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Notebooks are useful for interactive analytics and seeing results, but most "workhorse" code can be extracted into a reusable module.
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Use a **code formatter**. Common Python formatters are [black](https://pypi.org/project/black/) and [isort](https://pycqa.github.io/isort/). A typical approach is to use these tools as git [commit hooks](https://githooks.com/).
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Use a **code formatter**. Common Python formatters are [black](https://pypi.org/project/black/), [isort](https://pycqa.github.io/isort/), and [ruff](https://docs.astral.sh/ruff/). A typical approach is to use these tools as git [commit hooks](https://githooks.com/) with [pre-commit](https://pre-commit.com/).
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**Lint** your code. Common Python linters include [flake8](https://flake8.pycqa.org/) for code quality and [pydocstyle](https://www.pydocstyle.org/) for docstrings (see below).
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**Lint** your code. Common Python linters include [flake8](https://flake8.pycqa.org/) for code quality and [pydocstyle](https://www.pydocstyle.org/) for docstrings (see below). Nowadays, [ruff](https://docs.astral.sh/ruff/) is increasingly common.
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**Unit tests** are automated tests of individual pieces of your code. They test your individual functionality for bugs as you change bits of the codebase around them. Consider pairing your unit tests with a test coverage tool like [codecov](https://codecov.io).
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