How to debug advanced Python issues in Replit

1# example.py
2def calculate_total(items):
3    total = 0
4    for item in items:
5        breakpoint()  # Execution pauses here
6        total += item['price'] * item['quantity']
7    return total
8
9items = [
10    {'name': 'Widget', 'price': 9.99, 'quantity': 3},
11    {'name': 'Gadget', 'price': 24.99, 'quantity': 1},
12    {'name': 'Doohickey', 'price': None, 'quantity': 2},  # Bug: None price
13]
14
15result = calculate_total(items)
16print(f'Total: ${result:.2f}')

1# This code produces a traceback:
2def get_user_email(users, user_id):
3    user = users[user_id]        # Line that crashes
4    return user['email']
5
6users = {'alice': {'email': 'alice@example.com'}}
7email = get_user_email(users, 'bob')  # 'bob' not in dict
8
9# Traceback output:
10# Traceback (most recent call last):
11#   File "main.py", line 6, in <module>
12#     email = get_user_email(users, 'bob')
13#   File "main.py", line 2, in get_user_email
14#     user = users[user_id]
15# KeyError: 'bob'
16
17# Fix: use .get() with a default
18def get_user_email(users, user_id):
19    user = users.get(user_id)
20    if user is None:
21        return None
22    return user['email']

1import logging
2
3# Configure logging with timestamps and levels
4logging.basicConfig(
5    level=logging.DEBUG,
6    format='%(asctime)s [%(levelname)s] %(name)s: %(message)s',
7    datefmt='%H:%M:%S'
8)
9
10logger = logging.getLogger('myapp')
11
12def process_order(order):
13    logger.info(f"Processing order {order['id']}")
14    logger.debug(f"Order details: {order}")
15
16    if order['total'] <= 0:
17        logger.warning(f"Order {order['id']} has zero or negative total")
18        return False
19
20    try:
21        # Simulate payment processing
22        charge_payment(order)
23        logger.info(f"Order {order['id']} completed successfully")
24        return True
25    except Exception as e:
26        logger.error(f"Payment failed for order {order['id']}: {e}")
27        return False

1import tracemalloc
2
3# Start tracing memory allocations
4tracemalloc.start()
5
6def load_large_dataset():
7    # Simulating a memory-heavy operation
8    data = []
9    for i in range(100000):
10        data.append({'id': i, 'value': f'item_{i}' * 100})
11    return data
12
13# Run the operation
14result = load_large_dataset()
15
16# Take a snapshot and show top memory consumers
17snapshot = tracemalloc.take_snapshot()
18stats = snapshot.statistics('lineno')
19
20print('\nTop 10 memory allocations:')
21for stat in stats[:10]:
22    print(f'  {stat}')
23
24# Show current and peak memory usage
25current, peak = tracemalloc.get_traced_memory()
26print(f'\nCurrent memory: {current / 1024 / 1024:.1f} MB')
27print(f'Peak memory: {peak / 1024 / 1024:.1f} MB')
28
29tracemalloc.stop()

1import requests
2import logging
3
4logger = logging.getLogger('api')
5
6def fetch_weather(city):
7    api_key = os.getenv('WEATHER_API_KEY')
8    if not api_key:
9        raise ValueError('WEATHER_API_KEY not set. Add it in Tools → Secrets.')
10
11    url = f'https://api.example.com/weather?q={city}&key={api_key}'
12    logger.info(f'Fetching weather for {city}')
13
14    try:
15        response = requests.get(url, timeout=10)
16        logger.debug(f'Response status: {response.status_code}')
17
18        if response.status_code != 200:
19            logger.error(f'API error {response.status_code}: {response.text}')
20            response.raise_for_status()
21
22        return response.json()
23    except requests.Timeout:
24        logger.error(f'Request to weather API timed out after 10 seconds')
25        raise
26    except requests.ConnectionError as e:
27        logger.error(f'Cannot connect to weather API: {e}')
28        raise