1. Understand the Error → 2. Reproduce → 3. Isolate → 4. Identify Root Cause → 5. Fix → 6. Verify

Traceback (most recent call last):        ← Read bottom to top
  File "app.py", line 45, in main         ← Entry point
    result = process_data(data)           ← Call chain
  File "processor.py", line 23, in process_data
    return transform(item)                ← Getting closer
  File "transformer.py", line 12, in transform
    return item["value"] / item["count"]  ← Error location
ZeroDivisionError: division by zero       ← The actual error

# Create minimal test case that triggers the error
def test_reproduces_error():
    # Exact inputs that cause the failure
    data = {"value": 10, "count": 0}  # The problematic input

    # Call the failing function
    result = transform(data)  # Should raise ZeroDivisionError

def process_data(data):
    print(f"DEBUG: data type = {type(data)}")
    print(f"DEBUG: data = {data}")

    for i, item in enumerate(data):
        print(f"DEBUG: processing item {i}: {item}")
        result = transform(item)
        print(f"DEBUG: result = {result}")

    return results

import pdb

def problematic_function(x):
    pdb.set_trace()  # Execution stops here
    # Or use: breakpoint()  # Python 3.7+
    result = x * 2
    return result

from icecream import ic

def calculate(x, y):
    ic(x, y)  # Prints: ic| x: 5, y: 0
    result = x / y
    ic(result)
    return result

# Problem
user = get_user(user_id)  # Returns None if not found
name = user.name  # AttributeError: 'NoneType' has no attribute 'name'

# Fix
user = get_user(user_id)
if user is None:
    raise ValueError(f"User {user_id} not found")
name = user.name

# Problem
def add_numbers(a, b):
    return a + b

add_numbers("5", 3)  # TypeError: can only concatenate str to str

# Fix
def add_numbers(a: int, b: int) -> int:
    return int(a) + int(b)

# Problem - shared list across calls!
def append_to(item, target=[]):
    target.append(item)
    return target

# Fix
def append_to(item, target=None):
    if target is None:
        target = []
    target.append(item)
    return target

# Problem: a.py imports b.py, b.py imports a.py

# Fix: Import inside function or restructure
def get_processor():
    from .processor import Processor  # Lazy import
    return Processor()

# Problem: Forgetting await
async def fetch_data():
    result = fetch_from_api()  # Missing await!
    return result  # Returns coroutine, not result

# Fix
async def fetch_data():
    result = await fetch_from_api()
    return result

def safe_divide(a, b):
    if b == 0:
        raise ValueError("Cannot divide by zero")
    return a / b

def safe_get(data: dict, key: str, default=None):
    return data.get(key, default)

def process_user(user_id: int, data: dict) -> dict:
    if not isinstance(user_id, int) or user_id <= 0:
        raise ValueError(f"Invalid user_id: {user_id}")

    required_fields = ["name", "email"]
    missing = [f for f in required_fields if f not in data]
    if missing:
        raise ValueError(f"Missing required fields: {missing}")

    # Process...

import logging

logger = logging.getLogger(__name__)

def fetch_user_data(user_id: int) -> dict:
    try:
        response = api_client.get(f"/users/{user_id}")
        response.raise_for_status()
        return response.json()
    except requests.HTTPError as e:
        logger.error(f"HTTP error fetching user {user_id}: {e}")
        raise
    except requests.ConnectionError:
        logger.error(f"Connection failed for user {user_id}")
        raise ServiceUnavailableError("API unavailable")

import pytest

def test_transform_handles_zero_count():
    """Verify fix for ZeroDivisionError."""
    data = {"value": 10, "count": 0}

    with pytest.raises(ValueError, match="count cannot be zero"):
        transform(data)

def test_transform_normal_case():
    """Verify normal operation still works."""
    data = {"value": 10, "count": 2}
    result = transform(data)
    assert result == 5

import logging

logging.basicConfig(
    level=logging.DEBUG,
    format="%(asctime)s %(name)s %(levelname)s: %(message)s",
    handlers=[
        logging.FileHandler("debug.log"),
        logging.StreamHandler(),
    ],
)

logger = logging.getLogger(__name__)

def process(data):
    logger.debug(f"Processing data: {data}")
    try:
        result = transform(data)
        logger.info(f"Success: {result}")
        return result
    except Exception as e:
        logger.exception(f"Failed to process: {e}")
        raise

# Time profiling
import cProfile
cProfile.run("main()", "output.prof")

# Memory profiling
from memory_profiler import profile

@profile
def memory_heavy_function():
    # ...

from rich import print
from rich.traceback import install

install(show_locals=True)  # Enhanced tracebacks

print({"data": data, "result": result})  # Pretty printing