Day 3 added. Day 4 almost finished

Author: StructuralWizard

.gitignore

@@ -17,7 +17,8 @@ package.json
 vendor/
 
 # Ignore folders for mermaid diagrams
-.assets/
+assets/
 
 # Environment files
-.venv
+.venv
+.env

_python_code/Day2/car_factory.py

@@ -0,0 +1,32 @@
+class Car:
+    # This is the blueprint for a Car
+
+    def __init__(self, color, brand, num_wheels=4):
+        # This is a special method called the "constructor".
+        # It's like the initial assembly line for a new car.
+        # 'self' refers to the specific car object being created.
+        self.color = color         # Set the color attribute for this car
+        self.brand = brand         # Set the brand attribute for this car
+        self.num_wheels = num_wheels # Set the number of wheels (default to 4)
+
+    def accelerate(self):
+        # This is a method (behavior) for a Car object
+        print(f"The {self.color} {self.brand} car is accelerating!")
+
+    def brake(self):
+        # Another method
+        print(f"The {self.color} {self.brand} car is braking.")
+
+# Creating an object (a specific car) from the Car class
+my_red_car = Car("red", "Toyota")
+johns_blue_car = Car("blue", "Honda")
+my_red_car.accelerate()
+my_red_car.brake()
+
+# Accessing attributes
+print(f"My car's color: {my_red_car.color}")
+print(f"John's car's brand: {johns_blue_car.brand}")
+
+# Setting (modifying) an attribute
+my_red_car.color = "yellow"
+print(f"My car's new color: {my_red_car.color}")

_python_code/Day2/data/meals.csv

@@ -0,0 +1,16 @@
+date,meal_type,food,calories
+2025-06-01,Breakfast,Oatmeal,250
+2025-06-01,Lunch,Chicken Salad,500
+2025-06-01,Dinner,Pasta,600
+2025-06-02,Breakfast,Eggs,300
+2025-06-02,Lunch,Sandwich,450
+2025-06-02,Dinner,Steak,700
+2025-06-03,Breakfast,Smoothie,200
+2025-06-03,Lunch,Rice and Beans,550
+2025-06-03,Dinner,Grilled Fish,500
+2025-06-04,Breakfast,Yogurt with Granola,320
+2025-06-04,Lunch,Vegetable Soup,380
+2025-06-04,Dinner,Chicken Curry,650
+2025-06-05,Breakfast,Avocado Toast,400
+2025-06-05,Lunch,Caesar Salad,420
+2025-06-05,Dinner,Salmon with Vegetables,580

_python_code/Day2/data/workouts.csv

@@ -0,0 +1,6 @@
+date,type,duration_minutes,calories_burned
+2025-06-01,Running,30,300
+2025-06-02,Cycling,45,400
+2025-06-03,Yoga,60,200
+2025-06-04,Swimming,30,350
+2025-06-05,Running,40,350

_python_code/Day2/fitness_tracker.py

@@ -0,0 +1,135 @@
+import csv
+import os
+import pandas as pd
+import matplotlib.pyplot as plt
+from datetime import datetime
+from matplotlib.dates import DateFormatter
+
+# ---------- CLASSES ----------
+
+class LogEntry:
+    def __init__(self, date):
+        self.date = date
+
+class Workout(LogEntry):
+    def __init__(self, date, workout_type, duration, calories):
+        super().__init__(date)
+        self.workout_type = workout_type
+        self.duration = duration
+        self.calories = calories
+
+class Meal(LogEntry):
+    def __init__(self, date, meal_type, food, calories):
+        super().__init__(date)
+        self.meal_type = meal_type
+        self.food = food
+        self.calories = calories
+
+# ---------- FILE PATHS ----------
+
+DATA_DIR = os.path.join(os.path.dirname(__file__), 'data')
+WORKOUTS_FILE = os.path.join(DATA_DIR, 'workouts.csv')
+MEALS_FILE = os.path.join(DATA_DIR, 'meals.csv')
+
+# ---------- READ CSV MANUALLY ----------
+
+def read_workouts_manual(file_path):
+    workouts = []
+    with open(file_path, newline='') as csvfile:
+        reader = csv.reader(csvfile)
+        next(reader)  # Skip header
+        for row in reader:
+            date = row[0].strip()
+            workout_type = row[1].strip()
+            duration = int(row[2].strip())
+            calories = int(row[3].strip())
+            workouts.append(Workout(date, workout_type, duration, calories))
+    return workouts
+
+# ---------- USING PANDAS ----------
+
+def load_and_clean_data():
+    df_workouts = pd.read_csv(WORKOUTS_FILE)
+    df_meals = pd.read_csv(MEALS_FILE)
+
+    df_workouts['date'] = pd.to_datetime(df_workouts['date'])
+    df_meals['date'] = pd.to_datetime(df_meals['date'])
+
+    # Fill any missing values in workout data with zeros (e.g., missing durations or calories)
+    df_workouts.fillna(0, inplace=True)
+    # Fill any missing values in meal data with "Unknown" (e.g., missing food descriptions)
+    df_meals.fillna("Unknown", inplace=True)
+
+    return df_workouts, df_meals
+
+# ---------- ANALYSIS ----------
+
+def summarize_data(df_workouts, df_meals):
+    workout_summary = df_workouts.groupby('date')['calories_burned'].sum().reset_index()
+    meal_summary = df_meals.groupby('date')['calories'].sum().reset_index()
+
+    combined = pd.merge(workout_summary, meal_summary, on='date', how='outer').fillna(0)
+    combined['net_calories'] = combined['calories'] - combined['calories_burned']
+    return combined
+
+# ---------- VISUALIZATION ----------
+
+def plot_fitness_trends(combined_df):
+    # Create a new figure with specified size (width: 16 inches, height: 10 inches)
+    # This creates a larger plot that is easier to read and analyze
+    plt.figure(figsize=(16, 10)) 
+    
+    # Plot calories consumed with circular markers
+    plt.plot(combined_df['date'], combined_df['calories'], label="Calories Consumed", marker='o')
+    
+    # Plot calories burned with x markers for visual distinction
+    plt.plot(combined_df['date'], combined_df['calories_burned'], label="Calories Burned", marker='x')
+    
+    # Plot net calories (consumed - burned) with dashed line style
+    # This shows the caloric balance for each day
+    plt.plot(combined_df['date'], combined_df['net_calories'], label="Net Calories", linestyle='--')
+
+    # Calculate and plot a 2-day rolling average of net calories
+    # This smooths out daily fluctuations and shows the overall trend
+    rolling = combined_df['net_calories'].rolling(window=2).mean()
+    plt.plot(combined_df['date'], rolling, label="Rolling Mean (Net)", linestyle='dotted')
+
+    # Add axis labels with increased font size for better readability
+    plt.xlabel('Date', fontsize=14)
+    plt.ylabel('Calories', fontsize=14)
+    
+    # Format the x-axis to display dates in YYYY-MM-DD format
+    # This ensures consistent date representation on the chart
+    date_format = DateFormatter('%Y-%m-%d')
+    plt.gca().xaxis.set_major_formatter(date_format)
+    
+    # Rotate x-axis labels by 45 degrees to prevent overlap and increase font size
+    plt.xticks(rotation=45, fontsize=12)
+    plt.yticks(fontsize=12)
+    
+    plt.title('Fitness Tracker Summary', fontsize=16) # Add a descriptive title to the chart with larger font
+    
+    plt.legend() # Add a legend to identify each line in the plot
+    
+    plt.grid(True) # Add a grid to make it easier to read values from the chart
+    
+    plt.tight_layout() # Adjust layout to ensure all elements fit without overlapping
+    
+    plt.show() # Display the completed chart
+
+
+# ---------- MAIN FUNCTION ----------
+
+def main():
+    print("Loading data...")
+    df_workouts, df_meals = load_and_clean_data()
+
+    print("\nSummarizing data...")
+    combined = summarize_data(df_workouts, df_meals)
+    print(combined)
+
+    print("\nPlotting results...")
+    plot_fitness_trends(combined)
+
+if __name__ == "__main__":
+    main()

_python_code/Day2/vehicle_factory.py

@@ -0,0 +1,32 @@
+class Vehicle: # General blueprint
+    def __init__(self, num_wheels, top_speed):
+        self.num_wheels = num_wheels
+        self.top_speed = top_speed
+
+    def move(self):
+        print("Vehicle is moving.")
+
+class Car(Vehicle): # Car inherits from Vehicle
+    def __init__(self, color, brand):
+        super().__init__(4, 200) # Call the parent (Vehicle) constructor
+        self.color = color
+        self.brand = brand
+
+    def accelerate(self): # Car has its own specific method
+        print(f"The {self.color} {self.brand} car is accelerating!")
+
+class Motorcycle(Vehicle): # Motorcycle also inherits from Vehicle
+    def __init__(self, engine_size):
+        super().__init__(2, 180) # Call the parent (Vehicle) constructor
+        self.engine_size = engine_size
+
+    def wheelie(self):
+        print(f"The motorcycle is doing a wheelie!")
+
+my_car = Car("green", "BMW")
+my_car.move() # Car can use the Vehicle's move method
+my_car.accelerate()
+
+my_motorcycle = Motorcycle("1000cc")
+my_motorcycle.move()
+my_motorcycle.wheelie()

_python_code/Day3/amadeus_flight_finder_email_alert.py

@@ -0,0 +1,109 @@
+from amadeus import Client, ResponseError
+import os, smtplib
+from dotenv import load_dotenv
+from datetime import datetime, timedelta
+import json
+import csv
+
+# Load environment variables from .env file
+load_dotenv()
+
+
+amadeus = Client(
+    client_id= os.getenv("AMADEUS_API_KEY"),
+    client_secret= os.getenv("AMADEUS_API_SECRET")    
+)
+
+# Search for flights
+try:
+    response = amadeus.shopping.flight_offers_search.get(
+        originLocationCode='LON',
+        destinationLocationCode='SCQ',
+        departureDate=(datetime.now() + timedelta(days=10)).strftime("%Y-%m-%d"),
+        adults=1,
+        currencyCode='GBP')
+    
+    # Save response to a JSON file
+    with open('flight_offers.json', 'w') as f:
+        json.dump(response.data, f, indent=4)
+    
+    # Extract flight data for CSV
+    csv_data = []
+    for offer in response.data:
+        price_grand_total = offer['price']['grandTotal']
+        
+        # Process each itinerary
+        for itinerary in offer['itineraries']:
+            # For each segment in the itinerary
+            for segment in itinerary['segments']:
+                # Get basic segment info
+                dep_iata = segment['departure']['iataCode']
+                dep_time = segment['departure']['at']
+                arr_iata = segment['arrival']['iataCode']
+                arr_time = segment['arrival']['at']
+                carrier_code = segment['carrierCode']
+                
+                # Get baggage info from the first traveler pricing
+                baggage_info = {}
+                cabin_bags_qty = None
+                checked_bags_weight = None
+                checked_bags_weight_unit = None
+                
+                if 'travelerPricings' in offer:
+                    for pricing in offer['travelerPricings']:
+                        for fare_detail in pricing['fareDetailsBySegment']:
+                            if fare_detail['segmentId'] == segment['id']:
+                                if 'includedCheckedBags' in fare_detail:
+                                    if 'weight' in fare_detail['includedCheckedBags']:
+                                        checked_bags_weight = fare_detail['includedCheckedBags']['weight']
+                                        checked_bags_weight_unit = fare_detail['includedCheckedBags'].get('weightUnit', 'N/A')
+                                    elif 'quantity' in fare_detail['includedCheckedBags']:
+                                        checked_bags_weight = fare_detail['includedCheckedBags']['quantity']
+                                        checked_bags_weight_unit = 'PIECES'
+                                
+                                if 'includedCabinBags' in fare_detail and 'quantity' in fare_detail['includedCabinBags']:
+                                    cabin_bags_qty = fare_detail['includedCabinBags']['quantity']
+                
+                # Add to CSV data
+                csv_data.append({
+                    'departure_iatacode': dep_iata,
+                    'departure_at': dep_time,
+                    'arrival_iatacode': arr_iata,
+                    'arrival_at': arr_time,
+                    'carriercode': carrier_code,
+                    'price_grandtotal': price_grand_total,
+                    'included_checkedbags_weight': checked_bags_weight,
+                    'included_checkedbags_weightunit': checked_bags_weight_unit,
+                    'included_cabinbags_quantity': cabin_bags_qty
+                })
+    
+    # Write to CSV
+    csv_fields = ['departure_iatacode', 'departure_at', 'arrival_iatacode', 'arrival_at', 
+                 'carriercode', 'price_grandtotal', 'included_checkedbags_weight', 
+                 'included_checkedbags_weightunit', 'included_cabinbags_quantity']
+    with open('flight_data.csv', 'w', newline='') as csvfile:
+        writer = csv.DictWriter(csvfile, fieldnames=csv_fields)
+        writer.writeheader()
+        writer.writerows(csv_data)
+    
+    print(f"Flight data extracted and saved to flight_data.csv")
+    
+    # Check if any flights are below price threshold
+    for offer in response.data:
+        price_grand_total = float(offer['price']['grandTotal'])
+        if price_grand_total < 150:
+            try:
+                with smtplib.SMTP("smtp.gmail.com", 587) as connection:
+                    connection.starttls()
+                    connection.login(user=os.getenv("EMAIL_ADDRESS"), password=os.getenv("GMAIL_PASSWORD"))
+                    connection.sendmail(
+                        from_addr=os.getenv("EMAIL_ADDRESS"),
+                        to_addrs="[email protected]",
+                        msg=f"Subject:Cheap Flight Alert!\n\nOnly {price_grand_total}GBP to fly to Santiago de Compostela!\n On the {dep_time} with {offer['itineraries'][0]['segments'][0]['carrierCode']}.\n\n"
+                    )
+                print(f"Email alert sent for flight priced at £{price_grand_total}")
+            except Exception as e:
+                print(f"Failed to send email alert: {e}")
+    
+except ResponseError as error:
+    print(error)

_python_code/Day3/authentication_example.py

@@ -0,0 +1,16 @@
+import requests
+
+base_url = "http://api.openweathermap.org/data/2.5/weather"
+params = {
+    "q": "London",
+    "appid": "24a16cc554ff1dd57f5586f849772f01",
+    "units": "metric"  # You can change to "imperial" for Fahrenheit
+}
+
+response = requests.get(base_url, params=params)
+
+if response.status_code == 200:
+    data = response.json()
+    print(f"Weather in {params['q']}: {data['weather'][0]['description']}")
+else:
+    print("Error:", response.status_code, response.text)