Scrape the website of Danish Health Services SST to obtain their daily updated statistics about the covid19 epidemic.

sst_scrape.py

#! /usr/bin/env python3

# Scrape the website of Danish Health Services SST to obtain their
# daily updated statistics about the covid19 epidemic. The function
# `scrape` returns a dict with data from Denmark, Faeroe Islands,
# global and EU+EAA+UK. It looks like this (2020-03-12):
#
#{'Danmark': (3038, 674, 0),
# 'Færøerne': (92, 2, 0),
# 'Globalt': (None, 125518, 4617),
# 'EU,EØS og UK': (None, 22105, 943)}
#
# Cells without known data contain None (basically the number of
# tested patients globally and in the EU).
#
# This software is distributed according to the GPL-3 license.
# See https://www.gnu.org/licenses/gpl-3.0-standalone.html
# (C) Morten Kjeldgaard, 2020.

from bs4 import BeautifulSoup
import requests

url = "https://www.sst.dk/da/Viden/Smitsomme-sygdomme/Smitsomme-sygdomme-A-AA/Coronavirus/Spoergsmaal-og-svar"

def scrape():
    page = requests.get(url)
    soup = BeautifulSoup(page.content, 'html.parser')

    data = []
    content = soup.select("div.o-content-block__content--push-bottom")
    table_responsive = soup.find(class_='table-responsive')
    table_body = table_responsive.find('tbody')
    rows = table_body.find_all('tr')
    for row in rows:
        cols = row.find_all('td')
        cols = [e.text.strip() for e in cols]
        data.append([e for e in cols if e]) # Get rid of empty values
    #.

    # We scraped information into `data` convert to ints and
    # store in a dict for the user.
    D = {}
    for j in range(1,5):
        region = data[j][0]
        try:
            tested = int(data[j][1].replace('.',''))
        except:
            tested = None
        positive = int(data[j][2].replace('.',''))
        dead = int(data[j][3].replace('.',''))
        D[region] = (tested, positive, dead)
    #.
    return D
#.

if __name__ == "__main__":

    D = scrape()
    print("Antal smittede i dag (SST):", D['Danmark'][1])
#.