Which is the fastest implementation of Python?

The newer Python version is faster than the previous version. Python 3.8 comes with the lot of modification that enhances it performances. We can’t understand the performance of Python is that there is often a compromise between versatile, dynamic language, versus performance. We can’t have everything at the same time. To test the performance of Python, programmer should apply the alternative implementations. [Python] is an interpreted language, at the same time it also provide the facility to compile the source code into the byte code that runs on a virtual machine. We can use the different compiler for different purpose to give us a performance edge.

In this tutorial, we will see the different implementation of Python.


PyPy is one of the most popular alternative compilers which used by the Python developer to gain more speed. PyPy works on the JIT (Just-In Time) compiler that compiles the part of code that enhances the performance. It also manage the memory efficiently using the GC improvements . It supports the stackless mode that can work with the micro-thread for concurrency.

Programmers have dispute about which one is the fastest - PyPy and CPython, but the general consensus is that is PyPy is faster.


The CPython is the most commonly used compiler of Python that written in [C]. It is a default compiler. The CPython converts the source code into the intermediate byte code and runs it by using the CPython Virtual Machine . CPython also works with the stackless mode that provides the micro-thread for concurrency.

JPython or JPython

We can assume that JPython is Java implementation of the Python. It allows the unified Python script can use onto the Java Platform. Java Programmers will use it bind the Python script into the large Java Applications. We can also use the [Java] threads to write multiple-threaded programs. It provides some speed but slower than the CPython . Python can be provided the extra efficiency in large scale Java application development .


The IronPython is the implementation of Python which is used to work with the [.Net] . We can use the .Net libraries through the Python scripts. It doesn’t support the GIL; that means the performance of the multi-thread code is much better that other code. It provides the facility that we can work on the web server using the Python framework instead of.


Nuitka is a newly created compiler and not enough as the other compilers but it compiles the Python code in to C/[C++] executable. It can work with the every version of Python from 2.6 to 3.8 and is twice faster than the CPython. We can use the Nuitka to develop the stand-alone executable for Python code even on Windows.

This is all about of the different implementation of the Python. You can find the CPython faster than the other compilers but it is also dependent on the different use cases.