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What's the bad magic number error?

python
bytecode
magic-number
python-environment
Anton ShumikhinbyAnton Shumikhin·Sep 3, 2024
TLDR

When you face a "bad magic number" error, it's a sign that a .pyc file compiled with one Python version is being executed with a different version. To fix this, delete the .pyc file and let the Python interpreter recompile it using the actual Python version.

import py_compile

When life gives you .py, make it .pyc 🍋🍹

py_compile.compile('your_script.py')

This code generates a fresh `.pyc` file that is compatible with your interpreter.

## The error decoded

The "bad magic number" error pops up when you are dealing with **bytecode files**, specifically in Python. This error signifies a `.pyc` file compiled with a different Python version is being executed. Every `.pyc` file houses a **magic number** - a **version-specific** identifier that the Python interpreter uses to check compatibility.

## Solving the version riddle

Having a file with an inconsistent magic number means the interpreter can't load it causing the error. An easy resolution is to remove the `.pyc` files, thereby prompting Python to **regenerate them**. Here's a command for mass action:

```sh
## Let's play 'hide and seek'. Ready? Hide! 🙈
find . -name '*.pyc' -delete

Identifying magic numbers

For the curious who wish to unravel this mystery or for those looking to troubleshoot, inspect the first 4 bytes of a .pyc file using a hex editor to find the magic number. Cross-verify this number with the magic numbers in the Python/import.c file to identify the correct Python version. Remember, modifying the .pyc file to alter the magic number can stir up chaos.

Trapping intermittent issues

If this error sneaks up on you from time to time, it may hint at a more complex issue such as a volatile Python environment or a .pyc file compiled with a different Python version sneaking in. Keep your Python environments uniform, especially when working with virtual environments or container-based applications.

Taking a closer look at import errors

Handling specific module errors

Errors that are peculiar to a specific module, say Normalization, could be due to the associated .pyc file being compiled with a non-compatible Python version. This is common when you upgrade your Python version but forget to recompile the .py files.

Deciphering tracebacks

Tracebacks, while certainly helpful, may not always lead you to the root of the "bad magic number" error. Rather than focusing solely on code logic, consider it could be a file compatibility issue.

Setting up the right environment

If import errors are a persistent thorn in your side, look for an __init__.py file in the directory where your modules live - this file indicates to Python that the directory can be treated as a package. If problems persist even after all .pyc files are removed, then it might be time to reassess the module or its location.

Preventive measures

  • Keep a consistent Python environment. Seclude versions using tools like pyenv or virtualenv.
  • Use version control for your .py files and steer clear of checking in .pyc files to prevent cross-version mishaps.
  • Regularly clean up .pyc files when updating Python versions.
  • Include a step in your CI/CD pipeline to verify the absence of old .pyc files.
  • Raising awareness within your team about Python version inconsistencies and the need for recompilation can save you a ton of trouble.