remove unused time conversion funcs

pandas/_libs/index.pyx

@@ -13,29 +13,19 @@ cimport util
 
 import numpy as np
 
-cimport tslib
+from tslib cimport _to_i8
 
 from hashtable cimport HashTable
 
-from tslibs.timezones cimport is_utc, get_utcoffset
-from pandas._libs import tslib, algos, hashtable as _hash
+from pandas._libs import algos, hashtable as _hash
 from pandas._libs.tslib import Timestamp, Timedelta
 from datetime import datetime, timedelta
 
-from datetime cimport (get_datetime64_value, _pydatetime_to_dts,
-                       pandas_datetimestruct)
-
 from cpython cimport PyTuple_Check, PyList_Check
 
-cdef extern from "datetime.h":
-    bint PyDateTime_Check(object o)
-    void PyDateTime_IMPORT()
-
 cdef int64_t iNaT = util.get_nat()
 
 
-PyDateTime_IMPORT
-
 cdef extern from "Python.h":
     int PySlice_Check(object)
 
@@ -540,23 +530,6 @@ cpdef convert_scalar(ndarray arr, object value):
 
     return value
 
-cdef inline _to_i8(object val):
-    cdef pandas_datetimestruct dts
-    try:
-        return val.value
-    except AttributeError:
-        if util.is_datetime64_object(val):
-            return get_datetime64_value(val)
-        elif PyDateTime_Check(val):
-            tzinfo = getattr(val, 'tzinfo', None)
-            # Save the original date value so we can get the utcoffset from it.
-            ival = _pydatetime_to_dts(val, &dts)
-            if tzinfo is not None and not is_utc(tzinfo):
-                offset = get_utcoffset(tzinfo, val)
-                ival -= tslib._delta_to_nanoseconds(offset)
-            return ival
-        return val
-
 
 cdef class MultiIndexObjectEngine(ObjectEngine):
     """

pandas/_libs/lib.pyx

@@ -45,19 +45,11 @@ cdef double NaN = <double> np.NaN
 cdef double nan = NaN
 cdef double NAN = nan
 
-from datetime import datetime as pydatetime
-
 # this is our tseries.pxd
 from datetime cimport (
     get_timedelta64_value, get_datetime64_value,
     npy_timedelta, npy_datetime,
     PyDateTime_Check, PyDate_Check, PyTime_Check, PyDelta_Check,
-    PyDateTime_GET_YEAR,
-    PyDateTime_GET_MONTH,
-    PyDateTime_GET_DAY,
-    PyDateTime_DATE_GET_HOUR,
-    PyDateTime_DATE_GET_MINUTE,
-    PyDateTime_DATE_GET_SECOND,
     PyDateTime_IMPORT)
 
 
@@ -132,61 +124,6 @@ def memory_usage_of_objects(ndarray[object, ndim=1] arr):
         s += arr[i].__sizeof__()
     return s
 
-#----------------------------------------------------------------------
-# datetime / io related
-
-cdef int _EPOCH_ORD = 719163
-
-from datetime import date as pydate
-
-cdef inline int64_t gmtime(object date):
-    cdef int y, m, d, h, mn, s, days
-
-    y = PyDateTime_GET_YEAR(date)
-    m = PyDateTime_GET_MONTH(date)
-    d = PyDateTime_GET_DAY(date)
-    h = PyDateTime_DATE_GET_HOUR(date)
-    mn = PyDateTime_DATE_GET_MINUTE(date)
-    s = PyDateTime_DATE_GET_SECOND(date)
-
-    days = pydate(y, m, 1).toordinal() - _EPOCH_ORD + d - 1
-    return ((<int64_t> (((days * 24 + h) * 60 + mn))) * 60 + s) * 1000
-
-
-cpdef object to_datetime(int64_t timestamp):
-    return pydatetime.utcfromtimestamp(timestamp / 1000.0)
-
-
-cpdef object to_timestamp(object dt):
-    return gmtime(dt)
-
-
-def array_to_timestamp(ndarray[object, ndim=1] arr):
-    cdef int i, n
-    cdef ndarray[int64_t, ndim=1] result
-
-    n = len(arr)
-    result = np.empty(n, dtype=np.int64)
-
-    for i from 0 <= i < n:
-        result[i] = gmtime(arr[i])
-
-    return result
-
-
-def time64_to_datetime(ndarray[int64_t, ndim=1] arr):
-    cdef int i, n
-    cdef ndarray[object, ndim=1] result
-
-    n = len(arr)
-    result = np.empty(n, dtype=object)
-
-    for i from 0 <= i < n:
-        result[i] = to_datetime(arr[i])
-
-    return result
-
-
 #----------------------------------------------------------------------
 # isnull / notnull related
 

pandas/_libs/tslib.pxd

@@ -4,3 +4,5 @@ cdef convert_to_tsobject(object, object, object, bint, bint)
 cpdef convert_to_timedelta64(object, object)
 cdef bint _nat_scalar_rules[6]
 cdef bint _check_all_nulls(obj)
+
+cdef _to_i8(object val)

pandas/_libs/tslib.pyx

@@ -3436,7 +3436,18 @@ def cast_to_nanoseconds(ndarray arr):
     return result
 
 
-def pydt_to_i8(object pydt):
+cdef inline _to_i8(object val):
+    cdef pandas_datetimestruct dts
+    try:
+        return val.value
+    except AttributeError:
+        if is_datetime64_object(val):
+            return get_datetime64_value(val)
+        elif PyDateTime_Check(val):
+            return Timestamp(val).value
+        return val
+
+cpdef pydt_to_i8(object pydt):
     """
     Convert to int64 representation compatible with numpy datetime64; converts
     to UTC

pandas/io/pytables.py

@@ -25,7 +25,7 @@
 
 import numpy as np
 from pandas import (Series, DataFrame, Panel, Panel4D, Index,
-                    MultiIndex, Int64Index, isna, concat,
+                    MultiIndex, Int64Index, isna, concat, to_datetime,
                     SparseSeries, SparseDataFrame, PeriodIndex,
                     DatetimeIndex, TimedeltaIndex)
 from pandas.core import config
@@ -4529,7 +4529,7 @@ def _unconvert_index(data, kind, encoding=None):
 def _unconvert_index_legacy(data, kind, legacy=False, encoding=None):
     kind = _ensure_decoded(kind)
     if kind == u('datetime'):
-        index = lib.time64_to_datetime(data)
+        index = to_datetime(data)
     elif kind in (u('integer')):
         index = np.asarray(data, dtype=object)
     elif kind in (u('string')):