def main():
# Log status
logger.info("Loading local data files")
test_results = read_json_from_file(TEST_RESULTS_PATH)
# Get data for each chart
logger.info("Calculating data for charts")
infections_by_county = get_infection_count_by_county(
test_results, COUNTY_MAPPING)
infections_by_county_10000 = get_infections_data_by_count_10000(
infections_by_county, COUNTY_POPULATION)
tests_pop_ratio = get_test_data_pop_ratio(infections_by_county_10000)
# Create dictionary for final JSON
logger.info("Compiling final JSON")
final_json = {
"updatedOn": TODAY_DMYHM,
"dataTestsPopRatio": tests_pop_ratio,
}
# Dump JSON output
save_as_json(TESTS_POP_RATIO_PATH, final_json)
# Log finish time
logger.info("Finished update process")
def main():
# Log status
logger.info("Loading local data files")
test_results = read_json_from_file(TEST_RESULTS_PATH)
logger.info("Calculating data for charts")
positive_test_by_age_chart_data = get_positive_tests_by_age_chart_data(
test_results)
# Create dictionary for final JSON
logger.info("Compiling final JSON")
final_json = {
"updatedOn": TODAY_DMYHM,
"maleTotal": positive_test_by_age_chart_data["maleTotal"],
"femaleTotal": positive_test_by_age_chart_data["femaleTotal"],
"maleNegative": positive_test_by_age_chart_data["maleNegative"],
"malePositive": positive_test_by_age_chart_data["malePositive"],
"femaleNegative": positive_test_by_age_chart_data["femaleNegative"],
"femalePositive": positive_test_by_age_chart_data["femalePositive"],
}
# Dump JSON output
save_as_json(GENDER_PATH, final_json)
# Log finish time
logger.info("Finished update process")
def main():
# Log status
logger.info("Loading local data files")
test_results = read_json_from_file(TEST_RESULTS_PATH)
# Log status
logger.info("Calculating main statistics")
# Create date ranges for charts
case_dates = pd.date_range(start=DATE_SETTINGS["firstCaseDate"],
end=YESTERDAY_YMD)
# Set recovered, deceased, hospitalized and ICU time-series
cumulative_tests_chart_data = get_cumulative_tests_chart_data(
test_results, case_dates)
# Create dictionary for final JSON
logger.info("Compiling final JSON")
final_json = {
"updatedOn": TODAY_DMYHM,
"caseDates": [str(x.date()) for x in case_dates],
"testsAdministered": cumulative_tests_chart_data["testsAdministered"],
}
# Dump JSON output
save_as_json(CUMULATIVE_TESTS_PATH, final_json)
# Log finish time
logger.info("Finished update process")
def main():
# Log status
logger.info("Loading local data files")
test_results = read_json_from_file(TEST_RESULTS_PATH)
logger.info("Calculating main statistics")
# Create date ranges for charts
case_dates = pd.date_range(start=DATE_SETTINGS["firstCaseDate"],
end=YESTERDAY_YMD)
logger.info("Calculating data for charts")
tests_per_day_chart_data = get_tests_per_day_chart_data(
test_results, case_dates)
# Create dictionary for final JSON
logger.info("Compiling final JSON")
final_json = {
"updatedOn": TODAY_DMYHM,
"caseDates": [str(x.date()) for x in case_dates],
"dataTestsPerDayChart": tests_per_day_chart_data,
}
# Dump JSON output
save_as_json(TESTS_PER_DAY_PATH, final_json)
# Log finish time
logger.info("Finished update process")
def main():
# Log status
logger.info("Loading local data files")
vaccination = read_json_from_file(VACCINATIONS_PATH)
logger.info("Calculating main statistics")
vaccination_dates = pd.date_range(
start=DATE_SETTINGS["vaccinationStartDate"], end=YESTERDAY_YMD)
logger.info("Calculating data for charts")
vaccinated_people_chart_data = get_vaccinated_people_chart_data(
vaccination, vaccination_dates)
# Create dictionary for final JSON
logger.info("Compiling final JSON")
final_json = {
"updatedOn": TODAY_DMYHM,
"vaccinationDates": [str(x.date()) for x in vaccination_dates],
"dataVaccinatedPeopleChart": vaccinated_people_chart_data,
}
# Dump JSON output
save_as_json(VACCINATED_PEOPLE_PATH, final_json)
# Log finish time
logger.info("Finished update process")
def main():
# Log status
logger.info("Loading local data files")
test_results = read_json_from_file(TEST_RESULTS_PATH)
# Log status
logger.info("Calculating main statistics")
# Create date ranges for charts
case_dates = pd.date_range(start=DATE_SETTINGS["firstCaseDate"],
end=YESTERDAY_YMD)
# Get data for each chart
logger.info("Calculating data for charts")
county_by_day = get_county_by_day(test_results, case_dates, COUNTY_MAPPING,
COUNTY_POPULATION)
confirmed_cases_by_county = get_confirmed_cases_by_county(
test_results, COUNTY_MAPPING)
del county_by_day["mapPlayback"]
del county_by_day["mapPlayback10k"]
# Create dictionary for final JSON
logger.info("Compiling final JSON")
final_json = {
"updatedOn": TODAY_DMYHM,
"dataConfirmedCasesByCounties": confirmed_cases_by_county,
"countyByDay": county_by_day,
}
# Dump JSON output
save_as_json(CONFIRMED_CASES_BY_COUNTIES_PATH, final_json)
# Log finish time
logger.info("Finished update process")
def main():
# Log status
logger.info("Loading local data files")
test_results = read_json_from_file(TEST_RESULTS_PATH)
# Log status
logger.info("Calculating main statistics")
# Create date ranges for charts
case_dates = pd.date_range(start=DATE_SETTINGS["firstCaseDate"],
end=YESTERDAY_YMD)
county_by_day = get_county_by_day(test_results, case_dates, COUNTY_MAPPING,
COUNTY_POPULATION)
# Create dictionary for final JSON
logger.info("Compiling final JSON")
final_json = {
"updatedOn": TODAY_DMYHM,
"caseDates": [str(x.date()) for x in case_dates],
"newCountyByDay": county_by_day["newCountyByDay"],
}
# Dump JSON output
save_as_json(DAILY_COUNTY_NEW_CASES_PATH, final_json)
# Log finish time
logger.info("Finished update process")
def main():
# Log status
logger.info("Loading local data files")
test_results = read_json_from_file(TEST_RESULTS_PATH)
hospitalization = read_json_from_file(HOSPITALIZATION_PATH)
deaths = read_json_from_file(DEATHS_PATH)
manual_data = read_json_from_file(MANUAL_DATA_PATH)
# Log status
logger.info("Calculating main statistics")
# Create date ranges for charts
case_dates = pd.date_range(start=DATE_SETTINGS["firstCaseDate"],
end=YESTERDAY_YMD)
# Set recovered, deceased, hospitalized and ICU time-series
hospital = get_hospital_data(hospitalization,
DATE_SETTINGS["firstCaseDate"])
recovered = hospital["discharged"]
manual_data["deceased"].update(deaths)
deceased = list(manual_data["deceased"].values())
hospitalized = hospital["activeHospitalizations"]
# TODO: Based on cross-checking with the hospitalization data publishedby TEHIK, the data listed
# in the manual_data.json file with the field name "intensive" appears to show the number
# of patients on ventilation. We should fix the terminology and make sure that the intensive
# and on ventilation statistics are being calculated correctly.
intensive = list(
get_in_intensive_data(hospitalization,
manual_data["intensive"]).values())
on_ventilation = list(get_on_ventilation_data(hospitalization).values())
# Get data for each chart
logger.info("Calculating data for charts")
cumulative_cases_chart_data = get_cumulative_cases_chart_data(
test_results,
recovered,
deceased,
hospitalized,
intensive,
on_ventilation,
case_dates,
)
del cumulative_cases_chart_data["active100k"]
# Create dictionary for final JSON
logger.info("Compiling final JSON")
final_json = {
"updatedOn": TODAY_DMYHM,
"caseDates": [str(x.date()) for x in case_dates],
"dataCumulativeCasesChart": cumulative_cases_chart_data,
}
# Dump JSON output
save_as_json(CUMULATIVE_CASES_PATH, final_json)
# Log finish time
logger.info("Finished update process")
def main():
ap = ArgumentParser()
ap.add_argument("--parallel", type=int, default=1)
opts = ap.parse_args()
script_name = Path(__file__).name
scripts = []
for f in sorted(Path("build").glob("generate_*.py")):
if f.name == script_name:
continue
scripts.append(f)
total = len(scripts)
logger.info("Found {total} generators", total=total)
if opts.parallel == 1:
for idx, path in enumerate(scripts):
run(path, idx + 1, total)
else:
# Parallelism in Python can sometimes be a bit funky
# This takes care of sharing a sane logger, and handling Ctrl+C, sometimes
logger.remove()
logger.add(sys.stderr, enqueue=True)
original_sigint_handler = signal.signal(signal.SIGINT, signal.SIG_IGN)
with Pool(opts.parallel, initializer=set_logger,
initargs=(logger, )) as pool:
signal.signal(signal.SIGINT, original_sigint_handler)
args = [(path, idx + 1, total, True)
for idx, path in enumerate(scripts)]
try:
res = pool.starmap_async(run, args)
while True:
try:
res.get(
3
) # Without the timeout this blocking call ignores all signals.
pool.close()
break
except multiprocessing.context.TimeoutError:
continue
except KeyboardInterrupt:
logger.error("Caught KeyboardInterrupt, terminating workers")
pool.terminate()
raise
logger.info("Writing NavBar JSON package")
final_json = {
"updatedOn": TODAY_DMYHM,
}
# Dump JSON output
save_as_json(NAVBAR_PATH, final_json)
def main():
# Log status
logger.info("Loading local data files")
test_results = read_json_from_file(TEST_RESULTS_PATH)
test_locations = read_json_from_file(TEST_LOCATIONS_PATH)
# Log status
logger.info("Calculating main statistics")
case_dates = pd.date_range(start=DATE_SETTINGS["firstCaseDate"],
end=YESTERDAY_YMD)
# Get data for each chart
logger.info("Calculating data for charts")
infections_by_county = get_infection_count_by_county(
test_results, COUNTY_MAPPING)
infections_by_county_10000 = get_infections_data_by_count_10000(
infections_by_county, COUNTY_POPULATION)
county_by_day = get_county_by_day(test_results, case_dates, COUNTY_MAPPING,
COUNTY_POPULATION)
county_daily_active = get_county_daily_active(test_results, case_dates,
COUNTY_MAPPING,
COUNTY_POPULATION)
active_infections_by_county = [{
"MNIMI": k,
"sequence": v,
"drilldown": k
} for k, v in county_daily_active["countyByDayActive"].items()]
municipalities_data = get_municipality_data(test_locations, COUNTY_MAPPING)
# Create dictionary for final JSON
logger.info("Compiling final JSON")
final_json = {
"updatedOn": TODAY_DMYHM,
"caseDates": [str(x.date()) for x in case_dates],
"dataMunicipalities": municipalities_data,
"mapPlayback": county_by_day["mapPlayback"],
"mapPlayback10k": county_by_day["mapPlayback10k"],
"dataActiveInfectionsByCounty": active_infections_by_county,
"dataCountyDailyActive": county_daily_active,
"dataInfectionsByCounty": infections_by_county,
"dataInfectionsByCounty10000": infections_by_county_10000,
}
# Dump JSON output
save_as_json(MAP_PATH, final_json)
# Log finish time
logger.info("Finished update process")
def main():
# Log status
logger.info("Loading local data files")
test_results = read_json_from_file(TEST_RESULTS_PATH)
logger.info("Calculating data for charts")
positive_test_by_age_chart_data = get_positive_tests_by_age_chart_data(test_results)
# Create dictionary for final JSON
logger.info("Compiling final JSON")
final_json = {
"updatedOn": TODAY_DMYHM,
"dataPositiveTestsByAgeChart": positive_test_by_age_chart_data,
}
# Dump JSON output
save_as_json(TESTS_AGE_SEX_DISTRIBUTION_PATH, final_json)
# Log finish time
logger.info("Finished update process")
def main():
# Log status
logger.info("Loading local data files")
test_results = read_json_from_file(TEST_RESULTS_PATH)
# Log status
logger.info("Calculating data for charts")
positive_negative_chart_data = get_positive_negative_chart_data(
test_results, COUNTY_MAPPING)
# Create dictionary for final JSON
logger.info("Compiling final JSON")
final_json = {
"updatedOn": TODAY_DMYHM,
"dataPositiveNegativeChart": positive_negative_chart_data,
}
# Dump JSON output
save_as_json(POSITIVE_NEGATIVE_PATH, final_json)
# Log finish time
logger.info("Finished update process")
def scrape_deaths():
# Load content from Terviset's Covid dashboard and parse it
logger.info("Scraping data on deaths from {url}",
url=TERVISEAMET_COVID_DASHBOARD)
html = requests.get(TERVISEAMET_COVID_DASHBOARD).text
soup = BeautifulSoup(html, "html.parser")
# Extract number of deaths from page content and update JSON data on deaths
deaths_container = soup.select(DEATHS_SELECTOR)
if len(deaths_container) > 0:
# Get number of deaths and the current date
deaths_count = int(deaths_container[0].text.strip())
current_date = (datetime.now() -
timedelta(days=1)).strftime("%Y-%m-%d")
# Load existing deaths data
previous_deaths = read_json_from_file(DEATHS_PATH)
# Add new entry to deaths data for current date
deaths = {}
if len(previous_deaths):
deaths = previous_deaths
deaths[current_date] = deaths_count
# Save data on deaths
save_as_json(DEATHS_PATH + ".tmp", deaths)
# Log status
logger.info("Successfully scraped deaths. Total deaths: {deaths}",
deaths=deaths_count)
else:
# Log error
logger.debug("Couldn't find {selector}", selector=DEATHS_SELECTOR)
raise Exception(
"Couldn't scrape latest deaths data. Website structure probably changed."
)
def main():
# Log status
logger.info("Starting data update process")
test_results = read_json_from_file(TEST_RESULTS_PATH)
test_locations = read_json_from_file(TEST_LOCATIONS_PATH)
hospitalization = read_json_from_file(HOSPITALIZATION_PATH)
vaccination = read_json_from_file(VACCINATIONS_PATH)
# Load locally-stored data
logger.info("Loading local data files")
deaths = read_json_from_file(DEATHS_PATH)
manual_data = read_json_from_file(MANUAL_DATA_PATH)
# Log status
logger.info("Calculating main statistics")
# Statsbar
# Find count of confirmed cases
n_confirmed_cases = np.sum(
[res["ResultValue"] == "P" for res in test_results])
# Find total number of tests
n_tests_administered = len(test_results)
# Create date ranges for charts
# dates1 = pd.date_range(start=DATE_SETTINGS["dates1_start"], end=yesterday)
case_dates = pd.date_range(start=DATE_SETTINGS["firstCaseDate"],
end=YESTERDAY_YMD)
vaccination_dates = pd.date_range(
start=DATE_SETTINGS["vaccinationStartDate"], end=YESTERDAY_YMD)
# Set recovered, deceased, hospitalized and ICU time-series
hospital = get_hospital_data(hospitalization,
DATE_SETTINGS["firstCaseDate"])
recovered = hospital["discharged"]
manual_data["deceased"].update(deaths)
deceased = list(manual_data["deceased"].values())
hospitalized = hospital["activehospitalizations"]
# TODO: Based on cross-checking with the hospitalization data publishedby TEHIK, the data listed
# in the manual_data.json file with the field name "intensive" appears to show the number
# of patients on ventilation. We should fix the terminology and make sure that the intensive
# and on ventilation statistics are being calculated correctly.
intensive = list(
get_in_intensive_data(hospitalization,
manual_data["intensive"]).values())
on_ventilation = list(get_on_ventilation_data(hospitalization).values())
n_deaths = deceased[-1]
n_deaths_change = int(deceased[-1]) - int(deceased[-2])
# Get data for each chart
logger.info("Calculating data for charts")
infections_by_county = get_infection_count_by_county(
test_results, COUNTY_MAPPING)
infections_by_county_10000 = get_infections_data_by_count_10000(
infections_by_county, COUNTY_POPULATION)
tests_pop_ratio = get_test_data_pop_ratio(infections_by_county_10000)
county_by_day = get_county_by_day(test_results, case_dates, COUNTY_MAPPING,
COUNTY_POPULATION)
confirmed_cases_by_county = get_confirmed_cases_by_county(
test_results, COUNTY_MAPPING)
cumulative_cases_chart_data = get_cumulative_cases_chart_data(
test_results,
recovered,
deceased,
hospitalized,
intensive,
on_ventilation,
case_dates,
)
new_cases_per_day_chart_data = get_new_cases_per_day_chart_data(
cumulative_cases_chart_data)
cumulative_tests_chart_data = get_cumulative_tests_chart_data(
test_results, case_dates)
tests_per_day_chart_data = get_tests_per_day_chart_data(
test_results, case_dates)
positive_test_by_age_chart_data = get_positive_tests_by_age_chart_data(
test_results)
positive_negative_chart_data = get_positive_negative_chart_data(
test_results, COUNTY_MAPPING)
vaccinated_people_chart_data = get_vaccinated_people_chart_data(
vaccination, vaccination_dates)
county_daily_active = get_county_daily_active(test_results, case_dates,
COUNTY_MAPPING,
COUNTY_POPULATION)
n_active_cases = cumulative_cases_chart_data["active"][-1]
n_active_cases_change = (cumulative_cases_chart_data["active"][-1] -
cumulative_cases_chart_data["active"][-2])
active_infections_by_county = [{
"MNIMI": k,
"sequence": v,
"drilldown": k
} for k, v in county_daily_active["countyByDayActive"].items()]
active_infections_by_county_100k = [[
k, round(v[-1] / COUNTY_POPULATION[k] * 100000, 2)
] for k, v in county_daily_active["countyByDayActive"].items()]
municipalities_data = get_municipality_data(test_locations, COUNTY_MAPPING)
per_100k = cumulative_cases_chart_data["active100k"][-1]
# Calculate vaccination data
logger.info("Calculating vaccination data")
last_day_vaccination_data = [
x for x in vaccination if x["MeasurementType"] == "Vaccinated"
][-1]
last_day_completed_vaccination_data = [
x for x in vaccination if x["MeasurementType"] == "FullyVaccinated"
][-1]
# TODO: Doses administered
# last_day_doses_administered_data = [x for x in json_vaccination if x['MeasurementType'] == 'DosesAdministered'][-1]
completed_vaccination_number_total = last_day_completed_vaccination_data[
"TotalCount"]
completed_vaccination_number_last_day = last_day_completed_vaccination_data[
"DailyCount"]
all_vaccination_number_total = last_day_vaccination_data["TotalCount"]
all_vaccination_number_last_day = last_day_vaccination_data["DailyCount"]
vaccination_number_total = (all_vaccination_number_total -
completed_vaccination_number_total)
vaccination_number_last_day = (all_vaccination_number_last_day -
completed_vaccination_number_last_day)
fully_vaccinated_from_total_vaccinated_percentage = round(
completed_vaccination_number_total * 100 /
(all_vaccination_number_total), 2)
# Create dictionary for final JSON
logger.info("Compiling final JSON")
final_json = {
"updatedOn":
TODAY_DMYHM,
"confirmedCasesNumber":
str(n_confirmed_cases),
# TODO: For consistency, we should include the change in the number of confirmed cases as well.
"hospitalizedNumber":
str(hospital["activehospitalizations"][-1]),
"hospitalChanged":
str(hospital["activehospitalizations"][-1] -
hospital["activehospitalizations"][-2]),
"deceasedNumber":
str(n_deaths),
"deceasedChanged":
str(n_deaths_change),
"recoveredNumber":
str(hospital["discharged"][-1]),
"recoveredChanged":
str(hospital["discharged"][-1] - hospital["discharged"][-2]),
"testsAdministeredNumber":
str(n_tests_administered),
# TODO: For consistency, we should include the change in the number of tests as well.
"activeCasesNumber":
str(n_active_cases),
"activeChanged":
str(n_active_cases_change),
"perHundred":
str(per_100k), # TODO: This should be given a clearer name.
# TODO: I can't find anywhere in the app where "dates1" is used. Is it needed? Commented out for now.
# "dates1": [str(x.date()) for x in dates1],
"caseDates": [str(x.date()) for x in case_dates],
"vaccinationDates": [str(x.date()) for x in vaccination_dates],
"counties":
COUNTIES_INCL_UNKNOWN,
"age_groups":
AGE_GROUPS,
"dataInfectionsByCounty":
infections_by_county,
"dataInfectionsByCounty10000":
infections_by_county_10000,
"dataActiveInfectionsByCounty100k":
active_infections_by_county_100k,
"dataActiveInfectionsByCounty":
active_infections_by_county,
"dataTestsPopRatio":
tests_pop_ratio,
"countyByDay":
county_by_day,
"dataCountyDailyActive":
county_daily_active,
"dataConfirmedCasesByCounties":
confirmed_cases_by_county,
"dataCumulativeCasesChart":
cumulative_cases_chart_data,
"dataNewCasesPerDayChart":
new_cases_per_day_chart_data,
"dataCumulativeTestsChart":
cumulative_tests_chart_data,
"dataTestsPerDayChart":
tests_per_day_chart_data,
"dataPositiveTestsByAgeChart":
positive_test_by_age_chart_data,
"dataPositiveNegativeChart":
positive_negative_chart_data,
"dataVaccinatedPeopleChart":
vaccinated_people_chart_data,
"dataMunicipalities":
municipalities_data,
"hospital":
hospital, # TODO: Rename this to make it clearer what data it contains.
"vaccinationNumberTotal":
vaccination_number_total,
"vaccinationNumberLastDay":
vaccination_number_last_day,
"completedVaccinationNumberTotal":
completed_vaccination_number_total,
"completedVaccinationNumberLastDay":
completed_vaccination_number_last_day,
"allVaccinationNumberTotal":
all_vaccination_number_total,
"allVaccinationNumberLastDay":
all_vaccination_number_last_day,
"allVaccinationFromPopulationPercentage":
last_day_vaccination_data["PopulationCoverage"],
"completelyVaccinatedFromTotalVaccinatedPercentage":
fully_vaccinated_from_total_vaccinated_percentage,
}
# Dump JSON output
save_as_json(OUTPUT_PATH, final_json)
# Log finish time
logger.info("Finished update process")
def main():
# Log status
logger.info("Loading local data files")
test_results = read_json_from_file(TEST_RESULTS_PATH)
hospitalization = read_json_from_file(HOSPITALIZATION_PATH)
vaccination = read_json_from_file(VACCINATIONS_PATH)
deaths = read_json_from_file(DEATHS_PATH)
manual_data = read_json_from_file(MANUAL_DATA_PATH)
# Log status
logger.info("Calculating main statistics")
# Statsbar
# Find count of confirmed cases
n_confirmed_cases = np.sum(
[res["ResultValue"] == "P" for res in test_results])
# Find total number of tests
n_tests_administered = len(test_results)
# Create date ranges for charts
case_dates = pd.date_range(start=DATE_SETTINGS["firstCaseDate"],
end=YESTERDAY_YMD)
# Set recovered, deceased, hospitalized and ICU time-series
hospital = get_hospital_data(hospitalization,
DATE_SETTINGS["firstCaseDate"])
recovered = hospital["discharged"]
manual_data["deceased"].update(deaths)
deceased = list(manual_data["deceased"].values())
hospitalized = hospital["activeHospitalizations"]
# TODO: Based on cross-checking with the hospitalization data publishedby TEHIK, the data listed
# in the manual_data.json file with the field name "intensive" appears to show the number
# of patients on ventilation. We should fix the terminology and make sure that the intensive
# and on ventilation statistics are being calculated correctly.
intensive = list(
get_in_intensive_data(hospitalization,
manual_data["intensive"]).values())
on_ventilation = list(get_on_ventilation_data(hospitalization).values())
n_deaths = deceased[-1]
n_deaths_change = int(deceased[-1]) - int(deceased[-2])
# Get data for each chart
logger.info("Calculating data for charts")
tests_per_day_chart_data = get_tests_per_day_chart_data(
test_results, case_dates)
cumulative_cases_chart_data = get_cumulative_cases_chart_data(
test_results,
recovered,
deceased,
hospitalized,
intensive,
on_ventilation,
case_dates,
test_per_day_chart_data=tests_per_day_chart_data,
)
new_cases_per_day_chart_data = get_new_cases_per_day_chart_data(
cumulative_cases_chart_data)
cumulative_tests_chart_data = get_cumulative_tests_chart_data(
test_results, case_dates)
n_active_cases = cumulative_cases_chart_data["active"][-1]
n_active_cases_change = (cumulative_cases_chart_data["active"][-1] -
cumulative_cases_chart_data["active"][-2])
# Calculate vaccination data
logger.info("Calculating vaccination data")
last_day_vaccination_data = [
x for x in vaccination if x["MeasurementType"] == "Vaccinated"
][-1]
last_day_completed_vaccination_data = [
x for x in vaccination if x["MeasurementType"] == "FullyVaccinated"
][-1]
# TODO: Doses administered
completed_vaccination_number_total = last_day_completed_vaccination_data[
"TotalCount"]
completed_vaccination_number_last_day = last_day_completed_vaccination_data[
"DailyCount"]
all_vaccination_number_total = last_day_vaccination_data["TotalCount"]
all_vaccination_number_last_day = last_day_vaccination_data["DailyCount"]
vaccination_number_total = (all_vaccination_number_total -
completed_vaccination_number_total)
vaccination_number_last_day = (all_vaccination_number_last_day -
completed_vaccination_number_last_day)
fully_vaccinated_from_total_vaccinated_percentage = round(
completed_vaccination_number_total * 100 /
(all_vaccination_number_total), 2)
raw_active_100k = (cumulative_cases_chart_data["active"][-1] -
cumulative_cases_chart_data["active"][-2])
raw_confirmed_changed = new_cases_per_day_chart_data["confirmedCases"][-1]
raw_per_hundred_changed = (cumulative_cases_chart_data["active100k"][-1] -
cumulative_cases_chart_data["active100k"][-2])
confirmed_changed = new_cases_per_day_chart_data["confirmedCases"][-1]
tests_changed = (cumulative_tests_chart_data["testsAdministered"][-1] -
cumulative_tests_chart_data["testsAdministered"][-2])
partially_immunized_total = all_vaccination_number_total + n_confirmed_cases
partially_immunized_pct = round(
(float(partially_immunized_total) / float(POPULATION) * 100), 2)
# Create dictionary for final JSON
logger.info("Compiling final JSON")
final_json = {
"updatedOn":
TODAY_DMYHM,
"activeCasesNumber":
str(n_active_cases),
"activeChanged":
str(n_active_cases_change),
"allVaccinationFromPopulationPercentage":
last_day_vaccination_data["PopulationCoverage"],
"allVaccinationNumberLastDay":
all_vaccination_number_last_day,
"allVaccinationNumberTotal":
all_vaccination_number_total,
"completedVaccinationNumberLastDay":
completed_vaccination_number_last_day,
"completedVaccinationNumberTotal":
completed_vaccination_number_total,
"completelyVaccinatedFromTotalVaccinatedPercentage":
fully_vaccinated_from_total_vaccinated_percentage,
"confirmedCasesNumber":
str(n_confirmed_cases),
"confirmedChanged":
confirmed_changed,
"deceasedChanged":
str(n_deaths_change),
"deceasedNumber":
str(n_deaths),
"hospitalizedChanged":
str(hospital["activeHospitalizations"][-1] -
hospital["activeHospitalizations"][-2]),
"hospitalizedNumber":
hospital["activeHospitalizations"][-1],
"partiallyImmunized":
partially_immunized_total,
"partiallyImmunizedPercentage":
partially_immunized_pct,
"perHundred":
cumulative_cases_chart_data["active100k"][-1],
"positiveTestAverage14Percent":
tests_per_day_chart_data["positiveTestAverage14Percent"],
"rawActiveChanged":
raw_active_100k,
"rawConfirmedChanged":
raw_confirmed_changed,
"rawPerHundredChanged":
raw_per_hundred_changed,
"recoveredChanged":
str(hospital["discharged"][-1] - hospital["discharged"][-2]),
"recoveredNumber":
hospital["discharged"][-1],
"testsAdministeredNumber":
str(n_tests_administered),
"testsChanged":
tests_changed,
"vaccinationNumberLastDay":
vaccination_number_last_day,
"vaccinationNumberTotal":
vaccination_number_total,
}
# Dump JSON output
save_as_json(STATS_BAR_PATH, final_json)
# Log finish time
logger.info("Finished update process")
