Merge pull request #45 from ngoix/fix_travis

try and fix CI

Author: ngoix

.travis.yml

@@ -20,20 +20,20 @@ env:
     # This environment tests the newest supported Anaconda release (4.4.0)
     # It also runs tests requiring Pandas.
     - DISTRIB="conda" PYTHON_VERSION="3.6.1" INSTALL_MKL="true"
-      NUMPY_VERSION="1.13" SCIPY_VERSION="0.19.0" PANDAS_VERSION="0.20.2"
+      NUMPY_VERSION="1.13.3" SCIPY_VERSION="0.19.1" PANDAS_VERSION="0.20.2"
       CYTHON_VERSION="0.25.2" COVERAGE=true
 
     # This environment use pytest to run the tests. It uses the newest
     # supported Anaconda release (4.4.0). It also runs tests requiring Pandas.
     - USE_PYTEST="true" DISTRIB="conda" PYTHON_VERSION="3.6.1"
-      INSTALL_MKL="true" NUMPY_VERSION="1.12.1" SCIPY_VERSION="0.19.0"
-      PANDAS_VERSION="0.20.1" CYTHON_VERSION="0.25.2"
+      INSTALL_MKL="true" NUMPY_VERSION="1.13.3" SCIPY_VERSION="0.19.1"
+      PANDAS_VERSION="0.20.2" CYTHON_VERSION="0.25.2"
       TEST_DOCSTRINGS="true"
 
     # flake8 linting on diff wrt common ancestor with upstream/master
-    - RUN_FLAKE8="true" SKIP_TESTS="true"
-      DISTRIB="conda" PYTHON_VERSION="3.5" INSTALL_MKL="true"
-      NUMPY_VERSION="1.13" SCIPY_VERSION="0.19.0" CYTHON_VERSION="0.23.5"
+    - RUN_FLAKE8="true" SKIP_TESTS="true" PANDAS_VERSION="0.20.2"
+      DISTRIB="conda" PYTHON_VERSION="3.6.1" INSTALL_MKL="true"
+      NUMPY_VERSION="1.13" SCIPY_VERSION="0.19.1" CYTHON_VERSION="0.25.2"
 
 
 install: source ci_scripts/travis/install.sh

requirements.txt

@@ -4,4 +4,4 @@ scipy>=0.17.0
 pandas>=0.18.1
 numpydoc
 sphinx_gallery
-xlrd >= 0.9.0
+xlrd >= 0.9.0

skrules/skope_rules.py

@@ -9,7 +9,6 @@
 from sklearn.utils.multiclass import check_classification_targets
 from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
 from sklearn.ensemble import BaggingClassifier, BaggingRegressor
-from sklearn.externals import six
 from sklearn.tree import _tree
 
 from .rule import Rule, replace_feature_name
@@ -221,7 +220,7 @@ def fit(self, X, y, sample_weight=None):
         # ensure that max_samples is in [1, n_samples]:
         n_samples = X.shape[0]
 
-        if isinstance(self.max_samples, six.string_types):
+        if isinstance(self.max_samples, str):
             raise ValueError('max_samples (%s) is not supported.'
                              'Valid choices are: "auto", int or'
                              'float' % self.max_samples)