skore 0.1.1

Tooling and assistance for data scientists to "Own Your Data Science"

👋 Welcome to skore

skore allows data scientists to create tracking and visualization from their Python code:

1. Users can store objects of different types: python lists and dictionaries, numpy arrays, scikit-learn fitted models, matplotlib, altair, and plotly figures, etc. Storing some values over time allows one to perform tracking and also to visualize them:
2. They can visualize these stored objects on a dashboard. The dashboard is user-friendly: objects can easily be organized.
3. This dashboard can be exported into a HTML file.

These are only the first features of skore's roadmap. skore is a work in progress and, on the long run, it aims to be an all-inclusive library for data scientists. Stay tuned!

⚙️ Installation

You can install skore by using pip:

pip install -U skore

🚀 Quick start

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In your shell, run the following to create a project file project.skore (the default) in your current working directory:

python -m skore create 'project.skore'

Run the following in your Python code (in the same working directory) to load the project, store some objects, delete them, etc:

from skore import load

# load the project
project = load("project.skore")

# save an item you need to track in your project
project.put("my int", 3)

# get an item's value
project.get("my int")

# by default, strings are assumed to be Markdown:
project.put("my string", "Hello world!")

# `put` overwrites previous data
project.put("my string", "Hello again!")

# list all the keys in a project
print(project.list_item_keys())

# delete an item
project.delete_item("my int")

Then, in the directory containing your project, run the following command in your shell to start the UI locally:

python -m skore launch project.skore

This will automatically open a browser at the UI's location. In the Elements tab on the left, you can visualize the stored items. Create a new View, then you can then add items into this view.

💡 Note that after launching the dashboard, you can keep modifying current items or store new ones, and the dashboard will automatically be refreshed.

👨‍🏫 For a complete introductory example, see our basic usage notebook. It shows you how to store all types of items: python lists and dictionaries, numpy arrays, scikit-learn fitted models, matplotlib, altair, and plotly figures, etc. The resulting skore report has been exported to this HTML file.

🔨 Contributing

Thank you for your interest! See CONTRIBUTING.md.

💬 Where to ask questions

Type	Platforms
🐛 Bug reports	GitHub Issue Tracker
✨ Feature requests and ideas	GitHub Issue Tracker & Discord
💬 Usage questions, discussions, contributions, etc	Discord

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