Merge pull request #14647 from apache/release-dev

release: 5.1.0
tree: 876c6fda39a11c2ccb2cbeb7ec27f4bb1548219f
  1. .github/
  2. .vscode/
  3. asset/
  4. benchmark/
  5. build/
  6. dist/
  7. extension-src/
  8. i18n/
  9. licenses/
  10. src/
  11. test/
  12. theme/
  13. .asf.yaml
  14. .editorconfig
  15. .eslintignore
  16. .eslintrc-common.yaml
  17. .gitattributes
  18. .gitignore
  19. .headerignore
  20. .huskyrc
  21. .jshintrc-dist
  22. .lgtm.yml
  23. .npmignore
  24. CONTRIBUTING.md
  25. index.d.ts
  26. KEYS
  27. LICENSE
  28. NOTICE
  29. package-lock.json
  30. package.json
  31. README.md
  32. tsconfig.json
README.md

Apache ECharts

Apache ECharts is a free, powerful charting and visualization library offering an easy way of adding intuitive, interactive, and highly customizable charts to your commercial products. It is written in pure JavaScript and based on zrender, which is a whole new lightweight canvas library.

中文官网 | ENGLISH HOMEPAGE

Build Status Last npm release

Get Apache ECharts

You may choose one of the following methods:

Docs

Get Help

Build

Build echarts source code:

Execute the instructions in the root directory of the echarts: (Node.js is required)

# Install the dependencies from NPM:
npm install

# Rebuild source code immediately in watch mode when changing the source code.
npm run dev

# Check correctness of TypeScript code.
npm run checktype

# If intending to build and get all types of the "production" files:
npm run release

Then the “production” files are generated in the dist directory.

More custom build approaches can be checked in this tutorial: Create Custom Build of ECharts please.

Contribution

If you wish to debug locally or make pull requests, please refer to contributing document.

Resources

Awesome ECharts

https://github.com/ecomfe/awesome-echarts

Extensions

License

ECharts is available under the Apache License V2.

Code of Conduct

Please refer to Apache Code of Conduct.

Paper

Deqing Li, Honghui Mei, Yi Shen, Shuang Su, Wenli Zhang, Junting Wang, Ming Zu, Wei Chen. ECharts: A Declarative Framework for Rapid Construction of Web-based Visualization. Visual Informatics, 2018.