from dash import Dash, dcc, html, Input, Output
import plotly.graph_objects as go
import json
from datetime import datetime
from ema_algo import Ema_Algo

app = Dash(__name__)

# pull stock data from json files
# timestamps_file = open('timestamps.json', 'r')
# timestamps_file_data = timestamps_file.read()
# timestamps_raw = json.loads(timestamps_file_data)
# timestamps = [datetime.datetime.fromtimestamp(t) for t in timestamps_raw]

# prices_file = open('close_prices.json', 'r')
# prices = json.loads(prices_file.read())

# intersection_indices = find_intersections(ema_5, ema_13, offset=13) # offset so don't calculate the SMA days
# interpolated_intersections = [interpolate_intersection(indices, timestamps, ema_5, ema_13) for indices in intersection_indices]
# intersected_x = []
# intersected_y = []
# for x,y in interpolated_intersections:
#     intersected_x.append(x)
#     intersected_y.append(y)

app.layout = html.Div([
    html.H4('Backtesting using the EMA method (5 vs 13) [ALPHA VERSION 0.0.2]'),
    html.Div(
        [
            html.Label("Ticker ", htmlFor="ticker"),
            dcc.Input(id="ticker", value="SPY", type="text"),
            html.Br(),
            html.Label("Period ", htmlFor="period_dropdown"),
            dcc.Dropdown(
                id="period_dropdown",
                options=["1d","5d","1mo","3mo","6mo","1y","2y","5y","10y","ytd","max"],
                value = "1y"),
            html.Br(),
            html.Label("Interval ", htmlFor="interval_dropdown"),
            dcc.Dropdown(
                id="interval_dropdown",
                options=["1m", "2m", "5m", "15m", "30m", "60m", "90m", "1h", "4h", "1d", "5d", "1wk", "1mo", "3mo"],
                value = "1d",
            ),
            html.P(id='error_message'),
        ],
        id='input_params'
    ),
    html.Hr(),
    dcc.Graph(id="graph"),
    html.P("If bought and sold on these signals, the percent gain/loss would be:"),
    html.P(id="percent_gain")

])

@app.callback(
    Output("graph", "figure"),
    Output("percent_gain", "children"),
    Output("input_params", "style"),
    Output("error_message", "children"),
    Input("ticker", "value"),
    Input("period_dropdown", "value"),
    Input("interval_dropdown", "value")
    )
def display_color(ticker, period, interval):
        fd = open('bt-recent.json', 'r')
        raw_data = fd.read()
        trial_data = json.loads(raw_data)
        fd.close()

        chart_data = trial_data['chart_data']
        backtest_results = trial_data['backtest_results']
        url_params = trial_data['url_params']

        percent_gain = backtest_results['percent_gain']
        error_style = {"color" : "red"}
        error_message = "False error"

        # Code to execute no matter what (optional)

        raw_timestamps = chart_data['timestamps']
        timestamps = [datetime.fromtimestamp(t) for t in raw_timestamps]
        prices = chart_data['prices']

        # test to see if graphc works, TODO make it abstracted
        algoEMA = Ema_Algo()
        algo_graph_data = backtest_results['algo_graph_data']
        algo_graphs = algoEMA.export_graph(algo_graph_data)

        buy_indices = backtest_results['buy_indices']
        sell_indices = backtest_results['sell_indices']

        buy_prices, buy_times = [], []
        for i in buy_indices:
                buy_prices.append(prices[i])
                buy_times.append(timestamps[i])
        sell_prices, sell_times = [], []
        for i in sell_indices:
                sell_prices.append(prices[i])
                sell_times.append(timestamps[i])
        buy_sell_scatters = [
                go.Scatter(name='Buys', x=buy_times, y=buy_prices, line=dict(color='rgb(0, 0, 255)'), mode='markers', marker_size=10),
                go.Scatter(name='Sells', x=sell_times, y=sell_prices, line=dict(color='rgb(255, 255, 0)'), mode='markers', marker_size=10)
        ]
        fig = go.Figure(
            data = [
                go.Scatter(name='Price', x=timestamps, y=prices, line=dict(color='rgb(0, 0, 0)'), mode='lines'), 
            ] + algo_graphs + buy_sell_scatters,
            layout = go.Layout(
                title=go.layout.Title(text='Chart for ' + chart_data['name']),
                xaxis=go.layout.XAxis(title='Date (dt=' + url_params['interval'] + ', range=' + url_params['period'] + ')'),
                yaxis=go.layout.YAxis(title='Price ($)')
            )
        )
        return fig, percent_gain, error_style, error_message



app.run(debug=True)