import scrape_common as sc
base_url = 'https://www.jura.ch'
url = f'{base_url}/fr/Autorites/Coronavirus/Chiffres-H-JU/Evolution-des-cas-COVID-19-dans-le-Jura.html'
d = sc.download(url, silent=True)
d = d.replace(' ', ' ')
soup = BeautifulSoup(d, 'html.parser')
pdf_url = soup.find('a', title=re.compile(r'.*PDF.*')).get('href')
if not pdf_url.startswith('http'):
pdf_url = f'{base_url}{pdf_url}'
pdf_url = pdf_url.replace('?download=1', '')
pdf = sc.download_content(pdf_url, silent=True)
td = sc.TestData(canton='JU', url=pdf_url)
content = sc.pdftotext(pdf, page=1)
td.week = sc.find(r'Situation semaine épidémiologique (\d+)', content)
td.year = sc.find(r'Du \d+.* (\d{4})', content)
content = sc.pdftotext(pdf, page=2)
td.total_tests = sc.find(r'Nombre de tests\d?\s+(\d+)', content)
res = re.match(
r'.*Nombre de tests positifs .*\s+(\d+)\s+\((\d+\.?\d?)%\s?\d?\)', content,
re.DOTALL | re.MULTILINE)
assert res, 'failed to find number of positive tests and positivity rate'
td.positive_tests = res[1]
td.positivity_rate = res[2]
print(td)
res = re.search(r".*categories: \[('KW.*)\],", content)
assert res, f'failed to extract weeks, got {res}'
weeks = res[1].split(',')
res = re.search(r".*name: 'Anzahl negativer Tests.?',\s+color: '.*',\s+data: \[(.*)\],", content)
assert res, f'failed to extract negative tests, got {res}'
negative_tests = res[1].split(',')
res = re.search(r".*name: 'Anzahl positiver Tests.?',\s+color: '.*',\s+data: \[(.*)\],", content)
assert res, f'failed to extract positive tests, got {res}'
positive_tests = res[1].split(',')
res = re.search(r".*name: 'Positivitätsrate',\s+color: '.*',\s+data: \[(.*)\],", content)
assert res, f'failed to extract positivtiy rate, got {res}'
positivity_rate = res[1].split(',')
assert len(weeks) == len(negative_tests) == len(positive_tests) == len(positivity_rate), f'Expected same length for weeks {len(weeks)}, neg. tests {len(negative_tests)}, pos. tests {len(positive_tests)}, pos. rate {len(positivity_rate)}'
year = '2020'
for week, neg, pos, rate in zip(weeks, negative_tests, positive_tests, positivity_rate):
td = sc.TestData(canton='TG', url=url)
td.week = sc.find(r'KW (\d+)', week)
if int(td.week) == 1:
year = '2021'
td.year = year
td.positive_tests = int(pos)
td.negative_tests = int(neg)
td.positivity_rate = float(rate)
print(td)
def create_bs_test_data(date):
td = sc.TestData(canton='BL', url=main_url)
td.start_date = date
td.end_date = date
return td
return None
xls_url = sac.get_ag_xls_url()
xls = sc.xlsdownload(xls_url, silent=True)
year = '2020'
rows = sc.parse_xls(xls,
sheet_name='1.4 Labortests',
header_row=1,
enable_float=True)
for row in rows:
if not row['Anzahl Tests']:
continue
if row['Anzahl Tests'] == 'Anzahl Tests':
break
td = sc.TestData(canton='AG', url=xls_url)
td.week = int(row['Kalenderwoche'])
if td.week == 1:
year = '2021'
td.year = year
td.positive_tests = get_value_int(row['Positive Tests'])
td.negative_tests = get_value_int(row['Negative Tests'])
td.total_tests = int(row['Anzahl Tests'])
td.positivity_rate = get_value_float(row['Positivitätsrate'])
td.pcr_positivity_rate = get_value_float(row['F'])
td.ag_positivity_rate = get_value_float(row['G'])
if td:
print(td)
content, re.DOTALL)
if not res:
res = re.match(
r'.*Labortes\s?ts\s\(PCR\s-\sund\sS\s?chnelltes\s?ts\s?\)\s+(\d.*\n)?Total\s+\d+\s+\d+\.?\d?\s+(\d+)\s+\d+\.?\d?\s+(\d+)\s',
content, re.DOTALL)
assert res, f'PCR tests for week {week1} or {week2} could not be extracted!'
total_tests1 = res[2]
total_tests2 = res[3]
#res = re.match(r'.*Positivit.tsrate\s+\*?\s+\d.*%\s+(\d.*)%\s+(\d.*)%', content, re.DOTALL)
res = re.match(
r'.*Positivit.tsrate\s+\*+?\s+\d+\.?\d?%?\s+(\d+\.?\d?)%?\s+(\d+\.?\d?)%?',
content, re.DOTALL)
assert res, f'Positivity rate for week {week1} or {week2} could not be extracted!'
pos_rate1 = res[1]
pos_rate2 = res[2]
data = sc.TestData(canton='SO', url=pdf_url)
data.week = week1
data.year = year1
data.total_tests = total_tests1
data.positivity_rate = pos_rate1
print(data)
data = sc.TestData(canton='SO', url=pdf_url)
data.week = week2
data.year = year2
data.total_tests = total_tests2
data.positivity_rate = pos_rate2
print(data)
from datetime import timedelta
# weekly data
bulletin_urls = sbc.get_all_bl_bulletin_urls()
for bulletin_url in bulletin_urls:
bulletin_content = sc.download(bulletin_url, silent=True)
soup = BeautifulSoup(bulletin_content, 'html.parser')
content = soup.find(string=re.compile(r'Per heute .*')).string
content = sbc.strip_bl_bulletin_numbers(content)
date = sc.find(r'Per heute \w+, (\d+\. \w+ 20\d{2})', content)
date = sc.date_from_text(date)
# previous week
date = date - timedelta(days=7)
td = sc.TestData(canton='BL', url=bulletin_url)
td.week = date.isocalendar()[1]
td.year = date.year
td.total_tests = sc.find(r'In der Vorwoche wurden (\d+) PCR-Tests',
content)
td.positivity_rate = sc.find(
r'von diesen waren (\d+\.?,?\d?) Prozent positiv', content)
if td.total_tests and td.positivity_rate:
td.positivity_rate = td.positivity_rate.replace(',', '.')
print(td)
# daily data
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/covid-19-bl-tests'
main_content = sc.download(main_url, silent=True)
soup = BeautifulSoup(main_content, 'html.parser')
from io import StringIO
import scrape_common as sc
def prettify_positivity_rate(positivity_rate):
if not positivity_rate:
return None
return round(10 * float(positivity_rate)) / 10
url = 'https://data.bs.ch/explore/dataset/100094/download/?format=csv&timezone=Europe/Berlin&lang=en&use_labels_for_header=true&csv_separator=%3B'
data = sc.download(url, silent=True)
reader = csv.DictReader(StringIO(data), delimiter=';')
for row in reader:
td = sc.TestData(canton='BS', url=url)
td.start_date = row['Datum']
td.end_date = row['Datum']
td.positive_tests = row['Positive Tests'] or None
td.negative_tests = row['Negative Tests'] or None
td.total_tests = row['Total Tests'] or None
td.positivity_rate = row['Anteil positive Tests in Prozent'] or None
td.pcr_positive_tests = row['Positive PCR Tests'] or None
td.pcr_negative_tests = row['Negative PCR Tests'] or None
td.pcr_total_tests = row['Total PCR Tests'] or None
td.pcr_positivity_rate = row['Anteil positive PCR Tests in Prozent'] or None
td.ag_positive_tests = row['Positive Antigen Schnelltests'] or None
td.ag_negative_tests = row['Negative Antigen Schnelltests'] or None
td.ag_total_tests = row['Total Antigen Schnelltests'] or None
#!/usr/bin/env python3
from bs4 import BeautifulSoup
import re
import scrape_common as sc
html_url = 'https://www.besondere-lage.sites.be.ch/besondere-lage_sites/de/index/corona/index.html'
d = sc.download(html_url, silent=True)
soup = BeautifulSoup(d, 'html.parser')
for t in soup.find_all('table', summary=re.compile(r'.*die Zahl der durchgef.hrten Tests pro.*')):
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')]:
td = sc.TestData(canton='BE', url=html_url)
tot_tests = None
for col_num, cell in enumerate(row.find_all(['td'])):
value = " ".join(cell.stripped_strings)
if value:
value = re.sub(r'[^\d\.]', '', value)
if sc.find(r'^(Kalender.*)', headers[col_num]) is not None:
td.week = value
td.year = '2020'
elif sc.find(r'^(Durchge.*Tests)', headers[col_num]):
td.total_tests = int(value)
elif sc.find(r'^(davon.*positiv)', headers[col_num]):
td.positive_tests = int(value)
elif sc.find(r'^(Positivit.ts.*)', headers[col_num]):
td.positivity_rate = value
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import scrape_common as sc
from scrape_fr_common import get_fr_xls
xls_url, xls, main_url = get_fr_xls()
rows = sc.parse_xls(xls, header_row=0, sheet_name='tests', enable_float=True)
year = '2020'
for row in rows:
week = row['semaine /Woche']
if not week:
continue
if week == 1:
year = '2021'
td = sc.TestData(canton='FR', url=main_url)
td.week = int(week)
td.year = year
td.pcr_total_tests = int(row['Tests PCR'])
td.pcr_positivity_rate = round(row['Taux/Rate PCR'] * 100)
td.ag_total_tests = int(row['Tests AG'])
td.ag_positivity_rate = round(row['Taux/Rate AG'] * 100)
td.total_tests = td.pcr_total_tests + td.ag_total_tests
print(td)
import os
import db_common as dc
import scrape_common as sc
__location__ = dc.get_location()
input_failures = 0
try:
DATABASE_NAME = os.path.join(__location__, 'data.sqlite')
conn = sqlite3.connect(DATABASE_NAME)
i = 0
for line in sys.stdin:
td = sc.TestData()
if td.parse(line.strip()):
c = conn.cursor()
try:
print(td)
c.execute(
'''
INSERT INTO data (
canton,
start_date,
end_date,
week,
year,
pcr_positive_tests,
pcr_negative_tests,
import csv
import datetime
from io import StringIO
import scrape_common as sc
csv_url = 'https://www.zg.ch/behoerden/gesundheitsdirektion/statistikfachstelle/daten/themen/result-themen-14-03-07-i2-k4-b1.csv'
d_csv = sc.download(csv_url, silent=True)
"""
"Woche","Geschlecht","Anzahl Fälle","Meta","Type","Content"
2020-05-25,"männlich","151",NA,NA,NA
2020-06-01,"männlich","117",NA,NA,NA
"""
reader = csv.DictReader(StringIO(d_csv), delimiter=',')
data = collections.defaultdict(dict)
for row in reader:
if row['Woche'] == 'NA':
continue
date = sc.date_from_text(row['Woche'])
if date not in data:
data[date] = 0
data[date] += int(row['Anzahl Fälle'])
days = list(data.keys())
for day in days:
td = sc.TestData(canton='ZG', url=csv_url)
td.start_date = day.isoformat()
td.end_date = (day + datetime.timedelta(days=6)).isoformat()
td.total_tests = data[day]
print(td)
#!/usr/bin/env python3
import scrape_common as sc
url = 'https://www.llv.li/files/as/grafik_covid19_tests_pro_kw.xlsx'
xls = sc.xlsdownload(url, silent=True)
rows = sc.parse_xls(xls, header_row=52, sheet_name='gTests_AG')
for row in rows:
if row['B'] is None:
# skip the footer line
continue
td = sc.TestData(canton='FL', url=url)
td.week = sc.find(r'KW (\d+)', row['B'])
td.year = '2020'
td.negative_tests = row['Negativ']
td.positive_tests = row['Positiv']
print(td)
chrome_options = Options()
chrome_options.add_argument("--headless")
driver = webdriver.Chrome(options=chrome_options)
driver.implicitly_wait(5)
url = 'https://infocovid.smc.unige.ch/'
driver.get(url)
elem = driver.find_element_by_link_text('Graphiques')
elem.click()
elem = driver.find_element_by_partial_link_text('Tests')
elem.click()
xls_url = sgc.get_link_from_element(driver, 'save_plot_nombre_tests_data')
assert xls_url, "Couldn't find tests XLS url"
xls = sc.xlsdownload(xls_url, silent=True)
rows = sc.parse_xls(xls, header_row=0, enable_float=True)
for row in rows:
td = sc.TestData(canton='GE', url=url)
res = re.search(r'(\d{2})-(\d{2})', row['week_res'])
assert res, f"failed to extract year and week from {row['week_res']}"
td.week = int(res[2])
td.year = f'20{res[1]}'
td.positive_tests = int(row['positifs'])
td.negative_tests = int(row['négatifs'])
td.total_tests = int(row['total'])
# 2020-02/03 values are empty
td.positivity_rate = 0
if row['ratio']:
td.positivity_rate = float(row['ratio'])
print(td)
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import re
import scrape_common as sc
import scrape_nw_common as snc
url, soup = snc.get_nw_page()
td = sc.TestData(canton='NW', url=url)
item = soup.find(text=re.compile('Anzahl F.lle')).find_parent('p')
assert item, f"Could not find title item in {url}"
date = sc.find(r'Stand: (\d+\. .* 20\d{2})', item.text)
date = sc.date_from_text(date)
td.start_date = date.isoformat()
td.end_date = date.isoformat()
rows = item.find_next('table').findChildren('tr')
for row in rows:
cols = row.findChildren('td')
item = cols[0].text
if re.match(r'Covid-19-Tests innert 24h.*', item, re.I):
res = re.match(r'(\d+)\s+(\d+\.?\d?)%', cols[1].text)
assert res
td.total_tests = res[1]
td.positivity_rate = res[2]
assert td
print(td)
#!/usr/bin/env python3
import csv
from io import StringIO
import scrape_common as sc
url = 'https://raw.githubusercontent.com/openZH/covid_19/master/fallzahlen_kanton_zh/COVID19_Anteil_positiver_Test_pro_KW.csv'
data = sc.download(url, silent=True)
reader = csv.DictReader(StringIO(data), delimiter=',')
for row in reader:
td = sc.TestData(canton='ZH', url=url)
td.start_date = row['Woche_von']
td.end_date = row['Woche_bis']
td.week = row['Kalenderwoche']
td.positive_tests = int(row['Anzahl_positiv'])
td.negative_tests = int(row['Anzahl_negativ'])
td.positivity_rate = float(row['Anteil_positiv'])
print(td)