import pandas as pd
from rcounting import thread_navigation as tn, plots
from rcounting.counters import apply_alias
from pathlib import Path
import click

CONTEXT_SETTINGS = dict(help_option_names=["-h", "--help"])


@click.command(context_settings=CONTEXT_SETTINGS)
@click.argument("comment_id")
@click.option(
    "-l",
    "--length",
    default=1000,
    help="An upper bound for the run length. Used to avoid fetching more comments than necessary",
)
@click.option(
    "-f",
    "--filename",
    type=click.Path(path_type=Path),
    help="What file to save the histogram to. If none is specified, `histogram.png` is used",
)
@click.option(
    "--seaborn/--matplotlib",
    default=False,
    help="Use the default matplotlib style for the plot, or seaborn.",
)
def analyse_run(comment_id, length, seaborn, filename):
    """Generate a histogram of the run of counts ending in COMMENT_ID.

    Load at least LENGTH comments, and then restrict the comments to only the
    latest volley between the two most active counters in the loaded comments.
    """
    if seaborn:
        import seaborn as sns

        sns.set_theme()
    comments = pd.DataFrame(
        tn.fetch_comments(comment_id, limit=length if length < 1000 else None)
    )
    comments["dt"] = comments["timestamp"].diff()
    comments["username"] = comments["username"].apply(apply_alias)
    if comments["username"].nunique() > 2:
        counters = comments["username"].value_counts().head(2).index
        comments = comments.iloc[
            comments.query("username not in @counters").index[-1] + 1 :
        ].copy()
    fig = plots.speedrun_histogram(comments, n=2)
    if filename is None:
        filename = "histogram.png"
    fig.savefig(filename, bbox_inches="tight")
    print(
        comments.loc[comments["dt"] <= 10]
        .groupby("username")["dt"]
        .describe()
        .to_markdown()
    )


if __name__ == "__main__":
    analyse_run()