What does if __name__ == “__main__”: do in Python? [Answered]


Given the following code, what does the if __name__ == "__main__": do?

# Threading example
import time, thread

def myfunction(string, sleeptime, lock, *args):
    while True:

if __name__ == "__main__":
    lock = thread.allocate_lock()
    thread.start_new_thread(myfunction, ("Thread #: 1", 2, lock))
    thread.start_new_thread(myfunction, ("Thread #: 2", 2, lock))

What does if __name__ == “__main__“: do? Answer #1:

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 second script will trigger the first 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 functionA")
def functionA():
    print("Function A")

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

print("before __name__ guard")
if __name__ == '__main__':
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.


  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")
  1. It prints the string "before functionA".
  2. It executes the def block, creating a function object, then assigning that function object to a variable called functionA.
  3. It prints the string "before functionB".
  4. It executes the second def block, creating another function object, then assigning it to a variable called functionB.
  5. It prints the string "before __name__ guard".

Only When Your Module Is the Main Program

  1. 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

  1. (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.


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


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

# What gets printed if foo is the main program
before import
before functionA
before functionB
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 functionA
before functionB
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 functionA():
    from foo2 import functionB

def functionB():

if __name__ == "__main__":
  • Now, figure out what will happen if you remove the __name__ check in foo3.py:
# Suppose this is foo3.py.
import os, sys; sys.path.insert(0, os.path.dirname(__file__)) # needed for some interpreters

def functionA():
    from foo3 import functionB

def functionB():

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

Answer #2:

When your script is run by passing it as a command to the Python interpreter,

python myscript.py

all of the code that is at indentation level 0 gets executed. Functions and classes that are defined are, well, defined, but none of their code gets run. Unlike other languages, there’s no main() function that gets run automatically – the main() function is implicitly all the code at the top level.

In this case, the top-level code is an if block. __name__ is a built-in variable which evaluates to the name of the current module. However, if a module is being run directly (as in myscript.py above), then __name__ instead is set to the string "__main__". Thus, you can test whether your script is being run directly or being imported by something else by testing

if __name__ == "__main__":

If your script is being imported into another module, its various function and class definitions will be imported and its top-level code will be executed, but the code in the then-body of the if clause above won’t get run as the condition is not met. As a basic example, consider the following two scripts:

# file one.py
def func():
    print("func() in one.py")

print("top-level in one.py")

if __name__ == "__main__":
    print("one.py is being run directly")
    print("one.py is being imported into another module")
# file two.py
import one

print("top-level in two.py")

if __name__ == "__main__":
    print("two.py is being run directly")
    print("two.py is being imported into another module")

Now, if you invoke the interpreter as

python one.py

The output will be

top-level in one.py
one.py is being run directly

If you run two.py instead:

python two.py

You get

top-level in one.py
one.py is being imported into another module
top-level in two.py
func() in one.py
two.py is being run directly

Thus, when module one gets loaded, its __name__ equals "one" instead of "__main__".

Answer #3:

The simplest explanation for the __name__ variable (imho) is the following:

Create the following files.

# a.py
import b


# b.py
print "Hello World from %s!" % __name__

if __name__ == '__main__':
    print "Hello World again from %s!" % __name__

Running them will get you this output:

$ python a.py
Hello World from b!

As you can see, when a module is imported, Python sets globals()['__name__'] in this module to the module’s name. Also, upon import all the code in the module is being run. As the if statement evaluates to False this part is not executed.

$ python b.py
Hello World from __main__!
Hello World again from __main__!

As you can see, when a file is executed, Python sets globals()['__name__'] in this file to "__main__". This time, the if statement evaluates to True and is being run.

What does if __name__ == “__main__“: do? Answer #4:

To outline the basics:

  • The global variable, __name__, in the module that is the entry point to your program, is '__main__'. Otherwise, it’s the name you import the module by.
  • So, code under the if block will only run if the module is the entry point to your program.
  • It allows the code in the module to be importable by other modules, without executing the code block beneath on import.

Why do we need this?

Developing and Testing Your Code

Say you’re writing a Python script designed to be used as a module:

def do_important():
    """This function does something very important"""

You could test the module by adding this call of the function to the bottom:


and running it (on a command prompt) with something like:

~$ python important.py

The Problem

However, if you want to import the module to another script:

import important

On import, the do_important function would be called, so you’d probably comment out your function call, do_important(), at the bottom.

# do_important() # I must remember to uncomment to execute this!

And then you’ll have to remember whether or not you’ve commented out your test function call. And this extra complexity would mean you’re likely to forget, making your development process more troublesome.

A Better Way

The __name__ variable points to the namespace wherever the Python interpreter happens to be at the moment.

Inside an imported module, it’s the name of that module.

But inside the primary module (or an interactive Python session, i.e. the interpreter’s Read, Eval, Print Loop, or REPL) you are running everything from its "__main__".

So if you check before executing:

if __name__ == "__main__":

With the above, your code will only execute when you’re running it as the primary module (or intentionally call it from another script).

An Even Better Way

There’s a Pythonic way to improve on this, though.

What if we want to run this business process from outside the module?

If we put the code we want to exercise as we develop and test in a function like this and then do our check for '__main__' immediately after:

def main():
    """business logic for when running this module as the primary one!"""
    foo = do_important()
    bar = do_even_more_important(foo)
    for baz in bar:

# Here's our payoff idiom!
if __name__ == '__main__':

We now have a final function for the end of our module that will run if we run the module as the primary module.

It will allow the module and its functions and classes to be imported into other scripts without running the main function, and will also allow the module (and its functions and classes) to be called when running from a different '__main__' module, i.e.

import important

This idiom can also be found in the Python documentation in an explanation of the __main__ module. That text states:

This module represents the (otherwise anonymous) scope in which the interpreter’s main program executes — commands read either from standard input, from a script file, or from an interactive prompt. It is this environment in which the idiomatic “conditional script” stanza causes a script to run:

if __name__ == '__main__':

Answer #5:

There are lots of different takes here on the mechanics of the code in question, the “How”, but for me none of it made sense until I understood the “Why”. This should be especially helpful for new programmers.

Take file “ab.py”:

def a():
    print('A function in ab file');

And a second file “xy.py”:

import ab
def main():
    print('main function: this is where the action is')
def x():
    print ('peripheral task: might be useful in other projects')
if __name__ == "__main__":

What is this code actually doing?

When you execute xy.py, you import ab. The import statement runs the module immediately on import, so ab‘s operations get executed before the remainder of xy‘s. Once finished with ab, it continues with xy.

The interpreter keeps track of which scripts are running with __name__. When you run a script – no matter what you’ve named it – the interpreter calls it "__main__", making it the master or ‘home’ script that gets returned to after running an external script.

Any other script that’s called from this "__main__" script is assigned its filename as its __name__ (e.g., __name__ == "ab.py"). Hence, the line if __name__ == "__main__": is the interpreter’s test to determine if it’s interpreting/parsing the ‘home’ script that was initially executed, or if it’s temporarily peeking into another (external) script. This gives the programmer flexibility to have the script behave differently if it’s executed directly vs. called externally.

Let’s step through the above code to understand what’s happening, focusing first on the unindented lines and the order they appear in the scripts. Remember that function – or def – blocks don’t do anything by themselves until they’re called. What the interpreter might say if mumbled to itself:

  • Open xy.py as the ‘home’ file; call it "__main__" in the __name__ variable.
  • Import and open file with the __name__ == "ab.py".
  • Oh, a function. I’ll remember that.
  • Ok, function a(); I just learned that. Printing ‘A function in ab file‘.
  • End of file; back to "__main__"!
  • Oh, a function. I’ll remember that.
  • Another one.
  • Function x(); ok, printing ‘peripheral task: might be useful in other projects‘.
  • What’s this? An if statement. Well, the condition has been met (the variable __name__ has been set to "__main__"), so I’ll enter the main() function and print ‘main function: this is where the action is‘.

The bottom two lines mean: “If this is the "__main__" or ‘home’ script, execute the function called main()“. That’s why you’ll see a def main(): block up top, which contains the main flow of the script’s functionality.

Why implement this?

Remember what I said earlier about import statements? When you import a module it doesn’t just ‘recognize’ it and wait for further instructions – it actually runs all the executable operations contained within the script. So, putting the meat of your script into the main() function effectively quarantines it, putting it in isolation so that it won’t immediately run when imported by another script.

Again, there will be exceptions, but common practice is that main() doesn’t usually get called externally. So you may be wondering one more thing: if we’re not calling main(), why are we calling the script at all? It’s because many people structure their scripts with standalone functions that are built to be run independent of the rest of the code in the file. They’re then later called somewhere else in the body of the script. Which brings me to this:

But the code works without it

Yes, that’s right. These separate functions can be called from an in-line script that’s not contained inside a main() function. If you’re accustomed (as I am, in my early learning stages of programming) to building in-line scripts that do exactly what you need, and you’ll try to figure it out again if you ever need that operation again … well, you’re not used to this kind of internal structure to your code, because it’s more complicated to build and it’s not as intuitive to read.

But that’s a script that probably can’t have its functions called externally because if it did it would immediately start calculating and assigning variables. And chances are if you’re trying to re-use a function, your new script is related closely enough to the old one that there will be conflicting variables.

In splitting out independent functions, you gain the ability to re-use your previous work by calling them into another script. For example, “example.py” might import “xy.py” and call x(), making use of the ‘x’ function from “xy.py”. (Maybe it’s capitalizing the third word of a given text string; creating a NumPy array from a list of numbers and squaring them, or detrending a 3D surface. The possibilities are limitless.)

Hope you learned something from this post.

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Linux and Python enthusiast, in love with open source since 2014, Writer at programming-articles.com, India.

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