Compiling and Linking in Python

In Python, the process of compilation and loading involves several steps that occur when you run a Python script or module. Here's a breakdown of the process without specific examples:

Source Code

You start with the source code written in a .py file, which contains the Python program's instructions.

Lexical Analysis (Tokenization)

The Python interpreter performs lexical analysis to break the source code into tokens, which are the smallest units of meaningful components like keywords, identifiers, operators, and literals.

Parsing (Syntax Analysis)

The tokens are then analyzed to ensure they follow the correct syntax of the Python language. The parser builds a parse tree, a hierarchical structure representing the code's syntactic structure.

Abstract Syntax Tree (AST)

The parse tree is converted into an Abstract Syntax Tree (AST), which is a more concise and abstract representation of the program's structure.

Compilation to Bytecode

The Python code is not directly translated to machine code; instead, it is compiled to a lower-level bytecode that can be executed by the Python Virtual Machine (PVM). This compilation step generates .pyc files (compiled bytecode) for modules, which are stored in the __pycache__ directory.

Loading Bytecode

When you execute a Python script or import a module, the PVM checks for the presence of .pyc files or .py files (if .pyc is absent or outdated). The bytecode is then loaded into memory.


The loaded bytecode is interpreted and executed by the Python interpreter. The interpreter executes each bytecode instruction one by one, and your program's logic is executed accordingly.

Dynamic Typing

Python is dynamically typed, which means that the interpreter determines the data types of variables and objects during runtime. This allows for greater flexibility but requires the interpreter to perform type checking at runtime.


The compilation and loading process in Python is designed to provide a balance between ease of development and runtime efficiency. While Python is often considered an interpreted language, its bytecode compilation step improves execution speed and allows for portability across different platforms.