autoflake VS pytest

Ruff is not only much faster, but it is also very convenient to have an all-in-one solution that replaces multiple other widely used tools: Flake8 (linter), isort (imports sorting), Black (code formatter), autoflake, many Flake8 plugins and more. And it has drop-in parity with these tools, so it is really straightforward to migrate from them to Ruff.

Ruff can be used to replace Flake8 (plus dozens of plugins), isort, pydocstyle, yesqa, eradicate, pyupgrade, and autoflake, all while executing tens or hundreds of times faster than any individual tool.

Having unused imports in a Python file is a prevalent issue, with a very easy solution: autoflake. Running it over your files will remove any unused imports in place.

cleanimports: runs isort and removes unused imports with Autoflake. Be sure to set up profile=black in isort settings to avoid conflicts with Black.

We use isort[0] for this. It even has a "black" compatible profile that line spits along black's defaults. Additionally we use autoflake[1] to remove unused import statements in place.

[0](https://github.com/PyCQA/isort)

[1](https://github.com/PyCQA/autoflake)

yaml repos: - repo: https://github.com/myint/autoflake rev: v1.4 hooks: - id: autoflake args: - --in-place - --remove-all-unused-imports - --expand-star-imports - --remove-duplicate-keys - --remove-unused-variables - repo: https://github.com/asottile/pyupgrade rev: v2.29.0 hooks: - id: pyupgrade args: [--py36-plus] - repo: https://github.com/PyCQA/isort rev: 5.9.3 hooks: - id: isort - repo: https://github.com/psf/black rev: 21.10b0 hooks: - id: black args: [--safe, --quiet] - repo: https://github.com/PyCQA/flake8 rev: 4.0.1 hooks: - id: flake8 - repo: local hooks: - id: pylint name: pylint entry: pylint language: system types: [python] args: [ "-rn", "-sn", ] - repo: https://github.com/pre-commit/mirrors-mypy rev: v0.910-1 hooks: - id: mypy name: mypy entry: mypy language: python types: [python] args: [] require_serial: true - repo: https://github.com/pre-commit/mirrors-prettier rev: v2.4.1 hooks: - id: prettier args: [--prose-wrap=always, --print-width=88]

autoflake 400+⭐️

In this blog post I want to demonstrate how my lab equipment such as a lab power supply or a digital multimeter (DMM) have been integrated into some pytest-based tests. Would love to get your feedback and thoughts! 🚀

Pytest: is a third-party testing framework that supports fixtures, parameterized testing, and easy test discovery while having room to add plugins to extend its functionality.

Next, you need to install a testing framework that will be used for performing unit testing in your project. Several testing frameworks are available depending on the programming language used to create an application. For example, JUnit is commonly used for Java apps, pytest for Python apps, NUnit for .NET apps, Jest for JavaScript apps, and so on. We’ll use the Jest framework for this tutorial since we are using JavaScript.

Yea, read through the pytest docs.

I absolutely agree about fixtures-as-arguments thing. Ward does this a lot better, using default values for the fixture factory. There's a long issue on ideas to implement something like that as a pytest plugin (https://github.com/pytest-dev/pytest/issues/3834), but it seems the resulting plugin relies on something of a hack.

I recommend writing a few tests. py.test makes that quite simple:

Since ITK's inception in 1999, there has been a focus on engineering practices that result in high-quality software. High-quality scientific software is driven by regression testing. The ITK project supported the development of CTest and CDash unit testing and software quality dashboard tools for use with the CMake build system. In the Python programming language, the pytest test driver helps developers write small, readable scripts that ensure their software will continue to work as expected. However, pytest can only test Python scripts by default, and errors in untested computational notebooks are more common than well-tested Python code.