from __future__ import annotations

import pandas as pd
import plotly.graph_objects as go


def add_example_trade_markers(fig: go.Figure, example_trades: pd.DataFrame) -> None:
    if example_trades.empty:
        return

    long_entries = example_trades[example_trades["direction"] == "LONG"]
    short_entries = example_trades[example_trades["direction"] == "SHORT"]
    win_exits = example_trades[example_trades["outcome"] == "Win"]
    non_win_exits = example_trades[example_trades["outcome"] != "Win"]

    if not long_entries.empty:
        fig.add_trace(
            go.Scatter(
                x=long_entries["entry_timestamp"],
                y=long_entries["entry_price"],
                mode="markers",
                name="Example Entry (Long)",
                marker=dict(color="#1565C0", size=9, symbol="circle"),
            ),
            row=1,
            col=1,
        )
    if not short_entries.empty:
        fig.add_trace(
            go.Scatter(
                x=short_entries["entry_timestamp"],
                y=short_entries["entry_price"],
                mode="markers",
                name="Example Entry (Short)",
                marker=dict(color="#EF6C00", size=9, symbol="diamond"),
            ),
            row=1,
            col=1,
        )
    if not win_exits.empty:
        fig.add_trace(
            go.Scatter(
                x=win_exits["exit_timestamp"],
                y=win_exits["exit_price"],
                mode="markers",
                name="Example Exit (Win)",
                marker=dict(color="#2E7D32", size=10, symbol="x"),
            ),
            row=1,
            col=1,
        )
    if not non_win_exits.empty:
        fig.add_trace(
            go.Scatter(
                x=non_win_exits["exit_timestamp"],
                y=non_win_exits["exit_price"],
                mode="markers",
                name="Example Exit (Loss/Flat)",
                marker=dict(color="#C62828", size=10, symbol="x"),
            ),
            row=1,
            col=1,
        )


def highlight_selected_trade(
    fig: go.Figure,
    analyzed: pd.DataFrame,
    selected_trade: pd.Series | None,
    focus_chart_on_selected_example: bool,
) -> None:
    if selected_trade is None:
        return

    selected_entry_ts = pd.Timestamp(selected_trade["entry_timestamp"])
    selected_exit_ts = pd.Timestamp(selected_trade["exit_timestamp"])
    selected_entry_price = float(selected_trade["entry_price"])
    selected_exit_price = float(selected_trade["exit_price"])
    selected_direction = str(selected_trade["direction"])
    selected_outcome = str(selected_trade["outcome"])

    path_color = "#43A047" if selected_outcome == "Win" else ("#EF6C00" if selected_outcome == "Flat" else "#E53935")
    window_fill = "#BBDEFB" if selected_direction == "LONG" else "#FFE0B2"

    fig.add_vrect(
        x0=selected_entry_ts,
        x1=selected_exit_ts,
        fillcolor=window_fill,
        opacity=0.18,
        line_width=0,
        row=1,
        col=1,
    )
    fig.add_trace(
        go.Scatter(
            x=[selected_entry_ts, selected_exit_ts],
            y=[selected_entry_price, selected_exit_price],
            mode="lines+markers",
            name="Selected Example Path",
            line=dict(color=path_color, width=3, dash="dot"),
            marker=dict(color=path_color, size=11, symbol="star"),
        ),
        row=1,
        col=1,
    )

    if focus_chart_on_selected_example:
        entry_pos = int(analyzed.index.get_indexer([selected_entry_ts], method="nearest")[0])
        exit_pos = int(analyzed.index.get_indexer([selected_exit_ts], method="nearest")[0])
        left_pos = max(0, min(entry_pos, exit_pos) - 4)
        right_pos = min(len(analyzed) - 1, max(entry_pos, exit_pos) + 4)
        fig.update_xaxes(range=[analyzed.index[left_pos], analyzed.index[right_pos]])