61 lines
1.8 KiB
Python
61 lines
1.8 KiB
Python
from tennis import get_time_slots, get_club_address
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from weather import WeatherAPI
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from datetime import timedelta, datetime
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import asyncio as aio
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# Provided by my code monkey Lander
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GOOD_CODES = [1000, 1003, 1006, 1009, 1150, 1153]
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async def get_decent_timeslots(club_id, weather_api_key, days=1):
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club_address = await get_club_address(club_id)
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if club_address is None:
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return None
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weather_api = WeatherAPI(weather_api_key)
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weather_forecasts, timeslots = await aio.gather(
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weather_api.get_hourly_conditions(club_address, days=days),
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get_time_slots(club_id, days=days),
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)
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# Filter out bad weather forecasts & sort them according to date & time
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weather_forecasts = sorted(
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filter(lambda x: x[2] in GOOD_CODES, weather_forecasts), key=lambda x: x[0]
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)
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# Convert weather_forecasts to dict for faster lookups
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weather_forecasts = {
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date_obj: weather_str for date_obj, weather_str, _ in weather_forecasts
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}
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# Filter out non-free timeslots or timeslots in the past
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now = datetime.now()
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timeslots = list(filter(lambda x: x[1] == 0 and x[2] > now, timeslots))
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output = []
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for field_name, _, start_time, duration in timeslots:
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start_hour = start_time.replace(minute=0)
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weather_names = []
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valid = True
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while start_hour < start_time + duration:
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if weather_name := weather_forecasts.get(start_hour):
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weather_names.append(weather_name)
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# If we can't find any information about the timeslot, we assume
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# it's bad
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else:
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valid = False
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break
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start_hour += timedelta(hours=1)
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if valid:
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output.append((field_name, start_time, duration, weather_names))
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return output
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