Use python3 as the canonical command name course-wide (#104)
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Most current systems (default Debian/Ubuntu, recent macOS) install Python only as `python3`, with no bare `python` on PATH, so learners who copied `python cli.py ...` into their host shell hit "command not found". Convert host-shell `python <cmd>` -> `python3 <cmd>` across module/lab READMEs, lab `.py` docstrings & usage strings, blog posts, lab prompt and instruction files, the M04 verify.sh message, and the M10/M24 lab patches. Module 01's convention note (and its blog/02 mirror) is rewritten so `python3` is canonical and `python` is the documented fallback. Stop-lines respected: Docker image tags (`python:3.12-slim`), `.venv/.../python` and `...\.venv\Scripts\python.exe` paths, the M20 `"command": "python"` teaching example and surrounding venv prose, container-internal invocations (M16/M18 Dockerfiles, M16 README `docker run` examples), and CI-workflow `run:` steps fed by `actions/setup-python` / `image: python:3.12` are left as `python` on purpose. pip was left out of scope: most occurrences are prose or CI/container-internal, and `pip3` does not fix the PEP 668 externally-managed-environment refusal that the course already addresses with venvs. The M01 note is worded to stay consistent with bare `pip` (use whichever pip pairs with your Python). Build (tools/build_wiki.py) and tools/check.sh both pass. Closes #104 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01GAEzanEoGJT5o1VizQar47
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@@ -330,7 +330,7 @@ That's the entire client/server loop, end to end, with zero code you wrote. Now
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> contents so I can read it."*
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Then open the copied file yourself and read it. (It reuses `tasks.py` and shares the same
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`tasks.json`, so anything it changes shows up in `python cli.py list`.) The whole server is two
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`tasks.json`, so anything it changes shows up in `python3 cli.py list`.) The whole server is two
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tools:
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```python
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@@ -411,14 +411,14 @@ That's the entire client/server loop, end to end, with zero code you wrote. Now
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the way you'd verify any runtime effect, by reading the *state*, not the repo:
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```bash
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python cli.py list # the new task is there, because the server wrote the same tasks.json
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python3 cli.py list # the new task is there, because the server wrote the same tasks.json
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cat tasks.json # the raw state the server changed, end to end
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```
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The AI just changed real state in a real system through a tool call. Notice what you did *not*
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reach for: `git diff`. `tasks.json` is deliberately gitignored (Module 2's `.gitignore` treats it
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as generated runtime state, not source), so `git diff` stays empty here, and that's correct, not a
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bug. The proof the task list changed is the live state (`python cli.py list` / `cat tasks.json`),
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bug. The proof the task list changed is the live state (`python3 cli.py list` / `cat tasks.json`),
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not version control; runtime data the app owns is exactly the kind of thing you keep *out* of
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history. No copy-paste, no script you ran by hand, no pasting `tasks.json` into a chat. That's
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"hands."
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@@ -477,7 +477,7 @@ The caveats, and one of them is large enough that it gets its own module.
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connected with `list_tasks` and `add_task` available.
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- You asked the AI a question and it answered by **calling a tool** against the live system, and you
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asked it to add a task and then **verified the change outside the AI** by reading the runtime state
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(`python cli.py list` / `cat tasks.json`), not `git diff`, because `tasks.json` is deliberately
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(`python3 cli.py list` / `cat tasks.json`), not `git diff`, because `tasks.json` is deliberately
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gitignored (Module 2).
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- You can explain the client/server model in one breath (*servers expose tools/resources/prompts;
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the client (your agentic tool) discovers and calls them on the AI's behalf*) and why "it's a
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