"""
Tabular-family extractor: csv.

Renders to a markdown table (capped preview) with row/column metadata. Uses only
the stdlib so it always works.
"""
import csv
from pathlib import Path

from .base import ExtractionResult

EXTRACTOR_ID = "tabular/csv@1"
MAX_PREVIEW_ROWS = 200


def _md_table(rows: list) -> str:
    if not rows:
        return ""
    width = max(len(r) for r in rows)
    rows = [r + [""] * (width - len(r)) for r in rows]
    header, body = rows[0], rows[1:]

    def esc(c: str) -> str:
        return str(c).replace("|", "\\|").replace("\n", " ")

    lines = ["| " + " | ".join(esc(c) for c in header) + " |",
             "| " + " | ".join(["---"] * width) + " |"]
    for r in body:
        lines.append("| " + " | ".join(esc(c) for c in r) + " |")
    return "\n".join(lines) + "\n"


def extract(source: Path, options: dict) -> ExtractionResult:
    warnings = []
    with open(source, newline="", encoding="utf-8", errors="replace") as f:
        sample = f.read(8192)
        f.seek(0)
        try:
            dialect = csv.Sniffer().sniff(sample) if sample.strip() else csv.excel
        except csv.Error:
            dialect = csv.excel
        rows = list(csv.reader(f, dialect))

    total = len(rows)
    cols = max((len(r) for r in rows), default=0)
    preview = rows[: MAX_PREVIEW_ROWS + 1]  # +1 for header
    if total > MAX_PREVIEW_ROWS + 1:
        warnings.append(f"table has {total} rows; previewed first {MAX_PREVIEW_ROWS}")

    content = _md_table(preview)
    metadata = {
        "rows": max(total - 1, 0),
        "columns": cols,
        "header": rows[0] if rows else [],
    }
    return ExtractionResult(content=content, metadata=metadata,
                            warnings=warnings, extractor=EXTRACTOR_ID)