Grouping multiple C declarations

If you have a series of declarations that all begin with cdef, you can group them into a cdef block like this:

cdef:
    struct Spam:
        int tons

    int i
    float f
    Spam *p

    void f(Spam *s):
        print s.tons, "Tons of spam"

Python objects as parameters and return values

If no type is specified for a parameter or return value, it is assumed to be a Python object. (Note that this is different from the C convention, where it would default to int.) For example, the following defines a C function that takes two Python objects as parameters and returns a Python object:

cdef spamobjs(x, y):
    ...

Reference counting for these objects is performed automatically according to the standard Python/C API rules (i.e. borrowed references are taken as parameters and a new reference is returned).

The name object can also be used to explicitly declare something as a Python object. This can be useful if the name being declared would otherwise be taken as the name of a type, for example,:

cdef ftang(object int):
    ...

declares a parameter called int which is a Python object. You can also use object as the explicit return type of a function, e.g.:

cdef object ftang(object int):
    ...

In the interests of clarity, it is probably a good idea to always be explicit about object parameters in C functions.

Error return values

If you don’t do anything special, a function declared with cdef that does not return a Python object has no way of reporting Python exceptions to its caller. If an exception is detected in such a function, a warning message is printed and the exception is ignored.

If you want a C function that does not return a Python object to be able to propagate exceptions to its caller, you need to declare an exception value for it. Here is an example:

cdef int spam() except -1:
    ...

With this declaration, whenever an exception occurs inside spam, it will immediately return with the value -1. Furthermore, whenever a call to spam returns -1, an exception will be assumed to have occurred and will be propagated.

When you declare an exception value for a function, you should never explicitly return that value. If all possible return values are legal and you can’t reserve one entirely for signalling errors, you can use an alternative form of exception value declaration:

cdef int spam() except? -1:
    ...

The ”?” indicates that the value -1 only indicates a possible error. In this case, Cython generates a call to PyErr_Occurred() if the exception value is returned, to make sure it really is an error.

There is also a third form of exception value declaration:

cdef int spam() except *:
    ...

This form causes Cython to generate a call to PyErr_Occurred() after every call to spam, regardless of what value it returns. If you have a function returning void that needs to propagate errors, you will have to use this form, since there isn’t any return value to test. Otherwise there is little use for this form.

An external C++ function that may raise an exception can be declared with:

cdef int spam() except +

See Using C++ in Cython for more details.

Some things to note:

• Exception values can only declared for functions returning an integer, enum, float or pointer type, and the value must be a constant expression. Void functions can only use the except * form.

• The exception value specification is part of the signature of the function. If you’re passing a pointer to a function as a parameter or assigning it to a variable, the declared type of the parameter or variable must have the same exception value specification (or lack thereof). Here is an example of a pointer-to-function declaration with an exception value:

  int (*grail)(int, char*) except -1
  

• You don’t need to (and shouldn’t) declare exception values for functions which return Python objects. Remember that a function with no declared return type implicitly returns a Python object. (Exceptions on such functions are implicitly propagated by returning NULL.)

Checking return values of non-Cython functions

It’s important to understand that the except clause does not cause an error to be raised when the specified value is returned. For example, you can’t write something like:

cdef extern FILE *fopen(char *filename, char *mode) except NULL # WRONG!

and expect an exception to be automatically raised if a call to fopen() returns NULL. The except clause doesn’t work that way; its only purpose is for propagating Python exceptions that have already been raised, either by a Cython function or a C function that calls Python/C API routines. To get an exception from a non-Python-aware function such as fopen(), you will have to check the return value and raise it yourself, for example,:

cdef FILE* p
p = fopen("spam.txt", "r")
if p == NULL:
    raise SpamError("Couldn't open the spam file")

Caveats when using a Python string in a C context

You need to be careful when using a Python string in a context expecting a char*. In this situation, a pointer to the contents of the Python string is used, which is only valid as long as the Python string exists. So you need to make sure that a reference to the original Python string is held for as long as the C string is needed. If you can’t guarantee that the Python string will live long enough, you will need to copy the C string.

Cython detects and prevents some mistakes of this kind. For instance, if you attempt something like:

cdef char *s
s = pystring1 + pystring2

then Cython will produce the error message Obtaining char* from temporary Python value. The reason is that concatenating the two Python strings produces a new Python string object that is referenced only by a temporary internal variable that Cython generates. As soon as the statement has finished, the temporary variable will be decrefed and the Python string deallocated, leaving s dangling. Since this code could not possibly work, Cython refuses to compile it.

The solution is to assign the result of the concatenation to a Python variable, and then obtain the char* from that, i.e.:

cdef char *s
p = pystring1 + pystring2
s = p

It is then your responsibility to hold the reference p for as long as necessary.

Keep in mind that the rules used to detect such errors are only heuristics. Sometimes Cython will complain unnecessarily, and sometimes it will fail to detect a problem that exists. Ultimately, you need to understand the issue and be careful what you do.

Differences between C and Cython expressions

There are some differences in syntax and semantics between C expressions and Cython expressions, particularly in the area of C constructs which have no direct equivalent in Python.

• An integer literal is treated as a C constant, and will be truncated to whatever size your C compiler thinks appropriate. To get a Python integer (of arbitrary precision) cast immediately to an object (e.g. <object>100000000000000000000). The L, LL, and U suffixes have the same meaning as in C.

• There is no -> operator in Cython. Instead of p->x, use p.x

• There is no unary * operator in Cython. Instead of *p, use p[0]

• There is an & operator, with the same semantics as in C.

• The null C pointer is called NULL, not 0 (and NULL is a reserved word).

• Type casts are written <type>value , for example,:

  cdef char* p, float* q
  p = <char*>q
  

Scope rules

Cython determines whether a variable belongs to a local scope, the module scope, or the built-in scope completely statically. As with Python, assigning to a variable which is not otherwise declared implicitly declares it to be a Python variable residing in the scope where it is assigned.

try:
    x = True
except NameError:
    True = 1

import __builtin__
try:
    True = __builtin__.True
except AttributeError:
    True = 1

Built-in Functions

Cython compiles calls to most built-in functions into direct calls to the corresponding Python/C API routines, making them particularly fast.

Only direct function calls using these names are optimised. If you do something else with one of these names that assumes it’s a Python object, such as assign it to a Python variable, and later call it, the call will be made as a Python function call.

Note 1: Pyrex originally provided a function getattr3(obj, name, default)() corresponding to the three-argument form of the Python builtin getattr(). Cython still supports this function, but the usage is deprecated in favour of the normal builtin, which Cython can optimise in both forms.

Operator Precedence

Keep in mind that there are some differences in operator precedence between Python and C, and that Cython uses the Python precedences, not the C ones.

Integer for-loops

Cython recognises the usual Python for-in-range integer loop pattern:

for i in range(n):
    ...

If i is declared as a cdef integer type, it will optimise this into a pure C loop. This restriction is required as otherwise the generated code wouldn’t be correct due to potential integer overflows on the target architecture. If you are worried that the loop is not being converted correctly, use the annotate feature of the cython commandline (-a) to easily see the generated C code. See Automatic range conversion

For backwards compatibility to Pyrex, Cython also supports another form of for-loop:

for i from 0 <= i < n:
    ...

or:

for i from 0 <= i < n by s:
    ...

where s is some integer step size.

Some things to note about the for-from loop:

• The target expression must be a variable name.
• The name between the lower and upper bounds must be the same as the target name.
• The direction of iteration is determined by the relations. If they are both from the set {<, <=} then it is upwards; if they are both from the set {>, >=} then it is downwards. (Any other combination is disallowed.)

Like other Python looping statements, break and continue may be used in the body, and the loop may have an else clause.

Compile-Time Definitions

A compile-time constant can be defined using the DEF statement:

DEF FavouriteFood = "spam"
DEF ArraySize = 42
DEF OtherArraySize = 2 * ArraySize + 17

The right-hand side of the DEF must be a valid compile-time expression. Such expressions are made up of literal values and names defined using DEF statements, combined using any of the Python expression syntax.

The following compile-time names are predefined, corresponding to the values returned by os.uname().

UNAME_SYSNAME, UNAME_NODENAME, UNAME_RELEASE, UNAME_VERSION, UNAME_MACHINE

The following selection of builtin constants and functions are also available:

None, True, False, abs, bool, chr, cmp, complex, dict, divmod, enumerate, float, hash, hex, int, len, list, long, map, max, min, oct, ord, pow, range, reduce, repr, round, slice, str, sum, tuple, xrange, zip

A name defined using DEF can be used anywhere an identifier can appear, and it is replaced with its compile-time value as though it were written into the source at that point as a literal. For this to work, the compile-time expression must evaluate to a Python value of type int, long, float or str.:

cdef int a1[ArraySize]
cdef int a2[OtherArraySize]
print "I like", FavouriteFood

Conditional Statements

The IF statement can be used to conditionally include or exclude sections of code at compile time. It works in a similar way to the #if preprocessor directive in C.:

IF UNAME_SYSNAME == "Windows":
    include "icky_definitions.pxi"
ELIF UNAME_SYSNAME == "Darwin":
    include "nice_definitions.pxi"
ELIF UNAME_SYSNAME == "Linux":
    include "penguin_definitions.pxi"
ELSE:
    include "other_definitions.pxi"

The ELIF and ELSE clauses are optional. An IF statement can appear anywhere that a normal statement or declaration can appear, and it can contain any statements or declarations that would be valid in that context, including DEF statements and other IF statements.

The expressions in the IF and ELIF clauses must be valid compile-time expressions as for the DEF statement, although they can evaluate to any Python value, and the truth of the result is determined in the usual Python way.