How is Python interpreted?

Python is considered an interpreted language, meaning its source code is executed line-by-line at runtime by an interpreter rather than being compiled directly into machine code. However, Python’s interpretation involves a few key steps:

Steps in Python Interpretation:

1. Compilation to Bytecode:
   • When you run a Python script, the Python interpreter first compiles the source code (.py files) into bytecode.
   • Bytecode is a low-level, platform-independent representation of your code, stored in .pyc files within a __pycache__ directory.
   • This step happens automatically and is generally invisible to the user.
2. Execution by the Python Virtual Machine (PVM):
   • The compiled bytecode is then interpreted by the Python Virtual Machine (PVM), which executes the bytecode instructions.
   • The PVM translates these instructions into machine code specific to your operating system and CPU architecture.
3. Dynamic Nature:
   • Python’s interpreter also dynamically resolves types and manages memory at runtime, contributing to its interpreted nature.

Why Python Feels Interpreted:

• No Explicit Compilation Step: Users don’t need to manually compile the code into an executable file before running it.
• Line-by-Line Execution: Python scripts are executed immediately, which makes debugging and testing quicker.
• Portability: The bytecode can run on any platform with a compatible Python interpreter.

Interpreters and Implementation:

Different Python implementations have varying ways of interpreting the language:

• CPython: The standard and most widely used implementation of Python. It compiles code to bytecode and interprets it.
• PyPy: A just-in-time (JIT) compiler implementation of Python that speeds up execution by optimizing bytecode into machine code at runtime.
• Jython: Python implemented in Java, which compiles Python code into Java bytecode.
• IronPython: Python implemented in C#, designed to integrate with .NET.

In conclusion, Python is interpreted through a combination of compilation to bytecode and execution by the Python Virtual Machine, which abstracts the complexity and allows developers to focus on writing Python code.