#!/usr/bin/env python3
"""Show alpha weight(s) alongside daily bar data for a single symbol.

Joins the bar dataset and one or more alpha parquet files on (symbol, date) so
you can eyeball how a weight moves against price/volume over a time range.
"""

import click
import pandas as pd


def _filter_dates(df, start_date, end_date):
    if start_date:
        df = df[df["date"] >= pd.Timestamp(start_date)]
    if end_date:
        df = df[df["date"] <= pd.Timestamp(end_date)]
    return df


@click.command(name="alphaview")
@click.option("--data-path", required=True, type=click.Path(exists=True), help="Bar dataset dir or parquet file")
@click.option("--alpha-path", "alpha_paths", required=True, help="Comma-separated alpha parquet path(s)")
@click.option("--symbol", required=True, help="Symbol id, e.g. sh600000")
@click.option("--start-date", default=None, help="YYYY-MM-DD (inclusive)")
@click.option("--end-date", default=None, help="YYYY-MM-DD (inclusive)")
@click.option("-c", "--columns", default="close,volume", help="Comma-separated bar columns to show")
def alphaview(data_path, alpha_paths, symbol, start_date, end_date, columns):
    """Print bar columns + alpha weight(s) for SYMBOL over a date range."""
    bar_cols = [c.strip() for c in columns.split(",") if c.strip()]

    bars = pd.read_parquet(data_path)
    bars = bars[bars["symbol_id"] == symbol]
    if bars.empty:
        raise click.ClickException(f"Symbol {symbol!r} not found in {data_path}")
    missing = [c for c in bar_cols if c not in bars.columns]
    if missing:
        raise click.ClickException(f"Bar columns not found: {', '.join(missing)}")
    bars = _filter_dates(bars, start_date, end_date)
    out = bars[["date", *bar_cols]].set_index("date").sort_index()

    for path in (p.strip() for p in alpha_paths.split(",") if p.strip()):
        adf = pd.read_parquet(path)
        adf = adf[adf["symbol_id"] == symbol]
        adf = _filter_dates(adf, start_date, end_date)
        # One alpha file may carry multiple alpha_name values; spread to columns.
        wide = adf.pivot_table(index="date", columns="alpha_name", values="weight")
        out = out.join(wide, how="left")

    if out.empty:
        raise click.ClickException("No rows in the requested date range")

    with pd.option_context("display.max_rows", None, "display.max_columns", None, "display.width", None):
        click.echo(f"symbol: {symbol}  rows: {len(out):,}")
        click.echo(out.to_string())


if __name__ == "__main__":
    alphaview()