Adjust was_copied variable names

Author: mtsokol

numpy/_core/src/multiarray/array_coercion.c

@@ -99,7 +99,7 @@ enum _dtype_discovery_flags {
     DISCOVER_TUPLES_AS_ELEMENTS = 1 << 4,
     MAX_DIMS_WAS_REACHED = 1 << 5,
     DESCRIPTOR_WAS_SET = 1 << 6,
-    COPY_WAS_CREATED = 1 << 7,
+    COPY_WAS_CREATED_BY__ARRAY__ = 1 << 7,
 };
 
 
@@ -1028,18 +1028,18 @@ PyArray_DiscoverDTypeAndShape_Recursive(
             /* __array__ may be passed the requested descriptor if provided */
             requested_descr = *out_descr;
         }
-        int was_copied = 0;
+        int was_copied_by__array__ = 0;
         arr = (PyArrayObject *)_array_from_array_like(obj,
-                requested_descr, 0, NULL, copy, &was_copied);
+                requested_descr, 0, NULL, copy, &was_copied_by__array__);
         if (arr == NULL) {
             return -1;
         }
         else if (arr == (PyArrayObject *)Py_NotImplemented) {
             Py_DECREF(arr);
             arr = NULL;
         }
-        if (was_copied == 1) {
-            *flags |= COPY_WAS_CREATED;
+        if (was_copied_by__array__ == 1) {
+            *flags |= COPY_WAS_CREATED_BY__ARRAY__;
         }
     }
     if (arr != NULL) {
@@ -1231,8 +1231,8 @@ PyArray_DiscoverDTypeAndShape_Recursive(
  *        to choose a default.
  * @param copy Specifies the copy behavior. -1 is corresponds to copy=None,
  *        0 to copy=False, and 1 to copy=True in the Python API.
- * @param was_copied Set to 1 if it can be assumed that a copy was made
- *        by implementor.
+ * @param was_copied_by__array__ Set to 1 if it can be assumed that a copy was
+ *        made by implementor.
  * @return dimensions of the discovered object or -1 on error.
  *         WARNING: If (and only if) the output is a single array, the ndim
  *         returned _can_ exceed the maximum allowed number of dimensions.
@@ -1245,7 +1245,7 @@ PyArray_DiscoverDTypeAndShape(
         npy_intp out_shape[NPY_MAXDIMS],
         coercion_cache_obj **coercion_cache,
         PyArray_DTypeMeta *fixed_DType, PyArray_Descr *requested_descr,
-        PyArray_Descr **out_descr, int copy, int *was_copied)
+        PyArray_Descr **out_descr, int copy, int *was_copied_by__array__)
 {
     coercion_cache_obj **coercion_cache_head = coercion_cache;
     *coercion_cache = NULL;
@@ -1298,8 +1298,8 @@ PyArray_DiscoverDTypeAndShape(
         goto fail;
     }
 
-    if (was_copied != NULL && flags & COPY_WAS_CREATED) {
-        *was_copied = 1;
+    if (was_copied_by__array__ != NULL && flags & COPY_WAS_CREATED_BY__ARRAY__) {
+        *was_copied_by__array__ = 1;
     }
 
     if (NPY_UNLIKELY(flags & FOUND_RAGGED_ARRAY)) {

numpy/_core/src/multiarray/array_coercion.h

@@ -40,7 +40,7 @@ PyArray_DiscoverDTypeAndShape(
         npy_intp out_shape[NPY_MAXDIMS],
         coercion_cache_obj **coercion_cache,
         PyArray_DTypeMeta *fixed_DType, PyArray_Descr *requested_descr,
-        PyArray_Descr **out_descr, int copy, int *was_copied);
+        PyArray_Descr **out_descr, int copy, int *was_copied_by__array__);
 
 NPY_NO_EXPORT PyObject *
 _discover_array_parameters(PyObject *NPY_UNUSED(self),

numpy/_core/src/multiarray/ctors.c

@@ -1429,8 +1429,8 @@ _array_from_buffer_3118(PyObject *memoryview)
  * @param writeable whether the result must be writeable.
  * @param context Unused parameter, must be NULL (should be removed later).
  * @param copy Specifies the copy behavior.
- * @param was_copied Set to 1 if it can be assumed that a copy was made
- *        by implementor.
+ * @param was_copied_by__array__ Set to 1 if it can be assumed that a copy
+ *        was made by implementor.
  *
  * @returns The array object, Py_NotImplemented if op is not array-like,
  *          or NULL with an error set. (A new reference to Py_NotImplemented
@@ -1439,7 +1439,7 @@ _array_from_buffer_3118(PyObject *memoryview)
 NPY_NO_EXPORT PyObject *
 _array_from_array_like(PyObject *op,
         PyArray_Descr *requested_dtype, npy_bool writeable, PyObject *context,
-        int copy, int *was_copied) {
+        int copy, int *was_copied_by__array__) {
     PyObject* tmp;
 
     /*
@@ -1487,7 +1487,8 @@ _array_from_array_like(PyObject *op,
     }
 
     if (tmp == Py_NotImplemented) {
-        tmp = PyArray_FromArrayAttr_int(op, requested_dtype, copy, was_copied);
+        tmp = PyArray_FromArrayAttr_int(
+                op, requested_dtype, copy, was_copied_by__array__);
         if (tmp == NULL) {
             return NULL;
         }
@@ -1574,7 +1575,7 @@ PyArray_FromAny_int(PyObject *op, PyArray_Descr *in_descr,
 
     // Default is copy = None
     int copy = -1;
-    int was_copied = 0;
+    int was_copied_by__array__ = 0;
 
     if (flags & NPY_ARRAY_ENSURENOCOPY) {
         copy = 0;
@@ -1583,7 +1584,8 @@ PyArray_FromAny_int(PyObject *op, PyArray_Descr *in_descr,
     }
 
     ndim = PyArray_DiscoverDTypeAndShape(
-            op, NPY_MAXDIMS, dims, &cache, in_DType, in_descr, &dtype, copy, &was_copied);
+            op, NPY_MAXDIMS, dims, &cache, in_DType, in_descr, &dtype,
+            copy, &was_copied_by__array__);
 
     if (ndim < 0) {
         return NULL;
@@ -1620,7 +1622,7 @@ PyArray_FromAny_int(PyObject *op, PyArray_Descr *in_descr,
         assert(cache->converted_obj == op);
         arr = (PyArrayObject *)(cache->arr_or_sequence);
         /* we may need to cast or assert flags (e.g. copy) */
-        if (was_copied == 1 && flags & NPY_ARRAY_ENSURECOPY) {
+        if (was_copied_by__array__ == 1 && flags & NPY_ARRAY_ENSURECOPY) {
             flags = flags & ~NPY_ARRAY_ENSURECOPY;
             flags = flags | NPY_ARRAY_ENSURENOCOPY;
         }
@@ -2495,14 +2497,14 @@ check_or_clear_and_warn_error_if_due_to_copy_kwarg(PyObject *kwnames)
  *        NOTE: For copy == -1 it passes `op.__array__(copy=None)`,
  *              for copy == 0, `op.__array__(copy=False)`, and
  *              for copy == 1, `op.__array__(copy=True).
- * @param was_copied Set to 1 if it can be assumed that a copy was made
- *        by implementor.
+ * @param was_copied_by__array__ Set to 1 if it can be assumed that a copy
+ *        was made by implementor.
  * @returns NotImplemented if `__array__` is not defined or a NumPy array
  *          (or subclass).  On error, return NULL.
  */
 NPY_NO_EXPORT PyObject *
-PyArray_FromArrayAttr_int(
-        PyObject *op, PyArray_Descr *descr, int copy, int *was_copied)
+PyArray_FromArrayAttr_int(PyObject *op, PyArray_Descr *descr, int copy,
+                          int *was_copied_by__array__)
 {
     PyObject *new;
     PyObject *array_meth;
@@ -2589,9 +2591,10 @@ PyArray_FromArrayAttr_int(
         Py_DECREF(new);
         return NULL;
     }
-    if (was_copied != NULL && copy == 1 && must_copy_but_copy_kwarg_unimplemented == 0) {
+    if (was_copied_by__array__ != NULL && copy == 1 &&
+        must_copy_but_copy_kwarg_unimplemented == 0) {
         /* We can assume that a copy was made */
-        *was_copied = 1;
+        *was_copied_by__array__ = 1;
     }
 
     return new;

numpy/_core/src/multiarray/ctors.h

@@ -54,7 +54,7 @@ PyArray_New(
 NPY_NO_EXPORT PyObject *
 _array_from_array_like(PyObject *op,
         PyArray_Descr *requested_dtype, npy_bool writeable, PyObject *context,
-        int copy, int *was_copied);
+        int copy, int *was_copied_by__array__);
 
 NPY_NO_EXPORT PyObject *
 PyArray_FromAny_int(PyObject *op, PyArray_Descr *in_descr,
@@ -84,8 +84,8 @@ NPY_NO_EXPORT PyObject *
 PyArray_FromInterface(PyObject *input);
 
 NPY_NO_EXPORT PyObject *
-PyArray_FromArrayAttr_int(
-        PyObject *op, PyArray_Descr *descr, int copy, int *was_copied);
+PyArray_FromArrayAttr_int(PyObject *op, PyArray_Descr *descr, int copy,
+                          int *was_copied_by__array__);
 
 NPY_NO_EXPORT PyObject *
 PyArray_FromArrayAttr(PyObject *op, PyArray_Descr *typecode,

numpy/_core/tests/test_multiarray.py

@@ -8502,7 +8502,6 @@ def __array__(self, dtype=None):
                     match=r"Unable to avoid copy(.|\n)*numpy_2_0_migration_guide.html"):
                 np.array(a, copy=False)
 
-    @pytest.mark.skipif(IS_PYPY, reason="PyPy copies differently")
     def test___array__copy_once(self):
         size = 100
         base_arr = np.zeros((size, size))