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Run any Python code quality tool on a Jupyter Notebook!

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nbQA

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demo

Adapter to run any standard code-quality tool on a Jupyter notebook. Documentation is hosted here.

🎉 Installation

Install nbqa with pip:

pip install -U nbqa

🚀 Examples

Reformat your notebook with black:

$ nbqa black my_notebook.ipynb --nbqa-mutate
reformatted my_notebook.ipynb
All done!  🍰 1 files reformatted.

Sort your imports with isort:

$ nbqa isort my_notebook.ipynb --treat-comment-as-code '# %%' --nbqa-mutate
Fixing my_notebook.ipynb

Check your type annotations with mypy:

$ nbqa mypy my_notebook.ipynb --ignore-missing-imports
my_notebook.ipynb:cell_10:5: error: Argument "num1" to "add" has incompatible type "str"; expected "int"

Run your docstring tests with doctest:

$ nbqa doctest my_notebook.ipynb
**********************************************************************
File "my_notebook.ipynb", cell_2:11, in my_notebook.add
Failed example:
    add(2, 2)
Expected:
    4
Got:
    5
**********************************************************************
1 items had failures:
1 of   2 in my_notebook.hello
***Test Failed*** 1 failures.

Check for style guide enforcement with flake8:

$ nbqa flake8 my_notebook.ipynb
my_notebook.ipynb:cell_3:1:1: F401 'import pandas as pd' imported but unused

Upgrade your syntax with pyupgrade:

$ nbqa pyupgrade my_notebook.ipynb --py36-plus --nbqa-mutate
Rewriting my_notebook.ipynb

🔧 Configuration

You can configure nbQA either at the command line, or by using a pyproject.toml file - see configuration for details and examples.

👷 Usage as pre-commit hook

If you want to use nbqa with pre-commit, here's an example of what you could add to your .pre-commit-config.yaml file:

- repo: https://github.com/nbQA-dev/nbQA
  rev: 0.2.1
  hooks:
    - id: nbqa
      args: ["flake8"]
      name: nbqa-flake8
      alias: nbqa-flake8
      additional_dependencies: ["flake8"]
    - id: nbqa
      args: ["isort", "--nbqa-mutate"]
      name: nbqa-isort
      alias: nbqa-isort
      additional_dependencies: ["isort"]

💬 Testimonials

Alex Andorra, Data Scientist, ArviZ & PyMC Dev, Host of 'Learning Bayesian Statistics' Podcast 🎙️:

well done on nbqa @MarcoGorelli ! Will be super useful in CI 😉

Girish Pasupathy, Software engineer and now core-contributor:

thanks a lot for your effort to create such a useful tool

👥 Contributing

I will give write-access to anyone who contributes anything useful (e.g. pull request / bug report) - see the contributing guide for details on how to do so.

Thanks goes to these wonderful people (emoji key):


Marco Gorelli

💻 🚧 👀 ⚠️ 🤔

Sebastian Weigand

🔧 👀 📖 🤔

Girish Pasupathy

💻 🚇 🐛 👀 🤔

fcatus

🚇

HD23me

🐛

mani

🤔

This project follows the all-contributors specification. Contributions of any kind welcome!

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