Pipeline configs

A pipeline configuration is necessary to instantiate a Pipeline. To create a taipy.core.taipy.PipelineConfig you can use the Config.configure_pipeline() method with the following parameters:

  • id: The id of this new pipeline configuration. This id is mandatory and must be a unique and valid Python variable name.
  • tasks: The list of tasks configurations.
  • properties: A dictionary of additional properties.
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from taipy import Config

def double(nb):
    return nb * 2

input_data_node_config = Config.configure_data_node("input", default_value=21)
output_data_node_config = Config.configure_data_node("output")
task_config = Config.configure_task("double_task", double, input_data_node_config, output_data_node_config)

pipeline_cfg = Config.configure_pipeline("my_pipeline", [task_config])

In the previous code example, in line 10, we create a pipeline configuration with the id "my_pipeline" and made of a single task configuration task_config.

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from taipy import Config

def double(nb):
    return nb * 2

input_data_node_config = Config.configure_data_node("input", default_value=21)
intermediate_data_node_config = Config.configure_data_node("intermediate")
output_data_node_config = Config.configure_data_node("output")
first_task_config = Config.configure_task("first_double_task", double, input_data_node_config, intermediate_data_node_config)
second_task_config = Config.configure_task("second_double_task", double, intermediate_data_node_config, output_data_node_config)

other_pipeline_cfg = Config.configure_pipeline("another_pipeline", [first_task_config, second_task_config])

In this second code example, in line 12, we create a pipeline configuration with the id "another_pipeline" and made of the two task configuration created in lines 9 and 10 first_task_config and second_task_config.

Note

Note that the order of the task_config in the list does not matter. The two following lines are equivalent.

pipeline_cfg = Config.configure_pipeline("pipeline", [first_task_config, second_task_config])
pipeline_cfg = Config.configure_pipeline("pipeline", [second_task_config, first_task_config])

The next section introduces the scenario configuration.