BLD: remove support for 3.2, pandas-dev#9118

Author: jreback

.travis.yml

@@ -86,13 +86,6 @@ matrix:
       - CLIPBOARD=xsel
       - BUILD_TYPE=conda
       - JOB_NAME: "34_slow"
-    - python: 3.2
-      env:
-      - NOSE_ARGS="not slow and not network and not disabled"
-      - FULL_DEPS=true
-      - CLIPBOARD_GUI=qt4
-      - BUILD_TYPE=pydata
-      - JOB_NAME: "32_nslow"
     - python: 2.7
       env:
       - EXPERIMENTAL=true
@@ -103,13 +96,6 @@ matrix:
       - BUILD_TYPE=pydata
       - PANDAS_TESTING_MODE="deprecate"
     allow_failures:
-      - python: 3.2
-        env:
-        - NOSE_ARGS="not slow and not network and not disabled"
-        - FULL_DEPS=true
-        - CLIPBOARD_GUI=qt4
-        - BUILD_TYPE=pydata
-        - JOB_NAME: "32_nslow"
       - python: 2.7
         env:
         - NOSE_ARGS="slow and not network and not disabled"

ci/requirements-3.2.txt

@@ -18,7 +18,7 @@ Instructions for installing from source,
 Python version support
 ----------------------
 
-Officially Python 2.6, 2.7, 3.2, 3.3, and 3.4.
+Officially Python 2.6, 2.7, 3.3, and 3.4.
 
 Installing pandas
 -----------------

doc/source/install.rst

@@ -7,6 +7,10 @@ This is a major release from 0.16.2 and includes a small number of API changes,
 enhancements, and performance improvements along with a large number of bug fixes. We recommend that all
 users upgrade to this version.
 
+.. warning::
+
+   pandas >= 0.17.0 will no longer support compatibility with Python version 3.2 (:issue:`9118`)
+
 Highlights include:
 
 

doc/source/whatsnew/v0.17.0.txt

@@ -37,7 +37,6 @@
 import types
 
 PY3 = (sys.version_info[0] >= 3)
-PY3_2 = sys.version_info[:2] == (3, 2)
 PY2 = sys.version_info[0] == 2
 
 

pandas/compat/__init__.py

@@ -2813,11 +2813,7 @@ def _get_handle(path, mode, encoding=None, compression=None):
         else:
             raise ValueError('Unrecognized compression type: %s' %
                              compression)
-        if compat.PY3_2:
-            # gzip and bz2 don't work with TextIOWrapper in 3.2
-            encoding = encoding or get_option('display.encoding')
-            f = StringIO(f.read().decode(encoding))
-        elif compat.PY3:
+        if compat.PY3:
             from io import TextIOWrapper
             f = TextIOWrapper(f, encoding=encoding)
         return f

pandas/core/common.py

@@ -1327,10 +1327,7 @@ def _wrap_compressed(f, compression, encoding=None):
         import gzip
 
         f = gzip.GzipFile(fileobj=f)
-        if compat.PY3_2:
-            # 3.2's gzip doesn't support read1
-            f = StringIO(f.read().decode(encoding))
-        elif compat.PY3:
+        if compat.PY3:
             from io import TextIOWrapper
 
             f = TextIOWrapper(f)

pandas/io/parsers.py

@@ -395,8 +395,8 @@ def f():
         self.assertRaises(TypeError, lambda: cat_rev > a)
 
         # The following work via '__array_priority__ = 1000'
-        # works only on numpy >= 1.7.1 and not on PY3.2
-        if LooseVersion(np.__version__) > "1.7.1" and not compat.PY3_2:
+        # works only on numpy >= 1.7.1
+        if LooseVersion(np.__version__) > "1.7.1":
             self.assertRaises(TypeError, lambda: a < cat)
             self.assertRaises(TypeError, lambda: a < cat_rev)
 

pandas/tests/test_categorical.py

@@ -2690,14 +2690,6 @@ def create_index(self):
     def test_pickle_compat_construction(self):
         pass
 
-    def test_numeric_compat(self):
-        super(TestDatetimeIndex, self).test_numeric_compat()
-
-        if not compat.PY3_2:
-            for f in [lambda : np.timedelta64(1, 'D').astype('m8[ns]') * pd.date_range('2000-01-01', periods=3),
-                      lambda : pd.date_range('2000-01-01', periods=3) * np.timedelta64(1, 'D').astype('m8[ns]') ]:
-                self.assertRaises(TypeError, f)
-
     def test_get_loc(self):
         idx = pd.date_range('2000-01-01', periods=3)
 

pandas/tests/test_index.py

@@ -11,7 +11,7 @@
 from pandas import (Index, Series, DataFrame, Timestamp, Timedelta, TimedeltaIndex, isnull, notnull,
                     bdate_range, date_range, timedelta_range, Int64Index)
 import pandas.core.common as com
-from pandas.compat import StringIO, lrange, range, zip, u, OrderedDict, long, PY3_2
+from pandas.compat import StringIO, lrange, range, zip, u, OrderedDict, long
 from pandas import compat, to_timedelta, tslib
 from pandas.tseries.timedeltas import _coerce_scalar_to_timedelta_type as ct
 from pandas.util.testing import (assert_series_equal,
@@ -1040,8 +1040,6 @@ def test_comparisons_coverage(self):
         self.assert_numpy_array_equal(result, exp)
 
     def test_comparisons_nat(self):
-        if PY3_2:
-            raise nose.SkipTest('nat comparisons on 3.2 broken')
 
         tdidx1 = pd.TimedeltaIndex(['1 day', pd.NaT, '1 day 00:00:01', pd.NaT,
                                     '1 day 00:00:01', '5 day 00:00:03'])

pandas/tseries/tests/test_timedeltas.py

@@ -28,7 +28,7 @@
 
 import pandas.index as _index
 
-from pandas.compat import range, long, StringIO, lrange, lmap, zip, product, PY3_2
+from pandas.compat import range, long, StringIO, lrange, lmap, zip, product
 from numpy.random import rand
 from numpy.testing import assert_array_equal
 from pandas.util.testing import assert_frame_equal
@@ -2225,8 +2225,6 @@ def test_comparisons_coverage(self):
         self.assert_numpy_array_equal(result, exp)
 
     def test_comparisons_nat(self):
-        if PY3_2:
-            raise nose.SkipTest('nat comparisons on 3.2 broken')
 
         fidx1 = pd.Index([1.0, np.nan, 3.0, np.nan, 5.0, 7.0])
         fidx2 = pd.Index([2.0, 3.0, np.nan, np.nan, 6.0, 7.0])

pandas/tseries/tests/test_timeseries.py

@@ -2543,9 +2543,6 @@ cdef inline _get_datetime64_nanos(object val):
         npy_datetime ival
 
     unit = get_datetime64_unit(val)
-    if unit == 3:
-        raise ValueError('NumPy 1.6.1 business freq not supported')
-
     ival = get_datetime64_value(val)
 
     if unit != PANDAS_FR_ns:
@@ -2613,9 +2610,6 @@ def cast_to_nanoseconds(ndarray arr):
         return result
 
     unit = get_datetime64_unit(arr.flat[0])
-    if unit == 3:
-        raise ValueError('NumPy 1.6.1 business freq not supported')
-
     for i in range(n):
         pandas_datetime_to_datetimestruct(ivalues[i], unit, &dts)
         iresult[i] = pandas_datetimestruct_to_datetime(PANDAS_FR_ns, &dts)

pandas/tslib.pyx

@@ -185,7 +185,6 @@ def build_extensions(self):
     'Programming Language :: Python :: 3',
     'Programming Language :: Python :: 2.6',
     'Programming Language :: Python :: 2.7',
-    'Programming Language :: Python :: 3.2',
     'Programming Language :: Python :: 3.3',
     'Programming Language :: Python :: 3.4',
     'Programming Language :: Cython',