Update CI (keras-team#159)

### Summary
Update CI, basically separate every test component.
- PEP8 (no dependencies installed at all)
- PyTests (install test dependencies), runs for Python 2.6, 3.6 and Keras PyPI and Keras HEAD
- Imports (install package dependencies), runs for Python 2.6, 3.6. Basically imports the package and modules as a check that nothing breaks.

I also change where some of the logic happens. Before there was some logic in `travis.yml` that in my opinion `shuoldn't` be there but in `setup.py`, in this way the user can actually execute the same that travis is doing by `pip install -e .[tests] && pytest tests` or  `pip install -e .[pep8] && flake8`. So much easier to debug without the need to push and create a pull request to reproduce travis execution (up to some complexity).

This should lead to a more robust check and specially avoid the error given during the release of 1.0.6. That error for example will be catch in two places now: 
- PEP8: as an unused import
- Imports: since pandas is not installed on that check.

NOTE: The phase caching the bug in the 1.0.6 should not be the Pytest phase, that actually should work. Since pandas is needed for unit testing.

By running these tests on the current state of the repo I already found several bugs in the code, several overhead variables being assigned but unused (specially in tests) and like 30 plus PEP8 violations.

### Related Issues
keras-team#154 

### PR Overview

- [ n] This PR requires new unit tests [y/n] (make sure tests are included)
- [ n] This PR requires to update the documentation [y/n] (make sure the docs are up-to-date)
- [ y] This PR is backwards compatible [y/n]
- [ n] This PR changes the current API [y/n] (all API changes need to be approved by fchollet)

.travis.yml

@@ -3,20 +3,37 @@ dist: trusty
 language: python
 matrix:
     include:
+        # check code style and Python 2.7
         - python: 2.7
           env: TEST_MODE=PEP8
+        # run tests with keras from source and Python 2.7
         - python: 2.7
           env: KERAS_HEAD=true
+          env: TEST_MODE=TESTS
+        # run tests with keras from source and Python 3.6
         - python: 3.6
           env: KERAS_HEAD=true
+          env: TEST_MODE=TESTS
+        # run tests with keras from PyPI and Python 2.7
         - python: 2.7
+          env: TEST_MODE=TESTS
+        # run tests with keras from PyPI and Python 3.6
         - python: 3.6
-install:
-  # code below is taken from http://conda.pydata.org/docs/travis.html
+          env: TEST_MODE=TESTS
+        # run import test and Python 2.7
+        - python: 2.7
+          env: TEST_MODE=IMPORTS
+        # run import test and Python 3.6
+        - python: 3.6
+          env: TEST_MODE=IMPORTS
+
+
+before_install:
+  - sudo apt-get update
   # We do this conditionally because it saves us some downloading if the
   # version is the same.
   - if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]]; then
-      wget https://repo.continuum.io/miniconda/Miniconda-latest-Linux-x86_64.sh -O miniconda.sh;
+      wget https://repo.continuum.io/miniconda/Miniconda2-latest-Linux-x86_64.sh -O miniconda.sh;
     else
       wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh;
     fi
@@ -27,32 +44,26 @@ install:
   - conda update -q conda
   # Useful for debugging any issues with conda
   - conda info -a
-
-  - conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION pytest pandas
+  - conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION
   - source activate test-environment
-  - pip install --only-binary=numpy,scipy numpy nose scipy keras
-
-  # set library path
-  - export LD_LIBRARY_PATH=$HOME/miniconda/envs/test-environment/lib/:$LD_LIBRARY_PATH
 
-  # install PIL for image tests
-  - if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]]; then
-      conda install pil;
-    elif [[ "$TRAVIS_PYTHON_VERSION" == "3.6" ]]; then
-      conda install Pillow;
-    fi
+install:
   - if [[ $KERAS_HEAD == "true" ]]; then
-      pip install --no-deps git+https://github.com/keras-team/keras.git ;
+      pip install --no-deps git+https://github.com/keras-team/keras.git --upgrade;
+    fi
+  - if [[ "$TEST_MODE" == "PEP8" ]]; then
+      pip install -e .[pep8];
+    elif [[ "$TEST_MODE" == "TESTS" ]]; then
+      pip install -e .[tests];
+    elif [[ "$TEST_MODE" == "IMPORTS" ]]; then
+      pip install .;
     fi
-  - pip install -e .[tests]
-
-  # install TensorFlow (CPU version).
-  - pip install tensorflow==1.7
 
-# command to run tests
 script:
   - if [[ "$TEST_MODE" == "PEP8" ]]; then
-      PYTHONPATH=$PWD:$PYTHONPATH py.test --pep8 -m pep8 -n0;
-    else
-      PYTHONPATH=$PWD:$PYTHONPATH py.test tests/ --cov-config .coveragerc --cov=keras_preprocessing tests/;
+      flake8 -v --count;
+    elif [[ "$TEST_MODE" == "TESTS" ]]; then
+      py.test tests --cov-config .coveragerc --cov=keras_preprocessing tests;
+    elif [[ "$TEST_MODE" == "IMPORTS" ]]; then
+      python -c "import keras_preprocessing; from keras_preprocessing import image; from keras_preprocessing import sequence; from keras_preprocessing import text";
     fi

keras_preprocessing/__init__.py

@@ -39,4 +39,5 @@ def get_keras_submodule(name):
     elif name == 'utils':
         return _KERAS_UTILS
 
+
 __version__ = '1.0.8'

keras_preprocessing/image/__init__.py

@@ -1,9 +1,7 @@
 """Enables dynamic setting of underlying Keras module.
 """
 from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
+# flake8: noqa:F401
 from .affine_transformations import *
 from .dataframe_iterator import DataFrameIterator
 from .directory_iterator import DirectoryIterator

keras_preprocessing/image/affine_transformations.py

@@ -4,19 +4,13 @@
 from __future__ import division
 from __future__ import print_function
 
-import os
-import re
-import warnings
-
 import numpy as np
 
 from .utils import (array_to_img,
                     img_to_array)
 
 try:
     import scipy
-    # scipy.linalg cannot be accessed until explicitly imported
-    from scipy import linalg
     # scipy.ndimage cannot be accessed until explicitly imported
     from scipy import ndimage
 except ImportError:
@@ -327,7 +321,7 @@ def apply_affine_transform(x, theta=0, tx=0, ty=0, shear=0, zx=1, zy=1,
         final_affine_matrix = transform_matrix[:2, :2]
         final_offset = transform_matrix[:2, 2]
 
-        channel_images = [scipy.ndimage.interpolation.affine_transform(
+        channel_images = [ndimage.interpolation.affine_transform(
             x_channel,
             final_affine_matrix,
             final_offset,

keras_preprocessing/image/dataframe_iterator.py

@@ -7,13 +7,8 @@
 import os
 import warnings
 
-import numpy as np
-
 from .iterator import BatchFromFilesMixin, Iterator
-from .utils import (array_to_img,
-                    get_extension,
-                    img_to_array,
-                    load_img)
+from .utils import get_extension
 
 
 class DataFrameIterator(BatchFromFilesMixin, Iterator):
@@ -220,7 +215,7 @@ def remove_classes(labels, classes):
             else:
                 raise TypeError(
                     "Expect string, list or tuple but found {} in {} column "
-                    .format(type(x), y_col)
+                    .format(type(labels), y_col)
                 )
 
         if classes:

keras_preprocessing/image/directory_iterator.py

@@ -11,10 +11,7 @@
 import numpy as np
 
 from .iterator import BatchFromFilesMixin, Iterator
-from .utils import (array_to_img,
-                    img_to_array,
-                    _list_valid_filenames_in_directory,
-                    load_img)
+from .utils import _list_valid_filenames_in_directory
 
 
 class DirectoryIterator(BatchFromFilesMixin, Iterator):

keras_preprocessing/image/image_data_generator.py

@@ -14,7 +14,6 @@
     # scipy.linalg cannot be accessed until explicitly imported
     from scipy import linalg
     # scipy.ndimage cannot be accessed until explicitly imported
-    from scipy import ndimage
 except ImportError:
     scipy = None
 
@@ -957,6 +956,6 @@ def fit(self, x,
             flat_x = np.reshape(
                 x, (x.shape[0], x.shape[1] * x.shape[2] * x.shape[3]))
             sigma = np.dot(flat_x.T, flat_x) / flat_x.shape[0]
-            u, s, _ = scipy.linalg.svd(sigma)
+            u, s, _ = linalg.svd(sigma)
             s_inv = 1. / np.sqrt(s[np.newaxis] + self.zca_epsilon)
             self.principal_components = (u * s_inv).dot(u.T)

keras_preprocessing/image/iterator.py

@@ -4,6 +4,7 @@
 from __future__ import division
 from __future__ import print_function
 
+import os
 import threading
 import numpy as np
 from keras_preprocessing import get_keras_submodule

keras_preprocessing/image/utils.py

@@ -156,7 +156,7 @@ def _recursive_list(subpath):
                 warnings.warn('Using ".tiff" files with multiple bands '
                               'will cause distortion. Please verify your output.')
             if get_extension(fname) in white_list_formats:
-                    yield root, fname
+                yield root, fname
 
 
 def _list_valid_filenames_in_directory(directory, white_list_formats, split,

keras_preprocessing/sequence.py

@@ -384,15 +384,15 @@ def get_config(self):
             data = self.data.tolist()
         try:
             json_data = json.dumps(data)
-        except:
+        except TypeError:
             raise TypeError('Data not JSON Serializable:', data)
 
         targets = self.targets
         if type(self.targets).__module__ == np.__name__:
             targets = self.targets.tolist()
         try:
             json_targets = json.dumps(targets)
-        except:
+        except TypeError:
             raise TypeError('Targets not JSON Serializable:', targets)
 
         return {

keras_preprocessing/text.py

@@ -126,7 +126,8 @@ def hashing_trick(text, n,
     if hash_function is None:
         hash_function = hash
     elif hash_function == 'md5':
-        hash_function = lambda w: int(md5(w.encode()).hexdigest(), 16)
+        def hash_function(w):
+            return int(md5(w.encode()).hexdigest(), 16)
 
     seq = text_to_word_sequence(text,
                                 filters=filters,

pytest.ini → setup.cfg

@@ -1,18 +1,16 @@
 # Configuration of py.test
-[pytest]
-addopts=-v
-        -n 2
-        --durations=20
-
+[tool:pytest]]
+addopts=-v -n 2 --durations=20
 # Do not run tests in the build folder
-norecursedirs= build
+norecursedirs=build
 
+[flake8]
 # Use 85 as max line length in PEP8 test.
-pep8maxlinelength=85
-
+max-line-length=85
+# do not run pep8 test in the build folder
+exclude=build
 # PEP-8 The following are ignored:
 # E731 do not assign a lambda expression, use a def
 # E402 module level import not at top of file
-
 pep8ignore=* E731 \
-           * E402 \
+           * E402 \

setup.py

@@ -1,3 +1,5 @@
+import sys
+
 from setuptools import setup
 from setuptools import find_packages
 
@@ -33,10 +35,14 @@
       install_requires=['numpy>=1.9.1',
                         'six>=1.9.0'],
       extras_require={
-          'tests': ['pytest',
-                    'pytest-pep8',
+          'tests': ['pandas',
+                    'Pillow' if sys.version_info >= (3, 0) else 'pillow',
+                    'tensorflow==1.7',  # CPU version
+                    'keras',
+                    'pytest',
                     'pytest-xdist',
                     'pytest-cov'],
+          'pep8': ['flake8'],
           'image': ['scipy>=0.14',
                     'Pillow>=5.2.0'],
       },

tests/image_test.py

@@ -4,17 +4,9 @@
 import os
 import tempfile
 import shutil
-import keras
 import pandas as pd
 import random
 
-# TODO: remove the 3 lines below once the Keras release
-# is configured to use keras_preprocessing
-import keras_preprocessing
-keras_preprocessing.set_keras_submodules(
-    backend=keras.backend, utils=keras.utils)
-
-# This enables this import
 from keras_preprocessing import image
 
 
@@ -262,7 +254,7 @@ def test_image_data_generator_with_validation_split(self):
 
     def test_image_data_generator_with_split_value_error(self):
         with pytest.raises(ValueError):
-            generator = image.ImageDataGenerator(validation_split=5)
+            image.ImageDataGenerator(validation_split=5)
 
     def test_image_data_generator_invalid_data(self):
         generator = image.ImageDataGenerator(
@@ -535,12 +527,14 @@ def test_dataframe_iterator(self, tmpdir):
                                      dtype=str)
         batch_x, batch_y = next(df_multiple_y_iterator)
         with pytest.raises(TypeError):
-            df_multiple_y_iterator = generator.flow_from_dataframe(
+            generator.flow_from_dataframe(
                 df_regression, str(tmpdir), y_col=["col1", "col2"],
-                class_mode="other")
+                class_mode="other"
+            )
         with pytest.raises(TypeError):
-            df_single_y_iterator = generator.flow_from_dataframe(
-                df_regression, str(tmpdir), y_col="col1", class_mode="other")
+            generator.flow_from_dataframe(
+                df_regression, str(tmpdir), y_col="col1", class_mode="other"
+            )
         # check number of classes and images
         assert len(df_iterator.class_indices) == num_classes
         assert len(df_iterator.classes) == count
@@ -913,12 +907,12 @@ def test_dataframe_iterator_with_drop_duplicates(self, tmpdir):
         # create iterators
         generator = image.ImageDataGenerator()
         df_drop_iterator = generator.flow_from_dataframe(
-            df2, str(tmpdir), class_mode=None, drop_duplicates=True)
+            df, str(tmpdir), class_mode=None, drop_duplicates=True)
         df_no_drop_iterator = generator.flow_from_dataframe(
             df2, str(tmpdir), class_mode=None, drop_duplicates=False)
 
         # Test drop_duplicates
-        assert df_drop_iterator.n == len(set(input_filenames2))
+        assert df_drop_iterator.n == len(set(input_filenames))
         assert df_no_drop_iterator.n == len(input_filenames2)
 
     def test_dataframe_iterator_with_subdirs(self, tmpdir):
@@ -1230,5 +1224,6 @@ def test_load_img(self, tmpdir):
             loaded_im = image.load_img(filename_rgb, target_size=(25, 25),
                                        interpolation="unsupported")
 
+
 if __name__ == '__main__':
     pytest.main([__file__])

tests/sequence_test.py

@@ -5,14 +5,6 @@
 from numpy.testing import assert_equal
 from numpy.testing import assert_raises
 
-import keras
-
-# TODO: remove the 3 lines below once the Keras release
-# is configured to use keras_preprocessing
-import keras_preprocessing
-keras_preprocessing.set_keras_submodules(
-    backend=keras.backend, utils=keras.utils)
-
 from keras_preprocessing import sequence
 
 

tests/text_test.py

@@ -3,13 +3,6 @@
 import pytest
 
 import keras
-
-# TODO: remove the 3 lines below once the Keras release
-# is configured to use keras_preprocessing
-import keras_preprocessing
-keras_preprocessing.set_keras_submodules(
-    backend=keras.backend, utils=keras.utils)
-
 from keras_preprocessing import text
 from collections import OrderedDict
 
@@ -54,7 +47,7 @@ def test_tokenizer():
     tokenizer.fit_on_sequences(sequences)
 
     for mode in ['binary', 'count', 'tfidf', 'freq']:
-        matrix = tokenizer.texts_to_matrix(sample_texts, mode)
+        tokenizer.texts_to_matrix(sample_texts, mode)
 
 
 def test_tokenizer_serde_no_fitting():