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Show HN: Document parsing 5B tokens on a single CPU thread

mit license: https://github.com/john-friedman/doc2struct doc2struct is an algorithm that can parse documents fast on one thread. For example it can parse every every 2025 annual report 19GB in 40s. It preserves nesting, does mild table cleaning, among other things. It succeeds my earlier document parser https://github.com/john-friedman/doc2dict

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Source page screenshot: Show HN: Document parsing 5B tokens on a single CPU thread
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Recorded metrics

points · 1 votes
2026-11-06 09:45:15.073Z
cumulative since publication

Research analysis

What changed

Source account: mit license: https://github.com/john-friedman/doc2struct doc2struct is an algorithm that can parse documents fast on one thread. For example it can parse every every 2025 annual report 19GB in 40s. It preserves nesting, does mild table cleaning, among other things. It succeeds my earlier document parser https://github.com/john-friedman/doc2dict

Version & cost evidence

Source votes: 1 votes (Nov 6, 2026 UTC; cumulative since publication) Recent records to compare: “Show HN: Models[.]Dev Index on a Globe” (Show HN, Nov 7, 2026); “Show HN: NLP capabilities of Opus, Astra, Argon measured by Codenames skills” (Show HN, Nov 7, 2026). Shared themes are navigation hints; they have not been verified as the same need or independent corroboration.

Who is affected

Identify the existing workflow this change affects before recommending an upgrade. Launch attention does not establish improvement; an API, pricing or availability change may instead create migration work.

Missing comparison points

Missing checks: old versus new behavior, affected plans and regions, availability date, compatibility, rollback path and cost under the same workload.

Migration check

Save the release or policy notice, run the same task on the old and new option, and compare outputs and the full bill. For retirement notices, verify the deadline before scheduling migration.