# Python Implemention in Julia

**URL:** <https://discourse.julialang.org/t/python-implemention-in-julia/79522>\
**Category:** Offtopic\
**Tags:** question\
**Created:** [April 15, 2022, 8:23am UTC](https://discourse.julialang.org/t/python-implemention-in-julia/79522 "2022-04-15T08:23:54Z")\
**Posts on this page:** 1\
**Showing post:** 27

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**Author:** ![Palli](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/palli/32/3380_2.png) [@Palli](https://discourse.julialang.org/u/Palli)\
**Post date:** [April 21, 2022, 6:53pm UTC](https://discourse.julialang.org/t/python-implemention-in-julia/79522/27 "2022-04-21T18:53:54Z")

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FYI: The closest I know of is:

> **[GitHub - TotalVerb/PythonSyntax.jl: A pythonic syntax for Julia (for fun, not for...](https://github.com/TotalVerb/PythonSyntax.jl)**
>
> A pythonic syntax for Julia (for fun, not for serious use)

> A pythonic syntax for Julia (for fun, not for serious use)

[It’s not maintained for Julia 1.0+ (unlike LispSyntax.jl similar in spirit), but should be easy to resurrect…]

There’s not point in reimplementing Python i.e. syntax and semantics, in Julia. But it could be done, similar to APL implemented in APL.jl. I just don’t see any upside (just plenty of downsides) to reimplement Python once again, not for us, not for Python or Rust users.

What I find valuable is being able to call to and from Python (without any overhead, possible with e.g. PythonCall.jl), and same for R and more.

Why RustPython was done, is maybe for them to say, a hobby project (actually many, that got merged or abandoned)? Still, they might need a good other language with a REPL, or just wanted faster Python. We have the speed (like Rust and C).

In time it may be helpful to being able to call RustPython or Pyston or whatever alternative good Python implementation, but I only call Python for features/library access, more so than for speed (and often those “Python” libraries are fast enough; as also implemented in C).

What might be helpful is to be able to reuse CPython extensions, directly, or more likely the extensions to R (since it doesn’t run in the same process, when used with Julia?). And vise versa, also useful, using Julia this way from other languages, there from Python:

> [@Successful Static Compilation of Julia Code for use in Production](https://discourse.julialang.org/t/successful-static-compilation-of-julia-code-for-use-in-production/79318):
>
> The [StaticCompiler](https://github.com/tshort/StaticCompiler.jl) package was recently registered. This post records a successful experiment to statically compile a piece of Julia code into a small .so library on Linux, which is then loaded from Python and used in training of a deep learning model. TLDR Static compilation to a stand-alone library does work on Linux but has rather significant restrictions on the functionality available. It is mostly useful for core computational routines. Roughly speaking, if it could be implemented in plain…

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