nbqa 0.3.1

Run any Python code quality tool on a Jupyter Notebook!

nbQA

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

🎉 Installation

Install nbqa with pip:

python -m 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 --extend-ignore=E203,E302,E305,E703
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

Perform static code analysis with pylint:

$ nbqa pylint my_notebook.ipynb --disable=C0114
my_notebook.ipynb:cell_1:5:0: W0611: Unused import datetime (unused-import)

🔧 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

You can easily use nbqa as a pre-commit hook by passing your desired code quality tool in the args and additional_dependencies sections - see usage as pre-commit hook for examples.

💬 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 🤔

Daniel Mietchen 🤔

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