.. _cache: .. currentmodule:: pandas-datareader .. ipython:: python :suppress: import numpy as np from pandas import * import pandas as pd import requests_cache randn = np.random.randn np.set_printoptions(precision=4, suppress=True) options.display.max_rows = 15 *************** Caching queries *************** Making the same request repeatedly can use a lot of bandwidth, slow down your code and may result in your IP being banned. ``pandas-datareader`` allows you to cache queries using ``requests_cache`` by passing a ``requests_cache.Session`` to ``DataReader`` or ``Options`` using the ``session`` parameter. Below is an example with Yahoo! Finance. The session parameter is implemented for all datareaders. .. ipython:: python :okexcept: import pandas_datareader.data as web from pandas_datareader.yahoo.headers import DEFAULT_HEADERS import datetime import requests_cache expire_after = datetime.timedelta(days=3) session = requests_cache.CachedSession(cache_name='cache', backend='sqlite', expire_after=expire_after) session.headers = DEFAULT_HEADERS start = datetime.datetime(2010, 1, 1) end = datetime.datetime(2013, 1, 27) f = web.DataReader("F", 'yahoo', start, end, session=session) f.loc['2010-01-04'] A `SQLite `_ file named ``cache.sqlite`` will be created in the working directory, storing the request until the expiry date. For additional information on using requests-cache, see the `documentation `_.