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fixed time zone bug #9

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fixed time zone bug #9

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42 changes: 32 additions & 10 deletions googlefinance/client.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,9 +2,11 @@
import requests
from datetime import datetime
import pandas as pd
import pytz

def get_price_data(query):
r = requests.get("https://finance.google.com/finance/getprices", params=query)
# print(r.url)
lines = r.text.splitlines()
data = []
index = []
Expand All @@ -13,11 +15,15 @@ def get_price_data(query):
cols = price.split(",")
if cols[0][0] == 'a':
basetime = int(cols[0][1:])
index.append(datetime.fromtimestamp(basetime))
# index.append(datetime.fromtimestamp(basetime))
index.append(datetime.fromtimestamp(basetime, pytz.timezone(
'America/New_York')))
data.append([float(cols[4]), float(cols[2]), float(cols[3]), float(cols[1]), int(cols[5])])
elif cols[0][0].isdigit():
date = basetime + (int(cols[0])*int(query['i']))
index.append(datetime.fromtimestamp(date))
# index.append(datetime.fromtimestamp(date))
index.append(datetime.fromtimestamp(date, pytz.timezone(
'America/New_York')))
data.append([float(cols[4]), float(cols[2]), float(cols[3]), float(cols[1]), int(cols[5])])
return pd.DataFrame(data, index = index, columns = ['Open', 'High', 'Low', 'Close', 'Volume'])

Expand All @@ -37,11 +43,15 @@ def get_closing_data(queries, period):
basetime = int(cols[0][1:])
date = basetime
data.append(float(cols[1]))
index.append(datetime.fromtimestamp(date).date())
# index.append(datetime.fromtimestamp(date).date())
index.append(datetime.fromtimestamp(basetime, pytz.timezone(
'America/New_York')))
elif cols[0][0].isdigit():
date = basetime + (int(cols[0])*int(query['i']))
data.append(float(cols[1]))
index.append(datetime.fromtimestamp(date).date())
# index.append(datetime.fromtimestamp(date).date())
index.append(datetime.fromtimestamp(date, pytz.timezone(
'America/New_York')))
s = pd.Series(data,index=index,name=query['q'])
closing_data.append(s[~s.index.duplicated(keep='last')])
return pd.concat(closing_data, axis=1)
Expand All @@ -62,11 +72,15 @@ def get_open_close_data(queries, period):
basetime = int(cols[0][1:])
date = basetime
data.append([float(cols[4]), float(cols[1])])
index.append(datetime.fromtimestamp(date).date())
# index.append(datetime.fromtimestamp(date).date())
index.append(datetime.fromtimestamp(basetime, pytz.timezone(
'America/New_York')))
elif cols[0][0].isdigit():
date = basetime + (int(cols[0])*int(query['i']))
data.append([float(cols[4]), float(cols[1])])
index.append(datetime.fromtimestamp(date).date())
# index.append(datetime.fromtimestamp(date).date())
index.append(datetime.fromtimestamp(date, pytz.timezone(
'America/New_York')))
df = pd.DataFrame(data, index=index, columns=[query['q']+'_Open',query['q']+'_Close'])
open_close_data = pd.concat([open_close_data, df[~df.index.duplicated(keep='last')]], axis=1)
return open_close_data
Expand All @@ -87,11 +101,15 @@ def get_prices_data(queries, period):
basetime = int(cols[0][1:])
date = basetime
data.append([float(cols[4]), float(cols[2]), float(cols[3]), float(cols[1]), int(cols[5])])
index.append(datetime.fromtimestamp(date).date())
# index.append(datetime.fromtimestamp(date).date())
index.append(datetime.fromtimestamp(basetime, pytz.timezone(
'America/New_York')))
elif cols[0][0].isdigit():
date = basetime + (int(cols[0])*int(query['i']))
data.append([float(cols[4]), float(cols[2]), float(cols[3]), float(cols[1]), int(cols[5])])
index.append(datetime.fromtimestamp(date).date())
# index.append(datetime.fromtimestamp(date).date())
index.append(datetime.fromtimestamp(date, pytz.timezone(
'America/New_York')))
df = pd.DataFrame(data, index=index, columns=[query['q']+'_Open',query['q']+'_High',query['q']+'_Low',query['q']+'_Close',query['q']+'_Volume'])
prices_data = pd.concat([prices_data, df[~df.index.duplicated(keep='last')]], axis=1)
return prices_data
Expand All @@ -112,11 +130,15 @@ def get_prices_time_data(queries, period, interval):
basetime = int(cols[0][1:])
date = basetime
data.append([float(cols[4]), float(cols[2]), float(cols[3]), float(cols[1]), int(cols[5])])
index.append(datetime.fromtimestamp(date))
# index.append(datetime.fromtimestamp(date))
index.append(datetime.fromtimestamp(basetime, pytz.timezone(
'America/New_York')))
elif cols[0][0].isdigit():
date = basetime + (int(cols[0])*int(query['i']))
data.append([float(cols[4]), float(cols[2]), float(cols[3]), float(cols[1]), int(cols[5])])
index.append(datetime.fromtimestamp(date))
# index.append(datetime.fromtimestamp(date))
index.append(datetime.fromtimestamp(date, pytz.timezone(
'America/New_York')))
df = pd.DataFrame(data, index=index, columns=[query['q']+'_Open',query['q']+'_High',query['q']+'_Low',query['q']+'_Close',query['q']+'_Volume'])
prices_time_data = pd.concat([prices_time_data, df[~df.index.duplicated(keep='last')]], axis=1)
return prices_time_data
Expand Down