Hard filters encode claims the section may not make — a selective school is
not an alternative to a non-selective one, a special school is not comparable
to a mainstream one, a Girls school is not an option for a Boys school's
reader — so they never relax. Soft preferences describe closeness of fit, so
they relax across three tiers, and only far enough to reach three; the
remaining slots up to six fill from the tiers already opened.
PHASE_GROUPS moves to schemas.py so this module can share it without
importing app, which would be a cycle.
_mask() exists because Series.apply on an empty Series returns a DataFrame,
and using that as a mask drops every column — so the next lookup raises
KeyError instead of yielding no rows. A special school with no special school
near it empties the frame at the provision filter, which is the ordinary case
for most special schools, so this was a crash on a common path rather than an
edge case.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
