How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
Swift Algorithms is a library of sequence and collection algorithms for Swift, providing operations for splitting, cycling, combining, and sampling collections with lazy evaluation. It extends Swift's standard library with algorithms that work across all types conforming to Sequence and Collection protocols, enabling efficient data processing without intermediate storage.
The main features of apple/swift-algorithms are: Swift Collection Extensions, Collection Combinatorics, Generic Monomorphisation, Lazy Sequences, Combinatorial Generators, Generic Data Abstractions, Generator-Based Iterators, Copy-On-Write Proxying.
Projects with overlapping indexed features include: more-itertools/more-itertools — more-itertools is an extension library for the Python itertools module. It serves as a toolkit for manipulating… ankurp/dollar — Dollar is a functional programming library for Swift that provides a comprehensive toolkit for collection… morelinq/morelinq — MoreLINQ is a functional programming toolkit and extension library for .NET that augments LINQ to Objects with… pytoolz/toolz — Toolz is a Python library that implements functional programming utilities for iterable transformation, dictionary… aimeos/map — This PHP data collection library is a functional data wrapper and array manipulation framework. It converts arrays,… azl397985856/leetcode — This project is a curated educational resource and solution repository for algorithmic challenges, specifically…
more-itertools is an extension library for the Python itertools module. It serves as a toolkit for manipulating iterables, providing a wide range of routines for data transformation, combinatorial generation, and iterator state management. The library distinguishes itself through advanced state management and complex sequence generation. It provides capabilities for peeking at future elements, seeking within sequences, and producing unique permutations, combinations, and set partitions from collections that may contain duplicate elements. Its broader capability surface covers data processing
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 capab
MoreLINQ is a functional programming toolkit and extension library for .NET that augments LINQ to Objects with advanced operators for sequence manipulation and analysis. It provides a set of tools for declarative data transformation, leveraging lazy evaluation and composition to handle complex object sequences. The library is distinguished by its specialized capabilities for combinatorial generation, including the production of permutations, subsets, and Cartesian products. It also provides advanced sequence joining options, such as full, left, and right outer joins, and supports complex data
This PHP data collection library is a functional data wrapper and array manipulation framework. It converts arrays, JSON strings, and iterables into chainable collection objects designed for advanced filtering, sorting, and transformation. The library is distinguished by its ability to dynamically extend functionality through the registration of custom methods via closures. It also provides specialized capabilities for hierarchical data modeling, allowing flat datasets with parent-child identifiers to be reconstructed into nested tree structures. The toolkit covers a broad surface of data ma