ipychart 0.5.2

Bug fixes:

• Fix missing assets in the NPM distribution caused by incorrect instructions in the CI deployment script.

ipychart 0.5.1

New features in this version:

• Add automated deployment scripts for NPM and PyPi ipychart packages using GitHub Actions CI/CD.
• Add automated scripts that run frontend and backend tests on each contribution using GitHub Actions CI/CD.

Bug fixes:

• Fix old assets packaged with the latest version due to the ‘skip if exists’ key in the pyproject.toml file.

ipychart 0.5.0

New features in this version:

• Add a to_image() export method to the Chart class, allowing to export the chart as a .png or .jpg image.
• Convert complete JS frontend codebase to Typescript and esnext.
• Bump Chart.js version to 4.4.x
• Use custom exceptions for clearer error messages in Python backend.
• Refactoring of data validation and styling methods in Python backend for a better code quality.
• Refactoring of plots functions and utils in Python backend for a better code quality.
• Add several Python backend tests, including a mock of communications between frontend and backend.
• Add frontend UI tests using galata and playwright, copying the official ipywidgets repository UI tests folder.
• Include testing notebooks and docker sandbox image to the main repo for ease of maintenance.
• Switch from setup.py to pyproject.toml for python packaging.
• DOC: Format all code snippets of the documentation using Ruff.

Bug fixes:

• Fix charts not rendering
• Fix aggregation in plots function not working on recent pandas versions.
• DOC: Fix SyntaxError in documentation python code example comparing chartjs and ipychart code.

ipychart 0.4.1

New features in this version:

• Doc: Improve Introduction section of the documentation.
• Improve Python docstrings.

Bug fixes:

• Solve issue #5.
• Fix html-vue examples in official documentation not using the last npm package version, thus leading to incorrect charts displayed.

ipychart 0.4.0

New features in this version:

• Chart.js backend was updated to 3.x.x. This is a major update, all changes can be seen here: https://www.chartjs.org/docs/latest/getting-started/v3-migration.html. This implies large performance improvements, easier customization, a rewritten animation system, bug fixes etc.
• Doc: Move from GitLab pages to GitHub pages. Replace algolia search by flexsearch. Re-writing of some sections to match the new syntax of Chart.js 3.x.x. Better handling of components, which are now isolated in separates HTML files called by Vue scripts.
• Convert all JS code to ES6 Javascript standard. Use ESLint and Prettier to clean the JS codebase.
• Integration and adaptation of the colorscheme plugin into the codebase because original implementation is not compatible with Chart.js 3.x.x.
• Start TDD on Python side.

ipychart 0.3.3

Bug Fixes:

• Fix formatting of datalabels through a callback function (see related issue)

ipychart 0.3.2

New features in this version:

• Pandas Interface : Complete refactoring of the API. Charts are now created using functions.
• Added support of Jupyter Lab.
• Added dynamic update of charts when an agument of the chart is modified. This bring a lots of possibilities to dynamically modify a chart, for example by using ipywidgets (sliders, buttons ...).

ipychart 0.2.2

New features in this version:

• Full cleaning of Python code
• Reduce fontsize in tooltips (back to default size) for charts made using the Pandas Interface

ipychart 0.2.1

New features in this version:

• Add zoom feature (using https://github.com/chartjs/chartjs-plugin-zoom), allowing the user to zoom in the chart using his mouse. Double click on the chart will reset the zoom.

Bug Fixes:

• Fix tooltips for doughnut, pie, polarArea charts when using pandas interface (tooltips wasn't formatted in the same way as other charts).
• Fix typing in methods of ChartDataFrame class in pandas interface.
• Fix docstrings: removing excess arguments and adding missing arguments.
• Various fixes and minor modifications in the documentation

ipychart 0.1.4

New features in this version:

• Pandas Interface : Tooltips are automatically generated to use the column names of the dataframe used to draw the chart. Therefore, the information displayed when hovering the Chart is more relevant and more complete!
• Code optimization in both Chart & ChartDataFrame classes

Bug Fixes:

• Add missing requirements
• Requirements & LICENSE are now packaged in the source distribution