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Google_stocks <- function(sym, current = TRUE, sy = 2005, sm = 1, sd = 1, ey, em, ed) If(!'data.table' %in% installed.packages()) install.packages('data.table') For readers of my book, Automated Trading with R, this will serve as a replacement for the often-referenced yahoo() function, but not as a perfect replacement. In this post, we will build functions for accessing that API in both R and Python. It was Hidden!Īs it turns out, quantmod was using a hidden Google Finance API that was quite easy to reverse engineer. I found the answer by searching through the R package quantmod, which was successfully downloading data from Google despite this message on /finance/. After batting around a lot of potential replacements, I was still left searching for a good free source of data to use for education and retail trading. In one of my most popular posts, Download Price History for Every S&P 500 Stock, other traders and I despaired over the death of the Yahoo! Finance API. Users will need to download the Quandl package from CRAN to run this using: install.packages(‘Quandl’).Ĭredit to GitHub user johnatasjmo for this solution: Start_date and end_date are tuples of integers representing the year, month,Įnd_date defaults to the current date when None Symbol is a string representing a stock symbol, e.g. _key = 'your_api_key'ĭef quandl_stocks(symbol, start_date=(2000, 1, 1), end_date=None):
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Users will need install the Quandl library from pip to use the script with: pip install quandl. Users will need to visit Quandl’s website and sign up for an API key to access the data. They have a stable key-driven API that doesn’t seem to be going anywhere. It only returns a year’s worth of daily data as of the time of writing. Update: Using Quandl’s APIīecause everything I write about breaks, the Google Finance API stopped taking requests at this URL. Follow the hilarious change history of EOD stock data API’s at my other post.
#Python download stock data how to
Updates to this post are more about which API’s are still supported than how to access them with R, Python, or any other language.