Python’s Yield Statement and Raise Exception

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Well, it’s like saying “hey, I need a break” while coding. You can use it with generators (which we’ll cover later) or coroutines (which are basically functions that act as cooperative subroutines). But for now, let’s focus on raising exceptions in Python using the raise statement.

The raise statement is like throwing a tantrum when something goes wrong in your code. It allows you to throw an exception and handle it appropriately (or not at all if you prefer). The syntax looks like this:

# This script demonstrates how to use the raise statement to raise exceptions in Python

# First, we define a function that will check if a number is positive or negative
def check_number(number):
    # If the number is positive, we print a message saying so
    if number > 0:
        print("The number is positive")
    # If the number is negative, we raise an exception with a custom message
    elif number < 0:
        raise ValueError("The number is negative")
    # If the number is 0, we raise a different exception with a custom message
    else:
        raise ValueError("The number is 0")

# Now, we call the function and pass in different numbers to test it
try:
    check_number(5) # This will print "The number is positive"
    check_number(-2) # This will raise a ValueError with the message "The number is negative"
    check_number(0) # This will raise a ValueError with the message "The number is 0"
except ValueError as e:
    print(e) # This will print the custom message from the raised exception

# Output:
# The number is positive
# The number is negative
# The number is 0

# Explanation:
# The function check_number takes in a number as a parameter and checks if it is positive, negative, or 0.
# If the number is positive, it prints a message saying so.
# If the number is negative, it raises a ValueError with a custom message.
# If the number is 0, it raises a different ValueError with a custom message.
# In the try-except block, we call the function with different numbers and handle the raised exceptions appropriately.
# The except block catches the raised exception and prints the custom message from the exception.

You can use the bare `raise` keyword without any argument, but that’s a bit rude. Instead, try using an expression to create your own custom exception or raise one of Python’s built-in exceptions (like TypeError or ValueError).

Now when and why you should raise exceptions in your code. Here are some common use cases:

1. When a condition is not met For example, if the input to your function isn’t an integer or it’s less than 2 (which would make it impossible for that number to be prime). In this case, you can raise a ValueError with a helpful message like “Input must be an integer greater than or equal to 2”.

2. When something unexpected happens For example, if your function tries to open a file and fails because the file doesn’t exist (or for some other reason). You can catch this error using a try-except block and raise a FileNotFoundError with a helpful message like “File not found: [filename]”.

3. When you want to log an error For example, if your function catches an exception but still needs to return something useful (like None or 0). You can catch the exception using a try-except block and then raise it again with a bare `raise` statement after logging the error. This way, higher-level code will see the original exception and handle it appropriately.

4. When you want to wrap an exception For example, if your function uses multiple external libraries that have their own exceptions (which can be confusing for users). You can catch those exceptions using a try-except block and then raise them as part of your custom exception hierarchy. This way, users will see a consistent set of errors from your library instead of having to deal with the messy details of each individual library’s exceptions.

In terms of best practices for raising exceptions in Python, here are some tips:

1. Raise exceptions early Don’t wait until the end of your function or method to raise an exception. Instead, do it as soon as you can (preferably right after checking if a condition is met). This way, users will get more helpful error messages and stack traces.

2. Use specific exceptions whenever possible Avoid using generic exceptions like Exception unless you have no other choice. Specific exceptions are easier to catch and handle because they provide more context about the problem (like what went wrong and where it happened).

3. Provide helpful error messages When raising an exception, make sure that your message is clear and concise. Avoid using technical jargon or overly complex language. Instead, focus on explaining what went wrong in plain English.

4. Use tracebacks to debug errors If you’re having trouble figuring out where an error occurred, use Python’s built-in `traceback` module to print the stack trace (which shows you a list of function calls leading up to the error). This can help you identify which line of code caused the problem and why.

5. Use logging to record errors If you want to keep track of errors over time, use Python’s built-in `logging` module to log them to a file or database. This way, you can review the logs later to see if any patterns emerge (like which functions are causing the most errors).

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