P1 from ChatGPT Codex on #97, live at f128087 — in the change that fixed the
first instance of this same defect.
`preprocess` infers Numeric -> Date -> Categorical, and `encoded_width` had no
date arm at all. A date string does not parse as f64, so a measure column holding
dates fell through to the categorical count. `build_date` emits
epoch_day/year/month/day/dow, and seven parts once any cell carries a time, so a
column with ONE distinct timestamp promised 1 and materialised 5. Against a
budget of 64 that is an under-count of four on a single column, in the direction
that spends the allocation the preflight exists to prevent.
The fix is structural rather than another remembered branch, because two
instances one branch apart is the tell. `inferred_kind` reproduces `preprocess`'s
own match arm for arm and returns a `Forced`; `encoded_width` matches that with
NO wildcard, so a fourth variant is a compile error here instead of silently
taking the categorical arm — which is exactly how Date was missed. The .missing
flag moves out of the arms, since every branch owes it on the same terms.
The fixture carries a time case because of the RIVAL FIX, not the bug: "a date
column is 5" and "5, or 7 when any cell has a time" both repair the plain-date
failure and differ only on a column containing a time. Injected, `date_parts`
hard-coded to 5, the plain-date case still PASSES and the time case fails at
"promised 8 ... materialised 10". Injecting the bug proves the test sees the bug;
injecting the rival proves it sees the rule. Both arms compare against
`data.feature_names.len()`, never against a width computed a second way.
Also recorded in gp.md: the "must never under-count" line was written as a
proposed kb.pl invariant while the tree already held this counter-example. An
invariant generalised from the defect just fixed generalises the fix, not the
code; the question that would have caught it is "what else does `preprocess` do
that I have not mirrored", which is about the other function and not the bug.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01FC2jVn8Au7E9JPkw6bwXXH
Edward Langley
c2bc939608