Develop Reference

python setuptools: how can I install package with cython submodules?

I have a python package named pytools.
It contains a cython-based submodule nms.
When I install the root package pytools with sudo python -H setup.py,
the root package seems to be installed properly.
But the installation didn't copy compiled nms.so to /usr/local/lib/python2.7/dist-packages/pytools/nms/.
And When I import pytools in ipython, an error encountered:
ImportError: cannot import name nms
If I manually copy the pytools/nms/nms.so to /usr/local/lib/python2.7/dist-packages/pytools/nms/, the problem is solved.
Here is my setup.py of the root package:
import os
import numpy
from distutils.core import setup, Extension
from Cython.Build import cythonize
exec(open('pytools/version.py').read())
exts = [Extension(name='nms',
sources=["_nms.pyx", "nms.c"],
include_dirs=[numpy.get_include()])
]
setup(name='pytools',
version=__version__,
description='python tools',
url='http://kaiz.xyz/pytools',
author_email='zhaok1206#gmail.com',
license='MIT',
packages=['pytools', 'pytools.nms'],
#packages=['pytools'],
zip_safe=False
)
And setup.py of sub-package nms:
from distutils.core import setup, Extension
import numpy
from Cython.Distutils import build_ext
setup(
cmdclass={'build_ext': build_ext},
ext_modules=[Extension("nms",
sources=["_nms.pyx", "nms.c"],
include_dirs=[numpy.get_include()])],
)
It seems that this is a duplicated question with Attempting to build a cython extension to a python package, not creating shared object (.so) file, but I still want to post it here because there is no much discussions there.
Thank you!

You don't need the setup script in a subpackage. Just build the extension in the root setup script:
exts = [Extension(name='pytools.nms',
sources=["pytools/nms/_nms.pyx", "pytools/nms/nms.c"],
include_dirs=[numpy.get_include()])]
setup(
...
packages=['pytools'],
ext_modules=cythonize(exts)
)
Note that I wrap cythonized extension in cythonize() and use the full module name + full paths to extension sources. Also, since nms is a module in pytools package, including pytools.nms in packages has no effect.

In a setup.py involving Cython, if install_requires, then how can from library import something?

This doesn't make sense to me. How can I use the setup.py to install Cython and then also use the setup.py to compile a library proxy?
import sys, imp, os, glob
from setuptools import setup
from Cython.Build import cythonize # this isn't installed yet
setup(
name='mylib',
version='1.0',
package_dir={'mylib': 'mylib', 'mylib.tests': 'tests'},
packages=['mylib', 'mylib.tests'],
ext_modules = cythonize("mylib_proxy.pyx"), #how can we call cythonize here?
install_requires=['cython'],
test_suite='tests',
)
Later:
python setup.py build
Traceback (most recent call last):
File "setup.py", line 3, in <module>
from Cython.Build import cythonize
ImportError: No module named Cython.Build
It's because cython isn't installed yet.
What's odd is that a great many projects are written this way. A quick github search reveals as much: https://github.com/search?utf8=%E2%9C%93&q=install_requires+cython&type=Code

As I understand it, this is where PEP 518 comes in - also see some clarifications by one of its authors.
The idea is that you add yet another file to your Python project / package: pyproject.toml. It is supposed to contain information on build environment dependencies (among other stuff, long term). pip (or just any other package manager) could look into this file and before running setup.py (or any other build script) install the required build environment. A pyproject.toml could therefore look like this:
[build-system]
requires = ["setuptools", "wheel", "Cython"]
It is a fairly recent development and, as of yet (January 2019), it is not finalized / approved by the Python community, though (limited) support was added to pip in May 2017 / the 10.0 release.

One solution to this is to not make Cython a build requirement, and instead distribute the Cython generated C files with your package. I'm sure there is a simpler example somewhere, but this is what pandas does - it conditionally imports Cython, and if not present can be built from the c files.
https://github.com/pandas-dev/pandas/blob/3ff845b4e81d4dde403c29908f5a9bbfe4a87788/setup.py#L433
Edit: The doc link from #danny has an easier to follow example.
http://docs.cython.org/en/latest/src/reference/compilation.html#distributing-cython-modules

When you use setuptool, you should add cython to setup_requires (and also to install_requires if cython is used by installation), i.e.
# don't import cython, it isn't yet there
from setuptools import setup, Extension
# use Extension, rather than cythonize (it is not yet available)
cy_extension = Extension(name="mylib_proxy", sources=["mylib_proxy.pyx"])
setup(
name='mylib',
...
ext_modules = [cy_extension],
setup_requires=["cython"],
...
)
Cython isn't imported (it is not yet available when setup.pystarts), but setuptools.Extension is used instead of cythonize to add cython-extension to the setup.
It should work now. The reason: setuptools will try to import cython, after setup_requires are fulfilled:
...
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
...
It becomes more complicated, if your Cython-extension uses numpy, but also this is possible - see this SO post.

It doesn't make sense in general. It is, as you suspect, an attempt to use something that (possibly) has yet to be installed. If tested on a system that already has the dependency installed, you might not notice this defect. But run it on a system where your dependency is absent, and you will certainly notice.
There is another setup() keyword argument, setup_requires, that can appear to be parallel in form and use to install_requires, but this is an illusion. Whereas install_requires triggers a lovely ballet of automatic installation in environments that lack the dependencies it names, setup_requires is more documentation than automation. It won't auto-install, and certainly not magically jump back in time to auto-install modules that have already been called for in import statements.
There's more on this at the setuptools docs, but the quick answer is that you're right to be confused by a module that is trying to auto-install its own setup pre-requisites.
For a practical workaround, try installing cython separately, and then run this setup. While it won't fix the metaphysical illusions of this setup script, it will resolve the requirements and let you move on.

Cython unable to find shared object file

I am trying to link to my own C library from Cython, following the directions I've found on the web, including this answer:
Using Cython To Link Python To A Shared Library
I am running IPython through Spyder.
My setup.py looks like this:
from distutils.core import setup
from distutils.extension import Extension
from Cython.Build import cythonize
import numpy as np
setup(
ext_modules = cythonize(
[Extension("*",["*.pyx"],
libraries =["MyLib"],
extra_compile_args = ["-fopenmp","-O3"],
extra_link_args=["-L/path/to/lib"])
]),
include_dirs = [np.get_include()],
)
The file libMyLib.so is in /path/to/lib and it compiles fine.
I have a Python script in my IPython profile startup folder that does this
try:
os.environ["LD_LIBRARY_PATH"] += ":/path/to/lib"
except KeyError:
os.environ["LD_LIBRARY_PATH"] = "/path/to/lib"
I can confirm that this is running, because if I type os.environ["LD_LIBRARY_PATH"] into the IPython interpreter, it returns /path/to/lib
But when I try to load the Cython module (i.e. import mycythonmodule) I get:
ImportError: libMyLib.so: cannot open shared object file: No such file or directory
I've also tried putting libMyLib.so in other places to see if cython would find it:
In the directory where Python is running
On the Python path
In the same folder as the cython module
But it still doesn't find the shared library. The only way I can get it to find the library is by dropping it in /usr/lib, but I don't want it there, I want to be able to set the library path.
Am I missing something?

I'm self-answering, in case anyone else runs into the same problem. Looks like the answers are here:
Set LD_LIBRARY_PATH before importing in python
Changing LD_LIBRARY_PATH at runtime for ctypes
According to these answers (and my experience), the linker reads LD_LIBRARY_PATH when python is launched, so changing it from within python doesn't have any useful effect, at least not the effect I was hoping for. The only solution is to either wrap python in a shell script that sets LD_LIBRARY_PATH, or else drop the shared object somewhere on the linker search path.
Kind of a pain, but it is what it is.

I have fixed it by change setup.py.
I have a C++ dynamic shared library called "libtmsmdreader.so". and a header file named "TmsMdReader.hpp"
I wrapper C++ shared library to cython library called "tmsmdreader-pythonxxxxxx.so"
from setuptools import setup
from distutils.extension import Extension
from Cython.Build import cythonize
setup(
name="tmsmdreader",
ext_modules=cythonize([
Extension(
name="tmsmdreader",
language="c++",
sources=["TmsMdReaderApi.pyx"],
libraries=["tmsmdreader"],
library_dirs=["."],
include_dirs=["."],
extra_compile_args=["-std=c++14"],
compiler_directives={'language_level': 3},
runtime_library_dirs=["."])
]))
library_dirs=["."] and runtime_library_dirs=["."] can fixed LD_LIBRARY_PATH if libtmsmdreader.so in python scripy directory

Cython Compilation Error: dynamic module does not define module export function

I am building a package in Cython. I am using the following as the structure for setup.py:
from distutils.core import setup
from distutils.extension import Extension
from Cython.Build import cythonize
import numpy
import scipy
extensions = [
Extension("xxxxx",["xxxx/xxxxx.pyx"],
include_dirs=[numpy.get_include(),"."]),
Extension("nnls",["xxxxx/xxxxx.pyx"],
include_dirs=[numpy.get_include(),"."]),
]
setup(
name='xxxxxx',
version='0.0.0',
description='''********''',
url='xxxxxxx',
author='xxxxx',
author_email='xxxxx',
packages=[
'xxxxx',
],
install_requires=[
'cython',
'numpy',
'scipy',
],
ext_modules=cythonize(extensions),
)
However, I am getting an error upon installation in Python 3. It is working in Python 2 however, it is not compiling in Python 3 having the following error:
dynamic module does not define module export function
How can I solve this problem? Is the structure of the setup.py the reason why this is not compiling?

You need to call setup.py with Python 3 (python3 setup.py build_ext, maybe --inplace). It's because Python 3 defines a different name for the init function called when the module starts, and so you need to build it using Python 3 to ensure the correct name is generated.
See dynamic module does not define init function (PyInit_fuzzy) and How to specify Python 3 source in Cython's setup.py? for slightly more detail (it's bordering on a duplicate of these questions, but isn't quite in my view)

I experienced this and found that I had to use the same name of .pyx as the module name, e.g.
makefile:
# (default)
# INSTALL_DIR:=/usr/lib/python3.6/site-packages
# (my venv)
INSTALL_DIR:=/home/<username>/python3_venv/lib/python3.6/site-packages
all:
sudo python3 setup_myproj.py install --install-lib ${INSTALL_DIR}
setup_myproj.py
from distutils.core import setup, Extension
from Cython.Build import cythonize
ext = Extension("myproj",
sources=["myproj.pyx", "myCppProjFacade.cpp"],
<etc>
language="c++"
)
setup(name="myproj",
version="0.0.1",
ext_modules=cythonize(ext))
client module, run after installing to venv
import myproj as myCppProjWrapper
...
I also found that if the "myproj" names are different, under <python-lib-dir>/<python-vers>/site-packages the .so and .egg-info names are different and the client fails to load it.
In addition I found that the client's environment does not need to have the cython package installed.

I had the same error for torchvision. FIxed it by downgrading the installation versions:
pip install torch==1.2.0+cu92 torchvision==0.4.0+cu92 -f https://download.pytorch.org/whl/torch_stable.html

How should I structure a Python package that contains Cython code

I'd like to make a Python package containing some Cython code. I've got the the Cython code working nicely. However, now I want to know how best to package it.
For most people who just want to install the package, I'd like to include the .c file that Cython creates, and arrange for setup.py to compile that to produce the module. Then the user doesn't need Cython installed in order to install the package.
But for people who may want to modify the package, I'd also like to provide the Cython .pyx files, and somehow also allow for setup.py to build them using Cython (so those users would need Cython installed).
How should I structure the files in the package to cater for both these scenarios?
The Cython documentation gives a little guidance. But it doesn't say how to make a single setup.py that handles both the with/without Cython cases.

I've done this myself now, in a Python package simplerandom (BitBucket repo - EDIT: now github) (I don't expect this to be a popular package, but it was a good chance to learn Cython).
This method relies on the fact that building a .pyx file with Cython.Distutils.build_ext (at least with Cython version 0.14) always seems to create a .c file in the same directory as the source .pyx file.
Here is a cut-down version of setup.py which I hope shows the essentials:
from distutils.core import setup
from distutils.extension import Extension
try:
from Cython.Distutils import build_ext
except ImportError:
use_cython = False
else:
use_cython = True
cmdclass = {}
ext_modules = []
if use_cython:
ext_modules += [
Extension("mypackage.mycythonmodule", ["cython/mycythonmodule.pyx"]),
]
cmdclass.update({'build_ext': build_ext})
else:
ext_modules += [
Extension("mypackage.mycythonmodule", ["cython/mycythonmodule.c"]),
]
setup(
name='mypackage',
...
cmdclass=cmdclass,
ext_modules=ext_modules,
...
)
I also edited MANIFEST.in to ensure that mycythonmodule.c is included in a source distribution (a source distribution that is created with python setup.py sdist):
...
recursive-include cython *
...
I don't commit mycythonmodule.c to version control 'trunk' (or 'default' for Mercurial). When I make a release, I need to remember to do a python setup.py build_ext first, to ensure that mycythonmodule.c is present and up-to-date for the source code distribution. I also make a release branch, and commit the C file into the branch. That way I have a historical record of the C file that was distributed with that release.

Adding to Craig McQueen's answer: see below for how to override the sdist command to have Cython automatically compile your source files before creating a source distribution.
That way your run no risk of accidentally distributing outdated C sources. It also helps in the case where you have limited control over the distribution process e.g. when automatically creating distributions from continuous integration etc.
from distutils.command.sdist import sdist as _sdist
...
class sdist(_sdist):
def run(self):
# Make sure the compiled Cython files in the distribution are up-to-date
from Cython.Build import cythonize
cythonize(['cython/mycythonmodule.pyx'])
_sdist.run(self)
cmdclass['sdist'] = sdist

http://docs.cython.org/en/latest/src/userguide/source_files_and_compilation.html#distributing-cython-modules
It is strongly recommended that you distribute the generated .c files as well as your Cython sources, so that users can install your module without needing to have Cython available.
It is also recommended that Cython compilation not be enabled by default in the version you distribute. Even if the user has Cython installed, he probably doesn’t want to use it just to install your module. Also, the version he has may not be the same one you used, and may not compile your sources correctly.
This simply means that the setup.py file that you ship with will just be a normal distutils file on the generated .c files, for the basic example we would have instead:
from distutils.core import setup
from distutils.extension import Extension
setup(
ext_modules = [Extension("example", ["example.c"])]
)

The easiest is to include both but just use the c-file? Including the .pyx file is nice, but it's not needed once you have the .c file anyway. People who want to recompile the .pyx can install Pyrex and do it manually.
Otherwise you need to have a custom build_ext command for distutils that builds the C file first. Cython already includes one. http://docs.cython.org/src/userguide/source_files_and_compilation.html
What that documentation doesn't do is say how to make this conditional, but
try:
from Cython.distutils import build_ext
except ImportError:
from distutils.command import build_ext
Should handle it.

Including (Cython) generated .c files are pretty weird. Especially when we include that in git. I'd prefer to use setuptools_cython. When Cython is not available, it will build an egg which has built-in Cython environment, and then build your code using the egg.
A possible example: https://github.com/douban/greenify/blob/master/setup.py
Update(2017-01-05):
Since setuptools 18.0, there's no need to use setuptools_cython. Here is an example to build Cython project from scratch without setuptools_cython.

All other answers either rely on
distutils
importing from Cython.Build, which creates a chicken-and-egg problem between requiring cython via setup_requires and importing it.
A modern solution is to use setuptools instead, see this answer (automatic handling of Cython extensions requires setuptools 18.0, i.e., it's available for many years already). A modern standard setup.py with requirements handling, an entry point, and a cython module could look like this:
from setuptools import setup, Extension
with open('requirements.txt') as f:
requirements = f.read().splitlines()
setup(
name='MyPackage',
install_requires=requirements,
setup_requires=[
'setuptools>=18.0', # automatically handles Cython extensions
'cython>=0.28.4',
],
entry_points={
'console_scripts': [
'mymain = mypackage.main:main',
],
},
ext_modules=[
Extension(
'mypackage.my_cython_module',
sources=['mypackage/my_cython_module.pyx'],
),
],
)

The simple hack I came up with:
from distutils.core import setup
try:
from Cython.Build import cythonize
except ImportError:
from pip import pip
pip.main(['install', 'cython'])
from Cython.Build import cythonize
setup(…)
Just install Cython if it could not be imported. One should probably not share this code, but for my own dependencies it's good enough.

This is a setup script I wrote which makes it easier to include nested directories inside the build. One needs to run it from folder within a package.
Givig structure like this:
__init__.py
setup.py
test.py
subdir/
__init__.py
anothertest.py
setup.py
from setuptools import setup, Extension
from Cython.Distutils import build_ext
# from os import path
ext_names = (
'test',
'subdir.anothertest',
)
cmdclass = {'build_ext': build_ext}
# for modules in main dir
ext_modules = [
Extension(
ext,
[ext + ".py"],
)
for ext in ext_names if ext.find('.') < 0]
# for modules in subdir ONLY ONE LEVEL DOWN!!
# modify it if you need more !!!
ext_modules += [
Extension(
ext,
["/".join(ext.split('.')) + ".py"],
)
for ext in ext_names if ext.find('.') > 0]
setup(
name='name',
ext_modules=ext_modules,
cmdclass=cmdclass,
packages=["base", "base.subdir"],
)
# Build --------------------------
# python setup.py build_ext --inplace
Happy compiling ;)

The easiest way I found using only setuptools instead of the feature limited distutils is
from setuptools import setup
from setuptools.extension import Extension
try:
from Cython.Build import cythonize
except ImportError:
use_cython = False
else:
use_cython = True
ext_modules = []
if use_cython:
ext_modules += cythonize('package/cython_module.pyx')
else:
ext_modules += [Extension('package.cython_module',
['package/cython_modules.c'])]
setup(name='package_name', ext_modules=ext_modules)

I think I found a pretty good way of doing this by providing a custom build_ext command. The idea is the following:
I add the numpy headers by overriding finalize_options() and doing import numpy in the body of the function, which nicely avoids the problem of numpy not being available before setup() installs it.
If cython is available on the system, it hooks into the command's check_extensions_list() method and by cythonizes all out-of-date cython modules, replacing them with C extensions that can later handled by the build_extension() method. We just provide the latter part of the functionality in our module too: this means that if cython is not available but we have a C extension present, it still works, which allows you to do source distributions.
Here's the code:
import re, sys, os.path
from distutils import dep_util, log
from setuptools.command.build_ext import build_ext
try:
import Cython.Build
HAVE_CYTHON = True
except ImportError:
HAVE_CYTHON = False
class BuildExtWithNumpy(build_ext):
def check_cython(self, ext):
c_sources = []
for fname in ext.sources:
cname, matches = re.subn(r"(?i)\.pyx$", ".c", fname, 1)
c_sources.append(cname)
if matches and dep_util.newer(fname, cname):
if HAVE_CYTHON:
return ext
raise RuntimeError("Cython and C module unavailable")
ext.sources = c_sources
return ext
def check_extensions_list(self, extensions):
extensions = [self.check_cython(ext) for ext in extensions]
return build_ext.check_extensions_list(self, extensions)
def finalize_options(self):
import numpy as np
build_ext.finalize_options(self)
self.include_dirs.append(np.get_include())
This allows one to just write the setup() arguments without worrying about imports and whether one has cython available:
setup(
# ...
ext_modules=[Extension("_my_fast_thing", ["src/_my_fast_thing.pyx"])],
setup_requires=['numpy'],
cmdclass={'build_ext': BuildExtWithNumpy}
)