reference: BestCarDeal — Craigslist scraping patterns for future marketplace expansion #59

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opened 2026-06-15 12:16:59 -07:00 by pyr0ball · 0 comments

pyr0ball commented

2026-06-15 12:16:59 -07:00

Owner

Source: https://github.com/TheAhmadOsman/BestCarDeal
License: NOT SPECIFIED — reference only, no code reuse
Stack: Python + Flask + D3.js + Jupyter

What it is

Scraped 1.7M Craigslist used car listings, enriched with geo + weather context, built an interactive Flask/D3 pricing analysis app. Five modular components: scraper, Flask app, geo enrichment, weather enrichment, Jupyter analysis notebooks.

Why relevant for Snipe

Snipe currently handles eBay auctions. Future expansion: Craigslist (private party sales, estate liquidations, local lots) is a natural adjacency — especially for ND users who find in-person negotiation stressful and want pricing research beforehand.

What to learn from this project

Craigslist page structure: The scraper reveals what data is available in listing HTML (price, title, location, post date, attributes like mileage/condition).
Geo enrichment: Craigslist listings are inherently local; enriching with metro area data enables region-adjusted pricing comparisons — directly analogous to Snipe's trust-scoring use case.
No anti-bot documentation: Craigslist's scraping terms are restrictive. Any CF implementation needs ToS review and ethical rate-limiting. Treat this scraper as proof-of-concept only.

Action

No code adoption (no license). Study the scraper approach when Craigslist support is scoped for Snipe. File a proper design doc at that time covering ToS, rate-limiting, and robots.txt compliance.

**Source:** https://github.com/TheAhmadOsman/BestCarDeal **License:** NOT SPECIFIED — reference only, no code reuse **Stack:** Python + Flask + D3.js + Jupyter ## What it is Scraped 1.7M Craigslist used car listings, enriched with geo + weather context, built an interactive Flask/D3 pricing analysis app. Five modular components: scraper, Flask app, geo enrichment, weather enrichment, Jupyter analysis notebooks. ## Why relevant for Snipe Snipe currently handles eBay auctions. Future expansion: Craigslist (private party sales, estate liquidations, local lots) is a natural adjacency — especially for ND users who find in-person negotiation stressful and want pricing research beforehand. ## What to learn from this project 1. **Craigslist page structure:** The scraper reveals what data is available in listing HTML (price, title, location, post date, attributes like mileage/condition). 2. **Geo enrichment:** Craigslist listings are inherently local; enriching with metro area data enables region-adjusted pricing comparisons — directly analogous to Snipe's trust-scoring use case. 3. **No anti-bot documentation:** Craigslist's scraping terms are restrictive. Any CF implementation needs ToS review and ethical rate-limiting. Treat this scraper as proof-of-concept only. ## Action No code adoption (no license). Study the scraper approach when Craigslist support is scoped for Snipe. File a proper design doc at that time covering ToS, rate-limiting, and robots.txt compliance.