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• Apr 17, 2021 i had the same problem with twitter and Instagram. I ended up using official free api that twitter provides and used selenium for Instagram. Since some of the most popular twitter scraping packages in GitHub aren't working anymore, i came to the conclusion there is no clean way to do it. – aSaffary Apr 17 at 11:04.
• Web scraping, web harvesting, or web data extraction is data scraping used for extracting data from websites BeautifulSoup is one popular library provided by Python to scrape data from the web. To get the best out of it, one needs only to have a basic knowledge of HTML, which is covered in the guide.
• Nov 21, 2019 bs4 (BeautifulSoup) Remember to install these packages on a Python Virtual Environment for this project alone, it is a better practice. Scraping Facebook with Requests. As you may know, Facebook is pretty loaded of JavaScript but the requests package does not render JavaScript; it only allows you to make simple web requests like GET and POST.

Web scraping, web crawling, html scraping, and any other form of web data extraction can be complicated. Between obtaining the correct page source, to parsing the source correctly, rendering javascript, and obtaining data in a usable form, there’s a lot of work to be done. Using Selenium with geckodriver is a quick way to scrape the web pages that are using javascript but there are a few drawbacks. I have found that sometimes the page does not load (I’m sure that this could be more efficient by changing the javascript we execute as mentioned above, but I am new to JS so this might require some time), but also.

Sometimes we need to extract information from websites. We can extract data from websites by using there available API’s. But there are websites where API’s are not available.

Here, Web scraping comes into play!

Python is widely being used in web scraping, for the ease it provides in writing the core logic. Whether you are a data scientist, developer, engineer or someone who works with large amounts of data, web scraping with Python is of great help.

Without a direct way to download the data, you are left with web scraping in Python as it can extract massive quantities of data without any hassle and within a short period of time.

In this tutorial , we shall be looking into scraping using some very powerful Python based libraries like BeautifulSoup and Selenium.

BeautifulSoup and urllib

BeautifulSoup is a Python library for pulling data out of HTML and XML files. But it does not get data directly from a webpage. So here we will use urllib library to extract webpage.

First we need to install Python web scraping BeautifulSoup4 plugin in our system using following command :

$ sudo pip install BeatifulSoup4

$ pip install lxml

OR

Web Scraping Using Selenium And Beautifulsoup Free

$ sudo apt-get install python3-bs4

$ sudo apt-get install python-lxml

So here I am going to extract homepage from a website https://www.botreetechnologies.com

from urllib.request import urlopen

from bs4 import BeautifulSoup

We import our package that we are going to use in our program. Now we will extract our webpage using following.

response = urlopen('https://www.botreetechnologies.com/case-studies')

Beautiful Soup does not get data directly from content we just extract. So we need to parse it in html/XML data.

data = BeautifulSoup(response.read(),'lxml')

Here we parsed our webpage html content into XML using lxml parser.

As you can see in our web page there are many case studies available. I just want to read all the case studies available here.

There is a title of case studies at the top and then some details related to that case. I want to extract all that information.

We can extract an element based on tag , class, id , Xpath etc.

You can get class of an element by simply right click on that element and select inspect element.

case_studies = data.find('div', { 'class' : 'content-section' })

In case of multiple elements of this class in our page, it will return only first. So if you want to get all the elements having this class use findAll() method.

case_studies = data.find('div', { 'class' : 'content-section' })

Now we have div having class ‘content-section’ containing its child elements. We will get all <h2> tags to get our ‘TITLE’ and <ul> tag to get all children, the <li> elements.

case_stud.find('h2').find('a').text Ati drivers for mac os.

case_stud_details = case_stud.find(‘ul’).findAll(‘li’)

Now we got the list of all children of ul element.

To get first element from the children list simply write:

case_stud_details[0]

We can extract all attribute of a element . i.e we can get text for this element by using:

case_stud_details[2].text

But here I want to click on the ‘TITLE’ of any case study and open details page to get all information.

Since we want to interact with the website to get the dynamic content, we need to imitate the normal user interaction. Such behaviour cannot be achieved using BeautifulSoup or urllib, hence we need a webdriver to do this.

Webdriver basically creates a new browser window which we can control pragmatically. It also let us capture the user events like click and scroll.

Selenium is one such webdriver.

Selenium Webdriver

Selenium webdriver accepts cthe ommand and sends them to ba rowser and retrieves results. De noise for mac.

You can install selenium in your system using fthe ollowing simple command:

$ sudo pip install selenium

In order to use we need to import selenium in our Python script.

from selenium import webdriver

I am using Firefox webdriver in this tutorial. Now we are ready to extract our webpage and we can do this by using fthe ollowing:

self.url = 'https://www.botreetechnologies.com/'

self.browser = webdriver.Firefox()

Now we need to click on ‘CASE-STUDIES’ to open that page.

We can click on a selenium element by using following piece of code:

self.browser.find_element_by_xpath('//div[contains(@id,'navbar')]/ul[2]/li[1]').click()

Now we are transferred to case-studies page and here all the case studies are listed with some information.

Here, I want to click on each case study and open details page to extract all available information.

So, I created a list of links for all case studies and load them one after the other.

To load previous page you can use following piece of code:

self.browser.execute_script('window.history.go(-1)')

Final script for using Selenium will looks as under:

And we are done, Now you can extract static webpages or interact with webpages using the above script.

Conclusion: Web Scraping Python is an essential Skill to have

Today, more than ever, companies are working with huge amounts of data. Learning how to scrape data in Python web scraping projects will take you a long way. In this tutorial, you learn Python web scraping with beautiful soup.

Along with that, Python web scraping with selenium is also a useful skill. Companies need data engineers who can extract data and deliver it to them for gathering useful insights. You have a high chance of success in data extraction if you are working on Python web scraping projects.

If you want to hire Python developers for web scraping, then contact BoTree Technologies. We have a team of engineers who are experts in web scraping. Give us a call today.

Consulting is free – let us help you grow!

In this tutorial, we will learn how to scrap web using selenium and beautiful soup. I am going to use these tools to collect recipes from a food website and store them in a structured format in a database. The two tasks involved in collecting the recipes are:

• Get all the recipe urls from the website using selenium
• Convert the html information of a recipe webpage into a structed json using beautiful soup.

For our task, I picked the NDTV food as a source for extracting recipes.

Selenium

Selenim Webdriver automates web browsers. The important use case of it is for autmating web applications for the testing purposes. It can also be used for web scraping. In our case, I used it for extracting all the urls corresponding to the recipes.

Installation

I used selenium python bindings for using selenium web dirver. Through this python API, we can access all the functionalities of selenium web dirvers like Firefox, IE, Chrome, etc. We can use the following command for installing the selenium python API.

Selenium python API requires a web driver to interface with your choosen browser. The corresponding web drivers can be downloaded from the following links. And also make sure it is in your PATH, e.g. /usr/bin or /usr/local/bin. For more information regarding installation, please refer to the link.

I used chromedriver to automate the google chrome web browser. The following block of code opens the website in seperate window.

Traversing the Sitemap of website

The website that we want to scrape looks like this:

We need to collect all the group of the recipes like categories, cusine, festivals, occasion, member recipes, chefs, restaurant as shown in the above image. To do this, we will select the tab element and extract the text in it. We can find the id of the the tab and its attributes by inspect the source.In our case, id is insidetab. We can extract the tab contents and their hyper links using the following lines.

We need to follow each of these collected links and construct a link hierachy for the second level.

Python Web Scraping Example

When you load the leaf of the above sub_category_links dictionary, you will encounter the following pages with ‘Show More’ button as shown in the below image. Selenium shines at tasks like this where we can actually click the button using element.click() method.

For the click automation, we will use the below block of code.

Now let’s get all the recipes in NDTV!

Beautiful Soup

Now that we extracted all the recipe URLs, the next task is to open these URLs and parse HTML to extract relevant information. We will use Requests python library to open the urls and excellent Beautiful Soup library to parse the opened html.

Here’s how an example recipe page looks like:

Web Scraping Using Selenium And Beautifulsoup For Beginners

soup is the root of the parsed tree of our html page which will allow us to navigate and search elements in the tree. Let’s get the div containing the recipe and restrict our further search to this subtree.

Web Scraping Using Selenium And Beautifulsoup 2

Inspect the source page and get the class name for recipe container. In our case the recipe container class name is recp-det-cont.

Let’s start by extracting the name of the dish. get_text() extracts all the text inside the subtree.

Now let’s extract the source of the image of the dish. Inspect element reveals that img wrapped in picture inside a div of class art_imgwrap.

BeautifulSoup allows us to navigate the tree as desired.

Web Scraping Using Beautifulsoup

Finally, ingredients and instructions are li elements contained in div of classes ingredients and method respectively. While find gets first element matching the query, find_all returns list of all matched elements.

Using Selenium To Web Scrape

Overall, this project allowed me to extract 2031 recipes each with json which looks like this: