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Define pipeline

Without any orchestrator, the simplest pipeline could be the below functions:

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def generate():
    ...
    # write some files, data.csv
    ...
    # return objects or simple python data types.
    return x, y

def consume(x, y):
    ...
    # read from data.csv
    # do some computation with x and y


# Stich the functions together
# This is the driver pattern.
x, y = generate()
consume(x, y)

Runnable representation

The same workflow in runnable would be:

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from runnable import PythonTask, pickled, catalog, Pipeline

generate_task = PythonTask(name="generate", function=generate,
                returns=[pickled("x"), y],
                catalog=Catalog(put=["data.csv"])

consume_task = PythonTask(name="consume", function=consume,
                catalog=Catalog(get=["data.csv"])

pipeline = Pipeline(steps=[generate_task, consume_task])
pipeline.execute()
  • runnable wraps the functions generate and consume as tasks.
  • Tasks can access and return parameters.
  • Tasks can also share files between them using catalog.
  • Tasks are stitched together as pipeline
  • The execution environment is configured via # todo

Examples

All the concepts are accompanied by examples.