Split DB-driven constraints into hard + soft variants
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Timefold's penalize() emits one score axis per constraint, so the
'penalize as hard OR soft based on is_hard' pattern needs two
constraints. Each rule type now has _hard (filters is_hard=True,
penalises HardSoftScore.ONE_HARD) and _soft (filters is_hard=False,
penalises ONE_SOFT × max(weight, 1)).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
Benjamin Admin
2026-05-22 00:40:10 +02:00
parent d3f311a32e
commit 0744769d88
+123 -53
View File
@@ -1,16 +1,16 @@
"""Timefold constraint provider for the school timetable.
Three categories:
* universal hard — no double-booking class/teacher/room. These can't be
turned off; the school can't physically run lessons that overlap.
* DB-driven hard — soft-fallback if is_hard=False. Each constraint joins
Lesson against a rule-fact collection from the corresponding tt_
constraint_* table.
* Quality soft — preferred periods, etc.
Categories:
* universal hard — no double-booking class/teacher/room. Mandatory.
* DB-driven — each tt_constraint_* table maps to two constraints here:
a `_hard` variant filtering rules with is_hard=True (penalised as hard),
and a `_soft` variant for is_hard=False (penalised as soft, weighted).
Splitting is required because Timefold's penalize() can only emit one
score axis per constraint.
* Quality soft — preferred periods etc. Always soft.
Scoring uses HardSoftScore. Hard violations are weighted by 1; soft
violations use the rule's stored `weight` (0-100). The UI rejects any
solution where hard_score < 0.
Hard violations use HardSoftScore.ONE_HARD (one per match). Soft violations
multiply ONE_SOFT by the rule's weight (0-100).
"""
from timefold.solver.score import (
@@ -36,12 +36,17 @@ def define_constraints(factory: ConstraintFactory) -> list[Constraint]:
_teacher_conflict(factory),
_room_conflict(factory),
# ---------- DB-driven hard or soft ----------
_teacher_unavailable_day(factory),
_teacher_unavailable_window(factory),
_teacher_excluded_room(factory),
_room_unavailable(factory),
_room_requires_type(factory),
# ---------- DB-driven (each split hard/soft) ----------
_teacher_unavailable_day_hard(factory),
_teacher_unavailable_day_soft(factory),
_teacher_unavailable_window_hard(factory),
_teacher_unavailable_window_soft(factory),
_teacher_excluded_room_hard(factory),
_teacher_excluded_room_soft(factory),
_room_unavailable_hard(factory),
_room_unavailable_soft(factory),
_room_requires_type_hard(factory),
_room_requires_type_soft(factory),
# ---------- Quality soft ----------
_subject_preferred_period(factory),
@@ -96,17 +101,10 @@ def _room_conflict(factory: ConstraintFactory) -> Constraint:
# ==========================================================================
# DB-driven constraints
# DB-driven constraints — each split into hard + soft variants
# ==========================================================================
def _score_for(rule, *, hard_per_violation: int = 1) -> HardSoftScore:
"""Pick HardSoftScore from a rule's is_hard + weight."""
if rule.is_hard:
return HardSoftScore.of(hard_per_violation, 0)
return HardSoftScore.of(0, max(rule.weight, 1))
def _teacher_unavailable_day(factory: ConstraintFactory) -> Constraint:
def _teacher_unavailable_day_hard(factory: ConstraintFactory) -> Constraint:
return (
factory.for_each(Lesson)
.filter(lambda l: l.timeslot is not None)
@@ -115,19 +113,34 @@ def _teacher_unavailable_day(factory: ConstraintFactory) -> Constraint:
Joiners.equal(lambda l: l.teacher.id, lambda r: r.teacher_id),
Joiners.equal(lambda l: l.timeslot.day_of_week, lambda r: r.day_of_week),
)
.penalize(HardSoftScore.ONE_HARD, lambda l, r: 1 if r.is_hard else 0)
.penalize(HardSoftScore.ONE_SOFT, lambda l, r: r.weight if not r.is_hard else 0)
.as_constraint("teacher_unavailable_day")
.filter(lambda l, r: r.is_hard)
.penalize(HardSoftScore.ONE_HARD)
.as_constraint("teacher_unavailable_day_hard")
)
def _teacher_unavailable_window(factory: ConstraintFactory) -> Constraint:
def overlaps(l: Lesson, r: TeacherUnavailableWindowRule) -> bool:
if l.timeslot is None:
return False
# Compare HH:MM strings — they sort correctly when zero-padded.
return l.timeslot.start_time < r.end_time and l.timeslot.end_time > r.start_time
def _teacher_unavailable_day_soft(factory: ConstraintFactory) -> Constraint:
return (
factory.for_each(Lesson)
.filter(lambda l: l.timeslot is not None)
.join(
TeacherUnavailableDayRule,
Joiners.equal(lambda l: l.teacher.id, lambda r: r.teacher_id),
Joiners.equal(lambda l: l.timeslot.day_of_week, lambda r: r.day_of_week),
)
.filter(lambda l, r: not r.is_hard)
.penalize(HardSoftScore.ONE_SOFT, lambda l, r: max(r.weight, 1))
.as_constraint("teacher_unavailable_day_soft")
)
def _overlaps_window(l, r) -> bool:
if l.timeslot is None:
return False
return l.timeslot.start_time < r.end_time and l.timeslot.end_time > r.start_time
def _teacher_unavailable_window_hard(factory: ConstraintFactory) -> Constraint:
return (
factory.for_each(Lesson)
.filter(lambda l: l.timeslot is not None)
@@ -136,14 +149,28 @@ def _teacher_unavailable_window(factory: ConstraintFactory) -> Constraint:
Joiners.equal(lambda l: l.teacher.id, lambda r: r.teacher_id),
Joiners.equal(lambda l: l.timeslot.day_of_week, lambda r: r.day_of_week),
)
.filter(overlaps)
.penalize(HardSoftScore.ONE_HARD, lambda l, r: 1 if r.is_hard else 0)
.penalize(HardSoftScore.ONE_SOFT, lambda l, r: r.weight if not r.is_hard else 0)
.as_constraint("teacher_unavailable_window")
.filter(lambda l, r: r.is_hard and _overlaps_window(l, r))
.penalize(HardSoftScore.ONE_HARD)
.as_constraint("teacher_unavailable_window_hard")
)
def _teacher_excluded_room(factory: ConstraintFactory) -> Constraint:
def _teacher_unavailable_window_soft(factory: ConstraintFactory) -> Constraint:
return (
factory.for_each(Lesson)
.filter(lambda l: l.timeslot is not None)
.join(
TeacherUnavailableWindowRule,
Joiners.equal(lambda l: l.teacher.id, lambda r: r.teacher_id),
Joiners.equal(lambda l: l.timeslot.day_of_week, lambda r: r.day_of_week),
)
.filter(lambda l, r: not r.is_hard and _overlaps_window(l, r))
.penalize(HardSoftScore.ONE_SOFT, lambda l, r: max(r.weight, 1))
.as_constraint("teacher_unavailable_window_soft")
)
def _teacher_excluded_room_hard(factory: ConstraintFactory) -> Constraint:
return (
factory.for_each(Lesson)
.filter(lambda l: l.room is not None)
@@ -152,13 +179,28 @@ def _teacher_excluded_room(factory: ConstraintFactory) -> Constraint:
Joiners.equal(lambda l: l.teacher.id, lambda r: r.teacher_id),
Joiners.equal(lambda l: l.room.id, lambda r: r.room_id),
)
.penalize(HardSoftScore.ONE_HARD, lambda l, r: 1 if r.is_hard else 0)
.penalize(HardSoftScore.ONE_SOFT, lambda l, r: r.weight if not r.is_hard else 0)
.as_constraint("teacher_excluded_room")
.filter(lambda l, r: r.is_hard)
.penalize(HardSoftScore.ONE_HARD)
.as_constraint("teacher_excluded_room_hard")
)
def _room_unavailable(factory: ConstraintFactory) -> Constraint:
def _teacher_excluded_room_soft(factory: ConstraintFactory) -> Constraint:
return (
factory.for_each(Lesson)
.filter(lambda l: l.room is not None)
.join(
TeacherExcludedRoomRule,
Joiners.equal(lambda l: l.teacher.id, lambda r: r.teacher_id),
Joiners.equal(lambda l: l.room.id, lambda r: r.room_id),
)
.filter(lambda l, r: not r.is_hard)
.penalize(HardSoftScore.ONE_SOFT, lambda l, r: max(r.weight, 1))
.as_constraint("teacher_excluded_room_soft")
)
def _room_unavailable_hard(factory: ConstraintFactory) -> Constraint:
return (
factory.for_each(Lesson)
.filter(lambda l: l.room is not None and l.timeslot is not None)
@@ -168,14 +210,29 @@ def _room_unavailable(factory: ConstraintFactory) -> Constraint:
Joiners.equal(lambda l: l.timeslot.day_of_week, lambda r: r.day_of_week),
Joiners.equal(lambda l: l.timeslot.period_index, lambda r: r.period_index),
)
.penalize(HardSoftScore.ONE_HARD, lambda l, r: 1 if r.is_hard else 0)
.penalize(HardSoftScore.ONE_SOFT, lambda l, r: r.weight if not r.is_hard else 0)
.as_constraint("room_unavailable")
.filter(lambda l, r: r.is_hard)
.penalize(HardSoftScore.ONE_HARD)
.as_constraint("room_unavailable_hard")
)
def _room_requires_type(factory: ConstraintFactory) -> Constraint:
"""If a subject requires a specific room type, the assigned room must match."""
def _room_unavailable_soft(factory: ConstraintFactory) -> Constraint:
return (
factory.for_each(Lesson)
.filter(lambda l: l.room is not None and l.timeslot is not None)
.join(
RoomUnavailableRule,
Joiners.equal(lambda l: l.room.id, lambda r: r.room_id),
Joiners.equal(lambda l: l.timeslot.day_of_week, lambda r: r.day_of_week),
Joiners.equal(lambda l: l.timeslot.period_index, lambda r: r.period_index),
)
.filter(lambda l, r: not r.is_hard)
.penalize(HardSoftScore.ONE_SOFT, lambda l, r: max(r.weight, 1))
.as_constraint("room_unavailable_soft")
)
def _room_requires_type_hard(factory: ConstraintFactory) -> Constraint:
return (
factory.for_each(Lesson)
.filter(lambda l: l.room is not None)
@@ -183,10 +240,23 @@ def _room_requires_type(factory: ConstraintFactory) -> Constraint:
RoomRequiresTypeRule,
Joiners.equal(lambda l: l.subject.id, lambda r: r.subject_id),
)
.filter(lambda l, r: l.room.room_type != r.room_type)
.penalize(HardSoftScore.ONE_HARD, lambda l, r: 1 if r.is_hard else 0)
.penalize(HardSoftScore.ONE_SOFT, lambda l, r: r.weight if not r.is_hard else 0)
.as_constraint("room_requires_type")
.filter(lambda l, r: r.is_hard and l.room.room_type != r.room_type)
.penalize(HardSoftScore.ONE_HARD)
.as_constraint("room_requires_type_hard")
)
def _room_requires_type_soft(factory: ConstraintFactory) -> Constraint:
return (
factory.for_each(Lesson)
.filter(lambda l: l.room is not None)
.join(
RoomRequiresTypeRule,
Joiners.equal(lambda l: l.subject.id, lambda r: r.subject_id),
)
.filter(lambda l, r: not r.is_hard and l.room.room_type != r.room_type)
.penalize(HardSoftScore.ONE_SOFT, lambda l, r: max(r.weight, 1))
.as_constraint("room_requires_type_soft")
)
@@ -204,6 +274,6 @@ def _subject_preferred_period(factory: ConstraintFactory) -> Constraint:
Joiners.equal(lambda l: l.subject.id, lambda r: r.subject_id),
)
.filter(lambda l, r: not (r.period_from <= l.timeslot.period_index <= r.period_to))
.penalize(HardSoftScore.ONE_SOFT, lambda l, r: r.weight)
.penalize(HardSoftScore.ONE_SOFT, lambda l, r: max(r.weight, 1))
.as_constraint("subject_preferred_period")
)