Neo4j Graph Data Science Python Client 1.11

We are happy to announce the release of graphdatascience, the GDS Python client, version 1.11! It is published to PyPI!

Documentation: https://neo4j.com/docs/graph-data-science-client/1.11/

Highlights:

• Fixed a bug which caused the auth token returned from the GDS Arrow Server was not correctly received.
• Fixed a bug which didn't allow the user to specify relationship_types as a string in gds.graph.relationshipProperties.stream().
• Fixed a bug in kge-predict-transe-pyg-train.ipynb which now uses the gds.graph.relationshipProperty.stream() call and can correctly handle multiple relationships between the same pair of nodes. Issue ref: #554

The release can be pip installed with pip install graphdatascience==1.11.

Neo4j Graph Data Science Python Client 1.11a4

We are happy to announce the alpha release of graphdatascience, the GDS Python client, version 1.11a3. It is published to PyPI.

Documentation: https://neo4j.com/docs/graph-data-science-client/1.11-preview/

Highlights:

New features

• Add the new concept of GDS Sessions, used to manage GDS computations in Aura, based on data from an AuraDB instance.
  • Add a new gds.graph.project endpoint to project graphs from AuraDB instances to GDS sessions.
  • Add a new top-level class GdsSessions to manage GDS sessions in Aura.
    • GdsSessions support get_or_create(), list(), and delete().
  • Creating a new session supports various sizes.
  • The run_cypher() method will run Cypher queries targeting the configured AuraDB instance.

Bug fixes

• Fixed a bug which caused the auth token returned from the GDS Arrow Server was not correctly received.
• Fixed a bug which didn't allow the user to specify relationship_types as a string in gds.graph.relationshipProperties.stream().
• Fixed a bug in kge-predict-transe-pyg-train.ipynb which now uses the gds.graph.relationshipProperty.stream() call and can correctly handle multiple relationships between the same pair of nodes. Issue ref: #554

Improvements

• Improved the error message if gds.graph.project.cypher produces an empty graph.

Other changes

• Updated required neo4j driver from 4.4.2 to the latest 4.4 path release (4.4.12) or later.

Neo4j Graph Data Science Python Client 1.11a3

We are happy to announce the alpha release of graphdatascience, the GDS Python client, version 1.11a3. It is published to PyPI.

Documentation: https://neo4j.com/docs/graph-data-science-client/1.11-preview/

Highlights:

New features

• Add the new concept of GDS Sessions, used to manage GDS computations in Aura, based on data from an AuraDB instance.
  • Add a new gds.graph.project endpoint to project graphs from AuraDB instances to GDS sessions.
  • Add a new top-level class GdsSessions to manage GDS sessions in Aura.
    • GdsSessions support get_or_create(), list(), and delete().
  • Creating a new session supports various sizes.
  • The run_cypher() method will run Cypher queries targeting the configured AuraDB instance.

Bug fixes

• Fixed a bug which caused the auth token returned from the GDS Arrow Server was not correctly received.
• Fixed a bug which didn't allow the user to specify relationship_types as a string in gds.graph.relationshipProperties.stream().
• Fixed a bug in kge-predict-transe-pyg-train.ipynb which now uses the gds.graph.relationshipProperty.stream() call and can correctly handle multiple relationships between the same pair of nodes. Issue ref: #554

Neo4j Graph Data Science Python Client 1.11a2

We are happy to announce the alpha release of graphdatascience, the GDS Python client, version 1.11a2. It is published to PyPI.

Documentation: https://neo4j.com/docs/graph-data-science-client/1.11-preview/

Highlights:

New features

• Add the new concept of GDS Sessions, used to manage GDS computations in Aura, based on data from an AuraDB instance.
  • Add a new gds.graph.project endpoint to project graphs from AuraDB instances to GDS sessions.
  • Add a new top-level class GdsSessions to manage GDS sessions in Aura.
    • GdsSessions support get_or_create(), list(), and delete().
  • Creating a new session supports various sizes.
  • The run_cypher() method will run Cypher queries targeting the configured AuraDB instance.

Bug fixes

• Fixed a bug which caused the auth token returned from the GDS Arrow Server was not correctly received.

Neo4j Graph Data Science Python Client 1.11a1

We are happy to announce the alpha release of graphdatascience, the GDS Python client, version 1.11a. It is published to PyPI.

Documentation: https://neo4j.com/docs/graph-data-science-client/1.11-preview/

Highlights:

New features

• Add the new concept of GDS Sessions, used to manage GDS computations in Aura, based on data from an AuraDB instance.
  • Add a new gds.graph.project endpoint to project graphs from AuraDB instances to GDS sessions.
    • nodePropertySchema and relationshipPropertySchema can be used to optimise remote projections.
  • Add a new top-level class GdsSessions to manage GDS sessions in Aura.
    • GdsSessions support get_or_create(), list(), and delete().
  • Creating a new session supports various sizes.
  • The run_cypher() method will run Cypher queries targeting the configured AuraDB instance.

Bug fixes

• Fixed a bug which caused the auth token returned from the GDS Arrow Server to not be correctly received.

Graph Data Science Python Client 1.10

We are happy to announce the release of graphdatascience, the GDS Python client, version 1.10! It is published to PyPI!

Documentation: https://neo4j.com/docs/graph-data-science-client/1.10/

Highlights:

• Fixed an issue where source and target IDs of relationships in heterogeneous OGBL graphs were not parsed correctly.
• Fixed an issue where configuration parameters such as aggregation were ignored by gds.graph.toUndirected.
• Fixed an issue where the database given for the GraphDataScience construction was not used for metadata retrieval, causing an exception to be raised if the default "neo4j" database was missing.
• Fixed an issue where progress bars would not always complete.
• Fixed an issue where an empty relationship type could not be streamed.

The release can be pip installed with pip install graphdatascience==1.10.

Graph Data Science Python Client 1.10a1

We are happy to announce the alpha release of graphdatascience, the GDS Python client, version 1.10a1! It is published to PyPI!

Documentation: https://neo4j.com/docs/graph-data-science-client/1.10-preview/

Highlights:

• Add the new concept of GDS Sessions, used to manage GDS computations in Aura, based on data from an AuraDB instance
• Fixed an issue where source and target IDs of relationships in heterogeneous OGBL graphs were not parsed correctly.
• Fixed an issue where configuration parameters such as aggregation were ignored by gds.graph.toUndirected.

The release can be pip installed with pip install graphdatascience==1.10a1.

Graph Data Science Python Client 1.9

We are happy to announce the release of graphdatascience, the GDS Python client, version 1.9! It is published to PyPI!

Documentation: https://neo4j.com/docs/graph-data-science-client/1.9/

Highlights:

• Fixed a bug which caused an exception to be raised when running gds.license.state targeting an AuraDS instance.
• Fixed a bug where the parameter listNodeLabels was ignored for gds.graph.[nodeProperty|nodeProperties].stream calls via Arrow.
• Fixed a bug where the parameter listNodeLabels was ignored for gds.graph.[nodeProperty|nodeProperties].stream calls via Cypher and separate_property_columns=True.
• Expose user facing custom types so that they can be directly imported from graphdatascience.
• Allow dropping graphs through gds.graph.drop by name and not only based on Graph objects.

The release can be pip installed with pip install graphdatascience==1.9.

Graph Data Science Python Client 1.8

We are happy to announce the release of graphdatascience, the GDS Python client, version 1.8! It is published to PyPI!

Documentation: https://neo4j.com/docs/graph-data-science-client/1.8/

Highlights:

• New methods that support inference of KGE models (TransE and DistMult).
• New method gds.graph.cypher.project to project a graph using Cypher projection.
• Added new LastFM dataset through gds.graph.load_lastfm().
• Expose bookmarks to synchronize queries in a Neo4j cluster.
• Dropped support for Python 3.7 which is now EOL.
• Improved endpoint returning graphs to be used in with clauses. The expression with gds.graph.project(...)[0] as G can now be simplified to with gds.graph.project(...) AS G.
• Make gds.graph.construct more robust by ignoring empty dataframes inside. This makes it less error-prone to construct nodes only graphs.
• Improved error messages and deprecation warnings.

The release can be pip installed with pip install graphdatascience==1.8.

Graph Data Science Python client 1.7

We are happy to announce the release of graphdatascience, the GDS Python client, version 1.7! It is published to PyPI!

Documentation: https://neo4j.com/docs/graph-data-science-client/1.7/

Highlights:
New features:

• Add a new method GraphDataScience.server_version which returns the version of the server not as a str but as a ServerVersion. This allows easier inspection of the major, minor and patch version.
• Implement context management protocol for Graph. This allows usage as part of the with statements, where the graph is dropped at the end.
• Added possibility to load datasets from the Open Graph Benchmark via the new methods:
• gds.graph.ogbn.load for node property prediction datasets, and
• gds.graph.ogbl.load for link property prediction datasets.
• Added possibility to load NetworkX graphs via the new method gds.graph.networkx.load.
• Added new sphinx API reference documentation for all procedures.
• Promoted gds.alpha.graph.construct to gds.graph.construct.

Improvements:

• When an almost correct method is called, raise an error with a message that suggests the most probable correct method name that was intended.
• Improved IDE auto-completion support to give significantly fewer false positive suggestions.
• Failing to log progress of a call will no longer fail the call itself, but just warn that logging was unsuccessful.
• Underlying connections to a Neo4j DBMS is now being verified and retried automatically up to a timeout of 10 minutes.
• The GraphDataScience.from_neo4j_driver factory method now additionally takes the same Arrow related keyword parameters as the GraphDataScience constructor.
• Added an example for community detection thanks to community contributor @kedarghule.

The release can be pip installed with pip install graphdatascience==1.7.