File size: 6,621 Bytes
45f1e06 438c512 45f1e06 438c512 45f1e06 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 |
import csv
import os
import datasets
_DESCRIPTION = ""
_CITATION = ""
_HOMEPAGE = ""
_ROOT_URL = "https://digitalcorpora.s3.amazonaws.com/corpora/files/CC-MAIN-2021-31-PDF-UNTRUNCATED"
_ZIPFILES_URL_TEMPLATE = _ROOT_URL + "/zipfiles/{subdir}/{filename}"
_ZIPFILES_URLS = [
_ZIPFILES_URL_TEMPLATE.format(subdir=f"{thousand:04d}-{thousand + 999:04d}", filename=f"{thousand + i:04d}.zip")
for thousand in range(0, 8000, 1000) for i in range(933 if thousand == 7000 else 1000)
]
_CC_HOSTS_URL = _ROOT_URL + "/metadata/cc-hosts-20230303.csv.gz"
_CC_PROVENANCE_URL = _ROOT_URL + "/metadata/cc-provenance-20230303.csv.gz"
_PDFINFO_URL = _ROOT_URL + "/metadata/pdfinfo-20230315.csv.gz"
_MISSING_PDFS = {
"177150.pdf",
"594742.pdf",
"706328.pdf",
"1260258.pdf",
"1544119.pdf",
"1591732.pdf",
"1640603.pdf",
"1890087.pdf",
"1920911.pdf",
"1992331.pdf",
"2519839.pdf",
"2712444.pdf",
"2765539.pdf",
"3179469.pdf",
"4170238.pdf",
"4414331.pdf",
"4512373.pdf",
"4977579.pdf",
"5198714.pdf",
"5236677.pdf",
"5447694.pdf",
"6318895.pdf",
"6817632.pdf",
"6940914.pdf",
"7241425.pdf",
"7279847.pdf",
"7407159.pdf",
"7635694.pdf",
"7889525.pdf"
}
class Pdfa(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
citation=_CITATION,
homepage=_HOMEPAGE,
features = datasets.Features({
"pdf_bytes": datasets.Value("binary"),
"file_name": datasets.Value("string"),
"url_id": datasets.Value("string"),
"cc_host": {
"host": datasets.Value("string"),
"tld": datasets.Value("string"),
"ip_address": datasets.Value("string"),
"country": datasets.Value("string"),
"latitude": datasets.Value("float32"),
"longitude": datasets.Value("float32"),
},
"cc_provenance": {
"url": datasets.Value("string"),
"cc_digest": datasets.Value("string"),
"cc_http_mime": datasets.Value("string"),
"cc_detected_mime": datasets.Value("string"),
"cc_warc_file_name": datasets.Value("string"),
"cc_warc_start": datasets.Value("int64"),
"cc_warc_end": datasets.Value("int64"),
"cc_truncated": datasets.Value("string"),
"fetched_status": datasets.Value("string"),
"fetched_digest": datasets.Value("string"),
"fetched_length": datasets.Value("int64"),
},
"pdfinfo": {
"parse_time_millis": datasets.Value("int64"),
"exit_value": datasets.Value("int64"),
"timeout": datasets.Value("string"),
"stderr": datasets.Value("string"),
"pdf_version": datasets.Value("string"),
"creator": datasets.Value("string"),
"producer": datasets.Value("string"),
"created": datasets.Value("string"),
"modified": datasets.Value("string"),
"custom_metadata": datasets.Value("string"),
"metadata_stream": datasets.Value("string"),
"tagged": datasets.Value("string"),
"user_properties": datasets.Value("string"),
"form": datasets.Value("string"),
"javascript": datasets.Value("string"),
"pages": datasets.Value("int64"),
"page_size": datasets.Value("string"),
"page_rotation": datasets.Value("int64"),
"optimized": datasets.Value("string"),
},
})
)
def _split_generators(self, dl_manager):
cc_host_csv_path = dl_manager.download_and_extract(_CC_HOSTS_URL)
cc_provenance_csv_path = dl_manager.download_and_extract(_CC_PROVENANCE_URL)
pdfinfo_csv_path = dl_manager.download_and_extract(_PDFINFO_URL)
pdfs_directories = tuple(dl_manager.download_and_extract(_ZIPFILES_URLS)) # use tuple to disallow shuffling
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={
"cc_host_csv_path": cc_host_csv_path,
"cc_provenance_csv_path": cc_provenance_csv_path,
"pdfinfo_csv_path": pdfinfo_csv_path,
"pdfs_directories": pdfs_directories
}),
]
def _generate_examples(self, cc_host_csv_path, cc_provenance_csv_path, pdfinfo_csv_path, pdfs_directories):
"""Yields examples."""
with open(cc_host_csv_path, encoding="utf-8") as cc_host_file, \
open(cc_provenance_csv_path, encoding="utf-8") as cc_provenance_csv_file, \
open(pdfinfo_csv_path, encoding="utf-8") as pdfinfo_csv_file:
cc_host_reader = csv.DictReader(cc_host_file)
cc_provenance_reader = csv.DictReader(cc_provenance_csv_file)
pdfinfo_csv_reader = csv.DictReader(pdfinfo_csv_file)
for cc_host_dict, cc_provenance_dict, pdfinfo_dict in zip(cc_host_reader, cc_provenance_reader, pdfinfo_csv_reader):
file_name = cc_host_dict["file_name"]
url_id = cc_host_dict["url_id"]
if file_name in _MISSING_PDFS:
continue
pdf_idx = int(file_name.split(".")[0])
pdf_dir = pdfs_directories[pdf_idx // 1000]
pdf_path = os.path.join(pdf_dir, file_name)
cc_host_dict.pop("url_id")
cc_host_dict.pop("file_name")
cc_provenance_dict.pop("url_id")
cc_provenance_dict.pop("file_name")
pdfinfo_dict.pop("url_id")
pdfinfo_dict.pop("file_name")
with open(pdf_path, "rb") as pdf_file:
yield file_name, {
"pdf_bytes": pdf_file.read(),
"file_name": file_name,
"url_id": url_id,
"cc_host": {k: v if v else None for k, v in cc_host_dict.items()},
"cc_provenance": {k: v if v else None for k, v in cc_provenance_dict.items()},
"pdfinfo": {k: v if v else None for k, v in pdfinfo_dict.items()}
}
|