Pytest Port

.travis.yml

@@ -39,7 +39,7 @@ install:
   - pip install coveralls
   - python setup.py install
 script:
-  - nosetests -q --with-flaky -a '!slow' --with-coverage --cover-package=deepchem
+  - pytest -m "not slow" deepchem
     -v deepchem --nologcapture
   - if [ $TRAVIS_PYTHON_VERSION == '3.7' ]; then
     find ./deepchem | grep .py$ |xargs python -m doctest -v;

contrib/autoencoder_models/test_tensorflowEncoders.py

@@ -12,7 +12,7 @@
 
 class TestTensorflowEncoders(TestCase):
 
-  @attr('slow')
+  @pytest.mark.slow('slow')
   def test_fit(self):
     tf_enc = TensorflowMoleculeEncoder.zinc_encoder()
 

deepchem/dock/tests/test_binding_pocket.py

@@ -10,8 +10,9 @@
 import unittest
 import os
 import numpy as np
+import pytest
+
 import deepchem as dc
-from nose.tools import nottest
 from deepchem.utils import rdkit_util
 
 logger = logging.getLogger(__name__)
@@ -147,7 +148,7 @@ def test_convex_find_pockets(self):
 
     assert len(pockets) < len(all_pockets)
 
-  @nottest
+  @pytest.mark.skip(reson="Unknown")
   def test_rf_convex_find_pockets(self):
     """Test that filter with pre-trained RF models works."""
     if sys.version_info >= (3, 0):

deepchem/dock/tests/test_docking.py

@@ -7,25 +7,27 @@
 
 import unittest
 import os
-from nose.plugins.attrib import attr
-from nose.tools import nottest
+
 import sys
+
+import pytest
+
 import deepchem as dc
 
 
 class TestDocking(unittest.TestCase):
   """
-  Does sanity checks on pose generation. 
+  Does sanity checks on pose generation.
   """
 
-  @nottest
+  @pytest.mark.skip(reason="Unknown")
   def test_vina_grid_rf_docker_init(self):
     """Test that VinaGridRFDocker can be initialized."""
     if sys.version_info >= (3, 0):
       return
     docker = dc.dock.VinaGridRFDocker(exhaustiveness=1, detect_pockets=False)
 
-  @nottest
+  @pytest.mark.skip(reason="Unknown")
   def test_pocket_vina_grid_rf_docker_init(self):
     """Test that VinaGridRFDocker w/pockets can be initialized."""
     if sys.version_info >= (3, 0):
@@ -45,7 +47,7 @@ def test_pocket_vina_grid_dnn_docker_init(self):
     docker = dc.dock.VinaGridDNNDocker(exhaustiveness=1, detect_pockets=True)
   '''
 
-  @attr("slow")
+  @pytest.mark.slow
   def test_vina_grid_rf_docker_dock(self):
     """Test that VinaGridRFDocker can dock."""
     if sys.version_info >= (3, 0):
@@ -64,7 +66,7 @@ def test_vina_grid_rf_docker_dock(self):
     assert os.path.exists(protein_docked)
     assert os.path.exists(ligand_docked)
 
-  @nottest
+  @pytest.mark.skip(reason="Unknown")
   def test_vina_grid_rf_docker_specified_pocket(self):
     """Test that VinaGridRFDocker can dock into spec. pocket."""
     if sys.version_info >= (3, 0):
@@ -85,7 +87,7 @@ def test_vina_grid_rf_docker_specified_pocket(self):
     # Check returned files exist
     assert score.shape == (1,)
 
-  @nottest
+  @pytest.mark.skip(reason="Unknown")
   def test_pocket_vina_grid_rf_docker_dock(self):
     """Test that VinaGridRFDocker can dock."""
     if sys.version_info >= (3, 0):
@@ -106,7 +108,7 @@ def test_pocket_vina_grid_rf_docker_dock(self):
     assert score.shape == (1,)
 
   '''
-  @attr("slow")
+  @pytest.mark.slow("slow")
   def test_vina_grid_dnn_docker_dock(self):
     """Test that VinaGridDNNDocker can dock."""
     current_dir = os.path.dirname(os.path.realpath(__file__))
@@ -122,7 +124,7 @@ def test_vina_grid_dnn_docker_dock(self):
     assert os.path.exists(protein_docked)
     assert os.path.exists(ligand_docked)
 
-  @attr('slow')
+  @pytest.mark.slow('slow')
   def test_pocket_vina_grid_dnn_docker_dock(self):
     """Test that VinaGridDNNDocker can dock."""
     if sys.version_info >= (3, 0):

deepchem/dock/tests/test_pose_generation.py

@@ -9,29 +9,29 @@
 import sys
 import unittest
 import deepchem as dc
-from nose.plugins.attrib import attr
+import pytest
 
 
 class TestPoseGeneration(unittest.TestCase):
   """
   Does sanity checks on pose generation.
   """
 
-  @attr("slow")
+  @pytest.mark.slow
   def test_vina_initialization(self):
     """Test that VinaPoseGenerator can be initialized."""
     # Note this may download autodock Vina...
     vpg = dc.dock.VinaPoseGenerator(detect_pockets=False, exhaustiveness=1)
 
-  @attr("slow")
+  @pytest.mark.slow("slow")
   def test_pocket_vina_initialization(self):
     """Test that VinaPoseGenerator can be initialized."""
     # Note this may download autodock Vina...
     if sys.version_info >= (3, 0):
       return
     vpg = dc.dock.VinaPoseGenerator(detect_pockets=True, exhaustiveness=1)
 
-  @attr("slow")
+  @pytest.mark.slow("slow")
   def test_vina_poses(self):
     """Test that VinaPoseGenerator creates pose files."""
     current_dir = os.path.dirname(os.path.realpath(__file__))
@@ -47,7 +47,7 @@ def test_vina_poses(self):
     assert os.path.exists(protein_pose_file)
     assert os.path.exists(ligand_pose_file)
 
-  @attr('slow')
+  @pytest.mark.slow('slow')
   def test_pocket_vina_poses(self):
     """Test that VinaPoseGenerator creates pose files."""
     if sys.version_info >= (3, 0):

deepchem/dock/tests/test_pose_scoring.py

@@ -12,6 +12,8 @@
 import os
 import shutil
 import numpy as np
+import pytest
+
 import deepchem as dc
 from sklearn.ensemble import RandomForestRegressor
 from subprocess import call
@@ -21,6 +23,7 @@
 logger = logging.getLogger(__name__)
 
 
+@pytest.mark.linux_only
 class TestPoseScoring(unittest.TestCase):
   """
   Does sanity checks on pose generation.

deepchem/feat/tests/test_graph_features.py

@@ -8,7 +8,8 @@
 import unittest
 import os
 import numpy as np
-from nose.plugins.attrib import attr
+import pytest
+
 from deepchem.feat.graph_features import ConvMolFeaturizer, AtomicConvFeaturizer
 
 
@@ -94,7 +95,7 @@ def test_alkane(self):
 
 class TestAtomicConvFeaturizer(unittest.TestCase):
 
-  @attr("slow")
+  @pytest.mark.slow
   def test_feature_generation(self):
     """Test if featurization works using AtomicConvFeaturizer."""
     dir_path = os.path.dirname(os.path.realpath(__file__))

deepchem/feat/tests/test_one_hot.py

@@ -1,7 +1,6 @@
 from unittest import TestCase
 
 import deepchem as dc
-from nose.tools import assert_equals
 
 
 class TestOneHotFeaturizer(TestCase):
@@ -14,6 +13,6 @@ def test_featurize(self):
     featurizer = dc.feat.one_hot.OneHotFeaturizer(dc.feat.one_hot.zinc_charset)
     one_hots = featurizer.featurize(mols)
     untransformed = featurizer.untransform(one_hots)
-    assert_equals(len(smiles), len(untransformed))
+    len(smiles) == len(untransformed)
     for i in range(len(smiles)):
-      assert_equals(smiles[i], untransformed[i][0])
+      assert smiles[i] == untransformed[i][0]

deepchem/feat/tests/test_rdkit_grid_features.py

@@ -5,6 +5,8 @@
 import unittest
 
 import numpy as np
+import pytest
+
 np.random.seed(123)
 from deepchem.feat import rdkit_grid_featurizer as rgf
 
@@ -450,6 +452,7 @@ def test_featurize_splif(self):
     self.assertEqual(dicts, expected_dicts)
 
 
+@pytest.mark.linux_only
 class TestRdkitGridFeaturizer(unittest.TestCase):
   """
   Test RdkitGridFeaturizer class defined in rdkit_grid_featurizer module.

deepchem/feat/tests/test_smiles_featurizers.py

@@ -1,6 +1,5 @@
 from unittest import TestCase
 import numpy as np
-from nose.tools import assert_equals
 from deepchem.feat import SmilesToSeq, SmilesToImage
 from deepchem.feat.smiles_featurizers import create_char_to_idx
 import os
@@ -27,8 +26,8 @@ def test_smiles_to_seq_featurize(self):
     expected_seq_len = self.feat.max_len + 2 * self.feat.pad_len
 
     features = self.feat.featurize(mols)
-    assert_equals(features.shape[0], len(smiles))
-    assert_equals(features.shape[-1], expected_seq_len)
+    assert features.shape[0] == len(smiles)
+    assert features.shape[-1] == expected_seq_len
 
   def test_reconstruct_from_seq(self):
     """Test SMILES reconstruction from features."""
@@ -38,4 +37,4 @@ def test_reconstruct_from_seq(self):
     features = self.feat.featurize(mols)
 
     reconstructed_smile = self.feat.smiles_from_seq(features[0])
-    assert_equals(smiles[0], reconstructed_smile)
+    assert smiles[0] == reconstructed_smile

deepchem/models/tests/test_atomic_conv.py

@@ -1,9 +1,11 @@
 """
 Tests for Atomic Convolutions.
 """
-from nose.plugins.attrib import attr
 
 import os
+
+import pytest
+
 import deepchem
 import numpy as np
 import tensorflow as tf
@@ -16,7 +18,7 @@
 
 class TestAtomicConv(unittest.TestCase):
 
-  @attr("slow")
+  @pytest.mark.slow
   def test_atomic_conv(self):
     """A simple test that initializes and fits an AtomicConvModel."""
     # For simplicity, let's assume both molecules have same number of
@@ -64,7 +66,7 @@ def test_atomic_conv(self):
     atomic_convnet.fit(train, nb_epoch=300)
     assert np.allclose(labels, atomic_convnet.predict(train), atol=0.01)
 
-  @attr("slow")
+  @pytest.mark.slow("slow")
   def test_atomic_conv_variable(self):
     """A simple test that initializes and fits an AtomicConvModel on variable input size."""
     # For simplicity, let's assume both molecules have same number of
@@ -100,7 +102,7 @@ def test_atomic_conv_variable(self):
     train = NumpyDataset(features, labels)
     atomic_convnet.fit(train, nb_epoch=1)
 
-  @attr("slow")
+  @pytest.mark.slow("slow")
   def test_atomic_conv_with_feat(self):
     """A simple test for running an atomic convolution on featurized data."""
     dir_path = os.path.dirname(os.path.realpath(__file__))

deepchem/models/tests/test_chemnet_models.py

@@ -3,13 +3,15 @@
 import numpy as np
 import tempfile
 
+import pytest
+
 import deepchem as dc
 from deepchem.data import NumpyDataset
 from deepchem.models import Smiles2Vec, ChemCeption
 from deepchem.feat import SmilesToSeq, SmilesToImage
 from deepchem.molnet.load_function.chembl25_datasets import chembl25_tasks
 from deepchem.feat.smiles_featurizers import create_char_to_idx
-from nose.plugins.attrib import attr
+
 from flaky import flaky
 
 
@@ -66,7 +68,7 @@ def get_dataset(self, mode="classification", featurizer="smiles2seq"):
 
     return dataset, metric
 
-  @attr('slow')
+  @pytest.mark.slow
   def test_smiles_to_vec_regression(self):
     dataset, metric = self.get_dataset(
         mode="regression", featurizer="smiles2seq")
@@ -81,7 +83,7 @@ def test_smiles_to_vec_regression(self):
     scores = model.evaluate(dataset, [metric], [])
     assert all(s < 0.1 for s in scores['mean_absolute_error'])
 
-  @attr('slow')
+  @pytest.mark.slow
   def test_smiles_to_vec_classification(self):
     dataset, metric = self.get_dataset(
         mode="classification", featurizer="smiles2seq")
@@ -96,7 +98,7 @@ def test_smiles_to_vec_classification(self):
     scores = model.evaluate(dataset, [metric], [])
     assert scores['mean-roc_auc_score'] >= 0.9
 
-  @attr('slow')
+  @pytest.mark.slow
   def test_chemception_regression(self):
     dataset, metric = self.get_dataset(
         mode="regression", featurizer="smiles2img")
@@ -109,7 +111,7 @@ def test_chemception_regression(self):
     scores = model.evaluate(dataset, [metric], [])
     assert all(s < 0.1 for s in scores['mean_absolute_error'])
 
-  @attr('slow')
+  @pytest.mark.slow
   def test_chemception_classification(self):
     dataset, metric = self.get_dataset(
         mode="classification", featurizer="smiles2img")
@@ -122,7 +124,7 @@ def test_chemception_classification(self):
     scores = model.evaluate(dataset, [metric], [])
     assert scores['mean-roc_auc_score'] >= 0.9
 
-  @attr('slow')
+  @pytest.mark.slow
   def test_chemception_fit_with_augmentation(self):
     dataset, metric = self.get_dataset(
         mode="classification", featurizer="smiles2img")

deepchem/models/tests/test_gan.py

@@ -4,7 +4,6 @@
 import unittest
 from tensorflow.keras.layers import Input, Concatenate, Dense
 from flaky import flaky
-from nose.plugins.attrib import attr
 
 
 def generate_batch(batch_size):