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./devel/py-grako, Grammar compiler

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Branch: CURRENT, Version: 3.99.9nb2, Package name: py39-grako-3.99.9nb2, Maintainer: pkgsrc-users

Grako (for grammar compiler) is a tool that takes grammars in a variation of
EBNF as input, and outputs memoizing (Packrat) PEG parsers in Python.

Grako can also compile a grammar stored in a string into a Grammar object that
can be used to parse any given input, much like the re module does with
regular expressions.

Grako is different from other PEG parser generators:
* Generated parsers use Python's very efficient exception-handling system to
backtrack. Grako generated parsers simply assert what must be parsed. There
are no complicated if-then-else sequences for decision making or
backtracking. Memoization allows going over the same input sequence several
times in linear time.
* Positive and negative lookaheads, and the cut element (with its cleaning of
the memoization cache) allow for additional, hand-crafted optimizations at
the grammar level.
* Delegation to Python's re module for lexemes allows for (Perl-like) powerful
and efficient lexical analysis.
* The use of Python's context managers considerably reduces the size of the
generated parsers for code clarity, and enhanced CPU-cache hits.
* Include files, rule inheritance, and rule inclusion give Grako grammars
considerable expressive power.
* Automatic generation of Abstract Syntax Trees and Object Models, along with
Model Walkers and Code Generators make analysis and translation approachable.

Master sites:

Filesize: 155.545 KB

Version history: (Expand)

CVS history: (Expand)


   2022-01-05 16:41:32 by Thomas Klausner | Files touched by this commit (289) 
Log message:
python: egg.mk: add USE_PKG_RESOURCES flag

This flag should be set for packages that import pkg_resources
and thus need setuptools after the build step.

Set this flag for packages that need it and bump PKGREVISION.
   2022-01-04 21:55:40 by Thomas Klausner | Files touched by this commit (1595) 
Log message:
*: bump PKGREVISION for egg.mk users

They now have a tool dependency on py-setuptools instead of a DEPENDS
   2021-10-26 12:20:11 by Nia Alarie | Files touched by this commit (3016) 
Log message:
archivers: Replace RMD160 checksums with BLAKE2s checksums

All checksums have been double-checked against existing RMD160 and
SHA512 hashes

Could not be committed due to merge conflict:
devel/py-traitlets/distinfo

The following distfiles were unfetchable (note: some may be only fetched
conditionally):

./devel/pvs/distinfo pvs-3.2-solaris.tgz
./devel/eclipse/distinfo eclipse-sourceBuild-srcIncluded-3.0.1.zip
   2021-10-07 15:44:44 by Nia Alarie | Files touched by this commit (3017) 
Log message:
devel: Remove SHA1 hashes for distfiles
   2017-06-17 21:37:39 by Joerg Sonnenberger | Files touched by this commit (1) 
Log message:
Use the build dependency I reported to actually fix the build.
   2017-06-11 08:59:18 by Adam Ciarcinski | Files touched by this commit (1) 
Log message:
Added BUILD_DEPENDS for 'test' target
   2017-06-01 14:04:38 by Adam Ciarcinski | Files touched by this commit (5) 
Log message:
Grako (for grammar compiler) is a tool that takes grammars in a variation of
EBNF as input, and outputs memoizing (Packrat) PEG parsers in Python.

Grako can also compile a grammar stored in a string into a Grammar object that
can be used to parse any given input, much like the re module does with
regular expressions.

Grako is different from other PEG parser generators:
* Generated parsers use Python's very efficient exception-handling system to
  backtrack. Grako generated parsers simply assert what must be parsed. There
  are no complicated if-then-else sequences for decision making or
  backtracking. Memoization allows going over the same input sequence several
  times in linear time.
* Positive and negative lookaheads, and the cut element (with its cleaning of
  the memoization cache) allow for additional, hand-crafted optimizations at
  the grammar level.
* Delegation to Python's re module for lexemes allows for (Perl-like) powerful
  and efficient lexical analysis.
* The use of Python's context managers considerably reduces the size of the
  generated parsers for code clarity, and enhanced CPU-cache hits.
* Include files, rule inheritance, and rule inclusion give Grako grammars
  considerable expressive power.
* Automatic generation of Abstract Syntax Trees and Object Models, along with
  Model Walkers and Code Generators make analysis and translation approachable.