If you have ever copied a quick demo or a throwaway test into a Python file and then cursed when imports started doing weird things welcome to the world of the main guard. The expression __name__ == "__main__" is the polite way to say run this code only when the file is executed as the program and not when it is imported as a module.

What actually happens

Python gives every module a built in variable called __name__. When you run a file directly the interpreter sets that variable to "__main__". When another file imports the module Python sets __name__ to the module name instead. The check if __name__ == "__main__" is a gate that prevents code from running on import.

Why bother with the guard

• Keep tests safe Place quick demos or sanity checks inside the guard so importing the module does not execute test code.
• Provide a command line entry point You can parse arguments and call a main function so the same file works as a library and a script.
• Avoid surprise side effects Top level file IO or network calls during import make things flaky for other modules and for testing.

Minimal example

Replace top level prints with a clear entry point. This pattern is test friendly and plays nicely with importers and test runners.

def main():
    print("Running as a script")
    # parse args and run program logic here

if __name__ == "__main__":
    main()

Notes about module execution

If you run a module with python -m yourpackage.module Python will execute it as a script and set __name__ to "__main__". That lets packages act as convenient command line tools without rewriting code.

Common gotchas

• Forgetting the guard means side effects run on import and tests break mysteriously.
• Using top level argument parsing will try to eat sys.argv during imports so keep parsing inside main.
• Unit test frameworks import modules to inspect them so avoid running code at import time.

Quick checklist

• Define a main function that contains runnable behavior
• Call main() from inside the guard
• Keep module level code limited to definitions and safe initialization

In short treat the guard as an on off switch for script behavior. Use it and your modules will behave like polite citizens in the python ecosystem whether you are teaching a tutorial using python main examples or building reusable python modules for production and testing.