Python’s Default Mask for Compiling Modules

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You might be wondering what that even means, but trust me, it’s a game-changer.

So let’s say you have this code:

# This is a simple function that prints "Hello, world!" when called
def my_function():
    print("Hello, world!") # This line prints the string "Hello, world!" to the console

# This line calls the function, causing it to execute and print "Hello, world!"
my_function()

Now, if you want to use that function in another Python file (let’s call it `other_file.py`), all you need to do is copy and paste the code into your new file or import it using:

# Importing the function "my_function" from the module "my_module"
from my_module import my_function

# Now, the function "my_function" can be used in the current python file or in another python file by importing it.

# Example of using the function "my_function" in the current python file:
my_function()

# Example of using the function "my_function" in another python file:
# Importing the function "my_function" from the module "my_module"
from my_module import my_function

# Calling the function "my_function"
my_function()

# The function "my_function" can also be used with an alias by using the "as" keyword:
# Importing the function "my_function" from the module "my_module" with an alias "mf"
from my_module import my_function as mf

# Calling the function "my_function" using the alias "mf"
mf()

But what if you don’t want to expose that function to other parts of your project? What if you only want to use it in a specific module, but not anywhere else?

Well, Python has got you covered with its default mask for compiling modules. Here’s how it works: by default, any functions or variables defined within a `.py` file are private and cannot be accessed from outside that file unless they are explicitly exported using the `__all__` list at the bottom of your module.

So let’s say you have this code in `my_module.py`:

# This is a python script that defines a function and a variable within a module.

# The function is called "my_function" and it prints "Hello, world!" when called.
def my_function():
    print("Hello, world!")

# This variable is private by default and cannot be accessed from outside the module.
# To make it accessible, it needs to be explicitly exported using the "__all__" list at the bottom of the module.
some_variable = "I am a secret!"

# To export the variable, it needs to be added to the "__all__" list.
__all__ = ["my_function", "some_variable"]

If you want to expose only the function and not the variable, simply add this line at the bottom of your module:

# This script is used to expose only the function "my_function" and not the variable in a module.

# The "__all__" variable is used to specify which objects should be imported when using the "from module import *" syntax.
# In this case, we only want to import the "my_function" function.

# The following line creates a list containing the string "my_function".
__all__ = ["my_function"]

Now, if you import `my_module`, you can use the function but not access the variable.

If you want to expose both the function and the variable, simply add them to the list:

# Importing the module
import my_module

# Defining the list of elements to be exposed
__all__ = ["my_function", "some_variable"]

# Defining the function to be exposed
def my_function():
    """
    This function is used to perform a specific task.
    """
    # Code for the function goes here
    pass

# Defining the variable to be exposed
some_variable = "This is a variable"

# Now, if you import `my_module`, you can use the function and access the variable.
# This is because both the function and variable have been added to the list of elements to be exposed.
# This allows for easier access to commonly used elements within the module.

You now have complete control over what is exposed from your module.

It might seem like a small feature, but trust me, it can save you hours of headaches and prevent all sorts of errors in your code. And the best part? It’s completely free!

So go ahead, embrace this hidden gem of Python, and let us know how it has changed your life for the better. Until next time, happy coding and stay tech-savvy, my friends!

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