About this listing
Scrapers built for real sites, not demos
Production-ready data extraction tools are built in Python or Node.js for product catalogues, directories, marketplaces and dynamic single-page applications. Output arrives as CSV, JSON, or written straight into your database.
What is covered
- Single-page extraction with fields mapped to your specification
- Multi-page crawling across pagination, categories or sitemaps
- JavaScript-rendered pages handled with Puppeteer, Playwright or Selenium
- Session handling, cookies and form submission for login-gated content
- Anti-bot measures: rotating user agents, proxy rotation, request throttling, header variation
- CAPTCHA-aware flows, either manual-solve or a third-party solver
- Respect for crawl delays, with backoff on 403, 429 and 503 responses, plus concurrency tuning
- Data cleaning: deduplication, normalisation, field mapping, date and price parsing
- Delivery to CSV, JSON, Excel, Google Sheets, PostgreSQL, MySQL, MongoDB or Airtable
- Scheduled runs via cron, GitHub Actions or cloud functions
- Change detection flagging new, updated or removed records between runs
- Structured error logging with retry queues and dead-letter handling
Why it holds up
Many scrapers work once in testing and fail the moment a site changes its markup, blocks a user agent, or adds new protection layers. Builds rely on resilient selectors, retry logic, proxy fallback and clear logging, so when a selector breaks or a page returns an error instead of data, you see exactly which records failed and why, rather than getting silent empty rows.
Tools used
Python (BeautifulSoup, Scrapy, Playwright, Selenium, Requests) and Node.js (Puppeteer, Cheerio, Playwright, Axios) for scraping; rotating proxies and user-agent rotation plus headless browser fingerprinting for anti-bot work; storage across CSV, JSON, Excel, Google Sheets, PostgreSQL, MySQL, MongoDB, SQLite and Airtable; scheduling through cron, GitHub Actions, AWS Lambda, Vercel Cron or Railway; infrastructure on Docker, VPS providers, AWS or Render.
Testing before handoff
Each build runs a dry pass on a small sample first, then a full run with a success and failure summary. Output is checked against the expected schema, with missing fields, duplicate rows and parse errors flagged before delivery.
Ownership
Source code and scraper credentials pass fully to you on final delivery. A non-disclosure agreement is available on request for sensitive or competitive data projects.
Timelines
Basic ships in 2 to 3 days, Standard in 5 to 7 days, and Premium in 10 days.
What is needed from you
- The target URL or site to scrape
- The exact fields required, such as names, prices, URLs or images
- Your preferred output format: CSV, JSON, Google Sheets or database
- Whether this is a one-off scrape or a recurring job
Send over the target site and field list, and a working preview scraper can be ready within 48 hours, before any payment is required, so you can see real extracted data from your own target first.