Release Notes for version 3.1

This is the list of changes of taipy version 3.1.

Published on 2024-03.

taipy 3.1 contains the latest taipy-config 3.1, taipy-gui 3.1, taipy-core 3.1, taipy-templates 3.1, and taipy-rest 3.1 packages.

taipy

3.1.1

Significant bug fixes

• Data is not shown or not automatically refreshed in Data Node viewer.
  See issue #908 and issue #950.
• Data Nodes holding dates may not show in Data Node viewers.
  See issue #1043.

3.1.0

New features

• Taipy and all its dependencies now support Python 3.12.
  See Python documentation for details.

Improvements and changes

• Task nodes in the scenario_dag control dynamically reflect the status of related jobs for the user that submitted the scenario or sequences.
• The scenario control lets you add, modify, and edit sequences.
• The data_node control can now represent collections.

taipy-gui

3.1.0

New features

• The chart 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 Graphing Library for Python so you can create all sorts of graphs in Python.
  See the figure property of the chart control and the section on the figure property for more information.
• The part block has a new property called content that lets developers integrate any third-party library that can generate HTML.
  See the documentation for the part block and the examples using content providers for more information.
• A new control called date_range is available if you need to represent and edit date ranges in your application pages.
• A new control called login is available if you need users to authenticate in your application.

Improvements and changes

• The table control supports enumerated values. That allows for a better user experience when users edit cell values.
  See the section on enumerated values in tables for the details.
• The toggle control appears as a switch button if its value property holds a Boolean value.

Significant bug fixes

• Selectors with dropdown menus cannot be deactivated.
  See issue #894.
• Problems scoping non-global variables used in Partials.
  See issue #561.
• Important error messages are mangled.
  See issue #560.

taipy-core

3.1.1

Significant bug fixes

• The signatures for Config.configure_sql_data_node(), Config.configure_s3_object_data_node(), and configure_core() methods are out-of-date.
  See issue #1014.

3.1.0

New features

• The DataNode.filter() method and the indexing/filtering style now also support filtering a Numpy array, a list of objects, and a list of dictionaries.
  For more information, please refer to Filter a data node.
• You can now append new data to a data node using the DataNode.append() method. The method is available for CSVDataNode, ExcelDataNode, JSONDataNode, ParquetDataNode, SQLDataNode, SQLTableDataNode, and MongoCollectionDataNode.
  For more information, please refer to Append a data node.
• A new class called Submission holds meta-data (such as its status or submission date) related to a submitted entity: Scenario, Sequence, and/or Task.
  The function taipy.get_latest_submission() returns the last submission of a given entity.
  For more information, please refer to Submission.
• taipy.submit(), Scenario.submit(), Sequence.submit(), and Task.submit() now return a Submission entity.
• A new predefined data node named S3ObjectDataNode has been implemented.
  For more information, please refer to S3ObjectDataNode.

Improvements and changes

• Running twice the Orchestrator service raises an exception to prevent running multiple instances at the same time.
• Running the Orchestrator service or creating an entity by taipy.create_scenario() or taipy.create_global_data_node() blocks the configuration from being modified.

Deprecations

• The modin exposed type as been deprecated. When used, a fallback on Pandas is applied.
  See issue #631 for details.

taipy-enterprise

3.1.0

New features

• 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.