lizyml-widget 0.6.0

Jupyter Notebook / Google Colab / VS Code Notebooks widget for LizyML

LizyML Widget

Interactive Jupyter widget for LizyML — fit, tune, and run inference on machine learning models without writing code.

Features

• Data Tab — Load a DataFrame, select target, configure columns and cross-validation
• Config Tab — Edit LightGBM hyperparameters, configure tuning search space
• Results Tab — View scores, Plotly plots, feature importance, and inference results
• Config Import/Export — Save and load configurations as YAML
• Python API — Programmatic access to all widget functionality

Requirements

• Python >= 3.10
• Jupyter Notebook, JupyterLab, Google Colab, or VS Code Notebooks

Installation

pip install lizyml-widget

With the LizyML backend (required for Fit/Tune):

pip install lizyml-widget[lizyml]

Quick Start

import pandas as pd
from lizyml_widget import LizyWidget

df = pd.read_csv("train.csv")
w = LizyWidget()
w.load(df, target="price")
w  # display widget in notebook cell

Programmatic Usage

w = LizyWidget()
w.load(df, target="y").fit()

summary = w.get_fit_summary()
print(summary.metrics)

w.save_model("./model")
w.save_config("config.yaml")

Version

import lizyml_widget
print(lizyml_widget.__version__)

Tutorials

Notebook	Task	Dataset
Regression	Regression	California Housing (sklearn)
Binary Classification	Binary	Breast Cancer Wisconsin (sklearn)
Multiclass Classification	Multiclass	Wine (sklearn)

Supported Environments

• Jupyter Notebook
• JupyterLab
• Google Colab
• VS Code Notebooks

Powered by anywidget for cross-environment compatibility.

Development

# Python
uv sync --all-extras    # installs dev + lizyml dependencies
uv run pytest
uv run ruff check .
uv run mypy src/lizyml_widget/

# TypeScript
cd js
pnpm install
pnpm dev    # watch build
pnpm build  # production build
pnpm lint

Stable Notebook Launch

If VS Code gets stuck reconnecting to an old kernel, prefer launching Jupyter with workspace-local runtime files instead of the default global runtime directory:

./scripts/jupyter-reset.sh
./scripts/jupyter-lab.sh

This keeps runtime/config state under the repository and makes stale kernel/server state easier to clear than relying on Reload Window alone.

License

MIT