48 lines
1.7 KiB
Python
48 lines
1.7 KiB
Python
import requests
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from bs4 import BeautifulSoup
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from datetime import datetime, timedelta
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import requests_cache
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from ..util import Context, Prediction
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requests_cache.install_cache("requests_cache", expire_after=timedelta(minutes=10))
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def is_restaurant_open(name, open, close) -> Prediction:
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p = Prediction()
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headers = {
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'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_3) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/35.0.1916.47 Safari/537.36'}
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r = requests.get("https://www.just-eat.dk/area/8000-århusc", headers=headers)
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soup = BeautifulSoup(r.content, features='html5lib')
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listing_groups = soup.find_all('div', {'class': 'listing-group'})
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#p.reasons.append("Hopefully we are not banned from Just-eat ..")
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nice_group = None
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for x in listing_groups:
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if x['data-test-id'] == 'listingGroupOpen':
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nice_group = x
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if nice_group is None:
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p.reasons.append("Apparently we are banned from just-eat. We therefore have no clue.")
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p.probability = 0.5
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return p
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all_listings = nice_group.find_all('a', {'class': 'mediaElement'})
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if any(name in x['href'] for x in all_listings):
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p.reasons.append(f"Our favorite pizza place, {name}, is currently open.")
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p.reasons.append(f"We conclude from this, that there is {1 / 11}% chance of it being night outside")
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p.probability = 1 / 11
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else:
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p.reasons.append(f"Our favorite pizza place, {name}, is closed.")
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p.reasons.append(f"We can conclude from this, that there is {1 - (1/11)}% chance of it currently being night outside!")
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p.probability = 1 - (1 / 11)
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return p
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def do_just_eat_strat(context: Context) -> Prediction:
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return is_restaurant_open('stop2shop', 12, 23)
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