from __future__ import annotations

import altair as alt
import pandas as pd


def build_trend_chart(dataframe: pd.DataFrame, show_error_bands: bool = False) -> alt.Chart | None:
    if dataframe.empty:
        return None

    chart_data = dataframe.copy()
    chart_data = chart_data.dropna(subset=["timestamp", "value"])
    if chart_data.empty:
        return None

    chart_data["repo_class"] = chart_data["repo_id"] + " | " + chart_data["class"]

    base = alt.Chart(chart_data).encode(
        x=alt.X("timestamp:T", title="Time"),
        y=alt.Y("value:Q", title="Metric value"),
        color=alt.Color("repo_id:N", title="Repo"),
        strokeDash=alt.StrokeDash("class:N", title="Class"),
        tooltip=[
            alt.Tooltip("timestamp:T", title="Timestamp"),
            alt.Tooltip("repo_id:N", title="Repo"),
            alt.Tooltip("revision:N", title="Revision"),
            alt.Tooltip("class:N", title="Class"),
            alt.Tooltip("metric:N", title="Metric"),
            alt.Tooltip("value:Q", title="Value", format=".4f"),
            alt.Tooltip("std:Q", title="Std", format=".4f"),
        ],
    )

    line = base.mark_line(point=True)

    chart: alt.Chart | alt.LayerChart = line
    band_data = chart_data.dropna(subset=["std"]).copy()
    if show_error_bands and not band_data.empty:
        band_data["lower"] = band_data["value"] - band_data["std"]
        band_data["upper"] = band_data["value"] + band_data["std"]

        band = alt.Chart(band_data).mark_area(opacity=0.15).encode(
            x=alt.X("timestamp:T", title="Time"),
            y=alt.Y("lower:Q", title="Metric value"),
            y2="upper:Q",
            color=alt.Color("repo_id:N", title="Repo"),
            detail="repo_class:N",
        )
        chart = band + line

    metric_count = chart_data["metric"].nunique()
    if metric_count > 1:
        return chart.facet(row=alt.Row("metric:N", title=None)).resolve_scale(y="independent")

    return chart


def build_latest_comparison_chart(dataframe: pd.DataFrame, metric: str) -> alt.Chart | None:
    if dataframe.empty:
        return None

    latest = dataframe[dataframe["is_latest"] & (dataframe["metric"] == metric)].dropna(subset=["value"])
    if latest.empty:
        return None

    return (
        alt.Chart(latest)
        .mark_bar()
        .encode(
            x=alt.X("repo_id:N", title="Repo", sort="-y"),
            y=alt.Y("value:Q", title=f"Latest {metric}"),
            color=alt.Color("class:N", title="Class"),
            tooltip=[
                alt.Tooltip("repo_id:N", title="Repo"),
                alt.Tooltip("revision:N", title="Revision"),
                alt.Tooltip("class:N", title="Class"),
                alt.Tooltip("value:Q", title="Value", format=".4f"),
                alt.Tooltip("std:Q", title="Std", format=".4f"),
            ],
        )
    )


def build_class_small_multiples(dataframe: pd.DataFrame, metric: str) -> alt.Chart | None:
    if dataframe.empty:
        return None

    plot_df = dataframe[dataframe["metric"] == metric].dropna(subset=["value"])
    if plot_df.empty:
        return None

    chart = (
        alt.Chart(plot_df)
        .mark_line(point=True)
        .encode(
            x=alt.X("timestamp:T", title="Time"),
            y=alt.Y("value:Q", title=metric),
            color=alt.Color("repo_id:N", title="Repo"),
            tooltip=[
                alt.Tooltip("timestamp:T", title="Timestamp"),
                alt.Tooltip("repo_id:N", title="Repo"),
                alt.Tooltip("revision:N", title="Revision"),
                alt.Tooltip("class:N", title="Class"),
                alt.Tooltip("value:Q", title="Value", format=".4f"),
            ],
        )
    )

    return chart.facet(column=alt.Column("class:N", title=None, sort="ascending"))