Software-Development

AlgoGraph: Immutable Graph Library with Functional Transformers

AlgoGraph brings functional programming elegance to graph algorithms with immutable data structures, pipe-based transformers, declarative selectors, and lazy views.

BTK: Modern Database-First Bookmark Manager

A modern, database-first bookmark manager with powerful features for organizing, searching, and analyzing your bookmarks.

src2md: Context-Window-Optimized Code for LLMs

A tool that converts source code repositories into structured, context-window-optimized representations for Large Language Models with intelligent summarization.

Sparse Spatial Hash Grids: Efficient N-Dimensional Spatial Indexing

A deep dive into sparse spatial hash grids - a memory-efficient, high-performance data structure for spatial indexing that achieves 60,000x memory reduction over dense grids while maintaining O(1) insertions and O(k) neighbor queries.

EBK: A Modern eBook Management System with AI-Powered Features

EBK is a comprehensive eBook metadata management tool that combines a robust SQLite backend with AI-powered features including knowledge graphs, semantic search, and MCP server integration for AI assistants.

DagShell: A Content-Addressable Virtual Filesystem

A virtual POSIX-compliant filesystem implementation using content-addressable DAG storage with SHA256 deduplication.

AlgoTree: Immutable Tree Structures with Functional Transformers

A powerful, immutable-by-default tree manipulation library for Python with functional programming patterns, composable transformations, and advanced pattern matching.

Algebraic Hashing: Composable Hash Functions Through XOR

Most hash libraries treat hash functions as black boxes. Algebraic Hashing exposes their mathematical structure, letting you compose hash functions like algebraic expressions—with zero runtime overhead.

The Core Insight

Hash functions form an abelian …

likelihood.model: Composable Statistical Inference in R

Most R packages hardcode specific likelihood models. likelihood.model provides a generic framework where likelihoods are first-class composable objects—designed to work seamlessly with algebraic.mle for maximum likelihood estimation.

The Core Concept …

hypothesize: A Consistent API for Statistical Tests in R

R’s hypothesis testing functions are inconsistent—t.test() returns different structures than chisq.test(), making generic workflows painful. hypothesize provides a unified API so any test returns the same interface: p-value, test statistic, …

dfr.dist: Specify the Hazard Function Directly

Most survival analysis forces you to pick from a catalog—Weibull, exponential, log-normal. dfr.dist flips this: you specify the hazard function directly, and it handles all the math.

The Core Insight

Instead of choosing Weibull(shape, scale), you …

algebraic.mle: The Foundation of a Statistical Inference Ecosystem

An R package treating MLEs as first-class algebraic objects with composable statistical properties.

algebraic.dist: Treating Distributions as First-Class Algebraic Objects in R

Most statistical software treats probability distributions as static parameter sets you pass to sampling or density functions. algebraic.dist takes a different approach: distributions are algebraic objects that compose, transform, and combine using …