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.

Graph Data Science Python Client 1.7a1

We are happy to announce the first alpha 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-preview/

It contains the following changes:

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 managment 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.

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.

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Additionally, there is now reference documentation for the library which can be found here.

The release can be pip installed with pip install graphdatascience==1.7a1.

Graph Data Science Python client 1.6

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

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

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Additionally, there are new example notebooks available.

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

Graph Data Science Python client 1.6rc1

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.

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Additionally, there are new example notebooks available.

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

Graph Data Science Client 1.5

We are happy to announce the release of graphdatascience, the GDS Python client, version 1.5! It is published to PyPI!

Changes:

• Fixed a bug where the client could not connect to the server when the default db was set in the GraphDataScience constructor.
• For GDS admin users, gds.graph.get is now able to resolve graph names into Graph objects of other users graph projections.
• Add support for gds.alpha.triangles.
• Support calling gds.alpha.userLog to access hints and warnings for the recently run operations.
• Add support for gds.alpha.backup and gds.alpha.restore.
• Add support for gds.alpha.config.defaults.set and gds.alpha.config.defaults.list.

The release can be pip installed with pip install graphdatascience==1.5.

Graph Data Science Client 1.4

We are happy to announce the release of graphdatascience, the GDS Python client, version 1.4! It is published to PyPI!

Highlights:

• The DataFrame returned by gds.beta.graph.relationships.stream now has a convenience method called by_rel_type.
• Added a new optional string parameter database to GraphDataScience.run_cypher for overriding which database to target.
• Added new method gds.graph.load_cora to load the CORA dataset into GDS.
• Added a new optional string parameter database to the GraphDataScience constructor for specifying the targeted database.
• Fix resolving Node regression pipelines created via gds.alpha.pipeline.nodeRegression.create.
• Fix resolving Node regression models created via gds.alpha.pipeline.nodeRegression.train.
• Fix an issue where run_cypher did not execute Cypher correctly in some edge cases.

A full list of changes can be found in the changelog.

The release can be pip installed with pip install graphdatascience==1.4.

Graph Data Science client 1.3

We are happy to announce the release of graphdatascience, the GDS Python client, version 1.3! It is published to PyPI!

Highlights:

• New versioning scheme using only two numbers
• Add MLP training method addMLP to link prediction and node classification pipelines.
• Add support for new graph catalog API endpoints in GDS >= 2.2.0.
• Add support for random walk with restarts sampling procedure.
• Add support for graph property endpoints in GDS >= 2.2.0.
• Add Arrow Flight specific parameters to the GraphDataScience constructor:
  • arrow_tls_root_certs
  • arrow_disable_server_verification
• Add support for new stream graph relationships endpoint.
• Dropped support for Python 3.6.

A full list of changes can be found in the changelog.

The release can be pip installed with pip install graphdatascience==1.3.

Graph Data Science Client 1.3.0 Alpha 1

The first alpha release of version 1.3.0 of graphdatascience, the GDS Python client, has been published to PyPI!

Highlights:

• Add MLP training method addMLP to link prediction and node classification pipelines.
• Add support for new graph catalog API endpoints in GDS >= 2.2.0.
• Add support for random walk with restarts sampling procedure.
• Add support for graph property endpoints in GDS >= 2.2.0.
• Add Arrow Flight specific parameters to the GraphDataScience constructor:
  • arrow_tls_root_certs
  • arrow_disable_server_verification
• Add support for new stream graph relationships endpoint.
• Dropped support for Python 3.6.

A full list of changes can be found in the changelog.

The release can be pip installed with pip install graphdatascience==1.3.0a1.

Graph Data Science client 1.2.0

Version 1.2.0 of graphdatascience, the GDS Python client, has been published to PyPI!

Included are bug fixes for:

• The separate_property_columns=True option of gds.graph.streamNodeProperties did not handle list node properties correctly.
• An irrelevant warning was shown when creating a GraphDataScience object targeting an AuraDS instance with GDS server version >= 2.1.0.
• Calling gds.alpha.graph.construct targeting an AuraDS instance would raise an exception.

The release can be pip installed with pip install graphdatascience==1.2.0.