{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/5"}],"enrichment":{"capability":"Flupy provides a fluent interface for lazy evaluation of operations on Python iterables, allowing you to chain transformations like map, filter, and chunk while processing data in constant memory regardless of input size.","skillfed_tags":["lazy-evaluation","functional-programming","stream-processing"],"use_cases":["Process infinite or very large sequences (like itertools.count) without exhausting memory by chaining transformations.","Build readable, chainable data transformation pipelines in place of nested loops or complex list comprehensions.","Filter, map, and chunk streaming data in a shell script using the flupy CLI tool.","Prototype data processing logic that could later scale to Spark without rewriting the pipeline structure.","Combine multiple lazy operations (e.g., map \u2192 filter \u2192 chunk \u2192 take) while keeping intermediate results as generators."],"what_it_does":"Flupy is a lightweight, zero-dependency Python library that implements a fluent interface for working with iterables. It lets you chain operations like map, filter, chunk, and take in a readable, method-chaining style while maintaining lazy evaluation\u2014all transformations are generators that process data on-demand rather than loading everything into memory at once.\n\nThe library is designed as a pure-Python alternative to Apache Spark for scenarios where you need expressive, memory-efficient data pipelines without external dependencies. It supports both library usage (importing `flu` and chaining methods) and command-line usage through a `flu` shell command that applies the same lazy pipeline syntax to file or stdin input.","worth_installing":"Yes. Flupy is a low-friction, well-maintained library with zero dependencies, permissive licensing, and no known vulnerabilities. Install it if you want readable, chainable lazy evaluation for iterables without the overhead of larger frameworks. It's particularly useful for memory-constrained scenarios or when you prefer functional-style pipelines over imperative loops."},"id":"flupy","links":{"html":"https://skillfed.io/packages/flupy","md":"https://skillfed.io/packages/flupy.md","pypi":"https://pypi.org/project/flupy/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-18","license_spdx":"MIT","license_treatment":"permissive","name":"flupy","python_support":"supports_current","summary":"Fluent data processing in Python - a chainable stream processing library for expressive data manipulation using method chaining"},"popularity":{"monthly_downloads":1835286,"position":3503,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"1.2.4"}