What Is Pycache?

Are you curious to know what is pycache? You have come to the right place as I am going to tell you everything about pycache in a very simple explanation. Without further discussion let’s begin to know what is pycache?

If you’ve been working with Python, you might have come across a folder called “pycache” in your project directory. This folder contains bytecode files with the extension “.pyc”. In this blog post, we will demystify pycache by explaining its purpose, function, and the benefits it brings to Python programming.

What Is Pycache?

Pycache, short for Python cache, is a directory created by the Python interpreter to store compiled bytecode files. When you run a Python script or import a module, the Python interpreter translates the source code into bytecode, which is a lower-level representation that can be executed more efficiently. The bytecode is then stored in the pycache folder for future use.

Purpose Of Pycache:

The primary purpose of Pycache is to improve the execution performance of Python code. By storing precompiled bytecode, subsequent executions of the same code can skip the step of recompiling the source code into bytecode. Instead, the interpreter directly uses the bytecode stored in the pycache, resulting in faster program execution.

Function Of Pycache:

  1. Bytecode Compilation: When Python encounters a module or script for the first time, it compiles the source code into bytecode. The compiled bytecode is then stored in the pycache folder with a “.pyc” file extension. This process helps save time by avoiding repetitive compilation for subsequent executions.
  2. Timestamp Validation: Whenever Python executes a module or script, it checks the timestamp of the corresponding “.py” file against the “.pyc” file in the pycache. If the source code file has been modified since the bytecode was last compiled, the interpreter recompiles the code to update the bytecode.
  3. Improved Performance: By using precompiled bytecode from the pycache, Python programs execute faster compared to interpreting the source code directly. The bytecode is optimized for execution, making it more efficient and reducing the overhead of compilation.

Benefits Of Pycache:

  1. Faster Program Startup: With pycache, subsequent executions of Python code start faster because the bytecode is readily available. The interpreter can skip the compilation step and directly load the bytecode, resulting in reduced startup time.
  2. Improved Execution Speed: By using precompiled bytecode, Python programs experience improved execution speed. The interpreter can execute bytecode more efficiently than interpreting the source code, leading to faster program execution.
  3. Source Code Protection: The pycache files only contain bytecode and not the original source code. This provides a certain level of protection for your Python code as it is not readily accessible to others who may have access to your project directory.

Working With Pycache:

  1. Automatic Creation: Pycache directories and bytecode files are automatically generated by the Python interpreter when modules or scripts are executed or imported.
  2. Version Compatibility: Pycache files are tied to the specific version of Python used to generate them. Therefore, if you switch to a different Python version, it is recommended to delete the pycache files to avoid potential compatibility issues.
  3. Cleaning Pycache: To clear the pycache files, you can manually delete the “pycache” directories or use tools like “pyclean” provided by Python itself.


Pycache plays a crucial role in optimizing the execution performance of Python code. By storing precompiled bytecode, it allows for faster program startup and improved execution speed. Understanding pycache and its benefits can help you appreciate its role in Python programming and make the most of its advantages. Embrace the efficiency provided by pycache and enjoy faster and smoother Python code execution.

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What Is Pycache In Python?

__pycache__ is a directory that contains bytecode cache files that are automatically generated by Python, namely compiled Python, or. py, files. You might be wondering why Python, an “interpreted” language, has any compiled files at all.

What Happens If I Delete __ Pycache __ Folder?

Suppressing the creation of __pycache__

Again, this will prevent Python from trying to write. py files.

Can I Delete Pyc Files?

py files in the current directory and its subdirectories, and delete them. Note that deleting. py files are usually not necessary, as the Python interpreter will regenerate them as needed. However, in some cases, it may be useful to delete the files to force the interpreter to recompile the source code.

How To Ignore Pycache Files In Git?

psychache stores temporary files created when execution of the Python code is triggered. You can create. gitignore with __pycache__ and *. pyc is listed there, so you don’t commit them again by mistake.


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