BLD: require python-dateutil>=2.5.0

Author: jreback

ci/requirements-2.7.build

@@ -1,5 +1,5 @@
 python=2.7*
-python-dateutil=2.4.1
+python-dateutil=2.5.0
 pytz=2013b
 nomkl
 numpy

ci/requirements-2.7.run

@@ -1,4 +1,4 @@
-python-dateutil=2.4.1
+python-dateutil=2.5.0
 pytz=2013b
 numpy
 xlwt=0.7.5

ci/requirements-2.7_COMPAT.build

@@ -1,5 +1,5 @@
 python=2.7*
 numpy=1.9.2
 cython=0.23
-dateutil=1.5
+python-dateutil=2.5.0
 pytz=2013b

ci/requirements-2.7_COMPAT.run

@@ -1,5 +1,5 @@
 numpy=1.9.2
-dateutil=1.5
+python-dateutil=2.5.0
 pytz=2013b
 scipy=0.14.0
 xlwt=0.7.5

conda.recipe/meta.yaml

@@ -22,7 +22,7 @@ requirements:
   run:
     - python
     - numpy x.x
-    - python-dateutil
+    - python-dateutil >=2.5.0
     - pytz
 
 test:

doc/source/install.rst

@@ -200,7 +200,7 @@ Dependencies
 
 * `setuptools <https://setuptools.readthedocs.io/en/latest/>`__
 * `NumPy <http://www.numpy.org>`__: 1.9.0 or higher
-* `python-dateutil <http://labix.org/python-dateutil>`__: 1.5 or higher
+* `python-dateutil <//https://dateutil.readthedocs.io/en/stable/>`__: 2.5 or higher
 * `pytz <http://pytz.sourceforge.net/>`__: Needed for time zone support
 
 .. _install.recommended_dependencies:

doc/source/whatsnew/v0.22.0.txt

@@ -85,8 +85,20 @@ Backwards incompatible API changes
 - :func:`Series.fillna` now raises a ``TypeError`` instead of a ``ValueError`` when passed a list, tuple or DataFrame as a ``value`` (:issue:`18293`)
 - :func:`pandas.DataFrame.merge` no longer casts a ``float`` column to ``object`` when merging on ``int`` and ``float`` columns (:issue:`16572`)
 - The default NA value for :class:`UInt64Index` has changed from 0 to ``NaN``, which impacts methods that mask with NA, such as ``UInt64Index.where()`` (:issue:`18398`)
--
 
+Dependencies have increased minimum versions
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+We have updated our minimum supported versions of dependencies ().
+If installed, we now require:
+
+   +-----------------+-----------------+----------+
+   | Package         | Minimum Version | Required |
+   +=================+=================+==========+
+   | python-dateutil | 2.5.0           |    X     |
+   +-----------------+-----------------+----------+
+
+- :func:`Series.fillna` now raises a ``TypeError`` instead of a ``ValueError`` when passed a list, tuple or DataFrame as a ``value`` (:issue:`18293`)
 
 
 

pandas/compat/__init__.py

@@ -396,25 +396,13 @@ def raise_with_traceback(exc, traceback=Ellipsis):
 If traceback is not passed, uses sys.exc_info() to get traceback."""
 
 
-# http://stackoverflow.com/questions/4126348
-# Thanks to @martineau at SO
-
+# dateutil minimum version
 import dateutil
 
-if PY2 and LooseVersion(dateutil.__version__) == '2.0':
-    # dateutil brokenness
-    raise Exception('dateutil 2.0 incompatible with Python 2.x, you must '
-    'install version 1.5 or 2.1+!')
-
+if LooseVersion(dateutil.__version__) < '2.5':
+    raise ImportError('dateutil 2.5.0 is the minimum required version')
 from dateutil import parser as _date_parser
-if LooseVersion(dateutil.__version__) < '2.0':
-
-    @functools.wraps(_date_parser.parse)
-    def parse_date(timestr, *args, **kwargs):
-        timestr = bytes(timestr)
-        return _date_parser.parse(timestr, *args, **kwargs)
-else:
-    parse_date = _date_parser.parse
+parse_date = _date_parser.parse
 
 
 # https://github.com/pandas-dev/pandas/pull/9123

pandas/tests/indexes/datetimes/test_tools.py

@@ -1160,9 +1160,9 @@ class TestDatetimeParsingWrappers(object):
     @pytest.mark.parametrize('cache', [True, False])
     def test_parsers(self, cache):
 
+        # dateutil >= 2.5.0 defaults to yearfirst=True
         # https://github.com/dateutil/dateutil/issues/217
-        import dateutil
-        yearfirst = dateutil.__version__ >= LooseVersion('2.5.0')
+        yearfirst = True
 
         cases = {'2011-01-01': datetime(2011, 1, 1),
                  '2Q2005': datetime(2005, 4, 1),

pandas/tests/scalar/test_timestamp.py

@@ -17,7 +17,7 @@
 import pandas.util.testing as tm
 from pandas.tseries import offsets, frequencies
 from pandas._libs import period
-from pandas._libs.tslibs.timezones import get_timezone
+from pandas._libs.tslibs.timezones import get_timezone, dateutil_gettz as gettz
 from pandas._libs.tslibs import conversion
 
 from pandas.compat import long, PY3
@@ -341,9 +341,7 @@ def test_repr(self):
                  '2014-01-01 00:00:00.000000001']
 
         # dateutil zone change (only matters for repr)
-        if (dateutil.__version__ >= LooseVersion('2.3') and
-            (dateutil.__version__ <= LooseVersion('2.4.0') or
-             dateutil.__version__ >= LooseVersion('2.6.0'))):
+        if dateutil.__version__ >= LooseVersion('2.6.0'):
             timezones = ['UTC', 'Asia/Tokyo', 'US/Eastern',
                          'dateutil/US/Pacific']
         else:
@@ -1345,7 +1343,6 @@ def test_timestamp_to_datetime_explicit_pytz(self):
     def test_timestamp_to_datetime_explicit_dateutil(self):
         tm._skip_if_windows_python_3()
 
-        from pandas._libs.tslibs.timezones import dateutil_gettz as gettz
         stamp = Timestamp('20090415', tz=gettz('US/Eastern'), freq='D')
         dtval = stamp.to_pydatetime()
         assert stamp == dtval