The 6 best habits of Python developers
The purpose of this article is to detail six great development practices for using the Python coding language. By taking into account these six steps, development teams will be able to use Python optimally, and to its full potential.
When a developer consistently uses good development practices in a language, the code has a much greater likelihood of being of good quality.
So what are some of the good Python programming habits that developers should embrace to ensure they are using the language most effectively?
Habit # 1: Use the Right Project Management Tools and Virtual Environments
The first step is to select project management tools that are best suited to the specific development project. With inappropriate tools, building the software cannot be done in the best possible conditions, and the final result will probably not be of the best quality.
The second step is to choose and use a virtual environment, which brings a lot of advantages. For example:
- Tool for automated installation: Poetry
- Virtual environment: venv
- Code management tool: Git
Even in the case of small projects, the use of a virtual environment and a versioning tool is highly recommended.
Habit # 2: Make Efficient Use of the Standard Python Library
If you’re a new Python developer, you’ve probably already asked yourself the following question: “How can I find out if a function integrated in the standard Python library can meet my development needs?”
One tip is to bookmark the contents of the library with the presentation pages for each function. By doing this, you can easily browse back through them whenever you’re faced with a common development use case to solve.
What we mean here is that the more you explore and utilize the tools that Python offers, the more your knowledge and speed of finding common programming solutions will be effective.
Routine tasks are found in the standard Python library.
Habit # 3: Take advantage of use cases in projects that are similar to yours
You may find yourself in the situation where there is not one but several modules that could solve your use case. How can you know which one to choose? The best approach is to use the number of stars or GitHub forks to identify the project that could contain your use case, or has a high adoption. Indeed, it is highly likely that other developers before you have already had to face your use case, which can potentially save you a lot of time and headaches.
You can perform a search using the PyPI web front-end, and the results will offer you turnkey solutions. If modules that answer your problem already exist, you can use them directly and save considerable time.
In addition, with Python, you benefit from the performance of the C language, which brings with it accelerated development and program execution speeds.
Habit # 4: Avoid using OOP (Object Oriented Programming) as much as possible
Your Python code does not necessarily need to be all object-oriented. Consider if your work really needs a POO approach. If it’s not necessary, you’ll find that 20 lines of “get-it-done-and-get-on-with-it” code can do the trick. In addition, you can save a lot of time if you don’t have to go through OOP.
Be flexible in your evaluation and perception of your needs, and try not to rush into choosing an alternative that may not be suited to your project.
Habit # 5: Avoid using the latest version of Python and Python 2
Python 2 is actually no longer supported by the official Python development team. So it’s best to migrate your project to version 3 of Python.
The latest version of Python is currently version 3.8.3. This does not mean that you are obliged to use it for your software. Instead, rely on using the previous version, which will give you fewer surprises.
Always remember that your goal is to be able to exploit the maximum number of modules in your code and to be sure that they are compatible with third-party modules.
Habit # 6: Test Your Code Systematically
As Python is a high-level language, you should always incorporate test suites into your code roadmap. The implementation of tests that are written in parallel with the code you produce is essential, and this is even more true for software with a high level of complexity.
Writing the tests at the same time as your functions may seem tedious at first, but by doing so you will remove obstacles that might prevent you from realizing a high quality application. Do not skip the tests.
At Bocasay, our teams develop projects in Python using continuous integration throughout the development process. Do you have some Python development needs? Entrust us with the creation of your future software or application.
