Remove src/numpy.pxd (pandas-dev#19418)

Author: jbrockmendel

pandas/_libs/index.pyx

@@ -8,10 +8,14 @@ from cpython.slice cimport PySlice_Check
 
 import numpy as np
 cimport numpy as cnp
-from numpy cimport (ndarray, float64_t, int32_t, int64_t, uint8_t, uint64_t,
-                    NPY_DATETIME, NPY_TIMEDELTA)
+from numpy cimport ndarray, float64_t, int32_t, int64_t, uint8_t, uint64_t
 cnp.import_array()
 
+cdef extern from "numpy/arrayobject.h":
+    # These can be cimported directly from numpy in cython>=0.27.3
+    cdef enum NPY_TYPES:
+        NPY_DATETIME
+        NPY_TIMEDELTA
 
 cimport util
 

pandas/_libs/src/inference.pyx

@@ -12,6 +12,22 @@ iNaT = util.get_nat()
 cdef bint PY2 = sys.version_info[0] == 2
 cdef double nan = <double> np.NaN
 
+cdef extern from "numpy/arrayobject.h":
+    # cython's numpy.dtype specification is incorrect, which leads to
+    # errors in issubclass(self.dtype.type, np.bool_), so we directly
+    # include the correct version
+    # https://github.com/cython/cython/issues/2022
+
+    ctypedef class numpy.dtype [object PyArray_Descr]:
+        # Use PyDataType_* macros when possible, however there are no macros
+        # for accessing some of the fields, so some are defined. Please
+        # ask on cython-dev if you need more.
+        cdef int type_num
+        cdef int itemsize "elsize"
+        cdef char byteorder
+        cdef object fields
+        cdef tuple names
+
 from util cimport UINT8_MAX, UINT64_MAX, INT64_MAX, INT64_MIN
 
 # core.common import for fast inference checks
@@ -609,13 +625,13 @@ cdef class Validator:
 
     cdef:
         Py_ssize_t n
-        cnp.dtype dtype
+        dtype dtype
         bint skipna
 
     def __cinit__(
         self,
         Py_ssize_t n,
-        cnp.dtype dtype=np.dtype(np.object_),
+        dtype dtype=np.dtype(np.object_),
         bint skipna=False
     ):
         self.n = n
@@ -823,7 +839,7 @@ cdef class TemporalValidator(Validator):
     def __cinit__(
         self,
         Py_ssize_t n,
-        cnp.dtype dtype=np.dtype(np.object_),
+        dtype dtype=np.dtype(np.object_),
         bint skipna=False
     ):
         self.n = n