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Kirill Smelkov
cython
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bfc4c3fa
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bfc4c3fa
authored
Apr 18, 2020
by
Stefan Behnel
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Start writing up some help for users who want to migrate from Cython 0.29.x to Cython 3.0.
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docs/src/userguide/index.rst
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wrapping_CPlusPlus
fusedtypes
pypy
migrating_to_cy30
limitations
pyrex_differences
memoryviews
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.. highlight:: cython
.. _cython30:
*********************************
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, unless ``cdivision`` is enabled.
* ``print`` is a function, not a statement.
* Annotations (type hints) are now stored as strings.
(`PEP 563 <https://github.com/cython/cython/issues/2863>`_)
* ``StopIteration`` handling in generators has been changed according to
`PEP 479 <https://www.python.org/dev/peps/pep-0479/>`_.
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 :ref:`binding directive <compiler-directives>` 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 <https://www.python.org/dev/peps/pep-0420/>`_.
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
<https://docs.scipy.org/doc/numpy-1.17.0/reference/c-api.array.html#importing-the-api>`_
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
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