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This release is a pre-release and may not be stable for production use.

SegmentStream pipeline SDK

Declare source tables with s.ingestion and warehouse SQL transformations with s.model. The SDK resolves inputs, validates explicit partitioning and capabilities, and compiles native Dagster definitions using the existing warehouse loader.

from collections.abc import Iterator

import ibis.expr.types as ir
import segmentstream as s


@s.ingestion(
    tier=s.Tier.Bronze,
    partitioning=s.Partitioning.Unpartitioned,
    schema={"amount": "float64"},
)
def orders() -> Iterator[s.IngestionRow]:
    yield {"amount": 25.0}


@s.model(
    tier=s.Tier.Gold,
    partitioning=s.Partitioning.Unpartitioned,
    schema={"total_revenue": "float64"},
)
def revenue(orders: ir.Table) -> ir.Table:
    return orders.aggregate(total_revenue=orders.amount.sum())


defs = s.definitions(
    assets=[orders, revenue],
    jobs=[s.job("revenue", assets=[revenue], include_upstream=True)],
)

The workspace documentation is organized by concept: connections, ingestion, models, partitioning, jobs, execution, checks, runtime values, and warehouse storage. The CLI bundles these same pages into every starter workspace.

s.validate(defs) checks the graph and named job configuration without executing assets. s.describe(defs) explains resolved inputs, per-asset policies, storage, capabilities, and job selections without resolving credentials. See the modular commerce starter for daily row ingestion, batched models, and a partitioned check.

Compatibility

segmentstream.dagster retains its native exports. Native assets and high-level declarations can coexist in s.definitions. Root s.resource and s.IngestionResource remain available for legacy ingestion. Import their helpers from segmentstream; the old public segmentstream.ingestion module is retired so s.ingestion can be the decorator. Migration examples cover the mapping and IO defaults.

Releases

This change targets 0.1.0a20. Publish the SDK before releasing a CLI whose starter pins it. PyPI versions are immutable; do not republish an existing version.

The protected pipeline-sdk-release.yml workflow builds a wheel and source distribution from a pipeline-sdk-v<version> tag, then uses PyPI Trusted Publishing from the pypi GitHub environment. No long-lived publishing token is stored in GitHub.

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