JSON and CSV Exports: Design Data Other Tools Can Use
Make exported data predictable by defining records, missing values, identifiers, validation, and the handoff to the next tool.
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Structured Data, in practice.
Read focused structured data articles and connect the ideas to the rest of your tools API workflow.
Structured data needs more than familiar field names. Types, missing-value rules, units, identity, and provenance all affect how another system will interpret a record. Define those meanings before building a parser or export.
The guides below connect source extraction to a reviewable output contract. Keep malformed inputs and uncertain values distinguishable from valid empty fields. Test representative examples with the real receiving tool, and document compatibility when a schema changes. Clear data handling lets the next stage make a decision without reconstructing assumptions from the implementation. Review question: Can the receiving system tell a genuinely empty value from a failed extraction, and are the relevant conversion rules explicit?
Articles in this collection
HTML Parsing: Turn Pages into Structured Data
Turn page markup into records you can trust by separating extraction, normalization, validation, and the evidence needed to explain every result.
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