def test_one(self):
"""
All start values valid, only one end value valid, 1/3 rooms returns
"""
r1 = pd.DataFrame({
"start": [datetime.datetime(2020, 7, 7)],
"end": [datetime.datetime(2020, 7, 31)],
})
r2 = pd.DataFrame({
"start": [datetime.datetime(2020, 6, 9)],
"end": [datetime.datetime(2020, 6, 30)],
})
r3 = pd.DataFrame({
"start": [datetime.datetime(2020, 8, 5)],
"end": [datetime.datetime(2020, 8, 31)],
})
r1 = (r1.set_index(r1["start"]).rename(columns={
"end": "1"
}).drop("start", axis=1))
r2 = (r2.set_index(r2["start"]).rename(columns={
"end": "2"
}).drop("start", axis=1))
r3 = (r3.set_index(r3["start"]).rename(columns={
"end": "3"
}).drop("start", axis=1))
data = pd.concat([r1, r2, r3], axis=1, sort=False)
start = datetime.datetime(2020, 8, 22)
end = datetime.datetime(2020, 8, 28)
result = get_room_number_optimized(data, start, end)
answer = pd.DataFrame({"room": ["3"], "order": [3]})
assert_frame_equal(result.reset_index(drop=True),
answer.reset_index(drop=True))
def test_one_value(self):
"""
One unique value each, 2/3 rooms returns
"""
r1 = pd.DataFrame({
"start": [datetime.datetime(2020, 8, 7)],
"end": [datetime.datetime(2022, 12, 31)],
})
r2 = pd.DataFrame({
"start": [datetime.datetime(2020, 10, 9)],
"end": [datetime.datetime(2022, 12, 31)],
})
r3 = pd.DataFrame({
"start": [datetime.datetime(2020, 6, 5)],
"end": [datetime.datetime(2022, 12, 31)],
})
r1 = (r1.set_index(r1["start"]).rename(columns={
"end": "1"
}).drop("start", axis=1))
r2 = (r2.set_index(r2["start"]).rename(columns={
"end": "2"
}).drop("start", axis=1))
r3 = (r3.set_index(r3["start"]).rename(columns={
"end": "3"
}).drop("start", axis=1))
data = pd.concat([r1, r2, r3], axis=1, sort=False)
start = datetime.datetime(2020, 8, 22)
end = datetime.datetime(2020, 8, 28)
result = get_room_number_optimized(data, start, end)
answer = pd.DataFrame({"room": ["1", "3"], "order": [15, 78]})
assert_frame_equal(result.reset_index(drop=True),
answer.reset_index(drop=True))
def test_all_same_value(self):
"""
Allow multiple same value
"""
r1 = pd.DataFrame({
"start": [
datetime.datetime(2020, 8, 7),
datetime.datetime(2020, 8, 20),
],
"end": [
datetime.datetime(2020, 8, 12),
datetime.datetime(2022, 12, 31),
],
})
r2 = pd.DataFrame({
"start": [
datetime.datetime(2020, 8, 7),
datetime.datetime(2020, 8, 20),
],
"end": [
datetime.datetime(2020, 8, 12),
datetime.datetime(2022, 12, 31),
],
})
r3 = pd.DataFrame({
"start": [
datetime.datetime(2020, 8, 7),
datetime.datetime(2020, 8, 20),
],
"end": [
datetime.datetime(2020, 8, 12),
datetime.datetime(2022, 12, 31),
],
})
r1 = (r1.set_index(r1["start"]).rename(columns={
"end": "1"
}).drop("start", axis=1))
r2 = (r2.set_index(r2["start"]).rename(columns={
"end": "2"
}).drop("start", axis=1))
r3 = (r3.set_index(r3["start"]).rename(columns={
"end": "3"
}).drop("start", axis=1))
data = pd.concat([r1, r2, r3], axis=1, sort=False)
start = datetime.datetime(2020, 8, 22)
end = datetime.datetime(2020, 8, 28)
result = get_room_number_optimized(data, start, end)
answer = pd.DataFrame({"room": ["1", "2", "3"], "order": [2, 2, 2]})
assert_frame_equal(result.reset_index(drop=True),
answer.reset_index(drop=True))
def test_no_rooms(self):
"""
No rooms found!
"""
r1 = pd.DataFrame({
"start": [
datetime.datetime(2020, 8, 7),
datetime.datetime(2020, 8, 20),
],
"end": [
datetime.datetime(2020, 8, 12),
datetime.datetime(2022, 12, 31),
],
})
r2 = pd.DataFrame({
"start": [
datetime.datetime(2020, 8, 7),
datetime.datetime(2020, 8, 20),
],
"end": [
datetime.datetime(2020, 8, 12),
datetime.datetime(2022, 12, 31),
],
})
r3 = pd.DataFrame({
"start": [
datetime.datetime(2020, 8, 7),
datetime.datetime(2020, 8, 20),
],
"end": [
datetime.datetime(2020, 8, 12),
datetime.datetime(2022, 12, 31),
],
})
r1 = (r1.set_index(r1["start"]).rename(columns={
"end": "1"
}).drop("start", axis=1))
r2 = (r2.set_index(r2["start"]).rename(columns={
"end": "2"
}).drop("start", axis=1))
r3 = (r3.set_index(r3["start"]).rename(columns={
"end": "3"
}).drop("start", axis=1))
data = pd.concat([r1, r2, r3], axis=1, sort=False)
start = datetime.datetime(2020, 8, 10)
end = datetime.datetime(2020, 8, 28)
result = get_room_number_optimized(data, start, end)
self.assertTrue(result.empty)
def test_standard(self):
"""
Values used during development
"""
r1 = pd.DataFrame({
"start": [
datetime.datetime(2020, 8, 10),
datetime.datetime(2020, 9, 22),
],
"end":
[datetime.datetime(2020, 9, 3),
datetime.datetime(2022, 12, 31)],
})
r2 = pd.DataFrame({
"start": [
datetime.datetime(2020, 7, 12),
datetime.datetime(2020, 8, 2),
datetime.datetime(2020, 10, 3),
],
"end": [
datetime.datetime(2020, 7, 18),
datetime.datetime(2020, 8, 30),
datetime.datetime(2022, 12, 31),
],
})
r3 = pd.DataFrame({
"start": [datetime.datetime(2020, 8, 15)],
"end": [datetime.datetime(2022, 12, 31)],
})
r1 = (r1.set_index(r1["start"]).rename(columns={
"end": "1"
}).drop("start", axis=1))
r2 = (r2.set_index(r2["start"]).rename(columns={
"end": "2"
}).drop("start", axis=1))
r3 = (r3.set_index(r3["start"]).rename(columns={
"end": "3"
}).drop("start", axis=1))
data = pd.concat([r1, r2, r3], axis=1, sort=False)
start = datetime.datetime(2020, 8, 22)
end = datetime.datetime(2020, 8, 28)
result = get_room_number_optimized(data, start, end)
answer = pd.DataFrame({"room": ["2", "1", "3"], "order": [2, 6, 7]})
# Ignore index values
# np.array_equal(result.values,answer.values)
assert_frame_equal(result.reset_index(drop=True),
answer.reset_index(drop=True))
def reserve_dates(config, client_id, room_type, start, end):
"""
Find ideal rooms based on criteria given.
Usage:\n
hotel reserve-dates client_id room_type start_date end_date\n
Arguments:\n
client_id is type INT\n
room_type is type INT\n
start_date is format %Y-%m-%d\n
end_date is format %Y-%m-%d\n
Description:\n
This commmand returns a list of rooms that match the criteria given\n
Rooms are ordered by the minimal disruption of free intervals\n
Creates new reservation in rooms/reservations/{best_room}.csv\n
Splits and adds new interverl in rooms/interval/{best_rom}.csv\n
Updates client_list.csv with new informtion, reserved state = 2
"""
helpers.handle_session()
if client_id in config.client_list.index:
if config.client_list.loc[client_id, "state"] == 3:
hotel_path = helpers.get_hotel_path()
full_path = os.path.join(config.cwd_path, hotel_path)
room_matching_type = helpers.get_room_of_type(
config.hotel, room_type)
df_intervals = config.intervals[room_matching_type].dropna(
axis=0, how="all")
available_rooms = helpers.get_room_number_optimized(
df_intervals, start, end)
delta = end - start
if available_rooms.empty:
click.echo("Sorry! There are no rooms available!")
else:
best_room = available_rooms["room"][0]
payment = helpers.get_payment(config.hotel, best_room)
payment_due = delta.days * payment
paid = False
helpers.add_reservation_client_list(
config.client_list,
client_id,
2,
start,
end,
best_room,
payment_due,
paid,
)
helpers.overwrite_client_list(config.client_list, full_path)
helpers.add_reservations(config.reservations, best_room,
client_id, start)
helpers.overwrite_reservations(config.reservations,
config.cwd_path, hotel_path,
best_room)
helpers.add_intervals(config.intervals, best_room, start, end,
hotel_path)
helpers.overwrite_intervals(config.intervals, config.cwd_path,
hotel_path, best_room)
click.echo("Reservation successful!")
else:
click.echo(
f"The client ID {client_id} is currently unable to accept a new reservation. Please verify the current client state"
)
else:
click.echo(
f"The client ID {client_id} does not exist. Please use a valid client ID"
)