EXPOOSE APP on 7860

main.py

@@ -1,61 +1,50 @@
-from flask import  Flask
-from flask import request
-import numpy as np
+from flask import Flask, request
 import pickle
 import pandas as pd
-import flasgger
-from flasgger import Swagger
-from flasgger import Swagger, LazyString, LazyJSONEncoder, swag_from
+from flasgger import Swagger, LazyString, LazyJSONEncoder
 
+app = Flask(__name__)  # Rename 'application' to 'app' for brevity
 
+# Set JSON encoder for the app
+app.json_encoder = LazyJSONEncoder
 
-application=Flask(__name__)        # debut de l'app
-
-
-# pas tres import: habillage det affivhage
-application.json_encoder = LazyJSONEncoder
-
-swagger_template = dict(
-                      info = {
-                          'title': LazyString(lambda: "Modèle d'authentification de billets de banque"),
-                          'description': LazyString(lambda: " Les informations statistiques extraites nous permettra de savoir si les billets sont authentiques"),
-                             },
-                      host = LazyString(lambda: request.host)
-                      )
+# Swagger configuration
+swagger_template = {
+    'info': {
+        'title': LazyString(lambda: "Modèle d'authentification de billets de banque"),
+        'description': LazyString(lambda: " Les informations statistiques extraites nous permettra de savoir si les billets sont authentiques"),
+    },
+    'host': LazyString(lambda: request.host)
+}
 
 swagger_config = {
-                      "headers": [],
-                      "specs": [
-                          {
-                              "endpoint": '',
-                              "route": '/',
-                              "rule_filter": lambda rule: True,
-                              "model_filter": lambda tag: True,
-                          }
-                      ],
-                      "static_url_path": "/flasgger_static",
-                      "swagger_ui": True,
-                      "specs_route": "/apidocs/"
-                      
-                  }
-
-swagger= Swagger(application, template=swagger_template, config=swagger_config)
-# Swagger(application)
-
-# chargement du modèle
-modele=pickle.load(open("model.pkl","rb"))
-
-@application.route('/')
+    "headers": [],
+    "specs": [
+        {
+            "endpoint": '',
+            "route": '/',
+            "rule_filter": lambda rule: True,
+            "model_filter": lambda tag: True,
+        }
+    ],
+    "static_url_path": "/flasgger_static",
+    "swagger_ui": True,
+    "specs_route": "/apidocs/"
+}
+
+swagger = Swagger(app, template=swagger_template, config=swagger_config)
+
+# Load the model
+model = pickle.load(open("model.pkl", "rb"))
+
+
+@app.route('/')
 def welcome():
-    return "Bienvenu dans le site d'authentification"
+    return "Bienvenue dans le site d'authentification"
 
 
-
-
-
-@application.route('/predict',methods=["Get"])
+@app.route('/predict', methods=["GET"])
 def predict_note_authentication():
-    
     """Let's Authenticate the Banks Note 
     This is using docstrings for specifications.
     ---
@@ -79,19 +68,17 @@ def predict_note_authentication():
     responses:
         200:
             description: The output values
-        
     """
     variance = request.args.get("variance")
     skewness = request.args.get("skewness")
     curtosis = request.args.get("curtosis")
     entropy = request.args.get("entropy")
-    prediction = modele.predict([[variance, skewness, curtosis, entropy]])
+    prediction = model.predict([[variance, skewness, curtosis, entropy]])
     print(prediction)
-    return "Alors vraissemblablement la réponse est "+str(prediction)
-
-@application.route('/predict_file',methods=["POST"])
+    return "Alors vraissemblablement la réponse est " + str(prediction)
 
 
+@app.route('/predict_file', methods=["POST"])
 def predict_note_file():
     """Let's Authenticate the Banks Note 
     This is using docstrings for specifications.
@@ -101,19 +88,15 @@ def predict_note_file():
         in: formData
         type: file
         required: true
-      
     responses:
         200:
             description: The output values
-        
     """
-    df_test=pd.read_csv(request.files.get("file"))
+    df_test = pd.read_csv(request.files.get("file"))
     print(df_test.head())
-    prediction=modele.predict(df_test)
-    
+    prediction = model.predict(df_test)
     return str(list(prediction))
 
-if __name__=='__main__':               #  si 1 est exécuté alors l'application (codé en bas) sera mis en exécution
-    application.run()
-    
-    
+
+if __name__ == '__main__':
+    app.run(port=7860)