Drop Python 2 support (#331)

* Update Readme.rst * Update .appveyor.yml * Update DESCRIPTION * Update setup.py * Update README.md * Update setup.py * Update __init__.py * Update fastrgf_model.py * Update rgf_model.py * Update sklearn.py * Update test_rgf_python.py * Update rgf_model.py * Update fastrgf_model.py * Update Dockerfile * Update .appveyor.yml * Update Readme.rst * Update rgf_model.py * Update fastrgf_model.py * Update setup.py * Update utils.py * Update utils.py * Update utils.py * Update utils.py * Update utils.py
RGF-team · Feb 21, 2021 · cd99ce8 · cd99ce8
1 parent 1331b46
commit cd99ce8
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Showing 12 changed files with 56 additions and 75 deletions.
diff --git a/.appveyor.yml b/.appveyor.yml
@@ -9,7 +9,6 @@ environment:
   global:
     R_LIB_PATH: C:\RLibrary
   matrix:
-    - PYTHON_VERSION: 2.7
     - PYTHON_VERSION: 3.6
     - PYTHON_VERSION: 3.7
     - PYTHON_VERSION: 3.8
@@ -27,7 +26,6 @@ install:
   - set PATH=%PATH:C:\Program Files\Git\usr\bin;=%  # Delete sh.exe from PATH (mingw32-make fix)
   - ps: >-
       switch($env:PYTHON_VERSION) {
-          "2.7" {$env:MINICONDA = "C:\Miniconda"}
           "3.6" {$env:MINICONDA = "C:\Miniconda36"}
           "3.7" {$env:MINICONDA = "C:\Miniconda37"}
           default {$env:MINICONDA = "C:\Miniconda37"}
@@ -41,7 +39,7 @@ install:
   - set PATH=%MINICONDA%;%MINICONDA%\Scripts;%PATH%
   - conda config --set always_yes yes --set changeps1 no
   - conda update -q conda
-  - conda create -q -n test-environment python=%PYTHON_VERSION% joblib six numpy scipy pandas scikit-learn pytest
+  - conda create -q -n test-environment python=%PYTHON_VERSION% joblib numpy scipy pandas scikit-learn pytest
   - activate test-environment
   - cd python-package
   - ps: $env:RGF_VER = (Get-Content rgf\VERSION).trim()

diff --git a/R-package/DESCRIPTION b/R-package/DESCRIPTION
@@ -9,7 +9,7 @@ BugReports: https://github.com/RGF-team/rgf/issues
 URL: https://github.com/RGF-team/rgf/tree/master/R-package
 Description: Regularized Greedy Forest wrapper of the 'Regularized Greedy Forest' <https://github.com/RGF-team/rgf/tree/master/python-package> 'python' package, which also includes a Multi-core implementation (FastRGF) <https://github.com/RGF-team/rgf/tree/master/FastRGF>.
 License: MIT + file LICENSE
-SystemRequirements: Python (2.7 or >= 3.6), rgf_python, scikit-learn (>= 0.18.0), scipy, numpy. Detailed installation instructions for each operating system can be found in the README file.
+SystemRequirements: Python (>= 3.6), rgf_python, scikit-learn (>= 0.18.0), scipy, numpy. Detailed installation instructions for each operating system can be found in the README file.
 Depends:
     R(>= 3.2.0)
 Imports:

diff --git a/R-package/README.md b/R-package/README.md
@@ -35,7 +35,7 @@ The **RGF** package is a wrapper of the [Regularized Greedy Forest (RGF)](https:
 
 <br>
 
-* Python (2.7 or >= 3.6)
+* Python (>= 3.6)
 
 
 <br>
@@ -44,7 +44,7 @@ All modules should be installed in the default python configuration (the configu
 
 <br>
 
-#### **Debian/Ubuntu/Fedora**    [ installed / tested on Python 2.7 ]
+#### **Debian/Ubuntu/Fedora**
 
 <br>
 
@@ -87,7 +87,7 @@ sudo python setup.py install
 
 
 
-#### **Mac OS X**            [ installed / tested on Python >= 3.6 ]
+#### **Mac OS X**
 
 <br>
 
@@ -247,7 +247,7 @@ UserWarning: Cannot find FastRGF executable files. FastRGF estimators will be un
 
 <br><br>
 
-#### **Windows OS**            [ installed / tested on Python >= 3.6 ]
+#### **Windows OS**
 
 <br>
 

diff --git a/python-package/Readme.rst b/python-package/Readme.rst
@@ -54,9 +54,8 @@ Examples of using FastRGF estimators could be found `here <https://github.com/RG
 Software Requirements
 ---------------------
 
--  Python (2.7 or >= 3.6)
+-  Python (>= 3.6)
 -  joblib
--  six
 -  scikit-learn (>= 0.18)
 
 Installation

diff --git a/python-package/docker/Dockerfile b/python-package/docker/Dockerfile
@@ -10,7 +10,7 @@ RUN apt-get update && \
     /bin/bash Miniconda3-latest-Linux-x86_64.sh -f -b -p /opt/conda && \
     export PATH="/opt/conda/bin:$PATH" && \
     # rgf_python
-    conda install -y -q numpy joblib six scipy scikit-learn pandas && \
+    conda install -y -q numpy joblib scipy scikit-learn pandas && \
     git clone https://github.com/RGF-team/rgf.git && \
     cd rgf/python-package && python setup.py install && \
 

diff --git a/python-package/rgf/__init__.py b/python-package/rgf/__init__.py
@@ -1,6 +1,3 @@
-from __future__ import absolute_import
-
-
 __all__ = ('RGFClassifier', 'RGFRegressor',
            'FastRGFClassifier', 'FastRGFRegressor')
 

diff --git a/python-package/rgf/fastrgf_model.py b/python-package/rgf/fastrgf_model.py
@@ -1,11 +1,8 @@
-from __future__ import absolute_import
-
 import os
 from math import ceil
 
 import numpy as np
 from joblib import cpu_count
-from six import string_types
 from sklearn.base import ClassifierMixin, RegressorMixin, is_classifier
 from sklearn.exceptions import NotFittedError
 
@@ -193,7 +190,7 @@ def _validate_params(self,
         elif l2 < 0:
             raise ValueError("l2 must be no smaller than 0.0 but was %r." % l2)
 
-        if not isinstance(opt_algorithm, string_types):
+        if not isinstance(opt_algorithm, str):
             raise ValueError("opt_algorithm must be a string, got {0}.".format(
                 type(opt_algorithm)))
         elif opt_algorithm not in ALGORITHMS:
@@ -257,14 +254,14 @@ def _validate_params(self,
             raise ValueError(
                 "verbose must be no smaller than 0 but was %r." % verbose)
 
-        if not isinstance(loss, string_types):
+        if not isinstance(loss, str):
             raise ValueError(
                 "loss must be a string, got {0}.".format(type(loss)))
         elif loss not in LOSSES:
             raise ValueError(
                 "loss must be 'LS' or 'MODLS' or 'LOGISTIC' but was %r." % loss)
 
-        if not isinstance(calc_prob, string_types):
+        if not isinstance(calc_prob, str):
             raise ValueError(
                 "calc_prob must be a string, got {0}.".format(type(calc_prob)))
         elif calc_prob not in ("sigmoid", "softmax"):
@@ -317,7 +314,7 @@ def _set_params_with_dependencies(self):
         self._set_target_and_loss()
 
     def _get_params(self):
-        res = super(FastRGFEstimatorBase, self)._get_params()
+        res = super()._get_params()
         res.update(dict(max_depth=self.max_depth,
                         max_leaf=self.max_leaf,
                         tree_gain_ratio=self.tree_gain_ratio,
@@ -373,7 +370,7 @@ def __init__(self,
                  verbose=0):
         if not utils.Config().FASTRGF_AVAILABLE:
             raise Exception('FastRGF estimators are unavailable for usage.')
-        super(FastRGFRegressor, self).__init__()
+        super().__init__()
         self.n_estimators = n_estimators
         self.max_depth = max_depth
         self.max_leaf = max_leaf
@@ -430,7 +427,7 @@ def __init__(self,
                  verbose=0):
         if not utils.Config().FASTRGF_AVAILABLE:
             raise Exception('FastRGF estimators are unavailable for usage.')
-        super(FastRGFClassifier, self).__init__()
+        super().__init__()
         self.n_estimators = n_estimators
         self.max_depth = max_depth
         self.max_leaf = max_leaf

diff --git a/python-package/rgf/rgf_model.py b/python-package/rgf/rgf_model.py
@@ -1,12 +1,9 @@
-from __future__ import absolute_import
-
 from glob import glob
 from math import ceil
 from shutil import copyfile
 
 import numpy as np
 from joblib import Parallel, delayed, cpu_count
-from six import string_types
 from sklearn.base import ClassifierMixin, RegressorMixin, is_classifier
 from sklearn.exceptions import NotFittedError
 
@@ -182,14 +179,14 @@ def _validate_params(self,
             raise ValueError(
                 "test_interval must be greater than 0 but was %r." % test_interval)
 
-        if not isinstance(algorithm, string_types):
+        if not isinstance(algorithm, str):
             raise ValueError(
                 "algorithm must be a string, got {0}.".format(type(algorithm)))
         elif algorithm not in ALGORITHMS:
             raise ValueError(
                 "algorithm must be 'RGF' or 'RGF_Opt' or 'RGF_Sib' but was %r." % algorithm)
 
-        if not isinstance(loss, string_types):
+        if not isinstance(loss, str):
             raise ValueError(
                 "loss must be a string, got {0}.".format(type(loss)))
         elif loss not in LOSSES:
@@ -269,19 +266,19 @@ def _validate_params(self,
             raise ValueError(
                 "verbose must be no smaller than 0 but was %r." % verbose)
 
-        if not isinstance(memory_policy, string_types):
+        if not isinstance(memory_policy, str):
             raise ValueError("memory_policy must be a string, got {0}.".format(
                 type(memory_policy)))
         elif memory_policy not in ("conservative", "generous"):
             raise ValueError(
                 "memory_policy must be 'conservative' or 'generous' but was %r." % memory_policy)
 
-        if init_model is not None and not isinstance(init_model, string_types):
+        if init_model is not None and not isinstance(init_model, str):
             raise ValueError(
                 "init_model must be a string or None, got {0}.".format(
                     type(init_model)))
 
-        if not isinstance(calc_prob, string_types):
+        if not isinstance(calc_prob, str):
             raise ValueError(
                 "calc_prob must be a string, got {0}.".format(type(calc_prob)))
         elif calc_prob not in ("sigmoid", "softmax"):
@@ -345,7 +342,7 @@ def _set_params_with_dependencies(self):
             self._n_iter = self.n_iter
 
     def _get_params(self):
-        res = super(RGFEstimatorBase, self)._get_params()
+        res = super()._get_params()
         res.update(dict(max_leaf=self.max_leaf,
                         test_interval=self.test_interval,
                         algorithm=self.algorithm,
@@ -474,7 +471,7 @@ def __init__(self,
                  init_model=None):
         if not utils.Config().RGF_AVAILABLE:
             raise Exception('RGF estimators are unavailable for usage.')
-        super(RGFRegressor, self).__init__()
+        super().__init__()
         self.max_leaf = max_leaf
         self.test_interval = test_interval
         self.algorithm = algorithm
@@ -508,7 +505,7 @@ def __init__(self,
         __doc__ = __doc__.replace(_template, _value)
 
     def save_model(self, filename):
-        super(RGFRegressor, self).save_model(filename)
+        super().save_model(filename)
 
     _regressor_save_model_specific_values = {
         '{%file_singular_or_plural%}': 'file',
@@ -541,7 +538,7 @@ def __init__(self,
                  init_model=None):
         if not utils.Config().RGF_AVAILABLE:
             raise Exception('RGF estimators are unavailable for usage.')
-        super(RGFClassifier, self).__init__()
+        super().__init__()
         self.max_leaf = max_leaf
         self.test_interval = test_interval
         self.algorithm = algorithm
@@ -596,7 +593,7 @@ def __init__(self,
         __doc__ = __doc__.replace(_template, _value)
 
     def save_model(self, filename):
-        super(RGFClassifier, self).save_model(filename)
+        super().save_model(filename)
 
     _classifier_save_model_specific_values = {
         '{%file_singular_or_plural%}': 'file(s)',

diff --git a/python-package/rgf/sklearn.py b/python-package/rgf/sklearn.py
@@ -1,5 +1,3 @@
-from __future__ import absolute_import
-
 __all__ = ('RGFClassifier', 'RGFRegressor',
            'FastRGFClassifier', 'FastRGFRegressor')
 

diff --git a/python-package/rgf/utils.py b/python-package/rgf/utils.py
@@ -1,5 +1,3 @@
-from __future__ import absolute_import
-
 import atexit
 import codecs
 import glob
@@ -9,11 +7,12 @@
 import stat
 import subprocess
 import warnings
+from configparser import MissingSectionHeaderError, RawConfigParser
+from io import StringIO
 from tempfile import gettempdir
 from threading import Lock
 from uuid import uuid4
 
-import six
 import numpy as np
 import scipy.sparse as sp
 from sklearn.base import BaseEstimator
@@ -74,17 +73,17 @@ def __init__(self, verbose=False):
     @classmethod
     def init_paths(cls):
         if cls.TEMP_PATH is None:
-            config = six.moves.configparser.RawConfigParser()
+            config = RawConfigParser()
             path = os.path.join(os.path.expanduser('~'), '.rgfrc')
 
             try:
                 with codecs.open(path, 'r', 'utf-8') as cfg:
-                    with six.StringIO(cfg.read()) as strIO:
-                        config.readfp(strIO)
-            except six.moves.configparser.MissingSectionHeaderError:
+                    with StringIO(cfg.read()) as strIO:
+                        config.read_file(strIO)
+            except MissingSectionHeaderError:
                 with codecs.open(path, 'r', 'utf-8') as cfg:
-                    with six.StringIO('[glob]\n' + cfg.read()) as strIO:
-                        config.readfp(strIO)
+                    with StringIO('[glob]\n' + cfg.read()) as strIO:
+                        config.read_file(strIO)
             except Exception:
                 pass
 
@@ -244,7 +243,6 @@ def increment(self):
 
 
 def sparse_savetxt(filename, input_array, including_header=True):
-    zip_func = six.moves.zip
     if sp.isspmatrix_csr(input_array):
         input_array = input_array.tocoo()
     else:
@@ -255,7 +253,7 @@ def sparse_savetxt(filename, input_array, including_header=True):
     with open(filename, 'w') as fw:
         if including_header:
             fw.write('sparse {0:d}\n'.format(input_array.shape[-1]))
-        for i, j, v in zip_func(input_array.row, input_array.col, input_array.data):
+        for i, j, v in zip(input_array.row, input_array.col, input_array.data):
             if i == current_sample_row:
                 line.append('{0}:{1}'.format(j, v))
             else:

diff --git a/python-package/setup.py b/python-package/setup.py
@@ -5,7 +5,6 @@
 from setuptools.command.install_lib import install_lib
 from setuptools.command.sdist import sdist
 from shutil import rmtree
-import io
 import logging
 import os
 import subprocess
@@ -19,7 +18,7 @@
 
 
 def read(filename):
-    return io.open(os.path.join(CURRENT_DIR, filename), encoding='utf-8').read()
+    return open(os.path.join(CURRENT_DIR, filename), encoding='utf-8').read()
 
 
 def copy_files():
@@ -380,7 +379,7 @@ def run(self):
                 'sdist': CustomSdist},
       packages=find_packages(),
       include_package_data=True,
-      install_requires=["joblib", "six", "scikit-learn>=0.18"],
+      install_requires=["joblib", "scikit-learn>=0.18"],
       classifiers=['Development Status :: 5 - Production/Stable',
                    'Intended Audience :: Science/Research',
                    'License :: OSI Approved :: MIT License',
@@ -389,8 +388,6 @@ def run(self):
                    'Operating System :: Microsoft :: Windows',
                    'Operating System :: POSIX',
                    'Operating System :: Unix',
-                   'Programming Language :: Python :: 2',
-                   'Programming Language :: Python :: 2.7',
                    'Programming Language :: Python :: 3',
                    'Programming Language :: Python :: 3.6',
                    'Programming Language :: Python :: 3.7',