41 lines
1.2 KiB
Python
41 lines
1.2 KiB
Python
import requests
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from ..util import Prediction, Context
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def cars_in_traffic(context: Context) -> Prediction:
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"""
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How many cars are currently driving around Aarhus?
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"""
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r = requests.get('https://portal.opendata.dk/api/3/action/datastore_search?resource_id=b3eeb0ff-c8a8-4824-99d6-e0a3747c8b0d')
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night_avr = 3.38
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day_avr = 6.98
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p = Prediction()
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data = r.json()
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sum = 0
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len = 0
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for lel in data['result']['records']:
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sum += lel['vehicleCount']
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len += 1
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if sum > 0:
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curr_avg = len / sum
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else:
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curr_avg = 0
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diff = day_avr - night_avr
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if curr_avg >= day_avr:
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p.reasons.append(f"Because {curr_avg:.1f} cars are driving around Aarhus right now and {day_avr:.0f} is the expected number for daytime")
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p.probability = 0.0
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elif curr_avg <= night_avr:
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p.reasons.append(f"Because {curr_avg::.1f} cars are driving around Aarhus right now and {night_avr:.0f} is the expected number for nighttime")
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p.probability = 1.0
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else:
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p.reasons.append(f"Because average for daytime is {day_avr} and average for nighttime is {night_avr:.0f}, but the current average is {curr_avg}")
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res = 1 - curr_avg / diff
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p.probability = res
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return p
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