Python Basics

import numpy as np

# Create arrays
data = np.array([1, 2, 3, 4, 5])
matrix = np.random.rand(3, 3)

print("Array:", data)
print("Squared:", data ** 2)
print("Mean:", np.mean(data))
print("Matrix shape:", matrix.shape)
print("Matrix determinant:", np.linalg.det(matrix))

# Mathematical operations
result = np.dot(data, data)
print(f"Dot product: {result}")

import pandas as pd
import numpy as np

# Create sample dataset
data = {
    'name': ['Alice', 'Bob', 'Charlie', 'Diana', 'Eve'],
    'age': [25, 30, 35, 28, 32],
    'salary': [50000, 60000, 70000, 55000, 65000],
    'department': ['Engineering', 'Sales', 'Engineering', 'Marketing', 'Sales']
}

df = pd.DataFrame(data)

print("Dataset:")
print(df)

print("\nBasic Statistics:")
print(df.describe())

print("\nDepartment Summary:")
dept_summary = df.groupby('department').agg({
    'salary': ['mean', 'count'],
    'age': 'mean'
}).round(2)
print(dept_summary)

# Filter high earners
high_earners = df[df['salary'] > 60000]
print(f"\nHigh earners ({len(high_earners)} people):")
print(high_earners[['name', 'salary']])

import pandas as pd
import json

# Read CSV file from storage
try:
    # Files from Lyceum storage are mounted at /lyceum/storage/
    df = pd.read_csv('/lyceum/storage/data.csv')
    print(f"Loaded {len(df)} rows from CSV")
    print(df.head())
    
    # Process the data
    summary = {
        'total_rows': len(df),
        'columns': list(df.columns),
        'memory_usage': df.memory_usage().sum()
    }
    
    # Save results back to storage
    with open('/lyceum/storage/summary.json', 'w') as f:
        json.dump(summary, f, indent=2)
    
    print("Summary saved to storage!")
    
except FileNotFoundError:
    print("No data.csv found in storage - upload a file first!")
    
    # Create sample data instead
    sample_data = pd.DataFrame({
        'x': range(10),
        'y': [i**2 for i in range(10)]
    })
    
    sample_data.to_csv('/lyceum/storage/sample.csv', index=False)
    print("Created sample.csv in storage")

import os

# Read environment variables
api_key = os.environ.get('API_KEY', 'not-set')
debug_mode = os.environ.get('DEBUG', 'false').lower() == 'true'

print(f"API Key configured: {'Yes' if api_key != 'not-set' else 'No'}")
print(f"Debug mode: {debug_mode}")

# Lyceum-specific environment variables
storage_path = os.environ.get('LYCEUM_STORAGE_PATH', '/lyceum/storage/')
execution_id = os.environ.get('LYCEUM_EXECUTION_ID', 'unknown')

print(f"Storage path: {storage_path}")
print(f"Execution ID: {execution_id}")

# List all environment variables (be careful with secrets!)
if debug_mode:
    print("\nEnvironment variables:")
    for key in sorted(os.environ.keys()):
        if not any(secret in key.upper() for secret in ['KEY', 'TOKEN', 'SECRET', 'PASSWORD']):
            print(f"  {key}: {os.environ[key]}")

import sys
import traceback

def safe_division(a, b):
    """Demonstrate error handling"""
    try:
        result = a / b
        print(f"{a} / {b} = {result}")
        return result
    except ZeroDivisionError:
        print(f"Error: Cannot divide {a} by zero!")
        return None
    except Exception as e:
        print(f"Unexpected error: {e}")
        return None

def main():
    """Main execution with error handling"""
    try:
        # Test various operations
        safe_division(10, 2)
        safe_division(10, 0)  # This will cause an error
        safe_division(10, 3)
        
        # Simulate a success scenario
        print("Execution completed successfully!")
        sys.exit(0)
        
    except Exception as e:
        print(f"Fatal error in main: {e}")
        traceback.print_exc()
        sys.exit(1)

if __name__ == "__main__":
    main()