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[PLUS] Easily Fetch All Historical Trade Ticks from Gemini API using Python

by CryptoDataDownload

Historical trade ticks are often necessary for training machine learning and other high frequency trading models - the general rule of thumb is: "the more data, the better". Each trade "tick" represents one transaction between a buyer and a seller at a point in time for a price and amount. We will demonstrate how to use the public Gemini API to pull every trade print for any of their available tickers and save the results to a Sqlite database. The reason we use a database in this example instead of Excel is due to the sheer size of the data... easily could be millions of records. For BTC/USD, this will capture trade print data all the way back to October 2015!

As an aside, Sqlite also provides a great user interface to interact directly with the database (https://sqlitebrowser.org/) -- Every line of our Python code is commented so you know exactly what is going on. We will use 3 main functions and less than 110 lines of code to include everything! One function is used to create the database and data structure to store the trade print data. One function is specific to retrieving what is the ID of the last transaction stored in our database. And the last function will query the Gemini rest API and store results 500 at a time into the sqlite database! If you run the code and it fails, it will start capturing from where it left off in the database.

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Notice: Information contained herein is not and should not be construed as an offer, solicitation, or recommendation to buy or sell securities. The information has been obtained from sources we believe to be reliable; however no guarantee is made or implied with respect to its accuracy, timeliness, or completeness. Author does not own the any crypto currency discussed. The information and content are subject to change without notice. CryptoDataDownload and its affiliates do not provide investment, tax, legal or accounting advice.

This material has been prepared for informational purposes only and is the opinion of the author, and is not intended to provide, and should not be relied on for, investment, tax, legal, accounting advice. You should consult your own investment, tax, legal and accounting advisors before engaging in any transaction. All content published by CryptoDataDownload is not an endorsement whatsoever. CryptoDataDownload was not compensated to submit this article. Please also visit our Privacy policy; disclaimer; and terms and conditions page for further information.

THE PERFORMANCE OF TRADING SYSTEMS IS BASED ON THE USE OF COMPUTERIZED SYSTEM LOGIC. IT IS HYPOTHETICAL. PLEASE NOTE THE FOLLOWING DISCLAIMER. CFTC RULE 4.41: HYPOTHETICAL OR SIMULATED PERFORMANCE RESULTS HAVE CERTAIN LIMITATIONS. UNLIKE AN ACTUAL PERFORMANCE RECORD, SIMULATED RESULTS DO NOT REPRESENT ACTUAL TRADING. ALSO, SINCE THE TRADES HAVE NOT BEEN EXECUTED, THE RESULTS MAY HAVE UNDER-OR-OVER COMPENSATED FOR THE IMPACT, IF ANY, OF CERTAIN MARKET FACTORS, SUCH AS LACK OF LIQUIDITY. SIMULATED TRADING PROGRAMS IN GENERAL ARE ALSO SUBJECT TO THE FACT THAT THEY ARE DESIGNED WITH THE BENEFIT OF HINDSIGHT. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFIT OR LOSSES SIMILAR TO THOSE SHOWN. U.S. GOVERNMENT REQUIRED DISCLAIMER: COMMODITY FUTURES TRADING COMMISSION. FUTURES AND OPTIONS TRADING HAS LARGE POTENTIAL REWARDS, BUT ALSO LARGE POTENTIAL RISK. YOU MUST BE AWARE OF THE RISKS AND BE WILLING TO ACCEPT THEM IN ORDER TO INVEST IN THE FUTURES AND OPTIONS MARKETS. DON’T TRADE WITH MONEY YOU CAN’T AFFORD TO LOSE. THIS IS NEITHER A SOLICITATION NOR AN OFFER TO BUY/SELL FUTURES OR OPTIONS. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THOSE DISCUSSED ON THIS WEBSITE. THE PAST PERFORMANCE OF ANY TRADING SYSTEM OR METHODOLOGY IS NOT NECESSARILY INDICATIVE OF FUTURE RESULTS.
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Step into the full potential of your cryptocurrency research and market analysis with CryptoDataDownload. Access free historical data in CSV format, unlock unusual option activity signals, explore Plus+ Python code examples (where every line of code is commented), and tap premium aggregated file resources and bespoke data sets. Trusted by academics worldwide, we offer comprehensive data to empower traders, researchers, and enthusiasts alike.

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