As we all know that python is an Interpreted High-Level Programming language, which means python use Interpreter software as a translating and executing tool to execute the python file. Though by default, python termed as an interpreter, there are many software on the internet, which are known as Python compilers. A python compiler is a program that can translate your python code to another programming language code so it can run on different platforms. Here in this article, we have mentioned some best python compilers which you can explore.
What is a Compiler?
A Compiler is a computer program or software which is used to translate the code of one programming language to another programming language. The primary work of a compiler is to bring the high-level program to the machine language or byte code and make an executable file. Still, there are different kinds of compilers such as source to source compiler and cross compiler. A cross compiler is a program which is used to compile a code which belongs to the different operating system . A Source-to-Source compiler translates between high-level programming languages.
Best Python Compilers
Here we have mentioned some of the best python compilers which you can find on the internet. Though by default, python uses CPython compiler-cum-interpreter, you can install different translator tools to convert your python code to the corresponding other programming languages.
- Py JS
- Shed Skin
URL: http://nuitka.net/ Supported by Python 2.6, 2.7, 3.3 to 3.7 Nuitka is a source-to-source python compiler, which is capable of translating your python code to the equivalent C++/C source or executable code. It is supported by both the versions of Python, which includes 2.6, 2.7, 3.3, 3.4, 3.5, 3.6, and 3.7. The main objective of Nuitka to create stand-alone programs or applications using python so those systems which do not have python installed can also run the bytecode of C++ using the Operating System. The concept of Nuitka came into existence at the EuroPython conference in 2012, and at the end of 2014, Nuitka was able to use all the features of Python programming language, which includes all the python standard libraries and modules.
4. Shed Skin
GitHub Repo: https://github.com/shedskin/shedskin Supported by Python 2.4 to 2.6 versions It is another popular python source-to-source compiler that is capable of translating your python code to the corresponding C++ code, that’s why it is also known as Python to C++ programming language compiler. Both C++ and Python are different programming languages, so this compiler can purely translate your Dynamic Python code to the C++ implicit static code. As we all know python is built on C/C++, and it also uses some of their libraries, so Shed Skin often used to create stan-alone programs and extension modules that can be used in large python programs. There are some data types of restrictions in Shed Skin. Still, you can freely use the python standard libraries and modules such as random, math, etc. With Shed Skin, we can wrap C++ classes so they can be used in Python class-based programs.
URL: https://winpython.github.io/ Supported by Python 3.7 and upper versions The initial release of python was unstable, and there were many bugs in this programming language. Windows Operating Systems users were finding some troubles using python in their system, and to solve this problem, WinPython was introduced. WinPython is a Distributed Python compiler that was specially designed for the Windows Operating Systems, to solve the Python bug problems in windows. Though now python core developers have released the stable version of Python for every operating system so you would not find developers using WinPython, now you can use Python default implementation CPython.
Though there are not too many developers who use Python compilers to translate the Python code to some other programming languages because it’s of no use if you want to create some JS and C++ extensions or applications from scratch using Python. We hope you like this article, and you get to learn something new about python. If you have any suggestions related to this article, feel free to comment. People are also reading: