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Example 8: Multi-Edge Weights with Filters and dress Transforms

This example ingests ticker CSV data into Neo4j with:

  • Two vertex types — ticker (by oftic) and metric (by name + value), where metric rows are filtered so only Open, Close, and Volume with positive values become vertices.
  • One edge — ticker → metric with multiple weights (direct on t_obs plus nested vertices metadata on the metric endpoint).
  • Transforms with dress — round_str and int transforms targeted at specific (name, value) pairs via dress: { key: name, value: value }, plus a date parse that emits t_obs.

Layout

  • examples/8-multi-edges-weights/manifest.yaml — logical schema, DB profile (Neo4j indexes, edge specs), transforms, and ticker_data resource pipeline.
  • examples/8-multi-edges-weights/ingest.py — FileConnector + Bindings, then GraphEngine.define_and_ingest(...).
  • examples/8-multi-edges-weights/data.csv — sample OHLCV-style rows.

Run locally

From the example directory, with Neo4j running (see repo docker/neo4j), run:

uv run python ingest.py
  • Polymorphic routing (Example 7) uses vertex_router + dynamic edge for type-discriminated tables; this example uses filters on a vertex type and multi-weight edges instead.