rm.Trie 1.3.1-alpha

This is a .NET standard library that tries to parse and analyze the user agent string and extract as many relevant attributes as possible. The library aims to provides a reliable and extensible user agent parsing, browser and device detection. This is a semantic analyzer, so it doesn't rely on any database (except for some very little lookup tables), that means it is able to parse and recognize every day new kind of user agents and new patterns without updates. That makes the library very fast, flexible and easy to mantain, on the contrary the library can't extract info that are not present on user agent string without a proper mapping. The library doesn't aim to recognize every device in the world (there are several thousands), but it is able to work, analyze and extract all attributes available in the user agent. For most common devices we provide a lookup table in yaml file to identify device brand/model based on the few info available in the user agent. The library can be easily extended thanks to yaml files and a simple syntax (we don't rely on regular expression). Thanks to custom yaml definitions, you can make the library able to identify your company applications/ tools and extract your custom fields.

A spatial index backed by geohashing and Trie (prefix tree) maps. Geometries are encoded as geohashes and stored in a prefix tree, and reverse lookups are performing by encoding the queried geometry and using the prefix tree as an inverted lookup index. The index size can be tuned with the precision parameter. The geohasher and prefix tree map providers can be injected by implementing the IGeohasher and/or IGeohashTrieMap interfaces.

TAO3 is a .NET Interactive extension for writing data transformation quickly.

This is a .NET standard library that tries to parse and analyze the user agent string and extract as many relevant attributes as possible. The library aims to provides a reliable and extensible user agent parsing, browser and device detection. This is a semantic analyzer, so it doesn't rely on any database (except for some very little lookup tables), that means it is able to parse and recognize every day new kind of user agents and new patterns without updates. That makes the library very fast, flexible and easy to mantain, on the contrary the library can't extract info that are not present on user agent string without a proper mapping. The library doesn't aim to recognize every device in the world (there are several thousands), but it is able to work, analyze and extract all attributes available in the user agent. For most common devices we provide a lookup table in yaml file to identify device brand/model based on the few info available in the user agent. The library can be easily extended thanks to yaml files and a simple syntax (we don't rely on regular expression). Thanks to custom yaml definitions, you can make the library able to identify your company applications/ tools and extract your custom fields.