[MRG+1] Dropping python 2.6 support (scikit-learn#7890)

* Remove Python 2.6 support

Some details about some slightly orthogonal changes:
* Note about cheking safely for nan is likely not valid any more (commit
  introducing it is c80ca91)
* scipy.linalg.qr econ parameter removed since scipy 0.9 in favour of
  mode='economic'
* Remove unnecessary libgfortran in conda create command

* Putative fix by setting the random seed

* Revert unintended change

* Reinstate previous logic for checking for NaNs

* Reinstate change in error message

Error messages from Python 2.7 assertRegexp does not contain the
function name, in contrast with Python 3 assertRegex

.travis.yml

@@ -29,7 +29,7 @@ env:
     - DISTRIB="ubuntu" PYTHON_VERSION="2.7" CYTHON_VERSION="0.23.4"
       COVERAGE=true
     # This environment tests the oldest supported anaconda env
-    - DISTRIB="conda" PYTHON_VERSION="2.6" INSTALL_MKL="false"
+    - DISTRIB="conda" PYTHON_VERSION="2.7" INSTALL_MKL="false"
       NUMPY_VERSION="1.6.2" SCIPY_VERSION="0.11.0" CYTHON_VERSION="0.23"
     # This environment tests the newest supported anaconda env
     # It also runs tests requiring Pandas.

README.rst

@@ -48,7 +48,7 @@ Dependencies
 
 scikit-learn requires:
 
-- Python (>= 2.6 or >= 3.3)
+- Python (>= 2.7 or >= 3.3)
 - NumPy (>= 1.6.1)
 - SciPy (>= 0.9)
 

build_tools/travis/install.sh

@@ -53,23 +53,17 @@ if [[ "$DISTRIB" == "conda" ]]; then
     if [[ "$INSTALL_MKL" == "true" ]]; then
         conda create -n testenv --yes python=$PYTHON_VERSION pip nose \
             numpy=$NUMPY_VERSION scipy=$SCIPY_VERSION numpy scipy \
-            libgfortran mkl flake8 \
+            mkl flake8 cython=$CYTHON_VERSION \
             ${PANDAS_VERSION+pandas=$PANDAS_VERSION}
 
     else
         conda create -n testenv --yes python=$PYTHON_VERSION pip nose \
             numpy=$NUMPY_VERSION scipy=$SCIPY_VERSION \
-            libgfortran nomkl \
+            nomkl cython=$CYTHON_VERSION \
             ${PANDAS_VERSION+pandas=$PANDAS_VERSION}
     fi
     source activate testenv
 
-    # Temporary work around for Python 2.6 because cython >= 0.23 is
-    # required for building scikit-learn but python 2.6 and cython
-    # 0.23 are not compatible in conda. Remove the next line and
-    # install cython via conda when Python 2.6 support is removed.
-    pip install cython==$CYTHON_VERSION
-
     # Install nose-timer via pip
     pip install nose-timer
 

doc/developers/advanced_installation.rst

@@ -35,7 +35,7 @@ Installing an official release
 
 Scikit-learn requires:
 
-- Python (>= 2.6 or >= 3.3),
+- Python (>= 2.7 or >= 3.3),
 - NumPy (>= 1.6.1),
 - SciPy (>= 0.9).
 

doc/developers/contributing.rst

@@ -702,7 +702,7 @@ Python 3.x support
 All scikit-learn code should work unchanged in both Python 2.[67]
 and 3.2 or newer. Since Python 3.x is not backwards compatible,
 that may require changes to code and it certainly requires testing
-on both 2.6 or 2.7, and 3.2 or newer.
+on both 2.7 and 3.2 or newer.
 
 For most numerical algorithms, Python 3.x support is easy:
 just remember that ``print`` is a function and

doc/install.rst

@@ -15,7 +15,7 @@ Installing the latest release
 
 Scikit-learn requires:
 
-- Python (>= 2.6 or >= 3.3),
+- Python (>= 2.7 or >= 3.3),
 - NumPy (>= 1.6.1),
 - SciPy (>= 0.9).
 

setup.py

@@ -200,7 +200,6 @@ def setup_package():
                                  'Operating System :: Unix',
                                  'Operating System :: MacOS',
                                  'Programming Language :: Python :: 2',
-                                 'Programming Language :: Python :: 2.6',
                                  'Programming Language :: Python :: 2.7',
                                  'Programming Language :: Python :: 3',
                                  'Programming Language :: Python :: 3.4',

sklearn/ensemble/tests/test_base.py

@@ -16,7 +16,7 @@
 from sklearn.ensemble import BaggingClassifier
 from sklearn.ensemble.base import _set_random_states
 from sklearn.linear_model import Perceptron
-from sklearn.externals.odict import OrderedDict
+from collections import OrderedDict
 from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
 from sklearn.pipeline import Pipeline
 from sklearn.feature_selection import SelectFromModel

sklearn/externals/funcsigs.py

@@ -2,18 +2,15 @@
 """Function signature objects for callables
 
 Back port of Python 3.3's function signature tools from the inspect module,
-modified to be compatible with Python 2.6, 2.7 and 3.2+.
+modified to be compatible with Python 2.7 and 3.2+.
 """
 from __future__ import absolute_import, division, print_function
 import itertools
 import functools
 import re
 import types
 
-try:
-    from collections import OrderedDict
-except ImportError:
-    from .odict import OrderedDict
+from collections import OrderedDict
 
 __version__ = "0.4"
 

sklearn/gaussian_process/gaussian_process.py

@@ -618,14 +618,7 @@ def reduced_likelihood_function(self, theta=None):
 
         # Get generalized least squares solution
         Ft = linalg.solve_triangular(C, F, lower=True)
-        try:
-            Q, G = linalg.qr(Ft, econ=True)
-        except:
-            #/usr/lib/python2.6/dist-packages/scipy/linalg/decomp.py:1177:
-            # DeprecationWarning: qr econ argument will be removed after scipy
-            # 0.7. The economy transform will then be available through the
-            # mode='economic' argument.
-            Q, G = linalg.qr(Ft, mode='economic')
+        Q, G = linalg.qr(Ft, mode='economic')
 
         sv = linalg.svd(G, compute_uv=False)
         rcondG = sv[-1] / sv[0]