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real-estate · May 30, 2026 · 6 min read

How to Scrape Spitogatos.gr Greece Property Listings in 2026

A practical guide to extracting Greek real estate listings from Spitogatos.gr — price, €/m², coordinates, agency and images — past F5/Reese84 anti-bot protection.

Spitogatos.gr is Greece’s number-one property portal — the place where apartments in Athens, holiday homes on the islands, and commercial space in Thessaloniki actually get listed. For market research, investment analysis, or agency monitoring, it’s the canonical Greek real estate dataset. It’s also wrapped in one of the more serious anti-bot stacks you’ll meet outside of travel: an F5/Reese84 (formerly Distil) enterprise defense that kills naive requests instantly. This guide covers what’s worth extracting, why a simple HTTP request gets nowhere, and the browser-session approach that actually works.

What’s worth extracting

Spitogatos is a single-page app backed by a search API that both the map view and the list view consume. Once you can reach that API, each listing yields a rich record:

  • Identity — unique listing ID, canonical detail URL.
  • Type — apartment, house, studio, commercial, or land; rent vs. sale classification; subtype.
  • Pricing — numeric price, currency, and the all-important price per square meter.
  • Size — area in m², number of rooms, floor, facility/room counts.
  • Geography — neighborhood and region labels, latitude/longitude, plus an indicator of whether the coordinates are exact or deliberately randomized.
  • Media — image lists and counts, with CDN URLs reconstructed at multiple resolutions.
  • Provenance — agency/agent identifiers, advertising type markers, and upload/modified/published timestamps.

The €/m² field and the exact-vs-randomized geocode flag are the two that make this dataset analytically useful — they’re what let you build neighborhood heatmaps and yield models rather than just a list of ads.

Why a plain request fails

Try curl https://www.spitogatos.gr/... and you’ll get a challenge page, not data. Spitogatos runs F5/Reese84, an enterprise bot-defense layer that validates a multi-signal session before serving any real content:

  • TLS/JA3 fingerprint — generic HTTP clients don’t look like Chrome and are rejected.
  • A reese84 session token — minted only after the client executes JavaScript and exhibits believable behavioral signals (mouse movement, scroll, network-idle timing).
  • IP reputation — datacenter IPs are guilty by default; Greek residential IPs are trusted.
  • Cookie + fingerprint + IP cohesion — the token, cookies, TLS fingerprint, and IP must all agree across requests, or the session is invalidated.

You can’t forge a reese84 token from a script. The defense is specifically designed to require a real browser doing real-looking things.

The approach that works

The reliable pattern is a browser-context warm-up, then in-page fetch:

  1. Launch a real Chromium browser (Playwright) on a sticky residential Greek IP.
  2. Load the search page and warm the SPA — let it execute JS, generate mouse/scroll/network-idle behavioral signals, and mint a valid reese84 session token.
  3. Issue the search-API calls from inside the page’s own fetch context, so they reuse the exact same TLS fingerprint, cookies, and IP the token was bound to.
  4. The API returns geohash-clustered JSON (the map view groups listings spatially); flatten the clusters, dedupe, and paginate by offset until your limit or area coverage is reached.
  5. Reconstruct the image CDN URLs at the resolutions you want.

This is meaningfully harder than the no-browser JSON scrapers in this catalog — it’s closer to the Booking.com class of problem. The session warm-up, the sticky-IP cohesion, and the geohash flattening are exactly the parts that are tedious to build and brittle to maintain as the defense updates.

Run the Spitogatos.gr Real Estate Scraper — extracts Greek property listings (rent or sale) by area and price with €/m², lat/lng, agency and images. Bypasses F5/Reese84 automatically via a warmed browser session on a sticky Greek residential IP.

Schema design for downstream use

A clean per-listing record:

{
  "listing_id": "1357924680",
  "url": "https://www.spitogatos.gr/en/property/1357924680",
  "title": "2-bedroom apartment in Koukaki",
  "type": "apartment",
  "subtype": "maisonette",
  "transaction": "sale",
  "price": 285000,
  "currency": "EUR",
  "price_per_sqm": 3958,
  "area_sqm": 72,
  "rooms": 3,
  "floor": 4,
  "neighborhood": "Koukaki",
  "region": "Athens - Center",
  "lat": 37.963,
  "lng": 23.726,
  "geocode_exact": false,
  "image_count": 18,
  "images": ["https://cdn.spitogatos.gr/.../1.jpg"],
  "agency_id": "agm-4821",
  "uploaded_at": "2026-05-18T10:00:00Z",
  "modified_at": "2026-05-27T08:30:00Z",
  "scraped_at": "2026-05-30T12:00:00Z"
}

Choices worth making early:

  • Store price_per_sqm as its own field. Don’t recompute it downstream — the portal’s own figure is the comparable, and rounding differences will haunt you.
  • Keep geocode_exact. Randomized coordinates are common for privacy; treating them as exact will smear your heatmaps. Filter on exactness when geography matters.
  • Separate transaction (rent/sale) cleanly. Mixing rent and sale prices in one analysis is the single most common Greek-market analytics mistake.
  • Stamp modified_at and scraped_at. Together they power price-reduction tracking and time-on-market.

Typical use cases

  • Market research — rent prices by neighborhood, €/m² heatmaps across Athens and Thessaloniki, time-on-market trends.
  • Investment analysis — combine sale and rent data per area to estimate gross rental yields.
  • Real estate analytics — geo-cluster listings by lat/lng and filter to exact-geocode records for precise mapping.
  • Agency monitoring — track a competitor agency’s live inventory by agency/agent identifier.
  • Price tracking — periodic re-runs to detect price changes and reductions on the same listing.
  • Lead generation — surface active agencies operating in a target area and category.

The common thread is comparability over time: a one-off scrape gives you a snapshot, but the value compounds when you re-run weekly and watch prices and inventory move.

Cost math

This actor prices with a tiny per-run start fee and effectively free per-result extraction. The real cost driver is the browser session and the Greek residential proxy the bypass depends on. Even so, a realistic research pull — a few thousand Athens listings, refreshed weekly — lands in the low single digits of dollars per month, and a first exploratory run fits inside Apify’s free monthly credit.

Building it yourself means owning the entire F5/Reese84 fight:

  • A sticky Greek residential proxy pool (the geo requirement narrows your options and raises the price).
  • A Playwright warm-up routine that reliably mints a valid reese84 token, plus re-warming when sessions expire.
  • Geohash-cluster flattening and offset pagination.
  • Ongoing maintenance every time the anti-bot vendor ships an update — which for enterprise defenses is regularly.

The maintenance is the real cost. Reese84 is not a “write once” target.

Common pitfalls

  • Datacenter IPs. Non-Greek or datacenter IPs fail the reputation check before the token even matters. The IP geography is part of the defense.
  • Out-of-context API calls. Minting a token in the browser then replaying the API call from a separate HTTP client breaks fingerprint cohesion and gets you challenged. The fetch must come from inside the page.
  • Trusting all coordinates. Many listings randomize lat/lng for privacy. Honor geocode_exact.
  • Mixing rent and sale. Always partition by transaction before computing any €/m² statistics.
  • Currency assumptions. Prices are in EUR, but always read the field rather than hardcoding it.
  • Aggressive pacing. Even with a valid session, hammering the search API re-triggers the defense. Polite offset pagination keeps the session alive.

Wrapping up

Spitogatos has the data that matters for the Greek property market — €/m², coordinates, agency, freshness — but it sits behind a real enterprise anti-bot wall that punishes the naive approach instantly. The winning pattern (warm a real browser on a sticky Greek residential IP, then fetch in-context) is solvable but genuinely high-maintenance. For a one-off study you can grind through it; for a recurring market feed, a managed actor that already keeps the Reese84 bypass green is the saner path.

Open the Spitogatos.gr scraper on Apify — production Greek real estate data with €/m², geocodes, agency and images. F5/Reese84 bypass included. Pay per result. Start with Apify’s free monthly credit.

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