kivy-ios/recipes/numpy/__init__.py

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from toolchain import CythonRecipe
from os.path import join
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import sh
import shutil
class NumpyRecipe(CythonRecipe):
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version = "1.9.1"
url = "http://pypi.python.org/packages/source/n/numpy/numpy-{version}.tar.gz"
library = "libnumpy.a"
libraries = ["libnpymath.a", "libnpysort.a"]
include_dir = "numpy/core/include"
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depends = ["python"]
pbx_frameworks = ["Accelerate"]
cythonize = False
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def prebuild_arch(self, arch):
if self.has_marker("patched"):
return
self.apply_patch("numpy-1.9.1.patch")
self.set_marker("patched")
def get_recipe_env(self, arch):
env = super(NumpyRecipe, self).get_recipe_env(arch)
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# CC must have the CFLAGS with arm arch, because numpy tries first to
# compile and execute an empty C to see if the compiler works. This is
# obviously not working when crosscompiling
env["CC"] = "{} {}".format(env["CC"], env["CFLAGS"])
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# Numpy configuration. Don't try to compile anything related to it,
# we're going to use the Accelerate framework
env["NPYCONFIG"] = "env BLAS=None LAPACK=None ATLAS=None"
return env
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def build_arch(self, arch):
super(NumpyRecipe, self).build_arch(arch)
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sh.cp(sh.glob(join(self.build_dir, "build", "temp.*", "libnpy*.a")),
self.build_dir)
def reduce_python_package(self):
dest_dir = join(self.ctx.site_packages_dir, "numpy")
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shutil.rmtree(join(dest_dir, "core", "include"))
shutil.rmtree(join(dest_dir, "core", "tests"))
shutil.rmtree(join(dest_dir, "distutils"))
shutil.rmtree(join(dest_dir, "doc"))
shutil.rmtree(join(dest_dir, "f2py", "tests"))
shutil.rmtree(join(dest_dir, "fft", "tests"))
shutil.rmtree(join(dest_dir, "lib", "tests"))
shutil.rmtree(join(dest_dir, "ma", "tests"))
shutil.rmtree(join(dest_dir, "matrixlib", "tests"))
shutil.rmtree(join(dest_dir, "polynomial", "tests"))
shutil.rmtree(join(dest_dir, "random", "tests"))
shutil.rmtree(join(dest_dir, "tests"))
recipe = NumpyRecipe()