We are thrilled to announce the release of Taipy 3.1, a significant update that brings many new features and enhancements to our comprehensive platform.

This latest version underscores our commitment to providing robust, scalable, and intuitive functionalities that cater to the community and the enterprise needs. With Taipy 3.1, users can expect many improvements designed to enhance data visualization, integrate tightly with Python visualization libraries, and enable more efficient computing capabilities.

Empowering the Community Edition with New Features

Third-Party Component Integration

This enhancement allows users to seamlessly integrate a broad range of Python libraries into their Taipy application without waiting for specific integrations. By enabling the visualization of any html of Python objects into Taipy’s generic part object, users can now effortlessly incorporate tools with many Python visualization libraries like Folium, Bokeh, Altair, Matplotlib, etc.

To go in depth with this feature, the part block is used to group visual elements into a single element. This allows to show or hide them in one action and be placed as a unique element in a cell.

More technical info here

Third-party component integration

Native Plotly Integration

Further enriching the data visualization capabilities of Taipy, version 3.1 integrates Plotly Python natively. Until Taipy V3, integrating additional charts from Plotly has some complexity. Now, any Plotly chart can be embedded within a Taipy application in a single line of code while retaining the performance and interactivity of Taipy.

If we dig more in details, the control has a new property called figure that expects an instance of plotly.graph_objects.Figure. This class is provided by the Plotly Open Source Graphig Libary for Pyhon, so you can create all sorts of graphs in Python.

More technical info here

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Native Plotly Charts integration

Elevating Enterprise Solutions with Advanced Features

Distributed Computing

Recognizing the growing needs of enterprises for scalable data processing solutions, Taipy 3.1 introduces Distributed Computing capabilities.

This feature enables the distribution of computational tasks across multiple machines, significantly improving the performance of large-scale data projects. Companies can now leverage distributed computing to perform complex computation tasks more efficiently, reducing turnaround times and enhancing productivity.

If we go deeper in the technical aspect, a new job execution mode named cluster mode is available. It enables to run the jobs on a cluster of dedicated machines in a remote, distributed and scalable environment.

More technical info here

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Distributed Computing

Telemetry

To assist enterprises in maintaining the health and performance of their applications, Taipy 3.1 incorporates Telemetry features. This addition provides administrators and developers with valuable insights into application performance metrics and health indicators. By facilitating the monitoring and analysis of these metrics, Taipy aims to help enterprises proactively identify and address potential issues, ensuring smoother operations and optimal performance.

More technical info here

Telemetry

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And beside all this, Taipy and all its dependencies now support Python 3.12.

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Conclusion

Taipy 3.1 represents a major step forward in our mission to provide data scientists with a powerful, flexible and easy-to-use framework.

Whether you are part of the open-source community or seeking enterprise-level solutions, this release let you enhance your data projects. We are excited to see how you will leverage these new capabilities to build great pilots as well as fantastic production-ready applications.

For those interested in exploring these new features further, we encourage you to join our growing community of developers and data scientists and meet some of the on Discord.

Join us on Discord

Together, we can continue to innovate and make Taipy the standard framework for your Python application development needs.

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