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Neo4j Graph Data Science Client
Product Version
    • Introduction
    • Installation
    • Getting started
    • Aura Graph Analytics Serverless
    • The graph object
    • Running algorithms
    • Machine learning pipelines
    • Model objects from the model catalog
    • Datasets
    • Relationship embedding models
    • Coordinate parallel transactions
    • Visualization
    • Tutorials
      • Graph construct: Import from Pandas
      • Product recommendations with kNN based on FastRP embeddings
      • PyG integration: Sample and export
      • Centrality Algorithms
      • Community Detection
      • Machine learning pipelines: Node classification
      • Node Regression with Subgraph and Graph Sample projections
      • Node classification with HashGNN
      • Knowledge graph embeddings: Training in PyG, prediction with GDS
      • Graph Analytics Serverless for AuraDB
      • Graph Analytics Serverless for Self-Managed Neo4j DB
    • Known limitations
    • API Reference

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  • Known limitations
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Known limitations

Operations known to not work with the Python client are:

  • Numeric utility functions (will never be supported)

  • Running Cypher queries on GDS (functionality deprecated in GDS 2.6)

The GDS Python client is not compatible with Python’s multiprocessing or any operations that rely on forking. If running queries in parallel is required, multithreading can be used instead.

Graph Analytics Serverless for Self-Managed Neo4j DB

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