GSoC/2024/StatusReports/IsraelGaladima: Difference between revisions
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== Improve Python Interoperability with LabPlot == | == Improve Python Interoperability with LabPlot == | ||
LabPlot is a data analysis and visualisation application in KDE. Since Python is heavily used within the data science community, this project aims to make LabPlot a more "Python-friendly" application. The | LabPlot is a data analysis and visualisation application in KDE. Since Python is heavily used within the data science community, this project aims to make LabPlot a more "Python-friendly" application. The project goals are to: | ||
* Create Python bindings to LabPlot's C++ backend, and | |||
* Enable Python programs to control a running LabPlot application. | |||
These goals will respectively allow users to: | |||
* Access LabPlot's data analysis and visualisation tools from a Python program, and | |||
* Create complex workflows using Python within a running LabPlot application. | |||
== Work report == | == Work report == | ||
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== Links to Blogs and other writing == | == Links to Blogs and other writing == | ||
* [https://israelsgalaxy.hashnode.dev/improving-python-interoperability-with-labplot Blog Post #1] | * [https://israelsgalaxy.hashnode.dev/improving-python-interoperability-with-labplot Blog Post #1] | ||
* [https://israelsgalaxy.hashnode.dev/creating-python-bindings-to-labplots-c-backend-part-1 Blog Post #2] | |||
* [https://israelsgalaxy.hashnode.dev/creating-python-bindings-to-labplots-c-backend-part-2 Blog Post #3] | |||
Latest revision as of 17:39, 30 June 2024
Improve Python Interoperability with LabPlot
LabPlot is a data analysis and visualisation application in KDE. Since Python is heavily used within the data science community, this project aims to make LabPlot a more "Python-friendly" application. The project goals are to:
- Create Python bindings to LabPlot's C++ backend, and
- Enable Python programs to control a running LabPlot application.
These goals will respectively allow users to:
- Access LabPlot's data analysis and visualisation tools from a Python program, and
- Create complex workflows using Python within a running LabPlot application.