Code Fellows courses Notes
This project is maintained by QamarAlkhatib
Web scraping is a technique to automatically access and extract large amounts of information from a website, which can save a huge amount of time and effort. This is a great exercise for web scraping beginners who are looking to understand how to web scrape.
Important notes about web scraping, Read through the website’s Terms and Conditions to understand how you can legally use the data. Make sure you are not downloading data at too rapid a rate because this may break the website.
Python Code
We start by importing the following libraries.
import requests
import urllib.request
import time
from bs4 import BeautifulSoup
Next, we set the url to the website and access the site with our requests library.
url = 'http://web.mta.info/developers/turnstile.html'
response = requests.get(url)
Next we parse the html with BeautifulSoup so that we can work with a nicer, nested BeautifulSoup data structure. If you are interested in learning more about this library
soup = BeautifulSoup(response.text, “html.parser”)
We use the method .findAll to locate all of our <a> tags.
soup.findAll('a')
steps here
Web scraping, web harvesting, or web data extraction is data scraping used for extracting data from websites. The web scraping software may directly access the World Wide Web using the Hypertext Transfer Protocol or a web browser. While web scraping can be done manually by a software user, the term typically refers to automated processes implemented using a bot or web crawler.
It has specific rules for good behavior, such as how frequently you can scrape, which pages allow scraping, and which ones you can’t. Some websites allow Google to scrape their websites, by not allowing any other websites to scrape. This goes against the open nature of the Internet and may not seem fair, but the owners of the website are within their rights to resort to such behavior. Txt file on websites.
What if you need some data that is forbidden by Robots. Most anti-scraping tools block web scraping when you are scraping pages that are not allowed by Robots. By looking for a few indicators that real users do and bots don’t. Humans are random, bots are not. Humans are not predictable, bots are.
No human ever does that.
You can do this by specifying a ‘User-Agent’.
Web scraping bots fetch data very fast, but it is easy for a site to detect your scraper, as humans cannot browse that fast. If a website gets too many requests than it can handle it might become unresponsive. Ideally, put a delay of 10-20 seconds between clicks and not put much load on the website, treating the website nice. Use auto throttling mechanisms which will automatically throttle the crawling speed based on the load on both the spider and the website that you are crawling.
Web scraping bots tend to have the same crawling pattern because they are programmed that way unless specified. Sites that have intelligent anti-crawling mechanisms can easily detect spiders by finding patterns in their actions and can lead to web scraping getting blocked.
When scraping, your IP address can be seen. When we send requests from a proxy machine, the target website will not know where the original IP is from, making the detection harder. Create a pool of IPs that you can use and use random ones for each request.
They are cheaper than residential proxies and could be detected easily. Residential Proxies, if you are making a huge number of requests to websites that block to actively. These are very expensive . Try everything else before getting a residential proxy.