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Dagster connector for Floe CLI (config-driven ingestion)

Project description

Floe + Dagster

This folder contains the Dagster connector for Floe.

For local setup of both Dagster and Airflow with isolated virtual environments, see:

  • orchestrators/LOCAL_DEV.md

Current model:

  • Parse-time reads Floe manifests (floe.manifest.v1), not Floe YAML.
  • Supports single manifest and multi-manifest directory loading.
  • Builds one asset per entity and one job per manifest.
  • Runs Floe with manifest execution contract and JSON logs.
  • Publishes run/entity metadata from NDJSON + summary.

What Is Implemented

  • Manifest-first orchestration (floe.manifest.v1).
  • Strict schema validation at manifest load time.
  • Asset generation from entities[] (asset_key, group_name respected).
  • One Dagster job per manifest (stable job names).
  • Multi-manifest loading (*.manifest.json) with collision checks.
  • Local runner (local_process) support.
  • execution.defaults.env and execution.defaults.workdir support.
  • Floe quality outcomes exposed as Dagster native Asset Checks (cast_error, not_null, unique, schema_mismatch, file_status) from Floe reports.

Install

Prereqs:

  • Floe installed (either the floe CLI binary or Docker with a Floe image).
  • Python 3.10+.
pip install dagster-floe

Development install (from this repo)

python3 -m venv orchestrators/dagster-floe/.venv
source orchestrators/dagster-floe/.venv/bin/activate
pip install -e orchestrators/dagster-floe[dev]

Generate a manifest

floe manifest generate \
  -c orchestrators/dagster-floe/example/config.yml \
  --output orchestrators/dagster-floe/example/manifest.dagster.json

Run the example (repo-only)

cd orchestrators/dagster-floe
FLOE_MANIFEST_DIR=./example/manifests dagster dev

The example workspace loads example/definitions.py, which wires local example files/manifest to the reusable connector APIs. The repository example includes two manifests by domain:

  • example/manifests/hr.manifest.json
  • example/manifests/sales.manifest.json

Asset checks

Every accepted-output asset automatically gets quality checks registered in Dagster — no extra config needed. After each run, the connector reads the Floe run report and publishes pass/fail results for each entity.

Check Fails when
file_status One or more input files had a failed or error-level processing status (e.g., unreadable file, parse failure)
cast_error Type-casting failures exceeded the entity's policy threshold
not_null Null values found in non-nullable columns
unique Duplicate values found in uniqueness-constrained columns
schema_mismatch Incoming file schema is incompatible with the declared schema

Checks appear in the Dagster UI under each asset, linked to the run that produced them. A WARN-severity violation marks the check as a warning; REJECT or ABORT marks it as a failure.

Lineage integration

The connector automatically injects two environment variables into every floe subprocess:

  • DAGSTER_RUN_ID — the current Dagster run ID
  • DAGSTER_JOB_NAME — the Dagster job name

When lineage is enabled and both variables are present, floe attaches a parent facet to its OpenLineage run event. This facet declares that the Floe run is a child of the Dagster run, making the lineage graph show the full Dagster → Floe pipeline hierarchy.

The Floe run event's own job.name is derived from lineage.job_name in the embedded manifest lineage config, or from the config file stem. To control it explicitly, add job_name to your lineage block when generating the manifest:

# prod.yml (profile)
lineage:
  url: "http://marquez:5000"
  namespace: "my-data-platform"
  job_name: "orders-pipeline"   # sets job.name on the Floe OpenLineage run event
floe manifest generate -c orders.yml -p prod.yml --output manifests/orders.json

See docs/lineage.md for the full lineage config reference.

Notes

  • This connector does not parse YAML directly; it consumes floe.manifest.v1.
  • Connector logic lives under src/floe_dagster/; local wiring for demo lives in example/definitions.py.
  • For local development without an installed floe binary, you can point LocalRunner to a custom command, e.g.:
    • LocalRunner(\"cargo run -p floe-cli --\")
  • Manifest runner support in connector is currently local_process only.
  • For local setup commands, use orchestrators/LOCAL_DEV.md.
  • Design notes and future work: orchestrators/dagster-floe/INTEGRATION_SPEC.md

What Is Not Implemented Yet

  • Kubernetes/ECS runner adapters.
  • Cloud summary loading (s3://, gs://, abfs://).
  • Single-process multi-entity fan-out execution mode.

Releasing

This repo is a monorepo. Floe and this connector are versioned and tagged independently:

  • Floe CLI release tags: vX.Y.Z
  • Dagster connector release tags: dagster-floe-vX.Y.Z (triggers the PyPI publish workflow)

Example:

git checkout main
git pull
git tag dagster-floe-v0.1.0
git push origin dagster-floe-v0.1.0

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