"""Load one ForensicBench sector into a PostgreSQL database.

Usage:
    python tools/load_postgres.py --sector energy --dsn "dbname=forensicbench_energy user=postgres"

The database must already exist. Tables are created from the parquet schemas.
Requires: pandas, pyarrow, psycopg2-binary.
"""
import argparse, io
import pandas as pd
import pyarrow.parquet as pq
import psycopg2

PG_TYPES = {"string": "text", "large_string": "text", "int64": "bigint", "int32": "integer",
            "double": "double precision", "float": "real", "bool": "boolean",
            "date32[day]": "date"}
TABLES = ["je_header", "je_line", "chart_of_accounts", "vendors", "customers", "employees"]

def pg_type(arrow_type) -> str:
    s = str(arrow_type)
    if s.startswith("timestamp"):
        return "timestamp"
    return PG_TYPES.get(s, "text")

def main():
    ap = argparse.ArgumentParser()
    ap.add_argument("--sector", required=True, choices=["energy", "healthcare", "luxurygoods", "manufacturing", "transport"])
    ap.add_argument("--dsn", required=True)
    ap.add_argument("--data-dir", default="data")
    args = ap.parse_args()
    conn = psycopg2.connect(args.dsn)
    cur = conn.cursor()
    for t in TABLES:
        path = f"{args.data_dir}/{args.sector}/{t}.parquet"
        schema = pq.read_schema(path)
        cols = ", ".join(f'"{f.name}" {pg_type(f.type)}' for f in schema)
        cur.execute(f'DROP TABLE IF EXISTS {t} CASCADE')
        cur.execute(f'CREATE TABLE {t} ({cols})')
        df = pd.read_parquet(path)
        buf = io.StringIO()
        df.to_csv(buf, index=False, header=False, na_rep="\\N")
        buf.seek(0)
        cur.copy_expert(f"COPY {t} FROM STDIN WITH (FORMAT csv, NULL '\\N')", buf)
        print(f"{t}: {len(df)} rows")
    cur.execute("CREATE INDEX IF NOT EXISTS je_line_doc ON je_line (document_id)")
    cur.execute("CREATE INDEX IF NOT EXISTS je_header_doc ON je_header (document_id)")
    conn.commit()
    conn.close()

if __name__ == "__main__":
    main()