Build Wine Website + Data Scraping

We need you to build a website called WineFinder. It will have four main components: Build a scraper that can pull data from [login to view URL] Build a second scraper that can pull data from [login to view URL] Match the wines found from Winecompanion with the auctions found from Langtons Build a website to display the data We need you to complete this using Python/Django/Postgres. Part 1. Scrape [login to view URL] You will need to scrape all of the “Tasting notes” from Winecompanion.com.au. This will need to run about every month, and the entire website won’t need to be scraped, just the new parts. The fields that we need are: Wine Name Winery Region Variety Vintage Rating Drink by Price (not always available, so default to null) Date tasted Alcohol Notes This is the main information we are interested in, but there may be other information that we need. We will let you know once we have confirmed the details of the project. Part 2. Scrape [login to view URL] We need you to scrape the wines that are for auction on Langtons.com.au. This will need to run about every hour, and so should not rescrape the entire website. The fields that we need for each auction are: Auction name Auction ID Auction closing datetime Scraped datetime Winery name Wine name Quantity Estimate cost per bottle (this is a range, we need high and low) Current bid (we will want to store the history of bids for each auction as well) Link to auction And for each wine in each auction we need: Style Size Varietal Vintage Country Classification Appellation Region Link to wine Again, this is the main information we are interested in, but there may be other information that we need. We will let you know once we have confirmed the details of the project. Part 3. Match the tasting notes from [login to view URL] with the wines for auction on [login to view URL] Essentially we want to match the tasting notes that we have from [login to view URL], with the wines that are for sale on Langtons.com.au. This will let us know which wines are worth buying (and which ones we should avoid). We are happy for you to do this match using exact text match, but please make this part easy to change, as we will likely adjust it later on. Part 4. Build a website to display the information The website will need the following pages: Login screen - Just use the standard Django login Auction list page - A simple paginated, sortable list of all the auctions in the database Auction view page - The details of each auction, including the content that was matched with Winecompanion data Django admin interface - Just so we can go in and manually fix any issues without needing to query the DB The website will need to be password protected, just using the standard Django login details is fine. We would also like you to style the front-end with Bootstrap or equivalent. Other notes: We want the scrapers to store all their historical data in the database, so that we can see price history, and, crucially, old auction results We need this built in Python with the Django framework and Postgres as the database This will be running on a Linux server, so please make sure your code is not O/S dependent We will not need you to deploy the software, although we can set up the server and final environment if you’d like it for testing