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app.py
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app.py
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from dash import Dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Output, Input, State
from dateutil.relativedelta import relativedelta
import plotly.graph_objs as go
import datetime
import pandas as pd
import requests
from pandas_datareader import data, wb
import datetime
import urllib
import time
import csv
from models.prophet import prophet_predict, stock_extractor
import os
import os.path
from os import path
start = datetime.datetime.today() - relativedelta(years=5)
end = datetime.datetime.today()
app = Dash(__name__)
colors = {
'background': '#f0e6e6',
'text': '#ffffff'
}
app.layout = html.Div([
html.Div([
html.H2("Stock Prediction"),
html.Img(src="assets/images.jpg")
], className="banner"),
html.Div([
dcc.Input(id="stock-input", value="IOC.NS", type="text"),
html.Button(id="submit-button", n_clicks=0, children="Submit")
]),
html.Div([
html.Div([
dcc.Graph(
id="graph_close",
)
], className="six columns"),
],className="row")
])
app.css.append_css({
"external_url":"https://codepen.io/chriddyp/pen/bWLwgP.css"
})
@app.callback(Output('graph_close', 'figure'),
[Input("submit-button", "n_clicks")],
[State("stock-input", "value")]
)
def update_fig(n_clicks, symbol):
from pandas_datareader import data, wb
# checking for stock file
if path.exists(f"./src/stock_price_{symbol}.csv"):
df= pd.read_csv(f'./src/stock_price_{symbol}.csv')
print(f'raw file already exist for date : {end}')
else:
stock_extractor(symbol)
print('data generated')
df= pd.read_csv(f'./src/stock_price_{symbol}.csv')
# checking for prediction file
if path.exists(f'./out/pred_prophet_{symbol}.csv'):
df_pred = pd.read_csv(f'out/pred_prophet_{symbol}.csv')
print('prediction file already existed')
else:
print('Generating prediction file')
prophet_predict(symbol)
time.sleep(3)
df_pred = pd.read_csv(f'out/pred_prophet_{symbol}.csv')
trace_line = go.Scatter(x=list(df.Date),
y=list(df.Close),
#visible=False,
name="Close",
showlegend=False)
trace_candle = go.Candlestick(x=df.Date,
open=df.Open,
high=df.High,
low=df.Low,
close=df.Close,
#increasing=dict(line=dict(color="#00ff00")),
#decreasing=dict(line=dict(color="white")),
visible=False,
showlegend=False)
pred_line = go.Scatter(x=list(df_pred.ds),
y=list(df_pred.yhat_upper),
#visible=False,
name="Prediction",
showlegend=False)
data = [trace_line, trace_candle, pred_line]
updatemenus = list([
dict(
buttons=list([
dict(
args=[{'visible': [True, False, False]}],
label='Line',
method='update'
),
dict(
args=[{'visible': [False, True, False]}],
label='Candle',
method='update'
),
dict(
args=[{'visible': [False, False, True]}],
label='Bar',
method='update'
),
]),
direction='down',
pad={'r': 10, 't': 10},
showactive=True,
x=0,
xanchor='left',
y=1.05,
yanchor='top'
),
])
layout = dict(
title=symbol,
updatemenus=updatemenus,
autosize=False,
plot_bgcolor=colors['background'],
paper_bgcolor=colors['background'],
font_color=colors['text'],
xaxis_title='Time stamp',
yaxis_title='stock Price',
xaxis=dict(
rangeselector=dict(
buttons=list([
dict(count=1,
label='1m',
step='month',
stepmode='backward'),
dict(count=6,
label='6m',
step='month',
stepmode='backward'),
dict(count=1,
label='YTD',
step='year',
stepmode='todate'),
dict(count=1,
label='1y',
step='year',
stepmode='backward'),
dict(step='all')
])
),
rangeslider=dict(
visible=True
),
type='date'
)
)
return {
"data": data,
"layout": layout
}
if __name__=="__main__":
app.run_server(debug=True, port=5001)