Azure Stream Analitics list in the list - azure

How do I take the data from the file list if json array is in the list? eg.
{"city":{"id":1851632,"name":"Shuzenji",
"coord":{"lon":138.933334,"lat":34.966671},
"country":"JP",
"cod":"200",
"message":0.0045,
"cnt":38,
"list":[{
"dt":1406106000,
"main":{
"temp":298.77,
"temp_min":298.77,
"temp_max":298.774,
"pressure":1005.93,
"sea_level":1018.18,
"grnd_level":1005.93,
"humidity":87
"temp_kf":0.26},
"weather":[{"id":804,"main":"Clouds","description":"overcast clouds","icon":"04d"}],
"clouds":{"all":88},
"wind":{"speed":5.71,"deg":229.501},
"sys":{"pod":"d"},
"dt_txt":"2014-07-23 09:00:00"}
]}
How do I get to weather.main?


First your JSON format seem to have errors, let's fix these first:
{"city":{"id":1851632,"name":"Shuzenji"},
"coord":{"lon":138.933334,"lat":34.966671},
"country":"JP",
"cod":"200",
"message":0.0045,
"cnt":38,
"list":[{
"dt":1406106000,
"main":{
"temp":298.77,
"temp_min":298.77,
"temp_max":298.774,
"pressure":1005.93,
"sea_level":1018.18,
"grnd_level":1005.93,
"humidity":87,
"temp_kf":0.26},
"weather":[{"id":804,"main":"Clouds","description":"overcast clouds","icon":"04d"}],
"clouds":{"all":88},
"wind":{"speed":5.71,"deg":229.501},
"sys":{"pod":"d"},
"dt_txt":"2014-07-23 09:00:00"}
]},
Note comma after at the end of humidity line, and closed record in the first line after Shuzenji.
Now, in the JSON example weather.main, is actually list[0].weather[0].main. Here is the way to get precisely this value
out of the JSON structure using Array and Record built-in functions:
SELECT
-- input.list[0].weather[0].main
WeatherMain = GetRecordPropertyValue(GetArrayElement(GetRecordPropertyValue(GetArrayElement(input.list, 0), 'weather'), 0), 'main')
FROM input

Related

How do I in FloPy Modflow6 output MAW head values for all timesteps?

I am creating a MAW well and want to use it as an observation well to compare it later to field data, it should be screened over multiple layers. However, I am only getting the head value in the well of the very last timestep in my output file. Any ideas on how to get all timesteps in the output?
The FloPy manual says something about it needing to be in Output Control, but I can't figure out how to do that:
print_head (boolean) – print_head (boolean) keyword to indicate that the list of multi-aquifer well heads will be printed to the listing file for every stress period in which “HEAD PRINT” is specified in Output Control. If there is no Output Control option and PRINT_HEAD is specified, then heads are printed for the last time step of each stress period.
In the MODFLOW6 manual I see that it is possible to make a continuous output:
modflow6
My MAW definition looks like this:
maw = flopy.mf6.ModflowGwfmaw(gwf,
nmawwells=1,
packagedata=[0, Rwell, minbot, wellhead,'MEAN',OBS1welllayers],
connectiondata=OBS1connectiondata,
perioddata=[(0,'STATUS','ACTIVE')],
flowing_wells=False,
save_flows=True,
mover=True,
flow_correction=True,
budget_filerecord='OBS1wellbudget',
print_flows=True,
print_head=True,
head_filerecord='OBS1wellhead',
)
My output control looks like this:
oc = flopy.mf6.ModflowGwfoc(gwf,
budget_filerecord=budget_file,
head_filerecord=head_file,
saverecord=[('HEAD', 'ALL'), ('BUDGET', 'ALL'), ],
)
Hope this is all clear and someone can help me, thanks!

You need to initialise the MAW observations file... it's not done in the OC package.
You can find the scripts for the three MAW examples in the MF6 documentation here:
https://github.com/MODFLOW-USGS/modflow6-examples/tree/master/notebooks
It looks something like this:
obs_file = "{}.maw.obs".format(name)
csv_file = obs_file + ".csv"
obs_dict = {csv_file: [
("head", "head", (0,)),
("Q1", "maw", (0,), (0,)),
("Q2", "maw", (0,), (1,)),
("Q3", "maw", (0,), (2,)),
]}
maw.obs.initialize(filename=obs_file, digits=10, print_input=True, continuous=obs_dict)

kdb/q: How to apply a string manipulation function to a vector of strings to output a vector of strings?

Thanks in advance for the help. I am new to kdb/q, coming from a Python and C++ background.
Just a simple syntax question: I have a string with fields and their corresponding values
pp_str: "field_1:abc field_2:xyz field_3:kdb"
I wrote an atomic (scalar) function to extract the value of a given field.
get_field_value: {[field; pp_str] pp_fields: " " vs pp_str; pid_field: pp_fields[where like[pp_fields; field,":*"]]; start_i: (pid_field[0] ss ":")[0] + 1; end_i: count pid_field[0]; indices: start_i + til (end_i - start_i); pid_field[0][indices]}
show get_field_value["field_1"; pp_str]
"abc"
show get_field_value["field_3"; pp_str]
"kdb"
Now how do I generalize this so that if I input a vector of fields, I get a vector of values? I want to input ("field_1"; "field_2"; "field_3") and output ("abc"; "xyz"; "kdb"). I tried multiple approaches (below) but I just don't understand kdb/q's syntax well enough to vectorize my function:
/ Attempt 1 - Fail
get_field_value[enlist ("field_1"; "field_2"); pp_str]
/ Attempt 2 - Fail
get_field_value[; pp_str] /. enlist ("field_1"; "field_3")
/ Attempt 3 - Fail
fields: ("field_1"; "field_2")
get_field_value[fields; pp_str]

To run your function for each you could project the pp_str variable and use each for the others
q)get_field_value[;pp_str]each("field_1";"field_3")
"abc"
"kdb"
Kdb actually has built-in functionality to handle this: https://code.kx.com/q/ref/file-text/#key-value-pairs
q){#[;x](!/)"S: "0:y}[`field_1;pp_str]
"abc"
q)
q){#[;x](!/)"S: "0:y}[`field_1`field_3;pp_str]
"abc"
"kdb"

I think this might be the syntax you're looking for.
q)get_field_value[; pp_str]each("field_1";"field_2")
"abc"
"xyz"

How to extract several timestamp pairs from a list in Python

I have extracted all timestamps from a transcript file. The output looks like this:
('[, 00:00:03,950, 00:00:06,840, 00:00:06,840, 00:00:09,180, 00:00:09,180, '
'00:00:10,830, 00:00:10,830, 00:00:14,070, 00:00:14,070, 00:00:16,890, '
'00:00:16,890, 00:00:19,080, 00:00:19,080, 00:00:21,590, 00:00:21,590, '
'00:00:24,030, 00:00:24,030, 00:00:26,910, 00:00:26,910, 00:00:29,640, '
'00:00:29,640, 00:00:31,920, 00:00:31,920, 00:00:35,850, 00:00:35,850, '
'00:00:38,629, 00:00:38,629, 00:00:40,859, 00:00:40,859, 00:00:43,170, '
'00:00:43,170, 00:00:45,570, 00:00:45,570, 00:00:48,859, 00:00:48,859, '
'00:00:52,019, 00:00:52,019, 00:00:54,449, 00:00:54,449, 00:00:57,210, '
'00:00:57,210, 00:00:59,519, 00:00:59,519, 00:01:02,690, 00:01:02,690, '
'00:01:05,820, 00:01:05,820, 00:01:08,549, 00:01:08,549, 00:01:10,490, '
'00:01:10,490, 00:01:13,409, 00:01:13,409, 00:01:16,409, 00:01:16,409, '
'00:01:18,149, 00:01:18,149, 00:01:20,340, 00:01:20,340, 00:01:22,649, '
'00:01:22,649, 00:01:26,159, 00:01:26,159, 00:01:28,740, 00:01:28,740, '
'00:01:30,810, 00:01:30,810, 00:01:33,719, 00:01:33,719, 00:01:36,990, '
'00:01:36,990, 00:01:39,119, 00:01:39,119, 00:01:41,759, 00:01:41,759, '
'00:01:43,799, 00:01:43,799, 00:01:46,619, 00:01:46,619, 00:01:49,140, '
'00:01:49,140, 00:01:51,240, 00:01:51,240, 00:01:53,759, 00:01:53,759, '
'00:01:56,460, 00:01:56,460, 00:01:58,740, 00:01:58,740, 00:02:01,640, '
'00:02:01,640, 00:02:04,409, 00:02:04,409, 00:02:07,229, 00:02:07,229, '
'00:02:09,380, 00:02:09,380, 00:02:12,060, 00:02:12,060, 00:02:14,840, ]')
In this output, there are always timestamp pairs, i.e. always 2 consecutive timestamps belong together, for example: 00:00:03,950 and 00:00:06,840, 00:00:06,840 and 00:00:09,180, etc.
Now, I want to extract all these timestamp pairs separately so that the output looks like this:
00:00:03,950 - 00:00:06,840
00:00:06,840 - 00:00:09,180
00:00:09,180 - 00:00:10,830
etc.
For now, I have the following (very inconvenient) solution for my problem:
# get first part of first timestamp
a = res_timestamps[2:15]
print(dedent(a))
# get second part of first timestamp
b = res_timestamps[17:29]
print(b)
# combine timestamp parts
c = a + ' - ' + b
print(dedent(c))
Of course, this is very bad since I cannot extract the indices manually for all transcripts. Trying to use a loop has not worked yet because each item is not a timestamp but a single character.
Is there an elegant solution for my problem?
I appreciate any help or tip.
Thank you very much in advance!

Regex to the rescue!
A solution that works perfectly on your example data:
import re
from pprint import pprint
pprint(re.findall(r"(\d{2}:\d{2}:\d{2},\d{3}), (\d{2}:\d{2}:\d{2},\d{3})", your_data))
This prints:
[('00:00:03,950', '00:00:06,840'),
('00:00:06,840', '00:00:09,180'),
('00:00:09,180', '00:00:10,830'),
('00:00:10,830', '00:00:14,070'),
('00:00:14,070', '00:00:16,890'),
('00:00:16,890', '00:00:19,080'),
('00:00:19,080', '00:00:21,590'),
('00:00:21,590', '00:00:24,030'),
('00:00:24,030', '00:00:26,910'),
('00:00:26,910', '00:00:29,640'),
('00:00:29,640', '00:00:31,920'),
('00:00:31,920', '00:00:35,850'),
('00:00:35,850', '00:00:38,629'),
('00:00:38,629', '00:00:40,859'),
('00:00:40,859', '00:00:43,170'),
('00:00:43,170', '00:00:45,570'),
('00:00:45,570', '00:00:48,859'),
('00:00:48,859', '00:00:52,019'),
('00:00:52,019', '00:00:54,449'),
('00:00:54,449', '00:00:57,210'),
('00:00:57,210', '00:00:59,519'),
('00:00:59,519', '00:01:02,690'),
('00:01:02,690', '00:01:05,820'),
('00:01:05,820', '00:01:08,549'),
('00:01:08,549', '00:01:10,490'),
('00:01:10,490', '00:01:13,409'),
('00:01:13,409', '00:01:16,409'),
('00:01:16,409', '00:01:18,149'),
('00:01:18,149', '00:01:20,340'),
('00:01:20,340', '00:01:22,649'),
('00:01:22,649', '00:01:26,159'),
('00:01:26,159', '00:01:28,740'),
('00:01:28,740', '00:01:30,810'),
('00:01:30,810', '00:01:33,719'),
('00:01:33,719', '00:01:36,990'),
('00:01:36,990', '00:01:39,119'),
('00:01:39,119', '00:01:41,759'),
('00:01:41,759', '00:01:43,799'),
('00:01:43,799', '00:01:46,619'),
('00:01:46,619', '00:01:49,140'),
('00:01:49,140', '00:01:51,240'),
('00:01:51,240', '00:01:53,759'),
('00:01:53,759', '00:01:56,460'),
('00:01:56,460', '00:01:58,740'),
('00:01:58,740', '00:02:01,640'),
('00:02:01,640', '00:02:04,409'),
('00:02:04,409', '00:02:07,229'),
('00:02:07,229', '00:02:09,380'),
('00:02:09,380', '00:02:12,060'),
('00:02:12,060', '00:02:14,840')]
You could output this in your desired format like so:
for start, end in timestamps:
print(f"{start} - {end}")

Here's a solution without regular expressions
Clean the string, and split on ', ' to create a list
Use string slicing to select the odd and even values and zip them together.
# give data as your string
# convert data into a list by removing end brackets and spaces, and splitting
data = data.replace('[, ', '').replace(', ]', '').split(', ')
# use list slicing and zip the two components
combinations = list(zip(data[::2], data[1::2]))
# print the first 5
print(combinations[:5])
[out]:
[('00:00:03,950', '00:00:06,840'),
('00:00:06,840', '00:00:09,180'),
('00:00:09,180', '00:00:10,830'),
('00:00:10,830', '00:00:14,070'),
('00:00:14,070', '00:00:16,890')]

How to get a list of all supported timezones?

How can we get a list of all supported timezones in NodeJs at runtime?
use-cases:
we want to implement a check when the application starts to make sure that the main timezone (set via env-var) is correct).
we want to show a list to the user so that they can select only valid time-zones
The nodejs docs mention that node can be used with different ICU settings, so a hardcoded list (like timezones.json) will not work.
I found some related questions, but none seems to answer this (simple?) question...
e.g. Where does Node.js get the Timezone data from?

I think that currently there is no easy way to get the list of supported timezones in node.js at runtime:
JavaScript Internationalization Api:
The specification does not provide a way to get the list of supported timezones
NodeJs:
NodeJs also does not provide a way go get the list of supported timezones
Workaround
A workaround is to somehow get a list of timezones and test each one separately.
There are many predefined timezone lists:
IANA Timezone database
Wikipedia: List of tz database time zones
Json Timezone List
Csv Timezone List
However, since we have a database application, we first get the list of all timezones supported by the database - see PostgreSql docs:
SELECT name
FROM pg_timezone_names
ORDER BY name;
and then check for each one if it is supported by nodejs (here's some typescript pseudo code):
try {
new Intl.DateTimeFormat('en-US', {
timeZone
})
// timezone is valid - add to the valid list
} catch (e) {
// timezone is invalid - maybe write a log msg
}
Stackblitz Test
Now we have a list of all timezones that are valid in the database and in NodeJs.
There are currently (PostgreSql 12, NodeJs 14):
547 valid timezones
49 invalid timezones (i.e. known by PostgreSql, but not by NodeJs): e.g. America/Argentina/ComodRivadavia, US/Alaska, ..

If you need a detailed JSON file, check out https://github.com/dmfilipenko/timezones.json/blob/master/timezones.json.
However, if you just need the names (e.g. America/Los_Angeles) in a JSON array, the following 3-liner script in Node.js would work to get that from timezones.json.
const namesSet = new Set();
require("timezones.json").forEach((tzDefinition) => tzDefinition.utc.forEach((tzName) => namesSet.add(tzName)));
console.log(JSON.stringify([...namesSet].sort()));
Output on 2021/11/14 from "timezones.json": "1.5.3":
["Africa/Abidjan","Africa/Accra","Africa/Addis_Ababa","Africa/Algiers","Africa/Asmera","Africa/Bamako","Africa/Bangui","Africa/Banjul","Africa/Bissau","Africa/Blantyre","Africa/Brazzaville","Africa/Bujumbura","Africa/Cairo","Africa/Casablanca","Africa/Ceuta","Africa/Conakry","Africa/Dakar","Africa/Dar_es_Salaam","Africa/Djibouti","Africa/Douala","Africa/El_Aaiun","Africa/Freetown","Africa/Gaborone","Africa/Harare","Africa/Johannesburg","Africa/Juba","Africa/Kampala","Africa/Khartoum","Africa/Kigali","Africa/Kinshasa","Africa/Lagos","Africa/Libreville","Africa/Lome","Africa/Luanda","Africa/Lubumbashi","Africa/Lusaka","Africa/Malabo","Africa/Maputo","Africa/Maseru","Africa/Mbabane","Africa/Mogadishu","Africa/Monrovia","Africa/Nairobi","Africa/Ndjamena","Africa/Niamey","Africa/Nouakchott","Africa/Ouagadougou","Africa/Porto-Novo","Africa/Sao_Tome","Africa/Tripoli","Africa/Tunis","Africa/Windhoek","America/Anchorage","America/Anguilla","America/Antigua","America/Araguaina","America/Argentina/La_Rioja","America/Argentina/Rio_Gallegos","America/Argentina/Salta","America/Argentina/San_Juan","America/Argentina/San_Luis","America/Argentina/Tucuman","America/Argentina/Ushuaia","America/Aruba","America/Asuncion","America/Bahia","America/Bahia_Banderas","America/Barbados","America/Belem","America/Belize","America/Blanc-Sablon","America/Boa_Vista","America/Bogota","America/Boise","America/Buenos_Aires","America/Cambridge_Bay","America/Campo_Grande","America/Cancun","America/Caracas","America/Catamarca","America/Cayenne","America/Cayman","America/Chicago","America/Chihuahua","America/Coral_Harbour","America/Cordoba","America/Costa_Rica","America/Creston","America/Cuiaba","America/Curacao","America/Danmarkshavn","America/Dawson","America/Dawson_Creek","America/Denver","America/Detroit","America/Dominica","America/Edmonton","America/Eirunepe","America/El_Salvador","America/Fortaleza","America/Glace_Bay","America/Godthab","America/Goose_Bay","America/Grand_Turk","America/Grenada","America/Guadeloupe","America/Guatemala","America/Guayaquil","America/Guyana","America/Halifax","America/Havana","America/Hermosillo","America/Indiana/Knox","America/Indiana/Marengo","America/Indiana/Petersburg","America/Indiana/Tell_City","America/Indiana/Vevay","America/Indiana/Vincennes","America/Indiana/Winamac","America/Indianapolis","America/Inuvik","America/Iqaluit","America/Jamaica","America/Jujuy","America/Juneau","America/Kentucky/Monticello","America/Kralendijk","America/La_Paz","America/Lima","America/Los_Angeles","America/Louisville","America/Lower_Princes","America/Maceio","America/Managua","America/Manaus","America/Marigot","America/Martinique","America/Matamoros","America/Mazatlan","America/Mendoza","America/Menominee","America/Merida","America/Mexico_City","America/Moncton","America/Monterrey","America/Montevideo","America/Montreal","America/Montserrat","America/Nassau","America/New_York","America/Nipigon","America/Nome","America/Noronha","America/North_Dakota/Beulah","America/North_Dakota/Center","America/North_Dakota/New_Salem","America/Ojinaga","America/Panama","America/Pangnirtung","America/Paramaribo","America/Phoenix","America/Port-au-Prince","America/Port_of_Spain","America/Porto_Velho","America/Puerto_Rico","America/Rainy_River","America/Rankin_Inlet","America/Recife","America/Regina","America/Resolute","America/Rio_Branco","America/Santa_Isabel","America/Santarem","America/Santiago","America/Santo_Domingo","America/Sao_Paulo","America/Scoresbysund","America/Sitka","America/St_Barthelemy","America/St_Johns","America/St_Kitts","America/St_Lucia","America/St_Thomas","America/St_Vincent","America/Swift_Current","America/Tegucigalpa","America/Thule","America/Thunder_Bay","America/Tijuana","America/Toronto","America/Tortola","America/Vancouver","America/Whitehorse","America/Winnipeg","America/Yakutat","America/Yellowknife","Antarctica/Casey","Antarctica/Davis","Antarctica/DumontDUrville","Antarctica/Macquarie","Antarctica/Mawson","Antarctica/McMurdo","Antarctica/Palmer","Antarctica/Rothera","Antarctica/Syowa","Antarctica/Vostok","Arctic/Longyearbyen","Asia/Aden","Asia/Almaty","Asia/Amman","Asia/Anadyr","Asia/Aqtau","Asia/Aqtobe","Asia/Ashgabat","Asia/Baghdad","Asia/Bahrain","Asia/Baku","Asia/Bangkok","Asia/Beirut","Asia/Bishkek","Asia/Brunei","Asia/Calcutta","Asia/Chita","Asia/Choibalsan","Asia/Colombo","Asia/Damascus","Asia/Dhaka","Asia/Dili","Asia/Dubai","Asia/Dushanbe","Asia/Hong_Kong","Asia/Hovd","Asia/Irkutsk","Asia/Jakarta","Asia/Jayapura","Asia/Jerusalem","Asia/Kabul","Asia/Kamchatka","Asia/Karachi","Asia/Kathmandu","Asia/Khandyga","Asia/Kolkata","Asia/Krasnoyarsk","Asia/Kuala_Lumpur","Asia/Kuching","Asia/Kuwait","Asia/Macau","Asia/Magadan","Asia/Makassar","Asia/Manila","Asia/Muscat","Asia/Nicosia","Asia/Novokuznetsk","Asia/Novosibirsk","Asia/Omsk","Asia/Oral","Asia/Phnom_Penh","Asia/Pontianak","Asia/Pyongyang","Asia/Qatar","Asia/Qyzylorda","Asia/Rangoon","Asia/Riyadh","Asia/Saigon","Asia/Sakhalin","Asia/Samarkand","Asia/Seoul","Asia/Shanghai","Asia/Singapore","Asia/Srednekolymsk","Asia/Taipei","Asia/Tashkent","Asia/Tbilisi","Asia/Tehran","Asia/Thimphu","Asia/Tokyo","Asia/Ulaanbaatar","Asia/Urumqi","Asia/Ust-Nera","Asia/Vientiane","Asia/Vladivostok","Asia/Yakutsk","Asia/Yekaterinburg","Asia/Yerevan","Atlantic/Azores","Atlantic/Bermuda","Atlantic/Canary","Atlantic/Cape_Verde","Atlantic/Faeroe","Atlantic/Madeira","Atlantic/Reykjavik","Atlantic/South_Georgia","Atlantic/St_Helena","Atlantic/Stanley","Australia/Adelaide","Australia/Brisbane","Australia/Broken_Hill","Australia/Currie","Australia/Darwin","Australia/Hobart","Australia/Lindeman","Australia/Melbourne","Australia/Perth","Australia/Sydney","CST6CDT","EST5EDT","Etc/GMT","Etc/GMT+1","Etc/GMT+10","Etc/GMT+11","Etc/GMT+12","Etc/GMT+2","Etc/GMT+3","Etc/GMT+4","Etc/GMT+5","Etc/GMT+6","Etc/GMT+7","Etc/GMT-1","Etc/GMT-10","Etc/GMT-11","Etc/GMT-12","Etc/GMT-13","Etc/GMT-2","Etc/GMT-3","Etc/GMT-4","Etc/GMT-5","Etc/GMT-6","Etc/GMT-7","Etc/GMT-8","Etc/GMT-9","Europe/Amsterdam","Europe/Andorra","Europe/Astrakhan","Europe/Athens","Europe/Belgrade","Europe/Berlin","Europe/Bratislava","Europe/Brussels","Europe/Bucharest","Europe/Budapest","Europe/Busingen","Europe/Chisinau","Europe/Copenhagen","Europe/Dublin","Europe/Gibraltar","Europe/Guernsey","Europe/Helsinki","Europe/Isle_of_Man","Europe/Istanbul","Europe/Jersey","Europe/Kaliningrad","Europe/Kiev","Europe/Kirov","Europe/Lisbon","Europe/Ljubljana","Europe/London","Europe/Luxembourg","Europe/Madrid","Europe/Malta","Europe/Mariehamn","Europe/Minsk","Europe/Monaco","Europe/Moscow","Europe/Nicosia","Europe/Oslo","Europe/Paris","Europe/Podgorica","Europe/Prague","Europe/Riga","Europe/Rome","Europe/Samara","Europe/San_Marino","Europe/Sarajevo","Europe/Simferopol","Europe/Skopje","Europe/Sofia","Europe/Stockholm","Europe/Tallinn","Europe/Tirane","Europe/Ulyanovsk","Europe/Uzhgorod","Europe/Vaduz","Europe/Vatican","Europe/Vienna","Europe/Vilnius","Europe/Volgograd","Europe/Warsaw","Europe/Zagreb","Europe/Zaporozhye","Europe/Zurich","Indian/Antananarivo","Indian/Chagos","Indian/Christmas","Indian/Cocos","Indian/Comoro","Indian/Kerguelen","Indian/Mahe","Indian/Maldives","Indian/Mauritius","Indian/Mayotte","Indian/Reunion","MST7MDT","PST8PDT","Pacific/Apia","Pacific/Auckland","Pacific/Efate","Pacific/Enderbury","Pacific/Fakaofo","Pacific/Fiji","Pacific/Funafuti","Pacific/Galapagos","Pacific/Guadalcanal","Pacific/Guam","Pacific/Honolulu","Pacific/Johnston","Pacific/Kosrae","Pacific/Kwajalein","Pacific/Majuro","Pacific/Midway","Pacific/Nauru","Pacific/Niue","Pacific/Noumea","Pacific/Pago_Pago","Pacific/Palau","Pacific/Ponape","Pacific/Port_Moresby","Pacific/Rarotonga","Pacific/Saipan","Pacific/Tahiti","Pacific/Tarawa","Pacific/Tongatapu","Pacific/Truk","Pacific/Wake","Pacific/Wallis"]
Pretty-printed:
// 434 entries extracted from "timezones.json#1.5.3" package at 2021-11-14T20:03:29.078Z
[
"Africa/Abidjan",
"Africa/Accra",
"Africa/Addis_Ababa",
"Africa/Algiers",
"Africa/Asmera",
"Africa/Bamako",
"Africa/Bangui",
"Africa/Banjul",
"Africa/Bissau",
"Africa/Blantyre",
"Africa/Brazzaville",
"Africa/Bujumbura",
"Africa/Cairo",
"Africa/Casablanca",
"Africa/Ceuta",
"Africa/Conakry",
"Africa/Dakar",
"Africa/Dar_es_Salaam",
"Africa/Djibouti",
"Africa/Douala",
"Africa/El_Aaiun",
"Africa/Freetown",
"Africa/Gaborone",
"Africa/Harare",
"Africa/Johannesburg",
"Africa/Juba",
"Africa/Kampala",
"Africa/Khartoum",
"Africa/Kigali",
"Africa/Kinshasa",
"Africa/Lagos",
"Africa/Libreville",
"Africa/Lome",
"Africa/Luanda",
"Africa/Lubumbashi",
"Africa/Lusaka",
"Africa/Malabo",
"Africa/Maputo",
"Africa/Maseru",
"Africa/Mbabane",
"Africa/Mogadishu",
"Africa/Monrovia",
"Africa/Nairobi",
"Africa/Ndjamena",
"Africa/Niamey",
"Africa/Nouakchott",
"Africa/Ouagadougou",
"Africa/Porto-Novo",
"Africa/Sao_Tome",
"Africa/Tripoli",
"Africa/Tunis",
"Africa/Windhoek",
"America/Anchorage",
"America/Anguilla",
"America/Antigua",
"America/Araguaina",
"America/Argentina/La_Rioja",
"America/Argentina/Rio_Gallegos",
"America/Argentina/Salta",
"America/Argentina/San_Juan",
"America/Argentina/San_Luis",
"America/Argentina/Tucuman",
"America/Argentina/Ushuaia",
"America/Aruba",
"America/Asuncion",
"America/Bahia",
"America/Bahia_Banderas",
"America/Barbados",
"America/Belem",
"America/Belize",
"America/Blanc-Sablon",
"America/Boa_Vista",
"America/Bogota",
"America/Boise",
"America/Buenos_Aires",
"America/Cambridge_Bay",
"America/Campo_Grande",
"America/Cancun",
"America/Caracas",
"America/Catamarca",
"America/Cayenne",
"America/Cayman",
"America/Chicago",
"America/Chihuahua",
"America/Coral_Harbour",
"America/Cordoba",
"America/Costa_Rica",
"America/Creston",
"America/Cuiaba",
"America/Curacao",
"America/Danmarkshavn",
"America/Dawson",
"America/Dawson_Creek",
"America/Denver",
"America/Detroit",
"America/Dominica",
"America/Edmonton",
"America/Eirunepe",
"America/El_Salvador",
"America/Fortaleza",
"America/Glace_Bay",
"America/Godthab",
"America/Goose_Bay",
"America/Grand_Turk",
"America/Grenada",
"America/Guadeloupe",
"America/Guatemala",
"America/Guayaquil",
"America/Guyana",
"America/Halifax",
"America/Havana",
"America/Hermosillo",
"America/Indiana/Knox",
"America/Indiana/Marengo",
"America/Indiana/Petersburg",
"America/Indiana/Tell_City",
"America/Indiana/Vevay",
"America/Indiana/Vincennes",
"America/Indiana/Winamac",
"America/Indianapolis",
"America/Inuvik",
"America/Iqaluit",
"America/Jamaica",
"America/Jujuy",
"America/Juneau",
"America/Kentucky/Monticello",
"America/Kralendijk",
"America/La_Paz",
"America/Lima",
"America/Los_Angeles",
"America/Louisville",
"America/Lower_Princes",
"America/Maceio",
"America/Managua",
"America/Manaus",
"America/Marigot",
"America/Martinique",
"America/Matamoros",
"America/Mazatlan",
"America/Mendoza",
"America/Menominee",
"America/Merida",
"America/Mexico_City",
"America/Moncton",
"America/Monterrey",
"America/Montevideo",
"America/Montreal",
"America/Montserrat",
"America/Nassau",
"America/New_York",
"America/Nipigon",
"America/Nome",
"America/Noronha",
"America/North_Dakota/Beulah",
"America/North_Dakota/Center",
"America/North_Dakota/New_Salem",
"America/Ojinaga",
"America/Panama",
"America/Pangnirtung",
"America/Paramaribo",
"America/Phoenix",
"America/Port-au-Prince",
"America/Port_of_Spain",
"America/Porto_Velho",
"America/Puerto_Rico",
"America/Rainy_River",
"America/Rankin_Inlet",
"America/Recife",
"America/Regina",
"America/Resolute",
"America/Rio_Branco",
"America/Santa_Isabel",
"America/Santarem",
"America/Santiago",
"America/Santo_Domingo",
"America/Sao_Paulo",
"America/Scoresbysund",
"America/Sitka",
"America/St_Barthelemy",
"America/St_Johns",
"America/St_Kitts",
"America/St_Lucia",
"America/St_Thomas",
"America/St_Vincent",
"America/Swift_Current",
"America/Tegucigalpa",
"America/Thule",
"America/Thunder_Bay",
"America/Tijuana",
"America/Toronto",
"America/Tortola",
"America/Vancouver",
"America/Whitehorse",
"America/Winnipeg",
"America/Yakutat",
"America/Yellowknife",
"Antarctica/Casey",
"Antarctica/Davis",
"Antarctica/DumontDUrville",
"Antarctica/Macquarie",
"Antarctica/Mawson",
"Antarctica/McMurdo",
"Antarctica/Palmer",
"Antarctica/Rothera",
"Antarctica/Syowa",
"Antarctica/Vostok",
"Arctic/Longyearbyen",
"Asia/Aden",
"Asia/Almaty",
"Asia/Amman",
"Asia/Anadyr",
"Asia/Aqtau",
"Asia/Aqtobe",
"Asia/Ashgabat",
"Asia/Baghdad",
"Asia/Bahrain",
"Asia/Baku",
"Asia/Bangkok",
"Asia/Beirut",
"Asia/Bishkek",
"Asia/Brunei",
"Asia/Calcutta",
"Asia/Chita",
"Asia/Choibalsan",
"Asia/Colombo",
"Asia/Damascus",
"Asia/Dhaka",
"Asia/Dili",
"Asia/Dubai",
"Asia/Dushanbe",
"Asia/Hong_Kong",
"Asia/Hovd",
"Asia/Irkutsk",
"Asia/Jakarta",
"Asia/Jayapura",
"Asia/Jerusalem",
"Asia/Kabul",
"Asia/Kamchatka",
"Asia/Karachi",
"Asia/Kathmandu",
"Asia/Khandyga",
"Asia/Kolkata",
"Asia/Krasnoyarsk",
"Asia/Kuala_Lumpur",
"Asia/Kuching",
"Asia/Kuwait",
"Asia/Macau",
"Asia/Magadan",
"Asia/Makassar",
"Asia/Manila",
"Asia/Muscat",
"Asia/Nicosia",
"Asia/Novokuznetsk",
"Asia/Novosibirsk",
"Asia/Omsk",
"Asia/Oral",
"Asia/Phnom_Penh",
"Asia/Pontianak",
"Asia/Pyongyang",
"Asia/Qatar",
"Asia/Qyzylorda",
"Asia/Rangoon",
"Asia/Riyadh",
"Asia/Saigon",
"Asia/Sakhalin",
"Asia/Samarkand",
"Asia/Seoul",
"Asia/Shanghai",
"Asia/Singapore",
"Asia/Srednekolymsk",
"Asia/Taipei",
"Asia/Tashkent",
"Asia/Tbilisi",
"Asia/Tehran",
"Asia/Thimphu",
"Asia/Tokyo",
"Asia/Ulaanbaatar",
"Asia/Urumqi",
"Asia/Ust-Nera",
"Asia/Vientiane",
"Asia/Vladivostok",
"Asia/Yakutsk",
"Asia/Yekaterinburg",
"Asia/Yerevan",
"Atlantic/Azores",
"Atlantic/Bermuda",
"Atlantic/Canary",
"Atlantic/Cape_Verde",
"Atlantic/Faeroe",
"Atlantic/Madeira",
"Atlantic/Reykjavik",
"Atlantic/South_Georgia",
"Atlantic/St_Helena",
"Atlantic/Stanley",
"Australia/Adelaide",
"Australia/Brisbane",
"Australia/Broken_Hill",
"Australia/Currie",
"Australia/Darwin",
"Australia/Hobart",
"Australia/Lindeman",
"Australia/Melbourne",
"Australia/Perth",
"Australia/Sydney",
"CST6CDT",
"EST5EDT",
"Etc/GMT",
"Etc/GMT+1",
"Etc/GMT+10",
"Etc/GMT+11",
"Etc/GMT+12",
"Etc/GMT+2",
"Etc/GMT+3",
"Etc/GMT+4",
"Etc/GMT+5",
"Etc/GMT+6",
"Etc/GMT+7",
"Etc/GMT-1",
"Etc/GMT-10",
"Etc/GMT-11",
"Etc/GMT-12",
"Etc/GMT-13",
"Etc/GMT-2",
"Etc/GMT-3",
"Etc/GMT-4",
"Etc/GMT-5",
"Etc/GMT-6",
"Etc/GMT-7",
"Etc/GMT-8",
"Etc/GMT-9",
"Europe/Amsterdam",
"Europe/Andorra",
"Europe/Astrakhan",
"Europe/Athens",
"Europe/Belgrade",
"Europe/Berlin",
"Europe/Bratislava",
"Europe/Brussels",
"Europe/Bucharest",
"Europe/Budapest",
"Europe/Busingen",
"Europe/Chisinau",
"Europe/Copenhagen",
"Europe/Dublin",
"Europe/Gibraltar",
"Europe/Guernsey",
"Europe/Helsinki",
"Europe/Isle_of_Man",
"Europe/Istanbul",
"Europe/Jersey",
"Europe/Kaliningrad",
"Europe/Kiev",
"Europe/Kirov",
"Europe/Lisbon",
"Europe/Ljubljana",
"Europe/London",
"Europe/Luxembourg",
"Europe/Madrid",
"Europe/Malta",
"Europe/Mariehamn",
"Europe/Minsk",
"Europe/Monaco",
"Europe/Moscow",
"Europe/Nicosia",
"Europe/Oslo",
"Europe/Paris",
"Europe/Podgorica",
"Europe/Prague",
"Europe/Riga",
"Europe/Rome",
"Europe/Samara",
"Europe/San_Marino",
"Europe/Sarajevo",
"Europe/Simferopol",
"Europe/Skopje",
"Europe/Sofia",
"Europe/Stockholm",
"Europe/Tallinn",
"Europe/Tirane",
"Europe/Ulyanovsk",
"Europe/Uzhgorod",
"Europe/Vaduz",
"Europe/Vatican",
"Europe/Vienna",
"Europe/Vilnius",
"Europe/Volgograd",
"Europe/Warsaw",
"Europe/Zagreb",
"Europe/Zaporozhye",
"Europe/Zurich",
"Indian/Antananarivo",
"Indian/Chagos",
"Indian/Christmas",
"Indian/Cocos",
"Indian/Comoro",
"Indian/Kerguelen",
"Indian/Mahe",
"Indian/Maldives",
"Indian/Mauritius",
"Indian/Mayotte",
"Indian/Reunion",
"MST7MDT",
"PST8PDT",
"Pacific/Apia",
"Pacific/Auckland",
"Pacific/Efate",
"Pacific/Enderbury",
"Pacific/Fakaofo",
"Pacific/Fiji",
"Pacific/Funafuti",
"Pacific/Galapagos",
"Pacific/Guadalcanal",
"Pacific/Guam",
"Pacific/Honolulu",
"Pacific/Johnston",
"Pacific/Kosrae",
"Pacific/Kwajalein",
"Pacific/Majuro",
"Pacific/Midway",
"Pacific/Nauru",
"Pacific/Niue",
"Pacific/Noumea",
"Pacific/Pago_Pago",
"Pacific/Palau",
"Pacific/Ponape",
"Pacific/Port_Moresby",
"Pacific/Rarotonga",
"Pacific/Saipan",
"Pacific/Tahiti",
"Pacific/Tarawa",
"Pacific/Tongatapu",
"Pacific/Truk",
"Pacific/Wake",
"Pacific/Wallis",
]
Note that any mapping from "Name" to anything (even text) wouldn't be unique -- e.g. America/Los_Angeles appears in two entries for with and without DST here.
The output of this can be dumped into a JSON5 file (last line has comment) and stored in your repo. You can run this script every now and then to get updated list.
A more detailed script that I wrote and I am actually going to store for generating this code is avaiable at: https://gist.github.com/eyedean/18f2611624c8f9624f8bc6a3b74e9dba

Write Past Value in data.txt

I want to write some list in data.txt.
The output from program is:
Triangle
('(a1, b1)', '(a2, b2)', '(a3, b3)')
Triangle
('(a4, b4)', '(a5, b5)', '(a6, b6)')
With this lines of code to write in data.txt;
data = {}
data['shapes'] = []
data['shapes'].append({
'name': str(triangle.name),
'Vertices': list(triangle.get_points())
I need output in my data.txt with json format like this:
{"shapes": [{"name": "Triangle", "Vertices": ["(a1, b1)", "(a2, b2)", "(a3, b3)"]}, {"name": "Triangle", "Vertices": ["(a4, b4)", "(a5, b5)", "(a6, b6)"]}]}
But this is what I get:
{"shapes": [{"name": "Triangle", "Vertices": ["(a4, b4)", "(a5, b5)", "(a6, b6)"]}]}
So, how can I write the past value of triangle that have vertices (a1, b1)...(a3, b3)?

This part of your code should be executed only once:
data = {}
data['shapes'] = []
The following part of your code you should execute repeatedly
data['shapes'].append({
'name': str(triangle.name),
'Vertices': list(triangle.get_points())
probably in a loop similar to this one
for triangle in triangles:
data['shapes'].append({
'name': str(triangle.name),
'Vertices': list(triangle.get_points())

It seems like you're overwriting the variable referencing the first triangle object with the next triangle object before appending the first triangle object's information to data['shapes'].
That block of code where you append to your data['shapes'] should be executed twice, once for each triangle object.

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