Run any Python code quality tool on a Jupyter Notebook!
Project description
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!
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