Algorithms to help you parse CSS from an array of tokens.
Xml digital signature and encryption library for Node.js
JWA implementation (supports all JWS algorithms)
Browser Compatible Object Hashing
Minimalistic and efficient FFT implementation
various machine learning routines for node
Boyer-Moore-Horspool algorithms
Digital Signal Processing for Javascript
Lightning fast hash functions for browsers and Node.js using hand-tuned WebAssembly binaries (MD4, MD5, SHA-1, SHA-2, SHA-3, Keccak, BLAKE2, BLAKE3, PBKDF2, Argon2, bcrypt, scrypt, Adler-32, CRC32, CRC32C, RIPEMD-160, HMAC, xxHash, SM3, Whirlpool)
Implementation of JSON Web Signatures
A JavaScript implementation of the JSON Object Signing and Encryption (JOSE) for current web browsers and node.js-based servers
Package implements data structures and algorithms for processing various types of graphs
Parse CSS media query lists.
Parse CSS Cascade Layer names.
Types and schema that specs of the Markup languages for markuplint
a fast vite compression plugin
JSON Web Token implementation (symmetric and asymmetric)
Solve CSS math expressions
Parse CSS color values
Transform stream that decompress its input if it's compressed, and echoes it if not
A Node.js module for the optimized JavaScript implementation of the MurmurHash algorithms.
A conversational AI-driven telecom multi-agent system for managing call balances, push notifications, marketing, targeting, and sales.
Native JS murmur hash implementation
A very basic crypto library
An implementation of the Cooley-Tukey algorithm for the Discrete Fourier Transform
The Automation-Audio gem is a powerful Ruby library designed for audio analysis and processing. It enables users to easily extract frequency domain information from WAV audio files by performing Fast Fourier Transform (FFT). This gem is ideal for developers, researchers, and audio enthusiasts looking to analyze sound data, visualize audio frequencies, or implement audio processing algorithms.
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