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GraphForge v0.3.10: Analytics Integration

GraphForge v0.3.10 made the engine easier to integrate with analytical and agentic graph workflows.

GraphForge v0.3.10: Analytics Integration visual summary

Open Source release

GraphForge is Curate Labs work, released through the DecisionNerd open-source organization. This post is a release note for embedded graph tooling and analytical Python workflows.

GraphForge v0.3.10 was an integration release.

After the TCK and performance push, this release added affordances that make GraphForge easier to embed in analytical, data pipeline, and agentic workflows.

What Shipped

  • Schema introspection with `labels()`, `relationship_types()`, `node_count()`, and `relationship_count()`

  • JSON export and import with roundtrip testing

  • `merge_node()` safe upsert with create/match semantics

  • `add_graph_documents()` for LangChain-compatible duck-typed ingestion

  • Parse/plan LRU cache with `cache_info()` and `clear_cache()`

  • Fixes for aliased `RETURN DISTINCT`, WITH-boundary variable reuse, and EXISTS edge cases

  • Analytics integration documentation

Why it matters

This is the sort of release that makes a library easier to compose. Introspection, import/export, safe upsert, and document ingestion are all practical bridges between graph storage and the rest of a modern data system.

Source

GraphForge v0.3.10: Analytics Integration | Curate Labs