[PARO-779] Prep for v2.2.1 release; remove six dependency (#65)

* RM no more six dependency

* MAINT version bump to 2.2.1

* MAINT update changelog

CHANGELOG.md

@@ -4,6 +4,11 @@ This project adheres to [Semantic Versioning](http://semver.org/).
 
 ## Unreleased
 
+## 2.2.1 - 2020-06-30
+### Fix
+* [#65](https://github.com/civisanalytics/python-glmnet/pull/65)
+  Remove `six` dependency entirely.
+
 ## 2.2.0 - 2020-06-29
 ### Changed
 * [#57](https://github.com/civisanalytics/python-glmnet/pull/57)

glmnet/linear.py

@@ -10,10 +10,10 @@
 
 from .errors import _check_error_flag
 from _glmnet import elnet, spelnet, solns
-from .util import (_fix_lambda_path,
-                   _check_user_lambda,
-                   _interpolate_model,
-                   _score_lambda_path)
+from glmnet.util import (_fix_lambda_path,
+                         _check_user_lambda,
+                         _interpolate_model,
+                         _score_lambda_path)
 
 
 class ElasticNet(BaseEstimator):

glmnet/logistic.py

@@ -12,10 +12,10 @@
 
 from .errors import _check_error_flag
 from _glmnet import lognet, splognet, lsolns
-from .util import (_fix_lambda_path,
-                   _check_user_lambda,
-                   _interpolate_model,
-                   _score_lambda_path)
+from glmnet.util import (_fix_lambda_path,
+                         _check_user_lambda,
+                         _interpolate_model,
+                         _score_lambda_path)
 
 
 class LogitNet(BaseEstimator):

glmnet/scorer.py

@@ -21,10 +21,9 @@
                roc_auc_score, average_precision_score,
                precision_score, recall_score, log_loss)
 from sklearn.utils.multiclass import type_of_target
-import six
 
 
-class _BaseScorer(six.with_metaclass(ABCMeta, object)):
+class _BaseScorer(metaclass=ABCMeta):
     def __init__(self, score_func, sign, kwargs):
         self._kwargs = kwargs
         self._score_func = score_func
@@ -173,7 +172,7 @@ def _factory_args(self):
 
 
 def get_scorer(scoring):
-    if isinstance(scoring, six.string_types):
+    if isinstance(scoring, str):
         try:
             scorer = SCORERS[scoring]
         except KeyError:

glmnet/tests/test_linear.py

@@ -9,7 +9,7 @@
 from sklearn.utils import estimator_checks
 from sklearn.utils.testing import ignore_warnings
 
-from util import sanity_check_regression
+from glmnet.tests.util import sanity_check_regression
 
 from glmnet import ElasticNet
 

glmnet/tests/test_logistic.py

@@ -10,7 +10,7 @@
 from sklearn.utils import estimator_checks, class_weight
 from sklearn.utils.testing import ignore_warnings
 
-from util import sanity_check_logistic
+from glmnet.tests.util import sanity_check_logistic
 
 from glmnet import LogitNet
 

glmnet/tests/test_pandas.py

@@ -3,7 +3,7 @@
 from sklearn.datasets import make_regression, make_classification
 from glmnet import LogitNet, ElasticNet
 
-from util import sanity_check_logistic, sanity_check_regression
+from glmnet.tests.util import sanity_check_logistic, sanity_check_regression
 
 pd = None
 try:

glmnet/util.py

@@ -9,7 +9,7 @@
 from sklearn.exceptions import UndefinedMetricWarning
 from joblib import Parallel, delayed
 
-from .scorer import check_scoring
+from glmnet.scorer import check_scoring
 
 
 def _score_lambda_path(est, X, y, groups, sample_weight, relative_penalties,

setup.py

@@ -18,7 +18,7 @@
              " \n  $ pip install numpy")
 
 
-_VERSION = "2.2.0"
+_VERSION = "2.2.1"
 
 f_compile_args = ['-ffixed-form', '-fdefault-real-8']