Skip to main content

Run any standard Python code quality tool on a Jupyter Notebook

Project description

nbQA

Run any standard Python code quality tool on a Jupyter Notebook

tox codecov pre-commit

versions chat docs

demo

Table of contents

๐ŸŽ‰ Installation

In your virtual environment, run one of the following:

  • python -m pip install -U nbqa (minimal installation)
  • python -m pip install -U nbqa[toolchain] (install supported code quality tools as well)
  • conda install -c conda-forge nbqa (if you use conda)

๐Ÿš€ Examples

Pre-commit (recommended)

Here's an example of how to set up some pre-commit hooks: put this in your .pre-commit-config.yaml file (see usage as pre-commit hook)

- repo: https://github.com/nbQA-dev/nbQA
  rev: 0.6.1
  hooks:
    - id: nbqa-black
      additional_dependencies: [black==20.8b1]
      args: [--nbqa-mutate]
    - id: nbqa-pyupgrade
      additional_dependencies: [pyupgrade==2.10.0]
      args: [--nbqa-mutate, --py36-plus]
    - id: nbqa-isort
      additional_dependencies: [isort==5.7.0]
      args: [--nbqa-mutate]

Command-line

Reformat your notebooks with black:

$ nbqa black my_notebook.ipynb --nbqa-mutate
reformatted my_notebook.ipynb
All done! โœจ ๐Ÿฐ โœจ
1 files reformatted.

Sort your imports with isort:

$ nbqa isort my_notebook.ipynb --nbqa-mutate
Fixing my_notebook.ipynb

Upgrade your syntax with pyupgrade:

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

See command-line examples for examples involving autoflake, check-ast, doctest, flake8, mypy, and pylint.

๐Ÿฅณ Used by

Take some inspiration from their config files ๐Ÿ˜‰

๐Ÿ’ฌ Testimonials

Michael Kennedy & Brian Okken, hosts of the Python Bytes podcast:

This is really cool. I think it brings so much of the code formatting and code analysis, clean up to notebooks, which I think had been really lacking

Nikita Sobolev, CTO at wemake.services:

It is amazing!

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

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

Matthew Feickert, Postdoc at University of Illinois working on LHC physics:

nbqa in your pre-commit hooks along with @codewithanthony 's pre-commit CI service is amazing! Everyone using Jupyter notebooks should be doing this.

Girish Pasupathy, Software engineer and now core-contributor:

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

Simon Brugman, Data scientist & pandas-profiling dev:

nbQA helps us to keep notebooks to the same standards as the rest of the code. If you're serious about your code standards, you should keep them consistent across both notebooks and python scripts. Great addition to the ecosystem, thanks!

Bradley Dice, PhD Candidate in Physics & Scientific Computing:

nbqa is a clean, easy to use, and effective tool for notebook code style. Formatting and readability makes a huge difference when rendering notebooks in a project's documentation!

๐Ÿ‘ฅ Contributing

I will give write-access to anyone who makes a useful pull request - see the contributing guide for details on how to do so.

Thanks goes to these wonderful people (emoji key):


Marco Gorelli

๐Ÿ’ป ๐Ÿšง ๐Ÿ‘€ โš ๏ธ ๐Ÿค”

Sebastian Weigand

๐Ÿ”ง ๐Ÿ‘€ ๐Ÿ“– ๐Ÿค”

Girish Pasupathy

๐Ÿ’ป ๐Ÿš‡ ๐Ÿ› ๐Ÿ‘€ ๐Ÿค”

fcatus

๐Ÿš‡

HD23me

๐Ÿ›

mani

๐Ÿค” ๐Ÿš‡

Daniel Mietchen

๐Ÿค”

Michaล‚ Gacka

๐Ÿ›

Happy

๐Ÿ“–

Nat Taylor

๐Ÿค” ๐Ÿ’ป ๐Ÿ”ง ๐Ÿ›

Caio Ariede

๐Ÿ“–

Nikita Sobolev

๐Ÿค” ๐Ÿ› ๐Ÿ“–

Amichay Oren

๐Ÿค”

pylang

๐Ÿค”

Henry Schreiner

๐Ÿ›

Kaiqi Dong

๐Ÿ“–

Simon Brugman

๐Ÿ›

John Sandall

๐Ÿ›

Nathan Cooper

๐Ÿ›

agruenberger

๐Ÿ›

Rafal Wojdyla

๐Ÿ›

Bradley Dice

๐Ÿค” ๐Ÿ’ป

Ivan Cheung

๐Ÿ›

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

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

nbqa-0.6.1.tar.gz (34.8 kB view details)

Uploaded Source

Built Distribution

nbqa-0.6.1-py3-none-any.whl (33.6 kB view details)

Uploaded Python 3

File details

Details for the file nbqa-0.6.1.tar.gz.

File metadata

  • Download URL: nbqa-0.6.1.tar.gz
  • Upload date:
  • Size: 34.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.25.1 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.55.0 CPython/3.8.5

File hashes

Hashes for nbqa-0.6.1.tar.gz
Algorithm Hash digest
SHA256 2c63d9d1d56e53537efb42f019dac0c04938e9f940409920eb11780c458c9275
MD5 d5432055e5ac977106e94e1020731bda
BLAKE2b-256 1bb5c4b12ce945d7e5d3b8a85e5abe59aa179d1b521c1b05b9861bf83d36b156

See more details on using hashes here.

Provenance

File details

Details for the file nbqa-0.6.1-py3-none-any.whl.

File metadata

  • Download URL: nbqa-0.6.1-py3-none-any.whl
  • Upload date:
  • Size: 33.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.25.1 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.55.0 CPython/3.8.5

File hashes

Hashes for nbqa-0.6.1-py3-none-any.whl
Algorithm Hash digest
SHA256 1b74cf247ec6c892b3f8b9edab00e99c54705d11b5a3a43c5384f2fe04b57cb0
MD5 b41b6d6d13722eb6b83b1c51b112b005
BLAKE2b-256 70a500b99e622f10ba7de547ba68a3c0c08634972079d171baf75c0920b91299

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page