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#!/usr/bin/env python
# Copyright (c) 2002-2005 ActiveState Software Ltd.
"""preprocess: a multi-language preprocessor
There are millions of templating systems out there (most of them
developed for the web). This isn't one of those, though it does share
some basics: a markup syntax for templates that are processed to give
resultant text output. The main difference with `preprocess.py` is
that its syntax is hidden in comments (whatever the syntax for comments
maybe in the target filetype) so that the file can still have valid
syntax. A comparison with the C preprocessor is more apt.
`preprocess.py` is targetted at build systems that deal with many
types of files. Languages for which it works include: C++, Python,
Perl, Tcl, XML, JavaScript, CSS, IDL, TeX, Fortran, PHP, Java, Shell
scripts (Bash, CSH, etc.) and C#. Preprocess is usable both as a
command line app and as a Python module.
"""
import os
import sys
import distutils
from distutils.core import setup
sys.path.insert(0, os.path.join(os.path.dirname(__file__), "lib"))
try:
import preprocess
finally:
del sys.path[0]
classifiers = """\
Development Status :: 5 - Production/Stable
Intended Audience :: Developers
License :: OSI Approved :: MIT License
Programming Language :: Python
Operating System :: OS Independent
Topic :: Software Development :: Libraries :: Python Modules
Topic :: Text Processing :: Filters
"""
if sys.version_info < (2, 3):
# Distutils before Python 2.3 doesn't accept classifiers.
_setup = setup
def setup(**kwargs):
if kwargs.has_key("classifiers"):
del kwargs["classifiers"]
_setup(**kwargs)
doclines = __doc__.split("\n")
script = (sys.platform == "win32" and "bin\\preprocess.exe" or "bin/preprocess")
setup(
name="preprocess",
version=preprocess.__version__,
maintainer="Trent Mick",
maintainer_email="trentm@gmail.com",
url="http://code.google.com/p/preprocess/",
license="http://www.opensource.org/licenses/mit-license.php",
platforms=["any"],
py_modules=["preprocess"],
package_dir={"": "lib"},
scripts=[script],
description=doclines[0],
classifiers=filter(None, classifiers.split("\n")),
long_description="\n".join(doclines[2:]),
)
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