MAINT: Fix typos

doc/neps/index.rst

@@ -6,7 +6,7 @@ This page provides an overview of development priorities for NumPy.
 Specifically, it contains a roadmap with a higher-level overview, as
 well as NumPy Enhancement Proposals (NEPs)—suggested changes
 to the library—in various stages of discussion or completion.
-See :doc:`nep-0000` for more informations about NEPs.
+See :doc:`nep-0000` for more information about NEPs.
 
 Roadmap
 -------

doc/source/conf.py

@@ -70,7 +70,7 @@ def replace_scalar_type_names():
         if sys.implementation.name == 'cpython':
             c_typ.tp_name = _name_cache[typ] = b"numpy." + name.encode('utf8')
         else:
-            # It is not guarenteed that the c_typ has this model on other
+            # It is not guaranteed that the c_typ has this model on other
             # implementations
             _name_cache[typ] = b"numpy." + name.encode('utf8')
 

doc/source/reference/c-api/generalized-ufuncs.rst

@@ -63,7 +63,7 @@ distances among them. The output dimension ``p`` must therefore be equal to
 in an output array of the right size. If the size of a core dimension of an output
 cannot be determined from a passed in input or output array, an error will be
 raised.  This can be changed by defining a ``PyUFunc_ProcessCoreDimsFunc`` function
-and assigning it to the ``proces_core_dims_func`` field of the ``PyUFuncObject``
+and assigning it to the ``process_core_dims_func`` field of the ``PyUFuncObject``
 structure.  See below for more details.
 
 Note: Prior to NumPy 1.10.0, less strict checks were in place: missing core

meson_cpu/meson.build

@@ -203,7 +203,7 @@ foreach opt_name, conf : parse_options
           warning('CPU Feature "@0@" is no longer explicitly supported, redirecting to "@1@".'.format(tok, ntok))
         endif
         warning('Please check the latest documentation for build options.')
-        if ntok == '' or not append # redirected features not safe to be execluded
+        if ntok == '' or not append # redirected features not safe to be excluded
           continue
         endif
         tok = ntok

numpy/__init__.pyi

@@ -3774,7 +3774,7 @@ class generic(_ArrayOrScalarCommon, Generic[_ItemT_co]):
     def setfield(self: Never, val: Never, /, dtype: Never, offset: L[0] = 0) -> None: ...  # type: ignore[misc]
     def searchsorted(self: Never, v: Never, /, side: L["left"] = "left", sorter: None = None) -> Never: ...  # type: ignore[misc]
 
-    # NOTE: this wont't raise, but won't do anything either
+    # NOTE: this won't raise, but won't do anything either
     @overload
     @deprecated("Resizing a NumPy generic inplace has been deprecated in NumPy 2.5")
     def resize(self, /, *, refcheck: py_bool = True) -> None: ...

numpy/_core/einsumfunc.py

@@ -1188,14 +1188,14 @@ def bmm_einsum(eq, a, b, out=None, **kwargs):
 
     # prepare left
     if eq_a is not None:
-        # diagonals, sums, and tranpose
+        # diagonals, sums, and transpose
         a = c_einsum(eq_a, a)
     if new_shape_a is not None:
         a = reshape(a, new_shape_a)
 
     # prepare right
     if eq_b is not None:
-        # diagonals, sums, and tranpose
+        # diagonals, sums, and transpose
         b = c_einsum(eq_b, b)
     if new_shape_b is not None:
         b = reshape(b, new_shape_b)

numpy/_core/include/numpy/dtype_api.h

@@ -495,7 +495,7 @@ typedef PyArray_Descr *(PyArrayDTypeMeta_EnsureCanonical)(PyArray_Descr *dtype);
 typedef PyArray_Descr *(PyArrayDTypeMeta_FinalizeDescriptor)(PyArray_Descr *dtype);
 
 /*
- * Constants that can be queried and used e.g. by reduce identies defaults.
+ * Constants that can be queried and used e.g. by reducing identities defaults.
  * These are also used to expose .finfo and .iinfo for example.
  */
 /* Numerical constants */

numpy/_core/src/common/npy_cpu_dispatch.h

@@ -8,7 +8,7 @@
  */
 #include "npy_cpu_features.h" // NPY_CPU_HAVE
 /**
- *  This header genereated by the build system and contains:
+ *  This header was generated by the build system and contains:
  *
  *   - Headers for platform-specific instruction sets.
  *   - Helper macros that encapsulate enabled features through user-defined build options
@@ -79,7 +79,7 @@ npy_cpu_dispatch_trace(const char *func_name, const char *signature,
  * Extract the enabled CPU targets from the generated configuration file.
  *
  * This macro is used to extract the enabled CPU targets from the generated configuration file,
- * which is derived from 'meson.multi_targets()' or from 'disutils.CCompilerOpt' in the case of using distutils.
+ * which is derived from 'meson.multi_targets()' or from 'disuttils.CCompilerOpt' in the case of using distutils.
  * It then calls 'npy_cpu_dispatch_trace()' to insert a new item into the '__cpu_targets_info__' dictionary,
  * based on the provided FUNC_NAME and SIGNATURE.
  *

numpy/_core/src/common/npy_cpu_features.c

@@ -502,7 +502,7 @@ npy__cpu_init_features(void)
     // long mode only
     npy__cpu_have[NPY_CPU_FEATURE_LAHF]  = (reg[2] & (1 << 0)) != 0;
 #else
-    // alawys available
+    // always available
     npy__cpu_have[NPY_CPU_FEATURE_LAHF]  = 1;
 #endif
     npy__cpu_have[NPY_CPU_FEATURE_LZCNT] = (reg[2] & (1 << 5))  != 0;

numpy/_core/src/common/simd/lsx/memory.h

@@ -528,7 +528,7 @@ NPYV_IMPL_LSX_REST_PARTIAL_TYPES_PAIR(u64, s64)
 NPYV_IMPL_LSX_REST_PARTIAL_TYPES_PAIR(f64, s64)
 
 /************************************************************
- *  de-interlave load / interleave contiguous store
+ *  de-interleave load / interleave contiguous store
  ************************************************************/
 // two channels
 #define NPYV_IMPL_LSX_MEM_INTERLEAVE(SFX, ZSFX)                              \

numpy/_core/src/common/simd/simd.hpp

@@ -39,7 +39,7 @@
 
 // Indicates if the SIMD operations are available for float16.
 #define NPY_HWY_F16 (NPY_HWY && HWY_HAVE_FLOAT16)
-// Note: Highway requires SIMD extentions with native float32 support, so we don't need
+// Note: Highway requires SIMD extensions with native float32 support, so we don't need
 // to check for it.
 
 // Indicates if the SIMD operations are available for float64.
@@ -64,7 +64,7 @@ namespace simd {
 /// We can not import all the symbols from the HWY_NAMESPACE because it will
 /// conflict with the existing symbols in the numpy namespace.
 namespace hn = hwy::HWY_NAMESPACE;
-// internaly used by the template header
+// internally used by the template header
 template <typename TLane>
 using _Tag = hn::ScalableTag<TLane>;
 #endif

numpy/_core/src/multiarray/array_method.c

@@ -567,7 +567,7 @@ boundarraymethod_dealloc(PyObject *self)
  *       changes and especially testing if they were to be made public.
  */
 static PyObject *
-boundarraymethod__resolve_descripors(
+boundarraymethod__resolve_descriptors(
         PyBoundArrayMethodObject *self, PyObject *descr_tuple)
 {
     int nin = self->method->nin;
@@ -957,7 +957,7 @@ PyArrayMethod_GetMaskedStridedLoop(
 
 
 PyMethodDef boundarraymethod_methods[] = {
-    {"_resolve_descriptors", (PyCFunction)boundarraymethod__resolve_descripors,
+    {"_resolve_descriptors", (PyCFunction)boundarraymethod__resolve_descriptors,
      METH_O, "Resolve the given dtypes."},
     {"_simple_strided_call", (PyCFunction)boundarraymethod__simple_strided_call,
      METH_O, "call on 1-d inputs and pre-allocated outputs (single call)."},

numpy/_core/src/multiarray/arraytypes.c.src

@@ -4380,7 +4380,7 @@ static int
 
 /* 
 Keeping Half macros consistent with standard C 
-Refernce: https://en.cppreference.com/w/c/types/limits.html
+Reference: https://en.cppreference.com/w/c/types/limits.html
 */
 #define HALF_MAX 31743       /* Bit pattern for 65504.0 */
 #define HALF_MIN 1024        /* Bit pattern for smallest positive normal: 2^-14 */
@@ -4476,7 +4476,7 @@ static int
             /*
             Definition: Minimum negative integer such that FLT_RADIX raised by power one less than that integer is a normalized float, double and long double respectively
 
-            refernce: https://en.cppreference.com/w/c/types/limits.html
+            reference: https://en.cppreference.com/w/c/types/limits.html
             */
             *(npy_intp *)ptr = @ABB@_MIN_EXP - 1;
             return 1;

numpy/_core/src/multiarray/calculation.c

@@ -654,7 +654,7 @@ PyArray_Round(PyArrayObject *a, int decimals, PyArrayObject *out)
         op2 = n_ops.multiply;
         if (decimals == INT_MIN) {
             // not technically correct but it doesn't matter because no one in
-            // this millenium is using floating point numbers with enough
+            // this milllenium is using floating point numbers with enough
             // accuracy for this to matter
             decimals = INT_MAX;
         }

numpy/_core/src/multiarray/ctors.c

@@ -1060,7 +1060,7 @@ PyArray_NewFromDescrAndBase(
  *             NPY_KEEPORDER - Keeps the axis ordering of prototype.
  * descr     - If not NULL, overrides the data type of the result.
  * dtype     - If not NULL and if descr is NULL, overrides the data type
-               of the result, so long as dtype is non-parameteric
+               of the result, so long as dtype is non-parametric
  * ndim      - If not -1, overrides the shape of the result.
  * dims      - If ndim is not -1, overrides the shape of the result.
  * subok     - If 1, use the prototype's array subtype, otherwise

numpy/_core/src/multiarray/mapping.c

@@ -2755,7 +2755,7 @@ indexing_error:
  *
  * @param Index information filled by prepare_index.
  * @param Number of indices (gotten through prepare_index).
- * @param Kind of index (gotten through preprare_index).
+ * @param Kind of index (gotten through prepare_index).
  * @param NpyIter flags for an extra array. If 0 assume that there is no
  *        extra operand. NPY_ITER_ALLOCATE can make sense here.
  * @param Array being indexed

numpy/_core/src/multiarray/scalarapi.c

@@ -346,7 +346,7 @@ PyArray_DescrFromTypeObject(PyObject *type)
         _PyArray_LegacyDescr *conv = NULL;
         int res = PyObject_GetOptionalAttr(type, npy_interned_str.dtype, &attr);
         if (res < 0) {
-            return NULL;  // Should be a rather criticial error, so just fail.
+            return NULL;  // Should be a rather critical error, so just fail.
         }
         if (res == 1) {
             if (!PyArray_DescrCheck(attr)) {

numpy/_core/src/multiarray/scalartypes.c.src

@@ -2128,7 +2128,7 @@ static PyObject *
 gentype___copy__(PyObject *self)
 {
     // scalars are immutable, so we can return a new reference
-    // the only expections are scalars with void dtype
+    // the only exceptions are scalars with void dtype
     if (PyObject_IsInstance(self, (PyObject *)&PyVoidArrType_Type)) {
         // path via array
         return gentype_generic_method(self, NULL, NULL, "__copy__");
@@ -2142,7 +2142,7 @@ gentype___deepcopy__(PyObject *self, PyObject *args)
     // note: maybe the signature needs to be updated as __deepcopy__ can accept the keyword memo
 
     // scalars are immutable, so we can return a new reference
-    // the only expections are scalars with void dtype
+    // the only exceptions are scalars with void dtype
     // if the number of arguments is not 1, we let gentype_generic_method do the
     // error handling
     if (PyObject_IsInstance(self, (PyObject *)&PyVoidArrType_Type) || (PyTuple_Size(args)!=1)) {

numpy/_core/src/npysort/binsearch.cpp

@@ -123,7 +123,7 @@ binsearch(const char *arr, const char *key, char *ret, npy_intp arr_len,
 
     Optimization: we unroll the first iteration for the following reasons:
         1. ret is not initialized with the bases, so we save |keys| writes
-        by not having to intialize it with 0s.
+        by not having to initialize it with 0s.
         2. By assuming the initial base for every key is 0, we also save
         |keys| reads.
         3. In the first iteration, all elements are compared against the

numpy/_core/src/umath/legacy_array_method.c

@@ -367,7 +367,7 @@ PyArray_NewLegacyWrappingArrayMethod(PyUFuncObject *ufunc,
         flags = _NPY_METH_FORCE_CAST_INPUTS;
     }
 
-    PyArrayMethod_GetReductionInitial *get_reduction_intial = NULL;
+    PyArrayMethod_GetReductionInitial *get_reduction_initial = NULL;
     if (ufunc->nin == 2 && ufunc->nout == 1) {
         npy_bool reorderable = NPY_FALSE;
         PyObject *identity_obj = PyUFunc_GetDefaultIdentity(
@@ -385,7 +385,7 @@ PyArray_NewLegacyWrappingArrayMethod(PyUFuncObject *ufunc,
             flags |= NPY_METH_IS_REORDERABLE;
         }
         if (identity_obj != Py_None) {
-            get_reduction_intial = &get_initial_from_ufunc;
+            get_reduction_initial = &get_initial_from_ufunc;
         }
     }
     for (int i = 0; i < ufunc->nin+ufunc->nout; i++) {
@@ -401,7 +401,7 @@ PyArray_NewLegacyWrappingArrayMethod(PyUFuncObject *ufunc,
     PyType_Slot slots[4] = {
         {NPY_METH_get_loop, &get_wrapped_legacy_ufunc_loop},
         {NPY_METH_resolve_descriptors, &simple_legacy_resolve_descriptors},
-        {NPY_METH_get_reduction_initial, get_reduction_intial},
+        {NPY_METH_get_reduction_initial, get_reduction_initial},
         {0, NULL},
     };
     if (any_output_flexible) {

numpy/_core/src/umath/special_integer_comparisons.cpp

@@ -141,7 +141,7 @@ get_value_range(PyObject *value, int type_num, int *range)
     }
     else {
         /*
-        * If we are checking for unisgned long long, the value may be larger
+        * If we are checking for unsigned long long, the value may be larger
         * then long long, but within range of unsigned long long.  Check this
         * by doing the normal Python integer comparison.
         */

numpy/_core/src/umath/ufunc_object.c

@@ -4546,7 +4546,7 @@ ufunc_generic_fastcall(PyUFuncObject *ufunc,
     PyObject *keepdims_obj = NULL, *casting_obj = NULL, *order_obj = NULL;
     PyObject *subok_obj = NULL, *signature_obj = NULL, *sig_obj = NULL;
     PyObject *dtype_obj = NULL;
-    /* Typically, NumPy defaults to returnin scalars for 0-D results */
+    /* Typically, NumPy defaults to returning scalars for 0-D results */
     npy_bool return_scalar = NPY_TRUE;
 
     /* Skip parsing if there are no keyword arguments, nothing left to do */
@@ -4640,7 +4640,7 @@ ufunc_generic_fastcall(PyUFuncObject *ufunc,
     if ((where_obj != NULL && where_obj != Py_True)
         && (full_args.out == NULL) && (out_obj == NULL)) {
         if (PyErr_WarnEx(PyExc_UserWarning,
-                "'where' used without 'out', expect unitialized memory in output. "
+                "'where' used without 'out', expect uninitialized memory in output. "
                 "If this is intentional, use out=None.", 1) < 0) {
             goto fail;
         }

numpy/_core/src/umath/ufunc_type_resolution.c

@@ -1158,7 +1158,7 @@ PyUFunc_MultiplicationTypeResolver(PyUFuncObject *ufunc,
                 return -1;
             }
 
-            // This is wrong agaian cause of elsize, but only the DType matters
+            // This is wrong again because of elsize, but only the DType matters
             // here (String or Unicode).
             out_dtypes[2] = out_dtypes[1];
             Py_INCREF(out_dtypes[1]);

numpy/_core/tests/test_api.py

@@ -475,7 +475,7 @@ def test_copyto_cast_safety():
         np.copyto(np.arange(3, dtype=np.float32), 2e300, casting="safe")
 
 
-def test_copyto_permut():
+def test_copyto_permute():
     # test explicit overflow case
     pad = 500
     l = [True] * pad + [True, True, True, True]

numpy/_core/tests/test_array_coercion.py

@@ -910,7 +910,7 @@ def test_empty_string():
 @pytest.mark.parametrize("res_dt,hug_val",
     [("float16", "1e30"), ("float32", "1e200")])
 def test_string_to_float_coercion_errors(dtype, res_dt, hug_val):
-    # This test primarly tests setitem
+    # This test primarily tests setitem
     val = np.array(["3M"], dtype=dtype)[0]  # use the scalar
 
     with pytest.raises(ValueError):

numpy/_core/tests/test_deprecations.py

@@ -345,7 +345,7 @@ class TestTooManyArgsExtremum(_DeprecationTestCase):
     message = "Passing more than 2 positional arguments to np.maximum and np.minimum "
 
     @pytest.mark.parametrize("ufunc", [np.minimum, np.maximum])
-    def test_extremem_3_args(self, ufunc):
+    def test_extremum_3_args(self, ufunc):
         self.assert_deprecated(ufunc, args=(np.ones(1), np.zeros(1), np.empty(1)))
 
 

numpy/_core/tests/test_dtype.py

@@ -1199,7 +1199,7 @@ class TestDTypeMakeCanonical:
 
     def test_object_flag_not_inherited(self):
         # The following dtype still indicates "object", because its included
-        # in the unaccessible space (maybe this could change at some point):
+        # in the inaccessible space (maybe this could change at some point):
         arr = np.ones(3, "i,O,i")[["f0", "f2"]]
         assert arr.dtype.hasobject
         canonical_dt = np.result_type(arr.dtype)

numpy/_core/tests/test_einsum.py

@@ -1184,7 +1184,7 @@ class TestEinsumPath:
             ret &= (comp[pos + 1] == benchmark[pos + 1])
         assert_(ret)
 
-    def test_memory_contraints(self):
+    def test_memory_constraints(self):
         # Ensure memory constraints are satisfied
 
         outer_test = self.build_operands('a,b,c->abc')

numpy/_core/tests/test_multiarray.py

@@ -1400,7 +1400,7 @@ class TestCreation:
         with pytest.raises(ValueError, match="ndmax must be in the range"):
             np.array(data, ndmax=-1)
 
-    def test_ndmax_greather_than_NPY_MAXDIMS(self):
+    def test_ndmax_greater_than_NPY_MAXDIMS(self):
         data = [1, 2, 3]
         # current NPY_MAXDIMS is 64
         with pytest.raises(ValueError, match="ndmax must be in the range"):
@@ -1808,7 +1808,7 @@ class TestStructured:
     @pytest.mark.parametrize("align", [True, False])
     def test_structured_promotion_packs(self, dtype_dict, align):
         # Structured dtypes are packed when promoted (we consider the packed
-        # form to be "canonical"), so tere is no extra padding.
+        # form to be "canonical"), so there is no extra padding.
         dtype = np.dtype(dtype_dict, align=align)
         # Remove non "canonical" dtype options:
         dtype_dict.pop("itemsize", None)
@@ -8331,22 +8331,22 @@ class TestWarnings:
 
 class TestMinScalarType:
 
-    def test_usigned_shortshort(self):
+    def test_unsigned_shortshort(self):
         dt = np.min_scalar_type(2**8 - 1)
         wanted = np.dtype('uint8')
         assert_equal(wanted, dt)
 
-    def test_usigned_short(self):
+    def test_unsigned_short(self):
         dt = np.min_scalar_type(2**16 - 1)
         wanted = np.dtype('uint16')
         assert_equal(wanted, dt)
 
-    def test_usigned_int(self):
+    def test_unsigned_int(self):
         dt = np.min_scalar_type(2**32 - 1)
         wanted = np.dtype('uint32')
         assert_equal(wanted, dt)
 
-    def test_usigned_longlong(self):
+    def test_unsigned_longlong(self):
         dt = np.min_scalar_type(2**63 - 1)
         wanted = np.dtype('uint64')
         assert_equal(wanted, dt)

numpy/_core/tests/test_numerictypes.py

@@ -257,7 +257,7 @@ class ReadValuesNested:
             assert_equal(h['z'], np.array([self._buffer[0][5],
                                            self._buffer[1][5]], dtype='u1'))
 
-    def test_nested1_acessors(self):
+    def test_nested1_accessors(self):
         """Check reading the nested fields of a nested array (1st level)"""
         h = np.array(self._buffer, dtype=self._descr)
         if not self.multiple_rows:
@@ -287,7 +287,7 @@ class ReadValuesNested:
                                 self._buffer[1][3][1]],
                                dtype='c16'))
 
-    def test_nested2_acessors(self):
+    def test_nested2_accessors(self):
         """Check reading the nested fields of a nested array (2nd level)"""
         h = np.array(self._buffer, dtype=self._descr)
         if not self.multiple_rows:
@@ -573,7 +573,7 @@ class TestScalarTypeNames:
         assert getattr(np, t.__name__) is t
 
     @pytest.mark.parametrize('t', numeric_types)
-    def test_names_are_undersood_by_dtype(self, t):
+    def test_names_are_understood_by_dtype(self, t):
         """ Test the dtype constructor maps names back to the type """
         assert np.dtype(t.__name__).type is t
 

numpy/_core/tests/test_scalarbuffer.py

@@ -134,7 +134,7 @@ class TestScalarPEP3118:
         v = memoryview(s)
         assert self._as_dict(v) == expected
 
-        # integers of the paltform-appropriate endianness
+        # integers of the platform-appropriate endianness
         code_points = np.frombuffer(v, dtype='i4')
 
         assert_equal(code_points, [ord(c) for c in s])

numpy/_core/tests/test_scalarmath.py

@@ -397,7 +397,7 @@ class TestModulus:
             a //= b
 
 class TestComparison:
-    def test_comparision_different_types(self):
+    def test_comparison_different_types(self):
         x = np.array(1)
         y = np.array('s')
         eq = x == y
@@ -1066,7 +1066,7 @@ def test_longdouble_complex():
 def test_pyscalar_subclasses(subtype, __op__, __rop__, op, cmp):
     # This tests that python scalar subclasses behave like a float64 (if they
     # don't override it).
-    # In an earlier version of NEP 50, they behaved like the Python buildins.
+    # In an earlier version of NEP 50, they behaved like the Python builtins.
     def op_func(self, other):
         return __op__
 

numpy/_core/tests/test_strings.py

@@ -193,7 +193,7 @@ def test_large_string_cast():
 
 
 @pytest.mark.parametrize("dt", ["S1", "U1"])
-def test_in_place_mutiply_no_overflow(dt):
+def test_in_place_multiply_no_overflow(dt):
     # see gh-30495
     a = np.array("a", dtype=dt)
     a *= 20

numpy/_globals.py

@@ -97,7 +97,7 @@ class _CopyMode(enum.Enum):
 
 
 class _SignatureDescriptor:
-    # A descriptor to store on the ufunc __dict__ that avoids definig a
+    # A descriptor to store on the ufunc __dict__ that avoids defining a
     # signature for the ufunc class/type but allows the instance to have one.
     # This is needed because inspect.signature() chokes on normal properties
     # (as of 3.14 at least).

numpy/_typing/_nested_sequence.py

@@ -15,7 +15,7 @@ class _NestedSequence[T](Protocol):
     Warning
     -------
     `_NestedSequence` currently does not work in combination with typevars,
-    *e.g.* ``def func(a: _NestedSequnce[T]) -> T: ...``.
+    *e.g.* ``def func(a: _NestedSequence[T]) -> T: ...``.
 
     See Also
     --------

numpy/_utils/__init__.py

@@ -11,7 +11,7 @@ in ``numpy._core``.
 import functools
 import warnings
 
-from ._convertions import asbytes, asunicode
+from ._conversions import asbytes, asunicode
 
 
 def set_module(module):

numpy/_utils/__init__.pyi

@@ -2,7 +2,7 @@ from _typeshed import IdentityFunction
 from collections.abc import Callable, Iterable
 from typing import Protocol, overload, type_check_only
 
-from ._convertions import asbytes as asbytes, asunicode as asunicode
+from ._conversions import asbytes as asbytes, asunicode as asunicode
 
 ###
 

numpy/conftest.py

@@ -23,9 +23,9 @@ except ModuleNotFoundError:
 
 try:
     import pytest_run_parallel  # noqa: F401
-    PARALLEL_RUN_AVALIABLE = True
+    PARALLEL_RUN_AVAILABLE = True
 except ModuleNotFoundError:
-    PARALLEL_RUN_AVALIABLE = False
+    PARALLEL_RUN_AVAILABLE = False
 
 _old_fpu_mode = None
 _collect_results = {}
@@ -66,7 +66,7 @@ def pytest_configure(config):
         "leaks_references: Tests that are known to leak references.")
     config.addinivalue_line("markers",
         "slow: Tests that are very slow.")
-    if not PARALLEL_RUN_AVALIABLE:
+    if not PARALLEL_RUN_AVAILABLE:
         config.addinivalue_line("markers",
             "parallel_threads(n): run the given test function in parallel "
             "using `n` threads.",

numpy/f2py/tests/test_array_from_pyobj.py

@@ -663,7 +663,7 @@ class TestSharedMemory:
         a = self.array(shape, intent.inplace, obj)
         # Spot check that they contain the same information initially.
         assert obj[1][2] == a.arr[1][2], repr((obj, a.arr))
-        # If we change a.arr, that will not immediatetly be reflected in obj.
+        # If we change a.arr, that will not immediately be reflected in obj.
         change_item = 54 if self.type.dtype != bool else False
         a.arr[1][2] = change_item
         assert a.arr[1][2] == np.array(change_item, dtype=self.type.dtype)
@@ -673,7 +673,7 @@ class TestSharedMemory:
         assert a.arr.base is obj
         # It has a different organization from obj.
         assert a.arr.flags["FORTRAN"] and not a.arr.flags["CONTIGUOUS"]
-        # If we resolve the write-back, obj will be propertly filled.
+        # If we resolve the write-back, obj will be properly filled.
         code = wrap.resolve_write_back_if_copy(a.arr)
         assert code == 1, "no write-back resolution was done!"
         assert obj[1][2] == np.array(change_item, dtype=self.type.dtype)

numpy/f2py/tests/test_crackfortran.py

@@ -60,7 +60,7 @@ class TestPublicPrivate:
         assert set(tt['b_']['attrspec']) == {'public', 'bind(c)'}
         assert set(tt['c']['attrspec']) == {'public'}
 
-    def test_nowrap_private_proceedures(self, tmp_path):
+    def test_nowrap_private_procedures(self, tmp_path):
         fpath = util.getpath("tests", "src", "crackfortran", "gh23879.f90")
         mod = crackfortran.crackfortran([str(fpath)])
         assert len(mod) == 1

numpy/f2py/tests/test_regression.py

@@ -123,7 +123,7 @@ class TestF77Comments(util.F2PyTest):
         res = self.module.testsub2()
         npt.assert_allclose(expected, res)
 
-class TestF90Contiuation(util.F2PyTest):
+class TestF90Continuation(util.F2PyTest):
     # Check that comments are stripped from F90 continuation lines
     sources = [util.getpath("tests", "src", "regression", "f90continuation.f90")]
 

numpy/lib/_function_base_impl.py

@@ -1956,7 +1956,7 @@ def trim_zeros(filt, trim='fb', axis=None):
         returned that still contains all values which are not zero.
         If an axis is specified, `filt` will be sliced in that dimension only
         on the sides specified by `trim`. The remaining area will be the
-        smallest that still contains all values wich are not zero.
+        smallest that still contains all values which are not zero.
 
         .. versionadded:: 2.2.0
 
@@ -5070,7 +5070,7 @@ def meshgrid(*xi, copy=True, sparse=False, indexing='xy'):
         ``(1, ..., 1, Ni, 1, ..., 1)``.  These sparse coordinate grids are
         intended to be used with :ref:`basics.broadcasting`.  When all
         coordinates are used in an expression, broadcasting still leads to a
-        fully-dimensonal result array.
+        fully-dimensional result array.
 
         Default is False.
 

numpy/lib/tests/test_function_base.py

@@ -507,9 +507,9 @@ class TestAverage:
         assert_equal(type(rw), subclass)
 
     def test_upcasting(self):
-        typs = [('i4', 'i4', 'f8'), ('i4', 'f4', 'f8'), ('f4', 'i4', 'f8'),
+        types = [('i4', 'i4', 'f8'), ('i4', 'f4', 'f8'), ('f4', 'i4', 'f8'),
                  ('f4', 'f4', 'f4'), ('f4', 'f8', 'f8')]
-        for at, wt, rt in typs:
+        for at, wt, rt in types:
             a = np.array([[1, 2], [3, 4]], dtype=at)
             w = np.array([[1, 2], [3, 4]], dtype=wt)
             assert_equal(np.average(a, weights=w).dtype, np.dtype(rt))

numpy/lib/tests/test_loadtxt.py

@@ -529,7 +529,7 @@ def test_quoted_field(q):
 
 
 @pytest.mark.parametrize("q", ('"', "'", "`"))
-def test_quoted_field_with_whitepace_delimiter(q):
+def test_quoted_field_with_whitespace_delimiter(q):
     txt = StringIO(
         f"{q}alpha, x{q}     2.5\n{q}beta, y{q} 4.5\n{q}gamma, z{q}   5.0\n"
     )

numpy/lib/tests/test_nanfunctions.py

@@ -835,7 +835,7 @@ _TIME_UNITS = (
     "Y", "M", "W", "D", "h", "m", "s", "ms", "us", "ns", "ps", "fs", "as"
 )
 
-# All `inexact` + `timdelta64` type codes
+# All `inexact` + `timedelta64` type codes
 _TYPE_CODES = list(np.typecodes["AllFloat"])
 _TYPE_CODES += [f"m8[{unit}]" for unit in _TIME_UNITS]
 

numpy/ma/tests/test_extras.py

@@ -1231,7 +1231,7 @@ class TestMedian:
         b[2] = np.nan
         assert_equal(np.ma.median(a, (0, 2)), b)
 
-    def test_ambigous_fill(self):
+    def test_ambiguous_fill(self):
         # 255 is max value, used as filler for sort
         a = np.array([[3, 3, 255], [3, 3, 255]], dtype=np.uint8)
         a = np.ma.masked_array(a, mask=a == 3)

numpy/matrixlib/tests/test_defmatrix.py

@@ -323,7 +323,7 @@ class TestIndexing:
 class TestNewScalarIndexing:
     a = matrix([[1, 2], [3, 4]])
 
-    def test_dimesions(self):
+    def test_dimensions(self):
         a = self.a
         x = a[0]
         assert_equal(x.ndim, 2)

numpy/random/tests/test_direct.py

@@ -458,7 +458,7 @@ class TestPCG64(Base):
         assert val_neg == val_pos
         assert val_big == val_pos
 
-    def test_advange_large(self):
+    def test_advance_large(self):
         rs = Generator(self.bit_generator(38219308213743))
         pcg = rs.bit_generator
         state = pcg.state["state"]
@@ -497,7 +497,7 @@ class TestPCG64DXSM(Base):
         assert val_neg == val_pos
         assert val_big == val_pos
 
-    def test_advange_large(self):
+    def test_advance_large(self):
         rs = Generator(self.bit_generator(38219308213743))
         pcg = rs.bit_generator
         state = pcg.state

numpy/random/tests/test_generator_mt19937.py

@@ -1685,7 +1685,7 @@ class TestRandomDist:
                             [1.093830802293668, 1.256977002164613]])
         assert_array_almost_equal(actual, desired, decimal=15)
 
-    def test_standard_expoential_type_error(self):
+    def test_standard_exponential_type_error(self):
         assert_raises(TypeError, random.standard_exponential, dtype=np.int32)
 
     def test_standard_gamma(self):

numpy/random/tests/test_generator_mt19937_regressions.py

@@ -112,7 +112,7 @@ class TestRegression:
         #    # CDF of the beta distribution at x:
         #    p = mp.betainc(a, b, x1=0, x2=x, regularized=True)
         #    n = 1000000
-        #    exprected_freq = float(n*p)
+        #    expected_freq = float(n*p)
         #
         expected_freq = 77616.90831318991
         assert 0.95 * expected_freq < nzeros < 1.05 * expected_freq

numpy/random/tests/test_randomstate_regression.py

@@ -161,7 +161,7 @@ class TestRegression:
         rs2 = np.random.RandomState(seed=123456789)
         assert rs1.randint(0, 100) == rs2.randint(0, 100)
 
-    def test_choice_retun_dtype(self):
+    def test_choice_return_dtype(self):
         # GH 9867, now long since the NumPy default changed.
         c = np.random.choice(10, p=[.1] * 10, size=2)
         assert c.dtype == np.dtype(np.long)

numpy/typing/tests/data/fail/ndarray_misc.pyi

@@ -21,7 +21,7 @@ f8.argpartition(0)  # type: ignore[attr-defined]
 f8.partition(0)  # type: ignore[attr-defined]
 f8.dot(1)  # type: ignore[attr-defined]
 
-# NOTE: The following functions retur `Never`, causing mypy to stop analysis at that
+# NOTE: The following functions return `Never`, causing mypy to stop analysis at that
 # point, which we circumvent by wrapping them in a function.
 
 def f8_diagonal(x: np.float64) -> Never: