{"categories":[{"label":"Application Frameworks","url":"https://skillfed.io/packages/category/software-development-libraries-application-frameworks/4"}],"enrichment":{"capability":"fasttransform provides a Transform class for building reusable, composable data transformations with support for reversibility, type-based dispatch, and type preservation.","skillfed_tags":["data-pipeline","type-dispatch","reversible-transform"],"use_cases":["Build reversible normalization transforms that can both encode data (e.g., z-score) and decode predictions back to original scale.","Handle heterogeneous input types in a pipeline by defining type-specialized encode functions that dispatch automatically.","Compose multiple transforms into a Pipeline for end-to-end data processing with single encode/decode calls.","Create stateful transforms that compute aggregate properties (mean, std) during setup and apply them consistently across data.","Preserve runtime subtypes through transformations so that custom numeric types remain their original type after operations."],"what_it_does":"fasttransform is a data transformation framework that wraps functions into Transform objects, enabling them to be composed into reusable pipelines. The core idea is that a single Transform can encode data forward and decode it backward, specialize behavior based on input types, and preserve or convert types intelligently. It depends on fastcore for core utilities and plum-dispatch for type-based function selection.\n\nThe package is designed for data pipeline construction where you need transformations that are reversible (useful for normalization/denormalization), type-aware (handling multiple input formats), and composable into larger workflows. It supports decorator syntax for simple cases and class-based definition for stateful transforms that need setup phases, like computing statistics from a dataset before normalizing.","worth_installing":"Yes, if you are building data pipelines that need reversible, type-aware transformations. The low install friction, active maintenance, permissive license, and clean API make it a reasonable choice. However, verify that it fits your specific dispatch and composition needs\u2014it is still in Beta (version 0.0.2) and may not yet be production-hardened for all use cases."},"id":"fasttransform","links":{"html":"https://skillfed.io/packages/fasttransform","md":"https://skillfed.io/packages/fasttransform.md","pypi":"https://pypi.org/project/fasttransform/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2025-04-18","license_spdx":null,"license_treatment":"permissive","name":"fasttransform","python_support":"supports_current","summary":"Transform is the main building block of data pipelines in fastai. And elsewhere if you want."},"popularity":{"monthly_downloads":215996,"position":9388,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.0.2"}