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cffi / doc / source / index.rst

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CFFI documentation
================================

.. toctree::
   :maxdepth: 2

Foreign Function Interface for Python calling C code. The aim of this project
is to provide a convenient and reliable way of calling C code from Python.
The interface is based on `LuaJIT's FFI`_ and follows a few principles:

* The goal is to call C code from Python.  You should be able to do so
  without learning a 3rd language: every alternative requires you to learn
  their own language (Cython_, SWIG_) or API (ctypes_).  So we tried to
  assume that you know Python and C and minimize the extra bits of API that
  you need to learn.

* Keep all the Python-related logic in Python so that you don't need to
  write much C code (unlike `CPython native C extensions`_).

* Work either at the level of the ABI (Application Binary Interface)
  or the API (Application Programming Interface).  Usually, C
  libraries have a specified C API but often not an ABI (e.g. they may
  document a "struct" as having at least these fields, but maybe more).
  (ctypes_ works at the ABI level, whereas Cython_ and `native C extensions`_
  work at the API level.)

* We try to be complete.  For now some C99 constructs are not supported,
  but all C89 should be, including macros (and including macro "abuses",
  which you can `manually wrap`_ in saner-looking C functions).

* We attempt to support both PyPy and CPython, with a reasonable path
  for other Python implementations like IronPython and Jython.

* Note that this project is **not** about embedding executable C code in
  Python, unlike `Weave`_.  This is about calling existing C libraries
  from Python.

.. _`LuaJIT's FFI`: http://luajit.org/ext_ffi.html
.. _`Cython`: http://www.cython.org
.. _`SWIG`: http://www.swig.org/
.. _`CPython native C extensions`: http://docs.python.org/extending/extending.html
.. _`native C extensions`: http://docs.python.org/extending/extending.html
.. _`ctypes`: http://docs.python.org/library/ctypes.html
.. _`Weave`: http://www.scipy.org/Weave
.. _`manually wrap`: `The verification step`_


Installation and Status
=======================================================

Quick installation:

* ``pip install cffi``

* or get the source code via the `Python Package Index`__.

.. __: http://pypi.python.org/pypi/cffi

In more details:

This code has been developed on Linux but should work on any POSIX
platform as well as on Win32.  There are some Windows-specific issues
left.

It supports CPython 2.6; 2.7; 3.x (tested with 3.2 and 3.3);
and PyPy 2.0 beta2 or later.

Its speed is comparable to ctypes on CPython (a bit faster but a higher
warm-up time).  It is already faster on PyPy (1.5x-2x), but not yet
*much* faster; stay tuned.

Requirements:

* CPython 2.6 or 2.7 or 3.x, or PyPy 2.0 beta2

* on CPython you need to build the C extension module, so you need
  ``python-dev`` and ``libffi-dev`` (for Windows, libffi is included
  with CFFI).

* pycparser >= 2.06: http://code.google.com/p/pycparser/
  (Note that in old downloads of 2.08, the tarball contained an
  installation issue; it was fixed without changing the version number.)

* a C compiler is required to use CFFI during development, but not to run
  correctly-installed programs that use CFFI.

* `py.test`_ is needed to run the tests of CFFI.

.. _`py.test`: http://pypi.python.org/pypi/pytest

Download and Installation:

* http://pypi.python.org/packages/source/c/cffi/cffi-0.7.1.tar.gz

   - Or grab the most current version by following the instructions below.

   - MD5: dcfbb32d9a757d515801463602e4c533

   - SHA: 44fa6b50d37b0b5be6a0bee7950a59ba9e373fb8

* Or get it from the `Bitbucket page`_:
  ``hg clone https://bitbucket.org/cffi/cffi``

* ``python setup.py install`` or ``python setup_base.py install``
  (should work out of the box on Linux or Windows; see below for
  `MacOS 10.6`_ or `Windows 64`_.)

* or you can directly import and use ``cffi``, but if you don't
  compile the ``_cffi_backend`` extension module, it will fall back
  to using internally ``ctypes`` (much slower; we recommend not to use it).

* running the tests: ``py.test c/ testing/`` (if you didn't
  install cffi yet, you may need ``python setup_base.py build``
  and ``PYTHONPATH=build/lib.xyz.../``)

.. _`Bitbucket page`: https://bitbucket.org/cffi/cffi

Demos:

* The `demo`_ directory contains a number of small and large demos
  of using ``cffi``.

* The documentation below is sketchy on the details; for now the
  ultimate reference is given by the tests, notably
  `testing/test_verify.py`_ and `testing/backend_tests.py`_.

.. _`demo`: https://bitbucket.org/cffi/cffi/src/default/demo
.. _`testing/backend_tests.py`: https://bitbucket.org/cffi/cffi/src/default/testing/backend_tests.py
.. _`testing/test_verify.py`: https://bitbucket.org/cffi/cffi/src/default/testing/test_verify.py


Platform-specific instructions
------------------------------

``libffi`` is notoriously messy to install and use --- to the point that
CPython includes its own copy to avoid relying on external packages.
CFFI does the same for Windows, but not for other platforms (which should
have their own working libffi's).
Modern Linuxes work out of the box thanks to ``pkg-config``.  Here are some
(user-supplied) instructions for other platforms.


MacOS 10.6
++++++++++

(Thanks Juraj Sukop for this)

For building libffi you can use the default install path, but then, in
``setup.py`` you need to change::

    include_dirs = []

to::

    include_dirs = ['/usr/local/lib/libffi-3.0.11/include']

Then running ``python setup.py build`` complains about "fatal error: error writing to -: Broken pipe", which can be fixed by running::

    ARCHFLAGS="-arch i386 -arch x86_64" python setup.py build

as described here_.

.. _here: http://superuser.com/questions/259278/python-2-6-1-pycrypto-2-3-pypi-package-broken-pipe-during-build


Windows 64
++++++++++

Win32 works and is tested at least each official release.

Status: Win64 received very basic testing and we applied a few essential
fixes in cffi 0.7.  Please report any other issue.

Note as usual that this is only about running the 64-bit version of
Python on the 64-bit OS.  If you're running the 32-bit version (the
common case apparently), then you're running Win32 as far as we're
concerned.

.. _`issue 9`: https://bitbucket.org/cffi/cffi/issue/9
.. _`Python issue 7546`: http://bugs.python.org/issue7546



=======================================================

Examples
=======================================================


Simple example (ABI level)
--------------------------

.. code-block:: python

    >>> from cffi import FFI
    >>> ffi = FFI()
    >>> ffi.cdef("""
    ...     int printf(const char *format, ...);   // copy-pasted from the man page
    ... """)                                  
    >>> C = ffi.dlopen(None)                     # loads the entire C namespace
    >>> arg = ffi.new("char[]", "world")         # equivalent to C code: char arg[] = "world";
    >>> C.printf("hi there, %s!\n", arg)         # call printf
    hi there, world!

Note that on Python 3 you need to pass byte strings to ``char *``
arguments.  In the above example it would be ``b"world"`` and ``b"hi
there, %s!\n"``.  In general it is ``somestring.encode(myencoding)``.


Real example (API level)
------------------------

.. code-block:: python

    from cffi import FFI
    ffi = FFI()
    ffi.cdef("""     // some declarations from the man page
        struct passwd {
            char *pw_name;
            ...;
        };
        struct passwd *getpwuid(int uid);
    """)
    C = ffi.verify("""   // passed to the real C compiler
    #include <sys/types.h>
    #include <pwd.h>
    """, libraries=[])   # or a list of libraries to link with
    p = C.getpwuid(0)
    assert ffi.string(p.pw_name) == 'root'    # on Python 3: b'root'

Note that the above example works independently of the exact layout of
``struct passwd``.  It requires a C compiler the first time you run it,
unless the module is distributed and installed according to the
`Distributing modules using CFFI`_ intructions below.  See also the
note about `Cleaning up the __pycache__ directory`_.

You will find a number of larger examples using ``verify()`` in the
`demo`_ directory.

Struct/Array Example
--------------------

.. code-block:: python

    from cffi import FFI
    ffi = FFI()
    ffi.cdef("""
        typedef struct {
            unsigned char r, g, b;
        } pixel_t;
    """)
    image = ffi.new("pixel_t[]", 800*600)

    f = open('data', 'rb')     # binary mode -- important
    f.readinto(ffi.buffer(image))
    f.close()

    image[100].r = 255
    image[100].g = 192
    image[100].b = 128

    f = open('data', 'wb')
    f.write(ffi.buffer(image))
    f.close()

This can be used as a more flexible replacement of the struct_ and
array_ modules.  You could also call ``ffi.new("pixel_t[600][800]")``
and get a two-dimensional array.

.. _struct: http://docs.python.org/library/struct.html
.. _array: http://docs.python.org/library/array.html


What actually happened?
-----------------------

The CFFI interface operates on the same level as C - you declare types
and functions using the same syntax as you would define them in C.  This
means that most of the documentation or examples can be copied straight
from the man pages.

The declarations can contain types, functions and global variables.  The
cdef in the above examples are just that - they declared "there is a
function in the C level with this given signature", or "there is a
struct type with this shape".

The ``dlopen()`` line loads libraries.  C has multiple namespaces - a
global one and local ones per library. In this example we load the
global one (``None`` as argument to ``dlopen()``) which always contains
the standard C library.  You get as a result a ``<FFILibrary>`` object
that has as attributes all symbols declared in the ``cdef()`` and coming
from this library.

The ``verify()`` line in the second example is an alternative: instead
of doing a ``dlopen``, it generates and compiles a piece of C code.
When using ``verify()`` you have the advantage that you can use "``...``"
at various places in the ``cdef()``, and the missing information will
be completed with the help of the C compiler.  It also does checking,
to verify that your declarations are correct.  If the C compiler gives
warnings or errors, they are reported here.

Finally, the ``ffi.new()`` lines allocate C objects.  They are filled
with zeroes initially, unless the optional second argument is used.
If specified, this argument gives an "initializer", like you can use
with C code to initialize global variables.

The actual function calls should be obvious.  It's like C.

=======================================================

Distributing modules using CFFI
=======================================================

If you use CFFI and ``verify()`` in a project that you plan to
distribute, other users will install it on machines that may not have a
C compiler.  Here is how to write a ``setup.py`` script using
``distutils`` in such a way that the extension modules are listed too.
This lets normal ``setup.py`` commands compile and package the C
extension modules too.

Example::

  from setuptools import setup
  --OR--
  from distutils.core import setup

  # you must import at least the module(s) that define the ffi's
  # that you use in your application
  import yourmodule

  setup(...
        zip_safe=False,     # with setuptools only
        ext_modules=[yourmodule.ffi.verifier.get_extension()])

Warning: with ``setuptools``, you have to say ``zip_safe=False``,
otherwise it might or might not work, depending on which verifier engine
is used!  (I tried to find either workarounds or proper solutions but
failed so far.)

.. versionadded:: 0.4
   If your ``setup.py`` installs a whole package, you can put the extension
   in it too:

::
  
  setup(...
        zip_safe=False,
        ext_package='yourpackage',     # but see below!
        ext_modules=[yourmodule.ffi.verifier.get_extension()])

However in this case you must also give the same ``ext_package``
argument to the original call to ``ffi.verify()``::

  ffi.verify("...", ext_package='yourpackage')

Usually that's all you need, but see the `Reference: verifier`_ section
for more details about the ``verifier`` object.


Cleaning up the __pycache__ directory
-------------------------------------

During development, every time you change the C sources that you pass to
``cdef()`` or ``verify()``, then the latter will create a new module
file name, based on two CRC32 hashes computed from these strings.
This creates more
and more files in the ``__pycache__`` directory.  It is recommended that
you clean it up from time to time.  A nice way to do that is to add, in
your test suite, a call to ``cffi.verifier.cleanup_tmpdir()``.
Alternatively, you can just completely remove the ``__pycache__``
directory.




=======================================================

Reference
=======================================================

As a guideline: you have already seen in the above examples all the
major pieces except maybe ``ffi.cast()``.  The rest of this
documentation gives a more complete reference.


Declaring types and functions
-----------------------------

``ffi.cdef(source)`` parses the given C source.  This should be done
first.  It registers all the functions, types, and global variables in
the C source.  The types can be used immediately in ``ffi.new()`` and
other functions.  Before you can access the functions and global
variables, you need to give ``ffi`` another piece of information: where
they actually come from (which you do with either ``ffi.dlopen()`` or
``ffi.verify()``).

The C source is parsed internally (using ``pycparser``).  This code
cannot contain ``#include``.  It should typically be a self-contained
piece of declarations extracted from a man page.  The only things it
can assume to exist are the standard types:

* char, short, int, long, long long (both signed and unsigned)

* float, double, long double

* intN_t, uintN_t (for N=8,16,32,64), intptr_t, uintptr_t, ptrdiff_t,
  size_t, ssize_t

* wchar_t (if supported by the backend)

* *New in version 0.4:* _Bool.  If not directly supported by the C compiler,
  this is declared with the size of ``unsigned char``.

* *New in version 0.6:* bool.  In CFFI 0.4 or 0.5, you had to manually say
  ``typedef _Bool bool;``.  Now such a line is optional.

* *New in version 0.4:* FILE.  You can declare C functions taking a
  ``FILE *`` argument and call them with a Python file object.  If needed,
  you can also do ``c_f = ffi.cast("FILE *", fileobj)`` and then pass around
  ``c_f``.

* *New in version 0.6:* all `common Windows types`_ are defined if you run
  on Windows (``DWORD``, ``LPARAM``, etc.).

.. _`common Windows types`: http://msdn.microsoft.com/en-us/library/windows/desktop/aa383751%28v=vs.85%29.aspx

.. "versionadded:: 0.4": _Bool
.. "versionadded:: 0.6": bool
.. "versionadded:: 0.4": FILE
.. "versionadded:: 0.6": Wintypes

As we will see on `the verification step`_ below, the declarations can
also contain "``...``" at various places; these are placeholders that will
be completed by a call to ``verify()``.

.. versionadded:: 0.6
   The standard type names listed above are now handled as *defaults*
   only (apart from the ones that are keywords in the C language).
   If your ``cdef`` contains an explicit typedef that redefines one of
   the types above, then the default described above is ignored.  (This
   is a bit hard to implement cleanly, so in some corner cases it might
   fail, notably with the error ``Multiple type specifiers with a type
   tag``.  Please report it as a bug if it does.)


Loading libraries
-----------------

``ffi.dlopen(libpath, [flags])``: this function opens a shared library and
returns a module-like library object.  You need to use *either*
``ffi.dlopen()`` *or* ``ffi.verify()``, documented below_.

You can use the library object to call the functions previously declared
by ``ffi.cdef()``, and to read or write global variables.  Note that you
can use a single ``cdef()`` to declare functions from multiple
libraries, as long as you load each of them with ``dlopen()`` and access
the functions from the correct one.

The ``libpath`` is the file name of the shared library, which can
contain a full path or not (in which case it is searched in standard
locations, as described in ``man dlopen``), with extensions or not.
Alternatively, if ``libpath`` is None, it returns the standard C library
(which can be used to access the functions of glibc, on Linux).

This gives ABI-level access to the library: you need to have all types
declared manually exactly as they were while the library was made.  No
checking is done.  For this reason, we recommend to use ``ffi.verify()``
instead when possible.

Note that only functions and global variables are in library objects;
types exist in the ``ffi`` instance independently of library objects.
This is due to the C model: the types you declare in C are not tied to a
particular library, as long as you ``#include`` their headers; but you
cannot call functions from a library without linking it in your program,
as ``dlopen()`` does dynamically in C.

For the optional ``flags`` argument, see ``man dlopen`` (ignored on
Windows).  It defaults to ``ffi.RTLD_NOW``.

This function returns a "library" object that gets closed when it goes
out of scope.  Make sure you keep the library object around as long as
needed.

.. _below:


The verification step
---------------------

``ffi.verify(source, tmpdir=.., ext_package=.., modulename=.., **kwargs)``:
verifies that the current ffi signatures
compile on this machine, and return a dynamic library object.  The
dynamic library can be used to call functions and access global
variables declared by a previous ``ffi.cdef()``.  You don't need to use
``ffi.dlopen()`` in this case.

The returned library is a custom one, compiled just-in-time by the C
compiler: it gives you C-level API compatibility (including calling
macros, as long as you declared them as functions in ``ffi.cdef()``).
This differs from ``ffi.dlopen()``, which requires ABI-level
compatibility and must be called several times to open several shared
libraries.

On top of CPython, the new library is actually a CPython C extension
module.

The arguments to ``ffi.verify()`` are:

*  ``source``: C code that is pasted verbatim in the generated code (it
   is *not* parsed internally).  It should contain at least the
   necessary ``#include``.  It can also contain the complete
   implementation of some functions declared in ``cdef()``; this is
   useful if you really need to write a piece of C code, e.g. to access
   some advanced macros (see the example of ``getyx()`` in
   `demo/_curses.py`_).

*  ``sources``, ``include_dirs``,
   ``define_macros``, ``undef_macros``, ``libraries``,
   ``library_dirs``, ``extra_objects``, ``extra_compile_args``,
   ``extra_link_args`` (keyword arguments): these are used when
   compiling the C code, and are passed directly to distutils_.  You
   typically need at least ``libraries=['foo']`` in order to link with
   ``libfoo.so`` or ``libfoo.so.X.Y``, or ``foo.dll`` on Windows.  The
   ``sources`` is a list of extra .c files compiled and linked together.  See
   the distutils documentation for `more information about the other
   arguments`__.

.. __: http://docs.python.org/distutils/setupscript.html#library-options
.. _distutils: http://docs.python.org/distutils/setupscript.html#describing-extension-modules
.. _`demo/_curses.py`: https://bitbucket.org/cffi/cffi/src/default/demo/_curses.py

On the plus side, this solution gives more "C-like" flexibility:

*  functions taking or returning integer or float-point arguments can be
   misdeclared: if e.g. a function is declared by ``cdef()`` as taking a
   ``int``, but actually takes a ``long``, then the C compiler handles the
   difference.

*  other arguments are checked: you get a compilation warning or error
   if you pass a ``int *`` argument to a function expecting a ``long *``.

Moreover, you can use "``...``" in the following places in the ``cdef()``
for leaving details unspecified, which are then completed by the C
compiler during ``verify()``:

*  structure declarations: any ``struct`` that ends with "``...;``" is
   partial: it may be missing fields and/or have them declared out of order.
   This declaration will be corrected by the compiler.  (But note that you
   can only access fields that you declared, not others.)  Any ``struct``
   declaration which doesn't use "``...``" is assumed to be exact, but this is
   checked: you get a ``VerificationError`` if it is not.

*  unknown types: the syntax "``typedef ... foo_t;``" declares the type
   ``foo_t`` as opaque.  Useful mainly for when the API takes and returns
   ``foo_t *`` without you needing to look inside the ``foo_t``.  Also
   works with "``typedef ... *foo_p;``" which declares the pointer type
   ``foo_p`` without giving a name to the opaque type itself.  Note that
   such an opaque struct has no known size, which prevents some operations
   from working (mostly like in C).  *You cannot use this syntax to
   declare a specific type, like an integer type!  It declares opaque
   types only.*  In some cases you need to say that
   ``foo_t`` is not opaque, but you just don't know any field in it; then
   you would use "``typedef struct { ...; } foo_t;``".

*  array lengths: when used as structure fields, arrays can have an
   unspecified length, as in "``int n[];``" or "``int n[...];``".
   The length is completed by the C compiler.

*  enums: if you don't know the exact order (or values) of the declared
   constants, then use this syntax: "``enum foo { A, B, C, ... };``"
   (with a trailing "``...``").  The C compiler will be used to figure
   out the exact values of the constants.  An alternative syntax is
   "``enum foo { A=..., B, C };``" or even
   "``enum foo { A=..., B=..., C=... };``".  Like
   with structs, an ``enum`` without "``...``" is assumed to
   be exact, and this is checked.

*  integer macros: you can write in the ``cdef`` the line
   "``#define FOO ...``", with any macro name FOO.  Provided the macro
   is defined to be an integer value, this value will be available via
   an attribute of the library object returned by ``verify()``.  The
   same effect can be achieved by writing a declaration
   ``static const int FOO;``.  The latter is more general because it
   supports other types than integer types (note: the syntax is then
   to write the ``const`` together with the variable name, as in
   ``static char *const FOO;``).

Currently, it is not supported to find automatically which of the
various integer or float types you need at which place.  In the case of
function arguments or return type, when it is a simple integer/float
type, it may be misdeclared (if you misdeclare a function ``void
f(long)`` as ``void f(int)``, it still works, but you have to call it
with arguments that fit an int).  But it doesn't work any longer for
more complex types (e.g. you cannot misdeclare a ``int *`` argument as
``long *``) or in other locations (e.g. a global array ``int a[5];``
must not be declared ``long a[5];``).  CFFI considers all types listed
above__ as primitive (so ``long long a[5];`` and ``int64_t a[5]`` are
different declarations).

.. __: `Declaring types and functions`_

Note the following hack to find explicitly the size of any type, in
bytes::

    ffi.cdef("const int mysize;")
    lib = ffi.verify("const int mysize = sizeof(THE_TYPE);")
    print lib.mysize

Note that ``verify()`` is meant to call C libraries that are *not* using
``#include <Python.h>``.  The C functions are called without the GIL,
and afterwards we don't check if they set a Python exception, for
example.  You may work around it, but mixing CFFI with ``Python.h`` is
not recommended.

.. versionadded:: 0.4
   Unions used to crash ``verify()``.  Fixed.

.. versionadded:: 0.4
   The ``tmpdir`` argument to ``verify()`` controls where the C
   files are created and compiled.  By default it is
   ``directory_containing_the_py_file/__pycache__``, using the
   directory name of the .py file that contains the actual call to
   ``ffi.verify()``.  (This is a bit of a hack but is generally
   consistent with the location of the .pyc files for your library.
   The name ``__pycache__`` itself comes from Python 3.)

   The ``ext_package`` argument controls in which package the
   compiled extension module should be looked from.  This is
   only useful after `distributing modules using CFFI`_.

   The ``tag`` argument gives an extra string inserted in the
   middle of the extension module's name: ``_cffi_<tag>_<hash>``.
   Useful to give a bit more context, e.g. when debugging.

.. _`warning about modulename`:

.. versionadded:: 0.5
   The ``modulename`` argument can be used to force a specific module
   name, overriding the name ``_cffi_<tag>_<hash>``.  Use with care,
   e.g. if you are passing variable information to ``verify()`` but
   still want the module name to be always the same (e.g. absolute
   paths to local files).  In this case, no hash is computed and if
   the module name already exists it will be reused without further
   check.  Be sure to have other means of clearing the ``tmpdir``
   whenever you change your sources.

This function returns a "library" object that gets closed when it goes
out of scope.  Make sure you keep the library object around as long as
needed.


Working with pointers, structures and arrays
--------------------------------------------

The C code's integers and floating-point values are mapped to Python's
regular ``int``, ``long`` and ``float``.  Moreover, the C type ``char``
corresponds to single-character strings in Python.  (If you want it to
map to small integers, use either ``signed char`` or ``unsigned char``.)

Similarly, the C type ``wchar_t`` corresponds to single-character
unicode strings, if supported by the backend.  Note that in some
situations (a narrow Python build with an underlying 4-bytes wchar_t
type), a single wchar_t character may correspond to a pair of
surrogates, which is represented as a unicode string of length 2.  If
you need to convert such a 2-chars unicode string to an integer,
``ord(x)`` does not work; use instead ``int(ffi.cast('wchar_t', x))``.

Pointers, structures and arrays are more complex: they don't have an
obvious Python equivalent.  Thus, they correspond to objects of type
``cdata``, which are printed for example as
``<cdata 'struct foo_s *' 0xa3290d8>``.

``ffi.new(ctype, [initializer])``: this function builds and returns a
new cdata object of the given ``ctype``.  The ctype is usually some
constant string describing the C type.  It must be a pointer or array
type.  If it is a pointer, e.g. ``"int *"`` or ``struct foo *``, then
it allocates the memory for one ``int`` or ``struct foo``.  If it is
an array, e.g. ``int[10]``, then it allocates the memory for ten
``int``.  In both cases the returned cdata is of type ``ctype``.

The memory is initially filled with zeros.  An initializer can be given
too, as described later.

Example::

    >>> ffi.new("char *")
    <cdata 'char *' owning 1 bytes>
    >>> ffi.new("int *")
    <cdata 'int *' owning 4 bytes>
    >>> ffi.new("int[10]")
    <cdata 'int[10]' owning 40 bytes>

.. versionchanged:: 0.2
   Note that this changed from CFFI version 0.1: what used to be
   ``ffi.new("int")`` is now ``ffi.new("int *")``.

Unlike C, the returned pointer object has *ownership* on the allocated
memory: when this exact object is garbage-collected, then the memory is
freed.  If, at the level of C, you store a pointer to the memory
somewhere else, then make sure you also keep the object alive for as
long as needed.  (This also applies if you immediately cast the returned
pointer to a pointer of a different type: only the original object has
ownership, so you must keep it alive.  As soon as you forget it, then
the casted pointer will point to garbage!  In other words, the ownership
rules are attached to the *wrapper* cdata objects: they are not, and
cannot, be attached to the underlying raw memory.)  Example::

    global_weakkeydict = weakref.WeakKeyDictionary()

    s1   = ffi.new("struct foo *")
    fld1 = ffi.new("struct bar *")
    fld2 = ffi.new("struct bar *")
    s1.thefield1 = fld1
    s1.thefield2 = fld2
    # here the 'fld1' and 'fld2' object must not go away,
    # otherwise 's1.thefield1/2' will point to garbage!
    global_weakkeydict[s1] = (fld1, fld2)
    # now 's1' keeps alive 'fld1' and 'fld2'.  When 's1' goes
    # away, then the weak dictionary entry will be removed.

The cdata objects support mostly the same operations as in C: you can
read or write from pointers, arrays and structures.  Dereferencing a
pointer is done usually in C with the syntax ``*p``, which is not valid
Python, so instead you have to use the alternative syntax ``p[0]``
(which is also valid C).  Additionally, the ``p.x`` and ``p->x``
syntaxes in C both become ``p.x`` in Python.

.. versionchanged:: 0.2
   You will find ``ffi.NULL`` to use in the same places as the C ``NULL``.
   Like the latter, it is actually defined to be ``ffi.cast("void *", 0)``.
   In version 0.1, reading a NULL pointer used to return None;
   now it returns a regular ``<cdata 'type *' NULL>``, which you can
   check for e.g. by comparing it with ``ffi.NULL``.

There is no general equivalent to the ``&`` operator in C (because it
would not fit nicely in the model, and it does not seem to be needed
here).  But see ``ffi.addressof()`` below__.

__ `Misc methods on ffi`_

Any operation that would in C return a pointer or array or struct type
gives you a fresh cdata object.  Unlike the "original" one, these fresh
cdata objects don't have ownership: they are merely references to
existing memory.

As an exception to the above rule, dereferencing a pointer that owns a
*struct* or *union* object returns a cdata struct or union object
that "co-owns" the same memory.  Thus in this case there are two
objects that can keep the same memory alive.  This is done for cases where
you really want to have a struct object but don't have any convenient
place to keep alive the original pointer object (returned by
``ffi.new()``).

Example::

    ffi.cdef("void somefunction(int *);")
    lib = ffi.verify("#include <foo.h>")

    x = ffi.new("int *")      # allocate one int, and return a pointer to it
    x[0] = 42                 # fill it
    lib.somefunction(x)       # call the C function
    print x[0]                # read the possibly-changed value

The equivalent of C casts are provided with ``ffi.cast("type", value)``.
They should work in the same cases as they do in C.  Additionally, this
is the only way to get cdata objects of integer or floating-point type::

    >>> x = ffi.cast("int", 42)
    >>> x
    <cdata 'int' 42>
    >>> int(x)
    42

To cast a pointer to an int, cast it to ``intptr_t`` or ``uintptr_t``,
which are defined by C to be large enough integer types (example on 32
bits)::

    >>> int(ffi.cast("intptr_t", pointer_cdata))    # signed
    -1340782304
    >>> int(ffi.cast("uintptr_t", pointer_cdata))   # unsigned
    2954184992L

The initializer given as the optional second argument to ``ffi.new()``
can be mostly anything that you would use as an initializer for C code,
with lists or tuples instead of using the C syntax ``{ .., .., .. }``.
Example::

    typedef struct { int x, y; } foo_t;

    foo_t v = { 1, 2 };            // C syntax
    v = ffi.new("foo_t *", [1, 2]) # CFFI equivalent

    foo_t v = { .y=1, .x=2 };                // C99 syntax
    v = ffi.new("foo_t *", {'y': 1, 'x': 2}) # CFFI equivalent

Like C, arrays of chars can also be initialized from a string, in
which case a terminating null character is appended implicitly::

    >>> x = ffi.new("char[]", "hello")
    >>> x
    <cdata 'char[]' owning 6 bytes>
    >>> len(x)        # the actual size of the array
    6
    >>> x[5]          # the last item in the array
    '\x00'
    >>> x[0] = 'H'    # change the first item
    >>> ffi.string(x) # interpret 'x' as a regular null-terminated string
    'Hello'

Similarly, arrays of wchar_t can be initialized from a unicode string,
and calling ``ffi.string()`` on the cdata object returns the current unicode
string stored in the wchar_t array (encoding and decoding surrogates as
needed if necessary).

Note that unlike Python lists or tuples, but like C, you *cannot* index in
a C array from the end using negative numbers.

More generally, the C array types can have their length unspecified in C
types, as long as their length can be derived from the initializer, like
in C::

    int array[] = { 1, 2, 3, 4 };           // C syntax
    array = ffi.new("int[]", [1, 2, 3, 4])  # CFFI equivalent

As an extension, the initializer can also be just a number, giving
the length (in case you just want zero-initialization)::

    int array[1000];                  // C syntax
    array = ffi.new("int[1000]")      # CFFI 1st equivalent
    array = ffi.new("int[]", 1000)    # CFFI 2nd equivalent

This is useful if the length is not actually a constant, to avoid things
like ``ffi.new("int[%d]" % x)``.  Indeed, this is not recommended:
``ffi`` normally caches the string ``"int[]"`` to not need to re-parse
it all the time.


Python 3 support
----------------

Python 3 is supported, but the main point to note is that the ``char`` C
type corresponds to the ``bytes`` Python type, and not ``str``.  It is
your responsibility to encode/decode all Python strings to bytes when
passing them to or receiving them from CFFI.

This only concerns the ``char`` type and derivative types; other parts
of the API that accept strings in Python 2 continue to accept strings in
Python 3.


An example of calling a main-like thing
---------------------------------------

Imagine we have something like this:

.. code-block:: python

   from cffi import FFI
   ffi = FFI()
   ffi.cdef("""
      int main_like(int argv, char *argv[]);
   """)
   lib = ffi.dlopen("some_library.so")

Now, everything is simple, except, how do we create the ``char**`` argument
here?
The first idea:

.. code-block:: python

   lib.main_like(2, ["arg0", "arg1"])

does not work, because the initializer receives two Python ``str`` objects
where it was expecting ``<cdata 'char *'>`` objects.  You need to use
``ffi.new()`` explicitly to make these objects:

.. code-block:: python

   lib.main_like(2, [ffi.new("char[]", "arg0"),
                     ffi.new("char[]", "arg1")])

Note that the two ``<cdata 'char[]'>`` objects are kept alive for the
duration of the call: they are only freed when the list itself is freed,
and the list is only freed when the call returns.

If you want instead to build an "argv" variable that you want to reuse,
then more care is needed:

.. code-block:: python

   # DOES NOT WORK!
   argv = ffi.new("char *[]", [ffi.new("char[]", "arg0"),
                               ffi.new("char[]", "arg1")])

In the above example, the inner "arg0" string is deallocated as soon
as "argv" is built.  You have to make sure that you keep a reference
to the inner "char[]" objects, either directly or by keeping the list
alive like this:

.. code-block:: python

   argv_keepalive = [ffi.new("char[]", "arg0"),
                     ffi.new("char[]", "arg1")]
   argv = ffi.new("char *[]", argv_keepalive)


.. versionchanged:: 0.3
   In older versions, passing a list as the ``char *[]`` argument did
   not work; you needed to make an ``argv_keepalive`` and an ``argv``
   in all cases.


Function calls
--------------

When calling C functions, passing arguments follows mostly the same
rules as assigning to structure fields, and the return value follows the
same rules as reading a structure field.  For example::

    ffi.cdef("""
        int foo(short a, int b);
    """)
    lib = ffi.verify("#include <foo.h>")

    n = lib.foo(2, 3)     # returns a normal integer
    lib.foo(40000, 3)     # raises OverflowError

As an extension, you can pass to ``char *`` arguments a normal Python
string (but don't pass a normal Python string to functions that take a
``char *`` argument and may mutate it!)::

    ffi.cdef("""
        size_t strlen(const char *);
    """)
    C = ffi.dlopen(None)

    assert C.strlen("hello") == 5

You can also pass unicode strings as ``wchar_t *`` arguments.  Note that
in general, there is no difference between C argument declarations that
use ``type *`` or ``type[]``.  For example, ``int *`` is fully
equivalent to ``int[]`` or ``int[5]``.  So you can pass an ``int *`` as
a list of integers::

    ffi.cdef("""
        void do_something_with_array(int *array);
    """)
    lib.do_something_with_array([1, 2, 3, 4, 5])

CFFI supports passing and returning structs to functions and callbacks.
Example (sketch)::

    >>> ffi.cdef("""
    ...     struct foo_s { int a, b; };
    ...     struct foo_s function_returning_a_struct(void);
    ... """)
    >>> lib = ffi.verify("#include <somewhere.h>")
    >>> lib.function_returning_a_struct()
    <cdata 'struct foo_s' owning 8 bytes>

There are a few (obscure) limitations to the argument types and return
type.  You cannot pass directly as argument a union (but a **pointer**
to a union is fine), nor a struct which uses bitfields (but a
**pointer** to such a struct is fine).  If you pass a struct (not a
**pointer** to a struct), the struct type cannot have been declared with
"``...;``" and completed with ``verify()``; you need to declare it
completely in ``cdef()``.  You can work around these limitations by
writing a C function with a simpler signature in the code passed to
``ffi.verify()``, which calls the real C function.

Aside from these limitations, functions and callbacks can return structs.


Variadic function calls
-----------------------

Variadic functions in C (which end with "``...``" as their last
argument) can be declared and called normally, with the exception that
all the arguments passed in the variable part *must* be cdata objects.
This is because it would not be possible to guess, if you wrote this::

    C.printf("hello, %d\n", 42)

that you really meant the 42 to be passed as a C ``int``, and not a
``long`` or ``long long``.  The same issue occurs with ``float`` versus
``double``.  So you have to force cdata objects of the C type you want,
if necessary with ``ffi.cast()``::
  
    C.printf("hello, %d\n", ffi.cast("int", 42))
    C.printf("hello, %ld\n", ffi.cast("long", 42))
    C.printf("hello, %f\n", ffi.cast("double", 42))
    C.printf("hello, %s\n", ffi.new("char[]", "world"))


Callbacks
---------

C functions can also be viewed as ``cdata`` objects, and so can be
passed as callbacks.  To make new C callback objects that will invoke a
Python function, you need to use::

    >>> def myfunc(x, y):
    ...    return x + y
    ...
    >>> ffi.callback("int(int, int)", myfunc)
    <cdata 'int(*)(int, int)' calling <function myfunc at 0xf757bbc4>>

.. versionadded:: 0.4
   Or equivalently as a decorator:

    >>> @ffi.callback("int(int, int)")
    ... def myfunc(x, y):
    ...    return x + y

Note that you can also use a C *function pointer* type like ``"int(*)(int,
int)"`` (as opposed to a C *function* type like ``"int(int, int)"``).  It
is equivalent here.

Warning: like ffi.new(), ffi.callback() returns a cdata that has
ownership of its C data.  (In this case, the necessary C data contains
the libffi data structures to do a callback.)  This means that the
callback can only be invoked as long as this cdata object is alive.  If
you store the function pointer into C code, then make sure you also keep this
object alive for as long as the callback may be invoked.  (If you want
the callback to remain valid forever, store the object in a fresh global
variable somewhere.)

Note that callbacks of a variadic function type are not supported.  A
workaround is to add custom C code.  In the following example, a
callback gets a first argument that counts how many extra ``int``
arguments are passed::

    ffi.cdef("""
        int (*python_callback)(int how_many, int *values);
        void *const c_callback;   /* pass this ptr to C routines */
    """)
    lib = ffi.verify("""
        #include <stdarg.h>
        #include <alloca.h>
        static int (*python_callback)(int how_many, int *values);
        static int c_callback(int how_many, ...) {
            va_list ap;
            /* collect the "..." arguments into the values[] array */
            int i, *values = alloca(how_many * sizeof(int));
            va_start(ap, how_many);
            for (i=0; i<how_many; i++)
                values[i] = va_arg(ap, int);
            va_end(ap);
            return python_callback(how_many, values);
        }
    """)
    lib.python_callback = python_callback

Windows: you can't yet specify the calling convention of callbacks.
(For regular calls, the correct calling convention should be
automatically inferred by the C backend.)  Use an indirection, like
in the example just above.

Be careful when writing the Python callback function: if it returns an
object of the wrong type, or more generally raises an exception, then
the exception cannot be propagated.  Instead, it is printed to stderr
and the C-level callback is made to return a default value.

The returned value in case of errors is 0 or null by default, but can be
specified with the ``error`` keyword argument to ``ffi.callback()``::

    >>> ffi.callback("int(int, int)", myfunc, error=42)

In all cases the exception is printed to stderr, so this should be
used only as a last-resort solution.


Misc methods on ffi
-------------------

``ffi.include(other_ffi)``: includes the typedefs, structs, unions and
enum types defined in another FFI instance.  Usage is similar to a
``#include`` in C, where a part of the program might include types
defined in another part for its own usage.  Note that the include()
method has no effect on functions, constants and global variables, which
must anyway be accessed directly from the ``lib`` object returned by the
original FFI instance.  *Note that you should only use one ffi object
per library; the intended usage of ffi.include() is if you want to
interface with several inter-dependent libraries.*  For only one
library, make one ``ffi`` object.  (If the source becomes too large,
split it up e.g. by collecting the cdef/verify strings from multiple
Python modules, as long as you call ``ffi.verify()`` only once.)  *New
in version 0.5.*

.. "versionadded:: 0.5" --- inlined in the previous paragraph

``ffi.errno``: the value of ``errno`` received from the most recent C call
in this thread, and passed to the following C call, is available via
reads and writes of the property ``ffi.errno``.  On Windows we also save
and restore the ``GetLastError()`` value, but to access it you need to
declare and call the ``GetLastError()`` function as usual.

``ffi.string(cdata, [maxlen])``: return a Python string (or unicode
string) from the 'cdata'.  *New in version 0.3.*

.. "versionadded:: 0.3" --- inlined in the previous paragraph

- If 'cdata' is a pointer or array of characters or bytes, returns the
  null-terminated string.  The returned string extends until the first
  null character, or at most 'maxlen' characters.  If 'cdata' is an
  array then 'maxlen' defaults to its length.  See ``ffi.buffer()`` below
  for a way to continue past the first null character.  *Python 3:* this
  returns a ``bytes``, not a ``str``.

- If 'cdata' is a pointer or array of wchar_t, returns a unicode string
  following the same rules.

- If 'cdata' is a single character or byte or a wchar_t, returns it as a
  byte string or unicode string.  (Note that in some situation a single
  wchar_t may require a Python unicode string of length 2.)

- If 'cdata' is an enum, returns the value of the enumerator as a string.
  If the value is out of range, it is simply returned as the stringified
  integer.


``ffi.buffer(cdata, [size])``: return a buffer object that references
the raw C data pointed to by the given 'cdata', of 'size' bytes.  The
'cdata' must be a pointer or an array.  If unspecified, the size of the
buffer is either the size of what ``cdata`` points to, or the whole size
of the array.  Getting a buffer is useful because you can read from it
without an extra copy, or write into it to change the original value;
you can use for example ``file.write()`` and ``file.readinto()`` with
such a buffer (for files opened in binary mode).  (Remember that like in
C, you use ``array + index`` to get the pointer to the index'th item of
an array.)

.. versionchanged:: 0.4
   The returned object is not a built-in buffer nor memoryview object,
   because these objects' API changes too much across Python versions.
   Instead it has the following Python API (a subset of ``buffer``):

- ``buf[:]``: fetch a copy as a regular byte string (or
  ``buf[start:end]`` for a part)

- ``buf[:] = newstr``: change the original content (or ``buf[start:end]
  = newstr``)

- ``len(buf), buf[index], buf[index] = newchar``: access as a sequence
  of characters.

.. versionchanged:: 0.5
   The buffer object returned by ``ffi.buffer(cdata)`` keeps alive the
   ``cdata`` object: if it was originally an owning cdata, then its
   owned memory will not be freed as long as the buffer is alive.
   Moreover buffer objects now support weakrefs to them.


``ffi.typeof("C type" or cdata object)``: return an object of type
``<ctype>`` corresponding to the parsed string, or to the C type of the
cdata instance.  Usually you don't need to call this function or to
explicitly manipulate ``<ctype>`` objects in your code: any place that
accepts a C type can receive either a string or a pre-parsed ``ctype``
object (and because of caching of the string, there is no real
performance difference).  It can still be useful in writing typechecks,
e.g.::
  
    def myfunction(ptr):
        assert ffi.typeof(ptr) is ffi.typeof("foo_t*")
        ...

.. versionadded:: 0.4
   ``ffi.CData, ffi.CType``: the Python type of the objects referred to
   as ``<cdata>`` and ``<ctype>`` in the rest of this document.  Note
   that some cdata objects may be actually of a subclass of
   ``ffi.CData``, and similarly with ctype, so you should check with
   ``if isinstance(x, ffi.CData)``.  Also, ``<ctype>`` objects have
   a number of attributes for introspection: ``kind`` and ``cname`` are
   always present, and depending on the kind they may also have
   ``item``, ``length``, ``fields``, ``args``, ``result``, ``ellipsis``,
   ``abi``, ``elements`` and ``relements``.

``ffi.sizeof("C type" or cdata object)``: return the size of the
argument in bytes.  The argument can be either a C type, or a cdata object,
like in the equivalent ``sizeof`` operator in C.

``ffi.alignof("C type")``: return the alignment of the C type.
Corresponds to the ``__alignof__`` operator in GCC.

``ffi.offsetof("C struct type", "fieldname")``: return the offset within
the struct of the given field.  Corresponds to ``offsetof()`` in C.

``ffi.getctype("C type" or <ctype>, extra="")``: return the string
representation of the given C type.  If non-empty, the "extra" string is
appended (or inserted at the right place in more complicated cases); it
can be the name of a variable to declare, or an extra part of the type
like ``"*"`` or ``"[5]"``.  For example
``ffi.getctype(ffi.typeof(x), "*")`` returns the string representation
of the C type "pointer to the same type than x"; and
``ffi.getctype("char[80]", "a") == "char a[80]"``.

``ffi.gc(cdata, destructor)``: return a new cdata object that points to the
same data.  Later, when this new cdata object is garbage-collected,
``destructor(old_cdata_object)`` will be called.  Example of usage:
``ptr = ffi.gc(lib.malloc(42), lib.free)``.  Note that like objects
returned by ``ffi.new()``, the returned pointer objects have *ownership*,
which means the destructor is called as soon as *this* exact returned
object is garbage-collected.  *New in version 0.3* (together
with the fact that any cdata object can be weakly referenced).

.. "versionadded:: 0.3" --- inlined in the previous paragraph

``ffi.new_handle(python_object)``: return a non-NULL cdata of type
``void *`` that contains an opaque reference to ``python_object``.  You
can pass it around to C functions or store it into C structures.  Later,
you can use ``ffi.from_handle(p)`` to retrive the original
``python_object`` from a value with the same ``void *`` pointer.  The
cdata object returned by ``new_handle()`` has *ownership*, in the same
sense as ``ffi.new()`` or ``ffi.gc()``: the association ``void * ->
python_object`` is only valid as long as *this* exact cdata returned by
``new_handle()`` is alive.  *Calling ffi.from_handle(p) is invalid and
will likely crash if the cdata object returned by new_handle() is not
kept alive!* *New in version 0.7.*

.. "versionadded:: 0.7" --- inlined in the previous paragraph

``ffi.addressof(cdata, field=None)``: from a cdata whose type is
``struct foo_s``, return its "address", as a cdata whose type is
``struct foo_s *``.  Also works on unions, but not on any other type.
(It would be difficult because only structs and unions are internally
stored as an indirect pointer to the data.  If you need a C int whose
address can be taken, use ``ffi.new("int[1]")`` in the first place;
similarly, if it's a C pointer, use ``ffi.new("foo_t *[1]")``.)
If ``field`` is given,
returns the address of that field in the structure.  The returned
pointer is only valid as long as the original ``cdata`` object is; be
sure to keep it alive if it was obtained directly from ``ffi.new()``.
*New in version 0.4.*

.. "versionadded:: 0.4" --- inlined in the previous paragraph


Unimplemented features
----------------------

All of the ANSI C declarations should be supported, and some of C99.
Known missing features that are GCC or MSVC extensions:

* Any ``__attribute__`` or ``#pragma pack(n)``

* Additional types: complex numbers, special-size floating and fixed
  point types, vector types, and so on.  You might be able to access an
  array of complex numbers by declaring it as an array of ``struct
  my_complex { double real, imag; }``, but in general you should declare
  them as ``struct { ...; }`` and cannot access them directly.  This
  means that you cannot call any function which has an argument or
  return value of this type (this would need added support in libffi).
  You need to write wrapper functions in C, e.g. ``void
  foo_wrapper(struct my_complex c) { foo(c.real + c.imag*1j); }``, and
  call ``foo_wrapper`` rather than ``foo`` directly.

* Thread-local variables (access them via getter/setter functions)

* Variable-length structures, i.e. whose last field is a variable-length
  array (work around like in C, e.g. by declaring it as an array of
  length 0, allocating a ``char[]`` of the correct size, and casting
  it to a struct pointer)

.. versionadded:: 0.4
   Now supported: the common GCC extension of anonymous nested
   structs/unions inside structs/unions.

.. versionadded:: 0.6
   Enum types follow the GCC rules: they are defined as the first of
   ``unsigned int``, ``int``, ``unsigned long`` or ``long`` that fits
   all numeric values.  Note that the first choice is unsigned.  In CFFI
   0.5 and before, enums were always ``int``.  *Unimplemented: if the enum
   has very large values in C not declared in CFFI, the enum will incorrectly
   be considered as an int even though it is really a long!  Work around
   this by naming the largest value.  A similar but less important problem
   involves negative values.*


Debugging dlopen'ed C libraries
-------------------------------

A few C libraries are actually hard to use correctly in a ``dlopen()``
setting.  This is because most C libraries are intented for, and tested
with, a situation where they are *linked* with another program, using
either static linking or dynamic linking --- but from a program written
in C, at start-up, using the linker's capabilities instead of
``dlopen()``.

This can occasionally create issues.  You would have the same issues in
another setting than CFFI, like with ``ctypes`` or even plain C code that
calls ``dlopen()``.  This section contains a few generally useful
environment variables (on Linux) that can help when debugging these
issues.

**export LD_TRACE_LOADED_OBJECTS=all**

    provides a lot of information, sometimes too much depending on the
    setting.  Output verbose debugging information about the dynamic
    linker. If set to ``all`` prints all debugging information it has, if
    set to ``help`` prints a help message about which categories can be
    specified in this environment variable

**export LD_VERBOSE=1**

    (glibc since 2.1) If set to a nonempty string, output symbol
    versioning information about the program if querying information
    about the program (i.e., either ``LD_TRACE_LOADED_OBJECTS`` has been set,
    or ``--list`` or ``--verify`` options have been given to the dynamic
    linker).

**export LD_WARN=1**

    (ELF only)(glibc since 2.1.3) If set to a nonempty string, warn
    about unresolved symbols.


Reference: conversions
----------------------

This section documents all the conversions that are allowed when
*writing into* a C data structure (or passing arguments to a function
call), and *reading from* a C data structure (or getting the result of a
function call).  The last column gives the type-specific operations
allowed.

+---------------+------------------------+------------------+----------------+
|    C type     |   writing into         | reading from     |other operations|
+===============+========================+==================+================+
|   integers    | an integer or anything | a Python int or  | int()          |
|   and enums   | on which int() works   | long, depending  |                |
|   `(*****)`   | (but not a float!).    | on the type      |                |
|               | Must be within range.  |                  |                |
+---------------+------------------------+------------------+----------------+
|   ``char``    | a string of length 1   | a string of      | int()          |
|               | or another <cdata char>| length 1         |                |
+---------------+------------------------+------------------+----------------+
|  ``wchar_t``  | a unicode of length 1  | a unicode of     |                |
|               | (or maybe 2 if         | length 1         | int()          |
|               | surrogates) or         | (or maybe 2 if   |                |
|               | another <cdata wchar_t>| surrogates)      |                |
+---------------+------------------------+------------------+----------------+
|  ``float``,   | a float or anything on | a Python float   | float(), int() |
|  ``double``   | which float() works    |                  |                |
+---------------+------------------------+------------------+----------------+
|``long double``| another <cdata> with   | a <cdata>, to    | float(), int() |
|               | a ``long double``, or  | avoid loosing    |                |
|               | anything on which      | precision `(***)`|                |
|               | float() works          |                  |                |
+---------------+------------------------+------------------+----------------+
|  pointers     | another <cdata> with   | a <cdata>        |``[]`` `(****)`,|
|               | a compatible type (i.e.|                  |``+``, ``-``,   |
|               | same type or ``char*`` |                  |bool()          |
|               | or ``void*``, or as an |                  |                |
|               | array instead) `(*)`   |                  |                |
+---------------+------------------------+                  |                |
|  ``void *``,  | another <cdata> with   |                  |                |
|  ``char *``   | any pointer or array   |                  |                |
|               | type                   |                  |                |
+---------------+------------------------+                  +----------------+
|  pointers to  | same as pointers       |                  | ``[]``, ``+``, |
|  structure or |                        |                  | ``-``, bool(), |
|  union        |                        |                  | and read/write |
|               |                        |                  | struct fields  |
+---------------+------------------------+                  +----------------+
| function      | same as pointers       |                  | bool(),        |
| pointers      |                        |                  | call `(**)`    |
+---------------+------------------------+------------------+----------------+
|  arrays       | a list or tuple of     | a <cdata>        |len(), iter(),  |
|               | items                  |                  |``[]`` `(****)`,|
|               |                        |                  |``+``, ``-``    |
+---------------+------------------------+                  +----------------+
|  ``char[]``   | same as arrays, or a   |                  | len(), iter(), |
|               | Python string          |                  | ``[]``, ``+``, |
|               |                        |                  | ``-``          |
+---------------+------------------------+                  +----------------+
| ``wchar_t[]`` | same as arrays, or a   |                  | len(), iter(), |
|               | Python unicode         |                  | ``[]``,        |
|               |                        |                  | ``+``, ``-``   |
|               |                        |                  |                |
+---------------+------------------------+------------------+----------------+
| structure     | a list or tuple or     | a <cdata>        | read/write     |
|               | dict of the field      |                  | fields         |
|               | values, or a same-type |                  |                |
|               | <cdata>                |                  |                |
+---------------+------------------------+                  +----------------+
| union         | same as struct, but    |                  | read/write     |
|               | with at most one field |                  | fields         |
+---------------+------------------------+------------------+----------------+

.. versionchanged:: 0.3
   `(*)` Note that when calling a function, as per C, a ``item *`` argument
   is identical to a ``item[]`` argument.  So you can pass an argument that
   is accepted by either C type, like for example passing a Python string
   to a ``char *`` argument (because it works for ``char[]`` arguments)
   or a list of integers to a ``int *`` argument (it works for ``int[]``
   arguments).  Note that even if you want to pass a single ``item``,
   you need to specify it in a list of length 1; for example, a ``struct
   foo *`` argument might be passed as ``[[field1, field2...]]``.

As an optimization, the CPython version of CFFI assumes that a function
with a ``char *`` argument to which you pass a Python string will not
actually modify the array of characters passed in, and so passes directly
a pointer inside the Python string object.

.. versionchanged:: 0.3
   `(**)` C function calls are now done with the GIL released.

.. versionadded:: 0.3
   `(***)` ``long double`` support.
   Such a number is passed around in a cdata object to avoid loosing
   precision, because a normal Python floating-point number only contains
   enough precision for a ``double``.  To convert it to a regular float,
   call ``float()``.  If you want to operate on such numbers
   without any precision loss, you need to define and use a family of C
   functions like ``long double add(long double a, long double b);``.

.. versionadded:: 0.6
   `(****)` Supports simple slices as well: ``x[start:stop]`` gives another
   cdata object that is a "view" of all items from ``start`` to ``stop``.
   It is a cdata of type "array" (so e.g. passing it as an argument to a
   C function would just convert it to a pointer to the ``start`` item).
   This makes cdata's of type "array" behave more like a Python list, but
   ``start`` and ``stop`` are not optional and a ``step`` is not supported.
   As with indexing, negative bounds mean really negative indices, like in
   C.  As for slice assignment, it accepts any iterable, including a list
   of items or another array-like cdata object, but the length must match.
   (Note that this behavior differs from initialization: e.g. if you pass
   a string when assigning to a slice of a ``char`` array, it must be of
   the correct length; no implicit null character is added.)

.. versionchanged:: 0.6
   `(*****)` Enums are now handled like ints (unsigned or signed, int or
   long, like GCC; note that the first choice is unsigned).  In previous
   versions, you would get the enum's value as a string.  Now we follow the C
   convention and treat them as really equivalent to integers.  To compare
   their value symbolically, use code like ``if x.field == lib.FOO``.
   If you really want to get their value as a string, use
   ``ffi.string(ffi.cast("the_enum_type", x.field))``.


Reference: verifier
-------------------

For advanced use cases, the ``Verifier`` class from ``cffi.verifier``
can be instantiated directly.  It is normally instantiated for you by
``ffi.verify()``, and the instance is attached as ``ffi.verifier``.

- ``Verifier(ffi, preamble, tmpdir=.., ext_package='', modulename=None,
  tag='', **kwds)``:
  instantiate the class with an
  FFI object and a preamble, which is C text that will be pasted into
  the generated C source.  The value of ``tmpdir`` defaults to the
  directory ``directory_of_the_caller/__pycache__``.  The value of
  ``ext_package`` is used when looking up an already-compiled, already-
  installed version of the extension module.  The module name is
  ``_cffi_<tag>_<hash>``, unless overridden with ``modulename``
  (see the `warning about modulename`_ above).
  The other keyword arguments are passed directly
  to `distutils when building the Extension object.`__

.. __: http://docs.python.org/distutils/setupscript.html#describing-extension-module

``Verifier`` objects have the following public attributes and methods:

- ``sourcefilename``: name of a C file.  Defaults to
  ``tmpdir/_cffi_CRCHASH.c``, with the ``CRCHASH`` part computed
  from the strings you passed to cdef() and verify() as well as the
  version numbers of Python and CFFI.  Can be changed before calling
  ``write_source()`` if you want to write the source somewhere else.

- ``modulefilename``: name of the ``.so`` file (or ``.pyd`` on Windows).
  Defaults to ``tmpdir/_cffi_CRCHASH.so``.  Can be changed before
  calling ``compile_module()``.

- ``get_module_name()``: extract the module name from ``modulefilename``.

- ``write_source(file=None)``: produces the C source of the extension
  module.  If ``file`` is specified, write it in that file (or file-like)
  object rather than to ``sourcefilename``.

- ``compile_module()``: writes the C source code (if not done already)
  and compiles it.  This produces a dynamic link library whose file is
  given by ``modulefilename``.

- ``load_library()``: loads the C module (if necessary, making it
  first; it looks for the existing module based on the checksum of the
  strings passed to ``ffi.cdef()`` and ``preamble``, either in the
  directory ``tmpdir`` or in the directory of the package ``ext_package``).
  Returns an instance of a FFILibrary class that behaves like
  the objects returned by ffi.dlopen(), but that delegates all
  operations to the C module.  This is what is returned by
  ``ffi.verify()``.

- ``get_extension()``: returns a distutils-compatible ``Extension`` instance.

The following are global functions in the ``cffi.verifier`` module:

- ``set_tmpdir(dirname)``: sets the temporary directory to use instead of
  ``directory_containing_the_py_file/__pycache__``.  This is a global, so
  avoid it in production code.

- ``cleanup_tmpdir(tmpdir=...)``: cleans up the temporary directory by
  removing all files in it called ``_cffi_*.{c,so}`` as well as all
  files in the ``build`` subdirectory.  By default it will clear
  ``directory_containing_the_py_file/__pycache__``.  This is the .py
  file containing the actual call to ``cleanup_tmpdir()``.




=================

Comments and bugs
=================

The best way to contact us is on the IRC ``#pypy`` channel of
``irc.freenode.net``.  Feel free to discuss matters either there or in
the `mailing list`_.  Please report to the `issue tracker`_ any bugs.

As a general rule, when there is a design issue to resolve, we pick the
solution that is the "most C-like".  We hope that this module has got
everything you need to access C code and nothing more.

--- the authors, Armin Rigo and Maciej Fijalkowski

.. _`issue tracker`: https://bitbucket.org/cffi/cffi/issues
.. _`mailing list`: https://groups.google.com/forum/#!forum/python-cffi



Indices and tables
==================

* :ref:`genindex`
* :ref:`search`