6 个仓库
Processes data in chunks using async iterators without buffering the entire payload.
Distinct from Data Iterators: Distinct from Data Iterators: focuses on async iteration over streaming data sources, not sequential access to in-memory collections.
Explore 6 awesome GitHub repositories matching data & databases · Async Iterable Streams. Refine with filters or upvote what's useful.
Node.js is an open-source, cross-platform JavaScript runtime environment built on the V8 engine, designed for executing JavaScript code outside a web browser. It operates as a server-side JavaScript platform with an event-driven, non-blocking I/O architecture that enables building scalable network applications and web servers. The runtime integrates the CommonJS module system for synchronous module loading and the npm ecosystem for sharing and reusing packages. The platform provides comprehensive capabilities for web server development, including creating HTTP and HTTPS servers, managing HTTP
Supports processing streaming data with async iterators for chunk-by-chunk consumption without full buffering.
Lazy.js is a JavaScript library that implements a lazy evaluation model for processing collections and data streams. It defers all computation until iteration begins, building chains of transformations that execute only when values are consumed, avoiding intermediate arrays and buffering. The library wraps data sources into a uniform sequence interface, enabling operations like map and filter to be chained together without materializing intermediate results. The library extends lazy processing beyond simple collections to handle asynchronous data sources, DOM events, strings, and Node.js stre
Integrates with asynchronous data sources by yielding values at timed intervals or from streams without blocking.
Slonik 是一个用于 Node.js 的类型安全 PostgreSQL 客户端,使用标记模板字面量(tagged template literals)来确保参数绑定并防止注入攻击。它提供了一个将应用连接到 PostgreSQL 的框架,并为查询和数据库模式提供自动类型检查。 该项目通过专门的 SQL 查询 Linter 脱颖而出,该 Linter 通过在开发过程中根据实时数据库模式验证代码,来检测无效列和类型不匹配。它还包括一个用于加载大数据集的高性能二进制批量数据插入器(使用原生二进制序列化),以及一个能够在主节点和副本节点之间进行动态查询路由的连接池管理器。 该库涵盖了广泛的数据库能力,包括原子事务管理、动态 SQL 查询构建,以及通过异步迭代流处理大数据集。它进一步提供了用于日志记录和基准测试的中间件拦截器、自定义类型解析,以及用于刷新数据库身份验证凭据的异步回调机制。
Provides memory-efficient processing of large database result sets using async iterable streams.
This is a typed server-side library and payment gateway SDK for integrating Stripe into Node.js applications. It provides a typed client to manage payments, customers, and subscriptions, while offering specialized tools for executing secure financial transactions and managing billing resources. The library distinguishes itself through an idempotent API client that prevents duplicate operations using idempotency keys and exponential backoff retry logic. It includes a webhook signature validator to verify that incoming HTTPS event notifications are authentic and an async-iterator pagination wra
Uses JavaScript async iterators to stream paginated data from the API without buffering the entire payload.
Umbrella is a comprehensive ecosystem of TypeScript-based libraries and a mono-repository designed for UI rendering, mathematical frameworks, WebAssembly bridging, and functional data processing. It provides a suite of tools for managing reactive data streams, binary serialization, and specialized memory management. The project includes a reactive component model for generating HTML, SVG, and Canvas elements from nested data structures, as well as a system for integrating JavaScript and WebAssembly through generated bindings. It features a mathematical framework for linear algebra, tensor ope
Implements async iterators and reactive event streams for transforming continuous data flows in Deno.
Data Hacks is a collection of command-line utilities designed for statistical computation, real-time stream processing, and text-based data visualization. The toolkit enables users to perform rapid analysis on large datasets directly within the terminal by processing information through standard input and output streams. The project distinguishes itself through its focus on memory-efficient, stream-oriented operations that allow for the analysis of large-scale data without requiring heavy infrastructure. It utilizes stateless functional transformations and reservoir sampling to handle data st
Samples data streams by selecting random subsets of records to facilitate analysis of large datasets.