How to Bootstrap numpy installation in setup.py

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.

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!

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

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'])