Fixup: Do not deprecate generic python types

Add a comment that we can think about only allowing it for `dtype=...`
though...

7 files changed, 32 insertions, 23 deletions

diff --git a/doc/source/reference/arrays.dtypes.rst b/doc/source/reference/arrays.dtypes.rst
index 231707b11..71c2fa5a4 100644
--- a/doc/source/reference/arrays.dtypes.rst
+++ b/doc/source/reference/arrays.dtypes.rst
@@ -156,6 +156,14 @@ Array-scalar types
 
 Generic types
 
+    .. deprecated NumPy 1.19::
+
+        The use of generic types is deprecated. This is because it can be
+        unexpected in a context such as ``arr.astype(dtype=np.floating)``.
+        ``arr.astype(dtype=np.floating)`` which casts an array of ``float32``
+        to an array of ``float64``, even though ``float32`` is a subdtype of
+        ``np.floating``.
+
     The generic hierarchical type objects convert to corresponding
     type objects according to the associations:
 
@@ -179,8 +187,7 @@ Built-in Python types
     :class:`float`    :class:`float\_`
     :class:`complex`  :class:`cfloat`
     :class:`bytes`    :class:`bytes\_`
-    :class:`str`      :class:`bytes\_` (Python2) or :class:`unicode\_` (Python3)
-    :class:`unicode`  :class:`unicode\_`
+    :class:`str`      :class:`str\_`
     :class:`buffer`   :class:`void`
     (all others)      :class:`object_`
     ================  ===============
@@ -196,6 +203,11 @@ Built-in Python types
        >>> dt = np.dtype(int)     # Python-compatible integer
        >>> dt = np.dtype(object)  # Python object
 
+    .. note::
+
+        All other types map to ``object_`` for convenience. Code should expect
+        that such types may map to a specific (new) dtype in future the future.
+
 Types with ``.dtype``
 
     Any type object with a ``dtype`` attribute: The attribute will be
diff --git a/numpy/core/src/multiarray/descriptor.c b/numpy/core/src/multiarray/descriptor.c
index 0079aa86e..ffbb02ce8 100644
--- a/numpy/core/src/multiarray/descriptor.c
+++ b/numpy/core/src/multiarray/descriptor.c
@@ -1436,13 +1436,13 @@ _convert_from_type(PyObject *obj) {
         }
         Py_DECREF(ret);
 
-        if (DEPRECATE("Converting a type/class not known to NumPy to a dtype "
-                      "currently always returns `np.dtype(object)`. This loses "
-                      "the type information and is deprecated.") < 0) {
-            return NULL;
-        }
-
-        /* All other classes are treated as object */
+        /*
+         * All other classes are treated as object. This can be convenient
+         * to convey an intention of using it for a specific python type
+         * and possibly allow future enforcement. It may make sense to
+         * only allow this only within `dtype=...` keyword argument context
+         * in the future.
+         */
         return PyArray_DescrFromType(NPY_OBJECT);
     }
 }
diff --git a/numpy/core/tests/test_deprecations.py b/numpy/core/tests/test_deprecations.py
index a89fc70d5..d2cf315a9 100644
--- a/numpy/core/tests/test_deprecations.py
+++ b/numpy/core/tests/test_deprecations.py
@@ -548,7 +548,7 @@ def test_deprecate_ragged_arrays():
         np.array(arg)
 
 
-class TestAbstractDTypeCoercion(_DeprecationTestCase):
+class TestDTypeCoercion(_DeprecationTestCase):
     # 2020-02-06 1.19.0
     message = "Converting .* to a dtype .*is deprecated"
     deprecated_types = [
@@ -558,9 +558,6 @@ class TestAbstractDTypeCoercion(_DeprecationTestCase):
         np.integer, np.unsignedinteger, np.signedinteger,
         # character is a deprecated S1 special case:
         np.character,
-        # Test python types that do not map to a NumPy type cleanly
-        # (currenlty map to object)
-        type, list, tuple, dict,
     ]
 
     def test_dtype_coercion(self):
@@ -576,3 +573,7 @@ class TestAbstractDTypeCoercion(_DeprecationTestCase):
         for group in np.sctypes.values():
             for scalar_type in group:
                 self.assert_not_deprecated(np.dtype, args=(scalar_type,))
+
+        for scalar_type in [type, dict, list, tuple]:
+            # Typical python types are coerced to object currently:
+            self.assert_not_deprecated(np.dtype, args=(scalar_type,))
diff --git a/numpy/core/tests/test_multiarray.py b/numpy/core/tests/test_multiarray.py
index f6181c900..ad38911cb 100644
--- a/numpy/core/tests/test_multiarray.py
+++ b/numpy/core/tests/test_multiarray.py
@@ -6456,7 +6456,7 @@ class TestRepeat:
 NEIGH_MODE = {'zero': 0, 'one': 1, 'constant': 2, 'circular': 3, 'mirror': 4}
 
 
-@pytest.mark.parametrize('dt', [float, object], ids=['float', 'object'])
+@pytest.mark.parametrize('dt', [float, Decimal], ids=['float', 'object'])
 class TestNeighborhoodIter:
     # Simple, 2d tests
     def test_simple2d(self, dt):
diff --git a/numpy/core/tests/test_numeric.py b/numpy/core/tests/test_numeric.py
index 0f7ac036f..3bc4cd187 100644
--- a/numpy/core/tests/test_numeric.py
+++ b/numpy/core/tests/test_numeric.py
@@ -2543,7 +2543,7 @@ class TestCorrelate:
         assert_array_almost_equal(z, self.zs)
 
     def test_object(self):
-        self._setup(object)
+        self._setup(Decimal)
         z = np.correlate(self.x, self.y, 'full')
         assert_array_almost_equal(z, self.z1)
         z = np.correlate(self.y, self.x, 'full')
diff --git a/numpy/core/tests/test_numerictypes.py b/numpy/core/tests/test_numerictypes.py
index 22fc2ed58..c72d13947 100644
--- a/numpy/core/tests/test_numerictypes.py
+++ b/numpy/core/tests/test_numerictypes.py
@@ -3,8 +3,7 @@ import itertools
 
 import pytest
 import numpy as np
-from numpy.testing import (
-    assert_, assert_equal, assert_raises, assert_warns, IS_PYPY)
+from numpy.testing import assert_, assert_equal, assert_raises, IS_PYPY
 
 # This is the structure of the table used for plain objects:
 #
@@ -452,11 +451,8 @@ class Test_sctype2char:
 
     def test_other_type(self):
         assert_equal(np.sctype2char(float), 'd')
-        assert_equal(np.sctype2char(object), 'O')
-        with assert_warns(DeprecationWarning):
-            assert_equal(np.sctype2char(list), 'O')
-        with assert_warns(DeprecationWarning):
-            assert_equal(np.sctype2char(np.ndarray), 'O')
+        assert_equal(np.sctype2char(list), 'O')
+        assert_equal(np.sctype2char(np.ndarray), 'O')
 
     def test_third_party_scalar_type(self):
         from numpy.core._rational_tests import rational
diff --git a/numpy/core/tests/test_regression.py b/numpy/core/tests/test_regression.py
index 50a543625..321723b9b 100644
--- a/numpy/core/tests/test_regression.py
+++ b/numpy/core/tests/test_regression.py
@@ -1152,7 +1152,7 @@ class TestRegression:
         assert_(dat.argmax(1).info == 'jubba')
         assert_(dat.argmin(1).info == 'jubba')
         assert_(dat.argsort(1).info == 'jubba')
-        assert_(dat.astype(object).info == 'jubba')
+        assert_(dat.astype(TestArray).info == 'jubba')
         assert_(dat.byteswap().info == 'jubba')
         assert_(dat.clip(2, 7).info == 'jubba')
         assert_(dat.compress([0, 1, 1]).info == 'jubba')