Python is a dynamically-typed language, so variables can change type over their lifetime, and the Python interpreter only does type checking as the code runs. This kind of structure can lead to confusion as well as runtime errors if you’re not careful. So what’s a good Python coding practice to better handle typing?
The package typing allows assigning types to variables. This allows for better code completion in your IDE. This package is great at assisting static type checkers and linters catch potential errors and lead to better code completion.
Unittest is a standard Python package that serves as a testing framework. It was inspired by the ubiquitous JUnit. Unittest “supports test automation, sharing of setup and shutdown code for tests, aggregation of tests into collections, and independence of the tests from the reporting framework”
Although unittest is a handy framework, there is still room for improvement. Pytest is a great package for elevated testing. For example, using pytest, you can easily parametrize fixtures and functions using the parametrize decorator, where you can pass in arguments for tests along with the corresponding expected output.
Structuring your Python project is key to its success. It’s very important that you set up your repository with a meaningful and simple folder structure. You should be able to quickly find what you’re looking for, and files should be strictly organized. Tests should be kept separate from production code.
Watch your dependencies. You should not have any circular dependencies, where two classes rely on each other. This will lead to confusing import statements as well as purposes. Every file should only contain one class, and each class should have one purpose.
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Blog Source: Boot.dev
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