How Good Python is for Web Scraping: Quick Tips
Hello readers, here I have come with my new article “How python is good for web scrapping”. Before we start you must learn first what is Python and How we use it. So, let’s start with Python.
What is Python?
Python is a high-level Interpreted programming language which gives control support to the high-level data structure to make attractive server-side dynamic and static web applications, GUI desktop applications etc. It is a general-purpose dynamic programming language which is used for data analysis in website scraping. “Scrapy” is a powerful scraping framework of Python.
Why to use Python?
As I mentioned above that Python is a high-level dynamic programming language that only focuses on programming readability. Python contains simple syntax as compared to C++ and Java. Now, developers are using Python language on a broader level only because of its different coding paradigms. It has a huge number of the consistent library that contains automatic memory and multiple features. There are a lot of reasons why most of the companies prefer Python in their web projects.
Why Companies prefer Python in Web Scraping & Development?
In the Information technology world, most of the companies are using Python because of its solid features like “Unicode support & Garbage Collector” which is used for both scrapings (static or dynamic website). Python language contains simple syntax as compared to other programming languages like C, C++, and Java. It has introduced a constructive design module to remove irrelevant data and constructs. Now, the companies are using its latest version 3.6.5 for standard platforms.
Most of the IT companies are using this language because of its amazing dynamic features and prototype programming codes. Near about 18% of the developers use Python on their operating systems like Mac OS, UNIX, Windows, and Linux.
A web-scraping or website scraping extracts source and the data of a website in a particular format. With the help of web-scraping, you can download data for both static and dynamic websites analysis and send the final data to the client. So, let’s discuss some rules how to do a web scraping with Python as follows.
Rule 1: First, if you are planning to scrap a website then you must verify website’s terms and conditions before scraping. You must take care of document of legal use of data. Generally, extracted data must not be used for any commercial activity.
Rule 2: Don’t send any request data aggressively from the website in your programming. You can call it as Spam because if this happens then it can break the website code. Do it in a reasonable way. I suggest you send one request for one web scrap per-second.
Rule 3: As you know sometimes there are certain changes required on websites because of their dynamic nature and big database storage. So, I suggest that if you are a web-scraper then you have to check these websites time to time. If there is any change required on a website then you will need to make changes in your code or sometimes complete programming.
Rule 4: Make sure that you integrate the code with only public APIs because data efficiency is much higher than website pages.
Rule 5: If your data goes in a large form then store your code into the MySQL database because MySQL is far better than SQL in storage.
Setting up Python Web-scraper
You can use Python 3 and virtual environment to set the things up.
$ python3 -m venv venv $ . ./venv/bin/activate
You need to install these two Python package libraries.
- Request for HTTP (Urllib2)
Urllib2: It is a Python package module which is used for retrieving the web URLs. Also, it verifies the classes and function to help with Url web actions like a cookie, redirect, authentication etc.
BeautifulSoup: It is an amazing tool for data extraction from websites. You can also use it for tables, paragraph, and lists which are extracted by data analysis management tool. You can even apply a filter for data extraction from web pages. Developers are using its latest version BeautifulSoup4. Now, we will use Python in web scraping with a simple Beautiful library by using pip. A pip is a special kind of package tool for Python.
easy_install pip install BeautifulSoup4
If you wish to run the above code, you can use “sudo in every line.
HTML Tags Required for Web scraping
If you are using Python programming language then you will need HTML tags in your programming while web scraping.
<!DOCTYPE html> <html> <head> </head> <body> <-h1> First web-Scrap </h1> <p id='world'> Hello World !! </p> <body> </html>
- HTML tags always start with a <!DOCTYPE html> declaration at the top line of the code.
- Your full documentation will be contained between start <html> tag and end </html> tag.
- Html tags contain script and meta description between these tages <head> and </head>.
- You can see the visible part of the Html code between tags <body> & </body>.
- You must declare main heading and its sub-heading with the help of heading <h1> and </h1> tags.
- <p> defines the visible paragraph in the webpage.
Assume that above data file is saved as contrived.html then you can easily use BeautifulSoup library as follows.
>>> from bs4 import BeautifulSoup >>> raw_html1 = open( "contrived.html').read() >>> html = BeautifulSoup(raw_html1, 'html.parser ') >>> for p in html.select("p" ): ... if p['id'] == 'world': ... print(p.text) 'Hello World !!'
Here, we have passed an argument ‘html.parser’ for multiple constructors. And, “select” method will let you locate CSS selector elements in the main document. In the example ‘html.select(p)’ returns all the list element from the paragraph.
Note: If you use any programming language like Python then you can scrap any website easily. This contains a very easy procedure to get this. One important thing is that while scrapping, always take data from the source. How to do it?, it’s very simple, just go to the website and right-click on your mouse and click on the inspect element or press Crtl+Shift+L.
I hope you enjoyed this article. This would really help you in your web scraping technique. By using Python, you can even scrap multiple sections of a website. You will find the basic way of HTML tags in web scraping step by step. I used these two structures of Python “requests” and “BeautifulSoup“, by applying these structures you can get the output in a quick manner.