v1.2.5

[1.2.5] - 2022-11-15

Release of pyTigerGraph version 1.2.5.

Fixed:

• Fix featurizer install of FastRP on versions DB versions 3.8+ with global schema elements.

v1.2.4

[1.2.4] - 2022-11-14

Release of pyTigerGraph version 1.2.4.

Changed:

• Improve data ingestion print out
• Skip downloading if dataset exists on disk

Fixed:

• Fix metrics issue
• Fix unit test issue in featurizer

v1.2.3

[1.2.3] - 2022-11-13

Release of pyTigerGraph version 1.2.3.

Fixed:

• NeighborLoader fetch() functionality restored.
• runInstalledQuery() defaulting back to GET REST requests.
  • If you wish to pass empty sets, set the usePost = True parameter.

v1.2.2

[1.2.2] - 2022-11-11

Release of pyTigerGraph version 1.2.2.

Fixed:

• The way empty sets are serialized into JSON for installed queries.

v1.2.1

[1.2.1] - 2022-11-09

Release of pyTigerGraph version 1.2.1.

Fixed:

• Error handling in visualization module
• Error handling FastRP in featurizer
• Fixed unit tests.

v1.2

[1.2] - 2022-11-09

Release of pyTigerGraph version 1.2.

Added:

• The Datasets class, a way to easily import standard datasets into a database instance.
• The visualizeSchema function to visualize graph schemas.
• Proper deprecation warnings.
• Logging capabilities using native Python logging tools.
• Ability to run asynchronous queries from runInstalledQuery()

Changed:

• Many changes to the featurizer capability, including:
  • Automatically selecting the correct version of a graph data science algorithm given your version of the database.
  • Automatically creating the schema change necessary to run the algorithm and store the results to an attribute.
  • If the algorithm is not already installed at runtime, and is included in the TigerGraph Graph Data Science Library, the algorithm will be installed automatically.
  • Adding more supported algorithms, in categories such as similarity and topological link prediction.

v1.1

[1.1] - 2022-09-06

Release of pyTigerGraph version 1.1.

Added:

• TensorFlow support for homogeneous GNNs via the Spektral library.
• Heterogeneous Graph Dataloading support for DGL.
• Support of lists of strings in dataloaders.

Changed:

• Fixed KeyError when creating a data loader on a graph where PrimaryIdAsAttribute is False.
• Error catch if Kafka dataloader doesn't run in async mode.
• Refresh schema during dataloader instantiation and featurizer attribute addition.
• Reduce connection instantiation time.
• Reinstall query if it is disabled.
• Confirm Kafka topic is created before subscription.
• More efficient use of Kafka resources.
• Allow multiple consumers on the same data.
• Improved deprecation warnings.

v1.0.2

[1.0.2] - 2022-08-03

Bug Fixes:

• Error catch if Kafka dataloader doesn't run in async mode.
• Refresh schema during dataloader instantiation.
• Reduce connection instantiation time.

v1.0.1

[1.0.1] - 2022-07-12

Changed:

• Fixed KeyError when creating a data loader on a graph where PrimaryIdAsAttribute is False.

Version 1.0

[1.0] - 2022-07-11

Release of pyTigerGraph version 1.0, in conjunction with version 1.0 of the TigerGraph Machine Learning Workbench.

Added:

• Kafka authentication support for ML Workbench enterprise users.
• Custom query support for Featurizer, allowing developers to generate their own graph-based features as well as use our built-in Graph Data Science algorithms.

Changed:

• Additional testing of GDS functionality
• More demos and tutorials for TigerGraph ML Workbench, found here.
• Various bug fixes.