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13 repositorios

Awesome GitHub RepositoriesStream Combinators

Operators for merging, concatenating, or zipping multiple data sources into a single unified stream.

Distinct from Stream Composition: Focuses on generic functional combinators (zip, merge, concat) rather than API-specific stream composition.

Explore 13 awesome GitHub repositories matching web development · Stream Combinators. Refine with filters or upvote what's useful.

Awesome Stream Combinators GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • reactive-extensions/rxjsAvatar de Reactive-Extensions

    Reactive-Extensions/RxJS

    19,353Ver en GitHub↗

    The Reactive Extensions for JavaScript

    Apply operators that map, filter, merge, or otherwise manipulate emitted items in a declarative chain.

    JavaScript
    Ver en GitHub↗19,353
  • zhisheng17/flink-learningAvatar de zhisheng17

    zhisheng17/flink-learning

    15,071Ver en GitHub↗

    This project is a collection of educational resources and reference implementations for the Apache Flink stream processing framework. It provides a learning resource focused on mastering distributed stream processing through implementation guides, performance tuning tutorials, and practical examples. The repository features detailed walkthroughs for building real-time data pipelines using the DataStream and Table APIs. It includes specific integration examples for connecting Apache Flink with Kafka brokers and Elasticsearch indices, as well as reference implementations for real-time deduplica

    Implements stream join operators to merge multiple unbounded data streams based on shared keys.

    Javaclickhouseelasticsearchflink
    Ver en GitHub↗15,071
  • kaushikgopal/rxjava-android-samplesAvatar de kaushikgopal

    kaushikgopal/RxJava-Android-Samples

    7,504Ver en GitHub↗

    This project is a sample library and implementation guide for using RxJava to manage asynchronous data streams and concurrent tasks in Android applications. It provides a collection of reference implementations for reactive programming, focusing on functional operators to transform and combine asynchronous data flows. The library demonstrates specific Android architectural patterns, such as implementing decoupled event buses for component communication and coordinating parallel network requests. It includes concrete examples of mobile-specific patterns including search input debouncing, list

    Uses functional stream combinators like zip, merge, and switchMap to compose complex asynchronous data flows.

    Javaconcurrencyexamplejava
    Ver en GitHub↗7,504
  • sammchardy/python-binanceAvatar de sammchardy

    sammchardy/python-binance

    7,176Ver en GitHub↗

    python-binance is a Python client library that provides programmatic access to the Binance cryptocurrency exchange through both REST and WebSocket APIs. It serves as a comprehensive toolkit for automated trading, account management, and market data retrieval, enabling developers to build trading bots, portfolio management tools, and data analysis applications that interact directly with the exchange. The library distinguishes itself through a dual-client architecture that separates synchronous REST calls from persistent WebSocket streams, allowing concurrent execution without blocking. It inc

    Joins multiple market data streams into a single multiplexed socket for efficient monitoring.

    Pythonapibinancecryptocurrency
    Ver en GitHub↗7,176
  • louthy/language-extAvatar de louthy

    louthy/language-ext

    7,057Ver en GitHub↗

    language-ext is a functional programming framework for C# that provides a suite of immutable data structures and monadic types. It enables the implementation of pure functional programming patterns, utilizing containers to manage side effects, optional values, and error handling. The library is distinguished by its advanced concurrency and state management tools, including a software transactional memory system and lock-free atomic references. It also provides specialized utilities for distributed systems, such as vector clocks for causality tracking and deterministic data conflict resolution

    Merges, concatenates, or zips multiple data sources into a single stream.

    C#
    Ver en GitHub↗7,057
  • baconjs/bacon.jsAvatar de baconjs

    baconjs/bacon.js

    6,458Ver en GitHub↗

    Bacon.js is a JavaScript functional reactive programming library used for coordinating complex asynchronous data flows. It functions as an observable event stream framework and an asynchronous data flow orchestrator, allowing developers to model events as declarative streams and properties. The library distinguishes itself through its ability to manage reactive state and synchronize timing across multiple sources. It provides specialized mechanisms for atomic state synchronization to prevent glitches in derived properties and offers advanced coordination strategies such as asynchronous stream

    Pairs values from multiple streams one-to-one to emit a combined result using a zip operator.

    TypeScript
    Ver en GitHub↗6,458
  • rust-lang/futures-rsAvatar de rust-lang

    rust-lang/futures-rs

    5,870Ver en GitHub↗

    Zero-cost asynchronous programming in Rust

    Defines the Stream trait and combinators for processing sequences of asynchronous values.

    Rustasync-foundations
    Ver en GitHub↗5,870
  • cube2222/octosqlAvatar de cube2222

    cube2222/octosql

    5,258Ver en GitHub↗

    Octosql es un motor de consultas SQL federado, transformador de datos y procesador de SQL en streaming. Permite a los usuarios ejecutar sentencias SQL únicas a través de múltiples fuentes de datos dispares, incluyendo diferentes tipos de bases de datos y formatos de archivo, para combinar y transformar resultados en un conjunto unificado. El sistema se distingue por tratar archivos CSV, JSONLines y Parquet como tablas virtuales y utilizar una arquitectura basada en plugins para extender la conectividad a motores de almacenamiento externos. Funciona como un procesador de streaming para flujos de datos infinitos, utilizando marcas de agua (watermarks), retracciones y ventanas deslizantes (tumbling windows) para mantener la consistencia en eventos fuera de orden. Además, sirve como generador de datos SQL capaz de producir conjuntos de datos sintéticos y flujos de registros mediante funciones con valores de tabla. El motor incluye capacidades para realizar joins entre fuentes de datos y análisis multi-fuente, optimizado mediante el push-down de predicados en el lado de la fuente para reducir la transferencia de datos. Gestiona datos complejos a través de un sistema de tipos estáticos con tipos unión y proporciona observabilidad mediante la visualización de planes de ejecución de consultas.

    Combines two live data streams in memory using watermarks to buffer records and ensure consistent results.

    Go
    Ver en GitHub↗5,258
  • reactivex/rxpyAvatar de ReactiveX

    ReactiveX/RxPY

    5,014Ver en GitHub↗

    RxPY es una librería de programación reactiva funcional y una librería de observables ReactiveX para Python. Funciona como un procesador de flujos asíncronos y un framework de coordinación basado en eventos, utilizado para construir pipelines de datos que reaccionan a cambios de estado o flujos de eventos a lo largo del tiempo. La librería proporciona un kit de herramientas para componer programas asíncronos y basados en eventos mediante secuencias observables y operadores. Se distingue por el uso de planificadores (schedulers) configurables para gestionar la concurrencia, el timing y los ciclos de vida de las suscripciones. El proyecto cubre una amplia gama de capacidades de procesamiento de flujos, incluyendo agregación, filtrado y combinación de datos. Proporciona mecanismos para la difusión de eventos, almacenamiento en búfer de secuencias y gestión de errores, así como herramientas para coordinar flujos observables con bucles de eventos asíncronos. Las pruebas y el aseguramiento de la calidad se apoyan en la simulación de tiempo virtual, el modelado con diagramas de mármol y la verificación de emisiones.

    Provides functional combinators like merge and zip to synchronize and unify multiple event streams.

    Python
    Ver en GitHub↗5,014
  • arroyosystems/arroyoAvatar de ArroyoSystems

    ArroyoSystems/arroyo

    4,819Ver en GitHub↗

    Arroyo is a high-performance stream processing platform built in Rust. It executes continuous SQL queries on streaming data with event-time semantics, enabling accurate windowed aggregations, joins, and stateful computations on unbounded event streams. The platform uses native Rust execution for high throughput and low latency, with periodic checkpointing for exactly-once fault tolerance and horizontal scaling across distributed workers. The system integrates deeply with Kafka for reading and writing topics with exactly-once delivery and supports change data capture (CDC) from MySQL and Postg

    Joins unbounded streams incrementally, outputting a changelog of inserts, updates, and deletes.

    Rustdatadata-stream-processingdev-tools
    Ver en GitHub↗4,819
  • zio/zioAvatar de zio

    zio/zio

    4,347Ver en GitHub↗

    ZIO is a functional effect system for the JVM that models asynchronous and concurrent programs as pure, composable values with typed error handling and dependency injection. Its core identity is built on fiber-based concurrency, where lightweight, non-blocking fibers execute millions of concurrent tasks with structured lifecycle management, and a dual-channel error model that separates expected business failures from unexpected system defects at compile time. The system provides effect-typed dependency injection through a layer-based dependency graph, pull-based reactive stream processing with

    Provides stream concatenation and flattening operators for sequential composition.

    Scalaasynchronicityasynchronousasynchronous-programming
    Ver en GitHub↗4,347
  • erikrose/more-itertoolsAvatar de erikrose

    erikrose/more-itertools

    4,074Ver en GitHub↗

    more-itertools is a Python iterable utility library providing advanced functions for manipulating, filtering, and transforming data sequences. It serves as a data stream processing toolkit and a set of utilities for iterator state management, extending the capabilities of the standard Python itertools module. The library includes a combinatorial math toolkit for generating permutations, combinations, and powersets, alongside routines for number theory calculations and matrix operations. It also provides tools for stream state management, allowing users to peek at upcoming elements or seek wit

    Provides operators for merging, interleaving, and zipping multiple data sources into a single unified stream.

    Python
    Ver en GitHub↗4,074
  • morelinq/morelinqAvatar de morelinq

    morelinq/MoreLINQ

    3,827Ver en GitHub↗

    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

    Merges multiple sequences into one stream using zipping, interleaving, or padding to handle length mismatches.

    C#dotnetlinq
    Ver en GitHub↗3,827
  1. Home
  2. Web Development
  3. Asynchronous API Clients
  4. Stream Composition
  5. Stream Combinators

Explorar subetiquetas

  • Async Stream Trait DefinitionsDefines the Stream trait and its combinators for composing and transforming sequences of asynchronous values. **Distinct from Stream Combinators:** Distinct from Stream Combinators: focuses on the core Stream trait definition and its foundational combinators, not just merge/zip/concat operations.
  • Multiplexed Market Data StreamsJoins multiple market data streams into a single multiplexed socket for efficient real-time monitoring. **Distinct from Stream Combinators:** Distinct from Stream Combinators: focuses on multiplexing exchange market data streams, not generic functional combinators.
  • Stream Join OperatorsOperators that join two or more unbounded data streams incrementally, outputting a changelog of results. **Distinct from Stream Combinators:** Distinct from Stream Combinators: focuses on stateful stream joins with changelog output, not generic functional combinators like zip or merge.