Errors and Exception Handling

Topics: errors

Errors are inevitable in programming — even in medical research and clinical data management. Learning how to handle them gracefully ensures that your programs remain robust, safe, and user-friendly, especially when dealing with sensitive or life-impacting information.

Types of Errors

Syntax Errors

These occur when Python cannot understand your code due to incorrect syntax. They prevent the program from running entirely.

print("Patient record loaded"
if age = 45:
    print("Valid age")

Pop quiz

Where do you think the errors are?

1. Missing closing parenthesis
2. The condition should use == instead of =
3. Improper indentation
Runtime Errors (Exceptions)

These occur during execution — the syntax is correct, but something unexpected happens (like dividing by zero or accessing missing data)..

print(10 / 0)              # ZeroDivisionError
print(ages[10])            # IndexError (if the list has fewer than 11 items)
print(int("fever"))        # ValueError
print(patient_record)      # NameError (if not defined)

Example:

A clinical data program might crash when trying to divide by zero if a patient’s height is accidentally recorded as 0 during BMI computation.

Basic Exception Handling

Try-Except Blocks

Handle potential errors using try and except statements.

def safe_bmi(weight, height):
    """Safely calculate BMI with error handling."""
    try:
        bmi = weight / (height ** 2)
        return bmi
    except ZeroDivisionError:
        print("Error: Height cannot be zero!")
        return None

Execute the function.

result1 = safe_bmi(60, 1.65)
result2 = safe_bmi(70, 0)

Output:

Error: Height cannot be zero!

Handling Multiple Exceptions

Sometimes multiple things can go wrong — like invalid inputs or user interruptions.

def get_patient_age():
    """Process patient age input safely."""
    try:
        age = int(input("Enter patient age: "))
        if age < 0:
            raise ValueError("Age cannot be negative")

        birth_year = 2025 - age
        return birth_year

    except ValueError as e:
        print(f"Invalid input: {e}")
        return None
    except KeyboardInterrupt:
        print("\nOperation cancelled by user.")
        return None

This ensures your program won’t crash even if the user makes a mistake.

Execute the function.

year = get_patient_age()
if year:
    print(f"You were born in {year}")
Try-Except-Else-Finally

These blocks let you handle file operations safely, which is vital when working with electronic medical records or lab results.

def read_patient_file(filename):
    """Read patient data with comprehensive error handling."""
    file_handle = None
    try:
        file_handle = open(filename, 'r')
        content = file_handle.read()
        print("Patient file read successfully!")

    except FileNotFoundError:
        print(f"Error: File '{filename}' not found.")
        content = None

    except PermissionError:
        print(f"Error: No permission to read '{filename}'.")
        content = None

    except Exception as e:
        print(f"Unexpected error: {e}")
        content = None

    else:
        print(f"File contains {len(content)} characters.")
    finally:
        if file_handle:
            file_handle.close()
            print("File closed.")
    return content
Raising Custom Exceptions

Custom exceptions make your programs specific to your domain — like raising an error when a hospital account or pharmacy balance is insufficient.

class InsufficientStockError(Exception):
    """Custom exception for low medication stock."""
    pass

class PharmacyInventory:
    def __init__(self, stock=0):
        self.stock = stock

    def dispense(self, quantity):
        """Dispense medication with error checks."""
        if quantity <= 0:
            raise ValueError("Dispense quantity must be positive.\)
        if quantity > self.stock:
            raise InsufficientStockError(
                f"Cannot dispense {quantity} units. Only {self.stock} available."
            )
        self.stock -= quantity
        return self.stock

Execute the function.

inventory = PharmacyInventory(20)

try:
    inventory.dispense(50)
except InsufficientStockError as e:
    print(f"Dispensing failed: {e}")

Debugging Tips

Debugging helps you trace problems when something goes wrong in your data pipeline or algorithm.

def debug_lab_results(data):
    \"\"\"Debugging function for lab result entries.\"\"\"
    print(f\"DEBUG: Input type: {type(data)}\")
    print(f\"DEBUG: Input value: {data}\")

    try:
        if isinstance(data, str):
            result = data.upper()
        elif isinstance(data, (int, float)):
            result = data * 2
        elif isinstance(data, list):
            result = [value * 2 for value in data]
        else:
            raise TypeError(f\"Unsupported data type: {type(data)}\")

        print(f\"DEBUG: Processed result: {result}\")
        return result

    except Exception as e:
        print(f\"DEBUG: Exception occurred: {e}\")
        print(f\"DEBUG: Exception type: {type(e).__name__}\")
        raise  # Re-raise the exception for further investigation

Execute the function.

test_data = [\"hello\", 42, [1, 2, 3], {\"key\": \"value\"}]

for data in test_data:
    try:
        result = debug_lab_results(data)
        print(f\"Success: {result}\n\")
    except Exception as e:
        print(f\"Failed: {e}\n\")
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