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ankurp avatar

ankurp/Dollar

0
View on GitHub↗
4,240 stele·362 fork-uri·Swift·MIT·8 vizualizăriwww.dollarswift.org↗

Dollar

Dollar este o bibliotecă de programare funcțională pentru Swift care oferă un toolkit cuprinzător pentru manipularea colecțiilor, procesarea șirurilor, calcule matematice și gestionarea datei și orei. Servește ca o suită de utilitare pentru filtrarea, agregarea și restructurarea array-urilor și dicționarelor.

Proiectul implementează tipare de programare funcțională precum currying, memoization și compunerea funcțiilor. De asemenea, dispune de o interfață wrapper înlănțuibilă care permite aplicarea secvențială a mai multor transformări de date înainte de extragerea unui rezultat final.

Biblioteca acoperă o gamă largă de domenii de capabilități, inclusiv igienizarea textului și conversia de carcase (casing), operațiuni cu expresii regulate și calculul valorilor matematice precum factoriale și divizori. Include, de asemenea, instrumente pentru parsarea timestamp-urilor Unix și calcularea decalajelor de timp relative.

Toolkit-ul extinde tipurile bibliotecii standard Swift cu metode generice pentru transformarea și agregarea datelor.

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.
  • Collection Element Transformations - Maps, flattens, or chunks elements into new formats and structures using callback functions.
  • Collection Filtering - Creates new collections based on specific keys or by removing duplicate and empty values.
  • Collection Groupings - Organizes collection elements into dictionaries based on callback functions or frequency counts.
  • Dictionary Extraction and Cleaning - Extracts keys and values, merges dictionaries, or clones them while filtering specific keys.
  • Dictionary Manipulation Utilities - Creates shallow clones of dictionaries by picking or omitting keys and merging multiple dictionaries.
  • Dictionary Key Management - Provides utilities to extract dictionary keys and values or create clones by picking specific keys.
  • Dictionary Merging - Combines multiple dictionaries into one where newer values override previous ones for the same key.
  • Function Chaining - Implements function composition allowing the output of one function to feed as input into the next.
  • Function Currying - Implements functional patterns for currying and partial application to fix specific function arguments.
  • Functional Utility Libraries - Ships a collection of functional programming primitives and collection manipulation tools for Swift.
  • Generic Collection Utilities - Extends Swift standard library types with generic methods for type-safe data transformation and aggregation.
  • Element Search - Locates the first or last element, or the index of a value, that matches a condition.
  • Collection Wrappers - Implements a fluent, chainable wrapper interface for applying sequential transformations to data collections.
  • Function Currying - Implements function currying to transform functions to accept arguments individually through successive calls.
  • Swift String Manipulation Libraries - Offers a toolkit for sanitizing text and converting casing styles natively in Swift.
  • Swift String Processing Libraries - Provides a comprehensive toolkit for sanitizing, formatting, and transforming text strings in Swift.
  • Function Execution Wrappers - Provides wrappers to control function invocation, including executing a function once or applying memoization.
  • Functional Programming - Implements functional programming patterns including currying, memoization, and composition for Swift.
  • Functional Programming Wrappers - Implements functional programming patterns such as currying, partial application, and memoization to control logic execution.
  • Function Composition - Provides tools for combining multiple independent functions into a single composite execution pipeline.
  • Regex Pattern Matching - Provides regular expression operations to match patterns and extract substrings from text.
  • Collection Restructuring - Reorganizes data into new formats such as chunks, flat lists, transposed matrices, or grouped dictionaries.
  • Predicate-Based Filtering - Employs callback functions as predicates to isolate, search, and partition elements within arrays and dictionaries.
  • Array Set Operations - Computes intersections, unions, and differences between multiple arrays to find unique or shared values.
  • Collection Property Plucking - Extracts specific properties from every member of a collection into a new array.
  • Date and Time Libraries - Provides utilities for parsing, validating, and manipulating date and time values.
  • Date Object Creators - Provides utilities for generating date and time objects from Unix timestamps and relative helpers.
  • Collection Sum Calculators - Computes the minimum, maximum, or sum of values within a collection.
  • Ordered Collection Manipulations - Shuffles elements, creates ranges, or retrieves subsets from the start or end of a collection.
  • Text String Cleaning - Provides tools for cleaning string data by removing whitespace and splitting text into arrays.
  • Date and Time Utilities - Provides utility helpers for parsing Unix timestamps and calculating relative time offsets.
  • Regular Expression Utilities - Tests strings against patterns and extracts substrings using regular expression operations.
  • String Case Transformers - Provides utilities for converting text between different naming conventions and sanitizing input.
  • Casing Formatters - Converts strings between camelCase, kebab-case, snake_case, and Start Case formats.
  • Function Invocation Control - Controls function execution flow using currying, composition, and execution limits.
  • Collection Intersections - Identifies intersections and common elements shared across multiple collections.
  • Unix Epoch Conversions - Translates integer Unix timestamps and formatted strings into date objects.
  • Discrete Algorithm Implementations - Provides a set of discrete mathematical procedures for computing factorials, divisors, and random numeric sequences.
  • Discrete Math Utilities - Computes factorials, greatest common divisors, least common multiples, and generates random numbers.
  • Discrete Math Utility Libraries - Implements mathematical procedures for computing factorials, divisors, and random numeric sequences.
  • GCD and LCM Calculators - Includes calculators for the greatest common divisor and least common multiple of integers.
  • Integer Mathematical Utilities - Provides calculations for factorials, divisors, and random integer generation.
  • Number Sequence Generation - Creates arrays of numbers based on defined ranges, specific increments, or arbitrary sequences.
  • Numerical Sequence Generation - Generates arrays of numbers progressing from a start point to an end point.
  • Collection Partitioning - Shuffles, chunks, or partitions array elements into groups based on size or callback functions.
  • Data Structures - Functional tool-belt for Swift collections.
  • General Utilities - Functional programming utilities similar to Lo-Dash.

Istoric stele

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Întrebări frecvente

Ce face ankurp/dollar?

Dollar este o bibliotecă de programare funcțională pentru Swift care oferă un toolkit cuprinzător pentru manipularea colecțiilor, procesarea șirurilor, calcule matematice și gestionarea datei și orei. Servește ca o suită de utilitare pentru filtrarea, agregarea și restructurarea array-urilor și dicționarelor.

Care sunt principalele funcționalități ale ankurp/dollar?

Principalele funcționalități ale ankurp/dollar sunt: Swift Collection Extensions, Transformation Chains, Array Transformations, Element Filtering, Collection Element Transformations, Collection Filtering, Collection Groupings, Dictionary Extraction and Cleaning.

Care sunt câteva alternative open-source pentru ankurp/dollar?

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