What makes Python a slow language ? Last Updated : 23 Jul, 2025 Comments Improve Suggest changes 15 Likes Like Report Python is a high-level language (than C or C++) thus Python itself manages details of a program like memory allocation, memory deallocation, pointers, etc. This makes writing codes in Python easier for programmers. Python code is first compiled into python Byte Code. The Byte Code interpreter conversion happens internally and most of it is hidden from the developer. Byte code is platform-independent and lower-level programming. Compilation of byte code is to ramp up the execution of source code. The source code compiled to byte code is then executed in Python’s virtual machine one by one, to carry out the operations. The virtual machine is an internal component of Python. Internally Python code is interpreted during run time rather than being compiled to native code hence it is a bit slower. Running of Python script v/s running of C/C++ code: Python: First it is compiled into Byte Code. This Byte Code is then interpreted and executed by the PVM (Python Virtual Machine). C/C++: The source code is compiled into Binary Code which can be directly executed by the CPU making them more efficient. Major Reasons for Python being slow: Being Interpreted: Unlike native languages like C/C++, Python code gets interpreted at runtime instead of being compiled to native code at compile time. Python is an interpreted language, which means that the Python code we write must go through many, many stages of abstraction before it can become executable machine code.Just In Time (JIT) Compiler: Other interpreted languages like Java/.NET byte code run faster than Python's byte code because their standard distribution includes a JIT compiler that compiles byte code into native code at run time. Python does not have a JIT compiler because the dynamic nature of Python makes it difficult to write one. It is impossible to say what type of parameters will be passed to a function, which makes optimization a bit harder.Global Interpreter Lock (GIL): It prevents multi-threading by mandating the interpreter to execute only a single thread within a single process (i.e. an instance of Python interpreter) at a time. Create Quiz Comment I imsushant12 Follow 15 Improve I imsushant12 Follow 15 Improve Article Tags : Python Python-Quizzes Explore Python FundamentalsPython Introduction 2 min read Input and Output in Python 4 min read Python Variables 4 min read Python Operators 4 min read Python Keywords 2 min read Python Data Types 8 min read Conditional Statements in Python 3 min read Loops in Python - For, While and Nested Loops 5 min read Python Functions 5 min read Recursion in Python 4 min read Python Lambda Functions 5 min read Python Data StructuresPython String 5 min read Python Lists 4 min read Python Tuples 4 min read Python Dictionary 3 min read Python Sets 6 min read Python Arrays 7 min read List Comprehension in Python 4 min read Advanced PythonPython OOP Concepts 11 min read Python Exception Handling 5 min read File Handling in Python 4 min read Python Database Tutorial 4 min read Python MongoDB Tutorial 3 min read Python MySQL 9 min read Python Packages 10 min read Python Modules 3 min read Python DSA Libraries 15 min read List of Python GUI Library and Packages 3 min read Data Science with PythonNumPy Tutorial - Python Library 3 min read Pandas Tutorial 4 min read Matplotlib Tutorial 5 min read Python Seaborn Tutorial 3 min read StatsModel Library - Tutorial 3 min read Learning Model Building in Scikit-learn 6 min read TensorFlow Tutorial 2 min read PyTorch Tutorial 6 min read Web Development with PythonFlask Tutorial 8 min read Django Tutorial | Learn Django Framework 7 min read Django ORM - Inserting, Updating & Deleting Data 4 min read Templating With Jinja2 in Flask 6 min read Django Templates 5 min read Build a REST API using Flask - Python 3 min read Building a Simple API with Django REST Framework 3 min read Python PracticePython Quiz 1 min read Python Coding Practice 1 min read Python Interview Questions and Answers 15+ min read Like