googlefinance.client 1.1.1

googlefinance.client is a python client library for google finance api.

googlefinance.client is a python client library for google finance api

Installation

$ pip install googlefinance.client

Usage

from googlefinance.client import get_price_data, get_closing_data, get_open_close_data

# Dow Jones
param = {
    'q': ".DJI", # Stock symbol (ex: "AAPL")
    'i': "86400", # Interval size in seconds ("86400" = 1 day intervals)
    'x': "INDEXDJX", # Stock exchange symbol on which stock is traded (ex: "NASD")
    'p': "1Y" # Period (Ex: "1Y" = 1 year)
}
# get price data (return pandas dataframe)
df = get_price_data(param)
print(df)
#                          Open      High       Low     Close     Volume
# 2016-05-17 05:00:00  17531.76   17755.8  17531.76  17710.71   88436105
# 2016-05-18 05:00:00  17701.46  17701.46  17469.92  17529.98  103253947
# 2016-05-19 05:00:00  17501.28  17636.22  17418.21  17526.62   79038923
# 2016-05-20 05:00:00  17514.16  17514.16  17331.07   17435.4   95531058
# 2016-05-21 05:00:00  17437.32  17571.75  17437.32  17500.94  111992332
# ...                       ...       ...       ...       ...        ...

params = [
    # Dow Jones
    {
        'q': ".DJI",
        'x': "INDEXDJX",
    },
    # NYSE COMPOSITE (DJ)
    {
        'q': "NYA",
        'x': "INDEXNYSEGIS",
    },
    # S&P 500
    {
        'q': ".INX",
        'x': "INDEXSP",
    }
]
period = "1Y"
# get closing price data (return pandas dataframe)
df = get_closing_data(params, period)
print(df)
#                 .DJI         NYA     .INX
# 2016-05-17  17710.71  10332.4261  2066.66
# 2016-05-18  17529.98  10257.6102  2047.21
# 2016-05-19  17526.62  10239.6501  2047.63
# 2016-05-20  17435.40  10192.5015  2040.04
# 2016-05-21  17500.94  10250.4961  2052.32
# ...              ...         ...      ...

params = [
    # Dow Jones
    {
        'q': ".DJI",
        'x': "INDEXDJX",
    },
    # NYSE COMPOSITE (DJ)
    {
        'q': "NYA",
        'x': "INDEXNYSEGIS",
    },
    # S&P 500
    {
        'q': ".INX",
        'x': "INDEXSP",
    }
]
period = "1Y"
# get open and close price data (return pandas dataframe)
df = get_open_close_data(params, period)
print(df)
#             .DJI_Open  .DJI_Close    NYA_Open   NYA_Close  .INX_Open  \
# 2016-06-21   17736.87    17804.87  10456.9207  10450.0288    2075.58
# 2016-06-22   17827.33    17829.73  10481.1576  10490.7800    2085.19
# 2016-06-23   17832.67    17780.83  10507.9429  10473.0578    2089.75
# 2016-06-24   17844.11    18011.07  10573.4669  10641.1686    2092.80
# 2016-06-25   17946.63    17400.75  10335.9189  10183.5145    2103.81
# ...               ...         ...         ...         ...        ...

Contributing

1. Fork it

2. Create your feature branch (git checkout -b my-new-feature)

3. Commit your changes (git commit -am 'Add some feature')

4. Push to the branch (git push origin my-new-feature)

5. Create new Pull Request