1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116 1117 1118 1119 1120 1121 1122 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133 1134 1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147 1148 1149 1150 1151 1152 1153 1154 1155 1156 1157 1158 1159 1160 1161 1162 1163 1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 1174 1175 1176 1177 1178 1179 1180 1181 1182 1183 1184 1185 1186 1187 1188 1189 1190 1191 1192 1193 1194 1195 1196 1197 1198 1199 1200 1201 1202 1203 1204 1205 1206 1207 1208 1209 1210 1211 1212 1213 1214 1215 1216 1217 1218 1219 1220 1221 1222 1223 1224 1225 1226 1227 1228 1229 1230 1231 1232 1233 1234 1235 1236 1237 1238 1239 1240 1241 1242 1243 1244 1245 1246 1247 1248 1249 1250 1251 1252 1253 1254 1255 1256 1257 1258 1259 1260 1261 1262 1263 1264 1265 1266 1267 1268 1269 1270 1271 1272 1273 1274 1275 1276 1277 1278 1279 1280 1281 1282 1283 1284 1285 1286 1287 1288 1289 1290 1291 1292 1293 1294 1295 1296 1297 1298 1299 1300 1301 1302 1303 1304 1305 1306 1307 1308 1309 1310 1311 1312 1313 1314 1315 1316 1317 1318 1319 1320 1321 1322 1323 1324 1325 1326 1327 1328 1329 1330 1331 1332 1333 1334 1335 1336 1337 1338 1339 1340 1341 1342 1343 1344 1345 1346 1347 1348 1349 1350 1351 1352 1353 1354 1355 1356 1357 1358 1359 1360 1361 1362 1363 1364 1365 1366 1367 1368 1369 1370 1371 1372 1373 1374 1375 1376 1377 1378 1379 1380 1381 1382 1383 1384 1385 1386 1387 1388 1389 1390 1391 1392 1393 1394 1395 1396 1397 1398 1399 1400 1401 1402 1403 1404 1405 1406 1407 1408 1409 1410 1411 1412 1413 1414 1415 1416 1417 1418 1419
|
.. highlight:: c
.. _extending-intro:
******************************
Extending Python with C or C++
******************************
It is quite easy to add new built-in modules to Python, if you know how to
program in C. Such :dfn:`extension modules` can do two things that can't be
done directly in Python: they can implement new built-in object types, and they
can call C library functions and system calls.
To support extensions, the Python API (Application Programmers Interface)
defines a set of functions, macros and variables that provide access to most
aspects of the Python run-time system. The Python API is incorporated in a C
source file by including the header ``"Python.h"``.
The compilation of an extension module depends on its intended use as well as on
your system setup; details are given in later chapters.
.. note::
The C extension interface is specific to CPython, and extension modules do
not work on other Python implementations. In many cases, it is possible to
avoid writing C extensions and preserve portability to other implementations.
For example, if your use case is calling C library functions or system calls,
you should consider using the :mod:`ctypes` module or the `cffi
<https://cffi.readthedocs.io/>`_ library rather than writing
custom C code.
These modules let you write Python code to interface with C code and are more
portable between implementations of Python than writing and compiling a C
extension module.
.. _extending-simpleexample:
A Simple Example
================
Let's create an extension module called ``spam`` (the favorite food of Monty
Python fans...) and let's say we want to create a Python interface to the C
library function :c:func:`system` [#]_. This function takes a null-terminated
character string as argument and returns an integer. We want this function to
be callable from Python as follows:
.. code-block:: pycon
>>> import spam
>>> status = spam.system("ls -l")
Begin by creating a file :file:`spammodule.c`. (Historically, if a module is
called ``spam``, the C file containing its implementation is called
:file:`spammodule.c`; if the module name is very long, like ``spammify``, the
module name can be just :file:`spammify.c`.)
The first two lines of our file can be::
#define PY_SSIZE_T_CLEAN
#include <Python.h>
which pulls in the Python API (you can add a comment describing the purpose of
the module and a copyright notice if you like).
.. note::
Since Python may define some pre-processor definitions which affect the standard
headers on some systems, you *must* include :file:`Python.h` before any standard
headers are included.
``#define PY_SSIZE_T_CLEAN`` was used to indicate that ``Py_ssize_t`` should be
used in some APIs instead of ``int``.
It is not necessary since Python 3.13, but we keep it here for backward compatibility.
See :ref:`arg-parsing-string-and-buffers` for a description of this macro.
All user-visible symbols defined by :file:`Python.h` have a prefix of ``Py`` or
``PY``, except those defined in standard header files.
.. tip::
For backward compatibility, :file:`Python.h` includes several standard header files.
C extensions should include the standard headers that they use,
and should not rely on these implicit includes.
If using the limited C API version 3.13 or newer, the implicit includes are:
* ``<assert.h>``
* ``<intrin.h>`` (on Windows)
* ``<inttypes.h>``
* ``<limits.h>``
* ``<math.h>``
* ``<stdarg.h>``
* ``<wchar.h>``
* ``<sys/types.h>`` (if present)
If :c:macro:`Py_LIMITED_API` is not defined, or is set to version 3.12 or older,
the headers below are also included:
* ``<ctype.h>``
* ``<unistd.h>`` (on POSIX)
If :c:macro:`Py_LIMITED_API` is not defined, or is set to version 3.10 or older,
the headers below are also included:
* ``<errno.h>``
* ``<stdio.h>``
* ``<stdlib.h>``
* ``<string.h>``
The next thing we add to our module file is the C function that will be called
when the Python expression ``spam.system(string)`` is evaluated (we'll see
shortly how it ends up being called)::
static PyObject *
spam_system(PyObject *self, PyObject *args)
{
const char *command;
int sts;
if (!PyArg_ParseTuple(args, "s", &command))
return NULL;
sts = system(command);
return PyLong_FromLong(sts);
}
There is a straightforward translation from the argument list in Python (for
example, the single expression ``"ls -l"``) to the arguments passed to the C
function. The C function always has two arguments, conventionally named *self*
and *args*.
The *self* argument points to the module object for module-level functions;
for a method it would point to the object instance.
The *args* argument will be a pointer to a Python tuple object containing the
arguments. Each item of the tuple corresponds to an argument in the call's
argument list. The arguments are Python objects --- in order to do anything
with them in our C function we have to convert them to C values. The function
:c:func:`PyArg_ParseTuple` in the Python API checks the argument types and
converts them to C values. It uses a template string to determine the required
types of the arguments as well as the types of the C variables into which to
store the converted values. More about this later.
:c:func:`PyArg_ParseTuple` returns true (nonzero) if all arguments have the right
type and its components have been stored in the variables whose addresses are
passed. It returns false (zero) if an invalid argument list was passed. In the
latter case it also raises an appropriate exception so the calling function can
return ``NULL`` immediately (as we saw in the example).
.. _extending-errors:
Intermezzo: Errors and Exceptions
=================================
An important convention throughout the Python interpreter is the following: when
a function fails, it should set an exception condition and return an error value
(usually ``-1`` or a ``NULL`` pointer). Exception information is stored in
three members of the interpreter's thread state. These are ``NULL`` if
there is no exception. Otherwise they are the C equivalents of the members
of the Python tuple returned by :meth:`sys.exc_info`. These are the
exception type, exception instance, and a traceback object. It is important
to know about them to understand how errors are passed around.
The Python API defines a number of functions to set various types of exceptions.
The most common one is :c:func:`PyErr_SetString`. Its arguments are an exception
object and a C string. The exception object is usually a predefined object like
:c:data:`PyExc_ZeroDivisionError`. The C string indicates the cause of the error
and is converted to a Python string object and stored as the "associated value"
of the exception.
Another useful function is :c:func:`PyErr_SetFromErrno`, which only takes an
exception argument and constructs the associated value by inspection of the
global variable :c:data:`errno`. The most general function is
:c:func:`PyErr_SetObject`, which takes two object arguments, the exception and
its associated value. You don't need to :c:func:`Py_INCREF` the objects passed
to any of these functions.
You can test non-destructively whether an exception has been set with
:c:func:`PyErr_Occurred`. This returns the current exception object, or ``NULL``
if no exception has occurred. You normally don't need to call
:c:func:`PyErr_Occurred` to see whether an error occurred in a function call,
since you should be able to tell from the return value.
When a function *f* that calls another function *g* detects that the latter
fails, *f* should itself return an error value (usually ``NULL`` or ``-1``). It
should *not* call one of the ``PyErr_*`` functions --- one has already
been called by *g*. *f*'s caller is then supposed to also return an error
indication to *its* caller, again *without* calling ``PyErr_*``, and so on
--- the most detailed cause of the error was already reported by the function
that first detected it. Once the error reaches the Python interpreter's main
loop, this aborts the currently executing Python code and tries to find an
exception handler specified by the Python programmer.
(There are situations where a module can actually give a more detailed error
message by calling another ``PyErr_*`` function, and in such cases it is
fine to do so. As a general rule, however, this is not necessary, and can cause
information about the cause of the error to be lost: most operations can fail
for a variety of reasons.)
To ignore an exception set by a function call that failed, the exception
condition must be cleared explicitly by calling :c:func:`PyErr_Clear`. The only
time C code should call :c:func:`PyErr_Clear` is if it doesn't want to pass the
error on to the interpreter but wants to handle it completely by itself
(possibly by trying something else, or pretending nothing went wrong).
Every failing :c:func:`malloc` call must be turned into an exception --- the
direct caller of :c:func:`malloc` (or :c:func:`realloc`) must call
:c:func:`PyErr_NoMemory` and return a failure indicator itself. All the
object-creating functions (for example, :c:func:`PyLong_FromLong`) already do
this, so this note is only relevant to those who call :c:func:`malloc` directly.
Also note that, with the important exception of :c:func:`PyArg_ParseTuple` and
friends, functions that return an integer status usually return a positive value
or zero for success and ``-1`` for failure, like Unix system calls.
Finally, be careful to clean up garbage (by making :c:func:`Py_XDECREF` or
:c:func:`Py_DECREF` calls for objects you have already created) when you return
an error indicator!
The choice of which exception to raise is entirely yours. There are predeclared
C objects corresponding to all built-in Python exceptions, such as
:c:data:`PyExc_ZeroDivisionError`, which you can use directly. Of course, you
should choose exceptions wisely --- don't use :c:data:`PyExc_TypeError` to mean
that a file couldn't be opened (that should probably be :c:data:`PyExc_OSError`).
If something's wrong with the argument list, the :c:func:`PyArg_ParseTuple`
function usually raises :c:data:`PyExc_TypeError`. If you have an argument whose
value must be in a particular range or must satisfy other conditions,
:c:data:`PyExc_ValueError` is appropriate.
You can also define a new exception that is unique to your module.
The simplest way to do this is to declare a static global object variable at
the beginning of the file::
static PyObject *SpamError = NULL;
and initialize it by calling :c:func:`PyErr_NewException` in the module's
:c:data:`Py_mod_exec` function (:c:func:`!spam_module_exec`)::
SpamError = PyErr_NewException("spam.error", NULL, NULL);
Since :c:data:`!SpamError` is a global variable, it will be overwitten every time
the module is reinitialized, when the :c:data:`Py_mod_exec` function is called.
For now, let's avoid the issue: we will block repeated initialization by raising an
:py:exc:`ImportError`::
static PyObject *SpamError = NULL;
static int
spam_module_exec(PyObject *m)
{
if (SpamError != NULL) {
PyErr_SetString(PyExc_ImportError,
"cannot initialize spam module more than once");
return -1;
}
SpamError = PyErr_NewException("spam.error", NULL, NULL);
if (PyModule_AddObjectRef(m, "SpamError", SpamError) < 0) {
return -1;
}
return 0;
}
static PyModuleDef_Slot spam_module_slots[] = {
{Py_mod_exec, spam_module_exec},
{0, NULL}
};
static struct PyModuleDef spam_module = {
.m_base = PyModuleDef_HEAD_INIT,
.m_name = "spam",
.m_size = 0, // non-negative
.m_slots = spam_module_slots,
};
PyMODINIT_FUNC
PyInit_spam(void)
{
return PyModuleDef_Init(&spam_module);
}
Note that the Python name for the exception object is :exc:`!spam.error`. The
:c:func:`PyErr_NewException` function may create a class with the base class
being :exc:`Exception` (unless another class is passed in instead of ``NULL``),
described in :ref:`bltin-exceptions`.
Note also that the :c:data:`!SpamError` variable retains a reference to the newly
created exception class; this is intentional! Since the exception could be
removed from the module by external code, an owned reference to the class is
needed to ensure that it will not be discarded, causing :c:data:`!SpamError` to
become a dangling pointer. Should it become a dangling pointer, C code which
raises the exception could cause a core dump or other unintended side effects.
For now, the :c:func:`Py_DECREF` call to remove this reference is missing.
Even when the Python interpreter shuts down, the global :c:data:`!SpamError`
variable will not be garbage-collected. It will "leak".
We did, however, ensure that this will happen at most once per process.
We discuss the use of :c:macro:`PyMODINIT_FUNC` as a function return type later in this
sample.
The :exc:`!spam.error` exception can be raised in your extension module using a
call to :c:func:`PyErr_SetString` as shown below::
static PyObject *
spam_system(PyObject *self, PyObject *args)
{
const char *command;
int sts;
if (!PyArg_ParseTuple(args, "s", &command))
return NULL;
sts = system(command);
if (sts < 0) {
PyErr_SetString(SpamError, "System command failed");
return NULL;
}
return PyLong_FromLong(sts);
}
.. _backtoexample:
Back to the Example
===================
Going back to our example function, you should now be able to understand this
statement::
if (!PyArg_ParseTuple(args, "s", &command))
return NULL;
It returns ``NULL`` (the error indicator for functions returning object pointers)
if an error is detected in the argument list, relying on the exception set by
:c:func:`PyArg_ParseTuple`. Otherwise the string value of the argument has been
copied to the local variable :c:data:`!command`. This is a pointer assignment and
you are not supposed to modify the string to which it points (so in Standard C,
the variable :c:data:`!command` should properly be declared as ``const char
*command``).
The next statement is a call to the Unix function :c:func:`system`, passing it
the string we just got from :c:func:`PyArg_ParseTuple`::
sts = system(command);
Our :func:`!spam.system` function must return the value of :c:data:`!sts` as a
Python object. This is done using the function :c:func:`PyLong_FromLong`. ::
return PyLong_FromLong(sts);
In this case, it will return an integer object. (Yes, even integers are objects
on the heap in Python!)
If you have a C function that returns no useful argument (a function returning
:c:expr:`void`), the corresponding Python function must return ``None``. You
need this idiom to do so (which is implemented by the :c:macro:`Py_RETURN_NONE`
macro)::
Py_INCREF(Py_None);
return Py_None;
:c:data:`Py_None` is the C name for the special Python object ``None``. It is a
genuine Python object rather than a ``NULL`` pointer, which means "error" in most
contexts, as we have seen.
.. _methodtable:
The Module's Method Table and Initialization Function
=====================================================
I promised to show how :c:func:`!spam_system` is called from Python programs.
First, we need to list its name and address in a "method table"::
static PyMethodDef spam_methods[] = {
...
{"system", spam_system, METH_VARARGS,
"Execute a shell command."},
...
{NULL, NULL, 0, NULL} /* Sentinel */
};
Note the third entry (``METH_VARARGS``). This is a flag telling the interpreter
the calling convention to be used for the C function. It should normally always
be ``METH_VARARGS`` or ``METH_VARARGS | METH_KEYWORDS``; a value of ``0`` means
that an obsolete variant of :c:func:`PyArg_ParseTuple` is used.
When using only ``METH_VARARGS``, the function should expect the Python-level
parameters to be passed in as a tuple acceptable for parsing via
:c:func:`PyArg_ParseTuple`; more information on this function is provided below.
The :c:macro:`METH_KEYWORDS` bit may be set in the third field if keyword
arguments should be passed to the function. In this case, the C function should
accept a third ``PyObject *`` parameter which will be a dictionary of keywords.
Use :c:func:`PyArg_ParseTupleAndKeywords` to parse the arguments to such a
function.
The method table must be referenced in the module definition structure::
static struct PyModuleDef spam_module = {
...
.m_methods = spam_methods,
...
};
This structure, in turn, must be passed to the interpreter in the module's
initialization function. The initialization function must be named
:c:func:`!PyInit_name`, where *name* is the name of the module, and should be the
only non-\ ``static`` item defined in the module file::
PyMODINIT_FUNC
PyInit_spam(void)
{
return PyModuleDef_Init(&spam_module);
}
Note that :c:macro:`PyMODINIT_FUNC` declares the function as ``PyObject *`` return type,
declares any special linkage declarations required by the platform, and for C++
declares the function as ``extern "C"``.
:c:func:`!PyInit_spam` is called when each interpreter imports its module
:mod:`!spam` for the first time. (See below for comments about embedding Python.)
A pointer to the module definition must be returned via :c:func:`PyModuleDef_Init`,
so that the import machinery can create the module and store it in ``sys.modules``.
When embedding Python, the :c:func:`!PyInit_spam` function is not called
automatically unless there's an entry in the :c:data:`PyImport_Inittab` table.
To add the module to the initialization table, use :c:func:`PyImport_AppendInittab`,
optionally followed by an import of the module::
#define PY_SSIZE_T_CLEAN
#include <Python.h>
int
main(int argc, char *argv[])
{
PyStatus status;
PyConfig config;
PyConfig_InitPythonConfig(&config);
/* Add a built-in module, before Py_Initialize */
if (PyImport_AppendInittab("spam", PyInit_spam) == -1) {
fprintf(stderr, "Error: could not extend in-built modules table\n");
exit(1);
}
/* Pass argv[0] to the Python interpreter */
status = PyConfig_SetBytesString(&config, &config.program_name, argv[0]);
if (PyStatus_Exception(status)) {
goto exception;
}
/* Initialize the Python interpreter. Required.
If this step fails, it will be a fatal error. */
status = Py_InitializeFromConfig(&config);
if (PyStatus_Exception(status)) {
goto exception;
}
PyConfig_Clear(&config);
/* Optionally import the module; alternatively,
import can be deferred until the embedded script
imports it. */
PyObject *pmodule = PyImport_ImportModule("spam");
if (!pmodule) {
PyErr_Print();
fprintf(stderr, "Error: could not import module 'spam'\n");
}
// ... use Python C API here ...
return 0;
exception:
PyConfig_Clear(&config);
Py_ExitStatusException(status);
}
.. note::
If you declare a global variable or a local static one, the module may
experience unintended side-effects on re-initialisation, for example when
removing entries from ``sys.modules`` or importing compiled modules into
multiple interpreters within a process
(or following a :c:func:`fork` without an intervening :c:func:`exec`).
If module state is not yet fully :ref:`isolated <isolating-extensions-howto>`,
authors should consider marking the module as having no support for subinterpreters
(via :c:macro:`Py_MOD_MULTIPLE_INTERPRETERS_NOT_SUPPORTED`).
A more substantial example module is included in the Python source distribution
as :file:`Modules/xxlimited.c`. This file may be used as a template or simply
read as an example.
.. _compilation:
Compilation and Linkage
=======================
There are two more things to do before you can use your new extension: compiling
and linking it with the Python system. If you use dynamic loading, the details
may depend on the style of dynamic loading your system uses; see the chapters
about building extension modules (chapter :ref:`building`) and additional
information that pertains only to building on Windows (chapter
:ref:`building-on-windows`) for more information about this.
If you can't use dynamic loading, or if you want to make your module a permanent
part of the Python interpreter, you will have to change the configuration setup
and rebuild the interpreter. Luckily, this is very simple on Unix: just place
your file (:file:`spammodule.c` for example) in the :file:`Modules/` directory
of an unpacked source distribution, add a line to the file
:file:`Modules/Setup.local` describing your file:
.. code-block:: sh
spam spammodule.o
and rebuild the interpreter by running :program:`make` in the toplevel
directory. You can also run :program:`make` in the :file:`Modules/`
subdirectory, but then you must first rebuild :file:`Makefile` there by running
':program:`make` Makefile'. (This is necessary each time you change the
:file:`Setup` file.)
If your module requires additional libraries to link with, these can be listed
on the line in the configuration file as well, for instance:
.. code-block:: sh
spam spammodule.o -lX11
.. _callingpython:
Calling Python Functions from C
===============================
So far we have concentrated on making C functions callable from Python. The
reverse is also useful: calling Python functions from C. This is especially the
case for libraries that support so-called "callback" functions. If a C
interface makes use of callbacks, the equivalent Python often needs to provide a
callback mechanism to the Python programmer; the implementation will require
calling the Python callback functions from a C callback. Other uses are also
imaginable.
Fortunately, the Python interpreter is easily called recursively, and there is a
standard interface to call a Python function. (I won't dwell on how to call the
Python parser with a particular string as input --- if you're interested, have a
look at the implementation of the :option:`-c` command line option in
:file:`Modules/main.c` from the Python source code.)
Calling a Python function is easy. First, the Python program must somehow pass
you the Python function object. You should provide a function (or some other
interface) to do this. When this function is called, save a pointer to the
Python function object (be careful to :c:func:`Py_INCREF` it!) in a global
variable --- or wherever you see fit. For example, the following function might
be part of a module definition::
static PyObject *my_callback = NULL;
static PyObject *
my_set_callback(PyObject *dummy, PyObject *args)
{
PyObject *result = NULL;
PyObject *temp;
if (PyArg_ParseTuple(args, "O:set_callback", &temp)) {
if (!PyCallable_Check(temp)) {
PyErr_SetString(PyExc_TypeError, "parameter must be callable");
return NULL;
}
Py_XINCREF(temp); /* Add a reference to new callback */
Py_XDECREF(my_callback); /* Dispose of previous callback */
my_callback = temp; /* Remember new callback */
/* Boilerplate to return "None" */
Py_INCREF(Py_None);
result = Py_None;
}
return result;
}
This function must be registered with the interpreter using the
:c:macro:`METH_VARARGS` flag; this is described in section :ref:`methodtable`. The
:c:func:`PyArg_ParseTuple` function and its arguments are documented in section
:ref:`parsetuple`.
The macros :c:func:`Py_XINCREF` and :c:func:`Py_XDECREF` increment/decrement the
reference count of an object and are safe in the presence of ``NULL`` pointers
(but note that *temp* will not be ``NULL`` in this context). More info on them
in section :ref:`refcounts`.
.. index:: single: PyObject_CallObject (C function)
Later, when it is time to call the function, you call the C function
:c:func:`PyObject_CallObject`. This function has two arguments, both pointers to
arbitrary Python objects: the Python function, and the argument list. The
argument list must always be a tuple object, whose length is the number of
arguments. To call the Python function with no arguments, pass in ``NULL``, or
an empty tuple; to call it with one argument, pass a singleton tuple.
:c:func:`Py_BuildValue` returns a tuple when its format string consists of zero
or more format codes between parentheses. For example::
int arg;
PyObject *arglist;
PyObject *result;
...
arg = 123;
...
/* Time to call the callback */
arglist = Py_BuildValue("(i)", arg);
result = PyObject_CallObject(my_callback, arglist);
Py_DECREF(arglist);
:c:func:`PyObject_CallObject` returns a Python object pointer: this is the return
value of the Python function. :c:func:`PyObject_CallObject` is
"reference-count-neutral" with respect to its arguments. In the example a new
tuple was created to serve as the argument list, which is
:c:func:`Py_DECREF`\ -ed immediately after the :c:func:`PyObject_CallObject`
call.
The return value of :c:func:`PyObject_CallObject` is "new": either it is a brand
new object, or it is an existing object whose reference count has been
incremented. So, unless you want to save it in a global variable, you should
somehow :c:func:`Py_DECREF` the result, even (especially!) if you are not
interested in its value.
Before you do this, however, it is important to check that the return value
isn't ``NULL``. If it is, the Python function terminated by raising an exception.
If the C code that called :c:func:`PyObject_CallObject` is called from Python, it
should now return an error indication to its Python caller, so the interpreter
can print a stack trace, or the calling Python code can handle the exception.
If this is not possible or desirable, the exception should be cleared by calling
:c:func:`PyErr_Clear`. For example::
if (result == NULL)
return NULL; /* Pass error back */
...use result...
Py_DECREF(result);
Depending on the desired interface to the Python callback function, you may also
have to provide an argument list to :c:func:`PyObject_CallObject`. In some cases
the argument list is also provided by the Python program, through the same
interface that specified the callback function. It can then be saved and used
in the same manner as the function object. In other cases, you may have to
construct a new tuple to pass as the argument list. The simplest way to do this
is to call :c:func:`Py_BuildValue`. For example, if you want to pass an integral
event code, you might use the following code::
PyObject *arglist;
...
arglist = Py_BuildValue("(l)", eventcode);
result = PyObject_CallObject(my_callback, arglist);
Py_DECREF(arglist);
if (result == NULL)
return NULL; /* Pass error back */
/* Here maybe use the result */
Py_DECREF(result);
Note the placement of ``Py_DECREF(arglist)`` immediately after the call, before
the error check! Also note that strictly speaking this code is not complete:
:c:func:`Py_BuildValue` may run out of memory, and this should be checked.
You may also call a function with keyword arguments by using
:c:func:`PyObject_Call`, which supports arguments and keyword arguments. As in
the above example, we use :c:func:`Py_BuildValue` to construct the dictionary. ::
PyObject *dict;
...
dict = Py_BuildValue("{s:i}", "name", val);
result = PyObject_Call(my_callback, NULL, dict);
Py_DECREF(dict);
if (result == NULL)
return NULL; /* Pass error back */
/* Here maybe use the result */
Py_DECREF(result);
.. _parsetuple:
Extracting Parameters in Extension Functions
============================================
.. index:: single: PyArg_ParseTuple (C function)
The :c:func:`PyArg_ParseTuple` function is declared as follows::
int PyArg_ParseTuple(PyObject *arg, const char *format, ...);
The *arg* argument must be a tuple object containing an argument list passed
from Python to a C function. The *format* argument must be a format string,
whose syntax is explained in :ref:`arg-parsing` in the Python/C API Reference
Manual. The remaining arguments must be addresses of variables whose type is
determined by the format string.
Note that while :c:func:`PyArg_ParseTuple` checks that the Python arguments have
the required types, it cannot check the validity of the addresses of C variables
passed to the call: if you make mistakes there, your code will probably crash or
at least overwrite random bits in memory. So be careful!
Note that any Python object references which are provided to the caller are
*borrowed* references; do not decrement their reference count!
Some example calls::
#define PY_SSIZE_T_CLEAN
#include <Python.h>
::
int ok;
int i, j;
long k, l;
const char *s;
Py_ssize_t size;
ok = PyArg_ParseTuple(args, ""); /* No arguments */
/* Python call: f() */
::
ok = PyArg_ParseTuple(args, "s", &s); /* A string */
/* Possible Python call: f('whoops!') */
::
ok = PyArg_ParseTuple(args, "lls", &k, &l, &s); /* Two longs and a string */
/* Possible Python call: f(1, 2, 'three') */
::
ok = PyArg_ParseTuple(args, "(ii)s#", &i, &j, &s, &size);
/* A pair of ints and a string, whose size is also returned */
/* Possible Python call: f((1, 2), 'three') */
::
{
const char *file;
const char *mode = "r";
int bufsize = 0;
ok = PyArg_ParseTuple(args, "s|si", &file, &mode, &bufsize);
/* A string, and optionally another string and an integer */
/* Possible Python calls:
f('spam')
f('spam', 'w')
f('spam', 'wb', 100000) */
}
::
{
int left, top, right, bottom, h, v;
ok = PyArg_ParseTuple(args, "((ii)(ii))(ii)",
&left, &top, &right, &bottom, &h, &v);
/* A rectangle and a point */
/* Possible Python call:
f(((0, 0), (400, 300)), (10, 10)) */
}
::
{
Py_complex c;
ok = PyArg_ParseTuple(args, "D:myfunction", &c);
/* a complex, also providing a function name for errors */
/* Possible Python call: myfunction(1+2j) */
}
.. _parsetupleandkeywords:
Keyword Parameters for Extension Functions
==========================================
.. index:: single: PyArg_ParseTupleAndKeywords (C function)
The :c:func:`PyArg_ParseTupleAndKeywords` function is declared as follows::
int PyArg_ParseTupleAndKeywords(PyObject *arg, PyObject *kwdict,
const char *format, char * const *kwlist, ...);
The *arg* and *format* parameters are identical to those of the
:c:func:`PyArg_ParseTuple` function. The *kwdict* parameter is the dictionary of
keywords received as the third parameter from the Python runtime. The *kwlist*
parameter is a ``NULL``-terminated list of strings which identify the parameters;
the names are matched with the type information from *format* from left to
right. On success, :c:func:`PyArg_ParseTupleAndKeywords` returns true, otherwise
it returns false and raises an appropriate exception.
.. note::
Nested tuples cannot be parsed when using keyword arguments! Keyword parameters
passed in which are not present in the *kwlist* will cause :exc:`TypeError` to
be raised.
.. index:: single: Philbrick, Geoff
Here is an example module which uses keywords, based on an example by Geoff
Philbrick (philbrick@hks.com)::
#define PY_SSIZE_T_CLEAN
#include <Python.h>
static PyObject *
keywdarg_parrot(PyObject *self, PyObject *args, PyObject *keywds)
{
int voltage;
const char *state = "a stiff";
const char *action = "voom";
const char *type = "Norwegian Blue";
static char *kwlist[] = {"voltage", "state", "action", "type", NULL};
if (!PyArg_ParseTupleAndKeywords(args, keywds, "i|sss", kwlist,
&voltage, &state, &action, &type))
return NULL;
printf("-- This parrot wouldn't %s if you put %i Volts through it.\n",
action, voltage);
printf("-- Lovely plumage, the %s -- It's %s!\n", type, state);
Py_RETURN_NONE;
}
static PyMethodDef keywdarg_methods[] = {
/* The cast of the function is necessary since PyCFunction values
* only take two PyObject* parameters, and keywdarg_parrot() takes
* three.
*/
{"parrot", (PyCFunction)(void(*)(void))keywdarg_parrot, METH_VARARGS | METH_KEYWORDS,
"Print a lovely skit to standard output."},
{NULL, NULL, 0, NULL} /* sentinel */
};
static struct PyModuleDef keywdarg_module = {
.m_base = PyModuleDef_HEAD_INIT,
.m_name = "keywdarg",
.m_size = 0,
.m_methods = keywdarg_methods,
};
PyMODINIT_FUNC
PyInit_keywdarg(void)
{
return PyModuleDef_Init(&keywdarg_module);
}
.. _buildvalue:
Building Arbitrary Values
=========================
This function is the counterpart to :c:func:`PyArg_ParseTuple`. It is declared
as follows::
PyObject *Py_BuildValue(const char *format, ...);
It recognizes a set of format units similar to the ones recognized by
:c:func:`PyArg_ParseTuple`, but the arguments (which are input to the function,
not output) must not be pointers, just values. It returns a new Python object,
suitable for returning from a C function called from Python.
One difference with :c:func:`PyArg_ParseTuple`: while the latter requires its
first argument to be a tuple (since Python argument lists are always represented
as tuples internally), :c:func:`Py_BuildValue` does not always build a tuple. It
builds a tuple only if its format string contains two or more format units. If
the format string is empty, it returns ``None``; if it contains exactly one
format unit, it returns whatever object is described by that format unit. To
force it to return a tuple of size 0 or one, parenthesize the format string.
Examples (to the left the call, to the right the resulting Python value):
.. code-block:: none
Py_BuildValue("") None
Py_BuildValue("i", 123) 123
Py_BuildValue("iii", 123, 456, 789) (123, 456, 789)
Py_BuildValue("s", "hello") 'hello'
Py_BuildValue("y", "hello") b'hello'
Py_BuildValue("ss", "hello", "world") ('hello', 'world')
Py_BuildValue("s#", "hello", 4) 'hell'
Py_BuildValue("y#", "hello", 4) b'hell'
Py_BuildValue("()") ()
Py_BuildValue("(i)", 123) (123,)
Py_BuildValue("(ii)", 123, 456) (123, 456)
Py_BuildValue("(i,i)", 123, 456) (123, 456)
Py_BuildValue("[i,i]", 123, 456) [123, 456]
Py_BuildValue("{s:i,s:i}",
"abc", 123, "def", 456) {'abc': 123, 'def': 456}
Py_BuildValue("((ii)(ii)) (ii)",
1, 2, 3, 4, 5, 6) (((1, 2), (3, 4)), (5, 6))
.. _refcounts:
Reference Counts
================
In languages like C or C++, the programmer is responsible for dynamic allocation
and deallocation of memory on the heap. In C, this is done using the functions
:c:func:`malloc` and :c:func:`free`. In C++, the operators ``new`` and
``delete`` are used with essentially the same meaning and we'll restrict
the following discussion to the C case.
Every block of memory allocated with :c:func:`malloc` should eventually be
returned to the pool of available memory by exactly one call to :c:func:`free`.
It is important to call :c:func:`free` at the right time. If a block's address
is forgotten but :c:func:`free` is not called for it, the memory it occupies
cannot be reused until the program terminates. This is called a :dfn:`memory
leak`. On the other hand, if a program calls :c:func:`free` for a block and then
continues to use the block, it creates a conflict with reuse of the block
through another :c:func:`malloc` call. This is called :dfn:`using freed memory`.
It has the same bad consequences as referencing uninitialized data --- core
dumps, wrong results, mysterious crashes.
Common causes of memory leaks are unusual paths through the code. For instance,
a function may allocate a block of memory, do some calculation, and then free
the block again. Now a change in the requirements for the function may add a
test to the calculation that detects an error condition and can return
prematurely from the function. It's easy to forget to free the allocated memory
block when taking this premature exit, especially when it is added later to the
code. Such leaks, once introduced, often go undetected for a long time: the
error exit is taken only in a small fraction of all calls, and most modern
machines have plenty of virtual memory, so the leak only becomes apparent in a
long-running process that uses the leaking function frequently. Therefore, it's
important to prevent leaks from happening by having a coding convention or
strategy that minimizes this kind of errors.
Since Python makes heavy use of :c:func:`malloc` and :c:func:`free`, it needs a
strategy to avoid memory leaks as well as the use of freed memory. The chosen
method is called :dfn:`reference counting`. The principle is simple: every
object contains a counter, which is incremented when a reference to the object
is stored somewhere, and which is decremented when a reference to it is deleted.
When the counter reaches zero, the last reference to the object has been deleted
and the object is freed.
An alternative strategy is called :dfn:`automatic garbage collection`.
(Sometimes, reference counting is also referred to as a garbage collection
strategy, hence my use of "automatic" to distinguish the two.) The big
advantage of automatic garbage collection is that the user doesn't need to call
:c:func:`free` explicitly. (Another claimed advantage is an improvement in speed
or memory usage --- this is no hard fact however.) The disadvantage is that for
C, there is no truly portable automatic garbage collector, while reference
counting can be implemented portably (as long as the functions :c:func:`malloc`
and :c:func:`free` are available --- which the C Standard guarantees). Maybe some
day a sufficiently portable automatic garbage collector will be available for C.
Until then, we'll have to live with reference counts.
While Python uses the traditional reference counting implementation, it also
offers a cycle detector that works to detect reference cycles. This allows
applications to not worry about creating direct or indirect circular references;
these are the weakness of garbage collection implemented using only reference
counting. Reference cycles consist of objects which contain (possibly indirect)
references to themselves, so that each object in the cycle has a reference count
which is non-zero. Typical reference counting implementations are not able to
reclaim the memory belonging to any objects in a reference cycle, or referenced
from the objects in the cycle, even though there are no further references to
the cycle itself.
The cycle detector is able to detect garbage cycles and can reclaim them.
The :mod:`gc` module exposes a way to run the detector (the
:func:`~gc.collect` function), as well as configuration
interfaces and the ability to disable the detector at runtime.
.. _refcountsinpython:
Reference Counting in Python
----------------------------
There are two macros, ``Py_INCREF(x)`` and ``Py_DECREF(x)``, which handle the
incrementing and decrementing of the reference count. :c:func:`Py_DECREF` also
frees the object when the count reaches zero. For flexibility, it doesn't call
:c:func:`free` directly --- rather, it makes a call through a function pointer in
the object's :dfn:`type object`. For this purpose (and others), every object
also contains a pointer to its type object.
The big question now remains: when to use ``Py_INCREF(x)`` and ``Py_DECREF(x)``?
Let's first introduce some terms. Nobody "owns" an object; however, you can
:dfn:`own a reference` to an object. An object's reference count is now defined
as the number of owned references to it. The owner of a reference is
responsible for calling :c:func:`Py_DECREF` when the reference is no longer
needed. Ownership of a reference can be transferred. There are three ways to
dispose of an owned reference: pass it on, store it, or call :c:func:`Py_DECREF`.
Forgetting to dispose of an owned reference creates a memory leak.
It is also possible to :dfn:`borrow` [#]_ a reference to an object. The
borrower of a reference should not call :c:func:`Py_DECREF`. The borrower must
not hold on to the object longer than the owner from which it was borrowed.
Using a borrowed reference after the owner has disposed of it risks using freed
memory and should be avoided completely [#]_.
The advantage of borrowing over owning a reference is that you don't need to
take care of disposing of the reference on all possible paths through the code
--- in other words, with a borrowed reference you don't run the risk of leaking
when a premature exit is taken. The disadvantage of borrowing over owning is
that there are some subtle situations where in seemingly correct code a borrowed
reference can be used after the owner from which it was borrowed has in fact
disposed of it.
A borrowed reference can be changed into an owned reference by calling
:c:func:`Py_INCREF`. This does not affect the status of the owner from which the
reference was borrowed --- it creates a new owned reference, and gives full
owner responsibilities (the new owner must dispose of the reference properly, as
well as the previous owner).
.. _ownershiprules:
Ownership Rules
---------------
Whenever an object reference is passed into or out of a function, it is part of
the function's interface specification whether ownership is transferred with the
reference or not.
Most functions that return a reference to an object pass on ownership with the
reference. In particular, all functions whose function it is to create a new
object, such as :c:func:`PyLong_FromLong` and :c:func:`Py_BuildValue`, pass
ownership to the receiver. Even if the object is not actually new, you still
receive ownership of a new reference to that object. For instance,
:c:func:`PyLong_FromLong` maintains a cache of popular values and can return a
reference to a cached item.
Many functions that extract objects from other objects also transfer ownership
with the reference, for instance :c:func:`PyObject_GetAttrString`. The picture
is less clear, here, however, since a few common routines are exceptions:
:c:func:`PyTuple_GetItem`, :c:func:`PyList_GetItem`, :c:func:`PyDict_GetItem`, and
:c:func:`PyDict_GetItemString` all return references that you borrow from the
tuple, list or dictionary.
The function :c:func:`PyImport_AddModule` also returns a borrowed reference, even
though it may actually create the object it returns: this is possible because an
owned reference to the object is stored in ``sys.modules``.
When you pass an object reference into another function, in general, the
function borrows the reference from you --- if it needs to store it, it will use
:c:func:`Py_INCREF` to become an independent owner. There are exactly two
important exceptions to this rule: :c:func:`PyTuple_SetItem` and
:c:func:`PyList_SetItem`. These functions take over ownership of the item passed
to them --- even if they fail! (Note that :c:func:`PyDict_SetItem` and friends
don't take over ownership --- they are "normal.")
When a C function is called from Python, it borrows references to its arguments
from the caller. The caller owns a reference to the object, so the borrowed
reference's lifetime is guaranteed until the function returns. Only when such a
borrowed reference must be stored or passed on, it must be turned into an owned
reference by calling :c:func:`Py_INCREF`.
The object reference returned from a C function that is called from Python must
be an owned reference --- ownership is transferred from the function to its
caller.
.. _thinice:
Thin Ice
--------
There are a few situations where seemingly harmless use of a borrowed reference
can lead to problems. These all have to do with implicit invocations of the
interpreter, which can cause the owner of a reference to dispose of it.
The first and most important case to know about is using :c:func:`Py_DECREF` on
an unrelated object while borrowing a reference to a list item. For instance::
void
bug(PyObject *list)
{
PyObject *item = PyList_GetItem(list, 0);
PyList_SetItem(list, 1, PyLong_FromLong(0L));
PyObject_Print(item, stdout, 0); /* BUG! */
}
This function first borrows a reference to ``list[0]``, then replaces
``list[1]`` with the value ``0``, and finally prints the borrowed reference.
Looks harmless, right? But it's not!
Let's follow the control flow into :c:func:`PyList_SetItem`. The list owns
references to all its items, so when item 1 is replaced, it has to dispose of
the original item 1. Now let's suppose the original item 1 was an instance of a
user-defined class, and let's further suppose that the class defined a
:meth:`!__del__` method. If this class instance has a reference count of 1,
disposing of it will call its :meth:`!__del__` method.
Since it is written in Python, the :meth:`!__del__` method can execute arbitrary
Python code. Could it perhaps do something to invalidate the reference to
``item`` in :c:func:`!bug`? You bet! Assuming that the list passed into
:c:func:`!bug` is accessible to the :meth:`!__del__` method, it could execute a
statement to the effect of ``del list[0]``, and assuming this was the last
reference to that object, it would free the memory associated with it, thereby
invalidating ``item``.
The solution, once you know the source of the problem, is easy: temporarily
increment the reference count. The correct version of the function reads::
void
no_bug(PyObject *list)
{
PyObject *item = PyList_GetItem(list, 0);
Py_INCREF(item);
PyList_SetItem(list, 1, PyLong_FromLong(0L));
PyObject_Print(item, stdout, 0);
Py_DECREF(item);
}
This is a true story. An older version of Python contained variants of this bug
and someone spent a considerable amount of time in a C debugger to figure out
why his :meth:`!__del__` methods would fail...
The second case of problems with a borrowed reference is a variant involving
threads. Normally, multiple threads in the Python interpreter can't get in each
other's way, because there is a :term:`global lock <global interpreter lock>`
protecting Python's entire object space.
However, it is possible to temporarily release this lock using the macro
:c:macro:`Py_BEGIN_ALLOW_THREADS`, and to re-acquire it using
:c:macro:`Py_END_ALLOW_THREADS`. This is common around blocking I/O calls, to
let other threads use the processor while waiting for the I/O to complete.
Obviously, the following function has the same problem as the previous one::
void
bug(PyObject *list)
{
PyObject *item = PyList_GetItem(list, 0);
Py_BEGIN_ALLOW_THREADS
...some blocking I/O call...
Py_END_ALLOW_THREADS
PyObject_Print(item, stdout, 0); /* BUG! */
}
.. _nullpointers:
NULL Pointers
-------------
In general, functions that take object references as arguments do not expect you
to pass them ``NULL`` pointers, and will dump core (or cause later core dumps) if
you do so. Functions that return object references generally return ``NULL`` only
to indicate that an exception occurred. The reason for not testing for ``NULL``
arguments is that functions often pass the objects they receive on to other
function --- if each function were to test for ``NULL``, there would be a lot of
redundant tests and the code would run more slowly.
It is better to test for ``NULL`` only at the "source:" when a pointer that may be
``NULL`` is received, for example, from :c:func:`malloc` or from a function that
may raise an exception.
The macros :c:func:`Py_INCREF` and :c:func:`Py_DECREF` do not check for ``NULL``
pointers --- however, their variants :c:func:`Py_XINCREF` and :c:func:`Py_XDECREF`
do.
The macros for checking for a particular object type (``Pytype_Check()``) don't
check for ``NULL`` pointers --- again, there is much code that calls several of
these in a row to test an object against various different expected types, and
this would generate redundant tests. There are no variants with ``NULL``
checking.
The C function calling mechanism guarantees that the argument list passed to C
functions (``args`` in the examples) is never ``NULL`` --- in fact it guarantees
that it is always a tuple [#]_.
It is a severe error to ever let a ``NULL`` pointer "escape" to the Python user.
.. Frank Stajano:
A pedagogically buggy example, along the lines of the previous listing, would
be helpful here -- showing in more concrete terms what sort of actions could
cause the problem. I can't very well imagine it from the description.
.. _cplusplus:
Writing Extensions in C++
=========================
It is possible to write extension modules in C++. Some restrictions apply. If
the main program (the Python interpreter) is compiled and linked by the C
compiler, global or static objects with constructors cannot be used. This is
not a problem if the main program is linked by the C++ compiler. Functions that
will be called by the Python interpreter (in particular, module initialization
functions) have to be declared using ``extern "C"``. It is unnecessary to
enclose the Python header files in ``extern "C" {...}`` --- they use this form
already if the symbol ``__cplusplus`` is defined (all recent C++ compilers
define this symbol).
.. _using-capsules:
Providing a C API for an Extension Module
=========================================
.. sectionauthor:: Konrad Hinsen <hinsen@cnrs-orleans.fr>
Many extension modules just provide new functions and types to be used from
Python, but sometimes the code in an extension module can be useful for other
extension modules. For example, an extension module could implement a type
"collection" which works like lists without order. Just like the standard Python
list type has a C API which permits extension modules to create and manipulate
lists, this new collection type should have a set of C functions for direct
manipulation from other extension modules.
At first sight this seems easy: just write the functions (without declaring them
``static``, of course), provide an appropriate header file, and document
the C API. And in fact this would work if all extension modules were always
linked statically with the Python interpreter. When modules are used as shared
libraries, however, the symbols defined in one module may not be visible to
another module. The details of visibility depend on the operating system; some
systems use one global namespace for the Python interpreter and all extension
modules (Windows, for example), whereas others require an explicit list of
imported symbols at module link time (AIX is one example), or offer a choice of
different strategies (most Unices). And even if symbols are globally visible,
the module whose functions one wishes to call might not have been loaded yet!
Portability therefore requires not to make any assumptions about symbol
visibility. This means that all symbols in extension modules should be declared
``static``, except for the module's initialization function, in order to
avoid name clashes with other extension modules (as discussed in section
:ref:`methodtable`). And it means that symbols that *should* be accessible from
other extension modules must be exported in a different way.
Python provides a special mechanism to pass C-level information (pointers) from
one extension module to another one: Capsules. A Capsule is a Python data type
which stores a pointer (:c:expr:`void \*`). Capsules can only be created and
accessed via their C API, but they can be passed around like any other Python
object. In particular, they can be assigned to a name in an extension module's
namespace. Other extension modules can then import this module, retrieve the
value of this name, and then retrieve the pointer from the Capsule.
There are many ways in which Capsules can be used to export the C API of an
extension module. Each function could get its own Capsule, or all C API pointers
could be stored in an array whose address is published in a Capsule. And the
various tasks of storing and retrieving the pointers can be distributed in
different ways between the module providing the code and the client modules.
Whichever method you choose, it's important to name your Capsules properly.
The function :c:func:`PyCapsule_New` takes a name parameter
(:c:expr:`const char \*`); you're permitted to pass in a ``NULL`` name, but
we strongly encourage you to specify a name. Properly named Capsules provide
a degree of runtime type-safety; there is no feasible way to tell one unnamed
Capsule from another.
In particular, Capsules used to expose C APIs should be given a name following
this convention::
modulename.attributename
The convenience function :c:func:`PyCapsule_Import` makes it easy to
load a C API provided via a Capsule, but only if the Capsule's name
matches this convention. This behavior gives C API users a high degree
of certainty that the Capsule they load contains the correct C API.
The following example demonstrates an approach that puts most of the burden on
the writer of the exporting module, which is appropriate for commonly used
library modules. It stores all C API pointers (just one in the example!) in an
array of :c:expr:`void` pointers which becomes the value of a Capsule. The header
file corresponding to the module provides a macro that takes care of importing
the module and retrieving its C API pointers; client modules only have to call
this macro before accessing the C API.
The exporting module is a modification of the :mod:`!spam` module from section
:ref:`extending-simpleexample`. The function :func:`!spam.system` does not call
the C library function :c:func:`system` directly, but a function
:c:func:`!PySpam_System`, which would of course do something more complicated in
reality (such as adding "spam" to every command). This function
:c:func:`!PySpam_System` is also exported to other extension modules.
The function :c:func:`!PySpam_System` is a plain C function, declared
``static`` like everything else::
static int
PySpam_System(const char *command)
{
return system(command);
}
The function :c:func:`!spam_system` is modified in a trivial way::
static PyObject *
spam_system(PyObject *self, PyObject *args)
{
const char *command;
int sts;
if (!PyArg_ParseTuple(args, "s", &command))
return NULL;
sts = PySpam_System(command);
return PyLong_FromLong(sts);
}
In the beginning of the module, right after the line ::
#include <Python.h>
two more lines must be added::
#define SPAM_MODULE
#include "spammodule.h"
The ``#define`` is used to tell the header file that it is being included in the
exporting module, not a client module. Finally, the module's :c:data:`mod_exec
<Py_mod_exec>` function must take care of initializing the C API pointer array::
static int
spam_module_exec(PyObject *m)
{
static void *PySpam_API[PySpam_API_pointers];
PyObject *c_api_object;
/* Initialize the C API pointer array */
PySpam_API[PySpam_System_NUM] = (void *)PySpam_System;
/* Create a Capsule containing the API pointer array's address */
c_api_object = PyCapsule_New((void *)PySpam_API, "spam._C_API", NULL);
if (PyModule_Add(m, "_C_API", c_api_object) < 0) {
return -1;
}
return 0;
}
Note that ``PySpam_API`` is declared ``static``; otherwise the pointer
array would disappear when :c:func:`!PyInit_spam` terminates!
The bulk of the work is in the header file :file:`spammodule.h`, which looks
like this::
#ifndef Py_SPAMMODULE_H
#define Py_SPAMMODULE_H
#ifdef __cplusplus
extern "C" {
#endif
/* Header file for spammodule */
/* C API functions */
#define PySpam_System_NUM 0
#define PySpam_System_RETURN int
#define PySpam_System_PROTO (const char *command)
/* Total number of C API pointers */
#define PySpam_API_pointers 1
#ifdef SPAM_MODULE
/* This section is used when compiling spammodule.c */
static PySpam_System_RETURN PySpam_System PySpam_System_PROTO;
#else
/* This section is used in modules that use spammodule's API */
static void **PySpam_API;
#define PySpam_System \
(*(PySpam_System_RETURN (*)PySpam_System_PROTO) PySpam_API[PySpam_System_NUM])
/* Return -1 on error, 0 on success.
* PyCapsule_Import will set an exception if there's an error.
*/
static int
import_spam(void)
{
PySpam_API = (void **)PyCapsule_Import("spam._C_API", 0);
return (PySpam_API != NULL) ? 0 : -1;
}
#endif
#ifdef __cplusplus
}
#endif
#endif /* !defined(Py_SPAMMODULE_H) */
All that a client module must do in order to have access to the function
:c:func:`!PySpam_System` is to call the function (or rather macro)
:c:func:`!import_spam` in its :c:data:`mod_exec <Py_mod_exec>` function::
static int
client_module_exec(PyObject *m)
{
if (import_spam() < 0) {
return -1;
}
/* additional initialization can happen here */
return 0;
}
The main disadvantage of this approach is that the file :file:`spammodule.h` is
rather complicated. However, the basic structure is the same for each function
that is exported, so it has to be learned only once.
Finally it should be mentioned that Capsules offer additional functionality,
which is especially useful for memory allocation and deallocation of the pointer
stored in a Capsule. The details are described in the Python/C API Reference
Manual in the section :ref:`capsules` and in the implementation of Capsules (files
:file:`Include/pycapsule.h` and :file:`Objects/pycapsule.c` in the Python source
code distribution).
.. rubric:: Footnotes
.. [#] An interface for this function already exists in the standard module :mod:`os`
--- it was chosen as a simple and straightforward example.
.. [#] The metaphor of "borrowing" a reference is not completely correct: the owner
still has a copy of the reference.
.. [#] Checking that the reference count is at least 1 **does not work** --- the
reference count itself could be in freed memory and may thus be reused for
another object!
.. [#] These guarantees don't hold when you use the "old" style calling convention ---
this is still found in much existing code.
|