We extract freelancer profiles, project listings, hourly offers, pricing tiers, and review histories from PeoplePerHour. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Freelancer Profiles objects from peopleperhour.com. All fields typed and schema-versioned.
"freelancer_id": "F938201", "name": "Sarah Jenkins", "title": "Senior React Developer", "hourly_rate": 45.0, "cert_level": "CERT 5", "jobs_completed": 142, "rating": 4.9, "skills": "['React', 'Node.js', 'TypeScript']"
| # | freelancer_id | name | title | location | hourly_rate | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Hourlies objects from peopleperhour.com. All fields typed and schema-versioned.
"offer_id": "H492018", "title": "I will build a custom WordPress theme", "category": "Technology & Programming", "price": 150.0, "delivery_days": 5, "sales_count": 84, "rating": 5.0, "tier_pricing": true
| # | offer_id | freelancer_id | title | category | price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Project Listings objects from peopleperhour.com. All fields typed and schema-versioned.
"project_id": "P882910", "title": "Need a Python scraping script", "budget_type": "Fixed", "budget_amount": 250.0, "proposals_count": 14, "status": "Open", "skills_required": "['Python', 'Web Scraping', 'Data Extraction']", "posted_date": "2026-05-12T08:30:00Z"
| # | project_id | title | buyer_id | category | subcategory | budget_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from peopleperhour.com. All fields typed and schema-versioned.
"review_id": "R449201", "freelancer_id": "F938201", "rating": 5.0, "review_text": "Excellent communication and fast delivery.", "date": "2026-04-20", "amount_paid": 450.0, "is_verified": true, "buyer_name": "TechCorp Ltd"
| # | review_id | freelancer_id | buyer_name | project_title | rating | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Buyer Profiles objects from peopleperhour.com. All fields typed and schema-versioned.
"buyer_id": "B392011", "name": "David Mitchell", "location": "London, UK", "jobs_posted": 24, "hire_rate": 85.0, "average_rating": 4.8, "member_since": "2021-03-15", "industry": "E-commerce"
| # | buyer_id | name | location | member_since | jobs_posted | total_spent |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our PeoplePerHour scraper handles the entire marketplace ecosystem: freelancer profiles, CERT algorithms, active project boards, and historical review data. Built with anti-bot circumvention and session management out of the box.
Capture titles, bios, skills, CERT rankings, hourly rates, total earnings, and jobs completed across the entire talent pool.
Extract pre-packaged services, base prices, add-on tiers, delivery times, and active sales counts for all Hourlies.
Monitor new buyer requests in real time. Capture fixed vs hourly budgets, proposal counts, and required skills.
Extract detailed historical ratings, buyer comments, project values, and freelancer responses across paginated review sections.
Deep traversal of design, development, writing, and marketing taxonomies to normalise skill classifications.
Monitor changes in freelancer CERT levels and search visibility to understand marketplace ranking factors.
Extract buyer spend history, hire rates, average project values, and location data to score lead quality.
Capture portfolio item descriptions, categories, and image URLs to evaluate freelancer output quality.
Run one-off bulk exports or configure continuous pipelines at hourly, daily, or real-time cadences with change detection.
Brief in. Clean data out.
Provide category URLs, skill sets, or specific profile lists. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, session management, and CAPTCHA handling for peopleperhour.com.
Schema validation, null-rate checks, and sample data reviews before full production launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Job boards deploy strict perimeter defences to protect user data. Here is how we maintain reliable extraction pipelines.
PeoplePerHour uses strict rate limiting and IP reputation checks. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing to avoid blocks.
Profile pages and project boards rely heavily on client-side rendering. We run full Playwright browser sessions to trigger lazy-loads and hydrate dynamic pricing widgets.
Marketplace search results are paginated and often capped. We use granular search filters and category intersections to bypass display limits and extract the complete catalogue.
For large talent pools, we maintain a hash index of last-seen values per profile. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, schema drift, and coverage drops, responding before you notice.
Track average hourly rates, project budgets, and skill demand across different geographies and categories.
Identify top-tier freelancers by CERT level, review volume, and specific skill combinations for direct recruitment.
Agencies monitor pricing for Hourlies and project bids to optimise their own service offerings and rates.
B2B service providers identify high-spend buyers and active project posters for targeted outreach.
Identify trending skills, supply-demand gaps, and emerging project categories in the freelance ecosystem.
Train NLP models on project descriptions, required skills, and proposal success rates to automate job matching.
"PeoplePerHour holds a wealth of unstructured pricing and skill data for the European gig economy, but extracting it requires bypassing aggressive perimeter defences."
Most teams underestimate the investment required. Reliable PeoplePerHour scraping requires residential proxies, full JavaScript rendering, CAPTCHA handling, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our peopleperhour.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows.
We maintain pools of residential ISP proxies across UK and EU regions. Rotation happens per-request with sticky sessions where required.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About peopleperhour.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible under applicable law, reinforced by the hiQ v. LinkedIn ruling. DataFlirt targets only public, non-authenticated profile, project, and review data. We do not extract personal private messages or circumvent authentication walls.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for rate limits in real time and trigger pool rotation automatically.
Yes. We can target specific taxonomies like software development, digital marketing, or design, extracting all relevant profiles and active projects within those constraints.
Real-time streaming pipelines achieve sub-5-minute latency for new project listings on defined category feeds. Full profile catalogue refreshes at weekly or monthly cadences depending on volume.
We extract public proposal counts on project listings. However, the actual text of proposals and specific bid amounts are private to the buyer and cannot be extracted without account credentials, which we do not support.
Our smallest packages start at a defined category list or target set of profiles with weekly delivery. For full marketplace monitoring, we price based on volume and delivery frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off profile dump or a continuous project monitoring feed, we scope, build, and operate the pipeline. Tell us what you need.
