Commit 19a453c4 authored by Stefan Behnel's avatar Stefan Behnel

clarifications and simplifications in C queue wrapping tutorial

parent ac8538fb
......@@ -4,11 +4,10 @@ Using C libraries
Apart from writing fast code, one of the main use cases of Cython is
to call external C libraries from Python code. As Cython code
compiles down to C code itself, it is actually trivial to call C
functions directly in the code. You may have already seen this in the
simple tutorial on calling C functions. The following gives a
complete example for using (and wrapping) an external C library in
Cython code, including appropriate error handling and considerations
about designing a suitable API for Python and Cython code.
functions directly in the code. The following gives a complete
example for using (and wrapping) an external C library in Cython code,
including appropriate error handling and considerations about
designing a suitable API for Python and Cython code.
Imagine you need an efficient way to store integer values in a FIFO
queue. Since memory really matters, and the values are actually
......@@ -66,13 +65,20 @@ file, say, ``cqueue.pxd``::
bint queue_is_empty(Queue* queue)
Note how these declarations are almost identical to the header file
declarations, so you can often just copy them over. One noteworthy
difference is the first line. ``Queue`` is in this case used as an
*opaque handle*; only the library that is called knows what is really
inside. Since no Cython code needs to know the contents of the
struct, we do not need to declare its contents, so we simply provide
an empty definition (as we do not want to declare the ``_Queue`` type
which is referenced in the C header) [#]_.
declarations, so you can often just copy them over. However, you do
not need to provide *all* declarations as above, just those that you
use in your code or in other declarations, so that Cython gets to see
a sufficient and consistent subset of them. Then, consider adapting
them somewhat to make them more comfortable to work with in Cython.
One noteworthy difference to the header file that we use above is the
declaration of the ``Queue`` struct in the first line. ``Queue`` is
in this case used as an *opaque handle*; only the library that is
called knows what is really inside. Since no Cython code needs to
know the contents of the struct, we do not need to declare its
contents, so we simply provide an empty definition (as we do not want
to declare the ``_Queue`` type which is referenced in the C header)
[#]_.
.. [#] There's a subtle difference between ``cdef struct Queue: pass``
and ``ctypedef struct Queue: pass``. The former declares a
......@@ -82,20 +88,26 @@ which is referenced in the C header) [#]_.
libraries use the ``ctypedef`` kind of struct.
Another exception is the last line. The integer return value of the
``queue_is_empty`` method is actually a C boolean value, i.e. it is
either zero or non-zero, indicating if the queue is empty or not.
This is best expressed by Cython's ``bint`` type, which is a normal
``int`` type when used in C but maps to Python's boolean values
``True`` and ``False`` when converted to a Python object.
Next, we need to design the Queue class that should wrap the C queue.
It will live in a file called ``queue.pyx``. [#]_
``queue_is_empty()`` function is actually a C boolean value, i.e. the
only interesting thing about it is whether it is non-zero or zero,
indicating if the queue is empty or not. This is best expressed by
Cython's ``bint`` type, which is a normal ``int`` type when used in C
but maps to Python's boolean values ``True`` and ``False`` when
converted to a Python object. This way of tightening declarations in
a ``.pxd`` file can often simplify the code that uses them.
After declaring our C library, we can start to design the Queue class
that should wrap the C queue. It will live in a file called
``queue.pyx``. [#]_
.. [#] Note that the name of the ``.pyx`` file must be different from
the ``cqueue.pxd`` file with declarations from the C library,
as both do not describe the same code. A ``.pxd`` file next to
a ``.pyx`` file with the same name defines exported
declarations for code in the ``.pyx`` file.
declarations for code in the ``.pyx`` file. As the
``cqueue.pxd`` file contains declarations of a regular C
library, there must not be a ``.pyx`` file with the same name
that Cython associates with it.
Here is a first start for the Queue class::
......@@ -134,13 +146,9 @@ only reason why the above can fail is due to insufficient memory. In
that case, it will return ``NULL``, whereas it would normally return a
pointer to the new queue.
The normal Python way to get out of this is to raise an exception, but
in this specific case, allocating a new exception instance may
actually fail because we are running out of memory. Luckily, CPython
provides a function ``PyErr_NoMemory()`` that safely raises the right
exception for us. We can thus change the init function as follows::
The Python way to get out of this is to raise a ``MemoryError`` [#]_.
We can thus change the init function as follows::
cimport cpython.exc # standard cimport from CPython's C-API
cimport cqueue
cdef class Queue:
......@@ -148,13 +156,22 @@ exception for us. We can thus change the init function as follows::
def __cinit__(self):
self._c_queue = cqueue.queue_new()
if self._c_queue is NULL:
cpython.exc.PyErr_NoMemory()
The ``cpython`` package contains pre-defined ``.pxd`` files that ship
with Cython. If you need any CPython C-API functions, you can cimport
them from this package. See Cython's ``Cython/Includes/`` source
package for a complete list of ``.pxd`` files, including parts of the
standard C library.
raise MemoryError()
.. [#] In the specific case of a ``MemoryError``, creating a new
exception instance in order to raise it may actually fail because
we are running out of memory. Luckily, CPython provides a C-API
function ``PyErr_NoMemory()`` that safely raises the right
exception for us. As of version 0.14.1, Cython automatically
substitutes this C-API call whenever you write ``raise
MemoryError`` or ``raise MemoryError()``. If you use an older
version, you have to cimport the C-API function from the standard
package ``cpython.exc`` and call it directly. This package
contains pre-defined ``.pxd`` files that ship with Cython. If you
need any CPython C-API functions, you can cimport them from there.
See Cython's ``Cython/Includes/`` source package for a complete
list of provided ``.pxd`` files, including parts of the standard C
library.
The next thing to do is to clean up when the Queue instance is no
longer used (i.e. all references to it have been deleted). To this
......@@ -169,7 +186,7 @@ the init method::
At this point, we have a working Cython module that we can test. To
compile it, we need to configure a ``setup.py`` script for distutils.
Reusing the basic script from the main tutorial::
Here is the most basic script for compiling a Cython module::
from distutils.core import setup
from distutils.extension import Extension
......@@ -180,10 +197,10 @@ Reusing the basic script from the main tutorial::
ext_modules = [Extension("queue", ["queue.pyx"])]
)
We can extend this script to include the necessary setup for building
against the external C library. Assuming it's installed in the normal
places (e.g. under ``/usr/lib`` and ``/usr/include`` on a Unix-like
system), we could simply change the extension setup from
To build against the external C library, we must extend this script to
include the necessary setup. Assuming the library is installed in the
usual places (e.g. under ``/usr/lib`` and ``/usr/include`` on a
Unix-like system), we could simply change the extension setup from
::
......@@ -220,8 +237,8 @@ practice to look at what interfaces Python offers, e.g. in its
queue, it's enough to provide the methods ``append()``, ``peek()`` and
``pop()``, and additionally an ``extend()`` method to add multiple
values at once. Also, since we already know that all values will be
coming from C, it's better to provide only ``cdef`` methods for now,
and to give them a straight C interface.
coming from C, it's best to provide only ``cdef`` methods for now, and
to give them a straight C interface.
In C, it is common for data structures to store data as a ``void*`` to
whatever data item type. Since we only want to store ``int`` values,
......@@ -242,18 +259,18 @@ implementation instead::
cdef append(self, int value):
if not cqueue.queue_push_tail(self._c_queue,
<void*>value):
cpython.exc.PyErr_NoMemory()
raise MemoryError()
Adding an ``extend()`` method should now be straight forward::
cdef extend(self, int* values, Py_ssize_t count):
cdef extend(self, int* values, size_t count):
"""Append all ints to the queue.
"""
cdef Py_ssize_t i
cdef size_t i
for i in range(count):
if not cqueue.queue_push_tail(
self._c_queue, <void*>values[i]):
cpython.exc.PyErr_NoMemory()
raise MemoryError()
This becomes handy when reading values from a NumPy array, for
example.
......@@ -278,7 +295,7 @@ first case to raise an exception, whereas the second case should
simply return ``0``. To deal with this, we need to special case this
value, and check if the queue really is empty or not::
cdef int peek(self) except? 0:
cdef int peek(self) except? -1:
cdef int value = \
<int>cqueue.queue_peek_head(self._c_queue)
if value == 0:
......@@ -288,44 +305,66 @@ value, and check if the queue really is empty or not::
raise IndexError("Queue is empty")
return value
The ``except? 0`` declaration is worth explaining. If the function
was a Python function returning a Python object value, CPython would
simply return ``NULL`` instead of a Python object to indicate a raised
exception, which would immediately be propagated by the surrounding
code. The problem is that any ``int`` value is a valid queue item
value, so there is no way to explicitly indicate an error to the
calling code.
The only way CPython (and Cython) can deal with this situation is to
call ``PyErr_Occurred()`` when returning from a function to check if
an exception was raised, and if so, propagate the exception. This
Note how we have effectively created a fast path through the method in
the hopefully common cases that the return value is not ``0``. Only
that specific case needs an additional check if the queue is empty.
The ``except? -1`` declaration in the method signature falls into the
same category. If the function was a Python function returning a
Python object value, CPython would simply return ``NULL`` internally
instead of a Python object to indicate an exception, which would
immediately be propagated by the surrounding code. The problem is
that the return type is ``int`` and any ``int`` value is a valid queue
item value, so there is no way to explicitly signal an error to the
calling code. In fact, without such a declaration, there is no
obvious way for Cython to know what to return on exceptions and for
calling code to even know that this method *may* exit with an
exception.
The only way calling code can deal with this situation is to call
``PyErr_Occurred()`` when returning from a function to check if an
exception was raised, and if so, propagate the exception. This
obviously has a performance penalty. Cython therefore allows you to
indicate which value is explicitly returned in the case of an
declare which value it should implicitly return in the case of an
exception, so that the surrounding code only needs to check for an
exception when receiving this exact value. All other values will be
accepted almost without a penalty.
exception when receiving this exact value.
We chose to use ``-1`` as the exception return value as we expect it
to be an unlikely value to be put into the queue. The question mark
in the ``except? -1`` declaration indicates that the return value is
ambiguous (there *may* be a ``-1`` value in the queue, after all) and
that an additional exception check using ``PyErr_Occurred()`` is
needed in calling code. Without it, Cython code that calls this
method and receives the exception return value would silently (and
sometimes incorrectly) assume that an exception has been raised. In
any case, all other return values will be passed through almost
without a penalty, thus again creating a fast path for 'normal'
values.
Now that the ``peek()`` method is implemented, the ``pop()`` method
also needs adaptation. Since it removes a value from the queue,
however, it is not enough to test if the queue is empty *after* the
removal. Instead, we must test it on entry::
cdef int pop(self) except? 0:
cdef int pop(self) except? -1:
if cqueue.queue_is_empty(self._c_queue):
raise IndexError("Queue is empty")
return <int>cqueue.queue_pop_head(self._c_queue)
The return value for exception propagation is declared exactly as for
``peek()``.
Lastly, we can provide the Queue with an emptiness indicator in the
normal Python way by defining the ``__bool__()`` special method (note
that Python 2 calls this method ``__nonzero__``, whereas Cython code
can use both)::
normal Python way by implementing the ``__bool__()`` special method
(note that Python 2 calls this method ``__nonzero__``, whereas Cython
code can use either name)::
def __bool__(self):
return not cqueue.queue_is_empty(self._c_queue)
Note that this method returns either ``True`` or ``False`` as we
declared the return type of the ``queue_is_empty`` function as
``bint``.
``bint`` in ``cqueue.pxd``.
Now that the implementation is complete, you may want to write some
tests for it to make sure it works correctly. Especially doctests are
......@@ -345,14 +384,22 @@ The following listing shows the complete implementation that uses
``cpdef`` methods where possible::
cimport cqueue
cimport cpython.exc
cdef class Queue:
"""A queue class for C integer values.
>>> q = Queue()
>>> q.append(5)
>>> q.peek()
5
>>> q.pop()
5
"""
cdef cqueue.Queue* _c_queue
def __cinit__(self):
self._c_queue = cqueue.queue_new()
if self._c_queue is NULL:
cpython.exc.PyErr_NoMemory()
raise MemoryError()
def __dealloc__(self):
if self._c_queue is not NULL:
......@@ -361,16 +408,16 @@ The following listing shows the complete implementation that uses
cpdef append(self, int value):
if not cqueue.queue_push_tail(self._c_queue,
<void*>value):
cpython.exc.PyErr_NoMemory()
raise MemoryError()
cdef extend(self, int* values, Py_ssize_t count):
cdef Py_ssize_t i
cdef extend(self, int* values, size_t count):
cdef size_t i
for i in xrange(count):
if not cqueue.queue_push_tail(
self._c_queue, <void*>values[i]):
cpython.exc.PyErr_NoMemory()
raise MemoryError()
cpdef int peek(self) except? 0:
cpdef int peek(self) except? -1:
cdef int value = \
<int>cqueue.queue_peek_head(self._c_queue)
if value == 0:
......@@ -380,7 +427,7 @@ The following listing shows the complete implementation that uses
raise IndexError("Queue is empty")
return value
cdef int pop(self) except? 0:
cdef int pop(self) except? -1:
if cqueue.queue_is_empty(self._c_queue):
raise IndexError("Queue is empty")
return <int>cqueue.queue_pop_head(self._c_queue)
......@@ -394,23 +441,23 @@ types. However, if wanted, we can rename the C-ish ``extend()``
method to e.g. ``c_extend()``, and write a new ``extend()`` method
instead that accepts an arbitrary Python iterable::
cdef c_extend(self, int* values, Py_ssize_t count):
cdef Py_ssize_t i
cdef c_extend(self, int* values, size_t count):
cdef size_t i
for i in range(count):
if not cqueue.queue_push_tail(
self._c_queue, <void*>values[i]):
cpython.exc.PyErr_NoMemory()
raise MemoryError()
cpdef extend(self, values):
for value in values:
self.append(value)
As a quick test with numbers from 0 to 9999 on the author's machine
indicates, using this Queue from Cython code with C ``int`` values is
about five times as fast as using it from Cython code with Python
values, almost eight times faster than using it from Python code in a
Python loop, and still more than twice as fast as using Python's
highly optimised ``collections.deque`` type from Cython code with
Python integers.
As a quick test with 10000 numbers on the author's machine indicates,
using this Queue from Cython code with C ``int`` values is about five
times as fast as using it from Cython code with Python object values,
almost eight times faster than using it from Python code in a Python
loop, and still more than twice as fast as using Python's highly
optimised ``collections.deque`` type from Cython code with Python
integers.
.. [CAlg] Simon Howard, C Algorithms library, http://c-algorithms.sourceforge.net/
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