Move time conversion funcs to tslibs.conversion

pandas/_libs/index.pyx

@@ -13,28 +13,19 @@ cimport util
 
 import numpy as np
 
-cimport tslib
-
 from hashtable cimport HashTable
 
 from tslibs.timezones cimport is_utc, get_utcoffset
+from tslibs.conversion cimport _to_i8
 from pandas._libs import tslib, 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 +531,6 @@ 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

@@ -45,8 +45,6 @@ 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,
@@ -134,58 +132,10 @@ def memory_usage_of_objects(ndarray[object, ndim=1] arr):
 
 #----------------------------------------------------------------------
 # 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
-
+from tslibs.conversion import (  # noqa
+    time64_to_datetime,
+    array_to_timestamp, to_timestamp, to_datetime)
+from tslibs.conversion cimport to_timestamp, to_datetime, gmtime  # noqa
 
 #----------------------------------------------------------------------
 # isnull / notnull related

pandas/_libs/tslibs/conversion.pxd

@@ -0,0 +1,10 @@
+# -*- coding: utf-8 -*-
+# cython: profile=False
+
+from numpy cimport int64_t
+
+cdef int64_t gmtime(object date)
+cpdef object to_datetime(int64_t timestamp)
+cpdef object to_timestamp(object dt)
+
+cdef _to_i8(object val)

pandas/_libs/tslibs/conversion.pyx

@@ -0,0 +1,104 @@
+# -*- coding: utf-8 -*-
+# cython: profile=False
+
+
+from datetime import (
+	date as pydate,
+	datetime as pydatetime)
+
+from cpython.datetime cimport (
+	PyDateTime_Check,
+    PyDateTime_GET_YEAR,
+    PyDateTime_GET_MONTH,
+    PyDateTime_GET_DAY,
+    PyDateTime_DATE_GET_HOUR,
+    PyDateTime_DATE_GET_MINUTE,
+    PyDateTime_DATE_GET_SECOND,
+    PyDateTime_IMPORT)
+PyDateTime_IMPORT
+
+from datetime cimport (get_datetime64_value, _pydatetime_to_dts,
+                       pandas_datetimestruct)
+
+import numpy as np
+cimport numpy as cnp
+from numpy cimport int64_t, ndarray
+cnp.import_array()
+
+cimport util
+
+from timezones cimport get_utcoffset, is_utc
+
+# ----------------------------------------------------------------------
+# Constants
+cdef int _EPOCH_ORD = 719163
+
+# ----------------------------------------------------------------------
+# Non-pandas-specific
+
+cpdef object to_datetime(int64_t timestamp):
+    return pydatetime.utcfromtimestamp(timestamp / 1000.0)
+
+
+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_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 in range(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 in range(n):
+        result[i] = to_datetime(arr[i])
+
+    return result
+
+
+# ----------------------------------------------------------------------
+
+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 -= int(offset.total_seconds() * 1e9)
+            return ival
+        return val

setup.py

@@ -341,6 +341,7 @@ class CheckSDist(sdist_class):
                  'pandas/_libs/window.pyx',
                  'pandas/_libs/sparse.pyx',
                  'pandas/_libs/parsers.pyx',
+                 'pandas/_libs/tslibs/conversion.pyx',
                  'pandas/_libs/tslibs/timezones.pyx',
                  'pandas/_libs/tslibs/frequencies.pyx',
                  'pandas/_libs/tslibs/parsing.pyx',
@@ -492,6 +493,7 @@ def pxd(name):
                     'depends': tseries_depends,
                     'sources': ['pandas/_libs/src/datetime/np_datetime.c',
                                 'pandas/_libs/src/datetime/np_datetime_strings.c']},
+    '_libs.tslibs.conversion': {'pyxfile': '_libs/tslibs/conversion'},
     '_libs.tslibs.timezones': {'pyxfile': '_libs/tslibs/timezones'},
     '_libs.period': {'pyxfile': '_libs/period',
                      'depends': (tseries_depends +