A library to compactly encode data which can be used in URL.
Small library to store booleans and small integers compactly
Convert tables to well-typed records. Compactly store large json as tables. Microlibrary.
convert bundle paths to IDS to save bytes in browserify bundles
Javascript lib for producing diffs of data structures and time-traveling with them
Create Declarative frameworks that output tree structures with properties (e.g. ArtReact)
Compact Claude/opencode-style renderers for Pi tools with rich diffs, apply_patch, generic/MCP rendering, and optional global chrome.
Semantic code and docs search for pi, backed by OpenAI-compatible embeddings and repo-local SQLite indexes.
Differential state logger
Terminal interface for managing tasks and todos in [x]it! format
A JSON alternative that retains references, handles circular dependencies, and encodes almost every data type available to standard JavaScript.
A directory layout for viewing code files
Progressive proof-first agent flow: start fast, deepen deliberately, stay honest by design.
Opencode plugin for rendering mermaid diagrams as Unicode/ASCII art using beautiful-mermaid
CLI tool to check npm outdated packages with dates, colors, and markdown support
Pi extension that shows the current GitHub pull request in a widget
This package is designed for convenient and flexible serialization of JavaScript objects.
Lightweight Format - A very compact, compression friendly, binary format for storing JSON like objects.
High-density Base-91 protocol with XOR encryption and CRC-16 integrity.
Lightweight file based NoSQL DB
Library for creating web safe base64 objects with custom bith widths and dynamic values.
Pi Codemode plugin - TypeScript code execution with sandboxed tools, just-bash shell, and MCP integration
### 📖 Table of Contents - [👋 Introduction](#-introduction) - [🔌 Getting Started](#-getting-started) - [ItemInstance](#iteminstance) - [Getting a Backpack](#getting-a-backpack) - [getUsedSlots](#getusedslots) - [getItemByAssetId]
Parser for MongoDB aggregation pipeline expression written in a formula-like style
Compactly encode data types using adaptive arithmetic coding
Synchronize state between a server and client.
Cut Salesforce metadata tokens in half for AI coding agents. Converts XML to compact YAML/JSON with AI instruction file integration.
A highly customizable, open-addressing dictionary in Rust.
This provides the REST API for admin operations
Compaction, pruning and stability subsystem for the Carnelia MDCS
Providers crate for halter
High-performance AI coding agent CLI - Rust port of Pi Agent
HTAP embedded database: transactional DeltaStore + columnar Vortex storage + DuckDB SQL engine
Qwen3 inference engine with Attention Management KV-cache compaction (CUDA + Apple Silicon via MLX)
A high-performance concurrent key-value store and log engine in Rust
CLI interface for manually fetching and reading Prestige-parquet files
Displays time compactly.
Ever needed to compactly store and query a set of mostly consecutive, non-negative integers? Probably not, but if you do this library may work for you. It's just about as fast as a Set and a lot smaller for numbers that stay close together.
is a Base32 encoding designed to be easier for human use and more compact. It includes 1, 8 and 9 but excludes l, v and 2. It also permutes the alphabet so that the easier characters are the ones that occur more frequently. It compactly encodes bitstrings whose length in bits is not a multiple of 8, and omits trailing padding characters
In computer science, a disjoint-set data structure, also called a union–find data structure or merge–find set, is a data structure that keeps track of a set of elements partitioned into a number of disjoint (non-overlapping) subsets. It provides near-constant-time operations (bounded by the inverse Ackermann function) to add new sets, to merge existing sets, and to determine whether elements are in the same set. In addition to many other uses (see the Applications section), disjoint-sets play a key role in Kruskal's algorithm for finding the minimum spanning tree of a graph. A disjoint-set forest consists of a number of elements each of which stores an id, a parent pointer, and, in efficient algorithms, a value called the "rank". The parent pointers of elements are arranged to form one or more trees, each representing a set. If an element's parent pointer points to no other element, then the element is the root of a tree and is the representative member of its set. A set may consist of only a single element. However, if the element has a parent, the element is part of whatever set is identified by following the chain of parents upwards until a representative element (one without a parent) is reached at the root of the tree. Forests can be represented compactly in memory as arrays in which parents are indicated by their array index. Disjoint-set data structures model the partitioning of a set, for example to keep track of the connected components of an undirected graph. This model can then be used to determine whether two vertices belong to the same component, or whether adding an edge between them would result in a cycle. The Union–Find algorithm is used in high-performance implementations of unification. This data structure is used by the Boost Graph Library to implement its Incremental Connected Components functionality. It is also a key component in implementing Kruskal's algorithm to find the minimum spanning tree of a graph. Note that the implementation as disjoint-set forests doesn't allow the deletion of edges, even without path compression or the rank heuristic. Sharir and Agarwal report connections between the worst-case behavior of disjoint-sets and the length of Davenport–Schinzel sequences, a combinatorial structure from computational geometry.
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