ruff format

app/app/__init__.py

@@ -2,15 +2,16 @@
 __init__.py: Flask server with Deep Learning model.
 """
 
-__author__      = "alvertogit"
-__copyright__   = "Copyright 2018-2020"
+__author__ = "alvertogit"
+__copyright__ = "Copyright 2018-2024"
 
 
 from flask import Flask, render_template
 
 from config import config
 from .model import init_model
 
+
 def create_app(config_name="default"):
     """Create and configure an instance of the Flask application."""
     app = Flask(__name__)
@@ -21,6 +22,7 @@ def create_app(config_name="default"):
         app.config["model"] = init_model()
 
     from .api import api
+
     app.register_blueprint(api, url_prefix="/api")
 
     @app.route("/dlflask", methods=["GET"])

app/app/api.py

@@ -2,8 +2,8 @@
 api.py: api views used by Flask server.
 """
 
-__author__      = "alvertogit"
-__copyright__   = "Copyright 2018-2024"
+__author__ = "alvertogit"
+__copyright__ = "Copyright 2018-2024"
 
 
 import io
@@ -12,7 +12,8 @@
 from .model import current_app, np, preprocess_image
 
 
-api = Blueprint('api', __name__)
+api = Blueprint("api", __name__)
+
 
 @api.route("/predictlabel", methods=["POST"])
 def predict():
@@ -37,7 +38,7 @@ def predict():
             # add generated predictions to result
             result["predictions"] = []
 
-            for i in range(0,10):
+            for i in range(0, 10):
                 pred = {"label": str(i), "probability": str(preds[0][i])}
                 result["predictions"].append(pred)
 

app/app/model.py

@@ -2,8 +2,8 @@
 model.py: Functions related to Deep Learning model based on Keras.
 """
 
-__author__      = "alvertogit"
-__copyright__   = "Copyright 2018-2024"
+__author__ = "alvertogit"
+__copyright__ = "Copyright 2018-2024"
 
 
 from tensorflow.keras.models import load_model
@@ -23,6 +23,7 @@ def init_model():
     model.make_predict_function()
     return model
 
+
 def preprocess_image(image):
     """Function that preprocess image.
     Returns:
@@ -32,8 +33,8 @@ def preprocess_image(image):
     # invert grayscale image
     image = util.invert(image)
     # resize and reshape image for model
-    image = transform.resize(image, (28,28), anti_aliasing=True, mode="constant")
+    image = transform.resize(image, (28, 28), anti_aliasing=True, mode="constant")
     image = np.array(image)
-    image = image.reshape((1,28*28))
+    image = image.reshape((1, 28 * 28))
 
     return image

app/config.py

@@ -2,12 +2,13 @@
 config.py: Configurations used by Flask server.
 """
 
-__author__      = "alvertogit"
-__copyright__   = "Copyright 2018-2024"
+__author__ = "alvertogit"
+__copyright__ = "Copyright 2018-2024"
 
 
 import os
 
+
 class DefaultConfig:
     if os.environ.get("SECRET_KEY"):
         SECRET_KEY = os.environ.get("SECRET_KEY")
@@ -41,5 +42,5 @@ def init_app(cls, app):
     "development": DevConfig,
     "testing": TestConfig,
     "production": DefaultConfig,
-    "default": DefaultConfig
+    "default": DefaultConfig,
 }

app/server.py

@@ -2,8 +2,8 @@
 server.py: Run Flask server with Deep Learning model.
 """
 
-__author__      = "alvertogit"
-__copyright__   = "Copyright 2018-2024"
+__author__ = "alvertogit"
+__copyright__ = "Copyright 2018-2024"
 
 
 from app import create_app

app/tests/conftest.py

@@ -2,18 +2,20 @@
 conftest.py: It contents fixture functions used in tests.
 """
 
-__author__      = "alvertogit"
-__copyright__   = "Copyright 2018-2024"
+__author__ = "alvertogit"
+__copyright__ = "Copyright 2018-2024"
 
 
 from app import create_app
 import pytest
 
+
 @pytest.fixture
 def app():
     app = create_app("testing")
     return app
 
+
 @pytest.fixture
 def client(app):
     return app.test_client()

app/tests/test_app.py

@@ -2,18 +2,20 @@
 test_app.py: It contents flask app tests.
 """
 
-__author__      = "alvertogit"
-__copyright__   = "Copyright 2018-2024"
+__author__ = "alvertogit"
+__copyright__ = "Copyright 2018-2024"
 
 
 import json
 
+
 def test_index(client):
     response = client.get("/")
     # check response
     assert response.status_code == 200
     assert response.data == b"Deep Learning on Flask"
 
+
 def test_api(client):
     # server REST API endpoint url and example image path
     SERVER_URL = "http://127.0.0.1:5000/api/predictlabel"
@@ -29,7 +31,7 @@ def test_api(client):
 
     # JSON format
     try:
-        json_response = json.loads(response.data.decode('utf8'))
+        json_response = json.loads(response.data.decode("utf8"))
     except ValueError as e:
         print(e)
         assert False