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Craigslist Scraper

Apify Actor for scraping Craigslist marketplace listings across any city. Uses CheerioCrawler for fast, efficient HTML parsing without a browser.

Features

• Search any Craigslist city by subdomain (newyork, sfbay, chicago, etc.)
• Filter by category, price range, and sort order
• Two modes: quick search results or full detail scraping
• Extracts JSON-LD structured data when available, falls back to HTML parsing
• Detail mode captures: price, description, images, location coordinates, item attributes, post date, and post ID

Input

Example Input

{
"searchQueries":["bicycle","laptop"],
"city":"sfbay",
"category":"sss",
"maxListings":50,
"scrapeDetails":true,
"minPrice":50,
"maxPrice":500
}

Output

Search-only mode (scrapeDetails: false)

{
"title":"Trek Mountain Bike",
"url":"https://sfbay.craigslist.org/sby/bik/d/trek-mountain-bike/123456.html",
"imageUrl":"https://images.craigslist.org/...",
"position":1,
"city":"sfbay",
"searchQuery":"bicycle",
"scrapedAt":"2026-03-17T12:00:00.000Z"
}

Detail mode (scrapeDetails: true)

{
"title":"Trek Mountain Bike",
"url":"https://sfbay.craigslist.org/sby/bik/d/trek-mountain-bike/123456.html",
"price":280,
"currency":"USD",
"description":"Great condition Trek mountain bike, 21 speed...",
"images":["https://images.craigslist.org/..."],
"imageCount":5,
"condition":"excellent",
"make":"Trek",
"model":"Marlin 5",
"attributes":{
"condition":"excellent",
"make":"Trek",
"model":"Marlin 5"
},
"addressLocality":"San Jose",
"addressRegion":"CA",
"latitude":37.3382,
"longitude":-121.8863,
"postedDate":"2026-03-15T10:30:00-0700",
"postId":"7654321",
"searchQuery":"bicycle",
"scrapedAt":"2026-03-17T12:00:00.000Z"
}

Common City Subdomains

How It Works

1. Builds search URLs for each query using the city subdomain and category
2. Parses search results via JSON-LD ItemList schema (300+ items per page)
3. Falls back to HTML parsing (li.cl-static-search-result) if JSON-LD is unavailable
4. Optionally visits each listing detail page for rich data extraction
5. Detail pages are parsed via JSON-LD Product schema with HTML fallback enrichment

Quick Start

$apify run --purge

Deploy to Apify

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Run on Apify

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