scikit-learn
@@ -65,6 +65,7 @@ jobs:
           path: ~/log.txt
           destination: log.txt
 
+
   deploy:
     docker:
       - image: circleci/python:3.6.1
@@ -91,4 +92,3 @@ workflows:
       - deploy:
           requires:
             - python3
-            - python2
@@ -38,13 +38,15 @@ matrix:
            NUMPY_VERSION="1.10.4" SCIPY_VERSION="0.16.1" CYTHON_VERSION="0.25.2"
            PILLOW_VERSION="4.0.0" COVERAGE=true
       if: type != cron
-    # This environment tests the newest supported Anaconda release (5.0.0)
-    # It also runs tests requiring Pandas and PyAMG
+    # This environment tests the newest supported Anaconda release.
+    # It runs tests requiring pandas and PyAMG.
+    # It also runs with the site joblib instead of the vendored copy of joblib.
     - env: DISTRIB="conda" PYTHON_VERSION="3.6.2" INSTALL_MKL="true"
            NUMPY_VERSION="1.14.2" SCIPY_VERSION="1.0.0" PANDAS_VERSION="0.20.3"
            CYTHON_VERSION="0.26.1" PYAMG_VERSION="3.3.2" PILLOW_VERSION="4.3.0"
-           COVERAGE=true
+           JOBLIB_VERSION="0.12" COVERAGE=true
            CHECK_PYTEST_SOFT_DEPENDENCY="true" TEST_DOCSTRINGS="true"
+           SKLEARN_SITE_JOBLIB=1
       if: type != cron
     # flake8 linting on diff wrt common ancestor with upstream/master
     - env: RUN_FLAKE8="true" SKIP_TESTS="true"
 
   * `Kyle Kastner <http://kastnerkyle.github.io>`_
   * `Manoj Kumar <https://manojbits.wordpress.com>`_
   * Robert Layton
+  * `Guillaume Lemaitre <https://github.com/glemaitre>`_
   * `Wei Li <http://kuantkid.github.io/>`_
   * Paolo Losi
   * `Gilles Louppe <http://glouppe.github.io/>`_
@@ -59,11 +60,14 @@ The following people have been core contributors to scikit-learn's development a
   * `Alexandre Passos <http://atpassos.posterous.com>`_
   * `Fabian Pedregosa <http://fa.bianp.net/blog/>`_
   * `Peter Prettenhofer <https://sites.google.com/site/peterprettenhofer/>`_
+  * `Hanmin Qin <https://github.com/qinhanmin2014>`_
   * Bertrand Thirion
+  * `Joris Van den Bossche <https://github.com/jorisvandenbossche>`_
   * `Jake VanderPlas <http://staff.washington.edu/jakevdp/>`_
   * Nelle Varoquaux
   * `Gael Varoquaux <http://gael-varoquaux.info/>`_
   * Ron Weiss
+  * `Roman Yurchak <https://github.com/rth>`_
 
 Please do not email the authors directly to ask for assistance or report issues.
 Instead, please see `What's the best way to ask questions about scikit-learn
 
@@ -53,6 +53,9 @@ scikit-learn requires:
 - NumPy (>= 1.8.2)
 - SciPy (>= 0.13.3)
 
+**Scikit-learn 0.20 is the last version to support Python2.7.**
+Scikit-learn 0.21 and later will require Python 3.5 or newer.
+
 For running the examples Matplotlib >= 1.3.1 is required. A few examples
 require scikit-image >= 0.9.3 and a few examples require pandas >= 0.13.1.
 
 
@@ -17,10 +17,6 @@ environment:
     SKLEARN_SKIP_NETWORK_TESTS: 1
 
   matrix:
-    - PYTHON: "C:\\Python37"
-      PYTHON_VERSION: "3.7.0"
-      PYTHON_ARCH: "32"
-
     - PYTHON: "C:\\Python37-x64"
       PYTHON_VERSION: "3.7.0"
       PYTHON_ARCH: "64"
@@ -29,10 +25,6 @@ environment:
       PYTHON_VERSION: "2.7.8"
       PYTHON_ARCH: "32"
 
-    - PYTHON: "C:\\Python27-x64"
-      PYTHON_VERSION: "2.7.8"
-      PYTHON_ARCH: "64"
-
 
 # Because we only have a single worker, we don't want to waste precious
 # appveyor CI time and make other PRs wait for repeated failures in a failing
@@ -49,7 +41,7 @@ install:
   # directly to master instead of just PR builds.
   # credits: JuliaLang developers.
   - ps: if ($env:APPVEYOR_PULL_REQUEST_NUMBER -and $env:APPVEYOR_BUILD_NUMBER -ne ((Invoke-RestMethod `
-        https://ci.appveyor.com/api/projects/$env:APPVEYOR_ACCOUNT_NAME/$env:APPVEYOR_PROJECT_SLUG/history?recordsNumber=50).builds | `
+        https://ci.appveyor.com/api/projects/$env:APPVEYOR_ACCOUNT_NAME/$env:APPVEYOR_PROJECT_SLUG/history?recordsNumber=500).builds | `
         Where-Object pullRequestId -eq $env:APPVEYOR_PULL_REQUEST_NUMBER)[0].buildNumber) { `
         throw "There are newer queued builds for this pull request, failing early." }
 
 
@@ -59,7 +59,7 @@
 from sklearn.ensemble import RandomForestClassifier, ExtraTreesClassifier
 from sklearn.ensemble import GradientBoostingClassifier
 from sklearn.metrics import zero_one_loss
-from sklearn.externals.joblib import Memory
+from sklearn.utils import Memory
 from sklearn.utils import check_array
 
 # Memoize the data extraction and memory map the resulting
 
@@ -119,7 +119,8 @@ def print_outlier_ratio(y):
     y_test = y[n_samples_train:]
 
     print('--- Fitting the IsolationForest estimator...')
-    model = IsolationForest(n_jobs=-1, random_state=random_state)
+    model = IsolationForest(behaviour='new', n_jobs=-1,
+                            random_state=random_state)
     tstart = time()
     model.fit(X_train)
     fit_time = time() - tstart
 
@@ -41,7 +41,7 @@
 from sklearn.ensemble import ExtraTreesClassifier
 from sklearn.ensemble import RandomForestClassifier
 from sklearn.dummy import DummyClassifier
-from sklearn.externals.joblib import Memory
+from sklearn.utils import Memory
 from sklearn.kernel_approximation import Nystroem
 from sklearn.kernel_approximation import RBFSampler
 from sklearn.metrics import zero_one_loss
 
@@ -22,7 +22,7 @@
 from sklearn.decomposition.nmf import _initialize_nmf
 from sklearn.decomposition.nmf import _beta_divergence
 from sklearn.decomposition.nmf import INTEGER_TYPES, _check_init
-from sklearn.externals.joblib import Memory
+from sklearn.utils import Memory
 from sklearn.exceptions import ConvergenceWarning
 from sklearn.utils.extmath import safe_sparse_dot, squared_norm
 from sklearn.utils import check_array
 
@@ -8,7 +8,7 @@
 import gc
 import time
 
-from sklearn.externals.joblib import Memory
+from sklearn.utils import Memory
 from sklearn.linear_model import (LogisticRegression, SGDClassifier)
 from sklearn.datasets import fetch_rcv1
 from sklearn.linear_model.sag import get_auto_step_size