Different types of Python interpreters

Python is, in essence, a specification for the Python programming language, which can be implemented in a variety of ways. A different interpreter is used for each Python programming language implementation.

Python, as the fastest-growing programming language in 2020, has no shortage of interpreters. However, since each one caters to a different set of needs, you must first determine which one is best for you.

Let’s take a quick look at what a Python interpreter is before we go into 6 of the most common Python interpreters.

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Role of a Python interpreter

By definition, a Python interpreter is a computer program that executes the instructions. Besides, you can write it in a programming language directly. By “direct execution,” we assume that the instructions are not first compiled into a machine language program.

Python is a programming language.

So, now that we’ve cleared that up, let’s move on to a quick rundown of six of the most common Python interpreters.

Py charm

Py Charm has Python interpreters. At least one Python interpreter must be configured in PyCharm before you can work with your Python file. A python interpreter that comes with your installation can be used. You can also build a virtual environment using Virtualenv, Pipenv, or Conda. A virtual environment is made up of a base interpreter and packages that have been added.

SSH, Vagrant, WSL (only for Windows), Docker, and Docker Compose are only a few of the interpreters you can use with PyCharm Professional to run your Python code in remote environments.


You must define the path to the Python executable in your framework when configuring a Python interpreter. So, before configuring a Python interpreter, make sure you’ve downloaded and installed Python on your device, and that you know where to find it. Using the same Python executable, you can build several Python interpreters. When you need to build various virtual worlds for different types of applications, this is useful. You can, for example, build a virtual environment based on Python 3.6 for developing Django applications and another based on the same Python 3.6 for working with scientific libraries.

Up to Python 3.7 is supported.

It is the Python programming language’s default and most commonly used implementation. C Python is a C and Python interpreter that gives C and other programming languages. This is a foreign function interface.

Since it translates Python code into bytecode before interpreting it, C Python is often known as a compiler. It employs a GIL, or Global Interpreter Lock, which has the drawback of disabling concurrent Python threads for a method.

C Python, as the standard Python implementation, has the greatest compatibility with Python packages and C extension modules. As a result, all Python programming language versions are written in C.

For Python packages that require C extensions to work properly, C Python is the only choice. If a program written in the Python programming language is to reach the widest possible audience, it must target C Python.

Up to Python 2.7 is supported by Iron Python.

Iron Python is a.NET platform implementation of the Python programming language that uses both Python and.NET framework libraries. It can also make Python code available to other.NET framework languages.

Iron Python has a built-in virtual console and supports dynamic compilation. Python scripts can communicate with.NET objects using the Python interpreter. Iron Python is directly incorporated into the Visual Studio IDE with the Python Tools for Visual Studio.

Up to Python 2.7 is supported by Jython.

Jython is a Java-based Python implementation that was previously known as JPython. Jython, which is written in both Java and Python, transforms Python code into Java bytecode, allowing Python code to run on any computer that has a JVM.

Both static and dynamic compilation is supported by Jython. The common Python interpreter allows you to import and use any Java class as a Python module, which is a useful feature.

If you need to interface with an existing Java codebase or write Python code for the JVM, Jython is your best choice.

Up to Python 2.7, Python 3.5, and Python 3.6 are supported by PyPy.

PyPy is a Python programming language implementation that is both fast and compliant. R Python, a limited statically-typed subset of the Python programming language, is used to implement the Python interpreter.

PyPy supports C, CLI, and JVM back-ends and has a JIT compiler. PyPy’s primary objective is to provide full consistency with the reference C Python implementation while also improving performance.

Python programmers who want to improve the efficiency of their Python code use PyPy. The famous Python interpreter PyPy is around 4.4 times faster than CPython, according to the official PyPy website.

Python 2.6 to Python 3.5 are supported by Python Net.

Python Net allows you to integrate a native Python installation with the.NET CLR in a nearly seamless manner. Its strategy is opposed to that of Iron Python.

Python Net allows a native Python installation on a non-Windows operating system. This is to use the.NET platform when combined with Mono. It is possible to use Python Net in conjunction with Iron Python without any problems.

Python Supports a Less Stacks — Up to Python 3.7

The C call is used by C Python and other common Python interpreters to construct their stack. This isn’t the case with the Stackless Python interpreter, however.

The C stack is used by Stackless Python, so it is cleared between function calls. As a result, the Python interpreter’s stack does not depend on the C call. Stackless Python, like C Python, is written in C and Python.

Stackless Python also supports communication channels, coroutines, pre-compiled binaries, round-robin scheduling, task serialization, and task lets, in addition to threads.

Python version 2 or Python version 3

Since the release of Python 3 in 2008, there has always been a debate on whether to continue with the older Python 2 or upgrade to the new Python 3.

For those new to Python, the response might be simple. This starts with Python 3, which is newer and better. For organizations or professionals who depend heavily on Python for their company and have large Python codebases, the decision is more difficult.

Python applications

Python 2.7 is used in the majority of Python applications today. However, the number of people switching to Python 3 is growing. This is partly because security updates for Python 2.7 will only be available until 2020.

Python 3 is needed for the development of new Python applications. If you’re writing a new open-source Python library, you can consider writing it for Python 2 as well as Python 3. This is because a sizable portion of Python developers already favors Python 2.

It is recommended that you use the most recent version of the Python 3.x interpreter since each new version improves bug fixes, stability, and standard library modules.

Only use Python 2 if you already have a Python 2 codebase or an exclusive Python 2 library.


That concludes the current list of the six most common Python interpreters. You are free to collaborate with all of them. However, each one has its own set of advantages. As a result, you should make wise decisions, particularly if you work professionally. Having a working knowledge of several Python interpreters may be beneficial. As a result, the more you attempt, the better. You can learn more about interpreters through Python online training.

Python certification training course will help you master the concepts and gain in-depth experience on writing Python code and packages like SciPy, Matplotlib,