Added error handling

Neuronal-Red/temperature_prediction.py

@@ -3,58 +3,61 @@
 
 import numpy as np
 
-# Input data
-celsius = np.array([-40, -10, 0, 8, 15, 22, 38], dtype=np.float32)
-fahrenheit = (celsius*1.8) + 32
-
-
-# Model definition
-Input_layer = tf.keras.layers.Input((1,))
-hidden1 = tf.keras.layers.Dense(units=2)   #Dense Layer With 2 units so as to not overfit the data
-output = tf.keras.layers.Dense(units=1)
-model = tf.keras.Sequential([Input_layer,hidden1, output])
-# Model compilation
-model.compile(
-    optimizer=tf.keras.optimizers.Adam(0.1),
-    loss='mean_squared_error'
-)
-
-# Model training
-epochs = 100
-print("Starting training...")
-history = model.fit(celsius, fahrenheit, epochs=epochs, verbose=False)
-loss = history.history["loss"]
-print("Model trained!")
-
-# Making a prediction
-print("Let's make a prediction!")
-result = model.predict(np.array([89.0]))
-print("The result is " + str(result) + " fahrenheit")
-print(f"True value = {(89.0*1.8) +32}")
-
-# Viewing the internal variables of the model
-print("Internal model variables")
-print(hidden1.get_weights())
-# print(hidden2.get_weights())
-print(output.get_weights())
-
-# loss changes 
-plt.figure(figsize = (10,10))
-plt.subplot(1,2,1)
-plt.plot(range(epochs),loss)
-plt.xlabel("Epochs")
-plt.ylabel("loss")
-plt.title("losse over epochs")
-
-# true values vs predicted values 
-plt.subplot(1,2,2)
-x_test = np.random.randint(0,100,[20,1])
-y_test = (x_test*1.8) +32
-y_pred = model.predict(x_test)
-
-plt.scatter(x_test, y_test, color='blue', label='True Values')
-plt.scatter(x_test, y_pred, color='red', label='Predicted Values')
-plt.xlabel("True values")
-plt.ylabel("predicted values")
-plt.title("True values vs Predicted values")
-plt.show()
+try:
+    # Input data
+    celsius = np.array([-40, -10, 0, 8, 15, 22, 38], dtype=np.float32)
+    fahrenheit = (celsius*1.8) + 32
+
+
+    # Model definition
+    Input_layer = tf.keras.layers.Input((1,))
+    hidden1 = tf.keras.layers.Dense(units=2)   #Dense Layer With 2 units so as to not overfit the data
+    output = tf.keras.layers.Dense(units=1)
+    model = tf.keras.Sequential([Input_layer,hidden1, output])
+    # Model compilation
+    model.compile(
+        optimizer=tf.keras.optimizers.Adam(0.1),
+        loss='mean_squared_error'
+    )
+
+    # Model training
+    epochs = 100
+    print("Starting training...")
+    history = model.fit(celsius, fahrenheit, epochs=epochs, verbose=False)
+    loss = history.history["loss"]
+    print("Model trained!")
+
+    # Making a prediction
+    print("Let's make a prediction!")
+    result = model.predict(np.array([89.0]))
+    print("The result is " + str(result) + " fahrenheit")
+    print(f"True value = {(89.0*1.8) +32}")
+
+    # Viewing the internal variables of the model
+    print("Internal model variables")
+    print(hidden1.get_weights())
+    # print(hidden2.get_weights())
+    print(output.get_weights())
+
+    # loss changes
+    plt.figure(figsize = (10,10))
+    plt.subplot(1,2,1)
+    plt.plot(range(epochs),loss)
+    plt.xlabel("Epochs")
+    plt.ylabel("loss")
+    plt.title("losse over epochs")
+
+    # true values vs predicted values
+    plt.subplot(1,2,2)
+    x_test = np.random.randint(0,100,[20,1])
+    y_test = (x_test*1.8) +32
+    y_pred = model.predict(x_test)
+
+    plt.scatter(x_test, y_test, color='blue', label='True Values')
+    plt.scatter(x_test, y_pred, color='red', label='Predicted Values')
+    plt.xlabel("True values")
+    plt.ylabel("predicted values")
+    plt.title("True values vs Predicted values")
+    plt.show()
+except Exception as e:
+    printf("Exception occured!", e)

Password_Manager/project.py

@@ -11,48 +11,69 @@
 
 def main_menu():
     """Display the main menu and get the user's choice."""
-    menu = [
-        "---------------------|",
-        "Password Manager App |",
-        "---------------------|",
-        "1. Create password   |",
-        "2. Check password    |",
-        "3. Edit password     |",
-        "4. Delete password   |",
-        "5. Exit              |",
-        "---------------------|"
-    ]
-    print("\n".join(menu))
-    return input("Pick a number: ")
+    try:
+        menu = [
+            "---------------------|",
+            "Password Manager App |",
+            "---------------------|",
+            "1. Create password   |",
+            "2. Check password    |",
+            "3. Edit password     |",
+            "4. Delete password   |",
+            "5. Exit              |",
+            "---------------------|"
+        ]
+        print("\n".join(menu))
+        return input("Pick a number: ")
+    except Exception as e:
+        print(f"An error occurred: {e}")
+        return
+
 
 def validate_aim(aim):
     """Validate if the aim is not empty."""
-    if not aim:
-        display_message("Aim unspecified or empty. Please specify an 'aim' value.", Fore.RED)
+    try:
+        if not aim:
+            display_message("Aim unspecified or empty. Please specify an 'aim' value.", Fore.RED)
+            return False
+        return True
+    except Exception as e:
+        print("Exception occured: ", e)
         return False
-    return True
 
 def read_csv_file():
     """Read the CSV file and return the data as a list of dictionaries."""
-    if not os.path.isfile(PASSWORD_FILE):
+    try:
+        if not os.path.isfile(PASSWORD_FILE):
+            return []
+        with open(PASSWORD_FILE, "r") as csvfile:
+            return list(csv.DictReader(csvfile))
+    except Exception as e:
+        print("Exception occured: ", e)
         return []
-    with open(PASSWORD_FILE, "r") as csvfile:
-        return list(csv.DictReader(csvfile))
 
 def write_csv_file(data):
     """Write the data to the CSV file."""
-    with open(PASSWORD_FILE, "w", newline="") as csvfile:
-        writer = csv.DictWriter(csvfile, fieldnames=["aim", "password"])
-        writer.writeheader()
-        writer.writerows(data)
+    try:
+        with open(PASSWORD_FILE, "w", newline="") as csvfile:
+            writer = csv.DictWriter(csvfile, fieldnames=["aim", "password"])
+            writer.writeheader()
+            writer.writerows(data)
+    except Exception as e:
+        print("Exception occured: ", e)
+        return
 
 def password_generator():
     """Generate a random password with lowercase, uppercase, punctuation, and numeric characters."""
-    char_sets = [string.ascii_lowercase, string.ascii_uppercase, string.punctuation, string.digits]
-    password = [random.choice(char_set) for char_set in char_sets]
-    password.extend(random.choices("".join(char_sets), k=STRING_LENGTH + PUNCTUATION_LENGTH + 4 - len(char_sets)))
-    random.shuffle(password)
-    return "".join(password)
+    try:
+        char_sets = [string.ascii_lowercase, string.ascii_uppercase, string.punctuation, string.digits]
+        password = [random.choice(char_set) for char_set in char_sets]
+        password.extend(random.choices("".join(char_sets), k=STRING_LENGTH + PUNCTUATION_LENGTH + 4 - len(char_sets)))
+        random.shuffle(password)
+        return "".join(password)
+    except Exception as e:
+        print("An error occurred: ", e)
+
 
 def display_message(message, color=Fore.GREEN):
     """Display a message in the specified color."""

tictactoe/tictactoe.py

@@ -107,12 +107,16 @@ def max_value(board):
 
 def min_value(board):
     """Returns the minimum value (for O) of a move."""
-    if terminal(board):
-        return utility(board)
-    value = float('inf')
-    for action in actions(board):
-        value = min(value, max_value(result(board, action)))
-    return value
+    try:
+        if terminal(board):
+            return utility(board)
+        value = float('inf')
+        for action in actions(board):
+            value = min(value, max_value(result(board, action)))
+        return value
+    except Exception as e:
+        print(f"Exception: {e}")
+        return None
 
 
 if __name__ == "__main__":