Version: 1.0.0 Web: http://bit.ly/2riPed7
It was already getting too late to try and read a magazine, but right after the sun and dropped below the horizon on a warm summer evening, we stumbled upon an ancient issue of Linux Format. Inside was an article on Beagle, the innovative file indexer from the land of Novell’s enterpriseready Linux distro that sported many cool tools and features.
Beagle took its inspiration from the Spotlight search engine from Mac OS X. Surprisingly, after all these years, more advanced indexers like Baloo and Tracker still leave many Linux users unsatisfied due to their slow speeds and noticeable drain on a system’s responsiveness.
ANGRYsearch is a standalone indexer and search engine that’s very similar to FSearch. Both are open source equivalents to the Windows-only Everything Search Engine by Void tools. We’d love to compare FSearch with ANGRYsearch in future, but as long as the test machine already has PythonQt development files after building Screencloud, it’s natural to start with ANGRYsearch that uses the same technologies under the hood.
The application shows up as a clean window with a search panel and the Update button next to it. There’s not much you can configure apart from choosing the icon theme and adding certain directories to the ignore list.
ANGRYsearch indexes everything it finds in / and puts it into the SQLite database. We have to say that it took relatively little time to complete the initial run for the average Linux distro. The authors boast that their app can cope with one million files in approximately two minutes, which sounds close to true after our tests. Of course, such speeds are only possible when the indexer crawls only through file names, not their contents, but it’s still very impressive when your file’s found just be typing its name.
Most of other search tools feel a little on a slow side after using ANGRYsearch. The lack of the built-in configuration options is compensated by the useful tips made by the ANGRYsearch author in the official README document. There you can learn how to automate database update using Cron, and much more besides.
“It indexes everything it finds in / and puts it into the SQLite database.”
Minimal set of options coupled with speedy searches.