applied black

test/unit_tests/conftest.py

@@ -1,4 +1,5 @@
 import random
+import random
 import string
 import tempfile
 from functools import partial
@@ -15,8 +16,12 @@ from image_prediction.classifier.classifier import Classifier
 from image_prediction.classifier.image_classifier import ImageClassifier
 from image_prediction.estimator.adapter.adapter import EstimatorAdapter
 from image_prediction.estimator.preprocessor.preprocessors.basic import BasicPreprocessor
-from image_prediction.exceptions import UnknownEstimatorAdapter, UnknownImageExtractor, UnknownDatabaseType, \
-    UnknownLabelFormat
+from image_prediction.exceptions import (
+    UnknownEstimatorAdapter,
+    UnknownImageExtractor,
+    UnknownDatabaseType,
+    UnknownLabelFormat,
+)
 from image_prediction.image_extractor.extractor import ImageMetadataPair
 from image_prediction.image_extractor.extractors.mock import ImageExtractorMock
 from image_prediction.image_extractor.extractors.parsable import ParsablePDFImageExtractor
@@ -87,7 +92,7 @@ def label_format(request):
 
 @pytest.fixture
 def expected_predictions_mapped(
-        label_format, batch_of_expected_string_labels, batch_of_expected_label_to_probability_mappings
+    label_format, batch_of_expected_string_labels, batch_of_expected_label_to_probability_mappings
 ):
     if label_format == "index":
         return batch_of_expected_string_labels
@@ -98,9 +103,7 @@ def expected_predictions_mapped(
 
 
 @pytest.fixture
-def expected_predictions(
-        label_format, batch_of_expected_numeric_labels, batch_of_expected_probability_arrays
-):
+def expected_predictions(label_format, batch_of_expected_numeric_labels, batch_of_expected_probability_arrays):
     if label_format == "index":
         return batch_of_expected_numeric_labels
     elif label_format == "probability":
@@ -111,7 +114,7 @@ def expected_predictions(
 
 @pytest.fixture
 def estimator_adapter(
-        estimator_type, estimator_mock, keras_model, model_handle_mock, output_batch_generator, monkeypatch
+    estimator_type, estimator_mock, keras_model, model_handle_mock, output_batch_generator, monkeypatch
 ):
     if estimator_type == "mock":
         estimator_adapter = EstimatorAdapter(estimator_mock)
@@ -227,13 +230,14 @@ def map_labels(numeric_labels, classes):
 
 @pytest.fixture
 def metadata_plus_mapped_prediction(expected_predictions_mapped, metadata):
-    return [{"classification": epm,  **mdt} for epm, mdt in zip(expected_predictions_mapped, metadata)]
+    return [{"classification": epm, **mdt} for epm, mdt in zip(expected_predictions_mapped, metadata)]
 
 
 @pytest.fixture
 def metadata_formatted_plus_mapped_prediction_formatted(expected_predictions_mapped_and_formatted, metadata_formatted):
     return [
-        {"classification": epm,  **mdt} for epm, mdt in zip(expected_predictions_mapped_and_formatted, metadata_formatted)
+        {"classification": epm, **mdt}
+        for epm, mdt in zip(expected_predictions_mapped_and_formatted, metadata_formatted)
     ]
 
 
@@ -330,7 +334,6 @@ def add_image_to_last_page(pdf: fpdf.fpdf.FPDF, image_metadata_pair):
 @pytest.fixture
 def model():
     class Model:
-
         @staticmethod
         def predict(*args):
             return True
@@ -377,12 +380,14 @@ def model_loader(database_connector):
 @pytest.fixture
 def mlflow_run_id():
     from image_prediction.config import CONFIG
+
     return CONFIG.service.run_id
 
 
 @pytest.fixture
 def mlruns_dir():
     from image_prediction.locations import MLRUNS_DIR
+
     return MLRUNS_DIR
 
 
@@ -394,7 +399,6 @@ def mlflow_reader(mlruns_dir):
 @pytest.fixture
 def model_handle_mock(estimator_mock):
     class ModelHandleMock:
-
         def __init__(self):
             self.model = estimator_mock
 

test/unit_tests/label_mapper_test.py

@@ -13,7 +13,7 @@ def test_index_label_mapper(batch_of_expected_numeric_labels, batch_of_expected_
 
 
 def test_array_label_mapper(
-        batch_of_expected_probability_arrays, batch_of_expected_label_to_probability_mappings, classes
+    batch_of_expected_probability_arrays, batch_of_expected_label_to_probability_mappings, classes
 ):
     mapper = ProbabilityMapper(classes)
     assert list(mapper(batch_of_expected_probability_arrays)) == batch_of_expected_label_to_probability_mappings

test/unit_tests/model_loader_test.py

@@ -18,4 +18,4 @@ def test_load_model_and_classes_from_mlflow_store(model_loader, mlflow_run_id):
     classes_loaded = model_loader.load_classes(mlflow_run_id)
 
     assert type(model_loaded) == PredictionModelHandle
-    assert classes_loaded == ['formula', 'logo', 'other', 'signature']
+    assert classes_loaded == ["formula", "logo", "other", "signature"]