Search Results for "data structures"

Parser for Rust source code is a major Rust crate for parsing Rust source code (token streams) into a syntax tree (AST) that procedural macros can inspect or transform. The primary target is macro authors: you can parse TokenStreams into syn::File, syn::Item, syn::Expr, syn::Type, etc. It offers rich data structures, fine-grained parsing, span tracking (for error reporting), traversal and mutation APIs (visit, fold, visit_mut), printing back to tokens, and strong feature-gating so you only compile what you need. The documentation emphasises that while the crate is geared for procedural macros (and custom derives), some of the APIs may be of more general use. ...

...The JSON data is returned to the caller as a set of hierarchical D-List list objects, that make the data very easy to manage, sort, search or use, and easy to remove when done. Package includes a JSON textural generator which will create JSON grammar data blocks from hierarchical D-List representations of JSON data. The package also includes a variety of support functions to allow C code to easily find, add, and modify JSON values and members in D-List hierarchical structures.

psd.js is an open-source JavaScript library (CoffeeScript/JS) for reading and parsing Adobe Photoshop PSD files in both Node.js and web browsers. It reconstructs the document into a DOM-like tree with layers, masks, text metadata, vector information, and pixel data. It enables developers to traverse layer structures, extract flattened or individual image buffers, and integrate PSD assets programmatically in web or backend applications.

...The implementation contains the following: (1) depth-first and breadth-first parsers and generators, based on hand-crafted domain-specific lexicons but cover a broad range of structures, including relatives and tense; (2) a prototype incremental dialogue system, DyLan, based on Jindigo (Skantze & Hjalmarsson, 2010), but using the Dynamic Syntax (Kempson et. al. 2001, Cann et. al. 2005) parser/generator; (3) a grammar induction module which learns DS incremental grammars from data (Eshghi et. al. 2013). For more information on DS, and this implementation, please see the files DSImp_TechReport.pdf, and README.txt included here under "files".