type hints and updated docs

README.md

@@ -160,7 +160,7 @@ It is possible to execute tests of [Flask] microservice created with [pytest] fr
 ~/app# make test
 ...
 ============================= test session starts ==============================
-platform linux -- Python 3.12.7, pytest-8.3.3, pluggy-1.5.0
+platform linux -- Python 3.12.8, pytest-8.3.4, pluggy-1.5.0
 rootdir: /app/tests
 collected 2 items
 
@@ -227,7 +227,7 @@ A POST example using [curl] from outside [Docker] container is shown below:
 ## CREDITS
 
 author: alvertogit
-copyright: 2018-2024
+copyright: 2018-2025
 
 [Python]: https://www.python.org/
 [Flask]: https://flask.palletsprojects.com/en/1.1.x/

app/app/__init__.py

@@ -3,7 +3,7 @@
 """
 
 __author__ = "alvertogit"
-__copyright__ = "Copyright 2018-2024"
+__copyright__ = "Copyright 2018-2025"
 
 
 from config import config
@@ -13,7 +13,7 @@
 from .model import init_model
 
 
-def create_app(config_name="default"):
+def create_app(config_name: str = "default") -> Flask:
     """Create and configure an instance of the Flask application."""
     app = Flask(__name__)
     app.config.from_object(config[config_name])

app/app/api.py

@@ -3,12 +3,12 @@
 """
 
 __author__ = "alvertogit"
-__copyright__ = "Copyright 2018-2024"
+__copyright__ = "Copyright 2018-2025"
 
 
 import io
 
-from flask import Blueprint, jsonify, request
+from flask import Blueprint, Response, jsonify, request
 from skimage.io import imread
 
 from .model import current_app, np, preprocess_image
@@ -17,7 +17,7 @@
 
 
 @api.route("/predictlabel", methods=["POST"])
-def predict():
+def predict() -> Response:
     """
     Predict the label of an uploaded image with the Deep Learning model.
 

app/app/model.py

@@ -3,16 +3,17 @@
 """
 
 __author__ = "alvertogit"
-__copyright__ = "Copyright 2018-2024"
+__copyright__ = "Copyright 2018-2025"
 
 
 import numpy as np
 from flask import current_app
 from skimage import transform, util
+from tensorflow.keras import Model
 from tensorflow.keras.models import load_model
 
 
-def init_model():
+def init_model() -> Model:
     """
     Load the pre-trained Deep Learning model.
 
@@ -25,7 +26,7 @@ def init_model():
     return model
 
 
-def preprocess_image(image):
+def preprocess_image(image: np.ndarray) -> np.ndarray:
     """
     Preprocess an image for the Deep Learning model.
 

app/app/templates/dlflask.html

@@ -72,7 +72,7 @@ <h4>POST example using curl</h4>
   </div>
   <br>
   <h5>CREDITS</h5>
-  <p>author: alvertogit<br>copyright: 2018-2024</p>
+  <p>author: alvertogit<br>copyright: 2018-2025</p>
   </div>
 </body>
 </html>

app/config.py

@@ -3,11 +3,13 @@
 """
 
 __author__ = "alvertogit"
-__copyright__ = "Copyright 2018-2024"
+__copyright__ = "Copyright 2018-2025"
 
 
 import os
 
+from flask import Flask
+
 
 class DefaultConfig:
     """
@@ -21,7 +23,7 @@ class DefaultConfig:
     MODEL_PATH = os.environ.get("MODEL_PATH") or "/app/mnist_model.keras"
 
     @staticmethod
-    def init_app(app):
+    def init_app(app: Flask) -> None:
         """
         Initialize the application with the default configuration.
         """
@@ -37,7 +39,7 @@ class DevConfig(DefaultConfig):
     DEBUG = True
 
     @classmethod
-    def init_app(cls, app):
+    def init_app(cls, app: Flask) -> None:
         """
         Initialize the application with the development configuration.
         """
@@ -53,7 +55,7 @@ class TestConfig(DefaultConfig):
     TESTING = True
 
     @classmethod
-    def init_app(cls, app):
+    def init_app(cls, app: Flask) -> None:
         """
         Initialize the application with the testing configuration.
         """

app/server.py

@@ -3,7 +3,7 @@
 """
 
 __author__ = "alvertogit"
-__copyright__ = "Copyright 2018-2024"
+__copyright__ = "Copyright 2018-2025"
 
 
 from app import create_app

app/tests/conftest.py

@@ -3,16 +3,18 @@
 """
 
 __author__ = "alvertogit"
-__copyright__ = "Copyright 2018-2024"
+__copyright__ = "Copyright 2018-2025"
 
 
 import pytest
+from flask import Flask
+from flask.testing import FlaskClient
 
 from app import create_app
 
 
 @pytest.fixture
-def app():
+def app() -> Flask:
     """
     Create a Flask app instance for testing.
 
@@ -25,7 +27,7 @@ def app():
 
 
 @pytest.fixture
-def client(app):
+def client(app: Flask) -> FlaskClient:
     """
     Create a Flask test client for the app.
 

app/tests/test_app.py

@@ -3,13 +3,15 @@
 """
 
 __author__ = "alvertogit"
-__copyright__ = "Copyright 2018-2024"
+__copyright__ = "Copyright 2018-2025"
 
 
 import json
 
+from flask.testing import FlaskClient
 
-def test_index(client):
+
+def test_index(client: FlaskClient) -> None:
     """
     Test the index route.
 
@@ -26,7 +28,7 @@ def test_index(client):
     assert response.data == b"Deep Learning on Flask"
 
 
-def test_api(client):
+def test_api(client: FlaskClient) -> None:
     """
     Test the API endpoint to predict the label of an uploaded image with the Deep Learning model.