Graph Data Science client 1.1.0

Version 1.1.0 of graphdatascience, the GDS Python client, has been published to PyPI!

Changes highlights:

• Support for GDS library version 2.1
• Additional and improved convenience functionality on the Graph object
• Supporting GDS Apache Arrow capabilities for graph catalog stream procedures
• New method gds.alpha.graph.construct for loading a graph directly into GDS from client side pandas DataFrames
  • Greatly sped up by Apache Arrow if enabled

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

The release can be pip installed with pip install graphdatascience==1.1.0.

Graph Data Science client 1.1.0 release candidate 1

The first release candidate of version 1.1.0 of graphdatascience, the GDS Python client, has been published to PyPI!

Highlights:

• Added support for auto tuning for machine learning pipelines.
• Added support for providing ranges as length two tuples to addLogisticRegression and addRandomForest.
• Added support for new GDS library 2.1 signature of gds.graph.removeNodeProperties.
• Added support for new function gds.close which calls .close() on a GraphDataScience object's underlying Neo4j driver.
• Added new method gds.alpha.graph.construct to construct a GDS graph from pandas DataFrames. When running against a GDS library with its Apache Arrow server enabled it will be a lot faster.
• Added support for new nodeRegression pipelines.
• New convenience methods on the Graph object.

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

The release can be pip installed with pip install graphdatascience==1.1.0rc1.

Graph Data Science client 1.1.0 Alpha 2

The second alpha release of version 1.1.0 of graphdatascience, the GDS Python client, has been published to PyPI!

Highlights:

• Added support for new configureAutoTuning method on NC and LP pipelines.
• Added support for providing ranges as length two tuples to addLogisticRegression and addRandomForest.
• Added new method auto_tuning_config to NC and LP pipelines for querying a pipelines auto-tuning config.
• Added support for new GDS library 2.1 signature of gds.graph.removeNodeProperties.
• Added support for new function gds.close which calls .close() on a GraphDataScience object's underlying Neo4j driver.
• Added new method gds.alpha.graph.construct to construct a GDS graph from pandas DataFrames, which works if the GDS Flight server is enabled.
• Added new function gds.database which can be used to see which database is currently being targeted.
• Added support for new nodeRegression pipelines.

The release can be pip installed with pip install graphdatascience==1.1.0a2.

Graph Data Science client 1.1.0 Alpha 1

The alpha release of version 1.1.0 of graphdatascience, the GDS Python client, has been published to PyPI!

Highlights:

• Added support for new configureAutoTuning method on NC and LP pipelines.
• Added support for providing ranges as length two tuples to addLogisticRegression and addRandomForest.
• Added support for new function gds.close which calls .close() on a GraphDataScience object's underlying Neo4j driver.
• Added new method gds.alpha.graph.construct to construct a GDS graph from pandas DataFrames, which works if the GDS Flight server is enabled.
• Added new function gds.database which can be used to see which database is currently being targeted.
• The functions gds.graph.streamNodeProperty and gds.graph.streamRelationshipProperty can leverage the Arrow Flight server of GDS to improve throughput.

The release can be pip installed with pip install graphdatascience==1.1.0a1.

Graph Data Science client 1.0.0

The first official major release, 1.0.0, of graphdatascience, the GDS Python client, has been published to PyPI!

Highlights:

• Replaced all dict return types with pandas Series.
• Replaced all list[dict,...] return types with pandas DataFrame.
• Replaced NC and LP training pipelines method configureParams by new methods addLogisticRegression and addRandomForest.
• All procedures of the GDS Pipeline catalog are supported.
• The NC and LP training pipelines support estimating train via a train_estimate method.
• All ML models support estimating predict via predict_[mode]_estimate methods.
• Removed support for GDS 1.x graph.create syntax.

Read more in the changelog.

The release can be pip installed with pip install graphdatascience==1.0.0.

Graph Data Science client 0.1.0

A new release 0.1.0 of graphdatascience, the GDS Python client, has been published at PyPI!

Highlights:

• When connecting to AuraDS, a specific user-agent will be set indicating that the graphdatascience client is used.
• The methods of NCTrainingPipeline and LPTrainingPipeline for building the pipelines now return metadata from the underlying Cypher procedures called.
• Methods creating Graph objects now additionally return the metadata from the underlying Cypher procedures called.
• Methods creating Model objects now additionally return the metadata from the underlying Cypher procedures called.

Read more in the changelog.

The release can be pip installed with pip install graphdatascience==0.1.0.

Graph Data Science client 0.0.9

A new release 0.0.9 of graphdatascience, the GDS Python client, has been published at PyPI!

Highlights:

• simpler return types for operations that always returns exactly one row
• compatibility with GDS 1.x by supporting graph.create syntax
• links to official preview documentation hosted within the GDS Manual
• a changelog!

Read more in the changelog.

The release can be pip installed with pip install graphdatascience==0.0.9.

Graph Data Science Client 0.0.8

A new release 0.0.8 of graphdatascience, which is the new and final name of the GDS Python client, formerly called gdsclient , has been published at PyPI!

Highlights:

• new library name!
• new source repository (this repo)
• support for all utility functions
• support for all Similarity functions
• simplified interface to construct GDS reference object (hidden driver)
• simplified interface to run Cypher queries (hidden query runner)

The release can be pip installed with pip install graphdatascience==0.0.8.