Short Answer

It's boilerplate code that protects users from accidentally invoking the script when they didn't intend to. Here are some common problems when the guard is omitted from a script:

• If you import the guardless script in another script (e.g. import my_script_without_a_name_eq_main_guard), then the latter script will trigger the former to run at import time and using the second script's command line arguments. This is almost always a mistake.

• If you have a custom class in the guardless script and save it to a pickle file, then unpickling it in another script will trigger an import of the guardless script, with the same problems outlined in the previous bullet.

Long Answer

To better understand why and how this matters, we need to take a step back to understand how Python initializes scripts and how this interacts with its module import mechanism.

Whenever the Python interpreter reads a source file, it does two things:

• it sets a few special variables like __name__, and then

• it executes all of the code found in the file.

Let's see how this works and how it relates to your question about the __name__ checks we always see in Python scripts.

Code Sample

Let's use a slightly different code sample to explore how imports and scripts work. Suppose the following is in a file called foo.py.

# Suppose this is foo.py.

print("before import")
import math

print("before function_a")
def function_a():
    print("Function A")

print("before function_b")
def function_b():
    print("Function B {}".format(math.sqrt(100)))

print("before __name__ guard")
if __name__ == '__main__':
    function_a()
    function_b()
print("after __name__ guard")

Special Variables

When the Python interpreter reads a source file, it first defines a few special variables. In this case, we care about the __name__ variable.

When Your Module Is the Main Program

If you are running your module (the source file) as the main program, e.g.

python foo.py

the interpreter will assign the hard-coded string "__main__" to the __name__ variable, i.e.

# It's as if the interpreter inserts this at the top
# of your module when run as the main program.
__name__ = "__main__" 

When Your Module Is Imported By Another

On the other hand, suppose some other module is the main program and it imports your module. This means there's a statement like this in the main program, or in some other module the main program imports:

# Suppose this is in some other main program.
import foo

The interpreter will search for your foo.py file (along with searching for a few other variants), and prior to executing that module, it will assign the name "foo" from the import statement to the __name__ variable, i.e.

# It's as if the interpreter inserts this at the top
# of your module when it's imported from another module.
__name__ = "foo"

Executing the Module's Code

After the special variables are set up, the interpreter executes all the code in the module, one statement at a time. You may want to open another window on the side with the code sample so you can follow along with this explanation.

Always

1. It prints the string "before import" (without quotes).

2. It loads the math module and assigns it to a variable called math. This is equivalent to replacing import math with the following (note that __import__ is a low-level function in Python that takes a string and triggers the actual import):

# Find and load a module given its string name, "math",
# then assign it to a local variable called math.
math = __import__("math")

3. It prints the string "before function_a".

4. It executes the def block, creating a function object, then assigning that function object to a variable called function_a.

5. It prints the string "before function_b".

6. It executes the second def block, creating another function object, then assigning it to a variable called function_b.

7. It prints the string "before __name__ guard".

Only When Your Module Is the Main Program

8. If your module is the main program, then it will see that __name__ was indeed set to "__main__" and it calls the two functions, printing the strings "Function A" and "Function B 10.0".

Only When Your Module Is Imported by Another

8. (instead) If your module is not the main program but was imported by another one, then __name__ will be "foo", not "__main__", and it'll skip the body of the if statement.

Always

9. It will print the string "after __name__ guard" in both situations.

Summary

In summary, here's what'd be printed in the two cases:

# What gets printed if foo is the main program
before import
before function_a
before function_b
before __name__ guard
Function A
Function B 10.0
after __name__ guard

# What gets printed if foo is imported as a regular module
before import
before function_a
before function_b
before __name__ guard
after __name__ guard

Why Does It Work This Way?

You might naturally wonder why anybody would want this. Well, sometimes you want to write a .py file that can be both used by other programs and/or modules as a module, and can also be run as the main program itself. Examples:

• Your module is a library, but you want to have a script mode where it runs some unit tests or a demo.

• Your module is only used as a main program, but it has some unit tests, and the testing framework works by importing .py files like your script and running special test functions. You don't want it to try running the script just because it's importing the module.

• Your module is mostly used as a main program, but it also provides a programmer-friendly API for advanced users.

Beyond those examples, it's elegant that running a script in Python is just setting up a few magic variables and importing the script. "Running" the script is a side effect of importing the script's module.

Food for Thought

• Question: Can I have multiple __name__ checking blocks? Answer: it's strange to do so, but the language won't stop you.

• Suppose the following is in foo2.py. What happens if you say python foo2.py on the command-line? Why?

# Suppose this is foo2.py.
import os, sys; sys.path.insert(0, os.path.dirname(__file__)) # needed for some interpreters

def function_a():
    print("a1")
    from foo2 import function_b
    print("a2")
    function_b()
    print("a3")

def function_b():
    print("b")

print("t1")
if __name__ == "__main__":
    print("m1")
    function_a()
    print("m2")
print("t2")
      

• Now, figure out what will happen in foo3.py (having removed the __name__ check):

# Suppose this is foo3.py.
import os, sys; sys.path.insert(0, os.path.dirname(__file__)) # needed for some interpreters

def function_a():
    print("a1")
    from foo3 import function_b
    print("a2")
    function_b()
    print("a3")

def function_b():
    print("b")

print("t1")
print("m1")
function_a()
print("m2")
print("t2")

• What will this do when used as a script? When imported as a module?

# Suppose this is in foo4.py
__name__ = "__main__"

def bar():
    print("bar")
    
print("before __name__ guard")
if __name__ == "__main__":
    bar()
print("after __name__ guard")

The Python approach to "main" is almost unique to the language(*).

The semantics are a bit subtle. The __name__ identifier is bound to the name of any module as it's being imported. However, when a file is being executed then __name__ is set to "__main__" (the literal string: __main__).

This is almost always used to separate the portion of code which should be executed from the portions of code which define functionality. So Python code often contains a line like:

#!/usr/bin/env python
from __future__ import print_function
import this, that, other, stuff
class SomeObject(object):
    pass

def some_function(*args,**kwargs):
    pass

if __name__ == '__main__':
    print("This only executes when %s is executed rather than imported" % __file__)

Using this convention one can have a file define classes and functions for use in other programs, and also include code to evaluate only when the file is called as a standalone script.

It's important to understand that all of the code above the if __name__ line is being executed, evaluated, in both cases. It's evaluated by the interpreter when the file is imported or when it's executed. If you put a print statement before the if __name__ line then it will print output every time any other code attempts to import that as a module. (Of course, this would be anti-social. Don't do that).

I, personally, like these semantics. It encourages programmers to separate functionality (definitions) from function (execution) and encourages re-use.

Ideally almost every Python module can do something useful if called from the command line. In many cases this is used for managing unit tests. If a particular file defines functionality which is only useful in the context of other components of a system then one can still use __name__ == "__main__" to isolate a block of code which calls a suite of unit tests that apply to this module.

(If you're not going to have any such functionality nor unit tests than it's best to ensure that the file mode is NOT executable).

Summary: if __name__ == '__main__': has two primary use cases:

• Allow a module to provide functionality for import into other code while also providing useful semantics as a standalone script (a command line wrapper around the functionality)
• Allow a module to define a suite of unit tests which are stored with (in the same file as) the code to be tested and which can be executed independently of the rest of the codebase.

It's fairly common to def main(*args) and have if __name__ == '__main__': simply call main(*sys.argv[1:]) if you want to define main in a manner that's similar to some other programming languages. If your .py file is primarily intended to be used as a module in other code then you might def test_module() and calling test_module() in your if __name__ == '__main__:' suite.

• (Ruby also implements a similar feature if __file__ == $0).