pg

pglockanalyze - See the locks your Postgres migrations will acquire

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pglockanalyze - See the locks your Postgres migrations will acquire

Hello! I created this tool to make reasoning about Postgres locks a bit easier. Given a database[1] and a set of DDL statements/migrations you want to check, pglockanalyze will open a transaction, execute the statements, read the pg_locks view to analyze the locks they acquire and rollback (or commit, depending on the flags you passed) the transaction. Then, it will output the results for each statement. I think there's merit in this idea, that said it's very much an experiment so there could be flaws and/or corner cases that this strategy won't work well for. It's meant to act as a complement, not a replacement, to things like static analysis and the official Postgres docs. Curious to see what others think; feedback is more than welcome! https://github.com/agis/pglockanalyze Thanks in advance [1] typically an ephemeral database spawned by your CI pipeline

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
72%72% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: open · Missing: mac, agents, macos
71%71% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, pipe, io · Missing: https docs, excited, just released
67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
42%42% 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
32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
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2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

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