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5 Commits

Author SHA1 Message Date
8798105aa1 Grade against 3.14 too, not just run on it
The pre-commit workflow already installs `python-version: "3.x"`, but ruff was
still grading the archive against py310 -- so it kept withholding the pyupgrade
and type-checking fixes that only become safe at the newer target.
`pin_ci_python.py` rewrites the knob.

The 17 findings that appeared are what the stale target was hiding:
`datetime.timezone.utc` where `datetime.UTC` is now correct (UP017), and 14
imports used only in annotations that belong under `TYPE_CHECKING` (TC002,
TC003) -- safe here precisely because 3.14's PEP 649 defers annotation
evaluation, which is the same reason ruff would not offer them at py310.

`ruff check` and `ruff format --check` are clean again, so the zero-findings
state this repo reached earlier today holds at the new target.

Still contradictory and deliberately untouched: the four
`Programming/ERSMS-project/*/Dockerfile` files say `FROM python:3.10-slim`.
They build an archived coursework service against its own era's pinned
dependencies, and nothing in this repo runs them; bumping the base image would
be a rewrite of that project, not a lint-target change.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01SfnJmxxsZ534AKk16rC2Gr
2026-08-29 11:55:43 +02:00
cc06bc0cd8 EARIN: zero findings, verified against byte-identical program output
749 findings across six labs and two projects. The mechanical half was
scripted; everything below is what the scripts got wrong or could not do, and
how it was caught.

Three regressions I introduced and then found by RUNNING the code, not by
reading it:

- Converting print() to logger.info() made the programs SILENT. logging's
  last-resort handler only emits WARNING and above, so with no basicConfig
  call `lab2/main.py -t 1 1` printed nothing at all. Fifteen files across the
  repo now configure logging where they log.
- The same conversion dropped `end=""`. lab2 draws its board one square at a
  time and lab1 draws the maze one cell at a time; both came out one glyph
  per line. Those thirteen call sites are sys.stdout.write again, and the
  rendered board now diffs byte-identically against the pre-change output.
- The B007 fix renamed `col` to `_col` in the FIRST loop it matched, which
  was print_letters -- where the variable IS used. That would have been a
  NameError on the first call.

And one the scripts caused silently: annotating 110 signatures dropped the
DEFAULT VALUES from 22 of them, so `preprocessing(a, b, USER_THRESHOLD,
ANIME_THRESHOLD)` would have raised TypeError. Every signature is now diffed
against the pre-change version, name by name and default by default: zero
mismatches.

Real defects the lint surfaced:

- `alpha_beta` ended with an unreachable `return None` that violated its own
  return type. Its maximising and minimising halves were mirror images, so
  they are one `_search_branch` now (C901 11 -> ok).
- `get_data`'s `gpu` switch, `predict`'s `auto`, `create_model`'s
  `rows_number` and five of `preprocess_model_predict`'s fifteen parameters
  were never read. Gone, with their call sites.
- np.random.* -> Generator throughout (NPY002), `.values` -> `.to_numpy()`,
  `datetime.now()` with a tzinfo, `inplace=True` removed, `except:` given a
  type, `random.*` -> `SystemRandom` (S311).
- print_board's three nested helpers became methods (C901 17 -> ok);
  user_input's nine-branch if-ladder became a table (C901 12 -> ok).

Verification, all by running: lab1 `-t` and lab2 `-t 1 1` produce output
byte-identical to the pre-change code; lab2's rendered 8x8 board diffs clean;
lab3's argument parsing returns the same dict for the same argv; lab4 fails
identically before and after (no sklearn here). Also included: the logging
configuration for NLP, MOM and ECRYPT_PROJECT, which had the same silence bug.

Repo-wide: 2,775 findings -> 1,883.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0172dj34FDpao6wsix8ZuCzE
2026-08-28 20:39:53 +02:00
b017c7500e NLP: zero findings, and two real bugs found on the way
384 findings to none across ten scripts. Most of it is annotation and
docstring work, but the lint surfaced two defects that had nothing to do with
style:

- `gpt_chunks.py` stripped its GPT preamble with
  `input_string.strip("iSTS chunks:")`. str.strip takes a SET OF CHARACTERS,
  not a prefix, so it also ate any leading i/S/T/s/c/h/u/n/k/space/colon:
  "iSTS chunks: sentence one" came out as "entence one", silently losing the
  first letter of every chunked sentence. Now removeprefix. ruff found it as
  B005 + PLE1310.
- `is_numbered_line_format` had `for string in string` in its list branch,
  which raises NameError the moment a list is passed (F821).
- `processing.test_XML()` read a module-level `alignments_data` that does not
  exist at module scope; it only ever ran when pasted into a live session. It
  takes the data as an argument now and is renamed `log_first_alignment` so
  pytest stops collecting a non-test as a test.

Also real rather than cosmetic:

- The OpenAI key was a placeholder string literal in three files, one of them
  carrying a "Replace me with os.environ['API_KEY']" comment. All three read
  OPENAI_API_KEY now and say so when it is missing -- as committed, none of
  these scripts could actually run.
- `rating.rate_similarity` was submitted unfinished: it built a client, never
  touched its two arguments and returned None despite `-> str`. It now makes
  the same call the rest of the package makes.
- The two 2 kB alignment prompts and one 344-character chunking prompt moved
  to prompts/*.txt. Wrapping them in source would have put newlines into the
  middle of the prompt.
- `format_alignments` parsed GPT's replies with `eval()`; the file holds one
  repr()'d string per line, so ast.literal_eval is both sufficient and safe.
- NLP/__init__.py deleted -- it made the course directory a package named
  "NLP", which is an invalid module name (N999) and which nothing imports;
  the scripts use plain `import processing`.

INP001 is settled the same way throughout: a coursework file run as
`python x.py` gets a shebang and the executable bit, which is what it is,
rather than an __init__.py that would make a course code into a module name.

Verified: every module compiles and `./run.sh run Programming/NLP` is clean.
The scripts themselves need the SemEval corpus and a paid API key, so they
are not executed here.

Repo-wide: 3,159 findings -> 2,775.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0172dj34FDpao6wsix8ZuCzE
2026-08-28 20:13:19 +02:00
bd24dd57ea Hold the coursework to the same lint bar as the tooling
kuhy overruled the "do not fix coursework to be better than it was submitted"
rule: git history is the archive, so the working tree can be clean. This lands
the config and the mechanical half of the cleanup -- 9,281 ruff findings under
the fleet config down to 3,686, with no per-file-ignores anywhere.

What is in here:

- pyproject.toml, the first one in this repo. select = ["ALL"], mypy strict,
  and the vendored list mirrored into ruff exclude and coverage omit. Five
  rules are off and each says why; CPY001 is the only judgement call, because
  stamping a copyright header onto 137 university assignments would assert a
  licence that was never claimed. No hook is wired up yet -- a gate lands only
  once its subject is clean.

- ruff format + the safe fixes, then a second pass over the docstring rules
  ruff marks unsafe (they only edit docstring text). 108 files.

- TRAK/sightpy is vendored, not coursework: it is rafael-fuente/Python-Raytracer
  (BSD 3-Clause). Verified against a fresh upstream clone with line endings
  normalised -- 30 of 32 files byte-identical, ray.py and scene.py carrying a
  12- and 13-line local patch that counts rays for the report. 35 files that
  should never have been linted, now excluded and restored.

- WDWR, SPD, MOM and ECRYPT are fully clean, by hand and verified by running
  them: WDWR's three plot scripts print the same statistics as before, MOM's
  PuLP model solves to the same cost. WDWR's graph.py had a 342-character CSV
  header embedded as a string literal, which cannot be wrapped -- the data
  moved to data/pareto_front.csv. Two 0-byte .py stubs are deleted; an empty
  file is not a deliverable and git still has it.

Three harness bugs found by actually running things:

- `run` now forces MPLBACKEND=Agg. TRAK finished its ray trace in 37 seconds
  and then sat for 45 minutes: plt.show() had opened an image viewer and was
  waiting for someone to close the window.
- TRAK's main.py only pops that viewer with --show now, and its runner writes
  to a gitignored build/ via the new --entry-args. The default output path is
  outputs/output.png, which is TRACKED -- a plain run overwrote a submitted
  deliverable.
- course_lib.sh was 357 lines, over this repo's own cap. Split into
  course_probe.sh and course_run.sh.

Verified: ECOTE 26 tests pass, ECRYPT_PROJECT 99 pass, TRAK renders
cornell_box in 37s and exits 0, every module compiles, and every import ruff
removed was checked to be genuinely unused.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0172dj34FDpao6wsix8ZuCzE
2026-08-28 19:53:04 +02:00
95fa9d2259 Add 'Programming/NLP/' from commit '56650422d8395d618206beb497ba99c3a81191cf'
git-subtree-dir: Programming/NLP
git-subtree-mainline: f3345d8610
git-subtree-split: 56650422d8
2026-02-06 22:15:08 +01:00