from datetime import datetime, timezone

import pyarrow as pa

from govdata.belastingdienst import extract
from govdata.belastingdienst.index import Page, fetch_index
from govdata.common.http import Fetcher

S = pa.string()
PAGES = pa.schema(
    [("url", S), ("title", S), ("topic", S), ("language", S), ("audience", S), ("lastmod", S), ("text", S)]
)


class Belastingdienst:
    name = "belastingdienst"
    repo_id = "ethux/belastingdienst-dataset"
    n_shards = 4
    key_col = "url"
    mod_col = "lastmod"
    shard_col = "url"
    raw_schema = pa.schema([("url", S), ("lastmod", S), ("fetched_at", S), ("html", S)])
    configs = {"pages": PAGES}
    rate = 2.0
    robots_exempt = frozenset()
    legacy = ("belastingdienst.csv", "data/legacy/belastingdienst.csv")

    def index(self, fetcher: Fetcher, limit: int | None) -> dict[str, Page]:
        return fetch_index(fetcher, limit)

    def modified(self, rec: Page) -> str:
        return rec.lastmod

    def fetch(self, fetcher: Fetcher, key: str, rec: Page) -> dict:
        r = fetcher.get(key)
        return {
            "url": key,
            "lastmod": rec.lastmod,
            "fetched_at": datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ"),
            "html": r.text,
        }

    def build(self, raw: pa.Table, index: dict[str, Page], run_date: str) -> dict[str, list[dict]]:
        pages = []
        for row in raw.to_pylist():
            page = extract.extract_page(row["html"], row["url"])
            if page is None:
                continue
            topic, language, audience = extract.classify(row["url"])
            pages.append(
                {
                    "url": row["url"],
                    "title": page["title"],
                    "topic": topic,
                    "language": language,
                    "audience": audience,
                    "lastmod": row["lastmod"],
                    "text": page["text"],
                }
            )
        return {"pages": pages}


SOURCE = Belastingdienst()