Pipederived

Pipederived is a Python library designed to facilitate the creation of data pipelines. It aims to simplify the process of chaining together data processing steps, making complex workflows more manageable and readable. The core concept behind pipederived is the idea of a "pipeline" object, which acts as a container for a sequence of operations.

Each operation in the pipeline is represented by a callable, typically a function or a method. When data is passed to the pipeline object, it is sequentially processed by each callable in the order they were added. The output of one callable becomes the input for the next. This allows for a clear, step-by-step transformation of data.

Pipederived offers features such as error handling within the pipeline, the ability to branch and merge pipelines, and options for parallel execution of certain stages. It is particularly useful for tasks involving data cleaning, feature engineering, and model training where multiple sequential transformations are common. The library promotes a functional programming style, encouraging immutability and the creation of small, reusable processing units. Its design prioritizes clarity and maintainability of data processing code.