Automate Your Life Through Web Scraping

You all know that knowledge is power. You have to perform some data collection tasks to gain access to the best pieces of information. One of the best methods is web scraping or web data extraction to compile and store information from websites on the Internet. But why do you need to use web scraping if you can perform the same task by copying and pasting data?

The answer to the question is that it is easy to copy the text and save the images. But this approach is practically impossible when extracting voluminous amounts of data from a website. It can take days and even months if you use the copy and paste technique for collecting the data. Hence comes the need for web scraping that is used to extract large amounts of data from websites in an automated manner. It will take only minutes or hours to collect data from thousands of website pages. Further, you can download and export the data to analyze the information conveniently.

Time is the most valuable asset in a person’s life. Using web scraping, you can save your time and scrape the data at a higher volume. Below are some use cases of web scraping that can automate your life.

You can use web scraping to perform daily tasks like:

How can web scraping perform these tasks? Let us consider an example of a job search. Suppose you are unemployed and looking for a job as a business analyst. Every day you wake up, check Indeed( the most prominent job website), and scroll multiple pages for new jobs. The job searching process through numerous pages can take 20-30 minutes. 

You can save time and effort by automating this process. For instance, you can create a web scraping program that can send you an email every day you wake up and has all the details of the business analyst job posting on Indeed in a sorted table. In this way, it will take only a few minutes of yours to see the daily job postings. 

Rather than copying and pasting data from the Internet, you can accurately collect and effectively manage the data using web scraping. Copying the data from the web and pasting it somewhere on a computer is a manual process that is tedious and time-consuming. You can use the automated process of web data extraction and save it in a structured format like a .csv file, spreadsheet, etc. This way, you can collect data at a higher volume than a normal human being could ever hope to achieve. For more advanced web scraping, you can store your data within a cloud database and run it daily. 

The brand of a company holds a significant worth. Every brand wishes to have a positive online sentiment and wants customers to purchase its products instead of its competitors. 

The brands use web scraping for:

They can understand the current voice of their customers by checking their comments on their products on social media platforms. This way, they can determine whether the customers like their products or not. Thus, web scraping allows them to quickly identify the negative comments and mitigate damage to brand awareness. 

If you run a business, you can optimize your existing prices by comparing them with the competitors’ prices. You can automatically do this by web scraping to create a competitive pricing plan. Here the question arises: How does web scraping help create a  pricing plan? The answer to the question is that you can collect millions of products’ pricing data via web scraping. The product prices will have to be dynamically changed to meet the fluctuating market demands. This way, the automatic data collection with web scraping helps businesses create a pricing plan.

Web scraping allows you to recruit the top talented candidates for your business compared to your competitors. First, you use web scraping to understand the current market skill, and then you can hire developers that fit your business needs.

Search Engine Optimization (SEO) aims to increase website traffic and converts visitors to leads. You can use web scraping to collect volumes of data, get an idea of the keywords they are optimizing and the content they are posting. Once you collect the data, you can analyze and draw valuable inferences to develop the strategies that best suit your niche. 

How are proxies important for scraping data from the web? Given below are some reasons to use proxies for safe web data extraction.

The proxy pool you use has a specific size that depends on several factors mentioned below.

Some websites offer a free proxy list to use. You can use the below code to grab the list of free proxies.

First, you have to make some necessary imports. You have to import Python’s requests and the BeautifulSoup module.

import requests
import random
from bs4 import BeautifulSoup as bs

You have to define a function that contains the URL of the website. You can create a soup object and get the HTTP response. 

def get_free_proxies():
    url = "https://free-proxy-list.net/"
   
    soup = bs(requests.get(url).content, "html.parser")
    proxies = []

Then, you have to use a for loop that can get the table of the free proxies as shown in the code below.

for row in soup.find("table", attrs={"id": "proxylisttable"}).find_all("tr")[1:]:
        tds = row.find_all("td")
        try:
            ip = tds[0].text.strip()
            port = tds[1].text.strip()
            host = f"{ip}:{port}"
            proxies.append(host)
        except IndexError:
            continue
    return proxies

The output below shows some running proxies.