Figma studio token parser. Convert your tokens to usable code in any language.
AXON v1.5.1 — first crates.io publication of the AXON language full-stack runtime. Lexer/parser/type-checker/IR generator (re-exported from axon-frontend) plus the native Rust runtime: typed channels (TypedEventBus with QoS×5, π-calculus mobility, capability extrusion via shield D8 — Fase 13.f.2), Free Monad CPS handlers (Fase 2), lease kernel + reconcile loop (Fase 3+5), Epistemic Security Kernel (ESK Fase 6), Trust Types + ReplayLog (Fase 11.a+11.c), Stateful PEM over WebSocket (Fase 11.d), Ontological Tool Synthesis (Fase 11.e), Mobile Typed Channels (Fase 13). Crate publishes as `axon-lang` to mirror the Python PyPI package; library import remains `use axon::*` so existing call sites keep working unchanged.
A highly parallel Perl 5 interpreter written in Rust
AI/Human task management system with file-based storage
Pure-Rust AV1 codec — orphan-rebuild scaffold pending clean-room re-implementation.
A secure, high-performance messaging protocol library
CME-coupled bridge crate for Omena semantic graph inputs
Semantic boundary crate for CSS Module Explainer style analysis
Blazing fast parser combinators: parse-while-lexing (zero-copy), deterministic LALR-style parsing, no backtracking. Flexible emitters for fail-fast runtime or greedy compiler diagnostics
'Freedom from `syn`'. A lightweight Rust lexer designed for use in bang-style proc macros.
A strongly-typed METAR and TAF parser library for aviation weather reports
The initial version of the Nenyr parser delivers robust foundational capabilities for interpreting Nenyr syntax. It intelligently processes central, layout, and module contexts, handling complex variable, aliases, themes, breakpoints, imports, typefaces definitions and precise class and animation declarations. Equipped with advanced tokenization, the parser ensures efficient parsing while offering detailed, context-aware error reporting. Designed for scalability, it provides the groundwork for seamless integration with larger projects, enabling future enhancements to support more complex styles and features. This version ensures both clarity and reliability in parsing, paving the way for continued innovation within the Nenyr ecosystem.