import argparse
import zipfile
import httpx
import polars as pl
from pathlib import Path
import tempfile
from tqdm import tqdm

# Ofcom Connected Nations 2025 - Fixed broadband performance (output area & local authority level)
# Source: https://www.ofcom.org.uk/phones-and-broadband/coverage-and-speeds/connected-nations-20252/data-downloads-2025
PERFORMANCE_URL = "https://www.ofcom.org.uk/siteassets/resources/documents/research-and-data/multi-sector/infrastructure-research/connected-nations-2025/202507_fixed_broadband_performance_r01.zip"


def download_with_progress(url: str, output_path: Path) -> None:
    with httpx.stream("GET", url, follow_redirects=True, timeout=120) as response:
        response.raise_for_status()  # pyright: ignore[reportUnusedCallResult]
        total = int(response.headers.get("content-length", 0))
        with (
            open(output_path, "wb") as f,
            tqdm(total=total, unit="B", unit_scale=True, desc="Downloading") as pbar,
        ):
            for chunk in response.iter_bytes(chunk_size=8192):
                f.write(chunk)
                pbar.update(len(chunk))


def extract_zip(zip_path: Path, extract_dir: Path) -> None:
    with zipfile.ZipFile(zip_path, "r") as z:
        z.extractall(extract_dir)


def convert_to_parquet(extract_dir: Path, parquet_path: Path) -> None:
    # Find CSV files in the extracted directory
    csv_files = list(extract_dir.rglob("*.csv"))
    if not csv_files:
        raise FileNotFoundError(f"No CSV files found in {extract_dir}")

    print(f"Found CSV files: {[f.name for f in csv_files]}")

    # Read and concatenate all CSVs (typically split by geography level)
    frames = []
    for csv_file in sorted(csv_files):
        print(f"Reading {csv_file.name}...")
        df = pl.read_csv(csv_file, infer_schema_length=10000, encoding="utf8-lossy")
        print(f"  Shape: {df.shape}, Columns: {df.columns}")
        frames.append((csv_file.stem, df))

    # Save each CSV as a separate parquet file in the output directory
    parquet_path.mkdir(parents=True, exist_ok=True)
    for name, df in frames:
        out = parquet_path / f"{name}.parquet"
        df.write_parquet(out, compression="zstd")
        print(f"Saved {out} ({df.shape[0]} rows)")


def main() -> None:
    parser = argparse.ArgumentParser(
        description="Download Ofcom broadband performance data"
    )
    parser.add_argument(
        "--output",
        type=Path,
        required=True,
        help="Output directory for parquet files",
    )
    args = parser.parse_args()

    with tempfile.TemporaryDirectory() as cache_dir:
        cache = Path(cache_dir)
        zip_path = cache / "broadband_performance.zip"
        extract_dir = cache / "extracted"
        extract_dir.mkdir()

        download_with_progress(PERFORMANCE_URL, zip_path)
        extract_zip(zip_path, extract_dir)
        convert_to_parquet(extract_dir, args.output)


if __name__ == "__main__":
    main()