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Simple solution solution in Clear category for Lightbulb More by khudr
from collections import defaultdict
from datetime import datetime, timedelta
from typing import List, Optional, Union, Tuple
def count_sum_light(els: List[datetime]) -> int:
return sum((els[i + 1] - els[i]).total_seconds() for i in range(0, len(els), 2))
def reduce_on_end(els: List[datetime], end_watching: Optional[datetime] = None) -> int:
if not end_watching:
return count_sum_light(els)
for i in range(0, len(els), 2):
if els[i] >= end_watching:
return count_sum_light(els[:i])
if i + 1 == len(els):
return int(count_sum_light(els[:i]) + (end_watching - els[i]).total_seconds())
if els[i] < end_watching < els[i + 1]:
return int((end_watching - els[i]).total_seconds() + count_sum_light(els[:i]))
return count_sum_light(els)
def reduce(
els: List[datetime],
start_watching: Optional[datetime] = None,
end_watching: Optional[datetime] = None,
) -> int:
if not start_watching:
return reduce_on_end(els, end_watching)
for i in range(0, len(els), 2):
if els[i] >= start_watching:
return reduce_on_end(els[i:], end_watching)
if i + 1 == len(els):
return reduce_on_end([start_watching], end_watching)
if els[i + 1] > start_watching:
return int((els[i + 1] - start_watching).total_seconds() + reduce_on_end(els[i + 2:], end_watching))
return 0
def sum_lamp_value(
els: List[Tuple[datetime, int]],
start_watching: Optional[datetime] = None,
end_watching: Optional[datetime] = None,
req: Optional[int] = None
) -> int:
if req is None:
req = 1
active = []
total_light = []
for el in els:
if el[1] in active:
active.remove(el[1])
# проверяем выключился ли свет
if len(active) == req - 1:
total_light.append(el[0])
else:
active.append(el[1])
# включение света
if len(active) == req:
total_light.append(el[0])
return reduce(total_light, start_watching, end_watching)
def group_by_second_el(items):
grouped_items = defaultdict(list)
for date, value in items:
grouped_items[value].append(date)
return [(value, dates) for value, dates in grouped_items.items()]
def sum_light(
els: List[Union[datetime, Tuple[datetime, int]]],
start_watching: Optional[datetime] = None,
end_watching: Optional[datetime] = None,
operating: Optional[timedelta] = None,
req: Optional[int] = None
) -> int:
for el in els:
if isinstance(el, datetime):
els[els.index(el)] = (el, 1)
if not operating:
els.sort(key=lambda el: el[0])
return sum_lamp_value(els, start_watching, end_watching, req)
grouped = group_by_second_el(els)
for lamp in grouped:
times = lamp[1]
cur_time_delta = timedelta()
is_went_out = False
for i in range(0, len(times), 2):
if is_went_out:
els.remove((times[i], lamp[0]))
if i + 1 != len(times):
els.remove((times[i + 1], lamp[0]))
elif i + 1 != len(times):
local_time_delta = (times[i + 1] - times[i])
if local_time_delta > operating - cur_time_delta:
delt = (operating - cur_time_delta)
els[els.index((times[i + 1], lamp[0]))] = (times[i] + delt, lamp[0])
is_went_out = True
cur_time_delta += local_time_delta
else:
els.append((times[i] + (operating - cur_time_delta), lamp[0]))
els.sort(key=lambda el: el[0])
return sum_lamp_value(els, start_watching, end_watching, req)
March 3, 2024
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