In this series of posts, I'm going to examine common design patterns in Python that make Python code feel "Pythonic." This second post covers Python's with statement, a syntax to elegantly handle code that requires set up and tear down.This post continues a series on “Pythonic” code. Pythonic code is code that fits well with the design of the Python language.
This post continues a series on “Pythonic” code. Pythonic code is code that fits well with the design of the Python language. Previously, I wrote about list comprehensions as a powerful way to manipulate Python’s list data structure. This post will cover the
One task that you are likely to encounter while programming Python is the need to open a file. That file might contain tables of data or pictures of kittens. Whatever you find yourself doing, you’ll come across the
open function. Let’s work through a thought experiment which can help explain why you should use
If you’re brand new to Python, you might open a file like so:
f = open('kitteh.jpg', 'rb') cat_pic = f.read() # Do other stuff with the cat picture.
After speaking with a friend with more Python experience than you, you learn that you’re supposed to close files or else the operating system will eventually run into trouble (because it can only track a limited number of open files). You rewrite your code:
f = open('kitteh.jpg', 'rb') cat_pic = f.read() # Do other stuff with the cat picture. f.close()
In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.
Today you're going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates. We gonna use Python OS remove( ) method to remove the duplicates on our drive. Well, that's simple you just call remove ( ) with a parameter of the name of the file you wanna remove done.
In the programming world, Data types play an important role. Each Variable is stored in different data types and responsible for various functions. Python had two different objects, and They are mutable and immutable objects.
Magic Methods are the special methods which gives us the ability to access built in syntactical features such as ‘<’, ‘>’, ‘==’, ‘+’ etc.. You must have worked with such methods without knowing them to be as magic methods. Magic methods can be identified with their names which start with __ and ends with __ like __init__, __call__, __str__ etc. These methods are also called Dunder Methods, because of their name starting and ending with Double Underscore (Dunder).
Having to handle exceptions is common in Python and so is having to define your own. Yet, I have seen competing ways of doing so in various projects. The inconsistency comes from Exceptions being something that can easily be subclassed and extended, but also something that can be easily instantiated and used in their base form.