can also work backwards: + +.. sourcecode:: python + + >>> regex.findall(r".", "abc") + ['a', 'b', 'c'] + >>> regex.findall(r"(?r).", "abc") + ['c', 'b', 'a'] + +Note that the result of a reverse search is not necessarily the reverse of a forward search: + +.. sourcecode:: python + + >>> regex.findall(r"..", "abcde") + ['ab', 'cd'] + >>> regex.findall(r"(?r)..", "abcde") + ['de', 'bc'] + +Matching a single grapheme ``\X`` +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +The grapheme matcher is supported. It conforms to the Unicode specification at ``http://www.unicode.org/reports/tr29/``. + +Branch reset ``(?|...|...)`` +^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Group numbers will be reused across the alternatives, but groups with different names will have different group numbers. + +.. sourcecode:: python + + >>> regex.match(r"(?|(first)|(second))", "first").groups() + ('first',) + >>> regex.match(r"(?|(first)|(second))", "second").groups() + ('second',) + +Note that there is only one group. + +Default Unicode word boundary +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +The ``WORD`` flag changes the definition of a 'word boundary' to that of a default Unicode word boundary. This applies to ``\b`` and ``\B``. + +Timeout +^^^^^^^ + +The matching methods and functions support timeouts. The timeout (in seconds) applies to the entire operation: + +.. sourcecode:: python + + >>> from time import sleep + >>> + >>> def fast_replace(m): + ... return 'X' + ... + >>> def slow_replace(m): + ... sleep(0.5) + ... return 'X' + ... + >>> regex.sub(r'[a-z]', fast_replace, 'abcde', timeout=2) + 'XXXXX' + >>> regex.sub(r'[a-z]', slow_replace, 'abcde', timeout=2) + Traceback (most recent call last): + File "", line 1, in + File "C:\Python310\lib\site-packages\regex\regex.py", line 278, in sub + return pat.sub(repl, string, count, pos, endpos, concurrent, timeout) + TimeoutError: regex timed out diff --git a/regex-2026.2.28.dist-info/RECORD b/regex-2026.2.28.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..15195626015cc33fffe30808e489028fd97724e3 --- /dev/null +++ b/regex-2026.2.28.dist-info/RECORD @@ -0,0 +1,12 @@ +regex-2026.2.28.dist-info/INSTALLER,sha256=5hhM4Q4mYTT9z6QB6PGpUAW81PGNFrYrdXMj4oM_6ak,2 +regex-2026.2.28.dist-info/METADATA,sha256=XpuKd1x2K-8IIle-qzU3TO4R5Maawp3kCZx5KUAW6D0,40418 +regex-2026.2.28.dist-info/RECORD,, +regex-2026.2.28.dist-info/REQUESTED,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0 +regex-2026.2.28.dist-info/WHEEL,sha256=ND-iKo1q8cWcsXAKXBKvQvxAFH_GQvThPpjreAAS6vI,190 +regex-2026.2.28.dist-info/licenses/LICENSE.txt,sha256=v_Ve9M3MjBTOJZ-OirYOJkQYRA1jNfTcE4Jz-9UGFE0,11584 +regex-2026.2.28.dist-info/top_level.txt,sha256=aQmiDMhNTF26cCK4_7D-qaVvhbxClG0wyCTnEhkzYBs,6 +regex/__init__.py,sha256=A5k0rm8Ln7HKsfG-8sEWYehek8zCKEe6sQW5QGUAmSU,75 +regex/_main.py,sha256=w_BoQCtLZbxOA0BMSqjUULpqZz0Upda9GIKyuIAtTOA,33344 +regex/_regex.cpython-312-x86_64-linux-gnu.so,sha256=B1Tong2wkKJQH_TNCRo7h0UbsWUF7M1uK-IoaGlV06Q,2575576 +regex/_regex_core.py,sha256=qDeLnme3R-VJDImGVqS6I2cq-jdy0-w86Xal8jSNDHo,147374 +regex/tests/test_regex.py,sha256=iE4XOfiEpWrGKDUZISDxlxNi-Y0rX8KPH8yAwpMTLbI,225809 diff --git a/regex-2026.2.28.dist-info/REQUESTED b/regex-2026.2.28.dist-info/REQUESTED new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/regex-2026.2.28.dist-info/WHEEL b/regex-2026.2.28.dist-info/WHEEL new file mode 100644 index 0000000000000000000000000000000000000000..e6d9007e27e3de36fddd18a30cff154a989b9aec --- /dev/null +++ b/regex-2026.2.28.dist-info/WHEEL @@ -0,0 +1,7 @@ +Wheel-Version: 1.0 +Generator: setuptools (82.0.0) +Root-Is-Purelib: false +Tag: cp312-cp312-manylinux_2_17_x86_64 +Tag: cp312-cp312-manylinux2014_x86_64 +Tag: cp312-cp312-manylinux_2_28_x86_64 + diff --git a/regex-2026.2.28.dist-info/top_level.txt b/regex-2026.2.28.dist-info/top_level.txt new file mode 100644 index 0000000000000000000000000000000000000000..4f9256d62325c75de027d1cd48f1ff520117413e --- /dev/null +++ b/regex-2026.2.28.dist-info/top_level.txt @@ -0,0 +1 @@ +regex diff --git a/requests/__init__.py b/requests/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..051cda1340effaa0706b46dd68ac002ceda3d45c --- /dev/null +++ b/requests/__init__.py @@ -0,0 +1,184 @@ +# __ +# /__) _ _ _ _ _/ _ +# / ( (- (/ (/ (- _) / _) +# / + +""" +Requests HTTP Library +~~~~~~~~~~~~~~~~~~~~~ + +Requests is an HTTP library, written in Python, for human beings. +Basic GET usage: + + >>> import requests + >>> r = requests.get('https://www.python.org') + >>> r.status_code + 200 + >>> b'Python is a programming language' in r.content + True + +... or POST: + + >>> payload = dict(key1='value1', key2='value2') + >>> r = requests.post('https://httpbin.org/post', data=payload) + >>> print(r.text) + { + ... + "form": { + "key1": "value1", + "key2": "value2" + }, + ... + } + +The other HTTP methods are supported - see `requests.api`. Full documentation +is at . + +:copyright: (c) 2017 by Kenneth Reitz. +:license: Apache 2.0, see LICENSE for more details. +""" + +import warnings + +import urllib3 + +from .exceptions import RequestsDependencyWarning + +try: + from charset_normalizer import __version__ as charset_normalizer_version +except ImportError: + charset_normalizer_version = None + +try: + from chardet import __version__ as chardet_version +except ImportError: + chardet_version = None + + +def check_compatibility(urllib3_version, chardet_version, charset_normalizer_version): + urllib3_version = urllib3_version.split(".") + assert urllib3_version != ["dev"] # Verify urllib3 isn't installed from git. + + # Sometimes, urllib3 only reports its version as 16.1. + if len(urllib3_version) == 2: + urllib3_version.append("0") + + # Check urllib3 for compatibility. + major, minor, patch = urllib3_version # noqa: F811 + major, minor, patch = int(major), int(minor), int(patch) + # urllib3 >= 1.21.1 + assert major >= 1 + if major == 1: + assert minor >= 21 + + # Check charset_normalizer for compatibility. + if chardet_version: + major, minor, patch = chardet_version.split(".")[:3] + major, minor, patch = int(major), int(minor), int(patch) + # chardet_version >= 3.0.2, < 6.0.0 + assert (3, 0, 2) <= (major, minor, patch) < (6, 0, 0) + elif charset_normalizer_version: + major, minor, patch = charset_normalizer_version.split(".")[:3] + major, minor, patch = int(major), int(minor), int(patch) + # charset_normalizer >= 2.0.0 < 4.0.0 + assert (2, 0, 0) <= (major, minor, patch) < (4, 0, 0) + else: + warnings.warn( + "Unable to find acceptable character detection dependency " + "(chardet or charset_normalizer).", + RequestsDependencyWarning, + ) + + +def _check_cryptography(cryptography_version): + # cryptography < 1.3.4 + try: + cryptography_version = list(map(int, cryptography_version.split("."))) + except ValueError: + return + + if cryptography_version < [1, 3, 4]: + warning = "Old version of cryptography ({}) may cause slowdown.".format( + cryptography_version + ) + warnings.warn(warning, RequestsDependencyWarning) + + +# Check imported dependencies for compatibility. +try: + check_compatibility( + urllib3.__version__, chardet_version, charset_normalizer_version + ) +except (AssertionError, ValueError): + warnings.warn( + "urllib3 ({}) or chardet ({})/charset_normalizer ({}) doesn't match a supported " + "version!".format( + urllib3.__version__, chardet_version, charset_normalizer_version + ), + RequestsDependencyWarning, + ) + +# Attempt to enable urllib3's fallback for SNI support +# if the standard library doesn't support SNI or the +# 'ssl' library isn't available. +try: + try: + import ssl + except ImportError: + ssl = None + + if not getattr(ssl, "HAS_SNI", False): + from urllib3.contrib import pyopenssl + + pyopenssl.inject_into_urllib3() + + # Check cryptography version + from cryptography import __version__ as cryptography_version + + _check_cryptography(cryptography_version) +except ImportError: + pass + +# urllib3's DependencyWarnings should be silenced. +from urllib3.exceptions import DependencyWarning + +warnings.simplefilter("ignore", DependencyWarning) + +# Set default logging handler to avoid "No handler found" warnings. +import logging +from logging import NullHandler + +from . import packages, utils +from .__version__ import ( + __author__, + __author_email__, + __build__, + __cake__, + __copyright__, + __description__, + __license__, + __title__, + __url__, + __version__, +) +from .api import delete, get, head, options, patch, post, put, request +from .exceptions import ( + ConnectionError, + ConnectTimeout, + FileModeWarning, + HTTPError, + JSONDecodeError, + ReadTimeout, + RequestException, + Timeout, + TooManyRedirects, + URLRequired, +) +from .models import PreparedRequest, Request, Response +from .sessions import Session, session +from .status_codes import codes + +logging.getLogger(__name__).addHandler(NullHandler()) + +# FileModeWarnings go off per the default. +warnings.simplefilter("default", FileModeWarning, append=True) diff --git a/requests/__version__.py b/requests/__version__.py new file mode 100644 index 0000000000000000000000000000000000000000..effdd98cf159371a36cb3ffaa8ad3e31ee3885f2 --- /dev/null +++ b/requests/__version__.py @@ -0,0 +1,14 @@ +# .-. .-. .-. . . .-. .-. .-. .-. +# |( |- |.| | | |- `-. | `-. +# ' ' `-' `-`.`-' `-' `-' ' `-' + +__title__ = "requests" +__description__ = "Python HTTP for Humans." +__url__ = "https://requests.readthedocs.io" +__version__ = "2.32.5" +__build__ = 0x023205 +__author__ = "Kenneth Reitz" +__author_email__ = "me@kennethreitz.org" +__license__ = "Apache-2.0" +__copyright__ = "Copyright Kenneth Reitz" +__cake__ = "\u2728 \U0001f370 \u2728" diff --git a/requests/_internal_utils.py b/requests/_internal_utils.py new file mode 100644 index 0000000000000000000000000000000000000000..f2cf635e2937ee9b123a1498c5c5f723a6e20084 --- /dev/null +++ b/requests/_internal_utils.py @@ -0,0 +1,50 @@ +""" +requests._internal_utils +~~~~~~~~~~~~~~ + +Provides utility functions that are consumed internally by Requests +which depend on extremely few external helpers (such as compat) +""" +import re + +from .compat import builtin_str + +_VALID_HEADER_NAME_RE_BYTE = re.compile(rb"^[^:\s][^:\r\n]*$") +_VALID_HEADER_NAME_RE_STR = re.compile(r"^[^:\s][^:\r\n]*$") +_VALID_HEADER_VALUE_RE_BYTE = re.compile(rb"^\S[^\r\n]*$|^$") +_VALID_HEADER_VALUE_RE_STR = re.compile(r"^\S[^\r\n]*$|^$") + +_HEADER_VALIDATORS_STR = (_VALID_HEADER_NAME_RE_STR, _VALID_HEADER_VALUE_RE_STR) +_HEADER_VALIDATORS_BYTE = (_VALID_HEADER_NAME_RE_BYTE, _VALID_HEADER_VALUE_RE_BYTE) +HEADER_VALIDATORS = { + bytes: _HEADER_VALIDATORS_BYTE, + str: _HEADER_VALIDATORS_STR, +} + + +def to_native_string(string, encoding="ascii"): + """Given a string object, regardless of type, returns a representation of + that string in the native string type, encoding and decoding where + necessary. This assumes ASCII unless told otherwise. + """ + if isinstance(string, builtin_str): + out = string + else: + out = string.decode(encoding) + + return out + + +def unicode_is_ascii(u_string): + """Determine if unicode string only contains ASCII characters. + + :param str u_string: unicode string to check. Must be unicode + and not Python 2 `str`. + :rtype: bool + """ + assert isinstance(u_string, str) + try: + u_string.encode("ascii") + return True + except UnicodeEncodeError: + return False diff --git a/requests/api.py b/requests/api.py new file mode 100644 index 0000000000000000000000000000000000000000..5960744552e7f8eea815429e7bdad38b0cc2741d --- /dev/null +++ b/requests/api.py @@ -0,0 +1,157 @@ +""" +requests.api +~~~~~~~~~~~~ + +This module implements the Requests API. + +:copyright: (c) 2012 by Kenneth Reitz. +:license: Apache2, see LICENSE for more details. +""" + +from . import sessions + + +def request(method, url, **kwargs): + """Constructs and sends a :class:`Request `. + + :param method: method for the new :class:`Request` object: ``GET``, ``OPTIONS``, ``HEAD``, ``POST``, ``PUT``, ``PATCH``, or ``DELETE``. + :param url: URL for the new :class:`Request` object. + :param params: (optional) Dictionary, list of tuples or bytes to send + in the query string for the :class:`Request`. + :param data: (optional) Dictionary, list of tuples, bytes, or file-like + object to send in the body of the :class:`Request`. + :param json: (optional) A JSON serializable Python object to send in the body of the :class:`Request`. + :param headers: (optional) Dictionary of HTTP Headers to send with the :class:`Request`. + :param cookies: (optional) Dict or CookieJar object to send with the :class:`Request`. + :param files: (optional) Dictionary of ``'name': file-like-objects`` (or ``{'name': file-tuple}``) for multipart encoding upload. + ``file-tuple`` can be a 2-tuple ``('filename', fileobj)``, 3-tuple ``('filename', fileobj, 'content_type')`` + or a 4-tuple ``('filename', fileobj, 'content_type', custom_headers)``, where ``'content_type'`` is a string + defining the content type of the given file and ``custom_headers`` a dict-like object containing additional headers + to add for the file. + :param auth: (optional) Auth tuple to enable Basic/Digest/Custom HTTP Auth. + :param timeout: (optional) How many seconds to wait for the server to send data + before giving up, as a float, or a :ref:`(connect timeout, read + timeout) ` tuple. + :type timeout: float or tuple + :param allow_redirects: (optional) Boolean. Enable/disable GET/OPTIONS/POST/PUT/PATCH/DELETE/HEAD redirection. Defaults to ``True``. + :type allow_redirects: bool + :param proxies: (optional) Dictionary mapping protocol to the URL of the proxy. + :param verify: (optional) Either a boolean, in which case it controls whether we verify + the server's TLS certificate, or a string, in which case it must be a path + to a CA bundle to use. Defaults to ``True``. + :param stream: (optional) if ``False``, the response content will be immediately downloaded. + :param cert: (optional) if String, path to ssl client cert file (.pem). If Tuple, ('cert', 'key') pair. + :return: :class:`Response ` object + :rtype: requests.Response + + Usage:: + + >>> import requests + >>> req = requests.request('GET', 'https://httpbin.org/get') + >>> req + + """ + + # By using the 'with' statement we are sure the session is closed, thus we + # avoid leaving sockets open which can trigger a ResourceWarning in some + # cases, and look like a memory leak in others. + with sessions.Session() as session: + return session.request(method=method, url=url, **kwargs) + + +def get(url, params=None, **kwargs): + r"""Sends a GET request. + + :param url: URL for the new :class:`Request` object. + :param params: (optional) Dictionary, list of tuples or bytes to send + in the query string for the :class:`Request`. + :param \*\*kwargs: Optional arguments that ``request`` takes. + :return: :class:`Response ` object + :rtype: requests.Response + """ + + return request("get", url, params=params, **kwargs) + + +def options(url, **kwargs): + r"""Sends an OPTIONS request. + + :param url: URL for the new :class:`Request` object. + :param \*\*kwargs: Optional arguments that ``request`` takes. + :return: :class:`Response ` object + :rtype: requests.Response + """ + + return request("options", url, **kwargs) + + +def head(url, **kwargs): + r"""Sends a HEAD request. + + :param url: URL for the new :class:`Request` object. + :param \*\*kwargs: Optional arguments that ``request`` takes. If + `allow_redirects` is not provided, it will be set to `False` (as + opposed to the default :meth:`request` behavior). + :return: :class:`Response ` object + :rtype: requests.Response + """ + + kwargs.setdefault("allow_redirects", False) + return request("head", url, **kwargs) + + +def post(url, data=None, json=None, **kwargs): + r"""Sends a POST request. + + :param url: URL for the new :class:`Request` object. + :param data: (optional) Dictionary, list of tuples, bytes, or file-like + object to send in the body of the :class:`Request`. + :param json: (optional) A JSON serializable Python object to send in the body of the :class:`Request`. + :param \*\*kwargs: Optional arguments that ``request`` takes. + :return: :class:`Response ` object + :rtype: requests.Response + """ + + return request("post", url, data=data, json=json, **kwargs) + + +def put(url, data=None, **kwargs): + r"""Sends a PUT request. + + :param url: URL for the new :class:`Request` object. + :param data: (optional) Dictionary, list of tuples, bytes, or file-like + object to send in the body of the :class:`Request`. + :param json: (optional) A JSON serializable Python object to send in the body of the :class:`Request`. + :param \*\*kwargs: Optional arguments that ``request`` takes. + :return: :class:`Response ` object + :rtype: requests.Response + """ + + return request("put", url, data=data, **kwargs) + + +def patch(url, data=None, **kwargs): + r"""Sends a PATCH request. + + :param url: URL for the new :class:`Request` object. + :param data: (optional) Dictionary, list of tuples, bytes, or file-like + object to send in the body of the :class:`Request`. + :param json: (optional) A JSON serializable Python object to send in the body of the :class:`Request`. + :param \*\*kwargs: Optional arguments that ``request`` takes. + :return: :class:`Response ` object + :rtype: requests.Response + """ + + return request("patch", url, data=data, **kwargs) + + +def delete(url, **kwargs): + r"""Sends a DELETE request. + + :param url: URL for the new :class:`Request` object. + :param \*\*kwargs: Optional arguments that ``request`` takes. + :return: :class:`Response ` object + :rtype: requests.Response + """ + + return request("delete", url, **kwargs) diff --git a/requests/auth.py b/requests/auth.py new file mode 100644 index 0000000000000000000000000000000000000000..4a7ce6dc1460e0de8aa0c38ea9123faa69bd5110 --- /dev/null +++ b/requests/auth.py @@ -0,0 +1,314 @@ +""" +requests.auth +~~~~~~~~~~~~~ + +This module contains the authentication handlers for Requests. +""" + +import hashlib +import os +import re +import threading +import time +import warnings +from base64 import b64encode + +from ._internal_utils import to_native_string +from .compat import basestring, str, urlparse +from .cookies import extract_cookies_to_jar +from .utils import parse_dict_header + +CONTENT_TYPE_FORM_URLENCODED = "application/x-www-form-urlencoded" +CONTENT_TYPE_MULTI_PART = "multipart/form-data" + + +def _basic_auth_str(username, password): + """Returns a Basic Auth string.""" + + # "I want us to put a big-ol' comment on top of it that + # says that this behaviour is dumb but we need to preserve + # it because people are relying on it." + # - Lukasa + # + # These are here solely to maintain backwards compatibility + # for things like ints. This will be removed in 3.0.0. + if not isinstance(username, basestring): + warnings.warn( + "Non-string usernames will no longer be supported in Requests " + "3.0.0. Please convert the object you've passed in ({!r}) to " + "a string or bytes object in the near future to avoid " + "problems.".format(username), + category=DeprecationWarning, + ) + username = str(username) + + if not isinstance(password, basestring): + warnings.warn( + "Non-string passwords will no longer be supported in Requests " + "3.0.0. Please convert the object you've passed in ({!r}) to " + "a string or bytes object in the near future to avoid " + "problems.".format(type(password)), + category=DeprecationWarning, + ) + password = str(password) + # -- End Removal -- + + if isinstance(username, str): + username = username.encode("latin1") + + if isinstance(password, str): + password = password.encode("latin1") + + authstr = "Basic " + to_native_string( + b64encode(b":".join((username, password))).strip() + ) + + return authstr + + +class AuthBase: + """Base class that all auth implementations derive from""" + + def __call__(self, r): + raise NotImplementedError("Auth hooks must be callable.") + + +class HTTPBasicAuth(AuthBase): + """Attaches HTTP Basic Authentication to the given Request object.""" + + def __init__(self, username, password): + self.username = username + self.password = password + + def __eq__(self, other): + return all( + [ + self.username == getattr(other, "username", None), + self.password == getattr(other, "password", None), + ] + ) + + def __ne__(self, other): + return not self == other + + def __call__(self, r): + r.headers["Authorization"] = _basic_auth_str(self.username, self.password) + return r + + +class HTTPProxyAuth(HTTPBasicAuth): + """Attaches HTTP Proxy Authentication to a given Request object.""" + + def __call__(self, r): + r.headers["Proxy-Authorization"] = _basic_auth_str(self.username, self.password) + return r + + +class HTTPDigestAuth(AuthBase): + """Attaches HTTP Digest Authentication to the given Request object.""" + + def __init__(self, username, password): + self.username = username + self.password = password + # Keep state in per-thread local storage + self._thread_local = threading.local() + + def init_per_thread_state(self): + # Ensure state is initialized just once per-thread + if not hasattr(self._thread_local, "init"): + self._thread_local.init = True + self._thread_local.last_nonce = "" + self._thread_local.nonce_count = 0 + self._thread_local.chal = {} + self._thread_local.pos = None + self._thread_local.num_401_calls = None + + def build_digest_header(self, method, url): + """ + :rtype: str + """ + + realm = self._thread_local.chal["realm"] + nonce = self._thread_local.chal["nonce"] + qop = self._thread_local.chal.get("qop") + algorithm = self._thread_local.chal.get("algorithm") + opaque = self._thread_local.chal.get("opaque") + hash_utf8 = None + + if algorithm is None: + _algorithm = "MD5" + else: + _algorithm = algorithm.upper() + # lambdas assume digest modules are imported at the top level + if _algorithm == "MD5" or _algorithm == "MD5-SESS": + + def md5_utf8(x): + if isinstance(x, str): + x = x.encode("utf-8") + return hashlib.md5(x).hexdigest() + + hash_utf8 = md5_utf8 + elif _algorithm == "SHA": + + def sha_utf8(x): + if isinstance(x, str): + x = x.encode("utf-8") + return hashlib.sha1(x).hexdigest() + + hash_utf8 = sha_utf8 + elif _algorithm == "SHA-256": + + def sha256_utf8(x): + if isinstance(x, str): + x = x.encode("utf-8") + return hashlib.sha256(x).hexdigest() + + hash_utf8 = sha256_utf8 + elif _algorithm == "SHA-512": + + def sha512_utf8(x): + if isinstance(x, str): + x = x.encode("utf-8") + return hashlib.sha512(x).hexdigest() + + hash_utf8 = sha512_utf8 + + KD = lambda s, d: hash_utf8(f"{s}:{d}") # noqa:E731 + + if hash_utf8 is None: + return None + + # XXX not implemented yet + entdig = None + p_parsed = urlparse(url) + #: path is request-uri defined in RFC 2616 which should not be empty + path = p_parsed.path or "/" + if p_parsed.query: + path += f"?{p_parsed.query}" + + A1 = f"{self.username}:{realm}:{self.password}" + A2 = f"{method}:{path}" + + HA1 = hash_utf8(A1) + HA2 = hash_utf8(A2) + + if nonce == self._thread_local.last_nonce: + self._thread_local.nonce_count += 1 + else: + self._thread_local.nonce_count = 1 + ncvalue = f"{self._thread_local.nonce_count:08x}" + s = str(self._thread_local.nonce_count).encode("utf-8") + s += nonce.encode("utf-8") + s += time.ctime().encode("utf-8") + s += os.urandom(8) + + cnonce = hashlib.sha1(s).hexdigest()[:16] + if _algorithm == "MD5-SESS": + HA1 = hash_utf8(f"{HA1}:{nonce}:{cnonce}") + + if not qop: + respdig = KD(HA1, f"{nonce}:{HA2}") + elif qop == "auth" or "auth" in qop.split(","): + noncebit = f"{nonce}:{ncvalue}:{cnonce}:auth:{HA2}" + respdig = KD(HA1, noncebit) + else: + # XXX handle auth-int. + return None + + self._thread_local.last_nonce = nonce + + # XXX should the partial digests be encoded too? + base = ( + f'username="{self.username}", realm="{realm}", nonce="{nonce}", ' + f'uri="{path}", response="{respdig}"' + ) + if opaque: + base += f', opaque="{opaque}"' + if algorithm: + base += f', algorithm="{algorithm}"' + if entdig: + base += f', digest="{entdig}"' + if qop: + base += f', qop="auth", nc={ncvalue}, cnonce="{cnonce}"' + + return f"Digest {base}" + + def handle_redirect(self, r, **kwargs): + """Reset num_401_calls counter on redirects.""" + if r.is_redirect: + self._thread_local.num_401_calls = 1 + + def handle_401(self, r, **kwargs): + """ + Takes the given response and tries digest-auth, if needed. + + :rtype: requests.Response + """ + + # If response is not 4xx, do not auth + # See https://github.com/psf/requests/issues/3772 + if not 400 <= r.status_code < 500: + self._thread_local.num_401_calls = 1 + return r + + if self._thread_local.pos is not None: + # Rewind the file position indicator of the body to where + # it was to resend the request. + r.request.body.seek(self._thread_local.pos) + s_auth = r.headers.get("www-authenticate", "") + + if "digest" in s_auth.lower() and self._thread_local.num_401_calls < 2: + self._thread_local.num_401_calls += 1 + pat = re.compile(r"digest ", flags=re.IGNORECASE) + self._thread_local.chal = parse_dict_header(pat.sub("", s_auth, count=1)) + + # Consume content and release the original connection + # to allow our new request to reuse the same one. + r.content + r.close() + prep = r.request.copy() + extract_cookies_to_jar(prep._cookies, r.request, r.raw) + prep.prepare_cookies(prep._cookies) + + prep.headers["Authorization"] = self.build_digest_header( + prep.method, prep.url + ) + _r = r.connection.send(prep, **kwargs) + _r.history.append(r) + _r.request = prep + + return _r + + self._thread_local.num_401_calls = 1 + return r + + def __call__(self, r): + # Initialize per-thread state, if needed + self.init_per_thread_state() + # If we have a saved nonce, skip the 401 + if self._thread_local.last_nonce: + r.headers["Authorization"] = self.build_digest_header(r.method, r.url) + try: + self._thread_local.pos = r.body.tell() + except AttributeError: + # In the case of HTTPDigestAuth being reused and the body of + # the previous request was a file-like object, pos has the + # file position of the previous body. Ensure it's set to + # None. + self._thread_local.pos = None + r.register_hook("response", self.handle_401) + r.register_hook("response", self.handle_redirect) + self._thread_local.num_401_calls = 1 + + return r + + def __eq__(self, other): + return all( + [ + self.username == getattr(other, "username", None), + self.password == getattr(other, "password", None), + ] + ) + + def __ne__(self, other): + return not self == other diff --git a/requests/certs.py b/requests/certs.py new file mode 100644 index 0000000000000000000000000000000000000000..be422c3e91e43bacf60ff3302688df0b28742333 --- /dev/null +++ b/requests/certs.py @@ -0,0 +1,17 @@ +#!/usr/bin/env python + +""" +requests.certs +~~~~~~~~~~~~~~ + +This module returns the preferred default CA certificate bundle. There is +only one — the one from the certifi package. + +If you are packaging Requests, e.g., for a Linux distribution or a managed +environment, you can change the definition of where() to return a separately +packaged CA bundle. +""" +from certifi import where + +if __name__ == "__main__": + print(where()) diff --git a/requests/compat.py b/requests/compat.py new file mode 100644 index 0000000000000000000000000000000000000000..7f9d754350c9fe28db41e328ea880b9e4b20cc8b --- /dev/null +++ b/requests/compat.py @@ -0,0 +1,106 @@ +""" +requests.compat +~~~~~~~~~~~~~~~ + +This module previously handled import compatibility issues +between Python 2 and Python 3. It remains for backwards +compatibility until the next major version. +""" + +import importlib +import sys + +# ------- +# urllib3 +# ------- +from urllib3 import __version__ as urllib3_version + +# Detect which major version of urllib3 is being used. +try: + is_urllib3_1 = int(urllib3_version.split(".")[0]) == 1 +except (TypeError, AttributeError): + # If we can't discern a version, prefer old functionality. + is_urllib3_1 = True + +# ------------------- +# Character Detection +# ------------------- + + +def _resolve_char_detection(): + """Find supported character detection libraries.""" + chardet = None + for lib in ("chardet", "charset_normalizer"): + if chardet is None: + try: + chardet = importlib.import_module(lib) + except ImportError: + pass + return chardet + + +chardet = _resolve_char_detection() + +# ------- +# Pythons +# ------- + +# Syntax sugar. +_ver = sys.version_info + +#: Python 2.x? +is_py2 = _ver[0] == 2 + +#: Python 3.x? +is_py3 = _ver[0] == 3 + +# json/simplejson module import resolution +has_simplejson = False +try: + import simplejson as json + + has_simplejson = True +except ImportError: + import json + +if has_simplejson: + from simplejson import JSONDecodeError +else: + from json import JSONDecodeError + +# Keep OrderedDict for backwards compatibility. +from collections import OrderedDict +from collections.abc import Callable, Mapping, MutableMapping +from http import cookiejar as cookielib +from http.cookies import Morsel +from io import StringIO + +# -------------- +# Legacy Imports +# -------------- +from urllib.parse import ( + quote, + quote_plus, + unquote, + unquote_plus, + urldefrag, + urlencode, + urljoin, + urlparse, + urlsplit, + urlunparse, +) +from urllib.request import ( + getproxies, + getproxies_environment, + parse_http_list, + proxy_bypass, + proxy_bypass_environment, +) + +builtin_str = str +str = str +bytes = bytes +basestring = (str, bytes) +numeric_types = (int, float) +integer_types = (int,) diff --git a/requests/cookies.py b/requests/cookies.py new file mode 100644 index 0000000000000000000000000000000000000000..f69d0cda9e1c893401015a09f2db2de5a5960fd2 --- /dev/null +++ b/requests/cookies.py @@ -0,0 +1,561 @@ +""" +requests.cookies +~~~~~~~~~~~~~~~~ + +Compatibility code to be able to use `http.cookiejar.CookieJar` with requests. + +requests.utils imports from here, so be careful with imports. +""" + +import calendar +import copy +import time + +from ._internal_utils import to_native_string +from .compat import Morsel, MutableMapping, cookielib, urlparse, urlunparse + +try: + import threading +except ImportError: + import dummy_threading as threading + + +class MockRequest: + """Wraps a `requests.Request` to mimic a `urllib2.Request`. + + The code in `http.cookiejar.CookieJar` expects this interface in order to correctly + manage cookie policies, i.e., determine whether a cookie can be set, given the + domains of the request and the cookie. + + The original request object is read-only. The client is responsible for collecting + the new headers via `get_new_headers()` and interpreting them appropriately. You + probably want `get_cookie_header`, defined below. + """ + + def __init__(self, request): + self._r = request + self._new_headers = {} + self.type = urlparse(self._r.url).scheme + + def get_type(self): + return self.type + + def get_host(self): + return urlparse(self._r.url).netloc + + def get_origin_req_host(self): + return self.get_host() + + def get_full_url(self): + # Only return the response's URL if the user hadn't set the Host + # header + if not self._r.headers.get("Host"): + return self._r.url + # If they did set it, retrieve it and reconstruct the expected domain + host = to_native_string(self._r.headers["Host"], encoding="utf-8") + parsed = urlparse(self._r.url) + # Reconstruct the URL as we expect it + return urlunparse( + [ + parsed.scheme, + host, + parsed.path, + parsed.params, + parsed.query, + parsed.fragment, + ] + ) + + def is_unverifiable(self): + return True + + def has_header(self, name): + return name in self._r.headers or name in self._new_headers + + def get_header(self, name, default=None): + return self._r.headers.get(name, self._new_headers.get(name, default)) + + def add_header(self, key, val): + """cookiejar has no legitimate use for this method; add it back if you find one.""" + raise NotImplementedError( + "Cookie headers should be added with add_unredirected_header()" + ) + + def add_unredirected_header(self, name, value): + self._new_headers[name] = value + + def get_new_headers(self): + return self._new_headers + + @property + def unverifiable(self): + return self.is_unverifiable() + + @property + def origin_req_host(self): + return self.get_origin_req_host() + + @property + def host(self): + return self.get_host() + + +class MockResponse: + """Wraps a `httplib.HTTPMessage` to mimic a `urllib.addinfourl`. + + ...what? Basically, expose the parsed HTTP headers from the server response + the way `http.cookiejar` expects to see them. + """ + + def __init__(self, headers): + """Make a MockResponse for `cookiejar` to read. + + :param headers: a httplib.HTTPMessage or analogous carrying the headers + """ + self._headers = headers + + def info(self): + return self._headers + + def getheaders(self, name): + self._headers.getheaders(name) + + +def extract_cookies_to_jar(jar, request, response): + """Extract the cookies from the response into a CookieJar. + + :param jar: http.cookiejar.CookieJar (not necessarily a RequestsCookieJar) + :param request: our own requests.Request object + :param response: urllib3.HTTPResponse object + """ + if not (hasattr(response, "_original_response") and response._original_response): + return + # the _original_response field is the wrapped httplib.HTTPResponse object, + req = MockRequest(request) + # pull out the HTTPMessage with the headers and put it in the mock: + res = MockResponse(response._original_response.msg) + jar.extract_cookies(res, req) + + +def get_cookie_header(jar, request): + """ + Produce an appropriate Cookie header string to be sent with `request`, or None. + + :rtype: str + """ + r = MockRequest(request) + jar.add_cookie_header(r) + return r.get_new_headers().get("Cookie") + + +def remove_cookie_by_name(cookiejar, name, domain=None, path=None): + """Unsets a cookie by name, by default over all domains and paths. + + Wraps CookieJar.clear(), is O(n). + """ + clearables = [] + for cookie in cookiejar: + if cookie.name != name: + continue + if domain is not None and domain != cookie.domain: + continue + if path is not None and path != cookie.path: + continue + clearables.append((cookie.domain, cookie.path, cookie.name)) + + for domain, path, name in clearables: + cookiejar.clear(domain, path, name) + + +class CookieConflictError(RuntimeError): + """There are two cookies that meet the criteria specified in the cookie jar. + Use .get and .set and include domain and path args in order to be more specific. + """ + + +class RequestsCookieJar(cookielib.CookieJar, MutableMapping): + """Compatibility class; is a http.cookiejar.CookieJar, but exposes a dict + interface. + + This is the CookieJar we create by default for requests and sessions that + don't specify one, since some clients may expect response.cookies and + session.cookies to support dict operations. + + Requests does not use the dict interface internally; it's just for + compatibility with external client code. All requests code should work + out of the box with externally provided instances of ``CookieJar``, e.g. + ``LWPCookieJar`` and ``FileCookieJar``. + + Unlike a regular CookieJar, this class is pickleable. + + .. warning:: dictionary operations that are normally O(1) may be O(n). + """ + + def get(self, name, default=None, domain=None, path=None): + """Dict-like get() that also supports optional domain and path args in + order to resolve naming collisions from using one cookie jar over + multiple domains. + + .. warning:: operation is O(n), not O(1). + """ + try: + return self._find_no_duplicates(name, domain, path) + except KeyError: + return default + + def set(self, name, value, **kwargs): + """Dict-like set() that also supports optional domain and path args in + order to resolve naming collisions from using one cookie jar over + multiple domains. + """ + # support client code that unsets cookies by assignment of a None value: + if value is None: + remove_cookie_by_name( + self, name, domain=kwargs.get("domain"), path=kwargs.get("path") + ) + return + + if isinstance(value, Morsel): + c = morsel_to_cookie(value) + else: + c = create_cookie(name, value, **kwargs) + self.set_cookie(c) + return c + + def iterkeys(self): + """Dict-like iterkeys() that returns an iterator of names of cookies + from the jar. + + .. seealso:: itervalues() and iteritems(). + """ + for cookie in iter(self): + yield cookie.name + + def keys(self): + """Dict-like keys() that returns a list of names of cookies from the + jar. + + .. seealso:: values() and items(). + """ + return list(self.iterkeys()) + + def itervalues(self): + """Dict-like itervalues() that returns an iterator of values of cookies + from the jar. + + .. seealso:: iterkeys() and iteritems(). + """ + for cookie in iter(self): + yield cookie.value + + def values(self): + """Dict-like values() that returns a list of values of cookies from the + jar. + + .. seealso:: keys() and items(). + """ + return list(self.itervalues()) + + def iteritems(self): + """Dict-like iteritems() that returns an iterator of name-value tuples + from the jar. + + .. seealso:: iterkeys() and itervalues(). + """ + for cookie in iter(self): + yield cookie.name, cookie.value + + def items(self): + """Dict-like items() that returns a list of name-value tuples from the + jar. Allows client-code to call ``dict(RequestsCookieJar)`` and get a + vanilla python dict of key value pairs. + + .. seealso:: keys() and values(). + """ + return list(self.iteritems()) + + def list_domains(self): + """Utility method to list all the domains in the jar.""" + domains = [] + for cookie in iter(self): + if cookie.domain not in domains: + domains.append(cookie.domain) + return domains + + def list_paths(self): + """Utility method to list all the paths in the jar.""" + paths = [] + for cookie in iter(self): + if cookie.path not in paths: + paths.append(cookie.path) + return paths + + def multiple_domains(self): + """Returns True if there are multiple domains in the jar. + Returns False otherwise. + + :rtype: bool + """ + domains = [] + for cookie in iter(self): + if cookie.domain is not None and cookie.domain in domains: + return True + domains.append(cookie.domain) + return False # there is only one domain in jar + + def get_dict(self, domain=None, path=None): + """Takes as an argument an optional domain and path and returns a plain + old Python dict of name-value pairs of cookies that meet the + requirements. + + :rtype: dict + """ + dictionary = {} + for cookie in iter(self): + if (domain is None or cookie.domain == domain) and ( + path is None or cookie.path == path + ): + dictionary[cookie.name] = cookie.value + return dictionary + + def __contains__(self, name): + try: + return super().__contains__(name) + except CookieConflictError: + return True + + def __getitem__(self, name): + """Dict-like __getitem__() for compatibility with client code. Throws + exception if there are more than one cookie with name. In that case, + use the more explicit get() method instead. + + .. warning:: operation is O(n), not O(1). + """ + return self._find_no_duplicates(name) + + def __setitem__(self, name, value): + """Dict-like __setitem__ for compatibility with client code. Throws + exception if there is already a cookie of that name in the jar. In that + case, use the more explicit set() method instead. + """ + self.set(name, value) + + def __delitem__(self, name): + """Deletes a cookie given a name. Wraps ``http.cookiejar.CookieJar``'s + ``remove_cookie_by_name()``. + """ + remove_cookie_by_name(self, name) + + def set_cookie(self, cookie, *args, **kwargs): + if ( + hasattr(cookie.value, "startswith") + and cookie.value.startswith('"') + and cookie.value.endswith('"') + ): + cookie.value = cookie.value.replace('\\"', "") + return super().set_cookie(cookie, *args, **kwargs) + + def update(self, other): + """Updates this jar with cookies from another CookieJar or dict-like""" + if isinstance(other, cookielib.CookieJar): + for cookie in other: + self.set_cookie(copy.copy(cookie)) + else: + super().update(other) + + def _find(self, name, domain=None, path=None): + """Requests uses this method internally to get cookie values. + + If there are conflicting cookies, _find arbitrarily chooses one. + See _find_no_duplicates if you want an exception thrown if there are + conflicting cookies. + + :param name: a string containing name of cookie + :param domain: (optional) string containing domain of cookie + :param path: (optional) string containing path of cookie + :return: cookie.value + """ + for cookie in iter(self): + if cookie.name == name: + if domain is None or cookie.domain == domain: + if path is None or cookie.path == path: + return cookie.value + + raise KeyError(f"name={name!r}, domain={domain!r}, path={path!r}") + + def _find_no_duplicates(self, name, domain=None, path=None): + """Both ``__get_item__`` and ``get`` call this function: it's never + used elsewhere in Requests. + + :param name: a string containing name of cookie + :param domain: (optional) string containing domain of cookie + :param path: (optional) string containing path of cookie + :raises KeyError: if cookie is not found + :raises CookieConflictError: if there are multiple cookies + that match name and optionally domain and path + :return: cookie.value + """ + toReturn = None + for cookie in iter(self): + if cookie.name == name: + if domain is None or cookie.domain == domain: + if path is None or cookie.path == path: + if toReturn is not None: + # if there are multiple cookies that meet passed in criteria + raise CookieConflictError( + f"There are multiple cookies with name, {name!r}" + ) + # we will eventually return this as long as no cookie conflict + toReturn = cookie.value + + if toReturn: + return toReturn + raise KeyError(f"name={name!r}, domain={domain!r}, path={path!r}") + + def __getstate__(self): + """Unlike a normal CookieJar, this class is pickleable.""" + state = self.__dict__.copy() + # remove the unpickleable RLock object + state.pop("_cookies_lock") + return state + + def __setstate__(self, state): + """Unlike a normal CookieJar, this class is pickleable.""" + self.__dict__.update(state) + if "_cookies_lock" not in self.__dict__: + self._cookies_lock = threading.RLock() + + def copy(self): + """Return a copy of this RequestsCookieJar.""" + new_cj = RequestsCookieJar() + new_cj.set_policy(self.get_policy()) + new_cj.update(self) + return new_cj + + def get_policy(self): + """Return the CookiePolicy instance used.""" + return self._policy + + +def _copy_cookie_jar(jar): + if jar is None: + return None + + if hasattr(jar, "copy"): + # We're dealing with an instance of RequestsCookieJar + return jar.copy() + # We're dealing with a generic CookieJar instance + new_jar = copy.copy(jar) + new_jar.clear() + for cookie in jar: + new_jar.set_cookie(copy.copy(cookie)) + return new_jar + + +def create_cookie(name, value, **kwargs): + """Make a cookie from underspecified parameters. + + By default, the pair of `name` and `value` will be set for the domain '' + and sent on every request (this is sometimes called a "supercookie"). + """ + result = { + "version": 0, + "name": name, + "value": value, + "port": None, + "domain": "", + "path": "/", + "secure": False, + "expires": None, + "discard": True, + "comment": None, + "comment_url": None, + "rest": {"HttpOnly": None}, + "rfc2109": False, + } + + badargs = set(kwargs) - set(result) + if badargs: + raise TypeError( + f"create_cookie() got unexpected keyword arguments: {list(badargs)}" + ) + + result.update(kwargs) + result["port_specified"] = bool(result["port"]) + result["domain_specified"] = bool(result["domain"]) + result["domain_initial_dot"] = result["domain"].startswith(".") + result["path_specified"] = bool(result["path"]) + + return cookielib.Cookie(**result) + + +def morsel_to_cookie(morsel): + """Convert a Morsel object into a Cookie containing the one k/v pair.""" + + expires = None + if morsel["max-age"]: + try: + expires = int(time.time() + int(morsel["max-age"])) + except ValueError: + raise TypeError(f"max-age: {morsel['max-age']} must be integer") + elif morsel["expires"]: + time_template = "%a, %d-%b-%Y %H:%M:%S GMT" + expires = calendar.timegm(time.strptime(morsel["expires"], time_template)) + return create_cookie( + comment=morsel["comment"], + comment_url=bool(morsel["comment"]), + discard=False, + domain=morsel["domain"], + expires=expires, + name=morsel.key, + path=morsel["path"], + port=None, + rest={"HttpOnly": morsel["httponly"]}, + rfc2109=False, + secure=bool(morsel["secure"]), + value=morsel.value, + version=morsel["version"] or 0, + ) + + +def cookiejar_from_dict(cookie_dict, cookiejar=None, overwrite=True): + """Returns a CookieJar from a key/value dictionary. + + :param cookie_dict: Dict of key/values to insert into CookieJar. + :param cookiejar: (optional) A cookiejar to add the cookies to. + :param overwrite: (optional) If False, will not replace cookies + already in the jar with new ones. + :rtype: CookieJar + """ + if cookiejar is None: + cookiejar = RequestsCookieJar() + + if cookie_dict is not None: + names_from_jar = [cookie.name for cookie in cookiejar] + for name in cookie_dict: + if overwrite or (name not in names_from_jar): + cookiejar.set_cookie(create_cookie(name, cookie_dict[name])) + + return cookiejar + + +def merge_cookies(cookiejar, cookies): + """Add cookies to cookiejar and returns a merged CookieJar. + + :param cookiejar: CookieJar object to add the cookies to. + :param cookies: Dictionary or CookieJar object to be added. + :rtype: CookieJar + """ + if not isinstance(cookiejar, cookielib.CookieJar): + raise ValueError("You can only merge into CookieJar") + + if isinstance(cookies, dict): + cookiejar = cookiejar_from_dict(cookies, cookiejar=cookiejar, overwrite=False) + elif isinstance(cookies, cookielib.CookieJar): + try: + cookiejar.update(cookies) + except AttributeError: + for cookie_in_jar in cookies: + cookiejar.set_cookie(cookie_in_jar) + + return cookiejar diff --git a/requests/exceptions.py b/requests/exceptions.py new file mode 100644 index 0000000000000000000000000000000000000000..83986b489849131efeb7f286b328961205256fd8 --- /dev/null +++ b/requests/exceptions.py @@ -0,0 +1,151 @@ +""" +requests.exceptions +~~~~~~~~~~~~~~~~~~~ + +This module contains the set of Requests' exceptions. +""" +from urllib3.exceptions import HTTPError as BaseHTTPError + +from .compat import JSONDecodeError as CompatJSONDecodeError + + +class RequestException(IOError): + """There was an ambiguous exception that occurred while handling your + request. + """ + + def __init__(self, *args, **kwargs): + """Initialize RequestException with `request` and `response` objects.""" + response = kwargs.pop("response", None) + self.response = response + self.request = kwargs.pop("request", None) + if response is not None and not self.request and hasattr(response, "request"): + self.request = self.response.request + super().__init__(*args, **kwargs) + + +class InvalidJSONError(RequestException): + """A JSON error occurred.""" + + +class JSONDecodeError(InvalidJSONError, CompatJSONDecodeError): + """Couldn't decode the text into json""" + + def __init__(self, *args, **kwargs): + """ + Construct the JSONDecodeError instance first with all + args. Then use it's args to construct the IOError so that + the json specific args aren't used as IOError specific args + and the error message from JSONDecodeError is preserved. + """ + CompatJSONDecodeError.__init__(self, *args) + InvalidJSONError.__init__(self, *self.args, **kwargs) + + def __reduce__(self): + """ + The __reduce__ method called when pickling the object must + be the one from the JSONDecodeError (be it json/simplejson) + as it expects all the arguments for instantiation, not just + one like the IOError, and the MRO would by default call the + __reduce__ method from the IOError due to the inheritance order. + """ + return CompatJSONDecodeError.__reduce__(self) + + +class HTTPError(RequestException): + """An HTTP error occurred.""" + + +class ConnectionError(RequestException): + """A Connection error occurred.""" + + +class ProxyError(ConnectionError): + """A proxy error occurred.""" + + +class SSLError(ConnectionError): + """An SSL error occurred.""" + + +class Timeout(RequestException): + """The request timed out. + + Catching this error will catch both + :exc:`~requests.exceptions.ConnectTimeout` and + :exc:`~requests.exceptions.ReadTimeout` errors. + """ + + +class ConnectTimeout(ConnectionError, Timeout): + """The request timed out while trying to connect to the remote server. + + Requests that produced this error are safe to retry. + """ + + +class ReadTimeout(Timeout): + """The server did not send any data in the allotted amount of time.""" + + +class URLRequired(RequestException): + """A valid URL is required to make a request.""" + + +class TooManyRedirects(RequestException): + """Too many redirects.""" + + +class MissingSchema(RequestException, ValueError): + """The URL scheme (e.g. http or https) is missing.""" + + +class InvalidSchema(RequestException, ValueError): + """The URL scheme provided is either invalid or unsupported.""" + + +class InvalidURL(RequestException, ValueError): + """The URL provided was somehow invalid.""" + + +class InvalidHeader(RequestException, ValueError): + """The header value provided was somehow invalid.""" + + +class InvalidProxyURL(InvalidURL): + """The proxy URL provided is invalid.""" + + +class ChunkedEncodingError(RequestException): + """The server declared chunked encoding but sent an invalid chunk.""" + + +class ContentDecodingError(RequestException, BaseHTTPError): + """Failed to decode response content.""" + + +class StreamConsumedError(RequestException, TypeError): + """The content for this response was already consumed.""" + + +class RetryError(RequestException): + """Custom retries logic failed""" + + +class UnrewindableBodyError(RequestException): + """Requests encountered an error when trying to rewind a body.""" + + +# Warnings + + +class RequestsWarning(Warning): + """Base warning for Requests.""" + + +class FileModeWarning(RequestsWarning, DeprecationWarning): + """A file was opened in text mode, but Requests determined its binary length.""" + + +class RequestsDependencyWarning(RequestsWarning): + """An imported dependency doesn't match the expected version range.""" diff --git a/requests/hooks.py b/requests/hooks.py new file mode 100644 index 0000000000000000000000000000000000000000..d181ba2ec2e55d274897315887b78fbdca757da8 --- /dev/null +++ b/requests/hooks.py @@ -0,0 +1,33 @@ +""" +requests.hooks +~~~~~~~~~~~~~~ + +This module provides the capabilities for the Requests hooks system. + +Available hooks: + +``response``: + The response generated from a Request. +""" +HOOKS = ["response"] + + +def default_hooks(): + return {event: [] for event in HOOKS} + + +# TODO: response is the only one + + +def dispatch_hook(key, hooks, hook_data, **kwargs): + """Dispatches a hook dictionary on a given piece of data.""" + hooks = hooks or {} + hooks = hooks.get(key) + if hooks: + if hasattr(hooks, "__call__"): + hooks = [hooks] + for hook in hooks: + _hook_data = hook(hook_data, **kwargs) + if _hook_data is not None: + hook_data = _hook_data + return hook_data diff --git a/requests/models.py b/requests/models.py new file mode 100644 index 0000000000000000000000000000000000000000..c4b25fa0790da44683dab185c89ac08b69fb7419 --- /dev/null +++ b/requests/models.py @@ -0,0 +1,1039 @@ +""" +requests.models +~~~~~~~~~~~~~~~ + +This module contains the primary objects that power Requests. +""" + +import datetime + +# Import encoding now, to avoid implicit import later. +# Implicit import within threads may cause LookupError when standard library is in a ZIP, +# such as in Embedded Python. See https://github.com/psf/requests/issues/3578. +import encodings.idna # noqa: F401 +from io import UnsupportedOperation + +from urllib3.exceptions import ( + DecodeError, + LocationParseError, + ProtocolError, + ReadTimeoutError, + SSLError, +) +from urllib3.fields import RequestField +from urllib3.filepost import encode_multipart_formdata +from urllib3.util import parse_url + +from ._internal_utils import to_native_string, unicode_is_ascii +from .auth import HTTPBasicAuth +from .compat import ( + Callable, + JSONDecodeError, + Mapping, + basestring, + builtin_str, + chardet, + cookielib, +) +from .compat import json as complexjson +from .compat import urlencode, urlsplit, urlunparse +from .cookies import _copy_cookie_jar, cookiejar_from_dict, get_cookie_header +from .exceptions import ( + ChunkedEncodingError, + ConnectionError, + ContentDecodingError, + HTTPError, + InvalidJSONError, + InvalidURL, +) +from .exceptions import JSONDecodeError as RequestsJSONDecodeError +from .exceptions import MissingSchema +from .exceptions import SSLError as RequestsSSLError +from .exceptions import StreamConsumedError +from .hooks import default_hooks +from .status_codes import codes +from .structures import CaseInsensitiveDict +from .utils import ( + check_header_validity, + get_auth_from_url, + guess_filename, + guess_json_utf, + iter_slices, + parse_header_links, + requote_uri, + stream_decode_response_unicode, + super_len, + to_key_val_list, +) + +#: The set of HTTP status codes that indicate an automatically +#: processable redirect. +REDIRECT_STATI = ( + codes.moved, # 301 + codes.found, # 302 + codes.other, # 303 + codes.temporary_redirect, # 307 + codes.permanent_redirect, # 308 +) + +DEFAULT_REDIRECT_LIMIT = 30 +CONTENT_CHUNK_SIZE = 10 * 1024 +ITER_CHUNK_SIZE = 512 + + +class RequestEncodingMixin: + @property + def path_url(self): + """Build the path URL to use.""" + + url = [] + + p = urlsplit(self.url) + + path = p.path + if not path: + path = "/" + + url.append(path) + + query = p.query + if query: + url.append("?") + url.append(query) + + return "".join(url) + + @staticmethod + def _encode_params(data): + """Encode parameters in a piece of data. + + Will successfully encode parameters when passed as a dict or a list of + 2-tuples. Order is retained if data is a list of 2-tuples but arbitrary + if parameters are supplied as a dict. + """ + + if isinstance(data, (str, bytes)): + return data + elif hasattr(data, "read"): + return data + elif hasattr(data, "__iter__"): + result = [] + for k, vs in to_key_val_list(data): + if isinstance(vs, basestring) or not hasattr(vs, "__iter__"): + vs = [vs] + for v in vs: + if v is not None: + result.append( + ( + k.encode("utf-8") if isinstance(k, str) else k, + v.encode("utf-8") if isinstance(v, str) else v, + ) + ) + return urlencode(result, doseq=True) + else: + return data + + @staticmethod + def _encode_files(files, data): + """Build the body for a multipart/form-data request. + + Will successfully encode files when passed as a dict or a list of + tuples. Order is retained if data is a list of tuples but arbitrary + if parameters are supplied as a dict. + The tuples may be 2-tuples (filename, fileobj), 3-tuples (filename, fileobj, contentype) + or 4-tuples (filename, fileobj, contentype, custom_headers). + """ + if not files: + raise ValueError("Files must be provided.") + elif isinstance(data, basestring): + raise ValueError("Data must not be a string.") + + new_fields = [] + fields = to_key_val_list(data or {}) + files = to_key_val_list(files or {}) + + for field, val in fields: + if isinstance(val, basestring) or not hasattr(val, "__iter__"): + val = [val] + for v in val: + if v is not None: + # Don't call str() on bytestrings: in Py3 it all goes wrong. + if not isinstance(v, bytes): + v = str(v) + + new_fields.append( + ( + field.decode("utf-8") + if isinstance(field, bytes) + else field, + v.encode("utf-8") if isinstance(v, str) else v, + ) + ) + + for k, v in files: + # support for explicit filename + ft = None + fh = None + if isinstance(v, (tuple, list)): + if len(v) == 2: + fn, fp = v + elif len(v) == 3: + fn, fp, ft = v + else: + fn, fp, ft, fh = v + else: + fn = guess_filename(v) or k + fp = v + + if isinstance(fp, (str, bytes, bytearray)): + fdata = fp + elif hasattr(fp, "read"): + fdata = fp.read() + elif fp is None: + continue + else: + fdata = fp + + rf = RequestField(name=k, data=fdata, filename=fn, headers=fh) + rf.make_multipart(content_type=ft) + new_fields.append(rf) + + body, content_type = encode_multipart_formdata(new_fields) + + return body, content_type + + +class RequestHooksMixin: + def register_hook(self, event, hook): + """Properly register a hook.""" + + if event not in self.hooks: + raise ValueError(f'Unsupported event specified, with event name "{event}"') + + if isinstance(hook, Callable): + self.hooks[event].append(hook) + elif hasattr(hook, "__iter__"): + self.hooks[event].extend(h for h in hook if isinstance(h, Callable)) + + def deregister_hook(self, event, hook): + """Deregister a previously registered hook. + Returns True if the hook existed, False if not. + """ + + try: + self.hooks[event].remove(hook) + return True + except ValueError: + return False + + +class Request(RequestHooksMixin): + """A user-created :class:`Request ` object. + + Used to prepare a :class:`PreparedRequest `, which is sent to the server. + + :param method: HTTP method to use. + :param url: URL to send. + :param headers: dictionary of headers to send. + :param files: dictionary of {filename: fileobject} files to multipart upload. + :param data: the body to attach to the request. If a dictionary or + list of tuples ``[(key, value)]`` is provided, form-encoding will + take place. + :param json: json for the body to attach to the request (if files or data is not specified). + :param params: URL parameters to append to the URL. If a dictionary or + list of tuples ``[(key, value)]`` is provided, form-encoding will + take place. + :param auth: Auth handler or (user, pass) tuple. + :param cookies: dictionary or CookieJar of cookies to attach to this request. + :param hooks: dictionary of callback hooks, for internal usage. + + Usage:: + + >>> import requests + >>> req = requests.Request('GET', 'https://httpbin.org/get') + >>> req.prepare() + + """ + + def __init__( + self, + method=None, + url=None, + headers=None, + files=None, + data=None, + params=None, + auth=None, + cookies=None, + hooks=None, + json=None, + ): + # Default empty dicts for dict params. + data = [] if data is None else data + files = [] if files is None else files + headers = {} if headers is None else headers + params = {} if params is None else params + hooks = {} if hooks is None else hooks + + self.hooks = default_hooks() + for k, v in list(hooks.items()): + self.register_hook(event=k, hook=v) + + self.method = method + self.url = url + self.headers = headers + self.files = files + self.data = data + self.json = json + self.params = params + self.auth = auth + self.cookies = cookies + + def __repr__(self): + return f"" + + def prepare(self): + """Constructs a :class:`PreparedRequest ` for transmission and returns it.""" + p = PreparedRequest() + p.prepare( + method=self.method, + url=self.url, + headers=self.headers, + files=self.files, + data=self.data, + json=self.json, + params=self.params, + auth=self.auth, + cookies=self.cookies, + hooks=self.hooks, + ) + return p + + +class PreparedRequest(RequestEncodingMixin, RequestHooksMixin): + """The fully mutable :class:`PreparedRequest ` object, + containing the exact bytes that will be sent to the server. + + Instances are generated from a :class:`Request ` object, and + should not be instantiated manually; doing so may produce undesirable + effects. + + Usage:: + + >>> import requests + >>> req = requests.Request('GET', 'https://httpbin.org/get') + >>> r = req.prepare() + >>> r + + + >>> s = requests.Session() + >>> s.send(r) + + """ + + def __init__(self): + #: HTTP verb to send to the server. + self.method = None + #: HTTP URL to send the request to. + self.url = None + #: dictionary of HTTP headers. + self.headers = None + # The `CookieJar` used to create the Cookie header will be stored here + # after prepare_cookies is called + self._cookies = None + #: request body to send to the server. + self.body = None + #: dictionary of callback hooks, for internal usage. + self.hooks = default_hooks() + #: integer denoting starting position of a readable file-like body. + self._body_position = None + + def prepare( + self, + method=None, + url=None, + headers=None, + files=None, + data=None, + params=None, + auth=None, + cookies=None, + hooks=None, + json=None, + ): + """Prepares the entire request with the given parameters.""" + + self.prepare_method(method) + self.prepare_url(url, params) + self.prepare_headers(headers) + self.prepare_cookies(cookies) + self.prepare_body(data, files, json) + self.prepare_auth(auth, url) + + # Note that prepare_auth must be last to enable authentication schemes + # such as OAuth to work on a fully prepared request. + + # This MUST go after prepare_auth. Authenticators could add a hook + self.prepare_hooks(hooks) + + def __repr__(self): + return f"" + + def copy(self): + p = PreparedRequest() + p.method = self.method + p.url = self.url + p.headers = self.headers.copy() if self.headers is not None else None + p._cookies = _copy_cookie_jar(self._cookies) + p.body = self.body + p.hooks = self.hooks + p._body_position = self._body_position + return p + + def prepare_method(self, method): + """Prepares the given HTTP method.""" + self.method = method + if self.method is not None: + self.method = to_native_string(self.method.upper()) + + @staticmethod + def _get_idna_encoded_host(host): + import idna + + try: + host = idna.encode(host, uts46=True).decode("utf-8") + except idna.IDNAError: + raise UnicodeError + return host + + def prepare_url(self, url, params): + """Prepares the given HTTP URL.""" + #: Accept objects that have string representations. + #: We're unable to blindly call unicode/str functions + #: as this will include the bytestring indicator (b'') + #: on python 3.x. + #: https://github.com/psf/requests/pull/2238 + if isinstance(url, bytes): + url = url.decode("utf8") + else: + url = str(url) + + # Remove leading whitespaces from url + url = url.lstrip() + + # Don't do any URL preparation for non-HTTP schemes like `mailto`, + # `data` etc to work around exceptions from `url_parse`, which + # handles RFC 3986 only. + if ":" in url and not url.lower().startswith("http"): + self.url = url + return + + # Support for unicode domain names and paths. + try: + scheme, auth, host, port, path, query, fragment = parse_url(url) + except LocationParseError as e: + raise InvalidURL(*e.args) + + if not scheme: + raise MissingSchema( + f"Invalid URL {url!r}: No scheme supplied. " + f"Perhaps you meant https://{url}?" + ) + + if not host: + raise InvalidURL(f"Invalid URL {url!r}: No host supplied") + + # In general, we want to try IDNA encoding the hostname if the string contains + # non-ASCII characters. This allows users to automatically get the correct IDNA + # behaviour. For strings containing only ASCII characters, we need to also verify + # it doesn't start with a wildcard (*), before allowing the unencoded hostname. + if not unicode_is_ascii(host): + try: + host = self._get_idna_encoded_host(host) + except UnicodeError: + raise InvalidURL("URL has an invalid label.") + elif host.startswith(("*", ".")): + raise InvalidURL("URL has an invalid label.") + + # Carefully reconstruct the network location + netloc = auth or "" + if netloc: + netloc += "@" + netloc += host + if port: + netloc += f":{port}" + + # Bare domains aren't valid URLs. + if not path: + path = "/" + + if isinstance(params, (str, bytes)): + params = to_native_string(params) + + enc_params = self._encode_params(params) + if enc_params: + if query: + query = f"{query}&{enc_params}" + else: + query = enc_params + + url = requote_uri(urlunparse([scheme, netloc, path, None, query, fragment])) + self.url = url + + def prepare_headers(self, headers): + """Prepares the given HTTP headers.""" + + self.headers = CaseInsensitiveDict() + if headers: + for header in headers.items(): + # Raise exception on invalid header value. + check_header_validity(header) + name, value = header + self.headers[to_native_string(name)] = value + + def prepare_body(self, data, files, json=None): + """Prepares the given HTTP body data.""" + + # Check if file, fo, generator, iterator. + # If not, run through normal process. + + # Nottin' on you. + body = None + content_type = None + + if not data and json is not None: + # urllib3 requires a bytes-like body. Python 2's json.dumps + # provides this natively, but Python 3 gives a Unicode string. + content_type = "application/json" + + try: + body = complexjson.dumps(json, allow_nan=False) + except ValueError as ve: + raise InvalidJSONError(ve, request=self) + + if not isinstance(body, bytes): + body = body.encode("utf-8") + + is_stream = all( + [ + hasattr(data, "__iter__"), + not isinstance(data, (basestring, list, tuple, Mapping)), + ] + ) + + if is_stream: + try: + length = super_len(data) + except (TypeError, AttributeError, UnsupportedOperation): + length = None + + body = data + + if getattr(body, "tell", None) is not None: + # Record the current file position before reading. + # This will allow us to rewind a file in the event + # of a redirect. + try: + self._body_position = body.tell() + except OSError: + # This differentiates from None, allowing us to catch + # a failed `tell()` later when trying to rewind the body + self._body_position = object() + + if files: + raise NotImplementedError( + "Streamed bodies and files are mutually exclusive." + ) + + if length: + self.headers["Content-Length"] = builtin_str(length) + else: + self.headers["Transfer-Encoding"] = "chunked" + else: + # Multi-part file uploads. + if files: + (body, content_type) = self._encode_files(files, data) + else: + if data: + body = self._encode_params(data) + if isinstance(data, basestring) or hasattr(data, "read"): + content_type = None + else: + content_type = "application/x-www-form-urlencoded" + + self.prepare_content_length(body) + + # Add content-type if it wasn't explicitly provided. + if content_type and ("content-type" not in self.headers): + self.headers["Content-Type"] = content_type + + self.body = body + + def prepare_content_length(self, body): + """Prepare Content-Length header based on request method and body""" + if body is not None: + length = super_len(body) + if length: + # If length exists, set it. Otherwise, we fallback + # to Transfer-Encoding: chunked. + self.headers["Content-Length"] = builtin_str(length) + elif ( + self.method not in ("GET", "HEAD") + and self.headers.get("Content-Length") is None + ): + # Set Content-Length to 0 for methods that can have a body + # but don't provide one. (i.e. not GET or HEAD) + self.headers["Content-Length"] = "0" + + def prepare_auth(self, auth, url=""): + """Prepares the given HTTP auth data.""" + + # If no Auth is explicitly provided, extract it from the URL first. + if auth is None: + url_auth = get_auth_from_url(self.url) + auth = url_auth if any(url_auth) else None + + if auth: + if isinstance(auth, tuple) and len(auth) == 2: + # special-case basic HTTP auth + auth = HTTPBasicAuth(*auth) + + # Allow auth to make its changes. + r = auth(self) + + # Update self to reflect the auth changes. + self.__dict__.update(r.__dict__) + + # Recompute Content-Length + self.prepare_content_length(self.body) + + def prepare_cookies(self, cookies): + """Prepares the given HTTP cookie data. + + This function eventually generates a ``Cookie`` header from the + given cookies using cookielib. Due to cookielib's design, the header + will not be regenerated if it already exists, meaning this function + can only be called once for the life of the + :class:`PreparedRequest ` object. Any subsequent calls + to ``prepare_cookies`` will have no actual effect, unless the "Cookie" + header is removed beforehand. + """ + if isinstance(cookies, cookielib.CookieJar): + self._cookies = cookies + else: + self._cookies = cookiejar_from_dict(cookies) + + cookie_header = get_cookie_header(self._cookies, self) + if cookie_header is not None: + self.headers["Cookie"] = cookie_header + + def prepare_hooks(self, hooks): + """Prepares the given hooks.""" + # hooks can be passed as None to the prepare method and to this + # method. To prevent iterating over None, simply use an empty list + # if hooks is False-y + hooks = hooks or [] + for event in hooks: + self.register_hook(event, hooks[event]) + + +class Response: + """The :class:`Response ` object, which contains a + server's response to an HTTP request. + """ + + __attrs__ = [ + "_content", + "status_code", + "headers", + "url", + "history", + "encoding", + "reason", + "cookies", + "elapsed", + "request", + ] + + def __init__(self): + self._content = False + self._content_consumed = False + self._next = None + + #: Integer Code of responded HTTP Status, e.g. 404 or 200. + self.status_code = None + + #: Case-insensitive Dictionary of Response Headers. + #: For example, ``headers['content-encoding']`` will return the + #: value of a ``'Content-Encoding'`` response header. + self.headers = CaseInsensitiveDict() + + #: File-like object representation of response (for advanced usage). + #: Use of ``raw`` requires that ``stream=True`` be set on the request. + #: This requirement does not apply for use internally to Requests. + self.raw = None + + #: Final URL location of Response. + self.url = None + + #: Encoding to decode with when accessing r.text. + self.encoding = None + + #: A list of :class:`Response ` objects from + #: the history of the Request. Any redirect responses will end + #: up here. The list is sorted from the oldest to the most recent request. + self.history = [] + + #: Textual reason of responded HTTP Status, e.g. "Not Found" or "OK". + self.reason = None + + #: A CookieJar of Cookies the server sent back. + self.cookies = cookiejar_from_dict({}) + + #: The amount of time elapsed between sending the request + #: and the arrival of the response (as a timedelta). + #: This property specifically measures the time taken between sending + #: the first byte of the request and finishing parsing the headers. It + #: is therefore unaffected by consuming the response content or the + #: value of the ``stream`` keyword argument. + self.elapsed = datetime.timedelta(0) + + #: The :class:`PreparedRequest ` object to which this + #: is a response. + self.request = None + + def __enter__(self): + return self + + def __exit__(self, *args): + self.close() + + def __getstate__(self): + # Consume everything; accessing the content attribute makes + # sure the content has been fully read. + if not self._content_consumed: + self.content + + return {attr: getattr(self, attr, None) for attr in self.__attrs__} + + def __setstate__(self, state): + for name, value in state.items(): + setattr(self, name, value) + + # pickled objects do not have .raw + setattr(self, "_content_consumed", True) + setattr(self, "raw", None) + + def __repr__(self): + return f"" + + def __bool__(self): + """Returns True if :attr:`status_code` is less than 400. + + This attribute checks if the status code of the response is between + 400 and 600 to see if there was a client error or a server error. If + the status code, is between 200 and 400, this will return True. This + is **not** a check to see if the response code is ``200 OK``. + """ + return self.ok + + def __nonzero__(self): + """Returns True if :attr:`status_code` is less than 400. + + This attribute checks if the status code of the response is between + 400 and 600 to see if there was a client error or a server error. If + the status code, is between 200 and 400, this will return True. This + is **not** a check to see if the response code is ``200 OK``. + """ + return self.ok + + def __iter__(self): + """Allows you to use a response as an iterator.""" + return self.iter_content(128) + + @property + def ok(self): + """Returns True if :attr:`status_code` is less than 400, False if not. + + This attribute checks if the status code of the response is between + 400 and 600 to see if there was a client error or a server error. If + the status code is between 200 and 400, this will return True. This + is **not** a check to see if the response code is ``200 OK``. + """ + try: + self.raise_for_status() + except HTTPError: + return False + return True + + @property + def is_redirect(self): + """True if this Response is a well-formed HTTP redirect that could have + been processed automatically (by :meth:`Session.resolve_redirects`). + """ + return "location" in self.headers and self.status_code in REDIRECT_STATI + + @property + def is_permanent_redirect(self): + """True if this Response one of the permanent versions of redirect.""" + return "location" in self.headers and self.status_code in ( + codes.moved_permanently, + codes.permanent_redirect, + ) + + @property + def next(self): + """Returns a PreparedRequest for the next request in a redirect chain, if there is one.""" + return self._next + + @property + def apparent_encoding(self): + """The apparent encoding, provided by the charset_normalizer or chardet libraries.""" + if chardet is not None: + return chardet.detect(self.content)["encoding"] + else: + # If no character detection library is available, we'll fall back + # to a standard Python utf-8 str. + return "utf-8" + + def iter_content(self, chunk_size=1, decode_unicode=False): + """Iterates over the response data. When stream=True is set on the + request, this avoids reading the content at once into memory for + large responses. The chunk size is the number of bytes it should + read into memory. This is not necessarily the length of each item + returned as decoding can take place. + + chunk_size must be of type int or None. A value of None will + function differently depending on the value of `stream`. + stream=True will read data as it arrives in whatever size the + chunks are received. If stream=False, data is returned as + a single chunk. + + If decode_unicode is True, content will be decoded using the best + available encoding based on the response. + """ + + def generate(): + # Special case for urllib3. + if hasattr(self.raw, "stream"): + try: + yield from self.raw.stream(chunk_size, decode_content=True) + except ProtocolError as e: + raise ChunkedEncodingError(e) + except DecodeError as e: + raise ContentDecodingError(e) + except ReadTimeoutError as e: + raise ConnectionError(e) + except SSLError as e: + raise RequestsSSLError(e) + else: + # Standard file-like object. + while True: + chunk = self.raw.read(chunk_size) + if not chunk: + break + yield chunk + + self._content_consumed = True + + if self._content_consumed and isinstance(self._content, bool): + raise StreamConsumedError() + elif chunk_size is not None and not isinstance(chunk_size, int): + raise TypeError( + f"chunk_size must be an int, it is instead a {type(chunk_size)}." + ) + # simulate reading small chunks of the content + reused_chunks = iter_slices(self._content, chunk_size) + + stream_chunks = generate() + + chunks = reused_chunks if self._content_consumed else stream_chunks + + if decode_unicode: + chunks = stream_decode_response_unicode(chunks, self) + + return chunks + + def iter_lines( + self, chunk_size=ITER_CHUNK_SIZE, decode_unicode=False, delimiter=None + ): + """Iterates over the response data, one line at a time. When + stream=True is set on the request, this avoids reading the + content at once into memory for large responses. + + .. note:: This method is not reentrant safe. + """ + + pending = None + + for chunk in self.iter_content( + chunk_size=chunk_size, decode_unicode=decode_unicode + ): + if pending is not None: + chunk = pending + chunk + + if delimiter: + lines = chunk.split(delimiter) + else: + lines = chunk.splitlines() + + if lines and lines[-1] and chunk and lines[-1][-1] == chunk[-1]: + pending = lines.pop() + else: + pending = None + + yield from lines + + if pending is not None: + yield pending + + @property + def content(self): + """Content of the response, in bytes.""" + + if self._content is False: + # Read the contents. + if self._content_consumed: + raise RuntimeError("The content for this response was already consumed") + + if self.status_code == 0 or self.raw is None: + self._content = None + else: + self._content = b"".join(self.iter_content(CONTENT_CHUNK_SIZE)) or b"" + + self._content_consumed = True + # don't need to release the connection; that's been handled by urllib3 + # since we exhausted the data. + return self._content + + @property + def text(self): + """Content of the response, in unicode. + + If Response.encoding is None, encoding will be guessed using + ``charset_normalizer`` or ``chardet``. + + The encoding of the response content is determined based solely on HTTP + headers, following RFC 2616 to the letter. If you can take advantage of + non-HTTP knowledge to make a better guess at the encoding, you should + set ``r.encoding`` appropriately before accessing this property. + """ + + # Try charset from content-type + content = None + encoding = self.encoding + + if not self.content: + return "" + + # Fallback to auto-detected encoding. + if self.encoding is None: + encoding = self.apparent_encoding + + # Decode unicode from given encoding. + try: + content = str(self.content, encoding, errors="replace") + except (LookupError, TypeError): + # A LookupError is raised if the encoding was not found which could + # indicate a misspelling or similar mistake. + # + # A TypeError can be raised if encoding is None + # + # So we try blindly encoding. + content = str(self.content, errors="replace") + + return content + + def json(self, **kwargs): + r"""Decodes the JSON response body (if any) as a Python object. + + This may return a dictionary, list, etc. depending on what is in the response. + + :param \*\*kwargs: Optional arguments that ``json.loads`` takes. + :raises requests.exceptions.JSONDecodeError: If the response body does not + contain valid json. + """ + + if not self.encoding and self.content and len(self.content) > 3: + # No encoding set. JSON RFC 4627 section 3 states we should expect + # UTF-8, -16 or -32. Detect which one to use; If the detection or + # decoding fails, fall back to `self.text` (using charset_normalizer to make + # a best guess). + encoding = guess_json_utf(self.content) + if encoding is not None: + try: + return complexjson.loads(self.content.decode(encoding), **kwargs) + except UnicodeDecodeError: + # Wrong UTF codec detected; usually because it's not UTF-8 + # but some other 8-bit codec. This is an RFC violation, + # and the server didn't bother to tell us what codec *was* + # used. + pass + except JSONDecodeError as e: + raise RequestsJSONDecodeError(e.msg, e.doc, e.pos) + + try: + return complexjson.loads(self.text, **kwargs) + except JSONDecodeError as e: + # Catch JSON-related errors and raise as requests.JSONDecodeError + # This aliases json.JSONDecodeError and simplejson.JSONDecodeError + raise RequestsJSONDecodeError(e.msg, e.doc, e.pos) + + @property + def links(self): + """Returns the parsed header links of the response, if any.""" + + header = self.headers.get("link") + + resolved_links = {} + + if header: + links = parse_header_links(header) + + for link in links: + key = link.get("rel") or link.get("url") + resolved_links[key] = link + + return resolved_links + + def raise_for_status(self): + """Raises :class:`HTTPError`, if one occurred.""" + + http_error_msg = "" + if isinstance(self.reason, bytes): + # We attempt to decode utf-8 first because some servers + # choose to localize their reason strings. If the string + # isn't utf-8, we fall back to iso-8859-1 for all other + # encodings. (See PR #3538) + try: + reason = self.reason.decode("utf-8") + except UnicodeDecodeError: + reason = self.reason.decode("iso-8859-1") + else: + reason = self.reason + + if 400 <= self.status_code < 500: + http_error_msg = ( + f"{self.status_code} Client Error: {reason} for url: {self.url}" + ) + + elif 500 <= self.status_code < 600: + http_error_msg = ( + f"{self.status_code} Server Error: {reason} for url: {self.url}" + ) + + if http_error_msg: + raise HTTPError(http_error_msg, response=self) + + def close(self): + """Releases the connection back to the pool. Once this method has been + called the underlying ``raw`` object must not be accessed again. + + *Note: Should not normally need to be called explicitly.* + """ + if not self._content_consumed: + self.raw.close() + + release_conn = getattr(self.raw, "release_conn", None) + if release_conn is not None: + release_conn() diff --git a/requests/packages.py b/requests/packages.py new file mode 100644 index 0000000000000000000000000000000000000000..5ab3d8e250de8475cb22553f564e5444e02c7460 --- /dev/null +++ b/requests/packages.py @@ -0,0 +1,23 @@ +import sys + +from .compat import chardet + +# This code exists for backwards compatibility reasons. +# I don't like it either. Just look the other way. :) + +for package in ("urllib3", "idna"): + locals()[package] = __import__(package) + # This traversal is apparently necessary such that the identities are + # preserved (requests.packages.urllib3.* is urllib3.*) + for mod in list(sys.modules): + if mod == package or mod.startswith(f"{package}."): + sys.modules[f"requests.packages.{mod}"] = sys.modules[mod] + +if chardet is not None: + target = chardet.__name__ + for mod in list(sys.modules): + if mod == target or mod.startswith(f"{target}."): + imported_mod = sys.modules[mod] + sys.modules[f"requests.packages.{mod}"] = imported_mod + mod = mod.replace(target, "chardet") + sys.modules[f"requests.packages.{mod}"] = imported_mod diff --git a/requests/sessions.py b/requests/sessions.py new file mode 100644 index 0000000000000000000000000000000000000000..731550de88aceb59747460faf519c2277e300e87 --- /dev/null +++ b/requests/sessions.py @@ -0,0 +1,831 @@ +""" +requests.sessions +~~~~~~~~~~~~~~~~~ + +This module provides a Session object to manage and persist settings across +requests (cookies, auth, proxies). +""" +import os +import sys +import time +from collections import OrderedDict +from datetime import timedelta + +from ._internal_utils import to_native_string +from .adapters import HTTPAdapter +from .auth import _basic_auth_str +from .compat import Mapping, cookielib, urljoin, urlparse +from .cookies import ( + RequestsCookieJar, + cookiejar_from_dict, + extract_cookies_to_jar, + merge_cookies, +) +from .exceptions import ( + ChunkedEncodingError, + ContentDecodingError, + InvalidSchema, + TooManyRedirects, +) +from .hooks import default_hooks, dispatch_hook + +# formerly defined here, reexposed here for backward compatibility +from .models import ( # noqa: F401 + DEFAULT_REDIRECT_LIMIT, + REDIRECT_STATI, + PreparedRequest, + Request, +) +from .status_codes import codes +from .structures import CaseInsensitiveDict +from .utils import ( # noqa: F401 + DEFAULT_PORTS, + default_headers, + get_auth_from_url, + get_environ_proxies, + get_netrc_auth, + requote_uri, + resolve_proxies, + rewind_body, + should_bypass_proxies, + to_key_val_list, +) + +# Preferred clock, based on which one is more accurate on a given system. +if sys.platform == "win32": + preferred_clock = time.perf_counter +else: + preferred_clock = time.time + + +def merge_setting(request_setting, session_setting, dict_class=OrderedDict): + """Determines appropriate setting for a given request, taking into account + the explicit setting on that request, and the setting in the session. If a + setting is a dictionary, they will be merged together using `dict_class` + """ + + if session_setting is None: + return request_setting + + if request_setting is None: + return session_setting + + # Bypass if not a dictionary (e.g. verify) + if not ( + isinstance(session_setting, Mapping) and isinstance(request_setting, Mapping) + ): + return request_setting + + merged_setting = dict_class(to_key_val_list(session_setting)) + merged_setting.update(to_key_val_list(request_setting)) + + # Remove keys that are set to None. Extract keys first to avoid altering + # the dictionary during iteration. + none_keys = [k for (k, v) in merged_setting.items() if v is None] + for key in none_keys: + del merged_setting[key] + + return merged_setting + + +def merge_hooks(request_hooks, session_hooks, dict_class=OrderedDict): + """Properly merges both requests and session hooks. + + This is necessary because when request_hooks == {'response': []}, the + merge breaks Session hooks entirely. + """ + if session_hooks is None or session_hooks.get("response") == []: + return request_hooks + + if request_hooks is None or request_hooks.get("response") == []: + return session_hooks + + return merge_setting(request_hooks, session_hooks, dict_class) + + +class SessionRedirectMixin: + def get_redirect_target(self, resp): + """Receives a Response. Returns a redirect URI or ``None``""" + # Due to the nature of how requests processes redirects this method will + # be called at least once upon the original response and at least twice + # on each subsequent redirect response (if any). + # If a custom mixin is used to handle this logic, it may be advantageous + # to cache the redirect location onto the response object as a private + # attribute. + if resp.is_redirect: + location = resp.headers["location"] + # Currently the underlying http module on py3 decode headers + # in latin1, but empirical evidence suggests that latin1 is very + # rarely used with non-ASCII characters in HTTP headers. + # It is more likely to get UTF8 header rather than latin1. + # This causes incorrect handling of UTF8 encoded location headers. + # To solve this, we re-encode the location in latin1. + location = location.encode("latin1") + return to_native_string(location, "utf8") + return None + + def should_strip_auth(self, old_url, new_url): + """Decide whether Authorization header should be removed when redirecting""" + old_parsed = urlparse(old_url) + new_parsed = urlparse(new_url) + if old_parsed.hostname != new_parsed.hostname: + return True + # Special case: allow http -> https redirect when using the standard + # ports. This isn't specified by RFC 7235, but is kept to avoid + # breaking backwards compatibility with older versions of requests + # that allowed any redirects on the same host. + if ( + old_parsed.scheme == "http" + and old_parsed.port in (80, None) + and new_parsed.scheme == "https" + and new_parsed.port in (443, None) + ): + return False + + # Handle default port usage corresponding to scheme. + changed_port = old_parsed.port != new_parsed.port + changed_scheme = old_parsed.scheme != new_parsed.scheme + default_port = (DEFAULT_PORTS.get(old_parsed.scheme, None), None) + if ( + not changed_scheme + and old_parsed.port in default_port + and new_parsed.port in default_port + ): + return False + + # Standard case: root URI must match + return changed_port or changed_scheme + + def resolve_redirects( + self, + resp, + req, + stream=False, + timeout=None, + verify=True, + cert=None, + proxies=None, + yield_requests=False, + **adapter_kwargs, + ): + """Receives a Response. Returns a generator of Responses or Requests.""" + + hist = [] # keep track of history + + url = self.get_redirect_target(resp) + previous_fragment = urlparse(req.url).fragment + while url: + prepared_request = req.copy() + + # Update history and keep track of redirects. + # resp.history must ignore the original request in this loop + hist.append(resp) + resp.history = hist[1:] + + try: + resp.content # Consume socket so it can be released + except (ChunkedEncodingError, ContentDecodingError, RuntimeError): + resp.raw.read(decode_content=False) + + if len(resp.history) >= self.max_redirects: + raise TooManyRedirects( + f"Exceeded {self.max_redirects} redirects.", response=resp + ) + + # Release the connection back into the pool. + resp.close() + + # Handle redirection without scheme (see: RFC 1808 Section 4) + if url.startswith("//"): + parsed_rurl = urlparse(resp.url) + url = ":".join([to_native_string(parsed_rurl.scheme), url]) + + # Normalize url case and attach previous fragment if needed (RFC 7231 7.1.2) + parsed = urlparse(url) + if parsed.fragment == "" and previous_fragment: + parsed = parsed._replace(fragment=previous_fragment) + elif parsed.fragment: + previous_fragment = parsed.fragment + url = parsed.geturl() + + # Facilitate relative 'location' headers, as allowed by RFC 7231. + # (e.g. '/path/to/resource' instead of 'http://domain.tld/path/to/resource') + # Compliant with RFC3986, we percent encode the url. + if not parsed.netloc: + url = urljoin(resp.url, requote_uri(url)) + else: + url = requote_uri(url) + + prepared_request.url = to_native_string(url) + + self.rebuild_method(prepared_request, resp) + + # https://github.com/psf/requests/issues/1084 + if resp.status_code not in ( + codes.temporary_redirect, + codes.permanent_redirect, + ): + # https://github.com/psf/requests/issues/3490 + purged_headers = ("Content-Length", "Content-Type", "Transfer-Encoding") + for header in purged_headers: + prepared_request.headers.pop(header, None) + prepared_request.body = None + + headers = prepared_request.headers + headers.pop("Cookie", None) + + # Extract any cookies sent on the response to the cookiejar + # in the new request. Because we've mutated our copied prepared + # request, use the old one that we haven't yet touched. + extract_cookies_to_jar(prepared_request._cookies, req, resp.raw) + merge_cookies(prepared_request._cookies, self.cookies) + prepared_request.prepare_cookies(prepared_request._cookies) + + # Rebuild auth and proxy information. + proxies = self.rebuild_proxies(prepared_request, proxies) + self.rebuild_auth(prepared_request, resp) + + # A failed tell() sets `_body_position` to `object()`. This non-None + # value ensures `rewindable` will be True, allowing us to raise an + # UnrewindableBodyError, instead of hanging the connection. + rewindable = prepared_request._body_position is not None and ( + "Content-Length" in headers or "Transfer-Encoding" in headers + ) + + # Attempt to rewind consumed file-like object. + if rewindable: + rewind_body(prepared_request) + + # Override the original request. + req = prepared_request + + if yield_requests: + yield req + else: + resp = self.send( + req, + stream=stream, + timeout=timeout, + verify=verify, + cert=cert, + proxies=proxies, + allow_redirects=False, + **adapter_kwargs, + ) + + extract_cookies_to_jar(self.cookies, prepared_request, resp.raw) + + # extract redirect url, if any, for the next loop + url = self.get_redirect_target(resp) + yield resp + + def rebuild_auth(self, prepared_request, response): + """When being redirected we may want to strip authentication from the + request to avoid leaking credentials. This method intelligently removes + and reapplies authentication where possible to avoid credential loss. + """ + headers = prepared_request.headers + url = prepared_request.url + + if "Authorization" in headers and self.should_strip_auth( + response.request.url, url + ): + # If we get redirected to a new host, we should strip out any + # authentication headers. + del headers["Authorization"] + + # .netrc might have more auth for us on our new host. + new_auth = get_netrc_auth(url) if self.trust_env else None + if new_auth is not None: + prepared_request.prepare_auth(new_auth) + + def rebuild_proxies(self, prepared_request, proxies): + """This method re-evaluates the proxy configuration by considering the + environment variables. If we are redirected to a URL covered by + NO_PROXY, we strip the proxy configuration. Otherwise, we set missing + proxy keys for this URL (in case they were stripped by a previous + redirect). + + This method also replaces the Proxy-Authorization header where + necessary. + + :rtype: dict + """ + headers = prepared_request.headers + scheme = urlparse(prepared_request.url).scheme + new_proxies = resolve_proxies(prepared_request, proxies, self.trust_env) + + if "Proxy-Authorization" in headers: + del headers["Proxy-Authorization"] + + try: + username, password = get_auth_from_url(new_proxies[scheme]) + except KeyError: + username, password = None, None + + # urllib3 handles proxy authorization for us in the standard adapter. + # Avoid appending this to TLS tunneled requests where it may be leaked. + if not scheme.startswith("https") and username and password: + headers["Proxy-Authorization"] = _basic_auth_str(username, password) + + return new_proxies + + def rebuild_method(self, prepared_request, response): + """When being redirected we may want to change the method of the request + based on certain specs or browser behavior. + """ + method = prepared_request.method + + # https://tools.ietf.org/html/rfc7231#section-6.4.4 + if response.status_code == codes.see_other and method != "HEAD": + method = "GET" + + # Do what the browsers do, despite standards... + # First, turn 302s into GETs. + if response.status_code == codes.found and method != "HEAD": + method = "GET" + + # Second, if a POST is responded to with a 301, turn it into a GET. + # This bizarre behaviour is explained in Issue 1704. + if response.status_code == codes.moved and method == "POST": + method = "GET" + + prepared_request.method = method + + +class Session(SessionRedirectMixin): + """A Requests session. + + Provides cookie persistence, connection-pooling, and configuration. + + Basic Usage:: + + >>> import requests + >>> s = requests.Session() + >>> s.get('https://httpbin.org/get') + + + Or as a context manager:: + + >>> with requests.Session() as s: + ... s.get('https://httpbin.org/get') + + """ + + __attrs__ = [ + "headers", + "cookies", + "auth", + "proxies", + "hooks", + "params", + "verify", + "cert", + "adapters", + "stream", + "trust_env", + "max_redirects", + ] + + def __init__(self): + #: A case-insensitive dictionary of headers to be sent on each + #: :class:`Request ` sent from this + #: :class:`Session `. + self.headers = default_headers() + + #: Default Authentication tuple or object to attach to + #: :class:`Request `. + self.auth = None + + #: Dictionary mapping protocol or protocol and host to the URL of the proxy + #: (e.g. {'http': 'foo.bar:3128', 'http://host.name': 'foo.bar:4012'}) to + #: be used on each :class:`Request `. + self.proxies = {} + + #: Event-handling hooks. + self.hooks = default_hooks() + + #: Dictionary of querystring data to attach to each + #: :class:`Request `. The dictionary values may be lists for + #: representing multivalued query parameters. + self.params = {} + + #: Stream response content default. + self.stream = False + + #: SSL Verification default. + #: Defaults to `True`, requiring requests to verify the TLS certificate at the + #: remote end. + #: If verify is set to `False`, requests will accept any TLS certificate + #: presented by the server, and will ignore hostname mismatches and/or + #: expired certificates, which will make your application vulnerable to + #: man-in-the-middle (MitM) attacks. + #: Only set this to `False` for testing. + self.verify = True + + #: SSL client certificate default, if String, path to ssl client + #: cert file (.pem). If Tuple, ('cert', 'key') pair. + self.cert = None + + #: Maximum number of redirects allowed. If the request exceeds this + #: limit, a :class:`TooManyRedirects` exception is raised. + #: This defaults to requests.models.DEFAULT_REDIRECT_LIMIT, which is + #: 30. + self.max_redirects = DEFAULT_REDIRECT_LIMIT + + #: Trust environment settings for proxy configuration, default + #: authentication and similar. + self.trust_env = True + + #: A CookieJar containing all currently outstanding cookies set on this + #: session. By default it is a + #: :class:`RequestsCookieJar `, but + #: may be any other ``cookielib.CookieJar`` compatible object. + self.cookies = cookiejar_from_dict({}) + + # Default connection adapters. + self.adapters = OrderedDict() + self.mount("https://", HTTPAdapter()) + self.mount("http://", HTTPAdapter()) + + def __enter__(self): + return self + + def __exit__(self, *args): + self.close() + + def prepare_request(self, request): + """Constructs a :class:`PreparedRequest ` for + transmission and returns it. The :class:`PreparedRequest` has settings + merged from the :class:`Request ` instance and those of the + :class:`Session`. + + :param request: :class:`Request` instance to prepare with this + session's settings. + :rtype: requests.PreparedRequest + """ + cookies = request.cookies or {} + + # Bootstrap CookieJar. + if not isinstance(cookies, cookielib.CookieJar): + cookies = cookiejar_from_dict(cookies) + + # Merge with session cookies + merged_cookies = merge_cookies( + merge_cookies(RequestsCookieJar(), self.cookies), cookies + ) + + # Set environment's basic authentication if not explicitly set. + auth = request.auth + if self.trust_env and not auth and not self.auth: + auth = get_netrc_auth(request.url) + + p = PreparedRequest() + p.prepare( + method=request.method.upper(), + url=request.url, + files=request.files, + data=request.data, + json=request.json, + headers=merge_setting( + request.headers, self.headers, dict_class=CaseInsensitiveDict + ), + params=merge_setting(request.params, self.params), + auth=merge_setting(auth, self.auth), + cookies=merged_cookies, + hooks=merge_hooks(request.hooks, self.hooks), + ) + return p + + def request( + self, + method, + url, + params=None, + data=None, + headers=None, + cookies=None, + files=None, + auth=None, + timeout=None, + allow_redirects=True, + proxies=None, + hooks=None, + stream=None, + verify=None, + cert=None, + json=None, + ): + """Constructs a :class:`Request `, prepares it and sends it. + Returns :class:`Response ` object. + + :param method: method for the new :class:`Request` object. + :param url: URL for the new :class:`Request` object. + :param params: (optional) Dictionary or bytes to be sent in the query + string for the :class:`Request`. + :param data: (optional) Dictionary, list of tuples, bytes, or file-like + object to send in the body of the :class:`Request`. + :param json: (optional) json to send in the body of the + :class:`Request`. + :param headers: (optional) Dictionary of HTTP Headers to send with the + :class:`Request`. + :param cookies: (optional) Dict or CookieJar object to send with the + :class:`Request`. + :param files: (optional) Dictionary of ``'filename': file-like-objects`` + for multipart encoding upload. + :param auth: (optional) Auth tuple or callable to enable + Basic/Digest/Custom HTTP Auth. + :param timeout: (optional) How many seconds to wait for the server to send + data before giving up, as a float, or a :ref:`(connect timeout, + read timeout) ` tuple. + :type timeout: float or tuple + :param allow_redirects: (optional) Set to True by default. + :type allow_redirects: bool + :param proxies: (optional) Dictionary mapping protocol or protocol and + hostname to the URL of the proxy. + :param hooks: (optional) Dictionary mapping hook name to one event or + list of events, event must be callable. + :param stream: (optional) whether to immediately download the response + content. Defaults to ``False``. + :param verify: (optional) Either a boolean, in which case it controls whether we verify + the server's TLS certificate, or a string, in which case it must be a path + to a CA bundle to use. Defaults to ``True``. When set to + ``False``, requests will accept any TLS certificate presented by + the server, and will ignore hostname mismatches and/or expired + certificates, which will make your application vulnerable to + man-in-the-middle (MitM) attacks. Setting verify to ``False`` + may be useful during local development or testing. + :param cert: (optional) if String, path to ssl client cert file (.pem). + If Tuple, ('cert', 'key') pair. + :rtype: requests.Response + """ + # Create the Request. + req = Request( + method=method.upper(), + url=url, + headers=headers, + files=files, + data=data or {}, + json=json, + params=params or {}, + auth=auth, + cookies=cookies, + hooks=hooks, + ) + prep = self.prepare_request(req) + + proxies = proxies or {} + + settings = self.merge_environment_settings( + prep.url, proxies, stream, verify, cert + ) + + # Send the request. + send_kwargs = { + "timeout": timeout, + "allow_redirects": allow_redirects, + } + send_kwargs.update(settings) + resp = self.send(prep, **send_kwargs) + + return resp + + def get(self, url, **kwargs): + r"""Sends a GET request. Returns :class:`Response` object. + + :param url: URL for the new :class:`Request` object. + :param \*\*kwargs: Optional arguments that ``request`` takes. + :rtype: requests.Response + """ + + kwargs.setdefault("allow_redirects", True) + return self.request("GET", url, **kwargs) + + def options(self, url, **kwargs): + r"""Sends a OPTIONS request. Returns :class:`Response` object. + + :param url: URL for the new :class:`Request` object. + :param \*\*kwargs: Optional arguments that ``request`` takes. + :rtype: requests.Response + """ + + kwargs.setdefault("allow_redirects", True) + return self.request("OPTIONS", url, **kwargs) + + def head(self, url, **kwargs): + r"""Sends a HEAD request. Returns :class:`Response` object. + + :param url: URL for the new :class:`Request` object. + :param \*\*kwargs: Optional arguments that ``request`` takes. + :rtype: requests.Response + """ + + kwargs.setdefault("allow_redirects", False) + return self.request("HEAD", url, **kwargs) + + def post(self, url, data=None, json=None, **kwargs): + r"""Sends a POST request. Returns :class:`Response` object. + + :param url: URL for the new :class:`Request` object. + :param data: (optional) Dictionary, list of tuples, bytes, or file-like + object to send in the body of the :class:`Request`. + :param json: (optional) json to send in the body of the :class:`Request`. + :param \*\*kwargs: Optional arguments that ``request`` takes. + :rtype: requests.Response + """ + + return self.request("POST", url, data=data, json=json, **kwargs) + + def put(self, url, data=None, **kwargs): + r"""Sends a PUT request. Returns :class:`Response` object. + + :param url: URL for the new :class:`Request` object. + :param data: (optional) Dictionary, list of tuples, bytes, or file-like + object to send in the body of the :class:`Request`. + :param \*\*kwargs: Optional arguments that ``request`` takes. + :rtype: requests.Response + """ + + return self.request("PUT", url, data=data, **kwargs) + + def patch(self, url, data=None, **kwargs): + r"""Sends a PATCH request. Returns :class:`Response` object. + + :param url: URL for the new :class:`Request` object. + :param data: (optional) Dictionary, list of tuples, bytes, or file-like + object to send in the body of the :class:`Request`. + :param \*\*kwargs: Optional arguments that ``request`` takes. + :rtype: requests.Response + """ + + return self.request("PATCH", url, data=data, **kwargs) + + def delete(self, url, **kwargs): + r"""Sends a DELETE request. Returns :class:`Response` object. + + :param url: URL for the new :class:`Request` object. + :param \*\*kwargs: Optional arguments that ``request`` takes. + :rtype: requests.Response + """ + + return self.request("DELETE", url, **kwargs) + + def send(self, request, **kwargs): + """Send a given PreparedRequest. + + :rtype: requests.Response + """ + # Set defaults that the hooks can utilize to ensure they always have + # the correct parameters to reproduce the previous request. + kwargs.setdefault("stream", self.stream) + kwargs.setdefault("verify", self.verify) + kwargs.setdefault("cert", self.cert) + if "proxies" not in kwargs: + kwargs["proxies"] = resolve_proxies(request, self.proxies, self.trust_env) + + # It's possible that users might accidentally send a Request object. + # Guard against that specific failure case. + if isinstance(request, Request): + raise ValueError("You can only send PreparedRequests.") + + # Set up variables needed for resolve_redirects and dispatching of hooks + allow_redirects = kwargs.pop("allow_redirects", True) + stream = kwargs.get("stream") + hooks = request.hooks + + # Get the appropriate adapter to use + adapter = self.get_adapter(url=request.url) + + # Start time (approximately) of the request + start = preferred_clock() + + # Send the request + r = adapter.send(request, **kwargs) + + # Total elapsed time of the request (approximately) + elapsed = preferred_clock() - start + r.elapsed = timedelta(seconds=elapsed) + + # Response manipulation hooks + r = dispatch_hook("response", hooks, r, **kwargs) + + # Persist cookies + if r.history: + # If the hooks create history then we want those cookies too + for resp in r.history: + extract_cookies_to_jar(self.cookies, resp.request, resp.raw) + + extract_cookies_to_jar(self.cookies, request, r.raw) + + # Resolve redirects if allowed. + if allow_redirects: + # Redirect resolving generator. + gen = self.resolve_redirects(r, request, **kwargs) + history = [resp for resp in gen] + else: + history = [] + + # Shuffle things around if there's history. + if history: + # Insert the first (original) request at the start + history.insert(0, r) + # Get the last request made + r = history.pop() + r.history = history + + # If redirects aren't being followed, store the response on the Request for Response.next(). + if not allow_redirects: + try: + r._next = next( + self.resolve_redirects(r, request, yield_requests=True, **kwargs) + ) + except StopIteration: + pass + + if not stream: + r.content + + return r + + def merge_environment_settings(self, url, proxies, stream, verify, cert): + """ + Check the environment and merge it with some settings. + + :rtype: dict + """ + # Gather clues from the surrounding environment. + if self.trust_env: + # Set environment's proxies. + no_proxy = proxies.get("no_proxy") if proxies is not None else None + env_proxies = get_environ_proxies(url, no_proxy=no_proxy) + for k, v in env_proxies.items(): + proxies.setdefault(k, v) + + # Look for requests environment configuration + # and be compatible with cURL. + if verify is True or verify is None: + verify = ( + os.environ.get("REQUESTS_CA_BUNDLE") + or os.environ.get("CURL_CA_BUNDLE") + or verify + ) + + # Merge all the kwargs. + proxies = merge_setting(proxies, self.proxies) + stream = merge_setting(stream, self.stream) + verify = merge_setting(verify, self.verify) + cert = merge_setting(cert, self.cert) + + return {"proxies": proxies, "stream": stream, "verify": verify, "cert": cert} + + def get_adapter(self, url): + """ + Returns the appropriate connection adapter for the given URL. + + :rtype: requests.adapters.BaseAdapter + """ + for prefix, adapter in self.adapters.items(): + if url.lower().startswith(prefix.lower()): + return adapter + + # Nothing matches :-/ + raise InvalidSchema(f"No connection adapters were found for {url!r}") + + def close(self): + """Closes all adapters and as such the session""" + for v in self.adapters.values(): + v.close() + + def mount(self, prefix, adapter): + """Registers a connection adapter to a prefix. + + Adapters are sorted in descending order by prefix length. + """ + self.adapters[prefix] = adapter + keys_to_move = [k for k in self.adapters if len(k) < len(prefix)] + + for key in keys_to_move: + self.adapters[key] = self.adapters.pop(key) + + def __getstate__(self): + state = {attr: getattr(self, attr, None) for attr in self.__attrs__} + return state + + def __setstate__(self, state): + for attr, value in state.items(): + setattr(self, attr, value) + + +def session(): + """ + Returns a :class:`Session` for context-management. + + .. deprecated:: 1.0.0 + + This method has been deprecated since version 1.0.0 and is only kept for + backwards compatibility. New code should use :class:`~requests.sessions.Session` + to create a session. This may be removed at a future date. + + :rtype: Session + """ + return Session() diff --git a/requests/status_codes.py b/requests/status_codes.py new file mode 100644 index 0000000000000000000000000000000000000000..c7945a2f06897ed980cc575df2f48d9e6c1a9f7e --- /dev/null +++ b/requests/status_codes.py @@ -0,0 +1,128 @@ +r""" +The ``codes`` object defines a mapping from common names for HTTP statuses +to their numerical codes, accessible either as attributes or as dictionary +items. + +Example:: + + >>> import requests + >>> requests.codes['temporary_redirect'] + 307 + >>> requests.codes.teapot + 418 + >>> requests.codes['\o/'] + 200 + +Some codes have multiple names, and both upper- and lower-case versions of +the names are allowed. For example, ``codes.ok``, ``codes.OK``, and +``codes.okay`` all correspond to the HTTP status code 200. +""" + +from .structures import LookupDict + +_codes = { + # Informational. + 100: ("continue",), + 101: ("switching_protocols",), + 102: ("processing", "early-hints"), + 103: ("checkpoint",), + 122: ("uri_too_long", "request_uri_too_long"), + 200: ("ok", "okay", "all_ok", "all_okay", "all_good", "\\o/", "✓"), + 201: ("created",), + 202: ("accepted",), + 203: ("non_authoritative_info", "non_authoritative_information"), + 204: ("no_content",), + 205: ("reset_content", "reset"), + 206: ("partial_content", "partial"), + 207: ("multi_status", "multiple_status", "multi_stati", "multiple_stati"), + 208: ("already_reported",), + 226: ("im_used",), + # Redirection. + 300: ("multiple_choices",), + 301: ("moved_permanently", "moved", "\\o-"), + 302: ("found",), + 303: ("see_other", "other"), + 304: ("not_modified",), + 305: ("use_proxy",), + 306: ("switch_proxy",), + 307: ("temporary_redirect", "temporary_moved", "temporary"), + 308: ( + "permanent_redirect", + "resume_incomplete", + "resume", + ), # "resume" and "resume_incomplete" to be removed in 3.0 + # Client Error. + 400: ("bad_request", "bad"), + 401: ("unauthorized",), + 402: ("payment_required", "payment"), + 403: ("forbidden",), + 404: ("not_found", "-o-"), + 405: ("method_not_allowed", "not_allowed"), + 406: ("not_acceptable",), + 407: ("proxy_authentication_required", "proxy_auth", "proxy_authentication"), + 408: ("request_timeout", "timeout"), + 409: ("conflict",), + 410: ("gone",), + 411: ("length_required",), + 412: ("precondition_failed", "precondition"), + 413: ("request_entity_too_large", "content_too_large"), + 414: ("request_uri_too_large", "uri_too_long"), + 415: ("unsupported_media_type", "unsupported_media", "media_type"), + 416: ( + "requested_range_not_satisfiable", + "requested_range", + "range_not_satisfiable", + ), + 417: ("expectation_failed",), + 418: ("im_a_teapot", "teapot", "i_am_a_teapot"), + 421: ("misdirected_request",), + 422: ("unprocessable_entity", "unprocessable", "unprocessable_content"), + 423: ("locked",), + 424: ("failed_dependency", "dependency"), + 425: ("unordered_collection", "unordered", "too_early"), + 426: ("upgrade_required", "upgrade"), + 428: ("precondition_required", "precondition"), + 429: ("too_many_requests", "too_many"), + 431: ("header_fields_too_large", "fields_too_large"), + 444: ("no_response", "none"), + 449: ("retry_with", "retry"), + 450: ("blocked_by_windows_parental_controls", "parental_controls"), + 451: ("unavailable_for_legal_reasons", "legal_reasons"), + 499: ("client_closed_request",), + # Server Error. + 500: ("internal_server_error", "server_error", "/o\\", "✗"), + 501: ("not_implemented",), + 502: ("bad_gateway",), + 503: ("service_unavailable", "unavailable"), + 504: ("gateway_timeout",), + 505: ("http_version_not_supported", "http_version"), + 506: ("variant_also_negotiates",), + 507: ("insufficient_storage",), + 509: ("bandwidth_limit_exceeded", "bandwidth"), + 510: ("not_extended",), + 511: ("network_authentication_required", "network_auth", "network_authentication"), +} + +codes = LookupDict(name="status_codes") + + +def _init(): + for code, titles in _codes.items(): + for title in titles: + setattr(codes, title, code) + if not title.startswith(("\\", "/")): + setattr(codes, title.upper(), code) + + def doc(code): + names = ", ".join(f"``{n}``" for n in _codes[code]) + return "* %d: %s" % (code, names) + + global __doc__ + __doc__ = ( + __doc__ + "\n" + "\n".join(doc(code) for code in sorted(_codes)) + if __doc__ is not None + else None + ) + + +_init() diff --git a/requests/utils.py b/requests/utils.py new file mode 100644 index 0000000000000000000000000000000000000000..8ab55852cc2188c53f08462ec4319c97fa49f04b --- /dev/null +++ b/requests/utils.py @@ -0,0 +1,1086 @@ +""" +requests.utils +~~~~~~~~~~~~~~ + +This module provides utility functions that are used within Requests +that are also useful for external consumption. +""" + +import codecs +import contextlib +import io +import os +import re +import socket +import struct +import sys +import tempfile +import warnings +import zipfile +from collections import OrderedDict + +from urllib3.util import make_headers, parse_url + +from . import certs +from .__version__ import __version__ + +# to_native_string is unused here, but imported here for backwards compatibility +from ._internal_utils import ( # noqa: F401 + _HEADER_VALIDATORS_BYTE, + _HEADER_VALIDATORS_STR, + HEADER_VALIDATORS, + to_native_string, +) +from .compat import ( + Mapping, + basestring, + bytes, + getproxies, + getproxies_environment, + integer_types, + is_urllib3_1, +) +from .compat import parse_http_list as _parse_list_header +from .compat import ( + proxy_bypass, + proxy_bypass_environment, + quote, + str, + unquote, + urlparse, + urlunparse, +) +from .cookies import cookiejar_from_dict +from .exceptions import ( + FileModeWarning, + InvalidHeader, + InvalidURL, + UnrewindableBodyError, +) +from .structures import CaseInsensitiveDict + +NETRC_FILES = (".netrc", "_netrc") + +DEFAULT_CA_BUNDLE_PATH = certs.where() + +DEFAULT_PORTS = {"http": 80, "https": 443} + +# Ensure that ', ' is used to preserve previous delimiter behavior. +DEFAULT_ACCEPT_ENCODING = ", ".join( + re.split(r",\s*", make_headers(accept_encoding=True)["accept-encoding"]) +) + + +if sys.platform == "win32": + # provide a proxy_bypass version on Windows without DNS lookups + + def proxy_bypass_registry(host): + try: + import winreg + except ImportError: + return False + + try: + internetSettings = winreg.OpenKey( + winreg.HKEY_CURRENT_USER, + r"Software\Microsoft\Windows\CurrentVersion\Internet Settings", + ) + # ProxyEnable could be REG_SZ or REG_DWORD, normalizing it + proxyEnable = int(winreg.QueryValueEx(internetSettings, "ProxyEnable")[0]) + # ProxyOverride is almost always a string + proxyOverride = winreg.QueryValueEx(internetSettings, "ProxyOverride")[0] + except (OSError, ValueError): + return False + if not proxyEnable or not proxyOverride: + return False + + # make a check value list from the registry entry: replace the + # '' string by the localhost entry and the corresponding + # canonical entry. + proxyOverride = proxyOverride.split(";") + # filter out empty strings to avoid re.match return true in the following code. + proxyOverride = filter(None, proxyOverride) + # now check if we match one of the registry values. + for test in proxyOverride: + if test == "": + if "." not in host: + return True + test = test.replace(".", r"\.") # mask dots + test = test.replace("*", r".*") # change glob sequence + test = test.replace("?", r".") # change glob char + if re.match(test, host, re.I): + return True + return False + + def proxy_bypass(host): # noqa + """Return True, if the host should be bypassed. + + Checks proxy settings gathered from the environment, if specified, + or the registry. + """ + if getproxies_environment(): + return proxy_bypass_environment(host) + else: + return proxy_bypass_registry(host) + + +def dict_to_sequence(d): + """Returns an internal sequence dictionary update.""" + + if hasattr(d, "items"): + d = d.items() + + return d + + +def super_len(o): + total_length = None + current_position = 0 + + if not is_urllib3_1 and isinstance(o, str): + # urllib3 2.x+ treats all strings as utf-8 instead + # of latin-1 (iso-8859-1) like http.client. + o = o.encode("utf-8") + + if hasattr(o, "__len__"): + total_length = len(o) + + elif hasattr(o, "len"): + total_length = o.len + + elif hasattr(o, "fileno"): + try: + fileno = o.fileno() + except (io.UnsupportedOperation, AttributeError): + # AttributeError is a surprising exception, seeing as how we've just checked + # that `hasattr(o, 'fileno')`. It happens for objects obtained via + # `Tarfile.extractfile()`, per issue 5229. + pass + else: + total_length = os.fstat(fileno).st_size + + # Having used fstat to determine the file length, we need to + # confirm that this file was opened up in binary mode. + if "b" not in o.mode: + warnings.warn( + ( + "Requests has determined the content-length for this " + "request using the binary size of the file: however, the " + "file has been opened in text mode (i.e. without the 'b' " + "flag in the mode). This may lead to an incorrect " + "content-length. In Requests 3.0, support will be removed " + "for files in text mode." + ), + FileModeWarning, + ) + + if hasattr(o, "tell"): + try: + current_position = o.tell() + except OSError: + # This can happen in some weird situations, such as when the file + # is actually a special file descriptor like stdin. In this + # instance, we don't know what the length is, so set it to zero and + # let requests chunk it instead. + if total_length is not None: + current_position = total_length + else: + if hasattr(o, "seek") and total_length is None: + # StringIO and BytesIO have seek but no usable fileno + try: + # seek to end of file + o.seek(0, 2) + total_length = o.tell() + + # seek back to current position to support + # partially read file-like objects + o.seek(current_position or 0) + except OSError: + total_length = 0 + + if total_length is None: + total_length = 0 + + return max(0, total_length - current_position) + + +def get_netrc_auth(url, raise_errors=False): + """Returns the Requests tuple auth for a given url from netrc.""" + + netrc_file = os.environ.get("NETRC") + if netrc_file is not None: + netrc_locations = (netrc_file,) + else: + netrc_locations = (f"~/{f}" for f in NETRC_FILES) + + try: + from netrc import NetrcParseError, netrc + + netrc_path = None + + for f in netrc_locations: + loc = os.path.expanduser(f) + if os.path.exists(loc): + netrc_path = loc + break + + # Abort early if there isn't one. + if netrc_path is None: + return + + ri = urlparse(url) + host = ri.hostname + + try: + _netrc = netrc(netrc_path).authenticators(host) + if _netrc: + # Return with login / password + login_i = 0 if _netrc[0] else 1 + return (_netrc[login_i], _netrc[2]) + except (NetrcParseError, OSError): + # If there was a parsing error or a permissions issue reading the file, + # we'll just skip netrc auth unless explicitly asked to raise errors. + if raise_errors: + raise + + # App Engine hackiness. + except (ImportError, AttributeError): + pass + + +def guess_filename(obj): + """Tries to guess the filename of the given object.""" + name = getattr(obj, "name", None) + if name and isinstance(name, basestring) and name[0] != "<" and name[-1] != ">": + return os.path.basename(name) + + +def extract_zipped_paths(path): + """Replace nonexistent paths that look like they refer to a member of a zip + archive with the location of an extracted copy of the target, or else + just return the provided path unchanged. + """ + if os.path.exists(path): + # this is already a valid path, no need to do anything further + return path + + # find the first valid part of the provided path and treat that as a zip archive + # assume the rest of the path is the name of a member in the archive + archive, member = os.path.split(path) + while archive and not os.path.exists(archive): + archive, prefix = os.path.split(archive) + if not prefix: + # If we don't check for an empty prefix after the split (in other words, archive remains unchanged after the split), + # we _can_ end up in an infinite loop on a rare corner case affecting a small number of users + break + member = "/".join([prefix, member]) + + if not zipfile.is_zipfile(archive): + return path + + zip_file = zipfile.ZipFile(archive) + if member not in zip_file.namelist(): + return path + + # we have a valid zip archive and a valid member of that archive + tmp = tempfile.gettempdir() + extracted_path = os.path.join(tmp, member.split("/")[-1]) + if not os.path.exists(extracted_path): + # use read + write to avoid the creating nested folders, we only want the file, avoids mkdir racing condition + with atomic_open(extracted_path) as file_handler: + file_handler.write(zip_file.read(member)) + return extracted_path + + +@contextlib.contextmanager +def atomic_open(filename): + """Write a file to the disk in an atomic fashion""" + tmp_descriptor, tmp_name = tempfile.mkstemp(dir=os.path.dirname(filename)) + try: + with os.fdopen(tmp_descriptor, "wb") as tmp_handler: + yield tmp_handler + os.replace(tmp_name, filename) + except BaseException: + os.remove(tmp_name) + raise + + +def from_key_val_list(value): + """Take an object and test to see if it can be represented as a + dictionary. Unless it can not be represented as such, return an + OrderedDict, e.g., + + :: + + >>> from_key_val_list([('key', 'val')]) + OrderedDict([('key', 'val')]) + >>> from_key_val_list('string') + Traceback (most recent call last): + ... + ValueError: cannot encode objects that are not 2-tuples + >>> from_key_val_list({'key': 'val'}) + OrderedDict([('key', 'val')]) + + :rtype: OrderedDict + """ + if value is None: + return None + + if isinstance(value, (str, bytes, bool, int)): + raise ValueError("cannot encode objects that are not 2-tuples") + + return OrderedDict(value) + + +def to_key_val_list(value): + """Take an object and test to see if it can be represented as a + dictionary. If it can be, return a list of tuples, e.g., + + :: + + >>> to_key_val_list([('key', 'val')]) + [('key', 'val')] + >>> to_key_val_list({'key': 'val'}) + [('key', 'val')] + >>> to_key_val_list('string') + Traceback (most recent call last): + ... + ValueError: cannot encode objects that are not 2-tuples + + :rtype: list + """ + if value is None: + return None + + if isinstance(value, (str, bytes, bool, int)): + raise ValueError("cannot encode objects that are not 2-tuples") + + if isinstance(value, Mapping): + value = value.items() + + return list(value) + + +# From mitsuhiko/werkzeug (used with permission). +def parse_list_header(value): + """Parse lists as described by RFC 2068 Section 2. + + In particular, parse comma-separated lists where the elements of + the list may include quoted-strings. A quoted-string could + contain a comma. A non-quoted string could have quotes in the + middle. Quotes are removed automatically after parsing. + + It basically works like :func:`parse_set_header` just that items + may appear multiple times and case sensitivity is preserved. + + The return value is a standard :class:`list`: + + >>> parse_list_header('token, "quoted value"') + ['token', 'quoted value'] + + To create a header from the :class:`list` again, use the + :func:`dump_header` function. + + :param value: a string with a list header. + :return: :class:`list` + :rtype: list + """ + result = [] + for item in _parse_list_header(value): + if item[:1] == item[-1:] == '"': + item = unquote_header_value(item[1:-1]) + result.append(item) + return result + + +# From mitsuhiko/werkzeug (used with permission). +def parse_dict_header(value): + """Parse lists of key, value pairs as described by RFC 2068 Section 2 and + convert them into a python dict: + + >>> d = parse_dict_header('foo="is a fish", bar="as well"') + >>> type(d) is dict + True + >>> sorted(d.items()) + [('bar', 'as well'), ('foo', 'is a fish')] + + If there is no value for a key it will be `None`: + + >>> parse_dict_header('key_without_value') + {'key_without_value': None} + + To create a header from the :class:`dict` again, use the + :func:`dump_header` function. + + :param value: a string with a dict header. + :return: :class:`dict` + :rtype: dict + """ + result = {} + for item in _parse_list_header(value): + if "=" not in item: + result[item] = None + continue + name, value = item.split("=", 1) + if value[:1] == value[-1:] == '"': + value = unquote_header_value(value[1:-1]) + result[name] = value + return result + + +# From mitsuhiko/werkzeug (used with permission). +def unquote_header_value(value, is_filename=False): + r"""Unquotes a header value. (Reversal of :func:`quote_header_value`). + This does not use the real unquoting but what browsers are actually + using for quoting. + + :param value: the header value to unquote. + :rtype: str + """ + if value and value[0] == value[-1] == '"': + # this is not the real unquoting, but fixing this so that the + # RFC is met will result in bugs with internet explorer and + # probably some other browsers as well. IE for example is + # uploading files with "C:\foo\bar.txt" as filename + value = value[1:-1] + + # if this is a filename and the starting characters look like + # a UNC path, then just return the value without quotes. Using the + # replace sequence below on a UNC path has the effect of turning + # the leading double slash into a single slash and then + # _fix_ie_filename() doesn't work correctly. See #458. + if not is_filename or value[:2] != "\\\\": + return value.replace("\\\\", "\\").replace('\\"', '"') + return value + + +def dict_from_cookiejar(cj): + """Returns a key/value dictionary from a CookieJar. + + :param cj: CookieJar object to extract cookies from. + :rtype: dict + """ + + cookie_dict = {cookie.name: cookie.value for cookie in cj} + return cookie_dict + + +def add_dict_to_cookiejar(cj, cookie_dict): + """Returns a CookieJar from a key/value dictionary. + + :param cj: CookieJar to insert cookies into. + :param cookie_dict: Dict of key/values to insert into CookieJar. + :rtype: CookieJar + """ + + return cookiejar_from_dict(cookie_dict, cj) + + +def get_encodings_from_content(content): + """Returns encodings from given content string. + + :param content: bytestring to extract encodings from. + """ + warnings.warn( + ( + "In requests 3.0, get_encodings_from_content will be removed. For " + "more information, please see the discussion on issue #2266. (This" + " warning should only appear once.)" + ), + DeprecationWarning, + ) + + charset_re = re.compile(r']', flags=re.I) + pragma_re = re.compile(r']', flags=re.I) + xml_re = re.compile(r'^<\?xml.*?encoding=["\']*(.+?)["\'>]') + + return ( + charset_re.findall(content) + + pragma_re.findall(content) + + xml_re.findall(content) + ) + + +def _parse_content_type_header(header): + """Returns content type and parameters from given header + + :param header: string + :return: tuple containing content type and dictionary of + parameters + """ + + tokens = header.split(";") + content_type, params = tokens[0].strip(), tokens[1:] + params_dict = {} + items_to_strip = "\"' " + + for param in params: + param = param.strip() + if param: + key, value = param, True + index_of_equals = param.find("=") + if index_of_equals != -1: + key = param[:index_of_equals].strip(items_to_strip) + value = param[index_of_equals + 1 :].strip(items_to_strip) + params_dict[key.lower()] = value + return content_type, params_dict + + +def get_encoding_from_headers(headers): + """Returns encodings from given HTTP Header Dict. + + :param headers: dictionary to extract encoding from. + :rtype: str + """ + + content_type = headers.get("content-type") + + if not content_type: + return None + + content_type, params = _parse_content_type_header(content_type) + + if "charset" in params: + return params["charset"].strip("'\"") + + if "text" in content_type: + return "ISO-8859-1" + + if "application/json" in content_type: + # Assume UTF-8 based on RFC 4627: https://www.ietf.org/rfc/rfc4627.txt since the charset was unset + return "utf-8" + + +def stream_decode_response_unicode(iterator, r): + """Stream decodes an iterator.""" + + if r.encoding is None: + yield from iterator + return + + decoder = codecs.getincrementaldecoder(r.encoding)(errors="replace") + for chunk in iterator: + rv = decoder.decode(chunk) + if rv: + yield rv + rv = decoder.decode(b"", final=True) + if rv: + yield rv + + +def iter_slices(string, slice_length): + """Iterate over slices of a string.""" + pos = 0 + if slice_length is None or slice_length <= 0: + slice_length = len(string) + while pos < len(string): + yield string[pos : pos + slice_length] + pos += slice_length + + +def get_unicode_from_response(r): + """Returns the requested content back in unicode. + + :param r: Response object to get unicode content from. + + Tried: + + 1. charset from content-type + 2. fall back and replace all unicode characters + + :rtype: str + """ + warnings.warn( + ( + "In requests 3.0, get_unicode_from_response will be removed. For " + "more information, please see the discussion on issue #2266. (This" + " warning should only appear once.)" + ), + DeprecationWarning, + ) + + tried_encodings = [] + + # Try charset from content-type + encoding = get_encoding_from_headers(r.headers) + + if encoding: + try: + return str(r.content, encoding) + except UnicodeError: + tried_encodings.append(encoding) + + # Fall back: + try: + return str(r.content, encoding, errors="replace") + except TypeError: + return r.content + + +# The unreserved URI characters (RFC 3986) +UNRESERVED_SET = frozenset( + "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz" + "0123456789-._~" +) + + +def unquote_unreserved(uri): + """Un-escape any percent-escape sequences in a URI that are unreserved + characters. This leaves all reserved, illegal and non-ASCII bytes encoded. + + :rtype: str + """ + parts = uri.split("%") + for i in range(1, len(parts)): + h = parts[i][0:2] + if len(h) == 2 and h.isalnum(): + try: + c = chr(int(h, 16)) + except ValueError: + raise InvalidURL(f"Invalid percent-escape sequence: '{h}'") + + if c in UNRESERVED_SET: + parts[i] = c + parts[i][2:] + else: + parts[i] = f"%{parts[i]}" + else: + parts[i] = f"%{parts[i]}" + return "".join(parts) + + +def requote_uri(uri): + """Re-quote the given URI. + + This function passes the given URI through an unquote/quote cycle to + ensure that it is fully and consistently quoted. + + :rtype: str + """ + safe_with_percent = "!#$%&'()*+,/:;=?@[]~" + safe_without_percent = "!#$&'()*+,/:;=?@[]~" + try: + # Unquote only the unreserved characters + # Then quote only illegal characters (do not quote reserved, + # unreserved, or '%') + return quote(unquote_unreserved(uri), safe=safe_with_percent) + except InvalidURL: + # We couldn't unquote the given URI, so let's try quoting it, but + # there may be unquoted '%'s in the URI. We need to make sure they're + # properly quoted so they do not cause issues elsewhere. + return quote(uri, safe=safe_without_percent) + + +def address_in_network(ip, net): + """This function allows you to check if an IP belongs to a network subnet + + Example: returns True if ip = 192.168.1.1 and net = 192.168.1.0/24 + returns False if ip = 192.168.1.1 and net = 192.168.100.0/24 + + :rtype: bool + """ + ipaddr = struct.unpack("=L", socket.inet_aton(ip))[0] + netaddr, bits = net.split("/") + netmask = struct.unpack("=L", socket.inet_aton(dotted_netmask(int(bits))))[0] + network = struct.unpack("=L", socket.inet_aton(netaddr))[0] & netmask + return (ipaddr & netmask) == (network & netmask) + + +def dotted_netmask(mask): + """Converts mask from /xx format to xxx.xxx.xxx.xxx + + Example: if mask is 24 function returns 255.255.255.0 + + :rtype: str + """ + bits = 0xFFFFFFFF ^ (1 << 32 - mask) - 1 + return socket.inet_ntoa(struct.pack(">I", bits)) + + +def is_ipv4_address(string_ip): + """ + :rtype: bool + """ + try: + socket.inet_aton(string_ip) + except OSError: + return False + return True + + +def is_valid_cidr(string_network): + """ + Very simple check of the cidr format in no_proxy variable. + + :rtype: bool + """ + if string_network.count("/") == 1: + try: + mask = int(string_network.split("/")[1]) + except ValueError: + return False + + if mask < 1 or mask > 32: + return False + + try: + socket.inet_aton(string_network.split("/")[0]) + except OSError: + return False + else: + return False + return True + + +@contextlib.contextmanager +def set_environ(env_name, value): + """Set the environment variable 'env_name' to 'value' + + Save previous value, yield, and then restore the previous value stored in + the environment variable 'env_name'. + + If 'value' is None, do nothing""" + value_changed = value is not None + if value_changed: + old_value = os.environ.get(env_name) + os.environ[env_name] = value + try: + yield + finally: + if value_changed: + if old_value is None: + del os.environ[env_name] + else: + os.environ[env_name] = old_value + + +def should_bypass_proxies(url, no_proxy): + """ + Returns whether we should bypass proxies or not. + + :rtype: bool + """ + + # Prioritize lowercase environment variables over uppercase + # to keep a consistent behaviour with other http projects (curl, wget). + def get_proxy(key): + return os.environ.get(key) or os.environ.get(key.upper()) + + # First check whether no_proxy is defined. If it is, check that the URL + # we're getting isn't in the no_proxy list. + no_proxy_arg = no_proxy + if no_proxy is None: + no_proxy = get_proxy("no_proxy") + parsed = urlparse(url) + + if parsed.hostname is None: + # URLs don't always have hostnames, e.g. file:/// urls. + return True + + if no_proxy: + # We need to check whether we match here. We need to see if we match + # the end of the hostname, both with and without the port. + no_proxy = (host for host in no_proxy.replace(" ", "").split(",") if host) + + if is_ipv4_address(parsed.hostname): + for proxy_ip in no_proxy: + if is_valid_cidr(proxy_ip): + if address_in_network(parsed.hostname, proxy_ip): + return True + elif parsed.hostname == proxy_ip: + # If no_proxy ip was defined in plain IP notation instead of cidr notation & + # matches the IP of the index + return True + else: + host_with_port = parsed.hostname + if parsed.port: + host_with_port += f":{parsed.port}" + + for host in no_proxy: + if parsed.hostname.endswith(host) or host_with_port.endswith(host): + # The URL does match something in no_proxy, so we don't want + # to apply the proxies on this URL. + return True + + with set_environ("no_proxy", no_proxy_arg): + # parsed.hostname can be `None` in cases such as a file URI. + try: + bypass = proxy_bypass(parsed.hostname) + except (TypeError, socket.gaierror): + bypass = False + + if bypass: + return True + + return False + + +def get_environ_proxies(url, no_proxy=None): + """ + Return a dict of environment proxies. + + :rtype: dict + """ + if should_bypass_proxies(url, no_proxy=no_proxy): + return {} + else: + return getproxies() + + +def select_proxy(url, proxies): + """Select a proxy for the url, if applicable. + + :param url: The url being for the request + :param proxies: A dictionary of schemes or schemes and hosts to proxy URLs + """ + proxies = proxies or {} + urlparts = urlparse(url) + if urlparts.hostname is None: + return proxies.get(urlparts.scheme, proxies.get("all")) + + proxy_keys = [ + urlparts.scheme + "://" + urlparts.hostname, + urlparts.scheme, + "all://" + urlparts.hostname, + "all", + ] + proxy = None + for proxy_key in proxy_keys: + if proxy_key in proxies: + proxy = proxies[proxy_key] + break + + return proxy + + +def resolve_proxies(request, proxies, trust_env=True): + """This method takes proxy information from a request and configuration + input to resolve a mapping of target proxies. This will consider settings + such as NO_PROXY to strip proxy configurations. + + :param request: Request or PreparedRequest + :param proxies: A dictionary of schemes or schemes and hosts to proxy URLs + :param trust_env: Boolean declaring whether to trust environment configs + + :rtype: dict + """ + proxies = proxies if proxies is not None else {} + url = request.url + scheme = urlparse(url).scheme + no_proxy = proxies.get("no_proxy") + new_proxies = proxies.copy() + + if trust_env and not should_bypass_proxies(url, no_proxy=no_proxy): + environ_proxies = get_environ_proxies(url, no_proxy=no_proxy) + + proxy = environ_proxies.get(scheme, environ_proxies.get("all")) + + if proxy: + new_proxies.setdefault(scheme, proxy) + return new_proxies + + +def default_user_agent(name="python-requests"): + """ + Return a string representing the default user agent. + + :rtype: str + """ + return f"{name}/{__version__}" + + +def default_headers(): + """ + :rtype: requests.structures.CaseInsensitiveDict + """ + return CaseInsensitiveDict( + { + "User-Agent": default_user_agent(), + "Accept-Encoding": DEFAULT_ACCEPT_ENCODING, + "Accept": "*/*", + "Connection": "keep-alive", + } + ) + + +def parse_header_links(value): + """Return a list of parsed link headers proxies. + + i.e. Link: ; rel=front; type="image/jpeg",; rel=back;type="image/jpeg" + + :rtype: list + """ + + links = [] + + replace_chars = " '\"" + + value = value.strip(replace_chars) + if not value: + return links + + for val in re.split(", *<", value): + try: + url, params = val.split(";", 1) + except ValueError: + url, params = val, "" + + link = {"url": url.strip("<> '\"")} + + for param in params.split(";"): + try: + key, value = param.split("=") + except ValueError: + break + + link[key.strip(replace_chars)] = value.strip(replace_chars) + + links.append(link) + + return links + + +# Null bytes; no need to recreate these on each call to guess_json_utf +_null = "\x00".encode("ascii") # encoding to ASCII for Python 3 +_null2 = _null * 2 +_null3 = _null * 3 + + +def guess_json_utf(data): + """ + :rtype: str + """ + # JSON always starts with two ASCII characters, so detection is as + # easy as counting the nulls and from their location and count + # determine the encoding. Also detect a BOM, if present. + sample = data[:4] + if sample in (codecs.BOM_UTF32_LE, codecs.BOM_UTF32_BE): + return "utf-32" # BOM included + if sample[:3] == codecs.BOM_UTF8: + return "utf-8-sig" # BOM included, MS style (discouraged) + if sample[:2] in (codecs.BOM_UTF16_LE, codecs.BOM_UTF16_BE): + return "utf-16" # BOM included + nullcount = sample.count(_null) + if nullcount == 0: + return "utf-8" + if nullcount == 2: + if sample[::2] == _null2: # 1st and 3rd are null + return "utf-16-be" + if sample[1::2] == _null2: # 2nd and 4th are null + return "utf-16-le" + # Did not detect 2 valid UTF-16 ascii-range characters + if nullcount == 3: + if sample[:3] == _null3: + return "utf-32-be" + if sample[1:] == _null3: + return "utf-32-le" + # Did not detect a valid UTF-32 ascii-range character + return None + + +def prepend_scheme_if_needed(url, new_scheme): + """Given a URL that may or may not have a scheme, prepend the given scheme. + Does not replace a present scheme with the one provided as an argument. + + :rtype: str + """ + parsed = parse_url(url) + scheme, auth, host, port, path, query, fragment = parsed + + # A defect in urlparse determines that there isn't a netloc present in some + # urls. We previously assumed parsing was overly cautious, and swapped the + # netloc and path. Due to a lack of tests on the original defect, this is + # maintained with parse_url for backwards compatibility. + netloc = parsed.netloc + if not netloc: + netloc, path = path, netloc + + if auth: + # parse_url doesn't provide the netloc with auth + # so we'll add it ourselves. + netloc = "@".join([auth, netloc]) + if scheme is None: + scheme = new_scheme + if path is None: + path = "" + + return urlunparse((scheme, netloc, path, "", query, fragment)) + + +def get_auth_from_url(url): + """Given a url with authentication components, extract them into a tuple of + username,password. + + :rtype: (str,str) + """ + parsed = urlparse(url) + + try: + auth = (unquote(parsed.username), unquote(parsed.password)) + except (AttributeError, TypeError): + auth = ("", "") + + return auth + + +def check_header_validity(header): + """Verifies that header parts don't contain leading whitespace + reserved characters, or return characters. + + :param header: tuple, in the format (name, value). + """ + name, value = header + _validate_header_part(header, name, 0) + _validate_header_part(header, value, 1) + + +def _validate_header_part(header, header_part, header_validator_index): + if isinstance(header_part, str): + validator = _HEADER_VALIDATORS_STR[header_validator_index] + elif isinstance(header_part, bytes): + validator = _HEADER_VALIDATORS_BYTE[header_validator_index] + else: + raise InvalidHeader( + f"Header part ({header_part!r}) from {header} " + f"must be of type str or bytes, not {type(header_part)}" + ) + + if not validator.match(header_part): + header_kind = "name" if header_validator_index == 0 else "value" + raise InvalidHeader( + f"Invalid leading whitespace, reserved character(s), or return " + f"character(s) in header {header_kind}: {header_part!r}" + ) + + +def urldefragauth(url): + """ + Given a url remove the fragment and the authentication part. + + :rtype: str + """ + scheme, netloc, path, params, query, fragment = urlparse(url) + + # see func:`prepend_scheme_if_needed` + if not netloc: + netloc, path = path, netloc + + netloc = netloc.rsplit("@", 1)[-1] + + return urlunparse((scheme, netloc, path, params, query, "")) + + +def rewind_body(prepared_request): + """Move file pointer back to its recorded starting position + so it can be read again on redirect. + """ + body_seek = getattr(prepared_request.body, "seek", None) + if body_seek is not None and isinstance( + prepared_request._body_position, integer_types + ): + try: + body_seek(prepared_request._body_position) + except OSError: + raise UnrewindableBodyError( + "An error occurred when rewinding request body for redirect." + ) + else: + raise UnrewindableBodyError("Unable to rewind request body for redirect.") diff --git a/rich/_emoji_codes.py b/rich/_emoji_codes.py new file mode 100644 index 0000000000000000000000000000000000000000..1f2877bb2bd520253502b1c05bb811bb0d7ef64c --- /dev/null +++ b/rich/_emoji_codes.py @@ -0,0 +1,3610 @@ +EMOJI = { + "1st_place_medal": "🥇", + "2nd_place_medal": "🥈", + "3rd_place_medal": "🥉", + "ab_button_(blood_type)": "🆎", + "atm_sign": "🏧", + "a_button_(blood_type)": "🅰", + "afghanistan": "🇦🇫", + "albania": "🇦🇱", + "algeria": "🇩🇿", + "american_samoa": "🇦🇸", + "andorra": "🇦🇩", + "angola": "🇦🇴", + "anguilla": "🇦🇮", + "antarctica": "🇦🇶", + "antigua_&_barbuda": "🇦🇬", + "aquarius": "♒", + "argentina": "🇦🇷", + "aries": "♈", + "armenia": "🇦🇲", + "aruba": "🇦🇼", + "ascension_island": "🇦🇨", + "australia": "🇦🇺", + "austria": "🇦🇹", + "azerbaijan": "🇦🇿", + "back_arrow": "🔙", + "b_button_(blood_type)": "🅱", + "bahamas": "🇧🇸", + "bahrain": "🇧🇭", + "bangladesh": "🇧🇩", + "barbados": "🇧🇧", + "belarus": "🇧🇾", + "belgium": "🇧🇪", + "belize": "🇧🇿", + "benin": "🇧🇯", + "bermuda": "🇧🇲", + "bhutan": "🇧🇹", + "bolivia": "🇧🇴", + "bosnia_&_herzegovina": "🇧🇦", + "botswana": "🇧🇼", + "bouvet_island": "🇧🇻", + "brazil": "🇧🇷", + "british_indian_ocean_territory": "🇮🇴", + "british_virgin_islands": "🇻🇬", + "brunei": "🇧🇳", + "bulgaria": "🇧🇬", + "burkina_faso": "🇧🇫", + "burundi": "🇧🇮", + "cl_button": "🆑", + "cool_button": "🆒", + "cambodia": "🇰🇭", + "cameroon": "🇨🇲", + "canada": "🇨🇦", + "canary_islands": "🇮🇨", + "cancer": "♋", + "cape_verde": "🇨🇻", + "capricorn": "♑", + "caribbean_netherlands": "🇧🇶", + "cayman_islands": "🇰🇾", + "central_african_republic": "🇨🇫", + "ceuta_&_melilla": "🇪🇦", + "chad": "🇹🇩", + "chile": "🇨🇱", + "china": "🇨🇳", + "christmas_island": "🇨🇽", + "christmas_tree": "🎄", + "clipperton_island": "🇨🇵", + "cocos_(keeling)_islands": "🇨🇨", + "colombia": "🇨🇴", + "comoros": "🇰🇲", + "congo_-_brazzaville": "🇨🇬", + "congo_-_kinshasa": "🇨🇩", + "cook_islands": "🇨🇰", + "costa_rica": "🇨🇷", + "croatia": "🇭🇷", + "cuba": "🇨🇺", + "curaçao": "🇨🇼", + "cyprus": "🇨🇾", + "czechia": "🇨🇿", + "côte_d’ivoire": "🇨🇮", + "denmark": "🇩🇰", + "diego_garcia": "🇩🇬", + "djibouti": "🇩🇯", + "dominica": "🇩🇲", + "dominican_republic": "🇩🇴", + "end_arrow": "🔚", + "ecuador": "🇪🇨", + "egypt": "🇪🇬", + "el_salvador": "🇸🇻", + "england": "🏴\U000e0067\U000e0062\U000e0065\U000e006e\U000e0067\U000e007f", + "equatorial_guinea": "🇬🇶", + "eritrea": "🇪🇷", + "estonia": "🇪🇪", + "ethiopia": "🇪🇹", + "european_union": "🇪🇺", + "free_button": "🆓", + "falkland_islands": "🇫🇰", + "faroe_islands": "🇫🇴", + "fiji": "🇫🇯", + "finland": "🇫🇮", + "france": "🇫🇷", + "french_guiana": "🇬🇫", + "french_polynesia": "🇵🇫", + "french_southern_territories": "🇹🇫", + "gabon": "🇬🇦", + "gambia": "🇬🇲", + "gemini": "♊", + "georgia": "🇬🇪", + "germany": "🇩🇪", + "ghana": "🇬🇭", + "gibraltar": "🇬🇮", + "greece": "🇬🇷", + "greenland": "🇬🇱", + "grenada": "🇬🇩", + "guadeloupe": "🇬🇵", + "guam": "🇬🇺", + "guatemala": "🇬🇹", + "guernsey": "🇬🇬", + "guinea": "🇬🇳", + "guinea-bissau": "🇬🇼", + "guyana": "🇬🇾", + "haiti": "🇭🇹", + "heard_&_mcdonald_islands": "🇭🇲", + "honduras": "🇭🇳", + "hong_kong_sar_china": "🇭🇰", + "hungary": "🇭🇺", + "id_button": "🆔", + "iceland": "🇮🇸", + "india": "🇮🇳", + "indonesia": "🇮🇩", + "iran": "🇮🇷", + "iraq": "🇮🇶", + "ireland": "🇮🇪", + "isle_of_man": "🇮🇲", + "israel": "🇮🇱", + "italy": "🇮🇹", + "jamaica": "🇯🇲", + "japan": "🗾", + "japanese_acceptable_button": "🉑", + "japanese_application_button": "🈸", + "japanese_bargain_button": "🉐", + "japanese_castle": "🏯", + "japanese_congratulations_button": "㊗", + "japanese_discount_button": "🈹", + "japanese_dolls": "🎎", + "japanese_free_of_charge_button": "🈚", + "japanese_here_button": "🈁", + "japanese_monthly_amount_button": "🈷", + "japanese_no_vacancy_button": "🈵", + "japanese_not_free_of_charge_button": "🈶", + "japanese_open_for_business_button": "🈺", + "japanese_passing_grade_button": "🈴", + "japanese_post_office": "🏣", + "japanese_prohibited_button": "🈲", + "japanese_reserved_button": "🈯", + "japanese_secret_button": "㊙", + "japanese_service_charge_button": "🈂", + "japanese_symbol_for_beginner": "🔰", + "japanese_vacancy_button": "🈳", + "jersey": "🇯🇪", + "jordan": "🇯🇴", + "kazakhstan": "🇰🇿", + "kenya": "🇰🇪", + "kiribati": "🇰🇮", + "kosovo": "🇽🇰", + "kuwait": "🇰🇼", + "kyrgyzstan": "🇰🇬", + "laos": "🇱🇦", + "latvia": "🇱🇻", + "lebanon": "🇱🇧", + "leo": "♌", + "lesotho": "🇱🇸", + "liberia": "🇱🇷", + "libra": "♎", + "libya": "🇱🇾", + "liechtenstein": "🇱🇮", + "lithuania": "🇱🇹", + "luxembourg": "🇱🇺", + "macau_sar_china": "🇲🇴", + "macedonia": "🇲🇰", + "madagascar": "🇲🇬", + "malawi": "🇲🇼", + "malaysia": "🇲🇾", + "maldives": "🇲🇻", + "mali": "🇲🇱", + "malta": "🇲🇹", + "marshall_islands": "🇲🇭", + "martinique": "🇲🇶", + "mauritania": "🇲🇷", + "mauritius": "🇲🇺", + "mayotte": "🇾🇹", + "mexico": "🇲🇽", + "micronesia": "🇫🇲", + "moldova": "🇲🇩", + "monaco": "🇲🇨", + "mongolia": "🇲🇳", + "montenegro": "🇲🇪", + "montserrat": "🇲🇸", + "morocco": "🇲🇦", + "mozambique": "🇲🇿", + "mrs._claus": "🤶", + "mrs._claus_dark_skin_tone": "🤶🏿", + "mrs._claus_light_skin_tone": "🤶🏻", + "mrs._claus_medium-dark_skin_tone": "🤶🏾", + "mrs._claus_medium-light_skin_tone": "🤶🏼", + "mrs._claus_medium_skin_tone": "🤶🏽", + "myanmar_(burma)": "🇲🇲", + "new_button": "🆕", + "ng_button": "🆖", + "namibia": "🇳🇦", + "nauru": "🇳🇷", + "nepal": "🇳🇵", + "netherlands": "🇳🇱", + "new_caledonia": "🇳🇨", + "new_zealand": "🇳🇿", + "nicaragua": "🇳🇮", + "niger": "🇳🇪", + "nigeria": "🇳🇬", + "niue": "🇳🇺", + "norfolk_island": "🇳🇫", + "north_korea": "🇰🇵", + "northern_mariana_islands": "🇲🇵", + "norway": "🇳🇴", + "ok_button": "🆗", + "ok_hand": "👌", + "ok_hand_dark_skin_tone": "👌🏿", + "ok_hand_light_skin_tone": "👌🏻", + "ok_hand_medium-dark_skin_tone": "👌🏾", + "ok_hand_medium-light_skin_tone": "👌🏼", + "ok_hand_medium_skin_tone": "👌🏽", + "on!_arrow": "🔛", + "o_button_(blood_type)": "🅾", + "oman": "🇴🇲", + "ophiuchus": "⛎", + "p_button": "🅿", + "pakistan": "🇵🇰", + "palau": "🇵🇼", + "palestinian_territories": "🇵🇸", + "panama": "🇵🇦", + "papua_new_guinea": "🇵🇬", + "paraguay": "🇵🇾", + "peru": "🇵🇪", + "philippines": "🇵🇭", + "pisces": "♓", + "pitcairn_islands": "🇵🇳", + "poland": "🇵🇱", + "portugal": "🇵🇹", + "puerto_rico": "🇵🇷", + "qatar": "🇶🇦", + "romania": "🇷🇴", + "russia": "🇷🇺", + "rwanda": "🇷🇼", + "réunion": "🇷🇪", + "soon_arrow": "🔜", + "sos_button": "🆘", + "sagittarius": "♐", + "samoa": "🇼🇸", + "san_marino": "🇸🇲", + "santa_claus": "🎅", + "santa_claus_dark_skin_tone": "🎅🏿", + "santa_claus_light_skin_tone": "🎅🏻", + "santa_claus_medium-dark_skin_tone": "🎅🏾", + "santa_claus_medium-light_skin_tone": "🎅🏼", + "santa_claus_medium_skin_tone": "🎅🏽", + "saudi_arabia": "🇸🇦", + "scorpio": "♏", + "scotland": "🏴\U000e0067\U000e0062\U000e0073\U000e0063\U000e0074\U000e007f", + "senegal": "🇸🇳", + "serbia": "🇷🇸", + "seychelles": "🇸🇨", + "sierra_leone": "🇸🇱", + "singapore": "🇸🇬", + "sint_maarten": "🇸🇽", + "slovakia": "🇸🇰", + "slovenia": "🇸🇮", + "solomon_islands": "🇸🇧", + "somalia": "🇸🇴", + "south_africa": "🇿🇦", + "south_georgia_&_south_sandwich_islands": "🇬🇸", + "south_korea": "🇰🇷", + "south_sudan": "🇸🇸", + "spain": "🇪🇸", + "sri_lanka": "🇱🇰", + "st._barthélemy": "🇧🇱", + "st._helena": "🇸🇭", + "st._kitts_&_nevis": "🇰🇳", + "st._lucia": "🇱🇨", + "st._martin": "🇲🇫", + "st._pierre_&_miquelon": "🇵🇲", + "st._vincent_&_grenadines": "🇻🇨", + "statue_of_liberty": "🗽", + "sudan": "🇸🇩", + "suriname": "🇸🇷", + "svalbard_&_jan_mayen": "🇸🇯", + "swaziland": "🇸🇿", + "sweden": "🇸🇪", + "switzerland": "🇨🇭", + "syria": "🇸🇾", + "são_tomé_&_príncipe": "🇸🇹", + "t-rex": "🦖", + "top_arrow": "🔝", + "taiwan": "🇹🇼", + "tajikistan": "🇹🇯", + "tanzania": "🇹🇿", + "taurus": "♉", + "thailand": "🇹🇭", + "timor-leste": "🇹🇱", + "togo": "🇹🇬", + "tokelau": "🇹🇰", + "tokyo_tower": "🗼", + "tonga": "🇹🇴", + "trinidad_&_tobago": "🇹🇹", + "tristan_da_cunha": "🇹🇦", + "tunisia": "🇹🇳", + "turkey": "🦃", + "turkmenistan": "🇹🇲", + "turks_&_caicos_islands": "🇹🇨", + "tuvalu": "🇹🇻", + "u.s._outlying_islands": "🇺🇲", + "u.s._virgin_islands": "🇻🇮", + "up!_button": "🆙", + "uganda": "🇺🇬", + "ukraine": "🇺🇦", + "united_arab_emirates": "🇦🇪", + "united_kingdom": "🇬🇧", + "united_nations": "🇺🇳", + "united_states": "🇺🇸", + "uruguay": "🇺🇾", + "uzbekistan": "🇺🇿", + "vs_button": "🆚", + "vanuatu": "🇻🇺", + "vatican_city": "🇻🇦", + "venezuela": "🇻🇪", + "vietnam": "🇻🇳", + "virgo": "♍", + "wales": "🏴\U000e0067\U000e0062\U000e0077\U000e006c\U000e0073\U000e007f", + "wallis_&_futuna": "🇼🇫", + "western_sahara": "🇪🇭", + "yemen": "🇾🇪", + "zambia": "🇿🇲", + "zimbabwe": "🇿🇼", + "abacus": "🧮", + "adhesive_bandage": "🩹", + "admission_tickets": "🎟", + "adult": "🧑", + "adult_dark_skin_tone": "🧑🏿", + "adult_light_skin_tone": "🧑🏻", + "adult_medium-dark_skin_tone": "🧑🏾", + "adult_medium-light_skin_tone": "🧑🏼", + "adult_medium_skin_tone": "🧑🏽", + "aerial_tramway": "🚡", + "airplane": "✈", + "airplane_arrival": "🛬", + "airplane_departure": "🛫", + "alarm_clock": "⏰", + "alembic": "⚗", + "alien": "👽", + "alien_monster": "👾", + "ambulance": "🚑", + "american_football": "🏈", + "amphora": "🏺", + "anchor": "⚓", + "anger_symbol": "💢", + "angry_face": "😠", + "angry_face_with_horns": "👿", + "anguished_face": "😧", + "ant": "🐜", + "antenna_bars": "📶", + "anxious_face_with_sweat": "😰", + "articulated_lorry": "🚛", + "artist_palette": "🎨", + "astonished_face": "😲", + "atom_symbol": "⚛", + "auto_rickshaw": "🛺", + "automobile": "🚗", + "avocado": "🥑", + "axe": "🪓", + "baby": "👶", + "baby_angel": "👼", + "baby_angel_dark_skin_tone": "👼🏿", + "baby_angel_light_skin_tone": "👼🏻", + "baby_angel_medium-dark_skin_tone": "👼🏾", + "baby_angel_medium-light_skin_tone": "👼🏼", + "baby_angel_medium_skin_tone": "👼🏽", + "baby_bottle": "🍼", + "baby_chick": "🐤", + "baby_dark_skin_tone": "👶🏿", + "baby_light_skin_tone": "👶🏻", + "baby_medium-dark_skin_tone": "👶🏾", + "baby_medium-light_skin_tone": "👶🏼", + "baby_medium_skin_tone": "👶🏽", + "baby_symbol": "🚼", + "backhand_index_pointing_down": "👇", + "backhand_index_pointing_down_dark_skin_tone": "👇🏿", + "backhand_index_pointing_down_light_skin_tone": "👇🏻", + "backhand_index_pointing_down_medium-dark_skin_tone": "👇🏾", + "backhand_index_pointing_down_medium-light_skin_tone": "👇🏼", + "backhand_index_pointing_down_medium_skin_tone": "👇🏽", + "backhand_index_pointing_left": "👈", + "backhand_index_pointing_left_dark_skin_tone": "👈🏿", + "backhand_index_pointing_left_light_skin_tone": "👈🏻", + "backhand_index_pointing_left_medium-dark_skin_tone": "👈🏾", + "backhand_index_pointing_left_medium-light_skin_tone": "👈🏼", + "backhand_index_pointing_left_medium_skin_tone": "👈🏽", + "backhand_index_pointing_right": "👉", + "backhand_index_pointing_right_dark_skin_tone": "👉🏿", + "backhand_index_pointing_right_light_skin_tone": "👉🏻", + "backhand_index_pointing_right_medium-dark_skin_tone": "👉🏾", + "backhand_index_pointing_right_medium-light_skin_tone": "👉🏼", + "backhand_index_pointing_right_medium_skin_tone": "👉🏽", + "backhand_index_pointing_up": "👆", + "backhand_index_pointing_up_dark_skin_tone": "👆🏿", + "backhand_index_pointing_up_light_skin_tone": "👆🏻", + "backhand_index_pointing_up_medium-dark_skin_tone": "👆🏾", + "backhand_index_pointing_up_medium-light_skin_tone": "👆🏼", + "backhand_index_pointing_up_medium_skin_tone": "👆🏽", + "bacon": "🥓", + "badger": "🦡", + "badminton": "🏸", + "bagel": "🥯", + "baggage_claim": "🛄", + "baguette_bread": "🥖", + "balance_scale": "⚖", + "bald": "🦲", + "bald_man": "👨\u200d🦲", + "bald_woman": "👩\u200d🦲", + "ballet_shoes": "🩰", + "balloon": "🎈", + "ballot_box_with_ballot": "🗳", + "ballot_box_with_check": "☑", + "banana": "🍌", + "banjo": "🪕", + "bank": "🏦", + "bar_chart": "📊", + "barber_pole": "💈", + "baseball": "⚾", + "basket": "🧺", + "basketball": "🏀", + "bat": "🦇", + "bathtub": "🛁", + "battery": "🔋", + "beach_with_umbrella": "🏖", + "beaming_face_with_smiling_eyes": "😁", + "bear_face": "🐻", + "bearded_person": "🧔", + "bearded_person_dark_skin_tone": "🧔🏿", + "bearded_person_light_skin_tone": "🧔🏻", + "bearded_person_medium-dark_skin_tone": "🧔🏾", + "bearded_person_medium-light_skin_tone": "🧔🏼", + "bearded_person_medium_skin_tone": "🧔🏽", + "beating_heart": "💓", + "bed": "🛏", + "beer_mug": "🍺", + "bell": "🔔", + "bell_with_slash": "🔕", + "bellhop_bell": "🛎", + "bento_box": "🍱", + "beverage_box": "🧃", + "bicycle": "🚲", + "bikini": "👙", + "billed_cap": "🧢", + "biohazard": "☣", + "bird": "🐦", + "birthday_cake": "🎂", + "black_circle": "⚫", + "black_flag": "🏴", + "black_heart": "🖤", + "black_large_square": "⬛", + "black_medium-small_square": "◾", + "black_medium_square": "◼", + "black_nib": "✒", + "black_small_square": "▪", + "black_square_button": "🔲", + "blond-haired_man": "👱\u200d♂️", + "blond-haired_man_dark_skin_tone": "👱🏿\u200d♂️", + "blond-haired_man_light_skin_tone": "👱🏻\u200d♂️", + "blond-haired_man_medium-dark_skin_tone": "👱🏾\u200d♂️", + "blond-haired_man_medium-light_skin_tone": "👱🏼\u200d♂️", + "blond-haired_man_medium_skin_tone": "👱🏽\u200d♂️", + "blond-haired_person": "👱", + "blond-haired_person_dark_skin_tone": "👱🏿", + "blond-haired_person_light_skin_tone": "👱🏻", + "blond-haired_person_medium-dark_skin_tone": "👱🏾", + "blond-haired_person_medium-light_skin_tone": "👱🏼", + "blond-haired_person_medium_skin_tone": "👱🏽", + "blond-haired_woman": "👱\u200d♀️", + "blond-haired_woman_dark_skin_tone": "👱🏿\u200d♀️", + "blond-haired_woman_light_skin_tone": "👱🏻\u200d♀️", + "blond-haired_woman_medium-dark_skin_tone": "👱🏾\u200d♀️", + "blond-haired_woman_medium-light_skin_tone": "👱🏼\u200d♀️", + "blond-haired_woman_medium_skin_tone": "👱🏽\u200d♀️", + "blossom": "🌼", + "blowfish": "🐡", + "blue_book": "📘", + "blue_circle": "🔵", + "blue_heart": "💙", + "blue_square": "🟦", + "boar": "🐗", + "bomb": "💣", + "bone": "🦴", + "bookmark": "🔖", + "bookmark_tabs": "📑", + "books": "📚", + "bottle_with_popping_cork": "🍾", + "bouquet": "💐", + "bow_and_arrow": "🏹", + "bowl_with_spoon": "🥣", + "bowling": "🎳", + "boxing_glove": "🥊", + "boy": "👦", + "boy_dark_skin_tone": "👦🏿", + "boy_light_skin_tone": "👦🏻", + "boy_medium-dark_skin_tone": "👦🏾", + "boy_medium-light_skin_tone": "👦🏼", + "boy_medium_skin_tone": "👦🏽", + "brain": "🧠", + "bread": "🍞", + "breast-feeding": "🤱", + "breast-feeding_dark_skin_tone": "🤱🏿", + "breast-feeding_light_skin_tone": "🤱🏻", + "breast-feeding_medium-dark_skin_tone": "🤱🏾", + "breast-feeding_medium-light_skin_tone": "🤱🏼", + "breast-feeding_medium_skin_tone": "🤱🏽", + "brick": "🧱", + "bride_with_veil": "👰", + "bride_with_veil_dark_skin_tone": "👰🏿", + "bride_with_veil_light_skin_tone": "👰🏻", + "bride_with_veil_medium-dark_skin_tone": "👰🏾", + "bride_with_veil_medium-light_skin_tone": "👰🏼", + "bride_with_veil_medium_skin_tone": "👰🏽", + "bridge_at_night": "🌉", + "briefcase": "💼", + "briefs": "🩲", + "bright_button": "🔆", + "broccoli": "🥦", + "broken_heart": "💔", + "broom": "🧹", + "brown_circle": "🟤", + "brown_heart": "🤎", + "brown_square": "🟫", + "bug": "🐛", + "building_construction": "🏗", + "bullet_train": "🚅", + "burrito": "🌯", + "bus": "🚌", + "bus_stop": "🚏", + "bust_in_silhouette": "👤", + "busts_in_silhouette": "👥", + "butter": "🧈", + "butterfly": "🦋", + "cactus": "🌵", + "calendar": "📆", + "call_me_hand": "🤙", + "call_me_hand_dark_skin_tone": "🤙🏿", + "call_me_hand_light_skin_tone": "🤙🏻", + "call_me_hand_medium-dark_skin_tone": "🤙🏾", + "call_me_hand_medium-light_skin_tone": "🤙🏼", + "call_me_hand_medium_skin_tone": "🤙🏽", + "camel": "🐫", + "camera": "📷", + "camera_with_flash": "📸", + "camping": "🏕", + "candle": "🕯", + "candy": "🍬", + "canned_food": "🥫", + "canoe": "🛶", + "card_file_box": "🗃", + "card_index": "📇", + "card_index_dividers": "🗂", + "carousel_horse": "🎠", + "carp_streamer": "🎏", + "carrot": "🥕", + "castle": "🏰", + "cat": "🐱", + "cat_face": "🐱", + "cat_face_with_tears_of_joy": "😹", + "cat_face_with_wry_smile": "😼", + "chains": "⛓", + "chair": "🪑", + "chart_decreasing": "📉", + "chart_increasing": "📈", + "chart_increasing_with_yen": "💹", + "cheese_wedge": "🧀", + "chequered_flag": "🏁", + "cherries": "🍒", + "cherry_blossom": "🌸", + "chess_pawn": "♟", + "chestnut": "🌰", + "chicken": "🐔", + "child": "🧒", + "child_dark_skin_tone": "🧒🏿", + "child_light_skin_tone": "🧒🏻", + "child_medium-dark_skin_tone": "🧒🏾", + "child_medium-light_skin_tone": "🧒🏼", + "child_medium_skin_tone": "🧒🏽", + "children_crossing": "🚸", + "chipmunk": "🐿", + "chocolate_bar": "🍫", + "chopsticks": "🥢", + "church": "⛪", + "cigarette": "🚬", + "cinema": "🎦", + "circled_m": "Ⓜ", + "circus_tent": "🎪", + "cityscape": "🏙", + "cityscape_at_dusk": "🌆", + "clamp": "🗜", + "clapper_board": "🎬", + "clapping_hands": "👏", + "clapping_hands_dark_skin_tone": "👏🏿", + "clapping_hands_light_skin_tone": "👏🏻", + "clapping_hands_medium-dark_skin_tone": "👏🏾", + "clapping_hands_medium-light_skin_tone": "👏🏼", + "clapping_hands_medium_skin_tone": "👏🏽", + "classical_building": "🏛", + "clinking_beer_mugs": "🍻", + "clinking_glasses": "🥂", + "clipboard": "📋", + "clockwise_vertical_arrows": "🔃", + "closed_book": "📕", + "closed_mailbox_with_lowered_flag": "📪", + "closed_mailbox_with_raised_flag": "📫", + "closed_umbrella": "🌂", + "cloud": "☁", + "cloud_with_lightning": "🌩", + "cloud_with_lightning_and_rain": "⛈", + "cloud_with_rain": "🌧", + "cloud_with_snow": "🌨", + "clown_face": "🤡", + "club_suit": "♣", + "clutch_bag": "👝", + "coat": "🧥", + "cocktail_glass": "🍸", + "coconut": "🥥", + "coffin": "⚰", + "cold_face": "🥶", + "collision": "💥", + "comet": "☄", + "compass": "🧭", + "computer_disk": "💽", + "computer_mouse": "🖱", + "confetti_ball": "🎊", + "confounded_face": "😖", + "confused_face": "😕", + "construction": "🚧", + "construction_worker": "👷", + "construction_worker_dark_skin_tone": "👷🏿", + "construction_worker_light_skin_tone": "👷🏻", + "construction_worker_medium-dark_skin_tone": "👷🏾", + "construction_worker_medium-light_skin_tone": "👷🏼", + "construction_worker_medium_skin_tone": "👷🏽", + "control_knobs": "🎛", + "convenience_store": "🏪", + "cooked_rice": "🍚", + "cookie": "🍪", + "cooking": "🍳", + "copyright": "©", + "couch_and_lamp": "🛋", + "counterclockwise_arrows_button": "🔄", + "couple_with_heart": "💑", + "couple_with_heart_man_man": "👨\u200d❤️\u200d👨", + "couple_with_heart_woman_man": "👩\u200d❤️\u200d👨", + "couple_with_heart_woman_woman": "👩\u200d❤️\u200d👩", + "cow": "🐮", + "cow_face": "🐮", + "cowboy_hat_face": "🤠", + "crab": "🦀", + "crayon": "🖍", + "credit_card": "💳", + "crescent_moon": "🌙", + "cricket": "🦗", + "cricket_game": "🏏", + "crocodile": "🐊", + "croissant": "🥐", + "cross_mark": "❌", + "cross_mark_button": "❎", + "crossed_fingers": "🤞", + "crossed_fingers_dark_skin_tone": "🤞🏿", + "crossed_fingers_light_skin_tone": "🤞🏻", + "crossed_fingers_medium-dark_skin_tone": "🤞🏾", + "crossed_fingers_medium-light_skin_tone": "🤞🏼", + "crossed_fingers_medium_skin_tone": "🤞🏽", + "crossed_flags": "🎌", + "crossed_swords": "⚔", + "crown": "👑", + "crying_cat_face": "😿", + "crying_face": "😢", + "crystal_ball": "🔮", + "cucumber": "🥒", + "cupcake": "🧁", + "cup_with_straw": "🥤", + "curling_stone": "🥌", + "curly_hair": "🦱", + "curly-haired_man": "👨\u200d🦱", + "curly-haired_woman": "👩\u200d🦱", + "curly_loop": "➰", + "currency_exchange": "💱", + "curry_rice": "🍛", + "custard": "🍮", + "customs": "🛃", + "cut_of_meat": "🥩", + "cyclone": "🌀", + "dagger": "🗡", + "dango": "🍡", + "dashing_away": "💨", + "deaf_person": "🧏", + "deciduous_tree": "🌳", + "deer": "🦌", + "delivery_truck": "🚚", + "department_store": "🏬", + "derelict_house": "🏚", + "desert": "🏜", + "desert_island": "🏝", + "desktop_computer": "🖥", + "detective": "🕵", + "detective_dark_skin_tone": "🕵🏿", + "detective_light_skin_tone": "🕵🏻", + "detective_medium-dark_skin_tone": "🕵🏾", + "detective_medium-light_skin_tone": "🕵🏼", + "detective_medium_skin_tone": "🕵🏽", + "diamond_suit": "♦", + "diamond_with_a_dot": "💠", + "dim_button": "🔅", + "direct_hit": "🎯", + "disappointed_face": "😞", + "diving_mask": "🤿", + "diya_lamp": "🪔", + "dizzy": "💫", + "dizzy_face": "😵", + "dna": "🧬", + "dog": "🐶", + "dog_face": "🐶", + "dollar_banknote": "💵", + "dolphin": "🐬", + "door": "🚪", + "dotted_six-pointed_star": "🔯", + "double_curly_loop": "➿", + "double_exclamation_mark": "‼", + "doughnut": "🍩", + "dove": "🕊", + "down-left_arrow": "↙", + "down-right_arrow": "↘", + "down_arrow": "⬇", + "downcast_face_with_sweat": "😓", + "downwards_button": "🔽", + "dragon": "🐉", + "dragon_face": "🐲", + "dress": "👗", + "drooling_face": "🤤", + "drop_of_blood": "🩸", + "droplet": "💧", + "drum": "🥁", + "duck": "🦆", + "dumpling": "🥟", + "dvd": "📀", + "e-mail": "📧", + "eagle": "🦅", + "ear": "👂", + "ear_dark_skin_tone": "👂🏿", + "ear_light_skin_tone": "👂🏻", + "ear_medium-dark_skin_tone": "👂🏾", + "ear_medium-light_skin_tone": "👂🏼", + "ear_medium_skin_tone": "👂🏽", + "ear_of_corn": "🌽", + "ear_with_hearing_aid": "🦻", + "egg": "🍳", + "eggplant": "🍆", + "eight-pointed_star": "✴", + "eight-spoked_asterisk": "✳", + "eight-thirty": "🕣", + "eight_o’clock": "🕗", + "eject_button": "⏏", + "electric_plug": "🔌", + "elephant": "🐘", + "eleven-thirty": "🕦", + "eleven_o’clock": "🕚", + "elf": "🧝", + "elf_dark_skin_tone": "🧝🏿", + "elf_light_skin_tone": "🧝🏻", + "elf_medium-dark_skin_tone": "🧝🏾", + "elf_medium-light_skin_tone": "🧝🏼", + "elf_medium_skin_tone": "🧝🏽", + "envelope": "✉", + "envelope_with_arrow": "📩", + "euro_banknote": "💶", + "evergreen_tree": "🌲", + "ewe": "🐑", + "exclamation_mark": "❗", + "exclamation_question_mark": "⁉", + "exploding_head": "🤯", + "expressionless_face": "😑", + "eye": "👁", + "eye_in_speech_bubble": "👁️\u200d🗨️", + "eyes": "👀", + "face_blowing_a_kiss": "😘", + "face_savoring_food": "😋", + "face_screaming_in_fear": "😱", + "face_vomiting": "🤮", + "face_with_hand_over_mouth": "🤭", + "face_with_head-bandage": "🤕", + "face_with_medical_mask": "😷", + "face_with_monocle": "🧐", + "face_with_open_mouth": "😮", + "face_with_raised_eyebrow": "🤨", + "face_with_rolling_eyes": "🙄", + "face_with_steam_from_nose": "😤", + "face_with_symbols_on_mouth": "🤬", + "face_with_tears_of_joy": "😂", + "face_with_thermometer": "🤒", + "face_with_tongue": "😛", + "face_without_mouth": "😶", + "factory": "🏭", + "fairy": "🧚", + "fairy_dark_skin_tone": "🧚🏿", + "fairy_light_skin_tone": "🧚🏻", + "fairy_medium-dark_skin_tone": "🧚🏾", + "fairy_medium-light_skin_tone": "🧚🏼", + "fairy_medium_skin_tone": "🧚🏽", + "falafel": "🧆", + "fallen_leaf": "🍂", + "family": "👪", + "family_man_boy": "👨\u200d👦", + "family_man_boy_boy": "👨\u200d👦\u200d👦", + "family_man_girl": "👨\u200d👧", + "family_man_girl_boy": "👨\u200d👧\u200d👦", + "family_man_girl_girl": "👨\u200d👧\u200d👧", + "family_man_man_boy": "👨\u200d👨\u200d👦", + "family_man_man_boy_boy": "👨\u200d👨\u200d👦\u200d👦", + "family_man_man_girl": "👨\u200d👨\u200d👧", + "family_man_man_girl_boy": "👨\u200d👨\u200d👧\u200d👦", + "family_man_man_girl_girl": "👨\u200d👨\u200d👧\u200d👧", + "family_man_woman_boy": "👨\u200d👩\u200d👦", + "family_man_woman_boy_boy": "👨\u200d👩\u200d👦\u200d👦", + "family_man_woman_girl": "👨\u200d👩\u200d👧", + "family_man_woman_girl_boy": "👨\u200d👩\u200d👧\u200d👦", + "family_man_woman_girl_girl": "👨\u200d👩\u200d👧\u200d👧", + "family_woman_boy": "👩\u200d👦", + "family_woman_boy_boy": "👩\u200d👦\u200d👦", + "family_woman_girl": "👩\u200d👧", + "family_woman_girl_boy": "👩\u200d👧\u200d👦", + "family_woman_girl_girl": "👩\u200d👧\u200d👧", + "family_woman_woman_boy": "👩\u200d👩\u200d👦", + "family_woman_woman_boy_boy": "👩\u200d👩\u200d👦\u200d👦", + "family_woman_woman_girl": "👩\u200d👩\u200d👧", + "family_woman_woman_girl_boy": "👩\u200d👩\u200d👧\u200d👦", + "family_woman_woman_girl_girl": "👩\u200d👩\u200d👧\u200d👧", + "fast-forward_button": "⏩", + "fast_down_button": "⏬", + "fast_reverse_button": "⏪", + "fast_up_button": "⏫", + "fax_machine": "📠", + "fearful_face": "😨", + "female_sign": "♀", + "ferris_wheel": "🎡", + "ferry": "⛴", + "field_hockey": "🏑", + "file_cabinet": "🗄", + "file_folder": "📁", + "film_frames": "🎞", + "film_projector": "📽", + "fire": "🔥", + "fire_extinguisher": "🧯", + "firecracker": "🧨", + "fire_engine": "🚒", + "fireworks": "🎆", + "first_quarter_moon": "🌓", + "first_quarter_moon_face": "🌛", + "fish": "🐟", + "fish_cake_with_swirl": "🍥", + "fishing_pole": "🎣", + "five-thirty": "🕠", + "five_o’clock": "🕔", + "flag_in_hole": "⛳", + "flamingo": "🦩", + "flashlight": "🔦", + "flat_shoe": "🥿", + "fleur-de-lis": "⚜", + "flexed_biceps": "💪", + "flexed_biceps_dark_skin_tone": "💪🏿", + "flexed_biceps_light_skin_tone": "💪🏻", + "flexed_biceps_medium-dark_skin_tone": "💪🏾", + "flexed_biceps_medium-light_skin_tone": "💪🏼", + "flexed_biceps_medium_skin_tone": "💪🏽", + "floppy_disk": "💾", + "flower_playing_cards": "🎴", + "flushed_face": "😳", + "flying_disc": "🥏", + "flying_saucer": "🛸", + "fog": "🌫", + "foggy": "🌁", + "folded_hands": "🙏", + "folded_hands_dark_skin_tone": "🙏🏿", + "folded_hands_light_skin_tone": "🙏🏻", + "folded_hands_medium-dark_skin_tone": "🙏🏾", + "folded_hands_medium-light_skin_tone": "🙏🏼", + "folded_hands_medium_skin_tone": "🙏🏽", + "foot": "🦶", + "footprints": "👣", + "fork_and_knife": "🍴", + "fork_and_knife_with_plate": "🍽", + "fortune_cookie": "🥠", + "fountain": "⛲", + "fountain_pen": "🖋", + "four-thirty": "🕟", + "four_leaf_clover": "🍀", + "four_o’clock": "🕓", + "fox_face": "🦊", + "framed_picture": "🖼", + "french_fries": "🍟", + "fried_shrimp": "🍤", + "frog_face": "🐸", + "front-facing_baby_chick": "🐥", + "frowning_face": "☹", + "frowning_face_with_open_mouth": "😦", + "fuel_pump": "⛽", + "full_moon": "🌕", + "full_moon_face": "🌝", + "funeral_urn": "⚱", + "game_die": "🎲", + "garlic": "🧄", + "gear": "⚙", + "gem_stone": "💎", + "genie": "🧞", + "ghost": "👻", + "giraffe": "🦒", + "girl": "👧", + "girl_dark_skin_tone": "👧🏿", + "girl_light_skin_tone": "👧🏻", + "girl_medium-dark_skin_tone": "👧🏾", + "girl_medium-light_skin_tone": "👧🏼", + "girl_medium_skin_tone": "👧🏽", + "glass_of_milk": "🥛", + "glasses": "👓", + "globe_showing_americas": "🌎", + "globe_showing_asia-australia": "🌏", + "globe_showing_europe-africa": "🌍", + "globe_with_meridians": "🌐", + "gloves": "🧤", + "glowing_star": "🌟", + "goal_net": "🥅", + "goat": "🐐", + "goblin": "👺", + "goggles": "🥽", + "gorilla": "🦍", + "graduation_cap": "🎓", + "grapes": "🍇", + "green_apple": "🍏", + "green_book": "📗", + "green_circle": "🟢", + "green_heart": "💚", + "green_salad": "🥗", + "green_square": "🟩", + "grimacing_face": "😬", + "grinning_cat_face": "😺", + "grinning_cat_face_with_smiling_eyes": "😸", + "grinning_face": "😀", + "grinning_face_with_big_eyes": "😃", + "grinning_face_with_smiling_eyes": "😄", + "grinning_face_with_sweat": "😅", + "grinning_squinting_face": "😆", + "growing_heart": "💗", + "guard": "💂", + "guard_dark_skin_tone": "💂🏿", + "guard_light_skin_tone": "💂🏻", + "guard_medium-dark_skin_tone": "💂🏾", + "guard_medium-light_skin_tone": "💂🏼", + "guard_medium_skin_tone": "💂🏽", + "guide_dog": "🦮", + "guitar": "🎸", + "hamburger": "🍔", + "hammer": "🔨", + "hammer_and_pick": "⚒", + "hammer_and_wrench": "🛠", + "hamster_face": "🐹", + "hand_with_fingers_splayed": "🖐", + "hand_with_fingers_splayed_dark_skin_tone": "🖐🏿", + "hand_with_fingers_splayed_light_skin_tone": "🖐🏻", + "hand_with_fingers_splayed_medium-dark_skin_tone": "🖐🏾", + "hand_with_fingers_splayed_medium-light_skin_tone": "🖐🏼", + "hand_with_fingers_splayed_medium_skin_tone": "🖐🏽", + "handbag": "👜", + "handshake": "🤝", + "hatching_chick": "🐣", + "headphone": "🎧", + "hear-no-evil_monkey": "🙉", + "heart_decoration": "💟", + "heart_suit": "♥", + "heart_with_arrow": "💘", + "heart_with_ribbon": "💝", + "heavy_check_mark": "✔", + "heavy_division_sign": "➗", + "heavy_dollar_sign": "💲", + "heavy_heart_exclamation": "❣", + "heavy_large_circle": "⭕", + "heavy_minus_sign": "➖", + "heavy_multiplication_x": "✖", + "heavy_plus_sign": "➕", + "hedgehog": "🦔", + "helicopter": "🚁", + "herb": "🌿", + "hibiscus": "🌺", + "high-heeled_shoe": "👠", + "high-speed_train": "🚄", + "high_voltage": "⚡", + "hiking_boot": "🥾", + "hindu_temple": "🛕", + "hippopotamus": "🦛", + "hole": "🕳", + "honey_pot": "🍯", + "honeybee": "🐝", + "horizontal_traffic_light": "🚥", + "horse": "🐴", + "horse_face": "🐴", + "horse_racing": "🏇", + "horse_racing_dark_skin_tone": "🏇🏿", + "horse_racing_light_skin_tone": "🏇🏻", + "horse_racing_medium-dark_skin_tone": "🏇🏾", + "horse_racing_medium-light_skin_tone": "🏇🏼", + "horse_racing_medium_skin_tone": "🏇🏽", + "hospital": "🏥", + "hot_beverage": "☕", + "hot_dog": "🌭", + "hot_face": "🥵", + "hot_pepper": "🌶", + "hot_springs": "♨", + "hotel": "🏨", + "hourglass_done": "⌛", + "hourglass_not_done": "⏳", + "house": "🏠", + "house_with_garden": "🏡", + "houses": "🏘", + "hugging_face": "🤗", + "hundred_points": "💯", + "hushed_face": "😯", + "ice": "🧊", + "ice_cream": "🍨", + "ice_hockey": "🏒", + "ice_skate": "⛸", + "inbox_tray": "📥", + "incoming_envelope": "📨", + "index_pointing_up": "☝", + "index_pointing_up_dark_skin_tone": "☝🏿", + "index_pointing_up_light_skin_tone": "☝🏻", + "index_pointing_up_medium-dark_skin_tone": "☝🏾", + "index_pointing_up_medium-light_skin_tone": "☝🏼", + "index_pointing_up_medium_skin_tone": "☝🏽", + "infinity": "♾", + "information": "ℹ", + "input_latin_letters": "🔤", + "input_latin_lowercase": "🔡", + "input_latin_uppercase": "🔠", + "input_numbers": "🔢", + "input_symbols": "🔣", + "jack-o-lantern": "🎃", + "jeans": "👖", + "jigsaw": "🧩", + "joker": "🃏", + "joystick": "🕹", + "kaaba": "🕋", + "kangaroo": "🦘", + "key": "🔑", + "keyboard": "⌨", + "keycap_#": "#️⃣", + "keycap_*": "*️⃣", + "keycap_0": "0️⃣", + "keycap_1": "1️⃣", + "keycap_10": "🔟", + "keycap_2": "2️⃣", + "keycap_3": "3️⃣", + "keycap_4": "4️⃣", + "keycap_5": "5️⃣", + "keycap_6": "6️⃣", + "keycap_7": "7️⃣", + "keycap_8": "8️⃣", + "keycap_9": "9️⃣", + "kick_scooter": "🛴", + "kimono": "👘", + "kiss": "💋", + "kiss_man_man": "👨\u200d❤️\u200d💋\u200d👨", + "kiss_mark": "💋", + "kiss_woman_man": "👩\u200d❤️\u200d💋\u200d👨", + "kiss_woman_woman": "👩\u200d❤️\u200d💋\u200d👩", + "kissing_cat_face": "😽", + "kissing_face": "😗", + "kissing_face_with_closed_eyes": "😚", + "kissing_face_with_smiling_eyes": "😙", + "kitchen_knife": "🔪", + "kite": "🪁", + "kiwi_fruit": "🥝", + "koala": "🐨", + "lab_coat": "🥼", + "label": "🏷", + "lacrosse": "🥍", + "lady_beetle": "🐞", + "laptop_computer": "💻", + "large_blue_diamond": "🔷", + "large_orange_diamond": "🔶", + "last_quarter_moon": "🌗", + "last_quarter_moon_face": "🌜", + "last_track_button": "⏮", + "latin_cross": "✝", + "leaf_fluttering_in_wind": "🍃", + "leafy_green": "🥬", + "ledger": "📒", + "left-facing_fist": "🤛", + "left-facing_fist_dark_skin_tone": "🤛🏿", + "left-facing_fist_light_skin_tone": "🤛🏻", + "left-facing_fist_medium-dark_skin_tone": "🤛🏾", + "left-facing_fist_medium-light_skin_tone": "🤛🏼", + "left-facing_fist_medium_skin_tone": "🤛🏽", + "left-right_arrow": "↔", + "left_arrow": "⬅", + "left_arrow_curving_right": "↪", + "left_luggage": "🛅", + "left_speech_bubble": "🗨", + "leg": "🦵", + "lemon": "🍋", + "leopard": "🐆", + "level_slider": "🎚", + "light_bulb": "💡", + "light_rail": "🚈", + "link": "🔗", + "linked_paperclips": "🖇", + "lion_face": "🦁", + "lipstick": "💄", + "litter_in_bin_sign": "🚮", + "lizard": "🦎", + "llama": "🦙", + "lobster": "🦞", + "locked": "🔒", + "locked_with_key": "🔐", + "locked_with_pen": "🔏", + "locomotive": "🚂", + "lollipop": "🍭", + "lotion_bottle": "🧴", + "loudly_crying_face": "😭", + "loudspeaker": "📢", + "love-you_gesture": "🤟", + "love-you_gesture_dark_skin_tone": "🤟🏿", + "love-you_gesture_light_skin_tone": "🤟🏻", + "love-you_gesture_medium-dark_skin_tone": "🤟🏾", + "love-you_gesture_medium-light_skin_tone": "🤟🏼", + "love-you_gesture_medium_skin_tone": "🤟🏽", + "love_hotel": "🏩", + "love_letter": "💌", + "luggage": "🧳", + "lying_face": "🤥", + "mage": "🧙", + "mage_dark_skin_tone": "🧙🏿", + "mage_light_skin_tone": "🧙🏻", + "mage_medium-dark_skin_tone": "🧙🏾", + "mage_medium-light_skin_tone": "🧙🏼", + "mage_medium_skin_tone": "🧙🏽", + "magnet": "🧲", + "magnifying_glass_tilted_left": "🔍", + "magnifying_glass_tilted_right": "🔎", + "mahjong_red_dragon": "🀄", + "male_sign": "♂", + "man": "👨", + "man_and_woman_holding_hands": "👫", + "man_artist": "👨\u200d🎨", + "man_artist_dark_skin_tone": "👨🏿\u200d🎨", + "man_artist_light_skin_tone": "👨🏻\u200d🎨", + "man_artist_medium-dark_skin_tone": "👨🏾\u200d🎨", + "man_artist_medium-light_skin_tone": "👨🏼\u200d🎨", + "man_artist_medium_skin_tone": "👨🏽\u200d🎨", + "man_astronaut": "👨\u200d🚀", + "man_astronaut_dark_skin_tone": "👨🏿\u200d🚀", + "man_astronaut_light_skin_tone": "👨🏻\u200d🚀", + "man_astronaut_medium-dark_skin_tone": "👨🏾\u200d🚀", + "man_astronaut_medium-light_skin_tone": "👨🏼\u200d🚀", + "man_astronaut_medium_skin_tone": "👨🏽\u200d🚀", + "man_biking": "🚴\u200d♂️", + "man_biking_dark_skin_tone": "🚴🏿\u200d♂️", + "man_biking_light_skin_tone": "🚴🏻\u200d♂️", + "man_biking_medium-dark_skin_tone": "🚴🏾\u200d♂️", + "man_biking_medium-light_skin_tone": "🚴🏼\u200d♂️", + "man_biking_medium_skin_tone": "🚴🏽\u200d♂️", + "man_bouncing_ball": "⛹️\u200d♂️", + "man_bouncing_ball_dark_skin_tone": "⛹🏿\u200d♂️", + "man_bouncing_ball_light_skin_tone": "⛹🏻\u200d♂️", + "man_bouncing_ball_medium-dark_skin_tone": "⛹🏾\u200d♂️", + "man_bouncing_ball_medium-light_skin_tone": "⛹🏼\u200d♂️", + "man_bouncing_ball_medium_skin_tone": "⛹🏽\u200d♂️", + "man_bowing": "🙇\u200d♂️", + "man_bowing_dark_skin_tone": "🙇🏿\u200d♂️", + "man_bowing_light_skin_tone": "🙇🏻\u200d♂️", + "man_bowing_medium-dark_skin_tone": "🙇🏾\u200d♂️", + "man_bowing_medium-light_skin_tone": "🙇🏼\u200d♂️", + "man_bowing_medium_skin_tone": "🙇🏽\u200d♂️", + "man_cartwheeling": "🤸\u200d♂️", + "man_cartwheeling_dark_skin_tone": "🤸🏿\u200d♂️", + "man_cartwheeling_light_skin_tone": "🤸🏻\u200d♂️", + "man_cartwheeling_medium-dark_skin_tone": "🤸🏾\u200d♂️", + "man_cartwheeling_medium-light_skin_tone": "🤸🏼\u200d♂️", + "man_cartwheeling_medium_skin_tone": "🤸🏽\u200d♂️", + "man_climbing": "🧗\u200d♂️", + "man_climbing_dark_skin_tone": "🧗🏿\u200d♂️", + "man_climbing_light_skin_tone": "🧗🏻\u200d♂️", + "man_climbing_medium-dark_skin_tone": "🧗🏾\u200d♂️", + "man_climbing_medium-light_skin_tone": "🧗🏼\u200d♂️", + "man_climbing_medium_skin_tone": "🧗🏽\u200d♂️", + "man_construction_worker": "👷\u200d♂️", + "man_construction_worker_dark_skin_tone": "👷🏿\u200d♂️", + "man_construction_worker_light_skin_tone": "👷🏻\u200d♂️", + "man_construction_worker_medium-dark_skin_tone": "👷🏾\u200d♂️", + "man_construction_worker_medium-light_skin_tone": "👷🏼\u200d♂️", + "man_construction_worker_medium_skin_tone": "👷🏽\u200d♂️", + "man_cook": "👨\u200d🍳", + "man_cook_dark_skin_tone": "👨🏿\u200d🍳", + "man_cook_light_skin_tone": "👨🏻\u200d🍳", + "man_cook_medium-dark_skin_tone": "👨🏾\u200d🍳", + "man_cook_medium-light_skin_tone": "👨🏼\u200d🍳", + "man_cook_medium_skin_tone": "👨🏽\u200d🍳", + "man_dancing": "🕺", + "man_dancing_dark_skin_tone": "🕺🏿", + "man_dancing_light_skin_tone": "🕺🏻", + "man_dancing_medium-dark_skin_tone": "🕺🏾", + "man_dancing_medium-light_skin_tone": "🕺🏼", + "man_dancing_medium_skin_tone": "🕺🏽", + "man_dark_skin_tone": "👨🏿", + "man_detective": "🕵️\u200d♂️", + "man_detective_dark_skin_tone": "🕵🏿\u200d♂️", + "man_detective_light_skin_tone": "🕵🏻\u200d♂️", + "man_detective_medium-dark_skin_tone": "🕵🏾\u200d♂️", + "man_detective_medium-light_skin_tone": "🕵🏼\u200d♂️", + "man_detective_medium_skin_tone": "🕵🏽\u200d♂️", + "man_elf": "🧝\u200d♂️", + "man_elf_dark_skin_tone": "🧝🏿\u200d♂️", + "man_elf_light_skin_tone": "🧝🏻\u200d♂️", + "man_elf_medium-dark_skin_tone": "🧝🏾\u200d♂️", + "man_elf_medium-light_skin_tone": "🧝🏼\u200d♂️", + "man_elf_medium_skin_tone": "🧝🏽\u200d♂️", + "man_facepalming": "🤦\u200d♂️", + "man_facepalming_dark_skin_tone": "🤦🏿\u200d♂️", + "man_facepalming_light_skin_tone": "🤦🏻\u200d♂️", + "man_facepalming_medium-dark_skin_tone": "🤦🏾\u200d♂️", + "man_facepalming_medium-light_skin_tone": "🤦🏼\u200d♂️", + "man_facepalming_medium_skin_tone": "🤦🏽\u200d♂️", + "man_factory_worker": "👨\u200d🏭", + "man_factory_worker_dark_skin_tone": "👨🏿\u200d🏭", + "man_factory_worker_light_skin_tone": "👨🏻\u200d🏭", + "man_factory_worker_medium-dark_skin_tone": "👨🏾\u200d🏭", + "man_factory_worker_medium-light_skin_tone": "👨🏼\u200d🏭", + "man_factory_worker_medium_skin_tone": "👨🏽\u200d🏭", + "man_fairy": "🧚\u200d♂️", + "man_fairy_dark_skin_tone": "🧚🏿\u200d♂️", + "man_fairy_light_skin_tone": "🧚🏻\u200d♂️", + "man_fairy_medium-dark_skin_tone": "🧚🏾\u200d♂️", + "man_fairy_medium-light_skin_tone": "🧚🏼\u200d♂️", + "man_fairy_medium_skin_tone": "🧚🏽\u200d♂️", + "man_farmer": "👨\u200d🌾", + "man_farmer_dark_skin_tone": "👨🏿\u200d🌾", + "man_farmer_light_skin_tone": "👨🏻\u200d🌾", + "man_farmer_medium-dark_skin_tone": "👨🏾\u200d🌾", + "man_farmer_medium-light_skin_tone": "👨🏼\u200d🌾", + "man_farmer_medium_skin_tone": "👨🏽\u200d🌾", + "man_firefighter": "👨\u200d🚒", + "man_firefighter_dark_skin_tone": "👨🏿\u200d🚒", + "man_firefighter_light_skin_tone": "👨🏻\u200d🚒", + "man_firefighter_medium-dark_skin_tone": "👨🏾\u200d🚒", + "man_firefighter_medium-light_skin_tone": "👨🏼\u200d🚒", + "man_firefighter_medium_skin_tone": "👨🏽\u200d🚒", + "man_frowning": "🙍\u200d♂️", + "man_frowning_dark_skin_tone": "🙍🏿\u200d♂️", + "man_frowning_light_skin_tone": "🙍🏻\u200d♂️", + "man_frowning_medium-dark_skin_tone": "🙍🏾\u200d♂️", + "man_frowning_medium-light_skin_tone": "🙍🏼\u200d♂️", + "man_frowning_medium_skin_tone": "🙍🏽\u200d♂️", + "man_genie": "🧞\u200d♂️", + "man_gesturing_no": "🙅\u200d♂️", + "man_gesturing_no_dark_skin_tone": "🙅🏿\u200d♂️", + "man_gesturing_no_light_skin_tone": "🙅🏻\u200d♂️", + "man_gesturing_no_medium-dark_skin_tone": "🙅🏾\u200d♂️", + "man_gesturing_no_medium-light_skin_tone": "🙅🏼\u200d♂️", + "man_gesturing_no_medium_skin_tone": "🙅🏽\u200d♂️", + "man_gesturing_ok": "🙆\u200d♂️", + "man_gesturing_ok_dark_skin_tone": "🙆🏿\u200d♂️", + "man_gesturing_ok_light_skin_tone": "🙆🏻\u200d♂️", + "man_gesturing_ok_medium-dark_skin_tone": "🙆🏾\u200d♂️", + "man_gesturing_ok_medium-light_skin_tone": "🙆🏼\u200d♂️", + "man_gesturing_ok_medium_skin_tone": "🙆🏽\u200d♂️", + "man_getting_haircut": "💇\u200d♂️", + "man_getting_haircut_dark_skin_tone": "💇🏿\u200d♂️", + "man_getting_haircut_light_skin_tone": "💇🏻\u200d♂️", + "man_getting_haircut_medium-dark_skin_tone": "💇🏾\u200d♂️", + "man_getting_haircut_medium-light_skin_tone": "💇🏼\u200d♂️", + "man_getting_haircut_medium_skin_tone": "💇🏽\u200d♂️", + "man_getting_massage": "💆\u200d♂️", + "man_getting_massage_dark_skin_tone": "💆🏿\u200d♂️", + "man_getting_massage_light_skin_tone": "💆🏻\u200d♂️", + "man_getting_massage_medium-dark_skin_tone": "💆🏾\u200d♂️", + "man_getting_massage_medium-light_skin_tone": "💆🏼\u200d♂️", + "man_getting_massage_medium_skin_tone": "💆🏽\u200d♂️", + "man_golfing": "🏌️\u200d♂️", + "man_golfing_dark_skin_tone": "🏌🏿\u200d♂️", + "man_golfing_light_skin_tone": "🏌🏻\u200d♂️", + "man_golfing_medium-dark_skin_tone": "🏌🏾\u200d♂️", + "man_golfing_medium-light_skin_tone": "🏌🏼\u200d♂️", + "man_golfing_medium_skin_tone": "🏌🏽\u200d♂️", + "man_guard": "💂\u200d♂️", + "man_guard_dark_skin_tone": "💂🏿\u200d♂️", + "man_guard_light_skin_tone": "💂🏻\u200d♂️", + "man_guard_medium-dark_skin_tone": "💂🏾\u200d♂️", + "man_guard_medium-light_skin_tone": "💂🏼\u200d♂️", + "man_guard_medium_skin_tone": "💂🏽\u200d♂️", + "man_health_worker": "👨\u200d⚕️", + "man_health_worker_dark_skin_tone": "👨🏿\u200d⚕️", + "man_health_worker_light_skin_tone": "👨🏻\u200d⚕️", + "man_health_worker_medium-dark_skin_tone": "👨🏾\u200d⚕️", + "man_health_worker_medium-light_skin_tone": "👨🏼\u200d⚕️", + "man_health_worker_medium_skin_tone": "👨🏽\u200d⚕️", + "man_in_lotus_position": "🧘\u200d♂️", + "man_in_lotus_position_dark_skin_tone": "🧘🏿\u200d♂️", + "man_in_lotus_position_light_skin_tone": "🧘🏻\u200d♂️", + "man_in_lotus_position_medium-dark_skin_tone": "🧘🏾\u200d♂️", + "man_in_lotus_position_medium-light_skin_tone": "🧘🏼\u200d♂️", + "man_in_lotus_position_medium_skin_tone": "🧘🏽\u200d♂️", + "man_in_manual_wheelchair": "👨\u200d🦽", + "man_in_motorized_wheelchair": "👨\u200d🦼", + "man_in_steamy_room": "🧖\u200d♂️", + "man_in_steamy_room_dark_skin_tone": "🧖🏿\u200d♂️", + "man_in_steamy_room_light_skin_tone": "🧖🏻\u200d♂️", + "man_in_steamy_room_medium-dark_skin_tone": "🧖🏾\u200d♂️", + "man_in_steamy_room_medium-light_skin_tone": "🧖🏼\u200d♂️", + "man_in_steamy_room_medium_skin_tone": "🧖🏽\u200d♂️", + "man_in_suit_levitating": "🕴", + "man_in_suit_levitating_dark_skin_tone": "🕴🏿", + "man_in_suit_levitating_light_skin_tone": "🕴🏻", + "man_in_suit_levitating_medium-dark_skin_tone": "🕴🏾", + "man_in_suit_levitating_medium-light_skin_tone": "🕴🏼", + "man_in_suit_levitating_medium_skin_tone": "🕴🏽", + "man_in_tuxedo": "🤵", + "man_in_tuxedo_dark_skin_tone": "🤵🏿", + "man_in_tuxedo_light_skin_tone": "🤵🏻", + "man_in_tuxedo_medium-dark_skin_tone": "🤵🏾", + "man_in_tuxedo_medium-light_skin_tone": "🤵🏼", + "man_in_tuxedo_medium_skin_tone": "🤵🏽", + "man_judge": "👨\u200d⚖️", + "man_judge_dark_skin_tone": "👨🏿\u200d⚖️", + "man_judge_light_skin_tone": "👨🏻\u200d⚖️", + "man_judge_medium-dark_skin_tone": "👨🏾\u200d⚖️", + "man_judge_medium-light_skin_tone": "👨🏼\u200d⚖️", + "man_judge_medium_skin_tone": "👨🏽\u200d⚖️", + "man_juggling": "🤹\u200d♂️", + "man_juggling_dark_skin_tone": "🤹🏿\u200d♂️", + "man_juggling_light_skin_tone": "🤹🏻\u200d♂️", + "man_juggling_medium-dark_skin_tone": "🤹🏾\u200d♂️", + "man_juggling_medium-light_skin_tone": "🤹🏼\u200d♂️", + "man_juggling_medium_skin_tone": "🤹🏽\u200d♂️", + "man_lifting_weights": "🏋️\u200d♂️", + "man_lifting_weights_dark_skin_tone": "🏋🏿\u200d♂️", + "man_lifting_weights_light_skin_tone": "🏋🏻\u200d♂️", + "man_lifting_weights_medium-dark_skin_tone": "🏋🏾\u200d♂️", + "man_lifting_weights_medium-light_skin_tone": "🏋🏼\u200d♂️", + "man_lifting_weights_medium_skin_tone": "🏋🏽\u200d♂️", + "man_light_skin_tone": "👨🏻", + "man_mage": "🧙\u200d♂️", + "man_mage_dark_skin_tone": "🧙🏿\u200d♂️", + "man_mage_light_skin_tone": "🧙🏻\u200d♂️", + "man_mage_medium-dark_skin_tone": "🧙🏾\u200d♂️", + "man_mage_medium-light_skin_tone": "🧙🏼\u200d♂️", + "man_mage_medium_skin_tone": "🧙🏽\u200d♂️", + "man_mechanic": "👨\u200d🔧", + "man_mechanic_dark_skin_tone": "👨🏿\u200d🔧", + "man_mechanic_light_skin_tone": "👨🏻\u200d🔧", + "man_mechanic_medium-dark_skin_tone": "👨🏾\u200d🔧", + "man_mechanic_medium-light_skin_tone": "👨🏼\u200d🔧", + "man_mechanic_medium_skin_tone": "👨🏽\u200d🔧", + "man_medium-dark_skin_tone": "👨🏾", + "man_medium-light_skin_tone": "👨🏼", + "man_medium_skin_tone": "👨🏽", + "man_mountain_biking": "🚵\u200d♂️", + "man_mountain_biking_dark_skin_tone": "🚵🏿\u200d♂️", + "man_mountain_biking_light_skin_tone": "🚵🏻\u200d♂️", + "man_mountain_biking_medium-dark_skin_tone": "🚵🏾\u200d♂️", + "man_mountain_biking_medium-light_skin_tone": "🚵🏼\u200d♂️", + "man_mountain_biking_medium_skin_tone": "🚵🏽\u200d♂️", + "man_office_worker": "👨\u200d💼", + "man_office_worker_dark_skin_tone": "👨🏿\u200d💼", + "man_office_worker_light_skin_tone": "👨🏻\u200d💼", + "man_office_worker_medium-dark_skin_tone": "👨🏾\u200d💼", + "man_office_worker_medium-light_skin_tone": "👨🏼\u200d💼", + "man_office_worker_medium_skin_tone": "👨🏽\u200d💼", + "man_pilot": "👨\u200d✈️", + "man_pilot_dark_skin_tone": "👨🏿\u200d✈️", + "man_pilot_light_skin_tone": "👨🏻\u200d✈️", + "man_pilot_medium-dark_skin_tone": "👨🏾\u200d✈️", + "man_pilot_medium-light_skin_tone": "👨🏼\u200d✈️", + "man_pilot_medium_skin_tone": "👨🏽\u200d✈️", + "man_playing_handball": "🤾\u200d♂️", + "man_playing_handball_dark_skin_tone": "🤾🏿\u200d♂️", + "man_playing_handball_light_skin_tone": "🤾🏻\u200d♂️", + "man_playing_handball_medium-dark_skin_tone": "🤾🏾\u200d♂️", + "man_playing_handball_medium-light_skin_tone": "🤾🏼\u200d♂️", + "man_playing_handball_medium_skin_tone": "🤾🏽\u200d♂️", + "man_playing_water_polo": "🤽\u200d♂️", + "man_playing_water_polo_dark_skin_tone": "🤽🏿\u200d♂️", + "man_playing_water_polo_light_skin_tone": "🤽🏻\u200d♂️", + "man_playing_water_polo_medium-dark_skin_tone": "🤽🏾\u200d♂️", + "man_playing_water_polo_medium-light_skin_tone": "🤽🏼\u200d♂️", + "man_playing_water_polo_medium_skin_tone": "🤽🏽\u200d♂️", + "man_police_officer": "👮\u200d♂️", + "man_police_officer_dark_skin_tone": "👮🏿\u200d♂️", + "man_police_officer_light_skin_tone": "👮🏻\u200d♂️", + "man_police_officer_medium-dark_skin_tone": "👮🏾\u200d♂️", + "man_police_officer_medium-light_skin_tone": "👮🏼\u200d♂️", + "man_police_officer_medium_skin_tone": "👮🏽\u200d♂️", + "man_pouting": "🙎\u200d♂️", + "man_pouting_dark_skin_tone": "🙎🏿\u200d♂️", + "man_pouting_light_skin_tone": "🙎🏻\u200d♂️", + "man_pouting_medium-dark_skin_tone": "🙎🏾\u200d♂️", + "man_pouting_medium-light_skin_tone": "🙎🏼\u200d♂️", + "man_pouting_medium_skin_tone": "🙎🏽\u200d♂️", + "man_raising_hand": "🙋\u200d♂️", + "man_raising_hand_dark_skin_tone": "🙋🏿\u200d♂️", + "man_raising_hand_light_skin_tone": "🙋🏻\u200d♂️", + "man_raising_hand_medium-dark_skin_tone": "🙋🏾\u200d♂️", + "man_raising_hand_medium-light_skin_tone": "🙋🏼\u200d♂️", + "man_raising_hand_medium_skin_tone": "🙋🏽\u200d♂️", + "man_rowing_boat": "🚣\u200d♂️", + "man_rowing_boat_dark_skin_tone": "🚣🏿\u200d♂️", + "man_rowing_boat_light_skin_tone": "🚣🏻\u200d♂️", + "man_rowing_boat_medium-dark_skin_tone": "🚣🏾\u200d♂️", + "man_rowing_boat_medium-light_skin_tone": "🚣🏼\u200d♂️", + "man_rowing_boat_medium_skin_tone": "🚣🏽\u200d♂️", + "man_running": "🏃\u200d♂️", + "man_running_dark_skin_tone": "🏃🏿\u200d♂️", + "man_running_light_skin_tone": "🏃🏻\u200d♂️", + "man_running_medium-dark_skin_tone": "🏃🏾\u200d♂️", + "man_running_medium-light_skin_tone": "🏃🏼\u200d♂️", + "man_running_medium_skin_tone": "🏃🏽\u200d♂️", + "man_scientist": "👨\u200d🔬", + "man_scientist_dark_skin_tone": "👨🏿\u200d🔬", + "man_scientist_light_skin_tone": "👨🏻\u200d🔬", + "man_scientist_medium-dark_skin_tone": "👨🏾\u200d🔬", + "man_scientist_medium-light_skin_tone": "👨🏼\u200d🔬", + "man_scientist_medium_skin_tone": "👨🏽\u200d🔬", + "man_shrugging": "🤷\u200d♂️", + "man_shrugging_dark_skin_tone": "🤷🏿\u200d♂️", + "man_shrugging_light_skin_tone": "🤷🏻\u200d♂️", + "man_shrugging_medium-dark_skin_tone": "🤷🏾\u200d♂️", + "man_shrugging_medium-light_skin_tone": "🤷🏼\u200d♂️", + "man_shrugging_medium_skin_tone": "🤷🏽\u200d♂️", + "man_singer": "👨\u200d🎤", + "man_singer_dark_skin_tone": "👨🏿\u200d🎤", + "man_singer_light_skin_tone": "👨🏻\u200d🎤", + "man_singer_medium-dark_skin_tone": "👨🏾\u200d🎤", + "man_singer_medium-light_skin_tone": "👨🏼\u200d🎤", + "man_singer_medium_skin_tone": "👨🏽\u200d🎤", + "man_student": "👨\u200d🎓", + "man_student_dark_skin_tone": "👨🏿\u200d🎓", + "man_student_light_skin_tone": "👨🏻\u200d🎓", + "man_student_medium-dark_skin_tone": "👨🏾\u200d🎓", + "man_student_medium-light_skin_tone": "👨🏼\u200d🎓", + "man_student_medium_skin_tone": "👨🏽\u200d🎓", + "man_surfing": "🏄\u200d♂️", + "man_surfing_dark_skin_tone": "🏄🏿\u200d♂️", + "man_surfing_light_skin_tone": "🏄🏻\u200d♂️", + "man_surfing_medium-dark_skin_tone": "🏄🏾\u200d♂️", + "man_surfing_medium-light_skin_tone": "🏄🏼\u200d♂️", + "man_surfing_medium_skin_tone": "🏄🏽\u200d♂️", + "man_swimming": "🏊\u200d♂️", + "man_swimming_dark_skin_tone": "🏊🏿\u200d♂️", + "man_swimming_light_skin_tone": "🏊🏻\u200d♂️", + "man_swimming_medium-dark_skin_tone": "🏊🏾\u200d♂️", + "man_swimming_medium-light_skin_tone": "🏊🏼\u200d♂️", + "man_swimming_medium_skin_tone": "🏊🏽\u200d♂️", + "man_teacher": "👨\u200d🏫", + "man_teacher_dark_skin_tone": "👨🏿\u200d🏫", + "man_teacher_light_skin_tone": "👨🏻\u200d🏫", + "man_teacher_medium-dark_skin_tone": "👨🏾\u200d🏫", + "man_teacher_medium-light_skin_tone": "👨🏼\u200d🏫", + "man_teacher_medium_skin_tone": "👨🏽\u200d🏫", + "man_technologist": "👨\u200d💻", + "man_technologist_dark_skin_tone": "👨🏿\u200d💻", + "man_technologist_light_skin_tone": "👨🏻\u200d💻", + "man_technologist_medium-dark_skin_tone": "👨🏾\u200d💻", + "man_technologist_medium-light_skin_tone": "👨🏼\u200d💻", + "man_technologist_medium_skin_tone": "👨🏽\u200d💻", + "man_tipping_hand": "💁\u200d♂️", + "man_tipping_hand_dark_skin_tone": "💁🏿\u200d♂️", + "man_tipping_hand_light_skin_tone": "💁🏻\u200d♂️", + "man_tipping_hand_medium-dark_skin_tone": "💁🏾\u200d♂️", + "man_tipping_hand_medium-light_skin_tone": "💁🏼\u200d♂️", + "man_tipping_hand_medium_skin_tone": "💁🏽\u200d♂️", + "man_vampire": "🧛\u200d♂️", + "man_vampire_dark_skin_tone": "🧛🏿\u200d♂️", + "man_vampire_light_skin_tone": "🧛🏻\u200d♂️", + "man_vampire_medium-dark_skin_tone": "🧛🏾\u200d♂️", + "man_vampire_medium-light_skin_tone": "🧛🏼\u200d♂️", + "man_vampire_medium_skin_tone": "🧛🏽\u200d♂️", + "man_walking": "🚶\u200d♂️", + "man_walking_dark_skin_tone": "🚶🏿\u200d♂️", + "man_walking_light_skin_tone": "🚶🏻\u200d♂️", + "man_walking_medium-dark_skin_tone": "🚶🏾\u200d♂️", + "man_walking_medium-light_skin_tone": "🚶🏼\u200d♂️", + "man_walking_medium_skin_tone": "🚶🏽\u200d♂️", + "man_wearing_turban": "👳\u200d♂️", + "man_wearing_turban_dark_skin_tone": "👳🏿\u200d♂️", + "man_wearing_turban_light_skin_tone": "👳🏻\u200d♂️", + "man_wearing_turban_medium-dark_skin_tone": "👳🏾\u200d♂️", + "man_wearing_turban_medium-light_skin_tone": "👳🏼\u200d♂️", + "man_wearing_turban_medium_skin_tone": "👳🏽\u200d♂️", + "man_with_probing_cane": "👨\u200d🦯", + "man_with_chinese_cap": "👲", + "man_with_chinese_cap_dark_skin_tone": "👲🏿", + "man_with_chinese_cap_light_skin_tone": "👲🏻", + "man_with_chinese_cap_medium-dark_skin_tone": "👲🏾", + "man_with_chinese_cap_medium-light_skin_tone": "👲🏼", + "man_with_chinese_cap_medium_skin_tone": "👲🏽", + "man_zombie": "🧟\u200d♂️", + "mango": "🥭", + "mantelpiece_clock": "🕰", + "manual_wheelchair": "🦽", + "man’s_shoe": "👞", + "map_of_japan": "🗾", + "maple_leaf": "🍁", + "martial_arts_uniform": "🥋", + "mate": "🧉", + "meat_on_bone": "🍖", + "mechanical_arm": "🦾", + "mechanical_leg": "🦿", + "medical_symbol": "⚕", + "megaphone": "📣", + "melon": "🍈", + "memo": "📝", + "men_with_bunny_ears": "👯\u200d♂️", + "men_wrestling": "🤼\u200d♂️", + "menorah": "🕎", + "men’s_room": "🚹", + "mermaid": "🧜\u200d♀️", + "mermaid_dark_skin_tone": "🧜🏿\u200d♀️", + "mermaid_light_skin_tone": "🧜🏻\u200d♀️", + "mermaid_medium-dark_skin_tone": "🧜🏾\u200d♀️", + "mermaid_medium-light_skin_tone": "🧜🏼\u200d♀️", + "mermaid_medium_skin_tone": "🧜🏽\u200d♀️", + "merman": "🧜\u200d♂️", + "merman_dark_skin_tone": "🧜🏿\u200d♂️", + "merman_light_skin_tone": "🧜🏻\u200d♂️", + "merman_medium-dark_skin_tone": "🧜🏾\u200d♂️", + "merman_medium-light_skin_tone": "🧜🏼\u200d♂️", + "merman_medium_skin_tone": "🧜🏽\u200d♂️", + "merperson": "🧜", + "merperson_dark_skin_tone": "🧜🏿", + "merperson_light_skin_tone": "🧜🏻", + "merperson_medium-dark_skin_tone": "🧜🏾", + "merperson_medium-light_skin_tone": "🧜🏼", + "merperson_medium_skin_tone": "🧜🏽", + "metro": "🚇", + "microbe": "🦠", + "microphone": "🎤", + "microscope": "🔬", + "middle_finger": "🖕", + "middle_finger_dark_skin_tone": "🖕🏿", + "middle_finger_light_skin_tone": "🖕🏻", + "middle_finger_medium-dark_skin_tone": "🖕🏾", + "middle_finger_medium-light_skin_tone": "🖕🏼", + "middle_finger_medium_skin_tone": "🖕🏽", + "military_medal": "🎖", + "milky_way": "🌌", + "minibus": "🚐", + "moai": "🗿", + "mobile_phone": "📱", + "mobile_phone_off": "📴", + "mobile_phone_with_arrow": "📲", + "money-mouth_face": "🤑", + "money_bag": "💰", + "money_with_wings": "💸", + "monkey": "🐒", + "monkey_face": "🐵", + "monorail": "🚝", + "moon_cake": "🥮", + "moon_viewing_ceremony": "🎑", + "mosque": "🕌", + "mosquito": "🦟", + "motor_boat": "🛥", + "motor_scooter": "🛵", + "motorcycle": "🏍", + "motorized_wheelchair": "🦼", + "motorway": "🛣", + "mount_fuji": "🗻", + "mountain": "⛰", + "mountain_cableway": "🚠", + "mountain_railway": "🚞", + "mouse": "🐭", + "mouse_face": "🐭", + "mouth": "👄", + "movie_camera": "🎥", + "mushroom": "🍄", + "musical_keyboard": "🎹", + "musical_note": "🎵", + "musical_notes": "🎶", + "musical_score": "🎼", + "muted_speaker": "🔇", + "nail_polish": "💅", + "nail_polish_dark_skin_tone": "💅🏿", + "nail_polish_light_skin_tone": "💅🏻", + "nail_polish_medium-dark_skin_tone": "💅🏾", + "nail_polish_medium-light_skin_tone": "💅🏼", + "nail_polish_medium_skin_tone": "💅🏽", + "name_badge": "📛", + "national_park": "🏞", + "nauseated_face": "🤢", + "nazar_amulet": "🧿", + "necktie": "👔", + "nerd_face": "🤓", + "neutral_face": "😐", + "new_moon": "🌑", + "new_moon_face": "🌚", + "newspaper": "📰", + "next_track_button": "⏭", + "night_with_stars": "🌃", + "nine-thirty": "🕤", + "nine_o’clock": "🕘", + "no_bicycles": "🚳", + "no_entry": "⛔", + "no_littering": "🚯", + "no_mobile_phones": "📵", + "no_one_under_eighteen": "🔞", + "no_pedestrians": "🚷", + "no_smoking": "🚭", + "non-potable_water": "🚱", + "nose": "👃", + "nose_dark_skin_tone": "👃🏿", + "nose_light_skin_tone": "👃🏻", + "nose_medium-dark_skin_tone": "👃🏾", + "nose_medium-light_skin_tone": "👃🏼", + "nose_medium_skin_tone": "👃🏽", + "notebook": "📓", + "notebook_with_decorative_cover": "📔", + "nut_and_bolt": "🔩", + "octopus": "🐙", + "oden": "🍢", + "office_building": "🏢", + "ogre": "👹", + "oil_drum": "🛢", + "old_key": "🗝", + "old_man": "👴", + "old_man_dark_skin_tone": "👴🏿", + "old_man_light_skin_tone": "👴🏻", + "old_man_medium-dark_skin_tone": "👴🏾", + "old_man_medium-light_skin_tone": "👴🏼", + "old_man_medium_skin_tone": "👴🏽", + "old_woman": "👵", + "old_woman_dark_skin_tone": "👵🏿", + "old_woman_light_skin_tone": "👵🏻", + "old_woman_medium-dark_skin_tone": "👵🏾", + "old_woman_medium-light_skin_tone": "👵🏼", + "old_woman_medium_skin_tone": "👵🏽", + "older_adult": "🧓", + "older_adult_dark_skin_tone": "🧓🏿", + "older_adult_light_skin_tone": "🧓🏻", + "older_adult_medium-dark_skin_tone": "🧓🏾", + "older_adult_medium-light_skin_tone": "🧓🏼", + "older_adult_medium_skin_tone": "🧓🏽", + "om": "🕉", + "oncoming_automobile": "🚘", + "oncoming_bus": "🚍", + "oncoming_fist": "👊", + "oncoming_fist_dark_skin_tone": "👊🏿", + "oncoming_fist_light_skin_tone": "👊🏻", + "oncoming_fist_medium-dark_skin_tone": "👊🏾", + "oncoming_fist_medium-light_skin_tone": "👊🏼", + "oncoming_fist_medium_skin_tone": "👊🏽", + "oncoming_police_car": "🚔", + "oncoming_taxi": "🚖", + "one-piece_swimsuit": "🩱", + "one-thirty": "🕜", + "one_o’clock": "🕐", + "onion": "🧅", + "open_book": "📖", + "open_file_folder": "📂", + "open_hands": "👐", + "open_hands_dark_skin_tone": "👐🏿", + "open_hands_light_skin_tone": "👐🏻", + "open_hands_medium-dark_skin_tone": "👐🏾", + "open_hands_medium-light_skin_tone": "👐🏼", + "open_hands_medium_skin_tone": "👐🏽", + "open_mailbox_with_lowered_flag": "📭", + "open_mailbox_with_raised_flag": "📬", + "optical_disk": "💿", + "orange_book": "📙", + "orange_circle": "🟠", + "orange_heart": "🧡", + "orange_square": "🟧", + "orangutan": "🦧", + "orthodox_cross": "☦", + "otter": "🦦", + "outbox_tray": "📤", + "owl": "🦉", + "ox": "🐂", + "oyster": "🦪", + "package": "📦", + "page_facing_up": "📄", + "page_with_curl": "📃", + "pager": "📟", + "paintbrush": "🖌", + "palm_tree": "🌴", + "palms_up_together": "🤲", + "palms_up_together_dark_skin_tone": "🤲🏿", + "palms_up_together_light_skin_tone": "🤲🏻", + "palms_up_together_medium-dark_skin_tone": "🤲🏾", + "palms_up_together_medium-light_skin_tone": "🤲🏼", + "palms_up_together_medium_skin_tone": "🤲🏽", + "pancakes": "🥞", + "panda_face": "🐼", + "paperclip": "📎", + "parrot": "🦜", + "part_alternation_mark": "〽", + "party_popper": "🎉", + "partying_face": "🥳", + "passenger_ship": "🛳", + "passport_control": "🛂", + "pause_button": "⏸", + "paw_prints": "🐾", + "peace_symbol": "☮", + "peach": "🍑", + "peacock": "🦚", + "peanuts": "🥜", + "pear": "🍐", + "pen": "🖊", + "pencil": "📝", + "penguin": "🐧", + "pensive_face": "😔", + "people_holding_hands": "🧑\u200d🤝\u200d🧑", + "people_with_bunny_ears": "👯", + "people_wrestling": "🤼", + "performing_arts": "🎭", + "persevering_face": "😣", + "person_biking": "🚴", + "person_biking_dark_skin_tone": "🚴🏿", + "person_biking_light_skin_tone": "🚴🏻", + "person_biking_medium-dark_skin_tone": "🚴🏾", + "person_biking_medium-light_skin_tone": "🚴🏼", + "person_biking_medium_skin_tone": "🚴🏽", + "person_bouncing_ball": "⛹", + "person_bouncing_ball_dark_skin_tone": "⛹🏿", + "person_bouncing_ball_light_skin_tone": "⛹🏻", + "person_bouncing_ball_medium-dark_skin_tone": "⛹🏾", + "person_bouncing_ball_medium-light_skin_tone": "⛹🏼", + "person_bouncing_ball_medium_skin_tone": "⛹🏽", + "person_bowing": "🙇", + "person_bowing_dark_skin_tone": "🙇🏿", + "person_bowing_light_skin_tone": "🙇🏻", + "person_bowing_medium-dark_skin_tone": "🙇🏾", + "person_bowing_medium-light_skin_tone": "🙇🏼", + "person_bowing_medium_skin_tone": "🙇🏽", + "person_cartwheeling": "🤸", + "person_cartwheeling_dark_skin_tone": "🤸🏿", + "person_cartwheeling_light_skin_tone": "🤸🏻", + "person_cartwheeling_medium-dark_skin_tone": "🤸🏾", + "person_cartwheeling_medium-light_skin_tone": "🤸🏼", + "person_cartwheeling_medium_skin_tone": "🤸🏽", + "person_climbing": "🧗", + "person_climbing_dark_skin_tone": "🧗🏿", + "person_climbing_light_skin_tone": "🧗🏻", + "person_climbing_medium-dark_skin_tone": "🧗🏾", + "person_climbing_medium-light_skin_tone": "🧗🏼", + "person_climbing_medium_skin_tone": "🧗🏽", + "person_facepalming": "🤦", + "person_facepalming_dark_skin_tone": "🤦🏿", + "person_facepalming_light_skin_tone": "🤦🏻", + "person_facepalming_medium-dark_skin_tone": "🤦🏾", + "person_facepalming_medium-light_skin_tone": "🤦🏼", + "person_facepalming_medium_skin_tone": "🤦🏽", + "person_fencing": "🤺", + "person_frowning": "🙍", + "person_frowning_dark_skin_tone": "🙍🏿", + "person_frowning_light_skin_tone": "🙍🏻", + "person_frowning_medium-dark_skin_tone": "🙍🏾", + "person_frowning_medium-light_skin_tone": "🙍🏼", + "person_frowning_medium_skin_tone": "🙍🏽", + "person_gesturing_no": "🙅", + "person_gesturing_no_dark_skin_tone": "🙅🏿", + "person_gesturing_no_light_skin_tone": "🙅🏻", + "person_gesturing_no_medium-dark_skin_tone": "🙅🏾", + "person_gesturing_no_medium-light_skin_tone": "🙅🏼", + "person_gesturing_no_medium_skin_tone": "🙅🏽", + "person_gesturing_ok": "🙆", + "person_gesturing_ok_dark_skin_tone": "🙆🏿", + "person_gesturing_ok_light_skin_tone": "🙆🏻", + "person_gesturing_ok_medium-dark_skin_tone": "🙆🏾", + "person_gesturing_ok_medium-light_skin_tone": "🙆🏼", + "person_gesturing_ok_medium_skin_tone": "🙆🏽", + "person_getting_haircut": "💇", + "person_getting_haircut_dark_skin_tone": "💇🏿", + "person_getting_haircut_light_skin_tone": "💇🏻", + "person_getting_haircut_medium-dark_skin_tone": "💇🏾", + "person_getting_haircut_medium-light_skin_tone": "💇🏼", + "person_getting_haircut_medium_skin_tone": "💇🏽", + "person_getting_massage": "💆", + "person_getting_massage_dark_skin_tone": "💆🏿", + "person_getting_massage_light_skin_tone": "💆🏻", + "person_getting_massage_medium-dark_skin_tone": "💆🏾", + "person_getting_massage_medium-light_skin_tone": "💆🏼", + "person_getting_massage_medium_skin_tone": "💆🏽", + "person_golfing": "🏌", + "person_golfing_dark_skin_tone": "🏌🏿", + "person_golfing_light_skin_tone": "🏌🏻", + "person_golfing_medium-dark_skin_tone": "🏌🏾", + "person_golfing_medium-light_skin_tone": "🏌🏼", + "person_golfing_medium_skin_tone": "🏌🏽", + "person_in_bed": "🛌", + "person_in_bed_dark_skin_tone": "🛌🏿", + "person_in_bed_light_skin_tone": "🛌🏻", + "person_in_bed_medium-dark_skin_tone": "🛌🏾", + "person_in_bed_medium-light_skin_tone": "🛌🏼", + "person_in_bed_medium_skin_tone": "🛌🏽", + "person_in_lotus_position": "🧘", + "person_in_lotus_position_dark_skin_tone": "🧘🏿", + "person_in_lotus_position_light_skin_tone": "🧘🏻", + "person_in_lotus_position_medium-dark_skin_tone": "🧘🏾", + "person_in_lotus_position_medium-light_skin_tone": "🧘🏼", + "person_in_lotus_position_medium_skin_tone": "🧘🏽", + "person_in_steamy_room": "🧖", + "person_in_steamy_room_dark_skin_tone": "🧖🏿", + "person_in_steamy_room_light_skin_tone": "🧖🏻", + "person_in_steamy_room_medium-dark_skin_tone": "🧖🏾", + "person_in_steamy_room_medium-light_skin_tone": "🧖🏼", + "person_in_steamy_room_medium_skin_tone": "🧖🏽", + "person_juggling": "🤹", + "person_juggling_dark_skin_tone": "🤹🏿", + "person_juggling_light_skin_tone": "🤹🏻", + "person_juggling_medium-dark_skin_tone": "🤹🏾", + "person_juggling_medium-light_skin_tone": "🤹🏼", + "person_juggling_medium_skin_tone": "🤹🏽", + "person_kneeling": "🧎", + "person_lifting_weights": "🏋", + "person_lifting_weights_dark_skin_tone": "🏋🏿", + "person_lifting_weights_light_skin_tone": "🏋🏻", + "person_lifting_weights_medium-dark_skin_tone": "🏋🏾", + "person_lifting_weights_medium-light_skin_tone": "🏋🏼", + "person_lifting_weights_medium_skin_tone": "🏋🏽", + "person_mountain_biking": "🚵", + "person_mountain_biking_dark_skin_tone": "🚵🏿", + "person_mountain_biking_light_skin_tone": "🚵🏻", + "person_mountain_biking_medium-dark_skin_tone": "🚵🏾", + "person_mountain_biking_medium-light_skin_tone": "🚵🏼", + "person_mountain_biking_medium_skin_tone": "🚵🏽", + "person_playing_handball": "🤾", + "person_playing_handball_dark_skin_tone": "🤾🏿", + "person_playing_handball_light_skin_tone": "🤾🏻", + "person_playing_handball_medium-dark_skin_tone": "🤾🏾", + "person_playing_handball_medium-light_skin_tone": "🤾🏼", + "person_playing_handball_medium_skin_tone": "🤾🏽", + "person_playing_water_polo": "🤽", + "person_playing_water_polo_dark_skin_tone": "🤽🏿", + "person_playing_water_polo_light_skin_tone": "🤽🏻", + "person_playing_water_polo_medium-dark_skin_tone": "🤽🏾", + "person_playing_water_polo_medium-light_skin_tone": "🤽🏼", + "person_playing_water_polo_medium_skin_tone": "🤽🏽", + "person_pouting": "🙎", + "person_pouting_dark_skin_tone": "🙎🏿", + "person_pouting_light_skin_tone": "🙎🏻", + "person_pouting_medium-dark_skin_tone": "🙎🏾", + "person_pouting_medium-light_skin_tone": "🙎🏼", + "person_pouting_medium_skin_tone": "🙎🏽", + "person_raising_hand": "🙋", + "person_raising_hand_dark_skin_tone": "🙋🏿", + "person_raising_hand_light_skin_tone": "🙋🏻", + "person_raising_hand_medium-dark_skin_tone": "🙋🏾", + "person_raising_hand_medium-light_skin_tone": "🙋🏼", + "person_raising_hand_medium_skin_tone": "🙋🏽", + "person_rowing_boat": "🚣", + "person_rowing_boat_dark_skin_tone": "🚣🏿", + "person_rowing_boat_light_skin_tone": "🚣🏻", + "person_rowing_boat_medium-dark_skin_tone": "🚣🏾", + "person_rowing_boat_medium-light_skin_tone": "🚣🏼", + "person_rowing_boat_medium_skin_tone": "🚣🏽", + "person_running": "🏃", + "person_running_dark_skin_tone": "🏃🏿", + "person_running_light_skin_tone": "🏃🏻", + "person_running_medium-dark_skin_tone": "🏃🏾", + "person_running_medium-light_skin_tone": "🏃🏼", + "person_running_medium_skin_tone": "🏃🏽", + "person_shrugging": "🤷", + "person_shrugging_dark_skin_tone": "🤷🏿", + "person_shrugging_light_skin_tone": "🤷🏻", + "person_shrugging_medium-dark_skin_tone": "🤷🏾", + "person_shrugging_medium-light_skin_tone": "🤷🏼", + "person_shrugging_medium_skin_tone": "🤷🏽", + "person_standing": "🧍", + "person_surfing": "🏄", + "person_surfing_dark_skin_tone": "🏄🏿", + "person_surfing_light_skin_tone": "🏄🏻", + "person_surfing_medium-dark_skin_tone": "🏄🏾", + "person_surfing_medium-light_skin_tone": "🏄🏼", + "person_surfing_medium_skin_tone": "🏄🏽", + "person_swimming": "🏊", + "person_swimming_dark_skin_tone": "🏊🏿", + "person_swimming_light_skin_tone": "🏊🏻", + "person_swimming_medium-dark_skin_tone": "🏊🏾", + "person_swimming_medium-light_skin_tone": "🏊🏼", + "person_swimming_medium_skin_tone": "🏊🏽", + "person_taking_bath": "🛀", + "person_taking_bath_dark_skin_tone": "🛀🏿", + "person_taking_bath_light_skin_tone": "🛀🏻", + "person_taking_bath_medium-dark_skin_tone": "🛀🏾", + "person_taking_bath_medium-light_skin_tone": "🛀🏼", + "person_taking_bath_medium_skin_tone": "🛀🏽", + "person_tipping_hand": "💁", + "person_tipping_hand_dark_skin_tone": "💁🏿", + "person_tipping_hand_light_skin_tone": "💁🏻", + "person_tipping_hand_medium-dark_skin_tone": "💁🏾", + "person_tipping_hand_medium-light_skin_tone": "💁🏼", + "person_tipping_hand_medium_skin_tone": "💁🏽", + "person_walking": "🚶", + "person_walking_dark_skin_tone": "🚶🏿", + "person_walking_light_skin_tone": "🚶🏻", + "person_walking_medium-dark_skin_tone": "🚶🏾", + "person_walking_medium-light_skin_tone": "🚶🏼", + "person_walking_medium_skin_tone": "🚶🏽", + "person_wearing_turban": "👳", + "person_wearing_turban_dark_skin_tone": "👳🏿", + "person_wearing_turban_light_skin_tone": "👳🏻", + "person_wearing_turban_medium-dark_skin_tone": "👳🏾", + "person_wearing_turban_medium-light_skin_tone": "👳🏼", + "person_wearing_turban_medium_skin_tone": "👳🏽", + "petri_dish": "🧫", + "pick": "⛏", + "pie": "🥧", + "pig": "🐷", + "pig_face": "🐷", + "pig_nose": "🐽", + "pile_of_poo": "💩", + "pill": "💊", + "pinching_hand": "🤏", + "pine_decoration": "🎍", + "pineapple": "🍍", + "ping_pong": "🏓", + "pirate_flag": "🏴\u200d☠️", + "pistol": "🔫", + "pizza": "🍕", + "place_of_worship": "🛐", + "play_button": "▶", + "play_or_pause_button": "⏯", + "pleading_face": "🥺", + "police_car": "🚓", + "police_car_light": "🚨", + "police_officer": "👮", + "police_officer_dark_skin_tone": "👮🏿", + "police_officer_light_skin_tone": "👮🏻", + "police_officer_medium-dark_skin_tone": "👮🏾", + "police_officer_medium-light_skin_tone": "👮🏼", + "police_officer_medium_skin_tone": "👮🏽", + "poodle": "🐩", + "pool_8_ball": "🎱", + "popcorn": "🍿", + "post_office": "🏣", + "postal_horn": "📯", + "postbox": "📮", + "pot_of_food": "🍲", + "potable_water": "🚰", + "potato": "🥔", + "poultry_leg": "🍗", + "pound_banknote": "💷", + "pouting_cat_face": "😾", + "pouting_face": "😡", + "prayer_beads": "📿", + "pregnant_woman": "🤰", + "pregnant_woman_dark_skin_tone": "🤰🏿", + "pregnant_woman_light_skin_tone": "🤰🏻", + "pregnant_woman_medium-dark_skin_tone": "🤰🏾", + "pregnant_woman_medium-light_skin_tone": "🤰🏼", + "pregnant_woman_medium_skin_tone": "🤰🏽", + "pretzel": "🥨", + "probing_cane": "🦯", + "prince": "🤴", + "prince_dark_skin_tone": "🤴🏿", + "prince_light_skin_tone": "🤴🏻", + "prince_medium-dark_skin_tone": "🤴🏾", + "prince_medium-light_skin_tone": "🤴🏼", + "prince_medium_skin_tone": "🤴🏽", + "princess": "👸", + "princess_dark_skin_tone": "👸🏿", + "princess_light_skin_tone": "👸🏻", + "princess_medium-dark_skin_tone": "👸🏾", + "princess_medium-light_skin_tone": "👸🏼", + "princess_medium_skin_tone": "👸🏽", + "printer": "🖨", + "prohibited": "🚫", + "purple_circle": "🟣", + "purple_heart": "💜", + "purple_square": "🟪", + "purse": "👛", + "pushpin": "📌", + "question_mark": "❓", + "rabbit": "🐰", + "rabbit_face": "🐰", + "raccoon": "🦝", + "racing_car": "🏎", + "radio": "📻", + "radio_button": "🔘", + "radioactive": "☢", + "railway_car": "🚃", + "railway_track": "🛤", + "rainbow": "🌈", + "rainbow_flag": "🏳️\u200d🌈", + "raised_back_of_hand": "🤚", + "raised_back_of_hand_dark_skin_tone": "🤚🏿", + "raised_back_of_hand_light_skin_tone": "🤚🏻", + "raised_back_of_hand_medium-dark_skin_tone": "🤚🏾", + "raised_back_of_hand_medium-light_skin_tone": "🤚🏼", + "raised_back_of_hand_medium_skin_tone": "🤚🏽", + "raised_fist": "✊", + "raised_fist_dark_skin_tone": "✊🏿", + "raised_fist_light_skin_tone": "✊🏻", + "raised_fist_medium-dark_skin_tone": "✊🏾", + "raised_fist_medium-light_skin_tone": "✊🏼", + "raised_fist_medium_skin_tone": "✊🏽", + "raised_hand": "✋", + "raised_hand_dark_skin_tone": "✋🏿", + "raised_hand_light_skin_tone": "✋🏻", + "raised_hand_medium-dark_skin_tone": "✋🏾", + "raised_hand_medium-light_skin_tone": "✋🏼", + "raised_hand_medium_skin_tone": "✋🏽", + "raising_hands": "🙌", + "raising_hands_dark_skin_tone": "🙌🏿", + "raising_hands_light_skin_tone": "🙌🏻", + "raising_hands_medium-dark_skin_tone": "🙌🏾", + "raising_hands_medium-light_skin_tone": "🙌🏼", + "raising_hands_medium_skin_tone": "🙌🏽", + "ram": "🐏", + "rat": "🐀", + "razor": "🪒", + "ringed_planet": "🪐", + "receipt": "🧾", + "record_button": "⏺", + "recycling_symbol": "♻", + "red_apple": "🍎", + "red_circle": "🔴", + "red_envelope": "🧧", + "red_hair": "🦰", + "red-haired_man": "👨\u200d🦰", + "red-haired_woman": "👩\u200d🦰", + "red_heart": "❤", + "red_paper_lantern": "🏮", + "red_square": "🟥", + "red_triangle_pointed_down": "🔻", + "red_triangle_pointed_up": "🔺", + "registered": "®", + "relieved_face": "😌", + "reminder_ribbon": "🎗", + "repeat_button": "🔁", + "repeat_single_button": "🔂", + "rescue_worker’s_helmet": "⛑", + "restroom": "🚻", + "reverse_button": "◀", + "revolving_hearts": "💞", + "rhinoceros": "🦏", + "ribbon": "🎀", + "rice_ball": "🍙", + "rice_cracker": "🍘", + "right-facing_fist": "🤜", + "right-facing_fist_dark_skin_tone": "🤜🏿", + "right-facing_fist_light_skin_tone": "🤜🏻", + "right-facing_fist_medium-dark_skin_tone": "🤜🏾", + "right-facing_fist_medium-light_skin_tone": "🤜🏼", + "right-facing_fist_medium_skin_tone": "🤜🏽", + "right_anger_bubble": "🗯", + "right_arrow": "➡", + "right_arrow_curving_down": "⤵", + "right_arrow_curving_left": "↩", + "right_arrow_curving_up": "⤴", + "ring": "💍", + "roasted_sweet_potato": "🍠", + "robot_face": "🤖", + "rocket": "🚀", + "roll_of_paper": "🧻", + "rolled-up_newspaper": "🗞", + "roller_coaster": "🎢", + "rolling_on_the_floor_laughing": "🤣", + "rooster": "🐓", + "rose": "🌹", + "rosette": "🏵", + "round_pushpin": "📍", + "rugby_football": "🏉", + "running_shirt": "🎽", + "running_shoe": "👟", + "sad_but_relieved_face": "😥", + "safety_pin": "🧷", + "safety_vest": "🦺", + "salt": "🧂", + "sailboat": "⛵", + "sake": "🍶", + "sandwich": "🥪", + "sari": "🥻", + "satellite": "📡", + "satellite_antenna": "📡", + "sauropod": "🦕", + "saxophone": "🎷", + "scarf": "🧣", + "school": "🏫", + "school_backpack": "🎒", + "scissors": "✂", + "scorpion": "🦂", + "scroll": "📜", + "seat": "💺", + "see-no-evil_monkey": "🙈", + "seedling": "🌱", + "selfie": "🤳", + "selfie_dark_skin_tone": "🤳🏿", + "selfie_light_skin_tone": "🤳🏻", + "selfie_medium-dark_skin_tone": "🤳🏾", + "selfie_medium-light_skin_tone": "🤳🏼", + "selfie_medium_skin_tone": "🤳🏽", + "service_dog": "🐕\u200d🦺", + "seven-thirty": "🕢", + "seven_o’clock": "🕖", + "shallow_pan_of_food": "🥘", + "shamrock": "☘", + "shark": "🦈", + "shaved_ice": "🍧", + "sheaf_of_rice": "🌾", + "shield": "🛡", + "shinto_shrine": "⛩", + "ship": "🚢", + "shooting_star": "🌠", + "shopping_bags": "🛍", + "shopping_cart": "🛒", + "shortcake": "🍰", + "shorts": "🩳", + "shower": "🚿", + "shrimp": "🦐", + "shuffle_tracks_button": "🔀", + "shushing_face": "🤫", + "sign_of_the_horns": "🤘", + "sign_of_the_horns_dark_skin_tone": "🤘🏿", + "sign_of_the_horns_light_skin_tone": "🤘🏻", + "sign_of_the_horns_medium-dark_skin_tone": "🤘🏾", + "sign_of_the_horns_medium-light_skin_tone": "🤘🏼", + "sign_of_the_horns_medium_skin_tone": "🤘🏽", + "six-thirty": "🕡", + "six_o’clock": "🕕", + "skateboard": "🛹", + "skier": "⛷", + "skis": "🎿", + "skull": "💀", + "skull_and_crossbones": "☠", + "skunk": "🦨", + "sled": "🛷", + "sleeping_face": "😴", + "sleepy_face": "😪", + "slightly_frowning_face": "🙁", + "slightly_smiling_face": "🙂", + "slot_machine": "🎰", + "sloth": "🦥", + "small_airplane": "🛩", + "small_blue_diamond": "🔹", + "small_orange_diamond": "🔸", + "smiling_cat_face_with_heart-eyes": "😻", + "smiling_face": "☺", + "smiling_face_with_halo": "😇", + "smiling_face_with_3_hearts": "🥰", + "smiling_face_with_heart-eyes": "😍", + "smiling_face_with_horns": "😈", + "smiling_face_with_smiling_eyes": "😊", + "smiling_face_with_sunglasses": "😎", + "smirking_face": "😏", + "snail": "🐌", + "snake": "🐍", + "sneezing_face": "🤧", + "snow-capped_mountain": "🏔", + "snowboarder": "🏂", + "snowboarder_dark_skin_tone": "🏂🏿", + "snowboarder_light_skin_tone": "🏂🏻", + "snowboarder_medium-dark_skin_tone": "🏂🏾", + "snowboarder_medium-light_skin_tone": "🏂🏼", + "snowboarder_medium_skin_tone": "🏂🏽", + "snowflake": "❄", + "snowman": "☃", + "snowman_without_snow": "⛄", + "soap": "🧼", + "soccer_ball": "⚽", + "socks": "🧦", + "softball": "🥎", + "soft_ice_cream": "🍦", + "spade_suit": "♠", + "spaghetti": "🍝", + "sparkle": "❇", + "sparkler": "🎇", + "sparkles": "✨", + "sparkling_heart": "💖", + "speak-no-evil_monkey": "🙊", + "speaker_high_volume": "🔊", + "speaker_low_volume": "🔈", + "speaker_medium_volume": "🔉", + "speaking_head": "🗣", + "speech_balloon": "💬", + "speedboat": "🚤", + "spider": "🕷", + "spider_web": "🕸", + "spiral_calendar": "🗓", + "spiral_notepad": "🗒", + "spiral_shell": "🐚", + "spoon": "🥄", + "sponge": "🧽", + "sport_utility_vehicle": "🚙", + "sports_medal": "🏅", + "spouting_whale": "🐳", + "squid": "🦑", + "squinting_face_with_tongue": "😝", + "stadium": "🏟", + "star-struck": "🤩", + "star_and_crescent": "☪", + "star_of_david": "✡", + "station": "🚉", + "steaming_bowl": "🍜", + "stethoscope": "🩺", + "stop_button": "⏹", + "stop_sign": "🛑", + "stopwatch": "⏱", + "straight_ruler": "📏", + "strawberry": "🍓", + "studio_microphone": "🎙", + "stuffed_flatbread": "🥙", + "sun": "☀", + "sun_behind_cloud": "⛅", + "sun_behind_large_cloud": "🌥", + "sun_behind_rain_cloud": "🌦", + "sun_behind_small_cloud": "🌤", + "sun_with_face": "🌞", + "sunflower": "🌻", + "sunglasses": "😎", + "sunrise": "🌅", + "sunrise_over_mountains": "🌄", + "sunset": "🌇", + "superhero": "🦸", + "supervillain": "🦹", + "sushi": "🍣", + "suspension_railway": "🚟", + "swan": "🦢", + "sweat_droplets": "💦", + "synagogue": "🕍", + "syringe": "💉", + "t-shirt": "👕", + "taco": "🌮", + "takeout_box": "🥡", + "tanabata_tree": "🎋", + "tangerine": "🍊", + "taxi": "🚕", + "teacup_without_handle": "🍵", + "tear-off_calendar": "📆", + "teddy_bear": "🧸", + "telephone": "☎", + "telephone_receiver": "📞", + "telescope": "🔭", + "television": "📺", + "ten-thirty": "🕥", + "ten_o’clock": "🕙", + "tennis": "🎾", + "tent": "⛺", + "test_tube": "🧪", + "thermometer": "🌡", + "thinking_face": "🤔", + "thought_balloon": "💭", + "thread": "🧵", + "three-thirty": "🕞", + "three_o’clock": "🕒", + "thumbs_down": "👎", + "thumbs_down_dark_skin_tone": "👎🏿", + "thumbs_down_light_skin_tone": "👎🏻", + "thumbs_down_medium-dark_skin_tone": "👎🏾", + "thumbs_down_medium-light_skin_tone": "👎🏼", + "thumbs_down_medium_skin_tone": "👎🏽", + "thumbs_up": "👍", + "thumbs_up_dark_skin_tone": "👍🏿", + "thumbs_up_light_skin_tone": "👍🏻", + "thumbs_up_medium-dark_skin_tone": "👍🏾", + "thumbs_up_medium-light_skin_tone": "👍🏼", + "thumbs_up_medium_skin_tone": "👍🏽", + "ticket": "🎫", + "tiger": "🐯", + "tiger_face": "🐯", + "timer_clock": "⏲", + "tired_face": "😫", + "toolbox": "🧰", + "toilet": "🚽", + "tomato": "🍅", + "tongue": "👅", + "tooth": "🦷", + "top_hat": "🎩", + "tornado": "🌪", + "trackball": "🖲", + "tractor": "🚜", + "trade_mark": "™", + "train": "🚋", + "tram": "🚊", + "tram_car": "🚋", + "triangular_flag": "🚩", + "triangular_ruler": "📐", + "trident_emblem": "🔱", + "trolleybus": "🚎", + "trophy": "🏆", + "tropical_drink": "🍹", + "tropical_fish": "🐠", + "trumpet": "🎺", + "tulip": "🌷", + "tumbler_glass": "🥃", + "turtle": "🐢", + "twelve-thirty": "🕧", + "twelve_o’clock": "🕛", + "two-hump_camel": "🐫", + "two-thirty": "🕝", + "two_hearts": "💕", + "two_men_holding_hands": "👬", + "two_o’clock": "🕑", + "two_women_holding_hands": "👭", + "umbrella": "☂", + "umbrella_on_ground": "⛱", + "umbrella_with_rain_drops": "☔", + "unamused_face": "😒", + "unicorn_face": "🦄", + "unlocked": "🔓", + "up-down_arrow": "↕", + "up-left_arrow": "↖", + "up-right_arrow": "↗", + "up_arrow": "⬆", + "upside-down_face": "🙃", + "upwards_button": "🔼", + "vampire": "🧛", + "vampire_dark_skin_tone": "🧛🏿", + "vampire_light_skin_tone": "🧛🏻", + "vampire_medium-dark_skin_tone": "🧛🏾", + "vampire_medium-light_skin_tone": "🧛🏼", + "vampire_medium_skin_tone": "🧛🏽", + "vertical_traffic_light": "🚦", + "vibration_mode": "📳", + "victory_hand": "✌", + "victory_hand_dark_skin_tone": "✌🏿", + "victory_hand_light_skin_tone": "✌🏻", + "victory_hand_medium-dark_skin_tone": "✌🏾", + "victory_hand_medium-light_skin_tone": "✌🏼", + "victory_hand_medium_skin_tone": "✌🏽", + "video_camera": "📹", + "video_game": "🎮", + "videocassette": "📼", + "violin": "🎻", + "volcano": "🌋", + "volleyball": "🏐", + "vulcan_salute": "🖖", + "vulcan_salute_dark_skin_tone": "🖖🏿", + "vulcan_salute_light_skin_tone": "🖖🏻", + "vulcan_salute_medium-dark_skin_tone": "🖖🏾", + "vulcan_salute_medium-light_skin_tone": "🖖🏼", + "vulcan_salute_medium_skin_tone": "🖖🏽", + "waffle": "🧇", + "waning_crescent_moon": "🌘", + "waning_gibbous_moon": "🌖", + "warning": "⚠", + "wastebasket": "🗑", + "watch": "⌚", + "water_buffalo": "🐃", + "water_closet": "🚾", + "water_wave": "🌊", + "watermelon": "🍉", + "waving_hand": "👋", + "waving_hand_dark_skin_tone": "👋🏿", + "waving_hand_light_skin_tone": "👋🏻", + "waving_hand_medium-dark_skin_tone": "👋🏾", + "waving_hand_medium-light_skin_tone": "👋🏼", + "waving_hand_medium_skin_tone": "👋🏽", + "wavy_dash": "〰", + "waxing_crescent_moon": "🌒", + "waxing_gibbous_moon": "🌔", + "weary_cat_face": "🙀", + "weary_face": "😩", + "wedding": "💒", + "whale": "🐳", + "wheel_of_dharma": "☸", + "wheelchair_symbol": "♿", + "white_circle": "⚪", + "white_exclamation_mark": "❕", + "white_flag": "🏳", + "white_flower": "💮", + "white_hair": "🦳", + "white-haired_man": "👨\u200d🦳", + "white-haired_woman": "👩\u200d🦳", + "white_heart": "🤍", + "white_heavy_check_mark": "✅", + "white_large_square": "⬜", + "white_medium-small_square": "◽", + "white_medium_square": "◻", + "white_medium_star": "⭐", + "white_question_mark": "❔", + "white_small_square": "▫", + "white_square_button": "🔳", + "wilted_flower": "🥀", + "wind_chime": "🎐", + "wind_face": "🌬", + "wine_glass": "🍷", + "winking_face": "😉", + "winking_face_with_tongue": "😜", + "wolf_face": "🐺", + "woman": "👩", + "woman_artist": "👩\u200d🎨", + "woman_artist_dark_skin_tone": "👩🏿\u200d🎨", + "woman_artist_light_skin_tone": "👩🏻\u200d🎨", + "woman_artist_medium-dark_skin_tone": "👩🏾\u200d🎨", + "woman_artist_medium-light_skin_tone": "👩🏼\u200d🎨", + "woman_artist_medium_skin_tone": "👩🏽\u200d🎨", + "woman_astronaut": "👩\u200d🚀", + "woman_astronaut_dark_skin_tone": "👩🏿\u200d🚀", + "woman_astronaut_light_skin_tone": "👩🏻\u200d🚀", + "woman_astronaut_medium-dark_skin_tone": "👩🏾\u200d🚀", + "woman_astronaut_medium-light_skin_tone": "👩🏼\u200d🚀", + "woman_astronaut_medium_skin_tone": "👩🏽\u200d🚀", + "woman_biking": "🚴\u200d♀️", + "woman_biking_dark_skin_tone": "🚴🏿\u200d♀️", + "woman_biking_light_skin_tone": "🚴🏻\u200d♀️", + "woman_biking_medium-dark_skin_tone": "🚴🏾\u200d♀️", + "woman_biking_medium-light_skin_tone": "🚴🏼\u200d♀️", + "woman_biking_medium_skin_tone": "🚴🏽\u200d♀️", + "woman_bouncing_ball": "⛹️\u200d♀️", + "woman_bouncing_ball_dark_skin_tone": "⛹🏿\u200d♀️", + "woman_bouncing_ball_light_skin_tone": "⛹🏻\u200d♀️", + "woman_bouncing_ball_medium-dark_skin_tone": "⛹🏾\u200d♀️", + "woman_bouncing_ball_medium-light_skin_tone": "⛹🏼\u200d♀️", + "woman_bouncing_ball_medium_skin_tone": "⛹🏽\u200d♀️", + "woman_bowing": "🙇\u200d♀️", + "woman_bowing_dark_skin_tone": "🙇🏿\u200d♀️", + "woman_bowing_light_skin_tone": "🙇🏻\u200d♀️", + "woman_bowing_medium-dark_skin_tone": "🙇🏾\u200d♀️", + "woman_bowing_medium-light_skin_tone": "🙇🏼\u200d♀️", + "woman_bowing_medium_skin_tone": "🙇🏽\u200d♀️", + "woman_cartwheeling": "🤸\u200d♀️", + "woman_cartwheeling_dark_skin_tone": "🤸🏿\u200d♀️", + "woman_cartwheeling_light_skin_tone": "🤸🏻\u200d♀️", + "woman_cartwheeling_medium-dark_skin_tone": "🤸🏾\u200d♀️", + "woman_cartwheeling_medium-light_skin_tone": "🤸🏼\u200d♀️", + "woman_cartwheeling_medium_skin_tone": "🤸🏽\u200d♀️", + "woman_climbing": "🧗\u200d♀️", + "woman_climbing_dark_skin_tone": "🧗🏿\u200d♀️", + "woman_climbing_light_skin_tone": "🧗🏻\u200d♀️", + "woman_climbing_medium-dark_skin_tone": "🧗🏾\u200d♀️", + "woman_climbing_medium-light_skin_tone": "🧗🏼\u200d♀️", + "woman_climbing_medium_skin_tone": "🧗🏽\u200d♀️", + "woman_construction_worker": "👷\u200d♀️", + "woman_construction_worker_dark_skin_tone": "👷🏿\u200d♀️", + "woman_construction_worker_light_skin_tone": "👷🏻\u200d♀️", + "woman_construction_worker_medium-dark_skin_tone": "👷🏾\u200d♀️", + "woman_construction_worker_medium-light_skin_tone": "👷🏼\u200d♀️", + "woman_construction_worker_medium_skin_tone": "👷🏽\u200d♀️", + "woman_cook": "👩\u200d🍳", + "woman_cook_dark_skin_tone": "👩🏿\u200d🍳", + "woman_cook_light_skin_tone": "👩🏻\u200d🍳", + "woman_cook_medium-dark_skin_tone": "👩🏾\u200d🍳", + "woman_cook_medium-light_skin_tone": "👩🏼\u200d🍳", + "woman_cook_medium_skin_tone": "👩🏽\u200d🍳", + "woman_dancing": "💃", + "woman_dancing_dark_skin_tone": "💃🏿", + "woman_dancing_light_skin_tone": "💃🏻", + "woman_dancing_medium-dark_skin_tone": "💃🏾", + "woman_dancing_medium-light_skin_tone": "💃🏼", + "woman_dancing_medium_skin_tone": "💃🏽", + "woman_dark_skin_tone": "👩🏿", + "woman_detective": "🕵️\u200d♀️", + "woman_detective_dark_skin_tone": "🕵🏿\u200d♀️", + "woman_detective_light_skin_tone": "🕵🏻\u200d♀️", + "woman_detective_medium-dark_skin_tone": "🕵🏾\u200d♀️", + "woman_detective_medium-light_skin_tone": "🕵🏼\u200d♀️", + "woman_detective_medium_skin_tone": "🕵🏽\u200d♀️", + "woman_elf": "🧝\u200d♀️", + "woman_elf_dark_skin_tone": "🧝🏿\u200d♀️", + "woman_elf_light_skin_tone": "🧝🏻\u200d♀️", + "woman_elf_medium-dark_skin_tone": "🧝🏾\u200d♀️", + "woman_elf_medium-light_skin_tone": "🧝🏼\u200d♀️", + "woman_elf_medium_skin_tone": "🧝🏽\u200d♀️", + "woman_facepalming": "🤦\u200d♀️", + "woman_facepalming_dark_skin_tone": "🤦🏿\u200d♀️", + "woman_facepalming_light_skin_tone": "🤦🏻\u200d♀️", + "woman_facepalming_medium-dark_skin_tone": "🤦🏾\u200d♀️", + "woman_facepalming_medium-light_skin_tone": "🤦🏼\u200d♀️", + "woman_facepalming_medium_skin_tone": "🤦🏽\u200d♀️", + "woman_factory_worker": "👩\u200d🏭", + "woman_factory_worker_dark_skin_tone": "👩🏿\u200d🏭", + "woman_factory_worker_light_skin_tone": "👩🏻\u200d🏭", + "woman_factory_worker_medium-dark_skin_tone": "👩🏾\u200d🏭", + "woman_factory_worker_medium-light_skin_tone": "👩🏼\u200d🏭", + "woman_factory_worker_medium_skin_tone": "👩🏽\u200d🏭", + "woman_fairy": "🧚\u200d♀️", + "woman_fairy_dark_skin_tone": "🧚🏿\u200d♀️", + "woman_fairy_light_skin_tone": "🧚🏻\u200d♀️", + "woman_fairy_medium-dark_skin_tone": "🧚🏾\u200d♀️", + "woman_fairy_medium-light_skin_tone": "🧚🏼\u200d♀️", + "woman_fairy_medium_skin_tone": "🧚🏽\u200d♀️", + "woman_farmer": "👩\u200d🌾", + "woman_farmer_dark_skin_tone": "👩🏿\u200d🌾", + "woman_farmer_light_skin_tone": "👩🏻\u200d🌾", + "woman_farmer_medium-dark_skin_tone": "👩🏾\u200d🌾", + "woman_farmer_medium-light_skin_tone": "👩🏼\u200d🌾", + "woman_farmer_medium_skin_tone": "👩🏽\u200d🌾", + "woman_firefighter": "👩\u200d🚒", + "woman_firefighter_dark_skin_tone": "👩🏿\u200d🚒", + "woman_firefighter_light_skin_tone": "👩🏻\u200d🚒", + "woman_firefighter_medium-dark_skin_tone": "👩🏾\u200d🚒", + "woman_firefighter_medium-light_skin_tone": "👩🏼\u200d🚒", + "woman_firefighter_medium_skin_tone": "👩🏽\u200d🚒", + "woman_frowning": "🙍\u200d♀️", + "woman_frowning_dark_skin_tone": "🙍🏿\u200d♀️", + "woman_frowning_light_skin_tone": "🙍🏻\u200d♀️", + "woman_frowning_medium-dark_skin_tone": "🙍🏾\u200d♀️", + "woman_frowning_medium-light_skin_tone": "🙍🏼\u200d♀️", + "woman_frowning_medium_skin_tone": "🙍🏽\u200d♀️", + "woman_genie": "🧞\u200d♀️", + "woman_gesturing_no": "🙅\u200d♀️", + "woman_gesturing_no_dark_skin_tone": "🙅🏿\u200d♀️", + "woman_gesturing_no_light_skin_tone": "🙅🏻\u200d♀️", + "woman_gesturing_no_medium-dark_skin_tone": "🙅🏾\u200d♀️", + "woman_gesturing_no_medium-light_skin_tone": "🙅🏼\u200d♀️", + "woman_gesturing_no_medium_skin_tone": "🙅🏽\u200d♀️", + "woman_gesturing_ok": "🙆\u200d♀️", + "woman_gesturing_ok_dark_skin_tone": "🙆🏿\u200d♀️", + "woman_gesturing_ok_light_skin_tone": "🙆🏻\u200d♀️", + "woman_gesturing_ok_medium-dark_skin_tone": "🙆🏾\u200d♀️", + "woman_gesturing_ok_medium-light_skin_tone": "🙆🏼\u200d♀️", + "woman_gesturing_ok_medium_skin_tone": "🙆🏽\u200d♀️", + "woman_getting_haircut": "💇\u200d♀️", + "woman_getting_haircut_dark_skin_tone": "💇🏿\u200d♀️", + "woman_getting_haircut_light_skin_tone": "💇🏻\u200d♀️", + "woman_getting_haircut_medium-dark_skin_tone": "💇🏾\u200d♀️", + "woman_getting_haircut_medium-light_skin_tone": "💇🏼\u200d♀️", + "woman_getting_haircut_medium_skin_tone": "💇🏽\u200d♀️", + "woman_getting_massage": "💆\u200d♀️", + "woman_getting_massage_dark_skin_tone": "💆🏿\u200d♀️", + "woman_getting_massage_light_skin_tone": "💆🏻\u200d♀️", + "woman_getting_massage_medium-dark_skin_tone": "💆🏾\u200d♀️", + "woman_getting_massage_medium-light_skin_tone": "💆🏼\u200d♀️", + "woman_getting_massage_medium_skin_tone": "💆🏽\u200d♀️", + "woman_golfing": "🏌️\u200d♀️", + "woman_golfing_dark_skin_tone": "🏌🏿\u200d♀️", + "woman_golfing_light_skin_tone": "🏌🏻\u200d♀️", + "woman_golfing_medium-dark_skin_tone": "🏌🏾\u200d♀️", + "woman_golfing_medium-light_skin_tone": "🏌🏼\u200d♀️", + "woman_golfing_medium_skin_tone": "🏌🏽\u200d♀️", + "woman_guard": "💂\u200d♀️", + "woman_guard_dark_skin_tone": "💂🏿\u200d♀️", + "woman_guard_light_skin_tone": "💂🏻\u200d♀️", + "woman_guard_medium-dark_skin_tone": "💂🏾\u200d♀️", + "woman_guard_medium-light_skin_tone": "💂🏼\u200d♀️", + "woman_guard_medium_skin_tone": "💂🏽\u200d♀️", + "woman_health_worker": "👩\u200d⚕️", + "woman_health_worker_dark_skin_tone": "👩🏿\u200d⚕️", + "woman_health_worker_light_skin_tone": "👩🏻\u200d⚕️", + "woman_health_worker_medium-dark_skin_tone": "👩🏾\u200d⚕️", + "woman_health_worker_medium-light_skin_tone": "👩🏼\u200d⚕️", + "woman_health_worker_medium_skin_tone": "👩🏽\u200d⚕️", + "woman_in_lotus_position": "🧘\u200d♀️", + "woman_in_lotus_position_dark_skin_tone": "🧘🏿\u200d♀️", + "woman_in_lotus_position_light_skin_tone": "🧘🏻\u200d♀️", + "woman_in_lotus_position_medium-dark_skin_tone": "🧘🏾\u200d♀️", + "woman_in_lotus_position_medium-light_skin_tone": "🧘🏼\u200d♀️", + "woman_in_lotus_position_medium_skin_tone": "🧘🏽\u200d♀️", + "woman_in_manual_wheelchair": "👩\u200d🦽", + "woman_in_motorized_wheelchair": "👩\u200d🦼", + "woman_in_steamy_room": "🧖\u200d♀️", + "woman_in_steamy_room_dark_skin_tone": "🧖🏿\u200d♀️", + "woman_in_steamy_room_light_skin_tone": "🧖🏻\u200d♀️", + "woman_in_steamy_room_medium-dark_skin_tone": "🧖🏾\u200d♀️", + "woman_in_steamy_room_medium-light_skin_tone": "🧖🏼\u200d♀️", + "woman_in_steamy_room_medium_skin_tone": "🧖🏽\u200d♀️", + "woman_judge": "👩\u200d⚖️", + "woman_judge_dark_skin_tone": "👩🏿\u200d⚖️", + "woman_judge_light_skin_tone": "👩🏻\u200d⚖️", + "woman_judge_medium-dark_skin_tone": "👩🏾\u200d⚖️", + "woman_judge_medium-light_skin_tone": "👩🏼\u200d⚖️", + "woman_judge_medium_skin_tone": "👩🏽\u200d⚖️", + "woman_juggling": "🤹\u200d♀️", + "woman_juggling_dark_skin_tone": "🤹🏿\u200d♀️", + "woman_juggling_light_skin_tone": "🤹🏻\u200d♀️", + "woman_juggling_medium-dark_skin_tone": "🤹🏾\u200d♀️", + "woman_juggling_medium-light_skin_tone": "🤹🏼\u200d♀️", + "woman_juggling_medium_skin_tone": "🤹🏽\u200d♀️", + "woman_lifting_weights": "🏋️\u200d♀️", + "woman_lifting_weights_dark_skin_tone": "🏋🏿\u200d♀️", + "woman_lifting_weights_light_skin_tone": "🏋🏻\u200d♀️", + "woman_lifting_weights_medium-dark_skin_tone": "🏋🏾\u200d♀️", + "woman_lifting_weights_medium-light_skin_tone": "🏋🏼\u200d♀️", + "woman_lifting_weights_medium_skin_tone": "🏋🏽\u200d♀️", + "woman_light_skin_tone": "👩🏻", + "woman_mage": "🧙\u200d♀️", + "woman_mage_dark_skin_tone": "🧙🏿\u200d♀️", + "woman_mage_light_skin_tone": "🧙🏻\u200d♀️", + "woman_mage_medium-dark_skin_tone": "🧙🏾\u200d♀️", + "woman_mage_medium-light_skin_tone": "🧙🏼\u200d♀️", + "woman_mage_medium_skin_tone": "🧙🏽\u200d♀️", + "woman_mechanic": "👩\u200d🔧", + "woman_mechanic_dark_skin_tone": "👩🏿\u200d🔧", + "woman_mechanic_light_skin_tone": "👩🏻\u200d🔧", + "woman_mechanic_medium-dark_skin_tone": "👩🏾\u200d🔧", + "woman_mechanic_medium-light_skin_tone": "👩🏼\u200d🔧", + "woman_mechanic_medium_skin_tone": "👩🏽\u200d🔧", + "woman_medium-dark_skin_tone": "👩🏾", + "woman_medium-light_skin_tone": "👩🏼", + "woman_medium_skin_tone": "👩🏽", + "woman_mountain_biking": "🚵\u200d♀️", + "woman_mountain_biking_dark_skin_tone": "🚵🏿\u200d♀️", + "woman_mountain_biking_light_skin_tone": "🚵🏻\u200d♀️", + "woman_mountain_biking_medium-dark_skin_tone": "🚵🏾\u200d♀️", + "woman_mountain_biking_medium-light_skin_tone": "🚵🏼\u200d♀️", + "woman_mountain_biking_medium_skin_tone": "🚵🏽\u200d♀️", + "woman_office_worker": "👩\u200d💼", + "woman_office_worker_dark_skin_tone": "👩🏿\u200d💼", + "woman_office_worker_light_skin_tone": "👩🏻\u200d💼", + "woman_office_worker_medium-dark_skin_tone": "👩🏾\u200d💼", + "woman_office_worker_medium-light_skin_tone": "👩🏼\u200d💼", + "woman_office_worker_medium_skin_tone": "👩🏽\u200d💼", + "woman_pilot": "👩\u200d✈️", + "woman_pilot_dark_skin_tone": "👩🏿\u200d✈️", + "woman_pilot_light_skin_tone": "👩🏻\u200d✈️", + "woman_pilot_medium-dark_skin_tone": "👩🏾\u200d✈️", + "woman_pilot_medium-light_skin_tone": "👩🏼\u200d✈️", + "woman_pilot_medium_skin_tone": "👩🏽\u200d✈️", + "woman_playing_handball": "🤾\u200d♀️", + "woman_playing_handball_dark_skin_tone": "🤾🏿\u200d♀️", + "woman_playing_handball_light_skin_tone": "🤾🏻\u200d♀️", + "woman_playing_handball_medium-dark_skin_tone": "🤾🏾\u200d♀️", + "woman_playing_handball_medium-light_skin_tone": "🤾🏼\u200d♀️", + "woman_playing_handball_medium_skin_tone": "🤾🏽\u200d♀️", + "woman_playing_water_polo": "🤽\u200d♀️", + "woman_playing_water_polo_dark_skin_tone": "🤽🏿\u200d♀️", + "woman_playing_water_polo_light_skin_tone": "🤽🏻\u200d♀️", + "woman_playing_water_polo_medium-dark_skin_tone": "🤽🏾\u200d♀️", + "woman_playing_water_polo_medium-light_skin_tone": "🤽🏼\u200d♀️", + "woman_playing_water_polo_medium_skin_tone": "🤽🏽\u200d♀️", + "woman_police_officer": "👮\u200d♀️", + "woman_police_officer_dark_skin_tone": "👮🏿\u200d♀️", + "woman_police_officer_light_skin_tone": "👮🏻\u200d♀️", + "woman_police_officer_medium-dark_skin_tone": "👮🏾\u200d♀️", + "woman_police_officer_medium-light_skin_tone": "👮🏼\u200d♀️", + "woman_police_officer_medium_skin_tone": "👮🏽\u200d♀️", + "woman_pouting": "🙎\u200d♀️", + "woman_pouting_dark_skin_tone": "🙎🏿\u200d♀️", + "woman_pouting_light_skin_tone": "🙎🏻\u200d♀️", + "woman_pouting_medium-dark_skin_tone": "🙎🏾\u200d♀️", + "woman_pouting_medium-light_skin_tone": "🙎🏼\u200d♀️", + "woman_pouting_medium_skin_tone": "🙎🏽\u200d♀️", + "woman_raising_hand": "🙋\u200d♀️", + "woman_raising_hand_dark_skin_tone": "🙋🏿\u200d♀️", + "woman_raising_hand_light_skin_tone": "🙋🏻\u200d♀️", + "woman_raising_hand_medium-dark_skin_tone": "🙋🏾\u200d♀️", + "woman_raising_hand_medium-light_skin_tone": "🙋🏼\u200d♀️", + "woman_raising_hand_medium_skin_tone": "🙋🏽\u200d♀️", + "woman_rowing_boat": "🚣\u200d♀️", + "woman_rowing_boat_dark_skin_tone": "🚣🏿\u200d♀️", + "woman_rowing_boat_light_skin_tone": "🚣🏻\u200d♀️", + "woman_rowing_boat_medium-dark_skin_tone": "🚣🏾\u200d♀️", + "woman_rowing_boat_medium-light_skin_tone": "🚣🏼\u200d♀️", + "woman_rowing_boat_medium_skin_tone": "🚣🏽\u200d♀️", + "woman_running": "🏃\u200d♀️", + "woman_running_dark_skin_tone": "🏃🏿\u200d♀️", + "woman_running_light_skin_tone": "🏃🏻\u200d♀️", + "woman_running_medium-dark_skin_tone": "🏃🏾\u200d♀️", + "woman_running_medium-light_skin_tone": "🏃🏼\u200d♀️", + "woman_running_medium_skin_tone": "🏃🏽\u200d♀️", + "woman_scientist": "👩\u200d🔬", + "woman_scientist_dark_skin_tone": "👩🏿\u200d🔬", + "woman_scientist_light_skin_tone": "👩🏻\u200d🔬", + "woman_scientist_medium-dark_skin_tone": "👩🏾\u200d🔬", + "woman_scientist_medium-light_skin_tone": "👩🏼\u200d🔬", + "woman_scientist_medium_skin_tone": "👩🏽\u200d🔬", + "woman_shrugging": "🤷\u200d♀️", + "woman_shrugging_dark_skin_tone": "🤷🏿\u200d♀️", + "woman_shrugging_light_skin_tone": "🤷🏻\u200d♀️", + "woman_shrugging_medium-dark_skin_tone": "🤷🏾\u200d♀️", + "woman_shrugging_medium-light_skin_tone": "🤷🏼\u200d♀️", + "woman_shrugging_medium_skin_tone": "🤷🏽\u200d♀️", + "woman_singer": "👩\u200d🎤", + "woman_singer_dark_skin_tone": "👩🏿\u200d🎤", + "woman_singer_light_skin_tone": "👩🏻\u200d🎤", + "woman_singer_medium-dark_skin_tone": "👩🏾\u200d🎤", + "woman_singer_medium-light_skin_tone": "👩🏼\u200d🎤", + "woman_singer_medium_skin_tone": "👩🏽\u200d🎤", + "woman_student": "👩\u200d🎓", + "woman_student_dark_skin_tone": "👩🏿\u200d🎓", + "woman_student_light_skin_tone": "👩🏻\u200d🎓", + "woman_student_medium-dark_skin_tone": "👩🏾\u200d🎓", + "woman_student_medium-light_skin_tone": "👩🏼\u200d🎓", + "woman_student_medium_skin_tone": "👩🏽\u200d🎓", + "woman_surfing": "🏄\u200d♀️", + "woman_surfing_dark_skin_tone": "🏄🏿\u200d♀️", + "woman_surfing_light_skin_tone": "🏄🏻\u200d♀️", + "woman_surfing_medium-dark_skin_tone": "🏄🏾\u200d♀️", + "woman_surfing_medium-light_skin_tone": "🏄🏼\u200d♀️", + "woman_surfing_medium_skin_tone": "🏄🏽\u200d♀️", + "woman_swimming": "🏊\u200d♀️", + "woman_swimming_dark_skin_tone": "🏊🏿\u200d♀️", + "woman_swimming_light_skin_tone": "🏊🏻\u200d♀️", + "woman_swimming_medium-dark_skin_tone": "🏊🏾\u200d♀️", + "woman_swimming_medium-light_skin_tone": "🏊🏼\u200d♀️", + "woman_swimming_medium_skin_tone": "🏊🏽\u200d♀️", + "woman_teacher": "👩\u200d🏫", + "woman_teacher_dark_skin_tone": "👩🏿\u200d🏫", + "woman_teacher_light_skin_tone": "👩🏻\u200d🏫", + "woman_teacher_medium-dark_skin_tone": "👩🏾\u200d🏫", + "woman_teacher_medium-light_skin_tone": "👩🏼\u200d🏫", + "woman_teacher_medium_skin_tone": "👩🏽\u200d🏫", + "woman_technologist": "👩\u200d💻", + "woman_technologist_dark_skin_tone": "👩🏿\u200d💻", + "woman_technologist_light_skin_tone": "👩🏻\u200d💻", + "woman_technologist_medium-dark_skin_tone": "👩🏾\u200d💻", + "woman_technologist_medium-light_skin_tone": "👩🏼\u200d💻", + "woman_technologist_medium_skin_tone": "👩🏽\u200d💻", + "woman_tipping_hand": "💁\u200d♀️", + "woman_tipping_hand_dark_skin_tone": "💁🏿\u200d♀️", + "woman_tipping_hand_light_skin_tone": "💁🏻\u200d♀️", + "woman_tipping_hand_medium-dark_skin_tone": "💁🏾\u200d♀️", + "woman_tipping_hand_medium-light_skin_tone": "💁🏼\u200d♀️", + "woman_tipping_hand_medium_skin_tone": "💁🏽\u200d♀️", + "woman_vampire": "🧛\u200d♀️", + "woman_vampire_dark_skin_tone": "🧛🏿\u200d♀️", + "woman_vampire_light_skin_tone": "🧛🏻\u200d♀️", + "woman_vampire_medium-dark_skin_tone": "🧛🏾\u200d♀️", + "woman_vampire_medium-light_skin_tone": "🧛🏼\u200d♀️", + "woman_vampire_medium_skin_tone": "🧛🏽\u200d♀️", + "woman_walking": "🚶\u200d♀️", + "woman_walking_dark_skin_tone": "🚶🏿\u200d♀️", + "woman_walking_light_skin_tone": "🚶🏻\u200d♀️", + "woman_walking_medium-dark_skin_tone": "🚶🏾\u200d♀️", + "woman_walking_medium-light_skin_tone": "🚶🏼\u200d♀️", + "woman_walking_medium_skin_tone": "🚶🏽\u200d♀️", + "woman_wearing_turban": "👳\u200d♀️", + "woman_wearing_turban_dark_skin_tone": "👳🏿\u200d♀️", + "woman_wearing_turban_light_skin_tone": "👳🏻\u200d♀️", + "woman_wearing_turban_medium-dark_skin_tone": "👳🏾\u200d♀️", + "woman_wearing_turban_medium-light_skin_tone": "👳🏼\u200d♀️", + "woman_wearing_turban_medium_skin_tone": "👳🏽\u200d♀️", + "woman_with_headscarf": "🧕", + "woman_with_headscarf_dark_skin_tone": "🧕🏿", + "woman_with_headscarf_light_skin_tone": "🧕🏻", + "woman_with_headscarf_medium-dark_skin_tone": "🧕🏾", + "woman_with_headscarf_medium-light_skin_tone": "🧕🏼", + "woman_with_headscarf_medium_skin_tone": "🧕🏽", + "woman_with_probing_cane": "👩\u200d🦯", + "woman_zombie": "🧟\u200d♀️", + "woman’s_boot": "👢", + "woman’s_clothes": "👚", + "woman’s_hat": "👒", + "woman’s_sandal": "👡", + "women_with_bunny_ears": "👯\u200d♀️", + "women_wrestling": "🤼\u200d♀️", + "women’s_room": "🚺", + "woozy_face": "🥴", + "world_map": "🗺", + "worried_face": "😟", + "wrapped_gift": "🎁", + "wrench": "🔧", + "writing_hand": "✍", + "writing_hand_dark_skin_tone": "✍🏿", + "writing_hand_light_skin_tone": "✍🏻", + "writing_hand_medium-dark_skin_tone": "✍🏾", + "writing_hand_medium-light_skin_tone": "✍🏼", + "writing_hand_medium_skin_tone": "✍🏽", + "yarn": "🧶", + "yawning_face": "🥱", + "yellow_circle": "🟡", + "yellow_heart": "💛", + "yellow_square": "🟨", + "yen_banknote": "💴", + "yo-yo": "🪀", + "yin_yang": "☯", + "zany_face": "🤪", + "zebra": "🦓", + "zipper-mouth_face": "🤐", + "zombie": "🧟", + "zzz": "💤", + "åland_islands": "🇦🇽", + "keycap_asterisk": "*⃣", + "keycap_digit_eight": "8⃣", + "keycap_digit_five": "5⃣", + "keycap_digit_four": "4⃣", + "keycap_digit_nine": "9⃣", + "keycap_digit_one": "1⃣", + "keycap_digit_seven": "7⃣", + "keycap_digit_six": "6⃣", + "keycap_digit_three": "3⃣", + "keycap_digit_two": "2⃣", + "keycap_digit_zero": "0⃣", + "keycap_number_sign": "#⃣", + "light_skin_tone": "🏻", + "medium_light_skin_tone": "🏼", + "medium_skin_tone": "🏽", + "medium_dark_skin_tone": "🏾", + "dark_skin_tone": "🏿", + "regional_indicator_symbol_letter_a": "🇦", + "regional_indicator_symbol_letter_b": "🇧", + "regional_indicator_symbol_letter_c": "🇨", + "regional_indicator_symbol_letter_d": "🇩", + "regional_indicator_symbol_letter_e": "🇪", + "regional_indicator_symbol_letter_f": "🇫", + "regional_indicator_symbol_letter_g": "🇬", + "regional_indicator_symbol_letter_h": "🇭", + "regional_indicator_symbol_letter_i": "🇮", + "regional_indicator_symbol_letter_j": "🇯", + "regional_indicator_symbol_letter_k": "🇰", + "regional_indicator_symbol_letter_l": "🇱", + "regional_indicator_symbol_letter_m": "🇲", + "regional_indicator_symbol_letter_n": "🇳", + "regional_indicator_symbol_letter_o": "🇴", + "regional_indicator_symbol_letter_p": "🇵", + "regional_indicator_symbol_letter_q": "🇶", + "regional_indicator_symbol_letter_r": "🇷", + "regional_indicator_symbol_letter_s": "🇸", + "regional_indicator_symbol_letter_t": "🇹", + "regional_indicator_symbol_letter_u": "🇺", + "regional_indicator_symbol_letter_v": "🇻", + "regional_indicator_symbol_letter_w": "🇼", + "regional_indicator_symbol_letter_x": "🇽", + "regional_indicator_symbol_letter_y": "🇾", + "regional_indicator_symbol_letter_z": "🇿", + "airplane_arriving": "🛬", + "space_invader": "👾", + "football": "🏈", + "anger": "💢", + "angry": "😠", + "anguished": "😧", + "signal_strength": "📶", + "arrows_counterclockwise": "🔄", + "arrow_heading_down": "⤵", + "arrow_heading_up": "⤴", + "art": "🎨", + "astonished": "😲", + "athletic_shoe": "👟", + "atm": "🏧", + "car": "🚗", + "red_car": "🚗", + "angel": "👼", + "back": "🔙", + "badminton_racquet_and_shuttlecock": "🏸", + "dollar": "💵", + "euro": "💶", + "pound": "💷", + "yen": "💴", + "barber": "💈", + "bath": "🛀", + "bear": "🐻", + "heartbeat": "💓", + "beer": "🍺", + "no_bell": "🔕", + "bento": "🍱", + "bike": "🚲", + "bicyclist": "🚴", + "8ball": "🎱", + "biohazard_sign": "☣", + "birthday": "🎂", + "black_circle_for_record": "⏺", + "clubs": "♣", + "diamonds": "♦", + "arrow_double_down": "⏬", + "hearts": "♥", + "rewind": "⏪", + "black_left__pointing_double_triangle_with_vertical_bar": "⏮", + "arrow_backward": "◀", + "black_medium_small_square": "◾", + "question": "❓", + "fast_forward": "⏩", + "black_right__pointing_double_triangle_with_vertical_bar": "⏭", + "arrow_forward": "▶", + "black_right__pointing_triangle_with_double_vertical_bar": "⏯", + "arrow_right": "➡", + "spades": "♠", + "black_square_for_stop": "⏹", + "sunny": "☀", + "phone": "☎", + "recycle": "♻", + "arrow_double_up": "⏫", + "busstop": "🚏", + "date": "📅", + "flags": "🎏", + "cat2": "🐈", + "joy_cat": "😹", + "smirk_cat": "😼", + "chart_with_downwards_trend": "📉", + "chart_with_upwards_trend": "📈", + "chart": "💹", + "mega": "📣", + "checkered_flag": "🏁", + "accept": "🉑", + "ideograph_advantage": "🉐", + "congratulations": "㊗", + "secret": "㊙", + "m": "Ⓜ", + "city_sunset": "🌆", + "clapper": "🎬", + "clap": "👏", + "beers": "🍻", + "clock830": "🕣", + "clock8": "🕗", + "clock1130": "🕦", + "clock11": "🕚", + "clock530": "🕠", + "clock5": "🕔", + "clock430": "🕟", + "clock4": "🕓", + "clock930": "🕤", + "clock9": "🕘", + "clock130": "🕜", + "clock1": "🕐", + "clock730": "🕢", + "clock7": "🕖", + "clock630": "🕡", + "clock6": "🕕", + "clock1030": "🕥", + "clock10": "🕙", + "clock330": "🕞", + "clock3": "🕒", + "clock1230": "🕧", + "clock12": "🕛", + "clock230": "🕝", + "clock2": "🕑", + "arrows_clockwise": "🔃", + "repeat": "🔁", + "repeat_one": "🔂", + "closed_lock_with_key": "🔐", + "mailbox_closed": "📪", + "mailbox": "📫", + "cloud_with_tornado": "🌪", + "cocktail": "🍸", + "boom": "💥", + "compression": "🗜", + "confounded": "😖", + "confused": "😕", + "rice": "🍚", + "cow2": "🐄", + "cricket_bat_and_ball": "🏏", + "x": "❌", + "cry": "😢", + "curry": "🍛", + "dagger_knife": "🗡", + "dancer": "💃", + "dark_sunglasses": "🕶", + "dash": "💨", + "truck": "🚚", + "derelict_house_building": "🏚", + "diamond_shape_with_a_dot_inside": "💠", + "dart": "🎯", + "disappointed_relieved": "😥", + "disappointed": "😞", + "do_not_litter": "🚯", + "dog2": "🐕", + "flipper": "🐬", + "loop": "➿", + "bangbang": "‼", + "double_vertical_bar": "⏸", + "dove_of_peace": "🕊", + "small_red_triangle_down": "🔻", + "arrow_down_small": "🔽", + "arrow_down": "⬇", + "dromedary_camel": "🐪", + "e__mail": "📧", + "corn": "🌽", + "ear_of_rice": "🌾", + "earth_americas": "🌎", + "earth_asia": "🌏", + "earth_africa": "🌍", + "eight_pointed_black_star": "✴", + "eight_spoked_asterisk": "✳", + "eject_symbol": "⏏", + "bulb": "💡", + "emoji_modifier_fitzpatrick_type__1__2": "🏻", + "emoji_modifier_fitzpatrick_type__3": "🏼", + "emoji_modifier_fitzpatrick_type__4": "🏽", + "emoji_modifier_fitzpatrick_type__5": "🏾", + "emoji_modifier_fitzpatrick_type__6": "🏿", + "end": "🔚", + "email": "✉", + "european_castle": "🏰", + "european_post_office": "🏤", + "interrobang": "⁉", + "expressionless": "😑", + "eyeglasses": "👓", + "massage": "💆", + "yum": "😋", + "scream": "😱", + "kissing_heart": "😘", + "sweat": "😓", + "face_with_head__bandage": "🤕", + "triumph": "😤", + "mask": "😷", + "no_good": "🙅", + "ok_woman": "🙆", + "open_mouth": "😮", + "cold_sweat": "😰", + "stuck_out_tongue": "😛", + "stuck_out_tongue_closed_eyes": "😝", + "stuck_out_tongue_winking_eye": "😜", + "joy": "😂", + "no_mouth": "😶", + "santa": "🎅", + "fax": "📠", + "fearful": "😨", + "field_hockey_stick_and_ball": "🏑", + "first_quarter_moon_with_face": "🌛", + "fish_cake": "🍥", + "fishing_pole_and_fish": "🎣", + "facepunch": "👊", + "punch": "👊", + "flag_for_afghanistan": "🇦🇫", + "flag_for_albania": "🇦🇱", + "flag_for_algeria": "🇩🇿", + "flag_for_american_samoa": "🇦🇸", + "flag_for_andorra": "🇦🇩", + "flag_for_angola": "🇦🇴", + "flag_for_anguilla": "🇦🇮", + "flag_for_antarctica": "🇦🇶", + "flag_for_antigua_&_barbuda": "🇦🇬", + "flag_for_argentina": "🇦🇷", + "flag_for_armenia": "🇦🇲", + "flag_for_aruba": "🇦🇼", + "flag_for_ascension_island": "🇦🇨", + "flag_for_australia": "🇦🇺", + "flag_for_austria": "🇦🇹", + "flag_for_azerbaijan": "🇦🇿", + "flag_for_bahamas": "🇧🇸", + "flag_for_bahrain": "🇧🇭", + "flag_for_bangladesh": "🇧🇩", + "flag_for_barbados": "🇧🇧", + "flag_for_belarus": "🇧🇾", + "flag_for_belgium": "🇧🇪", + "flag_for_belize": "🇧🇿", + "flag_for_benin": "🇧🇯", + "flag_for_bermuda": "🇧🇲", + "flag_for_bhutan": "🇧🇹", + "flag_for_bolivia": "🇧🇴", + "flag_for_bosnia_&_herzegovina": "🇧🇦", + "flag_for_botswana": "🇧🇼", + "flag_for_bouvet_island": "🇧🇻", + "flag_for_brazil": "🇧🇷", + "flag_for_british_indian_ocean_territory": "🇮🇴", + "flag_for_british_virgin_islands": "🇻🇬", + "flag_for_brunei": "🇧🇳", + "flag_for_bulgaria": "🇧🇬", + "flag_for_burkina_faso": "🇧🇫", + "flag_for_burundi": "🇧🇮", + "flag_for_cambodia": "🇰🇭", + "flag_for_cameroon": "🇨🇲", + "flag_for_canada": "🇨🇦", + "flag_for_canary_islands": "🇮🇨", + "flag_for_cape_verde": "🇨🇻", + "flag_for_caribbean_netherlands": "🇧🇶", + "flag_for_cayman_islands": "🇰🇾", + "flag_for_central_african_republic": "🇨🇫", + "flag_for_ceuta_&_melilla": "🇪🇦", + "flag_for_chad": "🇹🇩", + "flag_for_chile": "🇨🇱", + "flag_for_china": "🇨🇳", + "flag_for_christmas_island": "🇨🇽", + "flag_for_clipperton_island": "🇨🇵", + "flag_for_cocos__islands": "🇨🇨", + "flag_for_colombia": "🇨🇴", + "flag_for_comoros": "🇰🇲", + "flag_for_congo____brazzaville": "🇨🇬", + "flag_for_congo____kinshasa": "🇨🇩", + "flag_for_cook_islands": "🇨🇰", + "flag_for_costa_rica": "🇨🇷", + "flag_for_croatia": "🇭🇷", + "flag_for_cuba": "🇨🇺", + "flag_for_curaçao": "🇨🇼", + "flag_for_cyprus": "🇨🇾", + "flag_for_czech_republic": "🇨🇿", + "flag_for_côte_d’ivoire": "🇨🇮", + "flag_for_denmark": "🇩🇰", + "flag_for_diego_garcia": "🇩🇬", + "flag_for_djibouti": "🇩🇯", + "flag_for_dominica": "🇩🇲", + "flag_for_dominican_republic": "🇩🇴", + "flag_for_ecuador": "🇪🇨", + "flag_for_egypt": "🇪🇬", + "flag_for_el_salvador": "🇸🇻", + "flag_for_equatorial_guinea": "🇬🇶", + "flag_for_eritrea": "🇪🇷", + "flag_for_estonia": "🇪🇪", + "flag_for_ethiopia": "🇪🇹", + "flag_for_european_union": "🇪🇺", + "flag_for_falkland_islands": "🇫🇰", + "flag_for_faroe_islands": "🇫🇴", + "flag_for_fiji": "🇫🇯", + "flag_for_finland": "🇫🇮", + "flag_for_france": "🇫🇷", + "flag_for_french_guiana": "🇬🇫", + "flag_for_french_polynesia": "🇵🇫", + "flag_for_french_southern_territories": "🇹🇫", + "flag_for_gabon": "🇬🇦", + "flag_for_gambia": "🇬🇲", + "flag_for_georgia": "🇬🇪", + "flag_for_germany": "🇩🇪", + "flag_for_ghana": "🇬🇭", + "flag_for_gibraltar": "🇬🇮", + "flag_for_greece": "🇬🇷", + "flag_for_greenland": "🇬🇱", + "flag_for_grenada": "🇬🇩", + "flag_for_guadeloupe": "🇬🇵", + "flag_for_guam": "🇬🇺", + "flag_for_guatemala": "🇬🇹", + "flag_for_guernsey": "🇬🇬", + "flag_for_guinea": "🇬🇳", + "flag_for_guinea__bissau": "🇬🇼", + "flag_for_guyana": "🇬🇾", + "flag_for_haiti": "🇭🇹", + "flag_for_heard_&_mcdonald_islands": "🇭🇲", + "flag_for_honduras": "🇭🇳", + "flag_for_hong_kong": "🇭🇰", + "flag_for_hungary": "🇭🇺", + "flag_for_iceland": "🇮🇸", + "flag_for_india": "🇮🇳", + "flag_for_indonesia": "🇮🇩", + "flag_for_iran": "🇮🇷", + "flag_for_iraq": "🇮🇶", + "flag_for_ireland": "🇮🇪", + "flag_for_isle_of_man": "🇮🇲", + "flag_for_israel": "🇮🇱", + "flag_for_italy": "🇮🇹", + "flag_for_jamaica": "🇯🇲", + "flag_for_japan": "🇯🇵", + "flag_for_jersey": "🇯🇪", + "flag_for_jordan": "🇯🇴", + "flag_for_kazakhstan": "🇰🇿", + "flag_for_kenya": "🇰🇪", + "flag_for_kiribati": "🇰🇮", + "flag_for_kosovo": "🇽🇰", + "flag_for_kuwait": "🇰🇼", + "flag_for_kyrgyzstan": "🇰🇬", + "flag_for_laos": "🇱🇦", + "flag_for_latvia": "🇱🇻", + "flag_for_lebanon": "🇱🇧", + "flag_for_lesotho": "🇱🇸", + "flag_for_liberia": "🇱🇷", + "flag_for_libya": "🇱🇾", + "flag_for_liechtenstein": "🇱🇮", + "flag_for_lithuania": "🇱🇹", + "flag_for_luxembourg": "🇱🇺", + "flag_for_macau": "🇲🇴", + "flag_for_macedonia": "🇲🇰", + "flag_for_madagascar": "🇲🇬", + "flag_for_malawi": "🇲🇼", + "flag_for_malaysia": "🇲🇾", + "flag_for_maldives": "🇲🇻", + "flag_for_mali": "🇲🇱", + "flag_for_malta": "🇲🇹", + "flag_for_marshall_islands": "🇲🇭", + "flag_for_martinique": "🇲🇶", + "flag_for_mauritania": "🇲🇷", + "flag_for_mauritius": "🇲🇺", + "flag_for_mayotte": "🇾🇹", + "flag_for_mexico": "🇲🇽", + "flag_for_micronesia": "🇫🇲", + "flag_for_moldova": "🇲🇩", + "flag_for_monaco": "🇲🇨", + "flag_for_mongolia": "🇲🇳", + "flag_for_montenegro": "🇲🇪", + "flag_for_montserrat": "🇲🇸", + "flag_for_morocco": "🇲🇦", + "flag_for_mozambique": "🇲🇿", + "flag_for_myanmar": "🇲🇲", + "flag_for_namibia": "🇳🇦", + "flag_for_nauru": "🇳🇷", + "flag_for_nepal": "🇳🇵", + "flag_for_netherlands": "🇳🇱", + "flag_for_new_caledonia": "🇳🇨", + "flag_for_new_zealand": "🇳🇿", + "flag_for_nicaragua": "🇳🇮", + "flag_for_niger": "🇳🇪", + "flag_for_nigeria": "🇳🇬", + "flag_for_niue": "🇳🇺", + "flag_for_norfolk_island": "🇳🇫", + "flag_for_north_korea": "🇰🇵", + "flag_for_northern_mariana_islands": "🇲🇵", + "flag_for_norway": "🇳🇴", + "flag_for_oman": "🇴🇲", + "flag_for_pakistan": "🇵🇰", + "flag_for_palau": "🇵🇼", + "flag_for_palestinian_territories": "🇵🇸", + "flag_for_panama": "🇵🇦", + "flag_for_papua_new_guinea": "🇵🇬", + "flag_for_paraguay": "🇵🇾", + "flag_for_peru": "🇵🇪", + "flag_for_philippines": "🇵🇭", + "flag_for_pitcairn_islands": "🇵🇳", + "flag_for_poland": "🇵🇱", + "flag_for_portugal": "🇵🇹", + "flag_for_puerto_rico": "🇵🇷", + "flag_for_qatar": "🇶🇦", + "flag_for_romania": "🇷🇴", + "flag_for_russia": "🇷🇺", + "flag_for_rwanda": "🇷🇼", + "flag_for_réunion": "🇷🇪", + "flag_for_samoa": "🇼🇸", + "flag_for_san_marino": "🇸🇲", + "flag_for_saudi_arabia": "🇸🇦", + "flag_for_senegal": "🇸🇳", + "flag_for_serbia": "🇷🇸", + "flag_for_seychelles": "🇸🇨", + "flag_for_sierra_leone": "🇸🇱", + "flag_for_singapore": "🇸🇬", + "flag_for_sint_maarten": "🇸🇽", + "flag_for_slovakia": "🇸🇰", + "flag_for_slovenia": "🇸🇮", + "flag_for_solomon_islands": "🇸🇧", + "flag_for_somalia": "🇸🇴", + "flag_for_south_africa": "🇿🇦", + "flag_for_south_georgia_&_south_sandwich_islands": "🇬🇸", + "flag_for_south_korea": "🇰🇷", + "flag_for_south_sudan": "🇸🇸", + "flag_for_spain": "🇪🇸", + "flag_for_sri_lanka": "🇱🇰", + "flag_for_st._barthélemy": "🇧🇱", + "flag_for_st._helena": "🇸🇭", + "flag_for_st._kitts_&_nevis": "🇰🇳", + "flag_for_st._lucia": "🇱🇨", + "flag_for_st._martin": "🇲🇫", + "flag_for_st._pierre_&_miquelon": "🇵🇲", + "flag_for_st._vincent_&_grenadines": "🇻🇨", + "flag_for_sudan": "🇸🇩", + "flag_for_suriname": "🇸🇷", + "flag_for_svalbard_&_jan_mayen": "🇸🇯", + "flag_for_swaziland": "🇸🇿", + "flag_for_sweden": "🇸🇪", + "flag_for_switzerland": "🇨🇭", + "flag_for_syria": "🇸🇾", + "flag_for_são_tomé_&_príncipe": "🇸🇹", + "flag_for_taiwan": "🇹🇼", + "flag_for_tajikistan": "🇹🇯", + "flag_for_tanzania": "🇹🇿", + "flag_for_thailand": "🇹🇭", + "flag_for_timor__leste": "🇹🇱", + "flag_for_togo": "🇹🇬", + "flag_for_tokelau": "🇹🇰", + "flag_for_tonga": "🇹🇴", + "flag_for_trinidad_&_tobago": "🇹🇹", + "flag_for_tristan_da_cunha": "🇹🇦", + "flag_for_tunisia": "🇹🇳", + "flag_for_turkey": "🇹🇷", + "flag_for_turkmenistan": "🇹🇲", + "flag_for_turks_&_caicos_islands": "🇹🇨", + "flag_for_tuvalu": "🇹🇻", + "flag_for_u.s._outlying_islands": "🇺🇲", + "flag_for_u.s._virgin_islands": "🇻🇮", + "flag_for_uganda": "🇺🇬", + "flag_for_ukraine": "🇺🇦", + "flag_for_united_arab_emirates": "🇦🇪", + "flag_for_united_kingdom": "🇬🇧", + "flag_for_united_states": "🇺🇸", + "flag_for_uruguay": "🇺🇾", + "flag_for_uzbekistan": "🇺🇿", + "flag_for_vanuatu": "🇻🇺", + "flag_for_vatican_city": "🇻🇦", + "flag_for_venezuela": "🇻🇪", + "flag_for_vietnam": "🇻🇳", + "flag_for_wallis_&_futuna": "🇼🇫", + "flag_for_western_sahara": "🇪🇭", + "flag_for_yemen": "🇾🇪", + "flag_for_zambia": "🇿🇲", + "flag_for_zimbabwe": "🇿🇼", + "flag_for_åland_islands": "🇦🇽", + "golf": "⛳", + "fleur__de__lis": "⚜", + "muscle": "💪", + "flushed": "😳", + "frame_with_picture": "🖼", + "fries": "🍟", + "frog": "🐸", + "hatched_chick": "🐥", + "frowning": "😦", + "fuelpump": "⛽", + "full_moon_with_face": "🌝", + "gem": "💎", + "star2": "🌟", + "golfer": "🏌", + "mortar_board": "🎓", + "grimacing": "😬", + "smile_cat": "😸", + "grinning": "😀", + "grin": "😁", + "heartpulse": "💗", + "guardsman": "💂", + "haircut": "💇", + "hamster": "🐹", + "raising_hand": "🙋", + "headphones": "🎧", + "hear_no_evil": "🙉", + "cupid": "💘", + "gift_heart": "💝", + "heart": "❤", + "exclamation": "❗", + "heavy_exclamation_mark": "❗", + "heavy_heart_exclamation_mark_ornament": "❣", + "o": "⭕", + "helm_symbol": "⎈", + "helmet_with_white_cross": "⛑", + "high_heel": "👠", + "bullettrain_side": "🚄", + "bullettrain_front": "🚅", + "high_brightness": "🔆", + "zap": "⚡", + "hocho": "🔪", + "knife": "🔪", + "bee": "🐝", + "traffic_light": "🚥", + "racehorse": "🐎", + "coffee": "☕", + "hotsprings": "♨", + "hourglass": "⌛", + "hourglass_flowing_sand": "⏳", + "house_buildings": "🏘", + "100": "💯", + "hushed": "😯", + "ice_hockey_stick_and_puck": "🏒", + "imp": "👿", + "information_desk_person": "💁", + "information_source": "ℹ", + "capital_abcd": "🔠", + "abc": "🔤", + "abcd": "🔡", + "1234": "🔢", + "symbols": "🔣", + "izakaya_lantern": "🏮", + "lantern": "🏮", + "jack_o_lantern": "🎃", + "dolls": "🎎", + "japanese_goblin": "👺", + "japanese_ogre": "👹", + "beginner": "🔰", + "zero": "0️⃣", + "one": "1️⃣", + "ten": "🔟", + "two": "2️⃣", + "three": "3️⃣", + "four": "4️⃣", + "five": "5️⃣", + "six": "6️⃣", + "seven": "7️⃣", + "eight": "8️⃣", + "nine": "9️⃣", + "couplekiss": "💏", + "kissing_cat": "😽", + "kissing": "😗", + "kissing_closed_eyes": "😚", + "kissing_smiling_eyes": "😙", + "beetle": "🐞", + "large_blue_circle": "🔵", + "last_quarter_moon_with_face": "🌜", + "leaves": "🍃", + "mag": "🔍", + "left_right_arrow": "↔", + "leftwards_arrow_with_hook": "↩", + "arrow_left": "⬅", + "lock": "🔒", + "lock_with_ink_pen": "🔏", + "sob": "😭", + "low_brightness": "🔅", + "lower_left_ballpoint_pen": "🖊", + "lower_left_crayon": "🖍", + "lower_left_fountain_pen": "🖋", + "lower_left_paintbrush": "🖌", + "mahjong": "🀄", + "couple": "👫", + "man_in_business_suit_levitating": "🕴", + "man_with_gua_pi_mao": "👲", + "man_with_turban": "👳", + "mans_shoe": "👞", + "shoe": "👞", + "menorah_with_nine_branches": "🕎", + "mens": "🚹", + "minidisc": "💽", + "iphone": "📱", + "calling": "📲", + "money__mouth_face": "🤑", + "moneybag": "💰", + "rice_scene": "🎑", + "mountain_bicyclist": "🚵", + "mouse2": "🐁", + "lips": "👄", + "moyai": "🗿", + "notes": "🎶", + "nail_care": "💅", + "ab": "🆎", + "negative_squared_cross_mark": "❎", + "a": "🅰", + "b": "🅱", + "o2": "🅾", + "parking": "🅿", + "new_moon_with_face": "🌚", + "no_entry_sign": "🚫", + "underage": "🔞", + "non__potable_water": "🚱", + "arrow_upper_right": "↗", + "arrow_upper_left": "↖", + "office": "🏢", + "older_man": "👴", + "older_woman": "👵", + "om_symbol": "🕉", + "on": "🔛", + "book": "📖", + "unlock": "🔓", + "mailbox_with_no_mail": "📭", + "mailbox_with_mail": "📬", + "cd": "💿", + "tada": "🎉", + "feet": "🐾", + "walking": "🚶", + "pencil2": "✏", + "pensive": "😔", + "persevere": "😣", + "bow": "🙇", + "raised_hands": "🙌", + "person_with_ball": "⛹", + "person_with_blond_hair": "👱", + "pray": "🙏", + "person_with_pouting_face": "🙎", + "computer": "💻", + "pig2": "🐖", + "hankey": "💩", + "poop": "💩", + "shit": "💩", + "bamboo": "🎍", + "gun": "🔫", + "black_joker": "🃏", + "rotating_light": "🚨", + "cop": "👮", + "stew": "🍲", + "pouch": "👝", + "pouting_cat": "😾", + "rage": "😡", + "put_litter_in_its_place": "🚮", + "rabbit2": "🐇", + "racing_motorcycle": "🏍", + "radioactive_sign": "☢", + "fist": "✊", + "hand": "✋", + "raised_hand_with_fingers_splayed": "🖐", + "raised_hand_with_part_between_middle_and_ring_fingers": "🖖", + "blue_car": "🚙", + "apple": "🍎", + "relieved": "😌", + "reversed_hand_with_middle_finger_extended": "🖕", + "mag_right": "🔎", + "arrow_right_hook": "↪", + "sweet_potato": "🍠", + "robot": "🤖", + "rolled__up_newspaper": "🗞", + "rowboat": "🚣", + "runner": "🏃", + "running": "🏃", + "running_shirt_with_sash": "🎽", + "boat": "⛵", + "scales": "⚖", + "school_satchel": "🎒", + "scorpius": "♏", + "see_no_evil": "🙈", + "sheep": "🐑", + "stars": "🌠", + "cake": "🍰", + "six_pointed_star": "🔯", + "ski": "🎿", + "sleeping_accommodation": "🛌", + "sleeping": "😴", + "sleepy": "😪", + "sleuth_or_spy": "🕵", + "heart_eyes_cat": "😻", + "smiley_cat": "😺", + "innocent": "😇", + "heart_eyes": "😍", + "smiling_imp": "😈", + "smiley": "😃", + "sweat_smile": "😅", + "smile": "😄", + "laughing": "😆", + "satisfied": "😆", + "blush": "😊", + "smirk": "😏", + "smoking": "🚬", + "snow_capped_mountain": "🏔", + "soccer": "⚽", + "icecream": "🍦", + "soon": "🔜", + "arrow_lower_right": "↘", + "arrow_lower_left": "↙", + "speak_no_evil": "🙊", + "speaker": "🔈", + "mute": "🔇", + "sound": "🔉", + "loud_sound": "🔊", + "speaking_head_in_silhouette": "🗣", + "spiral_calendar_pad": "🗓", + "spiral_note_pad": "🗒", + "shell": "🐚", + "sweat_drops": "💦", + "u5272": "🈹", + "u5408": "🈴", + "u55b6": "🈺", + "u6307": "🈯", + "u6708": "🈷", + "u6709": "🈶", + "u6e80": "🈵", + "u7121": "🈚", + "u7533": "🈸", + "u7981": "🈲", + "u7a7a": "🈳", + "cl": "🆑", + "cool": "🆒", + "free": "🆓", + "id": "🆔", + "koko": "🈁", + "sa": "🈂", + "new": "🆕", + "ng": "🆖", + "ok": "🆗", + "sos": "🆘", + "up": "🆙", + "vs": "🆚", + "steam_locomotive": "🚂", + "ramen": "🍜", + "partly_sunny": "⛅", + "city_sunrise": "🌇", + "surfer": "🏄", + "swimmer": "🏊", + "shirt": "👕", + "tshirt": "👕", + "table_tennis_paddle_and_ball": "🏓", + "tea": "🍵", + "tv": "📺", + "three_button_mouse": "🖱", + "+1": "👍", + "thumbsup": "👍", + "__1": "👎", + "-1": "👎", + "thumbsdown": "👎", + "thunder_cloud_and_rain": "⛈", + "tiger2": "🐅", + "tophat": "🎩", + "top": "🔝", + "tm": "™", + "train2": "🚆", + "triangular_flag_on_post": "🚩", + "trident": "🔱", + "twisted_rightwards_arrows": "🔀", + "unamused": "😒", + "small_red_triangle": "🔺", + "arrow_up_small": "🔼", + "arrow_up_down": "↕", + "upside__down_face": "🙃", + "arrow_up": "⬆", + "v": "✌", + "vhs": "📼", + "wc": "🚾", + "ocean": "🌊", + "waving_black_flag": "🏴", + "wave": "👋", + "waving_white_flag": "🏳", + "moon": "🌔", + "scream_cat": "🙀", + "weary": "😩", + "weight_lifter": "🏋", + "whale2": "🐋", + "wheelchair": "♿", + "point_down": "👇", + "grey_exclamation": "❕", + "white_frowning_face": "☹", + "white_check_mark": "✅", + "point_left": "👈", + "white_medium_small_square": "◽", + "star": "⭐", + "grey_question": "❔", + "point_right": "👉", + "relaxed": "☺", + "white_sun_behind_cloud": "🌥", + "white_sun_behind_cloud_with_rain": "🌦", + "white_sun_with_small_cloud": "🌤", + "point_up_2": "👆", + "point_up": "☝", + "wind_blowing_face": "🌬", + "wink": "😉", + "wolf": "🐺", + "dancers": "👯", + "boot": "👢", + "womans_clothes": "👚", + "womans_hat": "👒", + "sandal": "👡", + "womens": "🚺", + "worried": "😟", + "gift": "🎁", + "zipper__mouth_face": "🤐", + "regional_indicator_a": "🇦", + "regional_indicator_b": "🇧", + "regional_indicator_c": "🇨", + "regional_indicator_d": "🇩", + "regional_indicator_e": "🇪", + "regional_indicator_f": "🇫", + "regional_indicator_g": "🇬", + "regional_indicator_h": "🇭", + "regional_indicator_i": "🇮", + "regional_indicator_j": "🇯", + "regional_indicator_k": "🇰", + "regional_indicator_l": "🇱", + "regional_indicator_m": "🇲", + "regional_indicator_n": "🇳", + "regional_indicator_o": "🇴", + "regional_indicator_p": "🇵", + "regional_indicator_q": "🇶", + "regional_indicator_r": "🇷", + "regional_indicator_s": "🇸", + "regional_indicator_t": "🇹", + "regional_indicator_u": "🇺", + "regional_indicator_v": "🇻", + "regional_indicator_w": "🇼", + "regional_indicator_x": "🇽", + "regional_indicator_y": "🇾", + "regional_indicator_z": "🇿", +} diff --git a/rich/_timer.py b/rich/_timer.py new file mode 100644 index 0000000000000000000000000000000000000000..a2ca6be03c43054caaa3660998273ebf704345dd --- /dev/null +++ b/rich/_timer.py @@ -0,0 +1,19 @@ +""" +Timer context manager, only used in debug. + +""" + +from time import time + +import contextlib +from typing import Generator + + +@contextlib.contextmanager +def timer(subject: str = "time") -> Generator[None, None, None]: + """print the elapsed time. (only used in debugging)""" + start = time() + yield + elapsed = time() - start + elapsed_ms = elapsed * 1000 + print(f"{subject} elapsed {elapsed_ms:.1f}ms") diff --git a/rich/box.py b/rich/box.py new file mode 100644 index 0000000000000000000000000000000000000000..82555b61cd29efab220cf47b9fb3c26b80e8adde --- /dev/null +++ b/rich/box.py @@ -0,0 +1,474 @@ +from typing import TYPE_CHECKING, Iterable, List, Literal + + +from ._loop import loop_last + +if TYPE_CHECKING: + from rich.console import ConsoleOptions + + +class Box: + """Defines characters to render boxes. + + ┌─┬┐ top + │ ││ head + ├─┼┤ head_row + │ ││ mid + ├─┼┤ row + ├─┼┤ foot_row + │ ││ foot + └─┴┘ bottom + + Args: + box (str): Characters making up box. + ascii (bool, optional): True if this box uses ascii characters only. Default is False. + """ + + def __init__(self, box: str, *, ascii: bool = False) -> None: + self._box = box + self.ascii = ascii + line1, line2, line3, line4, line5, line6, line7, line8 = box.splitlines() + # top + self.top_left, self.top, self.top_divider, self.top_right = iter(line1) + # head + self.head_left, _, self.head_vertical, self.head_right = iter(line2) + # head_row + ( + self.head_row_left, + self.head_row_horizontal, + self.head_row_cross, + self.head_row_right, + ) = iter(line3) + + # mid + self.mid_left, _, self.mid_vertical, self.mid_right = iter(line4) + # row + self.row_left, self.row_horizontal, self.row_cross, self.row_right = iter(line5) + # foot_row + ( + self.foot_row_left, + self.foot_row_horizontal, + self.foot_row_cross, + self.foot_row_right, + ) = iter(line6) + # foot + self.foot_left, _, self.foot_vertical, self.foot_right = iter(line7) + # bottom + self.bottom_left, self.bottom, self.bottom_divider, self.bottom_right = iter( + line8 + ) + + def __repr__(self) -> str: + return "Box(...)" + + def __str__(self) -> str: + return self._box + + def substitute(self, options: "ConsoleOptions", safe: bool = True) -> "Box": + """Substitute this box for another if it won't render due to platform issues. + + Args: + options (ConsoleOptions): Console options used in rendering. + safe (bool, optional): Substitute this for another Box if there are known problems + displaying on the platform (currently only relevant on Windows). Default is True. + + Returns: + Box: A different Box or the same Box. + """ + box = self + if options.legacy_windows and safe: + box = LEGACY_WINDOWS_SUBSTITUTIONS.get(box, box) + if options.ascii_only and not box.ascii: + box = ASCII + return box + + def get_plain_headed_box(self) -> "Box": + """If this box uses special characters for the borders of the header, then + return the equivalent box that does not. + + Returns: + Box: The most similar Box that doesn't use header-specific box characters. + If the current Box already satisfies this criterion, then it's returned. + """ + return PLAIN_HEADED_SUBSTITUTIONS.get(self, self) + + def get_top(self, widths: Iterable[int]) -> str: + """Get the top of a simple box. + + Args: + widths (List[int]): Widths of columns. + + Returns: + str: A string of box characters. + """ + + parts: List[str] = [] + append = parts.append + append(self.top_left) + for last, width in loop_last(widths): + append(self.top * width) + if not last: + append(self.top_divider) + append(self.top_right) + return "".join(parts) + + def get_row( + self, + widths: Iterable[int], + level: Literal["head", "row", "foot", "mid"] = "row", + edge: bool = True, + ) -> str: + """Get the top of a simple box. + + Args: + width (List[int]): Widths of columns. + + Returns: + str: A string of box characters. + """ + if level == "head": + left = self.head_row_left + horizontal = self.head_row_horizontal + cross = self.head_row_cross + right = self.head_row_right + elif level == "row": + left = self.row_left + horizontal = self.row_horizontal + cross = self.row_cross + right = self.row_right + elif level == "mid": + left = self.mid_left + horizontal = " " + cross = self.mid_vertical + right = self.mid_right + elif level == "foot": + left = self.foot_row_left + horizontal = self.foot_row_horizontal + cross = self.foot_row_cross + right = self.foot_row_right + else: + raise ValueError("level must be 'head', 'row' or 'foot'") + + parts: List[str] = [] + append = parts.append + if edge: + append(left) + for last, width in loop_last(widths): + append(horizontal * width) + if not last: + append(cross) + if edge: + append(right) + return "".join(parts) + + def get_bottom(self, widths: Iterable[int]) -> str: + """Get the bottom of a simple box. + + Args: + widths (List[int]): Widths of columns. + + Returns: + str: A string of box characters. + """ + + parts: List[str] = [] + append = parts.append + append(self.bottom_left) + for last, width in loop_last(widths): + append(self.bottom * width) + if not last: + append(self.bottom_divider) + append(self.bottom_right) + return "".join(parts) + + +# fmt: off +ASCII: Box = Box( + "+--+\n" + "| ||\n" + "|-+|\n" + "| ||\n" + "|-+|\n" + "|-+|\n" + "| ||\n" + "+--+\n", + ascii=True, +) + +ASCII2: Box = Box( + "+-++\n" + "| ||\n" + "+-++\n" + "| ||\n" + "+-++\n" + "+-++\n" + "| ||\n" + "+-++\n", + ascii=True, +) + +ASCII_DOUBLE_HEAD: Box = Box( + "+-++\n" + "| ||\n" + "+=++\n" + "| ||\n" + "+-++\n" + "+-++\n" + "| ||\n" + "+-++\n", + ascii=True, +) + +SQUARE: Box = Box( + "┌─┬┐\n" + "│ ││\n" + "├─┼┤\n" + "│ ││\n" + "├─┼┤\n" + "├─┼┤\n" + "│ ││\n" + "└─┴┘\n" +) + +SQUARE_DOUBLE_HEAD: Box = Box( + "┌─┬┐\n" + "│ ││\n" + "╞═╪╡\n" + "│ ││\n" + "├─┼┤\n" + "├─┼┤\n" + "│ ││\n" + "└─┴┘\n" +) + +MINIMAL: Box = Box( + " ╷ \n" + " │ \n" + "╶─┼╴\n" + " │ \n" + "╶─┼╴\n" + "╶─┼╴\n" + " │ \n" + " ╵ \n" +) + + +MINIMAL_HEAVY_HEAD: Box = Box( + " ╷ \n" + " │ \n" + "╺━┿╸\n" + " │ \n" + "╶─┼╴\n" + "╶─┼╴\n" + " │ \n" + " ╵ \n" +) + +MINIMAL_DOUBLE_HEAD: Box = Box( + " ╷ \n" + " │ \n" + " ═╪ \n" + " │ \n" + " ─┼ \n" + " ─┼ \n" + " │ \n" + " ╵ \n" +) + + +SIMPLE: Box = Box( + " \n" + " \n" + " ── \n" + " \n" + " \n" + " ── \n" + " \n" + " \n" +) + +SIMPLE_HEAD: Box = Box( + " \n" + " \n" + " ── \n" + " \n" + " \n" + " \n" + " \n" + " \n" +) + + +SIMPLE_HEAVY: Box = Box( + " \n" + " \n" + " ━━ \n" + " \n" + " \n" + " ━━ \n" + " \n" + " \n" +) + + +HORIZONTALS: Box = Box( + " ── \n" + " \n" + " ── \n" + " \n" + " ── \n" + " ── \n" + " \n" + " ── \n" +) + +ROUNDED: Box = Box( + "╭─┬╮\n" + "│ ││\n" + "├─┼┤\n" + "│ ││\n" + "├─┼┤\n" + "├─┼┤\n" + "│ ││\n" + "╰─┴╯\n" +) + +HEAVY: Box = Box( + "┏━┳┓\n" + "┃ ┃┃\n" + "┣━╋┫\n" + "┃ ┃┃\n" + "┣━╋┫\n" + "┣━╋┫\n" + "┃ ┃┃\n" + "┗━┻┛\n" +) + +HEAVY_EDGE: Box = Box( + "┏━┯┓\n" + "┃ │┃\n" + "┠─┼┨\n" + "┃ │┃\n" + "┠─┼┨\n" + "┠─┼┨\n" + "┃ │┃\n" + "┗━┷┛\n" +) + +HEAVY_HEAD: Box = Box( + "┏━┳┓\n" + "┃ ┃┃\n" + "┡━╇┩\n" + "│ ││\n" + "├─┼┤\n" + "├─┼┤\n" + "│ ││\n" + "└─┴┘\n" +) + +DOUBLE: Box = Box( + "╔═╦╗\n" + "║ ║║\n" + "╠═╬╣\n" + "║ ║║\n" + "╠═╬╣\n" + "╠═╬╣\n" + "║ ║║\n" + "╚═╩╝\n" +) + +DOUBLE_EDGE: Box = Box( + "╔═╤╗\n" + "║ │║\n" + "╟─┼╢\n" + "║ │║\n" + "╟─┼╢\n" + "╟─┼╢\n" + "║ │║\n" + "╚═╧╝\n" +) + +MARKDOWN: Box = Box( + " \n" + "| ||\n" + "|-||\n" + "| ||\n" + "|-||\n" + "|-||\n" + "| ||\n" + " \n", + ascii=True, +) +# fmt: on + +# Map Boxes that don't render with raster fonts on to equivalent that do +LEGACY_WINDOWS_SUBSTITUTIONS = { + ROUNDED: SQUARE, + MINIMAL_HEAVY_HEAD: MINIMAL, + SIMPLE_HEAVY: SIMPLE, + HEAVY: SQUARE, + HEAVY_EDGE: SQUARE, + HEAVY_HEAD: SQUARE, +} + +# Map headed boxes to their headerless equivalents +PLAIN_HEADED_SUBSTITUTIONS = { + HEAVY_HEAD: SQUARE, + SQUARE_DOUBLE_HEAD: SQUARE, + MINIMAL_DOUBLE_HEAD: MINIMAL, + MINIMAL_HEAVY_HEAD: MINIMAL, + ASCII_DOUBLE_HEAD: ASCII2, +} + + +if __name__ == "__main__": # pragma: no cover + from rich.columns import Columns + from rich.panel import Panel + + from . import box as box + from .console import Console + from .table import Table + from .text import Text + + console = Console(record=True) + + BOXES = [ + "ASCII", + "ASCII2", + "ASCII_DOUBLE_HEAD", + "SQUARE", + "SQUARE_DOUBLE_HEAD", + "MINIMAL", + "MINIMAL_HEAVY_HEAD", + "MINIMAL_DOUBLE_HEAD", + "SIMPLE", + "SIMPLE_HEAD", + "SIMPLE_HEAVY", + "HORIZONTALS", + "ROUNDED", + "HEAVY", + "HEAVY_EDGE", + "HEAVY_HEAD", + "DOUBLE", + "DOUBLE_EDGE", + "MARKDOWN", + ] + + console.print(Panel("[bold green]Box Constants", style="green"), justify="center") + console.print() + + columns = Columns(expand=True, padding=2) + for box_name in sorted(BOXES): + table = Table( + show_footer=True, style="dim", border_style="not dim", expand=True + ) + table.add_column("Header 1", "Footer 1") + table.add_column("Header 2", "Footer 2") + table.add_row("Cell", "Cell") + table.add_row("Cell", "Cell") + table.box = getattr(box, box_name) + table.title = Text(f"box.{box_name}", style="magenta") + columns.add_renderable(table) + console.print(columns) + + # console.save_svg("box.svg") diff --git a/rich/color.py b/rich/color.py new file mode 100644 index 0000000000000000000000000000000000000000..e2c23a6a91b833fd9bb20bd5238421a5c0f08df3 --- /dev/null +++ b/rich/color.py @@ -0,0 +1,621 @@ +import re +import sys +from colorsys import rgb_to_hls +from enum import IntEnum +from functools import lru_cache +from typing import TYPE_CHECKING, NamedTuple, Optional, Tuple + +from ._palettes import EIGHT_BIT_PALETTE, STANDARD_PALETTE, WINDOWS_PALETTE +from .color_triplet import ColorTriplet +from .repr import Result, rich_repr +from .terminal_theme import DEFAULT_TERMINAL_THEME + +if TYPE_CHECKING: # pragma: no cover + from .terminal_theme import TerminalTheme + from .text import Text + + +WINDOWS = sys.platform == "win32" + + +class ColorSystem(IntEnum): + """One of the 3 color system supported by terminals.""" + + STANDARD = 1 + EIGHT_BIT = 2 + TRUECOLOR = 3 + WINDOWS = 4 + + def __repr__(self) -> str: + return f"ColorSystem.{self.name}" + + def __str__(self) -> str: + return repr(self) + + +class ColorType(IntEnum): + """Type of color stored in Color class.""" + + DEFAULT = 0 + STANDARD = 1 + EIGHT_BIT = 2 + TRUECOLOR = 3 + WINDOWS = 4 + + def __repr__(self) -> str: + return f"ColorType.{self.name}" + + +ANSI_COLOR_NAMES = { + "black": 0, + "red": 1, + "green": 2, + "yellow": 3, + "blue": 4, + "magenta": 5, + "cyan": 6, + "white": 7, + "bright_black": 8, + "bright_red": 9, + "bright_green": 10, + "bright_yellow": 11, + "bright_blue": 12, + "bright_magenta": 13, + "bright_cyan": 14, + "bright_white": 15, + "grey0": 16, + "gray0": 16, + "navy_blue": 17, + "dark_blue": 18, + "blue3": 20, + "blue1": 21, + "dark_green": 22, + "deep_sky_blue4": 25, + "dodger_blue3": 26, + "dodger_blue2": 27, + "green4": 28, + "spring_green4": 29, + "turquoise4": 30, + "deep_sky_blue3": 32, + "dodger_blue1": 33, + "green3": 40, + "spring_green3": 41, + "dark_cyan": 36, + "light_sea_green": 37, + "deep_sky_blue2": 38, + "deep_sky_blue1": 39, + "spring_green2": 47, + "cyan3": 43, + "dark_turquoise": 44, + "turquoise2": 45, + "green1": 46, + "spring_green1": 48, + "medium_spring_green": 49, + "cyan2": 50, + "cyan1": 51, + "dark_red": 88, + "deep_pink4": 125, + "purple4": 55, + "purple3": 56, + "blue_violet": 57, + "orange4": 94, + "grey37": 59, + "gray37": 59, + "medium_purple4": 60, + "slate_blue3": 62, + "royal_blue1": 63, + "chartreuse4": 64, + "dark_sea_green4": 71, + "pale_turquoise4": 66, + "steel_blue": 67, + "steel_blue3": 68, + "cornflower_blue": 69, + "chartreuse3": 76, + "cadet_blue": 73, + "sky_blue3": 74, + "steel_blue1": 81, + "pale_green3": 114, + "sea_green3": 78, + "aquamarine3": 79, + "medium_turquoise": 80, + "chartreuse2": 112, + "sea_green2": 83, + "sea_green1": 85, + "aquamarine1": 122, + "dark_slate_gray2": 87, + "dark_magenta": 91, + "dark_violet": 128, + "purple": 129, + "light_pink4": 95, + "plum4": 96, + "medium_purple3": 98, + "slate_blue1": 99, + "yellow4": 106, + "wheat4": 101, + "grey53": 102, + "gray53": 102, + "light_slate_grey": 103, + "light_slate_gray": 103, + "medium_purple": 104, + "light_slate_blue": 105, + "dark_olive_green3": 149, + "dark_sea_green": 108, + "light_sky_blue3": 110, + "sky_blue2": 111, + "dark_sea_green3": 150, + "dark_slate_gray3": 116, + "sky_blue1": 117, + "chartreuse1": 118, + "light_green": 120, + "pale_green1": 156, + "dark_slate_gray1": 123, + "red3": 160, + "medium_violet_red": 126, + "magenta3": 164, + "dark_orange3": 166, + "indian_red": 167, + "hot_pink3": 168, + "medium_orchid3": 133, + "medium_orchid": 134, + "medium_purple2": 140, + "dark_goldenrod": 136, + "light_salmon3": 173, + "rosy_brown": 138, + "grey63": 139, + "gray63": 139, + "medium_purple1": 141, + "gold3": 178, + "dark_khaki": 143, + "navajo_white3": 144, + "grey69": 145, + "gray69": 145, + "light_steel_blue3": 146, + "light_steel_blue": 147, + "yellow3": 184, + "dark_sea_green2": 157, + "light_cyan3": 152, + "light_sky_blue1": 153, + "green_yellow": 154, + "dark_olive_green2": 155, + "dark_sea_green1": 193, + "pale_turquoise1": 159, + "deep_pink3": 162, + "magenta2": 200, + "hot_pink2": 169, + "orchid": 170, + "medium_orchid1": 207, + "orange3": 172, + "light_pink3": 174, + "pink3": 175, + "plum3": 176, + "violet": 177, + "light_goldenrod3": 179, + "tan": 180, + "misty_rose3": 181, + "thistle3": 182, + "plum2": 183, + "khaki3": 185, + "light_goldenrod2": 222, + "light_yellow3": 187, + "grey84": 188, + "gray84": 188, + "light_steel_blue1": 189, + "yellow2": 190, + "dark_olive_green1": 192, + "honeydew2": 194, + "light_cyan1": 195, + "red1": 196, + "deep_pink2": 197, + "deep_pink1": 199, + "magenta1": 201, + "orange_red1": 202, + "indian_red1": 204, + "hot_pink": 206, + "dark_orange": 208, + "salmon1": 209, + "light_coral": 210, + "pale_violet_red1": 211, + "orchid2": 212, + "orchid1": 213, + "orange1": 214, + "sandy_brown": 215, + "light_salmon1": 216, + "light_pink1": 217, + "pink1": 218, + "plum1": 219, + "gold1": 220, + "navajo_white1": 223, + "misty_rose1": 224, + "thistle1": 225, + "yellow1": 226, + "light_goldenrod1": 227, + "khaki1": 228, + "wheat1": 229, + "cornsilk1": 230, + "grey100": 231, + "gray100": 231, + "grey3": 232, + "gray3": 232, + "grey7": 233, + "gray7": 233, + "grey11": 234, + "gray11": 234, + "grey15": 235, + "gray15": 235, + "grey19": 236, + "gray19": 236, + "grey23": 237, + "gray23": 237, + "grey27": 238, + "gray27": 238, + "grey30": 239, + "gray30": 239, + "grey35": 240, + "gray35": 240, + "grey39": 241, + "gray39": 241, + "grey42": 242, + "gray42": 242, + "grey46": 243, + "gray46": 243, + "grey50": 244, + "gray50": 244, + "grey54": 245, + "gray54": 245, + "grey58": 246, + "gray58": 246, + "grey62": 247, + "gray62": 247, + "grey66": 248, + "gray66": 248, + "grey70": 249, + "gray70": 249, + "grey74": 250, + "gray74": 250, + "grey78": 251, + "gray78": 251, + "grey82": 252, + "gray82": 252, + "grey85": 253, + "gray85": 253, + "grey89": 254, + "gray89": 254, + "grey93": 255, + "gray93": 255, +} + + +class ColorParseError(Exception): + """The color could not be parsed.""" + + +RE_COLOR = re.compile( + r"""^ +\#([0-9a-f]{6})$| +color\(([0-9]{1,3})\)$| +rgb\(([\d\s,]+)\)$ +""", + re.VERBOSE, +) + + +@rich_repr +class Color(NamedTuple): + """Terminal color definition.""" + + name: str + """The name of the color (typically the input to Color.parse).""" + type: ColorType + """The type of the color.""" + number: Optional[int] = None + """The color number, if a standard color, or None.""" + triplet: Optional[ColorTriplet] = None + """A triplet of color components, if an RGB color.""" + + def __rich__(self) -> "Text": + """Displays the actual color if Rich printed.""" + from .style import Style + from .text import Text + + return Text.assemble( + f"", + ) + + def __rich_repr__(self) -> Result: + yield self.name + yield self.type + yield "number", self.number, None + yield "triplet", self.triplet, None + + @property + def system(self) -> ColorSystem: + """Get the native color system for this color.""" + if self.type == ColorType.DEFAULT: + return ColorSystem.STANDARD + return ColorSystem(int(self.type)) + + @property + def is_system_defined(self) -> bool: + """Check if the color is ultimately defined by the system.""" + return self.system not in (ColorSystem.EIGHT_BIT, ColorSystem.TRUECOLOR) + + @property + def is_default(self) -> bool: + """Check if the color is a default color.""" + return self.type == ColorType.DEFAULT + + def get_truecolor( + self, theme: Optional["TerminalTheme"] = None, foreground: bool = True + ) -> ColorTriplet: + """Get an equivalent color triplet for this color. + + Args: + theme (TerminalTheme, optional): Optional terminal theme, or None to use default. Defaults to None. + foreground (bool, optional): True for a foreground color, or False for background. Defaults to True. + + Returns: + ColorTriplet: A color triplet containing RGB components. + """ + + if theme is None: + theme = DEFAULT_TERMINAL_THEME + if self.type == ColorType.TRUECOLOR: + assert self.triplet is not None + return self.triplet + elif self.type == ColorType.EIGHT_BIT: + assert self.number is not None + return EIGHT_BIT_PALETTE[self.number] + elif self.type == ColorType.STANDARD: + assert self.number is not None + return theme.ansi_colors[self.number] + elif self.type == ColorType.WINDOWS: + assert self.number is not None + return WINDOWS_PALETTE[self.number] + else: # self.type == ColorType.DEFAULT: + assert self.number is None + return theme.foreground_color if foreground else theme.background_color + + @classmethod + def from_ansi(cls, number: int) -> "Color": + """Create a Color number from it's 8-bit ansi number. + + Args: + number (int): A number between 0-255 inclusive. + + Returns: + Color: A new Color instance. + """ + return cls( + name=f"color({number})", + type=(ColorType.STANDARD if number < 16 else ColorType.EIGHT_BIT), + number=number, + ) + + @classmethod + def from_triplet(cls, triplet: "ColorTriplet") -> "Color": + """Create a truecolor RGB color from a triplet of values. + + Args: + triplet (ColorTriplet): A color triplet containing red, green and blue components. + + Returns: + Color: A new color object. + """ + return cls(name=triplet.hex, type=ColorType.TRUECOLOR, triplet=triplet) + + @classmethod + def from_rgb(cls, red: float, green: float, blue: float) -> "Color": + """Create a truecolor from three color components in the range(0->255). + + Args: + red (float): Red component in range 0-255. + green (float): Green component in range 0-255. + blue (float): Blue component in range 0-255. + + Returns: + Color: A new color object. + """ + return cls.from_triplet(ColorTriplet(int(red), int(green), int(blue))) + + @classmethod + def default(cls) -> "Color": + """Get a Color instance representing the default color. + + Returns: + Color: Default color. + """ + return cls(name="default", type=ColorType.DEFAULT) + + @classmethod + @lru_cache(maxsize=1024) + def parse(cls, color: str) -> "Color": + """Parse a color definition.""" + original_color = color + color = color.lower().strip() + + if color == "default": + return cls(color, type=ColorType.DEFAULT) + + color_number = ANSI_COLOR_NAMES.get(color) + if color_number is not None: + return cls( + color, + type=(ColorType.STANDARD if color_number < 16 else ColorType.EIGHT_BIT), + number=color_number, + ) + + color_match = RE_COLOR.match(color) + if color_match is None: + raise ColorParseError(f"{original_color!r} is not a valid color") + + color_24, color_8, color_rgb = color_match.groups() + if color_24: + triplet = ColorTriplet( + int(color_24[0:2], 16), int(color_24[2:4], 16), int(color_24[4:6], 16) + ) + return cls(color, ColorType.TRUECOLOR, triplet=triplet) + + elif color_8: + number = int(color_8) + if number > 255: + raise ColorParseError(f"color number must be <= 255 in {color!r}") + return cls( + color, + type=(ColorType.STANDARD if number < 16 else ColorType.EIGHT_BIT), + number=number, + ) + + else: # color_rgb: + components = color_rgb.split(",") + if len(components) != 3: + raise ColorParseError( + f"expected three components in {original_color!r}" + ) + red, green, blue = components + triplet = ColorTriplet(int(red), int(green), int(blue)) + if not all(component <= 255 for component in triplet): + raise ColorParseError( + f"color components must be <= 255 in {original_color!r}" + ) + return cls(color, ColorType.TRUECOLOR, triplet=triplet) + + @lru_cache(maxsize=1024) + def get_ansi_codes(self, foreground: bool = True) -> Tuple[str, ...]: + """Get the ANSI escape codes for this color.""" + _type = self.type + if _type == ColorType.DEFAULT: + return ("39" if foreground else "49",) + + elif _type == ColorType.WINDOWS: + number = self.number + assert number is not None + fore, back = (30, 40) if number < 8 else (82, 92) + return (str(fore + number if foreground else back + number),) + + elif _type == ColorType.STANDARD: + number = self.number + assert number is not None + fore, back = (30, 40) if number < 8 else (82, 92) + return (str(fore + number if foreground else back + number),) + + elif _type == ColorType.EIGHT_BIT: + assert self.number is not None + return ("38" if foreground else "48", "5", str(self.number)) + + else: # self.standard == ColorStandard.TRUECOLOR: + assert self.triplet is not None + red, green, blue = self.triplet + return ("38" if foreground else "48", "2", str(red), str(green), str(blue)) + + @lru_cache(maxsize=1024) + def downgrade(self, system: ColorSystem) -> "Color": + """Downgrade a color system to a system with fewer colors.""" + + if self.type in (ColorType.DEFAULT, system): + return self + # Convert to 8-bit color from truecolor color + if system == ColorSystem.EIGHT_BIT and self.system == ColorSystem.TRUECOLOR: + assert self.triplet is not None + _h, l, s = rgb_to_hls(*self.triplet.normalized) + # If saturation is under 15% assume it is grayscale + if s < 0.15: + gray = round(l * 25.0) + if gray == 0: + color_number = 16 + elif gray == 25: + color_number = 231 + else: + color_number = 231 + gray + return Color(self.name, ColorType.EIGHT_BIT, number=color_number) + + red, green, blue = self.triplet + six_red = red / 95 if red < 95 else 1 + (red - 95) / 40 + six_green = green / 95 if green < 95 else 1 + (green - 95) / 40 + six_blue = blue / 95 if blue < 95 else 1 + (blue - 95) / 40 + + color_number = ( + 16 + 36 * round(six_red) + 6 * round(six_green) + round(six_blue) + ) + return Color(self.name, ColorType.EIGHT_BIT, number=color_number) + + # Convert to standard from truecolor or 8-bit + elif system == ColorSystem.STANDARD: + if self.system == ColorSystem.TRUECOLOR: + assert self.triplet is not None + triplet = self.triplet + else: # self.system == ColorSystem.EIGHT_BIT + assert self.number is not None + triplet = ColorTriplet(*EIGHT_BIT_PALETTE[self.number]) + + color_number = STANDARD_PALETTE.match(triplet) + return Color(self.name, ColorType.STANDARD, number=color_number) + + elif system == ColorSystem.WINDOWS: + if self.system == ColorSystem.TRUECOLOR: + assert self.triplet is not None + triplet = self.triplet + else: # self.system == ColorSystem.EIGHT_BIT + assert self.number is not None + if self.number < 16: + return Color(self.name, ColorType.WINDOWS, number=self.number) + triplet = ColorTriplet(*EIGHT_BIT_PALETTE[self.number]) + + color_number = WINDOWS_PALETTE.match(triplet) + return Color(self.name, ColorType.WINDOWS, number=color_number) + + return self + + +def parse_rgb_hex(hex_color: str) -> ColorTriplet: + """Parse six hex characters in to RGB triplet.""" + assert len(hex_color) == 6, "must be 6 characters" + color = ColorTriplet( + int(hex_color[0:2], 16), int(hex_color[2:4], 16), int(hex_color[4:6], 16) + ) + return color + + +def blend_rgb( + color1: ColorTriplet, color2: ColorTriplet, cross_fade: float = 0.5 +) -> ColorTriplet: + """Blend one RGB color in to another.""" + r1, g1, b1 = color1 + r2, g2, b2 = color2 + new_color = ColorTriplet( + int(r1 + (r2 - r1) * cross_fade), + int(g1 + (g2 - g1) * cross_fade), + int(b1 + (b2 - b1) * cross_fade), + ) + return new_color + + +if __name__ == "__main__": # pragma: no cover + from .console import Console + from .table import Table + from .text import Text + + console = Console() + + table = Table(show_footer=False, show_edge=True) + table.add_column("Color", width=10, overflow="ellipsis") + table.add_column("Number", justify="right", style="yellow") + table.add_column("Name", style="green") + table.add_column("Hex", style="blue") + table.add_column("RGB", style="magenta") + + colors = sorted((v, k) for k, v in ANSI_COLOR_NAMES.items()) + for color_number, name in colors: + if "grey" in name: + continue + color_cell = Text(" " * 10, style=f"on {name}") + if color_number < 16: + table.add_row(color_cell, f"{color_number}", Text(f'"{name}"')) + else: + color = EIGHT_BIT_PALETTE[color_number] # type: ignore[has-type] + table.add_row( + color_cell, str(color_number), Text(f'"{name}"'), color.hex, color.rgb + ) + + console.print(table) diff --git a/rich/console.py b/rich/console.py new file mode 100644 index 0000000000000000000000000000000000000000..ad92d529c0f8bdd09214ae393d598bb4d90067bc --- /dev/null +++ b/rich/console.py @@ -0,0 +1,2684 @@ +import inspect +import os +import sys +import threading +import zlib +from abc import ABC, abstractmethod +from dataclasses import dataclass, field +from datetime import datetime +from functools import wraps +from getpass import getpass +from html import escape +from inspect import isclass +from itertools import islice +from math import ceil +from time import monotonic +from types import FrameType, ModuleType, TracebackType +from typing import ( + IO, + TYPE_CHECKING, + Any, + Callable, + Dict, + Iterable, + List, + Literal, + Mapping, + NamedTuple, + Optional, + Protocol, + TextIO, + Tuple, + Type, + Union, + cast, + runtime_checkable, +) + +from rich._null_file import NULL_FILE + +from . import errors, themes +from ._emoji_replace import _emoji_replace +from ._export_format import CONSOLE_HTML_FORMAT, CONSOLE_SVG_FORMAT +from ._fileno import get_fileno +from ._log_render import FormatTimeCallable, LogRender +from .align import Align, AlignMethod +from .color import ColorSystem, blend_rgb +from .control import Control +from .emoji import EmojiVariant +from .highlighter import NullHighlighter, ReprHighlighter +from .markup import render as render_markup +from .measure import Measurement, measure_renderables +from .pager import Pager, SystemPager +from .pretty import Pretty, is_expandable +from .protocol import rich_cast +from .region import Region +from .scope import render_scope +from .screen import Screen +from .segment import Segment +from .style import Style, StyleType +from .styled import Styled +from .terminal_theme import DEFAULT_TERMINAL_THEME, SVG_EXPORT_THEME, TerminalTheme +from .text import Text, TextType +from .theme import Theme, ThemeStack + +if TYPE_CHECKING: + from ._windows import WindowsConsoleFeatures + from .live import Live + from .status import Status + +JUPYTER_DEFAULT_COLUMNS = 115 +JUPYTER_DEFAULT_LINES = 100 +WINDOWS = sys.platform == "win32" + +HighlighterType = Callable[[Union[str, "Text"]], "Text"] +JustifyMethod = Literal["default", "left", "center", "right", "full"] +OverflowMethod = Literal["fold", "crop", "ellipsis", "ignore"] + + +class NoChange: + pass + + +NO_CHANGE = NoChange() + +try: + _STDIN_FILENO = sys.__stdin__.fileno() # type: ignore[union-attr] +except Exception: + _STDIN_FILENO = 0 +try: + _STDOUT_FILENO = sys.__stdout__.fileno() # type: ignore[union-attr] +except Exception: + _STDOUT_FILENO = 1 +try: + _STDERR_FILENO = sys.__stderr__.fileno() # type: ignore[union-attr] +except Exception: + _STDERR_FILENO = 2 + +_STD_STREAMS = (_STDIN_FILENO, _STDOUT_FILENO, _STDERR_FILENO) +_STD_STREAMS_OUTPUT = (_STDOUT_FILENO, _STDERR_FILENO) + + +_TERM_COLORS = { + "kitty": ColorSystem.EIGHT_BIT, + "256color": ColorSystem.EIGHT_BIT, + "16color": ColorSystem.STANDARD, +} + + +class ConsoleDimensions(NamedTuple): + """Size of the terminal.""" + + width: int + """The width of the console in 'cells'.""" + height: int + """The height of the console in lines.""" + + +@dataclass +class ConsoleOptions: + """Options for __rich_console__ method.""" + + size: ConsoleDimensions + """Size of console.""" + legacy_windows: bool + """legacy_windows: flag for legacy windows.""" + min_width: int + """Minimum width of renderable.""" + max_width: int + """Maximum width of renderable.""" + is_terminal: bool + """True if the target is a terminal, otherwise False.""" + encoding: str + """Encoding of terminal.""" + max_height: int + """Height of container (starts as terminal)""" + justify: Optional[JustifyMethod] = None + """Justify value override for renderable.""" + overflow: Optional[OverflowMethod] = None + """Overflow value override for renderable.""" + no_wrap: Optional[bool] = False + """Disable wrapping for text.""" + highlight: Optional[bool] = None + """Highlight override for render_str.""" + markup: Optional[bool] = None + """Enable markup when rendering strings.""" + height: Optional[int] = None + + @property + def ascii_only(self) -> bool: + """Check if renderables should use ascii only.""" + return not self.encoding.startswith("utf") + + def copy(self) -> "ConsoleOptions": + """Return a copy of the options. + + Returns: + ConsoleOptions: a copy of self. + """ + options: ConsoleOptions = ConsoleOptions.__new__(ConsoleOptions) + options.__dict__ = self.__dict__.copy() + return options + + def update( + self, + *, + width: Union[int, NoChange] = NO_CHANGE, + min_width: Union[int, NoChange] = NO_CHANGE, + max_width: Union[int, NoChange] = NO_CHANGE, + justify: Union[Optional[JustifyMethod], NoChange] = NO_CHANGE, + overflow: Union[Optional[OverflowMethod], NoChange] = NO_CHANGE, + no_wrap: Union[Optional[bool], NoChange] = NO_CHANGE, + highlight: Union[Optional[bool], NoChange] = NO_CHANGE, + markup: Union[Optional[bool], NoChange] = NO_CHANGE, + height: Union[Optional[int], NoChange] = NO_CHANGE, + ) -> "ConsoleOptions": + """Update values, return a copy.""" + options = self.copy() + if not isinstance(width, NoChange): + options.min_width = options.max_width = max(0, width) + if not isinstance(min_width, NoChange): + options.min_width = min_width + if not isinstance(max_width, NoChange): + options.max_width = max_width + if not isinstance(justify, NoChange): + options.justify = justify + if not isinstance(overflow, NoChange): + options.overflow = overflow + if not isinstance(no_wrap, NoChange): + options.no_wrap = no_wrap + if not isinstance(highlight, NoChange): + options.highlight = highlight + if not isinstance(markup, NoChange): + options.markup = markup + if not isinstance(height, NoChange): + if height is not None: + options.max_height = height + options.height = None if height is None else max(0, height) + return options + + def update_width(self, width: int) -> "ConsoleOptions": + """Update just the width, return a copy. + + Args: + width (int): New width (sets both min_width and max_width) + + Returns: + ~ConsoleOptions: New console options instance. + """ + options = self.copy() + options.min_width = options.max_width = max(0, width) + return options + + def update_height(self, height: int) -> "ConsoleOptions": + """Update the height, and return a copy. + + Args: + height (int): New height + + Returns: + ~ConsoleOptions: New Console options instance. + """ + options = self.copy() + options.max_height = options.height = height + return options + + def reset_height(self) -> "ConsoleOptions": + """Return a copy of the options with height set to ``None``. + + Returns: + ~ConsoleOptions: New console options instance. + """ + options = self.copy() + options.height = None + return options + + def update_dimensions(self, width: int, height: int) -> "ConsoleOptions": + """Update the width and height, and return a copy. + + Args: + width (int): New width (sets both min_width and max_width). + height (int): New height. + + Returns: + ~ConsoleOptions: New console options instance. + """ + options = self.copy() + options.min_width = options.max_width = max(0, width) + options.height = options.max_height = height + return options + + +@runtime_checkable +class RichCast(Protocol): + """An object that may be 'cast' to a console renderable.""" + + def __rich__( + self, + ) -> Union["ConsoleRenderable", "RichCast", str]: # pragma: no cover + ... + + +@runtime_checkable +class ConsoleRenderable(Protocol): + """An object that supports the console protocol.""" + + def __rich_console__( + self, console: "Console", options: "ConsoleOptions" + ) -> "RenderResult": # pragma: no cover + ... + + +# A type that may be rendered by Console. +RenderableType = Union[ConsoleRenderable, RichCast, str] +"""A string or any object that may be rendered by Rich.""" + +# The result of calling a __rich_console__ method. +RenderResult = Iterable[Union[RenderableType, Segment]] + +_null_highlighter = NullHighlighter() + + +class CaptureError(Exception): + """An error in the Capture context manager.""" + + +class NewLine: + """A renderable to generate new line(s)""" + + def __init__(self, count: int = 1) -> None: + self.count = count + + def __rich_console__( + self, console: "Console", options: "ConsoleOptions" + ) -> Iterable[Segment]: + yield Segment("\n" * self.count) + + +class ScreenUpdate: + """Render a list of lines at a given offset.""" + + def __init__(self, lines: List[List[Segment]], x: int, y: int) -> None: + self._lines = lines + self.x = x + self.y = y + + def __rich_console__( + self, console: "Console", options: ConsoleOptions + ) -> RenderResult: + x = self.x + move_to = Control.move_to + for offset, line in enumerate(self._lines, self.y): + yield move_to(x, offset) + yield from line + + +class Capture: + """Context manager to capture the result of printing to the console. + See :meth:`~rich.console.Console.capture` for how to use. + + Args: + console (Console): A console instance to capture output. + """ + + def __init__(self, console: "Console") -> None: + self._console = console + self._result: Optional[str] = None + + def __enter__(self) -> "Capture": + self._console.begin_capture() + return self + + def __exit__( + self, + exc_type: Optional[Type[BaseException]], + exc_val: Optional[BaseException], + exc_tb: Optional[TracebackType], + ) -> None: + self._result = self._console.end_capture() + + def get(self) -> str: + """Get the result of the capture.""" + if self._result is None: + raise CaptureError( + "Capture result is not available until context manager exits." + ) + return self._result + + +class ThemeContext: + """A context manager to use a temporary theme. See :meth:`~rich.console.Console.use_theme` for usage.""" + + def __init__(self, console: "Console", theme: Theme, inherit: bool = True) -> None: + self.console = console + self.theme = theme + self.inherit = inherit + + def __enter__(self) -> "ThemeContext": + self.console.push_theme(self.theme) + return self + + def __exit__( + self, + exc_type: Optional[Type[BaseException]], + exc_val: Optional[BaseException], + exc_tb: Optional[TracebackType], + ) -> None: + self.console.pop_theme() + + +class PagerContext: + """A context manager that 'pages' content. See :meth:`~rich.console.Console.pager` for usage.""" + + def __init__( + self, + console: "Console", + pager: Optional[Pager] = None, + styles: bool = False, + links: bool = False, + ) -> None: + self._console = console + self.pager = SystemPager() if pager is None else pager + self.styles = styles + self.links = links + + def __enter__(self) -> "PagerContext": + self._console._enter_buffer() + return self + + def __exit__( + self, + exc_type: Optional[Type[BaseException]], + exc_val: Optional[BaseException], + exc_tb: Optional[TracebackType], + ) -> None: + if exc_type is None: + with self._console._lock: + buffer: List[Segment] = self._console._buffer[:] + del self._console._buffer[:] + segments: Iterable[Segment] = buffer + if not self.styles: + segments = Segment.strip_styles(segments) + elif not self.links: + segments = Segment.strip_links(segments) + content = self._console._render_buffer(segments) + self.pager.show(content) + self._console._exit_buffer() + + +class ScreenContext: + """A context manager that enables an alternative screen. See :meth:`~rich.console.Console.screen` for usage.""" + + def __init__( + self, console: "Console", hide_cursor: bool, style: StyleType = "" + ) -> None: + self.console = console + self.hide_cursor = hide_cursor + self.screen = Screen(style=style) + self._changed = False + + def update( + self, *renderables: RenderableType, style: Optional[StyleType] = None + ) -> None: + """Update the screen. + + Args: + renderable (RenderableType, optional): Optional renderable to replace current renderable, + or None for no change. Defaults to None. + style: (Style, optional): Replacement style, or None for no change. Defaults to None. + """ + if renderables: + self.screen.renderable = ( + Group(*renderables) if len(renderables) > 1 else renderables[0] + ) + if style is not None: + self.screen.style = style + self.console.print(self.screen, end="") + + def __enter__(self) -> "ScreenContext": + self._changed = self.console.set_alt_screen(True) + if self._changed and self.hide_cursor: + self.console.show_cursor(False) + return self + + def __exit__( + self, + exc_type: Optional[Type[BaseException]], + exc_val: Optional[BaseException], + exc_tb: Optional[TracebackType], + ) -> None: + if self._changed: + self.console.set_alt_screen(False) + if self.hide_cursor: + self.console.show_cursor(True) + + +class Group: + """Takes a group of renderables and returns a renderable object that renders the group. + + Args: + renderables (Iterable[RenderableType]): An iterable of renderable objects. + fit (bool, optional): Fit dimension of group to contents, or fill available space. Defaults to True. + """ + + def __init__(self, *renderables: "RenderableType", fit: bool = True) -> None: + self._renderables = renderables + self.fit = fit + self._render: Optional[List[RenderableType]] = None + + @property + def renderables(self) -> List["RenderableType"]: + if self._render is None: + self._render = list(self._renderables) + return self._render + + def __rich_measure__( + self, console: "Console", options: "ConsoleOptions" + ) -> "Measurement": + if self.fit: + return measure_renderables(console, options, self.renderables) + else: + return Measurement(options.max_width, options.max_width) + + def __rich_console__( + self, console: "Console", options: "ConsoleOptions" + ) -> RenderResult: + yield from self.renderables + + +def group(fit: bool = True) -> Callable[..., Callable[..., Group]]: + """A decorator that turns an iterable of renderables in to a group. + + Args: + fit (bool, optional): Fit dimension of group to contents, or fill available space. Defaults to True. + """ + + def decorator( + method: Callable[..., Iterable[RenderableType]], + ) -> Callable[..., Group]: + """Convert a method that returns an iterable of renderables in to a Group.""" + + @wraps(method) + def _replace(*args: Any, **kwargs: Any) -> Group: + renderables = method(*args, **kwargs) + return Group(*renderables, fit=fit) + + return _replace + + return decorator + + +def _is_jupyter() -> bool: # pragma: no cover + """Check if we're running in a Jupyter notebook.""" + try: + get_ipython # type: ignore[name-defined] + except NameError: + return False + ipython = get_ipython() # type: ignore[name-defined] + shell = ipython.__class__.__name__ + if ( + "google.colab" in str(ipython.__class__) + or os.getenv("DATABRICKS_RUNTIME_VERSION") + or shell == "ZMQInteractiveShell" + ): + return True # Jupyter notebook or qtconsole + elif shell == "TerminalInteractiveShell": + return False # Terminal running IPython + else: + return False # Other type (?) + + +COLOR_SYSTEMS = { + "standard": ColorSystem.STANDARD, + "256": ColorSystem.EIGHT_BIT, + "truecolor": ColorSystem.TRUECOLOR, + "windows": ColorSystem.WINDOWS, +} + +_COLOR_SYSTEMS_NAMES = {system: name for name, system in COLOR_SYSTEMS.items()} + + +@dataclass +class ConsoleThreadLocals(threading.local): + """Thread local values for Console context.""" + + theme_stack: ThemeStack + buffer: List[Segment] = field(default_factory=list) + buffer_index: int = 0 + + +class RenderHook(ABC): + """Provides hooks in to the render process.""" + + @abstractmethod + def process_renderables( + self, renderables: List[ConsoleRenderable] + ) -> List[ConsoleRenderable]: + """Called with a list of objects to render. + + This method can return a new list of renderables, or modify and return the same list. + + Args: + renderables (List[ConsoleRenderable]): A number of renderable objects. + + Returns: + List[ConsoleRenderable]: A replacement list of renderables. + """ + + +_windows_console_features: Optional["WindowsConsoleFeatures"] = None + + +def get_windows_console_features() -> "WindowsConsoleFeatures": # pragma: no cover + global _windows_console_features + if _windows_console_features is not None: + return _windows_console_features + from ._windows import get_windows_console_features + + _windows_console_features = get_windows_console_features() + return _windows_console_features + + +def detect_legacy_windows() -> bool: + """Detect legacy Windows.""" + return WINDOWS and not get_windows_console_features().vt + + +class Console: + """A high level console interface. + + Args: + color_system (str, optional): The color system supported by your terminal, + either ``"standard"``, ``"256"`` or ``"truecolor"``. Leave as ``"auto"`` to autodetect. + force_terminal (Optional[bool], optional): Enable/disable terminal control codes, or None to auto-detect terminal. Defaults to None. + force_jupyter (Optional[bool], optional): Enable/disable Jupyter rendering, or None to auto-detect Jupyter. Defaults to None. + force_interactive (Optional[bool], optional): Enable/disable interactive mode, or None to auto detect. Defaults to None. + soft_wrap (Optional[bool], optional): Set soft wrap default on print method. Defaults to False. + theme (Theme, optional): An optional style theme object, or ``None`` for default theme. + stderr (bool, optional): Use stderr rather than stdout if ``file`` is not specified. Defaults to False. + file (IO, optional): A file object where the console should write to. Defaults to stdout. + quiet (bool, Optional): Boolean to suppress all output. Defaults to False. + width (int, optional): The width of the terminal. Leave as default to auto-detect width. + height (int, optional): The height of the terminal. Leave as default to auto-detect height. + style (StyleType, optional): Style to apply to all output, or None for no style. Defaults to None. + no_color (Optional[bool], optional): Enabled no color mode, or None to auto detect. Defaults to None. + tab_size (int, optional): Number of spaces used to replace a tab character. Defaults to 8. + record (bool, optional): Boolean to enable recording of terminal output, + required to call :meth:`export_html`, :meth:`export_svg`, and :meth:`export_text`. Defaults to False. + markup (bool, optional): Boolean to enable :ref:`console_markup`. Defaults to True. + emoji (bool, optional): Enable emoji code. Defaults to True. + emoji_variant (str, optional): Optional emoji variant, either "text" or "emoji". Defaults to None. + highlight (bool, optional): Enable automatic highlighting. Defaults to True. + log_time (bool, optional): Boolean to enable logging of time by :meth:`log` methods. Defaults to True. + log_path (bool, optional): Boolean to enable the logging of the caller by :meth:`log`. Defaults to True. + log_time_format (Union[str, TimeFormatterCallable], optional): If ``log_time`` is enabled, either string for strftime or callable that formats the time. Defaults to "[%X] ". + highlighter (HighlighterType, optional): Default highlighter. + legacy_windows (bool, optional): Enable legacy Windows mode, or ``None`` to auto detect. Defaults to ``None``. + safe_box (bool, optional): Restrict box options that don't render on legacy Windows. + get_datetime (Callable[[], datetime], optional): Callable that gets the current time as a datetime.datetime object (used by Console.log), + or None for datetime.now. + get_time (Callable[[], time], optional): Callable that gets the current time in seconds, default uses time.monotonic. + """ + + _environ: Mapping[str, str] = os.environ + + def __init__( + self, + *, + color_system: Optional[ + Literal["auto", "standard", "256", "truecolor", "windows"] + ] = "auto", + force_terminal: Optional[bool] = None, + force_jupyter: Optional[bool] = None, + force_interactive: Optional[bool] = None, + soft_wrap: bool = False, + theme: Optional[Theme] = None, + stderr: bool = False, + file: Optional[IO[str]] = None, + quiet: bool = False, + width: Optional[int] = None, + height: Optional[int] = None, + style: Optional[StyleType] = None, + no_color: Optional[bool] = None, + tab_size: int = 8, + record: bool = False, + markup: bool = True, + emoji: bool = True, + emoji_variant: Optional[EmojiVariant] = None, + highlight: bool = True, + log_time: bool = True, + log_path: bool = True, + log_time_format: Union[str, FormatTimeCallable] = "[%X]", + highlighter: Optional["HighlighterType"] = ReprHighlighter(), + legacy_windows: Optional[bool] = None, + safe_box: bool = True, + get_datetime: Optional[Callable[[], datetime]] = None, + get_time: Optional[Callable[[], float]] = None, + _environ: Optional[Mapping[str, str]] = None, + ): + # Copy of os.environ allows us to replace it for testing + if _environ is not None: + self._environ = _environ + + self.is_jupyter = _is_jupyter() if force_jupyter is None else force_jupyter + if self.is_jupyter: + if width is None: + jupyter_columns = self._environ.get("JUPYTER_COLUMNS") + if jupyter_columns is not None and jupyter_columns.isdigit(): + width = int(jupyter_columns) + else: + width = JUPYTER_DEFAULT_COLUMNS + if height is None: + jupyter_lines = self._environ.get("JUPYTER_LINES") + if jupyter_lines is not None and jupyter_lines.isdigit(): + height = int(jupyter_lines) + else: + height = JUPYTER_DEFAULT_LINES + + self.tab_size = tab_size + self.record = record + self._markup = markup + self._emoji = emoji + self._emoji_variant: Optional[EmojiVariant] = emoji_variant + self._highlight = highlight + self.legacy_windows: bool = ( + (detect_legacy_windows() and not self.is_jupyter) + if legacy_windows is None + else legacy_windows + ) + + if width is None: + columns = self._environ.get("COLUMNS") + if columns is not None and columns.isdigit(): + width = int(columns) - self.legacy_windows + if height is None: + lines = self._environ.get("LINES") + if lines is not None and lines.isdigit(): + height = int(lines) + + self.soft_wrap = soft_wrap + self._width = width + self._height = height + + self._color_system: Optional[ColorSystem] + + self._force_terminal = None + if force_terminal is not None: + self._force_terminal = force_terminal + + self._file = file + self.quiet = quiet + self.stderr = stderr + + if color_system is None: + self._color_system = None + elif color_system == "auto": + self._color_system = self._detect_color_system() + else: + self._color_system = COLOR_SYSTEMS[color_system] + + self._lock = threading.RLock() + self._log_render = LogRender( + show_time=log_time, + show_path=log_path, + time_format=log_time_format, + ) + self.highlighter: HighlighterType = highlighter or _null_highlighter + self.safe_box = safe_box + self.get_datetime = get_datetime or datetime.now + self.get_time = get_time or monotonic + self.style = style + self.no_color = ( + no_color + if no_color is not None + else self._environ.get("NO_COLOR", "") != "" + ) + if force_interactive is None: + tty_interactive = self._environ.get("TTY_INTERACTIVE", None) + if tty_interactive is not None: + if tty_interactive == "0": + force_interactive = False + elif tty_interactive == "1": + force_interactive = True + + self.is_interactive = ( + (self.is_terminal and not self.is_dumb_terminal) + if force_interactive is None + else force_interactive + ) + + self._record_buffer_lock = threading.RLock() + self._thread_locals = ConsoleThreadLocals( + theme_stack=ThemeStack(themes.DEFAULT if theme is None else theme) + ) + self._record_buffer: List[Segment] = [] + self._render_hooks: List[RenderHook] = [] + self._live_stack: List[Live] = [] + self._is_alt_screen = False + + def __repr__(self) -> str: + return f"" + + @property + def file(self) -> IO[str]: + """Get the file object to write to.""" + file = self._file or (sys.stderr if self.stderr else sys.stdout) + file = getattr(file, "rich_proxied_file", file) + if file is None: + file = NULL_FILE + return file + + @file.setter + def file(self, new_file: IO[str]) -> None: + """Set a new file object.""" + self._file = new_file + + @property + def _buffer(self) -> List[Segment]: + """Get a thread local buffer.""" + return self._thread_locals.buffer + + @property + def _buffer_index(self) -> int: + """Get a thread local buffer.""" + return self._thread_locals.buffer_index + + @_buffer_index.setter + def _buffer_index(self, value: int) -> None: + self._thread_locals.buffer_index = value + + @property + def _theme_stack(self) -> ThemeStack: + """Get the thread local theme stack.""" + return self._thread_locals.theme_stack + + def _detect_color_system(self) -> Optional[ColorSystem]: + """Detect color system from env vars.""" + if self.is_jupyter: + return ColorSystem.TRUECOLOR + if not self.is_terminal or self.is_dumb_terminal: + return None + if WINDOWS: # pragma: no cover + if self.legacy_windows: # pragma: no cover + return ColorSystem.WINDOWS + windows_console_features = get_windows_console_features() + return ( + ColorSystem.TRUECOLOR + if windows_console_features.truecolor + else ColorSystem.EIGHT_BIT + ) + else: + color_term = self._environ.get("COLORTERM", "").strip().lower() + if color_term in ("truecolor", "24bit"): + return ColorSystem.TRUECOLOR + term = self._environ.get("TERM", "").strip().lower() + _term_name, _hyphen, colors = term.rpartition("-") + color_system = _TERM_COLORS.get(colors, ColorSystem.STANDARD) + return color_system + + def _enter_buffer(self) -> None: + """Enter in to a buffer context, and buffer all output.""" + self._buffer_index += 1 + + def _exit_buffer(self) -> None: + """Leave buffer context, and render content if required.""" + self._buffer_index -= 1 + self._check_buffer() + + def set_live(self, live: "Live") -> bool: + """Set Live instance. Used by Live context manager (no need to call directly). + + Args: + live (Live): Live instance using this Console. + + Returns: + Boolean that indicates if the live is the topmost of the stack. + + Raises: + errors.LiveError: If this Console has a Live context currently active. + """ + with self._lock: + self._live_stack.append(live) + return len(self._live_stack) == 1 + + def clear_live(self) -> None: + """Clear the Live instance. Used by the Live context manager (no need to call directly).""" + with self._lock: + self._live_stack.pop() + + def push_render_hook(self, hook: RenderHook) -> None: + """Add a new render hook to the stack. + + Args: + hook (RenderHook): Render hook instance. + """ + with self._lock: + self._render_hooks.append(hook) + + def pop_render_hook(self) -> None: + """Pop the last renderhook from the stack.""" + with self._lock: + self._render_hooks.pop() + + def __enter__(self) -> "Console": + """Own context manager to enter buffer context.""" + self._enter_buffer() + return self + + def __exit__(self, exc_type: Any, exc_value: Any, traceback: Any) -> None: + """Exit buffer context.""" + self._exit_buffer() + + def begin_capture(self) -> None: + """Begin capturing console output. Call :meth:`end_capture` to exit capture mode and return output.""" + self._enter_buffer() + + def end_capture(self) -> str: + """End capture mode and return captured string. + + Returns: + str: Console output. + """ + render_result = self._render_buffer(self._buffer) + del self._buffer[:] + self._exit_buffer() + return render_result + + def push_theme(self, theme: Theme, *, inherit: bool = True) -> None: + """Push a new theme on to the top of the stack, replacing the styles from the previous theme. + Generally speaking, you should call :meth:`~rich.console.Console.use_theme` to get a context manager, rather + than calling this method directly. + + Args: + theme (Theme): A theme instance. + inherit (bool, optional): Inherit existing styles. Defaults to True. + """ + self._theme_stack.push_theme(theme, inherit=inherit) + + def pop_theme(self) -> None: + """Remove theme from top of stack, restoring previous theme.""" + self._theme_stack.pop_theme() + + def use_theme(self, theme: Theme, *, inherit: bool = True) -> ThemeContext: + """Use a different theme for the duration of the context manager. + + Args: + theme (Theme): Theme instance to user. + inherit (bool, optional): Inherit existing console styles. Defaults to True. + + Returns: + ThemeContext: [description] + """ + return ThemeContext(self, theme, inherit) + + @property + def color_system(self) -> Optional[str]: + """Get color system string. + + Returns: + Optional[str]: "standard", "256" or "truecolor". + """ + + if self._color_system is not None: + return _COLOR_SYSTEMS_NAMES[self._color_system] + else: + return None + + @property + def encoding(self) -> str: + """Get the encoding of the console file, e.g. ``"utf-8"``. + + Returns: + str: A standard encoding string. + """ + return (getattr(self.file, "encoding", "utf-8") or "utf-8").lower() + + @property + def is_terminal(self) -> bool: + """Check if the console is writing to a terminal. + + Returns: + bool: True if the console writing to a device capable of + understanding escape sequences, otherwise False. + """ + # If dev has explicitly set this value, return it + if self._force_terminal is not None: + return self._force_terminal + + # Fudge for Idle + if hasattr(sys.stdin, "__module__") and sys.stdin.__module__.startswith( + "idlelib" + ): + # Return False for Idle which claims to be a tty but can't handle ansi codes + return False + + if self.is_jupyter: + # return False for Jupyter, which may have FORCE_COLOR set + return False + + environ = self._environ + + tty_compatible = environ.get("TTY_COMPATIBLE", "") + # 0 indicates device is not tty compatible + if tty_compatible == "0": + return False + # 1 indicates device is tty compatible + if tty_compatible == "1": + return True + + # https://force-color.org/ + force_color = environ.get("FORCE_COLOR") + if force_color is not None: + return force_color != "" + + # Any other value defaults to auto detect + isatty: Optional[Callable[[], bool]] = getattr(self.file, "isatty", None) + try: + return False if isatty is None else isatty() + except ValueError: + # in some situation (at the end of a pytest run for example) isatty() can raise + # ValueError: I/O operation on closed file + # return False because we aren't in a terminal anymore + return False + + @property + def is_dumb_terminal(self) -> bool: + """Detect dumb terminal. + + Returns: + bool: True if writing to a dumb terminal, otherwise False. + + """ + _term = self._environ.get("TERM", "") + is_dumb = _term.lower() in ("dumb", "unknown") + return self.is_terminal and is_dumb + + @property + def options(self) -> ConsoleOptions: + """Get default console options.""" + size = self.size + return ConsoleOptions( + max_height=size.height, + size=size, + legacy_windows=self.legacy_windows, + min_width=1, + max_width=size.width, + encoding=self.encoding, + is_terminal=self.is_terminal, + ) + + @property + def size(self) -> ConsoleDimensions: + """Get the size of the console. + + Returns: + ConsoleDimensions: A named tuple containing the dimensions. + """ + + if self._width is not None and self._height is not None: + return ConsoleDimensions(self._width - self.legacy_windows, self._height) + + if self.is_dumb_terminal: + return ConsoleDimensions(80, 25) + + width: Optional[int] = None + height: Optional[int] = None + + streams = _STD_STREAMS_OUTPUT if WINDOWS else _STD_STREAMS + for file_descriptor in streams: + try: + width, height = os.get_terminal_size(file_descriptor) + except (AttributeError, ValueError, OSError): # Probably not a terminal + pass + else: + break + + columns = self._environ.get("COLUMNS") + if columns is not None and columns.isdigit(): + width = int(columns) + lines = self._environ.get("LINES") + if lines is not None and lines.isdigit(): + height = int(lines) + + # get_terminal_size can report 0, 0 if run from pseudo-terminal + width = width or 80 + height = height or 25 + return ConsoleDimensions( + width - self.legacy_windows if self._width is None else self._width, + height if self._height is None else self._height, + ) + + @size.setter + def size(self, new_size: Tuple[int, int]) -> None: + """Set a new size for the terminal. + + Args: + new_size (Tuple[int, int]): New width and height. + """ + width, height = new_size + self._width = width + self._height = height + + @property + def width(self) -> int: + """Get the width of the console. + + Returns: + int: The width (in characters) of the console. + """ + return self.size.width + + @width.setter + def width(self, width: int) -> None: + """Set width. + + Args: + width (int): New width. + """ + self._width = width + + @property + def height(self) -> int: + """Get the height of the console. + + Returns: + int: The height (in lines) of the console. + """ + return self.size.height + + @height.setter + def height(self, height: int) -> None: + """Set height. + + Args: + height (int): new height. + """ + self._height = height + + def bell(self) -> None: + """Play a 'bell' sound (if supported by the terminal).""" + self.control(Control.bell()) + + def capture(self) -> Capture: + """A context manager to *capture* the result of print() or log() in a string, + rather than writing it to the console. + + Example: + >>> from rich.console import Console + >>> console = Console() + >>> with console.capture() as capture: + ... console.print("[bold magenta]Hello World[/]") + >>> print(capture.get()) + + Returns: + Capture: Context manager with disables writing to the terminal. + """ + capture = Capture(self) + return capture + + def pager( + self, pager: Optional[Pager] = None, styles: bool = False, links: bool = False + ) -> PagerContext: + """A context manager to display anything printed within a "pager". The pager application + is defined by the system and will typically support at least pressing a key to scroll. + + Args: + pager (Pager, optional): A pager object, or None to use :class:`~rich.pager.SystemPager`. Defaults to None. + styles (bool, optional): Show styles in pager. Defaults to False. + links (bool, optional): Show links in pager. Defaults to False. + + Example: + >>> from rich.console import Console + >>> from rich.__main__ import make_test_card + >>> console = Console() + >>> with console.pager(): + console.print(make_test_card()) + + Returns: + PagerContext: A context manager. + """ + return PagerContext(self, pager=pager, styles=styles, links=links) + + def line(self, count: int = 1) -> None: + """Write new line(s). + + Args: + count (int, optional): Number of new lines. Defaults to 1. + """ + + assert count >= 0, "count must be >= 0" + self.print(NewLine(count)) + + def clear(self, home: bool = True) -> None: + """Clear the screen. + + Args: + home (bool, optional): Also move the cursor to 'home' position. Defaults to True. + """ + if home: + self.control(Control.clear(), Control.home()) + else: + self.control(Control.clear()) + + def status( + self, + status: RenderableType, + *, + spinner: str = "dots", + spinner_style: StyleType = "status.spinner", + speed: float = 1.0, + refresh_per_second: float = 12.5, + ) -> "Status": + """Display a status and spinner. + + Args: + status (RenderableType): A status renderable (str or Text typically). + spinner (str, optional): Name of spinner animation (see python -m rich.spinner). Defaults to "dots". + spinner_style (StyleType, optional): Style of spinner. Defaults to "status.spinner". + speed (float, optional): Speed factor for spinner animation. Defaults to 1.0. + refresh_per_second (float, optional): Number of refreshes per second. Defaults to 12.5. + + Returns: + Status: A Status object that may be used as a context manager. + """ + from .status import Status + + status_renderable = Status( + status, + console=self, + spinner=spinner, + spinner_style=spinner_style, + speed=speed, + refresh_per_second=refresh_per_second, + ) + return status_renderable + + def show_cursor(self, show: bool = True) -> bool: + """Show or hide the cursor. + + Args: + show (bool, optional): Set visibility of the cursor. + """ + if self.is_terminal: + self.control(Control.show_cursor(show)) + return True + return False + + def set_alt_screen(self, enable: bool = True) -> bool: + """Enables alternative screen mode. + + Note, if you enable this mode, you should ensure that is disabled before + the application exits. See :meth:`~rich.Console.screen` for a context manager + that handles this for you. + + Args: + enable (bool, optional): Enable (True) or disable (False) alternate screen. Defaults to True. + + Returns: + bool: True if the control codes were written. + + """ + changed = False + if self.is_terminal and not self.legacy_windows: + self.control(Control.alt_screen(enable)) + changed = True + self._is_alt_screen = enable + return changed + + @property + def is_alt_screen(self) -> bool: + """Check if the alt screen was enabled. + + Returns: + bool: True if the alt screen was enabled, otherwise False. + """ + return self._is_alt_screen + + def set_window_title(self, title: str) -> bool: + """Set the title of the console terminal window. + + Warning: There is no means within Rich of "resetting" the window title to its + previous value, meaning the title you set will persist even after your application + exits. + + ``fish`` shell resets the window title before and after each command by default, + negating this issue. Windows Terminal and command prompt will also reset the title for you. + Most other shells and terminals, however, do not do this. + + Some terminals may require configuration changes before you can set the title. + Some terminals may not support setting the title at all. + + Other software (including the terminal itself, the shell, custom prompts, plugins, etc.) + may also set the terminal window title. This could result in whatever value you write + using this method being overwritten. + + Args: + title (str): The new title of the terminal window. + + Returns: + bool: True if the control code to change the terminal title was + written, otherwise False. Note that a return value of True + does not guarantee that the window title has actually changed, + since the feature may be unsupported/disabled in some terminals. + """ + if self.is_terminal: + self.control(Control.title(title)) + return True + return False + + def screen( + self, hide_cursor: bool = True, style: Optional[StyleType] = None + ) -> "ScreenContext": + """Context manager to enable and disable 'alternative screen' mode. + + Args: + hide_cursor (bool, optional): Also hide the cursor. Defaults to False. + style (Style, optional): Optional style for screen. Defaults to None. + + Returns: + ~ScreenContext: Context which enables alternate screen on enter, and disables it on exit. + """ + return ScreenContext(self, hide_cursor=hide_cursor, style=style or "") + + def measure( + self, renderable: RenderableType, *, options: Optional[ConsoleOptions] = None + ) -> Measurement: + """Measure a renderable. Returns a :class:`~rich.measure.Measurement` object which contains + information regarding the number of characters required to print the renderable. + + Args: + renderable (RenderableType): Any renderable or string. + options (Optional[ConsoleOptions], optional): Options to use when measuring, or None + to use default options. Defaults to None. + + Returns: + Measurement: A measurement of the renderable. + """ + measurement = Measurement.get(self, options or self.options, renderable) + return measurement + + def render( + self, renderable: RenderableType, options: Optional[ConsoleOptions] = None + ) -> Iterable[Segment]: + """Render an object in to an iterable of `Segment` instances. + + This method contains the logic for rendering objects with the console protocol. + You are unlikely to need to use it directly, unless you are extending the library. + + Args: + renderable (RenderableType): An object supporting the console protocol, or + an object that may be converted to a string. + options (ConsoleOptions, optional): An options object, or None to use self.options. Defaults to None. + + Returns: + Iterable[Segment]: An iterable of segments that may be rendered. + """ + + _options = options or self.options + if _options.max_width < 1: + # No space to render anything. This prevents potential recursion errors. + return + render_iterable: RenderResult + + renderable = rich_cast(renderable) + if hasattr(renderable, "__rich_console__") and not isclass(renderable): + render_iterable = renderable.__rich_console__(self, _options) + elif isinstance(renderable, str): + text_renderable = self.render_str( + renderable, highlight=_options.highlight, markup=_options.markup + ) + render_iterable = text_renderable.__rich_console__(self, _options) + else: + raise errors.NotRenderableError( + f"Unable to render {renderable!r}; " + "A str, Segment or object with __rich_console__ method is required" + ) + + try: + iter_render = iter(render_iterable) + except TypeError: + raise errors.NotRenderableError( + f"object {render_iterable!r} is not renderable" + ) + _Segment = Segment + _options = _options.reset_height() + for render_output in iter_render: + if isinstance(render_output, _Segment): + yield render_output + else: + yield from self.render(render_output, _options) + + def render_lines( + self, + renderable: RenderableType, + options: Optional[ConsoleOptions] = None, + *, + style: Optional[Style] = None, + pad: bool = True, + new_lines: bool = False, + ) -> List[List[Segment]]: + """Render objects in to a list of lines. + + The output of render_lines is useful when further formatting of rendered console text + is required, such as the Panel class which draws a border around any renderable object. + + Args: + renderable (RenderableType): Any object renderable in the console. + options (Optional[ConsoleOptions], optional): Console options, or None to use self.options. Default to ``None``. + style (Style, optional): Optional style to apply to renderables. Defaults to ``None``. + pad (bool, optional): Pad lines shorter than render width. Defaults to ``True``. + new_lines (bool, optional): Include "\n" characters at end of lines. + + Returns: + List[List[Segment]]: A list of lines, where a line is a list of Segment objects. + """ + with self._lock: + render_options = options or self.options + _rendered = self.render(renderable, render_options) + if style: + _rendered = Segment.apply_style(_rendered, style) + + render_height = render_options.height + if render_height is not None: + render_height = max(0, render_height) + + lines = list( + islice( + Segment.split_and_crop_lines( + _rendered, + render_options.max_width, + include_new_lines=new_lines, + pad=pad, + style=style, + ), + None, + render_height, + ) + ) + if render_options.height is not None: + extra_lines = render_options.height - len(lines) + if extra_lines > 0: + pad_line = [ + ( + [ + Segment(" " * render_options.max_width, style), + Segment("\n"), + ] + if new_lines + else [Segment(" " * render_options.max_width, style)] + ) + ] + lines.extend(pad_line * extra_lines) + + return lines + + def render_str( + self, + text: str, + *, + style: Union[str, Style] = "", + justify: Optional[JustifyMethod] = None, + overflow: Optional[OverflowMethod] = None, + emoji: Optional[bool] = None, + markup: Optional[bool] = None, + highlight: Optional[bool] = None, + highlighter: Optional[HighlighterType] = None, + ) -> "Text": + """Convert a string to a Text instance. This is called automatically if + you print or log a string. + + Args: + text (str): Text to render. + style (Union[str, Style], optional): Style to apply to rendered text. + justify (str, optional): Justify method: "default", "left", "center", "full", or "right". Defaults to ``None``. + overflow (str, optional): Overflow method: "crop", "fold", or "ellipsis". Defaults to ``None``. + emoji (Optional[bool], optional): Enable emoji, or ``None`` to use Console default. + markup (Optional[bool], optional): Enable markup, or ``None`` to use Console default. + highlight (Optional[bool], optional): Enable highlighting, or ``None`` to use Console default. + highlighter (HighlighterType, optional): Optional highlighter to apply. + Returns: + ConsoleRenderable: Renderable object. + + """ + emoji_enabled = emoji or (emoji is None and self._emoji) + markup_enabled = markup or (markup is None and self._markup) + highlight_enabled = highlight or (highlight is None and self._highlight) + + if markup_enabled: + rich_text = render_markup( + text, + style=style, + emoji=emoji_enabled, + emoji_variant=self._emoji_variant, + ) + rich_text.justify = justify + rich_text.overflow = overflow + else: + rich_text = Text( + ( + _emoji_replace(text, default_variant=self._emoji_variant) + if emoji_enabled + else text + ), + justify=justify, + overflow=overflow, + style=style, + ) + + _highlighter = (highlighter or self.highlighter) if highlight_enabled else None + if _highlighter is not None: + highlight_text = _highlighter(str(rich_text)) + highlight_text.copy_styles(rich_text) + return highlight_text + + return rich_text + + def get_style( + self, name: Union[str, Style], *, default: Optional[Union[Style, str]] = None + ) -> Style: + """Get a Style instance by its theme name or parse a definition. + + Args: + name (str): The name of a style or a style definition. + + Returns: + Style: A Style object. + + Raises: + MissingStyle: If no style could be parsed from name. + + """ + if isinstance(name, Style): + return name + + try: + style = self._theme_stack.get(name) + if style is None: + style = Style.parse(name) + return style.copy() if style.link else style + except errors.StyleSyntaxError as error: + if default is not None: + return self.get_style(default) + raise errors.MissingStyle( + f"Failed to get style {name!r}; {error}" + ) from None + + def _collect_renderables( + self, + objects: Iterable[Any], + sep: str, + end: str, + *, + justify: Optional[JustifyMethod] = None, + emoji: Optional[bool] = None, + markup: Optional[bool] = None, + highlight: Optional[bool] = None, + ) -> List[ConsoleRenderable]: + """Combine a number of renderables and text into one renderable. + + Args: + objects (Iterable[Any]): Anything that Rich can render. + sep (str): String to write between print data. + end (str): String to write at end of print data. + justify (str, optional): One of "left", "right", "center", or "full". Defaults to ``None``. + emoji (Optional[bool], optional): Enable emoji code, or ``None`` to use console default. + markup (Optional[bool], optional): Enable markup, or ``None`` to use console default. + highlight (Optional[bool], optional): Enable automatic highlighting, or ``None`` to use console default. + + Returns: + List[ConsoleRenderable]: A list of things to render. + """ + renderables: List[ConsoleRenderable] = [] + _append = renderables.append + text: List[Text] = [] + append_text = text.append + + append = _append + if justify in ("left", "center", "right"): + + def align_append(renderable: RenderableType) -> None: + _append(Align(renderable, cast(AlignMethod, justify))) + + append = align_append + + _highlighter: HighlighterType = _null_highlighter + if highlight or (highlight is None and self._highlight): + _highlighter = self.highlighter + + def check_text() -> None: + if text: + sep_text = Text(sep, justify=justify, end=end) + append(sep_text.join(text)) + text.clear() + + for renderable in objects: + renderable = rich_cast(renderable) + if isinstance(renderable, str): + append_text( + self.render_str( + renderable, + emoji=emoji, + markup=markup, + highlight=highlight, + highlighter=_highlighter, + ) + ) + elif isinstance(renderable, Text): + append_text(renderable) + elif isinstance(renderable, ConsoleRenderable): + check_text() + append(renderable) + elif is_expandable(renderable): + check_text() + append(Pretty(renderable, highlighter=_highlighter)) + else: + append_text(_highlighter(str(renderable))) + + check_text() + + if self.style is not None: + style = self.get_style(self.style) + renderables = [Styled(renderable, style) for renderable in renderables] + + return renderables + + def rule( + self, + title: TextType = "", + *, + characters: str = "─", + style: Union[str, Style] = "rule.line", + align: AlignMethod = "center", + ) -> None: + """Draw a line with optional centered title. + + Args: + title (str, optional): Text to render over the rule. Defaults to "". + characters (str, optional): Character(s) to form the line. Defaults to "─". + style (str, optional): Style of line. Defaults to "rule.line". + align (str, optional): How to align the title, one of "left", "center", or "right". Defaults to "center". + """ + from .rule import Rule + + rule = Rule(title=title, characters=characters, style=style, align=align) + self.print(rule) + + def control(self, *control: Control) -> None: + """Insert non-printing control codes. + + Args: + control_codes (str): Control codes, such as those that may move the cursor. + """ + if not self.is_dumb_terminal: + with self: + self._buffer.extend(_control.segment for _control in control) + + def out( + self, + *objects: Any, + sep: str = " ", + end: str = "\n", + style: Optional[Union[str, Style]] = None, + highlight: Optional[bool] = None, + ) -> None: + """Output to the terminal. This is a low-level way of writing to the terminal which unlike + :meth:`~rich.console.Console.print` won't pretty print, wrap text, or apply markup, but will + optionally apply highlighting and a basic style. + + Args: + sep (str, optional): String to write between print data. Defaults to " ". + end (str, optional): String to write at end of print data. Defaults to "\\\\n". + style (Union[str, Style], optional): A style to apply to output. Defaults to None. + highlight (Optional[bool], optional): Enable automatic highlighting, or ``None`` to use + console default. Defaults to ``None``. + """ + raw_output: str = sep.join(str(_object) for _object in objects) + self.print( + raw_output, + style=style, + highlight=highlight, + emoji=False, + markup=False, + no_wrap=True, + overflow="ignore", + crop=False, + end=end, + ) + + def print( + self, + *objects: Any, + sep: str = " ", + end: str = "\n", + style: Optional[Union[str, Style]] = None, + justify: Optional[JustifyMethod] = None, + overflow: Optional[OverflowMethod] = None, + no_wrap: Optional[bool] = None, + emoji: Optional[bool] = None, + markup: Optional[bool] = None, + highlight: Optional[bool] = None, + width: Optional[int] = None, + height: Optional[int] = None, + crop: bool = True, + soft_wrap: Optional[bool] = None, + new_line_start: bool = False, + ) -> None: + """Print to the console. + + Args: + objects (positional args): Objects to log to the terminal. + sep (str, optional): String to write between print data. Defaults to " ". + end (str, optional): String to write at end of print data. Defaults to "\\\\n". + style (Union[str, Style], optional): A style to apply to output. Defaults to None. + justify (str, optional): Justify method: "default", "left", "right", "center", or "full". Defaults to ``None``. + overflow (str, optional): Overflow method: "ignore", "crop", "fold", or "ellipsis". Defaults to None. + no_wrap (Optional[bool], optional): Disable word wrapping. Defaults to None. + emoji (Optional[bool], optional): Enable emoji code, or ``None`` to use console default. Defaults to ``None``. + markup (Optional[bool], optional): Enable markup, or ``None`` to use console default. Defaults to ``None``. + highlight (Optional[bool], optional): Enable automatic highlighting, or ``None`` to use console default. Defaults to ``None``. + width (Optional[int], optional): Width of output, or ``None`` to auto-detect. Defaults to ``None``. + crop (Optional[bool], optional): Crop output to width of terminal. Defaults to True. + soft_wrap (bool, optional): Enable soft wrap mode which disables word wrapping and cropping of text or ``None`` for + Console default. Defaults to ``None``. + new_line_start (bool, False): Insert a new line at the start if the output contains more than one line. Defaults to ``False``. + """ + if not objects: + objects = (NewLine(),) + + if soft_wrap is None: + soft_wrap = self.soft_wrap + if soft_wrap: + if no_wrap is None: + no_wrap = True + if overflow is None: + overflow = "ignore" + crop = False + render_hooks = self._render_hooks[:] + with self: + renderables = self._collect_renderables( + objects, + sep, + end, + justify=justify, + emoji=emoji, + markup=markup, + highlight=highlight, + ) + for hook in render_hooks: + renderables = hook.process_renderables(renderables) + render_options = self.options.update( + justify=justify, + overflow=overflow, + width=min(width, self.width) if width is not None else NO_CHANGE, + height=height, + no_wrap=no_wrap, + markup=markup, + highlight=highlight, + ) + + new_segments: List[Segment] = [] + extend = new_segments.extend + render = self.render + if style is None: + for renderable in renderables: + extend(render(renderable, render_options)) + else: + render_style = self.get_style(style) + new_line = Segment.line() + for renderable in renderables: + for line, add_new_line in Segment.split_lines_terminator( + render(renderable, render_options) + ): + extend(Segment.apply_style(line, render_style)) + if add_new_line: + new_segments.append(new_line) + + if new_line_start: + if ( + len("".join(segment.text for segment in new_segments).splitlines()) + > 1 + ): + new_segments.insert(0, Segment.line()) + if crop: + buffer_extend = self._buffer.extend + for line in Segment.split_and_crop_lines( + new_segments, self.width, pad=False + ): + buffer_extend(line) + else: + self._buffer.extend(new_segments) + + def print_json( + self, + json: Optional[str] = None, + *, + data: Any = None, + indent: Union[None, int, str] = 2, + highlight: bool = True, + skip_keys: bool = False, + ensure_ascii: bool = False, + check_circular: bool = True, + allow_nan: bool = True, + default: Optional[Callable[[Any], Any]] = None, + sort_keys: bool = False, + ) -> None: + """Pretty prints JSON. Output will be valid JSON. + + Args: + json (Optional[str]): A string containing JSON. + data (Any): If json is not supplied, then encode this data. + indent (Union[None, int, str], optional): Number of spaces to indent. Defaults to 2. + highlight (bool, optional): Enable highlighting of output: Defaults to True. + skip_keys (bool, optional): Skip keys not of a basic type. Defaults to False. + ensure_ascii (bool, optional): Escape all non-ascii characters. Defaults to False. + check_circular (bool, optional): Check for circular references. Defaults to True. + allow_nan (bool, optional): Allow NaN and Infinity values. Defaults to True. + default (Callable, optional): A callable that converts values that can not be encoded + in to something that can be JSON encoded. Defaults to None. + sort_keys (bool, optional): Sort dictionary keys. Defaults to False. + """ + from rich.json import JSON + + if json is None: + json_renderable = JSON.from_data( + data, + indent=indent, + highlight=highlight, + skip_keys=skip_keys, + ensure_ascii=ensure_ascii, + check_circular=check_circular, + allow_nan=allow_nan, + default=default, + sort_keys=sort_keys, + ) + else: + if not isinstance(json, str): + raise TypeError( + f"json must be str. Did you mean print_json(data={json!r}) ?" + ) + json_renderable = JSON( + json, + indent=indent, + highlight=highlight, + skip_keys=skip_keys, + ensure_ascii=ensure_ascii, + check_circular=check_circular, + allow_nan=allow_nan, + default=default, + sort_keys=sort_keys, + ) + self.print(json_renderable, soft_wrap=True) + + def update_screen( + self, + renderable: RenderableType, + *, + region: Optional[Region] = None, + options: Optional[ConsoleOptions] = None, + ) -> None: + """Update the screen at a given offset. + + Args: + renderable (RenderableType): A Rich renderable. + region (Region, optional): Region of screen to update, or None for entire screen. Defaults to None. + x (int, optional): x offset. Defaults to 0. + y (int, optional): y offset. Defaults to 0. + + Raises: + errors.NoAltScreen: If the Console isn't in alt screen mode. + + """ + if not self.is_alt_screen: + raise errors.NoAltScreen("Alt screen must be enabled to call update_screen") + render_options = options or self.options + if region is None: + x = y = 0 + render_options = render_options.update_dimensions( + render_options.max_width, render_options.height or self.height + ) + else: + x, y, width, height = region + render_options = render_options.update_dimensions(width, height) + + lines = self.render_lines(renderable, options=render_options) + self.update_screen_lines(lines, x, y) + + def update_screen_lines( + self, lines: List[List[Segment]], x: int = 0, y: int = 0 + ) -> None: + """Update lines of the screen at a given offset. + + Args: + lines (List[List[Segment]]): Rendered lines (as produced by :meth:`~rich.Console.render_lines`). + x (int, optional): x offset (column no). Defaults to 0. + y (int, optional): y offset (column no). Defaults to 0. + + Raises: + errors.NoAltScreen: If the Console isn't in alt screen mode. + """ + if not self.is_alt_screen: + raise errors.NoAltScreen("Alt screen must be enabled to call update_screen") + screen_update = ScreenUpdate(lines, x, y) + segments = self.render(screen_update) + self._buffer.extend(segments) + self._check_buffer() + + def print_exception( + self, + *, + width: Optional[int] = 100, + extra_lines: int = 3, + theme: Optional[str] = None, + word_wrap: bool = False, + show_locals: bool = False, + suppress: Iterable[Union[str, ModuleType]] = (), + max_frames: int = 100, + ) -> None: + """Prints a rich render of the last exception and traceback. + + Args: + width (Optional[int], optional): Number of characters used to render code. Defaults to 100. + extra_lines (int, optional): Additional lines of code to render. Defaults to 3. + theme (str, optional): Override pygments theme used in traceback + word_wrap (bool, optional): Enable word wrapping of long lines. Defaults to False. + show_locals (bool, optional): Enable display of local variables. Defaults to False. + suppress (Iterable[Union[str, ModuleType]]): Optional sequence of modules or paths to exclude from traceback. + max_frames (int): Maximum number of frames to show in a traceback, 0 for no maximum. Defaults to 100. + """ + from .traceback import Traceback + + traceback = Traceback( + width=width, + extra_lines=extra_lines, + theme=theme, + word_wrap=word_wrap, + show_locals=show_locals, + suppress=suppress, + max_frames=max_frames, + ) + self.print(traceback) + + @staticmethod + def _caller_frame_info( + offset: int, + currentframe: Callable[[], Optional[FrameType]] = inspect.currentframe, + ) -> Tuple[str, int, Dict[str, Any]]: + """Get caller frame information. + + Args: + offset (int): the caller offset within the current frame stack. + currentframe (Callable[[], Optional[FrameType]], optional): the callable to use to + retrieve the current frame. Defaults to ``inspect.currentframe``. + + Returns: + Tuple[str, int, Dict[str, Any]]: A tuple containing the filename, the line number and + the dictionary of local variables associated with the caller frame. + + Raises: + RuntimeError: If the stack offset is invalid. + """ + # Ignore the frame of this local helper + offset += 1 + + frame = currentframe() + if frame is not None: + # Use the faster currentframe where implemented + while offset and frame is not None: + frame = frame.f_back + offset -= 1 + assert frame is not None + return frame.f_code.co_filename, frame.f_lineno, frame.f_locals + else: + # Fallback to the slower stack + frame_info = inspect.stack()[offset] + return frame_info.filename, frame_info.lineno, frame_info.frame.f_locals + + def log( + self, + *objects: Any, + sep: str = " ", + end: str = "\n", + style: Optional[Union[str, Style]] = None, + justify: Optional[JustifyMethod] = None, + emoji: Optional[bool] = None, + markup: Optional[bool] = None, + highlight: Optional[bool] = None, + log_locals: bool = False, + _stack_offset: int = 1, + ) -> None: + """Log rich content to the terminal. + + Args: + objects (positional args): Objects to log to the terminal. + sep (str, optional): String to write between print data. Defaults to " ". + end (str, optional): String to write at end of print data. Defaults to "\\\\n". + style (Union[str, Style], optional): A style to apply to output. Defaults to None. + justify (str, optional): One of "left", "right", "center", or "full". Defaults to ``None``. + emoji (Optional[bool], optional): Enable emoji code, or ``None`` to use console default. Defaults to None. + markup (Optional[bool], optional): Enable markup, or ``None`` to use console default. Defaults to None. + highlight (Optional[bool], optional): Enable automatic highlighting, or ``None`` to use console default. Defaults to None. + log_locals (bool, optional): Boolean to enable logging of locals where ``log()`` + was called. Defaults to False. + _stack_offset (int, optional): Offset of caller from end of call stack. Defaults to 1. + """ + if not objects: + objects = (NewLine(),) + + render_hooks = self._render_hooks[:] + + with self: + renderables = self._collect_renderables( + objects, + sep, + end, + justify=justify, + emoji=emoji, + markup=markup, + highlight=highlight, + ) + if style is not None: + renderables = [Styled(renderable, style) for renderable in renderables] + + filename, line_no, locals = self._caller_frame_info(_stack_offset) + link_path = None if filename.startswith("<") else os.path.abspath(filename) + path = filename.rpartition(os.sep)[-1] + if log_locals: + locals_map = { + key: value + for key, value in locals.items() + if not key.startswith("__") + } + renderables.append(render_scope(locals_map, title="[i]locals")) + + renderables = [ + self._log_render( + self, + renderables, + log_time=self.get_datetime(), + path=path, + line_no=line_no, + link_path=link_path, + ) + ] + for hook in render_hooks: + renderables = hook.process_renderables(renderables) + new_segments: List[Segment] = [] + extend = new_segments.extend + render = self.render + render_options = self.options + for renderable in renderables: + extend(render(renderable, render_options)) + buffer_extend = self._buffer.extend + for line in Segment.split_and_crop_lines( + new_segments, self.width, pad=False + ): + buffer_extend(line) + + def on_broken_pipe(self) -> None: + """This function is called when a `BrokenPipeError` is raised. + + This can occur when piping Textual output in Linux and macOS. + The default implementation is to exit the app, but you could implement + this method in a subclass to change the behavior. + + See https://docs.python.org/3/library/signal.html#note-on-sigpipe for details. + """ + self.quiet = True + devnull = os.open(os.devnull, os.O_WRONLY) + os.dup2(devnull, sys.stdout.fileno()) + raise SystemExit(1) + + def _check_buffer(self) -> None: + """Check if the buffer may be rendered. Render it if it can (e.g. Console.quiet is False) + Rendering is supported on Windows, Unix and Jupyter environments. For + legacy Windows consoles, the win32 API is called directly. + This method will also record what it renders if recording is enabled via Console.record. + """ + if self.quiet: + del self._buffer[:] + return + + try: + self._write_buffer() + except BrokenPipeError: + self.on_broken_pipe() + + def _write_buffer(self) -> None: + """Write the buffer to the output file.""" + + with self._lock: + if self.record and not self._buffer_index: + with self._record_buffer_lock: + self._record_buffer.extend(self._buffer[:]) + + if self._buffer_index == 0: + if self.is_jupyter: # pragma: no cover + from .jupyter import display + + display(self._buffer, self._render_buffer(self._buffer[:])) + del self._buffer[:] + else: + if WINDOWS: + use_legacy_windows_render = False + if self.legacy_windows: + fileno = get_fileno(self.file) + if fileno is not None: + use_legacy_windows_render = ( + fileno in _STD_STREAMS_OUTPUT + ) + + if use_legacy_windows_render: + from rich._win32_console import LegacyWindowsTerm + from rich._windows_renderer import legacy_windows_render + + buffer = self._buffer[:] + if self.no_color and self._color_system: + buffer = list(Segment.remove_color(buffer)) + + legacy_windows_render(buffer, LegacyWindowsTerm(self.file)) + else: + # Either a non-std stream on legacy Windows, or modern Windows. + text = self._render_buffer(self._buffer[:]) + # https://bugs.python.org/issue37871 + # https://github.com/python/cpython/issues/82052 + # We need to avoid writing more than 32Kb in a single write, due to the above bug + write = self.file.write + # Worse case scenario, every character is 4 bytes of utf-8 + MAX_WRITE = 32 * 1024 // 4 + try: + if len(text) <= MAX_WRITE: + write(text) + else: + batch: List[str] = [] + batch_append = batch.append + size = 0 + for line in text.splitlines(True): + if size + len(line) > MAX_WRITE and batch: + write("".join(batch)) + batch.clear() + size = 0 + batch_append(line) + size += len(line) + if batch: + write("".join(batch)) + batch.clear() + except UnicodeEncodeError as error: + error.reason = f"{error.reason}\n*** You may need to add PYTHONIOENCODING=utf-8 to your environment ***" + raise + else: + text = self._render_buffer(self._buffer[:]) + try: + self.file.write(text) + except UnicodeEncodeError as error: + error.reason = f"{error.reason}\n*** You may need to add PYTHONIOENCODING=utf-8 to your environment ***" + raise + + self.file.flush() + del self._buffer[:] + + def _render_buffer(self, buffer: Iterable[Segment]) -> str: + """Render buffered output, and clear buffer.""" + output: List[str] = [] + append = output.append + color_system = self._color_system + legacy_windows = self.legacy_windows + not_terminal = not self.is_terminal + if self.no_color and color_system: + buffer = Segment.remove_color(buffer) + for text, style, control in buffer: + if style: + append( + style.render( + text, + color_system=color_system, + legacy_windows=legacy_windows, + ) + ) + elif not (not_terminal and control): + append(text) + + rendered = "".join(output) + return rendered + + def input( + self, + prompt: TextType = "", + *, + markup: bool = True, + emoji: bool = True, + password: bool = False, + stream: Optional[TextIO] = None, + ) -> str: + """Displays a prompt and waits for input from the user. The prompt may contain color / style. + + It works in the same way as Python's builtin :func:`input` function and provides elaborate line editing and history features if Python's builtin :mod:`readline` module is previously loaded. + + Args: + prompt (Union[str, Text]): Text to render in the prompt. + markup (bool, optional): Enable console markup (requires a str prompt). Defaults to True. + emoji (bool, optional): Enable emoji (requires a str prompt). Defaults to True. + password: (bool, optional): Hide typed text. Defaults to False. + stream: (TextIO, optional): Optional file to read input from (rather than stdin). Defaults to None. + + Returns: + str: Text read from stdin. + """ + if prompt: + self.print(prompt, markup=markup, emoji=emoji, end="") + if password: + result = getpass("", stream=stream) + else: + if stream: + result = stream.readline() + else: + result = input() + return result + + def export_text(self, *, clear: bool = True, styles: bool = False) -> str: + """Generate text from console contents (requires record=True argument in constructor). + + Args: + clear (bool, optional): Clear record buffer after exporting. Defaults to ``True``. + styles (bool, optional): If ``True``, ansi escape codes will be included. ``False`` for plain text. + Defaults to ``False``. + + Returns: + str: String containing console contents. + + """ + assert ( + self.record + ), "To export console contents set record=True in the constructor or instance" + + with self._record_buffer_lock: + if styles: + text = "".join( + (style.render(text) if style else text) + for text, style, _ in self._record_buffer + ) + else: + text = "".join( + segment.text + for segment in self._record_buffer + if not segment.control + ) + if clear: + del self._record_buffer[:] + return text + + def save_text(self, path: str, *, clear: bool = True, styles: bool = False) -> None: + """Generate text from console and save to a given location (requires record=True argument in constructor). + + Args: + path (str): Path to write text files. + clear (bool, optional): Clear record buffer after exporting. Defaults to ``True``. + styles (bool, optional): If ``True``, ansi style codes will be included. ``False`` for plain text. + Defaults to ``False``. + + """ + text = self.export_text(clear=clear, styles=styles) + with open(path, "w", encoding="utf-8") as write_file: + write_file.write(text) + + def export_html( + self, + *, + theme: Optional[TerminalTheme] = None, + clear: bool = True, + code_format: Optional[str] = None, + inline_styles: bool = False, + ) -> str: + """Generate HTML from console contents (requires record=True argument in constructor). + + Args: + theme (TerminalTheme, optional): TerminalTheme object containing console colors. + clear (bool, optional): Clear record buffer after exporting. Defaults to ``True``. + code_format (str, optional): Format string to render HTML. In addition to '{foreground}', + '{background}', and '{code}', should contain '{stylesheet}' if inline_styles is ``False``. + inline_styles (bool, optional): If ``True`` styles will be inlined in to spans, which makes files + larger but easier to cut and paste markup. If ``False``, styles will be embedded in a style tag. + Defaults to False. + + Returns: + str: String containing console contents as HTML. + """ + assert ( + self.record + ), "To export console contents set record=True in the constructor or instance" + fragments: List[str] = [] + append = fragments.append + _theme = theme or DEFAULT_TERMINAL_THEME + stylesheet = "" + + render_code_format = CONSOLE_HTML_FORMAT if code_format is None else code_format + + with self._record_buffer_lock: + if inline_styles: + for text, style, _ in Segment.filter_control( + Segment.simplify(self._record_buffer) + ): + text = escape(text) + if style: + rule = style.get_html_style(_theme) + if style.link: + text = f'{text}' + text = f'{text}' if rule else text + append(text) + else: + styles: Dict[str, int] = {} + for text, style, _ in Segment.filter_control( + Segment.simplify(self._record_buffer) + ): + text = escape(text) + if style: + rule = style.get_html_style(_theme) + style_number = styles.setdefault(rule, len(styles) + 1) + if style.link: + text = f'{text}' + else: + text = f'{text}' + append(text) + stylesheet_rules: List[str] = [] + stylesheet_append = stylesheet_rules.append + for style_rule, style_number in styles.items(): + if style_rule: + stylesheet_append(f".r{style_number} {{{style_rule}}}") + stylesheet = "\n".join(stylesheet_rules) + + rendered_code = render_code_format.format( + code="".join(fragments), + stylesheet=stylesheet, + foreground=_theme.foreground_color.hex, + background=_theme.background_color.hex, + ) + if clear: + del self._record_buffer[:] + return rendered_code + + def save_html( + self, + path: str, + *, + theme: Optional[TerminalTheme] = None, + clear: bool = True, + code_format: str = CONSOLE_HTML_FORMAT, + inline_styles: bool = False, + ) -> None: + """Generate HTML from console contents and write to a file (requires record=True argument in constructor). + + Args: + path (str): Path to write html file. + theme (TerminalTheme, optional): TerminalTheme object containing console colors. + clear (bool, optional): Clear record buffer after exporting. Defaults to ``True``. + code_format (str, optional): Format string to render HTML. In addition to '{foreground}', + '{background}', and '{code}', should contain '{stylesheet}' if inline_styles is ``False``. + inline_styles (bool, optional): If ``True`` styles will be inlined in to spans, which makes files + larger but easier to cut and paste markup. If ``False``, styles will be embedded in a style tag. + Defaults to False. + + """ + html = self.export_html( + theme=theme, + clear=clear, + code_format=code_format, + inline_styles=inline_styles, + ) + with open(path, "w", encoding="utf-8") as write_file: + write_file.write(html) + + def export_svg( + self, + *, + title: str = "Rich", + theme: Optional[TerminalTheme] = None, + clear: bool = True, + code_format: str = CONSOLE_SVG_FORMAT, + font_aspect_ratio: float = 0.61, + unique_id: Optional[str] = None, + ) -> str: + """ + Generate an SVG from the console contents (requires record=True in Console constructor). + + Args: + title (str, optional): The title of the tab in the output image + theme (TerminalTheme, optional): The ``TerminalTheme`` object to use to style the terminal + clear (bool, optional): Clear record buffer after exporting. Defaults to ``True`` + code_format (str, optional): Format string used to generate the SVG. Rich will inject a number of variables + into the string in order to form the final SVG output. The default template used and the variables + injected by Rich can be found by inspecting the ``console.CONSOLE_SVG_FORMAT`` variable. + font_aspect_ratio (float, optional): The width to height ratio of the font used in the ``code_format`` + string. Defaults to 0.61, which is the width to height ratio of Fira Code (the default font). + If you aren't specifying a different font inside ``code_format``, you probably don't need this. + unique_id (str, optional): unique id that is used as the prefix for various elements (CSS styles, node + ids). If not set, this defaults to a computed value based on the recorded content. + """ + + from rich.cells import cell_len + + style_cache: Dict[Style, str] = {} + + def get_svg_style(style: Style) -> str: + """Convert a Style to CSS rules for SVG.""" + if style in style_cache: + return style_cache[style] + css_rules = [] + color = ( + _theme.foreground_color + if (style.color is None or style.color.is_default) + else style.color.get_truecolor(_theme) + ) + bgcolor = ( + _theme.background_color + if (style.bgcolor is None or style.bgcolor.is_default) + else style.bgcolor.get_truecolor(_theme) + ) + if style.reverse: + color, bgcolor = bgcolor, color + if style.dim: + color = blend_rgb(color, bgcolor, 0.4) + css_rules.append(f"fill: {color.hex}") + if style.bold: + css_rules.append("font-weight: bold") + if style.italic: + css_rules.append("font-style: italic;") + if style.underline: + css_rules.append("text-decoration: underline;") + if style.strike: + css_rules.append("text-decoration: line-through;") + + css = ";".join(css_rules) + style_cache[style] = css + return css + + _theme = theme or SVG_EXPORT_THEME + + width = self.width + char_height = 20 + char_width = char_height * font_aspect_ratio + line_height = char_height * 1.22 + + margin_top = 1 + margin_right = 1 + margin_bottom = 1 + margin_left = 1 + + padding_top = 40 + padding_right = 8 + padding_bottom = 8 + padding_left = 8 + + padding_width = padding_left + padding_right + padding_height = padding_top + padding_bottom + margin_width = margin_left + margin_right + margin_height = margin_top + margin_bottom + + text_backgrounds: List[str] = [] + text_group: List[str] = [] + classes: Dict[str, int] = {} + style_no = 1 + + def escape_text(text: str) -> str: + """HTML escape text and replace spaces with nbsp.""" + return escape(text).replace(" ", " ") + + def make_tag( + name: str, content: Optional[str] = None, **attribs: object + ) -> str: + """Make a tag from name, content, and attributes.""" + + def stringify(value: object) -> str: + if isinstance(value, (float)): + return format(value, "g") + return str(value) + + tag_attribs = " ".join( + f'{k.lstrip("_").replace("_", "-")}="{stringify(v)}"' + for k, v in attribs.items() + ) + return ( + f"<{name} {tag_attribs}>{content}" + if content + else f"<{name} {tag_attribs}/>" + ) + + with self._record_buffer_lock: + segments = list(Segment.filter_control(self._record_buffer)) + if clear: + self._record_buffer.clear() + + if unique_id is None: + unique_id = "terminal-" + str( + zlib.adler32( + ("".join(repr(segment) for segment in segments)).encode( + "utf-8", + "ignore", + ) + + title.encode("utf-8", "ignore") + ) + ) + y = 0 + for y, line in enumerate(Segment.split_and_crop_lines(segments, length=width)): + x = 0 + for text, style, _control in line: + style = style or Style() + rules = get_svg_style(style) + if rules not in classes: + classes[rules] = style_no + style_no += 1 + class_name = f"r{classes[rules]}" + + if style.reverse: + has_background = True + background = ( + _theme.foreground_color.hex + if style.color is None + else style.color.get_truecolor(_theme).hex + ) + else: + bgcolor = style.bgcolor + has_background = bgcolor is not None and not bgcolor.is_default + background = ( + _theme.background_color.hex + if style.bgcolor is None + else style.bgcolor.get_truecolor(_theme).hex + ) + + text_length = cell_len(text) + if has_background: + text_backgrounds.append( + make_tag( + "rect", + fill=background, + x=x * char_width, + y=y * line_height + 1.5, + width=char_width * text_length, + height=line_height + 0.25, + shape_rendering="crispEdges", + ) + ) + + if text != " " * len(text): + text_group.append( + make_tag( + "text", + escape_text(text), + _class=f"{unique_id}-{class_name}", + x=x * char_width, + y=y * line_height + char_height, + textLength=char_width * len(text), + clip_path=f"url(#{unique_id}-line-{y})", + ) + ) + x += cell_len(text) + + line_offsets = [line_no * line_height + 1.5 for line_no in range(y)] + lines = "\n".join( + f""" + {make_tag("rect", x=0, y=offset, width=char_width * width, height=line_height + 0.25)} + """ + for line_no, offset in enumerate(line_offsets) + ) + + styles = "\n".join( + f".{unique_id}-r{rule_no} {{ {css} }}" for css, rule_no in classes.items() + ) + backgrounds = "".join(text_backgrounds) + matrix = "".join(text_group) + + terminal_width = ceil(width * char_width + padding_width) + terminal_height = (y + 1) * line_height + padding_height + chrome = make_tag( + "rect", + fill=_theme.background_color.hex, + stroke="rgba(255,255,255,0.35)", + stroke_width="1", + x=margin_left, + y=margin_top, + width=terminal_width, + height=terminal_height, + rx=8, + ) + + title_color = _theme.foreground_color.hex + if title: + chrome += make_tag( + "text", + escape_text(title), + _class=f"{unique_id}-title", + fill=title_color, + text_anchor="middle", + x=terminal_width // 2, + y=margin_top + char_height + 6, + ) + chrome += f""" + + + + + + """ + + svg = code_format.format( + unique_id=unique_id, + char_width=char_width, + char_height=char_height, + line_height=line_height, + terminal_width=char_width * width - 1, + terminal_height=(y + 1) * line_height - 1, + width=terminal_width + margin_width, + height=terminal_height + margin_height, + terminal_x=margin_left + padding_left, + terminal_y=margin_top + padding_top, + styles=styles, + chrome=chrome, + backgrounds=backgrounds, + matrix=matrix, + lines=lines, + ) + return svg + + def save_svg( + self, + path: str, + *, + title: str = "Rich", + theme: Optional[TerminalTheme] = None, + clear: bool = True, + code_format: str = CONSOLE_SVG_FORMAT, + font_aspect_ratio: float = 0.61, + unique_id: Optional[str] = None, + ) -> None: + """Generate an SVG file from the console contents (requires record=True in Console constructor). + + Args: + path (str): The path to write the SVG to. + title (str, optional): The title of the tab in the output image + theme (TerminalTheme, optional): The ``TerminalTheme`` object to use to style the terminal + clear (bool, optional): Clear record buffer after exporting. Defaults to ``True`` + code_format (str, optional): Format string used to generate the SVG. Rich will inject a number of variables + into the string in order to form the final SVG output. The default template used and the variables + injected by Rich can be found by inspecting the ``console.CONSOLE_SVG_FORMAT`` variable. + font_aspect_ratio (float, optional): The width to height ratio of the font used in the ``code_format`` + string. Defaults to 0.61, which is the width to height ratio of Fira Code (the default font). + If you aren't specifying a different font inside ``code_format``, you probably don't need this. + unique_id (str, optional): unique id that is used as the prefix for various elements (CSS styles, node + ids). If not set, this defaults to a computed value based on the recorded content. + """ + svg = self.export_svg( + title=title, + theme=theme, + clear=clear, + code_format=code_format, + font_aspect_ratio=font_aspect_ratio, + unique_id=unique_id, + ) + with open(path, "w", encoding="utf-8") as write_file: + write_file.write(svg) + + +def _svg_hash(svg_main_code: str) -> str: + """Returns a unique hash for the given SVG main code. + + Args: + svg_main_code (str): The content we're going to inject in the SVG envelope. + + Returns: + str: a hash of the given content + """ + return str(zlib.adler32(svg_main_code.encode())) + + +if __name__ == "__main__": # pragma: no cover + console = Console(record=True) + + console.log( + "JSONRPC [i]request[/i]", + 5, + 1.3, + True, + False, + None, + { + "jsonrpc": "2.0", + "method": "subtract", + "params": {"minuend": 42, "subtrahend": 23}, + "id": 3, + }, + ) + + console.log("Hello, World!", "{'a': 1}", repr(console)) + + console.print( + { + "name": None, + "empty": [], + "quiz": { + "sport": { + "answered": True, + "q1": { + "question": "Which one is correct team name in NBA?", + "options": [ + "New York Bulls", + "Los Angeles Kings", + "Golden State Warriors", + "Huston Rocket", + ], + "answer": "Huston Rocket", + }, + }, + "maths": { + "answered": False, + "q1": { + "question": "5 + 7 = ?", + "options": [10, 11, 12, 13], + "answer": 12, + }, + "q2": { + "question": "12 - 8 = ?", + "options": [1, 2, 3, 4], + "answer": 4, + }, + }, + }, + } + ) diff --git a/rich/live_render.py b/rich/live_render.py new file mode 100644 index 0000000000000000000000000000000000000000..e7ec970a7812919e192d0e8c43fe625ffc30af6e --- /dev/null +++ b/rich/live_render.py @@ -0,0 +1,116 @@ +from typing import Literal, Optional, Tuple + +from ._loop import loop_last +from .console import Console, ConsoleOptions, RenderableType, RenderResult +from .control import Control +from .segment import ControlType, Segment +from .style import StyleType +from .text import Text + +VerticalOverflowMethod = Literal["crop", "ellipsis", "visible"] + + +class LiveRender: + """Creates a renderable that may be updated. + + Args: + renderable (RenderableType): Any renderable object. + style (StyleType, optional): An optional style to apply to the renderable. Defaults to "". + """ + + def __init__( + self, + renderable: RenderableType, + style: StyleType = "", + vertical_overflow: VerticalOverflowMethod = "ellipsis", + ) -> None: + self.renderable = renderable + self.style = style + self.vertical_overflow = vertical_overflow + self._shape: Optional[Tuple[int, int]] = None + + @property + def last_render_height(self) -> int: + """The number of lines in the last render (may be 0 if nothing was rendered). + + Returns: + Height in lines + """ + if self._shape is None: + return 0 + return self._shape[1] + + def set_renderable(self, renderable: RenderableType) -> None: + """Set a new renderable. + + Args: + renderable (RenderableType): Any renderable object, including str. + """ + self.renderable = renderable + + def position_cursor(self) -> Control: + """Get control codes to move cursor to beginning of live render. + + Returns: + Control: A control instance that may be printed. + """ + if self._shape is not None: + _, height = self._shape + return Control( + ControlType.CARRIAGE_RETURN, + (ControlType.ERASE_IN_LINE, 2), + *( + ( + (ControlType.CURSOR_UP, 1), + (ControlType.ERASE_IN_LINE, 2), + ) + * (height - 1) + ) + ) + return Control() + + def restore_cursor(self) -> Control: + """Get control codes to clear the render and restore the cursor to its previous position. + + Returns: + Control: A Control instance that may be printed. + """ + if self._shape is not None: + _, height = self._shape + return Control( + ControlType.CARRIAGE_RETURN, + *((ControlType.CURSOR_UP, 1), (ControlType.ERASE_IN_LINE, 2)) * height + ) + return Control() + + def __rich_console__( + self, console: Console, options: ConsoleOptions + ) -> RenderResult: + renderable = self.renderable + style = console.get_style(self.style) + lines = console.render_lines(renderable, options, style=style, pad=False) + shape = Segment.get_shape(lines) + + _, height = shape + if height > options.size.height: + if self.vertical_overflow == "crop": + lines = lines[: options.size.height] + shape = Segment.get_shape(lines) + elif self.vertical_overflow == "ellipsis": + lines = lines[: (options.size.height - 1)] + overflow_text = Text( + "...", + overflow="crop", + justify="center", + end="", + style="live.ellipsis", + ) + lines.append(list(console.render(overflow_text))) + shape = Segment.get_shape(lines) + self._shape = shape + + new_line = Segment.line() + for last, line in loop_last(lines): + yield from line + if not last: + yield new_line diff --git a/rich/logging.py b/rich/logging.py new file mode 100644 index 0000000000000000000000000000000000000000..c3e7a5f670ec907eab694a9b0a7bf01e9861780a --- /dev/null +++ b/rich/logging.py @@ -0,0 +1,297 @@ +import logging +from datetime import datetime +from logging import Handler, LogRecord +from pathlib import Path +from types import ModuleType +from typing import ClassVar, Iterable, List, Optional, Type, Union + +from rich._null_file import NullFile + +from . import get_console +from ._log_render import FormatTimeCallable, LogRender +from .console import Console, ConsoleRenderable +from .highlighter import Highlighter, ReprHighlighter +from .text import Text +from .traceback import Traceback + + +class RichHandler(Handler): + """A logging handler that renders output with Rich. The time / level / message and file are displayed in columns. + The level is color coded, and the message is syntax highlighted. + + Note: + Be careful when enabling console markup in log messages if you have configured logging for libraries not + under your control. If a dependency writes messages containing square brackets, it may not produce the intended output. + + Args: + level (Union[int, str], optional): Log level. Defaults to logging.NOTSET. + console (:class:`~rich.console.Console`, optional): Optional console instance to write logs. + Default will use a global console instance writing to stdout. + show_time (bool, optional): Show a column for the time. Defaults to True. + omit_repeated_times (bool, optional): Omit repetition of the same time. Defaults to True. + show_level (bool, optional): Show a column for the level. Defaults to True. + show_path (bool, optional): Show the path to the original log call. Defaults to True. + enable_link_path (bool, optional): Enable terminal link of path column to file. Defaults to True. + highlighter (Highlighter, optional): Highlighter to style log messages, or None to use ReprHighlighter. Defaults to None. + markup (bool, optional): Enable console markup in log messages. Defaults to False. + rich_tracebacks (bool, optional): Enable rich tracebacks with syntax highlighting and formatting. Defaults to False. + tracebacks_width (Optional[int], optional): Number of characters used to render tracebacks, or None for full width. Defaults to None. + tracebacks_code_width (int, optional): Number of code characters used to render tracebacks, or None for full width. Defaults to 88. + tracebacks_extra_lines (int, optional): Additional lines of code to render tracebacks, or None for full width. Defaults to None. + tracebacks_theme (str, optional): Override pygments theme used in traceback. + tracebacks_word_wrap (bool, optional): Enable word wrapping of long tracebacks lines. Defaults to True. + tracebacks_show_locals (bool, optional): Enable display of locals in tracebacks. Defaults to False. + tracebacks_suppress (Sequence[Union[str, ModuleType]]): Optional sequence of modules or paths to exclude from traceback. + tracebacks_max_frames (int, optional): Optional maximum number of frames returned by traceback. + locals_max_length (int, optional): Maximum length of containers before abbreviating, or None for no abbreviation. + Defaults to 10. + locals_max_string (int, optional): Maximum length of string before truncating, or None to disable. Defaults to 80. + log_time_format (Union[str, TimeFormatterCallable], optional): If ``log_time`` is enabled, either string for strftime or callable that formats the time. Defaults to "[%x %X] ". + keywords (List[str], optional): List of words to highlight instead of ``RichHandler.KEYWORDS``. + """ + + KEYWORDS: ClassVar[Optional[List[str]]] = [ + "GET", + "POST", + "HEAD", + "PUT", + "DELETE", + "OPTIONS", + "TRACE", + "PATCH", + ] + HIGHLIGHTER_CLASS: ClassVar[Type[Highlighter]] = ReprHighlighter + + def __init__( + self, + level: Union[int, str] = logging.NOTSET, + console: Optional[Console] = None, + *, + show_time: bool = True, + omit_repeated_times: bool = True, + show_level: bool = True, + show_path: bool = True, + enable_link_path: bool = True, + highlighter: Optional[Highlighter] = None, + markup: bool = False, + rich_tracebacks: bool = False, + tracebacks_width: Optional[int] = None, + tracebacks_code_width: Optional[int] = 88, + tracebacks_extra_lines: int = 3, + tracebacks_theme: Optional[str] = None, + tracebacks_word_wrap: bool = True, + tracebacks_show_locals: bool = False, + tracebacks_suppress: Iterable[Union[str, ModuleType]] = (), + tracebacks_max_frames: int = 100, + locals_max_length: int = 10, + locals_max_string: int = 80, + log_time_format: Union[str, FormatTimeCallable] = "[%x %X]", + keywords: Optional[List[str]] = None, + ) -> None: + super().__init__(level=level) + self.console = console or get_console() + self.highlighter = highlighter or self.HIGHLIGHTER_CLASS() + self._log_render = LogRender( + show_time=show_time, + show_level=show_level, + show_path=show_path, + time_format=log_time_format, + omit_repeated_times=omit_repeated_times, + level_width=None, + ) + self.enable_link_path = enable_link_path + self.markup = markup + self.rich_tracebacks = rich_tracebacks + self.tracebacks_width = tracebacks_width + self.tracebacks_extra_lines = tracebacks_extra_lines + self.tracebacks_theme = tracebacks_theme + self.tracebacks_word_wrap = tracebacks_word_wrap + self.tracebacks_show_locals = tracebacks_show_locals + self.tracebacks_suppress = tracebacks_suppress + self.tracebacks_max_frames = tracebacks_max_frames + self.tracebacks_code_width = tracebacks_code_width + self.locals_max_length = locals_max_length + self.locals_max_string = locals_max_string + self.keywords = keywords + + def get_level_text(self, record: LogRecord) -> Text: + """Get the level name from the record. + + Args: + record (LogRecord): LogRecord instance. + + Returns: + Text: A tuple of the style and level name. + """ + level_name = record.levelname + level_text = Text.styled( + level_name.ljust(8), f"logging.level.{level_name.lower()}" + ) + return level_text + + def emit(self, record: LogRecord) -> None: + """Invoked by logging.""" + message = self.format(record) + traceback = None + if ( + self.rich_tracebacks + and record.exc_info + and record.exc_info != (None, None, None) + ): + exc_type, exc_value, exc_traceback = record.exc_info + assert exc_type is not None + assert exc_value is not None + traceback = Traceback.from_exception( + exc_type, + exc_value, + exc_traceback, + width=self.tracebacks_width, + code_width=self.tracebacks_code_width, + extra_lines=self.tracebacks_extra_lines, + theme=self.tracebacks_theme, + word_wrap=self.tracebacks_word_wrap, + show_locals=self.tracebacks_show_locals, + locals_max_length=self.locals_max_length, + locals_max_string=self.locals_max_string, + suppress=self.tracebacks_suppress, + max_frames=self.tracebacks_max_frames, + ) + message = record.getMessage() + if self.formatter: + record.message = record.getMessage() + formatter = self.formatter + if hasattr(formatter, "usesTime") and formatter.usesTime(): + record.asctime = formatter.formatTime(record, formatter.datefmt) + message = formatter.formatMessage(record) + + message_renderable = self.render_message(record, message) + log_renderable = self.render( + record=record, traceback=traceback, message_renderable=message_renderable + ) + if isinstance(self.console.file, NullFile): + # Handles pythonw, where stdout/stderr are null, and we return NullFile + # instance from Console.file. In this case, we still want to make a log record + # even though we won't be writing anything to a file. + self.handleError(record) + else: + try: + self.console.print(log_renderable) + except Exception: + self.handleError(record) + + def render_message(self, record: LogRecord, message: str) -> "ConsoleRenderable": + """Render message text in to Text. + + Args: + record (LogRecord): logging Record. + message (str): String containing log message. + + Returns: + ConsoleRenderable: Renderable to display log message. + """ + use_markup = getattr(record, "markup", self.markup) + message_text = Text.from_markup(message) if use_markup else Text(message) + + highlighter = getattr(record, "highlighter", self.highlighter) + if highlighter: + message_text = highlighter(message_text) + + if self.keywords is None: + self.keywords = self.KEYWORDS + + if self.keywords: + message_text.highlight_words(self.keywords, "logging.keyword") + + return message_text + + def render( + self, + *, + record: LogRecord, + traceback: Optional[Traceback], + message_renderable: "ConsoleRenderable", + ) -> "ConsoleRenderable": + """Render log for display. + + Args: + record (LogRecord): logging Record. + traceback (Optional[Traceback]): Traceback instance or None for no Traceback. + message_renderable (ConsoleRenderable): Renderable (typically Text) containing log message contents. + + Returns: + ConsoleRenderable: Renderable to display log. + """ + path = Path(record.pathname).name + level = self.get_level_text(record) + time_format = None if self.formatter is None else self.formatter.datefmt + log_time = datetime.fromtimestamp(record.created) + + log_renderable = self._log_render( + self.console, + [message_renderable] if not traceback else [message_renderable, traceback], + log_time=log_time, + time_format=time_format, + level=level, + path=path, + line_no=record.lineno, + link_path=record.pathname if self.enable_link_path else None, + ) + return log_renderable + + +if __name__ == "__main__": # pragma: no cover + from time import sleep + + FORMAT = "%(message)s" + # FORMAT = "%(asctime)-15s - %(levelname)s - %(message)s" + logging.basicConfig( + level="NOTSET", + format=FORMAT, + datefmt="[%X]", + handlers=[RichHandler(rich_tracebacks=True, tracebacks_show_locals=True)], + ) + log = logging.getLogger("rich") + + log.info("Server starting...") + log.info("Listening on http://127.0.0.1:8080") + sleep(1) + + log.info("GET /index.html 200 1298") + log.info("GET /imgs/backgrounds/back1.jpg 200 54386") + log.info("GET /css/styles.css 200 54386") + log.warning("GET /favicon.ico 404 242") + sleep(1) + + log.debug( + "JSONRPC request\n--> %r\n<-- %r", + { + "version": "1.1", + "method": "confirmFruitPurchase", + "params": [["apple", "orange", "mangoes", "pomelo"], 1.123], + "id": "194521489", + }, + {"version": "1.1", "result": True, "error": None, "id": "194521489"}, + ) + log.debug( + "Loading configuration file /adasd/asdasd/qeqwe/qwrqwrqwr/sdgsdgsdg/werwerwer/dfgerert/ertertert/ertetert/werwerwer" + ) + log.error("Unable to find 'pomelo' in database!") + log.info("POST /jsonrpc/ 200 65532") + log.info("POST /admin/ 401 42234") + log.warning("password was rejected for admin site.") + + def divide() -> None: + number = 1 + divisor = 0 + foos = ["foo"] * 100 + log.debug("in divide") + try: + number / divisor + except: + log.exception("An error of some kind occurred!") + + divide() + sleep(1) + log.critical("Out of memory!") + log.info("Server exited with code=-1") + log.info("[bold]EXITING...[/bold]", extra=dict(markup=True)) diff --git a/rich/measure.py b/rich/measure.py new file mode 100644 index 0000000000000000000000000000000000000000..a508ffa80bd715b47c190ed9d747dbc388fa5b19 --- /dev/null +++ b/rich/measure.py @@ -0,0 +1,151 @@ +from operator import itemgetter +from typing import TYPE_CHECKING, Callable, NamedTuple, Optional, Sequence + +from . import errors +from .protocol import is_renderable, rich_cast + +if TYPE_CHECKING: + from .console import Console, ConsoleOptions, RenderableType + + +class Measurement(NamedTuple): + """Stores the minimum and maximum widths (in characters) required to render an object.""" + + minimum: int + """Minimum number of cells required to render.""" + maximum: int + """Maximum number of cells required to render.""" + + @property + def span(self) -> int: + """Get difference between maximum and minimum.""" + return self.maximum - self.minimum + + def normalize(self) -> "Measurement": + """Get measurement that ensures that minimum <= maximum and minimum >= 0 + + Returns: + Measurement: A normalized measurement. + """ + minimum, maximum = self + minimum = min(max(0, minimum), maximum) + return Measurement(max(0, minimum), max(0, max(minimum, maximum))) + + def with_maximum(self, width: int) -> "Measurement": + """Get a RenderableWith where the widths are <= width. + + Args: + width (int): Maximum desired width. + + Returns: + Measurement: New Measurement object. + """ + minimum, maximum = self + return Measurement(min(minimum, width), min(maximum, width)) + + def with_minimum(self, width: int) -> "Measurement": + """Get a RenderableWith where the widths are >= width. + + Args: + width (int): Minimum desired width. + + Returns: + Measurement: New Measurement object. + """ + minimum, maximum = self + width = max(0, width) + return Measurement(max(minimum, width), max(maximum, width)) + + def clamp( + self, min_width: Optional[int] = None, max_width: Optional[int] = None + ) -> "Measurement": + """Clamp a measurement within the specified range. + + Args: + min_width (int): Minimum desired width, or ``None`` for no minimum. Defaults to None. + max_width (int): Maximum desired width, or ``None`` for no maximum. Defaults to None. + + Returns: + Measurement: New Measurement object. + """ + measurement = self + if min_width is not None: + measurement = measurement.with_minimum(min_width) + if max_width is not None: + measurement = measurement.with_maximum(max_width) + return measurement + + @classmethod + def get( + cls, console: "Console", options: "ConsoleOptions", renderable: "RenderableType" + ) -> "Measurement": + """Get a measurement for a renderable. + + Args: + console (~rich.console.Console): Console instance. + options (~rich.console.ConsoleOptions): Console options. + renderable (RenderableType): An object that may be rendered with Rich. + + Raises: + errors.NotRenderableError: If the object is not renderable. + + Returns: + Measurement: Measurement object containing range of character widths required to render the object. + """ + _max_width = options.max_width + if _max_width < 1: + return Measurement(0, 0) + if isinstance(renderable, str): + renderable = console.render_str( + renderable, markup=options.markup, highlight=False + ) + renderable = rich_cast(renderable) + if is_renderable(renderable): + get_console_width: Optional[ + Callable[["Console", "ConsoleOptions"], "Measurement"] + ] = getattr(renderable, "__rich_measure__", None) + if get_console_width is not None: + render_width = ( + get_console_width(console, options) + .normalize() + .with_maximum(_max_width) + ) + if render_width.maximum < 1: + return Measurement(0, 0) + return render_width.normalize() + else: + return Measurement(0, _max_width) + else: + raise errors.NotRenderableError( + f"Unable to get render width for {renderable!r}; " + "a str, Segment, or object with __rich_console__ method is required" + ) + + +def measure_renderables( + console: "Console", + options: "ConsoleOptions", + renderables: Sequence["RenderableType"], +) -> "Measurement": + """Get a measurement that would fit a number of renderables. + + Args: + console (~rich.console.Console): Console instance. + options (~rich.console.ConsoleOptions): Console options. + renderables (Iterable[RenderableType]): One or more renderable objects. + + Returns: + Measurement: Measurement object containing range of character widths required to + contain all given renderables. + """ + if not renderables: + return Measurement(0, 0) + get_measurement = Measurement.get + measurements = [ + get_measurement(console, options, renderable) for renderable in renderables + ] + measured_width = Measurement( + max(measurements, key=itemgetter(0)).minimum, + max(measurements, key=itemgetter(1)).maximum, + ) + return measured_width diff --git a/rich/screen.py b/rich/screen.py new file mode 100644 index 0000000000000000000000000000000000000000..b4f7fd19de7ffc7e3c18702389e093402a633c5b --- /dev/null +++ b/rich/screen.py @@ -0,0 +1,54 @@ +from typing import Optional, TYPE_CHECKING + +from .segment import Segment +from .style import StyleType +from ._loop import loop_last + + +if TYPE_CHECKING: + from .console import ( + Console, + ConsoleOptions, + RenderResult, + RenderableType, + Group, + ) + + +class Screen: + """A renderable that fills the terminal screen and crops excess. + + Args: + renderable (RenderableType): Child renderable. + style (StyleType, optional): Optional background style. Defaults to None. + """ + + renderable: "RenderableType" + + def __init__( + self, + *renderables: "RenderableType", + style: Optional[StyleType] = None, + application_mode: bool = False, + ) -> None: + from rich.console import Group + + self.renderable = Group(*renderables) + self.style = style + self.application_mode = application_mode + + def __rich_console__( + self, console: "Console", options: "ConsoleOptions" + ) -> "RenderResult": + width, height = options.size + style = console.get_style(self.style) if self.style else None + render_options = options.update(width=width, height=height) + lines = console.render_lines( + self.renderable or "", render_options, style=style, pad=True + ) + lines = Segment.set_shape(lines, width, height, style=style) + new_line = Segment("\n\r") if self.application_mode else Segment.line() + for last, line in loop_last(lines): + yield from line + if not last: + yield new_line diff --git a/rich/themes.py b/rich/themes.py new file mode 100644 index 0000000000000000000000000000000000000000..bf6db104a2c4fd4f3dc699e85f2b262c3d31e9a0 --- /dev/null +++ b/rich/themes.py @@ -0,0 +1,5 @@ +from .default_styles import DEFAULT_STYLES +from .theme import Theme + + +DEFAULT = Theme(DEFAULT_STYLES) diff --git a/rich/tree.py b/rich/tree.py new file mode 100644 index 0000000000000000000000000000000000000000..9a87d60ded6fc3c8a6e678644dbf2931005dc71f --- /dev/null +++ b/rich/tree.py @@ -0,0 +1,257 @@ +from typing import Iterator, List, Optional, Tuple + +from ._loop import loop_first, loop_last +from .console import Console, ConsoleOptions, RenderableType, RenderResult +from .jupyter import JupyterMixin +from .measure import Measurement +from .segment import Segment +from .style import Style, StyleStack, StyleType +from .styled import Styled + +GuideType = Tuple[str, str, str, str] + + +class Tree(JupyterMixin): + """A renderable for a tree structure. + + Attributes: + ASCII_GUIDES (GuideType): Guide lines used when Console.ascii_only is True. + TREE_GUIDES (List[GuideType, GuideType, GuideType]): Default guide lines. + + Args: + label (RenderableType): The renderable or str for the tree label. + style (StyleType, optional): Style of this tree. Defaults to "tree". + guide_style (StyleType, optional): Style of the guide lines. Defaults to "tree.line". + expanded (bool, optional): Also display children. Defaults to True. + highlight (bool, optional): Highlight renderable (if str). Defaults to False. + hide_root (bool, optional): Hide the root node. Defaults to False. + """ + + ASCII_GUIDES = (" ", "| ", "+-- ", "`-- ") + TREE_GUIDES = [ + (" ", "│ ", "├── ", "└── "), + (" ", "┃ ", "┣━━ ", "┗━━ "), + (" ", "║ ", "╠══ ", "╚══ "), + ] + + def __init__( + self, + label: RenderableType, + *, + style: StyleType = "tree", + guide_style: StyleType = "tree.line", + expanded: bool = True, + highlight: bool = False, + hide_root: bool = False, + ) -> None: + self.label = label + self.style = style + self.guide_style = guide_style + self.children: List[Tree] = [] + self.expanded = expanded + self.highlight = highlight + self.hide_root = hide_root + + def add( + self, + label: RenderableType, + *, + style: Optional[StyleType] = None, + guide_style: Optional[StyleType] = None, + expanded: bool = True, + highlight: Optional[bool] = False, + ) -> "Tree": + """Add a child tree. + + Args: + label (RenderableType): The renderable or str for the tree label. + style (StyleType, optional): Style of this tree. Defaults to "tree". + guide_style (StyleType, optional): Style of the guide lines. Defaults to "tree.line". + expanded (bool, optional): Also display children. Defaults to True. + highlight (Optional[bool], optional): Highlight renderable (if str). Defaults to False. + + Returns: + Tree: A new child Tree, which may be further modified. + """ + node = Tree( + label, + style=self.style if style is None else style, + guide_style=self.guide_style if guide_style is None else guide_style, + expanded=expanded, + highlight=self.highlight if highlight is None else highlight, + ) + self.children.append(node) + return node + + def __rich_console__( + self, console: "Console", options: "ConsoleOptions" + ) -> "RenderResult": + stack: List[Iterator[Tuple[bool, Tree]]] = [] + pop = stack.pop + push = stack.append + new_line = Segment.line() + + get_style = console.get_style + null_style = Style.null() + guide_style = get_style(self.guide_style, default="") or null_style + SPACE, CONTINUE, FORK, END = range(4) + + _Segment = Segment + + def make_guide(index: int, style: Style) -> Segment: + """Make a Segment for a level of the guide lines.""" + if options.ascii_only: + line = self.ASCII_GUIDES[index] + else: + guide = 1 if style.bold else (2 if style.underline2 else 0) + line = self.TREE_GUIDES[0 if options.legacy_windows else guide][index] + return _Segment(line, style) + + levels: List[Segment] = [make_guide(CONTINUE, guide_style)] + push(iter(loop_last([self]))) + + guide_style_stack = StyleStack(get_style(self.guide_style)) + style_stack = StyleStack(get_style(self.style)) + remove_guide_styles = Style(bold=False, underline2=False) + + depth = 0 + + while stack: + stack_node = pop() + try: + last, node = next(stack_node) + except StopIteration: + levels.pop() + if levels: + guide_style = levels[-1].style or null_style + levels[-1] = make_guide(FORK, guide_style) + guide_style_stack.pop() + style_stack.pop() + continue + push(stack_node) + if last: + levels[-1] = make_guide(END, levels[-1].style or null_style) + + guide_style = guide_style_stack.current + get_style(node.guide_style) + style = style_stack.current + get_style(node.style) + prefix = levels[(2 if self.hide_root else 1) :] + renderable_lines = console.render_lines( + Styled(node.label, style), + options.update( + width=options.max_width + - sum(level.cell_length for level in prefix), + highlight=self.highlight, + height=None, + ), + pad=options.justify is not None, + ) + + if not (depth == 0 and self.hide_root): + for first, line in loop_first(renderable_lines): + if prefix: + yield from _Segment.apply_style( + prefix, + style.background_style, + post_style=remove_guide_styles, + ) + yield from line + yield new_line + if first and prefix: + prefix[-1] = make_guide( + SPACE if last else CONTINUE, prefix[-1].style or null_style + ) + + if node.expanded and node.children: + levels[-1] = make_guide( + SPACE if last else CONTINUE, levels[-1].style or null_style + ) + levels.append( + make_guide(END if len(node.children) == 1 else FORK, guide_style) + ) + style_stack.push(get_style(node.style)) + guide_style_stack.push(get_style(node.guide_style)) + push(iter(loop_last(node.children))) + depth += 1 + + def __rich_measure__( + self, console: "Console", options: "ConsoleOptions" + ) -> "Measurement": + stack: List[Iterator[Tree]] = [iter([self])] + pop = stack.pop + push = stack.append + minimum = 0 + maximum = 0 + measure = Measurement.get + level = 0 + while stack: + iter_tree = pop() + try: + tree = next(iter_tree) + except StopIteration: + level -= 1 + continue + push(iter_tree) + min_measure, max_measure = measure(console, options, tree.label) + indent = level * 4 + minimum = max(min_measure + indent, minimum) + maximum = max(max_measure + indent, maximum) + if tree.expanded and tree.children: + push(iter(tree.children)) + level += 1 + return Measurement(minimum, maximum) + + +if __name__ == "__main__": # pragma: no cover + from rich.console import Group + from rich.markdown import Markdown + from rich.panel import Panel + from rich.syntax import Syntax + from rich.table import Table + + table = Table(row_styles=["", "dim"]) + + table.add_column("Released", style="cyan", no_wrap=True) + table.add_column("Title", style="magenta") + table.add_column("Box Office", justify="right", style="green") + + table.add_row("Dec 20, 2019", "Star Wars: The Rise of Skywalker", "$952,110,690") + table.add_row("May 25, 2018", "Solo: A Star Wars Story", "$393,151,347") + table.add_row("Dec 15, 2017", "Star Wars Ep. V111: The Last Jedi", "$1,332,539,889") + table.add_row("Dec 16, 2016", "Rogue One: A Star Wars Story", "$1,332,439,889") + + code = """\ +class Segment(NamedTuple): + text: str = "" + style: Optional[Style] = None + is_control: bool = False +""" + syntax = Syntax(code, "python", theme="monokai", line_numbers=True) + + markdown = Markdown( + """\ +### example.md +> Hello, World! +> +> Markdown _all_ the things +""" + ) + + root = Tree("🌲 [b green]Rich Tree", highlight=True, hide_root=True) + + node = root.add(":file_folder: Renderables", guide_style="red") + simple_node = node.add(":file_folder: [bold yellow]Atomic", guide_style="uu green") + simple_node.add(Group("📄 Syntax", syntax)) + simple_node.add(Group("📄 Markdown", Panel(markdown, border_style="green"))) + + containers_node = node.add( + ":file_folder: [bold magenta]Containers", guide_style="bold magenta" + ) + containers_node.expanded = True + panel = Panel.fit("Just a panel", border_style="red") + containers_node.add(Group("📄 Panels", panel)) + + containers_node.add(Group("📄 [b magenta]Table", table)) + + console = Console() + + console.print(root) diff --git a/safetensors/__init__.py b/safetensors/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..0aea2154eb6b993974d3e2874f2d3ad09e21d9c0 --- /dev/null +++ b/safetensors/__init__.py @@ -0,0 +1,10 @@ +# Re-export this +from ._safetensors_rust import ( # noqa: F401 + SafetensorError, + __version__, + deserialize, + safe_open, + _safe_open_handle, + serialize, + serialize_file, +) diff --git a/safetensors/__init__.pyi b/safetensors/__init__.pyi new file mode 100644 index 0000000000000000000000000000000000000000..a89e0655a1522224f44de863e9276d0562b27162 --- /dev/null +++ b/safetensors/__init__.pyi @@ -0,0 +1,164 @@ +# Generated content DO NOT EDIT +@staticmethod +def deserialize(bytes): + """ + Opens a safetensors lazily and returns tensors as asked + + Args: + data (`bytes`): + The byte content of a file + + Returns: + (`List[str, Dict[str, Dict[str, any]]]`): + The deserialized content is like: + [("tensor_name", {"shape": [2, 3], "dtype": "F32", "data": b"\0\0.." }), (...)] + """ + pass + +@staticmethod +def serialize(tensor_dict, metadata=None): + """ + Serializes raw data. + + Args: + tensor_dict (`Dict[str, Dict[Any]]`): + The tensor dict is like: + {"tensor_name": {"dtype": "F32", "shape": [2, 3], "data": b"\0\0"}} + metadata (`Dict[str, str]`, *optional*): + The optional purely text annotations + + Returns: + (`bytes`): + The serialized content. + """ + pass + +@staticmethod +def serialize_file(tensor_dict, filename, metadata=None): + """ + Serializes raw data into file. + + Args: + tensor_dict (`Dict[str, Dict[Any]]`): + The tensor dict is like: + {"tensor_name": {"dtype": "F32", "shape": [2, 3], "data": b"\0\0"}} + filename (`str`, or `os.PathLike`): + The name of the file to write into. + metadata (`Dict[str, str]`, *optional*): + The optional purely text annotations + + Returns: + (`NoneType`): + On success return None + """ + pass + +class safe_open: + """ + Opens a safetensors lazily and returns tensors as asked + + Args: + filename (`str`, or `os.PathLike`): + The filename to open + + framework (`str`): + The framework you want you tensors in. Supported values: + `pt`, `tf`, `flax`, `numpy`. + + device (`str`, defaults to `"cpu"`): + The device on which you want the tensors. + """ + def __init__(self, filename, framework, device=...): + pass + + def __enter__(self): + """ + Start the context manager + """ + pass + + def __exit__(self, _exc_type, _exc_value, _traceback): + """ + Exits the context manager + """ + pass + + def get_slice(self, name): + """ + Returns a full slice view object + + Args: + name (`str`): + The name of the tensor you want + + Returns: + (`PySafeSlice`): + A dummy object you can slice into to get a real tensor + Example: + ```python + from safetensors import safe_open + + with safe_open("model.safetensors", framework="pt", device=0) as f: + tensor_part = f.get_slice("embedding")[:, ::8] + + ``` + """ + pass + + def get_tensor(self, name): + """ + Returns a full tensor + + Args: + name (`str`): + The name of the tensor you want + + Returns: + (`Tensor`): + The tensor in the framework you opened the file for. + + Example: + ```python + from safetensors import safe_open + + with safe_open("model.safetensors", framework="pt", device=0) as f: + tensor = f.get_tensor("embedding") + + ``` + """ + pass + + def keys(self): + """ + Returns the names of the tensors in the file. + + Returns: + (`List[str]`): + The name of the tensors contained in that file + """ + pass + + def metadata(self): + """ + Return the special non tensor information in the header + + Returns: + (`Dict[str, str]`): + The freeform metadata. + """ + pass + + def offset_keys(self): + """ + Returns the names of the tensors in the file, ordered by offset. + + Returns: + (`List[str]`): + The name of the tensors contained in that file + """ + pass + +class SafetensorError(Exception): + """ + Custom Python Exception for Safetensor errors. + """ diff --git a/safetensors/flax.py b/safetensors/flax.py new file mode 100644 index 0000000000000000000000000000000000000000..a6471507dc44bff6c4a75e5b75a24241a693dad5 --- /dev/null +++ b/safetensors/flax.py @@ -0,0 +1,138 @@ +import os +from typing import Dict, Optional, Union + +import numpy as np + +import jax.numpy as jnp +from jax import Array +from safetensors import numpy, safe_open + + +def save(tensors: Dict[str, Array], metadata: Optional[Dict[str, str]] = None) -> bytes: + """ + Saves a dictionary of tensors into raw bytes in safetensors format. + + Args: + tensors (`Dict[str, Array]`): + The incoming tensors. Tensors need to be contiguous and dense. + metadata (`Dict[str, str]`, *optional*, defaults to `None`): + Optional text only metadata you might want to save in your header. + For instance it can be useful to specify more about the underlying + tensors. This is purely informative and does not affect tensor loading. + + Returns: + `bytes`: The raw bytes representing the format + + Example: + + ```python + from safetensors.flax import save + from jax import numpy as jnp + + tensors = {"embedding": jnp.zeros((512, 1024)), "attention": jnp.zeros((256, 256))} + byte_data = save(tensors) + ``` + """ + np_tensors = _jnp2np(tensors) + return numpy.save(np_tensors, metadata=metadata) + + +def save_file( + tensors: Dict[str, Array], + filename: Union[str, os.PathLike], + metadata: Optional[Dict[str, str]] = None, +) -> None: + """ + Saves a dictionary of tensors into raw bytes in safetensors format. + + Args: + tensors (`Dict[str, Array]`): + The incoming tensors. Tensors need to be contiguous and dense. + filename (`str`, or `os.PathLike`)): + The filename we're saving into. + metadata (`Dict[str, str]`, *optional*, defaults to `None`): + Optional text only metadata you might want to save in your header. + For instance it can be useful to specify more about the underlying + tensors. This is purely informative and does not affect tensor loading. + + Returns: + `None` + + Example: + + ```python + from safetensors.flax import save_file + from jax import numpy as jnp + + tensors = {"embedding": jnp.zeros((512, 1024)), "attention": jnp.zeros((256, 256))} + save_file(tensors, "model.safetensors") + ``` + """ + np_tensors = _jnp2np(tensors) + return numpy.save_file(np_tensors, filename, metadata=metadata) + + +def load(data: bytes) -> Dict[str, Array]: + """ + Loads a safetensors file into flax format from pure bytes. + + Args: + data (`bytes`): + The content of a safetensors file + + Returns: + `Dict[str, Array]`: dictionary that contains name as key, value as `Array` on cpu + + Example: + + ```python + from safetensors.flax import load + + file_path = "./my_folder/bert.safetensors" + with open(file_path, "rb") as f: + data = f.read() + + loaded = load(data) + ``` + """ + flat = numpy.load(data) + return _np2jnp(flat) + + +def load_file(filename: Union[str, os.PathLike]) -> Dict[str, Array]: + """ + Loads a safetensors file into flax format. + + Args: + filename (`str`, or `os.PathLike`)): + The name of the file which contains the tensors + + Returns: + `Dict[str, Array]`: dictionary that contains name as key, value as `Array` + + Example: + + ```python + from safetensors.flax import load_file + + file_path = "./my_folder/bert.safetensors" + loaded = load_file(file_path) + ``` + """ + result = {} + with safe_open(filename, framework="flax") as f: + for k in f.offset_keys(): + result[k] = f.get_tensor(k) + return result + + +def _np2jnp(numpy_dict: Dict[str, np.ndarray]) -> Dict[str, Array]: + for k, v in numpy_dict.items(): + numpy_dict[k] = jnp.array(v) + return numpy_dict + + +def _jnp2np(jnp_dict: Dict[str, Array]) -> Dict[str, np.array]: + for k, v in jnp_dict.items(): + jnp_dict[k] = np.asarray(v) + return jnp_dict diff --git a/safetensors/mlx.py b/safetensors/mlx.py new file mode 100644 index 0000000000000000000000000000000000000000..985b73b98ef19afc2104ed1b2464fdeaf829d3bd --- /dev/null +++ b/safetensors/mlx.py @@ -0,0 +1,140 @@ +import os +from typing import Dict, Optional, Union + +import numpy as np + +import mlx.core as mx +from safetensors import numpy, safe_open + + +def save( + tensors: Dict[str, mx.array], metadata: Optional[Dict[str, str]] = None +) -> bytes: + """ + Saves a dictionary of tensors into raw bytes in safetensors format. + + Args: + tensors (`Dict[str, mx.array]`): + The incoming tensors. Tensors need to be contiguous and dense. + metadata (`Dict[str, str]`, *optional*, defaults to `None`): + Optional text only metadata you might want to save in your header. + For instance it can be useful to specify more about the underlying + tensors. This is purely informative and does not affect tensor loading. + + Returns: + `bytes`: The raw bytes representing the format + + Example: + + ```python + from safetensors.mlx import save + import mlx.core as mx + + tensors = {"embedding": mx.zeros((512, 1024)), "attention": mx.zeros((256, 256))} + byte_data = save(tensors) + ``` + """ + np_tensors = _mx2np(tensors) + return numpy.save(np_tensors, metadata=metadata) + + +def save_file( + tensors: Dict[str, mx.array], + filename: Union[str, os.PathLike], + metadata: Optional[Dict[str, str]] = None, +) -> None: + """ + Saves a dictionary of tensors into raw bytes in safetensors format. + + Args: + tensors (`Dict[str, mx.array]`): + The incoming tensors. Tensors need to be contiguous and dense. + filename (`str`, or `os.PathLike`)): + The filename we're saving into. + metadata (`Dict[str, str]`, *optional*, defaults to `None`): + Optional text only metadata you might want to save in your header. + For instance it can be useful to specify more about the underlying + tensors. This is purely informative and does not affect tensor loading. + + Returns: + `None` + + Example: + + ```python + from safetensors.mlx import save_file + import mlx.core as mx + + tensors = {"embedding": mx.zeros((512, 1024)), "attention": mx.zeros((256, 256))} + save_file(tensors, "model.safetensors") + ``` + """ + np_tensors = _mx2np(tensors) + return numpy.save_file(np_tensors, filename, metadata=metadata) + + +def load(data: bytes) -> Dict[str, mx.array]: + """ + Loads a safetensors file into MLX format from pure bytes. + + Args: + data (`bytes`): + The content of a safetensors file + + Returns: + `Dict[str, mx.array]`: dictionary that contains name as key, value as `mx.array` + + Example: + + ```python + from safetensors.mlx import load + + file_path = "./my_folder/bert.safetensors" + with open(file_path, "rb") as f: + data = f.read() + + loaded = load(data) + ``` + """ + flat = numpy.load(data) + return _np2mx(flat) + + +def load_file(filename: Union[str, os.PathLike]) -> Dict[str, mx.array]: + """ + Loads a safetensors file into MLX format. + + Args: + filename (`str`, or `os.PathLike`)): + The name of the file which contains the tensors + + Returns: + `Dict[str, mx.array]`: dictionary that contains name as key, value as `mx.array` + + Example: + + ```python + from safetensors.flax import load_file + + file_path = "./my_folder/bert.safetensors" + loaded = load_file(file_path) + ``` + """ + result = {} + with safe_open(filename, framework="mlx") as f: + for k in f.offset_keys(): + result[k] = f.get_tensor(k) + return result + + +def _np2mx(numpy_dict: Dict[str, np.ndarray]) -> Dict[str, mx.array]: + for k, v in numpy_dict.items(): + numpy_dict[k] = mx.array(v) + return numpy_dict + + +def _mx2np(mx_dict: Dict[str, mx.array]) -> Dict[str, np.array]: + new_dict = {} + for k, v in mx_dict.items(): + new_dict[k] = np.asarray(v) + return new_dict diff --git a/safetensors/numpy.py b/safetensors/numpy.py new file mode 100644 index 0000000000000000000000000000000000000000..582c01be82c1ab1b7e0722b426ee561aec1a59a6 --- /dev/null +++ b/safetensors/numpy.py @@ -0,0 +1,187 @@ +import os +import sys +from typing import Dict, Optional, Union + +import numpy as np + +from safetensors import deserialize, safe_open, serialize, serialize_file + + +def _tobytes(tensor: np.ndarray) -> bytes: + if not _is_little_endian(tensor): + tensor = tensor.byteswap(inplace=False) + return tensor.tobytes() + + +def save( + tensor_dict: Dict[str, np.ndarray], metadata: Optional[Dict[str, str]] = None +) -> bytes: + """ + Saves a dictionary of tensors into raw bytes in safetensors format. + + Args: + tensor_dict (`Dict[str, np.ndarray]`): + The incoming tensors. Tensors need to be contiguous and dense. + metadata (`Dict[str, str]`, *optional*, defaults to `None`): + Optional text only metadata you might want to save in your header. + For instance it can be useful to specify more about the underlying + tensors. This is purely informative and does not affect tensor loading. + + Returns: + `bytes`: The raw bytes representing the format + + Example: + + ```python + from safetensors.numpy import save + import numpy as np + + tensors = {"embedding": np.zeros((512, 1024)), "attention": np.zeros((256, 256))} + byte_data = save(tensors) + ``` + """ + flattened = { + k: {"dtype": v.dtype.name, "shape": v.shape, "data": _tobytes(v)} + for k, v in tensor_dict.items() + } + serialized = serialize(flattened, metadata=metadata) + result = bytes(serialized) + return result + + +def save_file( + tensor_dict: Dict[str, np.ndarray], + filename: Union[str, os.PathLike], + metadata: Optional[Dict[str, str]] = None, +) -> None: + """ + Saves a dictionary of tensors into raw bytes in safetensors format. + + Args: + tensor_dict (`Dict[str, np.ndarray]`): + The incoming tensors. Tensors need to be contiguous and dense. + filename (`str`, or `os.PathLike`)): + The filename we're saving into. + metadata (`Dict[str, str]`, *optional*, defaults to `None`): + Optional text only metadata you might want to save in your header. + For instance it can be useful to specify more about the underlying + tensors. This is purely informative and does not affect tensor loading. + + Returns: + `None` + + Example: + + ```python + from safetensors.numpy import save_file + import numpy as np + + tensors = {"embedding": np.zeros((512, 1024)), "attention": np.zeros((256, 256))} + save_file(tensors, "model.safetensors") + ``` + """ + flattened = { + k: {"dtype": v.dtype.name, "shape": v.shape, "data": _tobytes(v)} + for k, v in tensor_dict.items() + } + serialize_file(flattened, filename, metadata=metadata) + + +def load(data: bytes) -> Dict[str, np.ndarray]: + """ + Loads a safetensors file into numpy format from pure bytes. + + Args: + data (`bytes`): + The content of a safetensors file + + Returns: + `Dict[str, np.ndarray]`: dictionary that contains name as key, value as `np.ndarray` on cpu + + Example: + + ```python + from safetensors.numpy import load + + file_path = "./my_folder/bert.safetensors" + with open(file_path, "rb") as f: + data = f.read() + + loaded = load(data) + ``` + """ + flat = deserialize(data) + return _view2np(flat) + + +def load_file(filename: Union[str, os.PathLike]) -> Dict[str, np.ndarray]: + """ + Loads a safetensors file into numpy format. + + Args: + filename (`str`, or `os.PathLike`)): + The name of the file which contains the tensors + + Returns: + `Dict[str, np.ndarray]`: dictionary that contains name as key, value as `np.ndarray` + + Example: + + ```python + from safetensors.numpy import load_file + + file_path = "./my_folder/bert.safetensors" + loaded = load_file(file_path) + ``` + """ + result = {} + with safe_open(filename, framework="np") as f: + for k in f.offset_keys(): + result[k] = f.get_tensor(k) + return result + + +_TYPES = { + "F64": np.float64, + "F32": np.float32, + "F16": np.float16, + "I64": np.int64, + "U64": np.uint64, + "I32": np.int32, + "U32": np.uint32, + "I16": np.int16, + "U16": np.uint16, + "I8": np.int8, + "U8": np.uint8, + "BOOL": bool, + "C64": np.complex64, +} + + +def _getdtype(dtype_str: str) -> np.dtype: + return _TYPES[dtype_str] + + +def _view2np(safeview) -> Dict[str, np.ndarray]: + result = {} + for k, v in safeview: + dtype = _getdtype(v["dtype"]) + arr = np.frombuffer(v["data"], dtype=dtype).reshape(v["shape"]) + result[k] = arr + return result + + +def _is_little_endian(tensor: np.ndarray) -> bool: + byteorder = tensor.dtype.byteorder + if byteorder == "=": + if sys.byteorder == "little": + return True + else: + return False + elif byteorder == "|": + return True + elif byteorder == "<": + return True + elif byteorder == ">": + return False + raise ValueError(f"Unexpected byte order {byteorder}") diff --git a/safetensors/paddle.py b/safetensors/paddle.py new file mode 100644 index 0000000000000000000000000000000000000000..0f3dd4aa332ddf3f553d2c73e7204719824f0b9b --- /dev/null +++ b/safetensors/paddle.py @@ -0,0 +1,290 @@ +import os +import sys +from typing import Any, Dict, Optional, Union + +import numpy as np +import paddle + +from safetensors import numpy, deserialize, safe_open, serialize, serialize_file + + +def save( + tensors: Dict[str, paddle.Tensor], metadata: Optional[Dict[str, str]] = None +) -> bytes: + """ + Saves a dictionary of tensors into raw bytes in safetensors format. + + Args: + tensors (`Dict[str, paddle.Tensor]`): + The incoming tensors. Tensors need to be contiguous and dense. + metadata (`Dict[str, str]`, *optional*, defaults to `None`): + Optional text only metadata you might want to save in your header. + For instance it can be useful to specify more about the underlying + tensors. This is purely informative and does not affect tensor loading. + + Returns: + `bytes`: The raw bytes representing the format + + Example: + + ```python + from safetensors.paddle import save + import paddle + + tensors = {"embedding": paddle.zeros((512, 1024)), "attention": paddle.zeros((256, 256))} + byte_data = save(tensors) + ``` + """ + serialized = serialize(_flatten(tensors), metadata=metadata) + result = bytes(serialized) + return result + + +def save_file( + tensors: Dict[str, paddle.Tensor], + filename: Union[str, os.PathLike], + metadata: Optional[Dict[str, str]] = None, +) -> None: + """ + Saves a dictionary of tensors into raw bytes in safetensors format. + + Args: + tensors (`Dict[str, paddle.Tensor]`): + The incoming tensors. Tensors need to be contiguous and dense. + filename (`str`, or `os.PathLike`)): + The filename we're saving into. + metadata (`Dict[str, str]`, *optional*, defaults to `None`): + Optional text only metadata you might want to save in your header. + For instance it can be useful to specify more about the underlying + tensors. This is purely informative and does not affect tensor loading. + + Returns: + `None` + + Example: + + ```python + from safetensors.paddle import save_file + import paddle + + tensors = {"embedding": paddle.zeros((512, 1024)), "attention": paddle.zeros((256, 256))} + save_file(tensors, "model.safetensors") + ``` + """ + serialize_file(_flatten(tensors), filename, metadata=metadata) + + +def load(data: bytes, device: str = "cpu") -> Dict[str, paddle.Tensor]: + """ + Loads a safetensors file into paddle format from pure bytes. + + Args: + data (`bytes`): + The content of a safetensors file + + Returns: + `Dict[str, paddle.Tensor]`: dictionary that contains name as key, value as `paddle.Tensor` on cpu + + Example: + + ```python + from safetensors.paddle import load + + file_path = "./my_folder/bert.safetensors" + with open(file_path, "rb") as f: + data = f.read() + + loaded = load(data) + ``` + """ + if paddle.__version__ >= "3.2.0": + flat = deserialize(data) + return _view2paddle(flat, device) + else: + flat = numpy.load(data) + return _np2paddle(flat, device) + + +def load_file( + filename: Union[str, os.PathLike], device="cpu" +) -> Dict[str, paddle.Tensor]: + """ + Loads a safetensors file into paddle format. + + Args: + filename (`str`, or `os.PathLike`)): + The name of the file which contains the tensors + device (`Union[Dict[str, any], str]`, *optional*, defaults to `cpu`): + The device where the tensors need to be located after load. + available options are all regular paddle device locations + + Returns: + `Dict[str, paddle.Tensor]`: dictionary that contains name as key, value as `paddle.Tensor` + + Example: + + ```python + from safetensors.paddle import load_file + + file_path = "./my_folder/bert.safetensors" + loaded = load_file(file_path) + ``` + """ + result = {} + if paddle.__version__ >= "3.2.0": + with safe_open(filename, framework="paddle", device=device) as f: + for k in f.offset_keys(): + result[k] = f.get_tensor(k) + else: + flat = numpy.load_file(filename) + result = _np2paddle(flat, device) + return result + + +def _np2paddle( + numpy_dict: Dict[str, np.ndarray], device: str = "cpu" +) -> Dict[str, paddle.Tensor]: + for k, v in numpy_dict.items(): + numpy_dict[k] = paddle.to_tensor(v, place=device) + return numpy_dict + + +def _paddle2np(paddle_dict: Dict[str, paddle.Tensor]) -> Dict[str, np.array]: + for k, v in paddle_dict.items(): + paddle_dict[k] = v.detach().cpu().numpy() + return paddle_dict + + +_SIZE = { + paddle.int64: 8, + paddle.float32: 4, + paddle.int32: 4, + paddle.bfloat16: 2, + paddle.float16: 2, + paddle.int16: 2, + paddle.uint8: 1, + paddle.int8: 1, + paddle.bool: 1, + paddle.float64: 8, + paddle.float8_e4m3fn: 1, + paddle.float8_e5m2: 1, + paddle.complex64: 8, + # XXX: These are not supported yet in paddle + # paddle.uint64: 8, + # paddle.uint32: 4, + # paddle.uint16: 2, + # paddle.float8_e8m0: 1, + # paddle.float4_e2m1_x2: 1, +} + +_TYPES = { + "F64": paddle.float64, + "F32": paddle.float32, + "F16": paddle.float16, + "BF16": paddle.bfloat16, + "I64": paddle.int64, + "I32": paddle.int32, + "I16": paddle.int16, + "I8": paddle.int8, + "U8": paddle.uint8, + "BOOL": paddle.bool, + "F8_E4M3": paddle.float8_e4m3fn, + "F8_E5M2": paddle.float8_e5m2, +} + +NPDTYPES = { + paddle.int64: np.int64, + paddle.float32: np.float32, + paddle.int32: np.int32, + # XXX: This is ok because both have the same width + paddle.bfloat16: np.float16, + paddle.float16: np.float16, + paddle.int16: np.int16, + paddle.uint8: np.uint8, + paddle.int8: np.int8, + paddle.bool: bool, + paddle.float64: np.float64, + # XXX: This is ok because both have the same width and byteswap is a no-op anyway + paddle.float8_e4m3fn: np.uint8, + paddle.float8_e5m2: np.uint8, +} + + +def _getdtype(dtype_str: str) -> paddle.dtype: + return _TYPES[dtype_str] + + +def _view2paddle(safeview, device) -> Dict[str, paddle.Tensor]: + result = {} + for k, v in safeview: + dtype = _getdtype(v["dtype"]) + if len(v["data"]) == 0: + # Workaround because frombuffer doesn't accept zero-size tensors + assert any(x == 0 for x in v["shape"]) + arr = paddle.empty(v["shape"], dtype=dtype) + else: + arr = paddle.base.core.frombuffer(v["data"], dtype).reshape(v["shape"]) + if device != "cpu": + arr = arr.to(device) + if sys.byteorder == "big": + arr = paddle.to_tensor(arr.numpy().byteswap(inplace=False), place=device) + result[k] = arr + + return result + + +def _tobytes(tensor: paddle.Tensor, name: str) -> bytes: + if not tensor.is_contiguous(): + raise ValueError( + f"You are trying to save a non contiguous tensor: `{name}` which is not allowed. It either means you" + " are trying to save tensors which are reference of each other in which case it's recommended to save" + " only the full tensors, and reslice at load time, or simply call `.contiguous()` on your tensor to" + " pack it before saving." + ) + if not tensor.place.is_cpu_place(): + # Moving tensor to cpu before saving + tensor = tensor.cpu() + + import ctypes + + import numpy as np + + # When shape is empty (scalar), np.prod returns a float + # we need a int for the following calculations + length = int(np.prod(tensor.shape).item()) + bytes_per_item = _SIZE[tensor.dtype] + + total_bytes = length * bytes_per_item + + ptr = tensor.data_ptr() + if ptr == 0: + return b"" + newptr = ctypes.cast(ptr, ctypes.POINTER(ctypes.c_ubyte)) + data = np.ctypeslib.as_array(newptr, (total_bytes,)) # no internal copy + if sys.byteorder == "big": + npdtype = NPDTYPES[tensor.dtype] + # Not in place as that would potentially modify a live running model + data = data.view(npdtype).byteswap(inplace=False) + return data.tobytes() + + +def _flatten(tensors: Dict[str, paddle.Tensor]) -> Dict[str, Dict[str, Any]]: + if not isinstance(tensors, dict): + raise ValueError( + f"Expected a dict of [str, paddle.Tensor] but received {type(tensors)}" + ) + + for k, v in tensors.items(): + if not isinstance(v, paddle.Tensor): + raise ValueError( + f"Key `{k}` is invalid, expected paddle.Tensor but received {type(v)}" + ) + + return { + k: { + "dtype": str(v.dtype).split(".")[-1], + "shape": v.shape, + "data": _tobytes(v, k), + } + for k, v in tensors.items() + } diff --git a/safetensors/py.typed b/safetensors/py.typed new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/safetensors/tensorflow.py b/safetensors/tensorflow.py new file mode 100644 index 0000000000000000000000000000000000000000..c2bfc936ebae5350c0599a79c8ec3841fd6cda0c --- /dev/null +++ b/safetensors/tensorflow.py @@ -0,0 +1,139 @@ +import os +from typing import Dict, Optional, Union + +import numpy as np +import tensorflow as tf + +from safetensors import numpy, safe_open + + +def save( + tensors: Dict[str, tf.Tensor], metadata: Optional[Dict[str, str]] = None +) -> bytes: + """ + Saves a dictionary of tensors into raw bytes in safetensors format. + + Args: + tensors (`Dict[str, tf.Tensor]`): + The incoming tensors. Tensors need to be contiguous and dense. + metadata (`Dict[str, str]`, *optional*, defaults to `None`): + Optional text only metadata you might want to save in your header. + For instance it can be useful to specify more about the underlying + tensors. This is purely informative and does not affect tensor loading. + + Returns: + `bytes`: The raw bytes representing the format + + Example: + + ```python + from safetensors.tensorflow import save + import tensorflow as tf + + tensors = {"embedding": tf.zeros((512, 1024)), "attention": tf.zeros((256, 256))} + byte_data = save(tensors) + ``` + """ + np_tensors = _tf2np(tensors) + return numpy.save(np_tensors, metadata=metadata) + + +def save_file( + tensors: Dict[str, tf.Tensor], + filename: Union[str, os.PathLike], + metadata: Optional[Dict[str, str]] = None, +) -> None: + """ + Saves a dictionary of tensors into raw bytes in safetensors format. + + Args: + tensors (`Dict[str, tf.Tensor]`): + The incoming tensors. Tensors need to be contiguous and dense. + filename (`str`, or `os.PathLike`)): + The filename we're saving into. + metadata (`Dict[str, str]`, *optional*, defaults to `None`): + Optional text only metadata you might want to save in your header. + For instance it can be useful to specify more about the underlying + tensors. This is purely informative and does not affect tensor loading. + + Returns: + `None` + + Example: + + ```python + from safetensors.tensorflow import save_file + import tensorflow as tf + + tensors = {"embedding": tf.zeros((512, 1024)), "attention": tf.zeros((256, 256))} + save_file(tensors, "model.safetensors") + ``` + """ + np_tensors = _tf2np(tensors) + return numpy.save_file(np_tensors, filename, metadata=metadata) + + +def load(data: bytes) -> Dict[str, tf.Tensor]: + """ + Loads a safetensors file into tensorflow format from pure bytes. + + Args: + data (`bytes`): + The content of a safetensors file + + Returns: + `Dict[str, tf.Tensor]`: dictionary that contains name as key, value as `tf.Tensor` on cpu + + Example: + + ```python + from safetensors.tensorflow import load + + file_path = "./my_folder/bert.safetensors" + with open(file_path, "rb") as f: + data = f.read() + + loaded = load(data) + ``` + """ + flat = numpy.load(data) + return _np2tf(flat) + + +def load_file(filename: Union[str, os.PathLike]) -> Dict[str, tf.Tensor]: + """ + Loads a safetensors file into tensorflow format. + + Args: + filename (`str`, or `os.PathLike`)): + The name of the file which contains the tensors + + Returns: + `Dict[str, tf.Tensor]`: dictionary that contains name as key, value as `tf.Tensor` + + Example: + + ```python + from safetensors.tensorflow import load_file + + file_path = "./my_folder/bert.safetensors" + loaded = load_file(file_path) + ``` + """ + result = {} + with safe_open(filename, framework="tf") as f: + for k in f.offset_keys(): + result[k] = f.get_tensor(k) + return result + + +def _np2tf(numpy_dict: Dict[str, np.ndarray]) -> Dict[str, tf.Tensor]: + for k, v in numpy_dict.items(): + numpy_dict[k] = tf.convert_to_tensor(v) + return numpy_dict + + +def _tf2np(tf_dict: Dict[str, tf.Tensor]) -> Dict[str, np.array]: + for k, v in tf_dict.items(): + tf_dict[k] = v.numpy() + return tf_dict diff --git a/safetensors/torch.py b/safetensors/torch.py new file mode 100644 index 0000000000000000000000000000000000000000..861dee7a53669d99d4529188a4b899772b60f750 --- /dev/null +++ b/safetensors/torch.py @@ -0,0 +1,550 @@ +import os +import sys +from collections import defaultdict +from typing import Any, Dict, List, Optional, Set, Tuple, Union +from packaging.version import Version + +import torch + +from safetensors import deserialize, safe_open, serialize, serialize_file + + +def storage_ptr(tensor: torch.Tensor) -> int: + try: + return tensor.untyped_storage().data_ptr() + except Exception: + # Fallback for torch==1.10 + try: + return tensor.storage().data_ptr() + except NotImplementedError: + # Fallback for meta storage + return 0 + + +def _end_ptr(tensor: torch.Tensor) -> int: + if tensor.nelement(): + stop = tensor.view(-1)[-1].data_ptr() + _SIZE[tensor.dtype] + else: + stop = tensor.data_ptr() + return stop + + +def storage_size(tensor: torch.Tensor) -> int: + try: + return tensor.untyped_storage().nbytes() + except AttributeError: + # Fallback for torch==1.10 + try: + return tensor.storage().size() * _SIZE[tensor.dtype] + except NotImplementedError: + # Fallback for meta storage + # On torch >=2.0 this is the tensor size + return tensor.nelement() * _SIZE[tensor.dtype] + + +def _filter_shared_not_shared( + tensors: List[Set[str]], state_dict: Dict[str, torch.Tensor] +) -> List[Set[str]]: + filtered_tensors = [] + for shared in tensors: + if len(shared) < 2: + filtered_tensors.append(shared) + continue + + areas = [] + for name in shared: + tensor = state_dict[name] + areas.append((tensor.data_ptr(), _end_ptr(tensor), name)) + areas.sort() + + _, last_stop, last_name = areas[0] + filtered_tensors.append({last_name}) + for start, stop, name in areas[1:]: + if start >= last_stop: + filtered_tensors.append({name}) + else: + filtered_tensors[-1].add(name) + last_stop = stop + + return filtered_tensors + + +def _find_shared_tensors(state_dict: Dict[str, torch.Tensor]) -> List[Set[str]]: + tensors = defaultdict(set) + for k, v in state_dict.items(): + if ( + v.device != torch.device("meta") + and storage_ptr(v) != 0 + and storage_size(v) != 0 + ): + # Need to add device as key because of multiple GPU. + tensors[(v.device, storage_ptr(v), storage_size(v))].add(k) + tensors = list(sorted(tensors.values())) + tensors = _filter_shared_not_shared(tensors, state_dict) + return tensors + + +def _is_complete(tensor: torch.Tensor) -> bool: + return tensor.data_ptr() == storage_ptr(tensor) and tensor.nelement() * _SIZE[ + tensor.dtype + ] == storage_size(tensor) + + +def _remove_duplicate_names( + state_dict: Dict[str, torch.Tensor], + *, + preferred_names: Optional[List[str]] = None, + discard_names: Optional[List[str]] = None, +) -> Dict[str, List[str]]: + if preferred_names is None: + preferred_names = [] + preferred_names = set(preferred_names) + if discard_names is None: + discard_names = [] + discard_names = set(discard_names) + + shareds = _find_shared_tensors(state_dict) + to_remove = defaultdict(list) + for shared in shareds: + complete_names = set( + [name for name in shared if _is_complete(state_dict[name])] + ) + if not complete_names: + raise RuntimeError( + "Error while trying to find names to remove to save state dict, but found no suitable name to keep" + f" for saving amongst: {shared}. None is covering the entire storage.Refusing to save/load the model" + " since you could be storing much more memory than needed. Please refer to" + " https://huggingface.co/docs/safetensors/torch_shared_tensors for more information. Or open an" + " issue." + ) + + keep_name = sorted(list(complete_names))[0] + + # Mechanism to preferentially select keys to keep + # coming from the on-disk file to allow + # loading models saved with a different choice + # of keep_name + preferred = complete_names.difference(discard_names) + if preferred: + keep_name = sorted(list(preferred))[0] + + if preferred_names: + preferred = preferred_names.intersection(complete_names) + if preferred: + keep_name = sorted(list(preferred))[0] + for name in sorted(shared): + if name != keep_name: + to_remove[keep_name].append(name) + return to_remove + + +def save_model( + model: torch.nn.Module, + filename: str, + metadata: Optional[Dict[str, str]] = None, + force_contiguous: bool = True, +): + """ + Saves a given torch model to specified filename. + This method exists specifically to avoid tensor sharing issues which are + not allowed in `safetensors`. [More information on tensor sharing](../torch_shared_tensors) + + Args: + model (`torch.nn.Module`): + The model to save on disk. + filename (`str`): + The filename location to save the file + metadata (`Dict[str, str]`, *optional*): + Extra information to save along with the file. + Some metadata will be added for each dropped tensors. + This information will not be enough to recover the entire + shared structure but might help understanding things + force_contiguous (`boolean`, *optional*, defaults to True): + Forcing the state_dict to be saved as contiguous tensors. + This has no effect on the correctness of the model, but it + could potentially change performance if the layout of the tensor + was chosen specifically for that reason. + """ + state_dict = model.state_dict() + to_removes = _remove_duplicate_names(state_dict) + + for kept_name, to_remove_group in to_removes.items(): + for to_remove in to_remove_group: + if metadata is None: + metadata = {} + + if to_remove not in metadata: + # Do not override user data + metadata[to_remove] = kept_name + del state_dict[to_remove] + if force_contiguous: + state_dict = {k: v.contiguous() for k, v in state_dict.items()} + try: + save_file(state_dict, filename, metadata=metadata) + except ValueError as e: + msg = str(e) + msg += " Or use save_model(..., force_contiguous=True), read the docs for potential caveats." + raise ValueError(msg) + + +def load_model( + model: torch.nn.Module, + filename: Union[str, os.PathLike], + strict: bool = True, + device: Union[str, int] = "cpu", +) -> Tuple[List[str], List[str]]: + """ + Loads a given filename onto a torch model. + This method exists specifically to avoid tensor sharing issues which are + not allowed in `safetensors`. [More information on tensor sharing](../torch_shared_tensors) + + Args: + model (`torch.nn.Module`): + The model to load onto. + filename (`str`, or `os.PathLike`): + The filename location to load the file from. + strict (`bool`, *optional*, defaults to True): + Whether to fail if you're missing keys or having unexpected ones. + When false, the function simply returns missing and unexpected names. + device (`Union[str, int]`, *optional*, defaults to `cpu`): + The device where the tensors need to be located after load. + available options are all regular torch device locations. + + Returns: + `(missing, unexpected): (List[str], List[str])` + `missing` are names in the model which were not modified during loading + `unexpected` are names that are on the file, but weren't used during + the load. + """ + state_dict = load_file(filename, device=device) + model_state_dict = model.state_dict() + to_removes = _remove_duplicate_names( + model_state_dict, preferred_names=state_dict.keys() + ) + missing, unexpected = model.load_state_dict(state_dict, strict=False) + missing = set(missing) + for to_remove_group in to_removes.values(): + for to_remove in to_remove_group: + if to_remove not in missing: + unexpected.append(to_remove) + else: + missing.remove(to_remove) + if strict and (missing or unexpected): + missing_keys = ", ".join([f'"{k}"' for k in sorted(missing)]) + unexpected_keys = ", ".join([f'"{k}"' for k in sorted(unexpected)]) + error = f"Error(s) in loading state_dict for {model.__class__.__name__}:" + if missing: + error += f"\n Missing key(s) in state_dict: {missing_keys}" + if unexpected: + error += f"\n Unexpected key(s) in state_dict: {unexpected_keys}" + raise RuntimeError(error) + return missing, unexpected + + +def save( + tensors: Dict[str, torch.Tensor], metadata: Optional[Dict[str, str]] = None +) -> bytes: + """ + Saves a dictionary of tensors into raw bytes in safetensors format. + + Args: + tensors (`Dict[str, torch.Tensor]`): + The incoming tensors. Tensors need to be contiguous and dense. + metadata (`Dict[str, str]`, *optional*, defaults to `None`): + Optional text only metadata you might want to save in your header. + For instance it can be useful to specify more about the underlying + tensors. This is purely informative and does not affect tensor loading. + + Returns: + `bytes`: The raw bytes representing the format + + Example: + + ```python + from safetensors.torch import save + import torch + + tensors = {"embedding": torch.zeros((512, 1024)), "attention": torch.zeros((256, 256))} + byte_data = save(tensors) + ``` + """ + serialized = serialize(_flatten(tensors), metadata=metadata) + result = bytes(serialized) + return result + + +def save_file( + tensors: Dict[str, torch.Tensor], + filename: Union[str, os.PathLike], + metadata: Optional[Dict[str, str]] = None, +): + """ + Saves a dictionary of tensors into raw bytes in safetensors format. + + Args: + tensors (`Dict[str, torch.Tensor]`): + The incoming tensors. Tensors need to be contiguous and dense. + filename (`str`, or `os.PathLike`)): + The filename we're saving into. + metadata (`Dict[str, str]`, *optional*, defaults to `None`): + Optional text only metadata you might want to save in your header. + For instance it can be useful to specify more about the underlying + tensors. This is purely informative and does not affect tensor loading. + + Returns: + `None` + + Example: + + ```python + from safetensors.torch import save_file + import torch + + tensors = {"embedding": torch.zeros((512, 1024)), "attention": torch.zeros((256, 256))} + save_file(tensors, "model.safetensors") + ``` + """ + serialize_file(_flatten(tensors), filename, metadata=metadata) + + +def load_file( + filename: Union[str, os.PathLike], device: Union[str, int] = "cpu" +) -> Dict[str, torch.Tensor]: + """ + Loads a safetensors file into torch format. + + Args: + filename (`str`, or `os.PathLike`): + The name of the file which contains the tensors + device (`Union[str, int]`, *optional*, defaults to `cpu`): + The device where the tensors need to be located after load. + available options are all regular torch device locations. + + Returns: + `Dict[str, torch.Tensor]`: dictionary that contains name as key, value as `torch.Tensor` + + Example: + + ```python + from safetensors.torch import load_file + + file_path = "./my_folder/bert.safetensors" + loaded = load_file(file_path) + ``` + """ + result = {} + with safe_open(filename, framework="pt", device=device) as f: + for k in f.offset_keys(): + result[k] = f.get_tensor(k) + return result + + +def load(data: bytes) -> Dict[str, torch.Tensor]: + """ + Loads a safetensors file into torch format from pure bytes. + + Args: + data (`bytes`): + The content of a safetensors file + + Returns: + `Dict[str, torch.Tensor]`: dictionary that contains name as key, value as `torch.Tensor` on cpu + + Example: + + ```python + from safetensors.torch import load + + file_path = "./my_folder/bert.safetensors" + with open(file_path, "rb") as f: + data = f.read() + + loaded = load(data) + ``` + """ + flat = deserialize(data) + return _view2torch(flat) + + +# torch.float8 formats require 2.1; we do not support these dtypes on earlier versions +_float8_e4m3fn = getattr(torch, "float8_e4m3fn", None) +_float8_e5m2 = getattr(torch, "float8_e5m2", None) +_float8_e8m0 = getattr(torch, "float8_e8m0fnu", None) +_float4_e2m1_x2 = getattr(torch, "float4_e2m1fn_x2", None) + +_SIZE = { + torch.int64: 8, + torch.float32: 4, + torch.int32: 4, + torch.bfloat16: 2, + torch.float16: 2, + torch.int16: 2, + torch.uint8: 1, + torch.int8: 1, + torch.bool: 1, + torch.float64: 8, + torch.complex64: 8, + _float8_e4m3fn: 1, + _float8_e5m2: 1, + _float8_e8m0: 1, + _float4_e2m1_x2: 1, +} +if Version(torch.__version__) >= Version("2.3.0"): + _SIZE.update( + { + torch.uint64: 8, + torch.uint32: 4, + torch.uint16: 2, + } + ) + +_TYPES = { + "F64": torch.float64, + "F32": torch.float32, + "F16": torch.float16, + "BF16": torch.bfloat16, + "I64": torch.int64, + "I32": torch.int32, + "I16": torch.int16, + "I8": torch.int8, + "U8": torch.uint8, + "BOOL": torch.bool, + "F8_E4M3": _float8_e4m3fn, + "F8_E5M2": _float8_e5m2, + "C64": torch.complex64, +} +if Version(torch.__version__) >= Version("2.3.0"): + _TYPES.update( + { + "U64": torch.uint64, + "U32": torch.uint32, + "U16": torch.uint16, + } + ) + + +def _getdtype(dtype_str: str) -> torch.dtype: + return _TYPES[dtype_str] + + +def _view2torch(safeview) -> Dict[str, torch.Tensor]: + result = {} + for k, v in safeview: + dtype = _getdtype(v["dtype"]) + if len(v["data"]) == 0: + # Workaround because frombuffer doesn't accept zero-size tensors + assert any(x == 0 for x in v["shape"]) + arr = torch.empty(v["shape"], dtype=dtype) + else: + arr = torch.frombuffer(v["data"], dtype=dtype).reshape(v["shape"]) + if sys.byteorder == "big": + arr = torch.from_numpy(arr.numpy().byteswap(inplace=False)) + result[k] = arr + + return result + + +def _tobytes(tensor: torch.Tensor, name: str) -> bytes: + if tensor.layout != torch.strided: + raise ValueError( + f"You are trying to save a sparse tensor: `{name}` which this library does not support." + " You can make it a dense tensor before saving with `.to_dense()` but be aware this might" + " make a much larger file than needed." + ) + + if not tensor.is_contiguous(): + raise ValueError( + f"You are trying to save a non contiguous tensor: `{name}` which is not allowed. It either means you" + " are trying to save tensors which are reference of each other in which case it's recommended to save" + " only the full tensors, and reslice at load time, or simply call `.contiguous()` on your tensor to" + " pack it before saving." + ) + if tensor.device.type != "cpu": + # Moving tensor to cpu before saving + tensor = tensor.to("cpu") + + import ctypes + + import numpy as np + + # When shape is empty (scalar), np.prod returns a float + # we need a int for the following calculations + length = int(np.prod(tensor.shape).item()) + bytes_per_item = _SIZE[tensor.dtype] + + total_bytes = length * bytes_per_item + + ptr = tensor.data_ptr() + if ptr == 0: + return b"" + newptr = ctypes.cast(ptr, ctypes.POINTER(ctypes.c_ubyte)) + data = np.ctypeslib.as_array(newptr, (total_bytes,)) # no internal copy + if sys.byteorder == "big": + NPDTYPES = { + torch.int64: np.int64, + torch.float32: np.float32, + torch.int32: np.int32, + # XXX: This is ok because both have the same width + torch.bfloat16: np.float16, + torch.float16: np.float16, + torch.int16: np.int16, + torch.uint8: np.uint8, + torch.int8: np.int8, + torch.bool: bool, + torch.float64: np.float64, + # XXX: This is ok because both have the same width and byteswap is a no-op anyway + _float8_e4m3fn: np.uint8, + _float8_e5m2: np.uint8, + torch.complex64: np.complex64, + } + npdtype = NPDTYPES[tensor.dtype] + # Not in place as that would potentially modify a live running model + data = data.view(npdtype).byteswap(inplace=False) + return data.tobytes() + + +def _flatten(tensors: Dict[str, torch.Tensor]) -> Dict[str, Dict[str, Any]]: + if not isinstance(tensors, dict): + raise ValueError( + f"Expected a dict of [str, torch.Tensor] but received {type(tensors)}" + ) + + invalid_tensors = [] + for k, v in tensors.items(): + if not isinstance(v, torch.Tensor): + raise ValueError( + f"Key `{k}` is invalid, expected torch.Tensor but received {type(v)}" + ) + + if v.layout != torch.strided: + invalid_tensors.append(k) + if invalid_tensors: + raise ValueError( + f"You are trying to save a sparse tensors: `{invalid_tensors}` which this library does not support." + " You can make it a dense tensor before saving with `.to_dense()` but be aware this might" + " make a much larger file than needed." + ) + + shared_pointers = _find_shared_tensors(tensors) + failing = [] + for names in shared_pointers: + if len(names) > 1: + failing.append(names) + + if failing: + raise RuntimeError( + f""" + Some tensors share memory, this will lead to duplicate memory on disk and potential differences when loading them again: {failing}. + A potential way to correctly save your model is to use `save_model`. + More information at https://huggingface.co/docs/safetensors/torch_shared_tensors + """ + ) + + return { + k: { + "dtype": str(v.dtype).split(".")[-1], + "shape": v.shape, + "data": _tobytes(v, k), + } + for k, v in tensors.items() + } diff --git a/scipy-1.17.1.dist-info/INSTALLER b/scipy-1.17.1.dist-info/INSTALLER new file mode 100644 index 0000000000000000000000000000000000000000..5c69047b2eb8235994febeeae1da4a82365a240a --- /dev/null +++ b/scipy-1.17.1.dist-info/INSTALLER @@ -0,0 +1 @@ +uv \ No newline at end of file diff --git a/scipy-1.17.1.dist-info/LICENSE.txt b/scipy-1.17.1.dist-info/LICENSE.txt new file mode 100644 index 0000000000000000000000000000000000000000..189ca4227f9abe0cebe5e64e163f8df4a9a2240c --- /dev/null +++ b/scipy-1.17.1.dist-info/LICENSE.txt @@ -0,0 +1,934 @@ +Copyright (c) 2001-2002 Enthought, Inc. 2003, SciPy Developers. +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions +are met: + +1. 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If your program is a subroutine library, you + may consider it more useful to permit linking proprietary applications with + the library. If this is what you want to do, use the GNU Lesser General + Public License instead of this License. But first, please read + . + + + Name: libquadmath + Files: scipy.libs/libquadmath*.so + Description: dynamically linked to files compiled with gcc + Availability: https://gcc.gnu.org/git/?p=gcc.git;a=tree;f=libquadmath + License: LGPL-2.1-or-later + + GCC Quad-Precision Math Library + Copyright (C) 2010-2019 Free Software Foundation, Inc. + Written by Francois-Xavier Coudert + + This file is part of the libquadmath library. + Libquadmath is free software; you can redistribute it and/or + modify it under the terms of the GNU Library General Public + License as published by the Free Software Foundation; either + version 2.1 of the License, or (at your option) any later version. + + Libquadmath is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU + Lesser General Public License for more details. + https://www.gnu.org/licenses/old-licenses/lgpl-2.1.html + +Classifier: Development Status :: 5 - Production/Stable +Classifier: Intended Audience :: Science/Research +Classifier: Intended Audience :: Developers +Classifier: License :: OSI Approved :: BSD License +Classifier: Programming Language :: C +Classifier: Programming Language :: Python +Classifier: Programming Language :: Python :: 3 +Classifier: Programming Language :: Python :: 3.11 +Classifier: Programming Language :: Python :: 3.12 +Classifier: Programming Language :: Python :: 3.13 +Classifier: Programming Language :: Python :: 3.14 +Classifier: Topic :: Software Development :: Libraries +Classifier: Topic :: Scientific/Engineering +Classifier: Operating System :: Microsoft :: Windows +Classifier: Operating System :: POSIX :: Linux +Classifier: Operating System :: POSIX +Classifier: Operating System :: Unix +Classifier: Operating System :: MacOS +Project-URL: homepage, https://scipy.org/ +Project-URL: documentation, https://docs.scipy.org/doc/scipy/ +Project-URL: source, https://github.com/scipy/scipy +Project-URL: download, https://github.com/scipy/scipy/releases +Project-URL: tracker, https://github.com/scipy/scipy/issues +Requires-Python: >=3.11 +Requires-Dist: numpy<2.7,>=1.26.4 +Provides-Extra: test +Requires-Dist: pytest>=8.0.0; extra == "test" +Requires-Dist: pytest-cov; extra == "test" +Requires-Dist: pytest-timeout; extra == "test" +Requires-Dist: pytest-xdist; extra == "test" +Requires-Dist: asv; extra == "test" +Requires-Dist: mpmath; extra == "test" +Requires-Dist: gmpy2; extra == "test" +Requires-Dist: threadpoolctl; extra == "test" +Requires-Dist: scikit-umfpack; extra == "test" +Requires-Dist: pooch; extra == "test" +Requires-Dist: hypothesis>=6.30; extra == "test" +Requires-Dist: array-api-strict>=2.3.1; extra == "test" +Requires-Dist: Cython; extra == "test" +Requires-Dist: meson; extra == "test" +Requires-Dist: ninja; sys_platform != "emscripten" and extra == "test" +Provides-Extra: doc +Requires-Dist: sphinx<8.2.0,>=5.0.0; extra == "doc" +Requires-Dist: intersphinx_registry; extra == "doc" +Requires-Dist: pydata-sphinx-theme>=0.15.2; extra == "doc" +Requires-Dist: sphinx-copybutton; extra == "doc" +Requires-Dist: sphinx-design>=0.4.0; extra == "doc" +Requires-Dist: matplotlib>=3.5; extra == "doc" +Requires-Dist: numpydoc; extra == "doc" +Requires-Dist: jupytext; extra == "doc" +Requires-Dist: myst-nb>=1.2.0; extra == "doc" +Requires-Dist: pooch; extra == "doc" +Requires-Dist: jupyterlite-sphinx>=0.19.1; extra == "doc" +Requires-Dist: jupyterlite-pyodide-kernel; extra == "doc" +Requires-Dist: linkify-it-py; extra == "doc" +Requires-Dist: tabulate; extra == "doc" +Provides-Extra: dev +Requires-Dist: click<8.3.0; extra == "dev" +Requires-Dist: spin; extra == "dev" +Requires-Dist: mypy==1.10.0; extra == "dev" +Requires-Dist: typing_extensions; extra == "dev" +Requires-Dist: types-psutil; extra == "dev" +Requires-Dist: pycodestyle; extra == "dev" +Requires-Dist: ruff>=0.12.0; extra == "dev" +Requires-Dist: cython-lint>=0.12.2; extra == "dev" +Description-Content-Type: text/x-rst + +.. image:: https://raw.githubusercontent.com/scipy/scipy/main/doc/source/_static/logo.svg + :target: https://scipy.org + :width: 110 + :height: 110 + :align: left + +.. image:: https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A + :target: https://numfocus.org + +.. image:: https://img.shields.io/pypi/dm/scipy.svg?label=Pypi%20downloads + :target: https://pypi.org/project/scipy/ + +.. image:: https://img.shields.io/conda/dn/conda-forge/scipy.svg?label=Conda%20downloads + :target: https://anaconda.org/conda-forge/scipy + +.. image:: https://img.shields.io/badge/stackoverflow-Ask%20questions-blue.svg + :target: https://stackoverflow.com/questions/tagged/scipy + +.. image:: https://img.shields.io/badge/DOI-10.1038%2Fs41592--019--0686--2-blue.svg + :target: https://www.nature.com/articles/s41592-019-0686-2 + +.. image:: https://insights.linuxfoundation.org/api/badge/health-score?project=scipy + :target: https://insights.linuxfoundation.org/project/scipy + +SciPy (pronounced "Sigh Pie") is an open-source software for mathematics, +science, and engineering. It includes modules for statistics, optimization, +integration, linear algebra, Fourier transforms, signal and image processing, +ODE solvers, and more. + +- **Website:** https://scipy.org +- **Documentation:** https://docs.scipy.org/doc/scipy/ +- **Development version of the documentation:** https://scipy.github.io/devdocs +- **SciPy development forum:** https://discuss.scientific-python.org/c/contributor/scipy +- **Stack Overflow:** https://stackoverflow.com/questions/tagged/scipy +- **Source code:** https://github.com/scipy/scipy +- **Contributing:** https://scipy.github.io/devdocs/dev/index.html +- **Bug reports:** https://github.com/scipy/scipy/issues +- **Code of Conduct:** https://docs.scipy.org/doc/scipy/dev/conduct/code_of_conduct.html +- **Report a security vulnerability:** https://tidelift.com/docs/security +- **Citing in your work:** https://www.scipy.org/citing-scipy/ + +SciPy is built to work with +NumPy arrays, and provides many user-friendly and efficient numerical routines, +such as routines for numerical integration and optimization. Together, they +run on all popular operating systems, are quick to install, and are free of +charge. NumPy and SciPy are easy to use, but powerful enough to be depended +upon by some of the world's leading scientists and engineers. If you need to +manipulate numbers on a computer and display or publish the results, give +SciPy a try! + +For the installation instructions, see `our install +guide `__. + + +Call for Contributions +---------------------- + +We appreciate and welcome contributions. Small improvements or fixes are always appreciated; issues labeled as "good +first issue" may be a good starting point. Have a look at `our contributing +guide `__. + +Writing code isn’t the only way to contribute to SciPy. You can also: + +- review pull requests +- triage issues +- develop tutorials, presentations, and other educational materials +- maintain and improve `our website `__ +- develop graphic design for our brand assets and promotional materials +- help with outreach and onboard new contributors +- write grant proposals and help with other fundraising efforts + +If you’re unsure where to start or how your skills fit in, reach out! You can +ask on the `forum `__ +or here, on GitHub, by leaving a comment on a relevant issue that is already +open. + +If you are new to contributing to open source, `this +guide `__ helps explain why, what, +and how to get involved. diff --git a/scipy-1.17.1.dist-info/RECORD b/scipy-1.17.1.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..ca329329dad4fd2950258f55f3d0e732535d974c --- /dev/null +++ b/scipy-1.17.1.dist-info/RECORD @@ -0,0 +1,1427 @@ +scipy-1.17.1.dist-info/INSTALLER,sha256=5hhM4Q4mYTT9z6QB6PGpUAW81PGNFrYrdXMj4oM_6ak,2 +scipy-1.17.1.dist-info/LICENSE.txt,sha256=Ta8U43Qy5wJhZZeey3o5kwcHo-ib70h2z6-drTbtNko,46838 +scipy-1.17.1.dist-info/METADATA,sha256=fN1VROthC4bgALbwoh6G-EQj-vCqy7mZkPPUHyXh8xQ,62142 +scipy-1.17.1.dist-info/RECORD,, +scipy-1.17.1.dist-info/REQUESTED,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0 +scipy-1.17.1.dist-info/WHEEL,sha256=rJCplGeGFjRoUvxJWhVONRgyGYGZoOkhyej0s3KyjoI,138 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0000000000000000000000000000000000000000..8e8a09f81ee274a67208d44d2b799643ee85d5fe --- /dev/null +++ b/scipy/__config__.py @@ -0,0 +1,173 @@ +# This file is generated by SciPy's build process +# It contains system_info results at the time of building this package. +from enum import Enum + +__all__ = ["show"] +_built_with_meson = True + + +class DisplayModes(Enum): + stdout = "stdout" + dicts = "dicts" + + +def _cleanup(d): + """ + Removes empty values in a `dict` recursively + This ensures we remove values that Meson could not provide to CONFIG + """ + if isinstance(d, dict): + return { k: _cleanup(v) for k, v in d.items() if v != '' and _cleanup(v) != '' } + else: + return d + + +CONFIG = _cleanup( + { + "Compilers": { + "c": { + "name": "gcc", + "linker": r"ld.bfd", + "version": "14.2.1", + "commands": r"cc", + "args": r"", + "linker args": r"", + }, + "cython": { + "name": r"cython", + "linker": r"cython", + "version": r"3.2.4", + "commands": r"cython", + "args": r"", + "linker args": r"", + }, + "c++": { + "name": "gcc", + "linker": r"ld.bfd", + "version": "14.2.1", + "commands": r"c++", + "args": r"", + "linker args": r"", + }, + "fortran": { + "name": "gcc", + "linker": r"ld.bfd", + "version": "14.2.1", + "commands": r"gfortran", + "args": r"", + "linker args": r"", + }, + "pythran": { + "version": r"0.18.1", + "include directory": r"../../tmp/build-env-l4psv2j0/lib/python3.12/site-packages/pythran" + }, + }, + "Machine Information": { + "host": { + "cpu": r"x86_64", + "family": r"x86_64", + "endian": r"little", + "system": r"linux", + }, + "build": { + "cpu": r"x86_64", + "family": r"x86_64", + "endian": r"little", + "system": r"linux", + }, + "cross-compiled": bool("False".lower().replace('false', '')), + }, + "Build Dependencies": { + "blas": { + "name": "scipy-openblas", + "found": bool("True".lower().replace('false', '')), + "version": "0.3.30", + "detection method": "pkgconfig", + "include directory": r"/opt/_internal/cpython-3.12.11/lib/python3.12/site-packages/scipy_openblas32/include", + "lib directory": r"/opt/_internal/cpython-3.12.11/lib/python3.12/site-packages/scipy_openblas32/lib", + "openblas configuration": r"OpenBLAS 0.3.30 DYNAMIC_ARCH NO_AFFINITY Haswell MAX_THREADS=64", + "pc file directory": r"/project/", + "has ilp64": bool(r"False".lower().replace('false', '')), + }, + "lapack": { + "name": "scipy-openblas", + "found": bool("True".lower().replace('false', '')), + "version": "0.3.30", + "detection method": "pkgconfig", + "include directory": r"/opt/_internal/cpython-3.12.11/lib/python3.12/site-packages/scipy_openblas32/include", + "lib directory": r"/opt/_internal/cpython-3.12.11/lib/python3.12/site-packages/scipy_openblas32/lib", + "openblas configuration": r"OpenBLAS 0.3.30 DYNAMIC_ARCH NO_AFFINITY Haswell MAX_THREADS=64", + "pc file directory": r"/project/", + "has ilp64": bool(r"False".lower().replace('false', '')), + }, + "pybind11": { + "name": "pybind11", + "version": "3.0.2", + "detection method": "config-tool", + "include directory": r"unknown", + }, + }, + "Python Information": { + "path": r"/tmp/build-env-l4psv2j0/bin/python", + "version": "3.12", + }, + } +) + + +def _check_pyyaml(): + import yaml + + return yaml + + +def show(mode=DisplayModes.stdout.value): + """ + Show libraries and system information on which SciPy was built + and is being used + + Parameters + ---------- + mode : {`'stdout'`, `'dicts'`}, optional. + Indicates how to display the config information. + `'stdout'` prints to console, `'dicts'` returns a dictionary + of the configuration. + + Returns + ------- + out : {`dict`, `None`} + If mode is `'dicts'`, a dict is returned, else None + + Examples + -------- + >>> import scipy + >>> scipy.show_config() + ... # formatted output is printed to the console + + >>> config_dict = scipy.show_config(mode='dicts') + >>> list(config_dict.keys()) + ['Compilers', 'Machine Information', 'Build Dependencies', 'Python Information'] + + Notes + ----- + 1. The `'stdout'` mode will give more readable + output if ``pyyaml`` is installed + + """ + if mode == DisplayModes.stdout.value: + try: # Non-standard library, check import + yaml = _check_pyyaml() + + print(yaml.dump(CONFIG)) + except ModuleNotFoundError: + import warnings + import json + + warnings.warn("Install `pyyaml` for better output", stacklevel=1) + print(json.dumps(CONFIG, indent=2)) + elif mode == DisplayModes.dicts.value: + return CONFIG + else: + raise AttributeError( + f"Invalid `mode`, use one of: {', '.join([e.value for e in DisplayModes])}" + ) diff --git a/scipy/__init__.py b/scipy/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..cbbe00ea4b7187aa9768a15ef2ef1dd7ef5a48c3 --- /dev/null +++ b/scipy/__init__.py @@ -0,0 +1,138 @@ +""" +SciPy: A scientific computing package for Python +================================================ + +Documentation is available in the docstrings and +online at https://docs.scipy.org/doc/scipy/ + +Subpackages +----------- +:: + + cluster --- Vector Quantization / Kmeans + constants --- Physical and mathematical constants and units + datasets --- Dataset methods + differentiate --- Finite difference differentiation tools + fft --- Discrete Fourier transforms + fftpack --- Legacy discrete Fourier transforms + integrate --- Integration routines + interpolate --- Interpolation Tools + io --- Data input and output + linalg --- Linear algebra routines + ndimage --- N-D image package + odr --- Orthogonal Distance Regression + optimize --- Optimization Tools + signal --- Signal Processing Tools + sparse --- Sparse Matrices + spatial --- Spatial data structures and algorithms + special --- Special functions + stats --- Statistical Functions + +Public API in the main SciPy namespace +-------------------------------------- +:: + + __version__ --- SciPy version string + LowLevelCallable --- Low-level callback function + show_config --- Show scipy build configuration + test --- Run scipy unittests + +""" + +import importlib as _importlib + +from numpy import __version__ as __numpy_version__ + + +try: + from scipy.__config__ import show as show_config +except ImportError as e: + msg = """Error importing SciPy: you cannot import SciPy while + being in scipy source directory; please exit the SciPy source + tree first and relaunch your Python interpreter.""" + raise ImportError(msg) from e + + +from scipy.version import version as __version__ + + +# Allow distributors to run custom init code +from . import _distributor_init +del _distributor_init + + +from scipy._lib import _pep440 +# In maintenance branch, change to np_maxversion N+3 if numpy is at N +np_minversion = '1.26.4' +np_maxversion = '2.7.0' +if (_pep440.parse(__numpy_version__) < _pep440.Version(np_minversion) or + _pep440.parse(__numpy_version__) >= _pep440.Version(np_maxversion)): + import warnings + warnings.warn(f"A NumPy version >={np_minversion} and <{np_maxversion}" + f" is required for this version of SciPy (detected " + f"version {__numpy_version__})", + UserWarning, stacklevel=2) +del _pep440 + + +# This is the first import of an extension module within SciPy. If there's +# a general issue with the install, such that extension modules are missing +# or cannot be imported, this is where we'll get a failure - so give an +# informative error message. +try: + from scipy._lib._ccallback import LowLevelCallable +except ImportError as e: + msg = "The `scipy` install you are using seems to be broken, " + \ + "(extension modules cannot be imported), " + \ + "please try reinstalling." + raise ImportError(msg) from e + + +from scipy._lib._testutils import PytestTester +test = PytestTester(__name__) +del PytestTester + + +submodules = [ + 'cluster', + 'constants', + 'datasets', + 'differentiate', + 'fft', + 'fftpack', + 'integrate', + 'interpolate', + 'io', + 'linalg', + 'ndimage', + 'odr', + 'optimize', + 'signal', + 'sparse', + 'spatial', + 'special', + 'stats' +] + +__all__ = submodules + [ + 'LowLevelCallable', + 'test', + 'show_config', + '__version__', +] + + +def __dir__(): + return __all__ + + +def __getattr__(name): + if name in submodules: + return _importlib.import_module(f'scipy.{name}') + else: + try: + return globals()[name] + except KeyError: + raise AttributeError( + f"Module 'scipy' has no attribute '{name}'" + ) diff --git a/scipy/_distributor_init.py b/scipy/_distributor_init.py new file mode 100644 index 0000000000000000000000000000000000000000..5df134975aa27d31beaff74c3cbfd2d3fb0a55dd --- /dev/null +++ b/scipy/_distributor_init.py @@ -0,0 +1,18 @@ +""" Distributor init file + +Distributors: you can replace the contents of this file with your own custom +code to support particular distributions of SciPy. + +For example, this is a good place to put any checks for hardware requirements +or BLAS/LAPACK library initialization. + +The SciPy standard source distribution will not put code in this file beyond +the try-except import of `_distributor_init_local` (which is not part of a +standard source distribution), so you can safely replace this file with your +own version. +""" + +try: + from . import _distributor_init_local # noqa: F401 +except ImportError: + pass diff --git a/scipy/conftest.py b/scipy/conftest.py new file mode 100644 index 0000000000000000000000000000000000000000..63676695bf6388f931acfc4374d770c0cac0e902 --- /dev/null +++ b/scipy/conftest.py @@ -0,0 +1,708 @@ +# Pytest customization +import json +import multiprocessing +import os +import sys +import warnings +import tempfile +from contextlib import contextmanager +from typing import Literal + +import numpy as np +import pytest +try: + import hypothesis + hypothesis_available = True +except ImportError: + hypothesis_available = False + +from scipy._lib._fpumode import get_fpu_mode +from scipy._lib._array_api import ( + SCIPY_ARRAY_API, SCIPY_DEVICE, array_namespace, default_xp, + is_cupy, is_dask, is_jax, is_torch, +) +from scipy._lib._testutils import FPUModeChangeWarning +from scipy._lib.array_api_extra.testing import patch_lazy_xp_functions +from scipy._lib import _pep440 + +try: + from scipy_doctest.conftest import dt_config + HAVE_SCPDT = True +except ModuleNotFoundError: + HAVE_SCPDT = False + +try: + import pytest_run_parallel # noqa:F401 + PARALLEL_RUN_AVAILABLE = True +except Exception: + PARALLEL_RUN_AVAILABLE = False + + +def pytest_configure(config): + """ + Add pytest markers to avoid PytestUnknownMarkWarning + + This needs to contain all markers that are SciPy-specific, as well as + dummy fallbacks for markers defined in optional test packages. + + Note that we need both the registration here *and* in `pytest.ini`. + """ + config.addinivalue_line("markers", + "slow: Tests that are very slow.") + config.addinivalue_line("markers", + "xslow: mark test as extremely slow (not run unless explicitly requested)") + config.addinivalue_line("markers", + "xfail_on_32bit: mark test as failing on 32-bit platforms") + config.addinivalue_line("markers", + "array_api_backends: test iterates on all array API backends") + config.addinivalue_line("markers", + ("skip_xp_backends(backends, reason=None, np_only=False, cpu_only=False, " + + "eager_only=False, exceptions=None): mark the desired skip configuration " + + "for the `skip_xp_backends` fixture")) + config.addinivalue_line("markers", + ("xfail_xp_backends(backends, reason=None, np_only=False, cpu_only=False, " + + "eager_only=False, exceptions=None): mark the desired xfail configuration " + + "for the `xfail_xp_backends` fixture")) + + try: + import pytest_timeout # noqa:F401 + except Exception: + config.addinivalue_line( + "markers", 'timeout: mark a test for a non-default timeout') + try: + # This is a more reliable test of whether pytest_fail_slow is installed + # When I uninstalled it, `import pytest_fail_slow` didn't fail! + from pytest_fail_slow import parse_duration # type: ignore[import-not-found] # noqa:F401,E501 + except Exception: + config.addinivalue_line( + "markers", 'fail_slow: mark a test for a non-default timeout failure') + + if not PARALLEL_RUN_AVAILABLE: + config.addinivalue_line( + 'markers', + 'parallel_threads_limit(n): run the given test function in parallel ' + 'using `n` threads.') + config.addinivalue_line( + "markers", + "thread_unsafe: mark the test function as single-threaded", + ) + config.addinivalue_line( + "markers", + "iterations(n): run the given test function `n` times in each thread", + ) + + if os.name == 'posix' and sys.version_info < (3, 14): + # On POSIX, Python 3.13 and older uses the 'fork' context by + # default. Calling fork() from multiple threads leads to + # deadlocks. This has been changed in 3.14 to 'forkserver'. + multiprocessing.set_start_method('forkserver', force=True) + + +def pytest_runtest_setup(item): + mark = item.get_closest_marker("xslow") + if mark is not None: + try: + v = int(os.environ.get('SCIPY_XSLOW', '0')) + except ValueError: + v = False + if not v: + pytest.skip("very slow test; " + "set environment variable SCIPY_XSLOW=1 to run it") + mark = item.get_closest_marker("xfail_on_32bit") + if mark is not None and np.intp(0).itemsize < 8: + pytest.xfail(f'Fails on our 32-bit test platform(s): {mark.args[0]}') + + # Older versions of threadpoolctl have an issue that may lead to this + # warning being emitted, see gh-14441 + with warnings.catch_warnings(): + warnings.simplefilter("ignore", pytest.PytestUnraisableExceptionWarning) + + try: + from threadpoolctl import threadpool_limits + + HAS_THREADPOOLCTL = True + except Exception: # observed in gh-14441: (ImportError, AttributeError) + # Optional dependency only. All exceptions are caught, for robustness + HAS_THREADPOOLCTL = False + + if HAS_THREADPOOLCTL: + # Set the number of openmp threads based on the number of workers + # xdist is using to prevent oversubscription. Simplified version of what + # sklearn does (it can rely on threadpoolctl and its builtin OpenMP helper + # functions) + try: + xdist_worker_count = int(os.environ['PYTEST_XDIST_WORKER_COUNT']) + except KeyError: + # raises when pytest-xdist is not installed + return + + if not os.getenv('OMP_NUM_THREADS'): + max_openmp_threads = os.cpu_count() // 2 # use nr of physical cores + threads_per_worker = max(max_openmp_threads // xdist_worker_count, 1) + try: + threadpool_limits(threads_per_worker, user_api='blas') + except Exception: + # May raise AttributeError for older versions of OpenBLAS. + # Catch any error for robustness. + return + + +@pytest.fixture(scope="function", autouse=True) +def check_fpu_mode(request): + """ + Check FPU mode was not changed during the test. + """ + old_mode = get_fpu_mode() + yield + new_mode = get_fpu_mode() + + if old_mode != new_mode: + warnings.warn(f"FPU mode changed from {old_mode:#x} to {new_mode:#x} during " + "the test", + category=FPUModeChangeWarning, stacklevel=0) + + +if not PARALLEL_RUN_AVAILABLE: + @pytest.fixture + def num_parallel_threads(): + return 1 + + +# Array API backend handling +xp_known_backends = {'numpy', 'array_api_strict', 'torch', 'cupy', 'jax.numpy', + 'dask.array'} +xp_available_backends = [ + pytest.param(np, id='numpy', marks=pytest.mark.array_api_backends) +] +xp_skip_cpu_only_backends = set() +xp_skip_eager_only_backends = set() + +if SCIPY_ARRAY_API: + # fill the dict of backends with available libraries + try: + import array_api_strict + xp_available_backends.append( + pytest.param(array_api_strict, id='array_api_strict', + marks=pytest.mark.array_api_backends)) + if _pep440.parse(array_api_strict.__version__) < _pep440.Version('2.3'): + raise ImportError("array-api-strict must be >= version 2.3") + array_api_strict.set_array_api_strict_flags( + api_version='2024.12' + ) + except ImportError: + pass + + try: + import torch # type: ignore[import-not-found] + xp_available_backends.append( + pytest.param(torch, id='torch', + marks=pytest.mark.array_api_backends)) + torch.set_default_device(SCIPY_DEVICE) + if SCIPY_DEVICE != "cpu": + xp_skip_cpu_only_backends.add('torch') + + # default to float64 unless explicitly requested + default = os.getenv('SCIPY_DEFAULT_DTYPE', default='float64') + if default == 'float64': + torch.set_default_dtype(torch.float64) + elif default != "float32": + raise ValueError( + "SCIPY_DEFAULT_DTYPE env var, if set, can only be either 'float64' " + f"or 'float32'. Got '{default}' instead." + ) + except ImportError: + pass + + try: + import cupy # type: ignore[import-not-found] + # Note: cupy disregards SCIPY_DEVICE and always runs on cuda. + # It will fail to import if you don't have CUDA hardware and drivers. + xp_available_backends.append( + pytest.param(cupy, id='cupy', + marks=pytest.mark.array_api_backends)) + xp_skip_cpu_only_backends.add('cupy') + + # this is annoying in CuPy 13.x + warnings.filterwarnings( + 'ignore', 'cupyx.jit.rawkernel is experimental', category=FutureWarning + ) + from cupyx.scipy import signal + del signal + except ImportError: + pass + + try: + import jax.numpy # type: ignore[import-not-found] + + xp_available_backends.append( + pytest.param(jax.numpy, id='jax.numpy', + marks=[pytest.mark.array_api_backends, + # Uses xpx.testing.patch_lazy_xp_functions to monkey-patch module + pytest.mark.thread_unsafe])) + + jax.config.update("jax_enable_x64", True) + jax.config.update("jax_default_device", jax.devices(SCIPY_DEVICE)[0]) + if SCIPY_DEVICE != "cpu": + xp_skip_cpu_only_backends.add('jax.numpy') + # JAX can be eager or lazy (when wrapped in jax.jit). However it is + # recommended by upstream devs to assume it's always lazy. + xp_skip_eager_only_backends.add('jax.numpy') + except ImportError: + pass + + try: + import dask.array as da + + xp_available_backends.append( + pytest.param(da, id='dask.array', + marks=[pytest.mark.array_api_backends, + # Uses xpx.testing.patch_lazy_xp_functions to monkey-patch module + pytest.mark.thread_unsafe])) + + # Dask can wrap around cupy. However, this is untested in scipy + # (and will almost surely not work as delegation will misbehave). + + # Dask, strictly speaking, can be eager, in the sense that + # __array__, __bool__ etc. are implemented and do not raise. + # However, calling them triggers an extra computation of the whole graph + # until that point, which is highly destructive for performance. + xp_skip_eager_only_backends.add('dask.array') + except ImportError: + pass + + xp_available_backend_ids = {p.id for p in xp_available_backends} + assert not xp_available_backend_ids - xp_known_backends + + # by default, use all available backends + if ( + isinstance(SCIPY_ARRAY_API, str) + and SCIPY_ARRAY_API.lower() not in ("1", "true", "all") + ): + SCIPY_ARRAY_API_ = set(json.loads(SCIPY_ARRAY_API)) + if SCIPY_ARRAY_API_ != {'all'}: + if SCIPY_ARRAY_API_ - xp_available_backend_ids: + msg = ("'--array-api-backend' must be in " + f"{xp_available_backend_ids}; got {SCIPY_ARRAY_API_}") + raise ValueError(msg) + # Only select a subset of backends + xp_available_backends = [ + param for param in xp_available_backends + if param.id in SCIPY_ARRAY_API_ + ] + + +@pytest.fixture(params=xp_available_backends) +def xp(request): + """Run the test that uses this fixture on each available array API library. + + You can select all and only the tests that use the `xp` fixture by + passing `-m array_api_backends` to pytest. + + You can select where individual tests run through the `@skip_xp_backends`, + `@xfail_xp_backends`, and `@skip_xp_invalid_arg` pytest markers. + + Please read: https://docs.scipy.org/doc/scipy/dev/api-dev/array_api.html#adding-tests + """ + # Read all @pytest.marks.skip_xp_backends markers that decorate to the test, + # if any, and raise pytest.skip() if the current xp is in the list. + skip_or_xfail_xp_backends(request, "skip") + # Read all @pytest.marks.xfail_xp_backends markers that decorate the test, + # if any, and raise pytest.xfail() if the current xp is in the list. + skip_or_xfail_xp_backends(request, "xfail") + + xp = request.param + # Potentially wrap namespace with array_api_compat + xp = array_namespace(xp.empty(0)) + + if SCIPY_ARRAY_API: + # If xp==jax.numpy, wrap tested functions in jax.jit + # If xp==dask.array, wrap tested functions to test that graph is not computed + with patch_lazy_xp_functions(request=request, xp=request.param): + # Throughout all calls to assert_almost_equal, assert_array_almost_equal, + # and xp_assert_* functions, test that the array namespace is xp in both + # the expected and actual arrays. This is to detect the case where both + # arrays are erroneously just plain numpy while xp is something else. + with default_xp(xp): + yield xp + else: + yield xp + + +skip_xp_invalid_arg = pytest.mark.skipif(SCIPY_ARRAY_API, + reason = ('Test involves masked arrays, object arrays, or other types ' + 'that are not valid input when `SCIPY_ARRAY_API` is used.')) + + +def _backends_kwargs_from_request(request, skip_or_xfail): + """A helper for {skip,xfail}_xp_backends. + + Return dict of {backend to skip/xfail: top reason to skip/xfail it} + """ + markers = list(request.node.iter_markers(f'{skip_or_xfail}_xp_backends')) + reasons = {backend: [] for backend in xp_known_backends} + + for marker in markers: + invalid_kwargs = set(marker.kwargs) - { + "cpu_only", "np_only", "eager_only", "reason", "exceptions"} + if invalid_kwargs: + raise TypeError(f"Invalid kwargs: {invalid_kwargs}") + + exceptions = set(marker.kwargs.get('exceptions', [])) + invalid_exceptions = exceptions - xp_known_backends + if (invalid_exceptions := list(exceptions - xp_known_backends)): + raise ValueError(f"Unknown backend(s): {invalid_exceptions}; " + f"must be a subset of {list(xp_known_backends)}") + + if marker.kwargs.get('np_only', False): + reason = marker.kwargs.get("reason") or "do not run with non-NumPy backends" + for backend, backend_reasons in reasons.items(): + if backend != 'numpy' and backend not in exceptions: + backend_reasons.append(reason) + + elif marker.kwargs.get('cpu_only', False): + reason = marker.kwargs.get("reason") or ( + "no array-agnostic implementation or delegation available " + "for this backend and device") + for backend in xp_skip_cpu_only_backends - exceptions: + reasons[backend].append(reason) + + elif marker.kwargs.get('eager_only', False): + reason = marker.kwargs.get("reason") or ( + "eager checks not executed on lazy backends") + for backend in xp_skip_eager_only_backends - exceptions: + reasons[backend].append(reason) + + # add backends, if any + if len(marker.args) == 1: + backend = marker.args[0] + if backend not in xp_known_backends: + raise ValueError(f"Unknown backend: {backend}; " + f"must be one of {list(xp_known_backends)}") + reason = marker.kwargs.get("reason") or ( + f"do not run with array API backend: {backend}") + # reason overrides the ones from cpu_only, np_only, and eager_only. + # This is regardless of order of appearence of the markers. + reasons[backend].insert(0, reason) + + for kwarg in ("cpu_only", "np_only", "eager_only", "exceptions"): + if kwarg in marker.kwargs: + raise ValueError(f"{kwarg} is mutually exclusive with {backend}") + + elif len(marker.args) > 1: + raise ValueError( + f"Please specify only one backend per marker: {marker.args}" + ) + + return {backend: backend_reasons[0] + for backend, backend_reasons in reasons.items() + if backend_reasons} + + +def skip_or_xfail_xp_backends(request: pytest.FixtureRequest, + skip_or_xfail: Literal['skip', 'xfail']) -> None: + """ + Helper of the `xp` fixture. + Skip or xfail based on the ``skip_xp_backends`` or ``xfail_xp_backends`` markers. + + See the "Support for the array API standard" docs page for usage examples. + + Usage + ----- + :: + skip_xp_backends = pytest.mark.skip_xp_backends + xfail_xp_backends = pytest.mark.xfail_xp_backends + ... + + @skip_xp_backends(backend, *, reason=None) + @skip_xp_backends(*, cpu_only=True, exceptions=(), reason=None) + @skip_xp_backends(*, eager_only=True, exceptions=(), reason=None) + @skip_xp_backends(*, np_only=True, exceptions=(), reason=None) + + @xfail_xp_backends(backend, *, reason=None) + @xfail_xp_backends(*, cpu_only=True, exceptions=(), reason=None) + @xfail_xp_backends(*, eager_only=True, exceptions=(), reason=None) + @xfail_xp_backends(*, np_only=True, exceptions=(), reason=None) + + Parameters + ---------- + backend : str, optional + Backend to skip/xfail, e.g. ``"torch"``. + Mutually exclusive with ``cpu_only``, ``eager_only``, and ``np_only``. + cpu_only : bool, optional + When ``True``, the test is skipped/xfailed on non-CPU devices, + minus exceptions. Mutually exclusive with ``backend``. + eager_only : bool, optional + When ``True``, the test is skipped/xfailed for lazy backends, e.g. those + with major caveats when invoking ``__array__``, ``__bool__``, ``__float__``, + or ``__complex__``, minus exceptions. Mutually exclusive with ``backend``. + np_only : bool, optional + When ``True``, the test is skipped/xfailed for all backends other + than the default NumPy backend and the exceptions. + Mutually exclusive with ``backend``. Implies ``cpu_only`` and ``eager_only``. + reason : str, optional + A reason for the skip/xfail. If omitted, a default reason is used. + exceptions : list[str], optional + A list of exceptions for use with ``cpu_only``, ``eager_only``, or ``np_only``. + This should be provided when delegation is implemented for some, + but not all, non-CPU/non-NumPy backends. + """ + if f"{skip_or_xfail}_xp_backends" not in request.keywords: + return + + skip_xfail_reasons = _backends_kwargs_from_request( + request, skip_or_xfail=skip_or_xfail + ) + xp = request.param + if xp.__name__ in skip_xfail_reasons: + reason = skip_xfail_reasons[xp.__name__] + assert reason # Default reason applied above + skip_or_xfail = getattr(pytest, skip_or_xfail) + skip_or_xfail(reason=reason) + + +@pytest.fixture +def devices(xp): + """Fixture that returns a list of all devices for the backend, plus None. + Used to test input->output device propagation. + + Usage + ----- + from scipy._lib._array_api import xp_device + + def test_device(xp, devices): + for d in devices: + x = xp.asarray(..., device=d) + y = f(x) + assert xp_device(y) == xp_device(x) + """ + if is_cupy(xp): + # CuPy does not support devices other than the current one + # data-apis/array-api-compat#293 + pytest.xfail(reason="data-apis/array-api-compat#293") + if is_dask(xp): + # Skip dummy DASK_DEVICE from array-api-compat, which does not propagate + return ["cpu", None] + if is_jax(xp): + # The .device attribute is not accessible inside jax.jit; the consequence + # (downstream of array-api-compat hacks) is that a non-default device in + # input is not guaranteed to propagate to the output even if the scipy code + # states `device=xp_device(arg)`` in all array creation functions. + # While this issue is specific to jax.jit, it would be unnecessarily + # verbose to skip the test for each jit-capable function and run it for + # those that only support eager mode. + pytest.xfail(reason="jax-ml/jax#26000") + if is_torch(xp): + devices = xp.__array_namespace_info__().devices() + # open an issue about this - cannot branch based on `any`/`all`? + return (device for device in devices if device.type != 'meta') + + return xp.__array_namespace_info__().devices() + [None] + + +if hypothesis_available: + # Following the approach of NumPy's conftest.py... + # Use a known and persistent tmpdir for hypothesis' caches, which + # can be automatically cleared by the OS or user. + hypothesis.configuration.set_hypothesis_home_dir( + os.path.join(tempfile.gettempdir(), ".hypothesis") + ) + + # We register two custom profiles for SciPy - for details see + # https://hypothesis.readthedocs.io/en/latest/settings.html + # The first is designed for our own CI runs; the latter also + # forces determinism and is designed for use via scipy.test() + hypothesis.settings.register_profile( + name="nondeterministic", deadline=None, print_blob=True, + ) + hypothesis.settings.register_profile( + name="deterministic", + deadline=None, print_blob=True, database=None, derandomize=True, + suppress_health_check=list(hypothesis.HealthCheck), + ) + + # Profile is currently set by environment variable `SCIPY_HYPOTHESIS_PROFILE` + # In the future, it would be good to work the choice into `.spin/cmds.py`. + SCIPY_HYPOTHESIS_PROFILE = os.environ.get("SCIPY_HYPOTHESIS_PROFILE", + "deterministic") + hypothesis.settings.load_profile(SCIPY_HYPOTHESIS_PROFILE) + + +############################################################################ +# doctesting stuff + +if HAVE_SCPDT: + + # FIXME: populate the dict once + @contextmanager + def warnings_errors_and_rng(test=None): + """Temporarily turn (almost) all warnings to errors. + + Filter out known warnings which we allow. + """ + known_warnings = dict() + + # these functions are known to emit "divide by zero" RuntimeWarnings + divide_by_zero = [ + 'scipy.linalg.norm', 'scipy.ndimage.center_of_mass', + ] + for name in divide_by_zero: + known_warnings[name] = dict(category=RuntimeWarning, + message='divide by zero') + + # Deprecated stuff + deprecated = [] + for name in deprecated: + known_warnings[name] = dict(category=DeprecationWarning) + + from scipy import integrate + # the functions are known to emit IntegrationWarnings + integration_w = ['scipy.special.ellip_normal', + 'scipy.special.ellip_harm_2', + ] + for name in integration_w: + known_warnings[name] = dict(category=integrate.IntegrationWarning, + message='The occurrence of roundoff') + + # scipy.stats deliberately emits UserWarnings sometimes + user_w = ['scipy.stats.anderson_ksamp', 'scipy.stats.kurtosistest', + 'scipy.stats.normaltest', 'scipy.sparse.linalg.norm'] + for name in user_w: + known_warnings[name] = dict(category=UserWarning) + + # additional one-off warnings to filter + dct = { + 'scipy.sparse.linalg.norm': + dict(category=UserWarning, message="Exited at iteration"), + # tutorials + 'linalg.rst': + dict(message='the matrix subclass is not', + category=PendingDeprecationWarning), + 'stats.rst': + dict(message='The maximum number of subdivisions', + category=integrate.IntegrationWarning), + } + known_warnings.update(dct) + + # these legitimately emit warnings in examples + legit = set('scipy.signal.normalize') + + # Now, the meat of the matter: filter warnings, + # also control the random seed for each doctest. + + # XXX: this matches the refguide-check behavior, but is a tad strange: + # makes sure that the seed the old-fashioned np.random* methods is + # *NOT* reproducible but the new-style `default_rng()` *IS* repoducible. + # Should these two be either both repro or both not repro? + + from scipy._lib._util import _fixed_default_rng + import numpy as np + with _fixed_default_rng(): + np.random.seed(None) + with warnings.catch_warnings(): + if test and test.name in known_warnings: + warnings.filterwarnings('ignore', **known_warnings[test.name]) + yield + elif test and test.name in legit: + yield + else: + warnings.simplefilter('error', Warning) + warnings.filterwarnings('ignore', ".*odr.*", DeprecationWarning) + yield + + dt_config.user_context_mgr = warnings_errors_and_rng + dt_config.skiplist = set([ + 'scipy.linalg.LinAlgError', # comes from numpy + 'scipy.fftpack.fftshift', # fftpack stuff is also from numpy + 'scipy.fftpack.ifftshift', + 'scipy.fftpack.fftfreq', + 'scipy.special.sinc', # sinc is from numpy + 'scipy.optimize.show_options', # does not have much to doctest + 'scipy.signal.normalize', # manipulates warnings (XXX temp skip) + 'scipy.sparse.linalg.norm', # XXX temp skip + # these below test things which inherit from np.ndarray + # cross-ref https://github.com/numpy/numpy/issues/28019 + 'scipy.io.matlab.MatlabObject.strides', + 'scipy.io.matlab.MatlabObject.dtype', + 'scipy.io.matlab.MatlabOpaque.dtype', + 'scipy.io.matlab.MatlabOpaque.strides', + 'scipy.io.matlab.MatlabFunction.strides', + 'scipy.io.matlab.MatlabFunction.dtype' + ]) + + # these are affected by NumPy 2.0 scalar repr: rely on string comparison + if np.__version__ < "2": + dt_config.skiplist.update(set([ + 'scipy.io.hb_read', + 'scipy.io.hb_write', + 'scipy.sparse.csgraph.connected_components', + 'scipy.sparse.csgraph.depth_first_order', + 'scipy.sparse.csgraph.shortest_path', + 'scipy.sparse.csgraph.floyd_warshall', + 'scipy.sparse.csgraph.dijkstra', + 'scipy.sparse.csgraph.bellman_ford', + 'scipy.sparse.csgraph.johnson', + 'scipy.sparse.csgraph.yen', + 'scipy.sparse.csgraph.breadth_first_order', + 'scipy.sparse.csgraph.reverse_cuthill_mckee', + 'scipy.sparse.csgraph.structural_rank', + 'scipy.sparse.csgraph.construct_dist_matrix', + 'scipy.sparse.csgraph.reconstruct_path', + 'scipy.ndimage.value_indices', + 'scipy.stats.mstats.describe', + ])) + + # help pytest collection a bit: these names are either private + # (distributions), or just do not need doctesting. + dt_config.pytest_extra_ignore = [ + "scipy.stats.distributions", + "scipy.optimize.cython_optimize", + "scipy.test", + "scipy.show_config", + # equivalent to "pytest --ignore=path/to/file" + "scipy/special/_precompute", + "scipy/interpolate/_interpnd_info.py", + "scipy/interpolate/_rbfinterp_pythran.py", + "scipy/_build_utils/tempita.py", + "scipy/_lib/array_api_compat", + "scipy/_lib/highs", + "scipy/_lib/unuran", + "scipy/_lib/_gcutils.py", + "scipy/_lib/doccer.py", + "scipy/_lib/_uarray", + "scipy/linalg/_cython_signature_generator.py", + "scipy/linalg/_generate_pyx.py", + "scipy/linalg/_linalg_pythran.py", + "scipy/linalg/_matfuncs_sqrtm_triu.py", + "scipy/ndimage/utils/generate_label_testvectors.py", + "scipy/optimize/_group_columns.py", + "scipy/optimize/_max_len_seq_inner.py", + "scipy/signal/_max_len_seq_inner.py", + "scipy/sparse/_generate_sparsetools.py", + "scipy/special/_generate_pyx.py", + "scipy/stats/_stats_pythran.py", + ] + + dt_config.pytest_extra_xfail = { + # name: reason + "ND_regular_grid.rst": "ReST parser limitation", + "extrapolation_examples.rst": "ReST parser limitation", + "sampling_pinv.rst": "__cinit__ unexpected argument", + "sampling_srou.rst": "nan in scalar_power", + "probability_distributions.rst": "integration warning", + } + + # tutorials + dt_config.pseudocode = set(['integrate.nquad(func,']) + dt_config.local_resources = { + 'io.rst': [ + "octave_a.mat", + "octave_cells.mat", + "octave_struct.mat" + ] + } + + dt_config.strict_check = True + + # ignore Matplotlib's `ax.text`: + dt_config.stopwords.add('.text(') +############################################################################ diff --git a/scipy/version.py b/scipy/version.py new file mode 100644 index 0000000000000000000000000000000000000000..4bcd5a2d1d16508110740930bdb0707a3e00aa5c --- /dev/null +++ b/scipy/version.py @@ -0,0 +1,12 @@ + +""" +Module to expose more detailed version info for the installed `scipy` +""" +version = "1.17.1" +full_version = version +short_version = version.split('.dev')[0] +git_revision = "527eb7fd7953a1de068f94bf8b322f249b9405ae" +release = 'dev' not in version and '+' not in version + +if not release: + version = full_version diff --git a/scripts/enforce_kwargs_spacing.py b/scripts/enforce_kwargs_spacing.py new file mode 100644 index 0000000000000000000000000000000000000000..ca2ff343a0984800e9ba2535463966b71764762e --- /dev/null +++ b/scripts/enforce_kwargs_spacing.py @@ -0,0 +1,179 @@ +#!/usr/bin/env python3 +"""Ensure keyword arguments use spaces around '=', prune redundant pass statements.""" + +from __future__ import annotations + +import ast +import argparse +import io +import sys +import tokenize +from collections import defaultdict +from pathlib import Path + + +def enforce_spacing(text: str) -> tuple[str, bool]: + """Return updated text with keyword '=' padded by spaces, plus change flag.""" + lines = text.splitlines(keepends=True) + if not lines: + return text, False + + offsets: dict[int, int] = defaultdict(int) + changed = False + + reader = io.StringIO(text).readline + for token in tokenize.generate_tokens(reader): + if token.type != tokenize.OP or token.string != "=": + continue + + line_index = token.start[0] - 1 + col = token.start[1] + offsets[line_index] + + if line_index < 0 or line_index >= len(lines): + continue + + line = lines[line_index] + if col >= len(line) or line[col] != "=": + continue + + line_changed = False + + # Insert a space before '=' when missing and not preceded by whitespace. + if col > 0 and line[col - 1] not in {" ", "\t"}: + line = f"{line[:col]} {line[col:]}" + offsets[line_index] += 1 + col += 1 + line_changed = True + changed = True + + # Insert a space after '=' when missing and not followed by whitespace or newline. + next_index = col + 1 + if next_index < len(line) and line[next_index] not in {" ", "\t", "\n", "\r"}: + line = f"{line[:next_index]} {line[next_index:]}" + offsets[line_index] += 1 + line_changed = True + changed = True + + if line_changed: + lines[line_index] = line + + if not changed: + return text, False + + return "".join(lines), True + + +def remove_redundant_passes(text: str) -> tuple[str, bool]: + """Drop pass statements that share a block with other executable code.""" + + try: + tree = ast.parse(text) + except SyntaxError: + return text, False + + redundant: list[ast.Pass] = [] + + def visit(node: ast.AST) -> None: + for attr in ("body", "orelse", "finalbody"): + value = getattr(node, attr, None) + if not isinstance(value, list) or len(value) <= 1: + continue + for stmt in value: + if isinstance(stmt, ast.Pass): + redundant.append(stmt) + for stmt in value: + if isinstance(stmt, ast.AST): + visit(stmt) + handlers = getattr(node, "handlers", None) + if handlers: + for handler in handlers: + visit(handler) + + visit(tree) + + if not redundant: + return text, False + + lines = text.splitlines(keepends=True) + changed = False + + for node in sorted( + redundant, key=lambda item: (item.lineno, item.col_offset), reverse=True + ): + start = node.lineno - 1 + end = (node.end_lineno or node.lineno) - 1 + if start >= len(lines): + continue + changed = True + if start == end: + line = lines[start] + col_start = node.col_offset + col_end = node.end_col_offset or (col_start + 4) + segment = line[:col_start] + line[col_end:] + lines[start] = segment if segment.strip() else "" + continue + + # Defensive fall-back for unexpected multi-line 'pass'. + prefix = lines[start][: node.col_offset] + lines[start] = prefix if prefix.strip() else "" + for idx in range(start + 1, end): + lines[idx] = "" + suffix = lines[end][(node.end_col_offset or 0) :] + lines[end] = suffix + + # Normalise to ensure lines end with newlines except at EOF. + result_lines: list[str] = [] + for index, line in enumerate(lines): + if not line: + continue + if index < len(lines) - 1 and not line.endswith("\n"): + result_lines.append(f"{line}\n") + else: + result_lines.append(line) + + return "".join(result_lines), changed + + +def process_file(path: Path) -> bool: + try: + with tokenize.open(path) as handle: + original = handle.read() + encoding = handle.encoding + except (OSError, SyntaxError) as exc: # SyntaxError from tokenize on invalid python + print(f"Failed to read {path}: {exc}", file=sys.stderr) + return False + + updated, changed = enforce_spacing(original) + updated, removed = remove_redundant_passes(updated) + if changed or removed: + path.write_text(updated, encoding=encoding) + return True + return False + + +def main(argv: list[str]) -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("files", nargs="+", help="Python files to fix") + args = parser.parse_args(argv) + + touched: list[Path] = [] + self_path = Path(__file__).resolve() + + for entry in args.files: + path = Path(entry) + # Skip modifying this script to avoid self-edit loops. + if path.resolve() == self_path: + continue + if not path.exists() or path.is_dir(): + continue + if process_file(path): + touched.append(path) + + if touched: + for path in touched: + print(f"Adjusted kwarg spacing in {path}") + return 0 + + +if __name__ == "__main__": + sys.exit(main(sys.argv[1:])) diff --git a/scripts/run_ruff_format.py b/scripts/run_ruff_format.py new file mode 100644 index 0000000000000000000000000000000000000000..5ec16cd9f5dac5a54c7c98c4d35f0673271118b0 --- /dev/null +++ b/scripts/run_ruff_format.py @@ -0,0 +1,30 @@ +#!/usr/bin/env python3 +"""Run `ruff format` followed by kwarg spacing enforcement.""" + +from __future__ import annotations + +import subprocess +import sys +from pathlib import Path + +HERE = Path(__file__).resolve().parent + + +def main(argv: list[str]) -> int: + files = [arg for arg in argv if Path(arg).exists()] + if not files: + return 0 + + ruff_cmd = [sys.executable, "-m", "ruff", "format", *files] + ruff_proc = subprocess.run(ruff_cmd) + if ruff_proc.returncode != 0: + return ruff_proc.returncode + + spacing_script = HERE / "enforce_kwargs_spacing.py" + spacing_cmd = [sys.executable, str(spacing_script), *files] + spacing_proc = subprocess.run(spacing_cmd) + return spacing_proc.returncode + + +if __name__ == "__main__": + raise SystemExit(main(sys.argv[1:])) diff --git a/sentence_transformers-5.3.0.dist-info/INSTALLER b/sentence_transformers-5.3.0.dist-info/INSTALLER new file mode 100644 index 0000000000000000000000000000000000000000..5c69047b2eb8235994febeeae1da4a82365a240a --- /dev/null +++ b/sentence_transformers-5.3.0.dist-info/INSTALLER @@ -0,0 +1 @@ +uv \ No newline at end of file diff --git a/sentence_transformers-5.3.0.dist-info/METADATA b/sentence_transformers-5.3.0.dist-info/METADATA new file mode 100644 index 0000000000000000000000000000000000000000..daeda342896134a7ec71f555072689b5e9013164 --- /dev/null +++ b/sentence_transformers-5.3.0.dist-info/METADATA @@ -0,0 +1,347 @@ +Metadata-Version: 2.4 +Name: sentence-transformers +Version: 5.3.0 +Summary: Embeddings, Retrieval, and Reranking +Author-email: Nils Reimers , Tom Aarsen +Maintainer-email: Tom Aarsen +License: Apache 2.0 +Project-URL: Homepage, https://www.SBERT.net +Project-URL: Repository, https://github.com/huggingface/sentence-transformers/ +Keywords: Transformer Networks,BERT,XLNet,sentence embedding,PyTorch,NLP,deep learning +Classifier: Development Status :: 5 - Production/Stable +Classifier: Intended Audience :: Science/Research +Classifier: License :: OSI Approved :: Apache Software License +Classifier: Programming Language :: Python :: 3.10 +Classifier: Programming Language :: Python :: 3.11 +Classifier: Programming Language :: Python :: 3.12 +Classifier: Programming Language :: Python :: 3.13 +Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence +Requires-Python: >=3.10 +Description-Content-Type: text/markdown +License-File: LICENSE +License-File: NOTICE.txt +Requires-Dist: transformers<6.0.0,>=4.41.0 +Requires-Dist: huggingface-hub>=0.20.0 +Requires-Dist: torch>=1.11.0 +Requires-Dist: numpy +Requires-Dist: scikit-learn +Requires-Dist: scipy +Requires-Dist: typing_extensions>=4.5.0 +Requires-Dist: tqdm +Provides-Extra: image +Requires-Dist: Pillow; extra == "image" +Provides-Extra: train +Requires-Dist: datasets; extra == "train" +Requires-Dist: accelerate>=0.20.3; extra == "train" +Provides-Extra: onnx +Requires-Dist: optimum-onnx[onnxruntime]; extra == "onnx" +Provides-Extra: onnx-gpu +Requires-Dist: optimum-onnx[onnxruntime-gpu]; extra == "onnx-gpu" +Provides-Extra: openvino +Requires-Dist: optimum-intel[openvino]; extra == "openvino" +Provides-Extra: dev +Requires-Dist: datasets; extra == "dev" +Requires-Dist: accelerate>=0.20.3; extra == "dev" +Requires-Dist: pre-commit; extra == "dev" +Requires-Dist: pytest; extra == "dev" +Requires-Dist: pytest-cov; extra == "dev" +Requires-Dist: pytest-env; extra == "dev" +Requires-Dist: peft; extra == "dev" +Requires-Dist: Pillow; extra == "dev" +Dynamic: license-file + + + +[![HF Models](https://img.shields.io/badge/%F0%9F%A4%97-models-yellow)](https://huggingface.co/models?library=sentence-transformers) +[![GitHub - License](https://img.shields.io/github/license/huggingface/sentence-transformers?logo=github&style=flat&color=green)][#github-license] +[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/sentence-transformers?logo=pypi&style=flat&color=blue)][#pypi-package] +[![PyPI - Package Version](https://img.shields.io/pypi/v/sentence-transformers?logo=pypi&style=flat&color=orange)][#pypi-package] +[![Docs - GitHub.io](https://img.shields.io/static/v1?logo=github&style=flat&color=pink&label=docs&message=sentence-transformers)][#docs-package] + + + + + +# Sentence Transformers: Embeddings, Retrieval, and Reranking + +This framework provides an easy method to compute embeddings for accessing, using, and training state-of-the-art embedding and reranker models. It can be used to compute embeddings using Sentence Transformer models ([quickstart](https://sbert.net/docs/quickstart.html#sentence-transformer)), to calculate similarity scores using Cross-Encoder (a.k.a. reranker) models ([quickstart](https://sbert.net/docs/quickstart.html#cross-encoder)) or to generate sparse embeddings using Sparse Encoder models ([quickstart](https://sbert.net/docs/quickstart.html#sparse-encoder)). This unlocks a wide range of applications, including [semantic search](https://sbert.net/examples/applications/semantic-search/README.html), [semantic textual similarity](https://sbert.net/docs/sentence_transformer/usage/semantic_textual_similarity.html), and [paraphrase mining](https://sbert.net/examples/applications/paraphrase-mining/README.html). + +A wide selection of over [15,000 pre-trained Sentence Transformers models](https://huggingface.co/models?library=sentence-transformers) are available for immediate use on 🤗 Hugging Face, including many of the state-of-the-art models from the [Massive Text Embeddings Benchmark (MTEB) leaderboard](https://huggingface.co/spaces/mteb/leaderboard). Additionally, it is easy to train or finetune your own [embedding models](https://sbert.net/docs/sentence_transformer/training_overview.html), [reranker models](https://sbert.net/docs/cross_encoder/training_overview.html) or [sparse encoder models](https://sbert.net/docs/sparse_encoder/training_overview.html) using Sentence Transformers, enabling you to create custom models for your specific use cases. + +For the **full documentation**, see **[www.SBERT.net](https://www.sbert.net)**. + +## Installation + +We recommend **Python 3.10+**, **[PyTorch 1.11.0+](https://pytorch.org/get-started/locally/)**, and **[transformers v4.34.0+](https://github.com/huggingface/transformers)**. + +**Install with pip** + +``` +pip install -U sentence-transformers +``` + +**Install with conda** + +``` +conda install -c conda-forge sentence-transformers +``` + +**Install from sources** + +Alternatively, you can also clone the latest version from the [repository](https://github.com/huggingface/sentence-transformers) and install it directly from the source code: + +``` +pip install -e . +``` + +**PyTorch with CUDA** + +If you want to use a GPU / CUDA, you must install PyTorch with the matching CUDA Version. Follow +[PyTorch - Get Started](https://pytorch.org/get-started/locally/) for further details how to install PyTorch. + +## Getting Started + +See [Quickstart](https://www.sbert.net/docs/quickstart.html) in our documentation. + +### Embedding Models + +First download a pretrained embedding a.k.a. Sentence Transformer model. + +```python +from sentence_transformers import SentenceTransformer + +model = SentenceTransformer("all-MiniLM-L6-v2") +``` + +Then provide some texts to the model. + +```python +sentences = [ + "The weather is lovely today.", + "It's so sunny outside!", + "He drove to the stadium.", +] +embeddings = model.encode(sentences) +print(embeddings.shape) +# => (3, 384) +``` + +And that's already it. We now have numpy arrays with the embeddings, one for each text. We can use these to compute similarities. + +```python +similarities = model.similarity(embeddings, embeddings) +print(similarities) +# tensor([[1.0000, 0.6660, 0.1046], +# [0.6660, 1.0000, 0.1411], +# [0.1046, 0.1411, 1.0000]]) +``` + +### Reranker Models + +First download a pretrained reranker a.k.a. Cross Encoder model. + +```python +from sentence_transformers import CrossEncoder + +# 1. Load a pretrained CrossEncoder model +model = CrossEncoder("cross-encoder/ms-marco-MiniLM-L6-v2") +``` + +Then provide some texts to the model. + +```python +# The texts for which to predict similarity scores +query = "How many people live in Berlin?" +passages = [ + "Berlin had a population of 3,520,031 registered inhabitants in an area of 891.82 square kilometers.", + "Berlin has a yearly total of about 135 million day visitors, making it one of the most-visited cities in the European Union.", + "In 2013 around 600,000 Berliners were registered in one of the more than 2,300 sport and fitness clubs.", +] + +# 2a. predict scores for pairs of texts +scores = model.predict([(query, passage) for passage in passages]) +print(scores) +# => [8.607139 5.506266 6.352977] +``` + +And we're good to go. You can also use [`model.rank`](https://sbert.net/docs/package_reference/cross_encoder/cross_encoder.html#sentence_transformers.cross_encoder.CrossEncoder.rank) to avoid having to perform the reranking manually: + +```python +# 2b. Rank a list of passages for a query +ranks = model.rank(query, passages, return_documents=True) + +print("Query:", query) +for rank in ranks: + print(f"- #{rank['corpus_id']} ({rank['score']:.2f}): {rank['text']}") +""" +Query: How many people live in Berlin? +- #0 (8.61): Berlin had a population of 3,520,031 registered inhabitants in an area of 891.82 square kilometers. +- #2 (6.35): In 2013 around 600,000 Berliners were registered in one of the more than 2,300 sport and fitness clubs. +- #1 (5.51): Berlin has a yearly total of about 135 million day visitors, making it one of the most-visited cities in the European Union. +""" +``` + +### Sparse Encoder Models + +First download a pretrained sparse embedding a.k.a. Sparse Encoder model. + +```python + +from sentence_transformers import SparseEncoder + +# 1. Load a pretrained SparseEncoder model +model = SparseEncoder("naver/splade-cocondenser-ensembledistil") + +# The sentences to encode +sentences = [ + "The weather is lovely today.", + "It's so sunny outside!", + "He drove to the stadium.", +] + +# 2. Calculate sparse embeddings by calling model.encode() +embeddings = model.encode(sentences) +print(embeddings.shape) +# [3, 30522] - sparse representation with vocabulary size dimensions + +# 3. Calculate the embedding similarities +similarities = model.similarity(embeddings, embeddings) +print(similarities) +# tensor([[ 35.629, 9.154, 0.098], +# [ 9.154, 27.478, 0.019], +# [ 0.098, 0.019, 29.553]]) + +# 4. Check sparsity stats +stats = SparseEncoder.sparsity(embeddings) +print(f"Sparsity: {stats['sparsity_ratio']:.2%}") +# Sparsity: 99.84% +``` + +## Pre-Trained Models + +We provide a large list of pretrained models for more than 100 languages. Some models are general purpose models, while others produce embeddings for specific use cases. + +- [Pretrained Sentence Transformer (Embedding) Models](https://sbert.net/docs/sentence_transformer/pretrained_models.html) +- [Pretrained Cross Encoder (Reranker) Models](https://sbert.net/docs/cross_encoder/pretrained_models.html) +- [Pretrained Sparse Encoder (Sparse Embeddings) Models](https://sbert.net/docs/sparse_encoder/pretrained_models.html) + +## Training + +This framework allows you to fine-tune your own sentence embedding methods, so that you get task-specific sentence embeddings. You have various options to choose from in order to get perfect sentence embeddings for your specific task. + +- Embedding Models + - [Sentence Transformer > Training Overview](https://www.sbert.net/docs/sentence_transformer/training_overview.html) + - [Sentence Transformer > Training Examples](https://www.sbert.net/docs/sentence_transformer/training/examples.html) or [training examples on GitHub](https://github.com/huggingface/sentence-transformers/tree/main/examples/sentence_transformer/training). +- Reranker Models + - [Cross Encoder > Training Overview](https://www.sbert.net/docs/cross_encoder/training_overview.html) + - [Cross Encoder > Training Examples](https://www.sbert.net/docs/cross_encoder/training/examples.html) or [training examples on GitHub](https://github.com/huggingface/sentence-transformers/tree/main/examples/cross_encoder/training). +- Sparse Embedding Models + - [Sparse Encoder > Training Overview](https://www.sbert.net/docs/sparse_encoder/training_overview.html) + - [Sparse Encoder > Training Examples](https://www.sbert.net/docs/sparse_encoder/training/examples.html) or [training examples on GitHub](https://github.com/huggingface/sentence-transformers/tree/main/examples/sparse_encoder/training). + +Some highlights across the different types of training are: + +- Support of various transformer networks including BERT, RoBERTa, XLM-R, DistilBERT, Electra, BART, ... +- Multi-Lingual and multi-task learning +- Evaluation during training to find optimal model +- [20+ loss functions](https://www.sbert.net/docs/package_reference/sentence_transformer/losses.html) for embedding models, [10+ loss functions](https://www.sbert.net/docs/package_reference/cross_encoder/losses.html) for reranker models and [10+ loss functions](https://www.sbert.net/docs/package_reference/sparse_encoder/losses.html) for sparse embedding models, allowing you to tune models specifically for semantic search, paraphrase mining, semantic similarity comparison, clustering, triplet loss, contrastive loss, etc. + +## Application Examples + +You can use this framework for: + +- **Computing Sentence Embeddings** + + - [Dense Embeddings](https://www.sbert.net/examples/sentence_transformer/applications/computing-embeddings/README.html) + - [Sparse Embeddings](https://www.sbert.net/examples/sparse_encoder/applications/computing_embeddings/README.html) + +- **Semantic Textual Similarity** + + - [Dense STS](https://www.sbert.net/docs/sentence_transformer/usage/semantic_textual_similarity.html) + - [Sparse STS](https://www.sbert.net/examples/sparse_encoder/applications/semantic_textual_similarity/README.html) + +- **Semantic Search** + + - [Dense Search](https://www.sbert.net/examples/sentence_transformer/applications/semantic-search/README.html) + - [Sparse Search](https://www.sbert.net/examples/sparse_encoder/applications/semantic_search/README.html) + +- **Retrieve & Re-Rank** + + - [Dense only Retrieval](https://www.sbert.net/examples/sentence_transformer/applications/retrieve_rerank/README.html) + - [Sparse/Dense/Hybrid Retrieval](https://www.sbert.net/examples/sentence_transformer/applications/retrieve_rerank/README.html) + +- [Clustering](https://www.sbert.net/examples/sentence_transformer/applications/clustering/README.html) + +- [Paraphrase Mining](https://www.sbert.net/examples/sentence_transformer/applications/paraphrase-mining/README.html) + +- [Translated Sentence Mining](https://www.sbert.net/examples/sentence_transformer/applications/parallel-sentence-mining/README.html) + +- [Multilingual Image Search, Clustering & Duplicate Detection](https://www.sbert.net/examples/sentence_transformer/applications/image-search/README.html) + +and many more use-cases. + +For all examples, see [examples/sentence_transformer/applications](https://github.com/huggingface/sentence-transformers/tree/main/examples/sentence_transformer/applications). + +## Development setup + +After cloning the repo (or a fork) to your machine, in a virtual environment, run: + +``` +python -m pip install -e ".[dev]" + +pre-commit install +``` + +To test your changes, run: + +``` +pytest +``` + +## Citing & Authors + +If you find this repository helpful, feel free to cite our publication [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://huggingface.co/papers/1908.10084): + +```bibtex +@inproceedings{reimers-2019-sentence-bert, + title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks", + author = "Reimers, Nils and Gurevych, Iryna", + booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing", + month = "11", + year = "2019", + publisher = "Association for Computational Linguistics", + url = "https://arxiv.org/abs/1908.10084", +} +``` + +If you use one of the multilingual models, feel free to cite our publication [Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation](https://huggingface.co/papers/2004.09813): + +```bibtex +@inproceedings{reimers-2020-multilingual-sentence-bert, + title = "Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation", + author = "Reimers, Nils and Gurevych, Iryna", + booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing", + month = "11", + year = "2020", + publisher = "Association for Computational Linguistics", + url = "https://arxiv.org/abs/2004.09813", +} +``` + +Please have a look at [Publications](https://www.sbert.net/docs/publications.html) for our different publications that are integrated into SentenceTransformers. + +### Maintainers + +Maintainer: [Tom Aarsen](https://github.com/tomaarsen), 🤗 Hugging Face + +Don't hesitate to open an issue if something is broken (and it shouldn't be) or if you have further questions. + +--- + +This project was originally developed by the [Ubiquitous Knowledge Processing (UKP) Lab](https://www.ukp.tu-darmstadt.de/) at TU Darmstadt. We're grateful for their foundational work and continued contributions to the field. + +> This repository contains experimental software and is published for the sole purpose of giving additional background details on the respective publication. + +[#docs-package]: https://www.sbert.net/ +[#github-license]: https://github.com/huggingface/sentence-transformers/blob/main/LICENSE +[#pypi-package]: https://pypi.org/project/sentence-transformers/ diff --git a/sentence_transformers-5.3.0.dist-info/RECORD b/sentence_transformers-5.3.0.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..f6df5c0cf92ad7afd71edc3eb5ba9790d5b4a1c3 --- /dev/null +++ b/sentence_transformers-5.3.0.dist-info/RECORD @@ -0,0 +1,181 @@ +sentence_transformers-5.3.0.dist-info/INSTALLER,sha256=5hhM4Q4mYTT9z6QB6PGpUAW81PGNFrYrdXMj4oM_6ak,2 +sentence_transformers-5.3.0.dist-info/METADATA,sha256=3X7YuVzALCANcrLzdAjjFFd2k4gtzjD6Tt0wOgBFDyc,16644 +sentence_transformers-5.3.0.dist-info/RECORD,, 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diff --git a/sentence_transformers-5.3.0.dist-info/WHEEL b/sentence_transformers-5.3.0.dist-info/WHEEL new file mode 100644 index 0000000000000000000000000000000000000000..14a883f292bc96b20c2b76a3081991f2676523a9 --- /dev/null +++ b/sentence_transformers-5.3.0.dist-info/WHEEL @@ -0,0 +1,5 @@ +Wheel-Version: 1.0 +Generator: setuptools (82.0.1) +Root-Is-Purelib: true +Tag: py3-none-any + diff --git a/sentence_transformers-5.3.0.dist-info/top_level.txt b/sentence_transformers-5.3.0.dist-info/top_level.txt new file mode 100644 index 0000000000000000000000000000000000000000..470db3cc7a0102030df35d52d97a548cbd5bca18 --- /dev/null +++ b/sentence_transformers-5.3.0.dist-info/top_level.txt @@ -0,0 +1 @@ +sentence_transformers