Question

Name two ways to trigger exceptions in your script.

Short answer

Use the raise statement or invoke code that leads to built-in exceptions.

Step-by-step solution

- Using the raise Statement

One way to trigger exceptions in a script is by using the raise statement. The raise statement allows you to forcefully generate an exception at a specific point in your code. For example, you can trigger an exception if a certain condition is met: ```pythonif condition: raise Exception('This is an error message')```

- Invoking Code that Leads to Built-in Exceptions

Another way to trigger exceptions is by invoking code that inherently leads to built-in exceptions provided by the language. For example, dividing by zero will trigger a ZeroDivisionError:```pythondivision_by_zero = 1 / 0 # This will raise a ZeroDivisionError```Similarly, trying to access an index that does not exist in a list will raise an IndexError:```pythonmy_list = [1, 2, 3]element = my_list[10] # This will raise an IndexError```

Key concepts

raise statement

In Python, one straightforward way to generate exceptions is by using the raise statement. This allows you to intentionally create an exception under specific conditions.

For example, if you are writing a program that requires a certain input to lie within a particular range and the input does not meet that requirement, you can use the raise statement to notify the user of the error.

Here is a sample code snippet demonstrating the raise statement:
``` python
if age < 18:
raise ValueError('Age must be 18 or older.')
```
The above code triggers a ValueError if the variable age is less than 18. This mechanism can offer more controlled and meaningful error management in your scripts.

built-in exceptions

Python provides a variety of built-in exceptions that you can use to handle errors that often occur in programs.

These built-in exceptions make it easier for developers to catch common mistakes and handle them elegantly. Some common built-in exceptions are:

• ZeroDivisionError: Raised when a division by zero occurs.
• IndexError: Raised when trying to access an index that is not in a list.
• KeyError: Raised when a dictionary key is not found.
• TypeError: Raised when an operation is performed on an inappropriate type.

Using these built-in exceptions, you can enhance the robustness of your code by providing graceful error handling mechanisms. For example, calling an index that does not exist will automatically raise an IndexError:
``` python
my_list = [10, 20, 30]
print(my_list[5]) # This will raise an IndexError
```

error message

An important aspect of exception handling is communicating what went wrong.

This is where error messages come into play. When an exception occurs, Python provides a default error message to help you understand the cause.
Understanding these messages can help you debug the code efficiently.

Customizing error messages can make your code even clearer and easier to debug.
For instance, raising an exception with a custom message can look like this:
``` python
if amount < 0:
raise ValueError('Amount must be non-negative')
```
In the above example, if the condition is met (i.e., amount is less than zero), Python will raise a ValueError along with the custom message 'Amount must be non-negative'.
This approach not only stops the execution of faulty code but also communicates clearly why it was stopped.