Awesome GitHub RepositoriesParser Modules

This project is a static analysis engine designed to identify patterns, enforce coding standards, and automate code quality improvements in software projects. By parsing source code into structured abstract syntax trees, it enables deep programmatic inspection and the automated remediation of identified programming issues. The engine functions as a pluggable linting framework, allowing developers to extend its core capabilities through a modular architecture. Users can inject custom rules, parsers, and processors to support non-standard file formats or domain-specific logic. This extensibilit

This project provides an integration of Tree-sitter into the Neovim editor to enable structural code analysis. It serves as a framework for structural code navigation, context-aware syntax highlighting, and the management of language-specific parsers. The system distinguishes itself through a multi-language injection handler that identifies and parses embedded languages within a single document. It uses a dedicated parser manager to install, update, and remove grammar definitions and their associated query files. The tool covers several capability areas including incremental text selection,

TrumpScript is a Python-based domain specific language and compiler extension that wraps the Python runtime to enforce custom grammar and vocabulary rules. It transforms a specialized, case-insensitive vocabulary and natural speech patterns into executable Python instructions. The implementation distinguishes itself through strict constraints on source code, including a variable name system that restricts identifiers to a predefined whitelist and a numeric parser that rejects any integer not exceeding one million. It further utilizes a token-filtering preprocessor to remove filler words and n

This project is a comprehensive Lisp AI implementation library that provides reference implementations for various artificial intelligence paradigms and symbolic algorithms. It functions as a multi-purpose toolkit containing a logic programming engine, a natural language processing suite, and a symbolic mathematics toolkit. The library is distinguished by its diverse architectural frameworks, including a Prolog-style execution engine that uses unification and goal-driven backtracking, and a system for simulating human decision-making through expert system shells and certainty factors. It also

Lark est un toolkit d'analyse syntaxique Python utilisé pour définir des grammaires et convertir du texte brut en arbres d'analyse annotés. Il sert de générateur d'arbre syntaxique abstrait et de langage de définition de grammaire pour spécifier des règles de langage via des terminaux et des expressions régulières. La bibliothèque fournit deux implémentations d'analyse principales : une bibliothèque d'analyse Earley capable de gérer tous les langages non contextuels, y compris ceux avec ambiguïté et récursion à gauche, et une bibliothèque d'analyse LALR haute performance conçue pour les langages déterministes avec une faible surcharge mémoire. Au-delà de l'analyse de base, le toolkit inclut des capacités pour la composition de grammaire modulaire, la transformation d'arbre basée sur des règles et le suivi des coordonnées pour les positions sources. Il prend également en charge la sérialisation des grammaires LALR en modules d'analyse autonomes.

Pest est une bibliothèque de parsing Rust et un générateur de parser automatique qui transforme des définitions de grammaire formelles en parsers fonctionnels. Il se spécialise dans les Parsing Expression Grammars (PEG) pour reconnaître et structurer des motifs textuels complexes, fournissant un système pour le parsing de grammaires non contextuelles. La bibliothèque implémente une tokenisation sans copie (zero-copy) et une compilation de grammaire statique pour réduire la surcharge à l'exécution. Elle supporte la compatibilité no-std, permettant au parser d'être compilé pour des environnements embarqués ou bare-metal où la bibliothèque standard est indisponible. Le projet couvre une gamme de capacités de parsing, incluant l'extraction de paires de tokens imbriqués et la validation syntaxique automatisée. Il est utilisé pour implémenter des langages dédiés (DSL), le parsing de langages personnalisés et l'évaluation d'expressions mathématiques. Il fournit également des rapports d'erreurs automatisés pour identifier les tokens inattendus ou les entrées manquantes.

Nearley is a JavaScript parser toolkit used to define context-free grammars and generate corresponding parsers. It features an EBNF grammar compiler that transforms language definitions written in extended Backus-Naur Form into executable JavaScript code, utilizing an Earley parser implementation to process any context-free grammar. The toolkit distinguishes itself by its ability to handle left-recursion and ambiguity without failing, allowing it to identify and return multiple valid derivations for a single input string. It also includes a grammar fuzzing generator to produce random strings

Nearley is a JavaScript parser toolkit and context-free grammar compiler. It functions as an Earley parser generator that transforms BNF-like grammar definitions into executable code capable of analyzing text and generating abstract syntax trees. The project is distinguished by its ability to handle any context-free grammar, including those with left recursion and ambiguity, by maintaining multiple valid derivations for a single input. It further supports incremental parsing, allowing input strings to be processed in chunks to provide partial results and real-time feedback. Beyond core parsi

SBJson is an Objective-C JSON parser and generator designed for the parsing and generation of JSON data. It functions as a strict JSON validator, enforcing rigid grammar rules to ensure input data adheres to formal specifications. The project features an incremental JSON stream parser that processes UTF8 data in chunks to extract documents without loading the entire payload into memory. It also serves as a JSON data serializer that transforms native data objects into formatted strings using deterministic key sorting. The system manages data serialization workflows and implements security mea