Skip to main content

A Typical Guide to Exceptions in Python

By
In this blog, I will give you the basic but important information regarding the Exceptions in Python.

As we all know, we always get some Errors and Exceptions in program every now and then, so to know what that exception is all about. We should know all about exception.

So, let's dive into it.

First of all, let's understand what Exception is?

If a statement or expression is syntactically correct, it may cause an error when an attempt is made to execute it. This errors detected during execution are called Exceptions.

Example:- 




Exceptions are of different types and this error message indicates what happened.
Like you see here in example i.e. ZeroDivisionError, NameError, TypeError. These are basic errors in the program.

List of Standard Exception :-
  1. Exception - Base Class for all the exception

  2. Stop Iteration - Raised when the next() method of an iterator does not point to any object.
    Example :-

  3. System Exit - Raised by the sys.exit() function.

  4. Standard Error - Base Class for all the built-in exceptions except Stop Iteration and SystemExit.

  5. ArithmeticError - Base Class for all errors that occur for numeric calculation.

  6. OverFlowError - Raised when a calculation exceeds a maximum limit for a numeric type.
    Example:-


  7. FloatingPointError - Raised when a floating point calculation fails. Floating point exception handling is not standardized, so floats are not checked. Regular integer are converted to long values are needed.

  8. ZeroDivisionError - Raised when division or modulo by zero takes place for all numeric types.
    Example:-


  9. AssertionError - Raised in case of failure of the Assert Statement.
    Example :-


  10. AttributeError - Raised in case of failure of attribute reference or assignment.
    Example :-

These are some of the exceptions that generally occurred during the programming. There are some other exception that we will cover in our next post.

Hope this help, guys. Stay tune for next blog.

Comments

Post a Comment

Popular posts from this blog

Python 2 vs Python 3 Pystone benchmarking test!

By
When Python 3 came out, It was slower than Python 2. As Python's official blog says Python 3 is 10% slower than Python 2. So it means Python 2 is faster than python 3 by some margin. In this Benchmarking, we will use Pystone benchmarks to compare Python 2 and Python 3. My system specification is listed below: CPU = Intel core i3 2100 @ 3.10 GHZ GPU = Nvidia Geforce 210 RAM = 2 GB OS = Windows 10 Pro The benchmarking results may vary upon your system specification. Here's the result. python 3 pystone benchmarks python 2 pystone benchmarks As you can see python 2 has 24% higher benchmarks than python 3 which is pretty impressive. Maybe this is one of the reasons that some programmers prefers to use Python 2 instead of Python 3. Hope this helps :)
Post a Comment
Read more

Getting error while installing Scipy using pip3 for 64 bit version of Python ? Here's the solution!

By
As you know Scipy is one of the most used modules by the Python programmers for Data science and Machine Learning. So if you have ever try to install Scipy using pip3 (3 for Python 3!), you will get an error like this. As you can see, to install Scipy , simple pip3 install scipy  will not work. To install Scipy, you have to go to Unofficial Windows Binaries for Python Extension Packages  link. Then you have to find for Scipy. If you are using Chrome, you can use cntrl + F to search for scipy. I m using python 3.5 (64-bit) so I have downloaded this package. Make sure to install numpy before scipy otherwise this method wont work. To install numpy, simple pip3 install numpy   won't work . You have to download numpy + mkl from the same link and download it, then install it using pip. To install numpy and scipy wheel file you have to use pip  install  <path of the wheel file> As you can see,pip has successfully installed Scipy. Hope this he
Post a Comment
Read more