Errors¶
Errors or mistakes in a program are often referred to as bugs. They are almost always the fault of the programmer. The process of finding and eliminating errors is called debugging. Errors can be classified into three major groups:
- Syntax errors
- Runtime errors
- Logical errors
Syntax errors¶
Python will find these kinds of errors when it tries to parse your program, and exit with an error message without running anything. Syntax errors are mistakes in the use of the Python language, and are analogous to spelling or grammar mistakes in a language like English: for example, the sentence Would you some tea? does not make sense – it is missing a verb.
Common Python syntax errors include:
- leaving out a keyword
- putting a keyword in the wrong place
- leaving out a symbol, such as a colon, comma or brackets
- misspelling a keyword
- incorrect indentation
- empty block
Note
it is illegal for any block [like an if body, or the body of a function] to be left completely empty. If you want a block to do nothing, you can use the pass statement inside the block.
Python will do its best to tell you where the error is located, but sometimes its messages can be misleading: for example, if you forget to escape a quotation mark inside a string you may get a syntax error referring to a place later in your code, even though that is not the real source of the problem. If you can’t see anything wrong on the line specified in the error message, try backtracking through the previous few lines. As you program more, you will get better at identifying and fixing errors.
Here are some examples of syntax errors in Python:
myfunction[x, y]: return x + y else: print["Hello!"] if mark >= 50 print["You passed!"] if arriving: print["Hi!"] esle: print["Bye!"] if flag: print["Flag is set!"]
Runtime errors¶
If a program is syntactically correct – that is, free of syntax errors – it will be run by the Python interpreter. However, the program may exit unexpectedly during execution if it encounters a runtime error – a problem which was not detected when the program was parsed, but is only revealed when a particular line is executed. When a program comes to a halt because of a runtime error, we say that it has crashed.
Consider the English instruction flap your arms and fly to Australia. While the instruction is structurally correct and you can understand its meaning perfectly, it is impossible for you to follow it.
Some examples of Python runtime errors:
- division by zero
- performing an operation on incompatible types
- using an identifier which has not been defined
- accessing a list element, dictionary value or object attribute which doesn’t exist
- trying to access a file which doesn’t exist
Runtime errors often creep in if you don’t consider all possible values that a variable could contain, especially when you are processing user input. You should always try to add checks to your code to make sure that it can deal with bad input and edge cases gracefully. We will look at this in more detail in the chapter about exception handling.
Logical errors¶
Logical errors are the most difficult to fix. They occur when the program runs without crashing, but produces an incorrect result. The error is caused by a mistake in the program’s logic. You won’t get an error message, because no syntax or runtime error has occurred. You will have to find the problem on your own by reviewing all the relevant parts of your code – although some tools can flag suspicious code which looks like it could cause unexpected behaviour.
Sometimes there can be absolutely nothing wrong with your Python implementation of an algorithm – the algorithm itself can be incorrect. However, more frequently these kinds of errors are caused by programmer carelessness. Here are some examples of mistakes which lead to logical errors:
- using the wrong variable name
- indenting a block to the wrong level
- using integer division instead of floating-point division
- getting operator precedence wrong
- making a mistake in a boolean expression
- off-by-one, and other numerical errors
If you misspell an identifier name, you may get a runtime error or a logical error, depending on whether the misspelled name is defined.
A common source of variable name mix-ups and incorrect indentation is frequent copying and pasting of large blocks of code. If you have many duplicate lines with minor differences, it’s very easy to miss a necessary change when you are editing your pasted lines. You should always try to factor out excessive duplication using functions and loops – we will look at this in more detail later.
Exercise 1¶
Find all the syntax errors in the code snippet above, and explain why they are errors.
Find potential sources of runtime errors in this code snippet:
dividend = float[input["Please enter the dividend: "]] divisor = float[input["Please enter the divisor: "]] quotient = dividend / divisor quotient_rounded = math.round[quotient]
Find potential sources of runtime errors in this code snippet:
for x in range[a, b]: print["[%f, %f, %f]" % my_list[x]]
Find potential sources of logic errors in this code snippet:
product = 0 for i in range[10]: product *= i sum_squares = 0 for i in range[10]: i_sq = i**2 sum_squares += i_sq nums = 0 for num in range[10]: num += num
Handling exceptions¶
Until now, the programs that we have written have generally ignored the fact that things can go wrong. We have have tried to prevent runtime errors by checking data which may be incorrect before we used it, but we haven’t yet seen how we can handle errors when they do occur – our programs so far have just crashed suddenly whenever they have encountered one.
There are some situations in which runtime errors are likely to occur. Whenever we try to read a file or get input from a user, there is a chance that something unexpected will happen – the file may have been moved or deleted, and the user may enter data which is not in the right format. Good programmers should add safeguards to their programs so that common situations like this can be handled gracefully – a program which crashes whenever it encounters an easily foreseeable problem is not very pleasant to use. Most users expect programs to be robust enough to recover from these kinds of setbacks.
If we know that a particular section of our program is likely to cause an error, we can tell Python what to do if it does happen. Instead of letting the error crash our program we can intercept it, do something about it, and allow the program to continue.
All the runtime [and syntax] errors that we have encountered are called exceptions in Python – Python uses them to indicate that something exceptional has occurred, and that your program cannot continue unless it is handled. All exceptions are subclasses of the Exception class – we will learn more about classes, and how to write your own exception types, in later chapters.
The try and except statements¶
To handle possible exceptions, we use a try-except block:
try: age = int[input["Please enter your age: "]] print["I see that you are %d years old." % age] except ValueError: print["Hey, that wasn't a number!"]
Python will try to process all the statements inside the try block. If a ValueError occurs at any point as it is executing them, the flow of control will immediately pass to the except block, and any remaining statements in the try block will be skipped.
In this example, we know that the error is likely to occur when we try to convert the user’s input to an integer. If the input string is not a number, this line will trigger a ValueError – that is why we specified it as the type of error that we are going to handle.
We could have specified a more general type of error – or even left the type out entirely, which would have caused the except clause to match any kind of exception – but that would have been a bad idea. What if we got a completely different error that we hadn’t predicted? It would be handled as well, and we wouldn’t even notice that anything unusual was going wrong. We may also want to react in different ways to different kinds of errors. We should always try pick specific rather than general error types for our except clauses.
It is possible for one except clause to handle more than one kind of error: we can provide a tuple of exception types instead of a single type:
try: dividend = int[input["Please enter the dividend: "]] divisor = int[input["Please enter the divisor: "]] print["%d / %d = %f" % [dividend, divisor, dividend/divisor]] except[ValueError, ZeroDivisionError]: print["Oops, something went wrong!"]
A try-except block can also have multiple except clauses. If an exception occurs, Python will check each except clause from the top down to see if the exception type matches. If none of the except clauses match, the exception will be considered unhandled, and your program will crash:
try: dividend = int[input["Please enter the dividend: "]] divisor = int[input["Please enter the divisor: "]] print["%d / %d = %f" % [dividend, divisor, dividend/divisor]] except ValueError: print["The divisor and dividend have to be numbers!"] except ZeroDivisionError: print["The dividend may not be zero!"]
Note that in the example above if a ValueError occurs we won’t know whether it was caused by the dividend or the divisor not being an integer – either one of the input lines could cause that error. If we want to give the user more specific feedback about which input was wrong, we will have to wrap each input line in a separate try-except block:
try: dividend = int[input["Please enter the dividend: "]] except ValueError: print["The dividend has to be a number!"] try: divisor = int[input["Please enter the divisor: "]] except ValueError: print["The divisor has to be a number!"] try: print["%d / %d = %f" % [dividend, divisor, dividend/divisor]] except ZeroDivisionError: print["The dividend may not be zero!"]
In general, it is a better idea to use exception handlers to protect small blocks of code against specific errors than to wrap large blocks of code and write vague, generic error recovery code. It may sometimes seem inefficient and verbose to write many small try-except statements instead of a single catch-all statement, but we can mitigate this to some extent by making effective use of loops and functions to reduce the amount of code duplication.
How an exception is handled¶
When an exception occurs, the normal flow of execution is interrupted. Python checks to see if the line of code which caused the exception is inside a try block. If it is, it checks to see if any of the except blocks associated with the try block can handle that type of exception. If an appropriate handler is found, the exception is handled, and the program continues from the next statement after the end of that try-except.
If there is no such handler, or if the line of code was not in a try block, Python will go up one level of scope: if the line of code which caused the exception was inside a function, that function will exit immediately, and the line which called the function will be treated as if it had thrown the exception. Python will check if that line is inside a try block, and so on. When a function is called, it is placed on Python’s stack, which we will discuss in the chapter about functions. Python traverses this stack when it tries to handle an exception.
If an exception is thrown by a line which is in the main body of your program, not inside a function, the program will terminate. When the exception message is printed, you should also see a traceback – a list which shows the path the exception has taken, all the way back to the original line which caused the error.
Error checks vs exception handling¶
Exception handling gives us an alternative way to deal with error-prone situations in our code. Instead of performing more checks before we do something to make sure that an error will not occur, we just try to do it – and if an error does occur we handle it. This can allow us to write simpler and more readable code. Let’s look at a more complicated input example – one in which we want to keep asking the user for input until the input is correct. We will try to write this example using the two different approaches:
# with checks n = None while n is None: s = input["Please enter an integer: "] if s.lstrip['-'].isdigit[]: n = int[s] else: print["%s is not an integer." % s] # with exception handling n = None while n is None: try: s = input["Please enter an integer: "] n = int[s] except ValueError: print["%s is not an integer." % s]
In the first code snippet, we have to write quite a convoluted check to test whether the user’s input is an integer – first we strip off a minus sign if it exists, and then we check if the rest of the string consists only of digits. But there’s a very simple criterion which is also what we really want to know: will this string cause a ValueError if we try to convert it to an integer? In the second snippet we can in effect check for exactly the right condition instead of trying to replicate it ourselves – something which isn’t always easy to do. For example, we could easily have forgotten that integers can be negative, and written the check in the first snippet incorrectly.
Here are a few other advantages of exception handling:
- It separates normal code from code that handles errors.
- Exceptions can easily be passed along functions in the stack until they reach a function which knows how to handle them. The intermediate functions don’t need to have any error-handling code.
- Exceptions come with lots of useful error information built in – for example, they can print a traceback which helps us to see exactly where the error occurred.
The else and finally statements¶
There are two other clauses that we can add to a try-except block: else and finally. else will be executed only if the try clause doesn’t raise an exception:
try: age = int[input["Please enter your age: "]] except ValueError: print["Hey, that wasn't a number!"] else: print["I see that you are %d years old." % age]
We want to print a message about the user’s age only if the integer conversion succeeds. In the first exception handler example, we put this print statement directly after the conversion inside the try block. In both cases, the statement will only be executed if the conversion statement doesn’t raise an exception, but putting it in the else block is better practice – it means that the only code inside the try block is the single line that is the potential source of the error that we want to handle.
When we edit this program in the future, we may introduce additional statements that should also be executed if the age input is successfully converted. Some of these statements may also potentially raise a ValueError. If we don’t notice this, and put them inside the try clause, the except clause will also handle these errors if they occur. This is likely to cause some odd and unexpected behaviour. By putting all this extra code in the else clause instead, we avoid taking this risk.
The finally clause will be executed at the end of the try-except block no matter what – if there is no exception, if an exception is raised and handled, if an exception is raised and not handled, and even if we exit the block using break, continue or return. We can use the finally clause for cleanup code that we always want to be executed:
try: age = int[input["Please enter your age: "]] except ValueError: print["Hey, that wasn't a number!"] else: print["I see that you are %d years old." % age] finally: print["It was really nice talking to you. Goodbye!"]
Exercise 2¶
Extend the program in exercise 7 of the loop control statements chapter to include exception handling. Whenever the user enters input of the incorrect type, keep prompting the user for the same value until it is entered correctly. Give the user sensible feedback.
Add a try-except statement to the body of this function which handles a possible IndexError, which could occur if the index provided exceeds the length of the list. Print an error message if this happens:
def print_list_element[thelist, index]: print[thelist[index]]
This function adds an element to a list inside a dict of lists. Rewrite it to use a try-except statement which handles a possible KeyError if the list with the name provided doesn’t exist in the dictionary yet, instead of checking beforehand whether it does. Include else and finally clauses in your try-except block:
def add_to_list_in_dict[thedict, listname, element]: if listname in thedict: l = thedict[listname] print["%s already has %d elements." % [listname, len[l]]] else: thedict[listname] = [] print["Created %s." % listname] thedict[listname].append[element] print["Added %s to %s." % [element, listname]]
The with statement¶
Using the exception object¶
Python’s exception objects contain more information than just the error type. They also come with some kind of message – we have already seen some of these messages displayed when our programs have crashed. Often these messages aren’t very user-friendly – if we want to report an error to the user we usually need to write a more descriptive message which explains how the error is related to what the user did. For example, if the error was caused by incorrect input, it is helpful to tell the user which of the input values was incorrect.
Sometimes the exception message contains useful information which we want to display to the user. In order to access the message, we need to be able to access the exception object. We can assign the object to a variable that we can use inside the except clause like this:
try: age = int[input["Please enter your age: "]] except ValueError as err: print[err]
err is not a string, but Python knows how to convert it into one – the string representation of an exception is the message, which is exactly what we want. We can also combine the exception message with our own message:
try: age = int[input["Please enter your age: "]] except ValueError as err: print["You entered incorrect age input: %s" % err]
Note that inserting a variable into a formatted string using %s also converts the variable to a string.
Raising exceptions¶
We can raise exceptions ourselves using the raise statement:
try: age = int[input["Please enter your age: "]] if age