def intraday():
try:
todatestring = str(datetime.datetime.now().date())
fromdatestring = todatestring[:-2] + '01'
tickerstring = request.args.get('tickerstring',
default='MSFT,AAPL',
type=str)
fromdatestring = request.args.get('fromdate',
default=fromdatestring,
type=str)
todatestring = request.args.get('todate',
default=todatestring,
type=str)
days = request.args.get('days', default=1, type=int)
import pullstackedreturns as psp
symbols = tickerstring.split(',')
fromdate, todate = fromdatestring, todatestring
df_final = pd.DataFrame()
for symbol in symbols:
df = pid.intradaystockprices(ticker=symbol, period=60, days=days)
if len(df_final) == 0:
df_final = df
else:
df_final = df_final.append(df, ignore_index=True)
df_final.index = df_final.index.map(str)
list_of_dicts = df_final.T.to_dict()
ret = jsonify({'intraday': list_of_dicts})
except Exception as inst:
ret = 'Main.py My error was caught: ' + str(inst)
return ret
def stockhistoryasdataframeindividual(symbols, fromdate, todate):
import pullintradayprices as pid
import pandas as pd
from datetime import datetime
p = stockhistory(symbols, fromdate, todate)
list_of_dicts = []
list_of_missing = []
try:
for d, item in p.swapaxes(0, 1).iteritems():
for t, x in item.iteritems():
if np.isnan(x['Adj Close']) == True:
list_of_missing.append({
'Date': d,
'Ticker': t,
'Adj Close': x['Adj Close'],
'Close': x['Close']
})
else:
list_of_dicts.append({
'Date': d,
'Ticker': t,
'Adj Close': x['Adj Close'],
'Close': x['Close']
})
sysdate = str(datetime.now()).split()[0]
if todate >= sysdate:
for s in symbols:
df = pid.intradaystockprices(ticker=s, period=60, days=1)
datex = df.tail(1).index[0]
myvalue = df.tail(1)['Close'][0]
list_of_dicts.append({
'Date': datex,
'Ticker': s,
'Adj Close': myvalue,
'Close': myvalue
})
except Exception as e:
print(e)
df_good = pd.DataFrame(list_of_dicts)
#print 'check',isinstance(df_good.index, pd.DatetimeIndex)
#datetime_object = datetime.strptime(sysdate, '%Y-%m-%d')
#longdate = sysdate + ' 00:00:00'
#df_good.drop(longdate, inplace=True)
df_missing = pd.DataFrame(list_of_missing)
return df_good, df_missing
def stockcurrentasdataframe(symbols, ):
import pullintradayprices as pid
list_of_dicts = []
for s in symbols:
df = pid.intradaystockprices(ticker=s, period=60, days=1)
d = df.tail(1).index[0]
myvalue = df.tail(1)['Close'][0]
list_of_dicts.append({
'Date': d,
'Ticker': s,
'Adj Close': myvalue,
'Close': myvalue
})
print list_of_dicts
return df
def stockhistoryasdataframeindividual(symbols, fromdate, todate):
#import numpy as np
import pullintradayprices as pid
import pandas as pd
p = stockhistory(symbols, fromdate, todate)
list_of_dicts = []
list_of_missing = []
try:
for d, item in p.swapaxes(0, 1).iteritems():
for t, x in item.iteritems():
if np.isnan(x['Adj Close']) == True:
list_of_missing.append({
'Date': d,
'Ticker': t,
'Adj Close': x['Adj Close'],
'Close': x['Close']
})
else:
list_of_dicts.append({
'Date': d,
'Ticker': t,
'Adj Close': x['Adj Close'],
'Close': x['Close']
})
# Append intraday price
#list_of_dicts = []
for s in symbols:
df = pid.intradaystockprices(ticker=s, period=60, days=1)
d = df.tail(1).index[0]
myvalue = df.tail(1)['Close'][0]
list_of_dicts.append({
'Date': d,
'Ticker': s,
'Adj Close': myvalue,
'Close': myvalue
})
except Exception as e:
print(e)
df_good = pd.DataFrame(list_of_dicts)
df_missing = pd.DataFrame(list_of_missing)
return df_good, df_missing
def getfile():
try:
if request.method == 'POST':
clearcontentsofcache()
print 'yyyyy'
date14 = str(datetime.datetime.now().strftime("%Y%m%d%H%M%S"))
feature = request.form['feature']
tickerstring = request.form['tickerstring']
fromdate = request.form['fromdate']
todate = request.form['todate']
tickerstring = "".join(tickerstring.split())
symbols = tickerstring.split(',')
feature = feature[:3].lower()
print 'check', tickerstring, feature
print symbols
if feature == 'cov':
myfilename = covariancematrix(symbols, fromdate, todate)
elif feature == 'cor':
myfilename = correlationmatrix(symbols, fromdate, todate)
elif feature == 'pri':
myfilename = 'prices_' + date14 + '.csv'
cachedfilepathname = os.path.join(app.config['UPLOAD_FOLDER'],
myfilename)
df = psp.stockpricesstacked(symbols, fromdate, todate)
df.to_csv(cachedfilepathname,
columns=(list(df.columns.values)))
time.sleep(1.5)
elif feature == 'adj':
myfilename = 'adjclose_' + date14 + '.csv'
cachedfilepathname = os.path.join(app.config['UPLOAD_FOLDER'],
myfilename)
df = psp.stockpricesstacked(symbols,
fromdate,
todate,
pricechangeortotal='total')
df.to_csv(cachedfilepathname,
columns=(list(df.columns.values)))
time.sleep(1.5)
elif feature == 'ret':
myfilename = 'returns_' + date14 + '.csv'
cachedfilepathname = os.path.join(app.config['UPLOAD_FOLDER'],
myfilename)
df = psr.stockreturnsstacked(symbols, fromdate, todate)
df.to_csv(cachedfilepathname,
columns=(list(df.columns.values)))
time.sleep(1.5)
elif feature == 'int':
print 'got here xxx'
myfilename = 'intraday_' + date14 + '.csv'
cachedfilepathname = os.path.join(app.config['UPLOAD_FOLDER'],
myfilename)
days = request.args.get('days', default=1, type=int)
df = pd.DataFrame()
for symbol in symbols:
print 'xx', symbol
df_x = pid.intradaystockprices(ticker=symbol,
period=60,
days=days)
if len(df) == 0:
df = df_x
else:
df = df.append(df_x)
df.to_csv(cachedfilepathname,
columns=(list(df.columns.values)))
time.sleep(1.5)
ret = 'Successfully executed.'
return send_file('cache/' + myfilename,
mimetype='text/csv',
attachment_filename=myfilename,
as_attachment=True)
else:
#print 'xxx'
return initial_html
except Exception as inst:
ret = 'getfile My error was caught: ' + str(inst)
return initial_html