numpy · charris · Sep 11, 2024 · Sep 11, 2024 · charris · Sep 11, 2024
diff --git a/.github/workflows/linux_simd.yml b/.github/workflows/linux_simd.yml
@@ -17,7 +17,7 @@ name: Linux SIMD tests
 #
 # - native:
 #   Tests against the host CPU features set as the baseline without enabling any runtime dispatched features.
-#   Intended to assess the entire NumPy codebase against host flags, even for code sections lacking handwritten SIMD intrincis.
+#   Intended to assess the entire NumPy codebase against host flags, even for code sections lacking handwritten SIMD intrinsics.
 #
 # - without_avx512/avx2/fma3:
 #   Uses runtime SIMD dispatching but disables AVX2, FMA3, and AVX512.

diff --git a/doc/release/upcoming_changes/27156.change.rst b/doc/release/upcoming_changes/27156.change.rst
@@ -3,7 +3,7 @@ NEP 50 promotion state option removed
 The NEP 50 promotion state settings are now removed. They were always
 meant as temporary means for testing.
 A warning will be given if the environment variable is set to anything
-but ``NPY_PROMOTION_STATE=weak`` wile ``_set_promotion_state``
+but ``NPY_PROMOTION_STATE=weak`` while ``_set_promotion_state``
 and ``_get_promotion_state`` are removed.
 In case code used ``_no_nep50_warning``, a ``contextlib.nullcontext``
 could be used to replace it when not available.
diff --git a/doc/source/building/cross_compilation.rst b/doc/source/building/cross_compilation.rst
@@ -24,7 +24,7 @@ may need to pass to Meson to successfully cross compile.
 
 One possible hiccup is that the build requires running a compiled executable in
 order to determine the ``long double`` format for the host platform. This may be
-an obstable, since it requires ``crossenv`` or QEMU to run the host (cross)
+an obstacle, since it requires ``crossenv`` or QEMU to run the host (cross)
 Python. To avoid this problem, specify the paths to the relevant directories in
 your *cross file*:
 

diff --git a/doc/source/user/how-to-io.rst b/doc/source/user/how-to-io.rst
@@ -343,6 +343,6 @@ storage.
 
    >>> import os
    >>> # list all files created in testsetup. If needed there are
-   >>> # convenienes in e.g. astroquery to do this more automatically
+   >>> # conveniences in e.g. astroquery to do this more automatically
    >>> for filename in ['csv.txt', 'fixedwidth.txt', 'nan.txt', 'skip.txt', 'tabs.txt']:
    ...     os.remove(filename)
diff --git a/meson_cpu/main_config.h.in b/meson_cpu/main_config.h.in
@@ -11,7 +11,7 @@
  */
 #ifndef @P@_CPU_DISPATCHER_CONF_H_
 #define @P@_CPU_DISPATCHER_CONF_H_
-/// This definition is required to provides comptablity with NumPy distutils
+/// This definition is required to provide comptibility with NumPy distutils
 #define @P@_CPU_MESON_BUILD
 /**
  * @def @P@WITH_CPU_BASELINE

diff --git a/numpy/_core/src/multiarray/buffer.c b/numpy/_core/src/multiarray/buffer.c
@@ -26,7 +26,7 @@
 /*************************************************************************
  * PEP 3118 buffer protocol
  *
- * Implementing PEP 3118 is somewhat convoluted because of the desirata:
+ * Implementing PEP 3118 is somewhat convoluted because of the requirements:
  *
  * - Don't add new members to ndarray or descr structs, to preserve binary
  *   compatibility. (Also, adding the items is actually not very useful,

diff --git a/numpy/_core/tests/test_custom_dtypes.py b/numpy/_core/tests/test_custom_dtypes.py
@@ -116,7 +116,7 @@ def test_possible_and_impossible_reduce(self):
         # For reductions to work, the first and last operand must have the
         # same dtype.  For this parametric DType that is not necessarily true.
         a = self._get_array(2.)
-        # Addition reductin works (as of writing requires to pass initial
+        # Addition reduction works (as of writing requires to pass initial
         # because setting a scaled-float from the default `0` fails).
         res = np.add.reduce(a, initial=0.)
         assert res == a.astype(np.float64).sum()

diff --git a/numpy/_core/tests/test_numeric.py b/numpy/_core/tests/test_numeric.py
@@ -2179,9 +2179,9 @@ class TestArrayComparisons:
     )
     def test_array_equal_equal_nan(self, bx, by, equal_nan, expected):
         """
-        This test array_equal for a few combinaison:
+        This test array_equal for a few combinations:
 
-        - are the two inputs the same object or not (same object many not
+        - are the two inputs the same object or not (same object may not
           be equal if contains NaNs)
         - Whether we should consider or not, NaNs, being equal.
 

diff --git a/numpy/_core/tests/test_ufunc.py b/numpy/_core/tests/test_ufunc.py
@@ -2544,8 +2544,8 @@ def test_reducelike_out_promotes(self):
         assert single_res != res
 
     def test_reducelike_output_needs_identical_cast(self):
-        # Checks the case where the we have a simple byte-swap works, maily
-        # tests that this is not rejected directly.
+        # Checks the case where a simple byte-swap works, mainly tests that
+        # this is not rejected directly.
         # (interesting because we require descriptor identity in reducelikes).
         arr = np.ones(20, dtype="f8")
         out = np.empty((), dtype=arr.dtype.newbyteorder())

diff --git a/numpy/f2py/tests/test_array_from_pyobj.py b/numpy/f2py/tests/test_array_from_pyobj.py
@@ -143,7 +143,7 @@ def is_intent_exact(self, *names):
 
 # 32 bit system malloc typically does not provide the alignment required by
 # 16 byte long double types this means the inout intent cannot be satisfied
-# and several tests fail as the alignment flag can be randomly true or fals
+# and several tests fail as the alignment flag can be randomly true or false
 # when numpy gains an aligned allocator the tests could be enabled again
 #
 # Furthermore, on macOS ARM64, LONGDOUBLE is an alias for DOUBLE.

diff --git a/numpy/lib/__init__.py b/numpy/lib/__init__.py
@@ -53,7 +53,7 @@
 del PytestTester
 
 def __getattr__(attr):
-    # Warn for reprecated attributes
+    # Warn for deprecated/removed aliases
     import math
     import warnings
 

diff --git a/numpy/lib/recfunctions.py b/numpy/lib/recfunctions.py
@@ -1212,7 +1212,7 @@ def apply_along_fields(func, arr):
     Returns
     -------
     out : ndarray
-       Result of the recution operation
+       Result of the reduction operation
 
     Examples
     --------