Merge pull request #18671 from seberg/backport-small-pytest-leaks-fixes

BUG: Fix small issues found with pytest-leaks

numpy/core/src/multiarray/arrayfunction_override.c

@@ -341,18 +341,23 @@ array_implement_array_function(
         return NULL;
     }
 
-    /* Remove `like=` kwarg, which is NumPy-exclusive and thus not present
+    /*
+     * Remove `like=` kwarg, which is NumPy-exclusive and thus not present
      * in downstream libraries. If `like=` is specified but doesn't
      * implement `__array_function__`, raise a `TypeError`.
      */
     if (kwargs != NULL && PyDict_Contains(kwargs, npy_ma_str_like)) {
         PyObject *like_arg = PyDict_GetItem(kwargs, npy_ma_str_like);
-        if (like_arg && !get_array_function(like_arg)) {
-            return PyErr_Format(PyExc_TypeError,
-                    "The `like` argument must be an array-like that implements "
-                    "the `__array_function__` protocol.");
+        if (like_arg != NULL) {
+            PyObject *tmp_has_override = get_array_function(like_arg);
+            if (tmp_has_override == NULL) {
+                return PyErr_Format(PyExc_TypeError,
+                        "The `like` argument must be an array-like that "
+                        "implements the `__array_function__` protocol.");
+            }
+            Py_DECREF(tmp_has_override);
+            PyDict_DelItem(kwargs, npy_ma_str_like);
         }
-        PyDict_DelItem(kwargs, npy_ma_str_like);
     }
 
     PyObject *res = array_implement_array_function_internal(
@@ -387,14 +392,18 @@ array_implement_c_array_function_creation(
         return Py_NotImplemented;
     }
 
-    PyObject *like_arg = PyDict_GetItem(kwargs, npy_ma_str_like);
+    PyObject *like_arg = PyDict_GetItemWithError(kwargs, npy_ma_str_like);
     if (like_arg == NULL) {
         return NULL;
     }
-    else if (!get_array_function(like_arg)) {
-        return PyErr_Format(PyExc_TypeError,
-                "The `like` argument must be an array-like that implements "
-                "the `__array_function__` protocol.");
+    else {
+        PyObject *tmp_has_override = get_array_function(like_arg);
+        if (tmp_has_override == NULL) {
+            return PyErr_Format(PyExc_TypeError,
+                    "The `like` argument must be an array-like that "
+                    "implements the `__array_function__` protocol.");
+        }
+        Py_DECREF(tmp_has_override);
     }
     PyObject *relevant_args = PyTuple_Pack(1, like_arg);
     PyDict_DelItem(kwargs, npy_ma_str_like);

numpy/core/src/multiarray/convert_datatype.c

@@ -902,8 +902,7 @@ PyArray_FindConcatenationDescriptor(
                     "The dtype `%R` is not a valid dtype for concatenation "
                     "since it is a subarray dtype (the subarray dimensions "
                     "would be added as array dimensions).", result);
-            Py_DECREF(result);
-            return NULL;
+            Py_SETREF(result, NULL);
         }
         goto finish;
     }

numpy/core/src/multiarray/multiarraymodule.c

@@ -2100,6 +2100,7 @@ array_fromstring(PyObject *NPY_UNUSED(ignored), PyObject *args, PyObject *keywds
     array_function_result = array_implement_c_array_function_creation(
             "fromstring", args, keywds);
     if (array_function_result != Py_NotImplemented) {
+        Py_XDECREF(descr);
         return array_function_result;
     }
 

numpy/core/src/umath/_umath_tests.c.src

@@ -621,6 +621,7 @@ UMath_Tests_test_dispatch(PyObject *NPY_UNUSED(dummy), PyObject *NPY_UNUSED(dumm
         goto err;
     }
     NPY_CPU_DISPATCH_CALL_ALL(_umath_tests_dispatch_attach, (item));
+    Py_SETREF(item, NULL);
     if (PyErr_Occurred()) {
         goto err;
     }

numpy/core/src/umath/_umath_tests.dispatch.c

@@ -29,5 +29,6 @@ void NPY_CPU_DISPATCH_CURFX(_umath_tests_dispatch_attach)(PyObject *list)
     PyObject *item = PyUnicode_FromString(NPY_TOSTRING(NPY_CPU_DISPATCH_CURFX(func)));
     if (item) {
         PyList_Append(list, item);
+        Py_DECREF(item);
     }
 }

numpy/core/src/umath/ufunc_object.c

@@ -5495,6 +5495,7 @@ ufunc_outer(PyUFuncObject *ufunc, PyObject *args, PyObject *kwds)
         /* DEPRECATED 2020-05-13, NumPy 1.20 */
         if (PyErr_WarnFormat(PyExc_DeprecationWarning, 1,
                 matrix_deprecation_msg, ufunc->name, "first") < 0) {
+            Py_DECREF(tmp);
             return NULL;
         }
         ap1 = (PyArrayObject *) PyArray_FromObject(tmp, NPY_NOTYPE, 0, 0);
@@ -5514,6 +5515,7 @@ ufunc_outer(PyUFuncObject *ufunc, PyObject *args, PyObject *kwds)
         /* DEPRECATED 2020-05-13, NumPy 1.20 */
         if (PyErr_WarnFormat(PyExc_DeprecationWarning, 1,
                 matrix_deprecation_msg, ufunc->name, "second") < 0) {
+            Py_DECREF(tmp);
             Py_DECREF(ap1);
             return NULL;
         }
@@ -5538,7 +5540,7 @@ ufunc_outer(PyUFuncObject *ufunc, PyObject *args, PyObject *kwds)
                 "maximum supported dimension for an ndarray is %d, but "
                 "`%s.outer()` result would have %d.",
                 NPY_MAXDIMS, ufunc->name, newdims.len);
-        return NPY_FAIL;
+        goto fail;
     }
     if (newdims.ptr == NULL) {
         goto fail;

numpy/core/tests/test_overrides.py

@@ -1,5 +1,6 @@
 import inspect
 import sys
+import os
 import tempfile
 from io import StringIO
 from unittest import mock
@@ -558,18 +559,19 @@ def test_array_like_fromfile(self, numpy_ref):
 
         data = np.random.random(5)
 
-        fname = tempfile.mkstemp()[1]
-        data.tofile(fname)
-
-        array_like = np.fromfile(fname, like=ref)
-        if numpy_ref is True:
-            assert type(array_like) is np.ndarray
-            np_res = np.fromfile(fname, like=ref)
-            assert_equal(np_res, data)
-            assert_equal(array_like, np_res)
-        else:
-            assert type(array_like) is self.MyArray
-            assert array_like.function is self.MyArray.fromfile
+        with tempfile.TemporaryDirectory() as tmpdir:
+            fname = os.path.join(tmpdir, "testfile")
+            data.tofile(fname)
+
+            array_like = np.fromfile(fname, like=ref)
+            if numpy_ref is True:
+                assert type(array_like) is np.ndarray
+                np_res = np.fromfile(fname, like=ref)
+                assert_equal(np_res, data)
+                assert_equal(array_like, np_res)
+            else:
+                assert type(array_like) is self.MyArray
+                assert array_like.function is self.MyArray.fromfile
 
     @requires_array_function
     def test_exception_handling(self):