import os
import gradio as gr
import pandas as pd
from pymongo import MongoClient
from datetime import datetime, timedelta
import plotly.express as px
import plotly.graph_objects as go

DB_USER = os.getenv("DB_USER")
DB_PASSWORD = os.getenv("DB_PASSWORD")
DB_HOST = os.getenv("DB_HOST")
client = MongoClient(host=f"mongodb+srv://{DB_USER}:{DB_PASSWORD}@{DB_HOST}/?retryWrites=true&w=majority")

#select database
db = client['algotrading']
#select the collection within the database

def fetch_all_strategy():
    global db
    delta = datetime.now() - timedelta(days=7)
    orders_t = db.orders
    strategies = pd.DataFrame(list(orders_t.find({}, {"strategy_id":1, "created_ts": 1})))
    strategies['created_ts'] = pd.to_datetime(strategies['created_ts'])
    strategies = strategies[~(strategies['created_ts'] <  delta)]
    return list(strategies['strategy_id'].unique())
    


def fetch_orders_for_strategy(strategy):
    global db
    orders_t = db.orders
    #convert entire collection to Pandas dataframe
    orders = pd.DataFrame(list(orders_t.find({"strategy_id": strategy})))
    # orders = orders.dropna(axis=0, subset=['open_price', 'close_price'])
    orders['open_price'] =  orders['open_price'].astype(str).astype(float)
    orders['close_price'] =  orders['close_price'].astype(str).astype(float)
    # orders['created_ts'] = pd.to_datetime(orders['created_ts'])
    orders['created_ts'] = pd.to_datetime(orders['created_ts'])
    orders['closed_ts'] = pd.to_datetime(orders['closed_ts'])
    orders['profit'] = orders['close_price'] - orders['open_price']
    orders['profit'] = orders['profit'].round(2)
    orders['created_date'] = orders['created_ts'].dt.date
    orders['ticker_open_price'] = pd.to_numeric(orders['ticker_open_price'], errors="coerce")
    orders['ticker_close_price'] = pd.to_numeric(orders['ticker_close_price'], errors="coerce")
    orders['ticker_open_price'] = orders['ticker_open_price'].astype(int, errors='ignore')
    orders['ticker_close_price'] = orders['ticker_close_price'].astype(int, errors='ignore')
    orders['ticker_delta'] = orders['ticker_close_price'] - orders['ticker_open_price']
    orders['ticker_delta'] = orders['ticker_delta'].round(2)
    orders['ticker_delta'] = orders.apply(lambda o: o['ticker_delta'] if o['market_position'] == 'long' else -o['ticker_delta'], axis=1)
    #market_position
    orders = orders.sort_values(by='created_ts', ascending=False)
    return orders

def create_latest_profit_plot(strategy, profits):
    if profits not in ["Profits", "Trades"]:
        return gr.update(visible=False)
    orders = fetch_orders_for_strategy(strategy)
    latest_day = orders[orders['strategy_id'] == strategy].sort_values(by='created_ts', ascending=False)['created_date'].unique()[0]
    cumsum = orders[(orders['created_date'] == latest_day) & (orders['strategy_id'] == strategy)] \
        .sort_values(by='created_ts', ascending=True) \
        .groupby(['strategy_id', 'created_ts'])['profit'].sum() \
        .groupby(level=0).cumsum().reset_index()
    plot = px.line(cumsum, x="created_ts", y="profit",
                   title=f"Profits for day for {strategy}")
    plot.update_layout(legend=dict(x=0.5, y=0.99),  title_x=0.5, legend_title_text="")

    trades_table = go.Figure(data=[go.Table(
        header=dict(values=list(['Created', 'Closed',  'Market Type', 'Symbol', 'Qty', 'Ticker Delta', 'Open', 'Close', 'Profit']),
                    align='left'),
        cells=dict(values=[
                            orders.created_ts.dt.strftime("%d-%b %H:%M"),
                            orders.closed_ts.dt.strftime("%d-%b %H:%M"),
                            # orders.ticker_open_price,
                            # orders.ticker_close_price,
                            orders.market_type,
                            orders.tradingsymbol,
                            orders.quantity,
                            orders.ticker_delta,
                            orders.open_price,
                            orders.close_price,
                            orders.profit])
                )
    ])

    profits_table = go.Figure(data=[go.Table(
        header=dict(values=list(['Created', 'Closed',  'Market Type',  'Qty', 'Ticker Delta',  'Profit']),
                    align='left'),
        cells=dict(values=[
                            orders.created_ts.dt.strftime("%d-%b %H:%M"),
                            orders.closed_ts.dt.strftime("%d-%b %H:%M"),
                            orders.market_type,
                            orders.quantity,
                            orders.ticker_delta,
                            orders.profit])
                )
    ])

    if profits == 'Profits':
        return [gr.update(value=plot, visible=True), gr.update(value=profits_table, visible=True), gr.update(value=plot, visible=False)]
    if profits == 'Trades':
        return [gr.update(value=plot, visible=False), gr.update(value=profits_table, visible=False), gr.update(value=trades_table, visible=True)]


with gr.Blocks() as demo:
    with gr.Row():
        with gr.Column():
            with gr.Box():
                gr.Markdown("## Select strategies to display")
                strategy = gr.Radio(choices=fetch_all_strategy(), label="")
        with gr.Column():
            with gr.Box():
                gr.Markdown("## Select graphs to display")
                type = gr.Radio(choices=["Profits", "Trades"], label="", value="Profits")
    with gr.Row():
        fetch = gr.Button(value="Fetch")
    with gr.Row():
        with gr.Column():
            profits_plot = gr.Plot(visible=False)
    with gr.Row():
            profits_table = gr.Plot(visible=False)
    with gr.Row():
        with gr.Column():
            trades_plot = gr.Plot(visible=False)


    fetch.click(create_latest_profit_plot, inputs=[strategy, type], outputs=[profits_plot, profits_table, trades_plot])
    # fetch.click(create_latest_profit_plot, inputs=[strategy, type], outputs=trades_plot)
    # fetch.click(create_issue_plot, inputs=[libraries, issues], outputs=issue_plot)


if __name__ == "__main__":
    demo.launch()