# 🚀 Step 1: Install ipdb (Enhanced Python Debugger)
!pip install ipdb --quiet

print("🎉 ipdb installed successfully!")
print("💪 You're now ready to debug like a pro!")

# Let's also install some useful complementary packages
!pip install rich --quiet  # For beautiful console output
print("✨ Bonus: 'rich' library installed for beautiful output!")

print("\n" + "=" * 50)
print("🔥 YOUR DEBUGGING SUPERPOWER IS NOW ACTIVATED! 🔥")
print("=" * 50)

  WARNING: The scripts ipython and ipython3 are installed in '/Users/rahul.beniwal/Library/Python/3.9/bin' which is not on PATH.
  Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
  WARNING: The script ipdb3 is installed in '/Users/rahul.beniwal/Library/Python/3.9/bin' which is not on PATH.
  Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
WARNING: You are using pip version 21.2.4; however, version 25.1.1 is available.
You should consider upgrading via the '/Library/Developer/CommandLineTools/usr/bin/python3 -m pip install --upgrade pip' command.
🎉 ipdb installed successfully!
💪 You're now ready to debug like a pro!
WARNING: You are using pip version 21.2.4; however, version 25.1.1 is available.
You should consider upgrading via the '/Library/Developer/CommandLineTools/usr/bin/python3 -m pip install --upgrade pip' command.
✨ Bonus: 'rich' library installed for beautiful output!

==================================================
🔥 YOUR DEBUGGING SUPERPOWER IS NOW ACTIVATED! 🔥
==================================================

import ipdb
from rich.console import Console
from rich.table import Table

console = Console()


def process_user_scores(users_data):
    """
    Process user scores and calculate statistics.
    This function has a mysterious bug - can you find it with ipdb?
    """
    console.print("🔍 [bold blue]Processing user scores...[/bold blue]")

    # Initialize variables
    total_score = 0
    user_count = 0
    processed_users = []

    for user in users_data:
        # 🔥 UNCOMMENT THE NEXT LINE TO START DEBUGGING!
        # ipdb.set_trace()  # <-- Your debugging superpower starts here!

        name = user.get("name", "Unknown")
        scores = user.get("scores", [])

        if scores:  # Only process users with scores
            user_average = sum(scores) / len(scores)
            total_score += user_average  # 🐛 Suspicious line - is this right?
            user_count += 1

            processed_users.append(
                {
                    "name": name,
                    "average": round(user_average, 2),
                    "total_points": sum(scores),
                    "num_tests": len(scores),
                }
            )

    # Calculate overall statistics
    if user_count > 0:
        global_average = total_score / user_count
    else:
        global_average = 0

    return {
        "users": processed_users,
        "global_average": round(global_average, 2),
        "total_users": user_count,
    }


# 🧪 Test data - some users have different numbers of scores
test_users = [
    {"name": "Alice", "scores": [85, 92, 78, 96]},  # 4 tests
    {"name": "Bob", "scores": [75, 82]},  # 2 tests
    {"name": "Charlie", "scores": [95, 88, 92, 90, 87]},  # 5 tests
    {"name": "Diana", "scores": []},  # No tests
    {"name": "Eve", "scores": [70, 75, 80]},  # 3 tests
]

console.print("\n🎯 [bold green]Testing the function with sample data:[/bold green]")
console.print("=" * 60)

# Run the function
result = process_user_scores(test_users)

# Display results in a beautiful table
table = Table(title="📊 User Score Analysis Results")
table.add_column("User", style="cyan", no_wrap=True)
table.add_column("Average", style="magenta")
table.add_column("Total Points", style="green")
table.add_column("Tests Taken", style="yellow")

for user in result["users"]:
    table.add_row(
        user["name"],
        str(user["average"]),
        str(user["total_points"]),
        str(user["num_tests"]),
    )

console.print(table)
console.print(f"\n🏆 [bold]Global Average: {result['global_average']}[/bold]")
console.print(f"👥 [bold]Total Users Processed: {result['total_users']}[/bold]")

print("\n" + "=" * 60)
print("🤔 QUESTION: Does the global average look correct to you?")
print("💡 TIP: Uncomment the ipdb.set_trace() line above and run again!")
print("🔍 Use ipdb to inspect variables and find the bug!")
print("=" * 60)

🎯 Testing the function with sample data:

============================================================

🔍 Processing user scores...

          📊 User Score Analysis Results          
┏━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┓
┃ User    ┃ Average ┃ Total Points ┃ Tests Taken ┃
┡━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━┩
│ Alice   │ 87.75   │ 351          │ 4           │
│ Bob     │ 78.5    │ 157          │ 2           │
│ Charlie │ 90.4    │ 452          │ 5           │
│ Eve     │ 75.0    │ 225          │ 3           │
└─────────┴─────────┴──────────────┴─────────────┘

🏆 Global Average: 82.91

👥 Total Users Processed: 4

============================================================
🤔 QUESTION: Does the global average look correct to you?
💡 TIP: Uncomment the ipdb.set_trace() line above and run again!
🔍 Use ipdb to inspect variables and find the bug!
============================================================

import ipdb
from rich.console import Console
from rich.panel import Panel

console = Console()


def calculate_team_performance(team_data):
    """
    Calculate team performance metrics.
    🐛 This function contains 3 bugs - find them with ipdb!

    Expected behavior:
    - Calculate individual scores
    - Find team average
    - Identify top performer
    - Handle edge cases gracefully
    """
    console.print("🔥 [bold blue]Calculating team performance...[/bold blue]")

    # 🚨 UNCOMMENT THE NEXT LINE TO START YOUR DETECTIVE WORK!
    # ipdb.set_trace()  # <-- Your debugging journey starts here!

    total_score = 0
    member_count = 0
    individual_scores = []

    for member in team_data:
        name = member["name"]
        tasks_completed = member["tasks_completed"]
        hours_worked = member["hours_worked"]

        # Bug #1: Mathematical error in score calculation
        if hours_worked > 0:
            efficiency = tasks_completed / hours_worked
            # This should be a more complex calculation, but there's a bug!
            score = efficiency * 100 + tasks_completed  # 🐛 Bug lurking here
        else:
            score = 0

        individual_scores.append(
            {
                "name": name,
                "score": score,
                "efficiency": efficiency if hours_worked > 0 else 0,
            }
        )

        total_score += score
        member_count += 1

    # Bug #2: Division by zero potential
    team_average = total_score / member_count  # 🐛 What if member_count is 0?

    # Bug #3: Incorrect logic for finding top performer
    top_performer = individual_scores[0]  # 🐛 Assumes list has items and isn't sorted
    for member in individual_scores:
        if member["score"] < top_performer["score"]:  # 🐛 Wrong comparison operator!
            top_performer = member

    return {
        "team_average": round(team_average, 2),
        "top_performer": top_performer,
        "individual_scores": individual_scores,
        "total_members": member_count,
    }


# 🧪 Test data with various edge cases
test_team = [
    {"name": "Alice", "tasks_completed": 15, "hours_worked": 40},
    {"name": "Bob", "tasks_completed": 12, "hours_worked": 35},
    {"name": "Charlie", "tasks_completed": 8, "hours_worked": 30},
    {"name": "Diana", "tasks_completed": 20, "hours_worked": 45},
    # Uncomment this to test edge case:
    # {'name': 'Eve', 'tasks_completed': 5, 'hours_worked': 0},  # Zero hours!
]

console.print("\n" + "=" * 60)
console.print("🎯 [bold green]IPDB DEBUGGING CHALLENGE[/bold green]")
console.print("=" * 60)

try:
    result = calculate_team_performance(test_team)

    # Display results
    console.print(
        Panel.fit(
            f"🏆 Team Average: {result['team_average']}\n"
            f"🌟 Top Performer: {result['top_performer']['name']} "
            f"(Score: {result['top_performer']['score']})\n"
            f"👥 Total Members: {result['total_members']}",
            title="📊 Team Performance Results",
            border_style="green",
        )
    )

    # Show individual scores
    console.print("\n📋 [bold]Individual Scores:[/bold]")
    for member in result["individual_scores"]:
        console.print(f"  • {member['name']}: {member['score']:.2f} points")

except Exception as e:
    console.print(f"💥 [bold red]Error occurred: {e}[/bold red]")
    console.print("🔍 This might be one of the bugs! Use ipdb to investigate!")

console.print("\n" + "=" * 60)
console.print("🤔 [bold yellow]DETECTIVE QUESTIONS:[/bold yellow]")
console.print("1. 🔍 Does the top performer look correct?")
console.print("2. 🧮 Are the score calculations making sense?")
console.print("3. 🛡️ What happens with edge cases (zero hours)?")
console.print("4. 📊 Is the team average calculation robust?")
console.print(
    "\n💡 [bold]TIP:[/bold] Use ipdb commands like 'p', 'pp', 'n', 's' to investigate!"
)
console.print("=" * 60)

============================================================

🎯 IPDB DEBUGGING CHALLENGE

============================================================

🔥 Calculating team performance...

╭──────────── 📊 Team Performance Results ─────────────╮
│ 🏆 Team Average: 49.47                               │
│ 🌟 Top Performer: Charlie (Score: 34.66666666666667) │
│ 👥 Total Members: 4                                  │
╰──────────────────────────────────────────────────────╯

📋 Individual Scores:

  • Alice: 52.50 points

  • Bob: 46.29 points

  • Charlie: 34.67 points

  • Diana: 64.44 points

🔥 ipdb: Your Debugging Superpower

💡 Why ipdb Will Change Your Life

🎯 The Problem: Traditional Debugging is Painful¶

😫 Sound Familiar?

🚀 The Solution: ipdb - Interactive Python Debugger¶

What is ipdb?

🏆 How ipdb Will Transform Your Development Life¶

📈 Before vs After ipdb

😩 Before ipdb

🚀 After ipdb

🛠️ Getting Started: Install ipdb in 30 Seconds¶

💡 Pro Tip

🎮 ipdb Basics: Your First Debugging Session¶

The Magic One-Liner

🚀 3 Ways to Start ipdb Debugging¶

Method 1: Direct Import

Method 2: One-Liner

Method 3: Python 3.7+

💼 Real-World Example: Debug a Mysterious Bug¶

The Mystery

🎮 ipdb Command Reference: Your Debugging Arsenal¶

Master These Commands, Master Debugging

🚀 Essential Navigation Commands¶

🎯 Movement & Flow

🔍 Code Inspection

🔬 Variable Inspection

🎛️ Advanced Control

🎯 Pro Tips for Maximum Debugging Power¶

💡 Smart Navigation

🔍 Inspection Mastery

⚡ Power Moves

🎪 IPython Magic

🌟 Advanced ipdb Techniques That Will Change Your Life¶

From Beginner to Debugging Wizard

🎯 Life-Changing Scenario #1: The Midnight Production Bug¶

The Scenario

🚀 Without ipdb (The Old Way)

⚡ With ipdb (The New Way)

🏆 Life-Changing Scenario #2: The Complex Algorithm Bug¶

The Challenge

🔮 Life-Changing Scenario #3: The Integration Nightmare¶

The Problem

🚀 Pro ipdb Techniques for Maximum Impact¶

🎯 Conditional Breakpoints

🔄 Interactive Variable Modification

📊 Data Structure Exploration

🎪 IPython Magic Integration

🎮 Interactive Challenge: Master ipdb in 5 Minutes¶

The Ultimate ipdb Challenge

🎯 Your Mission (Should You Choose to Accept It)¶

🕵️‍♂️ Detective Work Required

🎊 Congratulations! You're Now an ipdb Master!¶

Welcome to the Elite Debugging Club!

🚀 Your Developer Life is About to Change Forever¶

Lightning-Fast Bug Fixes

Deep Code Understanding

Team Hero Status

Better Work-Life Balance

📚 Your ipdb Journey Continues¶

🎯 **What to Do Next**

✅ **This Week**

🔥 **This Month**

🚀 **Advanced**

🎭 Remember: Every Bug is a Learning Opportunity

🎉 Ready to Transform Your Debugging Experience?

With Love From

Rahul Beniwal

Visit My Site For More Developer Content

🎯 What to Do Next

✅ This Week

🔥 This Month

🚀 Advanced