8000 DOC: incorporate "upcoming changes" fragments into 2.0.0 release notes · numpy/numpy@34a8170 · GitHub
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DOC: incorporate "upcoming changes" fragments into 2.0.0 release notes
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‎doc/release/upcoming_changes/25168.change.rst

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‎doc/release/upcoming_changes/25754.c_api.rst

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‎doc/release/upcoming_changes/25812.c_api.rst

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‎doc/release/upcoming_changes/25816.c_api.rst

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‎doc/release/upcoming_changes/25816.change.rst

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‎doc/release/upcoming_changes/25866.c_api.rst

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‎doc/source/reference/c-api/array.rst

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@@ -3318,7 +3318,7 @@ Data Type Promotion and Inspection
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for a ``singleton`` first and only calls the ``default_descr`` function if
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necessary.
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.. dtype-api_
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.. _dtype-api:
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Custom Data Types
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-----------------

‎doc/source/release/2.0.0-notes.rst

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@@ -342,6 +342,31 @@ C API changes
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(`gh-25789 <https://github.com/numpy/numpy/pull/25789>`__)
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* The ``->f`` slot has been removed from ``PyArray_Descr``.
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If you use this slot, replace accessing it with
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``PyDataType_GetArrFuncs`` (see its documentation and the
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:ref:`numpy-2-migration-guide`). In some cases using other functions like
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``PyArray_GETITEM`` may be an alternatives.
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* ``PyArray_GETITEM`` and ``PyArray_SETITEM`` now require the import of the
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NumPy API table to be used and are no longer defined in ``ndarraytypes.h``.
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(`gh-25812 <https://github.com/numpy/numpy/pull/25812>`__)
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* Due to runtime dependencies, the definition for functionality accessing
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the dtype flags was moved from ``numpy/ndarraytypes.h`` and is only available
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after including ``numpy/ndarrayobject.h`` as it requires ``import_array()``.
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This includes ``PyDataType_FLAGCHK``, ``PyDataType_REFCHK`` and
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``NPY_BEGIN_THREADS_DESCR``.
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* The dtype flags on ``PyArray_Descr`` must now be accessed through the
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``PyDataType_FLAGS`` inline function to be compatible with both 1.x and 2.x.
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This function is defined in ``npy_2_compat.h`` to allow backporting.
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Most or all users should use ``PyDataType_FLAGCHK`` which is available on
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1.x and does not require backporting.
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Cython users should use Cython 3. Otherwise access will go through Python
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unless they use ``PyDataType_FLAGCHK`` instead.
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(`gh-25816 <https://github.com/numpy/numpy/pull/25816>`__)
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Datetime functionality exposed in the C API and Cython bindings
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---------------------------------------------------------------
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@@ -357,6 +382,7 @@ external libraries.
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Const correctness for the generalized ufunc C API
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-------------------------------------------------
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The NumPy C API's functions for constructing generalized ufuncs
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(``PyUFunc_FromFuncAndData``, ``PyUFunc_FromFuncAndDataAndSignature``,
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``PyUFunc_FromFuncAndDataAndSignatureAndIdentity``) take ``types`` and ``data``
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``NPY_MAXARGS`` not constant and ``PyArrayMultiIterObject`` size change
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-----------------------------------------------------------------------
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Since ``NPY_MAXARGS`` was increased, it is now a runtime constant and not
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compile-time constant anymore.
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We expect almost no users to notice this. But if used for stack allocations
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Required changes for custom legacy user dtypes
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----------------------------------------------
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In order to improve our DTypes it is unfortunately necessary
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to break with A 9E88 BI, which requires some changes for dtypes registered
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with `PyArray_RegisterDataType`.
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Please see the documentation of `PyArray_RegisterDataType` for how
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to break the ABI, which requires some changes for dtypes registered
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with ``PyArray_RegisterDataType``.
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Please see the documentation of ``PyArray_RegisterDataType`` for how
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to adapt your code and achieve compatibility with both 1.x and 2.x.
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(`gh-25792 <https://github.com/numpy/numpy/pull/25792>`__)
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New Public DType API
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--------------------
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The C implementation of the NEP 42 DType API is now public. While the DType API
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has shipped in NumPy for a few versions, it was only usable in sessions with a
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special environment variable set. It is now possible to write custom DTypes
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outside of NumPy using the new DType API and the normal ``import_array()``
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mechanism for importing the numpy C API.
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See :ref:`dtype-api` for more details about the API. As always with a new
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feature, please report any bugs you run into implementing or using a new
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DType. It is likely that downstream C code that works with dtypes will need to
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be updated to work correctly with new DTypes.
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(`gh-25754 <https://github.com/numpy/numpy/pull/25754>`__)
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New C-API import functions
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--------------------------
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We have now added ``PyArray_ImportNumPyAPI`` and ``PyUFunc_ImportUFuncAPI``
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as static inline functions to import the NumPy C-API tables.
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The new functions have two advantages over ``import_array`` and
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``import_ufunc``:
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- They check whether the import was already performed and are light-weight
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if not, allowing to add them judiciously (although this is not preferable
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in most cases).
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- The old mechanisms were macros rather than functions which included a
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``return`` statement.
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The ``PyArray_ImportNumPyAPI()`` function is included in ``npy_2_compat.h``
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for simpler backporting.
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(`gh-25866 <https://github.com/numpy/numpy/pull/25866>`__)
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NumPy 2.0 C API removals
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========================
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(`gh-25080 <https://github.com/numpy/numpy/pull/25080>`__)
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* The ``dtype.flags`` value was previously usually stored as a signed integer.
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This means that the aligned dtype struct flag lead to negative flags being
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set (-128 rather than 128). This flag is now stored unsigned (positive). Code
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which checks flags manually may need to adapt. This may include code
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compiled with Cython 0.29.x.
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(`gh-25816 <https://github.com/numpy/numpy/pull/25816>`__)
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Representation of NumPy scalars changed
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---------------------------------------
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As per :ref:`NEP 51 <NEP51>`, the scalar representation has been
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(`gh-25149 <https://github.com/numpy/numpy/pull/25149>`__)
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New ``copy`` keyword meaning for `numpy.array` and `numpy.asarray`
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------------------------------------------------------------------
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Now `numpy.array` and `numpy.asarray` support three values for ``copy`` parameter:
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* ``None`` - A copy will only be made if it is necessary.
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* ``True`` - Always make a copy.
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* ``False`` - Never make a copy. If a copy is required a ``ValueError`` is raised.
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The meaning of ``False`` changed as it now raises an exception if a copy is needed.
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(`gh-25168 <https://github.com/numpy/numpy/pull/25168>`__)
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The ``__array__`` special method now takes a ``copy`` keyword argument.
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-----------------------------------------------------------------------
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NumPy will pass ``copy`` to the ``__array__`` special method in situations where
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it would be set to a non-default value (e.g. in a call to
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``np.asarray(some_object, copy=False)``). Currently, if an
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unexpected keyword argument error is raised after this, NumPy will print a
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warning and re-try without the ``copy`` keyword argument. Implementations of
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objects implementing the ``__array__`` protocol should accept a ``copy`` keyword
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argument with the same meaning as when passed to `numpy.array` or
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`numpy.asarray`.
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(`gh-25168 <https://github.com/numpy/numpy/pull/25168>`__)
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Cleanup of initialization of ``numpy.dtype`` with strings with commas
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---------------------------------------------------------------------
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The interpretation of strings with commas is changed slightly, in that a

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