Python is a beginner’s programming language. It is a high-level language that is very versatile, interpreted and object-oriented language.
It is very easy to learn, read and maintain language having very small programs. Python interpreters are available on several OS like Windows, Linux, and Mac OS.
Other features which make it more useful is its portability and scalability.
Python library can be used with the following:
- Web Development
- Data Science
- Machine Learning
- Software Development
- Web frameworks like Django
- GUI application
Most of the geeks think Python is Interpreted Language but it also compiled language at first.
The compiled part is done at the time of your code execution and deleted. Then converts it into byte code. Further to python virtual machine by machine and operating system.
this article highlights 11 Best Python Compilers & Interpreters for python programmers.
How does Python Compiler work?
Best Python Compilers and Interpreters
It is designed for the Windows Operating System. It has several features over CPython. It comes with prepackaged popular libraries for Data Science and Machine Learning such as Numpy, Pandas, and Scipy.
It comes with C and C++ compiler which is not needed most of the time. Other than that It’s zero packages come with only Python Compiler.
Skulpt is the in-browser implementation of Python. It can also be added to the Html code.
Skulpt interpreter will execute your python code kept in .py file on your site by importing it.
It also comes with the latest specification of Html5/CSS3. It can use popular CSS frameworks like BootStrap3 and LESS.
Pyjs is a rich Internet application framework. It is also a lightweight Python Compiler that can be used directly from the web browser using Python Scripting and can execute programs from a web browser JS console.
5. Shed Skin
This compiler compiles Python code to C++ with standard libraries modules to use. It translates statically typed Python program into optimized C++ codes with many limitations.
It can enhance your performance by again implementing its built-in Python data types into own set of classes which implements efficiently in C++.
6. Active Python
This is Python distribution for Windows, Linux and Mac Os with free community version.
It supports the installation of many platforms some of which are even not supported by Python-like AIX platform. It provides more compatibility than Python.
It is a source to source Python Compiler which takes Python source code and converts it into C/C++ executable code. It also uses many Python libraries and extension modules.
It comes with Anaconda for making projects using Data Science and Machine Learning.
It is one of the popular Python Compiler which compiles Python code to easy and readable Java code. It is a lightweight Python compiler that provides support for slicing with matrix and vector operations.
Transcrypt can also run on Node.js. Hierarchical modules, multiple inheritance, and local classes add more features to its list.
It is written in Java and can execute on any platform having JVM. Jython compiles your Python code to Java Byte Code which makes it platform-independent.
It can be used to create solutions for Servelets, Swing, SWT and AWT packages. Jython uses Global Interpreter Lock like CPython.
Also, you can extend Java Classes to your Python code.
CPython is the default and most widely used Python Compiler. It is written in C language and uses GIL(Global Interpreter Lock) process which makes it harder for concurrent CPython processes to communicate.
The steps of compilation in CPython include:
Decoding, Tokenization, Parsing, Abstract Syntax Tree and Compiling.
This version of Python Compiler is implemented on Microsoft .Net framework and Mono.
It provides dynamic compilation and interactive console too. It makes the installation very easy and comes with cross-platform compatibility.
It also posses standard libraries and different modules. It is mainly designed to implement user interface libraries of .Net framework.
IronPython converts Python has in-memory bytecodes before execution.
Python Compilers give a more detail understanding of Python being very versatile.