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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)
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