Benjamin Admin
f042f2896b
school-service additions:
- tt_solution + tt_lesson migration. tt_lesson carries three UNIQUEs
(solution+class, solution+teacher, solution+room per slot) so the
DB itself rejects any double-booking the solver might emit by
mistake.
- Solution CRUD + GET solutions/:id/lessons endpoint with joined
class/subject/teacher/room names for display.
- POST /timetable/solutions creates the row then fires off the
solver-service via HTTP (5s timeout, mark failed if unreachable).
- SOLVER_SERVICE_URL config wired through main.go/handlers.
New service timetable-solver-service:
- Python 3.11 + FastAPI + Timefold Solver 1.21 (Apache-2.0). Dockerfile
bundles OpenJDK 17 since Timefold for Python is a JPype bridge.
- app/domain.py — Timefold @planning_entity Lesson with timeslot+room
as PlanningVariables; @planning_solution Timetable holds problem
facts (rooms/teachers/etc.) AND rule-fact collections.
- app/rules.py — frozen dataclasses mirroring 6 of the 15 tt_
constraint_* tables initially.
- app/constraints.py — ConstraintProvider with 3 universal hard
constraints (no double-booking) + 5 DB-driven constraints
(teacher_unavailable_day/window, teacher_excluded_room,
room_unavailable, room_requires_type) + 1 quality soft constraint
(subject_preferred_period). Remaining 9 constraint types ready to
plug in via the same join pattern.
- app/repository.py — async loaders for stammdaten + rules; builds
one Lesson per (curriculum row × weekly_hours), skipping rows
without a tt_assignment teacher.
- app/runner.py — runs solver in ThreadPoolExecutor so the FastAPI
event loop stays responsive. Updates tt_solution status
pending→running→completed|infeasible|failed.
- app/main.py — POST /api/v1/solve (202 Accepted, background task),
GET /api/v1/jobs/{id}, /health. School-service polls tt_solution
directly instead of GET /jobs for the typical case.
- docker-compose.yml adds the service on port 8095, depending on
core-health-check.
Tests:
- school-service: validator test for CreateTimetableSolutionRequest
(allows empty name).
- solver-service: tests/test_domain.py + tests/test_rules.py cover
construction + hashability of the planning facts. Full solve flow
deferred to Phase 8 integration with seed data.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
52 lines
1.5 KiB
Python
52 lines
1.5 KiB
Python
"""Unit tests for the planning domain dataclasses.
|
|
|
|
These tests deliberately avoid spinning up the JVM-backed solver — they
|
|
only verify that the domain objects construct, serialise, and compare as
|
|
expected. The full solver lifecycle is exercised by integration tests run
|
|
against a populated DB (Phase 8).
|
|
"""
|
|
|
|
from app.domain import Lesson, Room, SchoolClass, Subject, Teacher, Timeslot
|
|
|
|
|
|
def _ts() -> Timeslot:
|
|
return Timeslot(id="ts1", day_of_week=1, period_index=1, start_time="08:00", end_time="08:45")
|
|
|
|
|
|
def _room() -> Room:
|
|
return Room(id="r1", name="A101", room_type="standard")
|
|
|
|
|
|
def _teacher() -> Teacher:
|
|
return Teacher(id="t1", last_name="Schmidt", first_name="Anna", short_code="SCH")
|
|
|
|
|
|
def _class() -> SchoolClass:
|
|
return SchoolClass(id="c1", name="5a", grade_level=5)
|
|
|
|
|
|
def _subject() -> Subject:
|
|
return Subject(id="s1", name="Mathematik", short_code="M")
|
|
|
|
|
|
def test_timeslot_str() -> None:
|
|
assert str(_ts()) == "D1P1"
|
|
|
|
|
|
def test_teacher_str() -> None:
|
|
assert str(_teacher()) == "Schmidt, Anna"
|
|
|
|
|
|
def test_lesson_starts_unassigned() -> None:
|
|
lesson = Lesson(id="L1", school_class=_class(), subject=_subject(), teacher=_teacher())
|
|
assert lesson.timeslot is None
|
|
assert lesson.room is None
|
|
|
|
|
|
def test_lesson_accepts_assignment() -> None:
|
|
lesson = Lesson(id="L1", school_class=_class(), subject=_subject(), teacher=_teacher())
|
|
lesson.timeslot = _ts()
|
|
lesson.room = _room()
|
|
assert lesson.timeslot.day_of_week == 1
|
|
assert lesson.room.name == "A101"
|