New Python Libraries! Credit Semaphores + Plan Ahead

This week, we are sharing a Python library written by me to help in throttling our various API services.

https://github.com/hangukquant/credit_semaphore

There are great examples, easy to use interface and high utility library that can help to solve alot of the issues when it comes to dealing with external API’s rate limiting.

(we also have a synchronous semaphore inside the library, but we have not documented it yet. In case you do not want to support asyncio and use threads, you can check that out in the source code. The interface is pretty similar, and there are examples)

Next week, we will be using this library to continue with our data services and integrating it by writing our own SDK for the MetaAPI to communicate with a MetaTrader terminal.

With the developed SDK, this sets us up for using the SDK in our order executor. We will then have developed tools in data-retrieval, backtesting, and signal generation as well as order execution. Finally, we want to discuss logging some trades and analysing our positions in a dashboard. We will then put the pieces of the puzzle together to put together an end-to-end quant system, bringing us to a much more sophisticated version then the one we released back in February!

Alot of the readers had good feedback for that course - and this encouraged me to take it even a step further with more advanced/cleaner structure. Although the entire path has been somewhat scrappy, going from one part of the quant system to another, this was because I was programming it live each week! (and seeing which parts could be iterated towards a better solution)

I hope you are as excited as I am.