September 8, 2006 Announcing : PLY-2.0 (Python Lex-Yacc)
http://www.dabeaz.com/ply I'm pleased to announce a significant new update to PLY---a 100% Python implementation of the common parsing tools lex and yacc. PLY-2.0 features a completely new implementation of LALR(1) parsing that provides a significant speedup when generating the underlying parsing tables. This new implementation also (hopefully) fixes all outstanding bugs in LALR (1) parsing that were reported for previous versions of PLY-1.x. Here are a few PLY highlights: - PLY is closely modeled after traditional lex/yacc. If you know how to use these or similar tools in other languages, you will find PLY to be comparable. - PLY provides very extensive error reporting and diagnostic information to assist in parser construction. The original implementation was developed for instructional purposes. As a result, the system tries to identify the most common types of errors made by novice users. - PLY provides full support for empty productions, error recovery, precedence rules, and moderately ambiguous grammars. - Parsing is based on LR-parsing which is fast, memory efficient, better suited to large grammars, and which has a number of nice properties when dealing with syntax errors and other parsing problems. Currently, PLY can build its parsing tables using either SLR or LALR(1) algorithms. - PLY can be used to build parsers for large programming languages. Although it is not ultra-fast due to its Python implementation, PLY can be used to parse grammars consisting of several hundred rules (as might be found for a language like C). The lexer and LR parser are also reasonably efficient when parsing normal sized programs. More information about PLY can be obtained on the PLY webpage at: http://www.dabeaz.com/ply PLY is freely available and is licensed under the terms of the Lesser GNU Public License (LGPL). Cheers, David Beazley (http://www.dabeaz.com) -- http://mail.python.org/mailman/listinfo/python-announce-list Support the Python Software Foundation: http://www.python.org/psf/donations.html