use memoryviews instead of ndarrays (pandas-dev#22147)

Author: jbrockmendel

pandas/_libs/tslibs/timedeltas.pyx

@@ -13,7 +13,7 @@ from cpython cimport PyUnicode_Check, Py_NE, Py_EQ, PyObject_RichCompare
 
 import numpy as np
 cimport numpy as cnp
-from numpy cimport int64_t, ndarray
+from numpy cimport int64_t
 cnp.import_array()
 
 from cpython.datetime cimport (datetime, timedelta,
@@ -33,6 +33,7 @@ from np_datetime cimport (cmp_scalar, reverse_ops, td64_to_tdstruct,
 
 from nattype import nat_strings, NaT
 from nattype cimport checknull_with_nat, NPY_NAT
+from offsets cimport to_offset
 
 # ----------------------------------------------------------------------
 # Constants
@@ -78,6 +79,44 @@ cdef dict timedelta_abbrevs = { 'D': 'd',
 
 _no_input = object()
 
+
+# ----------------------------------------------------------------------
+# API
+
+def ints_to_pytimedelta(int64_t[:] arr, box=False):
+    """
+    convert an i8 repr to an ndarray of timedelta or Timedelta (if box ==
+    True)
+
+    Parameters
+    ----------
+    arr : ndarray[int64_t]
+    box : bool, default False
+
+    Returns
+    -------
+    result : ndarray[object]
+        array of Timedelta or timedeltas objects
+    """
+    cdef:
+        Py_ssize_t i, n = len(arr)
+        int64_t value
+        object[:] result = np.empty(n, dtype=object)
+
+    for i in range(n):
+
+        value = arr[i]
+        if value == NPY_NAT:
+            result[i] = NaT
+        else:
+            if box:
+                result[i] = Timedelta(value)
+            else:
+                result[i] = timedelta(microseconds=int(value) / 1000)
+
+    return result.base  # .base to access underlying np.ndarray
+
+
 # ----------------------------------------------------------------------
 
 cpdef int64_t delta_to_nanoseconds(delta) except? -1:
@@ -144,7 +183,11 @@ cpdef convert_to_timedelta64(object ts, object unit):
             ts = cast_from_unit(ts, unit)
             ts = np.timedelta64(ts)
     elif is_string_object(ts):
-        ts = np.timedelta64(parse_timedelta_string(ts))
+        if len(ts) > 0 and ts[0] == 'P':
+            ts = parse_iso_format_string(ts)
+        else:
+            ts = parse_timedelta_string(ts)
+        ts = np.timedelta64(ts)
     elif hasattr(ts, 'delta'):
         ts = np.timedelta64(delta_to_nanoseconds(ts), 'ns')
 
@@ -156,15 +199,15 @@ cpdef convert_to_timedelta64(object ts, object unit):
     return ts.astype('timedelta64[ns]')
 
 
-cpdef array_to_timedelta64(ndarray[object] values, unit='ns', errors='raise'):
+cpdef array_to_timedelta64(object[:] values, unit='ns', errors='raise'):
     """
     Convert an ndarray to an array of timedeltas. If errors == 'coerce',
     coerce non-convertible objects to NaT. Otherwise, raise.
     """
 
     cdef:
         Py_ssize_t i, n
-        ndarray[int64_t] iresult
+        int64_t[:] iresult
 
     if errors not in ('ignore', 'raise', 'coerce'):
         raise ValueError("errors must be one of 'ignore', "
@@ -190,7 +233,7 @@ cpdef array_to_timedelta64(ndarray[object] values, unit='ns', errors='raise'):
                 else:
                     raise
 
-    return iresult
+    return iresult.base  # .base to access underlying np.ndarray
 
 
 cpdef inline int64_t cast_from_unit(object ts, object unit) except? -1:
@@ -795,12 +838,81 @@ cdef class _Timedelta(timedelta):
 
     @property
     def asm8(self):
-        """ return a numpy timedelta64 array view of myself """
+        """
+        Return a numpy timedelta64 array scalar view.
+
+        Provides access to the array scalar view (i.e. a combination of the
+        value and the units) associated with the numpy.timedelta64().view(),
+        including a 64-bit integer representation of the timedelta in
+        nanoseconds (Python int compatible).
+
+        Returns
+        -------
+        numpy timedelta64 array scalar view
+            Array scalar view of the timedelta in nanoseconds.
+
+        Examples
+        --------
+        >>> td = pd.Timedelta('1 days 2 min 3 us 42 ns')
+        >>> td.asm8
+        numpy.timedelta64(86520000003042,'ns')
+
+        >>> td = pd.Timedelta('2 min 3 s')
+        >>> td.asm8
+        numpy.timedelta64(123000000000,'ns')
+
+        >>> td = pd.Timedelta('3 ms 5 us')
+        >>> td.asm8
+        numpy.timedelta64(3005000,'ns')
+
+        >>> td = pd.Timedelta(42, unit='ns')
+        >>> td.asm8
+        numpy.timedelta64(42,'ns')
+        """
         return np.int64(self.value).view('m8[ns]')
 
     @property
     def resolution(self):
-        """ return a string representing the lowest resolution that we have """
+        """
+        Return a string representing the lowest timedelta resolution.
+
+        Each timedelta has a defined resolution that represents the lowest OR
+        most granular level of precision. Each level of resolution is
+        represented by a short string as defined below:
+
+        Resolution:     Return value
+
+        * Days:         'D'
+        * Hours:        'H'
+        * Minutes:      'T'
+        * Seconds:      'S'
+        * Milliseconds: 'L'
+        * Microseconds: 'U'
+        * Nanoseconds:  'N'
+
+        Returns
+        -------
+        str
+            Timedelta resolution.
+
+        Examples
+        --------
+        >>> td = pd.Timedelta('1 days 2 min 3 us 42 ns')
+        >>> td.resolution
+        'N'
+
+        >>> td = pd.Timedelta('1 days 2 min 3 us')
+        >>> td.resolution
+        'U'
+
+        >>> td = pd.Timedelta('2 min 3 s')
+        >>> td.resolution
+        'S'
+
+        >>> td = pd.Timedelta(36, unit='us')
+        >>> td.resolution
+        'U'
+        """
 
         self._ensure_components()
         if self._ns:
@@ -904,6 +1016,9 @@ cdef class _Timedelta(timedelta):
     def __str__(self):
         return self._repr_base(format='long')
 
+    def __bool__(self):
+        return self.value != 0
+
     def isoformat(self):
         """
         Format Timedelta as ISO 8601 Duration like
@@ -1063,7 +1178,6 @@ class Timedelta(_Timedelta):
         cdef:
             int64_t result, unit
 
-        from pandas.tseries.frequencies import to_offset
         unit = to_offset(freq).nanos
         result = unit * rounder(self.value / float(unit))
         return Timedelta(result, unit='ns')