import pandas as pd
import gradio as gr
import matplotlib.pyplot as plt
import seaborn as sns
from typing import Tuple
import plotly.express as px


def plot_kl_div_per_market(closed_markets: pd.DataFrame) -> gr.Plot:

    # adding the total
    all_markets = closed_markets.copy(deep=True)
    all_markets["market_creator"] = "all"

    # merging both dataframes
    final_markets = pd.concat([closed_markets, all_markets], ignore_index=True)
    final_markets = final_markets.sort_values(by="opening_datetime", ascending=True)

    fig = px.box(
        final_markets,
        x="month_year_week",
        y="kl_divergence",
        color="market_creator",
        color_discrete_sequence=["purple", "goldenrod", "darkgreen"],
        category_orders={"market_creator": ["pearl", "quickstart", "all"]},
    )
    fig.update_traces(boxmean=True)
    fig.update_layout(
        xaxis_title="Markets closing Week",
        yaxis_title="Kullback–Leibler divergence",
        legend=dict(yanchor="top", y=0.5),
    )
    fig.update_xaxes(tickformat="%b %d\n%Y")

    return gr.Plot(
        value=fig,
    )