Get popular human names
map ev.keyCode to human names
Get popular human names
capitalizes human names properly
Get popular human names
Get popular human names
Generate unique, random, human names
Normalize Human Names
Human Name Parser is a simple tool for parsing human names into their components. It returns the parsed components of the human name.
🎓 Normalize real human names the way they’re actually written — fixes casing, particles, honorifics, suffixes, hyphenation, Mc/Mac and O’ prefixes into clean, properly formatted names.
Get popular human names
Human-friendly process signals
Generate random names
A lightweight Node.js package to generate realistic human names based on regions.
Does this JS environment support the `name` property on functions?
A simple list of possible Typed Array names.
Returns from a pool of 15m human-readable IDs
Give me a string and I'll tell you if it's a valid npm package name
The set of canonical Unicode property names supported in ECMAScript RegExp property escapes.
Validates whether a string matches the production for an XML name or qualified name
List of known MathML tag names
Human-readable error messages for Ajv (Another JSON Schema Validator).
Reduce a list of values using promises into a promise for a value
JavaScript parser, mangler/compressor and beautifier toolkit
A random generator for human first and last names
A library for parsing and comparing human names
Provides human readable names using continious LFSR
Converts bearings in degrees to human-readable names
Human readable Android device names
A human name parser in ruby. It attempts to determine name pieces like title, first name, surname, etc.
Simple human name formatter
Provides human readable names for Foreman hosts and other entities
Turns device model strings to their human names
A list of baby names given to tiny humans
Encapsulate common application behaviour with dynamically generated classes
Convert MD5 hashes to human-readable names in the format of adjective-animal-suffix
Namae (名前) is a parser for human names. It recognizes personal names of various cultural backgrounds and tries to split them into their component parts (e.g., given and family names, honorifics etc.).
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