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What if accurate semantic information about your code was available through a rich query language that produced results in milliseconds? And what if that worked at scale, so that you had information not just about the files you're working on, but the entire stack in which your code lives? You could use that to build IDE integration, code search and browsing tools, code analysis tools, as well as any ad-hoc tooling or infrastructure that needs accurate semantic information about code.
At Meta we're building Glean, an open-source system for storing and querying information about code at scale. Glean is implemented mostly in Haskell, using the open-source RocksDB engine for storage. Glean comes with indexers for several languages.
In this talk I'll take a tour through what Glean can offer, with a particular focus on how Haskell has enabled some rather nifty features that make working with Glean safer and more efficient.
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