def parse_weekly_pdf():
sc.add_cert_to_bundle()
base_url = 'https://www.infosan.vd.ch'
d = sc.download(base_url, silent=True)
soup = BeautifulSoup(d, 'html.parser')
html_url = base_url + soup.find(href=re.compile("/publications/covid-19-point-epidemiologique")).get('href')
d = sc.download(html_url, silent=True)
soup = BeautifulSoup(d, 'html.parser')
pdf_url = base_url + soup.find(href=re.compile("\.pdf$")).get('href')
pdf = sc.pdfdownload(pdf_url, silent=True)
"""
29.07.2020
Concernant le traçage des contacts de cas positifs, le 27 juillet, 83 personnes étaient en isolement, 633 en quarantaine de contacts étroits et 901 en quarantaine de retour de voyage.
"""
dd = sc.DayData(canton='VD', url=pdf_url)
year= sc.find('Situation au \d+.*(20\d{2})', pdf)
date = sc.find('Concernant le traçage des contacts de cas positifs, le (\d+.*),', pdf)
dd.datetime = date + ' ' + year
dd.isolated = sc.find('(\d+)\s(personnes|cas\spositifs)\sétaient\sen\sisolement', pdf)
dd.quarantined = text_to_int(sc.find('(\d.\d+|\d+)\scontacts\sétroits\sen\squarantaine\.', pdf))
print(dd)
print('-' * 10)
dd = sc.DayData(canton='VD', url=pdf_url)
date = sc.find('quarantaine. Le (\d+ .*),', pdf)
dd.datetime = date + ' ' + year
dd.quarantine_riskareatravel = text_to_int(sc.find(', (\d.\d+|\d+)\spersonnes\sétaient\sen\squarantaines\ssuite\sà\sun\sretour\sde\svoyage.', pdf))
print(dd)
print('-' * 10)
def parse_weekly_pdf():
pdf_url = svc.get_weekly_pdf_url()
pdf = sc.pdfdownload(pdf_url, silent=True)
"""
29.07.2020
Concernant le traçage des contacts de cas positifs, le 27 juillet, 83 personnes étaient en isolement, 633 en quarantaine de contacts étroits et 901 en quarantaine de retour de voyage.
"""
dd = sc.DayData(canton='VD', url=pdf_url)
year = sc.find('Situation au \d+.*(20\d{2})', pdf)
date = sc.find(
'Concernant le traçage des contacts de cas positifs, le (\d+.*),', pdf)
if not date:
print("isolated/quarantined numbers missing in weekly PDF of VD",
file=sys.stderr)
return
dd.datetime = date + ' ' + year
dd.isolated = sc.find(
'(\d+)\s(personnes|cas\spositifs)\sétaient\sen\sisolement', pdf)
dd.quarantined = text_to_int(
sc.find('(\d.\d+|\d+)\scontacts\sétroits\sen\squarantaine\.', pdf))
print(dd)
print('-' * 10)
dd = sc.DayData(canton='VD', url=pdf_url)
date = sc.find('quarantaine. Le (\d+ .*),', pdf)
dd.datetime = date + ' ' + year
dd.quarantine_riskareatravel = text_to_int(
sc.find(
', (\d.\d+|\d+)\spersonnes\sétaient\sen\squarantaines?\ssuite\sà\sun\sretour\sde\svoyage.',
pdf))
print(dd)
print('-' * 10)
def parse_table(title_pattern, data_url, column_count, parse_fn):
table = soup.find(string=re.compile(title_pattern)).find_parent(
'h2').find_next('div').find('table')
headers = [
" ".join(cell.stripped_strings)
for cell in table.find('tr').find_all('th')
]
for row in table.find_all('tr')[1:]:
dd = sc.DayData(canton='AG', url=data_url)
cells = row.find_all(['td'])
assert len(
cells
) == column_count, f"Number of columns changed: {len(cells)} != {column_count}"
col_num = 0
for cell in cells:
header = headers[col_num]
value = cell.string
value = value.replace("’", "")
value = value.replace("'", "")
dd = parse_fn(dd, value, header)
col_num += 1
print('-' * 10)
print(dd)
def parse_weekly_pdf():
pdf_url = svc.get_weekly_pdf_url()
pdf = sc.pdfdownload(pdf_url, silent=True)
dd = sc.DayData(canton='VD', url=pdf_url)
dd.datetime = sc.find('Point .pid.miologique au (\d+\s+\w+\s+\d{4})', pdf)
dd.cases = text_to_int(
sc.find(
'\s(\d+.\d+)\s+personnes ont .t. test.es positives au SARS-CoV-2.',
pdf))
dd.hospitalized = sc.find(
'(\d+)\s+patients\s+sont\s+actuellement\s+hospitalis.s', pdf)
dd.icu = sc.find('dont\s+(\d+)\s+en\s+soins\s+intensifs', pdf)
assert dd
print(dd)
print('-' * 10)
try:
xls_url = soup.find(
'a', string=re.compile(r'Coronaf.lle\s*im\s*Kanton\s*Schwyz'))['href']
except TypeError:
print("Unable to determine xls url", file=sys.stderr)
sys.exit(1)
xls = sc.xlsdownload(xls_url, silent=True)
rows = sc.parse_xls(xls)
for row in rows:
if not isinstance(row['Datum'], datetime.datetime):
continue
if not is_first:
print('-' * 10)
is_first = False
# TODO: remove when source is fixed
# handle wrong value on 2020-03-25, see issue #631
if row['Datum'].date().isoformat() == '2020-03-25':
row['Bestätigte Fälle (kumuliert)'] = ''
dd = sc.DayData(canton='SZ', url=url)
dd.datetime = row['Datum'].date().isoformat()
if row['Zeit']:
dd.datetime += ' ' + row['Zeit'].time().isoformat()
dd.cases = row['Bestätigte Fälle (kumuliert)']
dd.deaths = row['Todesfälle (kumuliert)']
dd.recovered = row['Genesene (kumuliert)']
print(dd)
text = re.sub(r'\s\s+', ' ', text)
return text.split(' ')
# weekly pdf
pdf_url = sgc.get_gl_pdf_url()
pdf = sc.download_content(pdf_url, silent=True)
content = sc.pdftotext(pdf, page=1)
pdf_date = sc.find(r'Stand: (\d{2}\.\d{2}.\d{4})', content)
pdf_date = sc.date_from_text(pdf_date)
number_of_tests = sc.find(r'PCR-Tests\sKanton Glarus\s(\d+\'?\d+)\s',
content).replace('\'', '')
is_first = True
if number_of_tests:
dd = sc.DayData(canton='GL', url=pdf_url)
dd.datetime = pdf_date
dd.tested = number_of_tests
is_first = False
print(dd)
content = sc.pdftotext(pdf, page=2, raw=True)
dates = split_whitespace(
sc.find(r'\n(\d+\.\d+\s+\d+\.\d+\s+.*)\nMassenquarant.ne', content))
travel_q = split_whitespace(
sc.find(r'\nEinreisequarant.ne\s+(\d.*)\n', content))
isolation = split_whitespace(sc.find(r'\nIsolation\s+(\d.*)\n', content))
quarantined = split_whitespace(sc.find(r'\nQuarant.ne\s+(\d.*)\n', content))
ips = split_whitespace(sc.find(r'\nCovid Patienten in IPS\s+(\d.*)\n',
content))
<td icms="">0</td>
<td icms="">47</td>
<td icms="">7</td>
<td icms=""> </td>
</tr>
</tbody>
</table>
"""
soup = BeautifulSoup(d, 'html.parser')
data_table = soup.find(string=re.compile(
r'Positiv\s+getestete\s+Erkrankungsfälle')).find_parent('table')
assert data_table, "Can't find data table"
dd = sc.DayData(canton='UR', url=url)
dd.datetime = sc.find(r'Stand[A-Za-z ]*[:,]? ([^<)]+ Uhr)<', d)
rows = data_table.find_all('tr')
assert len(rows) == 2, f"Number of rows changed, {len(rows)} != 2"
headers = rows[0].find_all('td') or rows[0].find_all('th')
assert len(
headers) == 6, f"Number of header columns changed, {len(headers)} != 6"
assert headers[0].text.strip() == "Aktive Fälle"
assert headers[1].text == "Positiv getestete Erkrankungsfälle"
assert headers[2].text == "Hospitalisiert"
assert headers[3].text == "Quarantäne"
assert headers[4].text == "Verstorben"
cells = rows[1].find_all('td')
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import scrape_common as sc
xls_url = 'http://www.nw.ch/coronastatistik'
xls = sc.xlsdownload(xls_url, silent=True)
rows = sc.parse_xls(xls, header_row=3)
is_first = True
for row in rows:
if not is_first:
print('-' * 10)
is_first = False
dd = sc.DayData(canton='NW', url=xls_url)
dd.datetime = row['A'].date().isoformat()
dd.cases = row['Positiv getestete Personen (kumuliert)']
dd.hospitalized = row['Hospitalisierte Personen']
dd.icu = row['Davon auf der Intensivstation']
dd.deaths = row['Verstorbene Personen']
print(dd)
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import scrape_common as sc
xls_url = 'https://www4.ti.ch/fileadmin/DSS/DSP/UMC/malattie_infettive/Coronavirus/dati/COVID19_Dati_TI_per_github.xlsx'
xls = sc.xlsdownload(xls_url, silent=True)
rows = sc.parse_xls(xls, header_row=0)
is_first = True
for row in rows:
if not is_first:
print('-' * 10)
is_first = False
dd = sc.DayData(canton='TI', url=xls_url)
dd.datetime = f"{row['date'].date().isoformat()}"
if row['time']:
dd.datetime += f"T{row['time'].time().isoformat()}"
dd.cases = row['ncumul_conf']
dd.hospitalized = row['current_hosp']
dd.icu = row['current_icu']
dd.vent = row['current_vent']
dd.recovered = row['ncumul_released']
dd.deaths = row['ncumul_deceased']
print(dd)
#!/usr/bin/env python3
import csv
from io import StringIO
import re
from bs4 import BeautifulSoup
import scrape_common as sc
# hospitalized
url_hospitalized = 'https://stada.sg.ch/covid/C19_Faelle_hospitalisiert.html'
soup = BeautifulSoup(sc.download(url_hospitalized, silent=True), 'html.parser')
dd_hosp = sc.DayData(canton='SG', url=url_hospitalized)
hosp_table = soup.find('table')
hosp_date = hosp_table.find_next(string=re.compile("Stand")).string
dd_hosp.datetime = sc.find(r'Stand:?\s*(.+[0-9]{4})', hosp_date)
rows = hosp_table.find_all('tr')
headers = rows[0].find_all('td') or rows[0].find_all('th')
assert len(
headers) == 2, f"Number of header columns changed, {len(headers)} != 2"
assert headers[1].text.strip() == "Anzahl"
for i in range(1, len(rows)):
cells = rows[i].find_all('td')
if cells[0].text.strip() == 'Total Covid-19 Patienten':
dd_hosp.hospitalized = cells[1].text
elif cells[0].text.strip() == '...davon auf Intensivstation ohne Beatmung':
dd_hosp.icu = int(cells[1].text)
elif cells[0].text.strip() == '...davon auf Intensivstation mit Beatmung':
is_first = True
# parse tested from PDF
pdf_url = sgc.get_latest_ge_weekly_pdf_url()
pdf = sc.pdfdownload(pdf_url, silent=True)
week_number = sc.find(r'Situation semaine (\d+)', pdf)
if week_number:
week_end_date = datetime.datetime.strptime('2021-W' + week_number + '-7',
'%G-W%V-%u').date()
number_of_tests = sc.find(r'Au total, (\d+\'\d+) tests PCR ont', pdf)
if number_of_tests is not None:
number_of_tests = number_of_tests.replace('\'', '')
dd_test = sc.DayData(canton='GE', url=pdf_url)
dd_test.datetime = week_end_date.isoformat()
dd_test.tested = number_of_tests
print(dd_test)
is_first = False
# get hospitalized number
hosp_url = 'https://www.hug.ch/coronavirus-maladie-covid-19/situation-aux-hug'
d = sc.download(hosp_url, silent=True)
d = d.replace(' ', ' ')
soup = BeautifulSoup(d, 'html.parser')
content = soup.find(string=re.compile(
"Evolution du nombre de malades.*")).find_previous('p').text
dd_hosp = sc.DayData(canton='GE', url=hosp_url)
hosp_date = sc.find(r'^Au (\d+\s*(:?\w+)?\s+\w+)\s+à\s+\d+h',
pdf_url = f'{base_url}{pdf_url}'
content = sc.pdfdownload(pdf_url, layout=True, silent=True)
"""
Hospitalisationen im Kanton Anzahl Personen in Isolation davon Kontakte in Quarantäne Anzahl zusätzlicher Personen in Quarantäne nach Rückkehr aus Risikoland Re- Wert***
6 (6) 120 (71) 280 (189) 388 (280) 1.46 (1.1)
"""
rows = []
date = sc.find(r'S\s?tand: (\d+\.\d+\.20\d{2})', content)
res = re.search(
r'Hospitalisationen im Kanton.*\d+ \(\d+\)\s+(\d+) \(\d+\)\s+(\d+) \(\d+\)\s+(\d+) \(\d+\)\s+\d\.\d+ \(\d\.\d+\)',
content, re.DOTALL)
if res is not None:
data = sc.DayData(canton='SO', url=pdf_url)
data.datetime = date
data.isolated = res[1]
data.quarantined = res[2]
data.quarantine_riskareatravel = res[3]
rows.append(data)
url = f"{base_url}/index.php?id=27979"
d = sc.download(url, silent=True)
d = d.replace(" ", " ")
soup = BeautifulSoup(d, 'html.parser')
data_table = soup.find(
'h2', text=re.compile("Situation Kanton Solothurn")).find_next("table")
if data_table:
headers = [cell.string for cell in data_table.find('tr').find_all('th')]
import scrape_common as sc
import scrape_ag_common as sac
xls_url = sac.get_ag_xls_url()
xls = sc.xlsdownload(xls_url, silent=True)
is_first = True
# quarantine_riskareatravel
rows = sc.parse_xls(xls,
sheet_name='5. Quarantäne nach Einreise',
header_row=2)
for row in rows:
if not isinstance(row['A'], datetime.datetime):
continue
dd = sc.DayData(canton='AG', url=xls_url)
dd.datetime = f"{row['A'].date().isoformat()} {row['A'].time().isoformat()}"
dd.quarantine_riskareatravel = row['Gesamtzahl aktuell betreuter Personen']
if dd:
if not is_first:
print('-' * 10)
is_first = False
print(dd)
# quarantine + isolation
rows = sc.parse_xls(xls, sheet_name='2. Contact Tracing', header_row=2)
for row in rows:
if not isinstance(row['A'], datetime.datetime):
continue
dd = sc.DayData(canton='AG', url=xls_url)
def fix_lu_date(date):
res = re.match(r'(20\d{2})/(\d+)/(\d+)', date)
assert res, 'date could not be matched!'
date = datetime.date(int(res[1]), int(res[2]) + 1, int(res[3]))
return date.isoformat()
hosp_url = 'https://www.lustat.ch/analysen/gesundheit/corona-reporting/hospitalisationen'
hosp_csv = 'https://www.lustat.ch/files_ftp/daten/covid/cov_hospitalisationen.csv'
is_first = True
data = sc.download(hosp_csv, silent=True, encoding='utf-8-sig')
reader = csv.DictReader(StringIO(data), delimiter=';')
for row in reader:
dd = sc.DayData(canton='LU', url=hosp_url)
dd.datetime = fix_lu_date(row['utcdatum'])
dd.hospitalized = row['current_hosp']
dd.vent = row['current_vent']
if dd:
if not is_first:
print('-' * 10)
is_first = False
print(dd)
cases_url = 'https://www.lustat.ch/analysen/gesundheit/corona-reporting/entwicklungen-seit-maerz-2020'
cases_csv = 'https://www.lustat.ch/files_ftp/daten/covid/cov_faelle_g2.csv'
data = sc.download(cases_csv, silent=True, encoding='utf-8-sig')
reader = csv.DictReader(StringIO(data), delimiter=';')
for row in reader:
assert xls_url, "URL is empty"
if not xls_url.startswith('http'):
xls_url = f'https://www.jura.ch{xls_url}'
xls = sc.xlsdownload(xls_url, silent=True)
rows = sc.parse_xls(xls, header_row=0)
for i, row in enumerate(rows):
if not isinstance(row['Date'], datetime.datetime):
continue
if not is_first:
print('-' * 10)
is_first = False
dd = sc.DayData(canton='JU', url=xls_url)
dd.datetime = row['Date'].date().isoformat()
dd.cases = row['Cumul des cas confimés']
dd.hospitalized = row.get('Nb cas actuellement hospitalisés')
dd.icu = row.get('Nb cas actuellement en SI')
if sc.represents_int(row.get('Nombre de nouveaux décès')):
dd.deaths = sum(r['Nombre de nouveaux décès']
for r in rows[:i + 1])
print(dd)
data_table = soup.find(
'caption', string=re.compile(
r'Evolution du nombre de cas.*Jura')).find_parent('table')
if data_table:
headers = [
" ".join(cell.stripped_strings)
#!/usr/bin/env python3
import scrape_common as sc
url = 'https://www.ar.ch/verwaltung/departement-gesundheit-und-soziales/amt-fuer-gesundheit/informationsseite-coronavirus/'
d = sc.download(url, silent=True)
d = d.replace(' ', ' ')
# Contact Tracing with its own timestamp
dd_ct = sc.DayData(canton='AR', url=url)
t = sc.find(r'Contact\s+tracing\s+\(?.*?Stand\:?\s+([^\)]+)(Uhr)?.*?\)?', d) or \
sc.find(r'Contact\s+tracing\s+\(?.*?Stand\:?\s+([0-9]+\.[0-9]+\.? \/ [0-9]+h).*?\)?', d)
dd_ct.datetime = t
dd_ct.isolated = sc.find(
r'Aktuell\s+COVID-19-Erkrankte\s+in\s+Isolation:\s+<strong>(\d+)</strong>',
d)
dd_ct.quarantined = sc.find(
r'Aktuell\s+im\s+Kanton\s+wohnhafte\s+Kontaktpersonen\s+in\s+Quarantäne:\s+<strong>(\d+)</strong>',
d)
print(dd_ct)
print('-' * 10)
# cases
dd = sc.DayData(canton='AR', url=url)
# d = sc.filter('Aktuelle Informationen: Zahlen', d)
#!/usr/bin/env python3
import re
import datetime
from bs4 import BeautifulSoup
import scrape_common as sc
url = 'https://gesundheit.lu.ch/themen/Humanmedizin/Infektionskrankheiten/Coronavirus'
d = sc.download(url, silent=True)
dd = sc.DayData(canton='LU', url=url)
# 2020-04-01
"""
<p><strong>Aktuelle Fallzahlen im Kanton Luzern </strong>(Stand: 1. April 2020, 11:00 Uhr)</p>
<table border="0" cellspacing="0" cellpadding="0">
<tbody>
<tr>
<td valign="top" style="width: 151px;">
<p><strong></strong>Bestätigte Fälle: </p>
</td>
<td valign="top" style="width: 47px;">
<p style="text-align: right;">401</p>
</td>
</tr>
<tr>
<td valign="top" style="width: 151px;">
<p>Hospitalisiert:</p>
</td>
<td valign="top" style="width: 47px;">
<p style="text-align: right;">57</p>
</td>
#!/usr/bin/env python3 import csv import re from io import StringIO from bs4 import BeautifulSoup import scrape_common as sc url = "https://www.zh.ch/de/gesundheit/coronavirus.html#-1310230111" # get quarantined and isolated from website dd_iso_q = sc.DayData(canton='ZH', url=url) d = sc.download(url, silent=True) # 2020-07-08 """ <div class="mdl-richtext "> <h2 class="atm-heading" id="-1310230111" tabindex="-1">Gesundheitliche Lage</h2> <p class="atm-paragraph">Personen mit Wohnsitz im Kanton Zürich<br> </p> <h4 class="atm-heading" id="-718243468">23</h4> <p class="atm-paragraph">neue positive Fälle in den letzten 24 Stunden</p> <h4 class="atm-heading" id="-718243501">11</h4> <p class="atm-paragraph">in Spitalbehandlung</p> <h4 class="atm-heading" id="808114848">3</h4> <p class="atm-paragraph">davon mit künstlicher Beatmung</p> <h4 class="atm-heading" id="-790711940">131</h4> <p class="atm-paragraph">Total Verstorbene seit Pandemiebeginn (78 in Alters- und Pflegeheimen, 51 im Spital, 2 Zuhause)</p> <h4 class="atm-heading" id="-790711785">181</h4> <p class="atm-paragraph">in Isolation</p> <h4 class="atm-heading" id="-790704311">914</h4> <p class="atm-paragraph">in Quarantäne </p>
reader = csv.DictReader(StringIO(d_csv), delimiter=',')
data = collections.defaultdict(dict)
for row in reader:
if row['Typ'] == 'NA' or row['Datum'] == 'NA':
continue
date = sc.date_from_text(row['Datum'])
data[date.isoformat()][row['Typ']] = row['Anzahl']
days = list(data.keys())
is_first = True
for day in days:
if not is_first:
print('-' * 10)
is_first = False
dd = sc.DayData(canton='ZG', url=main_url)
dd.datetime = day
dd.isolated = data[day]['Isolation']
dd.quarantined = data[day]['Quarantäne aus Contact Tracing']
dd.quarantine_riskareatravel = data[day].get(
'Quarantäne nach Rückkehr aus Risikoland')
dd.quarantine_total = data[day].get('Quarantäne Total')
print(dd)
cases_csv_url = 'https://www.zg.ch/behoerden/gesundheitsdirektion/statistikfachstelle/daten/themen/result-themen-14-03-01-e1.csv'
d_csv = sc.download(cases_csv_url, silent=True)
"""
"Typ","Datum","Anzahl","Stand","Meta","Type","Content"
"Fallzahl","22.04.2020","176","2020-04-22 08:00:00",NA,NA,NA
"Fallzahl","23.04.2020","178","2020-04-23 08:00:00",NA,NA,NA
#!/usr/bin/env python3
from bs4 import BeautifulSoup
import scrape_common as sc
# fetch latest data from HTML table
url = 'https://www.ag.ch/de/themen_1/coronavirus_2/coronavirus.jsp'
d = sc.download(url, silent=True)
d = d.replace("’", "")
d = d.replace("'", "")
dd = sc.DayData(canton='AG', url=url)
date = sc.find(
r'Stand: (?:Montag|Dienstag|Mittwoch|Donnerstag|Freitag|Samstag|Sonntag), (.+? Uhr)',
d)
dd.datetime = date
soup = BeautifulSoup(d, 'html.parser')
rows = []
for t in soup.find_all('table'):
headers = [
" ".join(cell.stripped_strings) for cell in t.find('tr').find_all('th')
]
for row in [r for r in t.find_all('tr') if r.find_all('td')]:
cells = row.find_all(['td'])
col_num = 0
for cell in cells:
stat_url = base_url + '/de/web/coronavirus/statistiques'
content = sc.download(stat_url, silent=True)
soup = BeautifulSoup(content, 'html.parser')
res = soup.find(
string=re.compile(r'Synthese COVID19 VS Woche\d+')).find_previous('a')
weekly_pdf_url = base_url + res.attrs['href']
weekly_pdf_url = weekly_pdf_url.replace(' ', '%20')
content = sc.pdfdownload(weekly_pdf_url, silent=True)
# add isolated/quarantined to the existing DayData item
week_end_date = sc.find(r'vom (\d+)\. bis (\d+\.\d+\.20\d{2})',
content,
group=2)
week_end_date = sc.date_from_text(week_end_date).isoformat()
dd = sc.DayData(canton='VS', url=weekly_pdf_url)
dd.datetime = week_end_date
dd.isolated = sc.find(
r'befanden\ssich\s(\d+)\spositive\sF.lle\snoch\simmer\sin\sIsolation',
content)
dd.quarantined = sc.find(r'Isolation\sund\s(\d+)\sKontakte\sin\sQuarant.ne',
content)
dd.quarantine_riskareatravel = sc.find(r'\s(\d+)\sReisende\sin\sQuarant.ne',
content)
print(dd)
xls_url = 'https://raw.githubusercontent.com/statistikZH/covid19_drop/master/Chiffres%20%20COVID-19%20Valais.xlsx'
main_url = 'https://www.vs.ch/de/web/coronavirus'
xls = sc.xlsdownload(xls_url, silent=True)
rows = sc.parse_xls(xls, header_row=1)
for i, row in enumerate(rows):
'table',
{
'summary':
'Laufend aktualisierte Zahlen zu den Corona-Erkrankungen im Kanton Bern'
}):
headers = [
" ".join(cell.stripped_strings) for cell in t.find('tr').find_all('th')
]
is_first = True
for row in [r for r in t.find_all('tr') if r.find_all('td')]:
if not is_first:
print('-' * 10)
is_first = False
dd = sc.DayData(canton='BE', url=html_url)
for col_num, cell in enumerate(row.find_all(['td'])):
value = " ".join(cell.stripped_strings)
if value:
value = value.replace("'", "")
if value and '*' in value and not '**' in value:
# the asteriks (*) indicates a not-current value
# ** means "Datenkorrektur"
continue
if value and '(' in value:
value = sc.find(r'(\d+)([\s<>br\w]*\(.*\))?', value)
if headers[col_num] == 'Datum':
date_string = "".join(list(cell.stripped_strings)[0:-1])
time_string = list(cell.stripped_strings)[-1]
# -*- coding: utf-8 -*-
from bs4 import BeautifulSoup
import re
import scrape_common as sc
import scrape_bl_common as sbc
from collections import OrderedDict, defaultdict
from datetime import datetime
bulletin_url = sbc.get_latest_bl_bulletin_url()
bulletin_content = sc.download(bulletin_url, silent=True)
soup = BeautifulSoup(bulletin_content, 'html.parser')
content = soup.find('strong', string=re.compile(r'Per heute .*')).string
# strip unwanted characters
content = content.encode("ascii", errors="ignore").decode()
dd = sc.DayData(canton='BL', url=bulletin_url)
dd.datetime = sc.find(r'Per heute \w+, (\d+\. \w+ 20\d{2})', content)
dd.isolated = sc.find(
r'Aktuell befinden sich.*(\d+\s?\d+) Personen in Isolation', content)
dd.quarantined = sc.find(
r'Aktuell befinden sich.*(\d+\s?\d+) Personen in Quarantäne', content)
is_first = True
if dd:
print(dd)
is_first = False
main_url = "https://www.baselland.ch/politik-und-behorden/direktionen/volkswirtschafts-und-gesundheitsdirektion/amt-fur-gesundheit/medizinische-dienste/kantonsarztlicher-dienst/aktuelles/covid-19-faelle-kanton-basel-landschaft"
main_site = sc.download(main_url, silent=True)
# 2020-04-08, two iframes
rows[key]['hospitalized'] = int(
float(c[1] or 0) + float(c[2] or 0) +
float(c[3] or 0))
rows[key]['icu'] = int(
float(c[2] or 0) + float(c[3] or 0))
rows[key]['vent'] = c[3]
# order dict by key to ensure the most recent entry is last
ordered_rows = OrderedDict(sorted(rows.items()))
is_first = True
for row_date, row in ordered_rows.items():
if not is_first:
print('-' * 10)
is_first = False
dd = sc.DayData(canton='BL', url=main_url)
dd.datetime = row['date']
dd.cases = sc.safeint(row['cases'])
try:
dd.hospitalized = sc.safeint(row['hospitalized'])
except KeyError:
pass
try:
dd.icu = sc.safeint(row['icu'])
except KeyError:
pass
try:
dd.vent = sc.safeint(row['vent'])
except KeyError:
pass
dd.deaths = sc.safeint(row['deaths'])
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import datetime
import scrape_common as sc
xls_url = 'https://raw.githubusercontent.com/statistikZH/covid19_drop/master/Chiffres%20%20COVID-19%20Valais.xlsx'
xls = sc.xlsdownload(xls_url, silent=True)
rows = sc.parse_xls(xls, header_row=1)
is_first = True
for row in rows:
if not isinstance(row['Date'], datetime.datetime):
continue
if not is_first:
print('-' * 10)
is_first = False
dd = sc.DayData(canton='VS', url=xls_url)
dd.datetime = row['Date'].date().isoformat()
dd.cases = row['Cumul cas positifs']
dd.hospitalized = row['Total hospitalisations COVID-19']
dd.icu = row['Patients COVID-19 aux SI total']
dd.vent = row['Patients COVID-19 intubés']
dd.deaths = row['Cumul décès COVID-19']
print(dd)
#!/usr/bin/env python3
import scrape_common as sc
url = "https://gd.zh.ch/internet/gesundheitsdirektion/de/themen/coronavirus.html"
dd = sc.DayData(canton='ZH', url=url)
d = sc.download(url, silent=True)
d = d.replace(' ', ' ')
d = d.replace('<strong>', ' ').replace('</strong>', ' ')
# d = sc.filter(r"Im Kanton Zürich sind zurzeit|\(Stand|Total ([0-9]+) Todesfälle|Spitalbehandlung|beatmet", d)
# <h2>Aktuelle Situation im Kanton Zürich (24.3.2020, 9.30 Uhr)</h2>
#
#
#
# <p>Im Kanton Zürich sind zurzeit 1211 Personen positiv auf das Coronavirus getestet worden. Total 5 Todesfälle (78-jährig, 80, 88, 96, 97).</p>
# <p>(Stand 24.3.2020, 9.30 Uhr)</p>
# 2020-03-26
"""
<h2>Aktuelle Situation im Kanton Zürich (26.3.2020, 9.30 Uhr)</h2>
<p>Im Kanton Zürich sind zurzeit 1476 Personen positiv auf das Coronavirus getestet worden.</p>
<p>152 positiv Getestete befinden sich in Spitalbehandlung, davon werden 32 künstlich beatmet.</p>
<p>Total 9 Todesfälle (78-jährig, 78, 80, 80, 85, 88, 90, 96, 97).</p>
<p>Die Gesundheitsdirektion beschafft sich eine Maschine, die täglich automatisch bis zu 32'000 FFP2-Schutzmasken herstellen kann. In der zweiten Hälfte des Monats April ist die Maschine betriebsbereit. </p>
<p>(Stand 26.3.2020, 9.30 Uhr)</p>
"""
import scrape_common as sc
# The list of articles is also available on https://www.gd.bs.ch/medienseite/medienmitteilungen.html
URL = sc.download("https://www.gd.bs.ch/", silent=True)
URL = sc.filter(
r'Tagesbulletin.*Corona.*\d+\s*bestätigte\s*(Fälle|Infektionen)', URL)
# 2020-03-25, List of sub-articles:
"""
<a href="/nm/2020-tagesbulletin-coronavirus-466-bestaetigte-faelle-im-kanton-basel-stadt-gd.html" target="_self">Tagesbulletin Coronavirus: 466 bestätigte Fälle im Kanton Basel-Stadt</a>
<a href="/nm/2020-tagesbulletin-coronavirus-414-bestaetigte-faelle-im-kanton-basel-stadt-gd.html" target="_self">Tagesbulletin Coronavirus: 414 bestätigte Fälle im Kanton Basel-Stadt</a>
<a href="/nm/2020-tagesbulletin-coronavirus-376-bestaetigte-faelle-im-kanton-basel-stadt-gd.html" target="_self">Tagesbulletin Coronavirus: 376 bestätigte Fälle im Kanton Basel-Stadt</a>
"""
url = 'https://www.gd.bs.ch/' + sc.filter(r'href', URL).split('"')[1]
dd = sc.DayData(canton='BS', url=url)
d = sc.download(url, silent=True)
d = d.replace('ä', 'ä')
d = d.replace('ö', 'ö')
d = d.replace(' ', ' ')
# 2020-03-25
"""
<p>Das Gesundheitsdepartement Basel-Stadt meldet mit Stand Mittwoch, 25. März 2020, 10 Uhr, insgesamt 466 positive Fälle von Personen mit Wohnsitz im Kanton Basel-Stadt sowie drei weitere Todesfälle. </p>
"""
# There are some extra (or repeated) information in the previous / next paragraphs:
# 2020-03-25
"""
from bs4 import BeautifulSoup
import scrape_common as sc
d = sc.download(
'https://www.sz.ch/behoerden/information-medien/medienmitteilungen/coronavirus.html/72-416-412-1379-6948',
silent=True)
soup = BeautifulSoup(d, 'html.parser')
pdf_url = soup.find('a', string=re.compile(r'Medienmitteilung vom'))['href']
pdf_content = sc.pdfdownload(pdf_url, layout=True, silent=True)
date = sc.find(r'Stand: (\d+\. .* 20\d{2})', pdf_content)
res = re.search(r'.*\s+\d+\s+\d+\s+\d+\s+(\d+)\s+(\d+)\s+(\d+)\s+',
pdf_content)
is_first = True
if res is not None:
dd = sc.DayData(canton='SZ', url=pdf_url)
dd.datetime = date
dd.hospitalized = res[1]
dd.quarantined = res[2]
dd.quarantine_riskareatravel = res[3]
print(dd)
is_first = False
try:
xls_url = soup.find(
'a', string=re.compile(r'Coronaf.lle\s*im\s*Kanton\s*Schwyz'))['href']
except TypeError:
print("Unable to determine xls url", file=sys.stderr)
sys.exit(1)
xls = sc.xlsdownload(xls_url, silent=True)
# get latest from list with all press releases
d = sc.download('https://www.regierung.li/coronavirus', silent=True)
pdf_url = sc.find(
r'<a.*?href="([^"]+\.pdf)[^"]*"[^>]*?>[^<]+?Situationsbericht[^<]+?<\/a>',
d)
assert pdf_url, "PDF URL not found"
# download latest PDF
d = sc.pdfdownload(pdf_url, raw=True, silent=True)
# extract case numbers reported for previous days
d = d.replace(u'\xa0', u' ')
# data from the most recent press release
dd = sc.DayData(canton='FL', url=pdf_url)
dd.datetime = sc.find(r'Situationsbericht vom (.*? 20\d{2})', d)
dd.cases = sc.find(r'insgesamt\s+([0-9]+)\s+laborbestätigte\s+Fälle', d)
m = re.search(r'Bisher\s+trat(en)?\s+(\S+)\s+(Todesfall|Todesfälle)',
d,
flags=re.I)
if m:
dd.deaths = sc.int_or_word(m[2])
if re.search(
'Alle\s+weiteren\s+Erkrankten\s+sind\s+in\s+der\s+Zwischenzeit\s+genesen',
d):
dd.recovered = int(dd.cases) - int(dd.deaths)
print(dd)
base_url = 'https://www.lustat.ch'
url = f'{base_url}/daten?id=28177'
d = sc.download(url, silent=True)
soup = BeautifulSoup(d, 'html.parser')
xls_url = soup.find('a', href=re.compile(r'.*\.xlsx')).get('href')
if not xls_url.startswith('http'):
xls_url = f'{base_url}{xls_url}'
xls = sc.xlsdownload(xls_url, silent=True)
rows = sc.parse_xls(xls, header_row=5)
total_cases = 0
total_deaths = 0
is_first = True
for row in rows:
dd = sc.DayData(canton='LU', url=xls_url)
dd.datetime = row['Datum']
dd.cases = sc.int_or_word(row.search(r'Neue\s+Fälle'))
if dd.cases:
total_cases += dd.cases
dd.cases = total_cases
dd.deaths = sc.int_or_word(row['Verstorbene'])
if dd.deaths:
total_deaths += dd.deaths
dd.deaths = total_deaths
dd.hospitalized = sc.int_or_word(row['Total'])
dd.vent = sc.int_or_word(row.search(r'davon\s+beatmet'))
dd.isolated = sc.int_or_word(row.search(r'in\s+Isolation'))
dd.quarantined = sc.int_or_word(row.search(r'in\s+Quarantäne'))
dd.quarantine_riskareatravel = sc.int_or_word(row.search(r'Reiserückkehrer\s+in\s+Quarantäne'))
if dd:
