25 Web Scraping Project Ideas (Beginner to Advanced)

Most lists of web scraping project ideas send you to Amazon, Zillow, or Instagram in paragraph three and never mention those sites wall anonymous scrapers. That is a bad first week. Every project below names a data source I checked from this machine today, a definition of done, and the trap that usually kills it, so you build the skill instead of a 403 collection.

How these web scraping project ideas are ranked

By the new concept each project introduces, not by lines of code. Tier 1 is static HTML with requests plus BeautifulSoup. Tier 2 adds one hard thing per project: state, logins, JavaScript, structured data. Tier 3 is scale, politeness, and monitoring. Ground rules for all 25: check robots.txt, set a real User-Agent, rate-limit to roughly one request per second, and never republish personal data. Where a site’s terms matter, I say so in the entry.

#	Project	New skill	Source
1	Quote collector with pagination	The pagination loop	quotes.toscrape.com
2	Book catalogue to typed CSV	CSS selectors + parsing	books.toscrape.com
3	Country table with an integrity check	Detecting silent failure	scrapethissite.com
4	Hacker News front page two ways	HTML vs API	news.ycombinator.com
5	Wikipedia GDP table to pandas	Table cleanup	en.wikipedia.org
6	GitHub repo stats watcher	Rate limits + conditional GET	api.github.com
7	RSS headline aggregator	XML + dedupe	BBC, Guardian feeds
8	Weather snapshot via Open-Meteo	When NOT to scrape	api.open-meteo.com
9	A price tracker you can legally finish	Snapshots + deltas	books.toscrape.com
10	Page-change monitor	Diffing + notifications	any changelog page
11	Login-gated scrape	Sessions + cookies	quotes.toscrape.com/login
12	JavaScript-rendered page	Headless browsers	quotes.toscrape.com/js
13	Job board from ATS JSON	Finding the feed first	api.ashbyhq.com
14	JSON-LD event finder	Structured data	pages that embed schema.org
15	News sentiment tracker	Text pipeline + a chart	the idea-7 feeds
16	Scoped site crawler	Scope + robots discipline	a small site you pick
17	Sports stats pipeline	Cleaning + joins	scrapethissite.com
18	Polite crawler from scratch	robots.txt + backoff	any open directory
19	Reddit sentiment via OAuth	OAuth2 + quota budgets	reddit.com OAuth API
20	SERP position tracker	Careful scraping of a picky site	html.duckduckgo.com
21	Selector-health monitor	Detecting your own rot	your ideas 1–9 output
22	LLM schema extraction, cost-capped	Structured LLM output	cleaned markdown
23	Two-worker crawl queue	Concurrency without hammering	your idea-16 crawler
24	Fingerprint lab	Why you got 403’d	httpbin.org, tls.peet.ws
25	Publish a documented dataset	Provenance + licensing	your choice, end to end

Tier 1: Beginner (static HTML)

1. Quote collector with pagination

Pull text, author, and tags from quotes.toscrape.com, ten quotes per page, and loop /page/N/ until the data runs out. The trap is the ending: page 11 returns HTTP 200 with “No quotes found”, not a 404. A loop that stops on error status runs forever. Stop on an empty result set instead.

Done: quotes.csv with exactly 100 rows (10 pages × 10).

2. Book catalogue to typed CSV

books.toscrape.com serves 50 pages of 20 books, each with title, price, rating, and stock text. Parse "£51.77" into a float and "In stock (22 available)" into an integer, because a CSV of strings is not a dataset. This is the project where CSS selectors become muscle memory.

Done: 1,000 rows, numeric columns that sum correctly, no £ left in the price column.

3. Country table with an integrity check

The countries page at scrapethissite.com paginates with ?page=N, but only in JavaScript. Request it without a browser and ?page is silently ignored, so a naive loop saves page 1 ten times and reports success. I like this project precisely because it teaches the paranoia that separates a toy from a tool.

Done: a script that fails loudly when row counts don’t grow with pages, or duplicates exceed zero.

4. Hacker News front page two ways

Build the same 30-story list twice: once by parsing the HTML table at news.ycombinator.com, once from the keyless Algolia API at hn.algolia.com/api/v1/search?tags=front_page. Both worked when I tested them today, no account needed. The lesson is route selection: when a site offers JSON, parsing its HTML is unpaid labor.

Done: both outputs matching on rank, title, and points for 30 stories.

5. Wikipedia GDP table to pandas

pandas.read_html() on the “List of countries by GDP (nominal)” page gets you a DataFrame in one line, then the real work starts: citation markers like [a] inside cells, a rank column you don’t need, and numbers stored as text. Clean until float("9.18") works on every row of the IMF column.

Done: a DataFrame with a numeric GDP column and zero NaNs you can’t explain.

6. GitHub repo stats watcher

The GitHub REST API takes keyless requests at 60 per hour, tracked in response headers. Poll stars and open issues for five repos once an hour using conditional requests (send If-None-Match with the stored ETag; a 304 costs nothing). Run it for a day without hitting the limit and you’ve learned quota budgeting, the skill that keeps real scrapers alive.

Done: 24 hourly snapshots per repo, zero 403/429 responses in the log.

7. RSS headline aggregator

BBC (feeds.bbci.co.uk/news/rss.xml) and the Guardian both publish RSS that is meant to be parsed. Pull five feeds, normalize entries to one schema (title, link, published, source), and dedupe on link. XML namespaces will fight you on the first feed; that fight is the curriculum. See what an RSS feed is if the format is new.

Done: one deduped JSON file holding each feed’s latest 10 items.

8. Weather snapshot via Open-Meteo

Open-Meteo serves forecasts keyless and free for non-commercial use, so the honest project is deciding not to scrape. Hit api.open-meteo.com for your city on a cron, append one JSON line per day, and note that the data is better than anything you’d have scraped. Knowing when a site has already done the work for you is a scraping skill too.

Done: a cron entry that has survived a week, one line per day, schema stable.

Tier 2: Intermediate (one hard thing each)

9. A price tracker you can legally finish

The internet’s favorite scraping project is an Amazon price tracker, and the trap is that Amazon gates prices behind session signals. I checked today: a complete 1.4 MB product page rendered zero .a-price elements for a plain client, and extraction that does get through drops the currency ({"amount": 1540.45} from a baht page; never read it as dollars). Build the identical skill set on books.toscrape instead: snapshot 1,000 prices nightly, store history in SQLite, alert on a 10% drop.

Done: a price history table and one alert you triggered by editing a fixture.

10. Page-change monitor

Pick a page you’re allowed to watch, like a tool’s changelog. Fetch, clean to text, hash, and store the hash; on change, store the new version and notify yourself. The engineering is normalization: timestamps, ads, and whitespace cause false positives until you diff cleaned text, not raw HTML. This is the core of competitor website monitoring, and building a small one teaches why that whole product category exists.

Done: two notified changes, both caused by you editing the page or a fixture.

11. Login-gated scrape

quotes.toscrape.com ships a practice login: a form with a CSRF token, then session cookies on a redirect. Log in with a requests.Session, keep the cookie jar, and scrape the quotes that only appear logged in. Compare the cleaned word count logged-in versus anonymous and you’ll see why content behind a login often measures differently; my authenticated run cleaned to 176 words against the anonymous page’s 210.

Done: the authenticated page scraped twice with one session, no second login.

12. JavaScript-rendered page

quotes.toscrape.com/js serves an HTML shell with zero quote elements in the source; a browser builds the DOM. Run it through a headless browser, wait for the .quote selector, then extract. Feel the cost too: the same fetch that took milliseconds in idea 1 now boots a browser. Start with what a headless browser is, and learn the wait-for-selector reflex before you need it on a real site.

Done: the same CSV schema as idea 1, produced from the JS site, with the wait recorded in a comment.

13. Job board from ATS JSON

Before scraping any job board’s HTML, look for the feed. Ashby, a common applicant-tracking system, exposes public listings keyless at api.ashbyhq.com/posting-api/job-board/<org>. I pulled a live board today and got clean JSON. Not every company keeps its feed open (Greenhouse boards I tried today 404’d), so the discovery step is the project: five companies, feed or HTML, your choice documented per company.

Done: one deduped jobs.json across five orgs, with a note of which came from a feed.

14. JSON-LD event finder

Thousands of pages embed JSON-LD, a script type="application/ld+json" block describing the page in schema.org vocabulary. Collect event pages from five local venues or city calendars, extract every Event object, and keep name, startDate, and location. You parse structured JSON instead of styling-sensitive HTML, which is why this technique survives redesigns that break every CSS selector.

Done: events.json with at least 20 events, dates parsed to ISO 8601.

15. News sentiment tracker

Reuse idea 7’s aggregator, score each headline with VADER (vaderSentiment, v3.3.2, runs offline), and plot the daily mean per source for a week. The hard part is not the model, it’s the pipeline: dedupe, normalize, score, aggregate, plot, without hand-editing anything. When two outlets’ lines diverge, you’ll want a method note, so write one.

Done: a 7-day chart plus a README paragraph explaining exactly what VADER measures.

16. Scoped site crawler

Crawl a small site within rules you set: same domain only, depth 2, 50-page cap, robots respected. Off-domain leakage is the classic failure: a crawl I ran of bbc.com content followed links into bbc.co.uk/food, a different host wearing a familiar name. Validate the domain of every URL before fetching, not after.

Done: a URL inventory that stayed inside the cap with zero off-domain fetches. The vocabulary is covered in what a web crawler is.

17. Sports stats pipeline

scrapethissite.com publishes fantasy hockey standings that are meant to be collected. Scrape two related tables, join them on team, clean the junk columns, and produce one chart that answers a question (“do penalties correlate with losses?”). This is the first project where the scraping is easy and the data work is the point, which is a realistic ratio.

Done: one chart plus a README note on every cleaning decision you made.

Tier 3: Advanced (scale, politeness, survival)

18. Polite crawler from scratch

No frameworks: parse robots.txt yourself, build a per-host token bucket at one request per second, set an honest User-Agent with contact info, and back off exponentially on 429 and 503. Decide deliberately what to do when robots.txt itself fails to load. 4xx and 5xx mean different things, and treating a server error as permission is how incidents happen. The ethics and mechanics are both covered in web scraping bots.

Done: a 500-page crawl of an open directory with a log showing zero rule violations.

19. Reddit sentiment via OAuth

Anonymous Reddit JSON endpoints now redirect to a locale stub instead of data (I watched it happen from this machine this month), so the honest path is the official OAuth API: register an app, use client credentials, and stay near the free tier’s roughly 100 requests per minute. Budget your quota in code, not in hope. Pull a subreddit’s last 1,000 comments and score them.

Done: 1,000 comments in JSON, zero 429s, token refresh handled.

20. SERP position tracker

Track where one domain ranks for ten queries using DuckDuckGo’s HTML endpoint (html.duckduckgo.com/html/?q=...), which answered plain requests when I tested it today. This site type punishes greed, so run one query per minute, from one machine, for your own keywords only, and read the ToS first. The constraints are the curriculum: scrapers that survive are the ones that never need to be fast.

Done: a daily CSV of positions for ten queries, collected for a week, no anomaly pages.

21. Selector-health monitor

Your scrapers from ideas 1–9 are now liabilities: sites redesign, selectors return null, pipelines silently emit empty files. Build the fix: a nightly replay against saved fixtures plus live pages, alerting when any selector’s null rate jumps. This idea, monitoring your own extraction, is rarer in portfolios than it is in production, which is exactly why it stands out in an interview.

Done: an alert that fired when you deliberately changed a fixture or a selector.

22. LLM schema extraction, cost-capped

Take 100 pages you already scrape cleanly, send their markdown to an LLM with a JSON schema, and grade the output field-by-field against your selector-based ground truth. The comparison — cost per 100 pages, accuracy per field, failure modes — is worth more than either pipeline alone. The trade-offs are laid out in LLM extraction vs CSS selectors; build the numbers yourself.

Done: one table comparing cost and accuracy for both methods on the same 100 pages.

23. Two-worker crawl queue

Run your idea-16 crawler from two processes against one SQLite queue with per-host locks and retry-with-backoff. The failure modes are the lesson: duplicate work, deadlocks on the same host, a worker dying mid-batch. Finish with two processes completing a 200-page crawl in under half the single-worker time and zero duplicate pages.

Done: a run log showing both workers, no duplicate URLs fetched, total time halved.

24. Fingerprint lab

When a site returns 403 to your script but loads in a browser, the site fingerprinted you. Build a lab: send requests to httpbin.org/headers and tls.peet.ws from requests, curl_cffi, and a real browser, then compare what each reveals about header order and TLS handshake shape. You’re learning why blocks happen, not how to defeat them; CAPTCHAs and bot walls are out of scope for a reason.

Done: a table of which client fails which check, with the offending signal named.

25. Publish a documented dataset

Capstone: collect a dataset nobody has published, from sources with clear rights, and ship it on Kaggle or Hugging Face with a data card covering provenance, collection dates, method, per-source license, and known gaps. Twenty-four projects made you capable; this one makes you accountable, because a stranger will try to reproduce your work and their only documentation is yours.

Done: a published dataset page whose method section would let someone re-run it.

A note on tools

I built most of these with requests and BeautifulSoup, and you should too, at least once. When I want a first pass without writing the script first, I run Magpie, a local Go CLI (AGPL-3.0-or-later or commercial): it handles fetch, clean, and extract, respects robots.txt, and does ideas 9–12 and 16–18 out of the box. It hits the same walls as your code will (no Amazon prices, no anonymous Reddit) because those are the sites’ rules, not the tool’s.

FAQ

What is a good first web scraping project? Project 1 or 2. Both run against practice sites built for scraping, so nothing blocks you while you learn the fetch-parse-store loop. Finishing either in an afternoon is realistic, and both produce a CSV you can show.

Are these web scraping projects legal? Scraping public data for personal learning is broadly tolerated, but legality depends on jurisdiction, the site’s terms, and what you collect. Stay on public pages, respect robots.txt, avoid personal data, and never republish. When money is involved, get advice.

What should a web scraping portfolio project include? A README with the method, the source and its terms, a schema, provenance dates, known limitations, and one chart or table that answers a question. Interviewers trust projects that admit their limits more than ones that claim perfection.

Do I need Python for these web scraping project ideas? No. The tiers track concepts, which transfer to any stack: JavaScript with Playwright and cheerio, or Go with colly, cover all 25. Python’s advantage is the shortest path from idea to working code, not a capability edge.

How do I know if a site will block my scraper? Check robots.txt, try one polite request with a browser-like User-Agent, and look for a public API first. Big e-commerce, social, and travel portals block by default, which is why every source in this list is open to anonymous readers.

Where to start

Start tonight with idea 1; it takes an afternoon and ends with 100 rows of real data. When you outgrow the practice sites, the best sites to practice on lists more sources that welcome scrapers, and open-source scraping tools shows what to graduate to. Pick project 25 within three months; a published dataset is the difference between “I did tutorials” and “I built this.”