09. Error Handling

Try/Except

def divide(a, b):
    try:
        result = a / b
        return result
    except ZeroDivisionError:
        return 0
    except TypeError:
        return None

Catching Multiple Exceptions

try:
    result = int(user_input) / divisor
except (ValueError, ZeroDivisionError) as e:
    print(f"Error: {e}")
    result = None

The Exception Object

try:
    data = json.loads(invalid_json)
except json.JSONDecodeError as e:
    print(f"Failed to parse JSON at position {e.pos}")
    print(f"Error: {e.msg}")

Finally

try:
    file = open("data.json")
    data = json.load(file)
finally:
    file.close()  # Always runs

Or use with to avoid explicit close:

try:
    with open("data.json") as f:
        data = json.load(f)
except FileNotFoundError:
    data = {}

Raising Errors

def call_api(model_name):
    valid_models = ["gpt-4", "gpt-3.5-turbo", "claude-3"]
    if model_name not in valid_models:
        raise ValueError(f"Unknown model: {model_name}. Valid: {valid_models}")
    # ... proceed with API call

Local verification checkpoint

Run the smallest example from this chapter in a local workspace and record the package version, runtime, data path, and observed output. If the result depends on model size, vector count, CPU/GPU backend, or available memory, note that constraint beside the exercise so the lesson remains reproducible.

Local verification checkpoint

Run the smallest example from this chapter in a local workspace and record the package version, runtime, data path, and observed output. If the result depends on model size, vector count, CPU/GPU backend, or available memory, note that constraint beside the exercise so the lesson remains reproducible.