Git basics
Build the first working focused Git commit
Page 3 implements the shortest complete path for the focused commit for evaluation-script change with inspectable intermediate values.
1Learn the idea
Read
Implement the minimal working path
Build only what the claim requires: git show --stat on HEAD lists train.py but not README.md. Prefer boring, deterministic code over frameworks you cannot yet explain. Run the path twice; identical output on this fixture is a feature, not a lack of creativity.
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Run the working path
git add train.py
git diff --cached --name-only
git commit -m 'Add held-out model evaluation'
Expected evidence: only train.py staged then committed. Read each printed intermediate as part of the argument that the path works—not as decoration.
Read
Trace one input end to end
Narrate the journey from raw input to result for a single example from repo with dirty train.py (eval) and README.md (docs). If you cannot name an intermediate, the implementation is still too opaque for this lab. Only after this path is solid should you generalize data sources or UI.
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Lab notebook: intermediates worth printing
While implementing the focused Git commit, print or log at least three intermediates that map to the claim (git show --stat on HEAD lists train.py but not README.md). Good intermediates are values a teammate could recompute with a calculator or diff. Bad intermediates are framework traces you cannot explain.
Re-run with repo with dirty train.py (eval) and README.md (docs) twice. If the second run differs, either the path is nondeterministic (document the seed) or you have hidden global state—both are lab bugs until named.
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Worked judgment
Stop adding features once the path supports land only the tested train.py evaluation change while README edits stay unstaged. Extra UI, extra tools, or extra models belong in later chapters. The mastery bar for this page is simply: a deterministic end-to-end path with intermediates.
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Why this stage matters for the focused Git commit
At the implementation stage for git-basics, the job is narrower than finishing a product demo. You are creating one progressive evidence piece about repo with dirty train.py (eval) and README.md (docs) that later pages inherit without redefining success. Keep that fixture small enough to inspect by hand, keep outputs copy-pasteable as text, and refuse to narrate this baseline as if it were a production SLA: git status and git diff before any add.
For this page specifically, success looks like a deterministic path with printed intermediates while still centering the user decision to land only the tested train.py evaluation change while README edits stay unstaged. If you cannot point to a file, command, or assertion that proves that for the focused Git commit, stay on this page instead of advancing.
Go deeper
Before you start
Why this matters
Without running code, predict the final output for fixture repo with dirty train.py (eval) and README.md (docs). Name one intermediate value that would prove the prediction. Then answer: what could look successful while actually being wrong at this stage for the focused Git commit?
In the wild
See how this idea shows up as a product and a company — then come back to the lesson. Skills transfer across vendors.
Related lessons
Check your understanding
Page assessment
Answer from memory. Completion is saved from this evidence, not from opening the next page.
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