optimizations

Author: jbrockmendel

pandas/_libs/tslibs/conversion.pyx

@@ -74,6 +74,8 @@ cdef inline int64_t get_datetime64_nanos(object val) except? -1:
     return ival
 
 
+@cython.boundscheck(False)
+@cython.wraparound(False)
 def ensure_datetime64ns(arr: ndarray, copy: bint = True):
     """
     Ensure a np.datetime64 array has dtype specifically 'datetime64[ns]'
@@ -138,6 +140,8 @@ def ensure_timedelta64ns(arr: ndarray, copy: bint = True):
     # TODO: check for overflows when going from a lower-resolution to nanos
 
 
+@cython.boundscheck(False)
+@cython.wraparound(False)
 def datetime_to_datetime64(values: object[:]):
     """
     Convert ndarray of datetime-like objects to int64 array representing
@@ -611,6 +615,8 @@ cpdef inline datetime localize_pydatetime(datetime dt, object tz):
 # ----------------------------------------------------------------------
 # Timezone Conversion
 
+@cython.boundscheck(False)
+@cython.wraparound(False)
 cdef inline int64_t[:] _tz_convert_dst(int64_t[:] values, tzinfo tz,
                                        bint to_utc=True):
     """
@@ -757,6 +763,8 @@ cpdef int64_t tz_convert_single(int64_t val, object tz1, object tz2):
         return _tz_convert_dst(arr, tz2, to_utc=False)[0]
 
 
+@cython.boundscheck(False)
+@cython.wraparound(False)
 cdef inline int64_t[:] _tz_convert_one_way(int64_t[:] vals, object tz,
                                            bint to_utc):
     """
@@ -1215,6 +1223,8 @@ cdef inline int64_t _normalized_stamp(npy_datetimestruct *dts) nogil:
     return dtstruct_to_dt64(dts)
 
 
+@cython.boundscheck(False)
+@cython.wraparound(False)
 def is_date_array_normalized(int64_t[:] stamps, object tz=None):
     """
     Check if all of the given (nanosecond) timestamps are normalized to

pandas/_libs/tslibs/fields.pyx

@@ -40,6 +40,8 @@ def get_time_micros(ndarray[int64_t] dtindex):
     return micros
 
 
+@cython.wraparound(False)
+@cython.boundscheck(False)
 def build_field_sarray(int64_t[:] dtindex):
     """
     Datetime as int64 representation to a structured array of fields
@@ -134,6 +136,7 @@ def get_date_name_field(int64_t[:] dtindex, object field, object locale=None):
 
 
 @cython.wraparound(False)
+@cython.boundscheck(False)
 def get_start_end_field(int64_t[:] dtindex, object field,
                         object freqstr=None, int month_kw=12):
     """

pandas/_libs/tslibs/timedeltas.pyx

@@ -6,6 +6,7 @@ import warnings
 import sys
 cdef bint PY3 = (sys.version_info[0] >= 3)
 
+import cython
 from cython import Py_ssize_t
 
 from cpython cimport Py_NE, Py_EQ, PyObject_RichCompare
@@ -82,6 +83,8 @@ _no_input = object()
 # ----------------------------------------------------------------------
 # API
 
+@cython.boundscheck(False)
+@cython.wraparound(False)
 def ints_to_pytimedelta(int64_t[:] arr, bint box=False):
     """
     convert an i8 repr to an ndarray of timedelta or Timedelta (if box ==
@@ -198,6 +201,8 @@ cpdef convert_to_timedelta64(object ts, object unit):
     return ts.astype('timedelta64[ns]')
 
 
+@cython.boundscheck(False)
+@cython.wraparound(False)
 def array_to_timedelta64(object[:] values, unit='ns', errors='raise'):
     """
     Convert an ndarray to an array of timedeltas. If errors == 'coerce',