🛡️ Reliable
Built-in fault tolerance and automatic recovery ensure your workflows complete successfully, even when individual tasks fail. Checkpoint and resume from any point in your pipeline.
🔍 Explainable
Full visibility into every step of your workflow execution. Detailed logs, lineage tracking, and clear error messages make debugging and auditing straightforward.
🚀 Scalable
Seamlessly scale from local development to production clusters. Distributed execution handles massive workloads without changing your workflow definitions.
Define Your Workflow
Intuitive Python DSLs let you define complex data pipelines.
@task(inject_context=True)
def extract(ctx: TaskExecutionContext): ...
@task
def filter_pass(data): ...
@task
def assign_grade(data): ...
@task
def load(data): ...
with workflow("hello_etl") as wf:
_ = extract >> (filter_pass | assign_grade).set_group_name("transforms") >> load
wf.execute("extract")
Learn More About Graflow
Why Graflow?
Graflow is designed to simplify complex data workflows while providing full transparency and reliability at scale.
- Intuitive Python API for workflow definitions
- Built-in monitoring and observability
- Seamless integration with existing tools
- Production-ready from day one