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Getting Started

Install

pip install fabric-data-pipelines
# or
uv add fabric-data-pipelines

Requires Python 3.10+.

Build your first pipeline

from fabric_data_pipelines import Notebook, Pipeline, Wait

wait = Wait(name="Wait_For_Upstream", wait_time_in_seconds=30)
transform = Notebook(
    name="Transform_Silver_Sales",
    notebook_id="00000000-0000-0000-0000-000000000002",
    workspace_id="00000000-0000-0000-0000-000000000001",
)

wait.then(transform)

pipeline = Pipeline(
    name="Daily_Silver_Sales_Transform",
    activities=[wait, transform],
)
pipeline.save("daily_silver_sales_transform.json")

This creates a Fabric-compatible pipeline definition without hand-writing the nested JSON payload.

Understand the building blocks

Most pipelines follow the same pattern:

  1. Create activities such as Wait, Notebook, Copy, or Script.
  2. Declare the execution order with .then(), .after(), or >>.
  3. Build a Pipeline.
  4. Export either a JSON definition or a Fabric item folder.

Choose your export shape

Save a pipeline definition

json_text = pipeline.to_json()
pipeline.save("daily_silver_sales_transform.json")

Save a Fabric item folder

pipeline.save_item("out")

That writes a Daily_Silver_Sales_Transform.DataPipeline/ folder containing pipeline-content.json, .platform, and .schedules when schedules are configured.

Run the examples

uv run python examples/daily_notebook_transform.py
uv run python examples/landing_truncate_copy.py
uv run python examples/scheduled_gold_refresh.py

Next steps