from dash import Dash, dcc, html, Input, Output
import plotly.graph_objects as go
import json
from datetime import datetime, timedelta
from ema_algo import Ema_Algo
from api import fetch_chart_data_yahoo
from analysis import compute_results
import pytz

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 EMA algos [ALPHA VERSION 0.0.5]'),
    dcc.table(id="results_table")
    dcc.Input(id="file_id", value="SPY", type="text"),
    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("results_table", "figure"),
    Output("graph", "figure"),
    Output("error_message", "children"),
    Input("file_id", "value"),
    )
def display_color(file_id):
        # compute the results to show in the table
        path = 'test-1-ema'
        result_summary = compute_results(path, file_id)
        if not result_summary:
            return go.Figure(), go.Figure(), "No results found for the given file ID."
        
        print(result_summary)

        table = go.Figure(
                data = [go.Table(
                        header=dict(values=["algo name", "algo params", "avg percent gain", "best stock order"]),
                        cells=dict(values=result_summary)
                )]
        )
        data = fetch_chart_data_yahoo('XRP-USD', '1d', None, timedelta(weeks=52))
        times = [datetime.fromtimestamp(t).astimezone(pytz.timezone('US/Eastern')) for t in data['timestamps']]
        comp_scatter = go.Scatter(name='Price (yahoo)', x=times, y=data['prices'], line=dict(color='rgb(255, 0, 0)'), mode='lines')
        fig = go.Figure(
            data = [
                go.Scatter(name='Price', x=timestamps, y=prices, line=dict(color='rgb(0, 0, 0)'), mode='lines'), 
                comp_scatter
            ] 
            # + 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)