""" Utilities for working with the local dataset cache. This file is adapted from the AllenNLP library at https://github.com/allenai/allennlp Copyright by the AllenNLP authors. """ import json import logging import os import shutil import tempfile from functools import wraps from hashlib import sha256 import sys from io import open import boto3 import requests from botocore.exceptions import ClientError from tqdm import tqdm try: from urllib.parse import urlparse except ImportError: from urlparse import urlparse try: from pathlib import Path PYTORCH_PRETRAINED_BERT_CACHE = Path(os.getenv('PYTORCH_PRETRAINED_BERT_CACHE', Path.home() / '.pytorch_pretrained_bert')) except (AttributeError, ImportError): PYTORCH_PRETRAINED_BERT_CACHE = os.getenv('PYTORCH_PRETRAINED_BERT_CACHE', os.path.join(os.path.expanduser("~"), '.pytorch_pretrained_bert')) logger = logging.getLogger(__name__) # pylint: disable=invalid-name def url_to_filename(url, etag=None): """ Convert `url` into a hashed filename in a repeatable way. If `etag` is specified, append its hash to the url's, delimited by a period. """ url_bytes = url.encode('utf-8') url_hash = sha256(url_bytes) filename = url_hash.hexdigest() if etag: etag_bytes = etag.encode('utf-8') etag_hash = sha256(etag_bytes) filename += '.' + etag_hash.hexdigest() return filename def filename_to_url(filename, cache_dir=None): """ Return the url and etag (which may be ``None``) stored for `filename`. Raise ``EnvironmentError`` if `filename` or its stored metadata do not exist. """ if cache_dir is None: cache_dir = PYTORCH_PRETRAINED_BERT_CACHE if sys.version_info[0] == 3 and isinstance(cache_dir, Path): cache_dir = str(cache_dir) cache_path = os.path.join(cache_dir, filename) if not os.path.exists(cache_path): raise EnvironmentError("file {} not found".format(cache_path)) meta_path = cache_path + '.json' if not os.path.exists(meta_path): raise EnvironmentError("file {} not found".format(meta_path)) with open(meta_path, encoding="utf-8") as meta_file: metadata = json.load(meta_file) url = metadata['url'] etag = metadata['etag'] return url, etag def cached_path(url_or_filename, cache_dir=None): """ Given something that might be a URL (or might be a local path), determine which. If it's a URL, download the file and cache it, and return the path to the cached file. If it's already a local path, make sure the file exists and then return the path. """ if cache_dir is None: cache_dir = PYTORCH_PRETRAINED_BERT_CACHE if sys.version_info[0] == 3 and isinstance(url_or_filename, Path): url_or_filename = str(url_or_filename) if sys.version_info[0] == 3 and isinstance(cache_dir, Path): cache_dir = str(cache_dir) parsed = urlparse(url_or_filename) if parsed.scheme in ('http', 'https', 's3'): # URL, so get it from the cache (downloading if necessary) return get_from_cache(url_or_filename, cache_dir) elif os.path.exists(url_or_filename): # File, and it exists. return url_or_filename elif parsed.scheme == '': # File, but it doesn't exist. raise EnvironmentError("file {} not found".format(url_or_filename)) else: # Something unknown raise ValueError("unable to parse {} as a URL or as a local path".format(url_or_filename)) def split_s3_path(url): """Split a full s3 path into the bucket name and path.""" parsed = urlparse(url) if not parsed.netloc or not parsed.path: raise ValueError("bad s3 path {}".format(url)) bucket_name = parsed.netloc s3_path = parsed.path # Remove '/' at beginning of path. if s3_path.startswith("/"): s3_path = s3_path[1:] return bucket_name, s3_path def s3_request(func): """ Wrapper function for s3 requests in order to create more helpful error messages. """ @wraps(func) def wrapper(url, *args, **kwargs): try: return func(url, *args, **kwargs) except ClientError as exc: if int(exc.response["Error"]["Code"]) == 404: raise EnvironmentError("file {} not found".format(url)) else: raise return wrapper @s3_request def s3_etag(url): """Check ETag on S3 object.""" s3_resource = boto3.resource("s3") bucket_name, s3_path = split_s3_path(url) s3_object = s3_resource.Object(bucket_name, s3_path) return s3_object.e_tag @s3_request def s3_get(url, temp_file): """Pull a file directly from S3.""" s3_resource = boto3.resource("s3") bucket_name, s3_path = split_s3_path(url) s3_resource.Bucket(bucket_name).download_fileobj(s3_path, temp_file) def http_get(url, temp_file): req = requests.get(url, stream=True) content_length = req.headers.get('Content-Length') total = int(content_length) if content_length is not None else None progress = tqdm(unit="B", total=total) for chunk in req.iter_content(chunk_size=1024): if chunk: # filter out keep-alive new chunks progress.update(len(chunk)) temp_file.write(chunk) progress.close() def get_from_cache(url, cache_dir=None): """ Given a URL, look for the corresponding dataset in the local cache. If it's not there, download it. Then return the path to the cached file. """ if cache_dir is None: cache_dir = PYTORCH_PRETRAINED_BERT_CACHE if sys.version_info[0] == 3 and isinstance(cache_dir, Path): cache_dir = str(cache_dir) if not os.path.exists(cache_dir): os.makedirs(cache_dir) # Get eTag to add to filename, if it exists. if url.startswith("s3://"): etag = s3_etag(url) else: response = requests.head(url, allow_redirects=True) if response.status_code != 200: raise IOError("HEAD request failed for url {} with status code {}" .format(url, response.status_code)) etag = response.headers.get("ETag") filename = url_to_filename(url, etag) # get cache path to put the file cache_path = os.path.join(cache_dir, filename) if not os.path.exists(cache_path): # Download to temporary file, then copy to cache dir once finished. # Otherwise you get corrupt cache entries if the download gets interrupted. with tempfile.NamedTemporaryFile() as temp_file: logger.info("%s not found in cache, downloading to %s", url, temp_file.name) # GET file object if url.startswith("s3://"): s3_get(url, temp_file) else: http_get(url, temp_file) # we are copying the file before closing it, so flush to avoid truncation temp_file.flush() # shutil.copyfileobj() starts at the current position, so go to the start temp_file.seek(0) logger.info("copying %s to cache at %s", temp_file.name, cache_path) with open(cache_path, 'wb') as cache_file: shutil.copyfileobj(temp_file, cache_file) logger.info("creating metadata file for %s", cache_path) meta = {'url': url, 'etag': etag} meta_path = cache_path + '.json' with open(meta_path, 'w', encoding="utf-8") as meta_file: json.dump(meta, meta_file) logger.info("removing temp file %s", temp_file.name) return cache_path def read_set_from_file(filename): ''' Extract a de-duped collection (set) of text from a file. Expected file format is one item per line. ''' collection = set() with open(filename, 'r', encoding='utf-8') as file_: for line in file_: collection.add(line.rstrip()) return collection def get_file_extension(path, dot=True, lower=True): ext = os.path.splitext(path)[1] ext = ext if dot else ext[1:] return ext.lower() if lower else ext