Dollar

Dollar is a functional programming library for Swift that provides a comprehensive toolkit for collection manipulation, string processing, mathematical calculations, and date and time management. It serves as a utility suite for filtering, aggregating, and restructuring arrays and dictionaries.

The project implements functional programming patterns such as currying, memoization, and function composition. It also features a chainable wrapper interface that allows multiple data transformations to be applied sequentially before extracting a final result.

The library covers a wide range of capability areas, including text sanitization and casing conversion, regular expression operations, and the calculation of mathematical values like factorials and divisors. It also includes tools for parsing Unix timestamps and calculating relative time offsets.

The toolkit extends Swift standard library types with generic methods for data transformation and aggregation.

Features

Swift Collection Extensions - Extends Swift arrays and dictionaries with generic methods for advanced manipulation and transformation.
Transformation Chains - Wraps collections in a proxy object to apply multiple sequential transformations before extracting the final result.
Array Transformations - Maps array elements to new values or flattens nested collections into a single-level array.
Element Filtering - Provides predicate-based filtering to create subsets of arrays or remove empty values.

pytoolz/toolz

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Toolz is a Python library that implements functional programming utilities for iterable transformation, dictionary manipulation, function composition, and lazy evaluation. It provides a set of pure functions designed to work with Python's built-in data structures, enabling concise and composable data processing workflows. What distinguishes toolz is its support for curried partial application, allowing functions to be incrementally applied and reused. It includes dictionary-centric operations that handle nested structures, and offers iterable chain transformers that combine mapping, filtering

ramda/ramda

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Ramda is a functional JavaScript standard library and toolset for immutable data transformation and composition. It provides a comprehensive suite of pure utility functions designed to enable declarative data processing pipelines. The library is distinguished by its use of automatic function currying and a data-last argument order. These design patterns allow multi-argument functions to be partially applied, simplifying the construction of processing chains where data is passed through a sequence of operations. The toolkit covers broad data manipulation capabilities, including list processin

lodash/lodash

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Lodash is a JavaScript utility library and data manipulation toolkit. It provides a collection of modular functions for transforming, filtering, and validating arrays, objects, strings, and numbers. The project functions as a functional programming toolkit, offering capabilities for function composition, currying, and lazy evaluation. It includes mechanisms for execution control, such as debouncing and throttling, to manage the timing and frequency of function invocations. The library covers a broad surface of data operations, including deep cloning and merging of complex nested structures,

sodiray/radash

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Radash is a TypeScript functional utility library designed for data transformation, validation, and workflow management. It provides a collection of typed helper functions to manipulate arrays, objects, and strings. The project features an asynchronous workflow toolkit for managing promises, retries, and concurrency limits, alongside a suite of boolean validators for verifying primitive types, objects, and promises. It also implements functional programming patterns such as function composition, partial application, and error-first response patterns. The library covers a broad surface of cap

ankurpDollar

Features