More shit
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import requests
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from bs4 import BeautifulSoup
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import pandas as pd
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import urllib.request
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from datetime import datetime, timedelta
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import json
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import os
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def determine_month():
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ds = pd.read_excel(urllib.request.urlopen('https://sundogbaelt.dk/wp-content/uploads/2019/04/trafiktal-maaned.xls'))
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cur_year = 2019
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amount_of_cur_year = sum([x == cur_year for x in ds['År']])
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cur_year_total = sum(ds['Total'][1:amount_of_cur_year+1])
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last_year_total = sum(ds['Total'][amount_of_cur_year+1:amount_of_cur_year+13])
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return (12/(last_year_total//cur_year_total))+1
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def is_tide():
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month = determine_month()
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tide_data = requests.get('https://www.dmi.dk/fileadmin/user_upload/Bruger_upload/Tidevand/2019/Aarhus.t.txt')
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lines = tide_data.text[570:].split('\n')
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tuples = [x.split('\t') for x in lines]
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lel = [[datetime.strptime(x[0], '%Y%m%d%H%M'), x[1]] for x in tuples[:-1]]
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matches = [[x[0], int(x[1])] for x in lel if x[0].month == month]
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all_the_data = requests.get('https://www.dmi.dk/NinJo2DmiDk/ninjo2dmidk?cmd=odj&stations=22331&datatype=obs')
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current_water_level = json.loads(all_the_data.content)[0]['values'][-1]['value']
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# Generate average of when the water is high
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last_match = matches[0]
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moments = []
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for idx, water_level in enumerate(matches[1:]):
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#print(last_match[1], water_level[1])
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diff = abs(last_match[1]) + abs(water_level[1])
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time_diff = (water_level[0] - last_match[0]).seconds
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average_inc = time_diff/diff
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average_delta = timedelta(seconds=average_inc)
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if last_match[1] < 0: # Increasing
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time = last_match
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while time[1] != current_water_level:
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time[0] += average_delta
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time[1] += 1
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elif last_match[1] > 0: # Decreasing
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time = last_match
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while time[1] != current_water_level:
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time[0] += average_delta
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time[1] -= 1
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last_match = water_level
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moments.append(time[0])
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night = sum([1 for x in moments if 6 >= x.hour or x.hour >= 22])
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return night / len(moments)
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def tmp():
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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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with open('traffic_data_13_23.json', 'w') as f:
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json.dump(r.json(), f)
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def scrape_traffic():
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@ -23,10 +88,17 @@ def scrape_traffic():
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elif curr_avg <= night_avr:
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return 1.0
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res = 1 - curr_avg / diff
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assert(res < 1 and res > 0)
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return res
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scrape_traffic()
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def scrape_weather():
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r = requests.get('https://weather.com/weather/hourbyhour/l/99546:4:US')
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soup = BeautifulSoup(r.content)
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print(soup.find_all('td', {'class': 'temp'})[0])
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1
server/nightr/traffic_data_13_23.json
Normal file
1
server/nightr/traffic_data_13_23.json
Normal file
File diff suppressed because one or more lines are too long
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