Clean Up C Warnings (#31935)

Author: WillAyd

pandas/_libs/algos.pyx

@@ -1173,12 +1173,12 @@ ctypedef fused out_t:
 
 @cython.boundscheck(False)
 @cython.wraparound(False)
-def diff_2d(ndarray[diff_t, ndim=2] arr,
-            ndarray[out_t, ndim=2] out,
+def diff_2d(diff_t[:, :] arr,
+            out_t[:, :] out,
             Py_ssize_t periods, int axis):
     cdef:
         Py_ssize_t i, j, sx, sy, start, stop
-        bint f_contig = arr.flags.f_contiguous
+        bint f_contig = arr.is_f_contig()
 
     # Disable for unsupported dtype combinations,
     #  see https://github.com/cython/cython/issues/2646

pandas/_libs/hashing.pyx

@@ -5,7 +5,7 @@ import cython
 from libc.stdlib cimport malloc, free
 
 import numpy as np
-from numpy cimport uint8_t, uint32_t, uint64_t, import_array
+from numpy cimport ndarray, uint8_t, uint32_t, uint64_t, import_array
 import_array()
 
 from pandas._libs.util cimport is_nan
@@ -15,7 +15,7 @@ DEF dROUNDS = 4
 
 
 @cython.boundscheck(False)
-def hash_object_array(object[:] arr, object key, object encoding='utf8'):
+def hash_object_array(ndarray[object] arr, object key, object encoding='utf8'):
     """
     Parameters
     ----------

pandas/_libs/tslibs/conversion.pyx

@@ -152,7 +152,7 @@ def ensure_timedelta64ns(arr: ndarray, copy: bool=True):
 
 @cython.boundscheck(False)
 @cython.wraparound(False)
-def datetime_to_datetime64(object[:] values):
+def datetime_to_datetime64(ndarray[object] values):
     """
     Convert ndarray of datetime-like objects to int64 array representing
     nanosecond timestamps.

pandas/_libs/window/aggregations.pyx

@@ -56,7 +56,7 @@ cdef:
 cdef inline int int_max(int a, int b): return a if a >= b else b
 cdef inline int int_min(int a, int b): return a if a <= b else b
 
-cdef inline bint is_monotonic_start_end_bounds(
+cdef bint is_monotonic_start_end_bounds(
     ndarray[int64_t, ndim=1] start, ndarray[int64_t, ndim=1] end
 ):
     return is_monotonic(start, False)[0] and is_monotonic(end, False)[0]