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Best practices in Python programming

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Python is a versatile programming languages and one of the most popular ones. It can be used for a variety of applications, including web development, data science, artificial intelligence, and more. A lot of people write Python programs, but not a lot of people know how to write quality codes by following best practices. To write clean, efficient, and maintainable Python code, it is important to follow best practices that help to improve code quality and reduce the likelihood of bugs or errors.

Below are some of the practices that will make your Python code of good quality:

Follow the PEP 8 style

One of the most important best practices in Python programming is following the PEP 8 style guide, which outlines coding conventions that help to improve the readability and consistency of code. This includes using clear and descriptive variable names, adhering to a consistent indentation style, and writing code that is easy to read and understand. Consistent use of PEP 8 conventions across all projects can also make code more accessible to other developers who may be working on the same project.

Use virtual environment

Another important best practice is the use of virtual environments to manage dependencies. Virtual environments are isolated spaces where you can install and manage the dependencies of your project without interfering with other projects or the system-wide Python installation. This helps to avoid version conflicts and makes it easier to manage dependencies, especially when working on multiple projects or collaborating with other developers.

Don’t Repeat Yourself (DRY) principle

The “Don’t Repeat Yourself” (DRY) principle is another key best practice in Python programming, as well as several other programming languages, including JavaScript. DRY refers to the avoidance of code duplication by creating reusable functions or classes that can be called in different parts of the program. This not only reduces the amount of code that needs to be written, but also makes the code easier to read and maintain.

Write small, focused functions

It is also important to write small, focused functions that do one thing and do it well. This makes the code easier to read, test, and maintain, as well as improving its overall performance. Similarly, using built-in functions and data structures wherever possible can help to make the code more concise and efficient.

Python provides excellent error handling mechanisms, and it is important to use these to write robust code that is less likely to crash or produce unexpected results. Using try/except blocks to handle errors and exceptions in code can help to make it more error-tolerant and resilient.

Write automated tests

Writing automated tests is another important best practice in Python programming. Automated tests can help to catch regressions early, ensure that code works as expected, and improve the overall quality of the code. There are a number of testing frameworks available for Python, including unittest and pytest.

Write clear documentation

Writing clear and concise documentation for code is an important best practice. This includes comments and docstrings that explain what the code does and how it works. Good documentation can help other developers understand the code more easily, and also make it easier to maintain and update the code in the future.

Read also: 5 reasons why you should learn computer programming

There are many best practices that can help to improve the quality and maintainability of Python code, and by following these best practices, developers can write more efficient, maintainable, and robust Python code that is easier to read, understand, and maintain.

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When I'm not reading about tech, I'm writing about it, or thinking about the next weird food combinations to try. I do all these with my headphones plugged in, and a sticky note on my computer with the words: "The galaxy needs saving, Star Lord."
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