# pyecharts

🎨 Python Echarts Plotting Library

Repository: https://github.com/pyecharts/pyecharts
Canonical: https://ross.abutalabs.com/products/pyecharts
Homepage: https://pyecharts.org
Language: Python
License: MIT
License Family: permissive
Topics: echarts, python
Last push: 2026-08-04T05:03:08+00:00

## Health v2 (maintenance only)
Score: 79/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 96, release rhythm 45, longevity 100
- inputs: {"age_days": 3359, "days_push": 29, "days_rel": 204, "gap_med": 123, "n_releases_24m": 4}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 15777, forks 2844 (observed 2026-08-28T04:11:14.100272+00:00)

## What it is
pyecharts is a Python plotting library that provides a Pythonic API for generating Apache ECharts visualizations. It supports 30+ chart types, notebook environments like Jupyter and JupyterLab, and integration with web frameworks such as Flask and Django.

## Use cases
- create interactive charts in python
- plot data with echarts from python
- visualize data in jupyter notebook
- embed charts in flask or django apps
- make geographic maps and visualizations
- generate html chart pages for reports

## When to choose
- you want ECharts-quality interactive charts from Python
- you work in Jupyter/JupyterLab or marimo notebooks
- you need to embed charts into Python web frameworks
- you need rich chart types including maps

## When to avoid
- you need static publication-quality plots for print (use matplotlib)
- you want a pure-JavaScript ECharts integration without Python
- you rely on the legacy 0.5.x API, which is unmaintained

## Facets
- artifact type: library
- maturity: stable
- function: data-visualization, charts
- domain: data-visualization, web-development, data-science
- platform: python, cross-platform
- tags: echarts, plotting, notebook-support, jupyter, charts

## Member repositories
- pyecharts/pyecharts (main) score 79
- pyecharts/pyecharts-gallery (examples) score 62

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:14.100272+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:05:32.456699+00:00, confidence not recorded.
  - readme: https://github.com/pyecharts/pyecharts (fetched 2026-08-28T04:11:14.100272+00:00, sha e90815309e2a)
  - registry_pypi: https://pypi.org/pypi/pyecharts/json (fetched 2026-08-29T08:03:22.176049+00:00, sha 7a2490803266)
- Data as of 2026-08-30T08:39:29.467469+00:00.