Search Results for "lru"

...Developers can use it to cache expensive computations, API responses, or frequently accessed data. The implementation focuses on correctness, speed, and compatibility with modern Node.js environments. Overall, node-lru-cache provides a reliable building block for performance optimization in JavaScript backends.

Cachex is a high-performance in-memory caching library for Elixir, offering a robust feature set including expirations, size limits, hooks, fallbacks, async operations, and clustering capabilities. The version 4.x release brought optimized janitor routines, modular streaming and querying, runtime cache warming, size pruning (LRW/LRU), distributed routing mechanisms, and a major documentation overhaul. It integrates seamlessly with Elixir applications via mix dependencies, supports advanced transactional use cases, and includes utilities for distributed node clusters.

...Its high-level proxy-agent package automatically selects the correct agent from standard environment variables such as HTTP_PROXY, HTTPS_PROXY, and NO_PROXY. Lower-level packages provide dedicated support for HTTP, HTTPS, SOCKS, and PAC-based proxy configurations. An LRU cache reuses compatible agent instances across requests to reduce repeated setup work. The repository also includes shared foundations, URI helpers, PAC resolution utilities, negotiation code, tests, and TypeScript configuration. Applications can use the main package as a drop-in Node HTTP agent or import a protocol-specific module for greater control. ...

...Its examples emphasize understanding core design ideas rather than relying on finished frameworks. The repository includes Gee, a Gin-like web framework with routing, middleware, templates, and panic recovery. GeeCache demonstrates LRU caching, concurrency, consistent hashing, distributed nodes, single-flight protection, and Protobuf communication. GeeORM covers mapping, queries, hooks, transactions, and migrations. GeeRPC builds on net/rpc with concurrent clients, timeouts, HTTP transport, load balancing, registration, and service discovery.

LRU caching map is Least Recent Used Map, (see Wiki), meaning that a Key,Value pair is stored in the cache, with a "expireTime", but every time the Key is retrieved (get method) the expire time is extended. It is a simple POJO one jar library. With complete documentation with examples and javadoc. When the cache reaches is "maxSize" or a cleanup of the cache is performed (automatically by deamon thread dependent on the "LRUCachingMapConfiguration"), it is the keys with least recent used (lowest expire time) that is discarded first. ...