Toolkit Components and Product Roadmap
The Toolkit’s Contents
The Highcharts for Python Toolkit features a number of separate Python
libraries which extend the core Highcharts Core for Python (highcharts-core) library.
This pattern maps quite naturally to the Highcharts (JS) design, where multiple
other modules extend the core Highcharts (JS) library.
The Highcharts for Python Toolkit includes two categories of tools:
These libraries correspond to each of the major Highcharts products:
Highcharts Core for Python: This is the foundational Python library, and is required by all other components in the toolkit. It provides the fundamental Python classes that are used throughout the toolkit, and importantly provides 100% coverage for the functionality in the Highcharts Core JavaScript library. For more details, please see the relevant Highcharts Core for Python documentation.
Highcharts Stock for Python: This is the Python wrapper for the Highcharts Stock JavaScript library, which provides extensive visualizations for time series and stock price visualizations. For more details, please see the relevant Highcharts Stock for Python documentation
Highcharts Maps for Python: This is the Python wrapper for the Highcharts Maps JavaScript library, which provides extensive geographic data visualization options with rich interactive maps. For more details, please see the relevant Highcharts Maps for Python documentation
Highcharts Gantt for Python: This is the Python wrapper for the Highcharts Gantt JavaScript library, which provides rich visualizations for resource allocation over time. For more details, please see the relevant Highcharts Gantt for Python documentation
These libraries serve as extensions to the core visualization libraries, providing specialized functionality to simplify usage of Highcharts for Python in various applications:
Note
A number of extension libraries are in progress, but have not yet been released. Watch this space for news soon!
Note
All extensions to Highcharts Core for Python support visualizations produced in any of the core libraries. For more information, please see Supported Visualizations.
The Toolkit’s Roadmap
There are a number of features (and in some cases complete components) slated for development. While detailed write-ups of each feature can be found in the respective project project repo, the lists below provides some high-level information.
Needed Script Tags ( #6 ). It would be helpful for Highcharts Maps for Python to support the production of the relevant
<script/>tags needed to include the Highcharts JS modules that are needed to render a specific chart (and to not include the modules that are not needed).Support for Explicit Defaults ( #7 ). Currently, Highcharts default values are always presented as
Nonein outputs within Python, and are stripped from the serialized JSON or JS literal representation of all objects (because that way the Highcharts JS library applies its default). While this is valuable to minimize irrelevant data and shrink content passed along the wire, it does force developers to track / remember / understand the Highcharts defaults (which are called out in the docs, obviously - but still…it’s a pain). So in the Zen of Python spirit that “explicit is better than implicit”, there needs to be a mechanism for users of the library to explicitly request that default values are accessible in Python and shown when serializing the chart configuration.Styled Mode Configuration ( #8 ). While styled mode can currently be enabled in Highcharts Maps for Python, the library does not provide for the actual definition or configuration of Highcharts CSS. It would be good if it did, so that all Highcharts-related configuration could be handled within the library.
Watch this space…we’ll be announcing some new extensions soon.
Additional Tools Needed?
Are you looking for additional tools that are not already part of the Highcharts for Python Toolkit? Drop us a note with a feature request in our Github Issues Page.