I want to try some reinforcement learning techniques (borrowed from AlphaZero, etc.) and so I need a chess environment in order to run games.

I code in python, so I found python-chess but unfortunately it is too slow to generate a large amount of games. Playing 100 games with random moves (average length of ~400 moves for a random game) takes 8 seconds, which doesn't scale to higher orders of magnitude well. My profiling shows that over 99.9% of the time taken is with the library as opposed to other code, so I can't optimize any further.

Is there already an existing chess environment that is faster than this in python?

  • Would it be a problem to use a C library and link it from Python? Not that I would know of something in particular but I would suggest to look at what the Leela zero fork uses. You might find something useful there. Commented Jun 20, 2018 at 17:31
  • C library would be great as well. I would need to look up how to hook it up to python, but I'm familiar enough with C that I can read it at least. I don't know what leela uses... seems like a big enough project that it would be tough to jump into it cold and try to understand it. Commented Jun 20, 2018 at 18:16
  • I don't know either, just a suggestion where to start. Anyway, I would suggest to edit your question so that other people know C libraries are acceptable and don't skip it just because they do not know any other python library. Commented Jun 20, 2018 at 18:55

1 Answer 1


Generating high volume of data directly in an interpreting Python environment is a bad idea. Furthermore, the python-chess package is not made for high performance; the package is not a wrapper for native C/C++.

If you want to generate hundreds and thousands of games quickly, you don't have any reason for avoiding native coding such as C++. Take the Stockfish code base, modify it for making games. That was what the Leela project had done, and it worked!

Please consider going into C++. Mutlit-threading if you haven't done it already.

  • Whenever a programmer asks, "how can I make my python code run high performance computing tasks more efficiently?" the answer invariably is rewrite it in C or C++. Commented Aug 22, 2018 at 20:33

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