Exceptions are errors that occur during the execution of Python code. They are caught by using the try/except blocks. The except block executes an alternative piece of code if an exception is raised. Some of the most common python exceptions include LookupError, ZeroDivisionError, and IOError. Others include IndexError and ValueError.
ArithmeticError
The ArithmeticError exception is raised when arithmetic operations fail. It includes errors like dividing by zero or a bitshift that exceeds the limit of an int.
Exceptions are handled with try and except blocks. The except block executes if an exception is found while the try block prevents the process from terminating. User code can also subclass the built-in exceptions but should always use Exception as its base class.
LookupError
In Python, when an exception is raised, the interpreter shows a Traceback that tells you what caused the error. For example, the following code raises a KeyError exception when it tries to access an invalid key in the dictionary.
To avoid the problem, try using a try except block. This will handle the key lookup failure and return a default value, such as None, instead.
ZeroDivisionError
ZeroDivisionError is raised if a division or modulo operation has a denominator that is not non-zero. This is a common error that can be handled with a try-except block.
Try-except allows you to separate your code into blocks that handle different types of errors. Python provides built in exceptions that you can catch with the except clause, or you can raise your own.
IOError
This exception is raised when a system function returns a system-related error, including I/O failures. It was merged with FileNotFoundError in Python 3.0.
This built-in exception can be handled by using the try/except block. The except clause can include classes that derive from Exception to handle specific exceptions. A finally clause can also be used to execute code after the try and except blocks. Get in-depth insights into python exceptions by visiting the site.
ImportError
Python raises this exception when it encounters a problem with an import statement. The problem could be that a required module is not available or the name of the module is misspelled.
Like other built-in exceptions, it has an associated value that provides detailed information about the error. This value is a tuple. It can be used for debugging purposes. The __traceback__, __cause__, and __context__ attributes are set implicitly when an exception is raised.
NameError
NameError is raised when your code references an identifier that does not exist in the current scope. This can happen when you forget to import a module or you mention a variable that is not defined.
The NameError traceback contains a lot of helpful information that can help you fix the problem. The last line of the traceback tells you the name that is missing.
TypeError
Encountering errors while coding in Python is an inevitable part of the programming process. While seeing some red text on the screen can be intimidating, it’s important to understand how these errors are handled and how to correct them.
TypeError is raised when an operation is performed on an object type that is not supported. For example, adding an integer value to a string will raise this error.
IndexError
Raised when trying to access an item in a list, tuple, or other sequence at an invalid index. The index must be within the range of the item’s length.
To avoid this error, make sure that you check the index before attempting to access the item. Also, use try-except blocks to handle errors in your code. This can help you debug your program more easily and fix errors. The site serves as a valuable resource for understanding python exceptions.
OutOfRangeError
Raised when an index in a list goes beyond its valid range. This error can be avoided by making sure that any indexes used in a list are within the valid range for that list.
Identifying the line of code that triggers this exception is possible by using the debugging tools provided in your IDE. This will help you find the invalid index and fix it accordingly.
NotEnoughMemoryError
This error is encountered when the computer doesn’t have enough memory to perform a certain task. This can be due to various reasons like insufficient RAM or disk space, hardware issues, or software conflicts.
To fix this issue, try closing programs that are consuming large amounts of memory and defragment your hard drive. This will free up space on your disk and improve performance. Get to know about this python exceptions in the link.
