7 Python Web Scraping Projects: Ideas for Beginners and Advanced Users
If you want to level up your web scraping skills with Python or find inspiration for new business ideas, you’ve come to the right place. We’ve prepared a list of practical Python web scraping projects.
Python is one of the most popular programming languages used by both beginners and advanced users. Web scraping can help you improve your business marketing strategies, give you ideas for investment opportunities, or be a fun and worthwhile project to practice your web scraping skills. And the best part – there are plenty of projects for you to try.
If you’re looking for ways to employ your data collection skills, we’ve listed seven great Python web scraping project ideas.
- Getting Started with Python Web Scraping
- Beginner Web Scraping Project Ideas Using Requests and Beautiful Soup
- Intermediate Web Scraping Project Ideas Using Selenium
- Advanced Web Scraping Project Ideas Using Scrapy
Web scraping with Python is relatively simple compared to alternatives like Java or PHP. It’s an easy to read and understand language, which doesn’t require compiling code. Python has many great tools and web scraping libraries like Requests, Beautiful Soup, or Selenium. What’s more, you’ll find multiple ideas online for Python-based projects and an extensive backlog of step-by-step guides from competitor analysis to investment opportunities.
Today websites apply strict anti-scraping techniques like IP blocks and CAPTCHAs, so without a proxy server, you won’t be able to do much. There are two main types of proxy servers used in web scraping: residential and datacenter. The one you choose depends on your project – some projects need speed, and others – anonymity. You can integrate your proxies with most Python web scraping libraries and frameworks.
If you fall short on web scraping skills, you can give a go at websites designed to practice data gathering and test different Python-based tools. Web scraping sandboxes include static and dynamic data. Beginners can scrape data points like tables and titles, and more advanced users can move to complex tasks like handling logins and sessions, or spoofing headers.
Requests and Beautiful Soup are well known for their easy implementation and use. In scraping, they usually go together – Requests fetches you raw HTML, while Beautiful Soup structures it into a readable format. Both Python web scraping libraries have strong community support that can help you solve any scraping issues along the way.
1. Get the Best Movie Recommendations
Wouldn’t it be nice to have a list of movies by their ratings, genre, or even year? A fun idea is to scrape IMDB – the largest database of movies, TV series, and shows. Find out which movies have the best reviews, and look for hidden gems of your taste by scraping descriptions or the review section. You can even try to create a movie recommendation engine.
A good starting point is to scrape data from one link. Choose the target URL and extract movie ratings with the following details: year, director, and star actors. Save your results to a CSV file, so you’d have the data in rows and columns; this way, you can sort your results.
2. Monitor Cryptocurrency Prices
There’s a lot of information on Bitcoin, Ethereum, Litecoin and other cryptocurrencies that can help you decide whether to purchase, sell, or hold your virtual money. If you want to do thorough research, building a scraper can help.
To get real-time data, you can target sites like CoinMarketCap, CoinBase, CoinGecko, or CoinDesk. These websites include historical data on different currencies from multiple websites. You can get the name, price, and updates every hour, day, or week. This data can be saved as an Excel file where you can easily analyze the results in any suitable format (be it a table or graph).
3. Find Great Hotel Deals
You probably know the hassle of finding the perfect accommodation for your travel – the scrolling can be endless. One of the most popular websites to target is Booking, where you can find thousands of hotels worldwide.
Scraping hotel listings can give you insights into the best hotel deals and competitive landscapes. Let’s say you want to find the best offer for a weekend stay in your chosen location. You can scrape hotel names, prices, availability on preferred dates, ratings, and reviews. If you save the results to a CSV file, you can compare the results by weekends, months or even throughout the year.
4. Get Cheaper Flight Tickets
Many people try to save a buck or two when travelling. And flight ticket prices are notoriously fickle – they can go from tens to hundreds of dollars just in one day. It usually happens at the most inconvenient times too.
One of the most popular websites for scraping flight data is Expedia. The way it works is simple – you add required information and send your crawler to fetch you price, arrival, departure, and other information you need. Wouldn’t it be nice to get an email every hour with the cheapest flight data?
5. Analyse the Job Market
Scraping job sites works for both job seekers and employers. The idea behind that is to scrape job postings for relevant information.
If you’re looking for new job opportunities, you can build a scraper to collect data from job portals like Indeed or Glassdoor. You could collect information such as job title, location, posting date, description, salary range, or skills needed. Then, download your data into an Excel sheet and analyse what skills employees seek or the number of vacancies available in each city.
If you’re running a company, you can gather valuable information about your competition. For example, you can compare the salary range for the same position in your company. Or what benefits they offer by analyzing their job descriptions.
If you’re up for some scraping challenges, try building a web scraper that can navigate through the website and scrape many pages quickly. Python-based framework Scrapy can handle and process requests asynchronously, so you can extract many pages at once. It contains everything you need to crawl, download, and parse the page, but it has a steep learning curve.
6. Collect Online Reviews and Ratings
It doesn’t matter if you’re looking to buy headphones or have a business selling them, collecting reviews and ratings from e-commerce websites such as Amazon or eBay can provide not biased insights from real users.
The idea works for both customers and businesses. I’d recommend scraping Best Buy – it’s less hostile toward bots than other e-commerce giants. You can narrow your scope to 4–5 star reviews based on a particular price range. Or you can scrape product images directly from the users and compare them with advertisement images.
7. Get the Best Discounts when Shopping
Who doesn’t enjoy discounts and special benefits when shopping? And today, you can get better deals online than going into an actual shop. But browsing various sites to see what they offer is a cumbersome task, not to mention that most offers are limited.
Most websites have discounts or promo code information. Web scraping is a faster way to gather such data. You can scrape information like discounted price, brand, category, product description, activation date, and expiration date.
The idea for your project – scrape the front page section of SlickDeals (it has the best deals). Every item on the page includes the product title and image, website, discount and original price, likes, and shipping information. This way, you can monitor which products have the best deals and where you can get them.