Difference between various Implementations of Python
Last Updated :
13 Sep, 2023
When we speak of Python we often mean not just the language but also the implementation. Python is actually a specification for a language that can be implemented in many different ways.
Background
Before proceeding further let us understand the difference between bytecode and machine code(native code).
Machine Code(aka native code)
Machine code is set of instructions that directly gets executed by the CPU. Each instruction performs a very unique task, such as load or an logical operation on data in CPU memory. Almost all the high level languages such as C translate the source code into executable machine code with the help of Compilers, loaders and linkers. Every processor or processor family has its own machine code instruction set.
Bytecode
Bytecode is also binary representation executed by virtual machine (not by CPU directly). The virtual machine (which is written different for different machines) converts binary instruction into a specific machine instruction. One of the language that uses the concept of Bytecode is Java.
Machine Code is much faster as compared to Bytecode but Bytecode is portable and secure as compared to Machine Code.
Implementations of Python
Cpython
The default implementation of the Python programming language is Cpython. As the name suggests Cpython is written in C language. Cpython compiles the python source code into intermediate bytecode, which is executed by the Cpython virtual machine. CPython is distributed with a large standard library written in a mixture of C and Python. CPython provides the highest level of compatibility with Python packages and C extension modules. All versions of the Python language are implemented in C because CPython is the reference implementation.
Some of the implementations which are based on CPython runtime core but with extended behavior or features in some aspects are Stackless Python, wpython, MicroPython.
Stackless Python – CPython with an emphasis on concurrency using tasklets and channels (used by dspython for the Nintendo DS)
Other Implementations
There are some other implementations of the Python language too The only implementations that are known to be compatible with a given version of the language are IronPython, Jython and PyPy.
Jython
Jython is an implementation of the Python programming language that can run on the Java platform. Jython programs use Java classes instead of Python modules .Jython compiles into Java byte code, which can then be run by Java virtual machine. Jython enables the use of Java class library functions from the Python program. Jython is slow as compared to Cpython and lacks compatibility with CPython libraries.
IronPython
A Python implementation written in C# targeting Microsoft’s .NET framework. Similar to Jython, it uses .Net Virtual Machine i.e Common Language Runtime. IronPython can use the .NET Framework and Python libraries, and other .NET languages can use Python code very efficiently. IronPython performs better in Python programs that use threads or multiple cores, as it has a JIT, and also because it doesn’t have the Global Interpreter Lock.
PyPy
“If you want your code to run faster, you should probably just use PyPy.” — Guido van Rossum (creator of Python)
Python is dynamic programming language. Python is said to be slow as the default CPython implementation compiles the python source code in bytecode which is slow as compared to machine code(native code). Here PyPy comes in.
PyPy is an implementation of the Python programming language written in Python. The Interpreter is written in RPython (a subset of Python).
PyPy uses (just-in-time compilation). In simple terms JIT uses compilation methods to make interpreter system more efficient and fast. So basically JIT makes it possible to compile the source code into native machine code which makes it very fast.
PyPy also comes with default with support for stackless mode, providing micro-threads for massive concurrency. Python is said to be approximately 7.5 times faster than Cpython.
Some other Implementations of Python are CLPython, Pyston, Psyco, Cython, IPython.
References:
Similar Reads
Difference between Method and Function in Python
Here, key differences between Method and Function in Python are explained. Java is also an OOP language, but there is no concept of Function in it. But Python has both concept of Method and Function. Python Method Method is called by its name, but it is associated to an object (dependent).A method d
3 min read
Difference between input() and raw_input() functions in Python
Developers often have a need to interact with users, either to get data or to provide some sort of result. Most programs today use a dialog box as a way of asking the user to provide some type of input. While Python provides us with two inbuilt functions to read the input from the keyboard. input (
4 min read
Difference between PySpark and Python
PySpark is the Python API that is used for Spark. Basically, it is a collection of Apache Spark, written in Scala programming language and Python programming to deal with data. Spark is a big data computational engine, whereas Python is a programming language. To work with PySpark, one needs to have
4 min read
Difference between abstract class and interface in Python
In this article, we are going to see the difference between abstract classes and interface in Python, Below are the points that are discussed in this article: What is an abstract class in Python?What is an interface in Python?Difference between abstract class and interface in PythonWhat is an Abstra
4 min read
Different Python IDEs and Code Editors
What Are IDEs and Code Editors : IDE is a combination of tools that help in software development. IDE makes coding easier. As the name implies the Integrated Development Environment(IDE), it is a pack of tools combined or integrated together to establish software development at ease. The combination
5 min read
Bridging the Gap Between Rust and Python with PyO3
In this article, we will explore how PyO3 bridges the gap between Rust and Python. Each programming language has its unique strengths and weaknesses. Rust is favored by system developers for its exceptional speed, memory protection, and low-level capabilities. Python, on the other hand, stands out f
6 min read
Advance Features of Python
Python is a high-level, interpreted programming language that has easy syntax. Python codes are compiled line-by-line which makes the debugging of errors much easier and efficient. Python works on almost all types of platforms such as Windows, Mac, Linux, Raspberry Pi, etc. Python supports modules a
7 min read
Absolute and Relative Imports in Python
In this article, we are going to see that absolute and relative imports in Python. Working of import in Python Import in Python is similar to #include header_file in C/C++. Python modules can get access to code from another module by importing the file/function using import. The import statement is
6 min read
Best Python libraries for Machine Learning
Machine learning has become an important component in various fields, enabling organizations to analyze data, make predictions, and automate processes. Python is known for its simplicity and versatility as it offers a wide range of libraries that facilitate machine learning tasks. These libraries al
9 min read
Check if two PDF documents are identical with Python
Python is an interpreted and general purpose programming language. It is a Object-Oriented and Procedural paradigms programming language. There are various types of modules imported in python such as difflib, hashlib. Modules used:difflib : It is a module that contains function that allows to compar
2 min read