0-4 yrs
0-4 yrs
20%
20%
5
5
100+
100+
Web Scraping
Web scraping projects split into two categories: building something new or fixing something that stopped working. New builds start with understanding the target sites, their structure, their rate limits, and how often their layout changes. Maintenance work is usually about scrapers that broke because a site redesigned, added bot detection, or changed their DOM structure.
At Essence Solusoft, we provide web scraping in Ruby that will allow organizations to make smarter decisions for their business, simplify market research, reduce costs, and automate large-scale data collection processes much more efficiently than they are currently.
Web scraping
Every scraping project is different because every target site is different. A simple product catalog with static HTML is a different problem than a React SPA behind Cloudflare's bot protection. We scope the work based on your data sources:
Custom Scraper Development
We build scrapers matched to your target sites. Static HTML sites get lightweight Nokogiri-based extractors. JavaScript-rendered pages get headless browser scrapers using Ferrum or Selenium. Sites with authentication get Mechanize-based crawlers that log in, navigate, and extract. Each scraper includes structured error handling, retry logic, and clean data output.
Scheduled Extraction & Data Pipelines
One-time scrapes are useful. Ongoing automated extraction is where the real value is. We build Sidekiq-powered scheduling that runs your scrapers on whatever cadence you need: every hour, daily, or triggered by events. Data flows through cleaning and normalization before landing in your database or being pushed to your API. Deduplication, change detection, and incremental scraping included.
Anti-Detection & Proxy
Management Sites fight scrapers. We plan for that. Rotating residential and datacenter proxies, randomized request timing, browser fingerprint rotation, and CAPTCHA handling for sites that deploy them. We respect robots.txt and rate limits. The goal is reliable, sustainable extraction, not hammering a server until it blocks you.
Scraper Monitoring & Maintenance
Websites change. Your scrapers need to change with them. We monitor extraction jobs for failures, data quality drops, and structural changes on target sites. When something breaks, we fix it. Monthly maintenance retainers cover ongoing selector updates, proxy rotation adjustments, and performance tuning as your data volume grows.
faqs
Everything you need to know before getting started with us. Below are out most common questions we get asked.
What is web scraping and what can it do for my business?
Web scraping is automated data collection from websites. Instead of someone manually visiting sites and copying data into a spreadsheet, a scraper does it programmatically. It fetches web pages, extracts specific data points (prices, product details, contact info, reviews), and stores them in a structured format. Businesses use it for competitor price monitoring, lead generation, market research, product catalog aggregation, and any situation where you need data from the web at a scale that manual collection can't handle.
Why use Ruby for web scraping instead of Python?
Both work fine. Python has more tutorials online because it's the default language for data science. Ruby's advantage is integration: if your application already runs on Rails, building your scrapers in Ruby means they share models, database connections, background job infrastructure, and deployment. No separate Python service to maintain. Ruby's scraping gems (Nokogiri, Ferrum, Mechanize) are mature and well-maintained. The choice usually comes down to what your team already uses.
What Ruby gems do you use for web scraping?
Nokogiri for HTML/XML parsing (CSS and XPath selectors, handles malformed markup). Ferrum for headless Chrome automation when sites render content with JavaScript. Mechanize for sites that require login, session management, or form submission. HTTParty or Faraday for HTTP requests. Sidekiq for background job scheduling. These cover the full range from simple static pages to complex JavaScript-heavy SPAs behind authentication.
How do you handle sites that block scrapers?
Rotating proxy pools (residential and datacenter), randomized request intervals, user-agent rotation, and header variation. For headless browser scrapers, browser fingerprint randomization to avoid bot detection. We also respect rate limits and robots.txt. The approach depends on the target: a government data portal needs different handling than an eCommerce site with aggressive bot protection. We scope the anti-detection strategy before building.
Can you scrape JavaScript-heavy websites (React, Vue, Angular)?
Yes. Sites built with frontend frameworks render content client-side, so standard HTTP requests return empty HTML. We use Ferrum (headless Chrome via Chrome DevTools Protocol) to load the page, wait for JavaScript execution, and extract the rendered content. This handles dynamic loading, infinite scroll, click-to-expand sections, and AJAX-loaded data. It's slower and more resource-intensive than static scraping, so we only use it where necessary.
How do you deliver the scraped data?
Depends on your needs. Common outputs: direct insertion into your PostgreSQL database via ActiveRecord, JSON or CSV files delivered to cloud storage (S3, GCS), API endpoints that your application calls, or real-time webhooks triggered when new data arrives. If your app is Rails, the simplest path is shared database models where scraped data is immediately queryable. We also build admin dashboards for monitoring extraction results.
How do you handle scraper maintenance when target sites change?
Websites redesign and restructure. When that happens, selectors break and scrapers return empty or wrong data. We monitor extraction jobs for data quality signals: record count drops, missing fields, parsing errors. When something breaks, we diagnose whether it's a minor selector change or a full site redesign, and update the scraper accordingly. Maintenance retainers cover this ongoing work.
Is web scraping legal?
Web scraping of publicly available data is generally legal, but the specifics depend on the jurisdiction, the target site's terms of service, and the type of data. We scrape public data, respect robots.txt directives, and avoid extracting personal data without a lawful basis. We don't scrape behind paywalls or bypass access controls. If your use case has legal sensitivity (competitor data in regulated industries, personal data under GDPR), we recommend getting legal advice specific to your situation before starting.