[Numpy-discussion] ANN: XDress v0.2
scopatz at gmail.com
Mon Jun 24 03:15:16 EDT 2013
I am pleased to announce the latest version of xdress, in preparation for
SciPy 2013. For more information please visit the website:
XDress 0.2 Release Notes
XDress is an automatic wrapper generator for C/C++ written in pure
xdress may generate Python bindings (via Cython) for C++ classes, functions, and
certain variable types. It also contains idiomatic wrappers for C++
containers (sets, vectors, maps). In the future, other tools and
bindings will be
The main enabling feature of xdress is a dynamic type system that was
the purpose of API generation in mind.
- First class support for C via pycparser.
- Python 3 support, by popular demand!
- A plethora of awesome type system updates, including:
- type matching
- lambda-valued converters
- function pointer support
- Easy to use and implement plugin architecture.
Please visit the website for more information: http://xdress.org/
Ask questions on the mailing list: xdress at googlegroups.com
Download the code from GitHub: http://github.com/scopatz/xdress
XDress is free & open source (BSD 2-clause license) and requires Python 2.7,
NumPy 1.5+, Cython 0.19+, and optionally GCC-XML, pycparser, and lxml.
First Class C Support
Wrapping C code is now fully handled through with the optional pycparser.
This means that you don't have to worry about whether or not the GCC-XML
parser will work on your particular bit of code. Furthermore, C structs
and their members are now handled idiomatically. (C++ structs are actually
treated as C++ classes, which means that their are allowed to have
constructors and other C++ concepts not present in C.)
Python 3 Support
The entire code base is built and tested under Python 3.3. This uses the single
code base model, as most development takes pace in Python 2.7. The Cython code
that is generated may be used by both Python 2 & 3.
The type system has been expanded and hardened to handle additional use cases,
largely motivated by the desire for realistic C support.
A new function pointer (``fucntion_pointer``) refinement type has been added.
When converting from C to Python, a new function object is created that wraps
the underlying call. For converting from Python to C, a virtual table of
callback functions is constructed that have the same signature of the pointer
but hold a reference to a Python function. The size of the table and thus how
many callbacks you can have before overwriting previous ones, is set by the
``max_callbacks`` key in the extra dictionary in class descriptions. This
defaults to 8.
A new enum refinement type now also comes stock. These may be exposed to Python
in the ``rc.variables`` list.
The type system now also comes with basic type matching tools. There is a new
``TypeMatcher`` class, a ``matches()`` function, and a singleton ``MatchAny``
that may be used for determining whether a type adheres to a pattern. The
TypeMatcher class itself is immutable and hashable and therefore may be used
anywhere other type elements (tuples, str, int) may be used including as dict
keys! This is helpful for specifying conversions for large groups of types.
Finally, the type system conversion dictionaries now accept callable objects
as values. This was put in to handle templated types where the number of
argument is not in general know beforehand, e.g. enums and function pointers.
The values must be callable with only a single argument -- the type itself.
For example, ``lambda t: rtnvalue`` is valid.
XDress is a suite of tools written on top of a type system. Thus the entire
core has been refactored to implement a very nimble and easy plugin system.
The plugin mechanism enables external projects with their own code generators
to easily hook into the xdress tools. Additionally, this allows users to
decide at run time which plugins they want to use.
* Why not use an existing solution (eg, SWIG)?
Their type systems don't support run-time, user provided refinement types,
and thus are unsuited for verification & validation use cases that often
arise in computational science.
Furthermore, they tend to not handle C++ dependent types well
does not come back as a np.view(..., dtype=T)).
* Why GCC-XML and not Clang's AST?
I tried using Clang's AST (and the remnants of a broken visitor class remain
in the code base). However, the official Clang AST Python bindings lack
support for template argument types. This is a really big deal.
Other C++ ASTs
may be supported in the future -- including Clang's.
* I run xdress and it creates these files, now what?!
It is your job to integrate the files created by xdress into your
Join in the Fun!
If you are interested in using xdress on your project (and need help),
back to xdress, starting up a development team, or writing your own
plugin tool on top of the type system and autodescriber, please let us know.
Participation is very welcome!
- `Anthony Scopatz <http://scopatz.com/>`_
- Spencer Lyon *
- Gerald Dalley *
- Alexander Eisenhuth *
An * indicates a first time contributor.
1. Homepage - http://xdress.org/
2. Mailing List - xdress at googlegroups.com
3. GitHub Organization - https://github.com/xdress
4. Pycparser - https://pypi.python.org/pypi/pycparser
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