GoldenFlow

Workflow orchestration for data pipelines.

GoldenFlow orchestrates multi-step data workflows — define dependencies, handle failures, and schedule recurring runs.

Basic Usage

import goldenflow

flow = goldenflow.Flow("nightly-dedup")
flow.add_task("profile", goldencheck.profile, "data.csv")
flow.add_task("match", goldenmatch.dedupe, "data.csv", depends_on="profile")
flow.run()

Try It

import goldenflow
flow = goldenflow.Flow("demo")
flow.add_task("profile", goldencheck.profile, "data.csv")
result = flow.run()
print(result.summary())

Task Dependencies

Tasks run in dependency order. If a task fails, downstream tasks are skipped:

flow.add_task("ingest", ingest_func)
flow.add_task("clean", clean_func, depends_on="ingest")
flow.add_task("match", match_func, depends_on="clean")
flow.add_task("export", export_func, depends_on="match")

Tip: Use flow.visualize() to see the task dependency graph.