diff options
60 files changed, 1335 insertions, 596 deletions
@@ -29,10 +29,11 @@ Call for Contributions The NumPy project welcomes your expertise and enthusiasm! -Small improvements or fixes are always appreciated; issues labeled as "good -first issue" may be a good starting point. If you are considering larger -contributions to the source code, please contact us through the [mailing -list](https://mail.python.org/mailman/listinfo/numpy-discussion) first. +Small improvements or fixes are always appreciated; issues labeled as ["good +first issue"](https://github.com/numpy/numpy/labels/good%20first%20issue) +may be a good starting point. If you are considering larger contributions +to the source code, please contact us through the [mailing +list](https://mail.python.org/mailman/listinfo/numpy-discussion) first. Writing code isn’t the only way to contribute to NumPy. You can also: - review pull requests diff --git a/doc/RELEASE_WALKTHROUGH.rst.txt b/doc/RELEASE_WALKTHROUGH.rst.txt index 4fbc7af1c..6febd554f 100644 --- a/doc/RELEASE_WALKTHROUGH.rst.txt +++ b/doc/RELEASE_WALKTHROUGH.rst.txt @@ -102,8 +102,8 @@ someone else, then create a new branch for the series. If the branch already exists skip this:: $ cd ../numpy-wheels - $ git co master - $ git pull upstream master + $ git checkout main + $ git pull upstream main $ git branch v1.19.x Checkout the new branch and edit the ``azure-pipelines.yml`` and diff --git a/doc/neps/nep-0035-array-creation-dispatch-with-array-function.rst b/doc/neps/nep-0035-array-creation-dispatch-with-array-function.rst index 427d91b7d..3a689a4dc 100644 --- a/doc/neps/nep-0035-array-creation-dispatch-with-array-function.rst +++ b/doc/neps/nep-0035-array-creation-dispatch-with-array-function.rst @@ -5,11 +5,11 @@ NEP 35 — Array Creation Dispatching With __array_function__ =========================================================== :Author: Peter Andreas Entschev <pentschev@nvidia.com> -:Status: Draft +:Status: Final :Type: Standards Track :Created: 2019-10-15 :Updated: 2020-11-06 -:Resolution: +:Resolution: https://mail.python.org/pipermail/numpy-discussion/2021-May/081761.html Abstract -------- diff --git a/doc/neps/nep-0042-new-dtypes.rst b/doc/neps/nep-0042-new-dtypes.rst index 1738bd1ab..bb85f1d10 100644 --- a/doc/neps/nep-0042-new-dtypes.rst +++ b/doc/neps/nep-0042-new-dtypes.rst @@ -1334,7 +1334,7 @@ Although verbose, the API will mimic the one for creating a new DType: typedef struct{ int flags; /* e.g. whether the cast requires the API */ int nin, nout; /* Number of Input and outputs (always 1) */ - NPY_CASTING casting; /* The default casting level */ + NPY_CASTING casting; /* The "minimal casting level" */ PyArray_DTypeMeta *dtypes; /* input and output DType class */ /* NULL terminated slots defining the methods */ PyType_Slot *slots; @@ -1342,7 +1342,7 @@ Although verbose, the API will mimic the one for creating a new DType: The focus differs between casting and general ufuncs. For example, for casts ``nin == nout == 1`` is always correct, while for ufuncs ``casting`` is -expected to be usually `"safe"`. +expected to be usually `"no"`. **Notes:** We may initially allow users to define only a single loop. Internally NumPy optimizes far more, and this should be made public @@ -1357,6 +1357,11 @@ incrementally in one of two ways: * Or, more likely, expose the ``get_loop`` function which is passed additional information, such as the fixed strides (similar to our internal API). +* The casting level denotes the minimal guaranteed casting level and can be + ``-1`` if the cast may be impossible. For most non-parametric casts, this + value will be the casting level. NumPy may skip the ``resolve_descriptors`` + call for ``np.can_cast()`` when the result is ``True`` based on this level. + The example does not yet include setup and error handling. Since these are similar to the UFunc machinery, they will be defined in :ref:`NEP 43 <NEP43>` and then incorporated identically into casting. diff --git a/doc/neps/nep-0043-extensible-ufuncs.rst b/doc/neps/nep-0043-extensible-ufuncs.rst index 3c6407728..cd73108e4 100644 --- a/doc/neps/nep-0043-extensible-ufuncs.rst +++ b/doc/neps/nep-0043-extensible-ufuncs.rst @@ -262,8 +262,8 @@ to define string equality, will be added to a ufunc. if given_descrs[2] is None: out_descr = DTypes[2]() - # The operation is always "safe" casting (most ufuncs are) - return (given_descrs[0], given_descrs[1], out_descr), "safe" + # The operation is always "no" casting (most ufuncs are) + return (given_descrs[0], given_descrs[1], out_descr), "no" def strided_loop(context, dimensions, data, strides, innerloop_data): """The 1-D strided loop, similar to those used in current ufuncs""" @@ -434,7 +434,7 @@ a new ``ArrayMethod`` object: # Casting safety information (almost always "safe", necessary to # unify casting and universal functions) - casting: Casting = "safe" + casting: Casting = "no" # More general flags: flags: int @@ -751,7 +751,7 @@ This step is required to allocate output arrays and has to happen before casting can be prepared. While the returned casting-safety (``NPY_CASTING``) will almost always be -"safe" for universal functions, including it has two big advantages: +"no" for universal functions, including it has two big advantages: * ``-1`` indicates that an error occurred. If a Python error is set, it will be raised. If no Python error is set this will be considered an "impossible" @@ -767,7 +767,7 @@ While the returned casting-safety (``NPY_CASTING``) will almost always be perspective. Currently, this would use ``int64 + int64 -> int64`` and then cast to ``int32``. An implementation that skips the cast would have to signal that it effectively includes the "same-kind" cast and is - thus not considered "safe". + thus not considered "no". ``get_loop`` method diff --git a/doc/source/conf.py b/doc/source/conf.py index 5ba7f70b8..a49074922 100644 --- a/doc/source/conf.py +++ b/doc/source/conf.py @@ -295,6 +295,7 @@ intersphinx_mapping = { 'pandas': ('https://pandas.pydata.org/pandas-docs/stable', None), 'scipy-lecture-notes': ('https://scipy-lectures.org', None), 'pytest': ('https://docs.pytest.org/en/stable', None), + 'numpy-tutorials': ('https://numpy.org/numpy-tutorials', None), } diff --git a/doc/source/docs/howto_build_docs.rst b/doc/source/docs/howto_build_docs.rst index 38ea1338c..737f69877 100644 --- a/doc/source/docs/howto_build_docs.rst +++ b/doc/source/docs/howto_build_docs.rst @@ -16,6 +16,33 @@ in several different formats. .. _Sphinx: http://www.sphinx-doc.org/ +To build the documentation, you must first build NumPy. + +There are two options for building NumPy and its documentation- building with +Gitpod or locally from source. Your choice depends on your operating system and +familiarity with the command line. + +Gitpod +------------ + +Gitpod is an open-source platform that automatically creates +the correct development environment right in your browser, reducing the need to +install local development environments and deal with incompatible dependencies. + +If you are a Windows user, unfamiliar with using the command line or building +NumPy's documentation for the first time, it is often faster to build with +Gitpod. Here are the in-depth instructions for building NumPy with `building +NumPy with Gitpod`_. + +.. _building NumPy with Gitpod: https://numpy.org/devdocs/dev/development_gitpod.html + +Building locally +------------------ + +Building locally on your machine gives you more granular control. If you are a +MacOS or Linux user familiar with using the command line, you can continue with +building NumPy locally by following the instructions below. + Instructions ------------ diff --git a/doc/source/reference/c-api/array.rst b/doc/source/reference/c-api/array.rst index 1673f1d6b..cb2f4b645 100644 --- a/doc/source/reference/c-api/array.rst +++ b/doc/source/reference/c-api/array.rst @@ -2647,6 +2647,12 @@ cost of a slight overhead. - If the position of iter is changed, any subsequent call to PyArrayNeighborhoodIter_Next is undefined behavior, and PyArrayNeighborhoodIter_Reset must be called. + - If the position of iter is not the beginning of the data and the + underlying data for iter is contiguous, the iterator will point to the + start of the data instead of position pointed by iter. + To avoid this situation, iter should be moved to the required position + only after the creation of iterator, and PyArrayNeighborhoodIter_Reset + must be called. .. code-block:: c @@ -2656,7 +2662,7 @@ cost of a slight overhead. /*For a 3x3 kernel */ bounds = {-1, 1, -1, 1}; - neigh_iter = (PyArrayNeighborhoodIterObject*)PyArrayNeighborhoodIter_New( + neigh_iter = (PyArrayNeighborhoodIterObject*)PyArray_NeighborhoodIterNew( iter, bounds, NPY_NEIGHBORHOOD_ITER_ZERO_PADDING, NULL); for(i = 0; i < iter->size; ++i) { diff --git a/doc/source/release/1.21.0-notes.rst b/doc/source/release/1.21.0-notes.rst index ac65b8fd0..c0d283b72 100644 --- a/doc/source/release/1.21.0-notes.rst +++ b/doc/source/release/1.21.0-notes.rst @@ -82,39 +82,6 @@ The methods in question are: Future Changes ============== -Promotion of strings with numbers and bools is deprecated ---------------------------------------------------------- -Any promotion of numbers and strings is deprecated and will -give a ``FutureWarning`` the main affected functionalities -are: - -* `numpy.promote_types` and `numpy.result_type` which will raise - an error in this case in the future. -* `numpy.concatenate` will raise an error when concatenating a string - and numeric array. You can use ``dtype="S"`` to explicitly request - a string result. -* `numpy.array` and related functions will start returning ``object`` - arrays because these functions use ``object`` as a fallback when - no common dtype can be found. However, it may happen that future - releases of NumPy will generally error in these cases. - -This will mainly affect code such as:: - - np.asarray(['string', 0]) - -and:: - - np.concatenate((['string'], [0])) - -in both cases adding ``dtype="U"`` or ``dtype="S"`` will give the -previous (string) result, while ``dtype=object`` will ensure an array with -object dtype is returned. - -Comparisons, universal functions, and casting are not affected by this. - -(`gh-18116 <https://github.com/numpy/numpy/pull/18116>`__) - - Expired deprecations ==================== diff --git a/doc/source/user/building.rst b/doc/source/user/building.rst index 52d7330bf..10983ce8f 100644 --- a/doc/source/user/building.rst +++ b/doc/source/user/building.rst @@ -3,8 +3,30 @@ Building from source ==================== -A general overview of building NumPy from source is given here, with detailed -instructions for specific platforms given separately. +There are two options for building NumPy- building with Gitpod or locally from +source. Your choice depends on your operating system and familiarity with the +command line. + +Gitpod +------------ + +Gitpod is an open-source platform that automatically creates +the correct development environment right in your browser, reducing the need to +install local development environments and deal with incompatible dependencies. + +If you are a Windows user, unfamiliar with using the command line or building +NumPy for the first time, it is often faster to build with Gitpod. Here are the +in-depth instructions for building NumPy with `building NumPy with Gitpod`_. + +.. _building NumPy with Gitpod: https://numpy.org/devdocs/dev/development_gitpod.html + +Building locally +------------------ + +Building locally on your machine gives you +more granular control. If you are a MacOS or Linux user familiar with using the +command line, you can continue with building NumPy locally by following the +instructions below. .. This page is referenced from numpy/numpy/__init__.py. Please keep its @@ -23,15 +45,16 @@ Building NumPy requires the following software installed: 2) Compilers - To build any extension modules for Python, you'll need a C compiler. - Various NumPy modules use FORTRAN 77 libraries, so you'll also need a - FORTRAN 77 compiler installed. + While a FORTRAN 77 compiler is not necessary for building NumPy, it is + needed to run the ``numpy.f2py`` tests. These tests are skipped if the + compiler is not auto-detected. Note that NumPy is developed mainly using GNU compilers and tested on MSVC and Clang compilers. Compilers from other vendors such as Intel, - Absoft, Sun, NAG, Compaq, Vast, Portland, Lahey, HP, IBM are only supported - in the form of community feedback, and may not work out of the box. - GCC 4.x (and later) compilers are recommended. On ARM64 (aarch64) GCC 8.x (and later) are recommended. + Absoft, Sun, NAG, Compaq, Vast, Portland, Lahey, HP, IBM are only + supported in the form of community feedback, and may not work out of the + box. GCC 4.x (and later) compilers are recommended. On ARM64 (aarch64) + GCC 8.x (and later) are recommended. 3) Linear Algebra libraries @@ -67,7 +90,8 @@ To perform an in-place build that can be run from the source folder run:: Testing ------- -Make sure to test your builds. To ensure everything stays in shape, see if all tests pass:: +Make sure to test your builds. To ensure everything stays in shape, see if +all tests pass:: $ python runtests.py -v -m full @@ -105,11 +129,12 @@ For more information see:: How to check the ABI of BLAS/LAPACK libraries ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -One relatively simple and reliable way to check for the compiler used to build -a library is to use ldd on the library. If libg2c.so is a dependency, this -means that g77 has been used (note: g77 is no longer supported for building NumPy). -If libgfortran.so is a dependency, gfortran has been used. If both are dependencies, -this means both have been used, which is almost always a very bad idea. +One relatively simple and reliable way to check for the compiler used to +build a library is to use ldd on the library. If libg2c.so is a dependency, +this means that g77 has been used (note: g77 is no longer supported for +building NumPy). If libgfortran.so is a dependency, gfortran has been used. +If both are dependencies, this means both have been used, which is almost +always a very bad idea. .. _accelerated-blas-lapack-libraries: @@ -155,11 +180,11 @@ Alternatively one may use ``!`` or ``^`` to negate all items:: NPY_BLAS_ORDER='^blas,atlas' python setup.py build -will allow using anything **but** NetLIB BLAS and ATLAS libraries, the order of the above -list is retained. +will allow using anything **but** NetLIB BLAS and ATLAS libraries, the order +of the above list is retained. -One cannot mix negation and positives, nor have multiple negations, such cases will -raise an error. +One cannot mix negation and positives, nor have multiple negations, such +cases will raise an error. LAPACK ~~~~~~ @@ -191,19 +216,19 @@ Alternatively one may use ``!`` or ``^`` to negate all items:: NPY_LAPACK_ORDER='^lapack' python setup.py build -will allow using anything **but** the NetLIB LAPACK library, the order of the above -list is retained. +will allow using anything **but** the NetLIB LAPACK library, the order of +the above list is retained. -One cannot mix negation and positives, nor have multiple negations, such cases will -raise an error. +One cannot mix negation and positives, nor have multiple negations, such +cases will raise an error. .. deprecated:: 1.20 The native libraries on macOS, provided by Accelerate, are not fit for use - in NumPy since they have bugs that cause wrong output under easily reproducible - conditions. If the vendor fixes those bugs, the library could be reinstated, - but until then users compiling for themselves should use another linear - algebra library or use the built-in (but slower) default, see the next - section. + in NumPy since they have bugs that cause wrong output under easily + reproducible conditions. If the vendor fixes those bugs, the library could + be reinstated, but until then users compiling for themselves should use + another linear algebra library or use the built-in (but slower) default, + see the next section. Disabling ATLAS and other accelerated libraries @@ -257,5 +282,6 @@ Supplying additional compiler flags Additional compiler flags can be supplied by setting the ``OPT``, ``FOPT`` (for Fortran), and ``CC`` environment variables. -When providing options that should improve the performance of the code ensure -that you also set ``-DNDEBUG`` so that debugging code is not executed. +When providing options that should improve the performance of the code +ensure that you also set ``-DNDEBUG`` so that debugging code is not +executed. diff --git a/doc/source/user/how-to-how-to.rst b/doc/source/user/how-to-how-to.rst index 16a2fc7a4..13d2b405f 100644 --- a/doc/source/user/how-to-how-to.rst +++ b/doc/source/user/how-to-how-to.rst @@ -105,10 +105,7 @@ deep dives intended to give understanding rather than immediate assistance, and `References`, which give complete, autoritative data on some concrete part of NumPy (like its API) but aren't obligated to paint a broader picture. -For more on tutorials, see the `tutorial how-to`_. - -.. _`tutorial how-to`: https://github.com/numpy/numpy-tutorials/blob/master/tutorial_style.ipynb - +For more on tutorials, see :doc:`content/tutorial-style-guide` ****************************************************************************** Is this page an example of a how-to? diff --git a/numpy/__init__.pyi b/numpy/__init__.pyi index ac37eb8ad..a83e5d9c7 100644 --- a/numpy/__init__.pyi +++ b/numpy/__init__.pyi @@ -1226,20 +1226,9 @@ class _ArrayOrScalarCommon: def __deepcopy__(self: _ArraySelf, __memo: Optional[dict] = ...) -> _ArraySelf: ... def __eq__(self, other): ... def __ne__(self, other): ... - def astype( - self: _ArraySelf, - dtype: DTypeLike, - order: _OrderKACF = ..., - casting: _Casting = ..., - subok: bool = ..., - copy: bool = ..., - ) -> _ArraySelf: ... def copy(self: _ArraySelf, order: _OrderKACF = ...) -> _ArraySelf: ... def dump(self, file: str) -> None: ... def dumps(self) -> bytes: ... - def getfield( - self: _ArraySelf, dtype: DTypeLike, offset: int = ... - ) -> _ArraySelf: ... def tobytes(self, order: _OrderKACF = ...) -> bytes: ... # NOTE: `tostring()` is deprecated and therefore excluded # def tostring(self, order=...): ... @@ -1248,14 +1237,6 @@ class _ArrayOrScalarCommon: ) -> None: ... # generics and 0d arrays return builtin scalars def tolist(self) -> Any: ... - @overload - def view(self, type: Type[_NdArraySubClass]) -> _NdArraySubClass: ... - @overload - def view(self: _ArraySelf, dtype: DTypeLike = ...) -> _ArraySelf: ... - @overload - def view( - self, dtype: DTypeLike, type: Type[_NdArraySubClass] - ) -> _NdArraySubClass: ... # TODO: Add proper signatures def __getitem__(self, key) -> Any: ... @@ -1637,6 +1618,12 @@ _T_co = TypeVar("_T_co", covariant=True) _2Tuple = Tuple[_T, _T] _Casting = L["no", "equiv", "safe", "same_kind", "unsafe"] +_DTypeLike = Union[ + dtype[_ScalarType], + Type[_ScalarType], + _SupportsDType[dtype[_ScalarType]], +] + _ArrayUInt_co = NDArray[Union[bool_, unsignedinteger[Any]]] _ArrayInt_co = NDArray[Union[bool_, integer[Any]]] _ArrayFloat_co = NDArray[Union[bool_, integer[Any], floating[Any]]] @@ -1874,6 +1861,53 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): self, *shape: SupportsIndex, order: _OrderACF = ... ) -> ndarray[Any, _DType_co]: ... + @overload + def astype( + self, + dtype: _DTypeLike[_ScalarType], + order: _OrderKACF = ..., + casting: _Casting = ..., + subok: bool = ..., + copy: bool = ..., + ) -> NDArray[_ScalarType]: ... + @overload + def astype( + self, + dtype: DTypeLike, + order: _OrderKACF = ..., + casting: _Casting = ..., + subok: bool = ..., + copy: bool = ..., + ) -> NDArray[Any]: ... + + @overload + def view(self: _ArraySelf) -> _ArraySelf: ... + @overload + def view(self, type: Type[_NdArraySubClass]) -> _NdArraySubClass: ... + @overload + def view(self, dtype: _DTypeLike[_ScalarType]) -> NDArray[_ScalarType]: ... + @overload + def view(self, dtype: DTypeLike) -> NDArray[Any]: ... + @overload + def view( + self, + dtype: DTypeLike, + type: Type[_NdArraySubClass], + ) -> _NdArraySubClass: ... + + @overload + def getfield( + self, + dtype: _DTypeLike[_ScalarType], + offset: SupportsIndex = ... + ) -> NDArray[_ScalarType]: ... + @overload + def getfield( + self, + dtype: DTypeLike, + offset: SupportsIndex = ... + ) -> NDArray[Any]: ... + # Dispatch to the underlying `generic` via protocols def __int__( self: ndarray[Any, dtype[SupportsInt]], # type: ignore[type-var] @@ -2846,6 +2880,59 @@ class generic(_ArrayOrScalarCommon): def byteswap(self: _ScalarType, inplace: L[False] = ...) -> _ScalarType: ... @property def flat(self: _ScalarType) -> flatiter[ndarray[Any, dtype[_ScalarType]]]: ... + + @overload + def astype( + self, + dtype: _DTypeLike[_ScalarType], + order: _OrderKACF = ..., + casting: _Casting = ..., + subok: bool = ..., + copy: bool = ..., + ) -> _ScalarType: ... + @overload + def astype( + self, + dtype: DTypeLike, + order: _OrderKACF = ..., + casting: _Casting = ..., + subok: bool = ..., + copy: bool = ..., + ) -> Any: ... + + # NOTE: `view` will perform a 0D->scalar cast, + # thus the array `type` is irrelevant to the output type + @overload + def view( + self: _ScalarType, + type: Type[ndarray[Any, Any]] = ..., + ) -> _ScalarType: ... + @overload + def view( + self, + dtype: _DTypeLike[_ScalarType], + type: Type[ndarray[Any, Any]] = ..., + ) -> _ScalarType: ... + @overload + def view( + self, + dtype: DTypeLike, + type: Type[ndarray[Any, Any]] = ..., + ) -> Any: ... + + @overload + def getfield( + self, + dtype: _DTypeLike[_ScalarType], + offset: SupportsIndex = ... + ) -> _ScalarType: ... + @overload + def getfield( + self, + dtype: DTypeLike, + offset: SupportsIndex = ... + ) -> Any: ... + def item( self, __args: Union[L[0], Tuple[()], Tuple[L[0]]] = ..., @@ -3042,11 +3129,24 @@ class datetime64(generic): if sys.version_info >= (3, 8): _IntValue = Union[SupportsInt, _CharLike_co, SupportsIndex] _FloatValue = Union[None, _CharLike_co, SupportsFloat, SupportsIndex] - _ComplexValue = Union[None, _CharLike_co, SupportsFloat, SupportsComplex, SupportsIndex] + _ComplexValue = Union[ + None, + _CharLike_co, + SupportsFloat, + SupportsComplex, + SupportsIndex, + complex, # `complex` is not a subtype of `SupportsComplex` + ] else: _IntValue = Union[SupportsInt, _CharLike_co] _FloatValue = Union[None, _CharLike_co, SupportsFloat] - _ComplexValue = Union[None, _CharLike_co, SupportsFloat, SupportsComplex] + _ComplexValue = Union[ + None, + _CharLike_co, + SupportsFloat, + SupportsComplex, + complex, + ] class integer(number[_NBit1]): # type: ignore # NOTE: `__index__` is technically defined in the bottom-most diff --git a/numpy/core/include/numpy/ndarraytypes.h b/numpy/core/include/numpy/ndarraytypes.h index d1acfdf26..3ea66b049 100644 --- a/numpy/core/include/numpy/ndarraytypes.h +++ b/numpy/core/include/numpy/ndarraytypes.h @@ -1236,6 +1236,8 @@ struct PyArrayIterObject_tag { _PyAIT(it)->dataptr = PyArray_BYTES(_PyAIT(it)->ao); \ for (__npy_i = 0; __npy_i<=_PyAIT(it)->nd_m1; \ __npy_i++) { \ + _PyAIT(it)->coordinates[__npy_i] = \ + (__npy_ind / _PyAIT(it)->factors[__npy_i]); \ _PyAIT(it)->dataptr += \ (__npy_ind / _PyAIT(it)->factors[__npy_i]) \ * _PyAIT(it)->strides[__npy_i]; \ diff --git a/numpy/core/overrides.py b/numpy/core/overrides.py index c2b5fb7fa..70085d896 100644 --- a/numpy/core/overrides.py +++ b/numpy/core/overrides.py @@ -18,11 +18,7 @@ array_function_like_doc = ( NumPy arrays. If an array-like passed in as ``like`` supports the ``__array_function__`` protocol, the result will be defined by it. In this case, it ensures the creation of an array object - compatible with that passed in via this argument. - - .. note:: - The ``like`` keyword is an experimental feature pending on - acceptance of :ref:`NEP 35 <NEP35>`.""" + compatible with that passed in via this argument.""" ) def set_array_function_like_doc(public_api): diff --git a/numpy/core/src/multiarray/_multiarray_tests.c.src b/numpy/core/src/multiarray/_multiarray_tests.c.src index bfdeae079..79140bdb7 100644 --- a/numpy/core/src/multiarray/_multiarray_tests.c.src +++ b/numpy/core/src/multiarray/_multiarray_tests.c.src @@ -87,7 +87,7 @@ static int copy_@name@(PyArrayIterObject *itx, PyArrayNeighborhoodIterObject *ni * For each point in itx, copy the current neighborhood into an array which * is appended at the output list */ - for (i = 0; i < itx->size; ++i) { + for (i = itx->index; i < itx->size; ++i) { PyArrayNeighborhoodIter_Reset(niterx); for (j = 0; j < PyArray_NDIM(itx->ao); ++j) { @@ -130,7 +130,7 @@ static int copy_object(PyArrayIterObject *itx, PyArrayNeighborhoodIterObject *ni * For each point in itx, copy the current neighborhood into an array which * is appended at the output list */ - for (i = 0; i < itx->size; ++i) { + for (i = itx->index; i < itx->size; ++i) { PyArrayNeighborhoodIter_Reset(niterx); for (j = 0; j < PyArray_NDIM(itx->ao); ++j) { @@ -161,10 +161,11 @@ test_neighborhood_iterator(PyObject* NPY_UNUSED(self), PyObject* args) PyArrayObject *ax, *afill; PyArrayIterObject *itx; int i, typenum, mode, st; + Py_ssize_t idxstart = 0; npy_intp bounds[NPY_MAXDIMS*2]; PyArrayNeighborhoodIterObject *niterx; - if (!PyArg_ParseTuple(args, "OOOi", &x, &b, &fill, &mode)) { + if (!PyArg_ParseTuple(args, "OOOi|n", &x, &b, &fill, &mode, &idxstart)) { return NULL; } @@ -224,12 +225,20 @@ test_neighborhood_iterator(PyObject* NPY_UNUSED(self), PyObject* args) } } + if (idxstart >= itx->size) { + PyErr_SetString(PyExc_ValueError, + "start index not compatible with x input"); + goto clean_itx; + } + niterx = (PyArrayNeighborhoodIterObject*)PyArray_NeighborhoodIterNew( (PyArrayIterObject*)itx, bounds, mode, afill); if (niterx == NULL) { goto clean_afill; } + PyArray_ITER_GOTO1D((PyArrayIterObject*)itx, idxstart); + switch (typenum) { case NPY_OBJECT: st = copy_object(itx, niterx, bounds, &out); diff --git a/numpy/core/src/multiarray/array_method.c b/numpy/core/src/multiarray/array_method.c index e13da12de..3ecc20d1d 100644 --- a/numpy/core/src/multiarray/array_method.c +++ b/numpy/core/src/multiarray/array_method.c @@ -210,10 +210,12 @@ validate_spec(PyArrayMethod_Spec *spec) case NPY_UNSAFE_CASTING: break; default: - PyErr_Format(PyExc_TypeError, - "ArrayMethod has invalid casting `%d`. (method: %s)", - spec->casting, spec->name); - return -1; + if (spec->casting != -1) { + PyErr_Format(PyExc_TypeError, + "ArrayMethod has invalid casting `%d`. (method: %s)", + spec->casting, spec->name); + return -1; + } } for (int i = 0; i < nargs; i++) { @@ -301,6 +303,13 @@ fill_arraymethod_from_slots( /* Check whether the slots are valid: */ if (meth->resolve_descriptors == &default_resolve_descriptors) { + if (spec->casting == -1) { + PyErr_Format(PyExc_TypeError, + "Cannot set casting to -1 (invalid) when not providing " + "the default `resolve_descriptors` function. " + "(method: %s)", spec->name); + return -1; + } for (int i = 0; i < meth->nin + meth->nout; i++) { if (res->dtypes[i] == NULL) { if (i < meth->nin) { @@ -573,6 +582,8 @@ boundarraymethod__resolve_descripors( /* * The casting flags should be the most generic casting level (except the * cast-is-view flag. If no input is parametric, it must match exactly. + * + * (Note that these checks are only debugging checks.) */ int parametric = 0; for (int i = 0; i < nin + nout; i++) { @@ -581,34 +592,34 @@ boundarraymethod__resolve_descripors( break; } } - if (!parametric) { - /* - * Non-parametric can only mismatch if it switches from no to equiv - * (e.g. due to byteorder changes). - */ - if (self->method->casting != (casting & ~_NPY_CAST_IS_VIEW) && - !(self->method->casting == NPY_NO_CASTING && - casting == NPY_EQUIV_CASTING)) { - PyErr_Format(PyExc_RuntimeError, - "resolve_descriptors cast level did not match stored one " - "(expected %d, got %d) for method %s", - self->method->casting, (casting & ~_NPY_CAST_IS_VIEW), - self->method->name); - Py_DECREF(result_tuple); - return NULL; - } - } - else { + if (self->method->casting != -1) { NPY_CASTING cast = casting & ~_NPY_CAST_IS_VIEW; - if (cast != PyArray_MinCastSafety(cast, self->method->casting)) { + if (self->method->casting != + PyArray_MinCastSafety(cast, self->method->casting)) { PyErr_Format(PyExc_RuntimeError, - "resolve_descriptors cast level did not match stored one " - "(expected %d, got %d) for method %s", - self->method->casting, (casting & ~_NPY_CAST_IS_VIEW), - self->method->name); + "resolve_descriptors cast level did not match stored one. " + "(set level is %d, got %d for method %s)", + self->method->casting, cast, self->method->name); Py_DECREF(result_tuple); return NULL; } + if (!parametric) { + /* + * Non-parametric can only mismatch if it switches from equiv to no + * (e.g. due to byteorder changes). + */ + if (cast != self->method->casting && + self->method->casting != NPY_EQUIV_CASTING) { + PyErr_Format(PyExc_RuntimeError, + "resolve_descriptors cast level changed even though " + "the cast is non-parametric where the only possible " + "change should be from equivalent to no casting. " + "(set level is %d, got %d for method %s)", + self->method->casting, cast, self->method->name); + Py_DECREF(result_tuple); + return NULL; + } + } } return Py_BuildValue("iN", casting, result_tuple); diff --git a/numpy/core/src/multiarray/convert_datatype.c b/numpy/core/src/multiarray/convert_datatype.c index 01ee56d16..1a962ef78 100644 --- a/numpy/core/src/multiarray/convert_datatype.c +++ b/numpy/core/src/multiarray/convert_datatype.c @@ -358,6 +358,45 @@ PyArray_CastAnyTo(PyArrayObject *out, PyArrayObject *mp) } +static NPY_CASTING +_get_cast_safety_from_castingimpl(PyArrayMethodObject *castingimpl, + PyArray_DTypeMeta *dtypes[2], PyArray_Descr *from, PyArray_Descr *to) +{ + PyArray_Descr *descrs[2] = {from, to}; + PyArray_Descr *out_descrs[2]; + + NPY_CASTING casting = castingimpl->resolve_descriptors( + castingimpl, dtypes, descrs, out_descrs); + if (casting < 0) { + return -1; + } + /* The returned descriptors may not match, requiring a second check */ + if (out_descrs[0] != descrs[0]) { + NPY_CASTING from_casting = PyArray_GetCastSafety( + descrs[0], out_descrs[0], NULL); + casting = PyArray_MinCastSafety(casting, from_casting); + if (casting < 0) { + goto finish; + } + } + if (descrs[1] != NULL && out_descrs[1] != descrs[1]) { + NPY_CASTING from_casting = PyArray_GetCastSafety( + descrs[1], out_descrs[1], NULL); + casting = PyArray_MinCastSafety(casting, from_casting); + if (casting < 0) { + goto finish; + } + } + + finish: + Py_DECREF(out_descrs[0]); + Py_DECREF(out_descrs[1]); + /* NPY_NO_CASTING has to be used for (NPY_EQUIV_CASTING|_NPY_CAST_IS_VIEW) */ + assert(casting != (NPY_EQUIV_CASTING|_NPY_CAST_IS_VIEW)); + return casting; +} + + /** * Given two dtype instances, find the correct casting safety. * @@ -375,7 +414,6 @@ NPY_NO_EXPORT NPY_CASTING PyArray_GetCastSafety( PyArray_Descr *from, PyArray_Descr *to, PyArray_DTypeMeta *to_dtype) { - NPY_CASTING casting; if (to != NULL) { to_dtype = NPY_DTYPE(to); } @@ -389,41 +427,67 @@ PyArray_GetCastSafety( } PyArrayMethodObject *castingimpl = (PyArrayMethodObject *)meth; - PyArray_DTypeMeta *dtypes[2] = {NPY_DTYPE(from), to_dtype}; - PyArray_Descr *descrs[2] = {from, to}; - PyArray_Descr *out_descrs[2]; - - casting = castingimpl->resolve_descriptors( - castingimpl, dtypes, descrs, out_descrs); + NPY_CASTING casting = _get_cast_safety_from_castingimpl(castingimpl, + dtypes, from, to); Py_DECREF(meth); - if (casting < 0) { + + return casting; +} + + +/** + * Check whether a cast is safe, see also `PyArray_GetCastSafety` for + * a similiar function. Unlike GetCastSafety, this function checks the + * `castingimpl->casting` when available. This allows for two things: + * + * 1. It avoids calling `resolve_descriptors` in some cases. + * 2. Strings need to discover the length, but in some cases we know that the + * cast is valid (assuming the string length is discovered first). + * + * The latter means that a `can_cast` could return True, but the cast fail + * because the parametric type cannot guess the correct output descriptor. + * (I.e. if `object_arr.astype("S")` did _not_ inspect the objects, and the + * user would have to guess the string length.) + * + * @param casting the requested casting safety. + * @param from + * @param to The descriptor to cast to (may be NULL) + * @param to_dtype If `to` is NULL, must pass the to_dtype (otherwise this + * is ignored). + * @return 0 for an invalid cast, 1 for a valid and -1 for an error. + */ +static int +PyArray_CheckCastSafety(NPY_CASTING casting, + PyArray_Descr *from, PyArray_Descr *to, PyArray_DTypeMeta *to_dtype) +{ + if (to != NULL) { + to_dtype = NPY_DTYPE(to); + } + PyObject *meth = PyArray_GetCastingImpl(NPY_DTYPE(from), to_dtype); + if (meth == NULL) { return -1; } - /* The returned descriptors may not match, requiring a second check */ - if (out_descrs[0] != descrs[0]) { - NPY_CASTING from_casting = PyArray_GetCastSafety( - descrs[0], out_descrs[0], NULL); - casting = PyArray_MinCastSafety(casting, from_casting); - if (casting < 0) { - goto finish; - } + if (meth == Py_None) { + Py_DECREF(Py_None); + return -1; } - if (descrs[1] != NULL && out_descrs[1] != descrs[1]) { - NPY_CASTING from_casting = PyArray_GetCastSafety( - descrs[1], out_descrs[1], NULL); - casting = PyArray_MinCastSafety(casting, from_casting); - if (casting < 0) { - goto finish; - } + PyArrayMethodObject *castingimpl = (PyArrayMethodObject *)meth; + + if (PyArray_MinCastSafety(castingimpl->casting, casting) == casting) { + /* No need to check using `castingimpl.resolve_descriptors()` */ + return 1; } - finish: - Py_DECREF(out_descrs[0]); - Py_DECREF(out_descrs[1]); - /* NPY_NO_CASTING has to be used for (NPY_EQUIV_CASTING|_NPY_CAST_IS_VIEW) */ - assert(casting != (NPY_EQUIV_CASTING|_NPY_CAST_IS_VIEW)); - return casting; + PyArray_DTypeMeta *dtypes[2] = {NPY_DTYPE(from), to_dtype}; + NPY_CASTING safety = _get_cast_safety_from_castingimpl(castingimpl, + dtypes, from, to); + Py_DECREF(meth); + /* If casting is the smaller (or equal) safety we match */ + if (safety < 0) { + return -1; + } + return PyArray_MinCastSafety(safety, casting) == casting; } @@ -565,6 +629,8 @@ NPY_NO_EXPORT npy_bool PyArray_CanCastTypeTo(PyArray_Descr *from, PyArray_Descr *to, NPY_CASTING casting) { + PyArray_DTypeMeta *to_dtype = NPY_DTYPE(to); + /* * NOTE: This code supports U and S, this is identical to the code * in `ctors.c` which does not allow these dtypes to be attached @@ -576,21 +642,21 @@ PyArray_CanCastTypeTo(PyArray_Descr *from, PyArray_Descr *to, * TODO: We should grow support for `np.can_cast("d", "S")` being * different from `np.can_cast("d", "S0")` here, at least for * the python side API. + * The `to = NULL` branch, which considers "S0" to be "flexible" + * should probably be deprecated. + * (This logic is duplicated in `PyArray_CanCastArrayTo`) */ - NPY_CASTING safety; if (PyDataType_ISUNSIZED(to) && to->subarray == NULL) { - safety = PyArray_GetCastSafety(from, NULL, NPY_DTYPE(to)); - } - else { - safety = PyArray_GetCastSafety(from, to, NPY_DTYPE(to)); + to = NULL; /* consider mainly S0 and U0 as S and U */ } - if (safety < 0) { + int is_valid = PyArray_CheckCastSafety(casting, from, to, to_dtype); + /* Clear any errors and consider this unsafe (should likely be changed) */ + if (is_valid < 0) { PyErr_Clear(); return 0; } - /* If casting is the smaller (or equal) safety we match */ - return PyArray_MinCastSafety(safety, casting) == casting; + return is_valid; } @@ -610,28 +676,22 @@ can_cast_scalar_to(PyArray_Descr *scal_type, char *scal_data, /* * If the two dtypes are actually references to the same object * or if casting type is forced unsafe then always OK. + * + * TODO: Assuming that unsafe casting always works is not actually correct */ if (scal_type == to || casting == NPY_UNSAFE_CASTING ) { return 1; } - /* NOTE: This is roughly the same code as `PyArray_CanCastTypeTo`: */ - NPY_CASTING safety; - if (PyDataType_ISUNSIZED(to) && to->subarray == NULL) { - safety = PyArray_GetCastSafety(scal_type, NULL, NPY_DTYPE(to)); - } - else { - safety = PyArray_GetCastSafety(scal_type, to, NPY_DTYPE(to)); - } - if (safety < 0) { - PyErr_Clear(); - return 0; - } - safety = PyArray_MinCastSafety(safety, casting); - if (safety == casting) { + int valid = PyArray_CheckCastSafety(casting, scal_type, to, NPY_DTYPE(to)); + if (valid == 1) { /* This is definitely a valid cast. */ return 1; } + if (valid < 0) { + /* Probably must return 0, but just keep trying for now. */ + PyErr_Clear(); + } /* * If the scalar isn't a number, value-based casting cannot kick in and @@ -692,14 +752,29 @@ PyArray_CanCastArrayTo(PyArrayObject *arr, PyArray_Descr *to, NPY_CASTING casting) { PyArray_Descr *from = PyArray_DESCR(arr); + PyArray_DTypeMeta *to_dtype = NPY_DTYPE(to); - /* If it's a scalar, check the value */ - if (PyArray_NDIM(arr) == 0 && !PyArray_HASFIELDS(arr)) { + /* NOTE, TODO: The same logic as `PyArray_CanCastTypeTo`: */ + if (PyDataType_ISUNSIZED(to) && to->subarray == NULL) { + to = NULL; + } + + /* + * If it's a scalar, check the value. (This only currently matters for + * numeric types and for `to == NULL` it can't be numeric.) + */ + if (PyArray_NDIM(arr) == 0 && !PyArray_HASFIELDS(arr) && to != NULL) { return can_cast_scalar_to(from, PyArray_DATA(arr), to, casting); } - /* Otherwise, use the standard rules */ - return PyArray_CanCastTypeTo(from, to, casting); + /* Otherwise, use the standard rules (same as `PyArray_CanCastTypeTo`) */ + int is_valid = PyArray_CheckCastSafety(casting, from, to, to_dtype); + /* Clear any errors and consider this unsafe (should likely be changed) */ + if (is_valid < 0) { + PyErr_Clear(); + return 0; + } + return is_valid; } @@ -2122,13 +2197,6 @@ PyArray_AddCastingImplementation(PyBoundArrayMethodObject *meth) meth->method->name); return -1; } - if ((meth->method->casting & ~_NPY_CAST_IS_VIEW) != NPY_NO_CASTING) { - PyErr_Format(PyExc_TypeError, - "A cast where input and output DType (class) are identical " - "must signal `no-casting`. (method: %s)", - meth->method->name); - return -1; - } if (meth->dtypes[0]->within_dtype_castingimpl != NULL) { PyErr_Format(PyExc_RuntimeError, "A cast was already added for %S -> %S. (method: %s)", @@ -2400,7 +2468,7 @@ add_numeric_cast(PyArray_DTypeMeta *from, PyArray_DTypeMeta *to) /* Find the correct casting level, and special case no-cast */ if (dtypes[0]->kind == dtypes[1]->kind && from_itemsize == to_itemsize) { - spec.casting = NPY_NO_CASTING; + spec.casting = NPY_EQUIV_CASTING; /* When there is no casting (equivalent C-types) use byteswap loops */ slots[0].slot = NPY_METH_resolve_descriptors; @@ -2558,7 +2626,6 @@ cast_to_string_resolve_descriptors( dtypes[1]->type_num == NPY_STRING); return NPY_UNSAFE_CASTING; } - assert(self->casting == NPY_SAFE_CASTING); if (loop_descrs[1]->elsize >= size) { return NPY_SAFE_CASTING; @@ -2600,9 +2667,9 @@ add_other_to_and_from_string_cast( .dtypes = dtypes, .slots = slots, }; - /* Almost everything can be safely cast to string (except unicode) */ + /* Almost everything can be same-kind cast to string (except unicode) */ if (other->type_num != NPY_UNICODE) { - spec.casting = NPY_SAFE_CASTING; + spec.casting = NPY_SAME_KIND_CASTING; /* same-kind if too short */ } else { spec.casting = NPY_UNSAFE_CASTING; @@ -2722,7 +2789,7 @@ PyArray_InitializeStringCasts(void) {0, NULL}}; PyArrayMethod_Spec spec = { .name = "string_to_string_cast", - .casting = NPY_NO_CASTING, + .casting = NPY_UNSAFE_CASTING, .nin = 1, .nout = 1, .flags = (NPY_METH_REQUIRES_PYAPI | @@ -2935,7 +3002,7 @@ PyArray_GetGenericToVoidCastingImpl(void) method->name = "any_to_void_cast"; method->flags = NPY_METH_SUPPORTS_UNALIGNED | NPY_METH_REQUIRES_PYAPI; - method->casting = NPY_SAFE_CASTING; + method->casting = -1; method->resolve_descriptors = &nonstructured_to_structured_resolve_descriptors; method->get_strided_loop = &nonstructured_to_structured_get_loop; @@ -3074,7 +3141,7 @@ PyArray_GetVoidToGenericCastingImpl(void) method->name = "void_to_any_cast"; method->flags = NPY_METH_SUPPORTS_UNALIGNED | NPY_METH_REQUIRES_PYAPI; - method->casting = NPY_UNSAFE_CASTING; + method->casting = -1; method->resolve_descriptors = &structured_to_nonstructured_resolve_descriptors; method->get_strided_loop = &structured_to_nonstructured_get_loop; @@ -3306,7 +3373,7 @@ PyArray_InitializeVoidToVoidCast(void) {0, NULL}}; PyArrayMethod_Spec spec = { .name = "void_to_void_cast", - .casting = NPY_NO_CASTING, + .casting = -1, /* may not cast at all */ .nin = 1, .nout = 1, .flags = NPY_METH_REQUIRES_PYAPI | NPY_METH_SUPPORTS_UNALIGNED, diff --git a/numpy/core/src/multiarray/datetime.c b/numpy/core/src/multiarray/datetime.c index fdf4c0839..b9d81e836 100644 --- a/numpy/core/src/multiarray/datetime.c +++ b/numpy/core/src/multiarray/datetime.c @@ -950,10 +950,6 @@ convert_datetime_divisor_to_multiple(PyArray_DatetimeMetaData *meta, return -1; } - ind = ((int)meta->base - (int)NPY_FR_Y)*2; - totry = _multiples_table[ind]; - baseunit = _multiples_table[ind + 1]; - num = 3; if (meta->base == NPY_FR_W) { num = 4; @@ -962,6 +958,7 @@ convert_datetime_divisor_to_multiple(PyArray_DatetimeMetaData *meta, num = 2; } if (meta->base >= NPY_FR_s) { + /* _multiplies_table only has entries up to NPY_FR_s */ ind = ((int)NPY_FR_s - (int)NPY_FR_Y)*2; totry = _multiples_table[ind]; baseunit = _multiples_table[ind + 1]; @@ -974,6 +971,11 @@ convert_datetime_divisor_to_multiple(PyArray_DatetimeMetaData *meta, num = 0; } } + else { + ind = ((int)meta->base - (int)NPY_FR_Y)*2; + totry = _multiples_table[ind]; + baseunit = _multiples_table[ind + 1]; + } for (i = 0; i < num; i++) { q = totry[i] / den; @@ -3952,7 +3954,6 @@ time_to_string_resolve_descriptors( return -1; } - assert(self->casting == NPY_UNSAFE_CASTING); return NPY_UNSAFE_CASTING; } @@ -4059,7 +4060,7 @@ PyArray_InitializeDatetimeCasts() .name = "datetime_casts", .nin = 1, .nout = 1, - .casting = NPY_NO_CASTING, + .casting = NPY_UNSAFE_CASTING, .flags = NPY_METH_SUPPORTS_UNALIGNED, .slots = slots, .dtypes = dtypes, diff --git a/numpy/core/src/multiarray/dtypemeta.c b/numpy/core/src/multiarray/dtypemeta.c index 40ca9ee2a..4ee721964 100644 --- a/numpy/core/src/multiarray/dtypemeta.c +++ b/numpy/core/src/multiarray/dtypemeta.c @@ -415,19 +415,6 @@ string_unicode_common_dtype(PyArray_DTypeMeta *cls, PyArray_DTypeMeta *other) Py_INCREF(Py_NotImplemented); return (PyArray_DTypeMeta *)Py_NotImplemented; } - if (other->type_num != NPY_STRING && other->type_num != NPY_UNICODE) { - /* Deprecated 2020-12-19, NumPy 1.21. */ - if (DEPRECATE_FUTUREWARNING( - "Promotion of numbers and bools to strings is deprecated. " - "In the future, code such as `np.concatenate((['string'], [0]))` " - "will raise an error, while `np.asarray(['string', 0])` will " - "return an array with `dtype=object`. To avoid the warning " - "while retaining a string result use `dtype='U'` (or 'S'). " - "To get an array of Python objects use `dtype=object`. " - "(Warning added in NumPy 1.21)") < 0) { - return NULL; - } - } /* * The builtin types are ordered by complexity (aside from object) here. * Arguably, we should not consider numbers and strings "common", but diff --git a/numpy/core/tests/test_api.py b/numpy/core/tests/test_api.py index 9e99e0bc3..291cdae89 100644 --- a/numpy/core/tests/test_api.py +++ b/numpy/core/tests/test_api.py @@ -281,6 +281,19 @@ def test_array_astype(): a = np.array(1000, dtype='i4') assert_raises(TypeError, a.astype, 'U1', casting='safe') +@pytest.mark.parametrize("dt", ["S", "U"]) +def test_array_astype_to_string_discovery_empty(dt): + # See also gh-19085 + arr = np.array([""], dtype=object) + # Note, the itemsize is the `0 -> 1` logic, which should change. + # The important part the test is rather that it does not error. + assert arr.astype(dt).dtype.itemsize == np.dtype(f"{dt}1").itemsize + + # check the same thing for `np.can_cast` (since it accepts arrays) + assert np.can_cast(arr, dt, casting="unsafe") + assert not np.can_cast(arr, dt, casting="same_kind") + # as well as for the object as a descriptor: + assert np.can_cast("O", dt, casting="unsafe") @pytest.mark.parametrize("dt", ["d", "f", "S13", "U32"]) def test_array_astype_to_void(dt): diff --git a/numpy/core/tests/test_deprecations.py b/numpy/core/tests/test_deprecations.py index ffe0147b2..42e632e4a 100644 --- a/numpy/core/tests/test_deprecations.py +++ b/numpy/core/tests/test_deprecations.py @@ -1105,41 +1105,6 @@ class TestNoseDecoratorsDeprecated(_DeprecationTestCase): self.assert_deprecated(_test_parametrize) -class TestStringPromotion(_DeprecationTestCase): - # Deprecated 2020-12-19, NumPy 1.21 - warning_cls = FutureWarning - message = "Promotion of numbers and bools to strings is deprecated." - - @pytest.mark.parametrize("dtype", "?bhilqpBHILQPefdgFDG") - @pytest.mark.parametrize("string_dt", ["S", "U"]) - def test_deprecated(self, dtype, string_dt): - self.assert_deprecated(lambda: np.promote_types(dtype, string_dt)) - - # concatenate has to be able to promote to find the result dtype: - arr1 = np.ones(3, dtype=dtype) - arr2 = np.ones(3, dtype=string_dt) - self.assert_deprecated(lambda: np.concatenate((arr1, arr2), axis=0)) - self.assert_deprecated(lambda: np.concatenate((arr1, arr2), axis=None)) - - self.assert_deprecated(lambda: np.array([arr1[0], arr2[0]])) - - @pytest.mark.parametrize("dtype", "?bhilqpBHILQPefdgFDG") - @pytest.mark.parametrize("string_dt", ["S", "U"]) - def test_not_deprecated(self, dtype, string_dt): - # The ufunc type resolvers run into this, but giving a futurewarning - # here is unnecessary (it ends up as an error anyway), so test that - # no warning is given: - arr1 = np.ones(3, dtype=dtype) - arr2 = np.ones(3, dtype=string_dt) - - # Adding two arrays uses result_type normally, which would fail: - with pytest.raises(TypeError): - self.assert_not_deprecated(lambda: arr1 + arr2) - # np.equal uses a different type resolver: - with pytest.raises(TypeError): - self.assert_not_deprecated(lambda: np.equal(arr1, arr2)) - - class TestSingleElementSignature(_DeprecationTestCase): # Deprecated 2021-04-01, NumPy 1.21 message = r"The use of a length 1" diff --git a/numpy/core/tests/test_half.py b/numpy/core/tests/test_half.py index 449a01d21..1b6fd21e1 100644 --- a/numpy/core/tests/test_half.py +++ b/numpy/core/tests/test_half.py @@ -71,10 +71,8 @@ class TestHalf: def test_half_conversion_to_string(self, string_dt): # Currently uses S/U32 (which is sufficient for float32) expected_dt = np.dtype(f"{string_dt}32") - with pytest.warns(FutureWarning): - assert np.promote_types(np.float16, string_dt) == expected_dt - with pytest.warns(FutureWarning): - assert np.promote_types(string_dt, np.float16) == expected_dt + assert np.promote_types(np.float16, string_dt) == expected_dt + assert np.promote_types(string_dt, np.float16) == expected_dt arr = np.ones(3, dtype=np.float16).astype(string_dt) assert arr.dtype == expected_dt diff --git a/numpy/core/tests/test_multiarray.py b/numpy/core/tests/test_multiarray.py index d567653f5..25dd76256 100644 --- a/numpy/core/tests/test_multiarray.py +++ b/numpy/core/tests/test_multiarray.py @@ -6947,6 +6947,13 @@ class TestNeighborhoodIter: x, [-1, 0, -1, 1], 4, NEIGH_MODE['constant']) assert_array_equal(l, r) + # Test with start in the middle + r = [np.array([[4, 0, 1], [4, 2, 3]], dtype=dt), + np.array([[0, 1, 4], [2, 3, 4]], dtype=dt)] + l = _multiarray_tests.test_neighborhood_iterator( + x, [-1, 0, -1, 1], 4, NEIGH_MODE['constant'], 2) + assert_array_equal(l, r) + def test_mirror2d(self, dt): x = np.array([[0, 1], [2, 3]], dtype=dt) r = [np.array([[0, 0, 1], [0, 0, 1]], dtype=dt), diff --git a/numpy/core/tests/test_numeric.py b/numpy/core/tests/test_numeric.py index aba90ece5..f5113150e 100644 --- a/numpy/core/tests/test_numeric.py +++ b/numpy/core/tests/test_numeric.py @@ -848,12 +848,10 @@ class TestTypes: assert_equal(np.promote_types('<i8', '<i8'), np.dtype('i8')) assert_equal(np.promote_types('>i8', '>i8'), np.dtype('i8')) - with pytest.warns(FutureWarning, - match="Promotion of numbers and bools to strings"): - assert_equal(np.promote_types('>i8', '>U16'), np.dtype('U21')) - assert_equal(np.promote_types('<i8', '<U16'), np.dtype('U21')) - assert_equal(np.promote_types('>U16', '>i8'), np.dtype('U21')) - assert_equal(np.promote_types('<U16', '<i8'), np.dtype('U21')) + assert_equal(np.promote_types('>i8', '>U16'), np.dtype('U21')) + assert_equal(np.promote_types('<i8', '<U16'), np.dtype('U21')) + assert_equal(np.promote_types('>U16', '>i8'), np.dtype('U21')) + assert_equal(np.promote_types('<U16', '<i8'), np.dtype('U21')) assert_equal(np.promote_types('<S5', '<U8'), np.dtype('U8')) assert_equal(np.promote_types('>S5', '>U8'), np.dtype('U8')) @@ -901,37 +899,32 @@ class TestTypes: S = string_dtype - with pytest.warns(FutureWarning, - match="Promotion of numbers and bools to strings") as record: - # Promote numeric with unsized string: - assert_equal(promote_types('bool', S), np.dtype(S+'5')) - assert_equal(promote_types('b', S), np.dtype(S+'4')) - assert_equal(promote_types('u1', S), np.dtype(S+'3')) - assert_equal(promote_types('u2', S), np.dtype(S+'5')) - assert_equal(promote_types('u4', S), np.dtype(S+'10')) - assert_equal(promote_types('u8', S), np.dtype(S+'20')) - assert_equal(promote_types('i1', S), np.dtype(S+'4')) - assert_equal(promote_types('i2', S), np.dtype(S+'6')) - assert_equal(promote_types('i4', S), np.dtype(S+'11')) - assert_equal(promote_types('i8', S), np.dtype(S+'21')) - # Promote numeric with sized string: - assert_equal(promote_types('bool', S+'1'), np.dtype(S+'5')) - assert_equal(promote_types('bool', S+'30'), np.dtype(S+'30')) - assert_equal(promote_types('b', S+'1'), np.dtype(S+'4')) - assert_equal(promote_types('b', S+'30'), np.dtype(S+'30')) - assert_equal(promote_types('u1', S+'1'), np.dtype(S+'3')) - assert_equal(promote_types('u1', S+'30'), np.dtype(S+'30')) - assert_equal(promote_types('u2', S+'1'), np.dtype(S+'5')) - assert_equal(promote_types('u2', S+'30'), np.dtype(S+'30')) - assert_equal(promote_types('u4', S+'1'), np.dtype(S+'10')) - assert_equal(promote_types('u4', S+'30'), np.dtype(S+'30')) - assert_equal(promote_types('u8', S+'1'), np.dtype(S+'20')) - assert_equal(promote_types('u8', S+'30'), np.dtype(S+'30')) - # Promote with object: - assert_equal(promote_types('O', S+'30'), np.dtype('O')) - - assert len(record) == 22 # each string promotion gave one warning - + # Promote numeric with unsized string: + assert_equal(promote_types('bool', S), np.dtype(S+'5')) + assert_equal(promote_types('b', S), np.dtype(S+'4')) + assert_equal(promote_types('u1', S), np.dtype(S+'3')) + assert_equal(promote_types('u2', S), np.dtype(S+'5')) + assert_equal(promote_types('u4', S), np.dtype(S+'10')) + assert_equal(promote_types('u8', S), np.dtype(S+'20')) + assert_equal(promote_types('i1', S), np.dtype(S+'4')) + assert_equal(promote_types('i2', S), np.dtype(S+'6')) + assert_equal(promote_types('i4', S), np.dtype(S+'11')) + assert_equal(promote_types('i8', S), np.dtype(S+'21')) + # Promote numeric with sized string: + assert_equal(promote_types('bool', S+'1'), np.dtype(S+'5')) + assert_equal(promote_types('bool', S+'30'), np.dtype(S+'30')) + assert_equal(promote_types('b', S+'1'), np.dtype(S+'4')) + assert_equal(promote_types('b', S+'30'), np.dtype(S+'30')) + assert_equal(promote_types('u1', S+'1'), np.dtype(S+'3')) + assert_equal(promote_types('u1', S+'30'), np.dtype(S+'30')) + assert_equal(promote_types('u2', S+'1'), np.dtype(S+'5')) + assert_equal(promote_types('u2', S+'30'), np.dtype(S+'30')) + assert_equal(promote_types('u4', S+'1'), np.dtype(S+'10')) + assert_equal(promote_types('u4', S+'30'), np.dtype(S+'30')) + assert_equal(promote_types('u8', S+'1'), np.dtype(S+'20')) + assert_equal(promote_types('u8', S+'30'), np.dtype(S+'30')) + # Promote with object: + assert_equal(promote_types('O', S+'30'), np.dtype('O')) @pytest.mark.parametrize(["dtype1", "dtype2"], [[np.dtype("V6"), np.dtype("V10")], diff --git a/numpy/core/tests/test_regression.py b/numpy/core/tests/test_regression.py index dbfb75c9a..312d0683d 100644 --- a/numpy/core/tests/test_regression.py +++ b/numpy/core/tests/test_regression.py @@ -782,9 +782,7 @@ class TestRegression: # Ticket #514 s = "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa" t = [] - with pytest.warns(FutureWarning, - match="Promotion of numbers and bools to strings"): - np.hstack((t, s)) + np.hstack((t, s)) def test_arr_transpose(self): # Ticket #516 diff --git a/numpy/distutils/intelccompiler.py b/numpy/distutils/intelccompiler.py index 0388ad577..0fa1c11dd 100644 --- a/numpy/distutils/intelccompiler.py +++ b/numpy/distutils/intelccompiler.py @@ -58,7 +58,7 @@ class IntelEM64TCCompiler(UnixCCompiler): v = self.get_version() mpopt = 'openmp' if v and v < '15' else 'qopenmp' - self.cc_exe = ('icc -m64 -fPIC -fp-model strict -O3 ' + self.cc_exe = ('icc -std=c99 -m64 -fPIC -fp-model strict -O3 ' '-fomit-frame-pointer -{}').format(mpopt) compiler = self.cc_exe diff --git a/numpy/lib/_version.py b/numpy/lib/_version.py index 00e00e9a7..bfac5f814 100644 --- a/numpy/lib/_version.py +++ b/numpy/lib/_version.py @@ -15,7 +15,7 @@ class NumpyVersion(): """Parse and compare numpy version strings. NumPy has the following versioning scheme (numbers given are examples; they - can be > 9) in principle): + can be > 9 in principle): - Released version: '1.8.0', '1.8.1', etc. - Alpha: '1.8.0a1', '1.8.0a2', etc. @@ -54,7 +54,7 @@ class NumpyVersion(): def __init__(self, vstring): self.vstring = vstring - ver_main = re.match(r'\d\.\d+\.\d+', vstring) + ver_main = re.match(r'\d+\.\d+\.\d+', vstring) if not ver_main: raise ValueError("Not a valid numpy version string") diff --git a/numpy/lib/function_base.pyi b/numpy/lib/function_base.pyi index da24ab21d..69c615c9c 100644 --- a/numpy/lib/function_base.pyi +++ b/numpy/lib/function_base.pyi @@ -30,7 +30,7 @@ def gradient(f, *varargs, axis=..., edge_order=...): ... def diff(a, n=..., axis=..., prepend = ..., append = ...): ... def interp(x, xp, fp, left=..., right=..., period=...): ... def angle(z, deg=...): ... -def unwrap(p, discont = ..., axis=...): ... +def unwrap(p, discont = ..., axis=..., *, period=...): ... def sort_complex(a): ... def trim_zeros(filt, trim=...): ... def extract(condition, arr): ... diff --git a/numpy/lib/index_tricks.py b/numpy/lib/index_tricks.py index 72d8e9de4..5140ffa61 100644 --- a/numpy/lib/index_tricks.py +++ b/numpy/lib/index_tricks.py @@ -631,7 +631,8 @@ class ndindex: Examples -------- - # dimensions as individual arguments + Dimensions as individual arguments + >>> for index in np.ndindex(3, 2, 1): ... print(index) (0, 0, 0) @@ -641,7 +642,8 @@ class ndindex: (2, 0, 0) (2, 1, 0) - # same dimensions - but in a tuple (3, 2, 1) + Same dimensions - but in a tuple ``(3, 2, 1)`` + >>> for index in np.ndindex((3, 2, 1)): ... print(index) (0, 0, 0) diff --git a/numpy/lib/polynomial.py b/numpy/lib/polynomial.py index 56fcce621..23021cafa 100644 --- a/numpy/lib/polynomial.py +++ b/numpy/lib/polynomial.py @@ -489,8 +489,11 @@ def polyfit(x, y, deg, rcond=None, full=False, w=None, cov=False): default) just the coefficients are returned, when True diagnostic information from the singular value decomposition is also returned. w : array_like, shape (M,), optional - Weights to apply to the y-coordinates of the sample points. For - gaussian uncertainties, use 1/sigma (not 1/sigma**2). + Weights. If not None, the weight ``w[i]`` applies to the unsquared + residual ``y[i] - y_hat[i]`` at ``x[i]``. Ideally the weights are + chosen so that the errors of the products ``w[i]*y[i]`` all have the + same variance. When using inverse-variance weighting, use + ``w[i] = 1/sigma(y[i])``. The default value is None. cov : bool or str, optional If given and not `False`, return not just the estimate but also its covariance matrix. By default, the covariance are scaled by @@ -498,7 +501,7 @@ def polyfit(x, y, deg, rcond=None, full=False, w=None, cov=False): to be unreliable except in a relative sense and everything is scaled such that the reduced chi2 is unity. This scaling is omitted if ``cov='unscaled'``, as is relevant for the case that the weights are - 1/sigma**2, with sigma known to be a reliable estimate of the + w = 1/sigma, with sigma known to be a reliable estimate of the uncertainty. Returns diff --git a/numpy/lib/tests/test__version.py b/numpy/lib/tests/test__version.py index 182504631..e6d41ad93 100644 --- a/numpy/lib/tests/test__version.py +++ b/numpy/lib/tests/test__version.py @@ -7,7 +7,7 @@ from numpy.lib import NumpyVersion def test_main_versions(): assert_(NumpyVersion('1.8.0') == '1.8.0') - for ver in ['1.9.0', '2.0.0', '1.8.1']: + for ver in ['1.9.0', '2.0.0', '1.8.1', '10.0.1']: assert_(NumpyVersion('1.8.0') < ver) for ver in ['1.7.0', '1.7.1', '0.9.9']: diff --git a/numpy/lib/tests/test_regression.py b/numpy/lib/tests/test_regression.py index 94fac7ef0..373226277 100644 --- a/numpy/lib/tests/test_regression.py +++ b/numpy/lib/tests/test_regression.py @@ -64,8 +64,7 @@ class TestRegression: def test_mem_string_concat(self): # Ticket #469 x = np.array([]) - with pytest.warns(FutureWarning): - np.append(x, 'asdasd\tasdasd') + np.append(x, 'asdasd\tasdasd') def test_poly_div(self): # Ticket #553 diff --git a/numpy/polynomial/_polybase.py b/numpy/polynomial/_polybase.py index b04b8e66b..5525b232b 100644 --- a/numpy/polynomial/_polybase.py +++ b/numpy/polynomial/_polybase.py @@ -936,11 +936,11 @@ class ABCPolyBase(abc.ABC): diagnostic information from the singular value decomposition is also returned. w : array_like, shape (M,), optional - Weights. If not None the contribution of each point - ``(x[i],y[i])`` to the fit is weighted by ``w[i]``. Ideally the - weights are chosen so that the errors of the products - ``w[i]*y[i]`` all have the same variance. The default value is - None. + Weights. If not None, the weight ``w[i]`` applies to the unsquared + residual ``y[i] - y_hat[i]`` at ``x[i]``. Ideally the weights are + chosen so that the errors of the products ``w[i]*y[i]`` all have + the same variance. When using inverse-variance weighting, use + ``w[i] = 1/sigma(y[i])``. The default value is None. .. versionadded:: 1.5.0 window : {[beg, end]}, optional diff --git a/numpy/polynomial/chebyshev.py b/numpy/polynomial/chebyshev.py index d24fc738f..210000ec4 100644 --- a/numpy/polynomial/chebyshev.py +++ b/numpy/polynomial/chebyshev.py @@ -1582,10 +1582,11 @@ def chebfit(x, y, deg, rcond=None, full=False, w=None): default) just the coefficients are returned, when True diagnostic information from the singular value decomposition is also returned. w : array_like, shape (`M`,), optional - Weights. If not None, the contribution of each point - ``(x[i],y[i])`` to the fit is weighted by ``w[i]``. Ideally the - weights are chosen so that the errors of the products ``w[i]*y[i]`` - all have the same variance. The default value is None. + Weights. If not None, the weight ``w[i]`` applies to the unsquared + residual ``y[i] - y_hat[i]`` at ``x[i]``. Ideally the weights are + chosen so that the errors of the products ``w[i]*y[i]`` all have the + same variance. When using inverse-variance weighting, use + ``w[i] = 1/sigma(y[i])``. The default value is None. .. versionadded:: 1.5.0 diff --git a/numpy/polynomial/hermite.py b/numpy/polynomial/hermite.py index eef5c25b2..c1b9f71c0 100644 --- a/numpy/polynomial/hermite.py +++ b/numpy/polynomial/hermite.py @@ -1310,10 +1310,11 @@ def hermfit(x, y, deg, rcond=None, full=False, w=None): default) just the coefficients are returned, when True diagnostic information from the singular value decomposition is also returned. w : array_like, shape (`M`,), optional - Weights. If not None, the contribution of each point - ``(x[i],y[i])`` to the fit is weighted by ``w[i]``. Ideally the - weights are chosen so that the errors of the products ``w[i]*y[i]`` - all have the same variance. The default value is None. + Weights. If not None, the weight ``w[i]`` applies to the unsquared + residual ``y[i] - y_hat[i]`` at ``x[i]``. Ideally the weights are + chosen so that the errors of the products ``w[i]*y[i]`` all have the + same variance. When using inverse-variance weighting, use + ``w[i] = 1/sigma(y[i])``. The default value is None. Returns ------- diff --git a/numpy/polynomial/hermite_e.py b/numpy/polynomial/hermite_e.py index 05d1337b0..b7095c910 100644 --- a/numpy/polynomial/hermite_e.py +++ b/numpy/polynomial/hermite_e.py @@ -1301,10 +1301,11 @@ def hermefit(x, y, deg, rcond=None, full=False, w=None): default) just the coefficients are returned, when True diagnostic information from the singular value decomposition is also returned. w : array_like, shape (`M`,), optional - Weights. If not None, the contribution of each point - ``(x[i],y[i])`` to the fit is weighted by ``w[i]``. Ideally the - weights are chosen so that the errors of the products ``w[i]*y[i]`` - all have the same variance. The default value is None. + Weights. If not None, the weight ``w[i]`` applies to the unsquared + residual ``y[i] - y_hat[i]`` at ``x[i]``. Ideally the weights are + chosen so that the errors of the products ``w[i]*y[i]`` all have the + same variance. When using inverse-variance weighting, use + ``w[i] = 1/sigma(y[i])``. The default value is None. Returns ------- diff --git a/numpy/polynomial/laguerre.py b/numpy/polynomial/laguerre.py index 69d557510..d3b6432dc 100644 --- a/numpy/polynomial/laguerre.py +++ b/numpy/polynomial/laguerre.py @@ -1307,10 +1307,11 @@ def lagfit(x, y, deg, rcond=None, full=False, w=None): default) just the coefficients are returned, when True diagnostic information from the singular value decomposition is also returned. w : array_like, shape (`M`,), optional - Weights. If not None, the contribution of each point - ``(x[i],y[i])`` to the fit is weighted by ``w[i]``. Ideally the - weights are chosen so that the errors of the products ``w[i]*y[i]`` - all have the same variance. The default value is None. + Weights. If not None, the weight ``w[i]`` applies to the unsquared + residual ``y[i] - y_hat[i]`` at ``x[i]``. Ideally the weights are + chosen so that the errors of the products ``w[i]*y[i]`` all have the + same variance. When using inverse-variance weighting, use + ``w[i] = 1/sigma(y[i])``. The default value is None. Returns ------- diff --git a/numpy/polynomial/legendre.py b/numpy/polynomial/legendre.py index cd4da2a79..d4cf4accf 100644 --- a/numpy/polynomial/legendre.py +++ b/numpy/polynomial/legendre.py @@ -1321,10 +1321,11 @@ def legfit(x, y, deg, rcond=None, full=False, w=None): default) just the coefficients are returned, when True diagnostic information from the singular value decomposition is also returned. w : array_like, shape (`M`,), optional - Weights. If not None, the contribution of each point - ``(x[i],y[i])`` to the fit is weighted by ``w[i]``. Ideally the - weights are chosen so that the errors of the products ``w[i]*y[i]`` - all have the same variance. The default value is None. + Weights. If not None, the weight ``w[i]`` applies to the unsquared + residual ``y[i] - y_hat[i]`` at ``x[i]``. Ideally the weights are + chosen so that the errors of the products ``w[i]*y[i]`` all have the + same variance. When using inverse-variance weighting, use + ``w[i] = 1/sigma(y[i])``. The default value is None. .. versionadded:: 1.5.0 diff --git a/numpy/polynomial/polynomial.py b/numpy/polynomial/polynomial.py index 940eed5e3..d8a032068 100644 --- a/numpy/polynomial/polynomial.py +++ b/numpy/polynomial/polynomial.py @@ -1252,10 +1252,11 @@ def polyfit(x, y, deg, rcond=None, full=False, w=None): diagnostic information from the singular value decomposition (used to solve the fit's matrix equation) is also returned. w : array_like, shape (`M`,), optional - Weights. If not None, the contribution of each point - ``(x[i],y[i])`` to the fit is weighted by ``w[i]``. Ideally the - weights are chosen so that the errors of the products ``w[i]*y[i]`` - all have the same variance. The default value is None. + Weights. If not None, the weight ``w[i]`` applies to the unsquared + residual ``y[i] - y_hat[i]`` at ``x[i]``. Ideally the weights are + chosen so that the errors of the products ``w[i]*y[i]`` all have the + same variance. When using inverse-variance weighting, use + ``w[i] = 1/sigma(y[i])``. The default value is None. .. versionadded:: 1.5.0 diff --git a/numpy/testing/__init__.py b/numpy/testing/__init__.py index e1f87621f..064a74a16 100644 --- a/numpy/testing/__init__.py +++ b/numpy/testing/__init__.py @@ -8,6 +8,7 @@ away. from unittest import TestCase from ._private.utils import * +from ._private.utils import _assert_valid_refcount, _gen_alignment_data from ._private import decorators as dec from ._private.nosetester import ( run_module_suite, NoseTester as Tester diff --git a/numpy/testing/__init__.pyi b/numpy/testing/__init__.pyi index 395626f6b..955dae862 100644 --- a/numpy/testing/__init__.pyi +++ b/numpy/testing/__init__.pyi @@ -1,113 +1,53 @@ -import sys -import warnings -from typing import Any, List, ClassVar, Tuple, Set - -if sys.version_info >= (3, 8): - from typing import Final -else: - from typing_extensions import Final +from typing import List from unittest import ( TestCase as TestCase, ) -from unittest.case import ( +from numpy.testing._private.utils import ( + assert_equal as assert_equal, + assert_almost_equal as assert_almost_equal, + assert_approx_equal as assert_approx_equal, + assert_array_equal as assert_array_equal, + assert_array_less as assert_array_less, + assert_string_equal as assert_string_equal, + assert_array_almost_equal as assert_array_almost_equal, + assert_raises as assert_raises, + build_err_msg as build_err_msg, + decorate_methods as decorate_methods, + jiffies as jiffies, + memusage as memusage, + print_assert_equal as print_assert_equal, + raises as raises, + rundocs as rundocs, + runstring as runstring, + verbose as verbose, + measure as measure, + assert_ as assert_, + assert_array_almost_equal_nulp as assert_array_almost_equal_nulp, + assert_raises_regex as assert_raises_regex, + assert_array_max_ulp as assert_array_max_ulp, + assert_warns as assert_warns, + assert_no_warnings as assert_no_warnings, + assert_allclose as assert_allclose, + IgnoreException as IgnoreException, + clear_and_catch_warnings as clear_and_catch_warnings, SkipTest as SkipTest, + KnownFailureException as KnownFailureException, + temppath as temppath, + tempdir as tempdir, + IS_PYPY as IS_PYPY, + HAS_REFCOUNT as HAS_REFCOUNT, + suppress_warnings as suppress_warnings, + assert_array_compare as assert_array_compare, + assert_no_gc_cycles as assert_no_gc_cycles, + break_cycles as break_cycles, + HAS_LAPACK64 as HAS_LAPACK64, ) __all__: List[str] -def run_module_suite(file_to_run=..., argv=...): ... - -class KnownFailureException(Exception): ... -class IgnoreException(Exception): ... - -class clear_and_catch_warnings(warnings.catch_warnings): - class_modules: ClassVar[Tuple[str, ...]] - modules: Set[str] - def __init__(self, record=..., modules=...): ... - def __enter__(self): ... - def __exit__(self, *exc_info): ... - -class suppress_warnings: - log: List[warnings.WarningMessage] - def __init__(self, forwarding_rule=...): ... - def filter(self, category=..., message=..., module=...): ... - def record(self, category=..., message=..., module=...): ... - def __enter__(self): ... - def __exit__(self, *exc_info): ... - def __call__(self, func): ... - -verbose: int -IS_PYPY: Final[bool] -HAS_REFCOUNT: Final[bool] -HAS_LAPACK64: Final[bool] - -def assert_(val, msg=...): ... -def memusage(processName=..., instance=...): ... -def jiffies(_proc_pid_stat=..., _load_time=...): ... -def build_err_msg( - arrays, - err_msg, - header=..., - verbose=..., - names=..., - precision=..., -): ... -def assert_equal(actual, desired, err_msg=..., verbose=...): ... -def print_assert_equal(test_string, actual, desired): ... -def assert_almost_equal( - actual, - desired, - decimal=..., - err_msg=..., - verbose=..., -): ... -def assert_approx_equal( - actual, - desired, - significant=..., - err_msg=..., - verbose=..., -): ... -def assert_array_compare( - comparison, - x, - y, - err_msg=..., - verbose=..., - header=..., - precision=..., - equal_nan=..., - equal_inf=..., -): ... -def assert_array_equal(x, y, err_msg=..., verbose=...): ... -def assert_array_almost_equal(x, y, decimal=..., err_msg=..., verbose=...): ... -def assert_array_less(x, y, err_msg=..., verbose=...): ... -def runstring(astr, dict): ... -def assert_string_equal(actual, desired): ... -def rundocs(filename=..., raise_on_error=...): ... -def raises(*args): ... -def assert_raises(*args, **kwargs): ... -def assert_raises_regex(exception_class, expected_regexp, *args, **kwargs): ... -def decorate_methods(cls, decorator, testmatch=...): ... -def measure(code_str, times=..., label=...): ... -def assert_allclose( - actual, - desired, - rtol=..., - atol=..., - equal_nan=..., - err_msg=..., - verbose=..., -): ... -def assert_array_almost_equal_nulp(x, y, nulp=...): ... -def assert_array_max_ulp(a, b, maxulp=..., dtype=...): ... -def assert_warns(warning_class, *args, **kwargs): ... -def assert_no_warnings(*args, **kwargs): ... -def tempdir(*args, **kwargs): ... -def temppath(*args, **kwargs): ... -def assert_no_gc_cycles(*args, **kwargs): ... -def break_cycles(): ... -def _assert_valid_refcount(op): ... -def _gen_alignment_data(dtype=..., type=..., max_size=...): ... +def run_module_suite( + file_to_run: None | str = ..., + argv: None | List[str] = ..., +) -> None: ... diff --git a/numpy/testing/_private/utils.py b/numpy/testing/_private/utils.py index 393fedc27..487aa0b4c 100644 --- a/numpy/testing/_private/utils.py +++ b/numpy/testing/_private/utils.py @@ -35,8 +35,7 @@ __all__ = [ 'assert_allclose', 'IgnoreException', 'clear_and_catch_warnings', 'SkipTest', 'KnownFailureException', 'temppath', 'tempdir', 'IS_PYPY', 'HAS_REFCOUNT', 'suppress_warnings', 'assert_array_compare', - '_assert_valid_refcount', '_gen_alignment_data', 'assert_no_gc_cycles', - 'break_cycles', 'HAS_LAPACK64' + 'assert_no_gc_cycles', 'break_cycles', 'HAS_LAPACK64' ] @@ -2518,4 +2517,3 @@ def _no_tracing(func): finally: sys.settrace(original_trace) return wrapper - diff --git a/numpy/testing/_private/utils.pyi b/numpy/testing/_private/utils.pyi new file mode 100644 index 000000000..29915309f --- /dev/null +++ b/numpy/testing/_private/utils.pyi @@ -0,0 +1,396 @@ +import os +import sys +import ast +import types +import warnings +import unittest +import contextlib +from typing import ( + Any, + AnyStr, + Callable, + ClassVar, + Dict, + Iterable, + List, + NoReturn, + overload, + Pattern, + Sequence, + Set, + Tuple, + Type, + type_check_only, + TypeVar, + Union, +) + +from numpy import generic, dtype, number, object_, bool_, _FloatValue +from numpy.typing import ( + NDArray, + ArrayLike, + DTypeLike, + _ArrayLikeNumber_co, + _ArrayLikeObject_co, + _ArrayLikeTD64_co, + _ArrayLikeDT64_co, +) + +from unittest.case import ( + SkipTest as SkipTest, +) + +if sys.version_info >= (3, 8): + from typing import Final, SupportsIndex, Literal as L +else: + from typing_extensions import Final, SupportsIndex, Literal as L + +_T = TypeVar("_T") +_ET = TypeVar("_ET", bound=BaseException) +_FT = TypeVar("_FT", bound=Callable[..., Any]) + +# Must return a bool or an ndarray/generic type +# that is supported by `np.logical_and.reduce` +_ComparisonFunc = Callable[ + [NDArray[Any], NDArray[Any]], + Union[ + bool, + bool_, + number[Any], + NDArray[Union[bool_, number[Any], object_]], + ], +] + +__all__: List[str] + +class KnownFailureException(Exception): ... +class IgnoreException(Exception): ... + +class clear_and_catch_warnings(warnings.catch_warnings): + class_modules: ClassVar[Tuple[types.ModuleType, ...]] + modules: Set[types.ModuleType] + @overload + def __new__( + cls, + record: L[False] = ..., + modules: Iterable[types.ModuleType] = ..., + ) -> _clear_and_catch_warnings_without_records: ... + @overload + def __new__( + cls, + record: L[True], + modules: Iterable[types.ModuleType] = ..., + ) -> _clear_and_catch_warnings_with_records: ... + @overload + def __new__( + cls, + record: bool, + modules: Iterable[types.ModuleType] = ..., + ) -> clear_and_catch_warnings: ... + def __enter__(self) -> None | List[warnings.WarningMessage]: ... + def __exit__( + self, + __exc_type: None | Type[BaseException] = ..., + __exc_val: None | BaseException = ..., + __exc_tb: None | types.TracebackType = ..., + ) -> None: ... + +# Type-check only `clear_and_catch_warnings` subclasses for both values of the +# `record` parameter. Copied from the stdlib `warnings` stubs. + +@type_check_only +class _clear_and_catch_warnings_with_records(clear_and_catch_warnings): + def __enter__(self) -> List[warnings.WarningMessage]: ... + +@type_check_only +class _clear_and_catch_warnings_without_records(clear_and_catch_warnings): + def __enter__(self) -> None: ... + +class suppress_warnings: + log: List[warnings.WarningMessage] + def __init__( + self, + forwarding_rule: L["always", "module", "once", "location"] = ..., + ) -> None: ... + def filter( + self, + category: Type[Warning] = ..., + message: str = ..., + module: None | types.ModuleType = ..., + ) -> None: ... + def record( + self, + category: Type[Warning] = ..., + message: str = ..., + module: None | types.ModuleType = ..., + ) -> List[warnings.WarningMessage]: ... + def __enter__(self: _T) -> _T: ... + def __exit__( + self, + __exc_type: None | Type[BaseException] = ..., + __exc_val: None | BaseException = ..., + __exc_tb: None | types.TracebackType = ..., + ) -> None: ... + def __call__(self, func: _FT) -> _FT: ... + +verbose: int +IS_PYPY: Final[bool] +HAS_REFCOUNT: Final[bool] +HAS_LAPACK64: Final[bool] + +def assert_(val: object, msg: str | Callable[[], str] = ...) -> None: ... + +# Contrary to runtime we can't do `os.name` checks while type checking, +# only `sys.platform` checks +if sys.platform == "win32" or sys.platform == "cygwin": + def memusage(processName: str = ..., instance: int = ...) -> int: ... +elif sys.platform == "linux": + def memusage(_proc_pid_stat: str | bytes | os.PathLike[Any] = ...) -> None | int: ... +else: + def memusage() -> NoReturn: ... + +if sys.platform == "linux": + def jiffies( + _proc_pid_stat: str | bytes | os.PathLike[Any] = ..., + _load_time: List[float] = ..., + ) -> int: ... +else: + def jiffies(_load_time: List[float] = ...) -> int: ... + +def build_err_msg( + arrays: Iterable[object], + err_msg: str, + header: str = ..., + verbose: bool = ..., + names: Sequence[str] = ..., + precision: None | SupportsIndex = ..., +) -> str: ... + +def assert_equal( + actual: object, + desired: object, + err_msg: str = ..., + verbose: bool = ..., +) -> None: ... + +def print_assert_equal( + test_string: str, + actual: object, + desired: object, +) -> None: ... + +def assert_almost_equal( + actual: _ArrayLikeNumber_co | _ArrayLikeObject_co, + desired: _ArrayLikeNumber_co | _ArrayLikeObject_co, + decimal: int = ..., + err_msg: str = ..., + verbose: bool = ..., +) -> None: ... + +# Anything that can be coerced into `builtins.float` +def assert_approx_equal( + actual: _FloatValue, + desired: _FloatValue, + significant: int = ..., + err_msg: str = ..., + verbose: bool = ..., +) -> None: ... + +def assert_array_compare( + comparison: _ComparisonFunc, + x: ArrayLike, + y: ArrayLike, + err_msg: str = ..., + verbose: bool = ..., + header: str = ..., + precision: SupportsIndex = ..., + equal_nan: bool = ..., + equal_inf: bool = ..., +) -> None: ... + +def assert_array_equal( + x: ArrayLike, + y: ArrayLike, + err_msg: str = ..., + verbose: bool = ..., +) -> None: ... + +def assert_array_almost_equal( + x: _ArrayLikeNumber_co | _ArrayLikeObject_co, + y: _ArrayLikeNumber_co | _ArrayLikeObject_co, + decimal: float = ..., + err_msg: str = ..., + verbose: bool = ..., +) -> None: ... + +@overload +def assert_array_less( + x: _ArrayLikeNumber_co | _ArrayLikeObject_co, + y: _ArrayLikeNumber_co | _ArrayLikeObject_co, + err_msg: str = ..., + verbose: bool = ..., +) -> None: ... +@overload +def assert_array_less( + x: _ArrayLikeTD64_co, + y: _ArrayLikeTD64_co, + err_msg: str = ..., + verbose: bool = ..., +) -> None: ... +@overload +def assert_array_less( + x: _ArrayLikeDT64_co, + y: _ArrayLikeDT64_co, + err_msg: str = ..., + verbose: bool = ..., +) -> None: ... + +def runstring( + astr: str | bytes | types.CodeType, + dict: None | Dict[str, Any], +) -> Any: ... + +def assert_string_equal(actual: str, desired: str) -> None: ... + +def rundocs( + filename: None | str | os.PathLike[str] = ..., + raise_on_error: bool = ..., +) -> None: ... + +def raises(*args: Type[BaseException]) -> Callable[[_FT], _FT]: ... + +@overload +def assert_raises( # type: ignore + __expected_exception: Type[BaseException] | Tuple[Type[BaseException], ...], + __callable: Callable[..., Any], + *args: Any, + **kwargs: Any, +) -> None: ... +@overload +def assert_raises( + expected_exception: Type[_ET] | Tuple[Type[_ET], ...], + *, + msg: None | str = ..., +) -> unittest.case._AssertRaisesContext[_ET]: ... + +@overload +def assert_raises_regex( + __expected_exception: Type[BaseException] | Tuple[Type[BaseException], ...], + __expected_regex: str | bytes | Pattern[Any], + __callable: Callable[..., Any], + *args: Any, + **kwargs: Any, +) -> None: ... +@overload +def assert_raises_regex( + expected_exception: Type[_ET] | Tuple[Type[_ET], ...], + expected_regex: str | bytes | Pattern[Any], + *, + msg: None | str = ..., +) -> unittest.case._AssertRaisesContext[_ET]: ... + +def decorate_methods( + cls: Type[Any], + decorator: Callable[[Callable[..., Any]], Any], + testmatch: None | str | bytes | Pattern[Any] = ..., +) -> None: ... + +def measure( + code_str: str | bytes | ast.mod | ast.AST, + times: int = ..., + label: None | str = ..., +) -> float: ... + +@overload +def assert_allclose( + actual: _ArrayLikeNumber_co | _ArrayLikeObject_co, + desired: _ArrayLikeNumber_co | _ArrayLikeObject_co, + rtol: float = ..., + atol: float = ..., + equal_nan: bool = ..., + err_msg: str = ..., + verbose: bool = ..., +) -> None: ... +@overload +def assert_allclose( + actual: _ArrayLikeTD64_co, + desired: _ArrayLikeTD64_co, + rtol: float = ..., + atol: float = ..., + equal_nan: bool = ..., + err_msg: str = ..., + verbose: bool = ..., +) -> None: ... + +def assert_array_almost_equal_nulp( + x: _ArrayLikeNumber_co, + y: _ArrayLikeNumber_co, + nulp: float = ..., +) -> None: ... + +def assert_array_max_ulp( + a: _ArrayLikeNumber_co, + b: _ArrayLikeNumber_co, + maxulp: float = ..., + dtype: DTypeLike = ..., +) -> NDArray[Any]: ... + +@overload +def assert_warns( + warning_class: Type[Warning], +) -> contextlib._GeneratorContextManager[None]: ... +@overload +def assert_warns( + __warning_class: Type[Warning], + __func: Callable[..., _T], + *args: Any, + **kwargs: Any, +) -> _T: ... + +@overload +def assert_no_warnings() -> contextlib._GeneratorContextManager[None]: ... +@overload +def assert_no_warnings( + __func: Callable[..., _T], + *args: Any, + **kwargs: Any, +) -> _T: ... + +@overload +def tempdir( + suffix: None = ..., + prefix: None = ..., + dir: None = ..., +) -> contextlib._GeneratorContextManager[str]: ... +@overload +def tempdir( + suffix: None | AnyStr = ..., + prefix: None | AnyStr = ..., + dir: None | AnyStr | os.PathLike[AnyStr] = ..., +) -> contextlib._GeneratorContextManager[AnyStr]: ... + +@overload +def temppath( + suffix: None = ..., + prefix: None = ..., + dir: None = ..., + text: bool = ..., +) -> contextlib._GeneratorContextManager[str]: ... +@overload +def temppath( + suffix: None | AnyStr = ..., + prefix: None | AnyStr = ..., + dir: None | AnyStr | os.PathLike[AnyStr] = ..., + text: bool = ..., +) -> contextlib._GeneratorContextManager[AnyStr]: ... + +@overload +def assert_no_gc_cycles() -> contextlib._GeneratorContextManager[None]: ... +@overload +def assert_no_gc_cycles( + __func: Callable[..., Any], + *args: Any, + **kwargs: Any, +) -> None: ... + +def break_cycles() -> None: ... diff --git a/numpy/testing/setup.py b/numpy/testing/setup.py index 7652a94a2..6f203e872 100755 --- a/numpy/testing/setup.py +++ b/numpy/testing/setup.py @@ -7,6 +7,7 @@ def configuration(parent_package='',top_path=None): config.add_subpackage('_private') config.add_subpackage('tests') config.add_data_files('*.pyi') + config.add_data_files('_private/*.pyi') return config if __name__ == '__main__': diff --git a/numpy/testing/utils.py b/numpy/testing/utils.py index 753258c13..20a883304 100644 --- a/numpy/testing/utils.py +++ b/numpy/testing/utils.py @@ -12,6 +12,7 @@ warnings.warn("Importing from numpy.testing.utils is deprecated " DeprecationWarning, stacklevel=2) from ._private.utils import * +from ._private.utils import _assert_valid_refcount, _gen_alignment_data __all__ = [ 'assert_equal', 'assert_almost_equal', 'assert_approx_equal', @@ -24,5 +25,5 @@ __all__ = [ 'assert_allclose', 'IgnoreException', 'clear_and_catch_warnings', 'SkipTest', 'KnownFailureException', 'temppath', 'tempdir', 'IS_PYPY', 'HAS_REFCOUNT', 'suppress_warnings', 'assert_array_compare', - '_assert_valid_refcount', '_gen_alignment_data', 'assert_no_gc_cycles' + 'assert_no_gc_cycles' ] diff --git a/numpy/typing/__init__.py b/numpy/typing/__init__.py index 252123a19..19424169a 100644 --- a/numpy/typing/__init__.py +++ b/numpy/typing/__init__.py @@ -164,7 +164,7 @@ API # NOTE: The API section will be appended with additional entries # further down in this file -from typing import TYPE_CHECKING, List +from typing import TYPE_CHECKING, List, Any if TYPE_CHECKING: # typing_extensions is always available when type-checking @@ -376,14 +376,14 @@ if TYPE_CHECKING: _GUFunc_Nin2_Nout1, ) else: - _UFunc_Nin1_Nout1 = NotImplemented - _UFunc_Nin2_Nout1 = NotImplemented - _UFunc_Nin1_Nout2 = NotImplemented - _UFunc_Nin2_Nout2 = NotImplemented - _GUFunc_Nin2_Nout1 = NotImplemented + _UFunc_Nin1_Nout1 = Any + _UFunc_Nin2_Nout1 = Any + _UFunc_Nin1_Nout2 = Any + _UFunc_Nin2_Nout2 = Any + _GUFunc_Nin2_Nout1 = Any # Clean up the namespace -del TYPE_CHECKING, final, List +del TYPE_CHECKING, final, List, Any if __doc__ is not None: from ._add_docstring import _docstrings diff --git a/numpy/typing/_array_like.py b/numpy/typing/_array_like.py index 2b823ecc0..3bdbed8f8 100644 --- a/numpy/typing/_array_like.py +++ b/numpy/typing/_array_like.py @@ -1,7 +1,7 @@ from __future__ import annotations import sys -from typing import Any, Sequence, TYPE_CHECKING, Union, TypeVar +from typing import Any, Sequence, TYPE_CHECKING, Union, TypeVar, Generic from numpy import ( ndarray, @@ -34,7 +34,7 @@ _ScalarType = TypeVar("_ScalarType", bound=generic) _DType = TypeVar("_DType", bound="dtype[Any]") _DType_co = TypeVar("_DType_co", covariant=True, bound="dtype[Any]") -if TYPE_CHECKING or _HAS_TYPING_EXTENSIONS: +if TYPE_CHECKING or _HAS_TYPING_EXTENSIONS or sys.version_info >= (3, 8): # The `_SupportsArray` protocol only cares about the default dtype # (i.e. `dtype=None` or no `dtype` parameter at all) of the to-be returned # array. @@ -43,7 +43,7 @@ if TYPE_CHECKING or _HAS_TYPING_EXTENSIONS: class _SupportsArray(Protocol[_DType_co]): def __array__(self) -> ndarray[Any, _DType_co]: ... else: - _SupportsArray = Any + class _SupportsArray(Generic[_DType_co]): ... # TODO: Wait for support for recursive types _NestedSequence = Union[ diff --git a/numpy/typing/_callable.py b/numpy/typing/_callable.py index 54f9b1425..8f911da3b 100644 --- a/numpy/typing/_callable.py +++ b/numpy/typing/_callable.py @@ -53,7 +53,7 @@ if sys.version_info >= (3, 8): elif _HAS_TYPING_EXTENSIONS: from typing_extensions import Protocol -if TYPE_CHECKING or _HAS_TYPING_EXTENSIONS: +if TYPE_CHECKING or _HAS_TYPING_EXTENSIONS or sys.version_info >= (3, 8): _T1 = TypeVar("_T1") _T2 = TypeVar("_T2") _2Tuple = Tuple[_T1, _T1] @@ -332,25 +332,25 @@ if TYPE_CHECKING or _HAS_TYPING_EXTENSIONS: def __call__(self, __other: _T2) -> NDArray[bool_]: ... else: - _BoolOp = NotImplemented - _BoolBitOp = NotImplemented - _BoolSub = NotImplemented - _BoolTrueDiv = NotImplemented - _BoolMod = NotImplemented - _BoolDivMod = NotImplemented - _TD64Div = NotImplemented - _IntTrueDiv = NotImplemented - _UnsignedIntOp = NotImplemented - _UnsignedIntBitOp = NotImplemented - _UnsignedIntMod = NotImplemented - _UnsignedIntDivMod = NotImplemented - _SignedIntOp = NotImplemented - _SignedIntBitOp = NotImplemented - _SignedIntMod = NotImplemented - _SignedIntDivMod = NotImplemented - _FloatOp = NotImplemented - _FloatMod = NotImplemented - _FloatDivMod = NotImplemented - _ComplexOp = NotImplemented - _NumberOp = NotImplemented - _ComparisonOp = NotImplemented + _BoolOp = Any + _BoolBitOp = Any + _BoolSub = Any + _BoolTrueDiv = Any + _BoolMod = Any + _BoolDivMod = Any + _TD64Div = Any + _IntTrueDiv = Any + _UnsignedIntOp = Any + _UnsignedIntBitOp = Any + _UnsignedIntMod = Any + _UnsignedIntDivMod = Any + _SignedIntOp = Any + _SignedIntBitOp = Any + _SignedIntMod = Any + _SignedIntDivMod = Any + _FloatOp = Any + _FloatMod = Any + _FloatDivMod = Any + _ComplexOp = Any + _NumberOp = Any + _ComparisonOp = Any diff --git a/numpy/typing/_char_codes.py b/numpy/typing/_char_codes.py index 6b33f995d..22ee168e9 100644 --- a/numpy/typing/_char_codes.py +++ b/numpy/typing/_char_codes.py @@ -8,7 +8,7 @@ if sys.version_info >= (3, 8): elif _HAS_TYPING_EXTENSIONS: from typing_extensions import Literal -if TYPE_CHECKING or _HAS_TYPING_EXTENSIONS: +if TYPE_CHECKING or _HAS_TYPING_EXTENSIONS or sys.version_info >= (3, 8): _BoolCodes = Literal["?", "=?", "<?", ">?", "bool", "bool_", "bool8"] _UInt8Codes = Literal["uint8", "u1", "=u1", "<u1", ">u1"] @@ -120,52 +120,52 @@ if TYPE_CHECKING or _HAS_TYPING_EXTENSIONS: ] else: - _BoolCodes = NotImplemented - - _UInt8Codes = NotImplemented - _UInt16Codes = NotImplemented - _UInt32Codes = NotImplemented - _UInt64Codes = NotImplemented - - _Int8Codes = NotImplemented - _Int16Codes = NotImplemented - _Int32Codes = NotImplemented - _Int64Codes = NotImplemented - - _Float16Codes = NotImplemented - _Float32Codes = NotImplemented - _Float64Codes = NotImplemented - - _Complex64Codes = NotImplemented - _Complex128Codes = NotImplemented - - _ByteCodes = NotImplemented - _ShortCodes = NotImplemented - _IntCCodes = NotImplemented - _IntPCodes = NotImplemented - _IntCodes = NotImplemented - _LongLongCodes = NotImplemented - - _UByteCodes = NotImplemented - _UShortCodes = NotImplemented - _UIntCCodes = NotImplemented - _UIntPCodes = NotImplemented - _UIntCodes = NotImplemented - _ULongLongCodes = NotImplemented - - _HalfCodes = NotImplemented - _SingleCodes = NotImplemented - _DoubleCodes = NotImplemented - _LongDoubleCodes = NotImplemented - - _CSingleCodes = NotImplemented - _CDoubleCodes = NotImplemented - _CLongDoubleCodes = NotImplemented - - _StrCodes = NotImplemented - _BytesCodes = NotImplemented - _VoidCodes = NotImplemented - _ObjectCodes = NotImplemented - - _DT64Codes = NotImplemented - _TD64Codes = NotImplemented + _BoolCodes = Any + + _UInt8Codes = Any + _UInt16Codes = Any + _UInt32Codes = Any + _UInt64Codes = Any + + _Int8Codes = Any + _Int16Codes = Any + _Int32Codes = Any + _Int64Codes = Any + + _Float16Codes = Any + _Float32Codes = Any + _Float64Codes = Any + + _Complex64Codes = Any + _Complex128Codes = Any + + _ByteCodes = Any + _ShortCodes = Any + _IntCCodes = Any + _IntPCodes = Any + _IntCodes = Any + _LongLongCodes = Any + + _UByteCodes = Any + _UShortCodes = Any + _UIntCCodes = Any + _UIntPCodes = Any + _UIntCodes = Any + _ULongLongCodes = Any + + _HalfCodes = Any + _SingleCodes = Any + _DoubleCodes = Any + _LongDoubleCodes = Any + + _CSingleCodes = Any + _CDoubleCodes = Any + _CLongDoubleCodes = Any + + _StrCodes = Any + _BytesCodes = Any + _VoidCodes = Any + _ObjectCodes = Any + + _DT64Codes = Any + _TD64Codes = Any diff --git a/numpy/typing/_dtype_like.py b/numpy/typing/_dtype_like.py index 405cc4a3c..b2ce3adb4 100644 --- a/numpy/typing/_dtype_like.py +++ b/numpy/typing/_dtype_like.py @@ -11,9 +11,6 @@ if sys.version_info >= (3, 8): from typing import Protocol, TypedDict elif _HAS_TYPING_EXTENSIONS: from typing_extensions import Protocol, TypedDict - -if sys.version_info >= (3, 9): - from types import GenericAlias else: from ._generic_alias import _GenericAlias as GenericAlias @@ -62,7 +59,7 @@ from ._char_codes import ( _DTypeLikeNested = Any # TODO: wait for support for recursive types _DType_co = TypeVar("_DType_co", covariant=True, bound=DType[Any]) -if TYPE_CHECKING or _HAS_TYPING_EXTENSIONS: +if TYPE_CHECKING or _HAS_TYPING_EXTENSIONS or sys.version_info >= (3, 8): # Mandatory keys class _DTypeDictBase(TypedDict): names: Sequence[str] @@ -81,7 +78,7 @@ if TYPE_CHECKING or _HAS_TYPING_EXTENSIONS: def dtype(self) -> _DType_co: ... else: - _DTypeDict = NotImplemented + _DTypeDict = Any class _SupportsDType: ... _SupportsDType = GenericAlias(_SupportsDType, _DType_co) diff --git a/numpy/typing/_extended_precision.py b/numpy/typing/_extended_precision.py index 3f1ce2038..0900bc659 100644 --- a/numpy/typing/_extended_precision.py +++ b/numpy/typing/_extended_precision.py @@ -28,15 +28,15 @@ if TYPE_CHECKING: complex256 = np.complexfloating[_128Bit, _128Bit] complex512 = np.complexfloating[_256Bit, _256Bit] else: - uint128 = NotImplemented - uint256 = NotImplemented - int128 = NotImplemented - int256 = NotImplemented - float80 = NotImplemented - float96 = NotImplemented - float128 = NotImplemented - float256 = NotImplemented - complex160 = NotImplemented - complex192 = NotImplemented - complex256 = NotImplemented - complex512 = NotImplemented + uint128 = Any + uint256 = Any + int128 = Any + int256 = Any + float80 = Any + float96 = Any + float128 = Any + float256 = Any + complex160 = Any + complex192 = Any + complex256 = Any + complex512 = Any diff --git a/numpy/typing/_generic_alias.py b/numpy/typing/_generic_alias.py index 0d30f54ca..8d65ef855 100644 --- a/numpy/typing/_generic_alias.py +++ b/numpy/typing/_generic_alias.py @@ -93,7 +93,7 @@ class _GenericAlias: return super().__getattribute__("_origin") @property - def __args__(self) -> Tuple[Any, ...]: + def __args__(self) -> Tuple[object, ...]: return super().__getattribute__("_args") @property @@ -101,16 +101,23 @@ class _GenericAlias: """Type variables in the ``GenericAlias``.""" return super().__getattribute__("_parameters") - def __init__(self, origin: type, args: Any) -> None: + def __init__( + self, + origin: type, + args: object | Tuple[object, ...], + ) -> None: self._origin = origin self._args = args if isinstance(args, tuple) else (args,) - self._parameters = tuple(_parse_parameters(args)) + self._parameters = tuple(_parse_parameters(self.__args__)) @property def __call__(self) -> type: return self.__origin__ - def __reduce__(self: _T) -> Tuple[Type[_T], Tuple[type, Tuple[Any, ...]]]: + def __reduce__(self: _T) -> Tuple[ + Type[_T], + Tuple[type, Tuple[object, ...]], + ]: cls = type(self) return cls, (self.__origin__, self.__args__) @@ -148,7 +155,7 @@ class _GenericAlias: origin = _to_str(self.__origin__) return f"{origin}[{args}]" - def __getitem__(self: _T, key: Any) -> _T: + def __getitem__(self: _T, key: object | Tuple[object, ...]) -> _T: """Return ``self[key]``.""" key_tup = key if isinstance(key, tuple) else (key,) diff --git a/numpy/typing/_shape.py b/numpy/typing/_shape.py index 0742be8a9..75698f3d3 100644 --- a/numpy/typing/_shape.py +++ b/numpy/typing/_shape.py @@ -1,5 +1,5 @@ import sys -from typing import Sequence, Tuple, Union +from typing import Sequence, Tuple, Union, Any from . import _HAS_TYPING_EXTENSIONS @@ -8,7 +8,7 @@ if sys.version_info >= (3, 8): elif _HAS_TYPING_EXTENSIONS: from typing_extensions import SupportsIndex else: - SupportsIndex = NotImplemented + SupportsIndex = Any _Shape = Tuple[int, ...] diff --git a/numpy/typing/tests/data/fail/testing.py b/numpy/typing/tests/data/fail/testing.py new file mode 100644 index 000000000..e753a9810 --- /dev/null +++ b/numpy/typing/tests/data/fail/testing.py @@ -0,0 +1,26 @@ +import numpy as np +import numpy.typing as npt + +AR_U: npt.NDArray[np.str_] + +def func() -> bool: ... + +np.testing.assert_(True, msg=1) # E: incompatible type +np.testing.build_err_msg(1, "test") # E: incompatible type +np.testing.assert_almost_equal(AR_U, AR_U) # E: incompatible type +np.testing.assert_approx_equal([1, 2, 3], [1, 2, 3]) # E: incompatible type +np.testing.assert_array_almost_equal(AR_U, AR_U) # E: incompatible type +np.testing.assert_array_less(AR_U, AR_U) # E: incompatible type +np.testing.assert_string_equal(b"a", b"a") # E: incompatible type + +np.testing.assert_raises(expected_exception=TypeError, callable=func) # E: No overload variant +np.testing.assert_raises_regex(expected_exception=TypeError, expected_regex="T", callable=func) # E: No overload variant + +np.testing.assert_allclose(AR_U, AR_U) # E: incompatible type +np.testing.assert_array_almost_equal_nulp(AR_U, AR_U) # E: incompatible type +np.testing.assert_array_max_ulp(AR_U, AR_U) # E: incompatible type + +np.testing.assert_warns(warning_class=RuntimeWarning, func=func) # E: No overload variant +np.testing.assert_no_warnings(func=func) # E: No overload variant + +np.testing.assert_no_gc_cycles(func=func) # E: No overload variant diff --git a/numpy/typing/tests/data/reveal/modules.py b/numpy/typing/tests/data/reveal/modules.py index fa356969a..b045585b2 100644 --- a/numpy/typing/tests/data/reveal/modules.py +++ b/numpy/typing/tests/data/reveal/modules.py @@ -29,9 +29,6 @@ reveal_type(np.polynomial.laguerre) # E: ModuleType reveal_type(np.polynomial.legendre) # E: ModuleType reveal_type(np.polynomial.polynomial) # E: ModuleType -# TODO: Remove when annotations have been added to `np.testing.assert_equal` -reveal_type(np.testing.assert_equal) # E: Any - reveal_type(np.__path__) # E: list[builtins.str] reveal_type(np.__version__) # E: str reveal_type(np.__git_version__) # E: str diff --git a/numpy/typing/tests/data/reveal/ndarray_conversion.py b/numpy/typing/tests/data/reveal/ndarray_conversion.py index 4ee637b75..03f2faf43 100644 --- a/numpy/typing/tests/data/reveal/ndarray_conversion.py +++ b/numpy/typing/tests/data/reveal/ndarray_conversion.py @@ -1,12 +1,13 @@ import numpy as np +import numpy.typing as npt -nd = np.array([[1, 2], [3, 4]]) +nd: npt.NDArray[np.int_] = np.array([[1, 2], [3, 4]]) # item -reveal_type(nd.item()) # E: Any -reveal_type(nd.item(1)) # E: Any -reveal_type(nd.item(0, 1)) # E: Any -reveal_type(nd.item((0, 1))) # E: Any +reveal_type(nd.item()) # E: int +reveal_type(nd.item(1)) # E: int +reveal_type(nd.item(0, 1)) # E: int +reveal_type(nd.item((0, 1))) # E: int # tolist reveal_type(nd.tolist()) # E: Any @@ -19,36 +20,32 @@ reveal_type(nd.tolist()) # E: Any # dumps is pretty simple # astype -reveal_type(nd.astype("float")) # E: numpy.ndarray -reveal_type(nd.astype(float)) # E: numpy.ndarray -reveal_type(nd.astype(float, "K")) # E: numpy.ndarray -reveal_type(nd.astype(float, "K", "unsafe")) # E: numpy.ndarray -reveal_type(nd.astype(float, "K", "unsafe", True)) # E: numpy.ndarray -reveal_type(nd.astype(float, "K", "unsafe", True, True)) # E: numpy.ndarray +reveal_type(nd.astype("float")) # E: numpy.ndarray[Any, numpy.dtype[Any]] +reveal_type(nd.astype(float)) # E: numpy.ndarray[Any, numpy.dtype[Any]] +reveal_type(nd.astype(np.float64)) # E: numpy.ndarray[Any, numpy.dtype[{float64}]] +reveal_type(nd.astype(np.float64, "K")) # E: numpy.ndarray[Any, numpy.dtype[{float64}]] +reveal_type(nd.astype(np.float64, "K", "unsafe")) # E: numpy.ndarray[Any, numpy.dtype[{float64}]] +reveal_type(nd.astype(np.float64, "K", "unsafe", True)) # E: numpy.ndarray[Any, numpy.dtype[{float64}]] +reveal_type(nd.astype(np.float64, "K", "unsafe", True, True)) # E: numpy.ndarray[Any, numpy.dtype[{float64}]] # byteswap -reveal_type(nd.byteswap()) # E: numpy.ndarray -reveal_type(nd.byteswap(True)) # E: numpy.ndarray +reveal_type(nd.byteswap()) # E: numpy.ndarray[Any, numpy.dtype[{int_}]] +reveal_type(nd.byteswap(True)) # E: numpy.ndarray[Any, numpy.dtype[{int_}]] # copy -reveal_type(nd.copy()) # E: numpy.ndarray -reveal_type(nd.copy("C")) # E: numpy.ndarray +reveal_type(nd.copy()) # E: numpy.ndarray[Any, numpy.dtype[{int_}]] +reveal_type(nd.copy("C")) # E: numpy.ndarray[Any, numpy.dtype[{int_}]] -# view -class SubArray(np.ndarray): - pass - - -reveal_type(nd.view()) # E: numpy.ndarray -reveal_type(nd.view(np.int64)) # E: numpy.ndarray -# replace `Any` with `numpy.matrix` when `matrix` will be added to stubs -reveal_type(nd.view(np.int64, np.matrix)) # E: Any -reveal_type(nd.view(np.int64, SubArray)) # E: SubArray +reveal_type(nd.view()) # E: numpy.ndarray[Any, numpy.dtype[{int_}]] +reveal_type(nd.view(np.float64)) # E: numpy.ndarray[Any, numpy.dtype[{float64}]] +reveal_type(nd.view(float)) # E: numpy.ndarray[Any, numpy.dtype[Any]] +reveal_type(nd.view(np.float64, np.matrix)) # E: numpy.matrix[Any, Any] # getfield -reveal_type(nd.getfield("float")) # E: numpy.ndarray -reveal_type(nd.getfield(float)) # E: numpy.ndarray -reveal_type(nd.getfield(float, 8)) # E: numpy.ndarray +reveal_type(nd.getfield("float")) # E: numpy.ndarray[Any, numpy.dtype[Any]] +reveal_type(nd.getfield(float)) # E: numpy.ndarray[Any, numpy.dtype[Any]] +reveal_type(nd.getfield(np.float64)) # E: numpy.ndarray[Any, numpy.dtype[{float64}]] +reveal_type(nd.getfield(np.float64, 8)) # E: numpy.ndarray[Any, numpy.dtype[{float64}]] # setflags does not return a value # fill does not return a value diff --git a/numpy/typing/tests/data/reveal/scalars.py b/numpy/typing/tests/data/reveal/scalars.py index d98388422..c081a5c67 100644 --- a/numpy/typing/tests/data/reveal/scalars.py +++ b/numpy/typing/tests/data/reveal/scalars.py @@ -114,3 +114,15 @@ reveal_type(f8.reshape(1)) # E: numpy.ndarray[Any, numpy.dtype[{float64}]] reveal_type(c16.reshape(1)) # E: numpy.ndarray[Any, numpy.dtype[{complex128}]] reveal_type(U.reshape(1)) # E: numpy.ndarray[Any, numpy.dtype[numpy.str_]] reveal_type(S.reshape(1)) # E: numpy.ndarray[Any, numpy.dtype[numpy.bytes_]] + +reveal_type(i8.astype(float)) # E: Any +reveal_type(i8.astype(np.float64)) # E: {float64} + +reveal_type(i8.view()) # E: {int64} +reveal_type(i8.view(np.float64)) # E: {float64} +reveal_type(i8.view(float)) # E: Any +reveal_type(i8.view(np.float64, np.ndarray)) # E: {float64} + +reveal_type(i8.getfield(float)) # E: Any +reveal_type(i8.getfield(np.float64)) # E: {float64} +reveal_type(i8.getfield(np.float64, 8)) # E: {float64} diff --git a/numpy/typing/tests/data/reveal/testing.py b/numpy/typing/tests/data/reveal/testing.py new file mode 100644 index 000000000..e244c225c --- /dev/null +++ b/numpy/typing/tests/data/reveal/testing.py @@ -0,0 +1,173 @@ +from __future__ import annotations + +import re +import sys +from typing import Any, Callable, TypeVar +from pathlib import Path + +import numpy as np +import numpy.typing as npt + +AR_f8: npt.NDArray[np.float64] +AR_i8: npt.NDArray[np.int64] + +bool_obj: bool +suppress_obj: np.testing.suppress_warnings +FT = TypeVar("FT", bound=Callable[..., Any]) + +def func() -> int: ... + +def func2( + x: npt.NDArray[np.number[Any]], + y: npt.NDArray[np.number[Any]], +) -> npt.NDArray[np.bool_]: ... + +reveal_type(np.testing.KnownFailureException()) # E: KnownFailureException +reveal_type(np.testing.IgnoreException()) # E: IgnoreException + +reveal_type(np.testing.clear_and_catch_warnings(modules=[np.testing])) # E: _clear_and_catch_warnings_without_records +reveal_type(np.testing.clear_and_catch_warnings(True)) # E: _clear_and_catch_warnings_with_records +reveal_type(np.testing.clear_and_catch_warnings(False)) # E: _clear_and_catch_warnings_without_records +reveal_type(np.testing.clear_and_catch_warnings(bool_obj)) # E: clear_and_catch_warnings +reveal_type(np.testing.clear_and_catch_warnings.class_modules) # E: tuple[_importlib_modulespec.ModuleType] +reveal_type(np.testing.clear_and_catch_warnings.modules) # E: set[_importlib_modulespec.ModuleType] + +with np.testing.clear_and_catch_warnings(True) as c1: + reveal_type(c1) # E: builtins.list[warnings.WarningMessage] +with np.testing.clear_and_catch_warnings() as c2: + reveal_type(c2) # E: None + +reveal_type(np.testing.suppress_warnings("once")) # E: suppress_warnings +reveal_type(np.testing.suppress_warnings()(func)) # E: def () -> builtins.int +reveal_type(suppress_obj.filter(RuntimeWarning)) # E: None +reveal_type(suppress_obj.record(RuntimeWarning)) # E: list[warnings.WarningMessage] +with suppress_obj as c3: + reveal_type(c3) # E: suppress_warnings + +reveal_type(np.testing.verbose) # E: int +reveal_type(np.testing.IS_PYPY) # E: bool +reveal_type(np.testing.HAS_REFCOUNT) # E: bool +reveal_type(np.testing.HAS_LAPACK64) # E: bool + +reveal_type(np.testing.assert_(1, msg="test")) # E: None +reveal_type(np.testing.assert_(2, msg=lambda: "test")) # E: None + +if sys.platform == "win32" or sys.platform == "cygwin": + reveal_type(np.testing.memusage()) # E: builtins.int +elif sys.platform == "linux": + reveal_type(np.testing.memusage()) # E: Union[None, builtins.int] +else: + reveal_type(np.testing.memusage()) # E: <nothing> + +reveal_type(np.testing.jiffies()) # E: builtins.int + +reveal_type(np.testing.build_err_msg([0, 1, 2], "test")) # E: str +reveal_type(np.testing.build_err_msg(range(2), "test", header="header")) # E: str +reveal_type(np.testing.build_err_msg(np.arange(9).reshape(3, 3), "test", verbose=False)) # E: str +reveal_type(np.testing.build_err_msg("abc", "test", names=["x", "y"])) # E: str +reveal_type(np.testing.build_err_msg([1.0, 2.0], "test", precision=5)) # E: str + +reveal_type(np.testing.assert_equal({1}, {1})) # E: None +reveal_type(np.testing.assert_equal([1, 2, 3], [1, 2, 3], err_msg="fail")) # E: None +reveal_type(np.testing.assert_equal(1, 1.0, verbose=True)) # E: None + +reveal_type(np.testing.print_assert_equal('Test XYZ of func xyz', [0, 1], [0, 1])) # E: None + +reveal_type(np.testing.assert_almost_equal(1.0, 1.1)) # E: None +reveal_type(np.testing.assert_almost_equal([1, 2, 3], [1, 2, 3], err_msg="fail")) # E: None +reveal_type(np.testing.assert_almost_equal(1, 1.0, verbose=True)) # E: None +reveal_type(np.testing.assert_almost_equal(1, 1.0001, decimal=2)) # E: None + +reveal_type(np.testing.assert_approx_equal(1.0, 1.1)) # E: None +reveal_type(np.testing.assert_approx_equal("1", "2", err_msg="fail")) # E: None +reveal_type(np.testing.assert_approx_equal(1, 1.0, verbose=True)) # E: None +reveal_type(np.testing.assert_approx_equal(1, 1.0001, significant=2)) # E: None + +reveal_type(np.testing.assert_array_compare(func2, AR_i8, AR_f8, err_msg="test")) # E: None +reveal_type(np.testing.assert_array_compare(func2, AR_i8, AR_f8, verbose=True)) # E: None +reveal_type(np.testing.assert_array_compare(func2, AR_i8, AR_f8, header="header")) # E: None +reveal_type(np.testing.assert_array_compare(func2, AR_i8, AR_f8, precision=np.int64())) # E: None +reveal_type(np.testing.assert_array_compare(func2, AR_i8, AR_f8, equal_nan=False)) # E: None +reveal_type(np.testing.assert_array_compare(func2, AR_i8, AR_f8, equal_inf=True)) # E: None + +reveal_type(np.testing.assert_array_equal(AR_i8, AR_f8)) # E: None +reveal_type(np.testing.assert_array_equal(AR_i8, AR_f8, err_msg="test")) # E: None +reveal_type(np.testing.assert_array_equal(AR_i8, AR_f8, verbose=True)) # E: None + +reveal_type(np.testing.assert_array_almost_equal(AR_i8, AR_f8)) # E: None +reveal_type(np.testing.assert_array_almost_equal(AR_i8, AR_f8, err_msg="test")) # E: None +reveal_type(np.testing.assert_array_almost_equal(AR_i8, AR_f8, verbose=True)) # E: None +reveal_type(np.testing.assert_array_almost_equal(AR_i8, AR_f8, decimal=1)) # E: None + +reveal_type(np.testing.assert_array_less(AR_i8, AR_f8)) # E: None +reveal_type(np.testing.assert_array_less(AR_i8, AR_f8, err_msg="test")) # E: None +reveal_type(np.testing.assert_array_less(AR_i8, AR_f8, verbose=True)) # E: None + +reveal_type(np.testing.runstring("1 + 1", {})) # E: Any +reveal_type(np.testing.runstring("int64() + 1", {"int64": np.int64})) # E: Any + +reveal_type(np.testing.assert_string_equal("1", "1")) # E: None + +reveal_type(np.testing.rundocs()) # E: None +reveal_type(np.testing.rundocs("test.py")) # E: None +reveal_type(np.testing.rundocs(Path("test.py"), raise_on_error=True)) # E: None + +@np.testing.raises(RuntimeError, RuntimeWarning) +def func3(a: int) -> bool: ... + +reveal_type(func3) # E: def (a: builtins.int) -> builtins.bool + +reveal_type(np.testing.assert_raises(RuntimeWarning)) # E: _AssertRaisesContext[builtins.RuntimeWarning] +reveal_type(np.testing.assert_raises(RuntimeWarning, func3, 5)) # E: None + +reveal_type(np.testing.assert_raises_regex(RuntimeWarning, r"test")) # E: _AssertRaisesContext[builtins.RuntimeWarning] +reveal_type(np.testing.assert_raises_regex(RuntimeWarning, b"test", func3, 5)) # E: None +reveal_type(np.testing.assert_raises_regex(RuntimeWarning, re.compile(b"test"), func3, 5)) # E: None + +class Test: ... + +def decorate(a: FT) -> FT: + return a + +reveal_type(np.testing.decorate_methods(Test, decorate)) # E: None +reveal_type(np.testing.decorate_methods(Test, decorate, None)) # E: None +reveal_type(np.testing.decorate_methods(Test, decorate, "test")) # E: None +reveal_type(np.testing.decorate_methods(Test, decorate, b"test")) # E: None +reveal_type(np.testing.decorate_methods(Test, decorate, re.compile("test"))) # E: None + +reveal_type(np.testing.measure("for i in range(1000): np.sqrt(i**2)")) # E: float +reveal_type(np.testing.measure(b"for i in range(1000): np.sqrt(i**2)", times=5)) # E: float + +reveal_type(np.testing.assert_allclose(AR_i8, AR_f8)) # E: None +reveal_type(np.testing.assert_allclose(AR_i8, AR_f8, rtol=0.005)) # E: None +reveal_type(np.testing.assert_allclose(AR_i8, AR_f8, atol=1)) # E: None +reveal_type(np.testing.assert_allclose(AR_i8, AR_f8, equal_nan=True)) # E: None +reveal_type(np.testing.assert_allclose(AR_i8, AR_f8, err_msg="err")) # E: None +reveal_type(np.testing.assert_allclose(AR_i8, AR_f8, verbose=False)) # E: None + +reveal_type(np.testing.assert_array_almost_equal_nulp(AR_i8, AR_f8, nulp=2)) # E: None + +reveal_type(np.testing.assert_array_max_ulp(AR_i8, AR_f8, maxulp=2)) # E: numpy.ndarray[Any, numpy.dtype[Any]] +reveal_type(np.testing.assert_array_max_ulp(AR_i8, AR_f8, dtype=np.float32)) # E: numpy.ndarray[Any, numpy.dtype[Any]] + +reveal_type(np.testing.assert_warns(RuntimeWarning)) # E: _GeneratorContextManager[None] +reveal_type(np.testing.assert_warns(RuntimeWarning, func3, 5)) # E: bool + +reveal_type(np.testing.assert_no_warnings()) # E: _GeneratorContextManager[None] +reveal_type(np.testing.assert_no_warnings(func3, 5)) # E: bool + +reveal_type(np.testing.tempdir("test_dir")) # E: _GeneratorContextManager[builtins.str] +reveal_type(np.testing.tempdir(prefix=b"test")) # E: _GeneratorContextManager[builtins.bytes] +reveal_type(np.testing.tempdir("test_dir", dir=Path("here"))) # E: _GeneratorContextManager[builtins.str] + +reveal_type(np.testing.temppath("test_dir", text=True)) # E: _GeneratorContextManager[builtins.str] +reveal_type(np.testing.temppath(prefix=b"test")) # E: _GeneratorContextManager[builtins.bytes] +reveal_type(np.testing.temppath("test_dir", dir=Path("here"))) # E: _GeneratorContextManager[builtins.str] + +reveal_type(np.testing.assert_no_gc_cycles()) # E: _GeneratorContextManager[None] +reveal_type(np.testing.assert_no_gc_cycles(func3, 5)) # E: None + +reveal_type(np.testing.break_cycles()) # E: None + +reveal_type(np.testing.TestCase()) # E: unittest.case.TestCase +reveal_type(np.testing.run_module_suite(file_to_run="numpy/tests/test_matlib.py")) # E: None diff --git a/numpy/typing/tests/test_generic_alias.py b/numpy/typing/tests/test_generic_alias.py index 0b9917439..538d7eae5 100644 --- a/numpy/typing/tests/test_generic_alias.py +++ b/numpy/typing/tests/test_generic_alias.py @@ -21,8 +21,8 @@ if sys.version_info >= (3, 9): NDArray_ref = types.GenericAlias(np.ndarray, (Any, DType_ref)) FuncType = Callable[[Union[_GenericAlias, types.GenericAlias]], Any] else: - DType_ref = NotImplemented - NDArray_ref = NotImplemented + DType_ref = Any + NDArray_ref = Any FuncType = Callable[[_GenericAlias], Any] GETATTR_NAMES = sorted(set(dir(np.ndarray)) - _GenericAlias._ATTR_EXCEPTIONS) @@ -41,6 +41,12 @@ class TestGenericAlias: @pytest.mark.parametrize("name,func", [ ("__init__", lambda n: n), + ("__init__", lambda n: _GenericAlias(np.ndarray, Any)), + ("__init__", lambda n: _GenericAlias(np.ndarray, (Any,))), + ("__init__", lambda n: _GenericAlias(np.ndarray, (Any, Any))), + ("__init__", lambda n: _GenericAlias(np.ndarray, T1)), + ("__init__", lambda n: _GenericAlias(np.ndarray, (T1,))), + ("__init__", lambda n: _GenericAlias(np.ndarray, (T1, T2))), ("__origin__", lambda n: n.__origin__), ("__args__", lambda n: n.__args__), ("__parameters__", lambda n: n.__parameters__), diff --git a/test_requirements.txt b/test_requirements.txt index e2a22464e..ca0edfbb4 100644 --- a/test_requirements.txt +++ b/test_requirements.txt @@ -1,10 +1,10 @@ cython==0.29.23 wheel<0.36.3 setuptools<49.2.0 -hypothesis==6.13.10 +hypothesis==6.13.14 pytest==6.2.4 pytz==2021.1 -pytest-cov==2.12.0 +pytest-cov==2.12.1 pickle5; python_version == '3.7' and platform_python_implementation != 'PyPy' # for numpy.random.test.test_extending cffi |