7 个仓库
Conversion of asynchronous effect blueprints into continuous streams of values.
Distinct from Stream Processing: Specifically addresses the lifting of functional effects into streams, not general data ingestion architectures.
Explore 7 awesome GitHub repositories matching data & databases · Effect-to-Stream Conversion. Refine with filters or upvote what's useful.
node-fetch 是一个轻量级的 HTTP 客户端库,为 Node.js 实现了浏览器标准的 Fetch API。它提供了一个基于 Promise 的接口,用于在服务器端环境中进行异步网络请求以检索或发送数据。 该项目专注于通过利用请求和响应流进行内存高效的数据处理。这允许通过原生系统流对大型网络负载进行增量处理,以防止内存耗尽。 该库涵盖了广泛的网络功能,包括使用自定义 HTTP 代理进行 DNS 和 SSL 配置、通过中止信号取消请求,以及处理各种内容编码和表单数据提交。
Converts raw binary data from the network layer into standard Node.js streams for asynchronous processing.
Fluent Bit 是一个云原生日志转发器和统一遥测收集器,设计为资源高效的数据流水线。它从多个来源摄取日志、指标和追踪信息,并在将数据路由到外部存储后端之前进行实时处理。 该项目作为一个实时流处理器和 OpenTelemetry 日志处理器,能够使用 SQL 和条件逻辑转换和过滤数据。它还充当分布式追踪代理,可以对追踪进行采样以减少数据量,同时保留完整的请求路径。 该系统通过基于文件系统的缓冲和有状态重试逻辑提供可靠的数据交付,以防止停机期间的数据丢失。其模块化架构支持可插拔的输入和输出插件、元数据驱动的路由,以及通过共享库扩展功能的能力。 该软件可以作为容器部署在不同的 CPU 架构和操作系统上。
Converts external text configurations into static array definitions during the build process.
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
Implements patterns for converting single-use data sequences into shared streams to allow multiple subscribers.
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
Provides a comprehensive set of utilities to generate event streams from DOM events, promises, callbacks, and polling functions.
go-flutter is a runtime and embedding library that enables Flutter applications to run natively on Windows, macOS, and Linux using Go and GLFW. It implements the Flutter Embedding API to render Flutter UIs on desktop platforms, providing a cross-platform desktop runtime that bridges Go and Dart code through standard Flutter method and event channels. The project includes a plugin framework that supports bidirectional communication between Go and Dart, allowing Go code to invoke Dart handlers and expose Go methods for Dart to call, with optional synchronous replies. It also provides event stre
Stream data from Go to Dart whenever an event occurs, using an EventChannel.
KurrentDB is an event-native database designed for event sourcing and event-driven architectures. It stores events as immutable, ordered records in streams, preserving a complete audit trail and enabling temporal queries. The database uses gRPC for all client-server and inter-node communication, providing efficient binary serialization and bidirectional streaming, and supports atomic multi-stream writes that ensure consistency across multiple streams in a single transaction. The database distinguishes itself with a built-in JavaScript projection engine that transforms, filters, and aggregates
Transforms and writes events from source streams into new streams using user-defined JavaScript functions.
R3 is a reactive extensions library and asynchronous data pipeline framework. It provides a system for composing asynchronous data streams, managing reactive state, and coordinating event sequences using observable patterns. The project distinguishes itself with a deterministic testing toolkit that mocks time and frame updates to ensure reproducible unit tests for asynchronous logic. It also includes observability tools for tracking active subscriptions and generating stack traces to identify memory leaks, alongside centralized exception routing for pipeline recovery. The framework covers a
Transforms standard event triggers into reactive streams to compose them with other asynchronous data sequences.