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)