Python: Functions Starting with Underscore are Not Imported by Default

Core Concepts

Functions starting with an underscore in Python are not imported by default when using the wildcard import (from module import *) syntax.

Abstract

The author shares a lesson they learned about Python module imports. Typically, when using the wildcard import syntax (from module import *), all functions and variables defined in the module are imported into the current namespace. However, the author discovered that functions starting with an underscore (_) are not imported by default. This behavior is by design in Python. Functions and variables starting with a single leading underscore (_) are considered "internal" or "private" and are not meant to be accessed directly from outside the module. The double leading underscore (__) is used for "name mangling" to avoid naming conflicts with subclasses. The author provides a simple example to demonstrate this concept. They have two Python scripts, a.py and b.py, where a.py defines a regular function public_func() and a "private" function _private_func(). When importing all functions from a.py using from a import *, only public_func() is available, while _private_func() is not imported. This knowledge can be useful when working with third-party libraries or when designing your own modules, to ensure that only the intended public API is exposed to the users of your code.

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Today I Learnt — Functions starting with _ are not imported

by Liu Zuo Lin at zlliu.medium.com 04-27-2024

https://zlliu.medium.com/today-i-learnt-functions-starting-with-are-not-imported-3338ac6dd25d

Deeper Inquiries

What are the advantages and disadvantages of using the wildcard import (from module import *) syntax in Python?

When using the wildcard import syntax in Python (from module import *), the main advantage is that it allows you to access all functions and variables from the module without having to prefix them with the module name. This can save time and make the code more concise, especially in situations where you need to use multiple functions or variables from the module. However, there are several disadvantages to using wildcard imports. One major drawback is that it can lead to namespace pollution, where the imported names may clash with existing names in the current module, causing confusion and potential conflicts. This can make the code harder to read and maintain, as it becomes unclear where certain functions or variables are coming from. Additionally, wildcard imports make it difficult to track the origin of functions and variables, which can hinder debugging and troubleshooting efforts. It also makes the code less explicit, as it's not immediately clear which functions and variables are being used from the imported module. In general, it is considered a best practice to avoid using wildcard imports in Python and instead import specific functions or variables that are needed from the module to maintain a clean and organized codebase.

How can you access the "private" functions and variables starting with an underscore in Python, if needed?

In Python, functions and variables that start with an underscore (_) are considered "private" and are not intended to be accessed from outside the module or class where they are defined. However, there may be situations where you need to access these private elements for specific reasons. To access private functions and variables starting with an underscore in Python, you can still do so by directly referencing them from within the module or class where they are defined. Since Python does not enforce strict privacy like some other languages, you can technically access these private elements from outside the module or class, although it is generally discouraged as it goes against the principle of encapsulation. If you absolutely need to access private functions or variables from outside the module or class, you can do so by importing the module or class and directly referencing the private elements using their full names, including the leading underscore. However, it is important to note that this is not recommended practice and should be done with caution, as it can lead to unexpected behavior and make the code harder to maintain.

What are some best practices for organizing and naming functions and variables in Python to maintain a clear and maintainable codebase?

To maintain a clear and maintainable codebase in Python, it is important to follow some best practices when organizing and naming functions and variables. Here are some guidelines to consider: Use descriptive and meaningful names for functions and variables: Choose names that accurately describe the purpose and functionality of the function or variable. This makes the code more readable and understandable for other developers. Follow the naming conventions: In Python, it is common to use snake_case for naming functions and variables, where words are separated by underscores. This convention helps maintain consistency across the codebase and makes it easier to read and understand. Organize functions logically: Group related functions together within modules or classes to improve code organization and maintainability. This helps developers quickly locate and understand the functionality of different parts of the code. Avoid global variables: Minimize the use of global variables as they can lead to unexpected side effects and make the code harder to debug. Instead, use local variables within functions or pass variables as parameters when needed. Use docstrings for documentation: Include docstrings for functions and classes to provide clear documentation on their purpose, parameters, and return values. This helps other developers understand how to use the code and encourages good coding practices. By following these best practices for organizing and naming functions and variables in Python, you can create a clear and maintainable codebase that is easier to read, understand, and maintain.