Commit 640fe60b authored by Stefan Behnel's avatar Stefan Behnel

Merge branch 'master' of git+ssh://github.com/cython/cython

parents f13b7c0a 4ed665be
......@@ -43,9 +43,10 @@ from . import Future
from ..Debugging import print_call_chain
from .DebugFlags import debug_disposal_code, debug_temp_alloc, \
debug_coercion
from .Pythran import to_pythran, is_pythran_supported_type, is_pythran_supported_operation_type, \
is_pythran_expr, pythran_func_type, pythran_binop_type, pythran_unaryop_type, has_np_pythran, \
pythran_indexing_code, pythran_indexing_type, is_pythran_supported_node_or_none, pythran_type
from .Pythran import (to_pythran, is_pythran_supported_type, is_pythran_supported_operation_type,
is_pythran_expr, pythran_func_type, pythran_binop_type, pythran_unaryop_type, has_np_pythran,
pythran_indexing_code, pythran_indexing_type, is_pythran_supported_node_or_none, pythran_type,
pythran_is_numpy_func_supported, pythran_get_func_include_file, pythran_functor)
from .PyrexTypes import PythranExpr
try:
......@@ -5408,7 +5409,8 @@ class SimpleCallNode(CallNode):
func_type = self.function_type()
self.is_numpy_call_with_exprs = False
if has_np_pythran(env) and self.function.is_numpy_attribute:
if (has_np_pythran(env) and function.is_numpy_attribute and
pythran_is_numpy_func_supported(function)):
has_pythran_args = True
self.arg_tuple = TupleNode(self.pos, args = self.args)
self.arg_tuple = self.arg_tuple.analyse_types(env)
......@@ -5416,12 +5418,12 @@ class SimpleCallNode(CallNode):
has_pythran_args &= is_pythran_supported_node_or_none(arg)
self.is_numpy_call_with_exprs = bool(has_pythran_args)
if self.is_numpy_call_with_exprs:
env.add_include_file("pythonic/numpy/%s.hpp" % self.function.attribute)
env.add_include_file(pythran_get_func_include_file(function))
return NumPyMethodCallNode.from_node(
self,
function=self.function,
function=function,
arg_tuple=self.arg_tuple,
type=PythranExpr(pythran_func_type(self.function.attribute, self.arg_tuple.args)),
type=PythranExpr(pythran_func_type(function, self.arg_tuple.args)),
)
elif func_type.is_pyobject:
self.arg_tuple = TupleNode(self.pos, args = self.args)
......@@ -5839,10 +5841,10 @@ class NumPyMethodCallNode(SimpleCallNode):
code.putln("// function evaluation code for numpy function")
code.putln("__Pyx_call_destructor(%s);" % self.result())
code.putln("new (&%s) decltype(%s){pythonic::numpy::functor::%s{}(%s)};" % (
code.putln("new (&%s) decltype(%s){%s{}(%s)};" % (
self.result(),
self.result(),
self.function.attribute,
pythran_functor(self.function),
", ".join(a.pythran_result() for a in args)))
......
......@@ -613,7 +613,8 @@ class TrackNumpyAttributes(VisitorTransform, SkipDeclarations):
def visit_AttributeNode(self, node):
self.visitchildren(node)
if node.obj.is_name and node.obj.name in self.numpy_module_names:
if (node.obj.is_name and node.obj.name in self.numpy_module_names) or \
node.obj.is_numpy_attribute:
node.is_numpy_attribute = True
return node
......
......@@ -6,16 +6,20 @@ from .PyrexTypes import CType, CTypedefType, CStructOrUnionType
import cython
try:
import pythran
_pythran_available = True
except ImportError:
_pythran_available = False
# Pythran/Numpy specific operations
def has_np_pythran(env):
while env is not None:
directives = getattr(env, 'directives', None)
if directives and env.directives.get('np_pythran', False):
return True
env = env.outer_scope
if env is None:
return False
directives = getattr(env, 'directives', None)
return (directives and directives.get('np_pythran', False))
@cython.ccall
def is_pythran_supported_dtype(type_):
......@@ -111,10 +115,32 @@ def pythran_indexing_type(type_, indices):
def pythran_indexing_code(indices):
return _index_access(_index_code, indices)
def np_func_to_list(func):
if not func.is_numpy_attribute:
return []
return np_func_to_list(func.obj) + [func.attribute]
if _pythran_available:
def pythran_is_numpy_func_supported(func):
CurF = pythran.tables.MODULES['numpy']
FL = np_func_to_list(func)
for F in FL:
CurF = CurF.get(F, None)
if CurF is None:
return False
return True
else:
def pythran_is_numpy_func_supported(name):
return False
def pythran_functor(func):
func = np_func_to_list(func)
submodules = "::".join(func[:-1] + ["functor"])
return "pythonic::numpy::%s::%s" % (submodules, func[-1])
def pythran_func_type(func, args):
args = ",".join(("std::declval<%s>()" % pythran_type(a.type) for a in args))
return "decltype(pythonic::numpy::functor::%s{}(%s))" % (func, args)
return "decltype(%s{}(%s))" % (pythran_functor(func), args)
@cython.ccall
......@@ -168,6 +194,9 @@ def is_pythran_buffer(type_):
return (type_.is_numpy_buffer and is_pythran_supported_dtype(type_.dtype) and
type_.mode in ("c", "strided") and not type_.cast)
def pythran_get_func_include_file(func):
func = np_func_to_list(func)
return "pythonic/include/numpy/%s.hpp" % "/".join(func)
def include_pythran_generic(env):
# Generic files
......
......@@ -6,14 +6,27 @@
Source Files and Compilation
****************************
.. note:: See :ref:`compilation-reference` reference section for more details
Cython source file names consist of the name of the module followed by a
``.pyx`` extension, for example a module called primes would have a source
file named :file:`primes.pyx`.
Cython code, unlike Python, must be compiled. This happens in two stages:
* A ``.pyx`` file is compiled by Cython to a ``.c`` file.
* The ``.c`` file is compiled by a C compiler to a ``.so`` file (or a
``.pyd`` file on Windows)
Once you have written your ``.pyx`` file, there are a couple of ways of turning it
into an extension module. One way is to compile it manually with the Cython
into an extension module.
The following sub-sections describe several ways to build your
extension modules, and how to pass directives to the Cython compiler.
Compiling from the command line
===============================
One way is to compile it manually with the Cython
compiler, e.g.:
.. sourcecode:: text
......@@ -54,6 +67,164 @@ current directory use:
$ python setup.py build_ext --inplace
Configuring the C-Build
------------------------
If you have include files in non-standard places you can pass an
``include_path`` parameter to ``cythonize``::
from distutils.core import setup
from Cython.Build import cythonize
setup(
name="My hello app",
ext_modules=cythonize("src/*.pyx", include_path=[...]),
)
Often, Python packages that offer a C-level API provide a way to find
the necessary include files, e.g. for NumPy::
include_path = [numpy.get_include()]
.. note::
Using memoryviews or importing NumPy with ``import numpy`` does not mean that
you have to add the path to NumPy include files. You need to add this path only
if you use ``cimport numpy``.
Despite this, you will still get warnings like the
following from the compiler, because Cython is using a deprecated Numpy API::
.../include/numpy/npy_1_7_deprecated_api.h:15:2: warning: #warning "Using deprecated NumPy API, disable it by " "#defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
For the time being, it is just a warning that you can ignore.
If you need to specify compiler options, libraries to link with or other
linker options you will need to create ``Extension`` instances manually
(note that glob syntax can still be used to specify multiple extensions
in one line)::
from distutils.core import setup
from distutils.extension import Extension
from Cython.Build import cythonize
extensions = [
Extension("primes", ["primes.pyx"],
include_dirs=[...],
libraries=[...],
library_dirs=[...]),
# Everything but primes.pyx is included here.
Extension("*", ["*.pyx"],
include_dirs=[...],
libraries=[...],
library_dirs=[...]),
]
setup(
name="My hello app",
ext_modules=cythonize(extensions),
)
Note that when using setuptools, you should import it before Cython as
setuptools may replace the ``Extension`` class in distutils. Otherwise,
both might disagree about the class to use here.
Note also that if you use setuptools instead of distutils, the default
action when running ``python setup.py install`` is to create a zipped
``egg`` file which will not work with ``cimport`` for ``pxd`` files
when you try to use them from a dependent package.
To prevent this, include ``zip_safe=False`` in the arguments to ``setup()``.
If your options are static (for example you do not need to call a tool like
``pkg-config`` to determine them) you can also provide them directly in your
.pyx or .pxd source file using a special comment block at the start of the file::
# distutils: libraries = spam eggs
# distutils: include_dirs = /opt/food/include
If you cimport multiple .pxd files defining libraries, then Cython
merges the list of libraries, so this works as expected (similarly
with other options, like ``include_dirs`` above).
If you have some C files that have been wrapped with Cython and you want to
compile them into your extension, you can define the distutils ``sources``
parameter::
# distutils: sources = helper.c, another_helper.c
Note that these sources are added to the list of sources of the current
extension module. Spelling this out in the :file:`setup.py` file looks
as follows::
from distutils.core import setup
from Cython.Build import cythonize
from distutils.extension import Extension
sourcefiles = ['example.pyx', 'helper.c', 'another_helper.c']
extensions = [Extension("example", sourcefiles)]
setup(
ext_modules=cythonize(extensions)
)
The :class:`Extension` class takes many options, and a fuller explanation can
be found in the `distutils documentation`_. Some useful options to know about
are ``include_dirs``, ``libraries``, and ``library_dirs`` which specify where
to find the ``.h`` and library files when linking to external libraries.
.. _distutils documentation: https://docs.python.org/extending/building.html
Sometimes this is not enough and you need finer customization of the
distutils :class:`Extension`.
To do this, you can provide a custom function ``create_extension``
to create the final :class:`Extension` object after Cython has processed
the sources, dependencies and ``# distutils`` directives but before the
file is actually Cythonized.
This function takes 2 arguments ``template`` and ``kwds``, where
``template`` is the :class:`Extension` object given as input to Cython
and ``kwds`` is a :class:`dict` with all keywords which should be used
to create the :class:`Extension`.
The function ``create_extension`` must return a 2-tuple
``(extension, metadata)``, where ``extension`` is the created
:class:`Extension` and ``metadata`` is metadata which will be written
as JSON at the top of the generated C files. This metadata is only used
for debugging purposes, so you can put whatever you want in there
(as long as it can be converted to JSON).
The default function (defined in ``Cython.Build.Dependencies``) is::
def default_create_extension(template, kwds):
if 'depends' in kwds:
include_dirs = kwds.get('include_dirs', []) + ["."]
depends = resolve_depends(kwds['depends'], include_dirs)
kwds['depends'] = sorted(set(depends + template.depends))
t = template.__class__
ext = t(**kwds)
metadata = dict(distutils=kwds, module_name=kwds['name'])
return ext, metadata
In case that you pass a string instead of an :class:`Extension` to
``cythonize()``, the ``template`` will be an :class:`Extension` without
sources. For example, if you do ``cythonize("*.pyx")``,
the ``template`` will be ``Extension(name="*.pyx", sources=[])``.
Just as an example, this adds ``mylib`` as library to every extension::
from Cython.Build.Dependencies import default_create_extension
def my_create_extension(template, kwds):
libs = kwds.get('libraries', []) + ["mylib"]
kwds['libraries'] = libs
return default_create_extension(template, kwds)
ext_modules = cythonize(..., create_extension=my_create_extension)
.. note::
If you Cythonize in parallel (using the ``nthreads`` argument),
then the argument to ``create_extension`` must be pickleable.
In particular, it cannot be a lambda function.
Multiple Cython Files in a Package
===================================
......
Markdown is supported
0%
or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment