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Post By AdminLast Updated At 2020-06-11
How web scraping with python is simple?

Web scraping with python is a Simple Software trick, for getting Data, from the website. With this trick, you can change Unstructured Data on the web element, into Structured Data.

Best Web scraping Services can get Data, from many unstructured Formats, like HTML, social media websites, pdf, and local listings, and some other portals, and blogs.

               Know more about Web scraping by Python Online Training

1. How web scraping with python is simple?

Python is the best programming language and has the best ecosystem that supports web scraping. Libraries and tools of Python help web scraping. Moreover, errors are fixed quicker with Python.

How web scrapping with python is simple | OnlineITGuru

2.Tools used for Python web scraping:

a)Urllib:

It is a python package, that used for initiating URLs. Urllib combines many modules, for operating with URLs like Urlib suggestions, for reading URLs, mostly the HTTP, urllib. error sample makes the exception classes that raised by urlib.parse, urlib.request.

It defines the standard and secure Interface for breaking uniform resource locator, strings, and components, and urllib.robotparser offers a single class.

b)Selenium:

It is an open-source automation tool, offers a simple API for scripting functional or acceptance tests, by selenium web driver. Moreover, it is basically a set of software tools, for every approach to support the test automation.

c)Scrapy:

It is an open-source and communicative framework, for getting data, what a user needs from websites. That scripted in python language, it is the fast level web crawling and scraping framework for python. Further, this is used for a wide range of cases, from data monitoring, mining, and automated testing.

Basically, it was an app framework for writing web spiders, that crawl websites' URLs, and pages, that extract data from them. Spiders are the classes that a user makes and it uses the spiders to scrape data from a website.

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3.Python Requests:

It is the Non-GMO HTTP library, for python, It accepts the user for sending Http/1.1  requests, and there is no requirement of manually added queries of your URLs. We have many numbers of supported browser style SSL verification, content decoding.

a)Mechanical Soup:

It is a library for automating communication with the website, it auto stores and sends cookies, that redirect and follow links and they submit forms. It also offers a similar API, that designed on python giant's suggestions and beautiful soup.

b) LXML:

It is a python tool for c libraries libxml2 and libxslt. It was identified as one of the main features and easy to implement libraries, for making XML and HTML to work in Python Language.

LXML is a Genuine case that combines the speed and XML feature of all these libraries with the small nativity of python API and it is compatible but superior for all well-known element tree_API.

c)Beautiful Soup:

It is also a python library for pulling the data out from an HTML and XML file. Soup mainly concentrates on some projects like web scraping. It offers easy methods and idioms for searching and modifying a parse tree. Moreover, it converts incoming files for Unicode and outgoing files to UT-8.

Using Beautiful Soup with pythonfrom urllib.request import urlopenfrom bs4 import BeautifulSouphtml = urlopen("https://www.onlineitguru.com/")res = BeautifulSoup(html.read(),"html5lib");print(res.title)Handling HTTP Exceptionsfrom urllib.request import urlopenfrom urllib.error import HTTPErrorfrom bs4 import BeautifulSouptry:html = urlopen("https://www.onlineitguru.com/")except HTTPError as e:print(e)else:res = BeautifulSoup(html.read(),"html5lib")print(res.title)Handling URL Exceptionsfrom urllib.request import urlopenfrom urllib.error import HTTPErrorfrom urllib.error import URLErrorfrom bs4 import BeautifulSouptry:html = urlopen("www.onlineitguru.com/")except HTTPError as e:print(e)except URLError:print("Server down or incorrect domain")else:res = BeautifulSoup(html.read(),"html5lib")print(res.titles)Using a simple if statement like this:from urllib.request import urlopenfrom urllib.error import HTTPErrorfrom urllib.error import URLErrorfrom bs4 import BeautifulSouptry:html = urlopen("https://www.onlineitguru.com/")except HTTPError as e:print(e)except URLError:print("Server down or incorrect domain")else:res = BeautifulSoup(html.read(),"html5lib")if res.title is None:print("Tag not found")else:print(res.title)Scrape HTML Tags using Class Attributefrom urllib.request import urlopenfrom urllib.error import HTTPErrorfrom urllib.error import URLErrorfrom bs4 import BeautifulSouptry:html = urlopen("https://www.onlineitguru.com/")except HTTP Error as e:print(e)except URL Error:print("Server down or incorrect domain")else:res = BeautifulSoup(html.read(),"html5lib")tags = res.findAll("h2", {"class": "widget-title"})for tag in tags:print(tag.getText())
Why use Python for web scraping?

There are many other coding languages that support web scraping but we found Python as the most popular approach. Moreover, the Beautiful Soap library of Python is also useful in this regard.

Furthermore, there are some most useful features that Python offers to do web scraping easily.

Ease of use

Python coding language is very simple and easy to use. The code written using Python language is very simple to understand, unlike other language codes. Moreover, with simple syntax and codes, you can work easily without any difficulty. 

Dynamically typed

Due to dynamically typed language, users don’t have to define data types for variables. Therefore, they can use these variables anywhere as per need. However, it helps to save precious time and makes the tasks faster to finish.

Great library collection

One of the reasons for using Python for web scraping is that it has a great collection of libraries like Pandas, Matplotlib, Numpy, etc. These different libraries provide different methods and services for various purposes. Moreover, they are also useful for doing any further changes other than web scraping. For web scraping purposes the most useful libraries are Beautiful Soap, Pandas, and Selenium. 

Small and simple coding

Typically, Web scraping is useful to save time for a user. If he writes lengthy codes then it will take much time and development becomes slow. Thus, python helps in this regard with less coding for large tasks. Hence, the small and simple codes will save much time while writing. 

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Easy to understand 

The syntax written in Python language is very simple/easy to understand like reading a statement in simple English. Furthermore, the language is much expressive and readable also with good indentation. So, the user can easily change the different blocks within the code. Thus, it is better to opt for Python language for scraping the web.

Community support

If you find any difficulty in writing the code in Python then you can ask for support from community members. Python has the largest community with loads of members where anyone can seek help easily. 

Is Python Web Scraping is legal?

It is difficult to say that web scraping is legal or not as some websites allow it and some not. Many websites don’t provide clear guidance on their way. But before going to scrape any website one must follow the rules and terms and conditions of the site whether explicitly allows scraping. Also, it needs to check the “robots.txt” file whether a website allows web scraping or not. 

The scraping of the web is done through automation where it consumes a large amount of data of the hosting website. While scraping a single page of any website doesn’t cause many issues. But while scraping a large number of pages may cost huge for the website owner. This may turn into legal action by him. 

How to perform web scraping?

When we run the written code for web scraping, then it sends a request to the URL or website host. In response to this, a server will return the source code written in HTML or XML and allows reading the data. Then the code parses the HTML page to find and extract the data from it.

To do the web scraping using Python by extracting data, the following steps will be useful.

Locate the URL and request the content for scraping

Inspect the required page

Locate the data for extracting

Write the code required

Run the code for extracting the data

Finally, store the data in the required format

This is all about performing web scraping in a simple way.

Final thoughts

Hence, web scraping is done to get the insights (data) of any website which may be structured or unstructured. To conduct this process it needs to check the credentials of the website whether they allow or not. Besides, some websites don’t allow to scrape their pages. I hope you got the main idea of Web scraping with Python and its methodology. If you are willing to get more knowledge on this topic, go through the Python Online Course with ITGuru. This learning could also help you update your existing skills in Python and its various aspects.

These are the best-known facts about web scrapping with python, in upcoming blogs, we will update more Data on this topic.