CFFI documentation ================================ C Foreign Function Interface for Python. The goal is to provide a convenient and reliable way to call compiled C code from Python using interface declarations written in C. The interface is based on `LuaJIT's FFI`_, and follows a few principles: * The goal is to call C code from Python without learning a 3rd language: existing alternatives require users to learn domain specific language (Cython_, SWIG_) or API (ctypes_). The CFFI design requires users to know only C and Python, minimizing the extra bits of API that need to be learned. * Keep all the Python-related logic in Python so that you don't need to write much C code (unlike `CPython native C extensions`_). * The preferred way is to work at the level of the API (Application Programming Interface): the C compiler is called from the declarations you write to validate and link to the C language constructs. Alternatively, it is also possible to work at the ABI level (Application Binary Interface), the way ctypes_ work. However, on non-Windows platforms, C libraries typically have a specified C API but not an ABI (e.g. they may document a "struct" as having at least these fields, but maybe more). * 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). * 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://wiki.scipy.org/Weave .. _`manually wrap`: `The verification step`_ Installation and Status ======================================================= Quick installation (for cpython, cffi is distributed with PyPy): * ``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 is distributed with 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 than ctypes 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: https://github.com/eliben/pycparser * 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-0.8.6.tar.gz - Or grab the most current version by following the instructions below. - MD5: ... - SHA: ... * 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 X`_ 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 X +++++++ **Homebrew** (Thanks David Griffin for this) 1) Install homebrew: http://brew.sh 2) Run the following commands in a terminal :: brew install pkg-config libffi export PKG_CONFIG_PATH=/usr/local/Cellar/libffi/3.0.13/lib/pkgconfig/ # May change with libffi version pip install cffi Aternatively, **on OS/X 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 or in global variables, arrays can have an unspecified length, as in "``int n[...];``". The length is completed by the C compiler. (Only the outermost array may have an unknown length, in case of array-of-array.) You can also use the syntax "``int n[];``". .. versionchanged:: 0.8 "``int n[];``" asks for an array of unknown length whose length must *not* be completed by the C compiler. See `variable-length array`_ below. If the structure does not contain the syntax ``...`` anywhere, it will be not be considered to have a partial layout to complete by the 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. .. versionadded:: 0.8.2 The ``ffi.cdef()`` call takes an optional argument ``packed``: if True, then all structs declared within this cdef are "packed". This has a meaning similar to ``__attribute__((packed))`` in GCC. It specifies that all structure fields should have an alignment of one byte. (Note that the packed attribute has no effect on bit fields so far, which mean that they may be packed differently than on GCC.) 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. CPython only: for performance, ``ffi.verify()`` returns functions as objects of type ``<built-in function>``. They are not ``<cdata>``, so you cannot e.g. pass them to some other C function expecting a function pointer argument. Only ``ffi.typeof()`` works on them. If you really need a pointer to the function, use the following workaround:: ffi.cdef(""" int (*foo)(int a, int b); """) i.e. declare them as pointer-to-function in the cdef (even if they are regular functions in the C code). 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``. ``ffi.getwinerror(code=-1)``: on Windows, in addition to ``errno`` we also save and restore the ``GetLastError()`` value across function calls. This function returns this error code as a tuple ``(code, message)``, adding a readable message like Python does when raising WindowsError. If the argument ``code`` is given, format that code into a message instead of using ``GetLastError()``. *New in version 0.8.* (Note that it is also possible to declare and call the ``GetLastError()`` function as usual.) .. "versionadded:: 0.8" --- inlined in the previous paragraph ``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[:]`` or ``bytes(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. .. versionchanged:: 0.8.2 Before version 0.8.2, ``bytes(buf)`` was supported in Python 3 to get the content of the buffer, but on Python 2 it would return the repr ``<_cffi_backend.buffer object>``. This has been fixed. But you should avoid using ``str(buf)``: it now gives inconsistent results between Python 2 and Python 3 (this is similar to how ``str()`` gives inconsistent results on regular byte strings). Use ``buf[:]`` instead. ``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). Note that this should be avoided for large memory allocations or for limited resources. This is particularly true on PyPy: its GC does not know how much memory or how many resources the returned ``ptr`` holds. It will only run its GC when enough memory it knows about has been allocated (and thus run the destructor possibly later than you would expect). Moreover, the destructor is called in whatever thread PyPy is at that moment, which might be a problem for some C libraries. In these cases, consider writing a wrapper class with custom ``__enter__()`` and ``__exit__()`` methods that allocate and free the C data at known points in time, and using it in a ``with`` statement. .. "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. *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.* Note that ``from_handle()`` conceptually works like this: it searches in the list of cdata objects made by ``new_handle()`` the one which has got the same ``void *`` value; and then it fetches in that cdata object the corresponding Python object. The cdata object keeps the Python object alive, similar to how ``ffi.new()`` returns a cdata object that keeps a piece of memory alive. If the cdata object *itself* is not alive any more, then the association ``void * -> python_object`` is dead and ``from_handle()`` will crash. .. "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) .. 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.* .. _`variable-length array`: .. versionadded:: 0.8 Now supported: variable-length structures, i.e. whose last field is a variable-length array. Note that since version 0.8, declarations like ``int field[];`` in structures are interpreted as variable-length structures. When used for structures that are not, in fact, variable-length, it works too; in this case, the difference with using ``int field[...];`` is that, as CFFI believes it cannot ask the C compiler for the length of the array, you get reduced safety checks: for example, you risk overwriting the following fields by passing too many array items in the constructor. 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`