FIX: Transition scheme for safer in-place ufunc operations

In numpy 1.6 and earlier, if you do np.add(int_arr, float_arr, out=int_arr) or int_arr += float_arr then the result will be silently truncated to integer values. This often produces bugs, because it's easy to accidentally end up with an integer array and not realize it. Therefore, there seems to be consensus that we should switch to using same_kind casting by default for in-place ufunc operations. However, just switching this (as was done initially during the 1.7 development cycle) breaks a lot of code, which is rude and violates our deprecation policy. This commit instead adds a special temporary casting rule which acts like "unsafe", but also checks whether each operation would be allowed under "same_kind" rules and issues a DeprecationWarning if not. It also moves NPY_DEFAULT_ASSIGN_CASTING into the formal API instead of leaving it as a #define. This way we can change it later, and any code which references it and is compiled against this version of numpy will automatically switch to whatever we change it too. This avoids the situation where we want to remove the temporary magic value we're using to create DeprecationWarnings now, but can't because it would be an ABI break.
numpy · njsmith · Sep 24, 2012 · Sep 20, 2012 · Sep 20, 2012 · Sep 20, 2012
commit cea0a209875be753a74b8c7bb02aa9531726ee98
diff --git a/doc/release/1.7.0-notes.rst b/doc/release/1.7.0-notes.rst
@@ -33,10 +33,14 @@ np.diagonal, numpy 1.7 produces a FutureWarning if it detects
 that you may be attemping to write to such an array. See the documentation
 for array indexing for details.
 
-The default casting rule for UFunc out= parameters has been changed from
-'unsafe' to 'same_kind'.  Most usages which violate the 'same_kind'
-rule are likely bugs, so this change may expose previously undetected
-errors in projects that depend on NumPy.
+In a future version of numpy, the default casting rule for UFunc out=
+parameters will be changed from 'unsafe' to 'same_kind'. (This also
+applies to in-place operations like a += b, which is equivalent to
+np.add(a, b, out=a).) Most usages which violate the 'same_kind' rule
+are likely bugs, so this change may expose previously undetected
+errors in projects that depend on NumPy. In this version of numpy,
+such usages will continue to succeed, but will raise a
+DeprecationWarning.
 
 Full-array boolean indexing has been optimized to use a different,
 optimized code path.   This code path should produce the same results,

diff --git a/doc/source/reference/ufuncs.rst b/doc/source/reference/ufuncs.rst
@@ -309,6 +309,12 @@ advanced usage and will not typically be used.
     'equiv', 'safe', 'same_kind', or 'unsafe'. See :func:`can_cast` for
     explanations of the parameter values.
 
+    In a future version of numpy, this argument will default to
+    'same_kind'. As part of this transition, starting in version 1.7,
+    ufuncs will produce a DeprecationWarning for calls which are
+    allowed under the 'unsafe' rules, but not under the 'same_kind'
+    rules.
+
 *order*
 
     .. versionadded:: 1.6

diff --git a/numpy/core/code_generators/numpy_api.py b/numpy/core/code_generators/numpy_api.py
@@ -14,10 +14,12 @@
 
 multiarray_global_vars = {
     'NPY_NUMUSERTYPES':             7,
+    'NPY_DEFAULT_ASSIGN_CASTING':   292,
 }
 
 multiarray_global_vars_types = {
     'NPY_NUMUSERTYPES':             'int',
+    'NPY_DEFAULT_ASSIGN_CASTING':   'NPY_CASTING',
 }
 
 multiarray_scalar_bool_values = {

diff --git a/numpy/core/include/numpy/ndarraytypes.h b/numpy/core/include/numpy/ndarraytypes.h
@@ -199,11 +199,12 @@ typedef enum {
         /* Allow safe casts or casts within the same kind */
         NPY_SAME_KIND_CASTING=3,
         /* Allow any casts */
-        NPY_UNSAFE_CASTING=4
-} NPY_CASTING;
+        NPY_UNSAFE_CASTING=4,
 
-/* The default casting to use for typical assignment operations */
-#define NPY_DEFAULT_ASSIGN_CASTING NPY_SAME_KIND_CASTING
+        /* Temporary internal definition only, will be removed in upcoming
+           release, see below */
+        NPY_INTERNAL_UNSAFE_CASTING_BUT_WARN_UNLESS_SAME_KIND = 100,
+} NPY_CASTING;
 
 typedef enum {
         NPY_CLIP=0,

diff --git a/numpy/core/src/multiarray/common.c b/numpy/core/src/multiarray/common.c
@@ -13,6 +13,20 @@
 #include "common.h"
 #include "buffer.h"
 
+/* The casting to use for implicit assignment operations resulting from
+ * in-place operations (like +=) and out= arguments. (Notice that this
+ * variable is misnamed, but it's part of the public API so I'm not sure we
+ * can just change it. Maybe someone should try and see if anyone notices.
+ */
+/* In numpy 1.6 and earlier, this was NPY_UNSAFE_CASTING. In a future
+ * release, it will become NPY_SAME_KIND_CASTING.  Right now, during the
+ * transitional period, we continue to follow the NPY_UNSAFE_CASTING rules (to
+ * avoid breaking people's code), but we also check for whether the cast would
+ * be allowed under the NPY_SAME_KIND_CASTING rules, and if not we issue a
+ * warning (that people's code will be broken in a future release.)
+ */
+NPY_NO_EXPORT NPY_CASTING NPY_DEFAULT_ASSIGN_CASTING = NPY_INTERNAL_UNSAFE_CASTING_BUT_WARN_UNLESS_SAME_KIND;
+
 
 NPY_NO_EXPORT PyArray_Descr *
 _array_find_python_scalar_type(PyObject *op)

diff --git a/numpy/core/src/multiarray/convert_datatype.c b/numpy/core/src/multiarray/convert_datatype.c
@@ -503,12 +503,41 @@ type_num_unsigned_to_signed(int type_num)
     }
 }
 
+/* NOTE: once the UNSAFE_CASTING -> SAME_KIND_CASTING transition is over,
+ * we should remove NPY_INTERNAL_UNSAFE_CASTING_BUT_WARN_UNLESS_SAME_KIND
+ * and PyArray_CanCastTypeTo_impl should be renamed back to
+ * PyArray_CanCastTypeTo.
+ */
+static npy_bool
+PyArray_CanCastTypeTo_impl(PyArray_Descr *from, PyArray_Descr *to,
+                           NPY_CASTING casting);
+
 /*NUMPY_API
  * Returns true if data of type 'from' may be cast to data of type
  * 'to' according to the rule 'casting'.
  */
 NPY_NO_EXPORT npy_bool
 PyArray_CanCastTypeTo(PyArray_Descr *from, PyArray_Descr *to,
+                      NPY_CASTING casting)
+{
+    if (casting == NPY_INTERNAL_UNSAFE_CASTING_BUT_WARN_UNLESS_SAME_KIND) {
+        npy_bool unsafe_ok, same_kind_ok;
+        unsafe_ok = PyArray_CanCastTypeTo_impl(from, to, NPY_UNSAFE_CASTING);
+        same_kind_ok = PyArray_CanCastTypeTo_impl(from, to,
+                                                  NPY_SAME_KIND_CASTING);
+        if (unsafe_ok && !same_kind_ok) {
+            DEPRECATE("Implicitly casting between incompatible kinds. In "
+                      "a future numpy release, this will become an error. "
+                      "Use casting=\"unsafe\" if this is intentional.");
+        }
+        return unsafe_ok;
+    } else {
+        return PyArray_CanCastTypeTo_impl(from, to, casting);
+    }
+}
+
+static npy_bool
+PyArray_CanCastTypeTo_impl(PyArray_Descr *from, PyArray_Descr *to,
                                                     NPY_CASTING casting)
 {
     /* If unsafe casts are allowed */

diff --git a/numpy/core/tests/test_ufunc.py b/numpy/core/tests/test_ufunc.py
@@ -742,5 +742,23 @@ def t(expect, func, n, m):
             uf.accumulate(np.zeros((30, 30)), axis=0)
             uf.accumulate(np.zeros((0, 0)), axis=0)
 
+    def test_safe_casting(self):
+        # In old numpy's, any casting was allowed for in-place operations. In
+        # future numpy's, only same_kind casting will be allowed by
+        # default.
+        a = np.array([1, 2, 3], dtype=int)
+        # Non-in-place addition is fine
+        assert_array_equal(assert_no_warnings(np.add, a, 1.1),
+                           [2.1, 3.1, 4.1])
+        assert_warns(DeprecationWarning, np.add, a, 1.1, out=a)
+        assert_array_equal(a, [2, 3, 4])
+        def add_inplace(a, b):
+            a += b
+        assert_warns(DeprecationWarning, add_inplace, a, 1.1)
+        assert_array_equal(a, [3, 4, 5])
+        # Make sure that explicitly overriding the warning is allowed:
+        assert_no_warnings(np.add, a, 1.1, out=a, casting="unsafe")
+        assert_array_equal(a, [4, 5, 6])
+
 if __name__ == "__main__":
     run_module_suite()