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From https://www.reddit.com/r/Python/comments/7zxptg/pulling_stock_market_data_yahoo_and_google_dont/dus01vk/ :
""" pydata/pandas-datareader has a number of financial data sources: https://github.com/pydata/pandas-datareader
pydata/pandas-datareader#454
#411 Morningstar (PR) #392 Robinhood #390 Tiingo #389 Alpha Vantage #368 Barchart #161 Bloomberg #156 TrueFX Quandl see-also.rst https://github.com/pydata/pandas-datareader/blob/master/docs/source/see-also.rst https://github.com/wilsonfreitas/awesome-quant#data-sources A table with columns for frequency and historical start datetime might be helpful. Zipline and Catalyst support a separate data ingestion step which downloads the data once: http://www.zipline.io/bundles.html https://github.com/quantopian/zipline/blob/master/zipline/data/ https://github.com/enigmampc/catalyst/tree/master/catalyst/data Is there a recommended way to handle caching?
A table with columns for frequency and historical start datetime might be helpful.
Zipline and Catalyst support a separate data ingestion step which downloads the data once:
https://github.com/quantopian/zipline/blob/master/zipline/data/
https://github.com/enigmampc/catalyst/tree/master/catalyst/data
Is there a recommended way to handle caching?
[...] """
The text was updated successfully, but these errors were encountered:
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From https://www.reddit.com/r/Python/comments/7zxptg/pulling_stock_market_data_yahoo_and_google_dont/dus01vk/ :
"""
pydata/pandas-datareader has a number of financial data sources: https://github.com/pydata/pandas-datareader
pydata/pandas-datareader#454
[...]
"""
The text was updated successfully, but these errors were encountered: