diff options
Diffstat (limited to 'app.py')
| -rw-r--r-- | app.py | 134 |
1 files changed, 81 insertions, 53 deletions
@@ -1,5 +1,7 @@ from dash import Dash, dcc, html, Input, Output -from analysis import calc_emas, find_intersections, interpolate_intersection, calculate_profit +from analysis import find_intersections, interpolate_intersection +from api import fetch_chart_data +from ema import calc_emas, calculate_profit import plotly.graph_objects as go import json import datetime @@ -7,71 +9,97 @@ import datetime 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] +# 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()) +# prices_file = open('close_prices.json', 'r') +# prices = json.loads(prices_file.read()) -ema_5 = calc_emas(5, prices) -ema_13 = calc_emas(13, prices) - -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) - -profit = calculate_profit(ema_5, ema_13, prices, timestamps, 13) -buy_info = profit[-2] -buy_x = [] -buy_y = [] -for x,y,_ in buy_info: - buy_x.append(x) - buy_y.append(y) - -sell_info = profit[-1] -sell_x = [] -sell_y = [] -for x,y,_ in sell_info: - sell_x.append(x) - sell_y.append(y) - -print("Result Analysis:\n", "Percent gain/loss:\t", profit[0]) -percent_gain = profit[0] * 100 +# 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) +percent_gain = 0 +memo_fig = None app.layout = html.Div([ html.H4('Interactive color selection with simple Dash example'), - html.P("Select color:"), + html.Label("Ticker ", htmlFor="ticker"), + dcc.Input(id="ticker", value="SPY", type="text"), + html.Br(), + html.Label("Period ", htmlFor="period"), dcc.Dropdown( - id="dropdown", - options=['Gold', 'MediumTurquoise', 'LightGreen'], - value='Gold', - clearable=False, + id="period_dropdown", + options=["1d","5d","1mo","3mo","6mo","1y","2y","5y","10y","ytd","max"], + value = "1y", ), + html.Br(), + html.Label("Interval ", htmlFor="Interval"), + dcc.Dropdown( + id="interval_dropdown", + options=["1m", "2m", "5m", "15m", "30m", "60m", "90m", "1h", "4h", "1d", "5d", "1wk", "1mo", "3mo"], + value = "1d", + ), + html.Hr(), dcc.Graph(id="graph"), - html.P("If bought and sold on these signals, the percent gain/loss would be: " + str(round(percent_gain, 4))) + html.P("If bought and sold on these signals, the percent gain/loss would be: " + str(percent_gain)) ]) @app.callback( Output("graph", "figure"), - Input("dropdown", "value")) -def display_color(color): - fig = go.Figure( - [ - go.Scatter(name='Price', x=timestamps, y=prices, line=dict(color='rgb(0, 255, 0)'), mode='lines'), - # go.Scatter(name='5 day EMA', x=timestamps, y=ema_5, line=dict(color='rgb(0, 255, 0)'), mode='lines'), - # go.Scatter(name='13 day EMA', x=timestamps, y=ema_13, line=dict(color='rgb(0, 0, 255)'), mode='lines'), - # go.Scatter(name='EMA Intersections', x=intersected_x, y=intersected_y, line=dict(color='rgb(255, 0, 0)'), mode='markers') - go.Scatter(name='Buys', x=buy_x, y=buy_y, line=dict(color='rgb(0, 0, 255)'), mode='markers', marker_size=10), - go.Scatter(name='Sells', x=sell_x, y=sell_y, line=dict(color='rgb(255, 255, 0)'), mode='markers', marker_size=10), - ] + Input("ticker", "value"), + Input("period_dropdown", "value"), + Input("interval_dropdown", "value") ) - return fig +def display_color(ticker, period, interval): + try: + chart_data = fetch_chart_data(ticker, period, interval) + except: + return memo_fig + else: + timestamps_raw = chart_data['timestamps'] + timestamps = [datetime.datetime.fromtimestamp(t) for t in timestamps_raw] + prices = chart_data['prices'] + + ema_5 = calc_emas(5, prices) + ema_13 = calc_emas(13, prices) + profit = calculate_profit(ema_5, ema_13, prices, timestamps, 13) + buy_info = profit[-2] + buy_x = [] + buy_y = [] + for x,y,_ in buy_info: + buy_x.append(x) + buy_y.append(y) + + sell_info = profit[-1] + sell_x = [] + sell_y = [] + for x,y,_ in sell_info: + sell_x.append(x) + sell_y.append(y) + + print("Result Analysis:\n", "Percent gain/loss:\t", profit[0], profit[1], profit[2]) + percent_gain = profit[0] * 100 + finally: + # Code to execute no matter what (optional) + fig = go.Figure( + [ + go.Scatter(name='Price', x=timestamps, y=prices, line=dict(color='rgb(0, 0, 0)'), mode='lines'), + # go.Scatter(name='5 day EMA', x=timestamps, y=ema_5, line=dict(color='rgb(0, 255, 0)'), mode='lines'), + # go.Scatter(name='13 day EMA', x=timestamps, y=ema_13, line=dict(color='rgb(0, 0, 255)'), mode='lines'), + # go.Scatter(name='EMA Intersections', x=intersected_x, y=intersected_y, line=dict(color='rgb(255, 0, 0)'), mode='markers'), + go.Scatter(name='Buys', x=buy_x, y=buy_y, line=dict(color='rgb(0, 0, 255)'), mode='markers', marker_size=10), + go.Scatter(name='Sells', x=sell_x, y=sell_y, line=dict(color='rgb(255, 255, 0)'), mode='markers', marker_size=10), + ] + ) + print(ticker, period, interval) + memo_fig = fig + return fig app.run(debug=True)
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