8 Python programming language variants

1. PyPy

PyPy is a Python interpreter implemented in Python. Compared with CPython, PyPy is more flexible, easy to use, and can be easily implemented by developing specific functions in different situations. The goal of this project is to make PyPy easier to adapt to various projects and facilitate cropping than Python implemented by C.

2. IronPython

IronPython is the implementation of Python on the. NET platform. Started by Microsoft's Jim Hugunin, it is an open-source project based on Microsoft's DLR engine.

3. Python for. NET

Python for. NET is a. NET universal language environment that allows Python programmers to seamlessly integrate the CLR and provides a powerful application scripting tool for. NET developers. With this project, you can use Python in. NET to compile the entire application and use. NET Services and components.

4. Cython

Specifically, Cython is a separate language used to write the extension library used for import in Python. In fact, the syntax of Cython is basically the same as that of Python, while Cython has a special "compiler" that converts Cython code into C and automatically adds a lot of C-Python APIs ), then, use the C compiler to compile the final Python callable module.

5. Jython

Jython is a pure Java implementation of Python. She seamlessly integrates Java classes with Python, enabling users to write software that runs on a Java VM in the Python language syntax. Compared with similar Java programs, Jython greatly reduces the amount of programming code. Jython has both the interpreter and compiler so that it can test program code without compilation.

6. Stackless Python

Stackless Python is an enhanced version of Python programming language that allows programmers to benefit from thread-based programming without half of the thread performance and complexity issues. Its biggest feature is microthread, which can avoid overhead caused by operating system threads.

7. mypy

The mypy programming language is an experienced Python variant designed to combine the advantages of dynamic and static types. Our goal is to provide an impressive, powerful, and convenient Python that provides type checks during compilation and efficient compilation to local code without some heavyweight virtual machines.

8. RPython

RPython is a subset of Python. Although rPython is not a complete Python, the Python implementation written in rPython can be used to explain the complete Python language.

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