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Graph Data Science Python client 1.6rc1

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@Mats-SX Mats-SX released this 13 Jan 16:06
· 2118 commits to main since this release
1.6rc1
a8b081a

We are happy to announce the first release candidate of graphdatascience, the GDS Python client, version 1.6rc1! It is published to PyPI!

Documentation: https://neo4j.com/docs/graph-data-science-client/1.6/

This release candidate is feature complete for the release of 1.6. It contains the following changes:

New features

  • Added a new parameter undirected_relationship_types to gds.alpha.graph.construct which allows constructing undirected graphs, when using GDS >= 2.3.0.
  • Added a new parameter undirected to gds.load_cora to load the dataset undirected.
  • Added new method gds.alpha.graph.nodeLabel.write to write back node labels to Neo4j database.
  • Added new convenience methods to the Model object:
    • model_info to get model metadata obtained during training.
    • classes to list all classes used during training (only for Node Classification models).
    • best_parameters which returns a pandas Series containing the parameters of the model candidate winning the model selection training.
    • feature_properties (only for Node Property models)
    • link_features (only for LP models)
    • node_property_steps
  • Added new convenience factory methods to create pipeline objects.
  • gds.graph.construct now renders a progress bar if Arrow support is enabled.
  • Added a new method gds.graph.relationships.to_undirected to turn a directed relationship type to an undirected, when using GDS >= 2.3.0
  • Added new common datasets:
    • gds.graph.load_karate_club
    • gds.graph.load_imdb
  • Added new optional parameter db_node_properties to gds.graph.nodeProperties.stream that can stream DB-only node properties that are not on the in-memory graph.
  • Added new method gds.alpha.graph.nodeLabel.mutate to mutate the in-memory graph with new node labels.

Improvements

  • Improved Model.metrics() method for pipeline models (e.g. LP, NC, NR) to return custom type.
  • Improved gds.graph.construct() to support multiple dataframes for nodes and relationships without arrow.

Additionally, there are new example notebooks available.

The release can be pip installed with pip install graphdatascience==1.6rc1.

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