Open-source alternatives to Stdlib

This repository is a collection of JavaScript coding challenges and a comprehensive interview guide. It provides reference implementations and educational examples designed to help developers master language fundamentals and prepare for technical interviews. The project covers a wide array of specialized implementations, including functional programming patterns like currying and partial application, as well as asynchronous patterns for concurrency control. It also includes practical examples of Document Object Model manipulation and the implementation of common data structures such as stacks

Returns is a functional programming library for Python that provides type-safe containers for managing state, error handling, and optionality. It serves as a monadic container library and a type-safe error handling framework, replacing traditional try-catch blocks and null checks with Result and Optional containers to treat exceptions as data. The project is distinguished by its use of a specialized Mypy static analysis plugin to validate functional pipelines and emulate higher kinded types. It provides mechanisms for isolating side effects through IO containers and offers a framework for typ

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

Underscore is a JavaScript utility library providing a suite of functional programming and data manipulation helpers. It serves as a framework for transforming data collections, composing functions, managing objects, and performing precise data type validation without modifying core language prototypes. The project includes a functional programming toolkit designed to control function execution timing and behavior through techniques such as debouncing, throttling, and partial application. It also provides a dedicated object manipulation utility for cloning, merging, picking, and omitting prop

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

Just is a collection of JavaScript utility libraries designed for data manipulation, functional programming, performance optimization, statistical analysis, and string processing. It provides a set of tools for deep cloning, filtering, and transforming complex objects and arrays. The project is structured as a series of zero-dependency modules, allowing utilities to be used independently to minimize bundle size. It implements functional programming patterns including currying, piping, and partial application, and provides execution control through memoization, debouncing, and throttling. The

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

collect.js is a dependency-free JavaScript library that provides a fluent, chainable interface for manipulating arrays and objects. It mirrors the Laravel Collection API, offering a consistent set of methods for data transformation across JavaScript and Laravel backend environments. The library stores collection data as plain arrays internally and supports fluent method chaining, where each method returns a new collection instance. The library distinguishes itself by closely replicating the Laravel Collection API in JavaScript, mapping each PHP method to an equivalent JavaScript implementatio

This is an interactive notebook-based course that teaches machine learning from Python fundamentals through deep learning and natural language processing. It uses real datasets and multiple frameworks within a structured, hands-on curriculum that combines concise explanations with executable code cells, built-in datasets, and embedded exercise checkpoints. Learning progresses through data preparation and exploration, classical machine learning workflows, computer vision with convolutional neural networks, and natural language processing with deep learning, all delivered as a cohesive progressi

NumPy is a foundational library for scientific computing in Python, providing a comprehensive framework for managing and manipulating large-scale numerical information. It centers on high-performance multidimensional array objects that serve as the primary data structure for complex mathematical operations and data analysis workflows. The library distinguishes itself through specialized mechanisms for handling multidimensional data, including advanced indexing, slicing, and broadcasting techniques that allow for efficient operations across arrays of varying shapes. It utilizes strided metadat

CuPy is a CUDA array computing library that implements a NumPy-compatible interface for executing array operations and numerical computing on NVIDIA GPUs. It serves as a GPU-accelerated numerical library and a CUDA-based SciPy implementation, offloading heavy calculations to graphics hardware to increase processing speed for scientific and engineering workloads. The library enables multi-framework tensor exchange, allowing data buffers to be shared between different deep learning frameworks using standardized memory layouts to avoid memory copies. It also supports custom GPU kernel integratio

Remeda is a type-safe functional utility library for TypeScript designed for building data transformation pipelines. It provides a toolkit of helper functions for manipulating arrays and objects while maintaining strict type integrity throughout the process. The library is characterized by its support for both data-first and data-last calling styles. It utilizes lazy evaluation to process data collections, evaluating transformations only when the final result is requested to avoid creating intermediate collection copies. The toolkit covers collection manipulation, function composition, and t

Functional-Light-JS is a JavaScript functional programming library designed to implement functional patterns within JavaScript applications. It serves as a toolkit for declarative data processing, immutable data management, and the construction of complex logic through higher-order functions. The library focuses on a pragmatic implementation of functional programming, providing utilities for curried argument application and function composition. It emphasizes the use of pure functions to calculate state updates and manage application data without side effects. The project covers broad capabi

Pkl is a configuration-as-code language used to define, validate, and generate structured configuration files. It functions as a type-safe configuration generator that enforces data integrity through a strongly-typed schema, ensuring configuration values meet defined constraints and types during evaluation. The project distinguishes itself by acting as both a configuration file generator and a binding generator. It transforms high-level programmable definitions into static formats such as JSON, YAML, or XML, and produces language-specific source code to synchronize settings and provide type s

The ECMAScript specification is the formal standard defining the syntax, semantics, and execution model that all JavaScript implementations must follow. It establishes the official language rules through a combination of formal grammar and step-by-step algorithmic prose. The project manages the technical evolution of the language via a consensus-driven governance framework and a staged proposal pipeline. This process tracks features from initial design through expert reviewer sign-off and committee approval. A specification-as-code toolchain compiles these formal definitions and algorithmic d

GluonTS is a probabilistic time series library and deep learning forecasting framework. It provides a toolkit for building, training, and evaluating neural network architectures that predict future values as probability distributions to quantify uncertainty. The project distinguishes itself by supporting zero-shot forecasting and integrating diverse modeling approaches, including deep probabilistic neural networks and wrappers for external statistical libraries such as Prophet and R forecast. It implements specialized architectural primitives like causal convolutions and invertible residual n

Torch7 is a scientific computing environment and tensor computation library used for deep learning research and numerical analysis. It functions as a Lua-based framework for training neural networks and learning agents, providing a toolkit for implementing architectures and training through reinforcement learning algorithms. The project is distinguished by its tight integration with C, utilizing a binding layer to map high-level scripting to low-level C structures for direct memory access. It supports hardware-accelerated computation by offloading linear algebra and convolution operations to

This project is a comprehensive educational resource and tutorial handbook for building, training, and deploying machine learning models using TensorFlow 2. It serves as a structured learning guide covering core deep learning concepts, including neural network architectures, automatic differentiation, and tensor operations. The handbook provides technical guidance on optimizing execution efficiency through GPU memory management, distributed training, and model quantization. It also includes detailed manuals for constructing high-performance data pipelines and exporting models for production s

doctest is a unit testing framework and assertion library for C++ delivered as a single-header library. It provides a test runner with a command line interface to execute tests, filter test suites, and generate execution reports. The framework supports in-source unit testing and allows for the complete removal of testing logic from compiled binaries via preprocessor stripping to eliminate performance overhead in production environments. It also enables cross-binary test registry sharing, allowing one executable to utilize the test runner of another. Capabilities include parameterized testing

Mapperly is a C# source generator used for high-performance object-to-object mapping in .NET. It functions as a compile-time mapping library that produces the necessary transformation code during the build process, eliminating the need for runtime reflection when converting between domain models and data transfer objects. The tool distinguishes itself by providing type-safe diagnostic validation and strict mapping enforcement, emitting warnings for unmapped properties at compile time. It includes specialized capabilities for circular reference handling and deep cloning to maintain object iden

quant-wiki is a comprehensive knowledge base and structured reference for quantitative finance, financial engineering, and algorithmic trading. It serves as a centralized library of documentation covering mathematical models, financial instruments, and systematic trading strategies. The project integrates AI-driven capabilities through a modular retrieval-augmented generation framework that extracts structured data from research papers and news. It features a multi-agent workflow engine designed to discover and validate predictive alpha factors, alongside tools for local large language model

This project is a comprehensive educational suite of coding challenges and implementation guides focused on JavaScript. It provides a collection of programmatic exercises and interview questions designed to practice core logic and algorithms. The repository serves as a test-driven development workbook, pairing coding problems with test suites to verify the correctness of implemented solutions. It includes a specific framework for exercise solution verification and the integration of asynchronous logic into automated testing flows. The content covers a wide range of computer science building

ts-toolbelt is a collection of specialized utilities for manipulating and validating TypeScript types. It provides a toolkit for performing complex transformations on objects, unions, and functions to enforce strict data consistency at compile time. The library features dedicated transformers for function types, including utilities for currying, composition, and signature extraction. It also includes an object type manipulator for deep merging, patching, and reshaping complex structures. The capability surface extends to literal string processing, type-level arithmetic, and tuple operations.

This project is a localized educational resource for learning the Rust programming language, providing a comprehensive guide and technical specifications translated into Simplified Chinese. It serves as an instructional tool for studying language idioms, memory management, and type systems. The repository focuses on software documentation localization, converting official guides into Simplified Chinese to increase accessibility for non-English speakers. It utilizes a markdown-based system to organize content and supports multi-format export to static HTML, PDF, and EPUB formats for both web a

Smile is a comprehensive JVM machine learning library and statistical computing toolkit. It provides a suite of algorithms for classification, regression, and clustering, implemented natively for Java, Scala, and Kotlin. The project also functions as a deep learning framework, a natural language processing library, and an inference engine for large language models. The library distinguishes itself through GPU acceleration via LibTorch bindings and support for the ONNX model interchange format. It includes specialized capabilities for large language model inference, featuring Byte-Pair Encodin

This project is a technical interview preparation resource focused on JavaScript. It provides a collection of common technical questions, detailed answers, and conceptual quizzes designed to help users master core language fundamentals and browser APIs. The resource utilizes an interactive infrastructure that includes a coding workspace with in-browser runtime execution and an automated test suite to validate code correctness. It organizes content through curated learning paths and modular concept mapping to decompose complex language fundamentals into searchable study modules. The curriculu

Go Package of validators and sanitizers for strings, numerics, slices and structs