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Retrait des disponibilités et des limites de temps dans la journée
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Disponibilités déclarées supprimées (table `availability`, migration 0022,
API, éditeur de la fiche bénévole, badge de couverture du panneau
d'affectation, colonnes des statistiques) ainsi que les règles
OUTSIDE_AVAILABILITY, DAILY_HOURS_EXCEEDED et INSUFFICIENT_REST, les malus
de disponibilité et de repos du solveur et le filtre « Surchargés » de la
vue bénévoles. Seul le chevauchement reste contrôlé. La case « je suis
disponible » du formulaire public est conservée.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
This commit is contained in:
AdamThomas
2026-10-05 21:29:58 +02:00
co-authored by Claude Opus 5.5
parent f671bb85bf
commit d722a81a87
40 changed files with 213 additions and 1845 deletions
Download Patch File Download Diff File Expand all files Collapse all files
backend/tests/test_solver_engine.py
+32 -68
View File
@@ -4,7 +4,7 @@ import datetime as dt
from app.solver.engine import solve
from app.solver.models import SolverInput, SolverShift, SolverVolunteer
from app.validation.models import AvailabilityWindow, ShiftInfo
from app.validation.models import ShiftInfo
def _dt(day: int, hour: int, minute: int = 0) -> dt.datetime:
@@ -39,7 +39,6 @@ def _shift(
def _volunteer(
vid: str,
*,
availability=(),
wished_position_ids=frozenset(),
wished_companion_ids=frozenset(),
wished_artist_windows=(),
@@ -48,7 +47,6 @@ def _volunteer(
) -> SolverVolunteer:
return SolverVolunteer(
id=vid,
availability=tuple(availability),
wished_position_ids=frozenset(wished_position_ids),
wished_companion_ids=frozenset(wished_companion_ids),
wished_artist_windows=tuple(wished_artist_windows),
@@ -57,10 +55,6 @@ def _volunteer(
)
def _full_day(day: int) -> AvailabilityWindow:
return AvailabilityWindow(dt.date(2026, 7, day), dt.time(6, 0), dt.time(4, 0))
def _by_shift(solution, shift_id: str) -> tuple[str, ...]:
for s in solution.suggestions:
if s.shift_id == shift_id:
@@ -75,7 +69,7 @@ def test_no_variables_returns_empty_solution():
def test_fully_staffed_shift_gets_no_suggestion():
shift = _shift(ideal_staff=1, already_assigned=1)
volunteer = _volunteer("v1", availability=[_full_day(10)])
volunteer = _volunteer("v1")
solution = solve(SolverInput(shifts=(shift,), volunteers=(volunteer,)))
assert solution.suggestions == ()
@@ -84,105 +78,77 @@ def test_picks_the_only_free_volunteer_over_a_busy_one():
shift = _shift()
busy = _volunteer(
"busy",
availability=[_full_day(10)],
existing_shifts=[ShiftInfo(id="e", starts_at=_dt(10, 15), ends_at=_dt(10, 19))],
)
free = _volunteer("free", availability=[_full_day(10)])
free = _volunteer("free")
solution = solve(SolverInput(shifts=(shift,), volunteers=(busy, free)))
assert _by_shift(solution, "s1") == ("free",)
def test_does_not_exceed_ideal_staff_cap():
shift = _shift(ideal_staff=2, already_assigned=1) # il ne manque qu'une place
a = _volunteer("a", availability=[_full_day(10)])
b = _volunteer("b", availability=[_full_day(10)])
a = _volunteer("a")
b = _volunteer("b")
solution = solve(SolverInput(shifts=(shift,), volunteers=(a, b)))
assert len(_by_shift(solution, "s1")) == 1
def test_prefers_volunteer_with_matching_position_wish():
shift = _shift(position_id="regie")
plain = _volunteer("plain", availability=[_full_day(10)])
plain = _volunteer("plain")
wisher = _volunteer(
"wisher", availability=[_full_day(10)], wished_position_ids={"regie"}
"wisher", wished_position_ids={"regie"}
)
solution = solve(SolverInput(shifts=(shift,), volunteers=(plain, wisher)))
assert _by_shift(solution, "s1") == ("wisher",)
def test_prefers_fully_available_volunteer_over_partially_available():
shift = _shift(start=_dt(10, 14), end=_dt(10, 18))
full = _volunteer("full", availability=[_full_day(10)])
partial = _volunteer(
"partial",
availability=[AvailabilityWindow(dt.date(2026, 7, 10), dt.time(14, 0), dt.time(16, 0))],
)
solution = solve(SolverInput(shifts=(shift,), volunteers=(full, partial)))
assert _by_shift(solution, "s1") == ("full",)
def test_ranks_both_candidates_when_two_slots_are_open():
shift = _shift(ideal_staff=2)
full = _volunteer("full", availability=[_full_day(10)])
partial = _volunteer(
"partial",
availability=[AvailabilityWindow(dt.date(2026, 7, 10), dt.time(14, 0), dt.time(16, 0))],
)
solution = solve(SolverInput(shifts=(shift,), volunteers=(full, partial)))
assert _by_shift(solution, "s1") == ("full", "partial")
def test_never_double_books_a_volunteer_across_two_new_suggestions():
# Deux créneaux qui se chevauchent, un seul bénévole disponible pour les
# deux : le solveur ne le propose qu'une fois.
shift_a = _shift("a", start=_dt(10, 14), end=_dt(10, 18))
shift_b = _shift("b", start=_dt(10, 16), end=_dt(10, 20))
only = _volunteer("only", availability=[_full_day(10)])
only = _volunteer("only")
solution = solve(SolverInput(shifts=(shift_a, shift_b), volunteers=(only,)))
picked_a = _by_shift(solution, "a")
picked_b = _by_shift(solution, "b")
assert len(picked_a) + len(picked_b) == 1
def test_avoids_volunteer_with_insufficient_rest_since_last_shift():
# < 8 h entre la fin d'un créneau déjà décidé et le début de celui-ci.
shift = _shift(start=_dt(10, 14), end=_dt(10, 18))
def test_short_rest_is_not_penalized():
# Plus de repos minimal (8 h) : 4 h après un créneau déjà décidé, le
# bénévole reste à égalité avec un autre.
shift = _shift(ideal_staff=2, start=_dt(10, 14), end=_dt(10, 18))
tired = _volunteer(
"tired",
availability=[_full_day(10)],
existing_shifts=[ShiftInfo(id="e", starts_at=_dt(10, 8), ends_at=_dt(10, 10))], # repos 4 h
existing_shifts=[ShiftInfo(id="e", starts_at=_dt(10, 8), ends_at=_dt(10, 10))],
)
fresh = _volunteer("fresh", availability=[_full_day(10)])
fresh = _volunteer("fresh")
solution = solve(SolverInput(shifts=(shift,), volunteers=(tired, fresh)))
assert _by_shift(solution, "s1") == ("fresh",)
assert set(_by_shift(solution, "s1")) == {"tired", "fresh"}
def test_daily_cumulative_hours_no_longer_penalized():
# Le solveur ne plafonne plus le cumul de 8 h/jour (retiré) : seule la
# validation, à la confirmation, le signale désormais
# (`DAILY_HOURS_EXCEEDED`). Repos respecté (8 h pile) ; cumul du jour
# (7 h + 2 h = 9 h) aurait auparavant été pénalisé.
# Aucun plafond de cumul journalier : 7 h + 2 h = 9 h sur la journée ne
# pénalise pas le bénévole.
shift = _shift(ideal_staff=2, start=_dt(10, 21), end=_dt(10, 23))
long_day = _volunteer(
"long_day",
availability=[_full_day(10)],
existing_shifts=[ShiftInfo(id="e", starts_at=_dt(10, 6), ends_at=_dt(10, 13))],
)
fresh = _volunteer("fresh", availability=[_full_day(10)])
fresh = _volunteer("fresh")
solution = solve(SolverInput(shifts=(shift,), volunteers=(long_day, fresh)))
assert set(_by_shift(solution, "s1")) == {"long_day", "fresh"}
def test_prefers_volunteer_without_the_immediately_preceding_shift():
# Repos suffisant (8 h pile) entre les deux créneaux : seul le chaînage
# doit différencier les deux bénévoles.
# Seul le chaînage doit différencier les deux bénévoles.
shift = _shift(start=_dt(10, 20), end=_dt(10, 23), predecessor_shift_ids={"prev"})
chained = _volunteer(
"chained",
availability=[_full_day(10)],
existing_shifts=[ShiftInfo(id="prev", starts_at=_dt(10, 8), ends_at=_dt(10, 12))],
)
fresh = _volunteer("fresh", availability=[_full_day(10)])
fresh = _volunteer("fresh")
solution = solve(SolverInput(shifts=(shift,), volunteers=(chained, fresh)))
assert _by_shift(solution, "s1") == ("fresh",)
@@ -196,10 +162,9 @@ def test_chain_penalty_applies_across_different_positions():
)
chained = _volunteer(
"chained",
availability=[_full_day(10)],
existing_shifts=[ShiftInfo(id="prev", starts_at=_dt(10, 8), ends_at=_dt(10, 12))],
)
fresh = _volunteer("fresh", availability=[_full_day(10)])
fresh = _volunteer("fresh")
solution = solve(SolverInput(shifts=(shift,), volunteers=(chained, fresh)))
assert _by_shift(solution, "s1") == ("fresh",)
@@ -210,7 +175,6 @@ def test_still_suggests_the_only_candidate_despite_chaining():
shift = _shift(start=_dt(10, 20), end=_dt(10, 23), predecessor_shift_ids={"prev"})
chained = _volunteer(
"chained",
availability=[_full_day(10)],
existing_shifts=[ShiftInfo(id="prev", starts_at=_dt(10, 8), ends_at=_dt(10, 12))],
)
solution = solve(SolverInput(shifts=(shift,), volunteers=(chained,)))
@@ -227,9 +191,9 @@ def test_an_unrelated_existing_shift_does_not_trigger_the_chain_penalty():
)
unrelated = ShiftInfo(id="not-the-predecessor", starts_at=_dt(10, 8), ends_at=_dt(10, 12))
almost_chained = _volunteer(
"almost_chained", availability=[_full_day(10)], existing_shifts=[unrelated]
"almost_chained", existing_shifts=[unrelated]
)
truly_fresh = _volunteer("truly_fresh", availability=[_full_day(10)])
truly_fresh = _volunteer("truly_fresh")
solution = solve(SolverInput(shifts=(shift,), volunteers=(almost_chained, truly_fresh)))
assert set(_by_shift(solution, "s1")) == {"almost_chained", "truly_fresh"}
@@ -241,9 +205,9 @@ def test_avoids_volunteer_whose_wished_artist_plays_during_the_shift():
shift = _shift(start=_dt(10, 14), end=_dt(10, 18))
passage = ShiftInfo(id="art1", starts_at=_dt(10, 16), ends_at=_dt(10, 17))
fan = _volunteer(
"fan", availability=[_full_day(10)], wished_artist_windows=[passage]
"fan", wished_artist_windows=[passage]
)
indiff = _volunteer("indiff", availability=[_full_day(10)])
indiff = _volunteer("indiff")
solution = solve(SolverInput(shifts=(shift,), volunteers=(fan, indiff)))
assert _by_shift(solution, "s1") == ("indiff",)
@@ -254,7 +218,7 @@ def test_still_suggests_the_only_candidate_despite_an_artist_conflict():
shift = _shift(start=_dt(10, 14), end=_dt(10, 18))
passage = ShiftInfo(id="art1", starts_at=_dt(10, 16), ends_at=_dt(10, 17))
fan = _volunteer(
"fan", availability=[_full_day(10)], wished_artist_windows=[passage]
"fan", wished_artist_windows=[passage]
)
solution = solve(SolverInput(shifts=(shift,), volunteers=(fan,)))
assert _by_shift(solution, "s1") == ("fan",)
@@ -266,7 +230,7 @@ def test_artist_conflict_outside_shift_hours_has_no_effect():
shift = _shift(start=_dt(10, 14), end=_dt(10, 18))
passage = ShiftInfo(id="art1", starts_at=_dt(10, 20), ends_at=_dt(10, 21))
fan = _volunteer(
"fan", availability=[_full_day(10)], wished_artist_windows=[passage]
"fan", wished_artist_windows=[passage]
)
solution = solve(SolverInput(shifts=(shift,), volunteers=(fan,)))
assert _by_shift(solution, "s1") == ("fan",)
@@ -277,9 +241,9 @@ def test_prefers_volunteer_whose_wished_companion_is_already_on_the_shift():
# préféré à « stranger », qui n'a pas ce lien.
shift = _shift(ideal_staff=2, already_assigned=1, assigned_volunteer_ids={"copain"})
buddy = _volunteer(
"buddy", availability=[_full_day(10)], wished_companion_ids={"copain"}
"buddy", wished_companion_ids={"copain"}
)
stranger = _volunteer("stranger", availability=[_full_day(10)])
stranger = _volunteer("stranger")
solution = solve(SolverInput(shifts=(shift,), volunteers=(buddy, stranger)))
assert _by_shift(solution, "s1") == ("buddy",)
@@ -290,10 +254,10 @@ def test_companion_bonus_scales_with_number_of_matches():
ideal_staff=4, already_assigned=2, assigned_volunteer_ids={"a", "b"}
)
two_friends = _volunteer(
"two_friends", availability=[_full_day(10)], wished_companion_ids={"a", "b"}
"two_friends", wished_companion_ids={"a", "b"}
)
one_friend = _volunteer(
"one_friend", availability=[_full_day(10)], wished_companion_ids={"a"}
"one_friend", wished_companion_ids={"a"}
)
solution = solve(SolverInput(shifts=(shift,), volunteers=(two_friends, one_friend)))
assert _by_shift(solution, "s1") == ("two_friends", "one_friend")
@@ -302,7 +266,7 @@ def test_companion_bonus_scales_with_number_of_matches():
def test_wished_companion_absent_from_the_shift_has_no_effect():
shift = _shift()
volunteer = _volunteer(
"v", availability=[_full_day(10)], wished_companion_ids={"not-here"}
"v", wished_companion_ids={"not-here"}
)
solution = solve(SolverInput(shifts=(shift,), volunteers=(volunteer,)))
assert _by_shift(solution, "s1") == ("v",)