I have a project which has a C extension which requires numpy. Ideally, I\'d like whoever downloads my project to just be able to run python setup.py install
or
Perhaps a more practical solution is to just require numpy to be installed beforehand and import numpy
inside a function scope. @coldfix solution works but compiling numpy takes forever. Much faster to pip install it first as a wheels package, especially now that we have wheels for most systems thanks to efforts like manylinux.
from __future__ import print_function
import sys
import textwrap
import pkg_resources
from setuptools import setup, Extension
def is_installed(requirement):
try:
pkg_resources.require(requirement)
except pkg_resources.ResolutionError:
return False
else:
return True
if not is_installed('numpy>=1.11.0'):
print(textwrap.dedent("""
Error: numpy needs to be installed first. You can install it via:
$ pip install numpy
"""), file=sys.stderr)
exit(1)
def ext_modules():
import numpy as np
some_extention = Extension(..., include_dirs=[np.get_include()])
return [some_extention]
setup(
ext_modules=ext_modules(),
)
I found a very easy solution in [this post][1]:
Or you can stick to https://github.com/pypa/pip/issues/5761. Here you install cython and numpy using setuptools.dist before actual setup:
from setuptools import dist
dist.Distribution().fetch_build_eggs(['Cython>=0.15.1', 'numpy>=1.10'])
Works well for me!
The following works at least with numpy1.8 and python{2.6,2.7,3.3}:
from setuptools import setup
from setuptools.command.build_ext import build_ext as _build_ext
class build_ext(_build_ext):
def finalize_options(self):
_build_ext.finalize_options(self)
# Prevent numpy from thinking it is still in its setup process:
__builtins__.__NUMPY_SETUP__ = False
import numpy
self.include_dirs.append(numpy.get_include())
setup(
...
cmdclass={'build_ext':build_ext},
setup_requires=['numpy'],
...
)
For a small explanation, see why it fails without the "hack", see this answer.
Note, that using setup_requires
has a subtle downside: numpy will not only be compiled before building extensions, but also when doing python setup.py --help
, for example. To avoid this, you could check for command line options, like suggested in https://github.com/scipy/scipy/blob/master/setup.py#L205, but on the other hand I don't really think it's worth the effort.
This is a fundamental problem with packages that need to use numpy (for distutils or get_include). I do not know of a way to "boot-strap" it using pip or easy-install.
However, it is easy to make a conda package for your module and provide the list of dependencies so that someone can just do a conda install pkg-name which will download and install everything needed.
Conda is available in Anaconda or in Miniconda (python + just conda).
See this website: http://docs.continuum.io/conda/index.html or this slide-deck for more information: https://speakerdeck.com/teoliphant/packaging-and-deployment-with-conda
@coldfix's solution doesn't work for Cython-extensions, if Cython isn't pre-installed on the target-machine, as it fails with the error
error: unknown file type '.pyx' (from 'xxxxx/yyyyyy.pyx')
The reason for the failure is the premature import of setuptools.command.build_ext
, because when imported, it tries to use Cython's build_ext
-functionality:
try:
# Attempt to use Cython for building extensions, if available
from Cython.Distutils.build_ext import build_ext as _build_ext
# Additionally, assert that the compiler module will load
# also. Ref #1229.
__import__('Cython.Compiler.Main')
except ImportError:
_build_ext = _du_build_ext
And normally setuptools is successful, because the import happens after setup_requirements
are fulfilled. However by importing it already in setup.py
, only fall back solution can be used, which doesn't know any about Cython.
One possibility to bootstrap Cython
alongside with numpy, would be to postpone the import of setuptools.command.build_ext
with help of an indirection/proxy:
# factory function
def my_build_ext(pars):
# import delayed:
from setuptools.command.build_ext import build_ext as _build_ext#
# include_dirs adjusted:
class build_ext(_build_ext):
def finalize_options(self):
_build_ext.finalize_options(self)
# Prevent numpy from thinking it is still in its setup process:
__builtins__.__NUMPY_SETUP__ = False
import numpy
self.include_dirs.append(numpy.get_include())
#object returned:
return build_ext(pars)
...
setup(
...
cmdclass={'build_ext' : my_build_ext},
...
)
There are other possibilities, discussed for example in this SO-question.
The key is to defer importing numpy
until after it has been installed. A trick I learned from this pybind11 example is to import numpy
in the __str__
method of a helper class (get_numpy_include
below).
from setuptools import setup, Extension
class get_numpy_include(object):
"""Defer numpy.get_include() until after numpy is installed."""
def __str__(self):
import numpy
return numpy.get_include()
ext_modules = [Extension('vme', ['vme.c'], extra_link_args=['-lvme'],
include_dirs=[get_numpy_include()])]
setup(name='vme',
version='0.1',
description='Module for communicating over VME with CAEN digitizers.',
ext_modules=ext_modules,
install_requires=['numpy','pyzmq', 'Sphinx'])