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https://github.com/leon-ai/leon.git
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feat(tcp server): remove unnecessary data from entity + detect most populated city
This commit is contained in:
Théo LUDWIG
parent
c512b422e7
commit
69ce669b4c
@ -389,17 +389,13 @@ interface SpacyEntity<
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interface SpacyLocationCountryData {
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name: string
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iso: string
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iso3: string
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isonumeric: number
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continentcode: string
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capital: string
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population: number
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tld: string
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currencycode: string
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currencyname: string
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phone: string
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languages: string
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neighbours: string
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}
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export interface SpacyLocationCountryEntity
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extends SpacyEntity<
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@ -415,20 +411,13 @@ export interface SpacyLocationCityEntity
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{
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value: string
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data: {
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geonameid: number
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name: string
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latitude: number
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longitude: number
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countrycode: string
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country: SpacyLocationCountryData
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population: number
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alternatenames: string[]
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time_zone: {
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country_code: string
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id: string
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coordinated_universal_time_offset_hours: number
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daylight_saving_time_offset_hours: number
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}
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timezone: string
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}
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}
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> {}
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@ -18,9 +18,9 @@ export const run: ActionFunction = async function (params) {
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})
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}
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const { time_zone } = cityEntity.resolution.data
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const { timezone } = cityEntity.resolution.data
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const currentDate = new Date(
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new Date().toLocaleString('en', { timeZone: time_zone.id })
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new Date().toLocaleString('en', { timeZone: timezone })
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)
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await leon.answer({
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key: 'current_date_time_with_time_zone',
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@ -1,11 +1,12 @@
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import socket
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import json
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from typing import Union
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import lib.nlp as nlp
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class TCPServer:
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def __init__(self, host, port):
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def __init__(self, host: str, port: Union[str, int]):
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self.host = host
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self.port = port
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self.tcp_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
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@ -48,7 +49,7 @@ class TCPServer:
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print(f'Client disconnected: {self.addr}')
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self.conn.close()
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def get_spacy_entities(self, utterance):
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def get_spacy_entities(self, utterance: str) -> dict:
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entities = nlp.extract_spacy_entities(utterance)
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return {
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@ -1,9 +1,7 @@
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import copy
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from sys import argv
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import os
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import spacy
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import geonamescache
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from typing import Union, TypedDict
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from geonamescache import GeonamesCache
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lang = argv[1] or 'en'
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spacy_nlp = None
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@ -28,48 +26,16 @@ spacy_model_mapping = {
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}
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}
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gc = geonamescache.GeonamesCache()
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countries = gc.get_countries()
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cities = gc.get_cities()
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class TimeZone(TypedDict):
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country_code: str
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id: str
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coordinated_universal_time_offset_hours: float
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daylight_saving_time_offset_hours: float
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# Extracted from: <https://download.geonames.org/export/dump/timeZones.txt>
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time_zones_path = os.path.join(os.path.dirname(__file__), 'time_zones.txt')
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time_zones: list[list[str]] = []
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with open(time_zones_path, 'r') as file:
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lines = file.read().splitlines()
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for line in lines:
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time_zones.append(line.rstrip().split('\t'))
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def get_time_zone_data(time_zone_id: str) -> Union[TimeZone, None]:
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time_zone_data: Union[TimeZone, None] = None
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for time_zone in time_zones:
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if time_zone[1] == time_zone_id:
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time_zone_data = {
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'country_code': time_zone[0],
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'id': time_zone[1],
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'coordinated_universal_time_offset_hours': float(time_zone[2]),
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'daylight_saving_time_offset_hours': float(time_zone[3])
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}
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break
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return time_zone_data
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geonamescache = GeonamesCache()
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countries = geonamescache.get_countries()
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cities = geonamescache.get_cities()
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"""
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Functions called from TCPServer class
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"""
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def load_spacy_model():
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def load_spacy_model() -> None:
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global spacy_nlp
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model = spacy_model_mapping[lang]['model']
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@ -80,9 +46,23 @@ def load_spacy_model():
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print('spaCy model loaded')
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def extract_spacy_entities(utterance):
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def delete_unneeded_country_data(data: dict) -> None:
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try:
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del data['geonameid']
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del data['neighbours']
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del data['languages']
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del data['iso3']
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del data['fips']
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del data['currencyname']
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del data['postalcoderegex']
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del data['areakm2']
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except BaseException:
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pass
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def extract_spacy_entities(utterance: str) -> list[dict]:
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doc = spacy_nlp(utterance)
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entities = []
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entities: list[dict] = []
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for ent in doc.ents:
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if ent.label_ in spacy_model_mapping[lang]['entity_mapping']:
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@ -95,22 +75,34 @@ def extract_spacy_entities(utterance):
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for country in countries:
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if countries[country]['name'].casefold() == ent.text.casefold():
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entity += ':country'
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resolution['data'] = countries[country]
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resolution['data'] = copy.deepcopy(countries[country])
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delete_unneeded_country_data(resolution['data'])
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break
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city_population = 0
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for city in cities:
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alternatenames = [name.casefold() for name in cities[city]['alternatenames']]
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if cities[city]['name'].casefold() == ent.text.casefold() or ent.text.casefold() in alternatenames:
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if city_population == 0:
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entity += ':city'
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resolution['data'] = cities[city]
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resolution['data']['time_zone'] = get_time_zone_data(cities[city]['timezone'])
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if cities[city]['population'] > city_population:
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resolution['data'] = copy.deepcopy(cities[city])
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city_population = cities[city]['population']
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for country in countries:
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if countries[country]['iso'] == cities[city]['countrycode']:
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resolution['data']['country'] = countries[country]
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break
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resolution['data']['country'] = copy.deepcopy(countries[country])
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break
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try:
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del resolution['data']['geonameid']
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del resolution['data']['alternatenames']
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del resolution['data']['admin1code']
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delete_unneeded_country_data(resolution['data']['country'])
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except BaseException:
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pass
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else:
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continue
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entities.append({
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'start': ent.start_char,
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@ -1,420 +0,0 @@
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CountryCode TimeZoneId GMT offset 1. Jan 2023 DST offset 1. Jul 2023 rawOffset (independant of DST)
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CI Africa/Abidjan 0.0 0.0 0.0
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GH Africa/Accra 0.0 0.0 0.0
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ET Africa/Addis_Ababa 3.0 3.0 3.0
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DZ Africa/Algiers 1.0 1.0 1.0
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ER Africa/Asmara 3.0 3.0 3.0
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ML Africa/Bamako 0.0 0.0 0.0
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CF Africa/Bangui 1.0 1.0 1.0
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GM Africa/Banjul 0.0 0.0 0.0
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GW Africa/Bissau 0.0 0.0 0.0
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MW Africa/Blantyre 2.0 2.0 2.0
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CG Africa/Brazzaville 1.0 1.0 1.0
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BI Africa/Bujumbura 2.0 2.0 2.0
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EG Africa/Cairo 2.0 3.0 2.0
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MA Africa/Casablanca 1.0 1.0 0.0
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ES Africa/Ceuta 1.0 2.0 1.0
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GN Africa/Conakry 0.0 0.0 0.0
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SN Africa/Dakar 0.0 0.0 0.0
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TZ Africa/Dar_es_Salaam 3.0 3.0 3.0
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DJ Africa/Djibouti 3.0 3.0 3.0
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CM Africa/Douala 1.0 1.0 1.0
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EH Africa/El_Aaiun 1.0 1.0 0.0
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SL Africa/Freetown 0.0 0.0 0.0
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BW Africa/Gaborone 2.0 2.0 2.0
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ZW Africa/Harare 2.0 2.0 2.0
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ZA Africa/Johannesburg 2.0 2.0 2.0
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SS Africa/Juba 2.0 2.0 2.0
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UG Africa/Kampala 3.0 3.0 3.0
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SD Africa/Khartoum 2.0 2.0 2.0
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RW Africa/Kigali 2.0 2.0 2.0
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CD Africa/Kinshasa 1.0 1.0 1.0
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NG Africa/Lagos 1.0 1.0 1.0
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GA Africa/Libreville 1.0 1.0 1.0
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TG Africa/Lome 0.0 0.0 0.0
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AO Africa/Luanda 1.0 1.0 1.0
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CD Africa/Lubumbashi 2.0 2.0 2.0
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ZM Africa/Lusaka 2.0 2.0 2.0
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GQ Africa/Malabo 1.0 1.0 1.0
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MZ Africa/Maputo 2.0 2.0 2.0
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LS Africa/Maseru 2.0 2.0 2.0
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SZ Africa/Mbabane 2.0 2.0 2.0
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SO Africa/Mogadishu 3.0 3.0 3.0
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LR Africa/Monrovia 0.0 0.0 0.0
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KE Africa/Nairobi 3.0 3.0 3.0
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TD Africa/Ndjamena 1.0 1.0 1.0
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NE Africa/Niamey 1.0 1.0 1.0
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MR Africa/Nouakchott 0.0 0.0 0.0
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BF Africa/Ouagadougou 0.0 0.0 0.0
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BJ Africa/Porto-Novo 1.0 1.0 1.0
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ST Africa/Sao_Tome 0.0 0.0 0.0
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LY Africa/Tripoli 2.0 2.0 2.0
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TN Africa/Tunis 1.0 1.0 1.0
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NA Africa/Windhoek 2.0 2.0 1.0
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US America/Adak -10.0 -9.0 -10.0
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US America/Anchorage -9.0 -8.0 -9.0
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AI America/Anguilla -4.0 -4.0 -4.0
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AG America/Antigua -4.0 -4.0 -4.0
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BR America/Araguaina -3.0 -3.0 -3.0
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AR America/Argentina/Buenos_Aires -3.0 -3.0 -3.0
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AR America/Argentina/Catamarca -3.0 -3.0 -3.0
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AR America/Argentina/Cordoba -3.0 -3.0 -3.0
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AR America/Argentina/Jujuy -3.0 -3.0 -3.0
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AR America/Argentina/La_Rioja -3.0 -3.0 -3.0
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AR America/Argentina/Mendoza -3.0 -3.0 -3.0
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AR America/Argentina/Rio_Gallegos -3.0 -3.0 -3.0
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AR America/Argentina/Salta -3.0 -3.0 -3.0
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AR America/Argentina/San_Juan -3.0 -3.0 -3.0
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AR America/Argentina/San_Luis -3.0 -3.0 -3.0
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AR America/Argentina/Tucuman -3.0 -3.0 -3.0
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AR America/Argentina/Ushuaia -3.0 -3.0 -3.0
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AW America/Aruba -4.0 -4.0 -4.0
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PY America/Asuncion -3.0 -4.0 -4.0
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CA America/Atikokan -5.0 -5.0 -5.0
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BR America/Bahia -3.0 -3.0 -3.0
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MX America/Bahia_Banderas -6.0 -6.0 -6.0
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BB America/Barbados -4.0 -4.0 -4.0
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BR America/Belem -3.0 -3.0 -3.0
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BZ America/Belize -6.0 -6.0 -6.0
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CA America/Blanc-Sablon -4.0 -4.0 -4.0
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BR America/Boa_Vista -4.0 -4.0 -4.0
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CO America/Bogota -5.0 -5.0 -5.0
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US America/Boise -7.0 -6.0 -7.0
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CA America/Cambridge_Bay -7.0 -6.0 -7.0
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BR America/Campo_Grande -4.0 -4.0 -4.0
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MX America/Cancun -5.0 -5.0 -5.0
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VE America/Caracas -4.0 -4.0 -4.0
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GF America/Cayenne -3.0 -3.0 -3.0
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KY America/Cayman -5.0 -5.0 -5.0
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US America/Chicago -6.0 -5.0 -6.0
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MX America/Chihuahua -6.0 -6.0 -6.0
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MX America/Ciudad_Juarez -7.0 -6.0 -7.0
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CR America/Costa_Rica -6.0 -6.0 -6.0
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CA America/Creston -7.0 -7.0 -7.0
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BR America/Cuiaba -4.0 -4.0 -4.0
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CW America/Curacao -4.0 -4.0 -4.0
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GL America/Danmarkshavn 0.0 0.0 0.0
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CA America/Dawson -7.0 -7.0 -7.0
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CA America/Dawson_Creek -7.0 -7.0 -7.0
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US America/Denver -7.0 -6.0 -7.0
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US America/Detroit -5.0 -4.0 -5.0
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DM America/Dominica -4.0 -4.0 -4.0
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CA America/Edmonton -7.0 -6.0 -7.0
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BR America/Eirunepe -5.0 -5.0 -5.0
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SV America/El_Salvador -6.0 -6.0 -6.0
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CA America/Fort_Nelson -7.0 -7.0 -7.0
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BR America/Fortaleza -3.0 -3.0 -3.0
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CA America/Glace_Bay -4.0 -3.0 -4.0
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CA America/Goose_Bay -4.0 -3.0 -4.0
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TC America/Grand_Turk -5.0 -4.0 -5.0
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GD America/Grenada -4.0 -4.0 -4.0
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GP America/Guadeloupe -4.0 -4.0 -4.0
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GT America/Guatemala -6.0 -6.0 -6.0
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EC America/Guayaquil -5.0 -5.0 -5.0
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GY America/Guyana -4.0 -4.0 -4.0
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CA America/Halifax -4.0 -3.0 -4.0
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CU America/Havana -5.0 -4.0 -5.0
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MX America/Hermosillo -7.0 -7.0 -7.0
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US America/Indiana/Indianapolis -5.0 -4.0 -5.0
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US America/Indiana/Knox -6.0 -5.0 -6.0
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US America/Indiana/Marengo -5.0 -4.0 -5.0
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US America/Indiana/Petersburg -5.0 -4.0 -5.0
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US America/Indiana/Tell_City -6.0 -5.0 -6.0
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US America/Indiana/Vevay -5.0 -4.0 -5.0
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US America/Indiana/Vincennes -5.0 -4.0 -5.0
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US America/Indiana/Winamac -5.0 -4.0 -5.0
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CA America/Inuvik -7.0 -6.0 -7.0
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CA America/Iqaluit -5.0 -4.0 -5.0
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JM America/Jamaica -5.0 -5.0 -5.0
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US America/Juneau -9.0 -8.0 -9.0
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US America/Kentucky/Louisville -5.0 -4.0 -5.0
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US America/Kentucky/Monticello -5.0 -4.0 -5.0
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BQ America/Kralendijk -4.0 -4.0 -4.0
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BO America/La_Paz -4.0 -4.0 -4.0
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PE America/Lima -5.0 -5.0 -5.0
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US America/Los_Angeles -8.0 -7.0 -8.0
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SX America/Lower_Princes -4.0 -4.0 -4.0
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BR America/Maceio -3.0 -3.0 -3.0
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NI America/Managua -6.0 -6.0 -6.0
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BR America/Manaus -4.0 -4.0 -4.0
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MF America/Marigot -4.0 -4.0 -4.0
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MQ America/Martinique -4.0 -4.0 -4.0
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MX America/Matamoros -6.0 -5.0 -6.0
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MX America/Mazatlan -7.0 -7.0 -7.0
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US America/Menominee -6.0 -5.0 -6.0
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MX America/Merida -6.0 -6.0 -6.0
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US America/Metlakatla -9.0 -8.0 -9.0
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MX America/Mexico_City -6.0 -6.0 -6.0
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PM America/Miquelon -3.0 -2.0 -3.0
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CA America/Moncton -4.0 -3.0 -4.0
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MX America/Monterrey -6.0 -6.0 -6.0
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UY America/Montevideo -3.0 -3.0 -3.0
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MS America/Montserrat -4.0 -4.0 -4.0
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BS America/Nassau -5.0 -4.0 -5.0
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US America/New_York -5.0 -4.0 -5.0
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US America/Nome -9.0 -8.0 -9.0
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BR America/Noronha -2.0 -2.0 -2.0
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US America/North_Dakota/Beulah -6.0 -5.0 -6.0
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US America/North_Dakota/Center -6.0 -5.0 -6.0
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US America/North_Dakota/New_Salem -6.0 -5.0 -6.0
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GL America/Nuuk -3.0 -2.0 -3.0
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MX America/Ojinaga -6.0 -5.0 -6.0
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PA America/Panama -5.0 -5.0 -5.0
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SR America/Paramaribo -3.0 -3.0 -3.0
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US America/Phoenix -7.0 -7.0 -7.0
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HT America/Port-au-Prince -5.0 -4.0 -5.0
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TT America/Port_of_Spain -4.0 -4.0 -4.0
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BR America/Porto_Velho -4.0 -4.0 -4.0
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PR America/Puerto_Rico -4.0 -4.0 -4.0
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CL America/Punta_Arenas -3.0 -3.0 -3.0
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CA America/Rankin_Inlet -6.0 -5.0 -6.0
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BR America/Recife -3.0 -3.0 -3.0
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CA America/Regina -6.0 -6.0 -6.0
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CA America/Resolute -6.0 -5.0 -6.0
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BR America/Rio_Branco -5.0 -5.0 -5.0
|
||||
BR America/Santarem -3.0 -3.0 -3.0
|
||||
CL America/Santiago -3.0 -4.0 -4.0
|
||||
DO America/Santo_Domingo -4.0 -4.0 -4.0
|
||||
BR America/Sao_Paulo -3.0 -3.0 -3.0
|
||||
GL America/Scoresbysund -1.0 0.0 -1.0
|
||||
US America/Sitka -9.0 -8.0 -9.0
|
||||
BL America/St_Barthelemy -4.0 -4.0 -4.0
|
||||
CA America/St_Johns -3.5 -2.5 -3.5
|
||||
KN America/St_Kitts -4.0 -4.0 -4.0
|
||||
LC America/St_Lucia -4.0 -4.0 -4.0
|
||||
VI America/St_Thomas -4.0 -4.0 -4.0
|
||||
VC America/St_Vincent -4.0 -4.0 -4.0
|
||||
CA America/Swift_Current -6.0 -6.0 -6.0
|
||||
HN America/Tegucigalpa -6.0 -6.0 -6.0
|
||||
GL America/Thule -4.0 -3.0 -4.0
|
||||
MX America/Tijuana -8.0 -7.0 -8.0
|
||||
CA America/Toronto -5.0 -4.0 -5.0
|
||||
VG America/Tortola -4.0 -4.0 -4.0
|
||||
CA America/Vancouver -8.0 -7.0 -8.0
|
||||
CA America/Whitehorse -7.0 -7.0 -7.0
|
||||
CA America/Winnipeg -6.0 -5.0 -6.0
|
||||
US America/Yakutat -9.0 -8.0 -9.0
|
||||
CA America/Yellowknife -7.0 -6.0 -7.0
|
||||
AQ Antarctica/Casey 11.0 11.0 11.0
|
||||
AQ Antarctica/Davis 7.0 7.0 7.0
|
||||
AQ Antarctica/DumontDUrville 10.0 10.0 10.0
|
||||
AU Antarctica/Macquarie 11.0 10.0 10.0
|
||||
AQ Antarctica/Mawson 5.0 5.0 5.0
|
||||
AQ Antarctica/McMurdo 13.0 12.0 12.0
|
||||
AQ Antarctica/Palmer -3.0 -3.0 -3.0
|
||||
AQ Antarctica/Rothera -3.0 -3.0 -3.0
|
||||
AQ Antarctica/Syowa 3.0 3.0 3.0
|
||||
AQ Antarctica/Troll 0.0 2.0 0.0
|
||||
AQ Antarctica/Vostok 6.0 6.0 6.0
|
||||
SJ Arctic/Longyearbyen 1.0 2.0 1.0
|
||||
YE Asia/Aden 3.0 3.0 3.0
|
||||
KZ Asia/Almaty 6.0 6.0 6.0
|
||||
JO Asia/Amman 3.0 3.0 3.0
|
||||
RU Asia/Anadyr 12.0 12.0 12.0
|
||||
KZ Asia/Aqtau 5.0 5.0 5.0
|
||||
KZ Asia/Aqtobe 5.0 5.0 5.0
|
||||
TM Asia/Ashgabat 5.0 5.0 5.0
|
||||
KZ Asia/Atyrau 5.0 5.0 5.0
|
||||
IQ Asia/Baghdad 3.0 3.0 3.0
|
||||
BH Asia/Bahrain 3.0 3.0 3.0
|
||||
AZ Asia/Baku 4.0 4.0 4.0
|
||||
TH Asia/Bangkok 7.0 7.0 7.0
|
||||
RU Asia/Barnaul 7.0 7.0 7.0
|
||||
LB Asia/Beirut 2.0 3.0 2.0
|
||||
KG Asia/Bishkek 6.0 6.0 6.0
|
||||
BN Asia/Brunei 8.0 8.0 8.0
|
||||
RU Asia/Chita 9.0 9.0 9.0
|
||||
MN Asia/Choibalsan 8.0 8.0 8.0
|
||||
LK Asia/Colombo 5.5 5.5 5.5
|
||||
SY Asia/Damascus 3.0 3.0 3.0
|
||||
BD Asia/Dhaka 6.0 6.0 6.0
|
||||
TL Asia/Dili 9.0 9.0 9.0
|
||||
AE Asia/Dubai 4.0 4.0 4.0
|
||||
TJ Asia/Dushanbe 5.0 5.0 5.0
|
||||
CY Asia/Famagusta 2.0 3.0 2.0
|
||||
PS Asia/Gaza 2.0 3.0 2.0
|
||||
PS Asia/Hebron 2.0 3.0 2.0
|
||||
VN Asia/Ho_Chi_Minh 7.0 7.0 7.0
|
||||
HK Asia/Hong_Kong 8.0 8.0 8.0
|
||||
MN Asia/Hovd 7.0 7.0 7.0
|
||||
RU Asia/Irkutsk 8.0 8.0 8.0
|
||||
ID Asia/Jakarta 7.0 7.0 7.0
|
||||
ID Asia/Jayapura 9.0 9.0 9.0
|
||||
IL Asia/Jerusalem 2.0 3.0 2.0
|
||||
AF Asia/Kabul 4.5 4.5 4.5
|
||||
RU Asia/Kamchatka 12.0 12.0 12.0
|
||||
PK Asia/Karachi 5.0 5.0 5.0
|
||||
NP Asia/Kathmandu 5.75 5.75 5.75
|
||||
RU Asia/Khandyga 9.0 9.0 9.0
|
||||
IN Asia/Kolkata 5.5 5.5 5.5
|
||||
RU Asia/Krasnoyarsk 7.0 7.0 7.0
|
||||
MY Asia/Kuala_Lumpur 8.0 8.0 8.0
|
||||
MY Asia/Kuching 8.0 8.0 8.0
|
||||
KW Asia/Kuwait 3.0 3.0 3.0
|
||||
MO Asia/Macau 8.0 8.0 8.0
|
||||
RU Asia/Magadan 11.0 11.0 11.0
|
||||
ID Asia/Makassar 8.0 8.0 8.0
|
||||
PH Asia/Manila 8.0 8.0 8.0
|
||||
OM Asia/Muscat 4.0 4.0 4.0
|
||||
CY Asia/Nicosia 2.0 3.0 2.0
|
||||
RU Asia/Novokuznetsk 7.0 7.0 7.0
|
||||
RU Asia/Novosibirsk 7.0 7.0 7.0
|
||||
RU Asia/Omsk 6.0 6.0 6.0
|
||||
KZ Asia/Oral 5.0 5.0 5.0
|
||||
KH Asia/Phnom_Penh 7.0 7.0 7.0
|
||||
ID Asia/Pontianak 7.0 7.0 7.0
|
||||
KP Asia/Pyongyang 9.0 9.0 9.0
|
||||
QA Asia/Qatar 3.0 3.0 3.0
|
||||
KZ Asia/Qostanay 6.0 6.0 6.0
|
||||
KZ Asia/Qyzylorda 5.0 5.0 5.0
|
||||
SA Asia/Riyadh 3.0 3.0 3.0
|
||||
RU Asia/Sakhalin 11.0 11.0 11.0
|
||||
UZ Asia/Samarkand 5.0 5.0 5.0
|
||||
KR Asia/Seoul 9.0 9.0 9.0
|
||||
CN Asia/Shanghai 8.0 8.0 8.0
|
||||
SG Asia/Singapore 8.0 8.0 8.0
|
||||
RU Asia/Srednekolymsk 11.0 11.0 11.0
|
||||
TW Asia/Taipei 8.0 8.0 8.0
|
||||
UZ Asia/Tashkent 5.0 5.0 5.0
|
||||
GE Asia/Tbilisi 4.0 4.0 4.0
|
||||
IR Asia/Tehran 3.5 3.5 3.5
|
||||
BT Asia/Thimphu 6.0 6.0 6.0
|
||||
JP Asia/Tokyo 9.0 9.0 9.0
|
||||
RU Asia/Tomsk 7.0 7.0 7.0
|
||||
MN Asia/Ulaanbaatar 8.0 8.0 8.0
|
||||
CN Asia/Urumqi 6.0 6.0 6.0
|
||||
RU Asia/Ust-Nera 10.0 10.0 10.0
|
||||
LA Asia/Vientiane 7.0 7.0 7.0
|
||||
RU Asia/Vladivostok 10.0 10.0 10.0
|
||||
RU Asia/Yakutsk 9.0 9.0 9.0
|
||||
MM Asia/Yangon 6.5 6.5 6.5
|
||||
RU Asia/Yekaterinburg 5.0 5.0 5.0
|
||||
AM Asia/Yerevan 4.0 4.0 4.0
|
||||
PT Atlantic/Azores -1.0 0.0 -1.0
|
||||
BM Atlantic/Bermuda -4.0 -3.0 -4.0
|
||||
ES Atlantic/Canary 0.0 1.0 0.0
|
||||
CV Atlantic/Cape_Verde -1.0 -1.0 -1.0
|
||||
FO Atlantic/Faroe 0.0 1.0 0.0
|
||||
PT Atlantic/Madeira 0.0 1.0 0.0
|
||||
IS Atlantic/Reykjavik 0.0 0.0 0.0
|
||||
GS Atlantic/South_Georgia -2.0 -2.0 -2.0
|
||||
SH Atlantic/St_Helena 0.0 0.0 0.0
|
||||
FK Atlantic/Stanley -3.0 -3.0 -3.0
|
||||
AU Australia/Adelaide 10.5 9.5 9.5
|
||||
AU Australia/Brisbane 10.0 10.0 10.0
|
||||
AU Australia/Broken_Hill 10.5 9.5 9.5
|
||||
AU Australia/Darwin 9.5 9.5 9.5
|
||||
AU Australia/Eucla 8.75 8.75 8.75
|
||||
AU Australia/Hobart 11.0 10.0 10.0
|
||||
AU Australia/Lindeman 10.0 10.0 10.0
|
||||
AU Australia/Lord_Howe 11.0 10.5 10.5
|
||||
AU Australia/Melbourne 11.0 10.0 10.0
|
||||
AU Australia/Perth 8.0 8.0 8.0
|
||||
AU Australia/Sydney 11.0 10.0 10.0
|
||||
NL Europe/Amsterdam 1.0 2.0 1.0
|
||||
AD Europe/Andorra 1.0 2.0 1.0
|
||||
RU Europe/Astrakhan 4.0 4.0 4.0
|
||||
GR Europe/Athens 2.0 3.0 2.0
|
||||
RS Europe/Belgrade 1.0 2.0 1.0
|
||||
DE Europe/Berlin 1.0 2.0 1.0
|
||||
SK Europe/Bratislava 1.0 2.0 1.0
|
||||
BE Europe/Brussels 1.0 2.0 1.0
|
||||
RO Europe/Bucharest 2.0 3.0 2.0
|
||||
HU Europe/Budapest 1.0 2.0 1.0
|
||||
DE Europe/Busingen 1.0 2.0 1.0
|
||||
MD Europe/Chisinau 2.0 3.0 2.0
|
||||
DK Europe/Copenhagen 1.0 2.0 1.0
|
||||
IE Europe/Dublin 0.0 1.0 0.0
|
||||
GI Europe/Gibraltar 1.0 2.0 1.0
|
||||
GG Europe/Guernsey 0.0 1.0 0.0
|
||||
FI Europe/Helsinki 2.0 3.0 2.0
|
||||
IM Europe/Isle_of_Man 0.0 1.0 0.0
|
||||
TR Europe/Istanbul 3.0 3.0 3.0
|
||||
JE Europe/Jersey 0.0 1.0 0.0
|
||||
RU Europe/Kaliningrad 2.0 2.0 2.0
|
||||
RU Europe/Kirov 3.0 3.0 3.0
|
||||
UA Europe/Kyiv 2.0 3.0 2.0
|
||||
PT Europe/Lisbon 0.0 1.0 0.0
|
||||
SI Europe/Ljubljana 1.0 2.0 1.0
|
||||
GB Europe/London 0.0 1.0 0.0
|
||||
LU Europe/Luxembourg 1.0 2.0 1.0
|
||||
ES Europe/Madrid 1.0 2.0 1.0
|
||||
MT Europe/Malta 1.0 2.0 1.0
|
||||
AX Europe/Mariehamn 2.0 3.0 2.0
|
||||
BY Europe/Minsk 3.0 3.0 3.0
|
||||
MC Europe/Monaco 1.0 2.0 1.0
|
||||
RU Europe/Moscow 3.0 3.0 3.0
|
||||
NO Europe/Oslo 1.0 2.0 1.0
|
||||
FR Europe/Paris 1.0 2.0 1.0
|
||||
ME Europe/Podgorica 1.0 2.0 1.0
|
||||
CZ Europe/Prague 1.0 2.0 1.0
|
||||
LV Europe/Riga 2.0 3.0 2.0
|
||||
IT Europe/Rome 1.0 2.0 1.0
|
||||
RU Europe/Samara 4.0 4.0 4.0
|
||||
SM Europe/San_Marino 1.0 2.0 1.0
|
||||
BA Europe/Sarajevo 1.0 2.0 1.0
|
||||
RU Europe/Saratov 4.0 4.0 4.0
|
||||
UA Europe/Simferopol 3.0 3.0 3.0
|
||||
MK Europe/Skopje 1.0 2.0 1.0
|
||||
BG Europe/Sofia 2.0 3.0 2.0
|
||||
SE Europe/Stockholm 1.0 2.0 1.0
|
||||
EE Europe/Tallinn 2.0 3.0 2.0
|
||||
AL Europe/Tirane 1.0 2.0 1.0
|
||||
RU Europe/Ulyanovsk 4.0 4.0 4.0
|
||||
LI Europe/Vaduz 1.0 2.0 1.0
|
||||
VA Europe/Vatican 1.0 2.0 1.0
|
||||
AT Europe/Vienna 1.0 2.0 1.0
|
||||
LT Europe/Vilnius 2.0 3.0 2.0
|
||||
RU Europe/Volgograd 3.0 3.0 3.0
|
||||
PL Europe/Warsaw 1.0 2.0 1.0
|
||||
HR Europe/Zagreb 1.0 2.0 1.0
|
||||
CH Europe/Zurich 1.0 2.0 1.0
|
||||
MG Indian/Antananarivo 3.0 3.0 3.0
|
||||
IO Indian/Chagos 6.0 6.0 6.0
|
||||
CX Indian/Christmas 7.0 7.0 7.0
|
||||
CC Indian/Cocos 6.5 6.5 6.5
|
||||
KM Indian/Comoro 3.0 3.0 3.0
|
||||
TF Indian/Kerguelen 5.0 5.0 5.0
|
||||
SC Indian/Mahe 4.0 4.0 4.0
|
||||
MV Indian/Maldives 5.0 5.0 5.0
|
||||
MU Indian/Mauritius 4.0 4.0 4.0
|
||||
YT Indian/Mayotte 3.0 3.0 3.0
|
||||
RE Indian/Reunion 4.0 4.0 4.0
|
||||
WS Pacific/Apia 13.0 13.0 13.0
|
||||
NZ Pacific/Auckland 13.0 12.0 12.0
|
||||
PG Pacific/Bougainville 11.0 11.0 11.0
|
||||
NZ Pacific/Chatham 13.75 12.75 12.75
|
||||
FM Pacific/Chuuk 10.0 10.0 10.0
|
||||
CL Pacific/Easter -5.0 -6.0 -6.0
|
||||
VU Pacific/Efate 11.0 11.0 11.0
|
||||
TK Pacific/Fakaofo 13.0 13.0 13.0
|
||||
FJ Pacific/Fiji 12.0 12.0 12.0
|
||||
TV Pacific/Funafuti 12.0 12.0 12.0
|
||||
EC Pacific/Galapagos -6.0 -6.0 -6.0
|
||||
PF Pacific/Gambier -9.0 -9.0 -9.0
|
||||
SB Pacific/Guadalcanal 11.0 11.0 11.0
|
||||
GU Pacific/Guam 10.0 10.0 10.0
|
||||
US Pacific/Honolulu -10.0 -10.0 -10.0
|
||||
KI Pacific/Kanton 13.0 13.0 13.0
|
||||
KI Pacific/Kiritimati 14.0 14.0 14.0
|
||||
FM Pacific/Kosrae 11.0 11.0 11.0
|
||||
MH Pacific/Kwajalein 12.0 12.0 12.0
|
||||
MH Pacific/Majuro 12.0 12.0 12.0
|
||||
PF Pacific/Marquesas -9.5 -9.5 -9.5
|
||||
UM Pacific/Midway -11.0 -11.0 -11.0
|
||||
NR Pacific/Nauru 12.0 12.0 12.0
|
||||
NU Pacific/Niue -11.0 -11.0 -11.0
|
||||
NF Pacific/Norfolk 12.0 11.0 11.0
|
||||
NC Pacific/Noumea 11.0 11.0 11.0
|
||||
AS Pacific/Pago_Pago -11.0 -11.0 -11.0
|
||||
PW Pacific/Palau 9.0 9.0 9.0
|
||||
PN Pacific/Pitcairn -8.0 -8.0 -8.0
|
||||
FM Pacific/Pohnpei 11.0 11.0 11.0
|
||||
PG Pacific/Port_Moresby 10.0 10.0 10.0
|
||||
CK Pacific/Rarotonga -10.0 -10.0 -10.0
|
||||
MP Pacific/Saipan 10.0 10.0 10.0
|
||||
PF Pacific/Tahiti -10.0 -10.0 -10.0
|
||||
KI Pacific/Tarawa 12.0 12.0 12.0
|
||||
TO Pacific/Tongatapu 13.0 13.0 13.0
|
||||
UM Pacific/Wake 12.0 12.0 12.0
|
||||
WF Pacific/Wallis 12.0 12.0 12.0
|
||||
@ -15,9 +15,6 @@ options = {
|
||||
'srsly.msgpack.util',
|
||||
'blis',
|
||||
'cymem'
|
||||
],
|
||||
'include_files': [
|
||||
'tcp_server/src/lib/time_zones.txt'
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
Loading…
Reference in New Issue
Block a user