Skip to content
Projects
Groups
Snippets
Help
Loading...
Help
Support
Keyboard shortcuts
?
Submit feedback
Contribute to GitLab
Sign in / Register
Toggle navigation
C
cython
Project overview
Project overview
Details
Activity
Releases
Repository
Repository
Files
Commits
Branches
Tags
Contributors
Graph
Compare
Issues
0
Issues
0
List
Boards
Labels
Milestones
Merge Requests
0
Merge Requests
0
Analytics
Analytics
Repository
Value Stream
Wiki
Wiki
Snippets
Snippets
Members
Members
Collapse sidebar
Close sidebar
Activity
Graph
Create a new issue
Commits
Issue Boards
Open sidebar
Boxiang Sun
cython
Commits
e3402907
Commit
e3402907
authored
May 30, 2014
by
Julien Delafontaine
Browse files
Options
Browse Files
Download
Email Patches
Plain Diff
Rewrote the 'Pure Python mode' tutorial and moved the 'Types' chapter to 'Language basics'.
parent
913d9a19
Changes
2
Show whitespace changes
Inline
Side-by-side
Showing
2 changed files
with
180 additions
and
105 deletions
+180
-105
docs/src/tutorial/pure.rst
docs/src/tutorial/pure.rst
+139
-88
docs/src/userguide/language_basics.rst
docs/src/userguide/language_basics.rst
+41
-17
No files found.
docs/src/tutorial/pure.rst
View file @
e3402907
...
...
@@ -4,20 +4,115 @@
Pure Python Mode
================
Cython provides language constructs to let the same file be either interpreted
or compiled. This is accomplished by the same "magic" module ``cython`` that
directives use and which must be imported. This is available for both :file:`.py` and
:file:`.pyx` files.
Sometimes one may want to speed up Python code without losing the possibility to run
it with the Python interpreter. While pure Python scripts can be compiled with Cython,
it usually results in a 20%-50% speed gain only.
To go beyond that, Cython provides language constructs to add static typing
and cythonic functionalities to a Python module to make it run much faster
when compiled, while still allowing it to be interpreted.
This is accomplished either via an augmenting :file:`.pxd` file, or
via special functions and decorators available after importing ``cython``.
Augmenting .pxd
---------------
Using an augmenting :file:`.pxd` allows to let the original :file:`.py` file
completely untouched. On the other hand, one needs to maintain both
the :file:`.pxd` and the :file:`.py` in parallel.
Note that this usage of the :file:`.pxd` is different of that when it is
accompanying a :file:`.pyx` file (see :doc:`pxd_files`).
If a :file:`.pxd` file is found with the same name as a :file:`.py` file,
it will be searched for :keyword:`cdef` classes and :keyword:`cdef`/:keyword:`cpdef`
functions and methods. It will then convert the corresponding
classes/functions/methods in the :file:`.py` file to be of the correct type.
Thus if one has a file :file:`A.py`::
def myfunction(x, y=2):
a = x-y
return a+(x*y)
class A:
def __init__(self, b=0):
self.a = 3
self.b = b
def foo(self, x):
print x + 1.0
and adds :file:`A.pxd`::
cpdef inline int myfunction(int x,int y):
cdef int a
cdef class A:
cdef public int a,b
cpdef foo(self, double x)
then at compilation time :file:`A.py` would be interpreted as::
cdef int myfunction(int x,int y):
cdef int a
a = x-y
return a+(x*y)
cdef class A:
cdef int a,b
def __init__(self, int b=0):
self.a = 3
self.b = b
cdef foo(self, double x):
print x + 1.0
while still letting the possibility of running the Python interpreter
as before with `python A.py`.
Note that in order to provide the Python wrappers to the :keyword:`cdef`
definitions in the :file:`.pxd`,
* functions are declared as `cpdef inline`;
* classes are declared as `cdef class`;
* class attributes are declared as `cdef public`;
* class methods are declared as `cpdef`.
Normal Python (:keyword:`def`) functions cannot be declared in
:file:`.pxd` files, so it is currently impossible to override the types of
Python functions in :file:`.pxd` files if they use ``*args`` or ``**kwargs``
in their signature, for instance.
This is accomplished via special functions and decorators and an (optional)
augmenting :file:`.pxd` file.
Magic Attributes
----------------
The currently supported attributes of the ``cython`` module are:
Special decorators are available using the ``cython`` module that can
be used to add static typing within the Python file, while being ignored
by the interpreter.
Their use is more limited than :file:`.pxd` extensions or usual Cython code,
and add the ``cython`` dependency to the original code. However they can
come in handy and do not require to maintain a supplementary file.
"Compiled" switch
^^^^^^^^^^^^^^^^^
* ``compiled`` is a special variable which is set to ``True`` when the compiler
runs, and ``False`` in the interpreter. Thus the code::
* ``declare`` declares a typed variable in the current scope, which can be used in
if cython.compiled:
print "Yep, I'm compiled."
else:
print "Just a lowly interpreted script."
will behave differently depending on whether or not the code is loaded as a
compiled :file:`.so` file or a plain :file:`.py` file.
Static typing
^^^^^^^^^^^^^
* ``cython.declare`` declares a typed variable in the current scope, which can be used in
place of the :samp:`cdef type var [= value]` construct. This has two forms, the
first as an assignment (useful as it creates a declaration in
interpreted mode as well)::
...
...
@@ -29,13 +124,17 @@ The currently supported attributes of the ``cython`` module are:
cython.declare(x=cython.int, y=cython.double) # cdef int x; cdef double y
* ``locals`` is a decorator that is used to specify the types of local variables
* ``
@cython.
locals`` is a decorator that is used to specify the types of local variables
in the function body (including any or all of the argument types)::
@cython.locals(a=cython.double, b=cython.double, n=cython.p_double)
def foo(a, b, x, y):
...
It cannot be used to type class constructor attributes.
* ``@cython.returns(<type>)`` specifies the function's return type.
* Starting with Cython 0.21, Python signature annotations can be used to
declare argument types. Cython recognises three ways to do this, as
shown in the following example::
...
...
@@ -46,6 +145,26 @@ The currently supported attributes of the ``cython`` module are:
explicit_c_type: {'ctype': 'int'}):
...
Extension types and cdef functions
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
* ``@cython.cclass`` creates a ``cdef class``.
* ``@cython.cfunc`` creates a :keyword:`cdef` function.
* ``@cython.ccall`` creates a :keyword:`cpdef` function.
* ``@cython.locals`` declares the argument types (see above).
* ``@cython.inline`` is the equivalent of the C ``inline`` modifier.
Here is an example of a :keyword:`cdef` function::
@cython.cfunc
@cython.returns(cython.bint)
@cython.locals(a=cython.int, b=cython.int)
def c_compare(a,b):
return a == b
Others attributes
^^^^^^^^^^^^^^^^^
* ``address`` is used in place of the ``&`` operator::
cython.declare(x=cython.int, x_ptr=cython.p_int)
...
...
@@ -55,7 +174,8 @@ The currently supported attributes of the ``cython`` module are:
expressions.::
cython.declare(n=cython.longlong)
print cython.sizeof(cython.longlong), cython.sizeof(n)
print cython.sizeof(cython.longlong)
print cython.sizeof(n)
* ``struct`` can be used to create struct types.::
...
...
@@ -71,51 +191,18 @@ The currently supported attributes of the ``cython`` module are:
cdef MyStruct a
* ``union`` creates union types with exactly the same syntax as ``struct``
* ``union`` creates union types with exactly the same syntax as ``struct``
.
* ``typedef`` creates a new type::
T = cython.typedef(cython.p_int) # ctypedef int* T
* ``compiled`` is a special variable which is set to ``True`` when the compiler
runs, and ``False`` in the interpreter. Thus the code::
if cython.compiled:
print "Yep, I'm compiled."
else:
print "Just a lowly interpreted script."
will behave differently depending on whether or not the code is loaded as a
compiled :file:`.so` file or a plain :file:`.py` file.
Augmenting .pxd
---------------
If a :file:`.pxd` file is found with the same name as a :file:`.py` file, it will be
searched for :keyword:`cdef` classes and :keyword:`cdef`/:keyword:`cpdef`
functions and methods. It will then convert the corresponding
classes/functions/methods in the :file:`.py` file to be of the correct type. Thus if
one had :file:`a.pxd`::
cdef class A:
cpdef foo(self, int i)
the file :file:`a.py`::
class A:
def foo(self, i):
print "Big" if i > 1000 else "Small"
would be interpreted as::
cdef class A:
cpdef foo(self, int i):
print "Big" if i > 1000 else "Small"
Magic Attributes within the .pxd
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
The special Cython module can also be imported and used within the augmenting
:file:`.pxd` file. This makes it possible to add types to a pure Python file without
changing the file itself. For example, the following Python file
:file:`dostuff.py`::
:file:`.pxd` file. For example, the following Python file :file:`dostuff.py`::
def dostuff(n):
t = 0
...
...
@@ -130,47 +217,11 @@ could be augmented with the following :file:`.pxd` file :file:`dostuff.pxd`::
@cython.locals(t = cython.int, i = cython.int)
cpdef int dostuff(int n)
Besides the ``cython.locals`` decorator, the :func:`cython.declare` function can also be
used to add types to global variables in the augmenting :file:`.pxd` file.
Note that normal Python (:keyword:`def`) functions cannot be declared in
:file:`.pxd` files, so it is currently impossible to override the types of
Python functions in :file:`.pxd` files if they use ``*args`` or ``**kwargs`` in their
signature, for instance.
Types
-----
There are numerous types built in to the Cython module. One has all the
standard C types, namely ``char``, ``short``, ``int``, ``long``, ``longlong``
as well as their unsigned versions ``uchar``, ``ushort``, ``uint``, ``ulong``,
``ulonglong``. One also has ``bint`` and ``Py_ssize_t``. For each type, there
are pointer types ``p_int``, ``pp_int``, . . ., up to three levels deep in
interpreted mode, and infinitely deep in compiled mode. The Python types int,
long and bool are interpreted as C ``int``, ``long`` and ``bint``
respectively. Also, the Python types ``list``, ``dict``, ``tuple``, . . . may
be used, as well as any user defined types.
Pointer types may be constructed with ``cython.pointer(cython.int)``, and
arrays as ``cython.int[10]``. A limited attempt is made to emulate these more
complex types, but only so much can be done from the Python language.
Extension types and cdef functions
-----------------------------------
Use the ``@cython.cclass`` decorator to create a ``cdef class``.
which is equivalent to::
Use the ``@cython.cfunc`` decorator for :keyword:`cdef` functions
and the ``@cython.ccall`` decorators for :keyword:`cpdef` functions
respectively. To declare the argument types, use the
``@cython.locals()`` decorator. For the return type, use
``@cython.returns(a_type)``. The C ``inline`` modifier is available
as ``@cython.inline`` decorator.
cpdef int dostuff(int n):
cdef int t,i
Here is an example of a :keyword:`cdef` function::
Besides the ``cython.locals`` decorator, the :func:`cython.declare` function can also be
used to add types to global variables in the augmenting :file:`.pxd` file.
@cython.cfunc
@cython.returns(cython.bint)
@cython.locals(a=cython.int, b=cython.int)
def c_compare(a,b):
return a == b
docs/src/userguide/language_basics.rst
View file @
e3402907
...
...
@@ -64,6 +64,30 @@ an anonymous :keyword:`enum` declaration for this purpose, for example,::
ctypedef int* IntPtr
Types
-----
There are numerous types built in to the Cython module. One has all the
standard C types, namely ``char``, ``short``, ``int``, ``long``, ``longlong``
as well as their unsigned versions ``uchar``, ``ushort``, ``uint``, ``ulong``,
``ulonglong``. One also has ``bint`` and ``Py_ssize_t``.
For each type, there are pointer types ``p_int``, ``pp_int``, . . ., up to
three levels deep in interpreted mode, and infinitely deep in compiled mode.
The Python types int, long and bool are interpreted as C ``int``, ``long``
and ``bint`` respectively.
Also, the Python types ``list``, ``dict``, ``tuple``, . . . may
be used, as well as any user defined types. However at the moment they add very
few in terms of optimization to a simple ``object`` typing.
Pointer types may be constructed with ``cython.pointer(cython.int)``, and
arrays as ``cython.int[10]``. A limited attempt is made to emulate these more
complex types, but only so much can be done from the Python language.
Grouping multiple C declarations
--------------------------------
...
...
Write
Preview
Markdown
is supported
0%
Try again
or
attach a new file
Attach a file
Cancel
You are about to add
0
people
to the discussion. Proceed with caution.
Finish editing this message first!
Cancel
Please
register
or
sign in
to comment