How to Prevent Python from Creating pycache Folders

You’re knee-deep in a project, running a quick test, and then you see it: a swarm of __pycache__ folders littering your directory tree. Honestly? It drives me nuts too. I’ve been coding in Python for over a decade, and those little bytecode caches have caused more confusion in version control than I care to admit. But here’s the thing—you don’t have to live with them. You can prevent Python from creating pycache folders with a few straightforward tricks. Let me show you how.

First, understand why Python bothers with these folders at all. When you import a module, the interpreter compiles it to bytecode for faster loading next time. That bytecode gets stashed in __pycache__ as .pyc files. Smart? Sure. Annoying when you’re cleaning up? Absolutely. The good news is you can disable pycache entirely or redirect it. We’ll cover the best methods for development, CI/CD, and even production.

Before we dive in, a quick note: I’m assuming you’re using Python 3.2+. The __pycache__ convention started there. Older versions used plain .pyc files next to the source. If you’re stuck on 2.7, well, you have bigger problems. Let’s focus on the modern approach.

Why You’d Want to Block __pycache__ (and When Not To)

Look, I get it. Preventing Python from creating pycache folders feels almost rebellious. But there are legitimate reasons. Version control gets cluttered—yes, you can add __pycache__/ to .gitignore, but sometimes you want zero generated files. Or you’re building a one-off script that runs on a server with read-only filesystems. Or you’re just a neat freak like me.

However, keep in mind: bytecode caching speeds up repeated imports. Disabling it means every module gets recompiled from scratch each run. For small scripts, you won’t notice. For large applications with hundreds of imports, you’ll feel the lag. So choose wisely. In production, you probably want caching enabled. For development or ephemeral environments, feel free to disable pycache without hesitation.

The Environment Variable Trick: PYTHONDONTWRITEBYTECODE

This is the quickest, dirtiest method. Set the environment variable PYTHONDONTWRITEBYTECODE=1 before running Python. It’s a global switch that tells the interpreter: 'Don't write any .pyc files, don't create any __pycache__ folders.' Seriously, it’s that simple.

On Linux or macOS, fire up your terminal:

export PYTHONDONTWRITEBYTECODE=1  
python myscript.py

On Windows (Command Prompt):

set PYTHONDONTWRITEBYTECODE=1  
python myscript.py

Or in PowerShell:

$env:PYTHONDONTWRITEBYTECODE=1  
python myscript.py

This works for the entire session. You can even add it to your shell profile (.bashrc, .zshrc) to prevent pycache globally. But careful—you might forget and wonder why your app suddenly feels sluggish.

One caveat: it only affects the current process. If you spawn subprocesses or use virtualenv activation scripts, you might need to set it again. Still, for a quick hack, it’s unbeatable.

Command-Line Flag: python -B

Don’t want to mess with environment variables? Use the -B flag. Run python -B myscript.py, and Python will skip bytecode writing entirely. No __pycache__ appears. It’s the same mechanism as the environment variable, but tied to the invocation rather than the session.

I use this constantly in testing. It’s especially handy when you’re running a one-liner or a quick import check. For example:

python -B -c 'import mymodule; print(mymodule.func())'

This keeps your workspace pristine. However, if your application uses multiple entry points or is wrapped in a launcher (like flask run or celery worker), you may not have control over the flags. In that case, the environment variable approach is more reliable.

Programmatic Control: Blocking __pycache__ Inside Your Code

Sometimes you need to disable pycache from within the script itself. Maybe you’re packaging a tool for a client and you don’t want any leftover files. Python offers a built-in switch: sys.dont_write_bytecode.

Add this line at the very start of your script (before any imports that trigger bytecode writing):

import sys  
sys.dont_write_bytecode = True

That’s it. Python will respect this flag for the rest of the process. No __pycache__ folders. It’s a powerful way to enforce prevention of pycache inside a specific project. I often include it in a __init__.py or a top-level config file.

Remember: It Only Affects the Current Interpreter

One pitfall: if your script forks or uses multiprocessing, child processes may not inherit this setting. You’ll need to set it again in the child’s entry point. Also, some third-party libraries (like pytest or numpy) may override this. Test it thoroughly.

For extra safety, combine sys.dont_write_bytecode with the environment variable. Belt and suspenders. Overkill? Maybe. But when you absolutely, positively need zero __pycache__ folders, this combo works every time.

Redirecting Cache to /dev/null or a Temp Directory

Here’s a trick the docs don’t shout about: you can set PYTHONPYCACHEPREFIX to a custom location. For example, export PYTHONPYCACHEPREFIX=/tmp/pycache. Python will write all bytecode there, keeping your project folder spotless.

But honestly? If you’re going that route, you might as well just disable pycache entirely. Redirecting is useful for shared filesystems (NFS) or when you want caching but not in the source tree. For most cases, PYTHONDONTWRITEBYTECODE=1 is cleaner.

One edge case: Python's zipimporter and frozen modules may ignore these settings. But for your average script, you’re covered.

Automating the Block: Aliases, Shell Functions, and IDEs

Let’s get practical. If you’re tired of typing -B or setting env vars manually, bake it into your workflow. Create an alias in your shell:

alias python='python -B'

This is a blunt instrument, but it works. Every python command now runs with the bytecode flag. I do this on my dev machine because I rarely need the performance boost during development—I’d rather keep my repo clean. Just remember to comment it out when you’re running benchmarks.

Visual Studio Code and PyCharm Settings

Both major IDEs let you pass command-line arguments to the Python interpreter. In VS Code, open settings.json and add:

"python.terminal.launchArgs": ["-B"]

In PyCharm, go to Run/Debug Configurations, find 'Interpreter options', and type -B. Now every run from the IDE respects your wish to prevent Python from creating pycache folders.

These tweaks save you from manually remembering each time. Plus, they act as a global preference for that project.

Common Questions About Preventing pycache

Will disabling __pycache__ break my code?

No. Python runs fine without bytecode caching. It simply recompiles every time. The only downside is startup performance. If your app is a small script or a web server that imports many modules, you’ll notice a slower cold start. For a long-running process, the overhead vanishes after the first few seconds.

Can I delete __pycache__ folders without consequences?

Absolutely. They’re generated automatically. Deleting them is safe—Python will recreate them next time it imports those modules (unless you’ve disabled caching). I often run find . -type d -name __pycache__ -exec rm -rf {} + to tidy up. Just be careful not to delete them while the interpreter is running.

Does sys.dont_write_bytecode affect all imports?

Yes, for the current process. But note that some C extensions and frozen modules may cache bytecode internally. For pure Python modules, it works perfectly. Set it before any imports that might trigger bytecode writing, ideally in the main script.

What about pip and virtualenv? Do they create __pycache__?

pip doesn’t create __pycache__ itself, but the packages you install will generate them when imported. If you set PYTHONDONTWRITEBYTECODE in the virtualenv activation script, all imports inside that environment will skip caching. Handy for disposable environments.

Is there a way to make 'no pycache' the default for my entire system?

You can export PYTHONDONTWRITEBYTECODE=1 in your shell profile (e.g., ~/.bashrc). Every new terminal session will then run Python with caching off. Just keep in mind that any script relying on __pycache__ for speed (like a large Django app) will be slower. I recommend per-project control instead.

There you have it. You now own the tools to prevent Python from creating pycache folders seamlessly. Environment variables, command flags, code-level switches, or IDE tweaks—pick the one that fits your workflow. No more clutter, no more accidental commits of bytecode. Your project folder will thank you.