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Home/ Questions/Q 6956385
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Editorial Team
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Editorial Team
Asked: May 27, 20262026-05-27T14:51:45+00:00 2026-05-27T14:51:45+00:00

I was wondering if someone was able to compile Django based projects (into shared

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I was wondering if someone was able to compile Django based projects (into shared object libs for instance) with pyrex (or anything similar) and still maintain the flexibility using normal Django projects with python.

We have to be able to use the project with apache so it cannot be compiled into a standalone binary. The way I think of it is that it will be compiled into libs and these libs will be exposed to the interpreter so it should behave like the current state of the project with python. Preferably without writing a lot of C code 🙂

Thanks in advance.

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  1. Editorial Team
    Editorial Team
    2026-05-27T14:51:46+00:00Added an answer on May 27, 2026 at 2:51 pm

    Pyrex and its sucessor – cython – are not fully python compatible – they are rather another language, although Python based.

    Django is a very complex project, and would require strict Python compliance to run – i doubt it would be possible without some months of work to make Django work directly in cython or Pyrex – although one could use a profiler to turn specific bottlenecks into native code with much less effort (by replacing individual django modules in the core with ones optimized with Cython)

    Moreover, optimization with Pyrex/Cython is not that “free” – one can have around a 30% speedup by running simple, numeric intensive code, in Cython without any changes in the code – but for greater speed increase, the code has to be manually tweaked so that some variables are made statically typed.

    On the other hand, you might try running Django with Pypy –
    there are some hints here:
    http://reinout.vanrees.org/weblog/2011/06/06/django-and-pypy.html

    Pypy is an extremly conformant Python interpretor, and Django core is known to work with it. It does use a Just In Time translation approach that makes it several times faster than the reference implementation of Python (CPython) for most workloads.

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