Data extraction is the step that turns a page, API response, or document into fields a task can use. A crawler may fetch HTML successfully and still extract nothing useful if it selects the wrong element, reads a placeholder, or misses content rendered after the initial response.
From response to records
Start by identifying the source format. JSON responses can often be mapped directly to fields; HTML requires a parser and selectors; a browser workflow may be needed when relevant content only appears after interaction. For each field, define its expected meaning and type before writing extraction logic.
A reliable extractor should handle missing values, repeated elements, and small layout changes deliberately. For example, a product page may show a price in more than one place. The extraction rule should identify the primary price and preserve the currency instead of returning whichever matching number appears first.
Keep extraction separate from cleaning and validation. Extraction answers “what did the source contain?”; later steps can normalize formats and decide whether the values meet the dataset’s requirements. Saving the source URL and capture time makes later corrections much easier.
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