ESP32-S3 Bench Guide
ESP32‑S3 N16R8 벤치 가이드: 실시간 핀아웃, 강의, 시뮬레이터 및 벤치 로그
아직 감지된 업데이트가 없습니다. GitHub 릴리스가 나오면 여기에 보입니다.
개인 계정의 공개 저장소 소유자는 GitHub로 로그인해 운영자를 확인하고 소개를 직접 관리할 수 있습니다. 관리자 승인은 필요하지 않습니다.
로그인한 뒤 확인 파일을 만들어 이 저장소의 기본 브랜치에 30분 안에 커밋해 주세요. 다른 브랜치나 포크의 파일은 인정하지 않습니다. 파일을 올린 뒤 아래에서 확인하면 관리자 승인 없이 관리할 수 있습니다. 자격을 유지하려면 파일을 남겨 두세요.
로그인이 필요하면 로그인 화면으로 이동합니다. 로그인 후 이곳으로 돌아와 원하는 확인 버튼을 다시 눌러 주세요.
프로젝트 폴더에서 /nomorevibe verify를 실행하면 소유권을 확인하고 소개를 직접 관리할 수 있습니다.
1분 만에 확인하기README 전체를 불러오는 중입니다. 아래는 저장된 발췌입니다.
Personal tool for practicing the full analytical reasoning chain — business problem → metric definition → population/grain → query architecture → SQL → validation. Single user, no accounts. See claude/v1-escopo-decisoes.md for the locked V1 scope and CONTEXT.md for domain terminology.README 전문 보기 ↗Personal tool for practicing the full analytical reasoning chain — business problem → metric definition → population/grain → query architecture → SQL → validation. Single user, no accounts. See claude/v1-escopo-decisoes.md for the locked V1 scope and CONTEXT.md for domain terminology.
CONTEXT.md's "Dataset" entry)npm install
npm run dev
Open http://localhost:3000.
Schema lives in src/db/schema.ts; migrations are generated with drizzle-kit into src/db/migrations/.
npm run db:generate # generate a migration after changing src/db/schema.ts
npm run db:migrate # apply pending migrations (requires DATABASE_URL)
Set DATABASE_URL (a Postgres connection string) in .env.local before running db:migrate against a real database. Schema contract tests (src/db/__tests__/) don't need it — they run migrations against an in-memory Postgres (@electric-sql/pglite).
Synthetic datasets (one per domain — e-commerce, SaaS, fintech) live under public/datasets/ (static assets the browser's DuckDB-WASM fetches directly); authored exercises live under content/exercises/. Both are generated/validated by scripts in scripts/:
npm run datasets:generate # (re)generate the 3 domain datasets as Parquet, into public/datasets/
npm run exercises:admit # validate batches in content/exercises/incoming/, admit the passing ones
To author new exercises: paste content/exercises/GENERATION_PROMPT.md into a Cowork/Claude session (it embeds the current dataset schemas and the output format), save the JSON reply as a file under content/exercises/incoming/, then run exercises:admit. Only exercises whose reference SQL actually runs against the real dataset get admitted into content/exercises/validated/; everything else is reported and discarded. content/exercises/generation-log.json tracks what's already been admitted, to avoid repeating the same skill/level combos.
Deployed to Vercel. Two env vars must be set in the Vercel project (see .env.example):
DATABASE_URL — the Postgres connection string (Vercel Postgres/Neon).SITE_PASSWORD — the shared password gating the whole app (single-user tool, no accounts). When this is set, middleware.ts redirects every request without a valid session cookie to /login; /api/auth/login checks the submitted password against it and sets the session cookie on success. Leaving it unset (e.g. local dev) leaves the app open.vercel link # first time only, links this directory to a Vercel project
vercel env pull # pull DATABASE_URL / SITE_PASSWORD into .env.local for local dev
vercel deploy --prod
npm test # run all tests once
npm run test:coverage # with coverage
npm run lint