Although Python has many uses, one of the most innovative and useful is web scraping or extracting web data through the code of a page.
ContentsPython Web ScrapingWhat is Web Scraping?How does Web Scraping work?Why Python is great for Web Scraping?Concise coding Flexible variablesA helpful community Relatively simple syntax How to extract data from any website How to extract data using PythonPackerPython web scraping is a great way to get information from websites, which users can then use to glean particular information. Also, it transforms unstructured data into a more structured and digestible format.
Web scraping with Python can quickly extract a lot of data. But before going into the details, how does web scraping work? Here's some background.
When you need to collect a lot of information from a website, web scraping lets you do that. There are many uses for web scraping including lead generation, price monitoring, research and many more.
Many businesses are taking advantage of web scraping to make smarter business decisions or keep tabs on their competitors.
There are two parts to web scraping – the caterpillar and the scraper. The crawler finds the information and the scraper can quickly extract data from a page.
Python has a variety of features that make it particularly suitable for web browsing. These include:
Python allows you to do big tasks with small codes. This saves time writing the code itself.
Python saves time because the language doesn't require you to define data types for variables. This means you can use the variable wherever you need it.
Fortunately, the Python community is one of the most active and helpful communities. Help is just a few clicks away at any time.
Python code is closer to English sentences than other programming languages, so it is easier to use. It also looks cleaner and you don't need to add semicolons or braces to the code.
There are a few steps to get information from a website using web scraping. They are:
Python has a few different applications as well as various libraries used for a variety of applications. Use Selenium, BeautifulSoup or Pandas to scrape the web. Selenium is a web testing library used to automate browser activities.
BeautifulSoup creates parse trees to make data extraction easier. Pandas is an ideal library for analyzing and manipulating data. It extracts the data and then stores it in the necessary format.
The first thing to do is identify a URL for scraping. Then inspect the page to find the data – it's usually in tags. To inspect, right click on an item and click inspect. This will open a browser inspect 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 will write your code in this file. Import all necessary libraries, then configure the web driver to use your browser. Identify the data you want, then run the code and extract the data.
Then, store the data in a format that will vary depending on your needs. If you're storing the data in a comma-separated value (CSV), add it to the code. Then run the code one more time.
This should create a products.csv file which will contain all the data.
Python is a great tool to help you collect data from around the web to monitor your competitors. By combining resources showing key market trends, niche details, and understanding your customers' wants and needs, you can aim to rank above your competition. Studying your competitor and what is working or not working for them is necessary for the success of your business. Collecting data on their market ranking can help you set a goal and achieve it.
