first commit

test.py

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+from clearml import PipelineDecorator
+
+@PipelineDecorator.component(cache=True, execution_queue="default")
+def step(size: int):
+    import numpy as np
+    return np.random.random(size=size)
+
+@PipelineDecorator.pipeline(
+    name='ingest',
+    project='data processing',
+    version='0.1'
+)
+def pipeline_logic(do_stuff: bool):
+    if do_stuff:
+        return step(size=42)
+
+if __name__ == '__main__':
+    # run the pipeline on the current machine, for local debugging
+    # for scale-out, comment-out the following line (Make sure a
+    # 'services' queue is available and serviced by a ClearML agent
+    # running either in services mode or through K8S/Autoscaler)
+    PipelineDecorator.run_locally()
+
+    pipeline_logic(do_stuff=True)