Web Scraping with Python using Requests, LXML and Splash

Web Scraping with Python using Requests, LXML and Splash

Become a Ninja in Web Scraping/Crawling with Python using Requests, the powerful LXML and Splash for JavaScript websites

What is web scraping?

Let’s say your boss at work gave you a task where he wants you to extract about 1000 product from a website, structure the data and save it to a database, would you copy paste manually all the product details from the product name, url and price ? I can imagine you would work days and nights and you wont finish the task, so this is where web scraping shines. So web scraping, or web harvesting or web data extraction is like writing a script that will automate data extraction from websites in a matter of minutes !.

Why learn Web Scraping?

Whether you’re a data analyst, a web developer or even someone who wants to work as a freelancer you should learn web scraping.

For a data analyst building a dataset is extremely important, so without web scraping you simply can’t generate it in addition to that adding web scraping in your resume is a plus for you.

Web scraping can be used in a variety of fields, so let me give you some examples on what you can do with it:

  • Generate leads,
  • Drop shipping where basically you gonna constantly scrape products from different online stores and show case them on your website to make money,
  • Monitor products prices to get the best deals, automation,
  • Machine learning,
  • Web scraping freelancer

Why LXML and not BeautifulSoup ?

LXML is a lightweight HTML parser even the most popular web scraping framework (Scrapy) is built on the top of LXML, BeautifulSoup is a little bit overloaded with the number of functions exposed to us, it has more functions to use, yes that’s right ! however in Web Scraping most of the time we use XPath and CSS Selectors to navigate and select what to scrape from the HTML web page (tree) so there is no need to learn about new functions and wasting all that time to familiarize yourself with the BeautifulSoup API and the internal architecture, in addition to all of that LXML in terms of performance is way better than BeautifulSoup.

What you’ll learn

  • LXML core fundamentals
  • XPath & CSS selectors
  • How send HTTP requests with Python
  • Scraping HTML web pages
  • Scraping multiple pages using recursion
  • Scraping APIs
  • Splash HTTP API
  • Scraping JavaScript websites using Splash
  • Authentication and Login to websites using Requests
  • Web scraping best practices
  • Building datasets

#python #web-development #javascript #html

What is GEEK

Buddha Community

Web Scraping with Python using Requests, LXML and Splash
Ray  Patel

Ray Patel

1619518440

top 30 Python Tips and Tricks for Beginners

Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.

1) swap two numbers.

2) Reversing a string in Python.

3) Create a single string from all the elements in list.

4) Chaining Of Comparison Operators.

5) Print The File Path Of Imported Modules.

6) Return Multiple Values From Functions.

7) Find The Most Frequent Value In A List.

8) Check The Memory Usage Of An Object.

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Osiki  Douglas

Osiki Douglas

1624595434

How POST Requests with Python Make Web Scraping Easier

When scraping a website with Python, it’s common to use the

urllibor theRequestslibraries to sendGETrequests to the server in order to receive its information.

However, you’ll eventually need to send some information to the website yourself before receiving the data you want, maybe because it’s necessary to perform a log-in or to interact somehow with the page.

To execute such interactions, Selenium is a frequently used tool. However, it also comes with some downsides as it’s a bit slow and can also be quite unstable sometimes. The alternative is to send a

POSTrequest containing the information the website needs using the request library.

In fact, when compared to Requests, Selenium becomes a very slow approach since it does the entire work of actually opening your browser to navigate through the websites you’ll collect data from. Of course, depending on the problem, you’ll eventually need to use it, but for some other situations, a

POSTrequest may be your best option, which makes it an important tool for your web scraping toolbox.

In this article, we’ll see a brief introduction to the

POSTmethod and how it can be implemented to improve your web scraping routines.

#python #web-scraping #requests #web-scraping-with-python #data-science #data-collection #python-tutorials #data-scraping

Sival Alethea

Sival Alethea

1624402800

Beautiful Soup Tutorial - Web Scraping in Python

The Beautiful Soup module is used for web scraping in Python. Learn how to use the Beautiful Soup and Requests modules in this tutorial. After watching, you will be able to start scraping the web on your own.
📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=87Gx3U0BDlo&list=PLWKjhJtqVAbnqBxcdjVGgT3uVR10bzTEB&index=12
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Thanks for visiting and watching! Please don’t forget to leave a like, comment and share!

#web scraping #python #beautiful soup #beautiful soup tutorial #web scraping in python #beautiful soup tutorial - web scraping in python

Ray  Patel

Ray Patel

1619510796

Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

August  Larson

August Larson

1625143020

Web Scraping Using Scrapy and Python

A beginner-friendly guide to scraping web data

Introduction

Web data is one of the most readily accessible sources of data out there. For this reason, being able to extract and utilize the plethora of data that exists on the web is a necessary skill for every data scientist. And if this skill is not in your skillset just yet, needless to worry because this tutorial has got you covered. By the end of this tutorial, you’ll have learned the fundamentals of web scraping using Scrapy and will have a fully functional Python web scraper that extracts Covid-19 data from Worldometers.info.

#scrapy #web-scraping #data #python #covid19 #web scraping using scrapy and python