Webscraping In Python

02-05-2021 by



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.

Python Web Scraping - Introduction. Web scraping is an automatic process of extracting information from web. This chapter will give you an in-depth idea of web scraping, its comparison with web crawling, and why you should opt for web scraping. Python Web Scraping Tutorial. Web scraping, also called web data mining or web harvesting, is the process of constructing an agent which can extract, parse, download and organize useful information from the web automatically. This tutorial will teach you various concepts of web scraping and makes you comfortable with scraping various types of. Python web data scraping gives you the ease of scraping to build brand intelligence and study customer reviews on your product or service. 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. How to scrape a website that requires login with Python. 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.

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

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

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:

Web Scraping In Python Github

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:

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

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.

** 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.

Web Scraping In Python

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

Web Scraping In Python Tutorial

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.

Webscraping In Python

for example:

Python Web Scraping Beautifulsoup

That’s it.

Web Scraping In Python Using Beautifulsoup

Full code sample can be found on Github.





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