Simple keyed tree data structure
An interface over BIP-32 and BIP-39 key derivation paths
Simple tool for storing/retrieving objects events based hierarchical keypaths.
Takes binding declarations and returns key-tree-store of functions that can be used to apply those bindings.
Add and remove items to a tree
Interval search tree with TypeScript support
Bindings for the Watchman file watching service
ember-cli addon tree cache key builder
A sorted list of key-value pairs in a fast, typed in-memory B+ tree with a powerful API.
Azure Key Vault Secrets
High-performance (binary) tree and sorted map implementation (AVL, Splay, Radix, Red-Black)
A library for creating standardized query keys, useful for cache management in @tanstack/query
Isomorphic client library for Azure KeyVault's keys.
TypeScript definitions for configstore
Different binary search tree implementations, including a self-balancing one (AVL)
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TypeScript client library for the Mistral AI API
parse, inspect, transform, and serialize content through syntax trees
Curated addons to bring out the best of Storybook
JWA, JWS, JWE, JWT, JWK, JWKS for Node.js, Browser, Cloudflare Workers, Deno, Bun, and other Web-interoperable runtimes
Microsoft Azure SDK for JavaScript - Aborter
TypeScript definitions for mime-types
A module for creating Discord bots using NestJS, based on Discord.js
A cross platform HTML5 QR Code & bar code scanner
Manage trees of keys
treestore stores two different types of data: 1) values, which are stored according to their SHA-1 hashcode 2) trees, which are sets of values and/or other trees, stored via a SHA-1 hashcode In addition, there are references that allow you to 'bookmark' a SHA-1 hashcode for easier lookup. If you think of the core git, but on any key-value backend store (like the included Redis one), you've got the right idea.
A RBTree is a sorted associative collection that is implemented with a Red-Black Tree. It maps keys to values like a Hash, but maintains its elements in ascending key order. The interface is the almost identical to that of Hash.
Trie-like, prefix-tree data structures. First, a prefix-tree based on Arrays, which differs from a traditional trie, which maps strings to values. Second, a more general prefix-tree data structure that works for any type of keys, provided those keys can be transformed to and from an array. Both of these data structures are implemented in terms of hashes.
Provides a generic tree data structure with ability to store keyed node elements in the tree. The implementation mixes in the Enumerable module.
A RBTree is a sorted associative collection that is implemented with a Red-Black Tree. It maps keys to values like a Hash, but maintains its elements in ascending key order. The interface is the almost identical to that of Hash. This is a fork of the original gem that fixes various bugs on Ruby 2.3+.
Splay tree is an efficient implementation of a balanced binary search tree that takes advantage of locality in the keys used in incoming lookup requests. For many applications, there is excellent key locality.
lithos is a self-contained embedded key-value store written from scratch as a native extension — no external database dependency. It uses a log-structured merge (LSM) tree: a write-ahead log makes every write durable, an in-memory sorted memtable flushes to immutable SSTables (with bloom filters), and compaction merges them. Keys and values are arbitrary binary strings; keys are kept in sorted order so you get ordered iteration and range scans, plus crash recovery via WAL replay. Windows MSVC (mswin) Ruby only.
Tokyo Cabinet is a library of routines for managing a database. The database is a simple data file containing records, each is a pair of a key and a value. Every key and value is serial bytes with variable length. Both binary data and character string can be used as a key and a value. There is neither concept of data tables nor data types. Records are organized in hash table, B+ tree, or fixed-length array.
Kyoto Cabinet is a library of routines for managing a database. The database is a simple data file containing records, each is a pair of a key and a value. Every key and value is serial bytes with variable length. Both binary data and character string can be used as a key and a value. Each key must be unique within a database. There is neither concept of data tables nor data types. Records are organized in hash table or B+ tree.
Kyoto Cabinet is a library of routines for managing a database. The database is a simple data file containing records, each is a pair of a key and a value. Every key and value is serial bytes with variable length. Both binary data and character string can be used as a key and a value. Each key must be unique within a database. There is neither concept of data tables nor data types. Records are organized in hash table or B+ tree.
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