Unleash the Power of Web Crawling with Python

Crawling is a term used to describe the process of retrieving information from websites, such as images or other resources that are not listed on a website’s home page. robots.txt files, form data, and other metadata available on the Internet help the user in easy web crawling.

Web Crawling or Web Scraping?

There is a huge difference between these two terms. While web crawling, a large-scale phenomenon, is used to index data on a webpage, web scrolling works for several websites. A web crawler is a spider bot because of this reason.

Pros of Web Crawling in Python

It offers several advantages over other methods of data extraction. Crawling through websites helps us in the following ways:

• To collect data about them and store it in some database or spreadsheet format. Here, data can refer to any type of website content like their pages and links etc.
• To write software applications that will crawl through websites and extract information from them, store the data in database or spreadsheet format.
• For analysis or research purposes
• Find, index and retrieve data (one uses XML or JSON files to represent websites and the information they contain.)
• Passive observation or monitoring of data is also done.
• WebCrawler can be deployed remotely without requiring personnel accesses to the source site’s servers—a significant advantage over other methods that require human interaction with their targets; this may be especially important when dealing with sensitive data like financial information or health records which must remain private at all times!
• Webcrawling also allows for more efficient caching than other methods since it does not require physical access to the source site.

Simple Methods of Web Crawling

Crawling can be done through the following ways :

• Manually by a human agent who follows links between pages on a website
• Using an automated search engine like Googlebot or Bingbot which crawls web pages automatically by looking for links between them and other pages online. Web Robots are also used these days.

How to do web crawling in python?

The term comes from the idea that, when a page is loaded by a browser, it sends a request to the server asking for information about that page. This request includes details about what kind of document it is and what type of data it contains.

The server then responds with some information about each requested resource (for example, images or documents) or even all available resources (such as all pages on one website).

How to use web crawler on a website?

First let us understand how a website works.

• When the user enters a website name, it means that he wishes to access information from the website.
• Once the correct website matches the request (using IP address mapping) the user obtains an html file. This is a raw file.
• The file is not in a readable format so the browser transforms it to a format which the user can interpret.

#readytocode

You may follow this web crawling code in python.

• Include these modules while working on python friendly environment.

pip install requests
pip install html5lib
pip install bs4

• Next, import requests module to deal with the html on webpage. Here, we have used get() function viz part of the requests module to get data in HTML format.

import requests
url = "https://pythonpool.com"
r = requests.get(url)		# r variable has all the HTML code now
htmlTexr = r.text              #return the response in unicode format
print(htmlText)               #printing the ans

• Parse data through BeautifulSoup(bs4) module.

from bs4 import BeautifulSoup
soup = BeautifulSoup(r.content, 'html.parser')
soup = BeautifulSoup(htmlContent, 'html.parser') //or store html data in a variable
//instead of parser, we can use lxml too

• To obtain all the code on the webpage, use find_all() function.

for i in soup.find_all("code"):
    print(i.text)
title = soup.title                                //to get title of webpage
print(title)                    
print(soup.find('a'))                        //get first a tag 
paras = soup.find_all('div')          //to get all div tags
print(paras)
for i in paras:                                   //to get separate answers(not in list format) 
    print(i)

# print(soup.find('p')['class'])      //finding via class name along with tag name

# print(soup.find_all(class_="code-toolbar"))     //finding only via class name

soup.find(‘element’).text              //to get the output without the title

for i in paras:                                   //to scrap href variable in anchor tags
    print(i['href'])

In case you face errors while coding, you may check Correct Grammatical Errors Using Python. To check for warnings while coding , Suppress Warnings In Python: will also be handy to you.

#readytocodewithdjango

Now, you might not be aware of the fact that django can also be used. for web crawling. The prerequisites are:

• Updated version of Python (Python 3 will work)
• Updated version of Django and Scrapy both

Now, install the required packages.

pip install django 
pip install scrapy

Give a name to your project.

django-admin startproject xyz

Create a virtual environment to work along with a model. Here, x refers to the python version you have installed on your system.

pythonx -m venv .venv && source .venv/bin/activate
python manage.py startapp movie     //
from django.db import models           //models is a package here
class Movie(models.Model):                 //specify  functions, data members of class
....

This way you can begin crawling via django

Web Crawling in Python or Javascript, what to choose ?

FAQs

Conclusion

In this article we learnt about web crawling, a widely adopted technique for extracting data from websites i.e. how to do web crawling in Python and make use of Python’s HTTP library for downloading data from website pages.