Web Scraping Project Ideas (With Practice Sites)

I have built dozens of scrapers, and the ones that taught me the most were small projects with a clear finish line. A good project gives you a target to hit and one new skill to learn. A bad one is vague (“scrape the web”) or points at a site that blocks you on request three, so you spend the whole evening fighting captchas instead of writing parsing logic.

This article lists 15 web scraping projects grouped by skill level. Each one names the target type and the specific skill it teaches. I also list the practice sites I use, all of which stay up and none of which block you. Start at your level, finish the project, then move up one tier.

What makes a good web scraping project?

A good web scraping project has a clear target, one new skill, and a way to check you got everything. The target is a specific site and a specific dataset, not “product data.” The new skill is one technique you have not used yet, like pagination or handling JavaScript. The check is a known number you can verify against, so you know your scraper is complete.

I rank projects by three things:

A beginner project is easy on all three. An advanced project is hard on all three at once. The sections below sort 15 ideas along that line.

Which web scraping projects suit my skill level?

Match the project to your level using the table below. Beginner projects scrape one static page. Intermediate projects add pagination, multiple pages, and structured export. Advanced projects deal with JavaScript rendering, login, and scale.

If you are new, read my beginner web scraping guide first, then start at project 1. The BeautifulSoup guide covers the parsing you need for projects 1 to 10.

What are good beginner web scraping projects?

Good beginner projects scrape one static page where the data sits in the HTML you get back. No JavaScript, no login, no pagination. You learn to fetch a page and pull values out of it.

Start with these five:

• Quote collector to CSV. Scrape every quote, author, and tag from the front page of quotes.toscrape.com and write them to a CSV. You learn element selection and file output. The page is clean HTML, so your selectors work on the first try.
• Book catalog price list. Pull the title and price of every book on the first page of books.toscrape.com. You learn to loop over repeated cards and extract two fields per card.
• Wikipedia table to spreadsheet. Grab a <table> from a Wikipedia article (list of countries by population is a good one) and save it as rows. You learn to read table headers and cells. See my Wikipedia scraping guide for the exact selectors.
• Country facts extractor. From a single reference page, pull named fields like capital, area, and currency by their label. You learn to target a value by the text next to it.
• Hacker News front page. Scrape the title, link, and points for each story on news.ycombinator.com. You learn to handle a list where each item spans two table rows.

Each of these took me under an hour the first time. The win is a working scraper end to end: fetch, parse, save.

What are good intermediate web scraping projects?

Good intermediate projects add pagination, multiple linked pages, and structured storage. The data no longer fits on one page, so your scraper has to navigate.

These five build that muscle:

• Multi-page book scraper. Scrape all 1000 books across the 50 pages of books.toscrape.com by following the “next” button. You learn pagination and when to stop. There are exactly 1000 books, so you can verify your count.
• Quotes by author and tags. Start on the quotes list, follow each author link to their bio page, and collect both. You learn to crawl from a list into detail pages and join the data.
• Job board snapshot. Take a daily snapshot of a job listing site, store each role once, and normalize fields like location and date. You learn deduping and scheduling reruns.
• Price tracker over time. Run the book scraper daily, store each run, and report which prices changed. You learn snapshotting and diffing across runs.
• Wikipedia category crawler. Start at one article and follow links to related articles, keeping a visited set so you do not loop. You learn recursive crawling with a frontier and a seen list.

For multi-page crawling at this level, a framework helps. My Scrapy guide shows how its built-in request queue handles pagination and link-following for projects 6, 7, and 10.

What are good advanced web scraping projects?

Good advanced projects deal with JavaScript rendering, authentication, and scale. The data is not in the initial HTML, sits behind a login, or lives across many sites you have to hit reliably.

These five are the hard tier:

• Infinite-scroll quote scraper. quotes.toscrape.com/scroll loads quotes as you scroll. Open the network tab, find the JSON request it fires, and call that directly. You learn to read the API behind a page instead of rendering it.
• JS-rendered content scraper. quotes.toscrape.com/js builds its content with JavaScript, so a plain request returns an empty shell. Drive a headless browser and wait for the elements to appear. You learn browser automation.
• Login-gated scraper. quotes.toscrape.com/login sits behind a login form with a CSRF token. Log in, keep the session, and scrape the page that requires it. You learn cookies, sessions, and hidden form fields.
• API-first data pipeline. Skip HTML and pull from a public JSON API. You learn pagination by query parameter, rate-limit handling, and retries. Good practice targets are below.
• Multi-site monitor at scale. Monitor several real sites at once, running often enough that a single IP gets rate-limited or blocked. You learn concurrency, error handling, and when to route through proxies or a scraper API.

That last project is where most beginners hit a wall. Real sites block repeated requests from one IP, throw captchas, and serve JavaScript-only pages. This is the point where a scraper API earns its place. Services in this category, like ChocoData, expose a universal endpoint plus hundreds of dedicated endpoints that handle IP rotation, browser rendering, and retries for you, so your code stays a simple request-and-parse loop even when the target fights back. You reach for that tier when scale or blocking makes do-it-yourself proxies the bottleneck, not before.

Which practice sites are safe to scrape?

The safest practice sites are ones built for scraping or explicitly open to it. They stay up, return predictable HTML, and never block you, so you can focus on technique. Here are the ones I use, with what each is good for.

The whole toscrape.com family was built by Zyte to practice on, which is why those URLs are the standard sandbox. I confirmed quotes.toscrape.com and books.toscrape.com were both live and serving their usual HTML on June 12, 2026.

For the API-first project, these public APIs return JSON, need no key for basic use, and are fine to hit while you learn:

• REST Countries (restcountries.com) returns country data as JSON. Good for project 4 without parsing HTML.
• Open Library (openlibrary.org/developers/api) returns book and author records.
• Hacker News API (github.com/HackerNews/API) returns items and lists as JSON, a clean alternative to scraping the HTML front page.
• GitHub REST API (docs.github.com/rest) returns repository and user data; mind the unauthenticated rate limit.

Read each API’s docs for its rate limit before you loop. The official docs are the only source I trust for current limits, since they change.

How do I pick the right tools for a project?

Pick tools by what the target throws at you. Static HTML needs a fetcher and a parser. JavaScript needs a browser engine. Many pages need a crawling framework. Scale and blocks need proxies or a scraper API.

This maps tools to the project tiers above:

For selecting elements, learn both CSS selectors and XPath; my XPath and CSS selectors guide covers when each wins. For one-off requests and inspecting what a server returns, curl is the fastest way to see the raw response before you write any parsing code.

The Python path covers most of these projects. My BeautifulSoup guide handles parsing for the beginner and intermediate tiers, and the Scrapy guide handles crawling for the multi-page projects. Start on the practice sites, hit your known-count check, then point the same code at a real target.

Where should I start?

Start with project 1, the quote collector, on quotes.toscrape.com. The HTML is clean, there are a fixed number of quotes, and you get a full fetch-parse-save loop in under an hour. Then work down the table one project at a time. Each row adds exactly one new skill, so by project 15 you have a complete scraping stack instead of fifteen copies of the same single-page scrape.

For the full walkthrough of the tools and concepts behind these projects, the web scraping pillar guide is the place to go next.