Pre-compiled packages now available for Pyston

We’re excited to announce today that it’s easier than ever to use Pyston, our faster Python implementation. We have pre-compiled hundreds of extension modules and are releasing them today, making it easy to use your favorite libraries with Pyston.

For a bit of background: Pyston has always supported third party extension modules, but the practical difficulty of compiling some of them from source has been a roadblock for our users. These modules are difficult to compile on CPython as well, but library authors typically provide pre-compiled versions of their packages specifically for CPython. This means that installing, for example, the “cryptography” library is easy on CPython, but will fail to install in Pyston if one doesn’t have a Rust compiler installed.

Now one can simply install a pre-compiled cryptography, or Tensorflow or PyTorch or pandas (or many others) and run one’s Python code with a speedup.

How to use

We’ve released the packages as conda packages at anaconda.org. The easiest way to get started is to download our custom installer which will install a conda client that is pre-configured to use Pyston and these packages. You can also use the pyston/conda docker image where we’ve done this for you. You can also set up an existing conda environment to use Pyston (wiki).

We’ve chosen to provide conda packages because we can leverage the excellent work of the conda-forge team, who have done the hard work of creating repeatable build scripts for all of the packages. We are currently working on producing wheels for people who use pip, but this is less systematic and we don’t have an estimated timeline for it.

Unfortunately the error messages at this point can be a bit cryptic. If you get an error message while trying to install packages along the lines of “package X requires python_abi 3.8.* *_cp38”, or “package X requires python”, this typically means that one of the libraries you are trying to install (or one of their dependencies) has not yet been built for Pyston. These issues are a bit tricky to debug, so feel free to let us know and we’ll figure it out and get the package built and uploaded.

These packages should work on any Linux distribution that conda supports, though they have only been tested on Ubuntu. For Mac users we provide a docker container (pyston/conda) with our environment pre-installed. Windows users have reported good results by using Pyston inside WSL2.

More technical details can be found on our wiki.

Get in touch

We’d love to hear from you and your experience with Pyston and these new packages. Whether it’s because you want a package that is not available, you run into some sort of difficulty, or if there are any other reasons that you are still unable to try Pyston, let us know in our issue tracker or discord server.

We aim to make it effortless to accelerate your Python code, and if there is anything preventing that please let us know!

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