Webscraping In Python

Watch it together with the written tutorial to deepen your understanding: Web Scraping With Beautiful Soup and Python The incredible amount of data on the Internet is a rich resource for any field of research or personal interest. To effectively harvest that data, you’ll need to become skilled at web scraping.

Manually Opening a Socket and Sending the HTTP Request. The most basic way to perform. Using APIs - Web Scraping with Python Book Chapter 4. Like many programmers who have worked on large projects, I have my share of horror stories when it comes to working with other people’s code. From namespace issues to type issues to misunderstandings of function output, simply trying to get information from point A to method. If you are just getting started in Python and would like to learn more, take DataCamp's Introduction to Data Science in Python course. In the time when the internet is rich with so much data, and apparently, data has become the new oil, web scraping has become even more important and practical to use in various applications.

I’ve recently had to perform some web scraping from a site that required login.It wasn’t very straight forward as I expected so I’ve decided to write a tutorial for it.

For this tutorial we will scrape a list of projects from our bitbucket account.

The code from this tutorial can be found on my Github.

We will perform the following steps:

  1. Extract the details that we need for the login
  2. Perform login to the site
  3. Scrape the required data
Webscraping In Python

For this tutorial, I’ve used the following packages (can be found in the requirements.txt):

Web scraping in python

Open the login page

Go to the following page “bitbucket.org/account/signin” .You will see the following page (perform logout in case you’re already logged in)

Check the details that we need to extract in order to login


In this section we will build a dictionary that will hold our details for performing login:

  1. Right click on the “Username or email” field and select “inspect element”. We will use the value of the “name” attribue for this input which is “username”. “username” will be the key and our user name / email will be the value (on other sites this might be “email”, “user_name”, “login”, etc.).
  2. Right click on the “Password” field and select “inspect element”. In the script we will need to use the value of the “name” attribue for this input which is “password”. “password” will be the key in the dictionary and our password will be the value (on other sites this might be “user_password”, “login_password”, “pwd”, etc.).
  3. In the page source, search for a hidden input tag called “csrfmiddlewaretoken”. “csrfmiddlewaretoken” will be the key and value will be the hidden input value (on other sites this might be a hidden input with the name “csrf_token”, “authentication_token”, etc.). For example “Vy00PE3Ra6aISwKBrPn72SFml00IcUV8”.

We will end up with a dict that will look like this:


Keep in mind that this is the specific case for this site. While this login form is simple, other sites might require us to check the request log of the browser and find the relevant keys and values that we should use for the login step.

For this script we will only need to import the following:

Web Scraping In Python+beautifullsoup

First, we would like to create our session object. This object will allow us to persist the login session across all our requests.

Python Web Scraping Beautifulsoup

Second, we would like to extract the csrf token from the web page, this token is used during login.For this example we are using lxml and xpath, we could have used regular expression or any other method that will extract this data.

Web Scraping In Python Github

** More about xpath and lxml can be found here.

Next, we would like to perform the login phase.In this phase, we send a POST request to the login url. We use the payload that we created in the previous step as the data.We also use a header for the request and add a referer key to it for the same url.

Now, that we were able to successfully login, we will perform the actual scraping from bitbucket dashboard page

In order to test this, let’s scrape the list of projects from the bitbucket dashboard page.Again, we will use xpath to find the target elements and print out the results. If everything went OK, the output should be the list of buckets / project that are in your bitbucket account.

You can also validate the requests results by checking the returned status code from each request.It won’t always let you know that the login phase was successful but it can be used as an indicator.

Web Scraping In Python Code

for example:

That’s it.

Web Scraping In Python

Full code sample can be found on Github.