Python __all__: A Comprehensive Guide to Module Exports


Python is a powerful and versatile programming language that offers a wide range of features and functionalities.

One essential aspect of Python programming is the ability to import and export modules, allowing developers to organize their code and reuse it across different projects.

Also Read: Python Regular Expression Split: An In-Depth Guide

In this article, we will explore the __all__ attribute in Python, which plays a crucial role in defining the public interface of a module.

We will delve into its usage, best practices, and common questions related to __all__ to help you enhance your understanding of this important concept.

Python __all__ Explained

The __all__ attribute in Python is a list that defines the public interface of a module.

When a module is imported, only the names listed in the __all__ list are accessible from outside the module.

Also Read: Ultimate Guide to Using os.environ in Python

It serves as a form of encapsulation, allowing module developers to control which attributes, functions, and classes are exposed to other parts of the program.

Defining __all__ in a Module

To define the __all__ attribute in a module, you simply assign a list of names to it.

These names represent the public entities that you want to make available when the module is imported.

Also Read: Python isset: Understanding the Key Concepts and Functionality

Let’s take a look at an example:

__all__ = ['function1', 'function2', 'Class1', 'variable1']

In this example, the module’s public interface includes function1, function2, Class1, and variable1.

Any other entities within the module will not be accessible from outside.

Also Read: 19 Pythonic Ways to Replace if-else Statements

Importing with __all__

When you import a module that has defined the __all__ attribute, you can only access the names listed in the __all__ list.

For example:

from mymodule import function1, Class1

In this case, only function1 and Class1 will be imported and available for use. Other entities within the module will not be directly accessible.

Also Read: Boost Python Code Efficiency: Eliminating Loops for Enhanced Performance

Importing Everything with __all__

If you want to import all the names defined in the __all__ list, you can use the asterisk (*) operator.

However, it is generally recommended to avoid using the asterisk import, as it can lead to namespace pollution and make it unclear which entities are being used from the module.

Also Read: Python Program to Delete an Element From a Dictionary

Nevertheless, here’s an example of importing everything using __all__:

from mymodule import *

Keep in mind that if the module does not define the __all__ attribute, importing everything with the asterisk operator will import all names that do not start with an underscore (_).

Also Read: Twin Prime Number Program in Python

This behavior differs from the __all__ attribute, which provides explicit control over the module’s public interface.

Exploring the Benefits of __all__

The __all__ attribute offers several advantages in Python development. Let’s explore some of these benefits:

Controlled Exports

By using the __all__ attribute, module developers can explicitly specify the public interface of their modules.

Also Read: Barplot Python: Visualizing Data with Python’s Matplotlib Library

This allows for better encapsulation and prevents accidental usage of internal entities that are not intended to be accessed from outside the module.

It provides a clear boundary between the module’s internal implementation and the public API.

Enhanced Readability and Maintenance

When using __all__, developers can easily understand which entities are meant to be used from the module without examining the entire codebase.

Also Read: Online Python Playground: Unleash Your Coding Potential

This improves code readability, especially for larger projects with multiple modules.

Additionally, it simplifies maintenance by reducing the risk of unintentional changes to internal entities.

Reduced Namespace Clutter

The __all__ attribute helps reduce namespace clutter by limiting the scope of imported names.

Also Read: Logical Operators Python: A Comprehensive Guide

By explicitly listing the names to be exported, developers can avoid polluting the namespace with unnecessary or conflicting names.

This makes code easier to understand and less prone to naming collisions.

Best Practices for Using __all__

To make the most of the __all__ attribute, it’s important to follow some best practices. Consider the following guidelines:

Be Explicit

Always be explicit when defining the __all__ attribute. Include only the names that you want to expose as part of the module’s public interface.

Also Read: Python Program to Check If Two Strings are Anagram

Avoid using the asterisk (*) operator unless absolutely necessary.

Document Your Module

To provide clear guidance to users of your module, document the public entities that are available for use.

Explain their functionality, parameters, and return values. This documentation can be in the form of comments within the code or a separate documentation file.

Regularly Review and Update __all__

As your module evolves, review and update the __all__ attribute accordingly. Remove any entities that are no longer needed or should not be part of the public interface.

Regularly maintaining __all__ ensures that your module remains clean and easy to use.

Consider Versioning and Deprecation

If your module is distributed as part of a larger project or a library, consider versioning and deprecation strategies for the __all__ attribute.

Also Read: Python Program to Check Armstrong Number

When introducing breaking changes, clearly communicate any modifications to the public interface and provide migration guides to assist users.

Python __all__ FAQs

Q1: What happens if a module does not define all?

If a module does not define the __all__ attribute, importing everything with the asterisk operator (from module import *) will import all names that do not start with an underscore (_). It is generally recommended for modules to explicitly define the __all__ attribute to have better control over the public interface.

Q2: Can I change the all attribute after importing a module?

Yes, you can modify the __all__ attribute of a module after importing it. However, this will not have any effect on the names that have already been imported. Only subsequent imports will reflect the changes made to __all__.

Q3: Can I access non-public entities from a module with all?

The __all__ attribute controls the names that are directly accessible from outside the module. Non-public entities, usually denoted by names starting with an underscore (_), are not included in __all__ and are not intended for direct usage.

Q4: Are there any risks in using the asterisk import with all?

Importing everything with the asterisk operator (from module import *) can lead to namespace pollution and make it unclear which entities are being used from the module. It is generally recommended to import only the specific names needed or use the module’s explicit import statements.

Q5: Does all apply to submodules?

The __all__ attribute is specific to each individual module and does not automatically apply to submodules. Submodules can define their own __all__ attribute to control their public interface separately.

Q6: Can I use all in a package’s file?

Yes, you can use the __all__ attribute in a package’s file to define the names that are exposed when the package is imported. This allows for a more controlled and explicit interface for the package.


In this article, we explored the __all__ attribute in Python and its significance in module exports.

By utilizing __all__, developers can control the public interface of their modules, leading to better encapsulation, code readability, and reduced namespace clutter.

We discussed best practices for using __all__ and addressed common questions related to its usage.

Remember to be explicit, document your modules, and regularly review and update __all__ to maintain clean and well-defined interfaces.

Now that you have a comprehensive understanding of __all__ in Python, you can leverage this powerful feature to enhance your module design and development process.