postgres

src/Run.py

@@ -4,6 +4,7 @@ from flask_oidc import OpenIDConnect
 from werkzeug.middleware.proxy_fix import ProxyFix
 import os
 import json
+import psycopg2
 
 app = Flask(__name__)
 app.config.update({
@@ -19,61 +20,17 @@ app.config.update({
 oidc = OpenIDConnect(app)
 
 
-# Datenbankverbindung konfigurieren
-def get_db_connection():
-    conn = sqlite3.connect('nutrition.db')  # 'nutrition.db' ist der Name der Datenbankdatei
-    conn.row_factory = sqlite3.Row  # Ermöglicht den Zugriff auf Daten durch Spaltennamen
-    return conn
-
-
-#def init_db():
-#    conn = get_db_connection()
-#    cursor = conn.cursor()
-#
-#    # Erstellen der Tabelle
-#    cursor.execute('''
-#        CREATE TABLE IF NOT EXISTS nutrition_table (
-#            id INTEGER PRIMARY KEY,
-#            name TEXT NOT NULL,
-#            kcal REAL,
-#            EW REAL,
-#            Fett REAL,
-#            KH REAL,
-#            BST REAL,
-#            CA REAL
-#        )
-#    ''')
-#
-#    # Testdaten einfügen
-#    test_data = [
-#        ('Apfel', 52, 0.3, 0.2, 14, 0.2, 6),
-#        ('Banane', 89, 1.1, 0.3, 23, 0.3, 5),
-#        ('Karotte', 41, 0.9, 0.2, 10, 0.2, 3),
-#        ('Tomate', 18, 0.9, 0.2, 3.9, 0.2, 4),
-#        ('Brokkoli', 34, 2.8, 0.4, 6.6, 0.4, 2),
-#        ('Spinat', 23, 2.9, 0.4, 3.6, 0.4, 99),
-#        ('Kartoffel', 77, 2, 0.1, 17, 0.1, 12),
-#        ('Huhn', 239, 27, 14, 0, 0, 2),
-#        ('Lachs', 208, 20, 13, 0, 0, 1),
-#        ('Ei', 155, 13, 11, 1.1, 1, 1)
-#    ]
-#
-#    cursor.executemany('INSERT INTO nutrition_table (name, kcal, EW, Fett, KH, BST, CA) VALUES (?, ?, ?, ?, ?, ?, ?)', test_data)
-#
-#    conn.commit()
-#    conn.close()
-
 
 
 def calculate_nutrition(food, weight):
-    conn = get_db_connection()
-    cursor = conn.cursor()
+    try:
+        conn = psycopg2.connect()
 
+        with conn.cursor() as cursor:
             # Abfrage der Nährwertdaten aus der Datenbank
             cursor.execute('SELECT kcal, EW, Fett, KH, BST, CA FROM nutrition_table WHERE name = ?', (food,))
 
             result = cursor.fetchone()
-    conn.close()
 
             if result:
                 # Runden und Berechnen der Nährwerte basierend auf dem Gewicht
@@ -89,6 +46,9 @@ def calculate_nutrition(food, weight):
                 return nutrition_values
             else:
                 return None
+    finally:
+        if conn:
+            conn.close()
 
 
 # Index-Route
@@ -102,16 +62,16 @@ def index():
 @app.route('/get_products')
 @oidc.require_login
 def get_products():
-    conn = get_db_connection()
-    cursor = conn.cursor()
+    try:
+        conn = psycopg2.connect()
+        with conn.cursor() as cursor:
             cursor.execute('SELECT name FROM nutrition_table')
             products = cursor.fetchall()
-    conn.close()
             print("ter")
             return {'products': [product[0] for product in products]}
-
-
-
+    finally:
+        if conn:
+            conn.close()
 
 
 # Route zum Hinzufügen und Berechnen von Lebensmitteln
@@ -152,14 +112,16 @@ def add_nutrition():
 
     print("test")
     # Verbindung zur Datenbank herstellen und Daten einfügen
-    conn = get_db_connection()
-    cursor = conn.cursor()
+    try:
+        conn = psycopg2.connect()
+        with conn.cursor() as cursor:
             cursor.execute("INSERT INTO nutrition_table (name, kcal, ew, fett, kh, bst, ca) VALUES (?, ?, ?, ?, ?, ?, ?)",
                            (food, kcal, ew, fett, kh, bst, ca))
-    conn.commit()
-    conn.close()
     
         return redirect(url_for('nutrition'))
+    finally:
+        if conn:
+            conn.close()
 
 
 @app.route('/nutrition')

src/db.py

@@ -1,14 +1,13 @@
 import csv
-import sqlite3
+import psycopg2
 
 # Pfad zur Ihrer CSV-Datei
 csv_file_path = 'nu.csv'
 
 # Pfad zur Ihrer SQLite-Datenbank
-sqlite_db_path = 'nutrition.db'
 
 # Verbindung zur SQLite-Datenbank herstellen
-conn = sqlite3.connect(sqlite_db_path)
+conn = psycopg2.connect()
 cursor = conn.cursor()
 
 # Erstellen der Tabelle (falls noch nicht vorhanden)
@@ -29,7 +28,7 @@ with open(csv_file_path, newline='', encoding='utf-8') as csvfile:
     reader = csv.reader(csvfile)
     next(reader, None)  # Überspringen der Kopfzeile
     for row in reader:
-        cursor.execute('INSERT INTO nutrition_table (name, kcal, EW, Fett, KH, BST, Ca) VALUES (?, ?, ?, ?, ?, ?, ?)', row)
+        cursor.execute('INSERT INTO nutrition_table (name, kcal, EW, Fett, KH, BST, Ca) VALUES (%s, %s, %s, %s, %s, %s, %s)', row)
 
 # Änderungen speichern und Verbindung schließen
 conn.commit()