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github.com/igrigorik
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An implementation of the simple bug prediction heuristic outlined by the Google Engineering team: Bug Prediction at Google Well, we actually have a great, authoritative record of where code has been requiring fixes: our bug tracker and our source control commit log! The research indicates that predicting bugs from the source history works very well, so we decided to deploy it at Google. Point bugs
Ultimately this functionality should be nothing more than a module in Nginx, Apache, or equivalent, but for the sake of a prototype, this is built via/with an async Goliath app server which parses the HTTP protocol and feeds us incoming data. Converting HTTP to a stream oriented protocol: HTTP is not built for stream multiplexing, but protocols like SPDY attempt to solve this by introducing an exp
Important warning: You should be aware when using fibers with Rails that you can get a stack overflow error if your stack grows bigger than 4Kb (which is enough for most things though), this got even worse with the 3.1 release in which you can easily overflow the stack, here is an example here. Simple async demo stack with Rails 3.1 + EventMachine and Fibers. Hit localhost:3000/widgets to do a 1s
Collection of convenience classes and primitives to help untangle evented code, plus a number of patched EM clients to make them Fiber aware. To learn more, please see: Untangling Evented Code with Ruby Fibers. Fiber aware ConnectionPool with sync/async query support Fiber aware Iterator to allow concurrency control & mixing of sync / async Fiber aware async inline support: turns any async functio
mysql2 gem now ships with an EM driver - I recommend you switch & use it! And if you want synchronous API but an async driver, then take a look at em-synchrony EventMachine wrapper for the C-based MySQL / MySQLPlus Ruby gems, which provides callbacks, errbacks and all other niceties of EventMachine while keeping the API of the original C-based MySQL gem. Features: Maintains C-based mysql gem API D
Video of FutureRuby talk (“Lean & Mean Tokyo Cabinet Recipes”) on InfoQ: www.infoq.com/presentations/grigorik-tokyo-cabinet-recipes Tokyo Cabinet is a library of routines for managing a database. The database is a simple data file containing records, each is a pair of a key and a value. Every key and value is serial bytes with variable length. Both binary data and character string can be used as a
Async (EventMachine) HTTP client, with support for: Asynchronous HTTP API for single & parallel request execution Keep-Alive and HTTP pipelining support Auto-follow 3xx redirects with max depth Automatic gzip & deflate decoding Streaming response processing Streaming file uploads HTTP proxy and SOCKS5 support Basic Auth & OAuth Connection-level & global middleware support HTTP parser via http_pars
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