update imports of DateParseError, remove unused imports from tslib (pandas-dev#17713)

See pandas-dev#17652

Author: jbrockmendel

pandas/_libs/tslib.pyx

@@ -1,12 +1,9 @@
 # -*- coding: utf-8 -*-
 # cython: profile=False
 
-import warnings
-
 cimport numpy as np
 from numpy cimport (int8_t, int32_t, int64_t, import_array, ndarray,
-                    float64_t,
-                    NPY_INT64, NPY_DATETIME, NPY_TIMEDELTA)
+                    float64_t, NPY_DATETIME, NPY_TIMEDELTA)
 import numpy as np
 
 import sys
@@ -16,12 +13,10 @@ from cpython cimport (
     PyTypeObject,
     PyFloat_Check,
     PyComplex_Check,
-    PyLong_Check,
     PyObject_RichCompareBool,
     PyObject_RichCompare,
     Py_GT, Py_GE, Py_EQ, Py_NE, Py_LT, Py_LE,
-    PyUnicode_Check,
-    PyUnicode_AsUTF8String)
+    PyUnicode_Check)
 
 cdef extern from "Python.h":
     cdef PyTypeObject *Py_TYPE(object)
@@ -38,7 +33,6 @@ from datetime cimport (
     pandas_datetimestruct,
     pandas_datetime_to_datetimestruct,
     pandas_datetimestruct_to_datetime,
-    cmp_pandas_datetimestruct,
     days_per_month_table,
     get_datetime64_value,
     get_timedelta64_value,
@@ -68,23 +62,12 @@ from khash cimport (
     kh_resize_int64, kh_get_int64)
 
 from .tslibs.parsing import parse_datetime_string
-from .tslibs.parsing import DateParseError  # noqa
 
 cimport cython
 
-import re
 import time
 
-# dateutil compat
-from dateutil.tz import (tzoffset, tzlocal as _dateutil_tzlocal,
-                         tzutc as _dateutil_tzutc,
-                         tzstr as _dateutil_tzstr)
-
-from dateutil.relativedelta import relativedelta
-from dateutil.parser import DEFAULTPARSER
-
-from pandas.compat import (parse_date, string_types, iteritems,
-                           StringIO, callable)
+from pandas.compat import iteritems, callable
 
 import operator
 import collections
@@ -97,9 +80,6 @@ import_array()
 # import datetime C API
 PyDateTime_IMPORT
 
-# in numpy 1.7, will prob need the following:
-# numpy_pydatetime_import
-
 cdef int64_t NPY_NAT = util.get_nat()
 iNaT = NPY_NAT
 
@@ -318,7 +298,7 @@ class Timestamp(_Timestamp):
         tz : string / timezone object, default None
             Timezone to localize to
         """
-        if isinstance(tz, string_types):
+        if util.is_string_object(tz):
             tz = maybe_get_tz(tz)
         return cls(datetime.now(tz))
 
@@ -613,7 +593,7 @@ class Timestamp(_Timestamp):
         if self.tzinfo is None:
             # tz naive, localize
             tz = maybe_get_tz(tz)
-            if not isinstance(ambiguous, string_types):
+            if not util.is_string_object(ambiguous):
                 ambiguous =   [ambiguous]
             value = tz_localize_to_utc(np.array([self.value], dtype='i8'), tz,
                                        ambiguous=ambiguous, errors=errors)[0]
@@ -2426,8 +2406,8 @@ class Timedelta(_Timedelta):
                 raise TypeError(
                     "Invalid type {0}. Must be int or float.".format(type(v)))
 
-            kwargs = dict([ (k, _to_py_int_float(v))
-                            for k, v in iteritems(kwargs) ])
+            kwargs = dict([(k, _to_py_int_float(v))
+                            for k, v in iteritems(kwargs)])
 
             try:
                 nano = kwargs.pop('nanoseconds', 0)
@@ -3682,7 +3662,7 @@ def tz_localize_to_utc(ndarray[int64_t] vals, object tz, object ambiguous=None,
             result[i] = v - delta
         return result
 
-    if isinstance(ambiguous, string_types):
+    if util.is_string_object(ambiguous):
         if ambiguous == 'infer':
             infer_dst = True
         elif ambiguous == 'NaT':

pandas/core/tools/datetimes.py

@@ -8,6 +8,7 @@
 from pandas._libs.tslibs import parsing
 from pandas._libs.tslibs.parsing import (  # noqa
     parse_time_string,
+    DateParseError,
     _format_is_iso,
     _guess_datetime_format)
 
@@ -561,7 +562,6 @@ def calc_with_mask(carg, mask):
     return None
 
 
-DateParseError = tslib.DateParseError
 normalize_date = tslib.normalize_date
 
 # Fixed time formats for time parsing

pandas/tests/indexes/datetimes/test_tools.py

@@ -1335,13 +1335,13 @@ def test_parsers_monthfreq(self):
     def test_parsers_quarterly_with_freq(self):
         msg = ('Incorrect quarterly string is given, quarter '
                'must be between 1 and 4: 2013Q5')
-        with tm.assert_raises_regex(tslib.DateParseError, msg):
+        with tm.assert_raises_regex(parsing.DateParseError, msg):
             tools.parse_time_string('2013Q5')
 
         # GH 5418
         msg = ('Unable to retrieve month information from given freq: '
                'INVLD-L-DEC-SAT')
-        with tm.assert_raises_regex(tslib.DateParseError, msg):
+        with tm.assert_raises_regex(parsing.DateParseError, msg):
             tools.parse_time_string('2013Q1', freq='INVLD-L-DEC-SAT')
 
         cases = {('2013Q2', None): datetime(2013, 4, 1),

pandas/tests/scalar/test_period.py

@@ -11,6 +11,7 @@
 from pandas.compat.numpy import np_datetime64_compat
 
 from pandas._libs import tslib, period as libperiod
+from pandas._libs.tslibs.parsing import DateParseError
 from pandas import Period, Timestamp, offsets
 from pandas.tseries.frequencies import DAYS, MONTHS
 
@@ -886,8 +887,8 @@ def test_constructor_infer_freq(self):
 
     def test_badinput(self):
         pytest.raises(ValueError, Period, '-2000', 'A')
-        pytest.raises(tslib.DateParseError, Period, '0', 'A')
-        pytest.raises(tslib.DateParseError, Period, '1/1/-2000', 'A')
+        pytest.raises(DateParseError, Period, '0', 'A')
+        pytest.raises(DateParseError, Period, '1/1/-2000', 'A')
 
     def test_multiples(self):
         result1 = Period('1989', freq='2A')