def main():
url = "https://www.terviseamet.ee/et/uudised"
soup = BeautifulSoup(requests.get(url).content, "html.parser")
for h2 in soup.find_all("h2", class_="views-field-title"):
if "COVID-19 blogi" in h2.text:
url = "https://www.terviseamet.ee" + h2.find("a")["href"]
break
soup = BeautifulSoup(requests.get(url).content, "html.parser")
text = soup.find(class_="node-published").text
people_vaccinated, people_fully_vaccinated = re.search(
r"Eestis on COVID-19 vastu vaktsineerimisi tehtud ([\d\s]+) inimesele, kaks doosi on saanud ([\d\s]+) inimest",
text).groups()
people_vaccinated = vaxutils.clean_count(people_vaccinated)
people_fully_vaccinated = vaxutils.clean_count(people_fully_vaccinated)
total_vaccinations = people_vaccinated + people_fully_vaccinated
date = soup.find(class_="field-name-post-date").text
date = vaxutils.clean_date(date, "%d.%m.%Y")
vaxutils.increment(location="Estonia",
total_vaccinations=total_vaccinations,
people_vaccinated=people_vaccinated,
people_fully_vaccinated=people_fully_vaccinated,
date=date,
source_url=url,
vaccine="Pfizer/BioNTech")
def main():
url = "https://covid19.gov.im/general-information/latest-updates/"
soup = BeautifulSoup(requests.get(url).content, "html.parser")
vax_box = soup.find(string=re.compile("Total first vaccinations")).parent.parent
date = vax_box.find("strong").text
date = vaxutils.clean_date(date, "%d %B %Y")
for p in vax_box.find_all("p"):
if "Total first vaccinations" in p.text:
data = p.text
people_vaccinated, people_fully_vaccinated = re.search(r"Total first vaccinations:\xa0 ([\d,]+)Total second vaccinations:\xa0 ([\d,]+)", data).groups()
people_vaccinated = vaxutils.clean_count(people_vaccinated)
people_fully_vaccinated = vaxutils.clean_count(people_fully_vaccinated)
total_vaccinations = people_vaccinated + people_fully_vaccinated
vaxutils.increment(
location="Isle of Man",
total_vaccinations=total_vaccinations,
people_vaccinated=people_vaccinated,
people_fully_vaccinated=people_fully_vaccinated,
date=date,
source_url=url,
vaccine="Pfizer/BioNTech"
)
def main():
url = "https://www.kemkes.go.id/"
soup = BeautifulSoup(requests.get(url).content, "html.parser")
date = soup.find(class_="covid-case-container").find(
class_="info-date").text.replace("Kondisi ", "")
date = str(dateparser.parse(date, languages=["id"]).date())
people_vaccinated = soup.find(
class_="description",
text="Vaksinasi-1").parent.find(class_="case").text
people_vaccinated = vaxutils.clean_count(people_vaccinated)
people_fully_vaccinated = soup.find(
class_="description",
text="Vaksinasi-2").parent.find(class_="case").text
people_fully_vaccinated = vaxutils.clean_count(people_fully_vaccinated)
total_vaccinations = people_vaccinated + people_fully_vaccinated
vaxutils.increment(location="Indonesia",
total_vaccinations=total_vaccinations,
people_vaccinated=people_vaccinated,
people_fully_vaccinated=people_fully_vaccinated,
date=date,
source_url=url,
vaccine="Sinovac")
def parse_data(soup: BeautifulSoup) -> pd.Series:
people_vaccinated = vaxutils.clean_count(
soup
.find(class_="status_infoArea")
.find(class_="round1")
.find(class_="big")
.text
)
people_fully_vaccinated = vaxutils.clean_count(
soup
.find(class_="status_infoArea")
.find(class_="round2")
.find(class_="big")
.text
)
total_vaccinations = people_vaccinated + people_fully_vaccinated
date = str((datetime.datetime.now(pytz.timezone("Asia/Seoul")) - datetime.timedelta(days=1)).date())
data = {
"date": date,
"people_vaccinated": people_vaccinated,
"people_fully_vaccinated": people_fully_vaccinated,
"total_vaccinations": total_vaccinations,
}
return pd.Series(data=data)
def connect_parse_data(source: str) -> pd.Series:
op = Options()
op.add_argument("--headless")
with webdriver.Chrome(options=op) as driver:
driver.get(source)
time.sleep(10)
date = driver.find_element_by_class_name(
"as_of").find_element_by_tag_name("span").text
date = vaxutils.clean_date(date, "%d.%m.%Y")
for elem in driver.find_elements_by_class_name("counter_block"):
if "1 ДОЗУ" in elem.text:
people_vaccinated = elem.find_element_by_tag_name("h2").text
if "2 ДОЗИ" in elem.text:
people_fully_vaccinated = elem.find_element_by_tag_name(
"h2").text
data = {
"people_vaccinated": vaxutils.clean_count(people_vaccinated),
"people_fully_vaccinated":
vaxutils.clean_count(people_fully_vaccinated),
"date": date,
}
return pd.Series(data=data)
def main():
url = "https://www.exploregov.ky/coronavirus-statistics#vaccine-dashboard"
soup = BeautifulSoup(requests.get(url).content, "html.parser")
total_vaccinations = re.search(
r"The total number of COVID-19 vaccines administered to date is ([\d,]+)",
soup.text)
total_vaccinations = vaxutils.clean_count(total_vaccinations.group(1))
people_fully_vaccinated = re.search(
r"The total number of people completing the two-dose course is ([\d,]+)",
soup.text)
people_fully_vaccinated = vaxutils.clean_count(
people_fully_vaccinated.group(1))
people_vaccinated = total_vaccinations - people_fully_vaccinated
date = str(datetime.datetime.now(pytz.timezone("America/Cayman")).date())
vaxutils.increment(location="Cayman Islands",
total_vaccinations=total_vaccinations,
people_vaccinated=people_vaccinated,
people_fully_vaccinated=people_fully_vaccinated,
date=date,
source_url=url,
vaccine="Pfizer/BioNTech")
def main():
url = "https://covid19asi.saglik.gov.tr/"
soup = BeautifulSoup(requests.get(url).content, "html.parser")
total_vaccinations = re.search(r"var yapilanasisayisi = (\d+);",
str(soup)).group(1)
total_vaccinations = vaxutils.clean_count(total_vaccinations)
people_vaccinated = re.search(r"var asiyapilankisisayisi1Doz = (\d+);",
str(soup)).group(1)
people_vaccinated = vaxutils.clean_count(people_vaccinated)
people_fully_vaccinated = re.search(
r"var asiyapilankisisayisi2Doz = (\d+);", str(soup)).group(1)
people_fully_vaccinated = vaxutils.clean_count(people_fully_vaccinated)
date = str(datetime.datetime.now(pytz.timezone("Asia/Istanbul")).date())
vaxutils.increment(location="Turkey",
total_vaccinations=total_vaccinations,
people_vaccinated=people_vaccinated,
people_fully_vaccinated=people_fully_vaccinated,
date=date,
source_url=url,
vaccine="Sinovac")
def main():
# Options for Chrome WebDriver
op = Options()
op.add_argument("--headless")
with webdriver.Chrome(options=op) as driver:
url = "https://datastudio.google.com/embed/u/0/reporting/2f2537fa-ac23-4f08-8741-794cdbedca03/page/CPFTB"
driver.get(url)
time.sleep(5)
for elem in driver.find_elements_by_class_name("kpimetric"):
if "1ª Dose" in elem.text:
people_vaccinated = elem.find_element_by_class_name(
"valueLabel").text
elif "2ª Dose" in elem.text:
people_fully_vaccinated = elem.find_element_by_class_name(
"valueLabel").text
people_vaccinated = vaxutils.clean_count(people_vaccinated)
people_fully_vaccinated = vaxutils.clean_count(people_fully_vaccinated)
total_vaccinations = people_vaccinated + people_fully_vaccinated
date = str(datetime.datetime.now(pytz.timezone("Brazil/East")).date())
vaxutils.increment(location="Brazil",
total_vaccinations=total_vaccinations,
people_vaccinated=people_vaccinated,
people_fully_vaccinated=people_fully_vaccinated,
date=date,
source_url="https://coronavirusbra1.github.io/",
vaccine="Oxford/AstraZeneca, Sinovac")
def parse_data(url: str) -> pd.Series:
kwargs = {"pandas_options": {"dtype": str, "header": None}}
dfs_from_pdf = tabula.read_pdf(url, pages="all", **kwargs)
assert len(dfs_from_pdf) == 1
df = dfs_from_pdf[0]
df = df[df[0] == "India"]
people_vaccinated = vaxutils.clean_count(df[1].item())
people_fully_vaccinated = vaxutils.clean_count(df[2].item())
total_vaccinations = vaxutils.clean_count(df[3].item())
return pd.Series({
"date":
str((datetime.datetime.now(pytz.timezone("Asia/Kolkata")) -
datetime.timedelta(days=1)).date()),
"people_vaccinated":
people_vaccinated,
"people_fully_vaccinated":
people_fully_vaccinated,
"total_vaccinations":
total_vaccinations,
"source_url":
url,
})
def main():
url = "https://data.public.lu/fr/datasets/covid-19-rapports-journaliers/#_"
# Locate newest pdf
soup = BeautifulSoup(requests.get(url).content, "html.parser")
pdf_path = soup.find(
"a", class_="btn-primary")["href"] # Get path to newest pdf
# Fetch data
dfs_from_pdf = tabula.read_pdf(pdf_path, pages="all")
df = pd.DataFrame(dfs_from_pdf[2]) # Hardcoded table location
people_vaccinated = df.loc[df["Unnamed: 0"] ==
"Personnes vaccinées - Dose 1",
"Unnamed: 2"].values[0]
people_vaccinated = vaxutils.clean_count(people_vaccinated)
people_fully_vaccinated = df.loc[df["Unnamed: 0"] ==
"Personnes vaccinées - Dose 2",
"Unnamed: 2"].values[0]
people_fully_vaccinated = vaxutils.clean_count(people_fully_vaccinated)
total_vaccinations = people_vaccinated + people_fully_vaccinated
date = df["Unnamed: 1"].str.replace("Journée du ", "").values[0]
date = vaxutils.clean_date(date, "%d.%m.%Y")
vaxutils.increment(location="Luxembourg",
total_vaccinations=total_vaccinations,
people_vaccinated=people_vaccinated,
people_fully_vaccinated=people_fully_vaccinated,
date=date,
source_url=pdf_path,
vaccine="Pfizer/BioNTech")
def connect_parse_data(source: str) -> pd.Series:
headers = {
"User-Agent":
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10.16; rv:86.0) Gecko/20100101 Firefox/86.0",
"Accept":
"text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8",
"Accept-Language": "fr,fr-FR;q=0.8,en-US;q=0.5,en;q=0.3",
"Accept-Encoding": "gzip, deflate, br",
"Connection": "keep-alive",
"Upgrade-Insecure-Requests": "1",
"Pragma": "no-cache",
"Cache-Control": "no-cache",
}
soup = BeautifulSoup(
requests.get(source, headers=headers).content, "html.parser")
data = re.search(r"De los ([\d\.]+) vacunados, ([\d\.]+)", soup.text)
people_vaccinated = vaxutils.clean_count(data.group(1))
people_fully_vaccinated = vaxutils.clean_count(data.group(2))
data = {
"people_vaccinated": people_vaccinated,
"people_fully_vaccinated": people_fully_vaccinated,
}
return pd.Series(data=data)
def parse_data(url: str) -> pd.Series:
kwargs = {"pandas_options": {"dtype": str, "header": None}}
dfs_from_pdf = tabula.read_pdf(url, pages="all", **kwargs)
for df in dfs_from_pdf:
if "Beneficiaries vaccinated" in dfs_from_pdf[0].values.flatten():
break
df = df[df[0] == "India"]
ncols = df.shape[1]
people_vaccinated = vaxutils.clean_count(df[ncols - 3].item())
people_fully_vaccinated = vaxutils.clean_count(df[ncols - 2].item())
total_vaccinations = vaxutils.clean_count(df[ncols - 1].item())
return pd.Series({
"date":
str((datetime.datetime.now(pytz.timezone("Asia/Kolkata")) -
datetime.timedelta(days=1)).date()),
"people_vaccinated":
people_vaccinated,
"people_fully_vaccinated":
people_fully_vaccinated,
"total_vaccinations":
total_vaccinations,
"source_url":
url,
})
def parse_data(soup: BeautifulSoup) -> pd.Series:
numbers = soup.find(class_="cifras-coronavirus").find_all(class_="cifra")
return pd.Series(
data={
"total_vaccinations": vaxutils.clean_count(numbers[1].text),
"people_fully_vaccinated": vaxutils.clean_count(numbers[2].text),
"date": set_date()
})
def parse_data(soup: BeautifulSoup) -> pd.Series:
regex = r"The total number of COVID-19 vaccines administered to date is ([\d,]+)\.\sSo far, ([\d,]+) .* have received at least one dose of the Pfizer-BioNTech vaccine"
matches = re.search(regex, soup.text)
total_vaccinations = vaxutils.clean_count(matches.group(1))
people_vaccinated = vaxutils.clean_count(matches.group(2))
assert total_vaccinations >= people_vaccinated
people_fully_vaccinated = total_vaccinations - people_vaccinated
return pd.Series({
"total_vaccinations": total_vaccinations,
"people_vaccinated": people_vaccinated,
"people_fully_vaccinated": people_fully_vaccinated,
})
def main():
url = "https://data.public.lu/fr/datasets/covid-19-rapports-journaliers/#_"
# Locate newest pdf
html_page = urllib.request.urlopen(url)
soup = BeautifulSoup(html_page, "html.parser")
pdf_path = soup.find(
"a", class_="btn-primary")["href"] # Get path to newest pdf
# Fetch data
dfs_from_pdf = tabula.read_pdf(pdf_path, pages="all")
df = pd.DataFrame(dfs_from_pdf[2]) # Hardcoded table location
total_vaccinations = df.loc[df["Unnamed: 0"] ==
"Nombre de doses administrées",
"Unnamed: 1"].values[0]
total_vaccinations = vaxutils.clean_count(total_vaccinations)
date = re.search(r"\d\d\.\d\d\.202\d", df.columns[1]).group(0)
date = vaxutils.clean_date(date, "%d.%m.%Y")
vaxutils.increment(location="Luxembourg",
total_vaccinations=total_vaccinations,
date=date,
source_url=pdf_path,
vaccine="Pfizer/BioNTech")
def parse_data(pdf_link) -> str:
url = "https://www.rivm.nl" + pdf_link["href"]
kwargs = {"pandas_options": {"dtype": str}}
dfs_from_pdf = tabula.read_pdf(url, pages="all", **kwargs)
for df in dfs_from_pdf:
if "Eerste" in df.columns:
break
people_vaccinated = vaxutils.clean_count(df.loc[df.Doelgroep == "Totaal",
"Eerste"].item())
people_fully_vaccinated = vaxutils.clean_count(
df.loc[df.Doelgroep == "Totaal", "Tweede"].item())
total_vaccinations = people_vaccinated + people_fully_vaccinated
return total_vaccinations, people_vaccinated, people_fully_vaccinated
def connect_parse_data(source: str) -> pd.Series:
headers = {
"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10.16; rv:86.0) Gecko/20100101 Firefox/86.0",
"Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8",
"Accept-Language": "fr,fr-FR;q=0.8,en-US;q=0.5,en;q=0.3",
"Accept-Encoding": "gzip, deflate, br",
"Connection": "keep-alive",
"Upgrade-Insecure-Requests": "1",
"Pragma": "no-cache",
"Cache-Control": "no-cache",
}
soup = BeautifulSoup(requests.get(source, headers=headers).content, "html.parser")
total_vaccinations = soup.find(class_="repart-stlucia").text
total_vaccinations = vaxutils.clean_count(total_vaccinations)
date = soup.find(class_="h2-blue").text
date = re.search(r"\w+ \d+, 202\d", date).group(0)
date = vaxutils.clean_date(date, "%B %d, %Y")
data = {
"total_vaccinations": total_vaccinations,
"date": date,
}
return pd.Series(data=data)
def main():
date = datetime.date.today() - datetime.timedelta(days=1)
url_date = date.strftime("%-d.%-m.%y")
url = f"http://www.covidmaroc.ma/Documents/BULLETIN/{url_date}.COVID-19.pdf"
os.system(
"curl http://www.covidmaroc.ma/Documents/BULLETIN/1.2.21.COVID-19.pdf -o morocco.pdf -s"
)
with open("morocco.pdf", "rb") as pdfFileObj:
pdfReader = PyPDF2.PdfFileReader(pdfFileObj)
text = pdfReader.getPage(0).extractText()
regex = r"Bénéficiaires de la vaccination\s+Cumul global([\d\s]+)Situation épidémiologique"
total_vaccinations = re.search(regex, text)
total_vaccinations = vaxutils.clean_count(total_vaccinations.group(1))
date = str(date)
vaxutils.increment(location="Morocco",
total_vaccinations=total_vaccinations,
date=date,
source_url=url,
vaccine="Oxford/AstraZeneca, Sinopharm")
os.remove("morocco.pdf")
def main():
url = "https://esriportugal.maps.arcgis.com/apps/opsdashboard/index.html#/acf023da9a0b4f9dbb2332c13f635829"
# Options for Chrome WebDriver
op = Options()
# op.add_argument("--headless")
with webdriver.Chrome(options=op) as driver:
driver.get(url)
time.sleep(4)
for box in driver.find_elements_by_class_name("indicator-top-text"):
if "Total de Vacinas Administradas" in box.text:
count_text = box.find_element_by_xpath("..").text
elif "Dados relativos ao boletim da DGS de" in box.text:
date_text = box.find_element_by_xpath("..").text
count = re.search(r"\n([\d\s]+$)", count_text).group(1)
count = vaxutils.clean_count(count)
date = re.search(r"\n([\d/]+$)", date_text).group(1)
date = vaxutils.clean_date(date, "%d/%m/%Y")
vaxutils.increment(location="Portugal",
total_vaccinations=count,
date=date,
source_url=url,
vaccine="Pfizer/BioNTech")
def main():
url = "https://datadashboard.health.gov.il/COVID-19/general"
# Options for Chrome WebDriver
op = Options()
op.add_argument("--headless")
with webdriver.Chrome(options=op) as driver:
driver.get(url)
time.sleep(2)
for counter in driver.find_elements_by_class_name("title-header"):
if "מתחסנים מנה ראשונה" in counter.text:
count = counter.find_element_by_class_name("total-amount").text
count = vaxutils.clean_count(count)
break
date = str(datetime.datetime.now(pytz.timezone("Asia/Jerusalem")).date())
vaxutils.increment(location="Israel",
total_vaccinations=count,
date=date,
source_url=url,
vaccine="Pfizer/BioNTech")
def main():
url = "https://vaccinocovid.iss.sm/"
soup = BeautifulSoup(
requests.get(url, verify=False).content, "html.parser")
for script in soup.find_all("script"):
if "new Chart" in str(script):
chart_data = str(script)
break
people_vaccinated = re.search(r"([\d,. ]+) [Vv]accinati",
chart_data).group(1)
people_vaccinated = vaxutils.clean_count(people_vaccinated)
people_fully_vaccinated = 0
total_vaccinations = people_vaccinated + people_fully_vaccinated
date = re.search(r"Dati aggiornati al (\d{2}/\d{2}/\d{4})",
chart_data).group(1)
date = vaxutils.clean_date(date, "%d/%m/%Y")
vaxutils.increment(location="San Marino",
total_vaccinations=total_vaccinations,
people_vaccinated=people_vaccinated,
people_fully_vaccinated=people_fully_vaccinated,
date=date,
source_url="https://vaccinocovid.iss.sm/",
vaccine="Sputnik V")
def main():
url = "https://vaccinare-covid.gov.ro/comunicate-oficiale/"
soup = BeautifulSoup(requests.get(url).content, "html.parser")
links = soup.find(class_="display-posts-listing").find_all("a",
class_="title")
for link in links:
if "Actualizare zilnică" in link.text:
url = link["href"]
break
soup = BeautifulSoup(requests.get(url).content, "html.parser")
date = soup.find(class_="post-date").find(class_="meta-text").text.strip()
date = vaxutils.clean_date(date, "%b %d, %Y")
main_text = soup.find(class_="entry-content-text").text
count = re.search(
r"Număr total de persoane vaccinate împotriva COVID-19 cu vaccinul Pfizer BioNTech \(începând cu data de 27 decembrie 2020\) – ([\d\.]+)",
main_text)
count = count.group(1)
count = vaxutils.clean_count(count)
vaxutils.increment(location="Romania",
total_vaccinations=count,
date=date,
source_url=url,
vaccine="Pfizer/BioNTech")
def main():
url = "https://thl.fi/fi/web/infektiotaudit-ja-rokotukset/ajankohtaista/ajankohtaista-koronaviruksesta-covid-19/tilannekatsaus-koronaviruksesta"
page = requests.get(url)
soup = BeautifulSoup(page.content, "html.parser")
for p in soup.find(class_="journal-content-article").find_all("p"):
if "Annetut rokoteannokset" in p.text:
break
count = p.find("strong").text
count = vaxutils.clean_count(count)
date = soup.find(class_="thl-image-caption").text
date = re.compile(r"Tiedot on päivitetty (\d+)\.(\d+)").search(date)
date = datetime.date(year=2021,
month=int(date.group(2)),
day=int(date.group(1)))
date = str(date)
vaxutils.increment(location="Finland",
total_vaccinations=count,
date=date,
source_url=url,
vaccine="Pfizer/BioNTech")
def main():
url = "https://www.gov.bm/sites/default/files/COVID-19%20Vaccination%20Updates.pdf"
os.system(f"curl {url} -o bermuda.pdf -s")
with open("bermuda.pdf", "rb") as pdfFileObj:
pdfReader = PyPDF2.PdfFileReader(pdfFileObj)
text = pdfReader.getPage(0).extractText()
regex = r"VACCINATION CENTRE(.*?)Total Vaccines Administered"
total_vaccinations = re.search(regex, text)
total_vaccinations = vaxutils.clean_count(total_vaccinations.group(1))
regex = r"As of (\w+ \d+, 20\d+)"
date = re.search(regex, text)
date = vaxutils.clean_date(date.group(1), "%B %d, %Y")
vaxutils.increment(
location="Bermuda",
total_vaccinations=total_vaccinations,
date=date,
source_url=url,
vaccine="Pfizer/BioNTech"
)
os.remove("bermuda.pdf")
def main():
data = {
"location": "Guatemala",
"source_url":
"https://gtmvigilanciacovid.shinyapps.io/3869aac0fb95d6baf2c80f19f2da5f98",
"vaccine": "Moderna",
}
with webdriver.Chrome() as driver:
driver.get(data["source_url"])
time.sleep(2)
driver.find_element_by_class_name("fa-syringe").click()
time.sleep(4)
date = driver.find_element_by_class_name("logo").text
dose1 = driver.find_element_by_id(
"dosisaplicadas").find_element_by_tag_name("h3").text
data["people_vaccinated"] = vaxutils.clean_count(dose1)
data["people_fully_vaccinated"] = 0
data["total_vaccinations"] = data["people_vaccinated"] + data[
"people_fully_vaccinated"]
date = re.search(r"\d+/\d+/202\d", date).group(0)
data["date"] = vaxutils.clean_date(date, "%d/%m/%Y")
vaxutils.increment(
location=data["location"],
total_vaccinations=data["total_vaccinations"],
people_vaccinated=data["people_vaccinated"],
people_fully_vaccinated=data["people_fully_vaccinated"],
date=data["date"],
source_url=data["source_url"],
vaccine=data["vaccine"],
)
def main():
url = "https://vaccinare-covid.gov.ro/comunicate-oficiale/"
soup = BeautifulSoup(requests.get(url).content, "html.parser")
links = soup.find(class_="display-posts-listing").find_all("a", class_="title")
for link in links:
if "Actualizare zilnică" in link.text:
url = link["href"]
break
soup = BeautifulSoup(requests.get(url).content, "html.parser")
date = soup.find(class_="post-date").find(class_="meta-text").text.strip()
date = vaxutils.clean_date(date, "%b %d, %Y")
paragraphs = soup.find(class_="entry-content").find_all("p")
for paragraph in paragraphs:
if "Număr total de persoane vaccinate" in paragraph.text:
count = paragraph.find_all("strong")
count = "".join(c.text for c in count)
count = vaxutils.clean_count(count)
vaxutils.increment(
location="Romania",
total_vaccinations=count,
date=date,
source_url=url,
vaccine="Pfizer/BioNTech"
)
def main():
url = "https://www.terviseamet.ee/et/uudised"
soup = BeautifulSoup(requests.get(url).content, "html.parser")
for h2 in soup.find_all("h2", class_="views-field-title"):
if "COVID-19 blogi" in h2.text:
url = "https://www.terviseamet.ee" + h2.find("a")["href"]
break
soup = BeautifulSoup(requests.get(url).content, "html.parser")
date = soup.find(class_="field-name-post-date").text
date = vaxutils.clean_date(date, "%d.%m.%Y")
count = soup.find(
string=re.compile(r"Eestis on COVID-19 vastu vaktsineerimisi"))
count = re.search(r"tehtud ([\d\s]+) inimesele", count).group(1)
count = vaxutils.clean_count(count)
vaxutils.increment(location="Estonia",
total_vaccinations=count,
date=date,
source_url=url,
vaccine="Pfizer/BioNTech")
def main():
op = Options()
op.add_argument("--headless")
with webdriver.Chrome(options=op) as driver:
url = "https://app.powerbi.com/view?r=eyJrIjoiMzg4YmI5NDQtZDM5ZC00ZTIyLTgxN2MtOTBkMWM4MTUyYTg0IiwidCI6ImFmZDBhNzVjLTg2NzEtNGNjZS05MDYxLTJjYTBkOTJlNDIyZiIsImMiOjh9"
driver.get(url)
# Wait for the desired element to load. If nothing is found after 25 seconds, returns.
timeout = 25
try:
element_present = EC.presence_of_element_located(
(By.CLASS_NAME, "value"))
data = WebDriverWait(driver, timeout).until(element_present).text
except TimeoutException:
return
count = vaxutils.clean_count(data)
try:
element_present = EC.presence_of_element_located(
(By.CLASS_NAME, "title"))
data = WebDriverWait(driver, timeout).until(element_present).text
except TimeoutException:
return
date = vaxutils.clean_date(data, "%m/%d/%Y %H:%M:%S %p")
vaxutils.increment(location="Italy",
total_vaccinations=count,
date=date,
source_url=url,
vaccine="Pfizer/BioNTech")
def parse_data(data: dict) -> pd.Series:
sheet_id = data["sheetNames"].index("Vakcinisani ukupno")
total_vaccinations = vaxutils.clean_count(data["data"][sheet_id][0][0])
date = vaxutils.clean_date(data["data"][1][0][0], "%d.%m.%Y.")
data = {"date": date, "total_vaccinations": total_vaccinations}
return pd.Series(data=data)
def parse_data(source: str) -> pd.Series:
os.system(f"curl {source} -o morocco.pdf -s")
dfs = tabula.read_pdf("morocco.pdf",
pages=1,
pandas_options={
"dtype": str,
"header": None
})
df = dfs[2]
data = {
"people_fully_vaccinated": vaxutils.clean_count(df[0].values[-1]),
"people_vaccinated": vaxutils.clean_count(df[1].values[-1]),
}
data["total_vaccinations"] = data["people_vaccinated"] + data[
"people_fully_vaccinated"]
return pd.Series(data=data)