Migrating from Cython 0.29 to 3.0¶
Cython 3.0 is a major revision of the compiler and the language that comes with some backwards incompatible changes. This document lists the important ones and explains how to deal with them in existing code.
Python 3 syntax/semantics¶
Cython 3.0 now uses Python 3 syntax and semantics by default, which previously
required setting the language_level
directive <compiler-directives> to
either 3
or 3str
.
The new default setting is now language_level=3str
, which means Python 3
semantics, but unprefixed strings are str
objects, i.e. unicode text strings
under Python 3 and byte strings under Python 2.7.
You can revert your code to the previous (Python 2.x) semantics by setting
language_level=2
.
Further semantic changes due to the language level include:
/
-division uses the true (float) division operator, unlesscdivision
is enabled.print
is a function, not a statement.Python classes that are defined without bases (
class C: ...
) are “new-style” classes also in Py2.x (if you never heard about “old-style classes”, you’re probably happy without them).Annotations (type hints) are now stored as strings. (PEP 563)
StopIteration
handling in generators has been changed according to PEP 479.
Python semantics¶
Some Python compatibility bugs were fixed, e.g.
Subscripting (
x[1]
) now tries the mapping protocol before the sequence protocol. (https://github.com/cython/cython/issues/1807)Exponentiation of integer literals now follows Python semantics and not C semantics. (https://github.com/cython/cython/issues/2133)
Binding functions¶
The binding directive is now enabled by default.
This makes Cython compiled Python (def
) functions mostly compatible
with normal (non-compiled) Python functions, regarding signature introspection,
annotations, etc.
It also makes them bind as methods in Python classes on attribute assignments,
thus the name.
If this is not intended, i.e. if a function is really meant to be a function
and never a method, you can disable the binding (and all other Python function
features) by setting binding=False
or selectively adding a decorator
@cython.binding(False)
.
In pure Python mode, the decorator was not available in Cython 0.29.16 yet,
but compiled code does not suffer from this.
We recommend, however, to keep the new function features and instead deal
with the binding issue using the standard Python staticmethod()
builtin.
def func(self, b): ...
class MyClass(object):
binding_method = func
no_method = staticmethod(func)
Namespace packages¶
Cython now has support for loading pxd files also from namespace packages according to PEP-420. This might have an impact on the import path.
NumPy C-API¶
Cython used to generate code that depended on the deprecated pre-NumPy-1.7 C-API. This is no longer the case with Cython 3.0.
You can now define the macro NPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION
to get rid of the long-standing build warnings that the compiled C module
uses a deprecated API. Either per file:
# distutils: define_macros=NPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION
or by setting it in your Extensions in setup.py
:
Extension(...
define_macros=[("NPY_NO_DEPRECATED_API", "NPY_1_7_API_VERSION")]
)
One side-effect of the different C-API usage is that your code may now require a call to the NumPy C-API initialisation function where it previously got away without doing so.
In order to reduce the user impact here, Cython 3.0 will now call it
automatically when it sees numpy
being cimported, but the function
not being used.
In the (hopefully rare) cases where this gets in the way, the internal
C-API initialisation can be disabled by faking the use of the function
without actually calling it, e.g.
# Explicitly disable the automatic initialisation of NumPy's C-API.
<void>import_array
Class-private name mangling¶
Cython has been updated to follow the Python rules for class-private names
more closely. Essentially any name that starts with and doesn’t end with
__
within a class is mangled with the class name. Most user code
should be unaffected – unlike in Python unmangled global names will
still be matched to ensure it is possible to access C names
beginning with __
:
cdef extern void __foo()
class C: # or "cdef class"
def call_foo(self):
return __foo() # still calls the global name
What will no-longer work is overriding methods starting with __
in
a cdef class
:
cdef class Base:
cdef __bar(self):
return 1
def call_bar(self):
return self.__bar()
cdef class Derived(Base):
cdef __bar(self):
return 2
Here Base.__bar
is mangled to _Base__bar
and Derived.__bar
to _Derived__bar
. Therefore call_bar
will always call
_Base__bar
. This matches established Python behaviour and applies
for def
, cdef
and cpdef
methods and attributes.
Arithmetic special methods¶
The behaviour of arithmetic special methods (for example __add__
and __pow__
) of cdef classes has changed in Cython 3.0. They now
support separate “reversed” versions of these methods (e.g.
__radd__
, __rpow__
) that behave like in pure Python.
The main incompatible change is that the type of the first operand
(usually __self__
) is now assumed to be that of the defining class,
rather than relying on the user to test and cast the type of each operand.
The old behaviour can be restored with the
directive c_api_binop_methods=True
.
More details are given in Arithmetic methods.
Exception values and noexcept
¶
cdef
functions that are not extern
now safely propagate Python
exceptions by default. Previously, they needed to explicitly be declared
with an exception value to prevent them from
swallowing exceptions. A new noexcept
modifier can be used to declare
cdef
functions that really will not raise exceptions.
In existing code, you should mainly look out for cdef
functions
that are declared without an exception value:
cdef int spam(int x):
pass
cdef void silent(int x):
pass
If you left out the exception value by mistake, i.e., the function should propagate Python exceptions, then the new behaviour will take care of this for you, and correctly propagate any exceptions. This was a common mistake in Cython code and the main reason to change the behaviour.
On the other hand, if you didn’t declare an exception value because
you want to avoid exceptions propagating out of this function, the new behaviour
will result in slightly less efficient code being generated, now involving an exception check.
To prevent that, you must declare the function explicitly as being
noexcept
:
cdef int spam(int x) noexcept:
pass
cdef void silent(int x) noexcept:
pass
The behaviour for cdef
functions that are also extern
is
unchanged as extern
functions are less likely to raise Python
exceptions and rather tend to be plain C functions. This mitigates
the effect of this change for code that talks to C libraries.
The behaviour for any cdef
function that is declared with an
explicit exception value (e.g., cdef int spam(int x) except -1
) is
also unchanged.
There is an easy-to-encounter performance pitfall here with nogil
functions
with an implicit exception specification of except *
. This can happen
most commonly when the return type is void
(but in principle applies
to most non-numeric return types). In this case, Cython is forced to
re-acquire the GIL briefly after each call to check the exception state.
To avoid this overhead, either change the signature to noexcept
(if
you have determined that it’s suitable to do so), or to returning an int
instead to let Cython use the int
as an error flag
(by default, -1
triggers the exception check).
Note
The unsafe legacy behaviour of not propagating exceptions by default can be enabled by
setting legacy_implicit_noexcept
compiler directive
to True
.
Annotation typing¶
Cython 3 has made substantial improvements in recognising types in annotations and it is well worth reading the pure Python tutorial to understand some of the improvements.
A notable backwards-incompatible change is that x: int
is now typed
such that x
is an exact Python int
(Cython 0.29 would accept
any Python object for x
), unless the language level is explicitly
set to 2. To mitigate the effect, Cython 3.0 still accepts both Python
int
and long
values under Python 2.x.
To make it easier to handle cases where your interpretation of type
annotations differs from Cython’s, Cython 3 now supports setting the
annotation_typing
directive on a
per-class or per-function level.
C++ postincrement/postdecrement operator¶
Cython 3 differentiates between pre/post-increment and pre/post-decrement
operators (Cython 0.29 implemented both as pre(in/de)crement operator).
This only has an effect when using cython.operator.postdecrement
/ cython.operator.postincrement
.
When running into an error it is required to add the corresponding operator:
cdef cppclass Example:
Example operator++(int)
Example operator--(int)
Public Declarations in C++¶
Public declarations in C++ mode are exported as C++ API in Cython 3, using extern "C++"
.
This behaviour can be changed by setting the export keyword using the CYTHON_EXTERN_C
macro
to allow Cython modules to be implemented in C++ but callable from C.
**
power operator¶
Cython 3 has changed the behaviour of the power operator to be more like Python. The consequences are that
a**b
of two ints may return a floating point type,a**b
of one or more non-complex floating point numbers may return a complex number.
The old behaviour can be restored by setting the cpow
compiler directive to True
.