nbcommands bring the goodness of Unix commands to Jupyter notebooks. This lets you interact with your Jupyter notebooks without spinning up a notebook server.
nbcommands: Unix Commands for Jupyter Notebooks Read More »
If you want to build a web app seamlessly within your Jupyter Notebook, use Mercury.
Mercury: Build Web Apps in Jupyter Notebook Read More »
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.
nbQA: Run Code Formatter and Code Checker on Jupyter Notebooks Read More »
To quickly analyze your pandas DataFrame in a few simple clicks directly in your Jupyter Notebook, try dtale.
Effortless DataFrame Analysis in Jupyter Notebook with dtale Read More »
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.
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Pigeon: Quickly Annotate Your Data on Jupyter Notebook Read More »
If you want to create an interactive presentation using Python in your Jupyter Notebook, try ipyvizzu-story.
Link to ipyvizzu-store.
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ipyvizzu-story: Create an Interactive Presentation in Your Jupyter Notebook Read More »
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.
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Bloxs: Create an Attractive Display in Your Jupyter Notebook Read More »
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.
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notedown: Create IPython Notebooks from Markdown and Vice Versa Read More »
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.
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Debug Your Jupyter Notebook’s Code with snoop Read More »
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.
ipytest: Unit Tests in IPython Notebooks Read More »
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