Dop, Awk-like processing for JSON/YAML/TOML with Lua

Hacker News

dop reads JSON, YAML, or TOML from stdin, walks the structure field by field, and lets you transform values with Lua. It can also query nested paths and convert between formats. It weights just 800kb and you don't need Lua installed in your pc. A few examples: echo '{"list":[1,2,3]}' | dop -e ' if type(VALUE) == "number" then set(VALUE * 2) end ' # => {"list":[2,4,6]} echo '{"data":{"some_list":[1,2,3]}}' | dop -q data.some_list # => [1,2,3] What I wanted was: - something simpler to reason about for non-trivial transforms - one tool for JSON/YAML/TOML - embedded scripting without needing Lua installed separately Repo: https://github.com/dhuan/dop Any feedback is welcome.

Visit product View on Hacker NewsMar 27, 2026

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Hacker NewsStrong engagement from HN community · Strong signals: lua · Missing: https docs, excited, just released

67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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TrustMRRFits verified-revenue profile · Strong signals: para · Missing: mobile apps, ios, personal

56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Strong signals: para · Missing: supports, reddit linkedin, podcasting

39%39% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

30%30% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

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