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.

1. Scrape Content From Website
2. Sites For Web Scraping Software
3. Web Scraping How To
4. What Is Web Scraping
5. Sites For Web Scraping And Painting
6. Scraping Meaning Web

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.

• ParseHub helps you develop web scrapers to crawl single and various websites with the assistance for JavaScript, AJAX, cookies, sessions, and switches using their desktop application and deploy them to their cloud service.
• How to Scrape a Websites' Data With Beautiful Soup Now that you have everything up and ready, open up a preferred code editor and create a new Python file, giving it a chosen name. However, you can also make use of web-based IDEs like Jupyter Notebook if you're not familiar with running Python via the command line.

Mar 05, 2020 Web scraping is the process of automating data extraction from websites on a large scale. With every field of work in the world becoming dependent on data, web scraping or web crawling methods are being increasingly used to gather data from the internet and gain insights for personal or business use. In the previous chapter, we have seen scraping dynamic websites. In this chapter, let us understand scraping of websites that work on user based inputs, that is form based websites. These days WWW (World Wide Web) is moving towards social media as well as usergenerated contents. Dec 31, 2019 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.

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:

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.

Scrape Content From Website

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.

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.

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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.

for example:

That’s it.

Full code sample can be found on Github.

Price comparison websites extract essential details such as product prices, reviews, features, and descriptions from multiple sites.

Many years ago, the easiest way to get the best shopping deals was to compare prices from different e-commerce sites before making a purchase. From time immemorial, a commodity has always had various price tags across different selling platforms, prompting smart sellers to monitor price changes among competitors by using real-time analytical technology. Even today, retailers seize every opportunity in the market to stay relevant in the competitive atmosphere and win more customers for their business. One of the trusted methods of doing this is by using price comparison websites.

Price comparison websites extract essential details such as product prices, reviews, features, and descriptions from multiple sites.

How price comparison websites work

Price comparison websites extract essential details such as product prices, reviews, features, and descriptions from multiple sites. These details are then compiled on the price comparison website and tailored accordingly for easy access. So, when a buyer searches for a product on the website, the site quickly compares and lists similar products from a number of retailers. This process simplifies the buying decision of the buyer since they can compare factors such as price deals, shipping costs, and other features.

However, the algorithms involved depend on massive data. As expected, data extraction in real-time is not only daunting but time-consuming. As if that wasn’t enough, the dynamic pricing system employed by e-commerce websites makes it difficult to keep track of price changes. Amazon, for instance, is approximately 417 hours faster than its competitors in adapting price changes.

So, why is it difficult to obtain data for these websites?

The reason is that the data volume involved is challenging as building a comparison technology to extract different structures of data from websites. Since web scraping became a trend in data extraction, more price comparison websites have emerged over the years, as data extraction is relatively easy.

How do you make money?

Web Scraping How To

The most common way of making money from a price comparison site is to become an affiliate partner and get referral commission for each sale that originates from your website. These commission ranges from 2-10% depending on the merchant

Tips to building a successful price comparison website

1. Pick a niche

Comparison sites are no longer a secret as many people have made a successful business using this business model. Hence they are already many very good and established price comparison websites. The trick is to always start with a niche, focusing an audience to a very niche market is an excellent way of attracting a specific group.

2. Identify all the websites that you want to aggregate products from

Make a list of all these websites and identify of all the products you would want to aggregate. Research all the individual websites to understand if they have a data feed, how often prices are updated and if they offer a commision for promoting their products

3. Identify all your data sources

This is always the hardest and most challenging part of the process. These are the options you will have

• Direct Feed from merchants : As traffic from price comparison sites are a great source of revenue for eCommerce merchants, some big websites will agree to do partnerships with comparison sites and provide them a feed directly via an API for a premium charge. The cons of this are sometimes getting real-time data isnt possible as you are at the mercy of the merchant
• Product feeds from third-party API : A few companies have gone through the trouble of aggregating data from different merchants and supply that feed to interested parties for a premium fee. If you have a big budget this would be the quickest way to get to market without development. A typical example of this would be an Affiliate network
• Web Scraping: This is the cheapest and gives you most control especially if you are just starting up and money is a limitation. You can either write custom code or use a web scraping tool or service to build a web scraper that will extract your data requirements. You will also have flexibilty to make changes or add/remove more data

4. Identify features and data enrichment

Now you have all you data, you have to come up with an experience that can help users shop better than just presenting all the options on a simple table. Features could include price alerts, price history, search filters or aggregated reviews

Data enrichment is another way of providing additional value to users , this could include adding calculated fields like average price, price history, price trends and scores

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But how can WebAutomation.io help?

webautomation.io scrapers employ data extractors to obtain product data from relevant sites, and the extracted data matches your requirements. A better alternative to building your web scraper, this scraper tailors extracted data to your needs or the needs of your visitors. The price comparison website must present quality and reliable data, enforcing the need to use an up-to-date scraper which extracts data in real-time. And because managing the site itself is quite cumbersome, it makes more sense to use a webautomation.io scraper.

The process begins with deploying crawling bots to relevant sites to extract essential parameters, after which extracted data is carefully formatted into readable data and sorted accordingly. The final process involves the storage of data to make it available to visitors on the website. Fortunately, the scraper is built in such a way that it tracks price changes in real-time, helping you to update the dataset on your site regularly.

Price comparison websites use similar methods as retailers use to monitor the prices of their competitors. A win-win for customers and business owners, price comparison websites present a number of benefits. Customers will enjoy a smoother shopping experience, endless varieties of products, broader coverage on e-commerce sites, and repeated shopping deals. Meanwhile, business owners generate more leads, earn better conversion rates, and incorporate better customer service in their business.

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