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pipefunc is a Python library for creating and running function pipelines. By annotating functions and specifying their outputs, it forms a pipeline that automatically organizes the execution order to satisfy dependencies. Just specify the names of the outputs you want to compute, and pipefunc will handle the rest by leveraging the parameter names of the annotated functions.
Whether you're working with data processing, scientific computations, machine learning (AI) workflows, or any other scenario involving interdependent functions, pipefunc helps you focus on the logic of your code while it handles the intricacies of function dependencies and execution order.
pipefunc provides a Pipeline class that you use to define your function pipeline. You add functions to the pipeline using the pipefunc decorator, which also lets you specify the function's output name. Once your pipeline is defined, you can execute it for specific output values, simplify it by combining function nodes, visualize it as a directed graph, and profile the resource usage of the pipeline functions. For more detailed usage instructions and examples, please check the usage example provided in the package.
This example demonstrates defining a pipeline with f_c, f_d, f_e functions, accessing and executing these functions using the pipeline, visualizing the pipeline graph, getting all possible argument mappings, and reporting on the resource usage. This basic example should give you an idea of how to use pipefunc to construct and manage function pipelines.
