Shed Skin

Shed Skin

Shed Skin is an experimental compiler, Python to C++, that makes creating Python extensions easy. It uses advanced static analysis and type inference techniques to generate optimized C++ code. Shed Skin can significantly improve the execution time of CPU-bound Python programs.
Shed Skin image
compiler python c optimization static-analysis

Shed Skin: Experimental Compiler for Easy Python Extensions

A compiler that makes creating Python extensions easy, utilizing static analysis and type inference techniques to generate optimized C++ code

What is Shed Skin?

Shed Skin is an experimental just-in-time compiler that can translate pure, but implicitly statically typed Python programs into optimized C++ code. It performs advanced type inference and program analysis to determine the types of all values at compile time, and uses this to generate faster code.

Some key features of Shed Skin include:

  • Translates a subset of Python into C++ code, focusing on numeric and array-oriented code
  • Uses advanced static analysis techniques to optimize the C++ output
  • Can provide significant speedups for CPU-bound Python programs, rivaling C/C++ implementations
  • Supports numpy arrays and common Python libraries like itertools and re
  • Relatively easy to use - just add static type comments and compile your Python script with Shed Skin

Because it relies on static types and analysis, Shed Skin has some limitations in terms of supported Python features. But for computational and numeric code, it can translate Python into highly efficient C++ without having to rewrite everything. If you have Python code that is too slow, give Shed Skin a try to accelerate it.

Shed Skin Features

Features

  1. Compiles Python code to C++
  2. Performs advanced static analysis and type inference
  3. Generates optimized C++ code
  4. Makes it easy to create Python extensions in C++
  5. Can significantly improve execution time of CPU-bound Python programs

Pricing

  • Open Source

Pros

Faster execution than pure Python

Easier than hand-writing C++ extensions

Seamless integration with existing Python code

Cons

Limited Python language support

May require some code changes for compilation

Extra build steps required

Additional dependencies introduced


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