Execution of Python code with -m option or not

When you use the -m command-line flag, Python will import a module or package for you, then run it as a script. When you don't use the -m flag, the file you named is run as just a script.

The distinction is important when you try to run a package. There is a big difference between:

python foo/bar/baz.py

and

python -m foo.bar.baz

as in the latter case, foo.bar is imported and relative imports will work correctly with foo.bar as the starting point.

Demo:

$ mkdir -p test/foo/bar
$ touch test/foo/__init__.py
$ touch test/foo/bar/__init__.py
$ cat << EOF > test/foo/bar/baz.py 
> if __name__ == "__main__":
>     print __package__
>     print __name__
> 
> EOF
$ PYTHONPATH=test python test/foo/bar/baz.py 
None
__main__
$ PYTHONPATH=test python -m foo.bar.baz 
foo.bar
__main__

As a result, Python has to actually care about packages when using the -m switch. A normal script can never be a package, so __package__ is set to None.

But run a package or module inside a package with -m and now there is at least the possibility of a package, so the __package__ variable is set to a string value; in the above demonstration it is set to 'foo.bar', for plain modules not inside a package it is set to an empty string.

As for the __main__ module, Python imports scripts being run as it would import regular modules. A new module object is created to hold the global namespace and is stored in sys.modules['__main__']. This is what the __name__ variable refers to, it is a key in that structure.

For packages, you can create a __main__.py module inside and have that run when running python -m package_name; in fact that is the only way you can run a package as a script:

$ PYTHONPATH=test python -m foo.bar
python: No module named foo.bar.__main__; 'foo.bar' is a package and cannot be directly executed
$ cp test/foo/bar/baz.py test/foo/bar/__main__.py
$ PYTHONPATH=test python -m foo.bar
foo.bar
__main__

So, when naming a package for running with -m, Python looks for a __main__ module contained in that package and executes that as a script. Its name is then still set to '__main__' and the module object is still stored in sys.modules['__main__'].

The main reason to run a module (or package) as a script with -m is to simplify deployment, especially on Windows. You can install scripts in the same place in the Python library where modules normally go - instead of polluting PATH or global executable directories such as ~/.local (the per-user scripts directory is ridiculously hard to find in Windows).

Then you just type -m and Python finds the script automagically. For example, python -m pip will find the correct pip for the same instance of Python interpreter which executes it. Without -m, if user has several Python versions installed, which one would be the "global" pip?

If user prefers "classic" entry points for command-line scripts, these can be easily added as small scripts somewhere in PATH, or pip can create these at install time with entry_points parameter in setup.py.

So just check for __name__ == '__main__' and ignore other non-reliable implementation details.

Execution of Python code with -m option or not

Use the -m flag.

The results are pretty much the same when you have a script, but when you develop a package, without the -m flag, there's no way to get the imports to work correctly if you want to run a subpackage or module in the package as the main entry point to your program (and believe me, I've tried.)

The docs

Like the docs on the -m flag say:

Search sys.path for the named module and execute its contents as the __main__ module.

and

As with the -c option, the current directory will be added to the start of sys.path.

so

python -m pdb

is roughly equivalent to

python /usr/lib/python3.5/pdb.py

(assuming you don't have a package or script in your current directory called pdb.py)

Explanation:

Behavior is made "deliberately similar to" scripts.

Many standard library modules contain code that is invoked on their execution as a script. An example is the timeit module:

Some python code is intended to be run as a module: (I think this example is better than the commandline option doc example)

$ python -m timeit '"-".join(str(n) for n in range(100))'
10000 loops, best of 3: 40.3 usec per loop
$ python -m timeit '"-".join([str(n) for n in range(100)])'
10000 loops, best of 3: 33.4 usec per loop
$ python -m timeit '"-".join(map(str, range(100)))'
10000 loops, best of 3: 25.2 usec per loop

And from the release note highlights for Python 2.4:

The -m command line option - python -m modulename will find a module in the standard library, and invoke it. For example, python -m pdb is equivalent to python /usr/lib/python2.4/pdb.py

Follow-up Question

Also, David Beazley's Python Essential Reference explains it as "The -m option runs a library module as a script which executes inside the __main__ module prior to the execution of the main script".

It means any module you can lookup with an import statement can be run as the entry point of the program - if it has a code block, usually near the end, with if __name__ == '__main__':.

-m without adding the current directory to the path:

A comment here elsewhere says:

That the -m option also adds the current directory to sys.path, is obviously a security issue (see: preload attack). This behavior is similar to library search order in Windows (before it had been hardened recently). It's a pity that Python does not follow the trend and does not offer a simple way to disable adding . to sys.path

Well, this demonstrates the possible issue - (in windows remove the quotes):

echo "import sys; print(sys.version)" > pdb.py

python -m pdb
3.5.2 |Anaconda 4.1.1 (64-bit)| (default, Jul  5 2016, 11:41:13) [MSC v.1900 64 bit (AMD64)]

Use the -I flag to lock this down for production environments (new in version 3.4):

python -Im pdb
usage: pdb.py [-c command] ... pyfile [arg] ...
etc...

from the docs:

-I

Run Python in isolated mode. This also implies -E and -s. In isolated mode sys.path contains neither the script’s directory nor the user’s site-packages directory. All PYTHON* environment variables are ignored, too. Further restrictions may be imposed to prevent the user from injecting malicious code.

What does __package__ do?

It enables explicit relative imports, not particularly germane to this question, though - see this answer here: What's the purpose of the "__package__" attribute in Python?