Search Results for "text to code"

ANTLR (ANother Tool for Language Recognition) is a powerful parser generator for reading, processing, executing, or translating structured text or binary files. It's widely used to build languages, tools, and frameworks. From a grammar, ANTLR generates a parser that can build and walk parse trees. It’s widely used in academia and industry to build all sorts of languages, tools, and frameworks. Twitter search uses ANTLR for query parsing, with over 2 billion queries a day. The languages for...

argh is a tiny, pragmatic command-line argument parsing library that favors simple, readable code over elaborate configuration. It’s designed for the case where you just want to declare a few flags, accept some positional arguments, and print helpful usage text without wiring up a heavy framework. The API is intentionally compact so you can parse arguments inline near main() and map them straight into native types. It supports short and long options, boolean switches, and key–value flags while keeping error messages and help output understandable for end users. ...

SableCC is a parser generator which generates object-oriented frameworks for building compilers, interpreters and other text parsers. SableCC keeps a clean separation between machine and user code which leads to a shorter development cycle.

RapidJSON is a JSON parser and generator for C++. It was inspired by RapidXml. RapidJSON is small but complete. It supports both SAX and DOM style API. The SAX parser is only a half thousand lines of code. RapidJSON is fast. Its performance can be comparable to strlen(). It also optionally supports SSE2/SSE4.2 for acceleration. RapidJSON is self-contained and header-only. It does not depend on external libraries such as BOOST. It even does not depend on STL. RapidJSON is memory-friendly. Each JSON value occupies exactly 16 bytes for most 32/64-bit machines (excluding text string). ...

IronMeta is an implementation of Alessandro Warth's OMeta metaprogramming system in C#. It provides a packrat parser generator that generates parsers for Parsing Expression Grammars that operate on arbitrary streams of objects.

The goal of this project is to create a simple and easy to use parser generator that will accept a textual grammar file as an input and output modularized classes representing a limited parser interface. Long term goals include a robust grammar file syntax, output suitable for multiple programming languages, and tools for better integrating compiler functionality, parse tree manipulation, and FSM based scanner generation.

In a nutshell it takes as input the formal specification of any text protocol in ABNF and generates the parser in C language for that grammar using lex/yacc.