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nlitsme/countries.txt

Created July 29, 2020 11:30
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python scripts to show corona statistics
Raw
countries.txt
EMRO AF Afghanistan 647500 37171921 World;Asia;NonCKIR
EURO AL Albania 28748 2876591 World;Europe;NonEU
AFRO DZ Algeria 2381740 34178188 World;Africa;North Africa
WPRO AS American Samoa (United States) 199 55465 World;Oceania;Polynesia
EURO AD Andorra 468 77281 World;Europe;NonEU
AFRO AO Angola 1246700 12799293 World;Africa;Central Africa
AMRO AI Anguilla (United Kingdom) 91 14731 World;North America
AMRO AG Antigua and Barbuda 442 96286 World;North America
AMRO AR Argentina 2766890 44361150 World;South America
EURO AM Armenia 29743 2951745 World;Europe;NonEU
AMRO AW Aruba (Kingdom of the Netherlands) 180 105845 World;North America
WPRO ?? Ashmore and Cartier Islands (Australia) 199 0 World;Oceania;Australasia
WPRO AU Australia 7686850 24898152 World;Oceania;Australasia
EURO AT Austria 83858 8823054 World;Europe;EU
EURO AZ Azerbaijan 86600 10027874 World;Europe;NonEU
EMRO BH Bahrain 760 1569446 World;Asia;NonCKIR
SEARO BD Bangladesh 147570 161376708 World;Asia;NonCKIR
AMRO BB Barbados 430 286641 World;North America
EURO BY Belarus 207560 9504700 World;Europe;NonEU
EURO BE Belgium 30528 11358357 World;Europe;EU
AMRO BZ Belize 22966 383071 World;North America
AFRO BJ Benin 112620 8791832 World;Africa;West Africa
AMRO BM Bermuda (United Kingdom) 54 62756 World;North America
SEARO BT Bhutan 38394 754388 World;Asia;NonCKIR
AMRO BO Bolivia 1098580 11353142 World;South America
AMRO BQ Bonaire (Kingdom of the Netherlands) 294 12093 World;North America
EURO BA Bosnia and Herzegovina 51129 3531159 World;Europe;NonEU
AFRO BW Botswana 600370 1990876 World;Africa;Southern Africa
AMRO ?? Bouvet Island (Norway) 49 0 World;South America
AMRO BR Brazil 8514877 209469323 World;South America
AMRO VG British Virgin Islands (United Kingdom) 151 29802 World;North America
WPRO BN Brunei 5765 428963 World;Asia;NonCKIR
EURO BG Bulgaria 110910 7101859 World;Europe;EU
AFRO BF Burkina Faso 274200 15746232 World;Africa;West Africa
AFRO BI Burundi 27830 8988091 World;Africa;East Africa
WPRO KH Cambodia 181035 16249792 World;Asia;NonCKIR
AFRO CM Cameroon 475440 18879301 World;Africa;Central Africa
AMRO CA Canada 9984670 37064562 World;North America
AFRO ?? Canary Islands (Spain) 7492 2154905 World;Africa;North Africa
AFRO CV Cape Verde 4033 429474 World;Africa;West Africa
AMRO KY Cayman Islands (United Kingdom) 264 64174 World;North America
AFRO CF Central African Republic 622984 4511488 World;Africa;Central Africa
AFRO ?? Ceuta (Spain) 20 85107 World;Africa;North Africa
AFRO TD Chad 1284000 10329208 World;Africa;Central Africa
AMRO CL Chile 756950 18729160 World;South America
WPRO CN China (PRC) 9596961 1427647786 World;Asia
AMRO ?? Clipperton Island (France) 6 0 World;North America
AMRO CO Colombia 1141748 49661048 World;South America
AFRO KM Comoros 2170 752438 World;Africa;East Africa
WPRO CK Cook Islands (New Zealand) 240 17518 World;Oceania;Polynesia
WPRO ?? Coral Sea Islands (Australia) 10 4 World;Oceania;Australasia
AMRO CR Costa Rica 51100 4999441 World;North America
EURO HR Croatia 56542 4284889 World;Europe;EU
AMRO CU Cuba 109886 11338134 World;North America
AMRO CW Curaçao (Kingdom of the Netherlands) 444 162752 World;North America
EURO CY Cyprus 9251 1189265 World;Europe;EU
EURO CZ Czech Republic 78866 10610947 World;Europe;EU
AFRO CD Democratic Republic of the Congo 2345410 69575000 World;Africa;Central Africa
EURO DK Denmark 43094 5748796 World;Europe;EU
SHIP Diamond Princess 0.1 3711 World;Ships
EMRO DJ Djibouti 23000 828324 World;Africa;East Africa
AMRO DM Dominica 751 71625 World;North America
AMRO DO Dominican Republic 48671 10627141 World;North America
SEARO TL East Timor 14874 1267974 World;Asia;NonCKIR
WPRO ?? Easter Island (Chile) 164 5761 World;Oceania;Polynesia
AMRO EC Ecuador 283560 17084358 World;South America
EMRO EG Egypt 1001450 82868000 World;Africa;North Africa
AMRO SV El Salvador 21041 6420746 World;North America
AFRO GQ Equatorial Guinea 28051 633441 World;Africa;Central Africa
AFRO ER Eritrea 121320 5647168 World;Africa;East Africa
EURO EE Estonia 45226 1319133 World;Europe;EU
AFRO SZ Eswatini 17363 1123913 World;Africa;Southern Africa
AFRO ET Ethiopia 1127127 84320987 World;Africa;East Africa
AMRO FK Falkland Islands (United Kingdom) 12173 3234 World;South America
AMRO ?? Federal Dependencies of Venezuela (Venezuela) 342 2155 World;North America
WPRO FM Federated States of Micronesia 702 112640 World;Oceania;Micronesia
WPRO FJ Fiji 18270 883483 World;Oceania;Melanesia
EURO FI Finland 336593 5509717 World;Europe;EU
EURO FR France 547030 67348000 World;Europe;EU
AMRO GF French Guiana (France) 91000 282938 World;South America
WPRO PF French Polynesia (France) 4167 277679 World;Oceania;Polynesia
AFRO ?? French Southern and Antarctic Lands (France) 439781 100 World;Africa;East Africa
AFRO GA Gabon 267667 1514993 World;Africa;Central Africa
EURO GE Georgia 69700 3723464 World;Europe;NonEU
EURO DE Germany 357168 82800000 World;Europe;EU
AFRO GH Ghana 239460 23832495 World;Africa;West Africa
EURO GR Greece 131957 10768477 World;Europe;EU
EURO GL Greenland (Kingdom of Denmark) 2166086 56564 World;North America
AMRO GD Grenada 344 111454 World;North America
AMRO GP Guadeloupe (France) 1628 399848 World;North America
WPRO GU Guam (United States) 549 165768 World;Oceania;Micronesia
AMRO GT Guatemala 108889 17247849 World;North America
AFRO GN Guinea 245857 10057975 World;Africa;West Africa
AFRO GW Guinea-Bissau 36120 1533964 World;Africa;West Africa
AMRO GY Guyana 214999 779006 World;South America
AMRO HT Haiti 27750 11123178 World;North America
WPRO ?? Hawaii (United States) 16636 1360301 World;Oceania;Polynesia
AMRO HN Honduras 112492 9587522 World;North America
EURO HU Hungary 93030 9797561 World;Europe;EU
EURO IS Iceland 103000 350710 World;Europe;NonEU
SEARO IN India 3287263 1352642280 World;Asia;NonCKIR
SEARO ID Indonesia 1904569 267670543 World;Asia;NonCKIR
EMRO IR Iran 1648195 81800188 World;Asia
EMRO IQ Iraq 438317 38433600 World;Asia;NonCKIR
EURO IE Ireland 70280 4761865 World;Europe;EU
EURO IL Israel 20770 8381516 World;Asia;NonCKIR
EURO IT Italy 301338 60589445 World;Europe;EU
AFRO CI Ivory Coast 322460 20617068 World;Africa;West Africa
AMRO JM Jamaica 10991 2934847 World;North America
WPRO JP Japan 377915 127202192 World;Asia;NonCKIR
EMRO JO Jordan 89342 9965318 World;Asia;NonCKIR
EURO KZ Kazakhstan 2724900 18448600 World;Asia;NonCKIR
AFRO KE Kenya 582650 39002772 World;Africa;East Africa
WPRO KI Kiribati 811 115847 World;Oceania;Micronesia
EURO XK Kosovo 10887 1810463 World;Europe;NonEU
EMRO KW Kuwait 17818 4137312 World;Asia;NonCKIR
EURO KG Kyrgyzstan 199951 6304030 World;Asia;NonCKIR
WPRO LA Laos 236800 7061507 World;Asia;NonCKIR
EURO LV Latvia 64589 1925800 World;Europe;EU
EMRO LB Lebanon 10400 6859408 World;Asia;NonCKIR
AFRO LS Lesotho 30355 2130819 World;Africa;Southern Africa
AFRO LR Liberia 111370 3441790 World;Africa;West Africa
EMRO LY Libya 1759540 6310434 World;Africa;North Africa
EURO LI Liechtenstein 160 38111 World;Europe;NonEU
EURO LT Lithuania 65300 2800667 World;Europe;EU
EURO LU Luxembourg 2586 602005 World;Europe;EU
SHIPS MS Zaandam 0.08 1829 World;Ships
AFRO MG Madagascar 587040 20653556 World;Africa;East Africa
AFRO ?? Madeira (Portugal) 797 245000 World;Africa;North Africa
AFRO MW Malawi 118480 14268711 World;Africa;East Africa
WPRO MY Malaysia 329847 31528033 World;Asia;NonCKIR
SEARO MV Maldives 298 515696 World;Asia;NonCKIR
AFRO ML Mali 1240000 12666987 World;Africa;West Africa
EURO MT Malta 316 445426 World;Europe;EU
WPRO MH Marshall Islands 181 58413 World;Oceania;Micronesia
AMRO MQ Martinique (France) 1128 375673 World;North America
AFRO MR Mauritania 1030700 3129486 World;Africa;West Africa
AFRO MU Mauritius 2040 1284264 World;Africa;East Africa
AFRO YT Mayotte (France) 374 223765 World;Africa;East Africa
AFRO ?? Melilla (Spain) 12 85116 World;Africa;North Africa
AMRO MX Mexico 1964375 126190788 World;North America
EURO MD Moldova 33846 4434547 World;Europe;NonEU
EURO MC Monaco 2.02 38400 World;Europe;NonEU
WPRO MN Mongolia 1564116 3170216 World;Asia;NonCKIR
EURO ME Montenegro 13812 642550 World;Europe;NonEU
AMRO MS Montserrat (United Kingdom) 102 4993 World;North America
EMRO MA Morocco 446550 35740000 World;Africa;North Africa
AFRO MZ Mozambique 801590 21669278 World;Africa;East Africa
SEARO MM Myanmar 676578 53708320 World;Asia;NonCKIR
AFRO NA Namibia 825418 2108665 World;Africa;Southern Africa
WPRO NR Nauru 21 10670 World;Oceania;Micronesia
SEARO NP Nepal 147181 28095714 World;Asia;NonCKIR
EURO NL Netherlands 41543 17271990 World;Europe;EU
WPRO NC New Caledonia (France) 19060 279993 World;Oceania;Melanesia
WPRO NZ New Zealand 268680 4743131 World;Oceania;Australasia
AMRO NI Nicaragua 130373 6465501 World;North America
AFRO NE Niger 1267000 15306252 World;Africa;West Africa
AFRO NG Nigeria 923768 166629000 World;Africa;West Africa
WPRO NU Niue (New Zealand) 260 1620 World;Oceania;Polynesia
WPRO NF Norfolk Island (Australia) 35 2302 World;Oceania;Australasia
SEARO KP North Korea 120538 25549604 World;Asia;NonCKIR
EURO MK North Macedonia 25713 2103721 World;Europe;NonEU
WPRO MP Northern Mariana Islands (United States) 477 56882 World;Oceania;Micronesia
EURO NO Norway 385203 5295619 World;Europe;NonEU
AMRO ?? Nueva Esparta (Venezuela) 1151 491610 World;North America
EMRO OM Oman 309500 4829473 World;Asia;NonCKIR
EMRO PK Pakistan 881913 211103000 World;Asia;NonCKIR
WPRO PW Palau 458 17907 World;Oceania;Micronesia
EMRO PS Palestine 6220 4862979 World;Asia;NonCKIR
AMRO PA Panama 75417 4176869 World;North America
WPRO ?? Papua (Indonesia) 319036 3486432 World;Oceania;Melanesia
WPRO PG Papua New Guinea 462840 8606323 World;Oceania;Melanesia
AMRO PY Paraguay 406750 6956066 World;South America
AMRO PE Peru 1285220 31989260 World;South America
WPRO PH Philippines 343448 106651394 World;Asia;NonCKIR
WPRO PN Pitcairn Islands (United Kingdom) 47 47 World;Oceania;Polynesia
EURO PL Poland 312685 38422346 World;Europe;EU
EURO PT Portugal 92212 10379537 World;Europe;EU
AMRO PR Puerto Rico (United States) 8870 3039596 World;North America
EMRO QA Qatar 11586 2781682 World;Asia;NonCKIR
AFRO CG Republic of the Congo 342000 4012809 World;Africa;Central Africa
EURO RO Romania 238397 19638000 World;Europe;EU
EURO RU Russia 17098246 146745098 World;Europe;NonEU
AFRO RW Rwanda 26338 10473282 World;Africa;East Africa
AFRO RE Réunion (France) 2512 743981 World;Africa;East Africa
AMRO BQ Saba (Kingdom of the Netherlands) 13 1537 World;North America
AMRO BL Saint Barthélemy (France) 21 7448 World;North America
AFRO SH Saint Helena, Ascension and Tristan da Cunha (United Kingdom) 420 7728 World;Africa;West Africa
AMRO KN Saint Kitts and Nevis 261 52441 World;North America
AMRO LC Saint Lucia 539 181889 World;North America
AMRO MF Saint Martin (France) 54 29820 World;North America
AMRO PM Saint Pierre and Miquelon (France) 242 5849 World;North America
AMRO VC Saint Vincent and the Grenadines 389 110211 World;North America
WPRO WS Samoa 2944 196129 World;Oceania;Polynesia
AMRO ?? San Andrés and Providencia (Colombia) 53 77701 World;North America
EURO SM San Marino 61.2 33285 World;Europe;NonEU
EMRO SA Saudi Arabia 2149690 33702756 World;Asia;NonCKIR
AFRO SN Senegal 196190 13711597 World;Africa;West Africa
EURO RS Serbia 88361 7040272 World;Europe;NonEU
AFRO SC Seychelles 455 87476 World;Africa;East Africa
AFRO SL Sierra Leone 71740 6440053 World;Africa;West Africa
WPRO SG Singapore 697 5757499 World;Asia;NonCKIR
AMRO BQ Sint Eustatius (Kingdom of the Netherlands) 21 2739 World;North America
AMRO SX Sint Maarten (Kingdom of the Netherlands) 34 41940 World;North America
EURO SK Slovakia 49035 5435343 World;Europe;EU
EURO SI Slovenia 20273 2066880 World;Europe;EU
WPRO SB Solomon Islands 28450 652857 World;Oceania;Melanesia
EMRO SO Somalia 637657 9832017 World;Africa;East Africa
AFRO ZA South Africa 1219912 51770560 World;Africa;Southern Africa
AMRO ?? South Georgia and the South Sandwich Islands (United Kingdom) 3093 20 World;South America
WPRO KR South Korea 100210 51171706 World;Asia
AFRO SS South Sudan 619745 8260490 World;Africa;East Africa
EURO ES Spain 505990 46698151 World;Europe;EU
SEARO LK Sri Lanka 65610 21228763 World;Asia;NonCKIR
EMRO SD Sudan 1861484 30894000 World;Africa;North Africa
AMRO SR Suriname 163270 575990 World;South America
EURO SE Sweden 450295 10151588 World;Europe;EU
EURO CH Switzerland 41285 8401120 World;Europe;NonEU
EMRO SY Syria 185180 16945057 World;Asia;NonCKIR
AFRO ST São Tomé and Príncipe 1001 212679 World;Africa;Central Africa
WPRO ?? Taiwan (ROC) 36193 23726460 World;Asia;NonCKIR
EURO TJ Tajikistan 143100 9100835 World;Asia;NonCKIR
AFRO TZ Tanzania 945087 44929002 World;Africa;East Africa
SEARO TH Thailand 513120 69428453 World;Asia;NonCKIR
AMRO BS The Bahamas 13943 385637 World;North America
AFRO GM The Gambia 11300 1782893 World;Africa;West Africa
AFRO TG Togo 56785 6019877 World;Africa;West Africa
WPRO TK Tokelau (New Zealand) 10 1319 World;Oceania;Polynesia
WPRO TO Tonga 748 103197 World;Oceania;Polynesia
AMRO TT Trinidad and Tobago 5130 1389843 World;North America
EMRO TN Tunisia 163610 10486339 World;Africa;North Africa
EURO TR Turkey 783356 83154997 World;Europe;NonEU
EURO TM Turkmenistan 488100 5850901 World;Asia;NonCKIR
AMRO TC Turks and Caicos Islands (United Kingdom) 948 37665 World;North America
WPRO TV Tuvalu 26 11508 World;Oceania;Polynesia
AFRO UG Uganda 236040 32369558 World;Africa;East Africa
EURO UA Ukraine 603628 42418235 World;Europe;NonEU
EMRO AE United Arab Emirates 83600 9630959 World;Asia;NonCKIR
EURO GB United Kingdom 244820 66040229 World;Europe;NonEU
AMRO US United States 9629091 327096265 World;North America
AMRO VI United States Virgin Islands (United States) 347 104680 World;North America
AMRO UY Uruguay 176220 3449285 World;South America
EURO UZ Uzbekistan 447400 32476244 World;Asia;NonCKIR
WPRO VU Vanuatu 12200 292680 World;Oceania;Melanesia
EURO VA Vatican City 0.44 1000 World;Europe;NonEU
AMRO VE Venezuela 916445 28887118 World;South America
WPRO VN Vietnam 331212 95545962 World;Asia;NonCKIR
WPRO WK Wake Island (United States) 2 150 World;Oceania;Micronesia
WPRO WF Wallis and Futuna (France) 274 11661 World;Oceania;Polynesia
WPRO ?? West Papua (Indonesia) 140375 760855 World;Oceania;Melanesia
AFRO EH Western Sahara 266000 405210 World;Africa;North Africa
EMRO YE Yemen 527968 28498683 World;Asia;NonCKIR
AFRO ZM Zambia 752614 11862740 World;Africa;Southern Africa
AFRO ZW Zimbabwe 390580 11392629 World;Africa;Southern Africa
WPRO CC Cocos (Keeling) Islands 14 544 World;Oceania;Australasia
WPRO CX Christmas Island 135 1843 World;Oceania;Australasia
EURO FO Faroe Islands 1399 52110 World;Europe
EURO GG Guernsey 65 62792 World;Europe
EURO GI Gibraltar 6.7 34003 World;Europe
EURO IM Isle of Man 572 83314 World;Europe
EURO JE Jersey 118.2 107800 World;Europe
EURO SJ Svalbard and Jan Mayen Islands 61022 2939 World;Europe
AMRO AN Netherlands Antilles 999 304759 World;North America
WPRO JT Johnston Atoll 1 0 World;Oceania;Australasia
WPRO UM Midway Islands 66 40 World;Oceania;Australasia
Raw
rivm.py
"""
Show dutch rivm corona statistics
Author: Willem Hengeveld <[email protected]>
"""
from collections import defaultdict
import urllib.request
import urllib.parse
import json
import os
import os.path
import time
import hashlib
x = dict()
class WebCache:
def __init__(self):
self.cachedir = os.path.join(os.getenv("HOME"), ".pywebcache")
if not os.path.isdir(self.cachedir):
os.mkdir(self.cachedir)
def calccachepath(self, url):
urlhash = hashlib.sha1(url.encode('utf-8')).hexdigest()
return os.path.join(self.cachedir, urlhash)
def read(self, url):
cachefile = self.calccachepath(url)
try:
st = os.stat(cachefile)
if time.time() - st.st_mtime > 86400/2:
return
if st.st_size==0:
return
with open(cachefile, "rb") as fh:
return fh.read()
except:
return
def write(self, url, text):
cachefile = self.calccachepath(url)
with open(cachefile, "wb") as fh:
fh.write(text)
webcache = WebCache()
def loadjson(url):
global webcache
try:
text = webcache.read(url)
if text:
return json.loads(text)
except:
pass
with urllib.request.urlopen(url) as response:
text = response.read()
webcache.write(url, text)
return json.loads(text)
def converttables():
def cv(x): return x[2:10]
global x
bydatebycity = defaultdict(dict)
cities = dict()
country = defaultdict(lambda:defaultdict(int))
for item in x["gem"]:
t = cv(item["Date_of_report"])
if item["Municipality_code"] is None:
bydatebycity[t][item["Province"]] = item
cities[item["Province"]] = item["Province"]
else:
bydatebycity[t][item["Municipality_code"]] = item
cities[item["Municipality_code"]] = item["Municipality_name"]
for key in ("Deceased", "Hospital_admission", "Total_reported"):
country[t][key] += item[key]
x["bycity"] =bydatebycity
x["city"] = cities
x["country"] = country
if "rval" in x:
rvalbydate = dict()
for item in x["rval"]:
rvalbydate[item["Date"]] = item
x["rbydate"] = rvalbydate
def showtables(dates, times, base, index, totals, key):
(w0,wp,w1,w2) = times
print("%-30s %8s" % ("", ""), end=" ")
for t in dates[:-w1:wp]:
print("%10s" % t, end=" ")
print()
for gemid, naam in index.items():
t0 = dates[w0]
t1 = dates[w1]
t2 = dates[w2]
x0 = base[t0][gemid][key]
x1 = base[t1][gemid][key]
x2 = base[t2][gemid][key]
groei = 100*(x0-x1)/(x0-x2) if x0-x2 else 0
print("%-30s %7.2f" % (naam, groei), end=" ")
for t0, t1 in zip(dates[::wp], dates[w1::wp]):
x0 = base[t0][gemid][key]
x1 = base[t1][gemid][key]
print("%10s" % (x0-x1), end=" ")
print()
print("--------")
t0 = dates[w0]
t1 = dates[w1]
t2 = dates[w2]
x0 = totals[t0][key]
x1 = totals[t1][key]
x2 = totals[t2][key]
groei = 100*(x0-x1)/(x0-x2) if x0-x2 else 0
print("%-30s %7.2f" % ("Nederland", groei), end=" ")
for t0, t1 in zip(dates[::wp], dates[w1::wp]):
x0 = totals[t0][key]
x1 = totals[t1][key]
print("%10s" % (x0-x1), end=" ")
print()
def main():
import argparse
parser = argparse.ArgumentParser(description='get rivm statistics')
parser.add_argument('--week', '-w', action='store_true', help='summarize per week')
parser.add_argument('--twoweeks', '-t', action='store_true', help='summarize per two weeks')
parser.add_argument('--sumdays', '-S', type=int, help='summarize per two weeks')
parser.add_argument('--printdays', '-P', type=int, help='output value every N days')
parser.add_argument('--delta', '-d', type=int, help='relative growth period', default=4)
args = parser.parse_args()
if args.week:
args.sumdays = 7
args.printdays = 7
elif args.twoweeks:
args.sumdays = 14
args.printdays = 7
else:
if args.sumdays is None:
args.sumdays = 1
if args.printdays is None:
args.printdays = 1
x["gem"] = loadjson("https://data.rivm.nl/covid-19/COVID-19_aantallen_gemeente_cumulatief.json")
#x["rval"] = loadjson("https://data.rivm.nl/covid-19/COVID-19_reproductiegetal.json")
converttables()
dates = list(sorted(x["bycity"].keys()))
dates = dates[::-1]
w0, wp, w1, w2 = 0, args.printdays, args.sumdays, args.delta*args.sumdays
for key in ("Deceased", "Hospital_admission", "Total_reported"):
print("==== %s" % key)
showtables(dates, (w0,wp,w1,w2), x["bycity"], x["city"], x["country"], key)
if __name__ == '__main__':
main()
Raw
who.py
"""
Show WHO corona statistics
Author: Willem Hengeveld <[email protected]>
"""
from collections import defaultdict
import urllib.request
import urllib.parse
import json
import datetime
import os
import os.path
import time
import hashlib
def readcountries():
class Country:
def __init__(self, region, name, iso2, area, pop, groups):
self.region = region
self.name = name
self.iso2 = iso2
self.area = float(area)
self.population = int(population)
self.groups = groups
# returns a dict of country => list of groups
with open("countries.txt", "r") as fh:
data = fh.read()
g = dict()
for line in data.split("\n"):
if not line:
continue
region, iso2, country, area, population, grouping = line.split("\t")
groups = grouping.split(";")
g[iso2] = Country(region, country, iso2, area, population, groups)
return g
class WebCache:
def __init__(self):
self.cachedir = os.path.join(os.getenv("HOME"), ".pywebcache")
if not os.path.isdir(self.cachedir):
os.mkdir(self.cachedir)
def calccachepath(self, url):
urlhash = hashlib.sha1(url.encode('utf-8')).hexdigest()
return os.path.join(self.cachedir, urlhash)
def read(self, url):
cachefile = self.calccachepath(url)
try:
st = os.stat(cachefile)
if time.time() - st.st_mtime > 3600:
return
if st.st_size==0:
return
with open(cachefile, "rb") as fh:
return fh.read()
except:
return
def write(self, url, text):
cachefile = self.calccachepath(url)
with open(cachefile, "wb") as fh:
fh.write(text)
webcache = WebCache()
def loadjson(url):
global webcache
try:
text = webcache.read(url)
if text:
return json.loads(text)
except:
pass
with urllib.request.urlopen(url) as response:
text = response.read()
webcache.write(url, text)
return json.loads(text)
def getitembymember(a, member):
"""
Get the first item from 'a' which has an element named 'member'
"""
for item in a:
if member in item:
return item
def getitem(d, *path):
"""
Traverse a nested python object, path items select which object is selected:
* a tuple: selects a dictionary from a list which contains the specified key
* an integer: select the specified item from a list.
* a string: select the specified item from a dictionary.
"""
for k in path:
if type(k) == tuple:
d = getitembymember(d, *k)
elif type(k) == int:
d = d[k]
else:
d = d.get(k)
if d is None:
return
return d
def cvt(t):
t = datetime.datetime.fromtimestamp(t/1000)
return "%02d-%02d" % (t.month, t.day)
def main():
import argparse
parser = argparse.ArgumentParser(description='get who statistics')
parser.add_argument('--week', '-w', action='store_true', help='summarize per week')
parser.add_argument('--twoweeks', '-t', action='store_true', help='summarize per two weeks')
parser.add_argument('--sumdays', '-S', type=int, help='summarize per two weeks')
parser.add_argument('--printdays', '-P', type=int, help='output value every N days')
parser.add_argument('--delta', '-d', type=int, help='relative growth period', default=4)
parser.add_argument('--bypopulation', '-p', action='store_true', help='show by 100000 people')
parser.add_argument('--byarea', '-a', action='store_true', help='show by km2')
parser.add_argument('--yesterday', '-y', action='store_true', help='use data from yesterday')
args = parser.parse_args()
if args.week:
args.sumdays = 7
args.printdays = 7
elif args.twoweeks:
args.sumdays = 14
args.printdays = 7
else:
if args.sumdays is None:
args.sumdays = 1
if args.printdays is None:
args.printdays = 1
x = loadjson("https://covid19.who.int/page-data/index/page-data.json")
#y = loadjson("https://covid19.who.int/geo/who-world-map-topo-split-1.json")
byday = getitem(x, "result", "pageContext", "rawDataSets", "dayGroups")
bycty = getitem(x, "result", "pageContext", "rawDataSets", "countryGroups")
table = dict()
dates = set()
cinfo = readcountries()
#codes = { "XK":{"name":"Kosovo", "region":"EURO"}, " ":{"name":"CruiseShips", "region":"SHIP"} }
#or item in getitem(y, "objects", "countries", "geometries"):
# prop = item.get("properties")
# cc = prop.get("ISO_2_CODE")
# info = cinfo.get(cc)
# if not info:
# print("no info for %s" % cc)
# info = Country(prop.get("ADM0_VIZ_N"), 0, 0, "World")
# ccodes[cc] = {
# "name":prop.get("ADM0_VIZ_N"),
# "region":prop.get("WHO_REGION") ,
# "area":info.area,
# "population":info.population,
# }
for data in bycty:
name = getitem(data, "value")
d = getitem(data, "data", "dimensions")
m = getitem(data, "data", "metrics")
table[name] = c = dict()
for row in getitem(data, "data", "rows"):
t = cvt(row[0])
delta = 0
if name == 'GB' and t >= '07-03':
delta = 30302
c[t] = { "deaths": row[3], "cases": row[8]+delta }
dates.add(t)
dates = list(sorted(dates))
dates = dates[::-1]
if args.yesterday:
# skip the partially incomplete statistics from today
dates = dates[1:]
w0, wp, w1, w2 = 0, args.printdays, args.sumdays, args.delta*args.sumdays
for key in ("deaths", "cases"):
print("==== %s" % key)
print("%-6s%-30s %8s" % ("", "", ""), end=" ")
for t in dates[:-w1:wp]:
print("%10s" % t, end=" ")
print()
for cc, row in table.items():
country = cinfo[cc]
if args.byarea:
factor = 1.0 / country.area if country.area else 0
elif args.bypopulation:
factor = 1.0 / country.population * 100000 if country.population else 0
else:
factor = None
dt = 0 ; mark = ' '
t0 = dates[w0] ; x0 = getitem(row, t0, key)
if x0 is None:
dt = 1
mark = '+'
t0 = dates[w0+dt] ; x0 = getitem(row, t0, key)
t1 = dates[w1+dt] ; x1 = getitem(row, t1, key)
t2 = dates[w2+dt] ; x2 = getitem(row, t2, key)
groei = 100*(x0-x1)/(x0-x2) if not (x0 is None or x1 is None or x2 is None) and x0-x2!=0 else 0
#groei -= 100*(w1-w0)/(w2-w0)
print("%-5s:%-30s %7.2f%s" % (country.region, country.name[:30], groei, mark), end=" ")
for t0, t1 in zip(dates[dt::wp], dates[dt+w1::wp]):
x0 = getitem(row, t0, key)
x1 = getitem(row, t1, key)
if x0 is None or x1 is None:
print("%10s" % "-", end=" ")
elif factor is None:
print("%10s" % (x0-x1), end=" ")
else:
print("%10.4f" % ((x0-x1)*factor), end=" ")
print()
if __name__ == '__main__':
main()
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