GDS Python Client 2.0 brings new algorithms and asynchronous execution to Aura Graph Analytics

Version 2.0 of the GDS Python client is out, with multiple upgrades specific to Aura Graph Analytics:

Asynchronous execution
: projections, algorithm runs, and write-backs can now return a handle instead of blocking, so you can trigger a job and check on it later, even from a different process. This makes it much easier to orchestrate AGA jobs from tools like Apache Airflow: one task kicks off a projection or algorithm run, and a separate task polls for completion. See the async execution docs · Read the production pipeline guide
HITS and topological link prediction algorithms
, available via
gds.hits
and
gds.topological_link_prediction
Per-algorithm AGA session memory estimation
:
GdsSessions.estimate
now takes an
algorithms
parameter, so you can estimate memory for individual algorithms instead of a given category (docs)
FastPath
: the algorithm for turning event sequences into embeddings, announced separately

Heads up — this release also renames the AGA projection methods:

The 1.x to 2.0 migration guide covers all breaking changes, make sure to update your scripts before upgrading.

Note: GDS Python Client 2.0 also updates AuraDS Enterprise and the AuraDB Pro Analytics Plugin; see the full changelog for everything included.