nbcommands: Unix Commands for Jupyter Notebooks
nbcommands bring the goodness of Unix commands to Jupyter notebooks. This lets you interact with your Jupyter notebooks without spinning up a notebook server.
Jupyter Notebook
Mercury: Build Web Apps in Jupyter Notebook
If you want to build a web app seamlessly within your Jupyter Notebook, use Mercury.
nbQA: Run Code Formatter and Code Checker on Jupyter Notebooks
If you want to run code checker and formatted such as ruff, isort, pyupgrade, mypy, pylint, flake8, black, and more on Jupyter Notebooks, use nbQA.
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Effortless DataFrame Analysis in Jupyter Notebook with dtale
To quickly analyze your pandas DataFrame in a few simple clicks directly in your Jupyter Notebook, try dtale.
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Pigeon: Quickly Annotate Your Data on Jupyter Notebook
Sometimes, your training data is unlabeled. If you want to quickly annotate your data within your Jupyter Notebook, use Pigeon. With, Pigeon, you can label data by simply clicking the label.Link to Pigeon.Favorite
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ipyvizzu-story: Create an Interactive Presentation in Your Jupyter Notebook
If you want to create an interactive presentation using Python in your Jupyter Notebook, try ipyvizzu-story.Link to ipyvizzu-store.Favorite
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Bloxs: Create an Attractive Display in Your Jupyter Notebook
If you want to create an attractive display for specific information in your notebook, try bloxs.bloxs is a Python library that is ideal for building dashboards, reports, and apps in the notebook.Link to bloxs.Favorite
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notedown: Create IPython Notebooks from Markdown and Vice Versa
Sometimes you might want to convert your markdown file to a Jupyter Notebook for execution. If so, try notedown.notedown allows you to convert your markdown file to a Jupyter Notebook and vice versa.Link to notedown.Favorite
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Debug Your Jupyter Notebook’s Code with snoop
Have you ever tried to print multiple attributes of a Python object in your Jupyter Notebook to debug it? snoop allows you to automatically print all of those attributes using one magic command.To use snoop, add %%snoop at the beginning of the cell you want to debug.You can also use snoop as a decorator of your Python function.Link to snoop.Favorite
ipytest: Unit Tests in IPython Notebooks
It is important to create unit tests for your functions to make sure they work as you expected, even the experimental code in your Jupyter Notebook. However, it can be difficult to create unit tests in a notebook.Luckily, ipytest allows you to run pytest inside the notebook environment. To use ipytest, simply add %%ipytest -qq inside the cell you want to run pytest.Link to ipytest.My previous tips on Jupyter Notebook.Favorite