Documentation

Build reliable web data pipelines without crawler infrastructure.

These docs explain the managed VStock Data workflow: define a target, approve sample data, and receive normalized records through the delivery channel your team already uses.

curl -X POST https://api.vstockdata.com/scrape \
  -H "Authorization: Bearer YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "target_url": "https://example.com/products",
    "fields": ["title", "price", "availability", "rating"],
    "render_js": true,
    "geo": "US",
    "delivery": {
      "format": "json",
      "type": "webhook",
      "url": "https://your-app.com/webhooks/vstock"
    }
  }'

1. Describe your target

Send the website URL, fields you need, geography, refresh cadence, and preferred delivery format.

2. Validate a free sample

We build the extractor, handle anti-bot access, normalize the schema, and deliver sample records for review.

3. Launch recurring delivery

Approved jobs run on schedule and push clean data through API, Webhook, S3, CSV, or database sync.

Request payload

target_url — public page, category, profile, search, or listing URL
fields — product price, reviews, seller, availability, job title, rating, or custom fields
render_js — enable full browser rendering for SPA and dynamic sites
geo — route collection through a target country or region when needed
schedule — one-time, hourly, daily, weekly, or custom cadence

Delivery options

REST API for job creation and record retrieval
Webhook push for near-real-time updates
S3, Google Cloud Storage, or Azure Blob exports
CSV, JSON, Excel, XML, or custom normalized schemas
Direct database sync for PostgreSQL, MySQL, MongoDB, or Snowflake

Reliability controls

Automatic retries for transient blocks and network failures
Schema validation before data leaves the pipeline
Parser health monitoring for site redesigns
Duplicate detection, freshness checks, and bad-data re-scrapes
Optional human review for high-value datasets