Object Oriented Python - Libraries

Requests is a Python module which is an elegant and simple HTTP library for Python. With this you can send all kinds of HTTP requests. With this library we can add headers, form data, multipart files and parameters and access the response data.
As Requests is not a built-in module, so we need to install it first.
You can install it by running the following command in the terminal −
pip install requests
Once you have installed the module, you can verify if the installation is successful by typing below command in the Python shell.
import requests
If the installation has been successful, you won’t see any error message.
As a means of example we’ll be using the “pokeapi”
The requests library methods for all of the HTTP verbs currently in use. If you wanted to make a simple POST request to an API endpoint then you can do that like so −
req = requests.post(‘http://api/user’, data = None, json = None)
This would work in exactly the same fashion as our previous GET request, however it features two additional keyword parameters −
data which can be populated with say a dictionary, a file or bytes that will be passed in the HTTP body of our POST request.
data which can be populated with say a dictionary, a file or bytes that will be passed in the HTTP body of our POST request.
json which can be populated with a json object that will be passed in the body of our HTTP request also.
json which can be populated with a json object that will be passed in the body of our HTTP request also.
Pandas is an open-source Python Library providing high-performance data manipulation and analysis tool using its powerful data structures. Pandas is one of the most widely used Python libraries in data science. It is mainly used for data munging, and with good reason: Powerful and flexible group of functionality.
Built on Numpy package and the key data structure is called the DataFrame. These dataframes allows us to store and manipulate tabular data in rows of observations and columns of variables.
There are several ways to create a DataFrame. One way is to use a dictionary. For example −
From the output we can see new brics DataFrame, Pandas has assigned a key for each country as the numerical values 0 through 4.
If instead of giving indexing values from 0 to 4, we would like to have different index values, say the two letter country code, you can do that easily as well −
Adding below one lines in the above code, gives
brics.index = ['BR', 'RU', 'IN', 'CH', 'SA']
Pygame is the open source and cross-platform library that is for making multimedia applications including games. It includes computer graphics and sound libraries designed to be used with the Python programming language. You can develop many cool games with Pygame.’
Pygame is composed of various modules, each dealing with a specific set of tasks. For example, the display module deals with the display window and screen, the draw module provides functions to draw shapes and the key module works with the keyboard. These are just some of the modules of the library.
The home of the Pygame library is at https://www.pygame.org/news
To make a Pygame application, you follow these steps −
Import the Pygame library
import pygame
Initialize the Pygame library
pygame.init()
Create a window.
screen = Pygame.display.set_mode((560,480))
Pygame.display.set_caption(‘First Pygame Game’)
Initialize game objects
In this step we load images, load sounds, do object positioning, set up some state variables, etc.
Start the game loop.
It is just a loop where we continuously handle events, checks for input, move objects, and draw them. Each iteration of the loop is called a frame.
Let’s put all the above logic into one below program,
Pygame_script.py
The general idea behind web scraping is to get the data that exists on a website, and convert it into some format that is usable for analysis.
It’s a Python library for pulling data out of HTML or XML files. With your favourite parser it provide idiomatic ways of navigating, searching and modifying the parse tree.
As BeautifulSoup is not a built-in library, we need to install it before we try to use it. To install BeautifulSoup, run the below command
$ apt-get install Python-bs4 # For Linux and Python2 
$ apt-get install Python3-bs4 # for Linux based system and Python3.

$ easy_install beautifulsoup4 # For windows machine, 
Or 
$ pip instal beatifulsoup4 # For window machine
Once the installation is done, we are ready to run few examples and explores Beautifulsoup in details,
Below are some simple ways to navigate that data structure −
One common task is extracting all the URLs found within a page’s <a> tags −
Another common task is extracting all the text from a page −

    14 Lectures 
     1.5 hours 

 Harshit Srivastava

    60 Lectures 
     8 hours 

 DigiFisk (Programming Is Fun)

    11 Lectures 
     35 mins

 Sandip Bhattacharya

    21 Lectures 
     2 hours 

 Pranjal Srivastava

    6 Lectures 
     43 mins

 Frahaan Hussain

    49 Lectures 
     4.5 hours 

 Abhilash Nelson
 Print
 Add Notes
 Bookmark this page