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from dash import Dash, dcc, html, Input, Output, dash_table
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 summarize_results
import pytz
import pandas as pd
app = Dash(__name__)
# pull the data from the files
table_data, algos_to_results = summarize_results('test-1-ema')
app.layout = html.Div([
html.H4('Backtesting using EMA algos [ALPHA VERSION 0.1.0]'),
dcc.Dropdown(
id='batch_name',
options=[
{'label': 'Test 1 - EMA', 'value': 'test-1-ema'}
],
value='test-1-ema',
clearable=False
),
html.Hr(),
dash_table.DataTable(
table_data.to_dict('records'),
[{"name": i, "id": i} for i in table_data.columns],
style_table={'overflowX': 'auto'},
style_cell={'textAlign': 'center'},
style_header={
'backgroundColor': 'rgb(230, 230, 230)',
'fontWeight': 'bold'
},
style_data={
'whiteSpace': 'normal',
'height': 'auto'
},
sort_action='native',
),
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"),
# for each algo, print the individual results given by the map
html.Div(id='algo_results', children=[
html.Div([
html.Div([
])
]) for algo_name, result in algos_to_results.items()
])
])
@app.callback(
Input("batch_name", "value"),
)
def display_color(batch_name):
# compute the results to show in the table
path = batch_name
result_summary = summarize_results(path)
if not result_summary:
return "No results found for the given file ID."
# update the table data
global table_data
table_data = result_summary
# table = go.Figure(
# data = [go.Table(
# header=dict(values=["algo name", "algo params", "avg percent gain", "best stock for gain"]),
# 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
app.run(debug=True)
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