Retrieving Full Historical Data for Every Cryptocurrency on BitMex Using the Python APIA single function to read, update, save and gather dataPeter NistrupBlockedUnblockFollowFollowingJun 6Disclaimer: I know this isn’t what I typically post but since it’s an interest of mine — just like traditional finance, machine learning, and data science — I think some of you might find this interesting as well.
I’ve recently been investigating the relationship between data science and the cryptocurrency market for a pretty long article I’m writing.
During the process, I needed to retrieve price history and other data, so I decided to write a supplementary piece about how I accomplished that.
I hope you find it useful.
Make sure to follow me if you enjoy this piece and want to see more!TL;DRTo retrieve Bitcoin prices and data (1m klines):Sign-up on BitMex to get API access.
Import the functions I’ve created for easy-of-use and add your API details.
Call the function: get_all_bitmex(“XBTUSD”, “1m”, save = True)Example use:It’s really that easy!Why BitMex?If you’ve had any experience with the cryptocurrency market you know that the answer to this question is obvious:BitMex is the largest volume exchange on the market.
And as we know, large volume equals big data and big data (usually) equals better modeling and predictions, especially for machine learning models.
Please note that you DON’T have to buy any Bitcoin or any other cryptocurrency whatsoever to perform the steps in this article.
The reason we need to sign up is that once signed up you’ll have access to their API’s, which is what we’re gonna be using for getting the actual data.
Retrieving and Storing the DataOur code will do the following:Check for existing saved dataFind the difference between the latest saved data (if any) and the newest dataSend API calls and append an existing or new DataFrameSave and/or return full DataFrameThe only thing you need to do is add your API-key and API-secret to your code, also remember to NEVER share these with anyone.
If you are trading or holding cryptocurrency on BitMex, this could result in a loss of funds.
It looks messy but it’s very functional and fast, the only limiting factor is the number of API calls allowed by BitMex each minute.
This is incredibly easy to use, simply call the function in Python with:data = get_all_bitmex(“XBTUSD”, “5m”, save = True)Once downloaded, the function will return the entire DataFrame for you to use as you wish.
If the argument save is passed as True, it’ll save the DataFrame on your computer with the filename “[symbol]-[kline_size]-data.
csv”, i.
e.
“XBTUSD-5m-data.
csv” in the case above.
The clever thing about this function is that it will keep your data up to date at all time.
Each time the function is called it will check the latest point of data you’ve downloaded and update with any new data!Just call the get_all_bitmex(“XBTUSD”, “5m”, save = True) each time you’re working with your XBTUSD data to make sure it’s up to date!But I Want Data for All the Markets!Don’t worry, this is just as easy to do!.You can retrieve the data for all markets with:ConclusionThanks for reading.
Hopefully, you found this useful!.I’ve followed this up with a similar piece on gathering data through the Binance API if you enjoyed this article and want to see more, be sure to follow my profile!Full historical data for EVERY crypto on Binance using the Python APIA single function to read, update, save and gather data.
medium.
com.