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Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

Unreleased

Added

  • Documentation site with MkDocs Material + mkdocstrings, deployed to GitHub Pages
  • LLM-friendly docs output: /llms.txt, /llms-full.txt, and per-page .md files via mkdocs-llmstxt
  • "Copy to LLM" buttons on every docs page (copy as Markdown, open in ChatGPT/Claude) via mkdocs-copy-to-llm
  • docs optional dependency group (mkdocs-material, mkdocstrings[python], mkdocs-llmstxt, mkdocs-copy-to-llm)
  • docs and docs-build taskipy tasks
  • GitHub Actions workflow for automatic docs deployment on push to main
  • Expanded README badge reference and usage notes in notes/readme-badges.md
  • Example index in examples/README.md with a Markdown table, per-demo descriptions, and Open in MoLab badges

Fixed

  • Incorrect import in MlflowChart docstring example (mlflow_chart -> mlflow_widgets)
  • README demo list now includes combo_demo.py and links to the example index

Changed

  • README top badge row now uses dynamic CI, Docs, PyPI, Python, and License badges

0.1.0 - 2026-04-01

First public release on PyPI.

Added

  • MlflowChart -- live-updating canvas-based line chart for MLflow metrics
  • Multiple run comparison with color-coded lines
  • X-axis modes: step, wall time, relative time
  • Smoothing: rolling mean, exponential moving average, gaussian
  • Interactive clickable legend with per-series toggle
  • Hover tooltips with exact values
  • Auto-polling with configurable interval
  • MlflowRunTable -- sortable HTML table showing experiment runs
  • Columns: run name, status, start time, duration, params, metrics
  • Nested run tree view (parent/child collapsible groups)
  • Status badges with color coding
  • Auto-polling support
  • MlflowParallelCoordinates -- parallel coordinates chart for hyperparameter comparison
  • Each axis is a parameter or metric; each polyline is a run
  • Color modes: by status, per run, by parameter value, by metric gradient
  • Status filtering checkboxes
  • Parameter/metric key filtering
  • MlflowRunSelector -- pure Python helper returning pandas DataFrames
  • Works with marimo.ui.table for interactive run selection
  • get_run_ids() static method extracts IDs from DataFrame or list
  • Hybrid architecture: Python fetches data (MlflowClient or REST fallback), JS renders
  • Works in Jupyter, Marimo, and any notebook supporting anywidget
  • py.typed marker for type checker support
  • 6 Marimo demo notebooks in examples/
  • CI with GitHub Actions (Python 3.10-3.13 matrix)
  • Automated publishing via Trusted Publishing (OIDC)