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.