Detect gender from name
Library to decline people & city names in Russian, and to detect gender by name
Gender detection from first name
Improved typeof detection for node.js and the browser.
Detect the dominant newline character of a string
Detect Node.JS (as opposite to browser environment). ESM modification
Node.js module to detect the C standard library (libc) implementation family and version
Node.js implementation of port detector
Detect the gender of a person using his/her first name.
Detects if a file exists and returns the resolved filepath.
Detect the gender of a person using his/her first name.
Unpack a browser type and version from the useragent string
A table component for Ink.
detect available port
Classify GPU's based on their benchmark score in order to provide an adaptive experience.
Detect the indentation of code
A JavaScript parser built from the Hermes engine
Detect which package manager you're using (yarn or npm)
Detect device type and render your component according to it
Package manager detector
Library will help you to detect if the locale is right-to-left language.
Detect if the browser supports passive events
Detect if a device is mouse only, touch only, or hybrid
Gender package provides functionality to generate a fake gender value.
Statistical gender detection for Ruby
The name_gender_classifier gem classifies Brazilian first names as either 'male' or 'female' based on the 2010 IBGE census.
Detect probable gender and split first/last name tokens using static CSV datasets.
This is a simple gem to detect any Arabian name gender
Guess gender by a first name using more detailed, better sourced data from Open Gender Tracker's Global Name Data.<br /> Beauvoir lets you set avg and lower bounds and choose countries from which to draw data. It's important to note that many people identify as neither a men nor a women. It's important, too, to note that many people who do identify as male or female have names that<br /> are held by far more people who identify as another gender. All of these people deserve not to be misgendered in public (or in private). Nevertheless, automatically classifying people by apparent gender can be a very useful tool to perform censuses of communities or publications to detect and quantify perhaps-invisible bias. VIDA is a pioneer in this field, but their "Count" is limited by a manual methodology that depends hundreds of person-hours of labor. There is a place for more automated counts and Beauvoir can help, but if you do a count like this, you should be careful in how you word your findings not to misgender anyone in particular and be responsive to the possibility of errors.