major test refactoring
This commit is contained in:
Ross
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import pytest
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import datetime
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from rota.shifts import RotaBuilder, SingleShift, days
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from rota.workers import Worker
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@pytest.fixture
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def limit_constraint_rota():
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weeks_to_rota = 8
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start_date = datetime.date(2022, 3, 7)
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Rota = RotaBuilder(
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start_date,
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weeks_to_rota=weeks_to_rota,
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)
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worker1 = Worker(name="worker1", site="group1", grade=2, remote_site="group1")
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worker2 = Worker(name="worker2", site="group1", grade=2, remote_site="group1")
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worker3 = Worker(name="worker3", site="group1", grade=2, remote_site="group1")
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worker4 = Worker(name="worker4", site="group3", grade=3, remote_site="group2")
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worker5 = Worker(name="worker5", site="group3", grade=3, remote_site="group2")
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worker6 = Worker(name="worker6", site="group3", grade=3, remote_site="group2")
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Rota.add_workers((worker1, worker2, worker3, worker4, worker5, worker6))
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Rota.shifts = []
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return Rota
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def test_constraint_limit_grades(limit_constraint_rota):
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Rota = limit_constraint_rota
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Rota.shifts = []
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Rota.add_shifts(
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SingleShift(
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sites=("group1", "group2", "group3"),
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name="weekday_night",
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length=12.5,
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days=days,
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balance_offset=60,
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workers_required=4,
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force_as_block=True,
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constraint=[{"name": "limit_grade_number", "options": {2: 1}}],
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),
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)
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Rota.build_and_solve(options={"ratio": 0.01})
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Rota.export_rota_to_html("constraint_limit_grades", folder="tests")
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assert Rota.results.solver.status == "ok"
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assert Rota.results.solver.termination_condition == "optimal"
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grade_workers = Rota.get_workers_by_grade()
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for grade in grade_workers:
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shift_patterns = [Rota.get_worker_shift_list(w) for w in grade_workers[grade]]
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zipped_lists = list(zip(*shift_patterns))
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limit = 1 if grade == 2 else 3
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for day_shifts in zipped_lists:
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assert day_shifts.count("weekday_night") == limit
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def test_constraint_limit_grades2(limit_constraint_rota):
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Rota = limit_constraint_rota
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Rota.shifts = []
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Rota.add_shifts(
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SingleShift(
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sites=("group1", "group2", "group3"),
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name="weekday_night",
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length=12.5,
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days=days,
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balance_offset=40,
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workers_required=4,
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force_as_block=True,
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constraint=[{"name": "limit_grade_number", "options": {3: 2}}],
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),
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)
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Rota.constraint_options["balance_shifts_quadratic"] = True
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Rota.build_and_solve(options={"ratio": 0.1})
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Rota.export_rota_to_html("test9")
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grade_workers = Rota.get_workers_by_grade()
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for grade in grade_workers:
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shift_patterns = [Rota.get_worker_shift_list(w) for w in grade_workers[grade]]
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zipped_lists = list(zip(*shift_patterns))
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limit = 2 if grade == 3 else 2
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for day_shifts in zipped_lists:
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assert day_shifts.count("weekday_night") == limit
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assert Rota.results.solver.status == "ok"
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assert Rota.results.solver.termination_condition == "optimal"
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def test_constraint_limit_grades3(limit_constraint_rota):
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Rota = limit_constraint_rota
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Rota.workers = []
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worker1 = Worker(name="worker1", site="group1", grade=2, remote_site="group1")
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worker2 = Worker(name="worker2", site="group1", grade=2, remote_site="group1")
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worker3 = Worker(name="worker3", site="group1", grade=2, remote_site="group1")
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worker4 = Worker(name="worker4", site="group3", grade=3, remote_site="group2")
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worker5 = Worker(name="worker5", site="group3", grade=3, remote_site="group2")
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worker6 = Worker(name="worker6", site="group3", grade=3, remote_site="group2")
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worker7 = Worker(name="worker7", site="group3", grade=2, remote_site="group2")
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Rota.add_workers((worker1, worker2, worker3, worker4, worker5, worker6, worker7))
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Rota.add_shifts(
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SingleShift(
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sites=("group1", "group2", "group3"),
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name="weekday_night",
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length=12.5,
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days=days,
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balance_offset=60,
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workers_required=4,
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force_as_block=True,
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constraint=[{"name": "limit_grade_number", "options": {2: 3, 3: 1}}],
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),
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)
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Rota.constraint_options["balance_shifts_quadratic"] = True
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Rota.build_and_solve(options={"ratio": 0.01})
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Rota.export_rota_to_html("test9")
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assert Rota.results.solver.status == "ok"
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assert Rota.results.solver.termination_condition == "optimal"
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grade_workers = Rota.get_workers_by_grade()
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for grade in grade_workers:
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shift_patterns = [Rota.get_worker_shift_list(w) for w in grade_workers[grade]]
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zipped_lists = list(zip(*shift_patterns))
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limit = 3 if grade == 2 else 1
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for day_shifts in zipped_lists:
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assert day_shifts.count("weekday_night") == limit
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def test_constraint_limit_grades4(limit_constraint_rota):
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Rota = limit_constraint_rota
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Rota.shifts = []
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Rota.add_shifts(
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SingleShift(
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sites=("group1", "group2", "group3"),
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name="weekday_night",
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length=12.5,
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days=days,
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balance_offset=40,
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workers_required=4,
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force_as_block=True,
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constraint=[{"name": "limit_grade_number", "options": {2: 4, 3: 0}}],
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),
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)
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Rota.constraint_options["balance_shifts_quadratic"] = True
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Rota.build_and_solve(options={"ratio": 0.1})
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assert Rota.results.solver.termination_condition == "infeasible"
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def test_constraint_minimum_grades(limit_constraint_rota):
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Rota = limit_constraint_rota
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Rota.shifts = []
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Rota.add_shifts(
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SingleShift(
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sites=("group1", "group2", "group3"),
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name="weekday_night",
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length=12.5,
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days=days,
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balance_offset=40,
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workers_required=1,
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force_as_block=True,
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constraint=[{"name": "minimum_grade_number", "options": (3, 1)}],
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),
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)
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Rota.constraint_options["balance_shifts_quadratic"] = True
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Rota.build_and_solve(options={"ratio": 0.1})
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Rota.export_rota_to_html("test9")
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assert Rota.results.solver.status == "ok"
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grade_workers = Rota.get_workers_by_grade()
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for grade in grade_workers:
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shift_patterns = [Rota.get_worker_shift_list(w) for w in grade_workers[grade]]
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zipped_lists = list(zip(*shift_patterns))
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limit = 1 if grade > 2 else 0
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for day_shifts in zipped_lists:
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assert day_shifts.count("weekday_night") == limit
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def test_constraint_minimum_grades2(limit_constraint_rota):
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Rota = limit_constraint_rota
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Rota.shifts = []
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Rota.add_shifts(
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SingleShift(
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sites=("group1", "group2", "group3"),
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name="weekday_night",
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length=12.5,
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days=days,
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balance_offset=40,
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workers_required=4,
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force_as_block=True,
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constraint=[{"name": "minimum_grade_number", "options": (3, 3)}],
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),
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)
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Rota.constraint_options["balance_shifts_quadratic"] = True
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Rota.build_and_solve(options={"ratio": 0.1})
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Rota.export_rota_to_html("test9")
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grade_workers = Rota.get_workers_by_grade()
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for grade in grade_workers:
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shift_patterns = [Rota.get_worker_shift_list(w) for w in grade_workers[grade]]
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zipped_lists = list(zip(*shift_patterns))
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limit = 3 if grade > 2 else 1
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for day_shifts in zipped_lists:
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assert day_shifts.count("weekday_night") == limit
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assert Rota.results.solver.status == "ok"
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def test_constraint_minimum_grades3(limit_constraint_rota):
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Rota = limit_constraint_rota
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Rota.shifts = []
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Rota.add_shifts(
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SingleShift(
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sites=("group1", "group2", "group3"),
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name="weekday_night",
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length=12.5,
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days=days,
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balance_offset=40,
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workers_required=4,
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force_as_block=True,
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constraint=[{"name": "minimum_grade_number", "options": (3, 0)}],
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),
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)
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Rota.constraint_options["balance_shifts_quadratic"] = True
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Rota.build_and_solve(options={"ratio": 0.1})
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Rota.export_rota_to_html("test9")
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assert Rota.results.solver.status == "ok"
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def test_constraint_minimum_grades_no_valid_worker(limit_constraint_rota):
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Rota = limit_constraint_rota
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Rota.shifts = []
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Rota.add_shifts(
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SingleShift(
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sites=("group1", "group2", "group3"),
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name="weekday_night",
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length=12.5,
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days=days,
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balance_offset=40,
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workers_required=4,
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force_as_block=True,
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constraint=[{"name": "minimum_grade_number", "options": (4, 1)}],
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),
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)
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Rota.constraint_options["balance_shifts_quadratic"] = True
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with pytest.raises(ValueError):
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Rota.build_and_solve(options={"ratio": 0.1})
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def test_constraint_require_remote_site_presence_week(limit_constraint_rota):
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Rota = limit_constraint_rota
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Rota.shifts = []
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Rota.add_shifts(
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SingleShift(
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sites=("group1", "group2", "group3"),
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name="night",
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length=12.5,
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days=days,
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balance_offset=40,
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workers_required=2,
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force_as_block=True,
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constraint=[
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{
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"name": "require_remote_site_presence_week",
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"options": ("group1", 2),
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}
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],
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),
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)
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Rota.build_and_solve(options={"ratio": 0.00})
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Rota.export_rota_to_html("remote1")
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group_workers = Rota.get_workers_by_group()
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for group in group_workers:
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shift_patterns = [Rota.get_worker_shift_list(w) for w in group_workers[group]]
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zipped_lists = list(zip(*shift_patterns))
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limit = 2 if group == "group1" else 0
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for day_shifts in zipped_lists:
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assert day_shifts.count("night") == limit
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assert Rota.results.solver.status == "ok"
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assert Rota.results.solver.termination_condition == "optimal"
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def test_constraint_require_remote_site_presence_week2(limit_constraint_rota):
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Rota = limit_constraint_rota
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Rota.constraint_options["minimise_shift_diffs"] = False
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Rota.constraint_options["balance_shifts_quadratic"] = False
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Rota.constraint_options["balance_shift"] = False
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Rota.constraint_options["balance_nights_across_sites"] = True
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Rota.shifts = []
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Rota.add_shifts(
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SingleShift(
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sites=("group1", "group2", "group3"),
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name="night",
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length=12.5,
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days=days,
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balance_offset=20,
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workers_required=3,
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force_as_block=True,
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constraint=[
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{
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"name": "require_remote_site_presence_week",
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"options": ("group1", 2),
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}
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],
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),
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)
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Rota.build_and_solve(options={"ratio": 0.00})
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Rota.export_rota_to_html("remote2")
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group_workers = Rota.get_workers_by_remote_group()
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for group in group_workers:
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shift_patterns = [Rota.get_worker_shift_list(w) for w in group_workers[group]]
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zipped_lists = list(zip(*shift_patterns))
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if group == "group1":
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for day_shifts in zipped_lists:
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assert day_shifts.count("night") >= 2
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assert Rota.results.solver.status == "ok"
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assert Rota.results.solver.termination_condition == "optimal"
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def test_constraint_require_remote_site_presence_week3(limit_constraint_rota):
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Rota = limit_constraint_rota
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Rota.shifts = []
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Rota.add_shifts(
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SingleShift(
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sites=("group1", "group2", "group3"),
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name="night",
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length=12.5,
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days=days,
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balance_offset=20,
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workers_required=3,
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force_as_block=True,
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constraint=[
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{
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"name": "require_remote_site_presence_week",
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"options": ("group2", 1),
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}
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],
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),
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)
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Rota.build_and_solve(options={"ratio": 0.00})
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Rota.export_rota_to_html("remote3")
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group_workers = Rota.get_workers_by_remote_group()
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for group in group_workers:
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shift_patterns = [Rota.get_worker_shift_list(w) for w in group_workers[group]]
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zipped_lists = list(zip(*shift_patterns))
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if group == "group2":
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for day_shifts in zipped_lists:
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assert day_shifts.count("night") >= 1
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assert Rota.results.solver.status == "ok"
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assert Rota.results.solver.termination_condition == "optimal"
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