My training ground, in one repo:
- Python and algorithms: timed drills and 43 tested problems
- SQL: 18 queries on a real PostgreSQL database, plus an interactive SQL path
- Interview prep: every stop of an R&D Software Developer hiring process at a Python ERP company, from the first coding drill to the first day in Belgium (route tracker)
- DevOps: Kubernetes, Docker, GitHub Actions, Argo CD and GitOps in
kube-lab/
An interactive app for everything above: runnable lessons and self-grading problems
for SQL, algorithm patterns and DevOps (a simulated Kubernetes cluster, Docker, CI/CD,
GitOps), in the browser. See app/README.md.
cd app && npm ci && npm run dev| Project | Folder | Covers |
|---|---|---|
| Gitea on Kubernetes | kube-lab/project-1-gitea/ |
Core Kubernetes by hand: StatefulSets, PVCs, probes, Jobs, CronJobs, NetworkPolicy, RBAC, Gateway API |
| ShipIt | kube-lab/project-2-shipit/ |
CI/CD + GitOps: GitHub Actions → GHCR → Argo CD, Kustomize environments, HPA, CloudNativePG, monitoring |
Start with kube-lab/README.md. Its workflows live in
.github/workflows/kube-*.yml.
| Stop | Folder | Status |
|---|---|---|
| A1 · Python fluency | A1-python-fluency/ |
ready · 5 drills |
| A2 · Online coding test | A2-online-test/ |
ready · 43 algorithm problems, 18 SQL queries, 3 mocks, aptitude, English, web MCQ |
| A3 · ERP framework | A3-erp-framework/ |
outline, built out when I get there |
| A4 · HR screen | A4-hr-screen/ |
outline |
| A5 · Technical interview | A5-technical-interview/ |
outline |
| A6 · Long live-coding session | A6-live-coding/ |
outline |
| A7 · Final round | A7-final-round/ |
outline |
| B · Resume, GitHub, referral | B-profile/ |
outline |
| C · Apply | C-apply/ |
outline |
| D · Track the process | D-tracking/ |
outline |
| E · Offer, permit, visa, move | E-relocation/ |
outline |
What the real process looks like (sources and details in RESEARCH.md): screening → online coding test (+ logic / English tests) → recruiter call → long technical interview → offer.
make setup # .venv with pytest + psycopg
make db # PostgreSQL in Docker, needed for the SQL exercises only- Open the exercise file, read the docstring, start a timer for the target minutes.
- Write the solution in that file. Don't look up the answer; if you're stuck after the target time, write down where you're stuck in the journal and move on.
- Run its tests:
.venv/bin/pytest A2-online-test/01-strings-stack/test_valid_markup.py - When it's green, think about the complexity and say it out loud, like in the interview.
- Write 3 lines in
journal/(what you solved, what was hard, what to review). make progress, commit, push. CI on GitHub reruns everything and shows the progress table.
Then ask Claude: "review my A2 strings work". Claude reads the diff and the journal, gives feedback, and updates the tracker.
- Python for algorithms and backend (the target stack's language). TypeScript is used for the live full-stack build in A6, where candidates may choose their stack.
- Every exercise has automatic tests; an exercise counts as solved only when all of them pass.
- Problems are original, written for this repo. Each one links to a similar public problem for extra practice after you solve it.