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Core API Quickstart

Strata Core is the programmatic materialization and artifact layer. Use this if you want the materialize() API, artifact caching, lineage, and executor integration.

The primitive

materialize(inputs, transform) → artifact

This gives you:

  • Immutable, versioned artifacts
  • Provenance-based deduplication (same inputs + transform = cache hit)
  • Explicit lineage
  • Safe reuse across runs and processes

1. Start the server

uv run strata-server

2. Run the demo

uv run python examples/hello_world.py

This creates a demo Iceberg table and exercises the cold → warm → restart cache path.

3. Materialize a result

from strata.client import StrataClient

client = StrataClient()

artifact = client.materialize(
    inputs=["file:///warehouse#db.events"],
    transform={
        "executor": "scan@v1",
        "params": {
            "columns": ["id", "value"],
            "filters": [{"column": "value", "op": ">", "value": 100}],
        },
    },
)

print(f"URI: {artifact.uri}")
print(f"Cache hit: {artifact.cache_hit}")

4. Fetch the result

table = client.fetch(artifact.uri)
df = table.to_pandas()

5. Integration with data libraries

from strata.integration.pandas import fetch_to_pandas
df = fetch_to_pandas("file:///warehouse#db.events")

from strata.integration.polars import fetch_to_polars
df = fetch_to_polars("file:///warehouse#db.events")

from strata.integration.duckdb import StrataScanner
with StrataScanner() as scanner:
    scanner.register("events", "file:///warehouse#db.events")
    result = scanner.query("SELECT * FROM events WHERE id > 100")

Core behaviors

  • Same inputs + transform → existing artifact, no recomputation
  • Artifacts are immutable and versioned
  • Names are mutable pointers to specific artifact versions
  • Provenance hash is derived from pinned inputs and transform identity

What's next