Web scraping and extraction
Web scraping
Also called: Scraping, screen scraping
Automated collection of information from websites by software that requests pages and pulls out the content it needs.
In practice
Getting pages is the easy part. Turning them into typed, reliable records every day, as sites change, is where most scraping projects fail.
Collection and extraction are different steps
A scraping workflow requests or renders web content, identifies relevant pages and extracts selected values. It may also schedule revisits, validate records and deliver results. Keeping these stages separate makes failures easier to diagnose: a page-access problem is not the same as a field-mapping error or a warehouse-loading failure.
Example: collecting a product catalogue
An illustrative workflow starts from category pages, follows product links, extracts agreed fields and writes records with source URLs and observation times. Pagination and product variants affect coverage. Some pages may require rendering before the required content is visible. A successful request only establishes that a response arrived, not that every expected product or field was collected.
Plan for repeated operation
Test representative page types, document allowed sources and fields, and monitor changes in record counts and validation failures. Define how retries, duplicates and removed pages are handled. Prefer an authorised structured interface when it meets the requirement. Operational reliability depends on maintenance and acceptance checks as well as the initial extraction, particularly when downstream decisions rely on recurring data.
Import.io extractors are built by point-and-click, AI assistance or engineers, with rendering, pagination and schema detection built in.
Web data extraction →