Python exception runtime error

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:

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¶

  1. Find all the syntax errors in the code snippet above, and explain why they are errors.

  2. 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)
    
  3. Find potential sources of runtime errors in this code snippet:

    for x in range(a, b):
        print("(%f, %f, %f)" % my_list[x])
    
  4. 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¶

  1. 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.

  2. 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])
    
  3. 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 < 0:
        raise ValueError("%d is not a valid age. Age must be positive or zero.")
except ValueError as err:
    print("You entered incorrect age input: %s" % err)
else:
    print("I see that you are %d years old." % age)

We can raise our own ValueError if the age input is a valid integer, but it’s negative. When we do this, it has exactly the same effect as any other exception – the flow of control will immediately exit the try clause at this point and pass to the except clause. This except clause can match our exception as well, since it is also a ValueError.

We picked ValueError as our exception type because it’s the most appropriate for this kind of error. There’s nothing stopping us from using a completely inappropriate exception class here, but we should try to be consistent. Here are a few common exception types which we are likely to raise in our own code:

  • TypeError: this is an error which indicates that a variable has the wrong type for some operation. We might raise it in a function if a parameter is not of a type that we know how to handle.
  • ValueError: this error is used to indicate that a variable has the right type but the wrong value. For example, we used it when age was an integer, but the wrong kind of integer.
  • NotImplementedError: we will see in the next chapter how we use this exception to indicate that a class’s method has to be implemented in a child class.

We can also write our own custom exception classes which are based on existing exception classes – we will see some examples of this in a later chapter.

Something we may want to do is raise an exception that we have just intercepted – perhaps because we want to handle it partially in the current function, but also want to respond to it in the code which called the function:

try:
    age = int(input("Please enter your age: "))
except ValueError as err:
    print("You entered incorrect age input: %s" % err)
    raise err

Exercise 3¶

  1. Rewrite the program from the first question of exercise 2 so that it prints the text of Python’s original exception inside the except clause instead of a custom message.
  2. Rewrite the program from the second question of exercise 2 so that the exception which is caught in the except clause is re-raised after the error message is printed.

Debugging programs¶

Syntax errors are usually quite straightforward to debug: the error message shows us the line in the file where the error is, and it should be easy to find it and fix it.

Runtime errors can be a little more difficult to debug: the error message and the traceback can tell us exactly where the error occurred, but that doesn’t necessarily tell us what the problem is. Sometimes they are caused by something obvious, like an incorrect identifier name, but sometimes they are triggered by a particular state of the program – it’s not always clear which of many variables has an unexpected value.

Logical errors are the most difficult to fix because they don’t cause any errors that can be traced to a particular line in the code. All that we know is that the code is not behaving as it should be – sometimes tracking down the area of the code which is causing the incorrect behaviour can take a long time.

It is important to test your code to make sure that it behaves the way that you expect. A quick and simple way of testing that a function is doing the right thing, for example, is to insert a print statement after every line which outputs the intermediate results which were calculated on that line. Most programmers intuitively do this as they are writing a function, or perhaps if they need to figure out why it isn’t doing the right thing:

def hypotenuse(x, y):
    print("x is %f and y is %f" % (x, y))
    x_2 = x**2
    print(x_2)
    y_2 = y**2
    print(y_2)
    z_2 = x_2 + y_2
    print(z_2)
    z = math.sqrt(z_2)
    print(z)
    return z

This is a quick and easy thing to do, and even experienced programmers are guilty of doing it every now and then, but this approach has several disadvantages:

  • As soon as the function is working, we are likely to delete all the print statements, because we don’t want our program to print all this debugging information all the time. The problem is that code often changes – the next time we want to test this function we will have to add the print statements all over again.

  • To avoid rewriting the print statements if we happen to need them again, we may be tempted to comment them out instead of deleting them – leaving them to clutter up our code, and possibly become so out of sync that they end up being completely useless anyway.

  • To print out all these intermediate values, we had to spread out the formula inside the function over many lines. Sometimes it is useful to break up a calculation into several steps, if it is very long and putting it all on one line makes it hard to read, but sometimes it just makes our code unnecessarily verbose. Here is what the function above would normally look like:

    def hypotenuse(x, y):
        return math.sqrt(x**2 + y**2)
    

How can we do this better? If we want to inspect the values of variables at various steps of a program’s execution, we can use a tool like pdb. If we want our program to print out informative messages, possibly to a file, and we want to be able to control the level of detail at runtime without having to change anything in the code, we can use logging.

Most importantly, to check that our code is working correctly now and will keep working correctly, we should write a permanent suite of tests which we can run on our code regularly. We will discuss testing in more detail in a later chapter.

Logging¶

Sometimes it is valuable for a program to output messages to a console or a file as it runs. These messages can be used as a record of the program’s execution, and help us to find errors. Sometimes a bug occurs intermittently, and we don’t know what triggers it – if we only add debugging output to our program when we want to begin an active search for the bug, we may be unable to reproduce it. If our program logs messages to a file all the time, however, we may find that some helpful information has been recorded when we check the log after the bug has occurred.

Some kinds of messages are more important than others – errors are noteworthy events which should almost always be logged. Messages which record that an operation has been completed successfully may sometimes be useful, but are not as important as errors. Detailed messages which debug every step of a calculation can be interesting if we are trying to debug the calculation, but if they were printed all the time they would fill the console with noise (or make our log file really, really big).

We can use Python’s logging module to add logging to our program in an easy and consistent way. Logging statements are almost like print statements, but whenever we log a message we specify a level for the message. When we run our program, we set a desired log level for the program. Only messages which have a level greater than or equal to the level which we have set will appear in the log. This means that we can temporarily switch on detailed logging and switch it off again just by changing the log level in one place.

There is a consistent set of logging level names which most languages use. In order, from the highest value (most severe) to the lowest value (least severe), they are:

  • CRITICAL – for very serious errors
  • ERROR – for less serious errors
  • WARNING – for warnings
  • INFO – for important informative messages
  • DEBUG – for detailed debugging messages

These names are used for integer constants defined in the logging module. The module also provides methods which we can use to log messages. By default these messages are printed to the console, and the default log level is WARNING. We can configure the module to customise its behaviour – for example, we can write the messages to a file instead, raise or lower the log level and change the message format. Here is a simple logging example:

import logging

# log messages to a file, ignoring anything less severe than ERROR
logging.basicConfig(filename='myprogram.log', level=logging.ERROR)

# these messages should appear in our file
logging.error("The washing machine is leaking!")
logging.critical("The house is on fire!")

# but these ones won't
logging.warning("We're almost out of milk.")
logging.info("It's sunny today.")
logging.debug("I had eggs for breakfast.")

There’s also a special exception method which is used for logging exceptions. The level used for these messages is ERROR, but additional information about the exception is added to them. This method is intended to be used inside exception handlers instead of error:

try:
    age = int(input("How old are you? "))
except ValueError as err:
    logging.exception(err)

If we have a large project, we may want to set up a more complicated system for logging – perhaps we want to format certain messages differently, log different messages to different files, or log to multiple locations at the same time. The logging module also provides us with logger and handler objects for this purpose. We can use multiple loggers to create our messages, customising each one independently. Different handlers are associated with different logging locations. We can connect up our loggers and handlers in any way we like – one logger can use many handlers, and multiple loggers can use the same handler.

Exercise 4¶

  1. Write logging configuration for a program which logs to a file called log.txt and discards all logs less important than INFO.
  2. Rewrite the second program from exercise 2 so that it uses this logging configuration instead of printing messages to the console (except for the first print statement, which is the purpose of the function).
  3. Do the same with the third program from exercise 2.

Answers to exercises¶

Answer to exercise 1¶

  1. There are five syntax errors:

    1. Missing def keyword in function definition
    2. else clause without an if
    3. Missing colon after if condition
    4. Spelling mistake (“esle”)
    5. The if block is empty because the print statement is not indented correctly
    1. The values entered by the user may not be valid integers or floating-point numbers.
    2. The user may enter zero for the divisor.
    3. If the math library hasn’t been imported, math.round is undefined.
    1. a, b and my_list need to be defined before this snippet.
    2. The attempt to access the list element with index x may fail during one of the loop iterations if the range from a to b exceeds the size of my_list.
    3. The string formatting operation inside the print statement expects my_list[x] to be a tuple with three numbers. If it has too many or too few elements, or isn’t a tuple at all, the attempt to format the string will fail.
    1. If you are accumulating a number total by multiplication, not addition, you need to initialise the total to 1, not 0, otherwise the product will always be zero!
    2. The line which adds i_sq to sum_squares is not aligned correctly, and will only add the last value of i_sq after the loop has concluded.
    3. The wrong variable is used: at each loop iteration the current number in the range is added to itself and nums remains unchanged.

Answer to exercise 2¶

  1. Here is an example program:

    person = {}
    
    properties = [
        ("name", str),
        ("surname", str),
        ("age", int),
        ("height", float),
        ("weight", float),
    ]
    
    for property, p_type in properties:
        valid_value = None
    
        while valid_value is None:
            try:
                value = input("Please enter your %s: " % property)
                valid_value = p_type(value)
            except ValueError:
                print("Could not convert %s '%s' to type %s. Please try again." % (property, value, p_type.__name__))
    
        person[property] = valid_value
    
  2. Here is an example program:

    def print_list_element(thelist, index):
        try:
            print(thelist[index])
        except IndexError:
            print("The list has no element at index %d." % index)
    
  3. Here is an example program:

    def add_to_list_in_dict(thedict, listname, element):
        try:
            l = thedict[listname]
        except KeyError:
            thedict[listname] = []
            print("Created %s." % listname)
        else:
            print("%s already has %d elements." % (listname, len(l)))
        finally:
            thedict[listname].append(element)
            print("Added %s to %s." % (element, listname))
    

Answer to exercise 3¶

  1. Here is an example program:

    person = {}
    
    properties = [
        ("name", str),
        ("surname", str),
        ("age", int),
        ("height", float),
        ("weight", float),
    ]
    
    for property, p_type in properties:
        valid_value = None
    
        while valid_value is None:
            try:
                value = input("Please enter your %s: " % property)
                valid_value = p_type(value)
            except ValueError as ve:
                print(ve)
    
        person[property] = valid_value
    
  2. Here is an example program:

    def print_list_element(thelist, index):
        try:
            print(thelist[index])
        except IndexError as ie:
            print("The list has no element at index %d." % index)
            raise ie
    

Answer to exercise 4¶

  1. Here is an example of the logging configuration:

    import logging
    logging.basicConfig(filename='log.txt', level=logging.INFO)
    
  2. Here is an example program:

    def print_list_element(thelist, index):
        try:
            print(thelist[index])
        except IndexError:
            logging.error("The list has no element at index %d." % index)
    
  3. Here is an example program:

    def add_to_list_in_dict(thedict, listname, element):
        try:
            l = thedict[listname]
        except KeyError:
            thedict[listname] = []
            logging.info("Created %s." % listname)
        else:
            logging.info("%s already has %d elements." % (listname, len(l)))
        finally:
            thedict[listname].append(element)
            logging.info("Added %s to %s." % (element, listname))
    

Обработка ошибок увеличивает отказоустойчивость кода, защищая его от потенциальных сбоев, которые могут привести к преждевременному завершению работы.

Синтаксис обработки исключений

Прежде чем переходить к обсуждению того, почему обработка исключений так важна, и рассматривать встроенные в Python исключения, важно понять, что есть тонкая грань между понятиями ошибки и исключения.

Ошибку нельзя обработать, а исключения Python обрабатываются при выполнении программы. Ошибка может быть синтаксической, но существует и много видов исключений, которые возникают при выполнении и не останавливают программу сразу же. Ошибка может указывать на критические проблемы, которые приложение и не должно перехватывать, а исключения — состояния, которые стоит попробовать перехватить. Ошибки — вид непроверяемых и невозвратимых ошибок, таких как OutOfMemoryError, которые не стоит пытаться обработать.

Обработка исключений делает код более отказоустойчивым и помогает предотвращать потенциальные проблемы, которые могут привести к преждевременной остановке выполнения. Представьте код, который готов к развертыванию, но все равно прекращает работу из-за исключения. Клиент такой не примет, поэтому стоит заранее обработать конкретные исключения, чтобы избежать неразберихи.

Ошибки могут быть разных видов:

  • Синтаксические
  • Недостаточно памяти
  • Ошибки рекурсии
  • Исключения

Разберем их по очереди.

Синтаксические ошибки (SyntaxError)

Синтаксические ошибки часто называют ошибками разбора. Они возникают, когда интерпретатор обнаруживает синтаксическую проблему в коде.

Рассмотрим на примере.

a = 8
b = 10
c = a b
File "", line 3
 c = a b
       ^
SyntaxError: invalid syntax

Стрелка вверху указывает на место, где интерпретатор получил ошибку при попытке исполнения. Знак перед стрелкой указывает на причину проблемы. Для устранения таких фундаментальных ошибок Python будет делать большую часть работы за программиста, выводя название файла и номер строки, где была обнаружена ошибка.

Недостаточно памяти (OutofMemoryError)

Ошибки памяти чаще всего связаны с оперативной памятью компьютера и относятся к структуре данных под названием “Куча” (heap). Если есть крупные объекты (или) ссылки на подобные, то с большой долей вероятности возникнет ошибка OutofMemory. Она может появиться по нескольким причинам:

  • Использование 32-битной архитектуры Python (максимальный объем выделенной памяти невысокий, между 2 и 4 ГБ);
  • Загрузка файла большого размера;
  • Запуск модели машинного обучения/глубокого обучения и много другое;

Обработать ошибку памяти можно с помощью обработки исключений — резервного исключения. Оно используется, когда у интерпретатора заканчивается память и он должен немедленно остановить текущее исполнение. В редких случаях Python вызывает OutofMemoryError, позволяя скрипту каким-то образом перехватить самого себя, остановить ошибку памяти и восстановиться.

Но поскольку Python использует архитектуру управления памятью из языка C (функция malloc()), не факт, что все процессы восстановятся — в некоторых случаях MemoryError приведет к остановке. Следовательно, обрабатывать такие ошибки не рекомендуется, и это не считается хорошей практикой.

Ошибка рекурсии (RecursionError)

Эта ошибка связана со стеком и происходит при вызове функций. Как и предполагает название, ошибка рекурсии возникает, когда внутри друг друга исполняется много методов (один из которых — с бесконечной рекурсией), но это ограничено размером стека.

Все локальные переменные и методы размещаются в стеке. Для каждого вызова метода создается стековый кадр (фрейм), внутрь которого помещаются данные переменной или результат вызова метода. Когда исполнение метода завершается, его элемент удаляется.

Чтобы воспроизвести эту ошибку, определим функцию recursion, которая будет рекурсивной — вызывать сама себя в бесконечном цикле. В результате появится ошибка StackOverflow или ошибка рекурсии, потому что стековый кадр будет заполняться данными метода из каждого вызова, но они не будут освобождаться.

def recursion():
    return recursion()

recursion()
---------------------------------------------------------------------------

RecursionError                            Traceback (most recent call last)

 in 
----> 1 recursion()


 in recursion()
      1 def recursion():
----> 2     return recursion()


... last 1 frames repeated, from the frame below ...


 in recursion()
      1 def recursion():
----> 2     return recursion()


RecursionError: maximum recursion depth exceeded

Ошибка отступа (IndentationError)

Эта ошибка похожа по духу на синтаксическую и является ее подвидом. Тем не менее она возникает только в случае проблем с отступами.

Пример:

for i in range(10):
    print('Привет Мир!')
  File "", line 2
    print('Привет Мир!')
        ^
IndentationError: expected an indented block

Исключения

Даже если синтаксис в инструкции или само выражение верны, они все равно могут вызывать ошибки при исполнении. Исключения Python — это ошибки, обнаруживаемые при исполнении, но не являющиеся критическими. Скоро вы узнаете, как справляться с ними в программах Python. Объект исключения создается при вызове исключения Python. Если скрипт не обрабатывает исключение явно, программа будет остановлена принудительно.

Программы обычно не обрабатывают исключения, что приводит к подобным сообщениям об ошибке:

Ошибка типа (TypeError)

a = 2
b = 'PythonRu'
a + b
---------------------------------------------------------------------------

TypeError                                 Traceback (most recent call last)

 in 
      1 a = 2
      2 b = 'PythonRu'
----> 3 a + b


TypeError: unsupported operand type(s) for +: 'int' and 'str'

Ошибка деления на ноль (ZeroDivisionError)

10 / 0
---------------------------------------------------------------------------

ZeroDivisionError                         Traceback (most recent call last)

 in 
----> 1 10 / 0


ZeroDivisionError: division by zero

Есть разные типы исключений в Python и их тип выводится в сообщении: вверху примеры TypeError и ZeroDivisionError. Обе строки в сообщениях об ошибке представляют собой имена встроенных исключений Python.

Оставшаяся часть строки с ошибкой предлагает подробности о причине ошибки на основе ее типа.

Теперь рассмотрим встроенные исключения Python.

Встроенные исключения

BaseException
 +-- SystemExit
 +-- KeyboardInterrupt
 +-- GeneratorExit
 +-- Exception
      +-- StopIteration
      +-- StopAsyncIteration
      +-- ArithmeticError
      |    +-- FloatingPointError
      |    +-- OverflowError
      |    +-- ZeroDivisionError
      +-- AssertionError
      +-- AttributeError
      +-- BufferError
      +-- EOFError
      +-- ImportError
      |    +-- ModuleNotFoundError
      +-- LookupError
      |    +-- IndexError
      |    +-- KeyError
      +-- MemoryError
      +-- NameError
      |    +-- UnboundLocalError
      +-- OSError
      |    +-- BlockingIOError
      |    +-- ChildProcessError
      |    +-- ConnectionError
      |    |    +-- BrokenPipeError
      |    |    +-- ConnectionAbortedError
      |    |    +-- ConnectionRefusedError
      |    |    +-- ConnectionResetError
      |    +-- FileExistsError
      |    +-- FileNotFoundError
      |    +-- InterruptedError
      |    +-- IsADirectoryError
      |    +-- NotADirectoryError
      |    +-- PermissionError
      |    +-- ProcessLookupError
      |    +-- TimeoutError
      +-- ReferenceError
      +-- RuntimeError
      |    +-- NotImplementedError
      |    +-- RecursionError
      +-- SyntaxError
      |    +-- IndentationError
      |         +-- TabError
      +-- SystemError
      +-- TypeError
      +-- ValueError
      |    +-- UnicodeError
      |         +-- UnicodeDecodeError
      |         +-- UnicodeEncodeError
      |         +-- UnicodeTranslateError
      +-- Warning
           +-- DeprecationWarning
           +-- PendingDeprecationWarning
           +-- RuntimeWarning
           +-- SyntaxWarning
           +-- UserWarning
           +-- FutureWarning
           +-- ImportWarning
           +-- UnicodeWarning
           +-- BytesWarning
           +-- ResourceWarning

Прежде чем переходить к разбору встроенных исключений быстро вспомним 4 основных компонента обработки исключения, как показано на этой схеме.

  • Try: он запускает блок кода, в котором ожидается ошибка.
  • Except: здесь определяется тип исключения, который ожидается в блоке try (встроенный или созданный).
  • Else: если исключений нет, тогда исполняется этот блок (его можно воспринимать как средство для запуска кода в том случае, если ожидается, что часть кода приведет к исключению).
  • Finally: вне зависимости от того, будет ли исключение или нет, этот блок кода исполняется всегда.

В следующем разделе руководства больше узнаете об общих типах исключений и научитесь обрабатывать их с помощью инструмента обработки исключения.

Ошибка прерывания с клавиатуры (KeyboardInterrupt)

Исключение KeyboardInterrupt вызывается при попытке остановить программу с помощью сочетания Ctrl + C или Ctrl + Z в командной строке или ядре в Jupyter Notebook. Иногда это происходит неумышленно и подобная обработка поможет избежать подобных ситуаций.

В примере ниже если запустить ячейку и прервать ядро, программа вызовет исключение KeyboardInterrupt. Теперь обработаем исключение KeyboardInterrupt.

try:
    inp = input()
    print('Нажмите Ctrl+C и прервите Kernel:')
except KeyboardInterrupt:
    print('Исключение KeyboardInterrupt')
else:
    print('Исключений не произошло')

Исключение KeyboardInterrupt

Стандартные ошибки (StandardError)

Рассмотрим некоторые базовые ошибки в программировании.

Арифметические ошибки (ArithmeticError)

  • Ошибка деления на ноль (Zero Division);
  • Ошибка переполнения (OverFlow);
  • Ошибка плавающей точки (Floating Point);

Все перечисленные выше исключения относятся к классу Arithmetic и вызываются при ошибках в арифметических операциях.

Деление на ноль (ZeroDivisionError)

Когда делитель (второй аргумент операции деления) или знаменатель равны нулю, тогда результатом будет ошибка деления на ноль.

try:  
    a = 100 / 0
    print(a)
except ZeroDivisionError:  
    print("Исключение ZeroDivisionError." )
else:  
    print("Успех, нет ошибок!")
Исключение ZeroDivisionError.

Переполнение (OverflowError)

Ошибка переполнение вызывается, когда результат операции выходил за пределы диапазона. Она характерна для целых чисел вне диапазона.

try:  
    import math
    print(math.exp(1000))
except OverflowError:  
    print("Исключение OverFlow.")
else:  
    print("Успех, нет ошибок!")
Исключение OverFlow.

Ошибка утверждения (AssertionError)

Когда инструкция утверждения не верна, вызывается ошибка утверждения.

Рассмотрим пример. Предположим, есть две переменные: a и b. Их нужно сравнить. Чтобы проверить, равны ли они, необходимо использовать ключевое слово assert, что приведет к вызову исключения Assertion в том случае, если выражение будет ложным.

try:  
    a = 100
    b = "PythonRu"
    assert a == b
except AssertionError:  
    print("Исключение AssertionError.")
else:  
    print("Успех, нет ошибок!")

Исключение AssertionError.

Ошибка атрибута (AttributeError)

При попытке сослаться на несуществующий атрибут программа вернет ошибку атрибута. В следующем примере можно увидеть, что у объекта класса Attributes нет атрибута с именем attribute.

class Attributes(obj):
    a = 2
    print(a)

try:
    obj = Attributes()
    print(obj.attribute)
except AttributeError:
    print("Исключение AttributeError.")

2
Исключение AttributeError.

Ошибка импорта (ModuleNotFoundError)

Ошибка импорта вызывается при попытке импортировать несуществующий (или неспособный загрузиться) модуль в стандартном пути или даже при допущенной ошибке в имени.

import nibabel
---------------------------------------------------------------------------

ModuleNotFoundError                       Traceback (most recent call last)

 in 
----> 1 import nibabel


ModuleNotFoundError: No module named 'nibabel'

Ошибка поиска (LookupError)

LockupError выступает базовым классом для исключений, которые происходят, когда key или index используются для связывания или последовательность списка/словаря неверна или не существует.

Здесь есть два вида исключений:

  • Ошибка индекса (IndexError);
  • Ошибка ключа (KeyError);

Ошибка ключа

Если ключа, к которому нужно получить доступ, не оказывается в словаре, вызывается исключение KeyError.

try:  
    a = {1:'a', 2:'b', 3:'c'}  
    print(a[4])  
except LookupError:  
    print("Исключение KeyError.")
else:  
    print("Успех, нет ошибок!")

Исключение KeyError.

Ошибка индекса

Если пытаться получить доступ к индексу (последовательности) списка, которого не существует в этом списке или находится вне его диапазона, будет вызвана ошибка индекса (IndexError: list index out of range python).

try:
    a = ['a', 'b', 'c']  
    print(a[4])  
except LookupError:  
    print("Исключение IndexError, индекс списка вне диапазона.")
else:  
    print("Успех, нет ошибок!")
Исключение IndexError, индекс списка вне диапазона.

Ошибка памяти (MemoryError)

Как уже упоминалось, ошибка памяти вызывается, когда операции не хватает памяти для выполнения.

Ошибка имени (NameError)

Ошибка имени возникает, когда локальное или глобальное имя не находится.

В следующем примере переменная ans не определена. Результатом будет ошибка NameError.

try:
    print(ans)
except NameError:  
    print("NameError: переменная 'ans' не определена")
else:  
    print("Успех, нет ошибок!")
NameError: переменная 'ans' не определена

Ошибка выполнения (Runtime Error)

Ошибка «NotImplementedError»
Ошибка выполнения служит базовым классом для ошибки NotImplemented. Абстрактные методы определенного пользователем класса вызывают это исключение, когда производные методы перезаписывают оригинальный.

class BaseClass(object):
    """Опередляем класс"""
    def __init__(self):
        super(BaseClass, self).__init__()
    def do_something(self):
	# функция ничего не делает
        raise NotImplementedError(self.__class__.__name__ + '.do_something')

class SubClass(BaseClass):
    """Реализует функцию"""
    def do_something(self):
        # действительно что-то делает
        print(self.__class__.__name__ + ' что-то делает!')

SubClass().do_something()
BaseClass().do_something()

SubClass что-то делает!



---------------------------------------------------------------------------

NotImplementedError                       Traceback (most recent call last)

 in 
     14
     15 SubClass().do_something()
---> 16 BaseClass().do_something()


 in do_something(self)
      5     def do_something(self):
      6         # функция ничего не делает
----> 7         raise NotImplementedError(self.__class__.__name__ + '.do_something')
      8
      9 class SubClass(BaseClass):


NotImplementedError: BaseClass.do_something

Ошибка типа (TypeError)

Ошибка типа вызывается при попытке объединить два несовместимых операнда или объекта.

В примере ниже целое число пытаются добавить к строке, что приводит к ошибке типа.

try:
    a = 5
    b = "PythonRu"
    c = a + b
except TypeError:
    print('Исключение TypeError')
else:
    print('Успех, нет ошибок!')

Исключение TypeError

Ошибка значения (ValueError)

Ошибка значения вызывается, когда встроенная операция или функция получают аргумент с корректным типом, но недопустимым значением.

В этом примере встроенная операция float получат аргумент, представляющий собой последовательность символов (значение), что является недопустимым значением для типа: число с плавающей точкой.

try:
    print(float('PythonRu'))
except ValueError:
    print('ValueError: не удалось преобразовать строку в float: 'PythonRu'')
else:
    print('Успех, нет ошибок!')
ValueError: не удалось преобразовать строку в float: 'PythonRu'

Пользовательские исключения в Python

В Python есть много встроенных исключений для использования в программе. Но иногда нужно создавать собственные со своими сообщениями для конкретных целей.

Это можно сделать, создав новый класс, который будет наследовать из класса Exception в Python.

class UnAcceptedValueError(Exception):   
    def __init__(self, data):    
        self.data = data
    def __str__(self):
        return repr(self.data)

Total_Marks = int(input("Введите общее количество баллов: "))
try:
    Num_of_Sections = int(input("Введите количество разделов: "))
    if(Num_of_Sections < 1):
        raise UnAcceptedValueError("Количество секций не может быть меньше 1")
except UnAcceptedValueError as e:
    print("Полученная ошибка:", e.data)

Введите общее количество баллов: 10
Введите количество разделов: 0
Полученная ошибка: Количество секций не может быть меньше 1

В предыдущем примере если ввести что-либо меньше 1, будет вызвано исключение. Многие стандартные исключения имеют собственные исключения, которые вызываются при возникновении проблем в работе их функций.

Недостатки обработки исключений в Python

У использования исключений есть свои побочные эффекты, как, например, то, что программы с блоками try-except работают медленнее, а количество кода возрастает.

Дальше пример, где модуль Python timeit используется для проверки времени исполнения 2 разных инструкций. В stmt1 для обработки ZeroDivisionError используется try-except, а в stmt2if. Затем они выполняются 10000 раз с переменной a=0. Суть в том, чтобы показать разницу во времени исполнения инструкций. Так, stmt1 с обработкой исключений занимает больше времени чем stmt2, который просто проверяет значение и не делает ничего, если условие не выполнено.

Поэтому стоит ограничить использование обработки исключений в Python и применять его в редких случаях. Например, когда вы не уверены, что будет вводом: целое или число с плавающей точкой, или не уверены, существует ли файл, который нужно открыть.

import timeit
setup="a=0"
stmt1 = '''
try:
    b=10/a
except ZeroDivisionError:
    pass'''

stmt2 = '''
if a!=0:
    b=10/a'''

print("time=",timeit.timeit(stmt1,setup,number=10000))
print("time=",timeit.timeit(stmt2,setup,number=10000))

time= 0.003897680000136461
time= 0.0002797570000439009

Выводы!

Как вы могли увидеть, обработка исключений помогает прервать типичный поток программы с помощью специального механизма, который делает код более отказоустойчивым.

Обработка исключений — один из основных факторов, который делает код готовым к развертыванию. Это простая концепция, построенная всего на 4 блоках: try выискивает исключения, а except их обрабатывает.

Очень важно поупражняться в их использовании, чтобы сделать свой код более отказоустойчивым.

No matter your skill as a programmer, you will eventually make a coding mistake.
Such mistakes come in three basic flavors:

  • Syntax errors: Errors where the code is not valid Python (generally easy to fix)
  • Runtime errors: Errors where syntactically valid code fails to execute, perhaps due to invalid user input (sometimes easy to fix)
  • Semantic errors: Errors in logic: code executes without a problem, but the result is not what you expect (often very difficult to track-down and fix)

Here we’re going to focus on how to deal cleanly with runtime errors.
As we’ll see, Python handles runtime errors via its exception handling framework.

Runtime Errors¶

If you’ve done any coding in Python, you’ve likely come across runtime errors.
They can happen in a lot of ways.

For example, if you try to reference an undefined variable:

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-3-e796bdcf24ff> in <module>()
----> 1 print(Q)

NameError: name 'Q' is not defined

Or if you try an operation that’s not defined:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-4-aab9e8ede4f7> in <module>()
----> 1 1 + 'abc'

TypeError: unsupported operand type(s) for +: 'int' and 'str'

Or you might be trying to compute a mathematically ill-defined result:

---------------------------------------------------------------------------
ZeroDivisionError                         Traceback (most recent call last)
<ipython-input-5-ae0c5d243292> in <module>()
----> 1 2 / 0

ZeroDivisionError: division by zero

Or maybe you’re trying to access a sequence element that doesn’t exist:

---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-6-06b6eb1b8957> in <module>()
      1 L = [1, 2, 3]
----> 2 L[1000]

IndexError: list index out of range

Note that in each case, Python is kind enough to not simply indicate that an error happened, but to spit out a meaningful exception that includes information about what exactly went wrong, along with the exact line of code where the error happened.
Having access to meaningful errors like this is immensely useful when trying to trace the root of problems in your code.

Catching Exceptions: try and except

The main tool Python gives you for handling runtime exceptions is the tryexcept clause.
Its basic structure is this:

In [7]:

try:
    print("this gets executed first")
except:
    print("this gets executed only if there is an error")

Note that the second block here did not get executed: this is because the first block did not return an error.
Let’s put a problematic statement in the try block and see what happens:

In [8]:

try:
    print("let's try something:")
    x = 1 / 0 # ZeroDivisionError
except:
    print("something bad happened!")
let's try something:
something bad happened!

Here we see that when the error was raised in the try statement (in this case, a ZeroDivisionError), the error was caught, and the except statement was executed.

One way this is often used is to check user input within a function or another piece of code.
For example, we might wish to have a function that catches zero-division and returns some other value, perhaps a suitably large number like $10^{100}$:

In [9]:

def safe_divide(a, b):
    try:
        return a / b
    except:
        return 1E100

There is a subtle problem with this code, though: what happens when another type of exception comes up? For example, this is probably not what we intended:

Dividing an integer and a string raises a TypeError, which our over-zealous code caught and assumed was a ZeroDivisionError!
For this reason, it’s nearly always a better idea to catch exceptions explicitly:

In [13]:

def safe_divide(a, b):
    try:
        return a / b
    except ZeroDivisionError:
        return 1E100
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-15-2331af6a0acf> in <module>()
----> 1 safe_divide(1, '2')

<ipython-input-13-10b5f0163af8> in safe_divide(a, b)
      1 def safe_divide(a, b):
      2     try:
----> 3         return a / b
      4     except ZeroDivisionError:
      5         return 1E100

TypeError: unsupported operand type(s) for /: 'int' and 'str'

We’re now catching zero-division errors only, and letting all other errors pass through un-modified.

Raising Exceptions: raise

We’ve seen how valuable it is to have informative exceptions when using parts of the Python language.
It’s equally valuable to make use of informative exceptions within the code you write, so that users of your code (foremost yourself!) can figure out what caused their errors.

The way you raise your own exceptions is with the raise statement. For example:

In [16]:

raise RuntimeError("my error message")
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-16-c6a4c1ed2f34> in <module>()
----> 1 raise RuntimeError("my error message")

RuntimeError: my error message

As an example of where this might be useful, let’s return to our fibonacci function that we defined previously:

In [17]:

def fibonacci(N):
    L = []
    a, b = 0, 1
    while len(L) < N:
        a, b = b, a + b
        L.append(a)
    return L

One potential problem here is that the input value could be negative.
This will not currently cause any error in our function, but we might want to let the user know that a negative N is not supported.
Errors stemming from invalid parameter values, by convention, lead to a ValueError being raised:

In [18]:

def fibonacci(N):
    if N < 0:
        raise ValueError("N must be non-negative")
    L = []
    a, b = 0, 1
    while len(L) < N:
        a, b = b, a + b
        L.append(a)
    return L

Out[19]:

[1, 1, 2, 3, 5, 8, 13, 21, 34, 55]
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-20-3d291499cfa7> in <module>()
----> 1 fibonacci(-10)

<ipython-input-18-01d0cf168d63> in fibonacci(N)
      1 def fibonacci(N):
      2     if N < 0:
----> 3         raise ValueError("N must be non-negative")
      4     L = []
      5     a, b = 0, 1

ValueError: N must be non-negative

Now the user knows exactly why the input is invalid, and could even use a tryexcept block to handle it!

In [21]:

N = -10
try:
    print("trying this...")
    print(fibonacci(N))
except ValueError:
    print("Bad value: need to do something else")
trying this...
Bad value: need to do something else

Diving Deeper into Exceptions¶

Briefly, I want to mention here some other concepts you might run into.
I’ll not go into detail on these concepts and how and why to use them, but instead simply show you the syntax so you can explore more on your own.

Accessing the error message¶

Sometimes in a tryexcept statement, you would like to be able to work with the error message itself.
This can be done with the as keyword:

In [22]:

try:
    x = 1 / 0
except ZeroDivisionError as err:
    print("Error class is:  ", type(err))
    print("Error message is:", err)
Error class is:   <class 'ZeroDivisionError'>
Error message is: division by zero

With this pattern, you can further customize the exception handling of your function.

Defining custom exceptions¶

In addition to built-in exceptions, it is possible to define custom exceptions through class inheritance.
For instance, if you want a special kind of ValueError, you can do this:

In [23]:

class MySpecialError(ValueError):
    pass

raise MySpecialError("here's the message")
---------------------------------------------------------------------------
MySpecialError                            Traceback (most recent call last)
<ipython-input-23-92c36e04a9d0> in <module>()
      2     pass
      3 
----> 4 raise MySpecialError("here's the message")

MySpecialError: here's the message

This would allow you to use a tryexcept block that only catches this type of error:

In [24]:

try:
    print("do something")
    raise MySpecialError("[informative error message here]")
except MySpecialError:
    print("do something else")
do something
do something else

You might find this useful as you develop more customized code.

tryexceptelsefinally

In addition to try and except, you can use the else and finally keywords to further tune your code’s handling of exceptions.
The basic structure is this:

In [25]:

try:
    print("try something here")
except:
    print("this happens only if it fails")
else:
    print("this happens only if it succeeds")
finally:
    print("this happens no matter what")
try something here
this happens only if it succeeds
this happens no matter what

The utility of else here is clear, but what’s the point of finally?
Well, the finally clause really is executed no matter what: I usually see it used to do some sort of cleanup after an operation completes.

  1. Home
  2. Python Tutorial
  3. Exception Handling in Python

Last updated on September 22, 2020


Exception handling is a mechanism which allows us to handle errors gracefully while the program is running instead of abruptly ending the program execution.

Runtime Errors #

Runtime errors are the errors which happens while the program is running. Note is that runtime errors do not indicate there is a problem in the structure (or syntax) of the program. When runtime errors occurs Python interpreter perfectly understands your statement but it just can’t execute it. However, Syntax Errors occurs due to incorrect structure of the program. Both type of errors halts the execution of the program as soon as they are encountered and displays an error message (or traceback) explaining the probable cause of the problem.

The following are some examples of runtime errors.

Example 1: Division by a zero.

>>>
>>> 2/0
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ZeroDivisionError: division by zero
>>>

Try it now

Example 2: Adding string to an integer.

>>>
>>> 10 + "12"
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: unsupported operand type(s) for +: 'int' and 'str'
>>>

Try it now

Example 3: Trying to access element at invalid index.

>>>
>>> list1 = [11, 3, 99, 15]
>>>
>>> list1[10]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
IndexError: list index out of range
>>>

Try it now

Example 4: Opening a file in read mode which doesn’t exist.

>>>
>>> f = open("filedoesntexists.txt", "r")
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
FileNotFoundError: [Errno 2] No such file or directory: 'filedoesntexists.txt'
>>>
>>>

Try it now

Again note that all the above statements are syntactically valid, the only problem is that when Python tries to execute them, they got into an invalid state.

An error which occur while the program is running is known as an exception. When this happens, we say Python has raised an exception or an exception is thrown. Whenever such errors happen, Python creates a special type of object which contains all the relevant information about the error just occurred. For example, it contains a line number at which the error occurred, error messages (remember it is called traceback) and so on. By default, these errors simply halts the execution of the program. Exception handling mechanism allows us to deal with such errors gracefully without halting the program.

try-except statement #

In Python, we use try-except statement for exception handling. Its syntax is as follows:

try:
    # try block
    # write code that might raise an exception here
    <statement_1>
    <statement_2>
except ExceptiomType:
    # except block
    # handle exception here
    <handler>

The code begins with the word try, which is a reserved keyword, followed by a colon (:). In the next line we have try block. The try block contains code that might raise an exception. After that, we have an except clause that starts with the word except, which is again a reserved keyword, followed by an exception type and a colon (:). In the next line, we have an except block. The except block contains code to handle the exception. As usual, code inside the try and except block must be properly indented, otherwise, you will get an error.

Here is how the try-except statement executes:

When an exception occurs in the try block, the execution of the rest of the statements in the try block is skipped. If the exception raised matches the exception type in the except clause, the corresponding handler is executed.

If the exception raised in the try block doesn’t matches with the exception type specified in the except clause the program halts with a traceback.

On the other hand, If no exception is raised in the try block, the except clause is skipped.

Let’s take an example:

python101/Chapter-19/exception_handling.py

try:
    num =  int(input("Enter a number: "))
    result = 10/num
    print("Result: ", result)    

except ZeroDivisionError:
    print("Exception Handler for ZeroDivisionError")
    print("We cant divide a number by 0")

Try it now

Run the program and enter 0.

First run output:

Enter a number: 0
Exception Handler for ZeroDivisionError
We cant divide a number by 0

In this example, the try block in line 3 raises a ZeroDivisionError. When an exception occurs Python looks for the except clause with the matching exception type. In this case, it finds one and runs the exception handler code in that block. Notice that because an exception is raised in line 3, the execution of reset of the statements in the try block is skipped.

Run the program again but this time enter a string instead of a number:

Second run output:

Enter a number: str
Traceback (most recent call last):
  File "exception_example.py", line 2, in <module>
    num = int(input("Enter a number: "))
ValueError: invalid literal for int() with base 10: 'str'

This time our program crashes with the ValueError exception. The problem is that the built-in int() only works with strings that contain numbers only, if you pass a string containing non-numeric character it will throw a ValueError exception.

>>>
>>> int("123")              // that's fine because string only contains numbers
123
>>>
>>> int("str")              // error can't converts characters to numbers
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: invalid literal for int() with base 10: 'str'
>>>

As we have don’t have an except clause with the ValueError exception, our program crashes with ValueError exception.

Run the program again and this time enter an integer other than 0.

Third run output:

Enter a number: 4
Result:  2.5

Try it now

In this case, statements in the try block executes without throwing any exception, as a result, the except clause is skipped.

Handling Multiple Exceptions #

We can add as many except clause as we want to handle different types of exceptions. The general format of such a try-except statement is as follows:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
try:
    # try block
    # write code that might raise an exception here
    <statement_1>
    <statement_2>
except <ExceptiomType1>:
    # except block
    # handle ExceptiomType1 here
    <handler>
except <ExceptiomType2>:
    # except block
    # handle ExceptiomType2 here
    <handler>
except <ExceptiomType2>:
    # except block
    # handle ExceptiomType3 here
    <handler>
except:
    # handle any type of exception here
    <handler>

Here is how it works:

When an exception occurs, Python matches the exception raised against every except clause sequentially. If a match is found then the handler in the corresponding except clause is executed and rest of the except clauses are skipped.

In case the exception raised doesn’t matches any except clause before the last except clause (line 18), then the handler in the last except clause is executed. Note that the last except clause doesn’t have any exception type in front of it, as a result, it can catch any type of exception. Of course, this last except clause is entirely optional but we commonly use it as a last resort to catch the unexpected errors and thus prevent the program from crashing.

The following program demonstrates how to use multiple except clauses.

python101/Chapter-19/handling_muliple_types_of_exceptions.py

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
try:
    num1 = int(input("Enter a num1: "))
    num2 = int(input("Enter a num2: "))

    result = num1 / num2
    print("Result: ", result)

except ZeroDivisionError:
    print("nException Handler for ZeroDivisionError")
    print("We cant divide a number by 0")

except ValueError:
    print("nException Handler for ValueError")
    print("Invalid input: Only integers are allowed")

except:
    print("nSome unexpected error occurred")

Try it now

First run output:

Enter a num1: 10
Enter a num2: 0

Exception Handler for ZeroDivisionError
We cant divide a number by 0

Second run output:

Enter a num1: 100
Enter a num2: a13

Exception Handler for ValueError
Invalid input: Only integers are allowed

Third run output:

Enter a num1: 5000
Enter a num2: 2
Result:  2500

Here is another example program that asks the user to enter the filename and then prints the content of the file to the console.

python101/Chapter-19/exception_handling_while_reading_file.py

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
filename = input("Enter file name: ")

try:
    f = open(filename, "r")

    for line in f:
        print(line, end="")

    f.close()

except FileNotFoundError:
    print("File not found")

except PermissionError:
    print("You don't have the permission to read the file")

except:
    print("Unexpected error while reading the file")

Try it now

Run the program and specify a file that doesn’t exist.

First run output:

Enter file name: file_doesnt_exists.md
File not found

Run the program again and this time specify a file that you don’t have permission to read.

Second run output:

Enter file name: /etc/passwd
You don't have the permission to read the file

Run the program once more but this time specify a file that does exist and you have the permission to read it.

Third run output:

Enter file name: ../Chapter-18/readme.md
First Line
Second Line
Third Line
Fourth Line
Fifth Line

The else and finally clause #

A try-except statement can also have an optional else clause which only gets executed when no exception is raised. The general format of try-except statement with else clause is as follows:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
try:    
    <statement_1>
    <statement_2>
except <ExceptiomType1>:    
    <handler>
except <ExceptiomType2>:    
    <handler>
else:
    # else block only gets executed
    # when no exception is raised in the try block
    <statement>
    <statement>

Here is a rewrite of the above program using the else clause.

python101/Chapter-19/else_clause_demo.py

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
import os
filename = input("Enter file name: ")

try:
    f = open(filename, "r")

    for line in f:
        print(line, end="")

    f.close()

except FileNotFoundError:
    print("File not found")

except PermissionError:
    print("You don't have the permission to read the file")

except FileExistsError:
    print("You don't have the permission to read the file")

except:
    print("Unexpected error while reading the file")

else:
    print("Program ran without any problem")

Try it now

Run the program and enter a file that doesn’t exist.

First run output:

Enter file name: terraform.txt
File not found

Again run the program but this time enter a file that does exist and you have the permission to access it.

Second run output:

Enter file name: ../Chapter-18/readme.md
First Line
Second Line
Third Line
Fourth Line
Fifth Line
Program ran without any problem

As expected, the statement in the else clause is executed this time. The else clause is usually used to write code which we want to run after the code in the try block ran successfully.

Similarly, we can have a finally clause after all except clauses. The statements under the finally clause will always execute irrespective of whether the exception is raised or not. It’s general form is as follows:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
try:    
    <statement_1>
    <statement_2>
except <ExceptiomType1>:    
    <handler>
except <ExceptiomType2>:    
    <handler>
finally:
    # statements here will always
    # execute no matter what
    <statement>
    <statement>

The finally clause is commonly used to define clean up actions that must be performed under any circumstance. If the try-except statement has an else clause then the finally clause must appear after it.

The following program shows the finally clause in action.

python101/Chapter-19/finally_clause_demo.py

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
import os
filename = input("Enter file name: ")

try:
    f = open(filename, "r")

    for line in f:
        print(line, end="")

    f.close()

except FileNotFoundError:
    print("File not found")

except PermissionError:
    print("You don't have the permission to read the file")

except FileExistsError:
    print("You don't have the permission to read the file")

except:
    print("Unexpected error while reading the file")

else:
    print("nProgram ran without any problem")

finally:
    print("finally clause: This will always execute")

Try it now

First run output:

Enter file name: little.txt
File not found
finally clause: This will always execute

Second run output:

Enter file name: readme.md
First Line
Second Line
Third Line
Fourth Line
Fifth Line
Program ran without any problem
finally clause: This will always execute

Exceptions Propagation and Raising Exceptions #

In the earlier few sections, we have learned how to deal with exceptions using the try-except statement. In this section, we will discuss who throws an exception, how to create an exception and how they propagate.

An exception is simply an object raised by a function signaling that something unexpected has happened which the function itself can’t handle. A function raises exception by creating an exception object from an appropriate class and then throws the exception to the calling code using the raise keyword as follows:

raise SomeExceptionClas("Error message describing cause of the error")

We can raise exceptions from our own functions by creating an instance of RuntimeError() as follows:

raise RuntimeError("Someting went very wrong")

When an exception is raised inside a function and is not caught there, it is automatically propagated to the calling function (and any function up in the stack), until it is caught by try-except statement in some calling function. If the exception reaches the main module and still not handled, the program terminates with an error message.

Let’s take an example.

Suppose we are creating a function to calculate factorial of a number. As factorial is only valid for positive integers, passing data of any other type would render the function useless. We can prevent this by checking the type of argument and raising an exception if the argument is not a positive integer. Here is the complete code.

python101/Chapter-19/factorial.py

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
def factorial(n):
    if  not isinstance(n, int):
        raise RuntimeError("Argument must be int")

    if n < 0:
        raise RuntimeError("Argument must be >= 0")

    f = 1
    for i in range(n):
        f *= n
        n -= 1

    return f

try:
    print("Factorial of 4 is:", factorial(4))
    print("Factorial of 12 is:", factorial("12"))
except RuntimeError:
    print("Invalid Input")

Try it now

Output:

Factorial of 4 is: 24
Invalid Input

Notice that when the factorial() function is called with a string argument (line 17), a runtime exception is raised in line 3. As factorial() function is not handling the exception, the raised exception is propagated back to the main module where it is caught by the except clause in line 18.

Note that in the above example we have coded the try-except statement outside the factorial() function but we could have easily done the same inside the factorial() function as follows.

python101/Chapter-19/handling_exception_inside_factorial_func.py

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
def factorial(n):

    try:
        if not isinstance(n, int):
            raise RuntimeError("Argument must be int")

        if n < 0:
            raise RuntimeError("Argument must be >= 0")

        f = 1
        for i in range(n):
            f *= n
            n -= 1

        return f

    except RuntimeError:
        return  "Invalid Input"

print("Factorial of 4 is:", factorial(4))
print("Factorial of 12 is:", factorial("12"))

Try it now

Output:

Factorial of 4 is: 24
Factorial of 12 is: Invalid Input

However, this is not recommended. Generally, the called function throws an exception to the caller and it’s the duty of the calling code to handle the exception. This approach allows us to to handle exceptions in different ways, for example, in one case we show an error message to the user while in other we silently log the problem. If we were handling exceptions in the called function, then we would have to update the function every time a new behavior is required. In addition to that, all the functions in the Python standard library also conforms to this behavior. The library function only detects the problem and raises an exception and the client decide what it needs to be done to handle those errors.

Now Let’s see what happens when an exception is raised in a deeply nested function call. Recall that if an exception is raised inside the function and is not caught by the function itself, it is passed to its caller. This process repeats until it is caught by some calling function down in the stack. Consider the following example.

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
def function3():
    try:

        ...
        raise SomeException()
    statement7
    except ExceptionType4:
        handler
    statement8


def function2():
    try:
        ...
        function3()
        statement5
    except ExceptionType3:
        handler
    statement6

def function1():
    try:
        ...
        function2()
        statement3
    except ExceptionType2:
        handler
    statement4

def main():
    try:
        ...
        function1()
        statement1
    except ExceptionType1:
        handler
     statement2
    
main()

The program execution starts by calling the main() function. The main() function then invokes function1(), function1() invokes function2(), finally function2() invokes function3(). Let’s assume function3() can raise different types of exceptions. Now consider the following cases.

  1. If the exception is of type ExceptionType4, statement7 is skipped and the except clause in line 7 catches it. The execution of function3() proceeds as usual and statement8 is executed.

  2. If exception is of type ExceptionType3, the execution of function3() is aborted (as there is no matching except clause to handle the raised exception) and the control is transferred to the caller i.e function2() where ExceptionType3 is handled by the except clause in line 17. The statement5 in function2() is skipped and statement6 is executed.

  3. If the exception is of type ExceptionType2, function3() is aborted and the control is transferred to the function2(). As function2() doesn’t have any matching except clause to catch the exception, its execution is aborted and control transferred to the function1() where the exception is caught by the except clause in line 26. The statement3 in function1() is skipped and statement4 is executed.

  4. If the exception is of type ExceptionType1, then control is transferred to the function main() (as function3(), function2() and function1() doesn’t have matching except clause to handle the exception) where the exception is handled by except clause in line 35. The statement1 in main() is skipped and statement2 is executed.

  5. If the exception is of type ExceptionType0. As none of the available functions have the ability to handle this exception, the program terminates with an error message.

Accessing Exception Object #

Now we know how to handle exceptions as well throw them whenever needed. One thing we didn’t yet cover is how to access exception object thrown by the function. We can access exception object using the following form of except clause.

except ExceptionType as e

From now on, whenever except clause catches an exception of type ExceptionType it assigns the exception object to the variable e.

The following example demonstrates how to access an exception object:

python101/Chapter-19/accessing_exception_object.py

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
def factorial(n):
    if not isinstance(n, int):
        raise RuntimeError("Argument must be int")

    if n < 0:
        raise RuntimeError("Argument must be >= 0")

    f = 1
    for i in range(n):
        f *= n
        n -= 1

    return f


try:
    print("Factorial of 4 is:", factorial(4))
    print("Factorial of 12 is:", factorial("12"))

except RuntimeError as e:
    print("Error:", e)

Try it now

Output:

Factorial of 4 is: 24
Error: Argument must be int

Notice that the error message printed by exception object (line 21) is the same which we passed while creating creating RuntimeError object (line 3).

Creating Your Own Exceptions #

So far in this chapter we have been using built-it exception classes such as ZeroDivisionError, ValueError, TypeError, RuntimeError etc. Python also allows you to create new exception classes to cater you own specific needs. The BaseException class is the root of all exception classes in Python. The following figure shows exception class hierarchy in Python.

We can create our own exception class by deriving it from Exception built-in class. The following examples shows how to create a custom exception.

python101/Chapter-19/InvalidFactorialArgumentException.py

class InvalidFactorialArgumentException(Exception):
    def __init__(self, message):
        super().__init__()
        self.message = message

    def __str__(self):
        return self.message

python101/Chapter-19/factorialWithCustomException.py

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
from InvalidFactorialArgumentException import *

def factorial(n):
    if not isinstance(n, int):
        raise InvalidFactorialArgumentException("Argument must be int")

    if n < 0:
        raise InvalidFactorialArgumentException("Argument must be >= 0")

    f = 1
    for i in range(n):
        f *= n
        n -= 1

    return f


try:
    print("Factorial of 4 is:", factorial(4))
    print("Factorial of 12 is:", factorial("12"))

except InvalidFactorialArgumentException as e:
    print("Error:", e)

Try it now

Output:

Factorial of 4 is: 24
Error: Argument must be int


Ezoic

Table of content

  • Exception Handing in Python
  • Syntax Error in Python Exception Handling
  • Runtime Error in Python Exception Handling
  • Default Exception Handling in Python
  • Pythons Exception Hierarchy
  • Customized Exception Handling in python
  • Control Flow in Try-Except Block in Python’s Exception Handling
  • Try Block with Multiple Exception Block in python
  • Single Exception block that can handle multiple exceptions in python
  • Default Except Block in python
  • Finally, Block in python
  • OS.__exit(0) vs Finally Block in python
  • Control Flow in try-except-finally blocks
  • Nested try-except-finally Blocks
  • else Block with try-except-finally in python’s exception Handling
  • The Various Possible Combinations of try-except-else-finally Block
  • Types of Exceptions in python Exception Handling

Exception : An exception if an error occurs during the execution of the program, which disrupts the normal flow of the program’s instructions.

Example:
Internet Error
FileNotFound Error
Division Error
Value Error

Exception Handling: Exception handling does not mean that repairing an exception, we have to define an alternative way to continue the program normally. The method of defining an alternative way is nothing but an exception handling.

Example:

try:
    Read data from Remote file locating at Landon
    
except FileNotFoundError:
       use a local file and continue rest of the program normally    

The Main Objective of the Exception Handling:

  • It is highly recommended to perform exception handling.
  • The main objective is to terminate the program in a graceful way/ normal termination of the application so that we should not miss anything or should not block our resources.

There are two types of Exceptions that Occur during the Execution of the program

  • Syntax Error
  • Runtime Error

The Errors which occur due to invalid syntax in the program are called syntax Errors; the programmer is responsible for correcting those errors. Once all the syntax errors are corrected, then only the program execution will start.

Example:

value=10
##missed colon(:) in the below line 
if value==10
   print("Hello")

##The output is:
 File "C:UsersUserAnaconda3libsite-packagesspyder_kernelscustomizespydercustomize.py", line 110, in execfile
    exec(compile(f.read(), filename, 'exec'), namespace)

  File "C:/Users/User/.spyder-py3/temp.py", line 2
    if value==10
            ^
SyntaxError: invalid syntax

Mutability in Python

Runtime errors are also known as exceptions. While executing the program, at the runtime if something goes wrong because of end-user input or due to memory problem or programming logic, etc..then we will encounter runtime errors.

The Exception handling concept is applicable only for Runtime errors and not for Syntax errors.

Example:

Example 1:
print(10/0)
##The output is:
  File "C:/Users/User/.spyder-py3/temp.py", line 1, in <module>
    print(10/0)

ZeroDivisionError: division by zero

Example 2:
Info=int(input("Enter Number:"))
print(Info)
##The output is:
Enter Number:Ten
Traceback (most recent call last):

  File "<ipython-input-5-5ba32625e270>", line 1, in <module>
    runfile('C:/Users/User/.spyder-py3/temp.py', wdir='C:/Users/User/.spyder-py3')

  File "C:UsersUserAnaconda3libsite-packagesspyder_kernelscustomizespydercustomize.py", line 786, in runfile
    execfile(filename, namespace)

  File "C:UsersUserAnaconda3libsite-packagesspyder_kernelscustomizespydercustomize.py", line 110, in execfile
    exec(compile(f.read(), filename, 'exec'), namespace)

  File "C:/Users/User/.spyder-py3/temp.py", line 1, in <module>
    Info=int(input("Enter Number:"))

ValueError: invalid literal for int() with base 10: 'Ten'

Python Immutability

Every exception in python is an object, and for every exception type, the corresponding class is available.

Whenever an exception occurs, the python virtual machine will create the corresponding exception object and will check for the handling code, if the corresponding handling code is available, then the code will be run normally.

If the handling code is not available, then the python interpreter terminates the program abnormally and prints corresponding exception information to the console, and the rest of the program won’t be executed.

To prevent this abnormal termination, we should handle exceptions explicitly, of course, by using try-except blocks.

Every exception in python is class, all the exception classes are child classes of a base class exception either directly or indirectly, and hence BaseException acts as a root for python exception hierarchy.

Being a programmer most of the time, we need to concentrate/handle the exception and its child classes.

The Image of Pythons Exception Hierarchy

The main objective of exception handling is to perform graceful termination of an application, and hence it is highly recommended to handle exceptions.

The code which may raise an exception is called risky code, and we have to take that code inside the try block and the corresponding handling code we have to take inside the except block.

So if any exceptions arise inside the try block immediately, the exception block will execute, and the alternative code will execute, and the program terminates normally.

The syntax for the customized exception handling is:

try:
 Risky Code
except YYY:
 Handling code/Alternative Code

Example: Without Try Except Block

In the below code, the exception is raised in the second statement, and hence there is no except block which provides the alternate code to terminate the program normally, then python will throw a ZeroDivisionError, and the program is terminated abnormally.

print("statement-1")
print(10/0)
print("statement-3")
##The output is:

  File "C:/Users/User/.spyder-py3/temp.py", line 2, in <module>
    print(10/0)

ZeroDivisionError: division by zero

Example: With Try-Except Block

In the below program an except block is present and hence, once the error occurs at the second statement, then the control will automatically go to except block which executes the alternate code, and the program will terminate normally by executing the third statement/ rest of the program.

print("statement-1")
try:
    print(10/0)
except ZeroDivisionError:
    print(10/2)
print("statement-3")

The output is:
running-program-with-try-except-block

None Datatype

Within the try block if anywhere an exception raised then the rest of the try block won’t be executed even though if we handled that exception, hence inside the try block we have to take only risky code and the length of the try block should be as less as possible.

try:
    print("statement-1")
    print(10/0)
    print("Statement-3")
    
except ZeroDivisionError:
    print("Statement-4")
print("statement-5")    

The output is: Even After providing the except block, the third statement in the try block won’t be executed.
python-flow-control-case-one

In addition to the try block, there may be a chance of raising exceptions inside the except and finally blocks also.

In any statement which is not a part of the try block and raising an exception, then it is always an abnormal termination.

How to print Exception Information to the Console

If you want to print the exception information inside the except blocks, like Name of the exception, Type of the exception or Description of the exception then you can enter the information before the handling code.

An Exception object got created with a reference variable, and the reference variable can be anything.

The syntax to print Exception Information to the console is:

try:
    print("statement-1")
    print("statement-2")  #Risky Code
except NameOfTheError as ReferenceVariable: #as is the keyword we have to use compulsory
    print("Statement-3")
print("statement-4")    

Example:

try:
    print(10/0)
except ZeroDivisionError as msg:
    print("Exception Type:", type(msg))

The output is:
printing-exception-information-into-console

We can print the type of the exception by using the corresponding class object as follow:

try:
    print(10/0)
except ZeroDivisionError as msg:
    print("Exception Type:", type(msg))
    print("Exception Type:",msg.__class__) ##printing the corresponding class object

The output is:
printing-the-corresponding-class-object

If you want to print only the exception class Name then:

try:
    print(10/0)
except ZeroDivisionError as msg:
    print("Exception Type:", type(msg))
    print("Exception Type:",msg.__class__)
##Printing exception class name
    print("Exception Type:", msg.__class__.__name__) 

The output is:
printing-exception-class-name

If you want to print the description of the exception, then :

try:
    print(10/0)
except ZeroDivisionError as msg:
##Printing the description of exception
    print("Description of Exception:", msg)

The output is:
printing-the-description-of-exception

The following example demonstrates handling both parent class exception and child class exceptions by using BaseException as the class object.

try:
    first_value=int(input("Enter First Number:"))
    second_value=int(input("Enter Second Number:"))
    print("The Result:",first_value/second_value)
except BaseException as result:
    print("Exception Type:", type(result))
    print("Exception Type:", type.__class__)
    print("Exception Class Name:", result.__class__.__name__)
    print("Description of Exception:", result)    

The output of the parent class:
output-of-parent-class

The output of handling child class exception:
handling-child-class-exception

Python List Datatypes

The Way of Handling an Exception is varied from exception to exception, hence for every possible exception type, We have to take separate except block. The exception block will execute until to get the matched exception block.

Try block with multiple exceptions is possible and recommended to use.

The syntax is:

try:
   print("statement-1")
except NameOfError:
  perform alternative operation
except NameOfError:
  use local file instead of remote file

If the try block with multiple blocks is available, based on the available exception the corresponding except block will be executed.

The following example will demonstrate the try block with multiple except block

try:
    value_one=int(input("Enter First Number:"))
    value_second=int(input("Enter Second Number:"))
    print("The Result:",value_one/value_second)
except ZeroDivisionError:
    print("Cannot Divide with Zero")
except ValueError:
    print("Please Provide int values only")    

The output is: When we give 10 as the first value and second value as 5
first-output-of-multiple-except-bloack

The output, when we give the first value as 10 and second value as 0
second-output-multiple-exception

The output, when we provide the first value as 10 and second value as Two
third-output-of-multiple-exception

If try block with multiple except blocks is available, then the order of these except block is important, and the python virtual machine will always consider from top to bottom until the matched except block is available.

The following example demonstrates how the except block will execute from top to bottom

try:
    print(20/0)
except ZeroDivisionError:    
    print("ZeroDivisionError")
except ArithmeticError:
    print("ArithmeticError")
    

The output is:
zero-division-error

The same code, if write the arithmetic error first and next to zero division error then, the arithmetic error exception will execute because the zero division error is the child class of arithmetic error.

try:
    print(20/0)
except ArithmeticError:
    print("ArithmeticError")
except ZeroDivisionError:    
    print("ZeroDivisionError")    
    

The output is:
arithmetic-error

Nested List in Python

If a handling code is the same for multiple exceptions then instead of taking different except blocks, we can take single except block that can handle all the exceptions.

Syntax is:

except(Exception1, Exception2,...):
except(Exception1, Exception2,...) as msg:

The parenthesis is mandatory and this group of exceptions internally considered as Tuple.

The following example demonstrates the single exception block handling multiple exceptions

try:
    value_one=int(input("Enter First Number:"))
    value_second=int(input("Enter Second Number:"))
    print("The Result:",value_one/value_second)
except (ZeroDivisionError, ValueError) as msg:
    print("The Raised Exception:", msg.__class__.__name__)
    print("Description of Exception:", msg)   
    print("Please provide valid inputs only...")

The output is: When the input is 10 and 5
single-exception-block-handling-mutliple-exception

The output is: When the input is 10 and 5, then the zerodivisionerror exception will execute
zero-division-error-occur-single-exception-block-handling-multiple-exception

The output is: When the input is 10 and Two, then the Valueerror exception will execute
valueerror-single-exception-block-handle-multiple-exception

Tuple Datatype

We can use default except block to handle any exceptions; In the default except block generally, we can print exception information to the console.

The syntax is:

except: 
          statements

The following example demonstrates the default except block

try:
    value_one=int(input("Enter First Number:"))
    value_second=int(input("Enter Second Number:"))
    print("The Result:",value_one/value_second)
except ZeroDivisionError:
    print("ZeroDivisionError:cannot divide wih zero")
except:
    print("Default Except:please provide valid input only")

The output is: The ZeroDivisionError block will execute when input is 30 and 0
default-exceptions-zerodivision-error

The output is: The Except block will execute when the zerodivisionerror does not match.
deafult-exception-except-block-execution

In the above code if we remove zerodivisionerror block also the except block can handle it

try:
    value_one=int(input("Enter First Number:"))
    value_second=int(input("Enter Second Number:"))
    print("The Result:",value_one/value_second)
except:
    print("Default Except:please provide valid input only")

The output is:
deafult-exception-execution

If default except block is defined then compulsory it must be a last except block; otherwise, we will get a syntax error.
This restriction is applicable only for Default except block and not for the normal Except blocks

Various possible combinations of except block

  • except ZeroDivisionError:
  • except (ZeroDivisionError):
  • except ZeroDivisionError as msg:
  • except (ZeroDivisionError) as msg
  • except (ZeroDivisionError, ValueError):
  • except (ZeroDivisionError, ValueError) as msg:
  • except:

If except block is defined for only one exception, then parenthesis is optional, and if except block is defined for more than one except block, then parenthesis is mandatory.

If we use parenthesis then as keyword must be outside the parenthesis.

Invalid Combinations of except Block

  • except (ZeroDivisionError as msg)
  • except ZeroDivisionError, ValueError:
  • except (ZeroDivisionError, ValueError as msg):

The finally keyword is used in a try…except blocks. It defines a block of code to run when the try…except…else block is final.

It is not recommended to place a cleanup code inside the try block because there is no guarantee for the execution of every statement inside the try block.

And also, it is not recommended to place a cleanup code inside the except block, because if there is no exception then except block won’t be executed.

We required someplace to define a cleanup code that executes irrespective of whether the exception raised or not raised and whether the exception is handled or not handled, the best place is nothing but a finally block.

The main purpose of the finally code is to maintain a cleanup code.

The Syntax is:

try:
    Risky code:
except:
       Handling code
finally:
      Cleanup code

Case 1: If No Exception

try:
    print("try")
except ZeroDivisionError:
    print("Except")
finally:
    print("finally")

If there is no exception then try and finally block will execute
if-there-is-no-exception-then-try-finally-blocks-will-execute

Case 2: If the exception raised and handled

try:
    print("try")
    print(10/0)
except ZeroDivisionError:
    print("Except")
finally:
    print("finally")

If an exception got raised and handled by exception block, then try, except and finally blocks got executed.
if-there-is-an-exception-then-try-except-finally-block-executes

Case 3:If exception raised but not handled

try:
    print("try")
    print(10/0)
except ValueError:
    print("Except")
finally:
    print("finally")

If the exception raised but not handled then first try and finally block will execute, and then zeroDivisionError will execute.
If-exception-raised-but-not-handled

There is only one situation where finally block won’t be executed, i.e., whenever we are using OS._exit(0).

Whenever we are using the OS_exit(0), then the python virtual machine itself will be shut down and in this particular case finally, the block won’t be executed.

OS._exit(0)

Here Zero represents the status Code.

Zero means normal termination.

Non-zero means abnormal termination

The python virtual machine internally uses this status code.

Whether it is zero or non zero, there is no difference in the result of the program.

The following example demonstrates the OS._exit(0)

import os
try:
    print("try")
    os._exit(0)
except ValueError:
    print("except")
finally:
    print("finally")

The output is:
try

Difference between Finally Block and Destructor

Finally Block Destructor
Finally block is meant for cleanup activities related to the try block, i.e., whatever the resources we opened as part of try block will be cleaned inside the finally block.

Destructor is meant for cleanup activities related to the object; whatever resources related to the object should be deallocated inside the destructor which will be executed before destroying the object.

The following cases demonstrate the control flow in try-except-finally blocks

Case 1: If there is no exception

try:
    print(statement-1)
    print(statement-2)
    print(statement-3)
except:
    print(statement-4)
finally:
    print(statement-5)
print(statement-6)   

If there is no exception occur, then, try block will execute and finally block will also execute, excluding the except and then the remaining code will execute normally.

The output will be : statement-1,2,3,5,6 and normal termination

Case 2: If an exception raised at the statement-2 and corresponding except block matched, then the control automatically goes to except block and then finally block will execute, also remaining blocks will execute normally.

The output will be: statement-1,4,5,6 and normal termination.

Case 3:If an exception raised at the statement-2 and the corresponding except block not matched; then the finally block will execute, and the abnormal termination will happen.

The output will be: statement-1, normal termination.

Case 4: If an exception raised at the statement-4 if an exception raised at the exception block, then finally block will execute and the abnormal termination will happen.

The output will be: statement-5 and abnormal termination.

Case 5:If an exception raised at statements 5 or 6 then it is always abnormal termination.

We can take try-except-finally blocks inside the try or except or finally. Hence nesting of try-except-finally blocks is possible.

The general risky code we have to take inside the outer try block and too much risky code we have to take inside the inner try block.

Inside the inner try block if an exception is raised, then the inner except block is responsible to handle it; if it is unable to handle, then the outer except block is responsible for handling it.

The following example demonstrates the nested try-except-finally block

try:
    print("outer try block")
    try:
        print("Inner try block")
    except ZeroDivisionError:
        print("Inner except block")
    finally:
        print("Inner finally block")
except:
    print("outer except block")
finally:
    print("outer finally block")        

There is no exception in the above program and hence the inner except and outer except block won’t be executed, except that all the blocks will execute.

The output is:
nested-try-except-finally-block

If an exception is raised in the inner try block and the inner except block will match then the inner exception block, and inner finally block will execute.

And the exception is handled by the inner exception itself, and hence the outer exception block won’t execute, but the outer finally block will execute.

try:
    print("outer try block")
    try:
        print("Inner try block")
        print(10/0)
    except ZeroDivisionError:
        print("Inner except block")
    finally:
        print("Inner finally block")
except:
    print("outer except block")
finally:
    print("outer finally block")     

The output is:
nested-try-except-finally-block-an-exception-is-raised-in-the-inner-try-block

In the below example, an exception is raised in the inner try block but the corresponding except block not matched, and hence the inner finally block will execute and then the outer except block will execute and then the outer finally block.

try:
    print("outer try block")
    try:
        print("Inner try block")
        print(10/0)
    except ValueError:
        print("Inner except block")
    finally:
        print("Inner finally block")
except:
    print("outer except block")
finally:
    print("outer finally block")   

The output is:
nested-try-except-block-exception-is-raised-in-the-innertryblock%20-but-the-corresponding-exceptblock-notmatched
If an exception is raised in the outer try block, then the corresponding except block will be outer except block, and hence the outer except block and the outer finally will be executed.

try:
    print("outer try block")
    print(10/0)
    try:
        print("Inner try block")
        
    except ValueError:
        print("Inner except block")
    finally:
        print("Inner finally block")
except:
    print("outer except block")
finally:
    print("outer finally block")   

The output is:
nested-try-except-finaly-if-an-exception-raised-in-the-outer-try-block

if-else==>if condition is false then only else will be executed
for-else==>If loop executed without a break, then only else block will execute.
while-else==>if loop executed without a break then only else will execute.

The following example demonstrates, if the condition is false, then only the else part will execute.

value=10
if value>10:
    print("value is greater than 10")
else:
    print("value is less than 10")

The output is:
else-block-execute-only-when-if-statement-fails

The following example demonstrates the loops with else block

for info in range(10):
    print("The Current Item:",info)
else:
    print("congratulations, all item processed successfully")

The output is:
loop-with-else

The following example demonstrates While executing a loop if the break statement is encountered, then the else part is not going to execute.

for info in range(10):
    if info>5:
        break
    print("The Current Item:",info)
else:
    print("congratulations, all item processed successfully")

The output is:
the-output-of-else-with-break-statement

If we use else block with try-except-finally, if there is no exception in a try block, then only the else block will execute

The Syntax is:

try:
    Risky code
except:
    Handling code
    will be executed if an exception inside try
else:
    will be executed if there is no exception inside try
finally:
    cleanup code
    will be executed whether exception raised or not raised and handled or not handled    

The following example demonstrates the; when there is no exception in the try block then else part will execute

try:
   print("try")
except:
       print("Except")
else:
     print("Else")
finally:
      print("Finally")

The output is:
else-block-execution-ehrn-there-is no-exception-in-the-try-block

The following example demonstrates the execution of else block with try-except-finally when an exception occurs in the try block then the else part will not execute.

try:
   print("try")
   print(10/0)
except:
       print("Except")
else:
     print("Else")
finally:
      print("Finally")

The output is:
else-block-with-try-except-finally

The following example demonstrates without except block the else part is not valid and the python will throw a syntax error

try:
   print("try")
else:
     print("Else")
finally:
      print("Finally")

The output is:
without-except-block-the-else-block-is-invalid

There is no chance of executing both except block and else simultaneously If we want to use the else block then compulsory the except block should be there

The following example demonstrates the else block with try-except-finally block

file=None
try:
    file=open("info.txt","r")
except:
    print("Some problem while locating and opening the file")
else:
     print("File opened successfully")
     print("The data present in the file is:")
     print("#",*30)
     print(file.read())
finally:
    if file is not None:
        file.close()

The output is: If the file is available in my system then

File opened successfully
The data present in the file is:
#############################
Line-1 of abc.txt file
Line-2 of abc.txt file
Line-3 of abc.txt file
Line-4 of abc.txt file
Line-5 of abc.txt file

The output is: If the file is not present in the system.
if-the-file-is-not-present-in-the-system

Whenever we are writing try block, compulsory we should write except or finally block, Because the try block without except or finally is invalid.

Whenever we are writing except block, compulsory try block should be there, because the except without try block is always invalid.

Whenever we are writing finally block compulsory try block should be there, because the finally block without try is always invalid.

Whenever we are writing else block compulsory except block should be there, because else without except is always invalid.

We can write multiple except blocks for the same try block with, but we cannot write various else block and finally block.

The try-except-else-finally order is important.

We can write try-except-else-finally block inside try-except-else-finally block

The following table explains the valid syntax for the try-except-else-finally block.

Syntax

Status

try:

print(«try»)

Invalid

except:

print(«Hello»)

Invalid

else:

print(«Hello»)

Invalid

finally:

print(«Hello»)

Invalid

try:

print(«try»)

except:

print(«except»)

Valid

try:

print(«try»)

finally:

print(«finally»)

Valid

try:

print(«try»)

except:

print(«except»)

else:

print(«else»)

Valid

try:

print(«try»)

else:

print(«else»)

Invalid

try:

print(«try»)

else:

print(«else»)

finally:

print(«finally»)

Invalid

try:

print(«try»)

except yyy:

print(«except-1»)

except yyyy:

print(«except-2»)

Valid

try:

print(«try»)

except:

print(«except-1»)

else:

print(«else»)

else:

print(«else»)

Invalid

try:

print(«try»)

except:

print(«except-1»)

finally:

print(«finally»)

finally:

print(«finally»)

Invalid

try:

print(«try»)

print(«Hello»)

except:

Invalid

try:

print(«try»)

except:

print(«except»)

print(«Hello»)

finally:

print(«finally»)

Invalid

try:

print(«try»)

except:

print(«except»)

print(«Hello»)

else: print(«else»)

Invalid

try:

print(«try»)

except:

print(«except»)

try:

print(«try»)

except:

print(«except»)

Valid

try:

print(«try»)

except:

print(«except»)

try:

print(«try»)

finally:

print(«finally»)

Valid

try:

print(«try»)

except:

print(«except»)

if 10>20

print(«if»)

else:

print(«esle»)

Valid

try:

print(«try»)

try:

print(«inner try»)

except:

print(«inner except block») finally:

print(«inner finally block») except:

print(«except»)

Valid

try:

print(«try»)

except:

print(«except»)

try:

print(«inner try»)

except:

print(«inner except block») finally:

print(«inner finally block»)

Valid

try:

print(«try»)

except:

print(«except»)

finally:

try:

print(«inner try»)

except:

print(«inner except block») finally:

print(«inner finally block»)

Valid

try:

print(«try»)

except:

print(«except»)

try:

print(«try»)

else:

print(«else»)

Invalid

try:

print(«try»)

try:

print(«inner try»)

except:

print(«except»)

Invalid

try:

print(«try»)

else:

print(«else»)

except:

print(«except»)

finally:

print(«finally»)

Invalid

There are two types of exceptions in python

  • Predefined Exceptions
  • User-Defined Exceptions

Predefined Exceptions:

The predefined exceptions will raise automatically by the python virtual machine whenever a particular event occurs.

The predefined exceptions are also known as inbuilt exceptions or PVM Exceptions.

Example 1: Whenever we are trying to perform a division by zero, automatically python will raise

ZeroDivisionError.

print(10/0)  #ZeroDivisionError

Example 2: Whenever we are trying to convert str type into int type and the string does not contain the int valve, then we will get ValueError Automatically.

data=int("Ten") ##ValueError

User-Defined Exceptions:

Sometimes we have to define and raise exceptions explicitly to indicate that something goes wrong, such types of exceptions are called User Defined Exceptions or Customized Exceptions. The user-defined exceptions are also known as Customized Exceptions or Programmatic Exceptions.

The programmer is responsible for defining these exceptions and Python not having any idea about these. Hence we have to raise explicitly based on our requirement by using the «raise» keyword.

Example:

InsufficientFundsException
InvalidPinException
TooYoungException
TooOldException

How to Define and Raise Customized Exceptions:

Every exception in python is a class, and it should be a child class of BaseException.

Example:

class NameofException(PredefinedException):
     def __init__(self,msg):
           self.msg=msg

Example:

class TooYongException(Exception):
      def __init__(self,msg):
            self.msg=msg

The TooYoungException is our exception class name, and it is the child class Exception, and we can raise an exception by using the raise keyword.

The Syntax is:

raise TooYoungException("Massage")

The following example demonstrates the customized exception

class TooYoungException(Exception):
    def __init__(self,msg):
        self.msg=msg
        
class TooOldException(Exception):
    def __init__(self,msg):
        self.msg=msg
        
age=int(input("Enter Age:"))
if age>17:
    raise TooYoungException("Please Wait some more time, definitely you will get chance to vote")
elif age>18:
   raise TooOldException("Now, you are eligible to vote")
else:
    print("As per the gov rules the age should 18 to participate in voting")        

The output is: When the input is 12 then
below-eighteen-to-vote

The output is: When the input is 25
when-the-age-ismore-than-18

0 results

Exceptions in Python

In this lesson, we will understand what is Exception Handling in Python Programming and how to implement it along with some examples.

What is Exception in Python?

An exception is a runtime error that only appears when we run a python program, and the process of eliminating runtime errors from a program is known as Exception Handling.

There are three types of errors that can arise in a python program, and they are:

  • Compile Time Errors or Syntax Errors
  • Logical Errors
  • Runtime Errors

Compile Time Errors or Syntax Errors

Compile Time Errors occur when a program fails to compile because of the wrong syntax used in the program statement. The python compiler show this type of error along with the line number and description of the error.

Let’s see how a syntax error appeared in a program when we forgot to give a semicolon at the end of a for loop statement.

Example

for i in range(1,6)
    print(i)

Output

Traceback (most recent call last):
  File "D:examplesyntaxerror.py", line 1
    for i in range(1,6)
                      ^
SyntaxError: invalid syntax

Logical Errors

Logical Errors occur when a programmer implements the wrong logic in a program. As a result, the final output of the program becomes wrong. The python compiler and python virtual machine (PVM) can’t detect logical errors. It is the programmer’s responsibility to figure out and rectify this type of error in a program.

Example

print('Enter 3 numbers')
a=int(input())
b=int(input())
c=int(input())
average = a+b+c/3
print('Average = %.2f' %(average))

Output

Enter 3 numbers
12
31
17
Average = 48.666667

In the above example, the average of the three numbers is 48.666667, which is wrong because there is a logical error in calculating the average. They should be calculated as (a+b+c)/3, giving us the correct average of 20.

Runtime Errors

Runtime Errors occur when the PVM fails to execute the code after compilation. The python compiler can’t detect the runtime errors. It is only detected by the PVM while executing the code.

Example 1

print('Enter 2 numbers')
a = int(input())
b = int(input())
c = a/b
print('Result = %f' %(c))

Output

Enter 2 numbers
5
0
Traceback (most recent call last):
  File "D:examplelogicalerror.py", line 4, in 
    c = a/b
ZeroDivisionError: division by zero

In the above example, when we try to divide 5 by 0, the PVM gives a runtime error because 5 can’t be divided by 0.

Example 2

x = [12, 36, 72, 37, 81]
print(x[3])
print(x[5])

Output

37
Traceback (most recent call last):
  File "D:examplepro.py", line 3, in 
    print(x[5])
IndexError: list index out of range

In the above example, when we try to access index 5 in the list, it gives a runtime error because there is no such index available.

List of Built-in Exceptions in Python

Below we have given some of the important lists of built-in exceptions in python that are normally raised in a python program.

Name of Exception Class Description
ArithmeticError This error arises when there is an error in a numeric calculation.
AssertionError This error arises when an assert statement fails.
AttributeError This error arises when an attribute reference or assignment fails.
Exception It is the base class for all exceptions.
EOFError This error arises when the input() method reaches the end of a file condition (EOF).
FloatingPointError This error arises when there is an error in floating point calculation.
GeneratorExit This error arises when a generator’s close() method executes.
IOError This error arises when an input or output operation fails.
ImportError This error arises when an imported module does not exist.
IndentationError This error arises when indentation is not specified correctly.
IndexError This error arises when an index does not exist in a sequence.
KeyError This error arises when a key does not exist in a dictionary.
KeyboardInterrupt This error arises when the user hits the Ctrl+C, Ctrl+Z, or Delete keys.
LookupError This error arises when errors raised can’t be found.
MemoryError This error arises when there is no memory left for a program to execute.
NameError This error arises when a variable does not exist.
NotImplementedError This error arises when an abstract method is not overridden in an inherited class.
OSError This error arises when a system-related operation causes an error.
OverflowError This error arises when the result of a numeric calculation is too large to be represented.
RuntimeError This error arises when an error does not belong to any specific exceptions.
StopIteration This error arises when an iterator’s next() method does not find any further values.
SyntaxError This error arises when a syntax error occurs in a program.
TabError This error arises when indentation consists of tabs or spaces.
SystemError This error arises when a system error occurs.
SystemExit This error arises when the sys.exit() function is executed.
TypeError This error arises when an operation is applied to two inappropriate data types.
UnboundLocalError This error arises when a local variable is referenced before the assignment.
UnicodeError This error arises when a problem occurs related to Unicode.
UnicodeEncodeError This error arises when a problem occurs during Unicode encoding.
UnicodeDecodeError This error arises when a problem occurs during Unicode decoding.
UnicodeTranslateError This error arises when a problem occurs during Unicode translation.
ValueError This error arises when a wrong type value is received in a data type that does not support it.
ZeroDivisionError This error arises when a number is divided by 0.

Exception Handling

We can handle exceptions in a python program using the following blocks.

  • try block
  • except block
  • else block
  • finally block

try block

In the try block, the programmer will write such statements that may cause exceptions in the program.

Syntax of try block

try:
    statement
    statement
    ...
    ...
    ...

except block

The programmer writes the except block, including the exception name to be handled in this block. Here programmer will display a detailed message to the user regarding the exception that has occurred in the program.

Syntax of except block

except exceptionname:
    message statement
    ...
    ...
    ...

else block

The else block is an optional block where the programmer writes statements that execute if there is no exception in the try block.

Syntax of else block

else:
    statement
    statement
    ...
    ...
    ...

finally block

The finally block is also an optional block where the programmer writes statements that are executed irrespective of whether an exception has occurred in the try block or not.

Syntax of finally block

finally:
    statement
    statement
    ...
    ...
    ...

Let’s handle the exception when a number is divided by 0.

Example

try:
    print('Enter 2 numbers')
    a = int(input())
    b = int(input())
    c = a/b
    print('Result = %f' %(c))

except ZeroDivisionError:
    print('A number can not be divide by 0')

Output

Enter 2 numbers
5
0
A number can not be divide by 0

To print only the default message of an exception, we have to define the exception name with a new name using the keyword as. After that, we can use the alias name to print the default message of the exception. See the example given below.

Example

try:
    print('Enter 2 numbers')
    a = int(input())
    b = int(input())
    c = a/b
    print('Result = %f' %(c))

except ZeroDivisionError as ex:
    print(ex)

Output

Enter 2 numbers
24
0
division by zero

In the above program, we have defined ex as the new name of the exception ZeroDivisionError.

Let’s see an example of handling multiple exceptions using the multiple except blocks.

Example

try:
    print('Enter 2 numbers')
    a = int(input())
    b = int(input())
    c = a/b
    print('Result = %f' %(c))

    data = [12, 84, 36, 91, 57]
    print(data)
    print('Enter index to print the value from the above list')
    i = int(input())
    print('The value at index %d = %d' %(i,data[i]))

except ZeroDivisionError:
    print('A number can not be divide by 0 Try again')

except IndexError:
    print('The index your are looking for does not exist in the list')

Output

Enter 2 numbers
5
2
Result = 2.500000
[12, 84, 36, 91, 57]
Enter index to print the value from the above list
6
The index your are looking for does not exist in the list

In the above example, we have implemented two except blocks to handle two different types of exceptions that may occur within the try block.

Let’s see how to implement else block along with try and except blocks.

Example

try:
    data = [12, 84, 36, 91, 57]
    print(data)
    print('Enter index to print the value from the above list')
    i = int(input())
    print('The value at index %d = %d' %(i,data[i]))

except IndexError:
    print('The index your are looking for does not exist in the list')

else:
    print('Program executed successfully')

Output

[12, 84, 36, 91, 57]
Enter index to print the value from the above list
2
The value at index 2 = 36
Program executed successfully

In the above program, if no exception arises in the try block, then the codes written in the else block will execute.

Let’s see one more example of how to implement else and finally block along with try and except blocks.

Example

try:
    print('Enter 2 numbers')
    a = int(input())
    b = int(input())
    c = a/b
    print('Result = %f' %(c))

except ZeroDivisionError:
    print('A number can not be divide by 0 Try again')

else:
    print('No exception arises')

finally:
    print('Program ends')

Output

Enter 2 numbers
5
0
A number can not be divide by 0 Try again
Program ends

Enter 2 numbers
5
2
Result = 2.500000
No exception arises
Program ends

If an exception arises in the try block, then the except and finally, blocks will execute. If no exception arises in the try block, then both else and finally block will execute. See the output of the above program.

Raise an Exception in Python

We can manually raise an exception in python program using the raise keyword.

Example

print('Enter a number between 1 to 7')
n = int(input())
if n<1 or n>7:
    raise Exception('Invalid Input')

Output

Enter a number between 1 to 7
0
Traceback (most recent call last):
  File "D:exampleraiseexception.py", line 4, in 
    raise Exception('Invalid Input')
Exception: Invalid Input

User-Defined Exceptions

Sometimes a programmer may want a specific type of exception which is not available in the built-in exceptions list. In that case, the programmer can create a new user-defined exception class by inheriting the Exception class in it.

Example

class RangeError(Exception):
    def __init__(self, msg):
        super().__init__(msg)

print('Enter a number in range 1 to 5')
n = int(input())

if n<1 or n>5:
    raise RangeError('Number not in range')

Output

Enter a number in range 1 to 5
8
Traceback (most recent call last):
  File "D:examplecustomerror.py", line 9, in 
    raise RangeError('Number not in range')
RangeError: Number not in range

In the above example, we have created a new custom error class named RangeError by inheriting the Exception class. After that, inside the sub-class (RangeError) constructor, using the super() function, we initialized the base class (Exception) constructor with the msg argument.

At last, we have used the raise keyword to raise errors using our user-defined exception class RangeError.

Понравилась статья? Поделить с друзьями:
  • Python exception get error message
  • Python exception error types
  • Python except как вывести ошибку
  • Python except socket error
  • Python except exception error