The Role of __pycache__ Folder in Python Programs

When you run Python code, you may sometimes notice that a folder called __pycache__ gets created in your project directory. Many developers, especially those new to Python, often wonder why this folder is created and what purpose it serves. In this article, let’s look at the role of the __pycache__ folder, why it exists, and how you can control its creation.

What Happens When a Python Script Runs

To understand the purpose of the __pycache__ folder, it is essential to know what occurs when a Python script is executed. A common misconception is that Python is purely an interpreted language. In fact, Python uses a combination of both compilation and interpretation.

When Python runs code, it does not directly execute the .py file line by line. Instead, it first compiles the code into bytecode. This bytecode is a lower-level, platform-independent version of the Python source code, making it easier for the interpreter to process. After compiling, the Python interpreter (also known as the Python Virtual Machine or PVM) executes the bytecode by converting it into machine-level instructions that the computer can run line by line.

What is Stored in the __pycache__ Folder?

The __pycache__ folder contains compiled bytecode files for Python programs. Rather than compiling the same code repeatedly every time you run it, Python caches the compiled bytecode so that future executions can skip the compilation step and directly interpret the bytecode.

Contents of the __pycache__ Folder

• Bytecode Files: These files have a .pyc extension and represent compiled versions of Python scripts. The name of the bytecode file is typically in the format module.cpython-<python-version>.pyc. For example, if a file is named example.py and Python 3.9 is being used, the bytecode file might be named example.cpython-39.pyc.
• Optimized Bytecode: Sometimes, optimized bytecode files with a .pyo extension are created if Python is run with optimization flags.

How Caching Improves Performance

By storing Python code as bytecode, Python eliminates the need to repeatedly process the source code with every run. When a script is executed, Python checks if the corresponding .pyc file exists and is up-to-date with the .py source file. If it is, Python skips the compilation step and directly executes the bytecode, speeding up program startup time.

This caching is especially useful in large projects with multiple modules, as it prevents unnecessary recompilation of unchanged files and enhances overall performance.

When is the __pycache__ Folder Created?

The __pycache__ folder is created only when a module is imported into the program, as Python compiles the module’s source code into bytecode. If no modules are imported in a Python script, the __pycache__ folder will not be generated.

Script Execution vs. Module Imports

• Single Script Execution: When a simple script is run without importing any modules, Python compiles it into bytecode in memory. However, it does not save this bytecode to disk, meaning no __pycache__ folder is created.
• Module Imports: When a module is imported, Python compiles the module into bytecode and stores the .pyc file in the __pycache__ folder. This is done because the module may be reused multiple times across different scripts, and caching the bytecode enhances performance by preventing recompilation.

How to Prevent the __pycache__ Folder from Being Created

There may be situations when it is desirable to prevent the creation of the __pycache__ folder, especially in controlled environments. Here are 3 methods to achieve this:

Here are three ways to prevent the __pycache__ folder from being created:

1. Use the -B Flag: You can run your Python script with the -B flag, which prevents Python from writing bytecode files. For example:
   

   python -B example.py
   

   This will prevent the __pycache__ folder from being created for that specific run.

2. Set the PYTHONDONTWRITEBYTECODE Environment Variable: You can set the PYTHONDONTWRITEBYTECODE environment variable to any value (like 1) before running your Python script. This tells Python not to write the bytecode files or create the __pycache__ directory. You can do this in your terminal or command prompt:

   • On Linux or macOS:
     

     export PYTHONDONTWRITEBYTECODE=1
     python your_script.py
     

   • On Windows:
     

     set PYTHONDONTWRITEBYTECODE=1
     python your_script.py
     

3. Modify the Script: If you prefer a more permanent solution for a specific script, you can modify the script to set the environment variable at the beginning:
   

   import sys
   sys.dont_write_bytecode = True
   

Using any of the above three methods will stop Python from creating the __pycache__ folder.

When Should the __pycache__ Folder be Disabled?

While it is possible to disable the creation of the __pycache__ folder, this is generally not recommended unless there is a specific reason. The cached bytecode significantly improves performance, especially in larger projects or when scripts are run repeatedly.

However, disabling __pycache__ may be helpful in restricted or temporary environments, such as a production server or containerized application, where controlling generated files is essential.