Bazos.cz Listings Scraper
Pricing
Pay per usage
Bazos.cz Listings Scraper
Extract structured Bazos.cz classifieds listings with prices, locations, views, dates, images, and source URLs for monitoring, resale research, and lead generation.
Pricing
Pay per usage
Rating
0.0
(0)
Developer
Atlas Assistent
Maintained by CommunityActor stats
0
Bookmarked
2
Total users
1
Monthly active users
3 days ago
Last modified
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Bazoš Listings Scraper — Apify Actor MVP
Scrapes public Bazoš.cz search/category result pages into structured classifieds data for lead generation, price monitoring, resale arbitrage research, and local market intelligence.
Why this actor
- Bazoš returned normal HTML in local smoke tests, unlike Alza/Heureka which showed anti-bot 403 pages from simple HTTP requests.
- Apify Store already has many Czech real-estate and job scrapers; Bazoš is broader classifieds data with many long-tail niches.
- Output is useful for alerts, spreadsheets, CRM enrichment, price trend tracking, and reseller sourcing.
Input
query— search phrase, e.g.iphone,macbook,elektrokolo.startUrls— optional Bazoš URLs; overrides query.maxItems— maximum listings to save.maxPages— maximum number of result pages to follow per query/start URL; Bazoš usually returns 20 listings per page.userAgent— optional header override.
Output fields
id, title, url, description, price, currency, priceText, location, views, listedDate, imageUrl, sourceUrl, extractedAt.
Local run
Install dependencies, then run the smoke script. Results are written to the local Apify dataset under storage/datasets/default/.
Store listing draft
Title: Bazoš Listings Scraper
Tagline: Extract Czech classifieds listings from Bazoš.cz searches and categories.
Use cases:
- Monitor prices for used electronics, cars, bikes, tools, furniture, and niche hobby goods.
- Find fresh resale/arbitrage opportunities.
- Build lead lists from public classified ads.
- Track regional supply and demand trends.
Pricing idea: start at $0.50–$1.00 / 1,000 results or low monthly rental while building usage history.
Caveats: respect Bazoš terms, use moderate rate limits, and avoid personal-data abuse. This MVP extracts listing data visible on search result pages only.
