Table of Contents
Python Web Scraping
While Python has many uses, one of the more innovative and helpful is web scraping or web data extraction through a page’s code.
Python web scraping is an excellent way to get information from websites, which users can then utilize to glean particular insights. Also, it turns unstructured data into a more structured and digestible format.
Web scraping with Python allows for extensive data pulls quickly. But before we get into the specifics, how does web scraping work? Here’s some background.
What is Web Scraping?
When you need to collect a lot of information from a website, web scraping allows you to do so. There are quite a few uses for web scraping, including lead generation, monitoring prices, research, and many others.
Many companies take advantage of web scraping to make more intelligent business decisions or keep an eye on competitors.
How does Web Scraping Work?
There are two parts to web scraping – the crawler and the scraper. The crawler finds the information, and the scraper can quickly extract the data from a page.
Why is Python Ideal for Web Scraping?
Python has a variety of features that make it particularly suited for web browsing. These include:
Concise Coding
Python allows for large tasks to be done with small codes. This saves time writing the code itself.
Flexible Variables
Python saves time because the language doesn’t force you to define data types for variables. This means you can use the variable wherever they’re needed.
A Helpful Community
Fortunately, the Python community is one of the most active and helpful communities out there. Help is just a few clicks away at all times.
A Relatively Simple Syntax
Python code is closer to English sentences than other programming languages, so it’s easier to use. It also looks cleaner, and you don’t have to add semicolons or curly brackets to the code.
How to Scrape Data from any Website
There are a few steps to get info from a website using web scraping. They are:
- Pick the URL to scrape
- Inspect the webpage
- Locate the extraction data
- Write the code
- Run the code to get the data
- Store the data
How to Scrape Data using Python
Python has a few different applications as well as various libraries used for a variety of applications. Use either Selenium, BeautifulSoup, or Pandas to scrape the web. Selenium is a web testing library that’s used to automate the activities of a browser.
BeautifulSoup creates parse trees to aid in extracting data. Pandas is a library that’s best for analysis and manipulating data. It extracts data and then stores it in whatever format is needed.
The first thing to do is to identify a URL for scraping. Next, inspect the page to find the data – it’s usually in tags. To inspect, right-click on an element and click on inspect. This will open a Browser Inspector Box.
Identify the data you want to extract. Now it’s time to write the code. Create a Python file by opening the terminal in Ubuntu. Type gedit (your file name) and add a .py extension.
You’ll write your code in this file. Import all of the necessary libraries and then configure the webdriver to use your browser. Identify the data you want and then run the code and extract the data.
Next, store the data in a format, which will vary depending on your requirement. If you’re storing the data in a Comma Separated Value (CSV), add that to the code. Then run the code an additional time.
This should create a products.csv file that will contain all of the data.
Wrap Up
Python is a great tool to help gather data from across the web to monitor your competitors. By combining resources showing the top market trends, niche details, and understanding your clients’ wants and needs, you can aim to rank above your competition.
Studying your competitor and what works or doesn’t work for them is necessary to the success of your business. Gathering data about their market rankings can help you set a goal and achieve it.
