File size: 2,631 Bytes
7046435 | 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 | from pprint import pprint
import polars as pl
from huggingface_hub import hf_hub_url, list_repo_files
from tqdm import tqdm
file_names = pl.Series(list_repo_files("allenai/c4", repo_type="dataset"))
# Take all splits of the realnewslike subset (513 files)
news_files = file_names.filter(
file_names.str.starts_with("realnewslike/") & file_names.str.ends_with(".json.gz"),
).str.strip_prefix("realnewslike/")
c4n_features = {"url": pl.String, "text": pl.String}
aggregator = pl.DataFrame(schema=c4n_features)
domain_capture = r"https?://([^/?]+)"
# subpage_capture = r"https?://[^/]+/([^/?]+)"
subpage_capture = r"https?://[^/]+(\/[^/?]+\/)" # Include pre/suffix slashes
url_match = r"^(news\.bbc\.co\.uk|www\.bbc\.co\.uk|www\.bbc\.com)$"
news_subpages = ["news"] # Blogs are the 2nd largest category but still far smaller
regions = [
"berkshire",
"birmingham",
"blackcountry",
"bradford",
"bristol",
"cambridgeshire",
"chelsea",
"cornwall",
"coventry",
"cumbria",
"derby",
"devon",
"dorset",
"england",
"essex",
"gloucestershire",
"guernsey",
"hampshire",
"herefordandworcester",
"humber",
"isleofman",
"jersey",
"kent",
"lancashire",
"leeds",
"leicester",
"lincolnshire",
"liverpool",
"london",
"manchester",
"norfolk",
"northamptonshire",
"northernireland",
"nottingham",
"oxford",
"readingandleeds",
"scotland",
"shropshire",
"somerset",
"southampton",
"southyorkshire",
"stoke",
"suffolk",
"tees",
"tyne",
"wales",
"wiltshire",
]
allowed_subpages = pl.DataFrame({"path": map("/{}/".format, news_subpages + regions)})
path_col = pl.col("url").str.extract(subpage_capture).alias("path")
for filename in tqdm(news_files):
json_url = hf_hub_url(
repo_id="allenai/c4",
filename=filename,
subfolder="realnewslike",
repo_type="dataset",
)
print(f"Processing {json_url}")
df = pl.read_ndjson(json_url, schema=c4n_features).filter(
pl.col("url").str.extract(domain_capture).str.contains(url_match),
~pl.col("url").str.contains(r"https?://[^/]+\/\?"), # Path is a ?
)
news_df = (
df.with_columns(path_col)
.sort("path")
.join(allowed_subpages, on="path")
.drop("path")
)
aggregator = pl.concat([aggregator, news_df])
print(aggregator)
with pl.Config() as cfg:
cfg.set_tbl_rows(-1)
aggregator.with_columns(path_col)["path"].value_counts().sort(
"count", descending=True
).with_row_index().pipe(print)
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