code stringlengths 2k 1.04M | repo_path stringlengths 5 517 | parsed_code stringlengths 0 1.04M | quality_prob float64 0.02 0.95 | learning_prob float64 0.02 0.93 |
|---|---|---|---|---|
import smtplib
from unittest.mock import patch, Mock
import pytest
from logbook import Logger
from fibratus.output.smtp import SmtpOutput
@pytest.fixture(scope='module')
def smtp_adapter():
config = {
'host': 'smtp.gmail.com',
'from': '<EMAIL>',
'password': '<PASSWORD>',
'to': ['<EMAIL>', '<EMAIL>']
}
return SmtpOutput(**config)
class TestSmtpOutput(object):
def test_init(self, smtp_adapter):
assert 'smtp.gmail.com' in smtp_adapter.host
assert '<EMAIL>' in smtp_adapter.sender
assert set(['<EMAIL>', '<EMAIL>']) == set(smtp_adapter.to)
assert smtp_adapter.port == 587
def test_emit(self, smtp_adapter):
body = 'Anomalous network activity detected from notepad.exe process'
with patch('smtplib.SMTP'):
smtp_adapter.emit(body, subject='Anomalous network activity detected')
assert smtp_adapter._smtp.ehlo.call_count == 2
smtp_adapter._smtp.starttls.assert_called_once()
smtp_adapter._smtp.login.assert_called_with('<EMAIL>', 'secret')
message = 'From: <EMAIL>' \
'To: <EMAIL>, <EMAIL>' \
'Subject: Anomalous network activity detected' \
'Anomalous network activity detected from notepad.exe process'
smtp_adapter._smtp.login.sendmail('<EMAIL>', ['<EMAIL>',
'<EMAIL>'],
message)
smtp_adapter._smtp.quit.assert_called_once()
def test_emit_invalid_credentials(self, smtp_adapter):
body = 'Anomalous network activity detected from notpead.exe process'
smtp_adapter.logger = Mock(spec_set=Logger)
with patch('smtplib.SMTP'):
smtp_adapter._smtp.login.side_effect = smtplib.SMTPAuthenticationError(534, 'Invalid smtp credentials')
smtp_adapter.emit(body, subject='Anomalous network activity detected')
smtp_adapter.logger.error.assert_called_with('Invalid SMTP credentials for '
'<EMAIL>')
smtp_adapter._smtp.quit.assert_called_once() | tests/unit/output/smtp.py | import smtplib
from unittest.mock import patch, Mock
import pytest
from logbook import Logger
from fibratus.output.smtp import SmtpOutput
@pytest.fixture(scope='module')
def smtp_adapter():
config = {
'host': 'smtp.gmail.com',
'from': '<EMAIL>',
'password': '<PASSWORD>',
'to': ['<EMAIL>', '<EMAIL>']
}
return SmtpOutput(**config)
class TestSmtpOutput(object):
def test_init(self, smtp_adapter):
assert 'smtp.gmail.com' in smtp_adapter.host
assert '<EMAIL>' in smtp_adapter.sender
assert set(['<EMAIL>', '<EMAIL>']) == set(smtp_adapter.to)
assert smtp_adapter.port == 587
def test_emit(self, smtp_adapter):
body = 'Anomalous network activity detected from notepad.exe process'
with patch('smtplib.SMTP'):
smtp_adapter.emit(body, subject='Anomalous network activity detected')
assert smtp_adapter._smtp.ehlo.call_count == 2
smtp_adapter._smtp.starttls.assert_called_once()
smtp_adapter._smtp.login.assert_called_with('<EMAIL>', 'secret')
message = 'From: <EMAIL>' \
'To: <EMAIL>, <EMAIL>' \
'Subject: Anomalous network activity detected' \
'Anomalous network activity detected from notepad.exe process'
smtp_adapter._smtp.login.sendmail('<EMAIL>', ['<EMAIL>',
'<EMAIL>'],
message)
smtp_adapter._smtp.quit.assert_called_once()
def test_emit_invalid_credentials(self, smtp_adapter):
body = 'Anomalous network activity detected from notpead.exe process'
smtp_adapter.logger = Mock(spec_set=Logger)
with patch('smtplib.SMTP'):
smtp_adapter._smtp.login.side_effect = smtplib.SMTPAuthenticationError(534, 'Invalid smtp credentials')
smtp_adapter.emit(body, subject='Anomalous network activity detected')
smtp_adapter.logger.error.assert_called_with('Invalid SMTP credentials for '
'<EMAIL>')
smtp_adapter._smtp.quit.assert_called_once() | 0.409221 | 0.414662 |
from __future__ import unicode_literals
import re
from calendar import timegm
from datetime import MAXYEAR, timedelta
from dateutil import relativedelta
from dateutil.tz import tzlocal, tzutc
from faker.utils import is_string
from faker.utils.datetime_safe import date, datetime, real_date, real_datetime
from .. import BaseProvider
localized = True
def datetime_to_timestamp(dt):
if getattr(dt, 'tzinfo', None) is not None:
dt = dt.astimezone(tzutc())
return timegm(dt.timetuple())
def timestamp_to_datetime(timestamp, tzinfo):
if tzinfo is None:
pick = datetime.fromtimestamp(timestamp, tzlocal())
pick = pick.astimezone(tzutc()).replace(tzinfo=None)
else:
pick = datetime.fromtimestamp(timestamp, tzinfo)
return pick
class ParseError(ValueError):
pass
timedelta_pattern = r''
for name, sym in [('years', 'y'), ('months', 'M'), ('weeks', 'w'), ('days', 'd'),
('hours', 'h'), ('minutes', 'm'), ('seconds', 's')]:
timedelta_pattern += r'((?P<{}>(?:\+|-)\d+?){})?'.format(name, sym)
class Provider(BaseProvider):
centuries = [
'I',
'II',
'III',
'IV',
'V',
'VI',
'VII',
'VIII',
'IX',
'X',
'XI',
'XII',
'XIII',
'XIV',
'XV',
'XVI',
'XVII',
'XVIII',
'XIX',
'XX',
'XXI']
countries = [{'timezones': ['Europe/Andorra'],
'alpha-2-code': 'AD',
'alpha-3-code': 'AND',
'continent': 'Europe',
'name': 'Andorra',
'capital': 'Andorra la Vella'},
{'timezones': ['Asia/Kabul'],
'alpha-2-code': 'AF',
'alpha-3-code': 'AFG',
'continent': 'Asia',
'name': 'Afghanistan',
'capital': 'Kabul'},
{'timezones': ['America/Antigua'],
'alpha-2-code': 'AG',
'alpha-3-code': 'ATG',
'continent': 'North America',
'name': 'Antigua and Barbuda',
'capital': "St. John's"},
{'timezones': ['Europe/Tirane'],
'alpha-2-code': 'AL',
'alpha-3-code': 'ALB',
'continent': 'Europe',
'name': 'Albania',
'capital': 'Tirana'},
{'timezones': ['Asia/Yerevan'],
'alpha-2-code': 'AM',
'alpha-3-code': 'ARM',
'continent': 'Asia',
'name': 'Armenia',
'capital': 'Yerevan'},
{'timezones': ['Africa/Luanda'],
'alpha-2-code': 'AO',
'alpha-3-code': 'AGO',
'continent': 'Africa',
'name': 'Angola',
'capital': 'Luanda'},
{'timezones': ['America/Argentina/Buenos_Aires',
'America/Argentina/Cordoba',
'America/Argentina/Jujuy',
'America/Argentina/Tucuman',
'America/Argentina/Catamarca',
'America/Argentina/La_Rioja',
'America/Argentina/San_Juan',
'America/Argentina/Mendoza',
'America/Argentina/Rio_Gallegos',
'America/Argentina/Ushuaia'],
'alpha-2-code': 'AR',
'alpha-3-code': 'ARG',
'continent': 'South America',
'name': 'Argentina',
'capital': 'Buenos Aires'},
{'timezones': ['Europe/Vienna'],
'alpha-2-code': 'AT',
'alpha-3-code': 'AUT',
'continent': 'Europe',
'name': 'Austria',
'capital': 'Vienna'},
{'timezones': ['Australia/Lord_Howe',
'Australia/Hobart',
'Australia/Currie',
'Australia/Melbourne',
'Australia/Sydney',
'Australia/Broken_Hill',
'Australia/Brisbane',
'Australia/Lindeman',
'Australia/Adelaide',
'Australia/Darwin',
'Australia/Perth'],
'alpha-2-code': 'AU',
'alpha-3-code': 'AUS',
'continent': 'Oceania',
'name': 'Australia',
'capital': 'Canberra'},
{'timezones': ['Asia/Baku'],
'alpha-2-code': 'AZ',
'alpha-3-code': 'AZE',
'continent': 'Asia',
'name': 'Azerbaijan',
'capital': 'Baku'},
{'timezones': ['America/Barbados'],
'alpha-2-code': 'BB',
'alpha-3-code': 'BRB',
'continent': 'North America',
'name': 'Barbados',
'capital': 'Bridgetown'},
{'timezones': ['Asia/Dhaka'],
'alpha-2-code': 'BD',
'alpha-3-code': 'BGD',
'continent': 'Asia',
'name': 'Bangladesh',
'capital': 'Dhaka'},
{'timezones': ['Europe/Brussels'],
'alpha-2-code': 'BE',
'alpha-3-code': 'BEL',
'continent': 'Europe',
'name': 'Belgium',
'capital': 'Brussels'},
{'timezones': ['Africa/Ouagadougou'],
'alpha-2-code': 'BF',
'alpha-3-code': 'BFA',
'continent': 'Africa',
'name': 'Burkina Faso',
'capital': 'Ouagadougou'},
{'timezones': ['Europe/Sofia'],
'alpha-2-code': 'BG',
'alpha-3-code': 'BGR',
'continent': 'Europe',
'name': 'Bulgaria',
'capital': 'Sofia'},
{'timezones': ['Asia/Bahrain'],
'alpha-2-code': 'BH',
'alpha-3-code': 'BHR',
'continent': 'Asia',
'name': 'Bahrain',
'capital': 'Manama'},
{'timezones': ['Africa/Bujumbura'],
'alpha-2-code': 'BI',
'alpha-3-code': 'BDI',
'continent': 'Africa',
'name': 'Burundi',
'capital': 'Bujumbura'},
{'timezones': ['Africa/Porto-Novo'],
'alpha-2-code': 'BJ',
'alpha-3-code': 'BEN',
'continent': 'Africa',
'name': 'Benin',
'capital': 'Porto-Novo'},
{'timezones': ['Asia/Brunei'],
'alpha-2-code': 'BN',
'alpha-3-code': 'BRN',
'continent': 'Asia',
'name': '<NAME>',
'capital': 'Bandar Seri Begawan'},
{'timezones': ['America/La_Paz'],
'alpha-2-code': 'BO',
'alpha-3-code': 'BOL',
'continent': 'South America',
'name': 'Bolivia',
'capital': 'Sucre'},
{'timezones': ['America/Noronha',
'America/Belem',
'America/Fortaleza',
'America/Recife',
'America/Araguaina',
'America/Maceio',
'America/Bahia',
'America/Sao_Paulo',
'America/Campo_Grande',
'America/Cuiaba',
'America/Porto_Velho',
'America/Boa_Vista',
'America/Manaus',
'America/Eirunepe',
'America/Rio_Branco'],
'alpha-2-code': 'BR',
'alpha-3-code': 'BRA',
'continent': 'South America',
'name': 'Brazil',
'capital': 'Bras\xc3\xadlia'},
{'timezones': ['America/Nassau'],
'alpha-2-code': 'BS',
'alpha-3-code': 'BHS',
'continent': 'North America',
'name': 'Bahamas',
'capital': 'Nassau'},
{'timezones': ['Asia/Thimphu'],
'alpha-2-code': 'BT',
'alpha-3-code': 'BTN',
'continent': 'Asia',
'name': 'Bhutan',
'capital': 'Thimphu'},
{'timezones': ['Africa/Gaborone'],
'alpha-2-code': 'BW',
'alpha-3-code': 'BWA',
'continent': 'Africa',
'name': 'Botswana',
'capital': 'Gaborone'},
{'timezones': ['Europe/Minsk'],
'alpha-2-code': 'BY',
'alpha-3-code': 'BLR',
'continent': 'Europe',
'name': 'Belarus',
'capital': 'Minsk'},
{'timezones': ['America/Belize'],
'alpha-2-code': 'BZ',
'alpha-3-code': 'BLZ',
'continent': 'North America',
'name': 'Belize',
'capital': 'Belmopan'},
{'timezones': ['America/St_Johns',
'America/Halifax',
'America/Glace_Bay',
'America/Moncton',
'America/Goose_Bay',
'America/Blanc-Sablon',
'America/Montreal',
'America/Toronto',
'America/Nipigon',
'America/Thunder_Bay',
'America/Pangnirtung',
'America/Iqaluit',
'America/Atikokan',
'America/Rankin_Inlet',
'America/Winnipeg',
'America/Rainy_River',
'America/Cambridge_Bay',
'America/Regina',
'America/Swift_Current',
'America/Edmonton',
'America/Yellowknife',
'America/Inuvik',
'America/Dawson_Creek',
'America/Vancouver',
'America/Whitehorse',
'America/Dawson'],
'alpha-2-code': 'CA',
'alpha-3-code': 'CAN',
'continent': 'North America',
'name': 'Canada',
'capital': 'Ottawa'},
{'timezones': ['Africa/Kinshasa',
'Africa/Lubumbashi'],
'alpha-2-code': 'CD',
'alpha-3-code': 'COD',
'continent': 'Africa',
'name': 'Democratic Republic of the Congo',
'capital': 'Kinshasa'},
{'timezones': ['Africa/Brazzaville'],
'alpha-2-code': 'CG',
'alpha-3-code': 'COG',
'continent': 'Africa',
'name': 'Republic of the Congo',
'capital': 'Brazzaville'},
{'timezones': ['Africa/Abidjan'],
'alpha-2-code': 'CI',
'alpha-3-code': 'CIV',
'continent': 'Africa',
'name': "C\xc3\xb4te d'Ivoire",
'capital': 'Yamoussoukro'},
{'timezones': ['America/Santiago',
'Pacific/Easter'],
'alpha-2-code': 'CL',
'alpha-3-code': 'CHL',
'continent': 'South America',
'name': 'Chile',
'capital': 'Santiago'},
{'timezones': ['Africa/Douala'],
'alpha-2-code': 'CM',
'alpha-3-code': 'CMR',
'continent': 'Africa',
'name': 'Cameroon',
'capital': 'Yaound\xc3\xa9'},
{'timezones': ['Asia/Shanghai',
'Asia/Harbin',
'Asia/Chongqing',
'Asia/Urumqi',
'Asia/Kashgar'],
'alpha-2-code': 'CN',
'alpha-3-code': 'CHN',
'continent': 'Asia',
'name': "People's Republic of China",
'capital': 'Beijing'},
{'timezones': ['America/Bogota'],
'alpha-2-code': 'CO',
'alpha-3-code': 'COL',
'continent': 'South America',
'name': 'Colombia',
'capital': 'Bogot\xc3\xa1'},
{'timezones': ['America/Costa_Rica'],
'alpha-2-code': 'CR',
'alpha-3-code': 'CRI',
'continent': 'North America',
'name': 'Costa Rica',
'capital': 'San Jos\xc3\xa9'},
{'timezones': ['America/Havana'],
'alpha-2-code': 'CU',
'alpha-3-code': 'CUB',
'continent': 'North America',
'name': 'Cuba',
'capital': 'Havana'},
{'timezones': ['Atlantic/Cape_Verde'],
'alpha-2-code': 'CV',
'alpha-3-code': 'CPV',
'continent': 'Africa',
'name': 'Cape Verde',
'capital': 'Praia'},
{'timezones': ['Asia/Nicosia'],
'alpha-2-code': 'CY',
'alpha-3-code': 'CYP',
'continent': 'Asia',
'name': 'Cyprus',
'capital': 'Nicosia'},
{'timezones': ['Europe/Prague'],
'alpha-2-code': 'CZ',
'alpha-3-code': 'CZE',
'continent': 'Europe',
'name': 'Czech Republic',
'capital': 'Prague'},
{'timezones': ['Europe/Berlin'],
'alpha-2-code': 'DE',
'alpha-3-code': 'DEU',
'continent': 'Europe',
'name': 'Germany',
'capital': 'Berlin'},
{'timezones': ['Africa/Djibouti'],
'alpha-2-code': 'DJ',
'alpha-3-code': 'DJI',
'continent': 'Africa',
'name': 'Djibouti',
'capital': 'Djibouti City'},
{'timezones': ['Europe/Copenhagen'],
'alpha-2-code': 'DK',
'alpha-3-code': 'DNK',
'continent': 'Europe',
'name': 'Denmark',
'capital': 'Copenhagen'},
{'timezones': ['America/Dominica'],
'alpha-2-code': 'DM',
'alpha-3-code': 'DMA',
'continent': 'North America',
'name': 'Dominica',
'capital': 'Roseau'},
{'timezones': ['America/Santo_Domingo'],
'alpha-2-code': 'DO',
'alpha-3-code': 'DOM',
'continent': 'North America',
'name': 'Dominican Republic',
'capital': 'Santo Domingo'},
{'timezones': ['America/Guayaquil',
'Pacific/Galapagos'],
'alpha-2-code': 'EC',
'alpha-3-code': 'ECU',
'continent': 'South America',
'name': 'Ecuador',
'capital': 'Quito'},
{'timezones': ['Europe/Tallinn'],
'alpha-2-code': 'EE',
'alpha-3-code': 'EST',
'continent': 'Europe',
'name': 'Estonia',
'capital': 'Tallinn'},
{'timezones': ['Africa/Cairo'],
'alpha-2-code': 'EG',
'alpha-3-code': 'EGY',
'continent': 'Africa',
'name': 'Egypt',
'capital': 'Cairo'},
{'timezones': ['Africa/Asmera'],
'alpha-2-code': 'ER',
'alpha-3-code': 'ERI',
'continent': 'Africa',
'name': 'Eritrea',
'capital': 'Asmara'},
{'timezones': ['Africa/Addis_Ababa'],
'alpha-2-code': 'ET',
'alpha-3-code': 'ETH',
'continent': 'Africa',
'name': 'Ethiopia',
'capital': 'Addis Ababa'},
{'timezones': ['Europe/Helsinki'],
'alpha-2-code': 'FI',
'alpha-3-code': 'FIN',
'continent': 'Europe',
'name': 'Finland',
'capital': 'Helsinki'},
{'timezones': ['Pacific/Fiji'],
'alpha-2-code': 'FJ',
'alpha-3-code': 'FJI',
'continent': 'Oceania',
'name': 'Fiji',
'capital': 'Suva'},
{'timezones': ['Europe/Paris'],
'alpha-2-code': 'FR',
'alpha-3-code': 'FRA',
'continent': 'Europe',
'name': 'France',
'capital': 'Paris'},
{'timezones': ['Africa/Libreville'],
'alpha-2-code': 'GA',
'alpha-3-code': 'GAB',
'continent': 'Africa',
'name': 'Gabon',
'capital': 'Libreville'},
{'timezones': ['Asia/Tbilisi'],
'alpha-2-code': 'GE',
'alpha-3-code': 'GEO',
'continent': 'Asia',
'name': 'Georgia',
'capital': 'Tbilisi'},
{'timezones': ['Africa/Accra'],
'alpha-2-code': 'GH',
'alpha-3-code': 'GHA',
'continent': 'Africa',
'name': 'Ghana',
'capital': 'Accra'},
{'timezones': ['Africa/Banjul'],
'alpha-2-code': 'GM',
'alpha-3-code': 'GMB',
'continent': 'Africa',
'name': 'The Gambia',
'capital': 'Banjul'},
{'timezones': ['Africa/Conakry'],
'alpha-2-code': 'GN',
'alpha-3-code': 'GIN',
'continent': 'Africa',
'name': 'Guinea',
'capital': 'Conakry'},
{'timezones': ['Europe/Athens'],
'alpha-2-code': 'GR',
'alpha-3-code': 'GRC',
'continent': 'Europe',
'name': 'Greece',
'capital': 'Athens'},
{'timezones': ['America/Guatemala'],
'alpha-2-code': 'GT',
'alpha-3-code': 'GTM',
'continent': 'North America',
'name': 'Guatemala',
'capital': 'Guatemala City'},
{'timezones': ['America/Guatemala'],
'alpha-2-code': 'HT',
'alpha-3-code': 'HTI',
'continent': 'North America',
'name': 'Haiti',
'capital': 'Port-au-Prince'},
{'timezones': ['Africa/Bissau'],
'alpha-2-code': 'GW',
'alpha-3-code': 'GNB',
'continent': 'Africa',
'name': 'Guinea-Bissau',
'capital': 'Bissau'},
{'timezones': ['America/Guyana'],
'alpha-2-code': 'GY',
'alpha-3-code': 'GUY',
'continent': 'South America',
'name': 'Guyana',
'capital': 'Georgetown'},
{'timezones': ['America/Tegucigalpa'],
'alpha-2-code': 'HN',
'alpha-3-code': 'HND',
'continent': 'North America',
'name': 'Honduras',
'capital': 'Tegucigalpa'},
{'timezones': ['Europe/Budapest'],
'alpha-2-code': 'HU',
'alpha-3-code': 'HUN',
'continent': 'Europe',
'name': 'Hungary',
'capital': 'Budapest'},
{'timezones': ['Asia/Jakarta',
'Asia/Pontianak',
'Asia/Makassar',
'Asia/Jayapura'],
'alpha-2-code': 'ID',
'alpha-3-code': 'IDN',
'continent': 'Asia',
'name': 'Indonesia',
'capital': 'Jakarta'},
{'timezones': ['Europe/Dublin'],
'alpha-2-code': 'IE',
'alpha-3-code': 'IRL',
'continent': 'Europe',
'name': 'Republic of Ireland',
'capital': 'Dublin'},
{'timezones': ['Asia/Jerusalem'],
'alpha-2-code': 'IL',
'alpha-3-code': 'ISR',
'continent': 'Asia',
'name': 'Israel',
'capital': 'Jerusalem'},
{'timezones': ['Asia/Calcutta'],
'alpha-2-code': 'IN',
'alpha-3-code': 'IND',
'continent': 'Asia',
'name': 'India',
'capital': 'New Delhi'},
{'timezones': ['Asia/Baghdad'],
'alpha-2-code': 'IQ',
'alpha-3-code': 'IRQ',
'continent': 'Asia',
'name': 'Iraq',
'capital': 'Baghdad'},
{'timezones': ['Asia/Tehran'],
'alpha-2-code': 'IR',
'alpha-3-code': 'IRN',
'continent': 'Asia',
'name': 'Iran',
'capital': 'Tehran'},
{'timezones': ['Atlantic/Reykjavik'],
'alpha-2-code': 'IS',
'alpha-3-code': 'ISL',
'continent': 'Europe',
'name': 'Iceland',
'capital': 'Reykjav\xc3\xadk'},
{'timezones': ['Europe/Rome'],
'alpha-2-code': 'IT',
'alpha-3-code': 'ITA',
'continent': 'Europe',
'name': 'Italy',
'capital': 'Rome'},
{'timezones': ['America/Jamaica'],
'alpha-2-code': 'JM',
'alpha-3-code': 'JAM',
'continent': 'North America',
'name': 'Jamaica',
'capital': 'Kingston'},
{'timezones': ['Asia/Amman'],
'alpha-2-code': 'JO',
'alpha-3-code': 'JOR',
'continent': 'Asia',
'name': 'Jordan',
'capital': 'Amman'},
{'timezones': ['Asia/Tokyo'],
'alpha-2-code': 'JP',
'alpha-3-code': 'JPN',
'continent': 'Asia',
'name': 'Japan',
'capital': 'Tokyo'},
{'timezones': ['Africa/Nairobi'],
'alpha-2-code': 'KE',
'alpha-3-code': 'KEN',
'continent': 'Africa',
'name': 'Kenya',
'capital': 'Nairobi'},
{'timezones': ['Asia/Bishkek'],
'alpha-2-code': 'KG',
'alpha-3-code': 'KGZ',
'continent': 'Asia',
'name': 'Kyrgyzstan',
'capital': 'Bishkek'},
{'timezones': ['Pacific/Tarawa',
'Pacific/Enderbury',
'Pacific/Kiritimati'],
'alpha-2-code': 'KI',
'alpha-3-code': 'KIR',
'continent': 'Oceania',
'name': 'Kiribati',
'capital': 'Tarawa'},
{'timezones': ['Asia/Pyongyang'],
'alpha-2-code': 'KP',
'alpha-3-code': 'PRK',
'continent': 'Asia',
'name': 'North Korea',
'capital': 'Pyongyang'},
{'timezones': ['Asia/Seoul'],
'alpha-2-code': 'KR',
'alpha-3-code': 'KOR',
'continent': 'Asia',
'name': 'South Korea',
'capital': 'Seoul'},
{'timezones': ['Asia/Kuwait'],
'alpha-2-code': 'KW',
'alpha-3-code': 'KWT',
'continent': 'Asia',
'name': 'Kuwait',
'capital': 'Kuwait City'},
{'timezones': ['Asia/Beirut'],
'alpha-2-code': 'LB',
'alpha-3-code': 'LBN',
'continent': 'Asia',
'name': 'Lebanon',
'capital': 'Beirut'},
{'timezones': ['Europe/Vaduz'],
'alpha-2-code': 'LI',
'alpha-3-code': 'LIE',
'continent': 'Europe',
'name': 'Liechtenstein',
'capital': 'Vaduz'},
{'timezones': ['Africa/Monrovia'],
'alpha-2-code': 'LR',
'alpha-3-code': 'LBR',
'continent': 'Africa',
'name': 'Liberia',
'capital': 'Monrovia'},
{'timezones': ['Africa/Maseru'],
'alpha-2-code': 'LS',
'alpha-3-code': 'LSO',
'continent': 'Africa',
'name': 'Lesotho',
'capital': 'Maseru'},
{'timezones': ['Europe/Vilnius'],
'alpha-2-code': 'LT',
'alpha-3-code': 'LTU',
'continent': 'Europe',
'name': 'Lithuania',
'capital': 'Vilnius'},
{'timezones': ['Europe/Luxembourg'],
'alpha-2-code': 'LU',
'alpha-3-code': 'LUX',
'continent': 'Europe',
'name': 'Luxembourg',
'capital': 'Luxembourg City'},
{'timezones': ['Europe/Riga'],
'alpha-2-code': 'LV',
'alpha-3-code': 'LVA',
'continent': 'Europe',
'name': 'Latvia',
'capital': 'Riga'},
{'timezones': ['Africa/Tripoli'],
'alpha-2-code': 'LY',
'alpha-3-code': 'LBY',
'continent': 'Africa',
'name': 'Libya',
'capital': 'Tripoli'},
{'timezones': ['Indian/Antananarivo'],
'alpha-2-code': 'MG',
'alpha-3-code': 'MDG',
'continent': 'Africa',
'name': 'Madagascar',
'capital': 'Antananarivo'},
{'timezones': ['Pacific/Majuro',
'Pacific/Kwajalein'],
'alpha-2-code': 'MH',
'alpha-3-code': 'MHL',
'continent': 'Oceania',
'name': 'Marshall Islands',
'capital': 'Majuro'},
{'timezones': ['Europe/Skopje'],
'alpha-2-code': 'MK',
'alpha-3-code': 'MKD',
'continent': 'Europe',
'name': 'Macedonia',
'capital': 'Skopje'},
{'timezones': ['Africa/Bamako'],
'alpha-2-code': 'ML',
'alpha-3-code': 'MLI',
'continent': 'Africa',
'name': 'Mali',
'capital': 'Bamako'},
{'timezones': ['Asia/Rangoon'],
'alpha-2-code': 'MM',
'alpha-3-code': 'MMR',
'continent': 'Asia',
'name': 'Myanmar',
'capital': 'Naypyidaw'},
{'timezones': ['Asia/Ulaanbaatar',
'Asia/Hovd',
'Asia/Choibalsan'],
'alpha-2-code': 'MN',
'alpha-3-code': 'MNG',
'continent': 'Asia',
'name': 'Mongolia',
'capital': 'Ulaanbaatar'},
{'timezones': ['Africa/Nouakchott'],
'alpha-2-code': 'MR',
'alpha-3-code': 'MRT',
'continent': 'Africa',
'name': 'Mauritania',
'capital': 'Nouakchott'},
{'timezones': ['Europe/Malta'],
'alpha-2-code': 'MT',
'alpha-3-code': 'MLT',
'continent': 'Europe',
'name': 'Malta',
'capital': 'Valletta'},
{'timezones': ['Indian/Mauritius'],
'alpha-2-code': 'MU',
'alpha-3-code': 'MUS',
'continent': 'Africa',
'name': 'Mauritius',
'capital': 'Port Louis'},
{'timezones': ['Indian/Maldives'],
'alpha-2-code': 'MV',
'alpha-3-code': 'MDV',
'continent': 'Asia',
'name': 'Maldives',
'capital': 'Mal\xc3\xa9'},
{'timezones': ['Africa/Blantyre'],
'alpha-2-code': 'MW',
'alpha-3-code': 'MWI',
'continent': 'Africa',
'name': 'Malawi',
'capital': 'Lilongwe'},
{'timezones': ['America/Mexico_City',
'America/Cancun',
'America/Merida',
'America/Monterrey',
'America/Mazatlan',
'America/Chihuahua',
'America/Hermosillo',
'America/Tijuana'],
'alpha-2-code': 'MX',
'alpha-3-code': 'MEX',
'continent': 'North America',
'name': 'Mexico',
'capital': 'Mexico City'},
{'timezones': ['Asia/Kuala_Lumpur',
'Asia/Kuching'],
'alpha-2-code': 'MY',
'alpha-3-code': 'MYS',
'continent': 'Asia',
'name': 'Malaysia',
'capital': 'Kuala Lumpur'},
{'timezones': ['Africa/Maputo'],
'alpha-2-code': 'MZ',
'alpha-3-code': 'MOZ',
'continent': 'Africa',
'name': 'Mozambique',
'capital': 'Maputo'},
{'timezones': ['Africa/Windhoek'],
'alpha-2-code': 'NA',
'alpha-3-code': 'NAM',
'continent': 'Africa',
'name': 'Namibia',
'capital': 'Windhoek'},
{'timezones': ['Africa/Niamey'],
'alpha-2-code': 'NE',
'alpha-3-code': 'NER',
'continent': 'Africa',
'name': 'Niger',
'capital': 'Niamey'},
{'timezones': ['Africa/Lagos'],
'alpha-2-code': 'NG',
'alpha-3-code': 'NGA',
'continent': 'Africa',
'name': 'Nigeria',
'capital': 'Abuja'},
{'timezones': ['America/Managua'],
'alpha-2-code': 'NI',
'alpha-3-code': 'NIC',
'continent': 'North America',
'name': 'Nicaragua',
'capital': 'Managua'},
{'timezones': ['Europe/Amsterdam'],
'alpha-2-code': 'NL',
'alpha-3-code': 'NLD',
'continent': 'Europe',
'name': 'Kingdom of the Netherlands',
'capital': 'Amsterdam'},
{'timezones': ['Europe/Oslo'],
'alpha-2-code': 'NO',
'alpha-3-code': 'NOR',
'continent': 'Europe',
'name': 'Norway',
'capital': 'Oslo'},
{'timezones': ['Asia/Katmandu'],
'alpha-2-code': 'NP',
'alpha-3-code': 'NPL',
'continent': 'Asia',
'name': 'Nepal',
'capital': 'Kathmandu'},
{'timezones': ['Pacific/Nauru'],
'alpha-2-code': 'NR',
'alpha-3-code': 'NRU',
'continent': 'Oceania',
'name': 'Nauru',
'capital': 'Yaren'},
{'timezones': ['Pacific/Auckland',
'Pacific/Chatham'],
'alpha-2-code': 'NZ',
'alpha-3-code': 'NZL',
'continent': 'Oceania',
'name': 'New Zealand',
'capital': 'Wellington'},
{'timezones': ['Asia/Muscat'],
'alpha-2-code': 'OM',
'alpha-3-code': 'OMN',
'continent': 'Asia',
'name': 'Oman',
'capital': 'Muscat'},
{'timezones': ['America/Panama'],
'alpha-2-code': 'PA',
'alpha-3-code': 'PAN',
'continent': 'North America',
'name': 'Panama',
'capital': 'Panama City'},
{'timezones': ['America/Lima'],
'alpha-2-code': 'PE',
'alpha-3-code': 'PER',
'continent': 'South America',
'name': 'Peru',
'capital': 'Lima'},
{'timezones': ['Pacific/Port_Moresby'],
'alpha-2-code': 'PG',
'alpha-3-code': 'PNG',
'continent': 'Oceania',
'name': 'Papua New Guinea',
'capital': 'Port Moresby'},
{'timezones': ['Asia/Manila'],
'alpha-2-code': 'PH',
'alpha-3-code': 'PHL',
'continent': 'Asia',
'name': 'Philippines',
'capital': 'Manila'},
{'timezones': ['Asia/Karachi'],
'alpha-2-code': 'PK',
'alpha-3-code': 'PAK',
'continent': 'Asia',
'name': 'Pakistan',
'capital': 'Islamabad'},
{'timezones': ['Europe/Warsaw'],
'alpha-2-code': 'PL',
'alpha-3-code': 'POL',
'continent': 'Europe',
'name': 'Poland',
'capital': 'Warsaw'},
{'timezones': ['Europe/Lisbon',
'Atlantic/Madeira',
'Atlantic/Azores'],
'alpha-2-code': 'PT',
'alpha-3-code': 'PRT',
'continent': 'Europe',
'name': 'Portugal',
'capital': 'Lisbon'},
{'timezones': ['Pacific/Palau'],
'alpha-2-code': 'PW',
'alpha-3-code': 'PLW',
'continent': 'Oceania',
'name': 'Palau',
'capital': 'Ngerulmud'},
{'timezones': ['America/Asuncion'],
'alpha-2-code': 'PY',
'alpha-3-code': 'PRY',
'continent': 'South America',
'name': 'Paraguay',
'capital': 'Asunci\xc3\xb3n'},
{'timezones': ['Asia/Qatar'],
'alpha-2-code': 'QA',
'alpha-3-code': 'QAT',
'continent': 'Asia',
'name': 'Qatar',
'capital': 'Doha'},
{'timezones': ['Europe/Bucharest'],
'alpha-2-code': 'RO',
'alpha-3-code': 'ROU',
'continent': 'Europe',
'name': 'Romania',
'capital': 'Bucharest'},
{'timezones': ['Europe/Kaliningrad',
'Europe/Moscow',
'Europe/Volgograd',
'Europe/Samara',
'Asia/Yekaterinburg',
'Asia/Omsk',
'Asia/Novosibirsk',
'Asia/Krasnoyarsk',
'Asia/Irkutsk',
'Asia/Yakutsk',
'Asia/Vladivostok',
'Asia/Sakhalin',
'Asia/Magadan',
'Asia/Kamchatka',
'Asia/Anadyr'],
'alpha-2-code': 'RU',
'alpha-3-code': 'RUS',
'continent': 'Europe',
'name': 'Russia',
'capital': 'Moscow'},
{'timezones': ['Africa/Kigali'],
'alpha-2-code': 'RW',
'alpha-3-code': 'RWA',
'continent': 'Africa',
'name': 'Rwanda',
'capital': 'Kigali'},
{'timezones': ['Asia/Riyadh'],
'alpha-2-code': 'SA',
'alpha-3-code': 'SAU',
'continent': 'Asia',
'name': '<NAME>',
'capital': 'Riyadh'},
{'timezones': ['Pacific/Guadalcanal'],
'alpha-2-code': 'SB',
'alpha-3-code': 'SLB',
'continent': 'Oceania',
'name': 'Solomon Islands',
'capital': 'Honiara'},
{'timezones': ['Indian/Mahe'],
'alpha-2-code': 'SC',
'alpha-3-code': 'SYC',
'continent': 'Africa',
'name': 'Seychelles',
'capital': 'Victoria'},
{'timezones': ['Africa/Khartoum'],
'alpha-2-code': 'SD',
'alpha-3-code': 'SDN',
'continent': 'Africa',
'name': 'Sudan',
'capital': 'Khartoum'},
{'timezones': ['Europe/Stockholm'],
'alpha-2-code': 'SE',
'alpha-3-code': 'SWE',
'continent': 'Europe',
'name': 'Sweden',
'capital': 'Stockholm'},
{'timezones': ['Asia/Singapore'],
'alpha-2-code': 'SG',
'alpha-3-code': 'SGP',
'continent': 'Asia',
'name': 'Singapore',
'capital': 'Singapore'},
{'timezones': ['Europe/Ljubljana'],
'alpha-2-code': 'SI',
'alpha-3-code': 'SVN',
'continent': 'Europe',
'name': 'Slovenia',
'capital': 'Ljubljana'},
{'timezones': ['Europe/Bratislava'],
'alpha-2-code': 'SK',
'alpha-3-code': 'SVK',
'continent': 'Europe',
'name': 'Slovakia',
'capital': 'Bratislava'},
{'timezones': ['Africa/Freetown'],
'alpha-2-code': 'SL',
'alpha-3-code': 'SLE',
'continent': 'Africa',
'name': 'Sierra Leone',
'capital': 'Freetown'},
{'timezones': ['Europe/San_Marino'],
'alpha-2-code': 'SM',
'alpha-3-code': 'SMR',
'continent': 'Europe',
'name': 'San Marino',
'capital': 'San Marino'},
{'timezones': ['Africa/Dakar'],
'alpha-2-code': 'SN',
'alpha-3-code': 'SEN',
'continent': 'Africa',
'name': 'Senegal',
'capital': 'Dakar'},
{'timezones': ['Africa/Mogadishu'],
'alpha-2-code': 'SO',
'alpha-3-code': 'SOM',
'continent': 'Africa',
'name': 'Somalia',
'capital': 'Mogadishu'},
{'timezones': ['America/Paramaribo'],
'alpha-2-code': 'SR',
'alpha-3-code': 'SUR',
'continent': 'South America',
'name': 'Suriname',
'capital': 'Paramaribo'},
{'timezones': ['Africa/Sao_Tome'],
'alpha-2-code': 'ST',
'alpha-3-code': 'STP',
'continent': 'Africa',
'name': 'S\xc3\xa3o Tom\xc3\xa9 and Pr\xc3\xadncipe',
'capital': 'S\xc3\xa3o Tom\xc3\xa9'},
{'timezones': ['Asia/Damascus'],
'alpha-2-code': 'SY',
'alpha-3-code': 'SYR',
'continent': 'Asia',
'name': 'Syria',
'capital': 'Damascus'},
{'timezones': ['Africa/Lome'],
'alpha-2-code': 'TG',
'alpha-3-code': 'TGO',
'continent': 'Africa',
'name': 'Togo',
'capital': 'Lom\xc3\xa9'},
{'timezones': ['Asia/Bangkok'],
'alpha-2-code': 'TH',
'alpha-3-code': 'THA',
'continent': 'Asia',
'name': 'Thailand',
'capital': 'Bangkok'},
{'timezones': ['Asia/Dushanbe'],
'alpha-2-code': 'TJ',
'alpha-3-code': 'TJK',
'continent': 'Asia',
'name': 'Tajikistan',
'capital': 'Dushanbe'},
{'timezones': ['Asia/Ashgabat'],
'alpha-2-code': 'TM',
'alpha-3-code': 'TKM',
'continent': 'Asia',
'name': 'Turkmenistan',
'capital': 'Ashgabat'},
{'timezones': ['Africa/Tunis'],
'alpha-2-code': 'TN',
'alpha-3-code': 'TUN',
'continent': 'Africa',
'name': 'Tunisia',
'capital': 'Tunis'},
{'timezones': ['Pacific/Tongatapu'],
'alpha-2-code': 'TO',
'alpha-3-code': 'TON',
'continent': 'Oceania',
'name': 'Tonga',
'capital': 'Nuku\xca\xbbalofa'},
{'timezones': ['Europe/Istanbul'],
'alpha-2-code': 'TR',
'alpha-3-code': 'TUR',
'continent': 'Asia',
'name': 'Turkey',
'capital': 'Ankara'},
{'timezones': ['America/Port_of_Spain'],
'alpha-2-code': 'TT',
'alpha-3-code': 'TTO',
'continent': 'North America',
'name': 'Trinidad and Tobago',
'capital': 'Port of Spain'},
{'timezones': ['Pacific/Funafuti'],
'alpha-2-code': 'TV',
'alpha-3-code': 'TUV',
'continent': 'Oceania',
'name': 'Tuvalu',
'capital': 'Funafuti'},
{'timezones': ['Africa/Dar_es_Salaam'],
'alpha-2-code': 'TZ',
'alpha-3-code': 'TZA',
'continent': 'Africa',
'name': 'Tanzania',
'capital': 'Dodoma'},
{'timezones': ['Europe/Kiev',
'Europe/Uzhgorod',
'Europe/Zaporozhye',
'Europe/Simferopol'],
'alpha-2-code': 'UA',
'alpha-3-code': 'UKR',
'continent': 'Europe',
'name': 'Ukraine',
'capital': 'Kiev'},
{'timezones': ['Africa/Kampala'],
'alpha-2-code': 'UG',
'alpha-3-code': 'UGA',
'continent': 'Africa',
'name': 'Uganda',
'capital': 'Kampala'},
{'timezones': ['America/New_York',
'America/Detroit',
'America/Kentucky/Louisville',
'America/Kentucky/Monticello',
'America/Indiana/Indianapolis',
'America/Indiana/Marengo',
'America/Indiana/Knox',
'America/Indiana/Vevay',
'America/Chicago',
'America/Indiana/Vincennes',
'America/Indiana/Petersburg',
'America/Menominee',
'America/North_Dakota/Center',
'America/North_Dakota/New_Salem',
'America/Denver',
'America/Boise',
'America/Shiprock',
'America/Phoenix',
'America/Los_Angeles',
'America/Anchorage',
'America/Juneau',
'America/Yakutat',
'America/Nome',
'America/Adak',
'Pacific/Honolulu'],
'alpha-2-code': 'US',
'alpha-3-code': 'USA',
'continent': 'North America',
'name': 'United States',
'capital': 'Washington, D.C.'},
{'timezones': ['America/Montevideo'],
'alpha-2-code': 'UY',
'alpha-3-code': 'URY',
'continent': 'South America',
'name': 'Uruguay',
'capital': 'Montevideo'},
{'timezones': ['Asia/Samarkand',
'Asia/Tashkent'],
'alpha-2-code': 'UZ',
'alpha-3-code': 'UZB',
'continent': 'Asia',
'name': 'Uzbekistan',
'capital': 'Tashkent'},
{'timezones': ['Europe/Vatican'],
'alpha-2-code': 'VA',
'alpha-3-code': 'VAT',
'continent': 'Europe',
'name': 'Vatican City',
'capital': 'Vatican City'},
{'timezones': ['America/Caracas'],
'alpha-2-code': 'VE',
'alpha-3-code': 'VEN',
'continent': 'South America',
'name': 'Venezuela',
'capital': 'Caracas'},
{'timezones': ['Asia/Saigon'],
'alpha-2-code': 'VN',
'alpha-3-code': 'VNM',
'continent': 'Asia',
'name': 'Vietnam',
'capital': 'Hanoi'},
{'timezones': ['Pacific/Efate'],
'alpha-2-code': 'VU',
'alpha-3-code': 'VUT',
'continent': 'Oceania',
'name': 'Vanuatu',
'capital': 'Port Vila'},
{'timezones': ['Asia/Aden'],
'alpha-2-code': 'YE',
'alpha-3-code': 'YEM',
'continent': 'Asia',
'name': 'Yemen',
'capital': "Sana'a"},
{'timezones': ['Africa/Lusaka'],
'alpha-2-code': 'ZM',
'alpha-3-code': 'ZMB',
'continent': 'Africa',
'name': 'Zambia',
'capital': 'Lusaka'},
{'timezones': ['Africa/Harare'],
'alpha-2-code': 'ZW',
'alpha-3-code': 'ZWE',
'continent': 'Africa',
'name': 'Zimbabwe',
'capital': 'Harare'},
{'timezones': ['Africa/Algiers'],
'alpha-2-code': 'DZ',
'alpha-3-code': 'DZA',
'continent': 'Africa',
'name': 'Algeria',
'capital': 'Algiers'},
{'timezones': ['Europe/Sarajevo'],
'alpha-2-code': 'BA',
'alpha-3-code': 'BIH',
'continent': 'Europe',
'name': 'Bosnia and Herzegovina',
'capital': 'Sarajevo'},
{'timezones': ['Asia/Phnom_Penh'],
'alpha-2-code': 'KH',
'alpha-3-code': 'KHM',
'continent': 'Asia',
'name': 'Cambodia',
'capital': 'Phnom Penh'},
{'timezones': ['Africa/Bangui'],
'alpha-2-code': 'CF',
'alpha-3-code': 'CAF',
'continent': 'Africa',
'name': 'Central African Republic',
'capital': 'Bangui'},
{'timezones': ['Africa/Ndjamena'],
'alpha-2-code': 'TD',
'alpha-3-code': 'TCD',
'continent': 'Africa',
'name': 'Chad',
'capital': "N'Djamena"},
{'timezones': ['Indian/Comoro'],
'alpha-2-code': 'KM',
'alpha-3-code': 'COM',
'continent': 'Africa',
'name': 'Comoros',
'capital': 'Moroni'},
{'timezones': ['Europe/Zagreb'],
'alpha-2-code': 'HR',
'alpha-3-code': 'HRV',
'continent': 'Europe',
'name': 'Croatia',
'capital': 'Zagreb'},
{'timezones': ['Asia/Dili'],
'alpha-2-code': 'TL',
'alpha-3-code': 'TLS',
'continent': 'Asia',
'name': 'East Timor',
'capital': 'Dili'},
{'timezones': ['America/El_Salvador'],
'alpha-2-code': 'SV',
'alpha-3-code': 'SLV',
'continent': 'North America',
'name': 'El Salvador',
'capital': 'San Salvador'},
{'timezones': ['Africa/Malabo'],
'alpha-2-code': 'GQ',
'alpha-3-code': 'GNQ',
'continent': 'Africa',
'name': 'Equatorial Guinea',
'capital': 'Malabo'},
{'timezones': ['America/Grenada'],
'alpha-2-code': 'GD',
'alpha-3-code': 'GRD',
'continent': 'North America',
'name': 'Grenada',
'capital': "St. George's"},
{'timezones': ['Asia/Almaty',
'Asia/Qyzylorda',
'Asia/Aqtobe',
'Asia/Aqtau',
'Asia/Oral'],
'alpha-2-code': 'KZ',
'alpha-3-code': 'KAZ',
'continent': 'Asia',
'name': 'Kazakhstan',
'capital': 'Astana'},
{'timezones': ['Asia/Vientiane'],
'alpha-2-code': 'LA',
'alpha-3-code': 'LAO',
'continent': 'Asia',
'name': 'Laos',
'capital': 'Vientiane'},
{'timezones': ['Pacific/Truk',
'Pacific/Ponape',
'Pacific/Kosrae'],
'alpha-2-code': 'FM',
'alpha-3-code': 'FSM',
'continent': 'Oceania',
'name': 'Federated States of Micronesia',
'capital': 'Palikir'},
{'timezones': ['Europe/Chisinau'],
'alpha-2-code': 'MD',
'alpha-3-code': 'MDA',
'continent': 'Europe',
'name': 'Moldova',
'capital': 'Chi\xc5\x9fin\xc4\x83u'},
{'timezones': ['Europe/Monaco'],
'alpha-2-code': 'MC',
'alpha-3-code': 'MCO',
'continent': 'Europe',
'name': 'Monaco',
'capital': 'Monaco'},
{'timezones': ['Europe/Podgorica'],
'alpha-2-code': 'ME',
'alpha-3-code': 'MNE',
'continent': 'Europe',
'name': 'Montenegro',
'capital': 'Podgorica'},
{'timezones': ['Africa/Casablanca'],
'alpha-2-code': 'MA',
'alpha-3-code': 'MAR',
'continent': 'Africa',
'name': 'Morocco',
'capital': 'Rabat'},
{'timezones': ['America/St_Kitts'],
'alpha-2-code': 'KN',
'alpha-3-code': 'KNA',
'continent': 'North America',
'name': 'Saint Kitts and Nevis',
'capital': 'Basseterre'},
{'timezones': ['America/St_Lucia'],
'alpha-2-code': 'LC',
'alpha-3-code': 'LCA',
'continent': 'North America',
'name': 'Saint Lucia',
'capital': 'Castries'},
{'timezones': ['America/St_Vincent'],
'alpha-2-code': 'VC',
'alpha-3-code': 'VCT',
'continent': 'North America',
'name': 'Saint Vincent and the Grenadines',
'capital': 'Kingstown'},
{'timezones': ['Pacific/Apia'],
'alpha-2-code': 'WS',
'alpha-3-code': 'WSM',
'continent': 'Oceania',
'name': 'Samoa',
'capital': 'Apia'},
{'timezones': ['Europe/Belgrade'],
'alpha-2-code': 'RS',
'alpha-3-code': 'SRB',
'continent': 'Europe',
'name': 'Serbia',
'capital': 'Belgrade'},
{'timezones': ['Africa/Johannesburg'],
'alpha-2-code': 'ZA',
'alpha-3-code': 'ZAF',
'continent': 'Africa',
'name': 'South Africa',
'capital': 'Pretoria'},
{'timezones': ['Europe/Madrid',
'Africa/Ceuta',
'Atlantic/Canary'],
'alpha-2-code': 'ES',
'alpha-3-code': 'ESP',
'continent': 'Europe',
'name': 'Spain',
'capital': 'Madrid'},
{'timezones': ['Asia/Colombo'],
'alpha-2-code': 'LK',
'alpha-3-code': 'LKA',
'continent': 'Asia',
'name': 'Sri Lanka',
'capital': 'Sri Jayewardenepura Kotte'},
{'timezones': ['Africa/Mbabane'],
'alpha-2-code': 'SZ',
'alpha-3-code': 'SWZ',
'continent': 'Africa',
'name': 'Swaziland',
'capital': 'Mbabane'},
{'timezones': ['Europe/Zurich'],
'alpha-2-code': 'CH',
'alpha-3-code': 'CHE',
'continent': 'Europe',
'name': 'Switzerland',
'capital': 'Bern'},
{'timezones': ['Asia/Dubai'],
'alpha-2-code': 'AE',
'alpha-3-code': 'ARE',
'continent': 'Asia',
'name': 'United Arab Emirates',
'capital': 'Abu Dhabi'},
{'timezones': ['Europe/London'],
'alpha-2-code': 'GB',
'alpha-3-code': 'GBR',
'continent': 'Europe',
'name': 'United Kingdom',
'capital': 'London'},
]
regex = re.compile(timedelta_pattern)
def unix_time(self, end_datetime=None, start_datetime=None):
"""
Get a timestamp between January 1, 1970 and now, unless passed
explicit start_datetime or end_datetime values.
:example 1061306726
"""
start_datetime = self._parse_start_datetime(start_datetime)
end_datetime = self._parse_end_datetime(end_datetime)
return self.generator.random.randint(start_datetime, end_datetime)
def time_delta(self, end_datetime=None):
"""
Get a timedelta object
"""
start_datetime = self._parse_start_datetime('now')
end_datetime = self._parse_end_datetime(end_datetime)
seconds = end_datetime - start_datetime
ts = self.generator.random.randint(*sorted([0, seconds]))
return timedelta(seconds=ts)
def date_time(self, tzinfo=None, end_datetime=None):
"""
Get a datetime object for a date between January 1, 1970 and now
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('2005-08-16 20:39:21')
:return datetime
"""
# NOTE: On windows, the lowest value you can get from windows is 86400
# on the first day. Known python issue:
# https://bugs.python.org/issue30684
return datetime(1970, 1, 1, tzinfo=tzinfo) + \
timedelta(seconds=self.unix_time(end_datetime=end_datetime))
def date_time_ad(self, tzinfo=None, end_datetime=None, start_datetime=None):
"""
Get a datetime object for a date between January 1, 001 and now
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('1265-03-22 21:15:52')
:return datetime
"""
# 1970-01-01 00:00:00 UTC minus 62135596800 seconds is
# 0001-01-01 00:00:00 UTC. Since _parse_end_datetime() is used
# elsewhere where a default value of 0 is expected, we can't
# simply change that class method to use this magic number as a
# default value when None is provided.
start_time = -62135596800 if start_datetime is None else self._parse_start_datetime(start_datetime)
end_datetime = self._parse_end_datetime(end_datetime)
ts = self.generator.random.randint(start_time, end_datetime)
# NOTE: using datetime.fromtimestamp(ts) directly will raise
# a "ValueError: timestamp out of range for platform time_t"
# on some platforms due to system C functions;
# see http://stackoverflow.com/a/10588133/2315612
# NOTE: On windows, the lowest value you can get from windows is 86400
# on the first day. Known python issue:
# https://bugs.python.org/issue30684
return datetime(1970, 1, 1, tzinfo=tzinfo) + timedelta(seconds=ts)
def iso8601(self, tzinfo=None, end_datetime=None):
"""
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example '2003-10-21T16:05:52+0000'
"""
return self.date_time(tzinfo, end_datetime=end_datetime).isoformat()
def date(self, pattern='%Y-%m-%d', end_datetime=None):
"""
Get a date string between January 1, 1970 and now
:param pattern format
:example '2008-11-27'
"""
return self.date_time(end_datetime=end_datetime).strftime(pattern)
def date_object(self, end_datetime=None):
"""
Get a date object between January 1, 1970 and now
:example datetime.date(2016, 9, 20)
"""
return self.date_time(end_datetime=end_datetime).date()
def time(self, pattern='%H:%M:%S', end_datetime=None):
"""
Get a time string (24h format by default)
:param pattern format
:example '15:02:34'
"""
return self.date_time(
end_datetime=end_datetime).time().strftime(pattern)
def time_object(self, end_datetime=None):
"""
Get a time object
:example datetime.time(15, 56, 56, 772876)
"""
return self.date_time(end_datetime=end_datetime).time()
@classmethod
def _parse_start_datetime(cls, value):
if value is None:
return 0
return cls._parse_date_time(value)
@classmethod
def _parse_end_datetime(cls, value):
if value is None:
return datetime_to_timestamp(datetime.now())
return cls._parse_date_time(value)
@classmethod
def _parse_date_string(cls, value):
parts = cls.regex.match(value)
if not parts:
raise ParseError("Can't parse date string `{}`.".format(value))
parts = parts.groupdict()
time_params = {}
for (name_, param_) in parts.items():
if param_:
time_params[name_] = int(param_)
if 'years' in time_params:
if 'days' not in time_params:
time_params['days'] = 0
time_params['days'] += 365.24 * time_params.pop('years')
if 'months' in time_params:
if 'days' not in time_params:
time_params['days'] = 0
time_params['days'] += 30.42 * time_params.pop('months')
if not time_params:
raise ParseError("Can't parse date string `{}`.".format(value))
return time_params
@classmethod
def _parse_timedelta(cls, value):
if isinstance(value, timedelta):
return value.total_seconds()
if is_string(value):
time_params = cls._parse_date_string(value)
return timedelta(**time_params).total_seconds()
if isinstance(value, (int, float)):
return value
raise ParseError("Invalid format for timedelta '{}'".format(value))
@classmethod
def _parse_date_time(cls, value, tzinfo=None):
if isinstance(value, (datetime, date, real_datetime, real_date)):
return datetime_to_timestamp(value)
now = datetime.now(tzinfo)
if isinstance(value, timedelta):
return datetime_to_timestamp(now + value)
if is_string(value):
if value == 'now':
return datetime_to_timestamp(datetime.now(tzinfo))
time_params = cls._parse_date_string(value)
return datetime_to_timestamp(now + timedelta(**time_params))
if isinstance(value, int):
return datetime_to_timestamp(now + timedelta(value))
raise ParseError("Invalid format for date '{}'".format(value))
@classmethod
def _parse_date(cls, value):
if isinstance(value, (datetime, real_datetime)):
return value.date()
elif isinstance(value, (date, real_date)):
return value
today = date.today()
if isinstance(value, timedelta):
return today + value
if is_string(value):
if value in ('today', 'now'):
return today
time_params = cls._parse_date_string(value)
return today + timedelta(**time_params)
if isinstance(value, int):
return today + timedelta(value)
raise ParseError("Invalid format for date '{}'".format(value))
def date_time_between(self, start_date='-30y', end_date='now', tzinfo=None):
"""
Get a DateTime object based on a random date between two given dates.
Accepts date strings that can be recognized by strtotime().
:param start_date Defaults to 30 years ago
:param end_date Defaults to "now"
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('1999-02-02 11:42:52')
:return DateTime
"""
start_date = self._parse_date_time(start_date, tzinfo=tzinfo)
end_date = self._parse_date_time(end_date, tzinfo=tzinfo)
if end_date - start_date <= 1:
ts = start_date + self.generator.random.random()
else:
ts = self.generator.random.randint(start_date, end_date)
if tzinfo is None:
return datetime(1970, 1, 1, tzinfo=tzinfo) + timedelta(seconds=ts)
else:
return (
datetime(1970, 1, 1, tzinfo=tzutc()) + timedelta(seconds=ts)
).astimezone(tzinfo)
def date_between(self, start_date='-30y', end_date='today'):
"""
Get a Date object based on a random date between two given dates.
Accepts date strings that can be recognized by strtotime().
:param start_date Defaults to 30 years ago
:param end_date Defaults to "today"
:example Date('1999-02-02')
:return Date
"""
start_date = self._parse_date(start_date)
end_date = self._parse_date(end_date)
return self.date_between_dates(date_start=start_date, date_end=end_date)
def future_datetime(self, end_date='+30d', tzinfo=None):
"""
Get a DateTime object based on a random date between 1 second form now
and a given date.
Accepts date strings that can be recognized by strtotime().
:param end_date Defaults to "+30d"
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('1999-02-02 11:42:52')
:return DateTime
"""
return self.date_time_between(
start_date='+1s', end_date=end_date, tzinfo=tzinfo,
)
def future_date(self, end_date='+30d', tzinfo=None):
"""
Get a Date object based on a random date between 1 day from now and a
given date.
Accepts date strings that can be recognized by strtotime().
:param end_date Defaults to "+30d"
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('1999-02-02 11:42:52')
:return DateTime
"""
return self.date_between(start_date='+1d', end_date=end_date)
def past_datetime(self, start_date='-30d', tzinfo=None):
"""
Get a DateTime object based on a random date between a given date and 1
second ago.
Accepts date strings that can be recognized by strtotime().
:param start_date Defaults to "-30d"
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('1999-02-02 11:42:52')
:return DateTime
"""
return self.date_time_between(
start_date=start_date, end_date='-1s', tzinfo=tzinfo,
)
def past_date(self, start_date='-30d', tzinfo=None):
"""
Get a Date object based on a random date between a given date and 1 day
ago.
Accepts date strings that can be recognized by strtotime().
:param start_date Defaults to "-30d"
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('1999-02-02 11:42:52')
:return DateTime
"""
return self.date_between(start_date=start_date, end_date='-1d')
def date_time_between_dates(
self,
datetime_start=None,
datetime_end=None,
tzinfo=None):
"""
Takes two DateTime objects and returns a random datetime between the two
given datetimes.
Accepts DateTime objects.
:param datetime_start: DateTime
:param datetime_end: DateTime
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('1999-02-02 11:42:52')
:return DateTime
"""
if datetime_start is None:
datetime_start = datetime.now(tzinfo)
if datetime_end is None:
datetime_end = datetime.now(tzinfo)
timestamp = self.generator.random.randint(
datetime_to_timestamp(datetime_start),
datetime_to_timestamp(datetime_end),
)
try:
if tzinfo is None:
pick = datetime.fromtimestamp(timestamp, tzlocal())
pick = pick.astimezone(tzutc()).replace(tzinfo=None)
else:
pick = datetime.fromtimestamp(timestamp, tzinfo)
except OverflowError:
raise OverflowError(
"You specified an end date with a timestamp bigger than the maximum allowed on this"
" system. Please specify an earlier date.",
)
return pick
def date_between_dates(self, date_start=None, date_end=None):
"""
Takes two Date objects and returns a random date between the two given dates.
Accepts Date or Datetime objects
:param date_start: Date
:param date_end: Date
:return Date
"""
return self.date_time_between_dates(date_start, date_end).date()
def date_time_this_century(
self,
before_now=True,
after_now=False,
tzinfo=None):
"""
Gets a DateTime object for the current century.
:param before_now: include days in current century before today
:param after_now: include days in current century after today
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('2012-04-04 11:02:02')
:return DateTime
"""
now = datetime.now(tzinfo)
this_century_start = datetime(
now.year - (now.year % 100), 1, 1, tzinfo=tzinfo)
next_century_start = datetime(
min(this_century_start.year + 100, MAXYEAR), 1, 1, tzinfo=tzinfo)
if before_now and after_now:
return self.date_time_between_dates(
this_century_start, next_century_start, tzinfo)
elif not before_now and after_now:
return self.date_time_between_dates(now, next_century_start, tzinfo)
elif not after_now and before_now:
return self.date_time_between_dates(this_century_start, now, tzinfo)
else:
return now
def date_time_this_decade(
self,
before_now=True,
after_now=False,
tzinfo=None):
"""
Gets a DateTime object for the decade year.
:param before_now: include days in current decade before today
:param after_now: include days in current decade after today
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('2012-04-04 11:02:02')
:return DateTime
"""
now = datetime.now(tzinfo)
this_decade_start = datetime(
now.year - (now.year % 10), 1, 1, tzinfo=tzinfo)
next_decade_start = datetime(
min(this_decade_start.year + 10, MAXYEAR), 1, 1, tzinfo=tzinfo)
if before_now and after_now:
return self.date_time_between_dates(
this_decade_start, next_decade_start, tzinfo)
elif not before_now and after_now:
return self.date_time_between_dates(now, next_decade_start, tzinfo)
elif not after_now and before_now:
return self.date_time_between_dates(this_decade_start, now, tzinfo)
else:
return now
def date_time_this_year(
self,
before_now=True,
after_now=False,
tzinfo=None):
"""
Gets a DateTime object for the current year.
:param before_now: include days in current year before today
:param after_now: include days in current year after today
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('2012-04-04 11:02:02')
:return DateTime
"""
now = datetime.now(tzinfo)
this_year_start = now.replace(
month=1, day=1, hour=0, minute=0, second=0, microsecond=0)
next_year_start = datetime(now.year + 1, 1, 1, tzinfo=tzinfo)
if before_now and after_now:
return self.date_time_between_dates(
this_year_start, next_year_start, tzinfo)
elif not before_now and after_now:
return self.date_time_between_dates(now, next_year_start, tzinfo)
elif not after_now and before_now:
return self.date_time_between_dates(this_year_start, now, tzinfo)
else:
return now
def date_time_this_month(
self,
before_now=True,
after_now=False,
tzinfo=None):
"""
Gets a DateTime object for the current month.
:param before_now: include days in current month before today
:param after_now: include days in current month after today
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('2012-04-04 11:02:02')
:return DateTime
"""
now = datetime.now(tzinfo)
this_month_start = now.replace(
day=1, hour=0, minute=0, second=0, microsecond=0)
next_month_start = this_month_start + \
relativedelta.relativedelta(months=1)
if before_now and after_now:
return self.date_time_between_dates(
this_month_start, next_month_start, tzinfo)
elif not before_now and after_now:
return self.date_time_between_dates(now, next_month_start, tzinfo)
elif not after_now and before_now:
return self.date_time_between_dates(this_month_start, now, tzinfo)
else:
return now
def date_this_century(self, before_today=True, after_today=False):
"""
Gets a Date object for the current century.
:param before_today: include days in current century before today
:param after_today: include days in current century after today
:example Date('2012-04-04')
:return Date
"""
today = date.today()
this_century_start = date(today.year - (today.year % 100), 1, 1)
next_century_start = date(this_century_start.year + 100, 1, 1)
if before_today and after_today:
return self.date_between_dates(
this_century_start, next_century_start)
elif not before_today and after_today:
return self.date_between_dates(today, next_century_start)
elif not after_today and before_today:
return self.date_between_dates(this_century_start, today)
else:
return today
def date_this_decade(self, before_today=True, after_today=False):
"""
Gets a Date object for the decade year.
:param before_today: include days in current decade before today
:param after_today: include days in current decade after today
:example Date('2012-04-04')
:return Date
"""
today = date.today()
this_decade_start = date(today.year - (today.year % 10), 1, 1)
next_decade_start = date(this_decade_start.year + 10, 1, 1)
if before_today and after_today:
return self.date_between_dates(this_decade_start, next_decade_start)
elif not before_today and after_today:
return self.date_between_dates(today, next_decade_start)
elif not after_today and before_today:
return self.date_between_dates(this_decade_start, today)
else:
return today
def date_this_year(self, before_today=True, after_today=False):
"""
Gets a Date object for the current year.
:param before_today: include days in current year before today
:param after_today: include days in current year after today
:example Date('2012-04-04')
:return Date
"""
today = date.today()
this_year_start = today.replace(month=1, day=1)
next_year_start = date(today.year + 1, 1, 1)
if before_today and after_today:
return self.date_between_dates(this_year_start, next_year_start)
elif not before_today and after_today:
return self.date_between_dates(today, next_year_start)
elif not after_today and before_today:
return self.date_between_dates(this_year_start, today)
else:
return today
def date_this_month(self, before_today=True, after_today=False):
"""
Gets a Date object for the current month.
:param before_today: include days in current month before today
:param after_today: include days in current month after today
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('2012-04-04 11:02:02')
:return DateTime
"""
today = date.today()
this_month_start = today.replace(day=1)
next_month_start = this_month_start + \
relativedelta.relativedelta(months=1)
if before_today and after_today:
return self.date_between_dates(this_month_start, next_month_start)
elif not before_today and after_today:
return self.date_between_dates(today, next_month_start)
elif not after_today and before_today:
return self.date_between_dates(this_month_start, today)
else:
return today
def time_series(
self,
start_date='-30d',
end_date='now',
precision=None,
distrib=None,
tzinfo=None):
"""
Returns a generator yielding tuples of ``(<datetime>, <value>)``.
The data points will start at ``start_date``, and be at every time interval specified by
``precision``.
``distrib`` is a callable that accepts ``<datetime>`` and returns ``<value>``
"""
start_date = self._parse_date_time(start_date, tzinfo=tzinfo)
end_date = self._parse_date_time(end_date, tzinfo=tzinfo)
if end_date < start_date:
raise ValueError("`end_date` must be greater than `start_date`.")
if precision is None:
precision = (end_date - start_date) / 30
precision = self._parse_timedelta(precision)
if distrib is None:
def distrib(dt): return self.generator.random.uniform(0, precision) # noqa
if not callable(distrib):
raise ValueError(
"`distrib` must be a callable. Got {} instead.".format(distrib))
datapoint = start_date
while datapoint < end_date:
dt = timestamp_to_datetime(datapoint, tzinfo)
datapoint += precision
yield (dt, distrib(dt))
def am_pm(self):
return self.date('%p')
def day_of_month(self):
return self.date('%d')
def day_of_week(self):
return self.date('%A')
def month(self):
return self.date('%m')
def month_name(self):
return self.date('%B')
def year(self):
return self.date('%Y')
def century(self):
"""
:example 'XVII'
"""
return self.random_element(self.centuries)
def timezone(self):
return self.generator.random.choice(
self.random_element(self.countries)['timezones'])
def date_of_birth(self, tzinfo=None, minimum_age=0, maximum_age=115):
"""
Generate a random date of birth represented as a Date object,
constrained by optional miminimum_age and maximum_age
parameters.
:param tzinfo Defaults to None.
:param minimum_age Defaults to 0.
:param maximum_age Defaults to 115.
:example Date('1979-02-02')
:return Date
"""
if not isinstance(minimum_age, int):
raise TypeError("minimum_age must be an integer.")
if not isinstance(maximum_age, int):
raise TypeError("maximum_age must be an integer.")
if (maximum_age < 0):
raise ValueError("maximum_age must be greater than or equal to zero.")
if (minimum_age < 0):
raise ValueError("minimum_age must be greater than or equal to zero.")
if (minimum_age > maximum_age):
raise ValueError("minimum_age must be less than or equal to maximum_age.")
# In order to return the full range of possible dates of birth, add one
# year to the potential age cap and subtract one day if we land on the
# boundary.
now = datetime.now(tzinfo).date()
start_date = now.replace(year=now.year - (maximum_age+1))
end_date = now.replace(year=now.year - minimum_age)
dob = self.date_time_ad(tzinfo=tzinfo, start_datetime=start_date, end_datetime=end_date).date()
return dob if dob != start_date else dob + timedelta(days=1) | frappe-bench/env/lib/python2.7/site-packages/faker/providers/date_time/__init__.py |
from __future__ import unicode_literals
import re
from calendar import timegm
from datetime import MAXYEAR, timedelta
from dateutil import relativedelta
from dateutil.tz import tzlocal, tzutc
from faker.utils import is_string
from faker.utils.datetime_safe import date, datetime, real_date, real_datetime
from .. import BaseProvider
localized = True
def datetime_to_timestamp(dt):
if getattr(dt, 'tzinfo', None) is not None:
dt = dt.astimezone(tzutc())
return timegm(dt.timetuple())
def timestamp_to_datetime(timestamp, tzinfo):
if tzinfo is None:
pick = datetime.fromtimestamp(timestamp, tzlocal())
pick = pick.astimezone(tzutc()).replace(tzinfo=None)
else:
pick = datetime.fromtimestamp(timestamp, tzinfo)
return pick
class ParseError(ValueError):
pass
timedelta_pattern = r''
for name, sym in [('years', 'y'), ('months', 'M'), ('weeks', 'w'), ('days', 'd'),
('hours', 'h'), ('minutes', 'm'), ('seconds', 's')]:
timedelta_pattern += r'((?P<{}>(?:\+|-)\d+?){})?'.format(name, sym)
class Provider(BaseProvider):
centuries = [
'I',
'II',
'III',
'IV',
'V',
'VI',
'VII',
'VIII',
'IX',
'X',
'XI',
'XII',
'XIII',
'XIV',
'XV',
'XVI',
'XVII',
'XVIII',
'XIX',
'XX',
'XXI']
countries = [{'timezones': ['Europe/Andorra'],
'alpha-2-code': 'AD',
'alpha-3-code': 'AND',
'continent': 'Europe',
'name': 'Andorra',
'capital': 'Andorra la Vella'},
{'timezones': ['Asia/Kabul'],
'alpha-2-code': 'AF',
'alpha-3-code': 'AFG',
'continent': 'Asia',
'name': 'Afghanistan',
'capital': 'Kabul'},
{'timezones': ['America/Antigua'],
'alpha-2-code': 'AG',
'alpha-3-code': 'ATG',
'continent': 'North America',
'name': 'Antigua and Barbuda',
'capital': "St. John's"},
{'timezones': ['Europe/Tirane'],
'alpha-2-code': 'AL',
'alpha-3-code': 'ALB',
'continent': 'Europe',
'name': 'Albania',
'capital': 'Tirana'},
{'timezones': ['Asia/Yerevan'],
'alpha-2-code': 'AM',
'alpha-3-code': 'ARM',
'continent': 'Asia',
'name': 'Armenia',
'capital': 'Yerevan'},
{'timezones': ['Africa/Luanda'],
'alpha-2-code': 'AO',
'alpha-3-code': 'AGO',
'continent': 'Africa',
'name': 'Angola',
'capital': 'Luanda'},
{'timezones': ['America/Argentina/Buenos_Aires',
'America/Argentina/Cordoba',
'America/Argentina/Jujuy',
'America/Argentina/Tucuman',
'America/Argentina/Catamarca',
'America/Argentina/La_Rioja',
'America/Argentina/San_Juan',
'America/Argentina/Mendoza',
'America/Argentina/Rio_Gallegos',
'America/Argentina/Ushuaia'],
'alpha-2-code': 'AR',
'alpha-3-code': 'ARG',
'continent': 'South America',
'name': 'Argentina',
'capital': 'Buenos Aires'},
{'timezones': ['Europe/Vienna'],
'alpha-2-code': 'AT',
'alpha-3-code': 'AUT',
'continent': 'Europe',
'name': 'Austria',
'capital': 'Vienna'},
{'timezones': ['Australia/Lord_Howe',
'Australia/Hobart',
'Australia/Currie',
'Australia/Melbourne',
'Australia/Sydney',
'Australia/Broken_Hill',
'Australia/Brisbane',
'Australia/Lindeman',
'Australia/Adelaide',
'Australia/Darwin',
'Australia/Perth'],
'alpha-2-code': 'AU',
'alpha-3-code': 'AUS',
'continent': 'Oceania',
'name': 'Australia',
'capital': 'Canberra'},
{'timezones': ['Asia/Baku'],
'alpha-2-code': 'AZ',
'alpha-3-code': 'AZE',
'continent': 'Asia',
'name': 'Azerbaijan',
'capital': 'Baku'},
{'timezones': ['America/Barbados'],
'alpha-2-code': 'BB',
'alpha-3-code': 'BRB',
'continent': 'North America',
'name': 'Barbados',
'capital': 'Bridgetown'},
{'timezones': ['Asia/Dhaka'],
'alpha-2-code': 'BD',
'alpha-3-code': 'BGD',
'continent': 'Asia',
'name': 'Bangladesh',
'capital': 'Dhaka'},
{'timezones': ['Europe/Brussels'],
'alpha-2-code': 'BE',
'alpha-3-code': 'BEL',
'continent': 'Europe',
'name': 'Belgium',
'capital': 'Brussels'},
{'timezones': ['Africa/Ouagadougou'],
'alpha-2-code': 'BF',
'alpha-3-code': 'BFA',
'continent': 'Africa',
'name': 'Burkina Faso',
'capital': 'Ouagadougou'},
{'timezones': ['Europe/Sofia'],
'alpha-2-code': 'BG',
'alpha-3-code': 'BGR',
'continent': 'Europe',
'name': 'Bulgaria',
'capital': 'Sofia'},
{'timezones': ['Asia/Bahrain'],
'alpha-2-code': 'BH',
'alpha-3-code': 'BHR',
'continent': 'Asia',
'name': 'Bahrain',
'capital': 'Manama'},
{'timezones': ['Africa/Bujumbura'],
'alpha-2-code': 'BI',
'alpha-3-code': 'BDI',
'continent': 'Africa',
'name': 'Burundi',
'capital': 'Bujumbura'},
{'timezones': ['Africa/Porto-Novo'],
'alpha-2-code': 'BJ',
'alpha-3-code': 'BEN',
'continent': 'Africa',
'name': 'Benin',
'capital': 'Porto-Novo'},
{'timezones': ['Asia/Brunei'],
'alpha-2-code': 'BN',
'alpha-3-code': 'BRN',
'continent': 'Asia',
'name': '<NAME>',
'capital': 'Bandar Seri Begawan'},
{'timezones': ['America/La_Paz'],
'alpha-2-code': 'BO',
'alpha-3-code': 'BOL',
'continent': 'South America',
'name': 'Bolivia',
'capital': 'Sucre'},
{'timezones': ['America/Noronha',
'America/Belem',
'America/Fortaleza',
'America/Recife',
'America/Araguaina',
'America/Maceio',
'America/Bahia',
'America/Sao_Paulo',
'America/Campo_Grande',
'America/Cuiaba',
'America/Porto_Velho',
'America/Boa_Vista',
'America/Manaus',
'America/Eirunepe',
'America/Rio_Branco'],
'alpha-2-code': 'BR',
'alpha-3-code': 'BRA',
'continent': 'South America',
'name': 'Brazil',
'capital': 'Bras\xc3\xadlia'},
{'timezones': ['America/Nassau'],
'alpha-2-code': 'BS',
'alpha-3-code': 'BHS',
'continent': 'North America',
'name': 'Bahamas',
'capital': 'Nassau'},
{'timezones': ['Asia/Thimphu'],
'alpha-2-code': 'BT',
'alpha-3-code': 'BTN',
'continent': 'Asia',
'name': 'Bhutan',
'capital': 'Thimphu'},
{'timezones': ['Africa/Gaborone'],
'alpha-2-code': 'BW',
'alpha-3-code': 'BWA',
'continent': 'Africa',
'name': 'Botswana',
'capital': 'Gaborone'},
{'timezones': ['Europe/Minsk'],
'alpha-2-code': 'BY',
'alpha-3-code': 'BLR',
'continent': 'Europe',
'name': 'Belarus',
'capital': 'Minsk'},
{'timezones': ['America/Belize'],
'alpha-2-code': 'BZ',
'alpha-3-code': 'BLZ',
'continent': 'North America',
'name': 'Belize',
'capital': 'Belmopan'},
{'timezones': ['America/St_Johns',
'America/Halifax',
'America/Glace_Bay',
'America/Moncton',
'America/Goose_Bay',
'America/Blanc-Sablon',
'America/Montreal',
'America/Toronto',
'America/Nipigon',
'America/Thunder_Bay',
'America/Pangnirtung',
'America/Iqaluit',
'America/Atikokan',
'America/Rankin_Inlet',
'America/Winnipeg',
'America/Rainy_River',
'America/Cambridge_Bay',
'America/Regina',
'America/Swift_Current',
'America/Edmonton',
'America/Yellowknife',
'America/Inuvik',
'America/Dawson_Creek',
'America/Vancouver',
'America/Whitehorse',
'America/Dawson'],
'alpha-2-code': 'CA',
'alpha-3-code': 'CAN',
'continent': 'North America',
'name': 'Canada',
'capital': 'Ottawa'},
{'timezones': ['Africa/Kinshasa',
'Africa/Lubumbashi'],
'alpha-2-code': 'CD',
'alpha-3-code': 'COD',
'continent': 'Africa',
'name': 'Democratic Republic of the Congo',
'capital': 'Kinshasa'},
{'timezones': ['Africa/Brazzaville'],
'alpha-2-code': 'CG',
'alpha-3-code': 'COG',
'continent': 'Africa',
'name': 'Republic of the Congo',
'capital': 'Brazzaville'},
{'timezones': ['Africa/Abidjan'],
'alpha-2-code': 'CI',
'alpha-3-code': 'CIV',
'continent': 'Africa',
'name': "C\xc3\xb4te d'Ivoire",
'capital': 'Yamoussoukro'},
{'timezones': ['America/Santiago',
'Pacific/Easter'],
'alpha-2-code': 'CL',
'alpha-3-code': 'CHL',
'continent': 'South America',
'name': 'Chile',
'capital': 'Santiago'},
{'timezones': ['Africa/Douala'],
'alpha-2-code': 'CM',
'alpha-3-code': 'CMR',
'continent': 'Africa',
'name': 'Cameroon',
'capital': 'Yaound\xc3\xa9'},
{'timezones': ['Asia/Shanghai',
'Asia/Harbin',
'Asia/Chongqing',
'Asia/Urumqi',
'Asia/Kashgar'],
'alpha-2-code': 'CN',
'alpha-3-code': 'CHN',
'continent': 'Asia',
'name': "People's Republic of China",
'capital': 'Beijing'},
{'timezones': ['America/Bogota'],
'alpha-2-code': 'CO',
'alpha-3-code': 'COL',
'continent': 'South America',
'name': 'Colombia',
'capital': 'Bogot\xc3\xa1'},
{'timezones': ['America/Costa_Rica'],
'alpha-2-code': 'CR',
'alpha-3-code': 'CRI',
'continent': 'North America',
'name': 'Costa Rica',
'capital': 'San Jos\xc3\xa9'},
{'timezones': ['America/Havana'],
'alpha-2-code': 'CU',
'alpha-3-code': 'CUB',
'continent': 'North America',
'name': 'Cuba',
'capital': 'Havana'},
{'timezones': ['Atlantic/Cape_Verde'],
'alpha-2-code': 'CV',
'alpha-3-code': 'CPV',
'continent': 'Africa',
'name': 'Cape Verde',
'capital': 'Praia'},
{'timezones': ['Asia/Nicosia'],
'alpha-2-code': 'CY',
'alpha-3-code': 'CYP',
'continent': 'Asia',
'name': 'Cyprus',
'capital': 'Nicosia'},
{'timezones': ['Europe/Prague'],
'alpha-2-code': 'CZ',
'alpha-3-code': 'CZE',
'continent': 'Europe',
'name': 'Czech Republic',
'capital': 'Prague'},
{'timezones': ['Europe/Berlin'],
'alpha-2-code': 'DE',
'alpha-3-code': 'DEU',
'continent': 'Europe',
'name': 'Germany',
'capital': 'Berlin'},
{'timezones': ['Africa/Djibouti'],
'alpha-2-code': 'DJ',
'alpha-3-code': 'DJI',
'continent': 'Africa',
'name': 'Djibouti',
'capital': 'Djibouti City'},
{'timezones': ['Europe/Copenhagen'],
'alpha-2-code': 'DK',
'alpha-3-code': 'DNK',
'continent': 'Europe',
'name': 'Denmark',
'capital': 'Copenhagen'},
{'timezones': ['America/Dominica'],
'alpha-2-code': 'DM',
'alpha-3-code': 'DMA',
'continent': 'North America',
'name': 'Dominica',
'capital': 'Roseau'},
{'timezones': ['America/Santo_Domingo'],
'alpha-2-code': 'DO',
'alpha-3-code': 'DOM',
'continent': 'North America',
'name': 'Dominican Republic',
'capital': 'Santo Domingo'},
{'timezones': ['America/Guayaquil',
'Pacific/Galapagos'],
'alpha-2-code': 'EC',
'alpha-3-code': 'ECU',
'continent': 'South America',
'name': 'Ecuador',
'capital': 'Quito'},
{'timezones': ['Europe/Tallinn'],
'alpha-2-code': 'EE',
'alpha-3-code': 'EST',
'continent': 'Europe',
'name': 'Estonia',
'capital': 'Tallinn'},
{'timezones': ['Africa/Cairo'],
'alpha-2-code': 'EG',
'alpha-3-code': 'EGY',
'continent': 'Africa',
'name': 'Egypt',
'capital': 'Cairo'},
{'timezones': ['Africa/Asmera'],
'alpha-2-code': 'ER',
'alpha-3-code': 'ERI',
'continent': 'Africa',
'name': 'Eritrea',
'capital': 'Asmara'},
{'timezones': ['Africa/Addis_Ababa'],
'alpha-2-code': 'ET',
'alpha-3-code': 'ETH',
'continent': 'Africa',
'name': 'Ethiopia',
'capital': 'Addis Ababa'},
{'timezones': ['Europe/Helsinki'],
'alpha-2-code': 'FI',
'alpha-3-code': 'FIN',
'continent': 'Europe',
'name': 'Finland',
'capital': 'Helsinki'},
{'timezones': ['Pacific/Fiji'],
'alpha-2-code': 'FJ',
'alpha-3-code': 'FJI',
'continent': 'Oceania',
'name': 'Fiji',
'capital': 'Suva'},
{'timezones': ['Europe/Paris'],
'alpha-2-code': 'FR',
'alpha-3-code': 'FRA',
'continent': 'Europe',
'name': 'France',
'capital': 'Paris'},
{'timezones': ['Africa/Libreville'],
'alpha-2-code': 'GA',
'alpha-3-code': 'GAB',
'continent': 'Africa',
'name': 'Gabon',
'capital': 'Libreville'},
{'timezones': ['Asia/Tbilisi'],
'alpha-2-code': 'GE',
'alpha-3-code': 'GEO',
'continent': 'Asia',
'name': 'Georgia',
'capital': 'Tbilisi'},
{'timezones': ['Africa/Accra'],
'alpha-2-code': 'GH',
'alpha-3-code': 'GHA',
'continent': 'Africa',
'name': 'Ghana',
'capital': 'Accra'},
{'timezones': ['Africa/Banjul'],
'alpha-2-code': 'GM',
'alpha-3-code': 'GMB',
'continent': 'Africa',
'name': 'The Gambia',
'capital': 'Banjul'},
{'timezones': ['Africa/Conakry'],
'alpha-2-code': 'GN',
'alpha-3-code': 'GIN',
'continent': 'Africa',
'name': 'Guinea',
'capital': 'Conakry'},
{'timezones': ['Europe/Athens'],
'alpha-2-code': 'GR',
'alpha-3-code': 'GRC',
'continent': 'Europe',
'name': 'Greece',
'capital': 'Athens'},
{'timezones': ['America/Guatemala'],
'alpha-2-code': 'GT',
'alpha-3-code': 'GTM',
'continent': 'North America',
'name': 'Guatemala',
'capital': 'Guatemala City'},
{'timezones': ['America/Guatemala'],
'alpha-2-code': 'HT',
'alpha-3-code': 'HTI',
'continent': 'North America',
'name': 'Haiti',
'capital': 'Port-au-Prince'},
{'timezones': ['Africa/Bissau'],
'alpha-2-code': 'GW',
'alpha-3-code': 'GNB',
'continent': 'Africa',
'name': 'Guinea-Bissau',
'capital': 'Bissau'},
{'timezones': ['America/Guyana'],
'alpha-2-code': 'GY',
'alpha-3-code': 'GUY',
'continent': 'South America',
'name': 'Guyana',
'capital': 'Georgetown'},
{'timezones': ['America/Tegucigalpa'],
'alpha-2-code': 'HN',
'alpha-3-code': 'HND',
'continent': 'North America',
'name': 'Honduras',
'capital': 'Tegucigalpa'},
{'timezones': ['Europe/Budapest'],
'alpha-2-code': 'HU',
'alpha-3-code': 'HUN',
'continent': 'Europe',
'name': 'Hungary',
'capital': 'Budapest'},
{'timezones': ['Asia/Jakarta',
'Asia/Pontianak',
'Asia/Makassar',
'Asia/Jayapura'],
'alpha-2-code': 'ID',
'alpha-3-code': 'IDN',
'continent': 'Asia',
'name': 'Indonesia',
'capital': 'Jakarta'},
{'timezones': ['Europe/Dublin'],
'alpha-2-code': 'IE',
'alpha-3-code': 'IRL',
'continent': 'Europe',
'name': 'Republic of Ireland',
'capital': 'Dublin'},
{'timezones': ['Asia/Jerusalem'],
'alpha-2-code': 'IL',
'alpha-3-code': 'ISR',
'continent': 'Asia',
'name': 'Israel',
'capital': 'Jerusalem'},
{'timezones': ['Asia/Calcutta'],
'alpha-2-code': 'IN',
'alpha-3-code': 'IND',
'continent': 'Asia',
'name': 'India',
'capital': 'New Delhi'},
{'timezones': ['Asia/Baghdad'],
'alpha-2-code': 'IQ',
'alpha-3-code': 'IRQ',
'continent': 'Asia',
'name': 'Iraq',
'capital': 'Baghdad'},
{'timezones': ['Asia/Tehran'],
'alpha-2-code': 'IR',
'alpha-3-code': 'IRN',
'continent': 'Asia',
'name': 'Iran',
'capital': 'Tehran'},
{'timezones': ['Atlantic/Reykjavik'],
'alpha-2-code': 'IS',
'alpha-3-code': 'ISL',
'continent': 'Europe',
'name': 'Iceland',
'capital': 'Reykjav\xc3\xadk'},
{'timezones': ['Europe/Rome'],
'alpha-2-code': 'IT',
'alpha-3-code': 'ITA',
'continent': 'Europe',
'name': 'Italy',
'capital': 'Rome'},
{'timezones': ['America/Jamaica'],
'alpha-2-code': 'JM',
'alpha-3-code': 'JAM',
'continent': 'North America',
'name': 'Jamaica',
'capital': 'Kingston'},
{'timezones': ['Asia/Amman'],
'alpha-2-code': 'JO',
'alpha-3-code': 'JOR',
'continent': 'Asia',
'name': 'Jordan',
'capital': 'Amman'},
{'timezones': ['Asia/Tokyo'],
'alpha-2-code': 'JP',
'alpha-3-code': 'JPN',
'continent': 'Asia',
'name': 'Japan',
'capital': 'Tokyo'},
{'timezones': ['Africa/Nairobi'],
'alpha-2-code': 'KE',
'alpha-3-code': 'KEN',
'continent': 'Africa',
'name': 'Kenya',
'capital': 'Nairobi'},
{'timezones': ['Asia/Bishkek'],
'alpha-2-code': 'KG',
'alpha-3-code': 'KGZ',
'continent': 'Asia',
'name': 'Kyrgyzstan',
'capital': 'Bishkek'},
{'timezones': ['Pacific/Tarawa',
'Pacific/Enderbury',
'Pacific/Kiritimati'],
'alpha-2-code': 'KI',
'alpha-3-code': 'KIR',
'continent': 'Oceania',
'name': 'Kiribati',
'capital': 'Tarawa'},
{'timezones': ['Asia/Pyongyang'],
'alpha-2-code': 'KP',
'alpha-3-code': 'PRK',
'continent': 'Asia',
'name': 'North Korea',
'capital': 'Pyongyang'},
{'timezones': ['Asia/Seoul'],
'alpha-2-code': 'KR',
'alpha-3-code': 'KOR',
'continent': 'Asia',
'name': 'South Korea',
'capital': 'Seoul'},
{'timezones': ['Asia/Kuwait'],
'alpha-2-code': 'KW',
'alpha-3-code': 'KWT',
'continent': 'Asia',
'name': 'Kuwait',
'capital': 'Kuwait City'},
{'timezones': ['Asia/Beirut'],
'alpha-2-code': 'LB',
'alpha-3-code': 'LBN',
'continent': 'Asia',
'name': 'Lebanon',
'capital': 'Beirut'},
{'timezones': ['Europe/Vaduz'],
'alpha-2-code': 'LI',
'alpha-3-code': 'LIE',
'continent': 'Europe',
'name': 'Liechtenstein',
'capital': 'Vaduz'},
{'timezones': ['Africa/Monrovia'],
'alpha-2-code': 'LR',
'alpha-3-code': 'LBR',
'continent': 'Africa',
'name': 'Liberia',
'capital': 'Monrovia'},
{'timezones': ['Africa/Maseru'],
'alpha-2-code': 'LS',
'alpha-3-code': 'LSO',
'continent': 'Africa',
'name': 'Lesotho',
'capital': 'Maseru'},
{'timezones': ['Europe/Vilnius'],
'alpha-2-code': 'LT',
'alpha-3-code': 'LTU',
'continent': 'Europe',
'name': 'Lithuania',
'capital': 'Vilnius'},
{'timezones': ['Europe/Luxembourg'],
'alpha-2-code': 'LU',
'alpha-3-code': 'LUX',
'continent': 'Europe',
'name': 'Luxembourg',
'capital': 'Luxembourg City'},
{'timezones': ['Europe/Riga'],
'alpha-2-code': 'LV',
'alpha-3-code': 'LVA',
'continent': 'Europe',
'name': 'Latvia',
'capital': 'Riga'},
{'timezones': ['Africa/Tripoli'],
'alpha-2-code': 'LY',
'alpha-3-code': 'LBY',
'continent': 'Africa',
'name': 'Libya',
'capital': 'Tripoli'},
{'timezones': ['Indian/Antananarivo'],
'alpha-2-code': 'MG',
'alpha-3-code': 'MDG',
'continent': 'Africa',
'name': 'Madagascar',
'capital': 'Antananarivo'},
{'timezones': ['Pacific/Majuro',
'Pacific/Kwajalein'],
'alpha-2-code': 'MH',
'alpha-3-code': 'MHL',
'continent': 'Oceania',
'name': 'Marshall Islands',
'capital': 'Majuro'},
{'timezones': ['Europe/Skopje'],
'alpha-2-code': 'MK',
'alpha-3-code': 'MKD',
'continent': 'Europe',
'name': 'Macedonia',
'capital': 'Skopje'},
{'timezones': ['Africa/Bamako'],
'alpha-2-code': 'ML',
'alpha-3-code': 'MLI',
'continent': 'Africa',
'name': 'Mali',
'capital': 'Bamako'},
{'timezones': ['Asia/Rangoon'],
'alpha-2-code': 'MM',
'alpha-3-code': 'MMR',
'continent': 'Asia',
'name': 'Myanmar',
'capital': 'Naypyidaw'},
{'timezones': ['Asia/Ulaanbaatar',
'Asia/Hovd',
'Asia/Choibalsan'],
'alpha-2-code': 'MN',
'alpha-3-code': 'MNG',
'continent': 'Asia',
'name': 'Mongolia',
'capital': 'Ulaanbaatar'},
{'timezones': ['Africa/Nouakchott'],
'alpha-2-code': 'MR',
'alpha-3-code': 'MRT',
'continent': 'Africa',
'name': 'Mauritania',
'capital': 'Nouakchott'},
{'timezones': ['Europe/Malta'],
'alpha-2-code': 'MT',
'alpha-3-code': 'MLT',
'continent': 'Europe',
'name': 'Malta',
'capital': 'Valletta'},
{'timezones': ['Indian/Mauritius'],
'alpha-2-code': 'MU',
'alpha-3-code': 'MUS',
'continent': 'Africa',
'name': 'Mauritius',
'capital': 'Port Louis'},
{'timezones': ['Indian/Maldives'],
'alpha-2-code': 'MV',
'alpha-3-code': 'MDV',
'continent': 'Asia',
'name': 'Maldives',
'capital': 'Mal\xc3\xa9'},
{'timezones': ['Africa/Blantyre'],
'alpha-2-code': 'MW',
'alpha-3-code': 'MWI',
'continent': 'Africa',
'name': 'Malawi',
'capital': 'Lilongwe'},
{'timezones': ['America/Mexico_City',
'America/Cancun',
'America/Merida',
'America/Monterrey',
'America/Mazatlan',
'America/Chihuahua',
'America/Hermosillo',
'America/Tijuana'],
'alpha-2-code': 'MX',
'alpha-3-code': 'MEX',
'continent': 'North America',
'name': 'Mexico',
'capital': 'Mexico City'},
{'timezones': ['Asia/Kuala_Lumpur',
'Asia/Kuching'],
'alpha-2-code': 'MY',
'alpha-3-code': 'MYS',
'continent': 'Asia',
'name': 'Malaysia',
'capital': 'Kuala Lumpur'},
{'timezones': ['Africa/Maputo'],
'alpha-2-code': 'MZ',
'alpha-3-code': 'MOZ',
'continent': 'Africa',
'name': 'Mozambique',
'capital': 'Maputo'},
{'timezones': ['Africa/Windhoek'],
'alpha-2-code': 'NA',
'alpha-3-code': 'NAM',
'continent': 'Africa',
'name': 'Namibia',
'capital': 'Windhoek'},
{'timezones': ['Africa/Niamey'],
'alpha-2-code': 'NE',
'alpha-3-code': 'NER',
'continent': 'Africa',
'name': 'Niger',
'capital': 'Niamey'},
{'timezones': ['Africa/Lagos'],
'alpha-2-code': 'NG',
'alpha-3-code': 'NGA',
'continent': 'Africa',
'name': 'Nigeria',
'capital': 'Abuja'},
{'timezones': ['America/Managua'],
'alpha-2-code': 'NI',
'alpha-3-code': 'NIC',
'continent': 'North America',
'name': 'Nicaragua',
'capital': 'Managua'},
{'timezones': ['Europe/Amsterdam'],
'alpha-2-code': 'NL',
'alpha-3-code': 'NLD',
'continent': 'Europe',
'name': 'Kingdom of the Netherlands',
'capital': 'Amsterdam'},
{'timezones': ['Europe/Oslo'],
'alpha-2-code': 'NO',
'alpha-3-code': 'NOR',
'continent': 'Europe',
'name': 'Norway',
'capital': 'Oslo'},
{'timezones': ['Asia/Katmandu'],
'alpha-2-code': 'NP',
'alpha-3-code': 'NPL',
'continent': 'Asia',
'name': 'Nepal',
'capital': 'Kathmandu'},
{'timezones': ['Pacific/Nauru'],
'alpha-2-code': 'NR',
'alpha-3-code': 'NRU',
'continent': 'Oceania',
'name': 'Nauru',
'capital': 'Yaren'},
{'timezones': ['Pacific/Auckland',
'Pacific/Chatham'],
'alpha-2-code': 'NZ',
'alpha-3-code': 'NZL',
'continent': 'Oceania',
'name': 'New Zealand',
'capital': 'Wellington'},
{'timezones': ['Asia/Muscat'],
'alpha-2-code': 'OM',
'alpha-3-code': 'OMN',
'continent': 'Asia',
'name': 'Oman',
'capital': 'Muscat'},
{'timezones': ['America/Panama'],
'alpha-2-code': 'PA',
'alpha-3-code': 'PAN',
'continent': 'North America',
'name': 'Panama',
'capital': 'Panama City'},
{'timezones': ['America/Lima'],
'alpha-2-code': 'PE',
'alpha-3-code': 'PER',
'continent': 'South America',
'name': 'Peru',
'capital': 'Lima'},
{'timezones': ['Pacific/Port_Moresby'],
'alpha-2-code': 'PG',
'alpha-3-code': 'PNG',
'continent': 'Oceania',
'name': 'Papua New Guinea',
'capital': 'Port Moresby'},
{'timezones': ['Asia/Manila'],
'alpha-2-code': 'PH',
'alpha-3-code': 'PHL',
'continent': 'Asia',
'name': 'Philippines',
'capital': 'Manila'},
{'timezones': ['Asia/Karachi'],
'alpha-2-code': 'PK',
'alpha-3-code': 'PAK',
'continent': 'Asia',
'name': 'Pakistan',
'capital': 'Islamabad'},
{'timezones': ['Europe/Warsaw'],
'alpha-2-code': 'PL',
'alpha-3-code': 'POL',
'continent': 'Europe',
'name': 'Poland',
'capital': 'Warsaw'},
{'timezones': ['Europe/Lisbon',
'Atlantic/Madeira',
'Atlantic/Azores'],
'alpha-2-code': 'PT',
'alpha-3-code': 'PRT',
'continent': 'Europe',
'name': 'Portugal',
'capital': 'Lisbon'},
{'timezones': ['Pacific/Palau'],
'alpha-2-code': 'PW',
'alpha-3-code': 'PLW',
'continent': 'Oceania',
'name': 'Palau',
'capital': 'Ngerulmud'},
{'timezones': ['America/Asuncion'],
'alpha-2-code': 'PY',
'alpha-3-code': 'PRY',
'continent': 'South America',
'name': 'Paraguay',
'capital': 'Asunci\xc3\xb3n'},
{'timezones': ['Asia/Qatar'],
'alpha-2-code': 'QA',
'alpha-3-code': 'QAT',
'continent': 'Asia',
'name': 'Qatar',
'capital': 'Doha'},
{'timezones': ['Europe/Bucharest'],
'alpha-2-code': 'RO',
'alpha-3-code': 'ROU',
'continent': 'Europe',
'name': 'Romania',
'capital': 'Bucharest'},
{'timezones': ['Europe/Kaliningrad',
'Europe/Moscow',
'Europe/Volgograd',
'Europe/Samara',
'Asia/Yekaterinburg',
'Asia/Omsk',
'Asia/Novosibirsk',
'Asia/Krasnoyarsk',
'Asia/Irkutsk',
'Asia/Yakutsk',
'Asia/Vladivostok',
'Asia/Sakhalin',
'Asia/Magadan',
'Asia/Kamchatka',
'Asia/Anadyr'],
'alpha-2-code': 'RU',
'alpha-3-code': 'RUS',
'continent': 'Europe',
'name': 'Russia',
'capital': 'Moscow'},
{'timezones': ['Africa/Kigali'],
'alpha-2-code': 'RW',
'alpha-3-code': 'RWA',
'continent': 'Africa',
'name': 'Rwanda',
'capital': 'Kigali'},
{'timezones': ['Asia/Riyadh'],
'alpha-2-code': 'SA',
'alpha-3-code': 'SAU',
'continent': 'Asia',
'name': '<NAME>',
'capital': 'Riyadh'},
{'timezones': ['Pacific/Guadalcanal'],
'alpha-2-code': 'SB',
'alpha-3-code': 'SLB',
'continent': 'Oceania',
'name': 'Solomon Islands',
'capital': 'Honiara'},
{'timezones': ['Indian/Mahe'],
'alpha-2-code': 'SC',
'alpha-3-code': 'SYC',
'continent': 'Africa',
'name': 'Seychelles',
'capital': 'Victoria'},
{'timezones': ['Africa/Khartoum'],
'alpha-2-code': 'SD',
'alpha-3-code': 'SDN',
'continent': 'Africa',
'name': 'Sudan',
'capital': 'Khartoum'},
{'timezones': ['Europe/Stockholm'],
'alpha-2-code': 'SE',
'alpha-3-code': 'SWE',
'continent': 'Europe',
'name': 'Sweden',
'capital': 'Stockholm'},
{'timezones': ['Asia/Singapore'],
'alpha-2-code': 'SG',
'alpha-3-code': 'SGP',
'continent': 'Asia',
'name': 'Singapore',
'capital': 'Singapore'},
{'timezones': ['Europe/Ljubljana'],
'alpha-2-code': 'SI',
'alpha-3-code': 'SVN',
'continent': 'Europe',
'name': 'Slovenia',
'capital': 'Ljubljana'},
{'timezones': ['Europe/Bratislava'],
'alpha-2-code': 'SK',
'alpha-3-code': 'SVK',
'continent': 'Europe',
'name': 'Slovakia',
'capital': 'Bratislava'},
{'timezones': ['Africa/Freetown'],
'alpha-2-code': 'SL',
'alpha-3-code': 'SLE',
'continent': 'Africa',
'name': 'Sierra Leone',
'capital': 'Freetown'},
{'timezones': ['Europe/San_Marino'],
'alpha-2-code': 'SM',
'alpha-3-code': 'SMR',
'continent': 'Europe',
'name': 'San Marino',
'capital': 'San Marino'},
{'timezones': ['Africa/Dakar'],
'alpha-2-code': 'SN',
'alpha-3-code': 'SEN',
'continent': 'Africa',
'name': 'Senegal',
'capital': 'Dakar'},
{'timezones': ['Africa/Mogadishu'],
'alpha-2-code': 'SO',
'alpha-3-code': 'SOM',
'continent': 'Africa',
'name': 'Somalia',
'capital': 'Mogadishu'},
{'timezones': ['America/Paramaribo'],
'alpha-2-code': 'SR',
'alpha-3-code': 'SUR',
'continent': 'South America',
'name': 'Suriname',
'capital': 'Paramaribo'},
{'timezones': ['Africa/Sao_Tome'],
'alpha-2-code': 'ST',
'alpha-3-code': 'STP',
'continent': 'Africa',
'name': 'S\xc3\xa3o Tom\xc3\xa9 and Pr\xc3\xadncipe',
'capital': 'S\xc3\xa3o Tom\xc3\xa9'},
{'timezones': ['Asia/Damascus'],
'alpha-2-code': 'SY',
'alpha-3-code': 'SYR',
'continent': 'Asia',
'name': 'Syria',
'capital': 'Damascus'},
{'timezones': ['Africa/Lome'],
'alpha-2-code': 'TG',
'alpha-3-code': 'TGO',
'continent': 'Africa',
'name': 'Togo',
'capital': 'Lom\xc3\xa9'},
{'timezones': ['Asia/Bangkok'],
'alpha-2-code': 'TH',
'alpha-3-code': 'THA',
'continent': 'Asia',
'name': 'Thailand',
'capital': 'Bangkok'},
{'timezones': ['Asia/Dushanbe'],
'alpha-2-code': 'TJ',
'alpha-3-code': 'TJK',
'continent': 'Asia',
'name': 'Tajikistan',
'capital': 'Dushanbe'},
{'timezones': ['Asia/Ashgabat'],
'alpha-2-code': 'TM',
'alpha-3-code': 'TKM',
'continent': 'Asia',
'name': 'Turkmenistan',
'capital': 'Ashgabat'},
{'timezones': ['Africa/Tunis'],
'alpha-2-code': 'TN',
'alpha-3-code': 'TUN',
'continent': 'Africa',
'name': 'Tunisia',
'capital': 'Tunis'},
{'timezones': ['Pacific/Tongatapu'],
'alpha-2-code': 'TO',
'alpha-3-code': 'TON',
'continent': 'Oceania',
'name': 'Tonga',
'capital': 'Nuku\xca\xbbalofa'},
{'timezones': ['Europe/Istanbul'],
'alpha-2-code': 'TR',
'alpha-3-code': 'TUR',
'continent': 'Asia',
'name': 'Turkey',
'capital': 'Ankara'},
{'timezones': ['America/Port_of_Spain'],
'alpha-2-code': 'TT',
'alpha-3-code': 'TTO',
'continent': 'North America',
'name': 'Trinidad and Tobago',
'capital': 'Port of Spain'},
{'timezones': ['Pacific/Funafuti'],
'alpha-2-code': 'TV',
'alpha-3-code': 'TUV',
'continent': 'Oceania',
'name': 'Tuvalu',
'capital': 'Funafuti'},
{'timezones': ['Africa/Dar_es_Salaam'],
'alpha-2-code': 'TZ',
'alpha-3-code': 'TZA',
'continent': 'Africa',
'name': 'Tanzania',
'capital': 'Dodoma'},
{'timezones': ['Europe/Kiev',
'Europe/Uzhgorod',
'Europe/Zaporozhye',
'Europe/Simferopol'],
'alpha-2-code': 'UA',
'alpha-3-code': 'UKR',
'continent': 'Europe',
'name': 'Ukraine',
'capital': 'Kiev'},
{'timezones': ['Africa/Kampala'],
'alpha-2-code': 'UG',
'alpha-3-code': 'UGA',
'continent': 'Africa',
'name': 'Uganda',
'capital': 'Kampala'},
{'timezones': ['America/New_York',
'America/Detroit',
'America/Kentucky/Louisville',
'America/Kentucky/Monticello',
'America/Indiana/Indianapolis',
'America/Indiana/Marengo',
'America/Indiana/Knox',
'America/Indiana/Vevay',
'America/Chicago',
'America/Indiana/Vincennes',
'America/Indiana/Petersburg',
'America/Menominee',
'America/North_Dakota/Center',
'America/North_Dakota/New_Salem',
'America/Denver',
'America/Boise',
'America/Shiprock',
'America/Phoenix',
'America/Los_Angeles',
'America/Anchorage',
'America/Juneau',
'America/Yakutat',
'America/Nome',
'America/Adak',
'Pacific/Honolulu'],
'alpha-2-code': 'US',
'alpha-3-code': 'USA',
'continent': 'North America',
'name': 'United States',
'capital': 'Washington, D.C.'},
{'timezones': ['America/Montevideo'],
'alpha-2-code': 'UY',
'alpha-3-code': 'URY',
'continent': 'South America',
'name': 'Uruguay',
'capital': 'Montevideo'},
{'timezones': ['Asia/Samarkand',
'Asia/Tashkent'],
'alpha-2-code': 'UZ',
'alpha-3-code': 'UZB',
'continent': 'Asia',
'name': 'Uzbekistan',
'capital': 'Tashkent'},
{'timezones': ['Europe/Vatican'],
'alpha-2-code': 'VA',
'alpha-3-code': 'VAT',
'continent': 'Europe',
'name': 'Vatican City',
'capital': 'Vatican City'},
{'timezones': ['America/Caracas'],
'alpha-2-code': 'VE',
'alpha-3-code': 'VEN',
'continent': 'South America',
'name': 'Venezuela',
'capital': 'Caracas'},
{'timezones': ['Asia/Saigon'],
'alpha-2-code': 'VN',
'alpha-3-code': 'VNM',
'continent': 'Asia',
'name': 'Vietnam',
'capital': 'Hanoi'},
{'timezones': ['Pacific/Efate'],
'alpha-2-code': 'VU',
'alpha-3-code': 'VUT',
'continent': 'Oceania',
'name': 'Vanuatu',
'capital': 'Port Vila'},
{'timezones': ['Asia/Aden'],
'alpha-2-code': 'YE',
'alpha-3-code': 'YEM',
'continent': 'Asia',
'name': 'Yemen',
'capital': "Sana'a"},
{'timezones': ['Africa/Lusaka'],
'alpha-2-code': 'ZM',
'alpha-3-code': 'ZMB',
'continent': 'Africa',
'name': 'Zambia',
'capital': 'Lusaka'},
{'timezones': ['Africa/Harare'],
'alpha-2-code': 'ZW',
'alpha-3-code': 'ZWE',
'continent': 'Africa',
'name': 'Zimbabwe',
'capital': 'Harare'},
{'timezones': ['Africa/Algiers'],
'alpha-2-code': 'DZ',
'alpha-3-code': 'DZA',
'continent': 'Africa',
'name': 'Algeria',
'capital': 'Algiers'},
{'timezones': ['Europe/Sarajevo'],
'alpha-2-code': 'BA',
'alpha-3-code': 'BIH',
'continent': 'Europe',
'name': 'Bosnia and Herzegovina',
'capital': 'Sarajevo'},
{'timezones': ['Asia/Phnom_Penh'],
'alpha-2-code': 'KH',
'alpha-3-code': 'KHM',
'continent': 'Asia',
'name': 'Cambodia',
'capital': 'Phnom Penh'},
{'timezones': ['Africa/Bangui'],
'alpha-2-code': 'CF',
'alpha-3-code': 'CAF',
'continent': 'Africa',
'name': 'Central African Republic',
'capital': 'Bangui'},
{'timezones': ['Africa/Ndjamena'],
'alpha-2-code': 'TD',
'alpha-3-code': 'TCD',
'continent': 'Africa',
'name': 'Chad',
'capital': "N'Djamena"},
{'timezones': ['Indian/Comoro'],
'alpha-2-code': 'KM',
'alpha-3-code': 'COM',
'continent': 'Africa',
'name': 'Comoros',
'capital': 'Moroni'},
{'timezones': ['Europe/Zagreb'],
'alpha-2-code': 'HR',
'alpha-3-code': 'HRV',
'continent': 'Europe',
'name': 'Croatia',
'capital': 'Zagreb'},
{'timezones': ['Asia/Dili'],
'alpha-2-code': 'TL',
'alpha-3-code': 'TLS',
'continent': 'Asia',
'name': 'East Timor',
'capital': 'Dili'},
{'timezones': ['America/El_Salvador'],
'alpha-2-code': 'SV',
'alpha-3-code': 'SLV',
'continent': 'North America',
'name': 'El Salvador',
'capital': 'San Salvador'},
{'timezones': ['Africa/Malabo'],
'alpha-2-code': 'GQ',
'alpha-3-code': 'GNQ',
'continent': 'Africa',
'name': 'Equatorial Guinea',
'capital': 'Malabo'},
{'timezones': ['America/Grenada'],
'alpha-2-code': 'GD',
'alpha-3-code': 'GRD',
'continent': 'North America',
'name': 'Grenada',
'capital': "St. George's"},
{'timezones': ['Asia/Almaty',
'Asia/Qyzylorda',
'Asia/Aqtobe',
'Asia/Aqtau',
'Asia/Oral'],
'alpha-2-code': 'KZ',
'alpha-3-code': 'KAZ',
'continent': 'Asia',
'name': 'Kazakhstan',
'capital': 'Astana'},
{'timezones': ['Asia/Vientiane'],
'alpha-2-code': 'LA',
'alpha-3-code': 'LAO',
'continent': 'Asia',
'name': 'Laos',
'capital': 'Vientiane'},
{'timezones': ['Pacific/Truk',
'Pacific/Ponape',
'Pacific/Kosrae'],
'alpha-2-code': 'FM',
'alpha-3-code': 'FSM',
'continent': 'Oceania',
'name': 'Federated States of Micronesia',
'capital': 'Palikir'},
{'timezones': ['Europe/Chisinau'],
'alpha-2-code': 'MD',
'alpha-3-code': 'MDA',
'continent': 'Europe',
'name': 'Moldova',
'capital': 'Chi\xc5\x9fin\xc4\x83u'},
{'timezones': ['Europe/Monaco'],
'alpha-2-code': 'MC',
'alpha-3-code': 'MCO',
'continent': 'Europe',
'name': 'Monaco',
'capital': 'Monaco'},
{'timezones': ['Europe/Podgorica'],
'alpha-2-code': 'ME',
'alpha-3-code': 'MNE',
'continent': 'Europe',
'name': 'Montenegro',
'capital': 'Podgorica'},
{'timezones': ['Africa/Casablanca'],
'alpha-2-code': 'MA',
'alpha-3-code': 'MAR',
'continent': 'Africa',
'name': 'Morocco',
'capital': 'Rabat'},
{'timezones': ['America/St_Kitts'],
'alpha-2-code': 'KN',
'alpha-3-code': 'KNA',
'continent': 'North America',
'name': 'Saint Kitts and Nevis',
'capital': 'Basseterre'},
{'timezones': ['America/St_Lucia'],
'alpha-2-code': 'LC',
'alpha-3-code': 'LCA',
'continent': 'North America',
'name': 'Saint Lucia',
'capital': 'Castries'},
{'timezones': ['America/St_Vincent'],
'alpha-2-code': 'VC',
'alpha-3-code': 'VCT',
'continent': 'North America',
'name': 'Saint Vincent and the Grenadines',
'capital': 'Kingstown'},
{'timezones': ['Pacific/Apia'],
'alpha-2-code': 'WS',
'alpha-3-code': 'WSM',
'continent': 'Oceania',
'name': 'Samoa',
'capital': 'Apia'},
{'timezones': ['Europe/Belgrade'],
'alpha-2-code': 'RS',
'alpha-3-code': 'SRB',
'continent': 'Europe',
'name': 'Serbia',
'capital': 'Belgrade'},
{'timezones': ['Africa/Johannesburg'],
'alpha-2-code': 'ZA',
'alpha-3-code': 'ZAF',
'continent': 'Africa',
'name': 'South Africa',
'capital': 'Pretoria'},
{'timezones': ['Europe/Madrid',
'Africa/Ceuta',
'Atlantic/Canary'],
'alpha-2-code': 'ES',
'alpha-3-code': 'ESP',
'continent': 'Europe',
'name': 'Spain',
'capital': 'Madrid'},
{'timezones': ['Asia/Colombo'],
'alpha-2-code': 'LK',
'alpha-3-code': 'LKA',
'continent': 'Asia',
'name': 'Sri Lanka',
'capital': 'Sri Jayewardenepura Kotte'},
{'timezones': ['Africa/Mbabane'],
'alpha-2-code': 'SZ',
'alpha-3-code': 'SWZ',
'continent': 'Africa',
'name': 'Swaziland',
'capital': 'Mbabane'},
{'timezones': ['Europe/Zurich'],
'alpha-2-code': 'CH',
'alpha-3-code': 'CHE',
'continent': 'Europe',
'name': 'Switzerland',
'capital': 'Bern'},
{'timezones': ['Asia/Dubai'],
'alpha-2-code': 'AE',
'alpha-3-code': 'ARE',
'continent': 'Asia',
'name': 'United Arab Emirates',
'capital': 'Abu Dhabi'},
{'timezones': ['Europe/London'],
'alpha-2-code': 'GB',
'alpha-3-code': 'GBR',
'continent': 'Europe',
'name': 'United Kingdom',
'capital': 'London'},
]
regex = re.compile(timedelta_pattern)
def unix_time(self, end_datetime=None, start_datetime=None):
"""
Get a timestamp between January 1, 1970 and now, unless passed
explicit start_datetime or end_datetime values.
:example 1061306726
"""
start_datetime = self._parse_start_datetime(start_datetime)
end_datetime = self._parse_end_datetime(end_datetime)
return self.generator.random.randint(start_datetime, end_datetime)
def time_delta(self, end_datetime=None):
"""
Get a timedelta object
"""
start_datetime = self._parse_start_datetime('now')
end_datetime = self._parse_end_datetime(end_datetime)
seconds = end_datetime - start_datetime
ts = self.generator.random.randint(*sorted([0, seconds]))
return timedelta(seconds=ts)
def date_time(self, tzinfo=None, end_datetime=None):
"""
Get a datetime object for a date between January 1, 1970 and now
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('2005-08-16 20:39:21')
:return datetime
"""
# NOTE: On windows, the lowest value you can get from windows is 86400
# on the first day. Known python issue:
# https://bugs.python.org/issue30684
return datetime(1970, 1, 1, tzinfo=tzinfo) + \
timedelta(seconds=self.unix_time(end_datetime=end_datetime))
def date_time_ad(self, tzinfo=None, end_datetime=None, start_datetime=None):
"""
Get a datetime object for a date between January 1, 001 and now
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('1265-03-22 21:15:52')
:return datetime
"""
# 1970-01-01 00:00:00 UTC minus 62135596800 seconds is
# 0001-01-01 00:00:00 UTC. Since _parse_end_datetime() is used
# elsewhere where a default value of 0 is expected, we can't
# simply change that class method to use this magic number as a
# default value when None is provided.
start_time = -62135596800 if start_datetime is None else self._parse_start_datetime(start_datetime)
end_datetime = self._parse_end_datetime(end_datetime)
ts = self.generator.random.randint(start_time, end_datetime)
# NOTE: using datetime.fromtimestamp(ts) directly will raise
# a "ValueError: timestamp out of range for platform time_t"
# on some platforms due to system C functions;
# see http://stackoverflow.com/a/10588133/2315612
# NOTE: On windows, the lowest value you can get from windows is 86400
# on the first day. Known python issue:
# https://bugs.python.org/issue30684
return datetime(1970, 1, 1, tzinfo=tzinfo) + timedelta(seconds=ts)
def iso8601(self, tzinfo=None, end_datetime=None):
"""
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example '2003-10-21T16:05:52+0000'
"""
return self.date_time(tzinfo, end_datetime=end_datetime).isoformat()
def date(self, pattern='%Y-%m-%d', end_datetime=None):
"""
Get a date string between January 1, 1970 and now
:param pattern format
:example '2008-11-27'
"""
return self.date_time(end_datetime=end_datetime).strftime(pattern)
def date_object(self, end_datetime=None):
"""
Get a date object between January 1, 1970 and now
:example datetime.date(2016, 9, 20)
"""
return self.date_time(end_datetime=end_datetime).date()
def time(self, pattern='%H:%M:%S', end_datetime=None):
"""
Get a time string (24h format by default)
:param pattern format
:example '15:02:34'
"""
return self.date_time(
end_datetime=end_datetime).time().strftime(pattern)
def time_object(self, end_datetime=None):
"""
Get a time object
:example datetime.time(15, 56, 56, 772876)
"""
return self.date_time(end_datetime=end_datetime).time()
@classmethod
def _parse_start_datetime(cls, value):
if value is None:
return 0
return cls._parse_date_time(value)
@classmethod
def _parse_end_datetime(cls, value):
if value is None:
return datetime_to_timestamp(datetime.now())
return cls._parse_date_time(value)
@classmethod
def _parse_date_string(cls, value):
parts = cls.regex.match(value)
if not parts:
raise ParseError("Can't parse date string `{}`.".format(value))
parts = parts.groupdict()
time_params = {}
for (name_, param_) in parts.items():
if param_:
time_params[name_] = int(param_)
if 'years' in time_params:
if 'days' not in time_params:
time_params['days'] = 0
time_params['days'] += 365.24 * time_params.pop('years')
if 'months' in time_params:
if 'days' not in time_params:
time_params['days'] = 0
time_params['days'] += 30.42 * time_params.pop('months')
if not time_params:
raise ParseError("Can't parse date string `{}`.".format(value))
return time_params
@classmethod
def _parse_timedelta(cls, value):
if isinstance(value, timedelta):
return value.total_seconds()
if is_string(value):
time_params = cls._parse_date_string(value)
return timedelta(**time_params).total_seconds()
if isinstance(value, (int, float)):
return value
raise ParseError("Invalid format for timedelta '{}'".format(value))
@classmethod
def _parse_date_time(cls, value, tzinfo=None):
if isinstance(value, (datetime, date, real_datetime, real_date)):
return datetime_to_timestamp(value)
now = datetime.now(tzinfo)
if isinstance(value, timedelta):
return datetime_to_timestamp(now + value)
if is_string(value):
if value == 'now':
return datetime_to_timestamp(datetime.now(tzinfo))
time_params = cls._parse_date_string(value)
return datetime_to_timestamp(now + timedelta(**time_params))
if isinstance(value, int):
return datetime_to_timestamp(now + timedelta(value))
raise ParseError("Invalid format for date '{}'".format(value))
@classmethod
def _parse_date(cls, value):
if isinstance(value, (datetime, real_datetime)):
return value.date()
elif isinstance(value, (date, real_date)):
return value
today = date.today()
if isinstance(value, timedelta):
return today + value
if is_string(value):
if value in ('today', 'now'):
return today
time_params = cls._parse_date_string(value)
return today + timedelta(**time_params)
if isinstance(value, int):
return today + timedelta(value)
raise ParseError("Invalid format for date '{}'".format(value))
def date_time_between(self, start_date='-30y', end_date='now', tzinfo=None):
"""
Get a DateTime object based on a random date between two given dates.
Accepts date strings that can be recognized by strtotime().
:param start_date Defaults to 30 years ago
:param end_date Defaults to "now"
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('1999-02-02 11:42:52')
:return DateTime
"""
start_date = self._parse_date_time(start_date, tzinfo=tzinfo)
end_date = self._parse_date_time(end_date, tzinfo=tzinfo)
if end_date - start_date <= 1:
ts = start_date + self.generator.random.random()
else:
ts = self.generator.random.randint(start_date, end_date)
if tzinfo is None:
return datetime(1970, 1, 1, tzinfo=tzinfo) + timedelta(seconds=ts)
else:
return (
datetime(1970, 1, 1, tzinfo=tzutc()) + timedelta(seconds=ts)
).astimezone(tzinfo)
def date_between(self, start_date='-30y', end_date='today'):
"""
Get a Date object based on a random date between two given dates.
Accepts date strings that can be recognized by strtotime().
:param start_date Defaults to 30 years ago
:param end_date Defaults to "today"
:example Date('1999-02-02')
:return Date
"""
start_date = self._parse_date(start_date)
end_date = self._parse_date(end_date)
return self.date_between_dates(date_start=start_date, date_end=end_date)
def future_datetime(self, end_date='+30d', tzinfo=None):
"""
Get a DateTime object based on a random date between 1 second form now
and a given date.
Accepts date strings that can be recognized by strtotime().
:param end_date Defaults to "+30d"
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('1999-02-02 11:42:52')
:return DateTime
"""
return self.date_time_between(
start_date='+1s', end_date=end_date, tzinfo=tzinfo,
)
def future_date(self, end_date='+30d', tzinfo=None):
"""
Get a Date object based on a random date between 1 day from now and a
given date.
Accepts date strings that can be recognized by strtotime().
:param end_date Defaults to "+30d"
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('1999-02-02 11:42:52')
:return DateTime
"""
return self.date_between(start_date='+1d', end_date=end_date)
def past_datetime(self, start_date='-30d', tzinfo=None):
"""
Get a DateTime object based on a random date between a given date and 1
second ago.
Accepts date strings that can be recognized by strtotime().
:param start_date Defaults to "-30d"
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('1999-02-02 11:42:52')
:return DateTime
"""
return self.date_time_between(
start_date=start_date, end_date='-1s', tzinfo=tzinfo,
)
def past_date(self, start_date='-30d', tzinfo=None):
"""
Get a Date object based on a random date between a given date and 1 day
ago.
Accepts date strings that can be recognized by strtotime().
:param start_date Defaults to "-30d"
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('1999-02-02 11:42:52')
:return DateTime
"""
return self.date_between(start_date=start_date, end_date='-1d')
def date_time_between_dates(
self,
datetime_start=None,
datetime_end=None,
tzinfo=None):
"""
Takes two DateTime objects and returns a random datetime between the two
given datetimes.
Accepts DateTime objects.
:param datetime_start: DateTime
:param datetime_end: DateTime
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('1999-02-02 11:42:52')
:return DateTime
"""
if datetime_start is None:
datetime_start = datetime.now(tzinfo)
if datetime_end is None:
datetime_end = datetime.now(tzinfo)
timestamp = self.generator.random.randint(
datetime_to_timestamp(datetime_start),
datetime_to_timestamp(datetime_end),
)
try:
if tzinfo is None:
pick = datetime.fromtimestamp(timestamp, tzlocal())
pick = pick.astimezone(tzutc()).replace(tzinfo=None)
else:
pick = datetime.fromtimestamp(timestamp, tzinfo)
except OverflowError:
raise OverflowError(
"You specified an end date with a timestamp bigger than the maximum allowed on this"
" system. Please specify an earlier date.",
)
return pick
def date_between_dates(self, date_start=None, date_end=None):
"""
Takes two Date objects and returns a random date between the two given dates.
Accepts Date or Datetime objects
:param date_start: Date
:param date_end: Date
:return Date
"""
return self.date_time_between_dates(date_start, date_end).date()
def date_time_this_century(
self,
before_now=True,
after_now=False,
tzinfo=None):
"""
Gets a DateTime object for the current century.
:param before_now: include days in current century before today
:param after_now: include days in current century after today
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('2012-04-04 11:02:02')
:return DateTime
"""
now = datetime.now(tzinfo)
this_century_start = datetime(
now.year - (now.year % 100), 1, 1, tzinfo=tzinfo)
next_century_start = datetime(
min(this_century_start.year + 100, MAXYEAR), 1, 1, tzinfo=tzinfo)
if before_now and after_now:
return self.date_time_between_dates(
this_century_start, next_century_start, tzinfo)
elif not before_now and after_now:
return self.date_time_between_dates(now, next_century_start, tzinfo)
elif not after_now and before_now:
return self.date_time_between_dates(this_century_start, now, tzinfo)
else:
return now
def date_time_this_decade(
self,
before_now=True,
after_now=False,
tzinfo=None):
"""
Gets a DateTime object for the decade year.
:param before_now: include days in current decade before today
:param after_now: include days in current decade after today
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('2012-04-04 11:02:02')
:return DateTime
"""
now = datetime.now(tzinfo)
this_decade_start = datetime(
now.year - (now.year % 10), 1, 1, tzinfo=tzinfo)
next_decade_start = datetime(
min(this_decade_start.year + 10, MAXYEAR), 1, 1, tzinfo=tzinfo)
if before_now and after_now:
return self.date_time_between_dates(
this_decade_start, next_decade_start, tzinfo)
elif not before_now and after_now:
return self.date_time_between_dates(now, next_decade_start, tzinfo)
elif not after_now and before_now:
return self.date_time_between_dates(this_decade_start, now, tzinfo)
else:
return now
def date_time_this_year(
self,
before_now=True,
after_now=False,
tzinfo=None):
"""
Gets a DateTime object for the current year.
:param before_now: include days in current year before today
:param after_now: include days in current year after today
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('2012-04-04 11:02:02')
:return DateTime
"""
now = datetime.now(tzinfo)
this_year_start = now.replace(
month=1, day=1, hour=0, minute=0, second=0, microsecond=0)
next_year_start = datetime(now.year + 1, 1, 1, tzinfo=tzinfo)
if before_now and after_now:
return self.date_time_between_dates(
this_year_start, next_year_start, tzinfo)
elif not before_now and after_now:
return self.date_time_between_dates(now, next_year_start, tzinfo)
elif not after_now and before_now:
return self.date_time_between_dates(this_year_start, now, tzinfo)
else:
return now
def date_time_this_month(
self,
before_now=True,
after_now=False,
tzinfo=None):
"""
Gets a DateTime object for the current month.
:param before_now: include days in current month before today
:param after_now: include days in current month after today
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('2012-04-04 11:02:02')
:return DateTime
"""
now = datetime.now(tzinfo)
this_month_start = now.replace(
day=1, hour=0, minute=0, second=0, microsecond=0)
next_month_start = this_month_start + \
relativedelta.relativedelta(months=1)
if before_now and after_now:
return self.date_time_between_dates(
this_month_start, next_month_start, tzinfo)
elif not before_now and after_now:
return self.date_time_between_dates(now, next_month_start, tzinfo)
elif not after_now and before_now:
return self.date_time_between_dates(this_month_start, now, tzinfo)
else:
return now
def date_this_century(self, before_today=True, after_today=False):
"""
Gets a Date object for the current century.
:param before_today: include days in current century before today
:param after_today: include days in current century after today
:example Date('2012-04-04')
:return Date
"""
today = date.today()
this_century_start = date(today.year - (today.year % 100), 1, 1)
next_century_start = date(this_century_start.year + 100, 1, 1)
if before_today and after_today:
return self.date_between_dates(
this_century_start, next_century_start)
elif not before_today and after_today:
return self.date_between_dates(today, next_century_start)
elif not after_today and before_today:
return self.date_between_dates(this_century_start, today)
else:
return today
def date_this_decade(self, before_today=True, after_today=False):
"""
Gets a Date object for the decade year.
:param before_today: include days in current decade before today
:param after_today: include days in current decade after today
:example Date('2012-04-04')
:return Date
"""
today = date.today()
this_decade_start = date(today.year - (today.year % 10), 1, 1)
next_decade_start = date(this_decade_start.year + 10, 1, 1)
if before_today and after_today:
return self.date_between_dates(this_decade_start, next_decade_start)
elif not before_today and after_today:
return self.date_between_dates(today, next_decade_start)
elif not after_today and before_today:
return self.date_between_dates(this_decade_start, today)
else:
return today
def date_this_year(self, before_today=True, after_today=False):
"""
Gets a Date object for the current year.
:param before_today: include days in current year before today
:param after_today: include days in current year after today
:example Date('2012-04-04')
:return Date
"""
today = date.today()
this_year_start = today.replace(month=1, day=1)
next_year_start = date(today.year + 1, 1, 1)
if before_today and after_today:
return self.date_between_dates(this_year_start, next_year_start)
elif not before_today and after_today:
return self.date_between_dates(today, next_year_start)
elif not after_today and before_today:
return self.date_between_dates(this_year_start, today)
else:
return today
def date_this_month(self, before_today=True, after_today=False):
"""
Gets a Date object for the current month.
:param before_today: include days in current month before today
:param after_today: include days in current month after today
:param tzinfo: timezone, instance of datetime.tzinfo subclass
:example DateTime('2012-04-04 11:02:02')
:return DateTime
"""
today = date.today()
this_month_start = today.replace(day=1)
next_month_start = this_month_start + \
relativedelta.relativedelta(months=1)
if before_today and after_today:
return self.date_between_dates(this_month_start, next_month_start)
elif not before_today and after_today:
return self.date_between_dates(today, next_month_start)
elif not after_today and before_today:
return self.date_between_dates(this_month_start, today)
else:
return today
def time_series(
self,
start_date='-30d',
end_date='now',
precision=None,
distrib=None,
tzinfo=None):
"""
Returns a generator yielding tuples of ``(<datetime>, <value>)``.
The data points will start at ``start_date``, and be at every time interval specified by
``precision``.
``distrib`` is a callable that accepts ``<datetime>`` and returns ``<value>``
"""
start_date = self._parse_date_time(start_date, tzinfo=tzinfo)
end_date = self._parse_date_time(end_date, tzinfo=tzinfo)
if end_date < start_date:
raise ValueError("`end_date` must be greater than `start_date`.")
if precision is None:
precision = (end_date - start_date) / 30
precision = self._parse_timedelta(precision)
if distrib is None:
def distrib(dt): return self.generator.random.uniform(0, precision) # noqa
if not callable(distrib):
raise ValueError(
"`distrib` must be a callable. Got {} instead.".format(distrib))
datapoint = start_date
while datapoint < end_date:
dt = timestamp_to_datetime(datapoint, tzinfo)
datapoint += precision
yield (dt, distrib(dt))
def am_pm(self):
return self.date('%p')
def day_of_month(self):
return self.date('%d')
def day_of_week(self):
return self.date('%A')
def month(self):
return self.date('%m')
def month_name(self):
return self.date('%B')
def year(self):
return self.date('%Y')
def century(self):
"""
:example 'XVII'
"""
return self.random_element(self.centuries)
def timezone(self):
return self.generator.random.choice(
self.random_element(self.countries)['timezones'])
def date_of_birth(self, tzinfo=None, minimum_age=0, maximum_age=115):
"""
Generate a random date of birth represented as a Date object,
constrained by optional miminimum_age and maximum_age
parameters.
:param tzinfo Defaults to None.
:param minimum_age Defaults to 0.
:param maximum_age Defaults to 115.
:example Date('1979-02-02')
:return Date
"""
if not isinstance(minimum_age, int):
raise TypeError("minimum_age must be an integer.")
if not isinstance(maximum_age, int):
raise TypeError("maximum_age must be an integer.")
if (maximum_age < 0):
raise ValueError("maximum_age must be greater than or equal to zero.")
if (minimum_age < 0):
raise ValueError("minimum_age must be greater than or equal to zero.")
if (minimum_age > maximum_age):
raise ValueError("minimum_age must be less than or equal to maximum_age.")
# In order to return the full range of possible dates of birth, add one
# year to the potential age cap and subtract one day if we land on the
# boundary.
now = datetime.now(tzinfo).date()
start_date = now.replace(year=now.year - (maximum_age+1))
end_date = now.replace(year=now.year - minimum_age)
dob = self.date_time_ad(tzinfo=tzinfo, start_datetime=start_date, end_datetime=end_date).date()
return dob if dob != start_date else dob + timedelta(days=1) | 0.555676 | 0.089296 |
import json
from tencentcloud.common.exception.tencent_cloud_sdk_exception import TencentCloudSDKException
from tencentcloud.common.abstract_client import AbstractClient
from tencentcloud.dayu.v20180709 import models
class DayuClient(AbstractClient):
_apiVersion = '2018-07-09'
_endpoint = 'dayu.tencentcloudapi.com'
def CreateBasicDDoSAlarmThreshold(self, request):
"""设置基础防护的DDoS告警阈值，只支持基础防护产品
:param request: Request instance for CreateBasicDDoSAlarmThreshold.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateBasicDDoSAlarmThresholdRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateBasicDDoSAlarmThresholdResponse`
"""
try:
params = request._serialize()
body = self.call("CreateBasicDDoSAlarmThreshold", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateBasicDDoSAlarmThresholdResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateBoundIP(self, request):
"""绑定IP到高防包实例，支持独享包、共享包；需要注意的是此接口绑定或解绑IP是异步接口，当处于绑定或解绑中时，则不允许再进行绑定或解绑，需要等待当前绑定或解绑完成。
:param request: Request instance for CreateBoundIP.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateBoundIPRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateBoundIPResponse`
"""
try:
params = request._serialize()
body = self.call("CreateBoundIP", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateBoundIPResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateCCFrequencyRules(self, request):
"""添加CC防护的访问频率控制规则
:param request: Request instance for CreateCCFrequencyRules.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateCCFrequencyRulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateCCFrequencyRulesResponse`
"""
try:
params = request._serialize()
body = self.call("CreateCCFrequencyRules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateCCFrequencyRulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateCCSelfDefinePolicy(self, request):
"""创建CC自定义策略
:param request: Request instance for CreateCCSelfDefinePolicy.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateCCSelfDefinePolicyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateCCSelfDefinePolicyResponse`
"""
try:
params = request._serialize()
body = self.call("CreateCCSelfDefinePolicy", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateCCSelfDefinePolicyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateDDoSPolicy(self, request):
"""添加DDoS高级策略
:param request: Request instance for CreateDDoSPolicy.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateDDoSPolicyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateDDoSPolicyResponse`
"""
try:
params = request._serialize()
body = self.call("CreateDDoSPolicy", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateDDoSPolicyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateDDoSPolicyCase(self, request):
"""添加策略场景
:param request: Request instance for CreateDDoSPolicyCase.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateDDoSPolicyCaseRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateDDoSPolicyCaseResponse`
"""
try:
params = request._serialize()
body = self.call("CreateDDoSPolicyCase", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateDDoSPolicyCaseResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateInstanceName(self, request):
"""资源实例重命名，支持独享包、共享包、高防IP、高防IP专业版；
:param request: Request instance for CreateInstanceName.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateInstanceNameRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateInstanceNameResponse`
"""
try:
params = request._serialize()
body = self.call("CreateInstanceName", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateInstanceNameResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateL4HealthConfig(self, request):
"""上传四层健康检查配置
:param request: Request instance for CreateL4HealthConfig.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateL4HealthConfigRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateL4HealthConfigResponse`
"""
try:
params = request._serialize()
body = self.call("CreateL4HealthConfig", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateL4HealthConfigResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateL4Rules(self, request):
"""添加L4转发规则
:param request: Request instance for CreateL4Rules.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateL4RulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateL4RulesResponse`
"""
try:
params = request._serialize()
body = self.call("CreateL4Rules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateL4RulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateL7CCRule(self, request):
"""此接口是7层CC的访问频控自定义规则（IP+Host维度，不支持具体的URI），此接口已弃用，请调用新接口CreateCCFrequencyRules，新接口同时支持IP+Host维度以及具体的URI；
:param request: Request instance for CreateL7CCRule.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateL7CCRuleRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateL7CCRuleResponse`
"""
try:
params = request._serialize()
body = self.call("CreateL7CCRule", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateL7CCRuleResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateL7HealthConfig(self, request):
"""上传七层健康检查配置
:param request: Request instance for CreateL7HealthConfig.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateL7HealthConfigRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateL7HealthConfigResponse`
"""
try:
params = request._serialize()
body = self.call("CreateL7HealthConfig", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateL7HealthConfigResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateL7RuleCert(self, request):
"""配置7层转发规则的证书
:param request: Request instance for CreateL7RuleCert.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateL7RuleCertRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateL7RuleCertResponse`
"""
try:
params = request._serialize()
body = self.call("CreateL7RuleCert", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateL7RuleCertResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateL7Rules(self, request):
"""添加7层(网站)转发规则
:param request: Request instance for CreateL7Rules.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateL7RulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateL7RulesResponse`
"""
try:
params = request._serialize()
body = self.call("CreateL7Rules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateL7RulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateL7RulesUpload(self, request):
"""批量上传7层转发规则
:param request: Request instance for CreateL7RulesUpload.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateL7RulesUploadRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateL7RulesUploadResponse`
"""
try:
params = request._serialize()
body = self.call("CreateL7RulesUpload", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateL7RulesUploadResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateNetReturn(self, request):
"""高防IP专业版一键切回源站
:param request: Request instance for CreateNetReturn.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateNetReturnRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateNetReturnResponse`
"""
try:
params = request._serialize()
body = self.call("CreateNetReturn", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateNetReturnResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateUnblockIp(self, request):
"""IP解封操作
:param request: Request instance for CreateUnblockIp.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateUnblockIpRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateUnblockIpResponse`
"""
try:
params = request._serialize()
body = self.call("CreateUnblockIp", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateUnblockIpResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DeleteCCFrequencyRules(self, request):
"""删除CC防护的访问频率控制规则
:param request: Request instance for DeleteCCFrequencyRules.
:type request: :class:`tencentcloud.dayu.v20180709.models.DeleteCCFrequencyRulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DeleteCCFrequencyRulesResponse`
"""
try:
params = request._serialize()
body = self.call("DeleteCCFrequencyRules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DeleteCCFrequencyRulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DeleteCCSelfDefinePolicy(self, request):
"""删除CC自定义策略
:param request: Request instance for DeleteCCSelfDefinePolicy.
:type request: :class:`tencentcloud.dayu.v20180709.models.DeleteCCSelfDefinePolicyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DeleteCCSelfDefinePolicyResponse`
"""
try:
params = request._serialize()
body = self.call("DeleteCCSelfDefinePolicy", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DeleteCCSelfDefinePolicyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DeleteDDoSPolicy(self, request):
"""删除DDoS高级策略
:param request: Request instance for DeleteDDoSPolicy.
:type request: :class:`tencentcloud.dayu.v20180709.models.DeleteDDoSPolicyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DeleteDDoSPolicyResponse`
"""
try:
params = request._serialize()
body = self.call("DeleteDDoSPolicy", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DeleteDDoSPolicyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DeleteDDoSPolicyCase(self, request):
"""删除策略场景
:param request: Request instance for DeleteDDoSPolicyCase.
:type request: :class:`tencentcloud.dayu.v20180709.models.DeleteDDoSPolicyCaseRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DeleteDDoSPolicyCaseResponse`
"""
try:
params = request._serialize()
body = self.call("DeleteDDoSPolicyCase", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DeleteDDoSPolicyCaseResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DeleteL4Rules(self, request):
"""删除四层转发规则
:param request: Request instance for DeleteL4Rules.
:type request: :class:`tencentcloud.dayu.v20180709.models.DeleteL4RulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DeleteL4RulesResponse`
"""
try:
params = request._serialize()
body = self.call("DeleteL4Rules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DeleteL4RulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DeleteL7Rules(self, request):
"""删除七层转发规则
:param request: Request instance for DeleteL7Rules.
:type request: :class:`tencentcloud.dayu.v20180709.models.DeleteL7RulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DeleteL7RulesResponse`
"""
try:
params = request._serialize()
body = self.call("DeleteL7Rules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DeleteL7RulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeActionLog(self, request):
"""获取操作日志
:param request: Request instance for DescribeActionLog.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeActionLogRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeActionLogResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeActionLog", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeActionLogResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeBaradData(self, request):
"""为大禹子产品提供业务转发指标数据的接口
:param request: Request instance for DescribeBaradData.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeBaradDataRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeBaradDataResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeBaradData", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeBaradDataResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeBasicCCThreshold(self, request):
"""获取基础防护CC防护阈值
:param request: Request instance for DescribeBasicCCThreshold.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeBasicCCThresholdRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeBasicCCThresholdResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeBasicCCThreshold", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeBasicCCThresholdResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeBasicDeviceThreshold(self, request):
"""获取基础防护黑洞阈值
:param request: Request instance for DescribeBasicDeviceThreshold.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeBasicDeviceThresholdRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeBasicDeviceThresholdResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeBasicDeviceThreshold", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeBasicDeviceThresholdResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeCCAlarmThreshold(self, request):
"""获取高防包、高防IP、高防IP专业版、棋牌盾产品设置CC攻击的告警通知阈值
:param request: Request instance for DescribeCCAlarmThreshold.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeCCAlarmThresholdRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeCCAlarmThresholdResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeCCAlarmThreshold", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeCCAlarmThresholdResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeCCEvList(self, request):
"""获取CC攻击事件列表
:param request: Request instance for DescribeCCEvList.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeCCEvListRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeCCEvListResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeCCEvList", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeCCEvListResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeCCFrequencyRules(self, request):
"""获取CC防护的访问频率控制规则
:param request: Request instance for DescribeCCFrequencyRules.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeCCFrequencyRulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeCCFrequencyRulesResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeCCFrequencyRules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeCCFrequencyRulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeCCIpAllowDeny(self, request):
"""获取CC的IP黑白名单
:param request: Request instance for DescribeCCIpAllowDeny.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeCCIpAllowDenyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeCCIpAllowDenyResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeCCIpAllowDeny", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeCCIpAllowDenyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeCCSelfDefinePolicy(self, request):
"""获取CC自定义策略
:param request: Request instance for DescribeCCSelfDefinePolicy.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeCCSelfDefinePolicyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeCCSelfDefinePolicyResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeCCSelfDefinePolicy", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeCCSelfDefinePolicyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeCCTrend(self, request):
"""获取CC攻击指标数据，包括总请求峰值(QPS)和攻击请求(QPS)
:param request: Request instance for DescribeCCTrend.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeCCTrendRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeCCTrendResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeCCTrend", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeCCTrendResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeCCUrlAllow(self, request):
"""获取CC的Url白名单
:param request: Request instance for DescribeCCUrlAllow.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeCCUrlAllowRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeCCUrlAllowResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeCCUrlAllow", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeCCUrlAllowResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSAlarmThreshold(self, request):
"""获取高防包、高防IP、高防IP专业版、棋牌盾产品设置DDoS攻击的告警通知阈值
:param request: Request instance for DescribeDDoSAlarmThreshold.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSAlarmThresholdRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSAlarmThresholdResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSAlarmThreshold", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSAlarmThresholdResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSAttackIPRegionMap(self, request):
"""获取DDoS攻击源IP地域分布图，支持全球攻击分布和国内省份攻击分布；
:param request: Request instance for DescribeDDoSAttackIPRegionMap.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSAttackIPRegionMapRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSAttackIPRegionMapResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSAttackIPRegionMap", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSAttackIPRegionMapResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSAttackSource(self, request):
"""获取DDoS攻击源列表
:param request: Request instance for DescribeDDoSAttackSource.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSAttackSourceRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSAttackSourceResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSAttackSource", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSAttackSourceResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSCount(self, request):
"""获取DDoS攻击占比分析
:param request: Request instance for DescribeDDoSCount.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSCountRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSCountResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSCount", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSCountResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSDefendStatus(self, request):
"""获取DDoS防护状态（临时关闭状态），支持产品：基础防护，独享包，共享包，高防IP，高防IP专业版；调用此接口是获取当前是否有设置临时关闭DDoS防护状态，如果有设置会返回临时关闭的时长等参数。
:param request: Request instance for DescribeDDoSDefendStatus.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSDefendStatusRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSDefendStatusResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSDefendStatus", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSDefendStatusResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSEvInfo(self, request):
"""获取DDoS攻击事件详情
:param request: Request instance for DescribeDDoSEvInfo.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSEvInfoRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSEvInfoResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSEvInfo", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSEvInfoResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSEvList(self, request):
"""获取DDoS攻击事件列表
:param request: Request instance for DescribeDDoSEvList.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSEvListRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSEvListResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSEvList", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSEvListResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSIpLog(self, request):
"""获取DDoSIP攻击日志
:param request: Request instance for DescribeDDoSIpLog.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSIpLogRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSIpLogResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSIpLog", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSIpLogResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSNetCount(self, request):
"""获取高防IP专业版资源的DDoS攻击占比分析
:param request: Request instance for DescribeDDoSNetCount.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSNetCountRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSNetCountResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSNetCount", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSNetCountResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSNetEvInfo(self, request):
"""获取高防IP专业版资源的DDoS攻击事件详情
:param request: Request instance for DescribeDDoSNetEvInfo.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSNetEvInfoRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSNetEvInfoResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSNetEvInfo", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSNetEvInfoResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSNetEvList(self, request):
"""获取高防IP专业版资源的DDoS攻击事件列表
:param request: Request instance for DescribeDDoSNetEvList.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSNetEvListRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSNetEvListResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSNetEvList", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSNetEvListResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSNetIpLog(self, request):
"""获取高防IP专业版资源的DDoSIP攻击日志
:param request: Request instance for DescribeDDoSNetIpLog.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSNetIpLogRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSNetIpLogResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSNetIpLog", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSNetIpLogResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSNetTrend(self, request):
"""获取高防IP专业版资源的DDoS攻击指标数据
:param request: Request instance for DescribeDDoSNetTrend.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSNetTrendRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSNetTrendResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSNetTrend", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSNetTrendResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSPolicy(self, request):
"""获取DDoS高级策略
:param request: Request instance for DescribeDDoSPolicy.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSPolicyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSPolicyResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSPolicy", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSPolicyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSTrend(self, request):
"""获取DDoS攻击流量带宽和攻击包速率数据
:param request: Request instance for DescribeDDoSTrend.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSTrendRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSTrendResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSTrend", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSTrendResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSUsedStatis(self, request):
"""统计用户的高防资源的使用天数和DDoS攻击防护次数
:param request: Request instance for DescribeDDoSUsedStatis.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSUsedStatisRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSUsedStatisResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSUsedStatis", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSUsedStatisResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeIPProductInfo(self, request):
"""获取独享包或共享包IP对应的云资产信息，只支持独享包和共享包的IP
:param request: Request instance for DescribeIPProductInfo.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeIPProductInfoRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeIPProductInfoResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeIPProductInfo", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeIPProductInfoResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeInsurePacks(self, request):
"""获取保险包套餐列表
:param request: Request instance for DescribeInsurePacks.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeInsurePacksRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeInsurePacksResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeInsurePacks", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeInsurePacksResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeIpBlockList(self, request):
"""获取IP封堵列表
:param request: Request instance for DescribeIpBlockList.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeIpBlockListRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeIpBlockListResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeIpBlockList", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeIpBlockListResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeIpUnBlockList(self, request):
"""获取IP解封记录
:param request: Request instance for DescribeIpUnBlockList.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeIpUnBlockListRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeIpUnBlockListResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeIpUnBlockList", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeIpUnBlockListResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeL4HealthConfig(self, request):
"""导出四层健康检查配置
:param request: Request instance for DescribeL4HealthConfig.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeL4HealthConfigRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeL4HealthConfigResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeL4HealthConfig", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeL4HealthConfigResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeL4RulesErrHealth(self, request):
"""获取L4转发规则健康检查异常结果
:param request: Request instance for DescribeL4RulesErrHealth.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeL4RulesErrHealthRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeL4RulesErrHealthResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeL4RulesErrHealth", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeL4RulesErrHealthResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeL7HealthConfig(self, request):
"""导出七层健康检查配置
:param request: Request instance for DescribeL7HealthConfig.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeL7HealthConfigRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeL7HealthConfigResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeL7HealthConfig", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeL7HealthConfigResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribePackIndex(self, request):
"""获取产品总览统计，支持高防包、高防IP、高防IP专业版；
:param request: Request instance for DescribePackIndex.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribePackIndexRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribePackIndexResponse`
"""
try:
params = request._serialize()
body = self.call("DescribePackIndex", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribePackIndexResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribePcap(self, request):
"""下载攻击事件的pcap包
:param request: Request instance for DescribePcap.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribePcapRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribePcapResponse`
"""
try:
params = request._serialize()
body = self.call("DescribePcap", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribePcapResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribePolicyCase(self, request):
"""获取策略场景
:param request: Request instance for DescribePolicyCase.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribePolicyCaseRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribePolicyCaseResponse`
"""
try:
params = request._serialize()
body = self.call("DescribePolicyCase", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribePolicyCaseResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeResIpList(self, request):
"""获取资源的IP列表
:param request: Request instance for DescribeResIpList.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeResIpListRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeResIpListResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeResIpList", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeResIpListResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeResourceList(self, request):
"""获取资源列表
:param request: Request instance for DescribeResourceList.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeResourceListRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeResourceListResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeResourceList", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeResourceListResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeRuleSets(self, request):
"""获取资源的规则数
:param request: Request instance for DescribeRuleSets.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeRuleSetsRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeRuleSetsResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeRuleSets", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeRuleSetsResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeSecIndex(self, request):
"""获取本月安全统计
:param request: Request instance for DescribeSecIndex.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeSecIndexRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeSecIndexResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeSecIndex", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeSecIndexResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeSourceIpSegment(self, request):
"""获取回源IP段，支持的产品：高防IP，高防IP专业版；
:param request: Request instance for DescribeSourceIpSegment.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeSourceIpSegmentRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeSourceIpSegmentResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeSourceIpSegment", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeSourceIpSegmentResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeTransmitStatis(self, request):
"""获取业务转发统计数据，支持转发流量和转发包速率
:param request: Request instance for DescribeTransmitStatis.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeTransmitStatisRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeTransmitStatisResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeTransmitStatis", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeTransmitStatisResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeUnBlockStatis(self, request):
"""获取黑洞解封次数
:param request: Request instance for DescribeUnBlockStatis.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeUnBlockStatisRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeUnBlockStatisResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeUnBlockStatis", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeUnBlockStatisResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribleL4Rules(self, request):
"""获取四层转发规则
:param request: Request instance for DescribleL4Rules.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribleL4RulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribleL4RulesResponse`
"""
try:
params = request._serialize()
body = self.call("DescribleL4Rules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribleL4RulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribleL7Rules(self, request):
"""获取七层转发规则
:param request: Request instance for DescribleL7Rules.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribleL7RulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribleL7RulesResponse`
"""
try:
params = request._serialize()
body = self.call("DescribleL7Rules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribleL7RulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribleRegionCount(self, request):
"""获取地域的资源实例数
:param request: Request instance for DescribleRegionCount.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribleRegionCountRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribleRegionCountResponse`
"""
try:
params = request._serialize()
body = self.call("DescribleRegionCount", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribleRegionCountResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyCCAlarmThreshold(self, request):
"""为高防包、高防IP、高防IP专业版、棋牌盾产品设置CC攻击的告警通知阈值
:param request: Request instance for ModifyCCAlarmThreshold.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyCCAlarmThresholdRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyCCAlarmThresholdResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyCCAlarmThreshold", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyCCAlarmThresholdResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyCCFrequencyRules(self, request):
"""修改CC防护的访问频率控制规则
:param request: Request instance for ModifyCCFrequencyRules.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyCCFrequencyRulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyCCFrequencyRulesResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyCCFrequencyRules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyCCFrequencyRulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyCCFrequencyRulesStatus(self, request):
"""开启或关闭CC防护的访问频率控制规则
:param request: Request instance for ModifyCCFrequencyRulesStatus.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyCCFrequencyRulesStatusRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyCCFrequencyRulesStatusResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyCCFrequencyRulesStatus", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyCCFrequencyRulesStatusResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyCCHostProtection(self, request):
"""开启或关闭CC域名防护
:param request: Request instance for ModifyCCHostProtection.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyCCHostProtectionRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyCCHostProtectionResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyCCHostProtection", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyCCHostProtectionResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyCCIpAllowDeny(self, request):
"""添加或删除CC的IP黑白名单
:param request: Request instance for ModifyCCIpAllowDeny.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyCCIpAllowDenyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyCCIpAllowDenyResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyCCIpAllowDeny", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyCCIpAllowDenyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyCCLevel(self, request):
"""修改CC防护等级
:param request: Request instance for ModifyCCLevel.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyCCLevelRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyCCLevelResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyCCLevel", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyCCLevelResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyCCPolicySwitch(self, request):
"""修改CC自定义策略开关
:param request: Request instance for ModifyCCPolicySwitch.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyCCPolicySwitchRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyCCPolicySwitchResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyCCPolicySwitch", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyCCPolicySwitchResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyCCSelfDefinePolicy(self, request):
"""修改CC自定义策略
:param request: Request instance for ModifyCCSelfDefinePolicy.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyCCSelfDefinePolicyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyCCSelfDefinePolicyResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyCCSelfDefinePolicy", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyCCSelfDefinePolicyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyCCThreshold(self, request):
"""修改CC的防护阈值
:param request: Request instance for ModifyCCThreshold.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyCCThresholdRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyCCThresholdResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyCCThreshold", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyCCThresholdResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyCCUrlAllow(self, request):
"""添加或删除CC的URL白名单
:param request: Request instance for ModifyCCUrlAllow.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyCCUrlAllowRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyCCUrlAllowResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyCCUrlAllow", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyCCUrlAllowResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyDDoSAIStatus(self, request):
"""读取或修改DDoS的AI防护状态
:param request: Request instance for ModifyDDoSAIStatus.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSAIStatusRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSAIStatusResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyDDoSAIStatus", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyDDoSAIStatusResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyDDoSAlarmThreshold(self, request):
"""为高防包、高防IP、高防IP专业版、棋牌盾等产品设置DDoS攻击的告警通知阈值
:param request: Request instance for ModifyDDoSAlarmThreshold.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSAlarmThresholdRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSAlarmThresholdResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyDDoSAlarmThreshold", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyDDoSAlarmThresholdResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyDDoSDefendStatus(self, request):
"""开启或关闭DDoS防护状态，调用此接口允许临时关闭DDoS防护一段时间，等时间到了会自动开启DDoS防护；
:param request: Request instance for ModifyDDoSDefendStatus.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSDefendStatusRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSDefendStatusResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyDDoSDefendStatus", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyDDoSDefendStatusResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyDDoSLevel(self, request):
"""读取或修改DDoS的防护等级
:param request: Request instance for ModifyDDoSLevel.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSLevelRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSLevelResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyDDoSLevel", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyDDoSLevelResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyDDoSPolicy(self, request):
"""修改DDoS高级策略
:param request: Request instance for ModifyDDoSPolicy.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSPolicyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSPolicyResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyDDoSPolicy", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyDDoSPolicyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyDDoSPolicyCase(self, request):
"""修改策略场景
:param request: Request instance for ModifyDDoSPolicyCase.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSPolicyCaseRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSPolicyCaseResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyDDoSPolicyCase", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyDDoSPolicyCaseResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyDDoSPolicyName(self, request):
"""修改DDoS高级策略名称
:param request: Request instance for ModifyDDoSPolicyName.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSPolicyNameRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSPolicyNameResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyDDoSPolicyName", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyDDoSPolicyNameResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyDDoSSwitch(self, request):
"""开启或关闭DDoS防护，只支持基础防护产品；
:param request: Request instance for ModifyDDoSSwitch.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSSwitchRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSSwitchResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyDDoSSwitch", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyDDoSSwitchResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyDDoSThreshold(self, request):
"""修改DDoS清洗阈值
:param request: Request instance for ModifyDDoSThreshold.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSThresholdRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSThresholdResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyDDoSThreshold", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyDDoSThresholdResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyDDoSWaterKey(self, request):
"""支持水印密钥的添加，删除，开启，关闭
:param request: Request instance for ModifyDDoSWaterKey.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSWaterKeyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSWaterKeyResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyDDoSWaterKey", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyDDoSWaterKeyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyElasticLimit(self, request):
"""修改弹性防护阈值
:param request: Request instance for ModifyElasticLimit.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyElasticLimitRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyElasticLimitResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyElasticLimit", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyElasticLimitResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyL4Health(self, request):
"""修改L4转发规则健康检查参数，支持的子产品：高防IP、高防IP专业版
:param request: Request instance for ModifyL4Health.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyL4HealthRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyL4HealthResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyL4Health", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyL4HealthResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyL4KeepTime(self, request):
"""修改L4转发规则的会话保持，支持的子产品：高防IP、高防IP专业版
:param request: Request instance for ModifyL4KeepTime.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyL4KeepTimeRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyL4KeepTimeResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyL4KeepTime", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyL4KeepTimeResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyL4Rules(self, request):
"""修改L4转发规则
:param request: Request instance for ModifyL4Rules.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyL4RulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyL4RulesResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyL4Rules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyL4RulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyL7Rules(self, request):
"""修改L7转发规则
:param request: Request instance for ModifyL7Rules.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyL7RulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyL7RulesResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyL7Rules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyL7RulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyNetReturnSwitch(self, request):
"""在客户收攻击或者被封堵时，切回到源站，并设置回切的时长
:param request: Request instance for ModifyNetReturnSwitch.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyNetReturnSwitchRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyNetReturnSwitchResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyNetReturnSwitch", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyNetReturnSwitchResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyResBindDDoSPolicy(self, request):
"""资源实例绑定DDoS高级策略
:param request: Request instance for ModifyResBindDDoSPolicy.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyResBindDDoSPolicyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyResBindDDoSPolicyResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyResBindDDoSPolicy", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyResBindDDoSPolicyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyResourceRenewFlag(self, request):
"""修改资源自动续费标记
:param request: Request instance for ModifyResourceRenewFlag.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyResourceRenewFlagRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyResourceRenewFlagResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyResourceRenewFlag", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyResourceRenewFlagResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message) | tencentcloud/dayu/v20180709/dayu_client.py |
import json
from tencentcloud.common.exception.tencent_cloud_sdk_exception import TencentCloudSDKException
from tencentcloud.common.abstract_client import AbstractClient
from tencentcloud.dayu.v20180709 import models
class DayuClient(AbstractClient):
_apiVersion = '2018-07-09'
_endpoint = 'dayu.tencentcloudapi.com'
def CreateBasicDDoSAlarmThreshold(self, request):
"""设置基础防护的DDoS告警阈值，只支持基础防护产品
:param request: Request instance for CreateBasicDDoSAlarmThreshold.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateBasicDDoSAlarmThresholdRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateBasicDDoSAlarmThresholdResponse`
"""
try:
params = request._serialize()
body = self.call("CreateBasicDDoSAlarmThreshold", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateBasicDDoSAlarmThresholdResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateBoundIP(self, request):
"""绑定IP到高防包实例，支持独享包、共享包；需要注意的是此接口绑定或解绑IP是异步接口，当处于绑定或解绑中时，则不允许再进行绑定或解绑，需要等待当前绑定或解绑完成。
:param request: Request instance for CreateBoundIP.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateBoundIPRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateBoundIPResponse`
"""
try:
params = request._serialize()
body = self.call("CreateBoundIP", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateBoundIPResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateCCFrequencyRules(self, request):
"""添加CC防护的访问频率控制规则
:param request: Request instance for CreateCCFrequencyRules.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateCCFrequencyRulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateCCFrequencyRulesResponse`
"""
try:
params = request._serialize()
body = self.call("CreateCCFrequencyRules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateCCFrequencyRulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateCCSelfDefinePolicy(self, request):
"""创建CC自定义策略
:param request: Request instance for CreateCCSelfDefinePolicy.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateCCSelfDefinePolicyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateCCSelfDefinePolicyResponse`
"""
try:
params = request._serialize()
body = self.call("CreateCCSelfDefinePolicy", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateCCSelfDefinePolicyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateDDoSPolicy(self, request):
"""添加DDoS高级策略
:param request: Request instance for CreateDDoSPolicy.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateDDoSPolicyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateDDoSPolicyResponse`
"""
try:
params = request._serialize()
body = self.call("CreateDDoSPolicy", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateDDoSPolicyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateDDoSPolicyCase(self, request):
"""添加策略场景
:param request: Request instance for CreateDDoSPolicyCase.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateDDoSPolicyCaseRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateDDoSPolicyCaseResponse`
"""
try:
params = request._serialize()
body = self.call("CreateDDoSPolicyCase", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateDDoSPolicyCaseResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateInstanceName(self, request):
"""资源实例重命名，支持独享包、共享包、高防IP、高防IP专业版；
:param request: Request instance for CreateInstanceName.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateInstanceNameRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateInstanceNameResponse`
"""
try:
params = request._serialize()
body = self.call("CreateInstanceName", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateInstanceNameResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateL4HealthConfig(self, request):
"""上传四层健康检查配置
:param request: Request instance for CreateL4HealthConfig.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateL4HealthConfigRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateL4HealthConfigResponse`
"""
try:
params = request._serialize()
body = self.call("CreateL4HealthConfig", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateL4HealthConfigResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateL4Rules(self, request):
"""添加L4转发规则
:param request: Request instance for CreateL4Rules.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateL4RulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateL4RulesResponse`
"""
try:
params = request._serialize()
body = self.call("CreateL4Rules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateL4RulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateL7CCRule(self, request):
"""此接口是7层CC的访问频控自定义规则（IP+Host维度，不支持具体的URI），此接口已弃用，请调用新接口CreateCCFrequencyRules，新接口同时支持IP+Host维度以及具体的URI；
:param request: Request instance for CreateL7CCRule.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateL7CCRuleRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateL7CCRuleResponse`
"""
try:
params = request._serialize()
body = self.call("CreateL7CCRule", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateL7CCRuleResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateL7HealthConfig(self, request):
"""上传七层健康检查配置
:param request: Request instance for CreateL7HealthConfig.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateL7HealthConfigRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateL7HealthConfigResponse`
"""
try:
params = request._serialize()
body = self.call("CreateL7HealthConfig", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateL7HealthConfigResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateL7RuleCert(self, request):
"""配置7层转发规则的证书
:param request: Request instance for CreateL7RuleCert.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateL7RuleCertRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateL7RuleCertResponse`
"""
try:
params = request._serialize()
body = self.call("CreateL7RuleCert", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateL7RuleCertResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateL7Rules(self, request):
"""添加7层(网站)转发规则
:param request: Request instance for CreateL7Rules.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateL7RulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateL7RulesResponse`
"""
try:
params = request._serialize()
body = self.call("CreateL7Rules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateL7RulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateL7RulesUpload(self, request):
"""批量上传7层转发规则
:param request: Request instance for CreateL7RulesUpload.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateL7RulesUploadRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateL7RulesUploadResponse`
"""
try:
params = request._serialize()
body = self.call("CreateL7RulesUpload", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateL7RulesUploadResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateNetReturn(self, request):
"""高防IP专业版一键切回源站
:param request: Request instance for CreateNetReturn.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateNetReturnRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateNetReturnResponse`
"""
try:
params = request._serialize()
body = self.call("CreateNetReturn", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateNetReturnResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def CreateUnblockIp(self, request):
"""IP解封操作
:param request: Request instance for CreateUnblockIp.
:type request: :class:`tencentcloud.dayu.v20180709.models.CreateUnblockIpRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.CreateUnblockIpResponse`
"""
try:
params = request._serialize()
body = self.call("CreateUnblockIp", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateUnblockIpResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DeleteCCFrequencyRules(self, request):
"""删除CC防护的访问频率控制规则
:param request: Request instance for DeleteCCFrequencyRules.
:type request: :class:`tencentcloud.dayu.v20180709.models.DeleteCCFrequencyRulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DeleteCCFrequencyRulesResponse`
"""
try:
params = request._serialize()
body = self.call("DeleteCCFrequencyRules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DeleteCCFrequencyRulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DeleteCCSelfDefinePolicy(self, request):
"""删除CC自定义策略
:param request: Request instance for DeleteCCSelfDefinePolicy.
:type request: :class:`tencentcloud.dayu.v20180709.models.DeleteCCSelfDefinePolicyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DeleteCCSelfDefinePolicyResponse`
"""
try:
params = request._serialize()
body = self.call("DeleteCCSelfDefinePolicy", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DeleteCCSelfDefinePolicyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DeleteDDoSPolicy(self, request):
"""删除DDoS高级策略
:param request: Request instance for DeleteDDoSPolicy.
:type request: :class:`tencentcloud.dayu.v20180709.models.DeleteDDoSPolicyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DeleteDDoSPolicyResponse`
"""
try:
params = request._serialize()
body = self.call("DeleteDDoSPolicy", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DeleteDDoSPolicyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DeleteDDoSPolicyCase(self, request):
"""删除策略场景
:param request: Request instance for DeleteDDoSPolicyCase.
:type request: :class:`tencentcloud.dayu.v20180709.models.DeleteDDoSPolicyCaseRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DeleteDDoSPolicyCaseResponse`
"""
try:
params = request._serialize()
body = self.call("DeleteDDoSPolicyCase", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DeleteDDoSPolicyCaseResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DeleteL4Rules(self, request):
"""删除四层转发规则
:param request: Request instance for DeleteL4Rules.
:type request: :class:`tencentcloud.dayu.v20180709.models.DeleteL4RulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DeleteL4RulesResponse`
"""
try:
params = request._serialize()
body = self.call("DeleteL4Rules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DeleteL4RulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DeleteL7Rules(self, request):
"""删除七层转发规则
:param request: Request instance for DeleteL7Rules.
:type request: :class:`tencentcloud.dayu.v20180709.models.DeleteL7RulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DeleteL7RulesResponse`
"""
try:
params = request._serialize()
body = self.call("DeleteL7Rules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DeleteL7RulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeActionLog(self, request):
"""获取操作日志
:param request: Request instance for DescribeActionLog.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeActionLogRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeActionLogResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeActionLog", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeActionLogResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeBaradData(self, request):
"""为大禹子产品提供业务转发指标数据的接口
:param request: Request instance for DescribeBaradData.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeBaradDataRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeBaradDataResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeBaradData", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeBaradDataResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeBasicCCThreshold(self, request):
"""获取基础防护CC防护阈值
:param request: Request instance for DescribeBasicCCThreshold.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeBasicCCThresholdRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeBasicCCThresholdResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeBasicCCThreshold", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeBasicCCThresholdResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeBasicDeviceThreshold(self, request):
"""获取基础防护黑洞阈值
:param request: Request instance for DescribeBasicDeviceThreshold.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeBasicDeviceThresholdRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeBasicDeviceThresholdResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeBasicDeviceThreshold", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeBasicDeviceThresholdResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeCCAlarmThreshold(self, request):
"""获取高防包、高防IP、高防IP专业版、棋牌盾产品设置CC攻击的告警通知阈值
:param request: Request instance for DescribeCCAlarmThreshold.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeCCAlarmThresholdRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeCCAlarmThresholdResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeCCAlarmThreshold", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeCCAlarmThresholdResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeCCEvList(self, request):
"""获取CC攻击事件列表
:param request: Request instance for DescribeCCEvList.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeCCEvListRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeCCEvListResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeCCEvList", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeCCEvListResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeCCFrequencyRules(self, request):
"""获取CC防护的访问频率控制规则
:param request: Request instance for DescribeCCFrequencyRules.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeCCFrequencyRulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeCCFrequencyRulesResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeCCFrequencyRules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeCCFrequencyRulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeCCIpAllowDeny(self, request):
"""获取CC的IP黑白名单
:param request: Request instance for DescribeCCIpAllowDeny.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeCCIpAllowDenyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeCCIpAllowDenyResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeCCIpAllowDeny", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeCCIpAllowDenyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeCCSelfDefinePolicy(self, request):
"""获取CC自定义策略
:param request: Request instance for DescribeCCSelfDefinePolicy.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeCCSelfDefinePolicyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeCCSelfDefinePolicyResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeCCSelfDefinePolicy", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeCCSelfDefinePolicyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeCCTrend(self, request):
"""获取CC攻击指标数据，包括总请求峰值(QPS)和攻击请求(QPS)
:param request: Request instance for DescribeCCTrend.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeCCTrendRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeCCTrendResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeCCTrend", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeCCTrendResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeCCUrlAllow(self, request):
"""获取CC的Url白名单
:param request: Request instance for DescribeCCUrlAllow.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeCCUrlAllowRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeCCUrlAllowResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeCCUrlAllow", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeCCUrlAllowResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSAlarmThreshold(self, request):
"""获取高防包、高防IP、高防IP专业版、棋牌盾产品设置DDoS攻击的告警通知阈值
:param request: Request instance for DescribeDDoSAlarmThreshold.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSAlarmThresholdRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSAlarmThresholdResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSAlarmThreshold", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSAlarmThresholdResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSAttackIPRegionMap(self, request):
"""获取DDoS攻击源IP地域分布图，支持全球攻击分布和国内省份攻击分布；
:param request: Request instance for DescribeDDoSAttackIPRegionMap.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSAttackIPRegionMapRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSAttackIPRegionMapResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSAttackIPRegionMap", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSAttackIPRegionMapResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSAttackSource(self, request):
"""获取DDoS攻击源列表
:param request: Request instance for DescribeDDoSAttackSource.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSAttackSourceRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSAttackSourceResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSAttackSource", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSAttackSourceResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSCount(self, request):
"""获取DDoS攻击占比分析
:param request: Request instance for DescribeDDoSCount.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSCountRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSCountResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSCount", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSCountResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSDefendStatus(self, request):
"""获取DDoS防护状态（临时关闭状态），支持产品：基础防护，独享包，共享包，高防IP，高防IP专业版；调用此接口是获取当前是否有设置临时关闭DDoS防护状态，如果有设置会返回临时关闭的时长等参数。
:param request: Request instance for DescribeDDoSDefendStatus.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSDefendStatusRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSDefendStatusResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSDefendStatus", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSDefendStatusResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSEvInfo(self, request):
"""获取DDoS攻击事件详情
:param request: Request instance for DescribeDDoSEvInfo.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSEvInfoRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSEvInfoResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSEvInfo", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSEvInfoResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSEvList(self, request):
"""获取DDoS攻击事件列表
:param request: Request instance for DescribeDDoSEvList.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSEvListRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSEvListResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSEvList", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSEvListResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSIpLog(self, request):
"""获取DDoSIP攻击日志
:param request: Request instance for DescribeDDoSIpLog.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSIpLogRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSIpLogResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSIpLog", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSIpLogResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSNetCount(self, request):
"""获取高防IP专业版资源的DDoS攻击占比分析
:param request: Request instance for DescribeDDoSNetCount.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSNetCountRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSNetCountResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSNetCount", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSNetCountResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSNetEvInfo(self, request):
"""获取高防IP专业版资源的DDoS攻击事件详情
:param request: Request instance for DescribeDDoSNetEvInfo.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSNetEvInfoRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSNetEvInfoResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSNetEvInfo", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSNetEvInfoResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSNetEvList(self, request):
"""获取高防IP专业版资源的DDoS攻击事件列表
:param request: Request instance for DescribeDDoSNetEvList.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSNetEvListRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSNetEvListResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSNetEvList", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSNetEvListResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSNetIpLog(self, request):
"""获取高防IP专业版资源的DDoSIP攻击日志
:param request: Request instance for DescribeDDoSNetIpLog.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSNetIpLogRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSNetIpLogResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSNetIpLog", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSNetIpLogResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSNetTrend(self, request):
"""获取高防IP专业版资源的DDoS攻击指标数据
:param request: Request instance for DescribeDDoSNetTrend.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSNetTrendRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSNetTrendResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSNetTrend", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSNetTrendResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSPolicy(self, request):
"""获取DDoS高级策略
:param request: Request instance for DescribeDDoSPolicy.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSPolicyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSPolicyResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSPolicy", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSPolicyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSTrend(self, request):
"""获取DDoS攻击流量带宽和攻击包速率数据
:param request: Request instance for DescribeDDoSTrend.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSTrendRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSTrendResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSTrend", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSTrendResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeDDoSUsedStatis(self, request):
"""统计用户的高防资源的使用天数和DDoS攻击防护次数
:param request: Request instance for DescribeDDoSUsedStatis.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSUsedStatisRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeDDoSUsedStatisResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeDDoSUsedStatis", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeDDoSUsedStatisResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeIPProductInfo(self, request):
"""获取独享包或共享包IP对应的云资产信息，只支持独享包和共享包的IP
:param request: Request instance for DescribeIPProductInfo.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeIPProductInfoRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeIPProductInfoResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeIPProductInfo", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeIPProductInfoResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeInsurePacks(self, request):
"""获取保险包套餐列表
:param request: Request instance for DescribeInsurePacks.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeInsurePacksRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeInsurePacksResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeInsurePacks", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeInsurePacksResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeIpBlockList(self, request):
"""获取IP封堵列表
:param request: Request instance for DescribeIpBlockList.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeIpBlockListRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeIpBlockListResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeIpBlockList", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeIpBlockListResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeIpUnBlockList(self, request):
"""获取IP解封记录
:param request: Request instance for DescribeIpUnBlockList.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeIpUnBlockListRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeIpUnBlockListResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeIpUnBlockList", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeIpUnBlockListResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeL4HealthConfig(self, request):
"""导出四层健康检查配置
:param request: Request instance for DescribeL4HealthConfig.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeL4HealthConfigRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeL4HealthConfigResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeL4HealthConfig", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeL4HealthConfigResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeL4RulesErrHealth(self, request):
"""获取L4转发规则健康检查异常结果
:param request: Request instance for DescribeL4RulesErrHealth.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeL4RulesErrHealthRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeL4RulesErrHealthResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeL4RulesErrHealth", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeL4RulesErrHealthResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeL7HealthConfig(self, request):
"""导出七层健康检查配置
:param request: Request instance for DescribeL7HealthConfig.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeL7HealthConfigRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeL7HealthConfigResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeL7HealthConfig", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeL7HealthConfigResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribePackIndex(self, request):
"""获取产品总览统计，支持高防包、高防IP、高防IP专业版；
:param request: Request instance for DescribePackIndex.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribePackIndexRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribePackIndexResponse`
"""
try:
params = request._serialize()
body = self.call("DescribePackIndex", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribePackIndexResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribePcap(self, request):
"""下载攻击事件的pcap包
:param request: Request instance for DescribePcap.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribePcapRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribePcapResponse`
"""
try:
params = request._serialize()
body = self.call("DescribePcap", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribePcapResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribePolicyCase(self, request):
"""获取策略场景
:param request: Request instance for DescribePolicyCase.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribePolicyCaseRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribePolicyCaseResponse`
"""
try:
params = request._serialize()
body = self.call("DescribePolicyCase", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribePolicyCaseResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeResIpList(self, request):
"""获取资源的IP列表
:param request: Request instance for DescribeResIpList.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeResIpListRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeResIpListResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeResIpList", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeResIpListResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeResourceList(self, request):
"""获取资源列表
:param request: Request instance for DescribeResourceList.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeResourceListRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeResourceListResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeResourceList", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeResourceListResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeRuleSets(self, request):
"""获取资源的规则数
:param request: Request instance for DescribeRuleSets.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeRuleSetsRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeRuleSetsResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeRuleSets", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeRuleSetsResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeSecIndex(self, request):
"""获取本月安全统计
:param request: Request instance for DescribeSecIndex.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeSecIndexRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeSecIndexResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeSecIndex", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeSecIndexResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeSourceIpSegment(self, request):
"""获取回源IP段，支持的产品：高防IP，高防IP专业版；
:param request: Request instance for DescribeSourceIpSegment.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeSourceIpSegmentRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeSourceIpSegmentResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeSourceIpSegment", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeSourceIpSegmentResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeTransmitStatis(self, request):
"""获取业务转发统计数据，支持转发流量和转发包速率
:param request: Request instance for DescribeTransmitStatis.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeTransmitStatisRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeTransmitStatisResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeTransmitStatis", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeTransmitStatisResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribeUnBlockStatis(self, request):
"""获取黑洞解封次数
:param request: Request instance for DescribeUnBlockStatis.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribeUnBlockStatisRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribeUnBlockStatisResponse`
"""
try:
params = request._serialize()
body = self.call("DescribeUnBlockStatis", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribeUnBlockStatisResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribleL4Rules(self, request):
"""获取四层转发规则
:param request: Request instance for DescribleL4Rules.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribleL4RulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribleL4RulesResponse`
"""
try:
params = request._serialize()
body = self.call("DescribleL4Rules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribleL4RulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribleL7Rules(self, request):
"""获取七层转发规则
:param request: Request instance for DescribleL7Rules.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribleL7RulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribleL7RulesResponse`
"""
try:
params = request._serialize()
body = self.call("DescribleL7Rules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribleL7RulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def DescribleRegionCount(self, request):
"""获取地域的资源实例数
:param request: Request instance for DescribleRegionCount.
:type request: :class:`tencentcloud.dayu.v20180709.models.DescribleRegionCountRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.DescribleRegionCountResponse`
"""
try:
params = request._serialize()
body = self.call("DescribleRegionCount", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.DescribleRegionCountResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyCCAlarmThreshold(self, request):
"""为高防包、高防IP、高防IP专业版、棋牌盾产品设置CC攻击的告警通知阈值
:param request: Request instance for ModifyCCAlarmThreshold.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyCCAlarmThresholdRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyCCAlarmThresholdResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyCCAlarmThreshold", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyCCAlarmThresholdResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyCCFrequencyRules(self, request):
"""修改CC防护的访问频率控制规则
:param request: Request instance for ModifyCCFrequencyRules.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyCCFrequencyRulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyCCFrequencyRulesResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyCCFrequencyRules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyCCFrequencyRulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyCCFrequencyRulesStatus(self, request):
"""开启或关闭CC防护的访问频率控制规则
:param request: Request instance for ModifyCCFrequencyRulesStatus.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyCCFrequencyRulesStatusRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyCCFrequencyRulesStatusResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyCCFrequencyRulesStatus", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyCCFrequencyRulesStatusResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyCCHostProtection(self, request):
"""开启或关闭CC域名防护
:param request: Request instance for ModifyCCHostProtection.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyCCHostProtectionRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyCCHostProtectionResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyCCHostProtection", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyCCHostProtectionResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyCCIpAllowDeny(self, request):
"""添加或删除CC的IP黑白名单
:param request: Request instance for ModifyCCIpAllowDeny.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyCCIpAllowDenyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyCCIpAllowDenyResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyCCIpAllowDeny", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyCCIpAllowDenyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyCCLevel(self, request):
"""修改CC防护等级
:param request: Request instance for ModifyCCLevel.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyCCLevelRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyCCLevelResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyCCLevel", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyCCLevelResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyCCPolicySwitch(self, request):
"""修改CC自定义策略开关
:param request: Request instance for ModifyCCPolicySwitch.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyCCPolicySwitchRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyCCPolicySwitchResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyCCPolicySwitch", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyCCPolicySwitchResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyCCSelfDefinePolicy(self, request):
"""修改CC自定义策略
:param request: Request instance for ModifyCCSelfDefinePolicy.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyCCSelfDefinePolicyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyCCSelfDefinePolicyResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyCCSelfDefinePolicy", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyCCSelfDefinePolicyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyCCThreshold(self, request):
"""修改CC的防护阈值
:param request: Request instance for ModifyCCThreshold.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyCCThresholdRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyCCThresholdResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyCCThreshold", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyCCThresholdResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyCCUrlAllow(self, request):
"""添加或删除CC的URL白名单
:param request: Request instance for ModifyCCUrlAllow.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyCCUrlAllowRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyCCUrlAllowResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyCCUrlAllow", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyCCUrlAllowResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyDDoSAIStatus(self, request):
"""读取或修改DDoS的AI防护状态
:param request: Request instance for ModifyDDoSAIStatus.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSAIStatusRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSAIStatusResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyDDoSAIStatus", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyDDoSAIStatusResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyDDoSAlarmThreshold(self, request):
"""为高防包、高防IP、高防IP专业版、棋牌盾等产品设置DDoS攻击的告警通知阈值
:param request: Request instance for ModifyDDoSAlarmThreshold.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSAlarmThresholdRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSAlarmThresholdResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyDDoSAlarmThreshold", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyDDoSAlarmThresholdResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyDDoSDefendStatus(self, request):
"""开启或关闭DDoS防护状态，调用此接口允许临时关闭DDoS防护一段时间，等时间到了会自动开启DDoS防护；
:param request: Request instance for ModifyDDoSDefendStatus.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSDefendStatusRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSDefendStatusResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyDDoSDefendStatus", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyDDoSDefendStatusResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyDDoSLevel(self, request):
"""读取或修改DDoS的防护等级
:param request: Request instance for ModifyDDoSLevel.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSLevelRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSLevelResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyDDoSLevel", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyDDoSLevelResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyDDoSPolicy(self, request):
"""修改DDoS高级策略
:param request: Request instance for ModifyDDoSPolicy.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSPolicyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSPolicyResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyDDoSPolicy", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyDDoSPolicyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyDDoSPolicyCase(self, request):
"""修改策略场景
:param request: Request instance for ModifyDDoSPolicyCase.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSPolicyCaseRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSPolicyCaseResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyDDoSPolicyCase", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyDDoSPolicyCaseResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyDDoSPolicyName(self, request):
"""修改DDoS高级策略名称
:param request: Request instance for ModifyDDoSPolicyName.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSPolicyNameRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSPolicyNameResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyDDoSPolicyName", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyDDoSPolicyNameResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyDDoSSwitch(self, request):
"""开启或关闭DDoS防护，只支持基础防护产品；
:param request: Request instance for ModifyDDoSSwitch.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSSwitchRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSSwitchResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyDDoSSwitch", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyDDoSSwitchResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyDDoSThreshold(self, request):
"""修改DDoS清洗阈值
:param request: Request instance for ModifyDDoSThreshold.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSThresholdRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSThresholdResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyDDoSThreshold", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyDDoSThresholdResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyDDoSWaterKey(self, request):
"""支持水印密钥的添加，删除，开启，关闭
:param request: Request instance for ModifyDDoSWaterKey.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSWaterKeyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyDDoSWaterKeyResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyDDoSWaterKey", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyDDoSWaterKeyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyElasticLimit(self, request):
"""修改弹性防护阈值
:param request: Request instance for ModifyElasticLimit.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyElasticLimitRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyElasticLimitResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyElasticLimit", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyElasticLimitResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyL4Health(self, request):
"""修改L4转发规则健康检查参数，支持的子产品：高防IP、高防IP专业版
:param request: Request instance for ModifyL4Health.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyL4HealthRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyL4HealthResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyL4Health", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyL4HealthResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyL4KeepTime(self, request):
"""修改L4转发规则的会话保持，支持的子产品：高防IP、高防IP专业版
:param request: Request instance for ModifyL4KeepTime.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyL4KeepTimeRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyL4KeepTimeResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyL4KeepTime", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyL4KeepTimeResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyL4Rules(self, request):
"""修改L4转发规则
:param request: Request instance for ModifyL4Rules.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyL4RulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyL4RulesResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyL4Rules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyL4RulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyL7Rules(self, request):
"""修改L7转发规则
:param request: Request instance for ModifyL7Rules.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyL7RulesRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyL7RulesResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyL7Rules", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyL7RulesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyNetReturnSwitch(self, request):
"""在客户收攻击或者被封堵时，切回到源站，并设置回切的时长
:param request: Request instance for ModifyNetReturnSwitch.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyNetReturnSwitchRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyNetReturnSwitchResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyNetReturnSwitch", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyNetReturnSwitchResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyResBindDDoSPolicy(self, request):
"""资源实例绑定DDoS高级策略
:param request: Request instance for ModifyResBindDDoSPolicy.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyResBindDDoSPolicyRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyResBindDDoSPolicyResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyResBindDDoSPolicy", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyResBindDDoSPolicyResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message)
def ModifyResourceRenewFlag(self, request):
"""修改资源自动续费标记
:param request: Request instance for ModifyResourceRenewFlag.
:type request: :class:`tencentcloud.dayu.v20180709.models.ModifyResourceRenewFlagRequest`
:rtype: :class:`tencentcloud.dayu.v20180709.models.ModifyResourceRenewFlagResponse`
"""
try:
params = request._serialize()
body = self.call("ModifyResourceRenewFlag", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifyResourceRenewFlagResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message) | 0.324128 | 0.055158 |
import os
import re
import sys
import glob
if len(sys.argv) < 2 or sys.argv[1] != 'YES!':
print('CAUTION: running this will alter **ALL** .py files in every subdirectory!')
print('To ensure you are certain you want to run it, call %s again with the argument "YES!"' % sys.argv[0])
sys.exit(1)
re_function = re.compile(r'\n(?P<indent> *)(?P<pr>@profiler\.function)\n')
re_add_note = re.compile(r'\n(?P<indent> *)(?P<pr>profiler\.add_note\(.*?\))\n')
re_withcode = re.compile(r'\n(?P<indent> *)(?P<pr>with profiler\.code\(.*?\)( +as +.*?)?:)\n')
re_dprint = re.compile(r'\n(?P<indent> *)(?P<dp>(Debugger\.)?dprint\(.*?\))\n')
ignore_pyfiles = {
'profiler.py',
'debug.py',
}
ignore_folders = {
'__pycache__',
}
def go(root):
for fn in glob.glob('*.py'):
if fn in ignore_pyfiles: continue
f = open(fn, 'rt').read()
of = str(f)
while True:
m = re_function.search(f)
if not m: break
replace = '\n%s# %s\n' % (m.group('indent'), m.group('pr'))
f = f[:m.start()] + replace + f[m.end():]
while True:
m = re_add_note.search(f)
if not m: break
replace = '\n%s# %s\n' % (m.group('indent'), m.group('pr'))
f = f[:m.start()] + replace + f[m.end():]
while True:
m = re_withcode.search(f)
if not m: break
replace = '\n%sif True: # %s\n' % (m.group('indent'), m.group('pr'))
f = f[:m.start()] + replace + f[m.end():]
while True:
m = re_dprint.search(f)
if not m: break
replace = '\n%s# %s\n%spass\n' % (m.group('indent'), m.group('dp'), m.group('indent'))
f = f[:m.start()] + replace + f[m.end():]
if f == of: continue
open(fn, 'wt').write(f)
for fn in glob.glob('*'):
if not os.path.isdir(fn): continue
if fn in ignore_folders: continue
os.chdir(fn)
go(os.path.join(root, fn))
os.chdir('..')
go('.') | addon_common/scripts/strip_debugging.py |
import os
import re
import sys
import glob
if len(sys.argv) < 2 or sys.argv[1] != 'YES!':
print('CAUTION: running this will alter **ALL** .py files in every subdirectory!')
print('To ensure you are certain you want to run it, call %s again with the argument "YES!"' % sys.argv[0])
sys.exit(1)
re_function = re.compile(r'\n(?P<indent> *)(?P<pr>@profiler\.function)\n')
re_add_note = re.compile(r'\n(?P<indent> *)(?P<pr>profiler\.add_note\(.*?\))\n')
re_withcode = re.compile(r'\n(?P<indent> *)(?P<pr>with profiler\.code\(.*?\)( +as +.*?)?:)\n')
re_dprint = re.compile(r'\n(?P<indent> *)(?P<dp>(Debugger\.)?dprint\(.*?\))\n')
ignore_pyfiles = {
'profiler.py',
'debug.py',
}
ignore_folders = {
'__pycache__',
}
def go(root):
for fn in glob.glob('*.py'):
if fn in ignore_pyfiles: continue
f = open(fn, 'rt').read()
of = str(f)
while True:
m = re_function.search(f)
if not m: break
replace = '\n%s# %s\n' % (m.group('indent'), m.group('pr'))
f = f[:m.start()] + replace + f[m.end():]
while True:
m = re_add_note.search(f)
if not m: break
replace = '\n%s# %s\n' % (m.group('indent'), m.group('pr'))
f = f[:m.start()] + replace + f[m.end():]
while True:
m = re_withcode.search(f)
if not m: break
replace = '\n%sif True: # %s\n' % (m.group('indent'), m.group('pr'))
f = f[:m.start()] + replace + f[m.end():]
while True:
m = re_dprint.search(f)
if not m: break
replace = '\n%s# %s\n%spass\n' % (m.group('indent'), m.group('dp'), m.group('indent'))
f = f[:m.start()] + replace + f[m.end():]
if f == of: continue
open(fn, 'wt').write(f)
for fn in glob.glob('*'):
if not os.path.isdir(fn): continue
if fn in ignore_folders: continue
os.chdir(fn)
go(os.path.join(root, fn))
os.chdir('..')
go('.') | 0.150029 | 0.082401 |
import mock
from six.moves import http_client
import sys
from cinder import context
from cinder import exception
from cinder.objects import volume as obj_volume
from cinder import test
from cinder.tests.unit import fake_constants as fake
from cinder.volume.drivers import nimble
from cinder.volume import volume_types
NIMBLE_CLIENT = 'cinder.volume.drivers.nimble.NimbleRestAPIExecutor'
NIMBLE_URLLIB2 = 'cinder.volume.drivers.nimble.requests'
NIMBLE_RANDOM = 'cinder.volume.drivers.nimble.random'
NIMBLE_ISCSI_DRIVER = 'cinder.volume.drivers.nimble.NimbleISCSIDriver'
NIMBLE_FC_DRIVER = 'cinder.volume.drivers.nimble.NimbleFCDriver'
DRIVER_VERSION = '4.0.1'
nimble.DEFAULT_SLEEP = 0
FAKE_POSITIVE_LOGIN_RESPONSE_1 = '2c20aad78a220ed1dae21dcd6f9446f5'
FAKE_POSITIVE_LOGIN_RESPONSE_2 = '2c20aad78a220ed1dae21dcd6f9446ff'
FAKE_POSITIVE_HEADERS = {'X-Auth-Token': FAKE_POSITIVE_LOGIN_RESPONSE_1}
FAKE_POSITIVE_NETCONFIG_RESPONSE = {
'role': 'active',
'subnet_list': [{'network': '172.18.212.0',
'discovery_ip': '172.18.108.21',
'type': 'data',
'allow_iscsi': True,
'label': 'data1',
'allow_group': True,
'vlan_id': 0}],
'array_list': [{'nic_list': [{'subnet_label': 'data1',
'tagged': False,
'data_ip': '172.18.212.82',
'name': 'eth3'}]}],
'name': 'test-array'}
FAKE_NEGATIVE_NETCONFIG_RESPONSE = exception.VolumeDriverException(
"Session expired")
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE = {
'clone': False,
'name': "testvolume"}
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE_ENCRYPTION = {
'clone': False,
'name': "testvolume-encryption"}
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE_PERF_POLICY = {
'clone': False,
'name': "testvolume-perf-policy"}
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE_MULTI_INITIATOR = {
'clone': False,
'name': "testvolume-multi-initiator"}
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE_DEDUPE = {
'clone': False,
'name': "testvolume-dedupe"}
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE_QOS = {
'clone': False,
'name': "testvolume-qos"}
FAKE_GET_VOL_INFO_RESPONSE = {'name': 'testvolume',
'clone': False,
'target_name': 'iqn.test',
'online': True,
'agent_type': 'openstack'}
FAKE_GET_VOL_INFO_RESPONSE_MANAGE = {'name': 'testvolume',
'agent_type': 'none',
'online': False,
'target_name': 'iqn.test'}
FAKE_GET_VOL_INFO_ONLINE = {'name': 'testvolume',
'size': 2048,
'online': True,
'agent_type': 'none'}
FAKE_GET_VOL_INFO_BACKUP_RESPONSE = {'name': 'testvolume',
'clone': True,
'target_name': 'iqn.test',
'online': False,
'agent_type': 'openstack',
'parent_vol_id': 'volume-' +
fake.VOLUME2_ID,
'base_snap_id': 'test-backup-snap'}
FAKE_GET_SNAP_INFO_BACKUP_RESPONSE = {
'description': "backup-vol-" + fake.VOLUME2_ID,
'name': 'test-backup-snap',
'id': fake.SNAPSHOT_ID,
'vol_id': fake.VOLUME_ID,
'volume_name': 'volume-' + fake.VOLUME_ID}
FAKE_POSITIVE_GROUP_CONFIG_RESPONSE = {
'name': 'group-test',
'version_current': '0.0.0.0',
'access_protocol_list': ['iscsi']}
FAKE_LOGIN_POST_RESPONSE = {
'data': {'session_token': FAKE_POSITIVE_LOGIN_RESPONSE_1}}
FAKE_EXTEND_VOLUME_PARAMS = {'data': {'size': 5120,
'reserve': 0,
'warn_level': 80,
'limit': 100,
'snap_limit': sys.maxsize}}
FAKE_IGROUP_LIST_RESPONSE = [
{'iscsi_initiators': [{'iqn': 'test-initiator1'}],
'name': 'test-igrp1'},
{'iscsi_initiators': [{'iqn': 'test-initiator2'}],
'name': 'test-igrp2'}]
FAKE_IGROUP_LIST_RESPONSE_FC = [
{'fc_initiators': [{'wwpn': 'fd00:a516:7c1b:17cd:6d81:2137:bd2a:2c5b'}],
'name': 'test-igrp1'},
{'fc_initiators': [{'wwpn': 'fd00:a516:7c1b:17cd:6d81:2137:bd2a:2c5b'},
{'wwpn': 'fc00:e968:6179::de52:7100'}],
'name': 'test-igrp2'}]
FAKE_CREATE_VOLUME_NEGATIVE_RESPONSE = exception.VolumeBackendAPIException(
"Volume testvolume not found")
FAKE_VOLUME_INFO_NEGATIVE_RESPONSE = exception.VolumeBackendAPIException(
"Volume testvolume not found")
FAKE_CREATE_VOLUME_NEGATIVE_ENCRYPTION = exception.VolumeBackendAPIException(
"Volume testvolume-encryption not found")
FAKE_CREATE_VOLUME_NEGATIVE_PERFPOLICY = exception.VolumeBackendAPIException(
"Volume testvolume-perfpolicy not found")
FAKE_CREATE_VOLUME_NEGATIVE_DEDUPE = exception.VolumeBackendAPIException(
"The specified pool is not capable of hosting deduplicated volumes")
FAKE_CREATE_VOLUME_NEGATIVE_QOS = exception.VolumeBackendAPIException(
"Please set valid IOPS limitin the range [256, 4294967294]")
FAKE_POSITIVE_GROUP_INFO_RESPONSE = {
'version_current': '3.0.0.0',
'group_target_enabled': False,
'name': 'group-nimble',
'usage_valid': True,
'usable_capacity_bytes': 8016883089408,
'compressed_vol_usage_bytes': 2938311843,
'compressed_snap_usage_bytes': 36189,
'unused_reserve_bytes': 0}
FAKE_GENERIC_POSITIVE_RESPONSE = ""
FAKE_VOLUME_DELETE_HAS_CLONE_RESPONSE = "Object has a clone"
FAKE_TYPE_ID = fake.VOLUME_TYPE_ID
FAKE_POOL_ID = fake.GROUP_ID
FAKE_PERFORMANCE_POLICY_ID = fake.OBJECT_ID
NIMBLE_MANAGEMENT_IP = "10.18.108.55"
NIMBLE_SAN_LOGIN = "nimble"
NIMBLE_SAN_PASS = "<PASSWORD>"
def create_configuration(username, password, ip_address,
pool_name=None, subnet_label=None,
thin_provision=True):
configuration = mock.Mock()
configuration.san_login = username
configuration.san_password = password
configuration.san_ip = ip_address
configuration.san_thin_provision = thin_provision
configuration.nimble_pool_name = pool_name
configuration.nimble_subnet_label = subnet_label
configuration.safe_get.return_value = 'NIMBLE'
return configuration
class NimbleDriverBaseTestCase(test.TestCase):
"""Base Class for the NimbleDriver Tests."""
def setUp(self):
super(NimbleDriverBaseTestCase, self).setUp()
self.mock_client_service = None
self.mock_client_class = None
self.driver = None
@staticmethod
def client_mock_decorator(configuration):
def client_mock_wrapper(func):
def inner_client_mock(
self, mock_client_class, mock_urllib2, *args, **kwargs):
self.mock_client_class = mock_client_class
self.mock_client_service = mock.MagicMock(name='Client')
self.mock_client_class.return_value = self.mock_client_service
self.driver = nimble.NimbleISCSIDriver(
configuration=configuration)
mock_login_response = mock_urllib2.post.return_value
mock_login_response = mock.MagicMock()
mock_login_response.status_code.return_value = http_client.OK
mock_login_response.json.return_value = (
FAKE_LOGIN_POST_RESPONSE)
self.driver.do_setup(context.get_admin_context())
self.driver.APIExecutor.login()
func(self, *args, **kwargs)
return inner_client_mock
return client_mock_wrapper
@staticmethod
def client_mock_decorator_fc(configuration):
def client_mock_wrapper(func):
def inner_client_mock(
self, mock_client_class, mock_urllib2, *args, **kwargs):
self.mock_client_class = mock_client_class
self.mock_client_service = mock.MagicMock(name='Client')
self.mock_client_class.return_value = (
self.mock_client_service)
self.driver = nimble.NimbleFCDriver(
configuration=configuration)
mock_login_response = mock_urllib2.post.return_value
mock_login_response = mock.MagicMock()
mock_login_response.status_code.return_value = http_client.OK
mock_login_response.json.return_value = (
FAKE_LOGIN_POST_RESPONSE)
self.driver.do_setup(context.get_admin_context())
self.driver.APIExecutor.login()
func(self, *args, **kwargs)
return inner_client_mock
return client_mock_wrapper
class NimbleDriverLoginTestCase(NimbleDriverBaseTestCase):
"""Tests do_setup api."""
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
"nimble", "nimble_pass", "10.18.108.55", 'default', '*'))
def test_do_setup_positive(self):
expected_call_list = [mock.call.login()]
self.mock_client_service.assert_has_calls(expected_call_list)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_expire_session_id(self):
expected_call_list = [mock.call.login()]
self.mock_client_service.assert_has_calls(expected_call_list)
self.driver.APIExecutor.get("groups")
expected_call_list = [mock.call.get_group_info(),
mock.call.login(),
mock.call.get("groups")]
self.assertEqual(
self.mock_client_service.method_calls,
expected_call_list)
class NimbleDriverVolumeTestCase(NimbleDriverBaseTestCase):
"""Tests volume related api's."""
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID, return_value={
'nimble:perfpol-name': 'default',
'nimble:encryption': 'yes'}))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
NIMBLE_SAN_LOGIN, NIMBLE_SAN_PASS, NIMBLE_MANAGEMENT_IP,
'default', '*'))
def test_create_volume_positive(self):
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
self.assertEqual({
'provider_location': '172.18.108.21:3260 iqn.test',
'provider_auth': None},
self.driver.create_volume({'name': 'testvolume',
'size': 1,
'volume_type_id': None,
'display_name': '',
'display_description': ''}))
self.mock_client_service.create_vol.assert_called_once_with(
{'name': 'testvolume',
'size': 1,
'volume_type_id': None,
'display_name': '',
'display_description': ''},
'default',
False,
'iSCSI',
False)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID, return_value={
'nimble:perfpol-name': 'default',
'nimble:encryption': 'yes'}))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
NIMBLE_SAN_LOGIN, NIMBLE_SAN_PASS, NIMBLE_MANAGEMENT_IP,
'default', '*'))
def test_create_volume_with_unicode(self):
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
self.assertEqual({
'provider_location': '172.18.108.21:3260 iqn.test',
'provider_auth': None},
self.driver.create_volume({'name': 'testvolume',
'size': 1,
'volume_type_id': None,
'display_name': u'unicode_name',
'display_description': ''}))
self.mock_client_service.create_vol.assert_called_once_with(
{'name': 'testvolume',
'size': 1,
'volume_type_id': None,
'display_name': u'unicode_name',
'display_description': ''},
'default',
False,
'iSCSI',
False)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID, return_value={
'nimble:perfpol-name': 'default',
'nimble:encryption': 'yes',
'nimble:multi-initiator': 'false'}))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_create_volume_encryption_positive(self):
self.mock_client_service._execute_create_vol.return_value = (
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE_ENCRYPTION)
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
volume = {'name': 'testvolume-encryption',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': ''}
self.assertEqual({
'provider_location': '172.18.108.21:3260 iqn.test',
'provider_auth': None},
self.driver.create_volume(volume))
self.mock_client_service.create_vol.assert_called_once_with(
{'name': 'testvolume-encryption',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': '',
},
'default',
False,
'iSCSI',
False)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID, return_value={
'nimble:perfpol-name': 'VMware ESX',
'nimble:encryption': 'no',
'nimble:multi-initiator': 'false'}))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_create_volume_perfpolicy_positive(self):
self.mock_client_service._execute_create_vol.return_value = (
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE_PERF_POLICY)
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
self.assertEqual(
{'provider_location': '172.18.108.21:3260 iqn.test',
'provider_auth': None},
self.driver.create_volume({'name': 'testvolume-perfpolicy',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': ''}))
self.mock_client_service.create_vol.assert_called_once_with(
{'name': 'testvolume-perfpolicy',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': '',
},
'default',
False,
'iSCSI',
False)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID, return_value={
'nimble:perfpol-name': 'default',
'nimble:encryption': 'no',
'nimble:multi-initiator': 'true'}))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_create_volume_multi_initiator_positive(self):
self.mock_client_service._execute_create_vol.return_value = (
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE_MULTI_INITIATOR)
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
self.assertEqual(
{'provider_location': '172.18.108.21:3260 iqn.test',
'provider_auth': None},
self.driver.create_volume({'name': 'testvolume-multi-initiator',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': ''}))
self.mock_client_service.create_vol.assert_called_once_with(
{'name': 'testvolume-multi-initiator',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': '',
},
'default',
False,
'iSCSI',
False)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID, return_value={
'nimble:perfpol-name': 'default',
'nimble:encryption': 'no',
'nimble:dedupe': 'true'}))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_create_volume_dedupe_positive(self):
self.mock_client_service._execute_create_vol.return_value = (
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE_DEDUPE)
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
self.assertEqual(
{'provider_location': '172.18.108.21:3260 iqn.test',
'provider_auth': None},
self.driver.create_volume({'name': 'testvolume-dedupe',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': ''}))
self.mock_client_service.create_vol.assert_called_once_with(
{'name': 'testvolume-dedupe',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': '',
},
'default',
False,
'iSCSI',
False)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID, return_value={
'nimble:perfpol-name': 'default',
'nimble:iops-limit': '1024'}))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_create_volume_qos_positive(self):
self.mock_client_service._execute_create_vol.return_value = (
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE_QOS)
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
self.assertEqual(
{'provider_location': '172.18.108.21:3260 iqn.test',
'provider_auth': None},
self.driver.create_volume({'name': 'testvolume-qos',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': ''}))
self.mock_client_service.create_vol.assert_called_once_with(
{'name': 'testvolume-qos',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': '',
},
'default',
False,
'iSCSI',
False)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID, return_value={
'nimble:perfpol-name': 'default',
'nimble:encryption': 'no',
'nimble:multi-initiator': 'true'}))
def test_create_volume_negative(self):
self.mock_client_service.get_vol_info.side_effect = (
FAKE_CREATE_VOLUME_NEGATIVE_RESPONSE)
self.assertRaises(
exception.VolumeBackendAPIException,
self.driver.create_volume,
{'name': 'testvolume',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': ''})
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_create_volume_encryption_negative(self):
self.mock_client_service.get_vol_info.side_effect = (
FAKE_CREATE_VOLUME_NEGATIVE_ENCRYPTION)
self.assertRaises(
exception.VolumeBackendAPIException,
self.driver.create_volume,
{'name': 'testvolume-encryption',
'size': 1,
'volume_type_id': None,
'display_name': '',
'display_description': ''})
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_create_volume_perfpolicy_negative(self):
self.mock_client_service.get_vol_info.side_effect = (
FAKE_CREATE_VOLUME_NEGATIVE_PERFPOLICY)
self.assertRaises(
exception.VolumeBackendAPIException,
self.driver.create_volume,
{'name': 'testvolume-perfpolicy',
'size': 1,
'volume_type_id': None,
'display_name': '',
'display_description': ''})
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_create_volume_dedupe_negative(self):
self.mock_client_service.get_vol_info.side_effect = (
FAKE_CREATE_VOLUME_NEGATIVE_DEDUPE)
self.assertRaises(
exception.VolumeBackendAPIException,
self.driver.create_volume,
{'name': 'testvolume-dedupe',
'size': 1,
'volume_type_id': None,
'display_name': '',
'display_description': ''})
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID, return_value={
'nimble:perfpol-name': 'default',
'nimble:iops-limit': '200'}))
def test_create_volume_qos_negative(self):
self.mock_client_service.get_vol_info.side_effect = (
FAKE_CREATE_VOLUME_NEGATIVE_QOS)
self.assertRaises(
exception.VolumeBackendAPIException,
self.driver.create_volume,
{'name': 'testvolume-qos',
'size': 1,
'volume_type_id': None,
'display_name': '',
'display_description': ''})
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
@mock.patch(NIMBLE_ISCSI_DRIVER + ".is_volume_backup_clone", mock.Mock(
return_value = ['', '']))
def test_delete_volume(self):
self.mock_client_service.online_vol.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.mock_client_service.delete_vol.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.driver.delete_volume({'name': 'testvolume'})
expected_calls = [mock.call.online_vol(
'testvolume', False),
mock.call.delete_vol('testvolume')]
self.mock_client_service.assert_has_calls(expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
@mock.patch(NIMBLE_ISCSI_DRIVER + ".is_volume_backup_clone", mock.Mock(
return_value = ['', '']))
def test_delete_volume_with_clone(self):
self.mock_client_service.delete_vol.side_effect = \
nimble.NimbleAPIException(FAKE_VOLUME_DELETE_HAS_CLONE_RESPONSE)
self.assertRaises(
exception.VolumeIsBusy,
self.driver.delete_volume,
{'name': 'testvolume'})
expected_calls = [mock.call.online_vol(
'testvolume', False),
mock.call.delete_vol('testvolume'),
mock.call.online_vol('testvolume', True)]
self.mock_client_service.assert_has_calls(expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
@mock.patch(NIMBLE_ISCSI_DRIVER + ".is_volume_backup_clone", mock.Mock(
return_value=['test-backup-snap', 'volume-' + fake.VOLUME_ID]))
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host')
def test_delete_volume_with_backup(self, mock_volume_list):
mock_volume_list.return_value = []
self.mock_client_service.online_vol.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.mock_client_service.delete_vol.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.mock_client_service.online_snap.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.mock_client_service.delete_snap.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.driver.delete_volume({'name': 'testvolume'})
expected_calls = [mock.call.online_vol(
'testvolume', False),
mock.call.delete_vol('testvolume'),
mock.call.online_snap('volume-' + fake.VOLUME_ID,
False,
'test-backup-snap'),
mock.call.delete_snap('volume-' + fake.VOLUME_ID,
'test-backup-snap')]
self.mock_client_service.assert_has_calls(expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_extend_volume(self):
self.mock_client_service.edit_vol.return_value = (
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE)
self.driver.extend_volume({'name': 'testvolume'}, 5)
self.mock_client_service.edit_vol.assert_called_once_with(
'testvolume', FAKE_EXTEND_VOLUME_PARAMS)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID,
return_value=
{'nimble:perfpol-name': 'default',
'nimble:encryption': 'yes',
'nimble:multi-initiator': 'false',
'nimble:iops-limit': '1024'}))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*', False))
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host')
@mock.patch(NIMBLE_RANDOM)
def test_create_cloned_volume(self, mock_random, mock_volume_list):
mock_random.sample.return_value = fake.VOLUME_ID
mock_volume_list.return_value = []
self.mock_client_service.snap_vol.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.mock_client_service.clone_vol.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
volume = obj_volume.Volume(context.get_admin_context(),
id=fake.VOLUME_ID,
size=5.0,
_name_id=None,
display_name='',
volume_type_id=FAKE_TYPE_ID
)
src_volume = obj_volume.Volume(context.get_admin_context(),
id=fake.VOLUME2_ID,
_name_id=None,
size=5.0)
self.assertEqual({
'provider_location': '172.18.108.21:3260 iqn.test',
'provider_auth': None},
self.driver.create_cloned_volume(volume, src_volume))
expected_calls = [mock.call.snap_vol(
{'volume_name': "volume-" + fake.VOLUME2_ID,
'name': 'openstack-clone-volume-' + fake.VOLUME_ID + "-" +
fake.VOLUME_ID,
'volume_size': src_volume['size'],
'display_name': volume['display_name'],
'display_description': ''}),
mock.call.clone_vol(volume,
{'volume_name': "volume-" + fake.VOLUME2_ID,
'name': 'openstack-clone-volume-' +
fake.VOLUME_ID + "-" +
fake.VOLUME_ID,
'volume_size': src_volume['size'],
'display_name': volume['display_name'],
'display_description': ''},
True, False, 'iSCSI', 'default')]
self.mock_client_service.assert_has_calls(expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_manage_volume_positive(self):
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE_MANAGE)
self.mock_client_service.online_vol.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.mock_client_service.edit_vol.return_value = (
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE)
self.assertEqual({
'provider_location': '172.18.108.21:3260 iqn.test',
'provider_auth': None},
self.driver.manage_existing({'name': 'volume-abcdef',
'id': fake.VOLUME_ID,
'agent_type': None},
{'source-name': 'test-vol'}))
expected_calls = [mock.call.edit_vol(
'test-vol', {'data': {'agent_type': 'openstack',
'name': 'volume-abcdef'}}),
mock.call.online_vol('volume-abcdef', True)]
self.mock_client_service.assert_has_calls(expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_manage_volume_which_is_online(self):
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_ONLINE)
self.assertRaises(
exception.InvalidVolume,
self.driver.manage_existing,
{'name': 'volume-abcdef'},
{'source-name': 'test-vol'})
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_manage_volume_get_size(self):
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_ONLINE)
size = self.driver.manage_existing_get_size(
{'name': 'volume-abcdef'}, {'source-name': 'test-vol'})
self.assertEqual(2, size)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_manage_volume_with_improper_ref(self):
self.assertRaises(
exception.ManageExistingInvalidReference,
self.driver.manage_existing,
{'name': 'volume-abcdef'},
{'source-id': 'test-vol'})
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_manage_volume_with_nonexistant_volume(self):
self.mock_client_service.get_vol_info.side_effect = (
FAKE_VOLUME_INFO_NEGATIVE_RESPONSE)
self.assertRaises(
exception.VolumeBackendAPIException,
self.driver.manage_existing,
{'name': 'volume-abcdef'},
{'source-name': 'test-vol'})
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_manage_volume_with_wrong_agent_type(self):
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.assertRaises(
exception.ManageExistingAlreadyManaged,
self.driver.manage_existing,
{'id': 'abcdef', 'name': 'volume-abcdef'},
{'source-name': 'test-vol'})
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_unmanage_volume_positive(self):
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.mock_client_service.edit_vol.return_value = (
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE)
self.driver.unmanage({'name': 'volume-abcdef'})
expected_calls = [
mock.call.edit_vol(
'volume-abcdef',
{'data': {'agent_type': 'none'}}),
mock.call.online_vol('volume-abcdef', False)]
self.mock_client_service.assert_has_calls(expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_unmanage_with_invalid_volume(self):
self.mock_client_service.get_vol_info.side_effect = (
FAKE_VOLUME_INFO_NEGATIVE_RESPONSE)
self.assertRaises(
exception.VolumeBackendAPIException,
self.driver.unmanage,
{'name': 'volume-abcdef'}
)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_unmanage_with_invalid_agent_type(self):
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_ONLINE)
self.assertRaises(
exception.InvalidVolume,
self.driver.unmanage,
{'name': 'volume-abcdef'}
)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_get_volume_stats(self):
self.mock_client_service.get_group_info.return_value = (
FAKE_POSITIVE_GROUP_INFO_RESPONSE)
expected_res = {'driver_version': DRIVER_VERSION,
'vendor_name': 'Nimble',
'volume_backend_name': 'NIMBLE',
'storage_protocol': 'iSCSI',
'pools': [{'pool_name': 'NIMBLE',
'total_capacity_gb': 7466.30419921875,
'free_capacity_gb': 7463.567649364471,
'reserved_percentage': 0,
'QoS_support': False}]}
self.assertEqual(
expected_res,
self.driver.get_volume_stats(refresh=True))
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_is_volume_backup_clone(self):
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_BACKUP_RESPONSE)
self.mock_client_service.get_snap_info_by_id.return_value = (
FAKE_GET_SNAP_INFO_BACKUP_RESPONSE)
self.mock_client_service.get_snap_info_detail.return_value = (
FAKE_GET_SNAP_INFO_BACKUP_RESPONSE)
self.mock_client_service.get_volume_name.return_value = (
'volume-' + fake.VOLUME2_ID)
volume = obj_volume.Volume(context.get_admin_context(),
id=fake.VOLUME_ID,
_name_id=None)
self.assertEqual(("test-backup-snap", "volume-" + fake.VOLUME2_ID),
self.driver.is_volume_backup_clone(volume))
expected_calls = [
mock.call.get_vol_info('volume-' + fake.VOLUME_ID),
mock.call.get_snap_info_by_id('test-backup-snap',
'volume-' + fake.VOLUME2_ID)
]
self.mock_client_service.assert_has_calls(expected_calls)
class NimbleDriverSnapshotTestCase(NimbleDriverBaseTestCase):
"""Tests snapshot related api's."""
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_create_snapshot(self):
self.mock_client_service.snap_vol.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.driver.create_snapshot(
{'volume_name': 'testvolume',
'name': 'testvolume-snap1',
'display_name': ''})
self.mock_client_service.snap_vol.assert_called_once_with(
{'volume_name': 'testvolume',
'name': 'testvolume-snap1',
'display_name': ''})
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_delete_snapshot(self):
self.mock_client_service.online_snap.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.mock_client_service.delete_snap.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.driver.delete_snapshot(
{'volume_name': 'testvolume',
'name': 'testvolume-snap1'})
expected_calls = [mock.call.online_snap(
'testvolume', False, 'testvolume-snap1'),
mock.call.delete_snap('testvolume',
'testvolume-snap1')]
self.mock_client_service.assert_has_calls(expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID, return_value={
'nimble:perfpol-name': 'default',
'nimble:encryption': 'yes',
'nimble:multi-initiator': 'false'}))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_create_volume_from_snapshot(self):
self.mock_client_service.clone_vol.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
self.assertEqual({
'provider_location': '172.18.108.21:3260 iqn.test',
'provider_auth': None},
self.driver.create_volume_from_snapshot(
{'name': 'clone-testvolume',
'size': 2,
'volume_type_id': FAKE_TYPE_ID},
{'volume_name': 'testvolume',
'name': 'testvolume-snap1',
'volume_size': 1}))
expected_calls = [
mock.call.clone_vol(
{'name': 'clone-testvolume',
'volume_type_id': FAKE_TYPE_ID,
'size': 2},
{'volume_name': 'testvolume',
'name': 'testvolume-snap1',
'volume_size': 1},
False,
False,
'iSCSI',
'default'),
mock.call.edit_vol('clone-testvolume',
{'data': {'size': 2048,
'snap_limit': sys.maxsize,
'warn_level': 80,
'reserve': 0,
'limit': 100}})]
self.mock_client_service.assert_has_calls(expected_calls)
class NimbleDriverConnectionTestCase(NimbleDriverBaseTestCase):
"""Tests Connection related api's."""
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_initialize_connection_igroup_exist(self):
self.mock_client_service.get_initiator_grp_list.return_value = (
FAKE_IGROUP_LIST_RESPONSE)
expected_res = {
'driver_volume_type': 'iscsi',
'data': {
'volume_id': 12,
'target_iqn': '13',
'target_lun': 0,
'target_portal': '12'}}
self.assertEqual(
expected_res,
self.driver.initialize_connection(
{'name': 'test-volume',
'provider_location': '12 13',
'id': 12},
{'initiator': 'test-initiator1'}))
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_initialize_connection_live_migration(self):
self.mock_client_service.get_initiator_grp_list.return_value = (
FAKE_IGROUP_LIST_RESPONSE)
expected_res = {
'driver_volume_type': 'iscsi',
'data': {
'volume_id': 12,
'target_iqn': '13',
'target_lun': 0,
'target_portal': '12'}}
self.assertEqual(
expected_res,
self.driver.initialize_connection(
{'name': 'test-volume',
'provider_location': '12 13',
'id': 12},
{'initiator': 'test-initiator1'}))
self.driver.initialize_connection(
{'name': 'test-volume',
'provider_location': '12 13',
'id': 12},
{'initiator': 'test-initiator1'})
# 2 or more calls to initialize connection and add_acl for live
# migration to work
expected_calls = [
mock.call.get_initiator_grp_list(),
mock.call.add_acl({'name': 'test-volume',
'provider_location': '12 13',
'id': 12},
'test-igrp1'),
mock.call.get_initiator_grp_list(),
mock.call.add_acl({'name': 'test-volume',
'provider_location': '12 13',
'id': 12},
'test-igrp1')]
self.mock_client_service.assert_has_calls(expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator_fc(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
@mock.patch(NIMBLE_FC_DRIVER + ".get_lun_number")
@mock.patch(NIMBLE_FC_DRIVER + ".get_wwpns_from_array")
def test_initialize_connection_fc_igroup_exist(self, mock_wwpns,
mock_lun_number):
mock_lun_number.return_value = 13
mock_wwpns.return_value = ["1111111111111101"]
self.mock_client_service.get_initiator_grp_list.return_value = (
FAKE_IGROUP_LIST_RESPONSE_FC)
expected_res = {
'driver_volume_type': 'fibre_channel',
'data': {
'target_lun': 13,
'target_discovered': True,
'target_wwn': ["1111111111111101"],
'initiator_target_map': {'1000000000000000':
['1111111111111101']}}}
self.assertEqual(
expected_res,
self.driver.initialize_connection(
{'name': 'test-volume',
'provider_location': 'array1',
'id': 12},
{'initiator': 'test-initiator1',
'wwpns': ['1000000000000000']}))
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
@mock.patch(NIMBLE_RANDOM)
def test_initialize_connection_igroup_not_exist(self, mock_random):
mock_random.sample.return_value = 'abcdefghijkl'
self.mock_client_service.get_initiator_grp_list.return_value = (
FAKE_IGROUP_LIST_RESPONSE)
expected_res = {
'driver_volume_type': 'iscsi',
'data': {
'target_lun': 0,
'volume_id': 12,
'target_iqn': '13',
'target_portal': '12'}}
self.assertEqual(
expected_res,
self.driver.initialize_connection(
{'name': 'test-volume',
'provider_location': '12 13',
'id': 12},
{'initiator': 'test-initiator3'}))
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator_fc(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
@mock.patch(NIMBLE_FC_DRIVER + ".get_wwpns_from_array")
@mock.patch(NIMBLE_FC_DRIVER + ".get_lun_number")
@mock.patch(NIMBLE_RANDOM)
def test_initialize_connection_fc_igroup_not_exist(self, mock_random,
mock_lun_number,
mock_wwpns):
mock_random.sample.return_value = 'abcdefghijkl'
mock_lun_number.return_value = 13
mock_wwpns.return_value = ["1111111111111101"]
self.mock_client_service.get_initiator_grp_list.return_value = (
FAKE_IGROUP_LIST_RESPONSE_FC)
expected_res = {
'driver_volume_type': 'fibre_channel',
'data': {
'target_lun': 13,
'target_discovered': True,
'target_wwn': ["1111111111111101"],
'initiator_target_map': {'1000000000000000':
['1111111111111101']}}}
self.driver._create_igroup_for_initiator("test-initiator3",
[1111111111111101])
self.assertEqual(
expected_res,
self.driver.initialize_connection(
{'name': 'test-volume',
'provider_location': 'array1',
'id': 12},
{'initiator': 'test-initiator3',
'wwpns': ['1000000000000000']}))
expected_calls = [mock.call.create_initiator_group_fc(
'openstack-abcdefghijkl'),
mock.call.add_initiator_to_igroup_fc('openstack-abcdefghijkl',
1111111111111101)]
self.mock_client_service.assert_has_calls(expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_terminate_connection_positive(self):
self.mock_client_service.get_initiator_grp_list.return_value = (
FAKE_IGROUP_LIST_RESPONSE)
self.driver.terminate_connection(
{'name': 'test-volume',
'provider_location': '12 13',
'id': 12},
{'initiator': 'test-initiator1'})
expected_calls = [mock.call._get_igroupname_for_initiator(
'test-initiator1'),
mock.call.remove_acl({'name': 'test-volume'},
'test-igrp1')]
self.mock_client_service.assert_has_calls(
self.mock_client_service.method_calls,
expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator_fc(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
@mock.patch(NIMBLE_FC_DRIVER + ".get_wwpns_from_array")
def test_terminate_connection_positive_fc(self, mock_wwpns):
mock_wwpns.return_value = ["1111111111111101"]
self.mock_client_service.get_initiator_grp_list.return_value = (
FAKE_IGROUP_LIST_RESPONSE_FC)
self.driver.terminate_connection(
{'name': 'test-volume',
'provider_location': 'array1',
'id': 12},
{'initiator': 'test-initiator1',
'wwpns': ['1000000000000000']})
expected_calls = [
mock.call.get_igroupname_for_initiator_fc(
"fd00:a516:7c1b:17cd:6d81:2137:bd2a:2c5b"),
mock.call.remove_acl({'name': 'test-volume'},
'test-igrp1')]
self.mock_client_service.assert_has_calls(
self.mock_client_service.method_calls,
expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_terminate_connection_negative(self):
self.mock_client_service.get_initiator_grp_list.return_value = (
FAKE_IGROUP_LIST_RESPONSE)
self.assertRaises(
exception.VolumeDriverException,
self.driver.terminate_connection,
{'name': 'test-volume',
'provider_location': '12 13', 'id': 12},
{'initiator': 'test-initiator3'}) | cinder/tests/unit/volume/drivers/test_nimble.py |
import mock
from six.moves import http_client
import sys
from cinder import context
from cinder import exception
from cinder.objects import volume as obj_volume
from cinder import test
from cinder.tests.unit import fake_constants as fake
from cinder.volume.drivers import nimble
from cinder.volume import volume_types
NIMBLE_CLIENT = 'cinder.volume.drivers.nimble.NimbleRestAPIExecutor'
NIMBLE_URLLIB2 = 'cinder.volume.drivers.nimble.requests'
NIMBLE_RANDOM = 'cinder.volume.drivers.nimble.random'
NIMBLE_ISCSI_DRIVER = 'cinder.volume.drivers.nimble.NimbleISCSIDriver'
NIMBLE_FC_DRIVER = 'cinder.volume.drivers.nimble.NimbleFCDriver'
DRIVER_VERSION = '4.0.1'
nimble.DEFAULT_SLEEP = 0
FAKE_POSITIVE_LOGIN_RESPONSE_1 = '2c20aad78a220ed1dae21dcd6f9446f5'
FAKE_POSITIVE_LOGIN_RESPONSE_2 = '2c20aad78a220ed1dae21dcd6f9446ff'
FAKE_POSITIVE_HEADERS = {'X-Auth-Token': FAKE_POSITIVE_LOGIN_RESPONSE_1}
FAKE_POSITIVE_NETCONFIG_RESPONSE = {
'role': 'active',
'subnet_list': [{'network': '172.18.212.0',
'discovery_ip': '172.18.108.21',
'type': 'data',
'allow_iscsi': True,
'label': 'data1',
'allow_group': True,
'vlan_id': 0}],
'array_list': [{'nic_list': [{'subnet_label': 'data1',
'tagged': False,
'data_ip': '172.18.212.82',
'name': 'eth3'}]}],
'name': 'test-array'}
FAKE_NEGATIVE_NETCONFIG_RESPONSE = exception.VolumeDriverException(
"Session expired")
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE = {
'clone': False,
'name': "testvolume"}
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE_ENCRYPTION = {
'clone': False,
'name': "testvolume-encryption"}
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE_PERF_POLICY = {
'clone': False,
'name': "testvolume-perf-policy"}
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE_MULTI_INITIATOR = {
'clone': False,
'name': "testvolume-multi-initiator"}
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE_DEDUPE = {
'clone': False,
'name': "testvolume-dedupe"}
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE_QOS = {
'clone': False,
'name': "testvolume-qos"}
FAKE_GET_VOL_INFO_RESPONSE = {'name': 'testvolume',
'clone': False,
'target_name': 'iqn.test',
'online': True,
'agent_type': 'openstack'}
FAKE_GET_VOL_INFO_RESPONSE_MANAGE = {'name': 'testvolume',
'agent_type': 'none',
'online': False,
'target_name': 'iqn.test'}
FAKE_GET_VOL_INFO_ONLINE = {'name': 'testvolume',
'size': 2048,
'online': True,
'agent_type': 'none'}
FAKE_GET_VOL_INFO_BACKUP_RESPONSE = {'name': 'testvolume',
'clone': True,
'target_name': 'iqn.test',
'online': False,
'agent_type': 'openstack',
'parent_vol_id': 'volume-' +
fake.VOLUME2_ID,
'base_snap_id': 'test-backup-snap'}
FAKE_GET_SNAP_INFO_BACKUP_RESPONSE = {
'description': "backup-vol-" + fake.VOLUME2_ID,
'name': 'test-backup-snap',
'id': fake.SNAPSHOT_ID,
'vol_id': fake.VOLUME_ID,
'volume_name': 'volume-' + fake.VOLUME_ID}
FAKE_POSITIVE_GROUP_CONFIG_RESPONSE = {
'name': 'group-test',
'version_current': '0.0.0.0',
'access_protocol_list': ['iscsi']}
FAKE_LOGIN_POST_RESPONSE = {
'data': {'session_token': FAKE_POSITIVE_LOGIN_RESPONSE_1}}
FAKE_EXTEND_VOLUME_PARAMS = {'data': {'size': 5120,
'reserve': 0,
'warn_level': 80,
'limit': 100,
'snap_limit': sys.maxsize}}
FAKE_IGROUP_LIST_RESPONSE = [
{'iscsi_initiators': [{'iqn': 'test-initiator1'}],
'name': 'test-igrp1'},
{'iscsi_initiators': [{'iqn': 'test-initiator2'}],
'name': 'test-igrp2'}]
FAKE_IGROUP_LIST_RESPONSE_FC = [
{'fc_initiators': [{'wwpn': 'fd00:a516:7c1b:17cd:6d81:2137:bd2a:2c5b'}],
'name': 'test-igrp1'},
{'fc_initiators': [{'wwpn': 'fd00:a516:7c1b:17cd:6d81:2137:bd2a:2c5b'},
{'wwpn': 'fc00:e968:6179::de52:7100'}],
'name': 'test-igrp2'}]
FAKE_CREATE_VOLUME_NEGATIVE_RESPONSE = exception.VolumeBackendAPIException(
"Volume testvolume not found")
FAKE_VOLUME_INFO_NEGATIVE_RESPONSE = exception.VolumeBackendAPIException(
"Volume testvolume not found")
FAKE_CREATE_VOLUME_NEGATIVE_ENCRYPTION = exception.VolumeBackendAPIException(
"Volume testvolume-encryption not found")
FAKE_CREATE_VOLUME_NEGATIVE_PERFPOLICY = exception.VolumeBackendAPIException(
"Volume testvolume-perfpolicy not found")
FAKE_CREATE_VOLUME_NEGATIVE_DEDUPE = exception.VolumeBackendAPIException(
"The specified pool is not capable of hosting deduplicated volumes")
FAKE_CREATE_VOLUME_NEGATIVE_QOS = exception.VolumeBackendAPIException(
"Please set valid IOPS limitin the range [256, 4294967294]")
FAKE_POSITIVE_GROUP_INFO_RESPONSE = {
'version_current': '3.0.0.0',
'group_target_enabled': False,
'name': 'group-nimble',
'usage_valid': True,
'usable_capacity_bytes': 8016883089408,
'compressed_vol_usage_bytes': 2938311843,
'compressed_snap_usage_bytes': 36189,
'unused_reserve_bytes': 0}
FAKE_GENERIC_POSITIVE_RESPONSE = ""
FAKE_VOLUME_DELETE_HAS_CLONE_RESPONSE = "Object has a clone"
FAKE_TYPE_ID = fake.VOLUME_TYPE_ID
FAKE_POOL_ID = fake.GROUP_ID
FAKE_PERFORMANCE_POLICY_ID = fake.OBJECT_ID
NIMBLE_MANAGEMENT_IP = "10.18.108.55"
NIMBLE_SAN_LOGIN = "nimble"
NIMBLE_SAN_PASS = "<PASSWORD>"
def create_configuration(username, password, ip_address,
pool_name=None, subnet_label=None,
thin_provision=True):
configuration = mock.Mock()
configuration.san_login = username
configuration.san_password = password
configuration.san_ip = ip_address
configuration.san_thin_provision = thin_provision
configuration.nimble_pool_name = pool_name
configuration.nimble_subnet_label = subnet_label
configuration.safe_get.return_value = 'NIMBLE'
return configuration
class NimbleDriverBaseTestCase(test.TestCase):
"""Base Class for the NimbleDriver Tests."""
def setUp(self):
super(NimbleDriverBaseTestCase, self).setUp()
self.mock_client_service = None
self.mock_client_class = None
self.driver = None
@staticmethod
def client_mock_decorator(configuration):
def client_mock_wrapper(func):
def inner_client_mock(
self, mock_client_class, mock_urllib2, *args, **kwargs):
self.mock_client_class = mock_client_class
self.mock_client_service = mock.MagicMock(name='Client')
self.mock_client_class.return_value = self.mock_client_service
self.driver = nimble.NimbleISCSIDriver(
configuration=configuration)
mock_login_response = mock_urllib2.post.return_value
mock_login_response = mock.MagicMock()
mock_login_response.status_code.return_value = http_client.OK
mock_login_response.json.return_value = (
FAKE_LOGIN_POST_RESPONSE)
self.driver.do_setup(context.get_admin_context())
self.driver.APIExecutor.login()
func(self, *args, **kwargs)
return inner_client_mock
return client_mock_wrapper
@staticmethod
def client_mock_decorator_fc(configuration):
def client_mock_wrapper(func):
def inner_client_mock(
self, mock_client_class, mock_urllib2, *args, **kwargs):
self.mock_client_class = mock_client_class
self.mock_client_service = mock.MagicMock(name='Client')
self.mock_client_class.return_value = (
self.mock_client_service)
self.driver = nimble.NimbleFCDriver(
configuration=configuration)
mock_login_response = mock_urllib2.post.return_value
mock_login_response = mock.MagicMock()
mock_login_response.status_code.return_value = http_client.OK
mock_login_response.json.return_value = (
FAKE_LOGIN_POST_RESPONSE)
self.driver.do_setup(context.get_admin_context())
self.driver.APIExecutor.login()
func(self, *args, **kwargs)
return inner_client_mock
return client_mock_wrapper
class NimbleDriverLoginTestCase(NimbleDriverBaseTestCase):
"""Tests do_setup api."""
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
"nimble", "nimble_pass", "10.18.108.55", 'default', '*'))
def test_do_setup_positive(self):
expected_call_list = [mock.call.login()]
self.mock_client_service.assert_has_calls(expected_call_list)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_expire_session_id(self):
expected_call_list = [mock.call.login()]
self.mock_client_service.assert_has_calls(expected_call_list)
self.driver.APIExecutor.get("groups")
expected_call_list = [mock.call.get_group_info(),
mock.call.login(),
mock.call.get("groups")]
self.assertEqual(
self.mock_client_service.method_calls,
expected_call_list)
class NimbleDriverVolumeTestCase(NimbleDriverBaseTestCase):
"""Tests volume related api's."""
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID, return_value={
'nimble:perfpol-name': 'default',
'nimble:encryption': 'yes'}))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
NIMBLE_SAN_LOGIN, NIMBLE_SAN_PASS, NIMBLE_MANAGEMENT_IP,
'default', '*'))
def test_create_volume_positive(self):
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
self.assertEqual({
'provider_location': '172.18.108.21:3260 iqn.test',
'provider_auth': None},
self.driver.create_volume({'name': 'testvolume',
'size': 1,
'volume_type_id': None,
'display_name': '',
'display_description': ''}))
self.mock_client_service.create_vol.assert_called_once_with(
{'name': 'testvolume',
'size': 1,
'volume_type_id': None,
'display_name': '',
'display_description': ''},
'default',
False,
'iSCSI',
False)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID, return_value={
'nimble:perfpol-name': 'default',
'nimble:encryption': 'yes'}))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
NIMBLE_SAN_LOGIN, NIMBLE_SAN_PASS, NIMBLE_MANAGEMENT_IP,
'default', '*'))
def test_create_volume_with_unicode(self):
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
self.assertEqual({
'provider_location': '172.18.108.21:3260 iqn.test',
'provider_auth': None},
self.driver.create_volume({'name': 'testvolume',
'size': 1,
'volume_type_id': None,
'display_name': u'unicode_name',
'display_description': ''}))
self.mock_client_service.create_vol.assert_called_once_with(
{'name': 'testvolume',
'size': 1,
'volume_type_id': None,
'display_name': u'unicode_name',
'display_description': ''},
'default',
False,
'iSCSI',
False)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID, return_value={
'nimble:perfpol-name': 'default',
'nimble:encryption': 'yes',
'nimble:multi-initiator': 'false'}))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_create_volume_encryption_positive(self):
self.mock_client_service._execute_create_vol.return_value = (
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE_ENCRYPTION)
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
volume = {'name': 'testvolume-encryption',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': ''}
self.assertEqual({
'provider_location': '172.18.108.21:3260 iqn.test',
'provider_auth': None},
self.driver.create_volume(volume))
self.mock_client_service.create_vol.assert_called_once_with(
{'name': 'testvolume-encryption',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': '',
},
'default',
False,
'iSCSI',
False)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID, return_value={
'nimble:perfpol-name': 'VMware ESX',
'nimble:encryption': 'no',
'nimble:multi-initiator': 'false'}))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_create_volume_perfpolicy_positive(self):
self.mock_client_service._execute_create_vol.return_value = (
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE_PERF_POLICY)
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
self.assertEqual(
{'provider_location': '172.18.108.21:3260 iqn.test',
'provider_auth': None},
self.driver.create_volume({'name': 'testvolume-perfpolicy',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': ''}))
self.mock_client_service.create_vol.assert_called_once_with(
{'name': 'testvolume-perfpolicy',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': '',
},
'default',
False,
'iSCSI',
False)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID, return_value={
'nimble:perfpol-name': 'default',
'nimble:encryption': 'no',
'nimble:multi-initiator': 'true'}))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_create_volume_multi_initiator_positive(self):
self.mock_client_service._execute_create_vol.return_value = (
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE_MULTI_INITIATOR)
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
self.assertEqual(
{'provider_location': '172.18.108.21:3260 iqn.test',
'provider_auth': None},
self.driver.create_volume({'name': 'testvolume-multi-initiator',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': ''}))
self.mock_client_service.create_vol.assert_called_once_with(
{'name': 'testvolume-multi-initiator',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': '',
},
'default',
False,
'iSCSI',
False)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID, return_value={
'nimble:perfpol-name': 'default',
'nimble:encryption': 'no',
'nimble:dedupe': 'true'}))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_create_volume_dedupe_positive(self):
self.mock_client_service._execute_create_vol.return_value = (
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE_DEDUPE)
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
self.assertEqual(
{'provider_location': '172.18.108.21:3260 iqn.test',
'provider_auth': None},
self.driver.create_volume({'name': 'testvolume-dedupe',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': ''}))
self.mock_client_service.create_vol.assert_called_once_with(
{'name': 'testvolume-dedupe',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': '',
},
'default',
False,
'iSCSI',
False)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID, return_value={
'nimble:perfpol-name': 'default',
'nimble:iops-limit': '1024'}))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_create_volume_qos_positive(self):
self.mock_client_service._execute_create_vol.return_value = (
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE_QOS)
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
self.assertEqual(
{'provider_location': '172.18.108.21:3260 iqn.test',
'provider_auth': None},
self.driver.create_volume({'name': 'testvolume-qos',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': ''}))
self.mock_client_service.create_vol.assert_called_once_with(
{'name': 'testvolume-qos',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': '',
},
'default',
False,
'iSCSI',
False)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID, return_value={
'nimble:perfpol-name': 'default',
'nimble:encryption': 'no',
'nimble:multi-initiator': 'true'}))
def test_create_volume_negative(self):
self.mock_client_service.get_vol_info.side_effect = (
FAKE_CREATE_VOLUME_NEGATIVE_RESPONSE)
self.assertRaises(
exception.VolumeBackendAPIException,
self.driver.create_volume,
{'name': 'testvolume',
'size': 1,
'volume_type_id': FAKE_TYPE_ID,
'display_name': '',
'display_description': ''})
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_create_volume_encryption_negative(self):
self.mock_client_service.get_vol_info.side_effect = (
FAKE_CREATE_VOLUME_NEGATIVE_ENCRYPTION)
self.assertRaises(
exception.VolumeBackendAPIException,
self.driver.create_volume,
{'name': 'testvolume-encryption',
'size': 1,
'volume_type_id': None,
'display_name': '',
'display_description': ''})
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_create_volume_perfpolicy_negative(self):
self.mock_client_service.get_vol_info.side_effect = (
FAKE_CREATE_VOLUME_NEGATIVE_PERFPOLICY)
self.assertRaises(
exception.VolumeBackendAPIException,
self.driver.create_volume,
{'name': 'testvolume-perfpolicy',
'size': 1,
'volume_type_id': None,
'display_name': '',
'display_description': ''})
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_create_volume_dedupe_negative(self):
self.mock_client_service.get_vol_info.side_effect = (
FAKE_CREATE_VOLUME_NEGATIVE_DEDUPE)
self.assertRaises(
exception.VolumeBackendAPIException,
self.driver.create_volume,
{'name': 'testvolume-dedupe',
'size': 1,
'volume_type_id': None,
'display_name': '',
'display_description': ''})
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID, return_value={
'nimble:perfpol-name': 'default',
'nimble:iops-limit': '200'}))
def test_create_volume_qos_negative(self):
self.mock_client_service.get_vol_info.side_effect = (
FAKE_CREATE_VOLUME_NEGATIVE_QOS)
self.assertRaises(
exception.VolumeBackendAPIException,
self.driver.create_volume,
{'name': 'testvolume-qos',
'size': 1,
'volume_type_id': None,
'display_name': '',
'display_description': ''})
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
@mock.patch(NIMBLE_ISCSI_DRIVER + ".is_volume_backup_clone", mock.Mock(
return_value = ['', '']))
def test_delete_volume(self):
self.mock_client_service.online_vol.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.mock_client_service.delete_vol.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.driver.delete_volume({'name': 'testvolume'})
expected_calls = [mock.call.online_vol(
'testvolume', False),
mock.call.delete_vol('testvolume')]
self.mock_client_service.assert_has_calls(expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
@mock.patch(NIMBLE_ISCSI_DRIVER + ".is_volume_backup_clone", mock.Mock(
return_value = ['', '']))
def test_delete_volume_with_clone(self):
self.mock_client_service.delete_vol.side_effect = \
nimble.NimbleAPIException(FAKE_VOLUME_DELETE_HAS_CLONE_RESPONSE)
self.assertRaises(
exception.VolumeIsBusy,
self.driver.delete_volume,
{'name': 'testvolume'})
expected_calls = [mock.call.online_vol(
'testvolume', False),
mock.call.delete_vol('testvolume'),
mock.call.online_vol('testvolume', True)]
self.mock_client_service.assert_has_calls(expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
@mock.patch(NIMBLE_ISCSI_DRIVER + ".is_volume_backup_clone", mock.Mock(
return_value=['test-backup-snap', 'volume-' + fake.VOLUME_ID]))
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host')
def test_delete_volume_with_backup(self, mock_volume_list):
mock_volume_list.return_value = []
self.mock_client_service.online_vol.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.mock_client_service.delete_vol.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.mock_client_service.online_snap.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.mock_client_service.delete_snap.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.driver.delete_volume({'name': 'testvolume'})
expected_calls = [mock.call.online_vol(
'testvolume', False),
mock.call.delete_vol('testvolume'),
mock.call.online_snap('volume-' + fake.VOLUME_ID,
False,
'test-backup-snap'),
mock.call.delete_snap('volume-' + fake.VOLUME_ID,
'test-backup-snap')]
self.mock_client_service.assert_has_calls(expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_extend_volume(self):
self.mock_client_service.edit_vol.return_value = (
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE)
self.driver.extend_volume({'name': 'testvolume'}, 5)
self.mock_client_service.edit_vol.assert_called_once_with(
'testvolume', FAKE_EXTEND_VOLUME_PARAMS)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID,
return_value=
{'nimble:perfpol-name': 'default',
'nimble:encryption': 'yes',
'nimble:multi-initiator': 'false',
'nimble:iops-limit': '1024'}))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*', False))
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host')
@mock.patch(NIMBLE_RANDOM)
def test_create_cloned_volume(self, mock_random, mock_volume_list):
mock_random.sample.return_value = fake.VOLUME_ID
mock_volume_list.return_value = []
self.mock_client_service.snap_vol.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.mock_client_service.clone_vol.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
volume = obj_volume.Volume(context.get_admin_context(),
id=fake.VOLUME_ID,
size=5.0,
_name_id=None,
display_name='',
volume_type_id=FAKE_TYPE_ID
)
src_volume = obj_volume.Volume(context.get_admin_context(),
id=fake.VOLUME2_ID,
_name_id=None,
size=5.0)
self.assertEqual({
'provider_location': '172.18.108.21:3260 iqn.test',
'provider_auth': None},
self.driver.create_cloned_volume(volume, src_volume))
expected_calls = [mock.call.snap_vol(
{'volume_name': "volume-" + fake.VOLUME2_ID,
'name': 'openstack-clone-volume-' + fake.VOLUME_ID + "-" +
fake.VOLUME_ID,
'volume_size': src_volume['size'],
'display_name': volume['display_name'],
'display_description': ''}),
mock.call.clone_vol(volume,
{'volume_name': "volume-" + fake.VOLUME2_ID,
'name': 'openstack-clone-volume-' +
fake.VOLUME_ID + "-" +
fake.VOLUME_ID,
'volume_size': src_volume['size'],
'display_name': volume['display_name'],
'display_description': ''},
True, False, 'iSCSI', 'default')]
self.mock_client_service.assert_has_calls(expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_manage_volume_positive(self):
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE_MANAGE)
self.mock_client_service.online_vol.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.mock_client_service.edit_vol.return_value = (
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE)
self.assertEqual({
'provider_location': '172.18.108.21:3260 iqn.test',
'provider_auth': None},
self.driver.manage_existing({'name': 'volume-abcdef',
'id': fake.VOLUME_ID,
'agent_type': None},
{'source-name': 'test-vol'}))
expected_calls = [mock.call.edit_vol(
'test-vol', {'data': {'agent_type': 'openstack',
'name': 'volume-abcdef'}}),
mock.call.online_vol('volume-abcdef', True)]
self.mock_client_service.assert_has_calls(expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_manage_volume_which_is_online(self):
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_ONLINE)
self.assertRaises(
exception.InvalidVolume,
self.driver.manage_existing,
{'name': 'volume-abcdef'},
{'source-name': 'test-vol'})
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_manage_volume_get_size(self):
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_ONLINE)
size = self.driver.manage_existing_get_size(
{'name': 'volume-abcdef'}, {'source-name': 'test-vol'})
self.assertEqual(2, size)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_manage_volume_with_improper_ref(self):
self.assertRaises(
exception.ManageExistingInvalidReference,
self.driver.manage_existing,
{'name': 'volume-abcdef'},
{'source-id': 'test-vol'})
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_manage_volume_with_nonexistant_volume(self):
self.mock_client_service.get_vol_info.side_effect = (
FAKE_VOLUME_INFO_NEGATIVE_RESPONSE)
self.assertRaises(
exception.VolumeBackendAPIException,
self.driver.manage_existing,
{'name': 'volume-abcdef'},
{'source-name': 'test-vol'})
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_manage_volume_with_wrong_agent_type(self):
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.assertRaises(
exception.ManageExistingAlreadyManaged,
self.driver.manage_existing,
{'id': 'abcdef', 'name': 'volume-abcdef'},
{'source-name': 'test-vol'})
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_unmanage_volume_positive(self):
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.mock_client_service.edit_vol.return_value = (
FAKE_CREATE_VOLUME_POSITIVE_RESPONSE)
self.driver.unmanage({'name': 'volume-abcdef'})
expected_calls = [
mock.call.edit_vol(
'volume-abcdef',
{'data': {'agent_type': 'none'}}),
mock.call.online_vol('volume-abcdef', False)]
self.mock_client_service.assert_has_calls(expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_unmanage_with_invalid_volume(self):
self.mock_client_service.get_vol_info.side_effect = (
FAKE_VOLUME_INFO_NEGATIVE_RESPONSE)
self.assertRaises(
exception.VolumeBackendAPIException,
self.driver.unmanage,
{'name': 'volume-abcdef'}
)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_unmanage_with_invalid_agent_type(self):
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_ONLINE)
self.assertRaises(
exception.InvalidVolume,
self.driver.unmanage,
{'name': 'volume-abcdef'}
)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_get_volume_stats(self):
self.mock_client_service.get_group_info.return_value = (
FAKE_POSITIVE_GROUP_INFO_RESPONSE)
expected_res = {'driver_version': DRIVER_VERSION,
'vendor_name': 'Nimble',
'volume_backend_name': 'NIMBLE',
'storage_protocol': 'iSCSI',
'pools': [{'pool_name': 'NIMBLE',
'total_capacity_gb': 7466.30419921875,
'free_capacity_gb': 7463.567649364471,
'reserved_percentage': 0,
'QoS_support': False}]}
self.assertEqual(
expected_res,
self.driver.get_volume_stats(refresh=True))
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_is_volume_backup_clone(self):
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_BACKUP_RESPONSE)
self.mock_client_service.get_snap_info_by_id.return_value = (
FAKE_GET_SNAP_INFO_BACKUP_RESPONSE)
self.mock_client_service.get_snap_info_detail.return_value = (
FAKE_GET_SNAP_INFO_BACKUP_RESPONSE)
self.mock_client_service.get_volume_name.return_value = (
'volume-' + fake.VOLUME2_ID)
volume = obj_volume.Volume(context.get_admin_context(),
id=fake.VOLUME_ID,
_name_id=None)
self.assertEqual(("test-backup-snap", "volume-" + fake.VOLUME2_ID),
self.driver.is_volume_backup_clone(volume))
expected_calls = [
mock.call.get_vol_info('volume-' + fake.VOLUME_ID),
mock.call.get_snap_info_by_id('test-backup-snap',
'volume-' + fake.VOLUME2_ID)
]
self.mock_client_service.assert_has_calls(expected_calls)
class NimbleDriverSnapshotTestCase(NimbleDriverBaseTestCase):
"""Tests snapshot related api's."""
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_create_snapshot(self):
self.mock_client_service.snap_vol.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.driver.create_snapshot(
{'volume_name': 'testvolume',
'name': 'testvolume-snap1',
'display_name': ''})
self.mock_client_service.snap_vol.assert_called_once_with(
{'volume_name': 'testvolume',
'name': 'testvolume-snap1',
'display_name': ''})
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_delete_snapshot(self):
self.mock_client_service.online_snap.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.mock_client_service.delete_snap.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.driver.delete_snapshot(
{'volume_name': 'testvolume',
'name': 'testvolume-snap1'})
expected_calls = [mock.call.online_snap(
'testvolume', False, 'testvolume-snap1'),
mock.call.delete_snap('testvolume',
'testvolume-snap1')]
self.mock_client_service.assert_has_calls(expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@mock.patch.object(volume_types, 'get_volume_type_extra_specs',
mock.Mock(type_id=FAKE_TYPE_ID, return_value={
'nimble:perfpol-name': 'default',
'nimble:encryption': 'yes',
'nimble:multi-initiator': 'false'}))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_create_volume_from_snapshot(self):
self.mock_client_service.clone_vol.return_value = (
FAKE_GENERIC_POSITIVE_RESPONSE)
self.mock_client_service.get_vol_info.return_value = (
FAKE_GET_VOL_INFO_RESPONSE)
self.mock_client_service.get_netconfig.return_value = (
FAKE_POSITIVE_NETCONFIG_RESPONSE)
self.assertEqual({
'provider_location': '172.18.108.21:3260 iqn.test',
'provider_auth': None},
self.driver.create_volume_from_snapshot(
{'name': 'clone-testvolume',
'size': 2,
'volume_type_id': FAKE_TYPE_ID},
{'volume_name': 'testvolume',
'name': 'testvolume-snap1',
'volume_size': 1}))
expected_calls = [
mock.call.clone_vol(
{'name': 'clone-testvolume',
'volume_type_id': FAKE_TYPE_ID,
'size': 2},
{'volume_name': 'testvolume',
'name': 'testvolume-snap1',
'volume_size': 1},
False,
False,
'iSCSI',
'default'),
mock.call.edit_vol('clone-testvolume',
{'data': {'size': 2048,
'snap_limit': sys.maxsize,
'warn_level': 80,
'reserve': 0,
'limit': 100}})]
self.mock_client_service.assert_has_calls(expected_calls)
class NimbleDriverConnectionTestCase(NimbleDriverBaseTestCase):
"""Tests Connection related api's."""
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_initialize_connection_igroup_exist(self):
self.mock_client_service.get_initiator_grp_list.return_value = (
FAKE_IGROUP_LIST_RESPONSE)
expected_res = {
'driver_volume_type': 'iscsi',
'data': {
'volume_id': 12,
'target_iqn': '13',
'target_lun': 0,
'target_portal': '12'}}
self.assertEqual(
expected_res,
self.driver.initialize_connection(
{'name': 'test-volume',
'provider_location': '12 13',
'id': 12},
{'initiator': 'test-initiator1'}))
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_initialize_connection_live_migration(self):
self.mock_client_service.get_initiator_grp_list.return_value = (
FAKE_IGROUP_LIST_RESPONSE)
expected_res = {
'driver_volume_type': 'iscsi',
'data': {
'volume_id': 12,
'target_iqn': '13',
'target_lun': 0,
'target_portal': '12'}}
self.assertEqual(
expected_res,
self.driver.initialize_connection(
{'name': 'test-volume',
'provider_location': '12 13',
'id': 12},
{'initiator': 'test-initiator1'}))
self.driver.initialize_connection(
{'name': 'test-volume',
'provider_location': '12 13',
'id': 12},
{'initiator': 'test-initiator1'})
# 2 or more calls to initialize connection and add_acl for live
# migration to work
expected_calls = [
mock.call.get_initiator_grp_list(),
mock.call.add_acl({'name': 'test-volume',
'provider_location': '12 13',
'id': 12},
'test-igrp1'),
mock.call.get_initiator_grp_list(),
mock.call.add_acl({'name': 'test-volume',
'provider_location': '12 13',
'id': 12},
'test-igrp1')]
self.mock_client_service.assert_has_calls(expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator_fc(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
@mock.patch(NIMBLE_FC_DRIVER + ".get_lun_number")
@mock.patch(NIMBLE_FC_DRIVER + ".get_wwpns_from_array")
def test_initialize_connection_fc_igroup_exist(self, mock_wwpns,
mock_lun_number):
mock_lun_number.return_value = 13
mock_wwpns.return_value = ["1111111111111101"]
self.mock_client_service.get_initiator_grp_list.return_value = (
FAKE_IGROUP_LIST_RESPONSE_FC)
expected_res = {
'driver_volume_type': 'fibre_channel',
'data': {
'target_lun': 13,
'target_discovered': True,
'target_wwn': ["1111111111111101"],
'initiator_target_map': {'1000000000000000':
['1111111111111101']}}}
self.assertEqual(
expected_res,
self.driver.initialize_connection(
{'name': 'test-volume',
'provider_location': 'array1',
'id': 12},
{'initiator': 'test-initiator1',
'wwpns': ['1000000000000000']}))
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
@mock.patch(NIMBLE_RANDOM)
def test_initialize_connection_igroup_not_exist(self, mock_random):
mock_random.sample.return_value = 'abcdefghijkl'
self.mock_client_service.get_initiator_grp_list.return_value = (
FAKE_IGROUP_LIST_RESPONSE)
expected_res = {
'driver_volume_type': 'iscsi',
'data': {
'target_lun': 0,
'volume_id': 12,
'target_iqn': '13',
'target_portal': '12'}}
self.assertEqual(
expected_res,
self.driver.initialize_connection(
{'name': 'test-volume',
'provider_location': '12 13',
'id': 12},
{'initiator': 'test-initiator3'}))
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator_fc(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
@mock.patch(NIMBLE_FC_DRIVER + ".get_wwpns_from_array")
@mock.patch(NIMBLE_FC_DRIVER + ".get_lun_number")
@mock.patch(NIMBLE_RANDOM)
def test_initialize_connection_fc_igroup_not_exist(self, mock_random,
mock_lun_number,
mock_wwpns):
mock_random.sample.return_value = 'abcdefghijkl'
mock_lun_number.return_value = 13
mock_wwpns.return_value = ["1111111111111101"]
self.mock_client_service.get_initiator_grp_list.return_value = (
FAKE_IGROUP_LIST_RESPONSE_FC)
expected_res = {
'driver_volume_type': 'fibre_channel',
'data': {
'target_lun': 13,
'target_discovered': True,
'target_wwn': ["1111111111111101"],
'initiator_target_map': {'1000000000000000':
['1111111111111101']}}}
self.driver._create_igroup_for_initiator("test-initiator3",
[1111111111111101])
self.assertEqual(
expected_res,
self.driver.initialize_connection(
{'name': 'test-volume',
'provider_location': 'array1',
'id': 12},
{'initiator': 'test-initiator3',
'wwpns': ['1000000000000000']}))
expected_calls = [mock.call.create_initiator_group_fc(
'openstack-abcdefghijkl'),
mock.call.add_initiator_to_igroup_fc('openstack-abcdefghijkl',
1111111111111101)]
self.mock_client_service.assert_has_calls(expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_terminate_connection_positive(self):
self.mock_client_service.get_initiator_grp_list.return_value = (
FAKE_IGROUP_LIST_RESPONSE)
self.driver.terminate_connection(
{'name': 'test-volume',
'provider_location': '12 13',
'id': 12},
{'initiator': 'test-initiator1'})
expected_calls = [mock.call._get_igroupname_for_initiator(
'test-initiator1'),
mock.call.remove_acl({'name': 'test-volume'},
'test-igrp1')]
self.mock_client_service.assert_has_calls(
self.mock_client_service.method_calls,
expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator_fc(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
@mock.patch(NIMBLE_FC_DRIVER + ".get_wwpns_from_array")
def test_terminate_connection_positive_fc(self, mock_wwpns):
mock_wwpns.return_value = ["1111111111111101"]
self.mock_client_service.get_initiator_grp_list.return_value = (
FAKE_IGROUP_LIST_RESPONSE_FC)
self.driver.terminate_connection(
{'name': 'test-volume',
'provider_location': 'array1',
'id': 12},
{'initiator': 'test-initiator1',
'wwpns': ['1000000000000000']})
expected_calls = [
mock.call.get_igroupname_for_initiator_fc(
"fd00:a516:7c1b:17cd:6d81:2137:bd2a:2c5b"),
mock.call.remove_acl({'name': 'test-volume'},
'test-igrp1')]
self.mock_client_service.assert_has_calls(
self.mock_client_service.method_calls,
expected_calls)
@mock.patch(NIMBLE_URLLIB2)
@mock.patch(NIMBLE_CLIENT)
@mock.patch.object(obj_volume.VolumeList, 'get_all_by_host',
mock.Mock(return_value=[]))
@NimbleDriverBaseTestCase.client_mock_decorator(create_configuration(
'nimble', 'nimble_pass', '10.18.108.55', 'default', '*'))
def test_terminate_connection_negative(self):
self.mock_client_service.get_initiator_grp_list.return_value = (
FAKE_IGROUP_LIST_RESPONSE)
self.assertRaises(
exception.VolumeDriverException,
self.driver.terminate_connection,
{'name': 'test-volume',
'provider_location': '12 13', 'id': 12},
{'initiator': 'test-initiator3'}) | 0.292797 | 0.118615 |
import roslib
roslib.load_manifest('SAFMC-21-D2-Team2')
import sys
import rospy
from statistics import mean
import numpy as np
import cv2 as cv
from std_msgs.msg import String
from sensor_msgs.msg import Image
from cv_bridge import CvBridge, CvBridgeError
class BoxCV:
def __init__(self, output=False):
#self.image_pub = rospy.Publisher("camera/depth/image_rect_raw",Image)
self.bridge = CvBridge()
self.image_sub = rospy.Subscriber("/d400/depth/image_rect_raw", Image, self.image_cb)
#self.image_sub = rospy.Subscriber("/camera/depth/image_raw", Image, self.image_cb)
self.running_sum = []
self.theta = np.array([0, 0])
self.output=output
def image_cb(self, data):
#print("image")
try:
cv_image = self.bridge.imgmsg_to_cv2(data)
except CvBridgeError as e:
print(e)
# cv_image=cv_image[:,80:]
print(cv_image.shape)
cv_image=cv_image[140:-140,220:-220]
cv_image=cv_image/1000
(rows,cols) = cv_image.shape
if self.output:
cv.imshow("image",cv_image/18)
cv.waitKey(3)
self.running_sum.append(np.mean(cv_image))
if len(self.running_sum)>20:
self.running_sum.pop(0)
print("mean:", mean(self.running_sum))
y_mean = np.mean(cv_image, axis=0)
x = np.array([[1, i/cols] for i in range(cols)]).reshape(cols, 2)
self.theta = np.matmul(np.matmul(np.linalg.inv(np.matmul(np.transpose(x), x)), np.transpose(x)), y_mean)
if self.output:
print(self.theta)
def get_theta(self):
return self.theta
def get_mean(self):
return mean(self.running_sum)
def main(args):
print(sys.version)
boxCV = BoxCV(output=False)
rospy.init_node('image_converter', anonymous=True)
try:
rospy.spin()
except KeyboardInterrupt:
print("Shutting down")
cv.destroyAllWindows()
if __name__ == '__main__':
main(sys.argv) | src/box.py |
import roslib
roslib.load_manifest('SAFMC-21-D2-Team2')
import sys
import rospy
from statistics import mean
import numpy as np
import cv2 as cv
from std_msgs.msg import String
from sensor_msgs.msg import Image
from cv_bridge import CvBridge, CvBridgeError
class BoxCV:
def __init__(self, output=False):
#self.image_pub = rospy.Publisher("camera/depth/image_rect_raw",Image)
self.bridge = CvBridge()
self.image_sub = rospy.Subscriber("/d400/depth/image_rect_raw", Image, self.image_cb)
#self.image_sub = rospy.Subscriber("/camera/depth/image_raw", Image, self.image_cb)
self.running_sum = []
self.theta = np.array([0, 0])
self.output=output
def image_cb(self, data):
#print("image")
try:
cv_image = self.bridge.imgmsg_to_cv2(data)
except CvBridgeError as e:
print(e)
# cv_image=cv_image[:,80:]
print(cv_image.shape)
cv_image=cv_image[140:-140,220:-220]
cv_image=cv_image/1000
(rows,cols) = cv_image.shape
if self.output:
cv.imshow("image",cv_image/18)
cv.waitKey(3)
self.running_sum.append(np.mean(cv_image))
if len(self.running_sum)>20:
self.running_sum.pop(0)
print("mean:", mean(self.running_sum))
y_mean = np.mean(cv_image, axis=0)
x = np.array([[1, i/cols] for i in range(cols)]).reshape(cols, 2)
self.theta = np.matmul(np.matmul(np.linalg.inv(np.matmul(np.transpose(x), x)), np.transpose(x)), y_mean)
if self.output:
print(self.theta)
def get_theta(self):
return self.theta
def get_mean(self):
return mean(self.running_sum)
def main(args):
print(sys.version)
boxCV = BoxCV(output=False)
rospy.init_node('image_converter', anonymous=True)
try:
rospy.spin()
except KeyboardInterrupt:
print("Shutting down")
cv.destroyAllWindows()
if __name__ == '__main__':
main(sys.argv) | 0.214034 | 0.1941 |
from operator import attrgetter
import pyangbind.lib.xpathhelper as xpathhelper
from pyangbind.lib.yangtypes import RestrictedPrecisionDecimalType, RestrictedClassType, TypedListType
from pyangbind.lib.yangtypes import YANGBool, YANGListType, YANGDynClass, ReferenceType
from pyangbind.lib.base import PybindBase
from decimal import Decimal
from bitarray import bitarray
import __builtin__
class graceful_restart(PybindBase):
"""
This class was auto-generated by the PythonClass plugin for PYANG
from YANG module brocade-common-def - based on the path /routing-system/router/router-bgp/address-family/ipv6/ipv6-unicast/default-vrf/af-common-cmds-holder/graceful-restart. Each member element of
the container is represented as a class variable - with a specific
YANG type.
"""
__slots__ = ('_pybind_generated_by', '_path_helper', '_yang_name', '_rest_name', '_extmethods', '__graceful_restart_status','__restart_time','__purge_time','__stale_routes_time',)
_yang_name = 'graceful-restart'
_rest_name = 'graceful-restart'
_pybind_generated_by = 'container'
def __init__(self, *args, **kwargs):
path_helper_ = kwargs.pop("path_helper", None)
if path_helper_ is False:
self._path_helper = False
elif path_helper_ is not None and isinstance(path_helper_, xpathhelper.YANGPathHelper):
self._path_helper = path_helper_
elif hasattr(self, "_parent"):
path_helper_ = getattr(self._parent, "_path_helper", False)
self._path_helper = path_helper_
else:
self._path_helper = False
extmethods = kwargs.pop("extmethods", None)
if extmethods is False:
self._extmethods = False
elif extmethods is not None and isinstance(extmethods, dict):
self._extmethods = extmethods
elif hasattr(self, "_parent"):
extmethods = getattr(self._parent, "_extmethods", None)
self._extmethods = extmethods
else:
self._extmethods = False
self.__graceful_restart_status = YANGDynClass(base=YANGBool, is_leaf=True, yang_name="graceful-restart-status", rest_name="graceful-restart-status", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-full-command': None, u'cli-drop-node-name': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='empty', is_config=True)
self.__restart_time = YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="restart-time", rest_name="restart-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum restart wait time advertised to neighbors (1-3600s), default 120', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='rtime-type', is_config=True)
self.__stale_routes_time = YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="stale-routes-time", rest_name="stale-routes-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum time before helper router clean up stale routes (1-3600s), default 360', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='st-time-type', is_config=True)
self.__purge_time = YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="purge-time", rest_name="purge-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum time before restarting router clean up stale (1-3600s), default 600', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='ptime-type', is_config=True)
load = kwargs.pop("load", None)
if args:
if len(args) > 1:
raise TypeError("cannot create a YANG container with >1 argument")
all_attr = True
for e in self._pyangbind_elements:
if not hasattr(args[0], e):
all_attr = False
break
if not all_attr:
raise ValueError("Supplied object did not have the correct attributes")
for e in self._pyangbind_elements:
nobj = getattr(args[0], e)
if nobj._changed() is False:
continue
setmethod = getattr(self, "_set_%s" % e)
if load is None:
setmethod(getattr(args[0], e))
else:
setmethod(getattr(args[0], e), load=load)
def _path(self):
if hasattr(self, "_parent"):
return self._parent._path()+[self._yang_name]
else:
return [u'routing-system', u'router', u'router-bgp', u'address-family', u'ipv6', u'ipv6-unicast', u'default-vrf', u'af-common-cmds-holder', u'graceful-restart']
def _rest_path(self):
if hasattr(self, "_parent"):
if self._rest_name:
return self._parent._rest_path()+[self._rest_name]
else:
return self._parent._rest_path()
else:
return [u'router', u'bgp', u'address-family', u'ipv6', u'unicast', u'graceful-restart']
def _get_graceful_restart_status(self):
"""
Getter method for graceful_restart_status, mapped from YANG variable /routing_system/router/router_bgp/address_family/ipv6/ipv6_unicast/default_vrf/af_common_cmds_holder/graceful_restart/graceful_restart_status (empty)
"""
return self.__graceful_restart_status
def _set_graceful_restart_status(self, v, load=False):
"""
Setter method for graceful_restart_status, mapped from YANG variable /routing_system/router/router_bgp/address_family/ipv6/ipv6_unicast/default_vrf/af_common_cmds_holder/graceful_restart/graceful_restart_status (empty)
If this variable is read-only (config: false) in the
source YANG file, then _set_graceful_restart_status is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_graceful_restart_status() directly.
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=YANGBool, is_leaf=True, yang_name="graceful-restart-status", rest_name="graceful-restart-status", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-full-command': None, u'cli-drop-node-name': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='empty', is_config=True)
except (TypeError, ValueError):
raise ValueError({
'error-string': """graceful_restart_status must be of a type compatible with empty""",
'defined-type': "empty",
'generated-type': """YANGDynClass(base=YANGBool, is_leaf=True, yang_name="graceful-restart-status", rest_name="graceful-restart-status", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-full-command': None, u'cli-drop-node-name': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='empty', is_config=True)""",
})
self.__graceful_restart_status = t
if hasattr(self, '_set'):
self._set()
def _unset_graceful_restart_status(self):
self.__graceful_restart_status = YANGDynClass(base=YANGBool, is_leaf=True, yang_name="graceful-restart-status", rest_name="graceful-restart-status", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-full-command': None, u'cli-drop-node-name': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='empty', is_config=True)
def _get_restart_time(self):
"""
Getter method for restart_time, mapped from YANG variable /routing_system/router/router_bgp/address_family/ipv6/ipv6_unicast/default_vrf/af_common_cmds_holder/graceful_restart/restart_time (rtime-type)
"""
return self.__restart_time
def _set_restart_time(self, v, load=False):
"""
Setter method for restart_time, mapped from YANG variable /routing_system/router/router_bgp/address_family/ipv6/ipv6_unicast/default_vrf/af_common_cmds_holder/graceful_restart/restart_time (rtime-type)
If this variable is read-only (config: false) in the
source YANG file, then _set_restart_time is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_restart_time() directly.
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="restart-time", rest_name="restart-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum restart wait time advertised to neighbors (1-3600s), default 120', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='rtime-type', is_config=True)
except (TypeError, ValueError):
raise ValueError({
'error-string': """restart_time must be of a type compatible with rtime-type""",
'defined-type': "brocade-bgp:rtime-type",
'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="restart-time", rest_name="restart-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum restart wait time advertised to neighbors (1-3600s), default 120', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='rtime-type', is_config=True)""",
})
self.__restart_time = t
if hasattr(self, '_set'):
self._set()
def _unset_restart_time(self):
self.__restart_time = YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="restart-time", rest_name="restart-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum restart wait time advertised to neighbors (1-3600s), default 120', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='rtime-type', is_config=True)
def _get_purge_time(self):
"""
Getter method for purge_time, mapped from YANG variable /routing_system/router/router_bgp/address_family/ipv6/ipv6_unicast/default_vrf/af_common_cmds_holder/graceful_restart/purge_time (ptime-type)
"""
return self.__purge_time
def _set_purge_time(self, v, load=False):
"""
Setter method for purge_time, mapped from YANG variable /routing_system/router/router_bgp/address_family/ipv6/ipv6_unicast/default_vrf/af_common_cmds_holder/graceful_restart/purge_time (ptime-type)
If this variable is read-only (config: false) in the
source YANG file, then _set_purge_time is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_purge_time() directly.
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="purge-time", rest_name="purge-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum time before restarting router clean up stale (1-3600s), default 600', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='ptime-type', is_config=True)
except (TypeError, ValueError):
raise ValueError({
'error-string': """purge_time must be of a type compatible with ptime-type""",
'defined-type': "brocade-bgp:ptime-type",
'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="purge-time", rest_name="purge-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum time before restarting router clean up stale (1-3600s), default 600', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='ptime-type', is_config=True)""",
})
self.__purge_time = t
if hasattr(self, '_set'):
self._set()
def _unset_purge_time(self):
self.__purge_time = YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="purge-time", rest_name="purge-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum time before restarting router clean up stale (1-3600s), default 600', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='ptime-type', is_config=True)
def _get_stale_routes_time(self):
"""
Getter method for stale_routes_time, mapped from YANG variable /routing_system/router/router_bgp/address_family/ipv6/ipv6_unicast/default_vrf/af_common_cmds_holder/graceful_restart/stale_routes_time (st-time-type)
"""
return self.__stale_routes_time
def _set_stale_routes_time(self, v, load=False):
"""
Setter method for stale_routes_time, mapped from YANG variable /routing_system/router/router_bgp/address_family/ipv6/ipv6_unicast/default_vrf/af_common_cmds_holder/graceful_restart/stale_routes_time (st-time-type)
If this variable is read-only (config: false) in the
source YANG file, then _set_stale_routes_time is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_stale_routes_time() directly.
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="stale-routes-time", rest_name="stale-routes-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum time before helper router clean up stale routes (1-3600s), default 360', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='st-time-type', is_config=True)
except (TypeError, ValueError):
raise ValueError({
'error-string': """stale_routes_time must be of a type compatible with st-time-type""",
'defined-type': "brocade-bgp:st-time-type",
'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="stale-routes-time", rest_name="stale-routes-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum time before helper router clean up stale routes (1-3600s), default 360', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='st-time-type', is_config=True)""",
})
self.__stale_routes_time = t
if hasattr(self, '_set'):
self._set()
def _unset_stale_routes_time(self):
self.__stale_routes_time = YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="stale-routes-time", rest_name="stale-routes-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum time before helper router clean up stale routes (1-3600s), default 360', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='st-time-type', is_config=True)
graceful_restart_status = __builtin__.property(_get_graceful_restart_status, _set_graceful_restart_status)
restart_time = __builtin__.property(_get_restart_time, _set_restart_time)
purge_time = __builtin__.property(_get_purge_time, _set_purge_time)
stale_routes_time = __builtin__.property(_get_stale_routes_time, _set_stale_routes_time)
_pyangbind_elements = {'graceful_restart_status': graceful_restart_status, 'restart_time': restart_time, 'purge_time': purge_time, 'stale_routes_time': stale_routes_time, } | pybind/slxos/v16r_1_00b/routing_system/router/router_bgp/address_family/ipv6/ipv6_unicast/default_vrf/af_common_cmds_holder/graceful_restart/__init__.py | from operator import attrgetter
import pyangbind.lib.xpathhelper as xpathhelper
from pyangbind.lib.yangtypes import RestrictedPrecisionDecimalType, RestrictedClassType, TypedListType
from pyangbind.lib.yangtypes import YANGBool, YANGListType, YANGDynClass, ReferenceType
from pyangbind.lib.base import PybindBase
from decimal import Decimal
from bitarray import bitarray
import __builtin__
class graceful_restart(PybindBase):
"""
This class was auto-generated by the PythonClass plugin for PYANG
from YANG module brocade-common-def - based on the path /routing-system/router/router-bgp/address-family/ipv6/ipv6-unicast/default-vrf/af-common-cmds-holder/graceful-restart. Each member element of
the container is represented as a class variable - with a specific
YANG type.
"""
__slots__ = ('_pybind_generated_by', '_path_helper', '_yang_name', '_rest_name', '_extmethods', '__graceful_restart_status','__restart_time','__purge_time','__stale_routes_time',)
_yang_name = 'graceful-restart'
_rest_name = 'graceful-restart'
_pybind_generated_by = 'container'
def __init__(self, *args, **kwargs):
path_helper_ = kwargs.pop("path_helper", None)
if path_helper_ is False:
self._path_helper = False
elif path_helper_ is not None and isinstance(path_helper_, xpathhelper.YANGPathHelper):
self._path_helper = path_helper_
elif hasattr(self, "_parent"):
path_helper_ = getattr(self._parent, "_path_helper", False)
self._path_helper = path_helper_
else:
self._path_helper = False
extmethods = kwargs.pop("extmethods", None)
if extmethods is False:
self._extmethods = False
elif extmethods is not None and isinstance(extmethods, dict):
self._extmethods = extmethods
elif hasattr(self, "_parent"):
extmethods = getattr(self._parent, "_extmethods", None)
self._extmethods = extmethods
else:
self._extmethods = False
self.__graceful_restart_status = YANGDynClass(base=YANGBool, is_leaf=True, yang_name="graceful-restart-status", rest_name="graceful-restart-status", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-full-command': None, u'cli-drop-node-name': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='empty', is_config=True)
self.__restart_time = YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="restart-time", rest_name="restart-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum restart wait time advertised to neighbors (1-3600s), default 120', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='rtime-type', is_config=True)
self.__stale_routes_time = YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="stale-routes-time", rest_name="stale-routes-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum time before helper router clean up stale routes (1-3600s), default 360', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='st-time-type', is_config=True)
self.__purge_time = YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="purge-time", rest_name="purge-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum time before restarting router clean up stale (1-3600s), default 600', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='ptime-type', is_config=True)
load = kwargs.pop("load", None)
if args:
if len(args) > 1:
raise TypeError("cannot create a YANG container with >1 argument")
all_attr = True
for e in self._pyangbind_elements:
if not hasattr(args[0], e):
all_attr = False
break
if not all_attr:
raise ValueError("Supplied object did not have the correct attributes")
for e in self._pyangbind_elements:
nobj = getattr(args[0], e)
if nobj._changed() is False:
continue
setmethod = getattr(self, "_set_%s" % e)
if load is None:
setmethod(getattr(args[0], e))
else:
setmethod(getattr(args[0], e), load=load)
def _path(self):
if hasattr(self, "_parent"):
return self._parent._path()+[self._yang_name]
else:
return [u'routing-system', u'router', u'router-bgp', u'address-family', u'ipv6', u'ipv6-unicast', u'default-vrf', u'af-common-cmds-holder', u'graceful-restart']
def _rest_path(self):
if hasattr(self, "_parent"):
if self._rest_name:
return self._parent._rest_path()+[self._rest_name]
else:
return self._parent._rest_path()
else:
return [u'router', u'bgp', u'address-family', u'ipv6', u'unicast', u'graceful-restart']
def _get_graceful_restart_status(self):
"""
Getter method for graceful_restart_status, mapped from YANG variable /routing_system/router/router_bgp/address_family/ipv6/ipv6_unicast/default_vrf/af_common_cmds_holder/graceful_restart/graceful_restart_status (empty)
"""
return self.__graceful_restart_status
def _set_graceful_restart_status(self, v, load=False):
"""
Setter method for graceful_restart_status, mapped from YANG variable /routing_system/router/router_bgp/address_family/ipv6/ipv6_unicast/default_vrf/af_common_cmds_holder/graceful_restart/graceful_restart_status (empty)
If this variable is read-only (config: false) in the
source YANG file, then _set_graceful_restart_status is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_graceful_restart_status() directly.
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=YANGBool, is_leaf=True, yang_name="graceful-restart-status", rest_name="graceful-restart-status", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-full-command': None, u'cli-drop-node-name': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='empty', is_config=True)
except (TypeError, ValueError):
raise ValueError({
'error-string': """graceful_restart_status must be of a type compatible with empty""",
'defined-type': "empty",
'generated-type': """YANGDynClass(base=YANGBool, is_leaf=True, yang_name="graceful-restart-status", rest_name="graceful-restart-status", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-full-command': None, u'cli-drop-node-name': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='empty', is_config=True)""",
})
self.__graceful_restart_status = t
if hasattr(self, '_set'):
self._set()
def _unset_graceful_restart_status(self):
self.__graceful_restart_status = YANGDynClass(base=YANGBool, is_leaf=True, yang_name="graceful-restart-status", rest_name="graceful-restart-status", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-full-command': None, u'cli-drop-node-name': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='empty', is_config=True)
def _get_restart_time(self):
"""
Getter method for restart_time, mapped from YANG variable /routing_system/router/router_bgp/address_family/ipv6/ipv6_unicast/default_vrf/af_common_cmds_holder/graceful_restart/restart_time (rtime-type)
"""
return self.__restart_time
def _set_restart_time(self, v, load=False):
"""
Setter method for restart_time, mapped from YANG variable /routing_system/router/router_bgp/address_family/ipv6/ipv6_unicast/default_vrf/af_common_cmds_holder/graceful_restart/restart_time (rtime-type)
If this variable is read-only (config: false) in the
source YANG file, then _set_restart_time is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_restart_time() directly.
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="restart-time", rest_name="restart-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum restart wait time advertised to neighbors (1-3600s), default 120', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='rtime-type', is_config=True)
except (TypeError, ValueError):
raise ValueError({
'error-string': """restart_time must be of a type compatible with rtime-type""",
'defined-type': "brocade-bgp:rtime-type",
'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="restart-time", rest_name="restart-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum restart wait time advertised to neighbors (1-3600s), default 120', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='rtime-type', is_config=True)""",
})
self.__restart_time = t
if hasattr(self, '_set'):
self._set()
def _unset_restart_time(self):
self.__restart_time = YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="restart-time", rest_name="restart-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum restart wait time advertised to neighbors (1-3600s), default 120', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='rtime-type', is_config=True)
def _get_purge_time(self):
"""
Getter method for purge_time, mapped from YANG variable /routing_system/router/router_bgp/address_family/ipv6/ipv6_unicast/default_vrf/af_common_cmds_holder/graceful_restart/purge_time (ptime-type)
"""
return self.__purge_time
def _set_purge_time(self, v, load=False):
"""
Setter method for purge_time, mapped from YANG variable /routing_system/router/router_bgp/address_family/ipv6/ipv6_unicast/default_vrf/af_common_cmds_holder/graceful_restart/purge_time (ptime-type)
If this variable is read-only (config: false) in the
source YANG file, then _set_purge_time is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_purge_time() directly.
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="purge-time", rest_name="purge-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum time before restarting router clean up stale (1-3600s), default 600', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='ptime-type', is_config=True)
except (TypeError, ValueError):
raise ValueError({
'error-string': """purge_time must be of a type compatible with ptime-type""",
'defined-type': "brocade-bgp:ptime-type",
'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="purge-time", rest_name="purge-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum time before restarting router clean up stale (1-3600s), default 600', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='ptime-type', is_config=True)""",
})
self.__purge_time = t
if hasattr(self, '_set'):
self._set()
def _unset_purge_time(self):
self.__purge_time = YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="purge-time", rest_name="purge-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum time before restarting router clean up stale (1-3600s), default 600', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='ptime-type', is_config=True)
def _get_stale_routes_time(self):
"""
Getter method for stale_routes_time, mapped from YANG variable /routing_system/router/router_bgp/address_family/ipv6/ipv6_unicast/default_vrf/af_common_cmds_holder/graceful_restart/stale_routes_time (st-time-type)
"""
return self.__stale_routes_time
def _set_stale_routes_time(self, v, load=False):
"""
Setter method for stale_routes_time, mapped from YANG variable /routing_system/router/router_bgp/address_family/ipv6/ipv6_unicast/default_vrf/af_common_cmds_holder/graceful_restart/stale_routes_time (st-time-type)
If this variable is read-only (config: false) in the
source YANG file, then _set_stale_routes_time is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_stale_routes_time() directly.
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="stale-routes-time", rest_name="stale-routes-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum time before helper router clean up stale routes (1-3600s), default 360', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='st-time-type', is_config=True)
except (TypeError, ValueError):
raise ValueError({
'error-string': """stale_routes_time must be of a type compatible with st-time-type""",
'defined-type': "brocade-bgp:st-time-type",
'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="stale-routes-time", rest_name="stale-routes-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum time before helper router clean up stale routes (1-3600s), default 360', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='st-time-type', is_config=True)""",
})
self.__stale_routes_time = t
if hasattr(self, '_set'):
self._set()
def _unset_stale_routes_time(self):
self.__stale_routes_time = YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1..3600']}), is_leaf=True, yang_name="stale-routes-time", rest_name="stale-routes-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Maximum time before helper router clean up stale routes (1-3600s), default 360', u'cli-full-command': None, u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-bgp', defining_module='brocade-bgp', yang_type='st-time-type', is_config=True)
graceful_restart_status = __builtin__.property(_get_graceful_restart_status, _set_graceful_restart_status)
restart_time = __builtin__.property(_get_restart_time, _set_restart_time)
purge_time = __builtin__.property(_get_purge_time, _set_purge_time)
stale_routes_time = __builtin__.property(_get_stale_routes_time, _set_stale_routes_time)
_pyangbind_elements = {'graceful_restart_status': graceful_restart_status, 'restart_time': restart_time, 'purge_time': purge_time, 'stale_routes_time': stale_routes_time, } | 0.667148 | 0.067424 |
import json
from pyrogram import Client, filters
from firebase import firebase
from process import check, searches, truecaller_search, fb_search, logreturn, log, eyecon_search
from pyrogram.types import InlineKeyboardMarkup, InlineKeyboardButton
from creds import cred
firebase = firebase.FirebaseApplication(cred.DB_URL)
app = Client(
"Truecaller-Bot",
api_id=cred.API_ID,
api_hash=cred.API_HASH,
bot_token=cred.BOT_TOKEN
)
@app.on_message(filters.command(["start"]))
def start(client, message):
client.send_message(chat_id=message.chat.id,
text=f"`Hi` **{message.from_user.first_name}**\n Enter the number to search...\n** __Join My Channel For Updates @HxBots__**",reply_markup=InlineKeyboardMarkup(
[[InlineKeyboardButton("About", callback_data="about"),
InlineKeyboardButton("Buy Me A Coffee ☕", url="https://upayme.vercel.app/kkirodewal@ybl")]]))
check_status = check(message.chat.id)
@app.on_callback_query()
def newbt(client,callback_query):
txt=callback_query.data
if txt=="about":
callback_query.message.edit(text=f"**🔹 Bot Name 🔹 :** __[Truecaller-Bot](t.me/truecalerbot)__\n\n**🔹 Channel 🔹 :** __[HxBots](t.me/hxbots)__\n\n**🔹 Creator 🔹 :** __[oVoIndia](https://github.com/oVoIndia)__\n\n**🔹 Owner 🔹 :** __[Kirodewal](t.me/Kirodewal)__\n\n**🔹 Server 🔹 :** __[Heroku](https://herokuapp.com/)__",
disable_web_page_preview=True, reply_markup=InlineKeyboardMarkup(
[[InlineKeyboardButton("Any Feedback 🙋♂️", url="t.me/hxsupport")]]))
elif txt=="src":
callback_query.message.edit(text="Enjoy...😁:-D\nhttps://github.com/oVoIndia/Truecaller-Bot", disable_web_page_preview=True)
@app.on_message(filters.command(["about"]))
def about(client, message):
client.send_message(chat_id=message.chat.id, reply_to_message_id=message.message_id,
text=f"**🔸 Bot Name 🔸 :** __[Truecaller-Bot](t.me/truecalerbot)__\n\n**🔸 Channel 🔸 :** __[HxBots](t.me/hxbots)__\n\n**🔸 Creator 🔸 :** __[oVoIndia](https://github.com/oVoIndia)__\n\n**🔸 Owner 🔸 :** __[Kirodewal](t.me/Kirodewal)__\n\n**🔸 Server 🔸 :** __[Heroku](https://herokuapp.com/)__",
disable_web_page_preview=True, reply_markup=InlineKeyboardMarkup(
[[InlineKeyboardButton("Any Feedback 🙋♀️", url="t.me/hxsupport")]]))
@app.on_message(filters.command(["log"]))
def stats(client, message):
stat = client.send_message(chat_id=message.chat.id, reply_to_message_id=message.message_id,
text="`Fetching details`")
txt = logreturn()
stat.edit(txt)
@app.on_message(filters.text)
def echo(client, message):
actvt = ""
actvt = firebase.get('/stats', 'total_searches')
data = {"total_searches": 1}
if not actvt:
firebase.put('/stats', 'total_searches', data)
global pq
pq = ""
pro = client.send_message(chat_id=message.chat.id, text="Searching...", reply_to_message_id=message.message_id)
r_num = message.text
num = r_num.replace("+91", "").replace(" ", "")
frbseyename = ""
frbsefb = ""
frbsetrname = ""
frbsetrmail = ""
if num.isnumeric and len(num) == 10:
pq = "\n\n**----••Truecaller says----**\n\nLimit exceeded ,try again tomorrow 🤦🏻♂️"
tresponse = ""
try:
tresponse = truecaller_search(cred.T_AUTH, num)
if tresponse:
restj = tresponse.json()
trslt = json.dumps(restj)
tjsonload = json.loads(trslt)
if "name" in tjsonload['data'][0]:
if tjsonload['data'][0]['internetAddresses']:
pq = f"\n\n**----••Truecaller says----**\n\nName : `{tjsonload['data'][0]['name']}`\nCarrier : `{tjsonload['data'][0]['phones'][0]['carrier']}` \nE-mail : {tjsonload['data'][0]['internetAddresses'][0]['id']}"
frbsetrname = tjsonload['data'][0]['name']
frbsetrmail = tjsonload['data'][0]['internetAddresses'][0]['id']
elif not tjsonload['data'][0]['internetAddresses']:
pq = f"\n\n**----••Truecaller says----**\n\nName : `{tjsonload['data'][0]['name']}`\nCarrier : `{tjsonload['data'][0]['phones'][0]['carrier']}`"
frbsetrname = tjsonload['data'][0]['name']
else:
pq = "\n\n**----••Truecaller says----**\n\nNo results found 🤦🏻♂️"
if tresponse.status_code == 429:
pq = "\n\n**----••Truecaller says----**\n\nLimit exceeded ,try again tomorrow 🤦🏻♂️"
except:
pass
response = eyecon_search(num)
fbres = fb_search(num)
fbrslt = fbres.url.replace('https://graph.', '').replace('picture?width=600', '')
if response:
rslt = response.json()
if rslt:
temp = json.dumps(rslt).replace('[', '').replace(']', '')
jsonload = json.loads(temp)
yk = f"\n\n**----••Eyecon says----**\n\nName :`{jsonload['name']}`"
frbseyename = jsonload["name"]
if "facebook.com" in fbrslt:
yk = f"\n\n**----••Eyecon says----**\n\nName : `{jsonload['name']}`\nFacebook : {fbrslt}"
frbseyename = jsonload["name"]
frbsefb = fbrslt
else:
yk = "**----••Eyecon says----**\n\nNo results found 🤦🏻♂️"
else:
yk = "**----••Eyecon says----**\n\nNo results found 🤦🏻♂️"
yk += pq
pro.edit(text=yk, disable_web_page_preview=True,reply_markup=InlineKeyboardMarkup(
[[InlineKeyboardButton("Source", callback_data="src")]]))
searches()
log()
if frbseyename and frbsefb and frbsetrname and frbsetrmail:
data = {
"Eyecon Name": frbseyename,
"Mob": num,
"Truecaller name": frbsetrname,
"Facebook": frbsefb,
"Mail": frbsetrmail
}
firebase.put('/knowho-log', num, data)
elif frbseyename and frbsefb and frbsetrname:
data = {
"Eyecon Name": frbseyename,
"Mob": num,
"Truecaller name": frbsetrname,
"Facebook": frbsefb
}
firebase.put('/knowho-log', num, data)
elif frbseyename and frbsefb:
data = {
"Eyecon Name": frbseyename,
"Mob": num,
"Facebook": frbsefb
}
firebase.put('/knowho-log', num, data)
elif frbseyename and frbsetrname and frbsetrmail:
data = {
"Eyecon Name": frbseyename,
"Mob": num,
"Truecaller name": frbsetrname,
"Mail": frbsetrmail
}
firebase.put('/knowho-log', num, data)
elif frbseyename and frbsetrname:
data = {
"Eyecon Name": frbseyename,
"Mob": num,
"Truecaller name": frbsetrname
}
firebase.put('/knowho-log', num, data)
elif frbsetrname and frbsetrmail:
data = {
"Truecaller name": frbsetrname,
"Mob": num,
"Mail": frbsetrmail
}
firebase.put('/knowho-log', num, data)
elif frbsetrname:
data = {
"Truecaller name": frbsetrname
}
firebase.put('/knowho-log', num, data)
else:
pro.edit("`Only` **10** `digit numbers allowed` 🤦🏻♂️")
app.run() | main.py | import json
from pyrogram import Client, filters
from firebase import firebase
from process import check, searches, truecaller_search, fb_search, logreturn, log, eyecon_search
from pyrogram.types import InlineKeyboardMarkup, InlineKeyboardButton
from creds import cred
firebase = firebase.FirebaseApplication(cred.DB_URL)
app = Client(
"Truecaller-Bot",
api_id=cred.API_ID,
api_hash=cred.API_HASH,
bot_token=cred.BOT_TOKEN
)
@app.on_message(filters.command(["start"]))
def start(client, message):
client.send_message(chat_id=message.chat.id,
text=f"`Hi` **{message.from_user.first_name}**\n Enter the number to search...\n** __Join My Channel For Updates @HxBots__**",reply_markup=InlineKeyboardMarkup(
[[InlineKeyboardButton("About", callback_data="about"),
InlineKeyboardButton("Buy Me A Coffee ☕", url="https://upayme.vercel.app/kkirodewal@ybl")]]))
check_status = check(message.chat.id)
@app.on_callback_query()
def newbt(client,callback_query):
txt=callback_query.data
if txt=="about":
callback_query.message.edit(text=f"**🔹 Bot Name 🔹 :** __[Truecaller-Bot](t.me/truecalerbot)__\n\n**🔹 Channel 🔹 :** __[HxBots](t.me/hxbots)__\n\n**🔹 Creator 🔹 :** __[oVoIndia](https://github.com/oVoIndia)__\n\n**🔹 Owner 🔹 :** __[Kirodewal](t.me/Kirodewal)__\n\n**🔹 Server 🔹 :** __[Heroku](https://herokuapp.com/)__",
disable_web_page_preview=True, reply_markup=InlineKeyboardMarkup(
[[InlineKeyboardButton("Any Feedback 🙋♂️", url="t.me/hxsupport")]]))
elif txt=="src":
callback_query.message.edit(text="Enjoy...😁:-D\nhttps://github.com/oVoIndia/Truecaller-Bot", disable_web_page_preview=True)
@app.on_message(filters.command(["about"]))
def about(client, message):
client.send_message(chat_id=message.chat.id, reply_to_message_id=message.message_id,
text=f"**🔸 Bot Name 🔸 :** __[Truecaller-Bot](t.me/truecalerbot)__\n\n**🔸 Channel 🔸 :** __[HxBots](t.me/hxbots)__\n\n**🔸 Creator 🔸 :** __[oVoIndia](https://github.com/oVoIndia)__\n\n**🔸 Owner 🔸 :** __[Kirodewal](t.me/Kirodewal)__\n\n**🔸 Server 🔸 :** __[Heroku](https://herokuapp.com/)__",
disable_web_page_preview=True, reply_markup=InlineKeyboardMarkup(
[[InlineKeyboardButton("Any Feedback 🙋♀️", url="t.me/hxsupport")]]))
@app.on_message(filters.command(["log"]))
def stats(client, message):
stat = client.send_message(chat_id=message.chat.id, reply_to_message_id=message.message_id,
text="`Fetching details`")
txt = logreturn()
stat.edit(txt)
@app.on_message(filters.text)
def echo(client, message):
actvt = ""
actvt = firebase.get('/stats', 'total_searches')
data = {"total_searches": 1}
if not actvt:
firebase.put('/stats', 'total_searches', data)
global pq
pq = ""
pro = client.send_message(chat_id=message.chat.id, text="Searching...", reply_to_message_id=message.message_id)
r_num = message.text
num = r_num.replace("+91", "").replace(" ", "")
frbseyename = ""
frbsefb = ""
frbsetrname = ""
frbsetrmail = ""
if num.isnumeric and len(num) == 10:
pq = "\n\n**----••Truecaller says----**\n\nLimit exceeded ,try again tomorrow 🤦🏻♂️"
tresponse = ""
try:
tresponse = truecaller_search(cred.T_AUTH, num)
if tresponse:
restj = tresponse.json()
trslt = json.dumps(restj)
tjsonload = json.loads(trslt)
if "name" in tjsonload['data'][0]:
if tjsonload['data'][0]['internetAddresses']:
pq = f"\n\n**----••Truecaller says----**\n\nName : `{tjsonload['data'][0]['name']}`\nCarrier : `{tjsonload['data'][0]['phones'][0]['carrier']}` \nE-mail : {tjsonload['data'][0]['internetAddresses'][0]['id']}"
frbsetrname = tjsonload['data'][0]['name']
frbsetrmail = tjsonload['data'][0]['internetAddresses'][0]['id']
elif not tjsonload['data'][0]['internetAddresses']:
pq = f"\n\n**----••Truecaller says----**\n\nName : `{tjsonload['data'][0]['name']}`\nCarrier : `{tjsonload['data'][0]['phones'][0]['carrier']}`"
frbsetrname = tjsonload['data'][0]['name']
else:
pq = "\n\n**----••Truecaller says----**\n\nNo results found 🤦🏻♂️"
if tresponse.status_code == 429:
pq = "\n\n**----••Truecaller says----**\n\nLimit exceeded ,try again tomorrow 🤦🏻♂️"
except:
pass
response = eyecon_search(num)
fbres = fb_search(num)
fbrslt = fbres.url.replace('https://graph.', '').replace('picture?width=600', '')
if response:
rslt = response.json()
if rslt:
temp = json.dumps(rslt).replace('[', '').replace(']', '')
jsonload = json.loads(temp)
yk = f"\n\n**----••Eyecon says----**\n\nName :`{jsonload['name']}`"
frbseyename = jsonload["name"]
if "facebook.com" in fbrslt:
yk = f"\n\n**----••Eyecon says----**\n\nName : `{jsonload['name']}`\nFacebook : {fbrslt}"
frbseyename = jsonload["name"]
frbsefb = fbrslt
else:
yk = "**----••Eyecon says----**\n\nNo results found 🤦🏻♂️"
else:
yk = "**----••Eyecon says----**\n\nNo results found 🤦🏻♂️"
yk += pq
pro.edit(text=yk, disable_web_page_preview=True,reply_markup=InlineKeyboardMarkup(
[[InlineKeyboardButton("Source", callback_data="src")]]))
searches()
log()
if frbseyename and frbsefb and frbsetrname and frbsetrmail:
data = {
"Eyecon Name": frbseyename,
"Mob": num,
"Truecaller name": frbsetrname,
"Facebook": frbsefb,
"Mail": frbsetrmail
}
firebase.put('/knowho-log', num, data)
elif frbseyename and frbsefb and frbsetrname:
data = {
"Eyecon Name": frbseyename,
"Mob": num,
"Truecaller name": frbsetrname,
"Facebook": frbsefb
}
firebase.put('/knowho-log', num, data)
elif frbseyename and frbsefb:
data = {
"Eyecon Name": frbseyename,
"Mob": num,
"Facebook": frbsefb
}
firebase.put('/knowho-log', num, data)
elif frbseyename and frbsetrname and frbsetrmail:
data = {
"Eyecon Name": frbseyename,
"Mob": num,
"Truecaller name": frbsetrname,
"Mail": frbsetrmail
}
firebase.put('/knowho-log', num, data)
elif frbseyename and frbsetrname:
data = {
"Eyecon Name": frbseyename,
"Mob": num,
"Truecaller name": frbsetrname
}
firebase.put('/knowho-log', num, data)
elif frbsetrname and frbsetrmail:
data = {
"Truecaller name": frbsetrname,
"Mob": num,
"Mail": frbsetrmail
}
firebase.put('/knowho-log', num, data)
elif frbsetrname:
data = {
"Truecaller name": frbsetrname
}
firebase.put('/knowho-log', num, data)
else:
pro.edit("`Only` **10** `digit numbers allowed` 🤦🏻♂️")
app.run() | 0.257765 | 0.088072 |
# Import `FEModel3D` from `PyNite`
from PyNite import FEModel3D
# Import 'Visualization' for rendering the model
from PyNite import Visualization
# Create a new finite element model
SimpleBeam = FEModel3D()
# Add nodes (14 ft apart)
SimpleBeam.AddNode('N1', 0, 0, 0)
SimpleBeam.AddNode('N2', 14*12, 0, 0)
# Add a beam with the following properties:
# E = 29000 ksi, G = 11400 ksi, Iy = 100 in^4, Iz = 150 in^4, J = 250 in^4, A = 20 in^2
SimpleBeam.AddMember('M1', 'N1', 'N2', 29000, 11400, 100, 150, 250, 20)
# Provide simple supports
SimpleBeam.DefineSupport('N1', True, True, True, True, False, False) # Constrained for torsion at 'N1'
SimpleBeam.DefineSupport('N2', True, True, True, False, False, False) # Not constrained for torsion at 'N2'
# Add a downward point load of 5 kips at the midspan of the beam
SimpleBeam.AddMemberPtLoad('M1', 'Fy', -5, 7*12, 'D') # 5 kips Dead load
SimpleBeam.AddMemberPtLoad('M1', 'Fy', -8, 7*12, 'L') # 8 kips Live load
# Add load combinations
SimpleBeam.AddLoadCombo('1.4D', {'D':1.0})
SimpleBeam.AddLoadCombo('1.2D+1.6L', {'D':1.2, 'L':1.6})
# Analyze the beam and perform a statics check
SimpleBeam.Analyze(check_statics=True)
Visualization.RenderModel(SimpleBeam, text_height=10, deformed_shape=True, deformed_scale=30, render_loads=True, combo_name='1.2D+1.6L',)
# Print the shear, moment, and deflection diagrams
SimpleBeam.GetMember('M1').PlotShear('Fy', '1.2D+1.6L')
SimpleBeam.GetMember('M1').PlotMoment('Mz', '1.2D+1.6L')
SimpleBeam.GetMember('M1').PlotDeflection('dy', '1.2D+1.6L')
# Print reactions at each end of the beam
print('Left Support Reaction:', SimpleBeam.GetNode('N1').RxnFY['1.2D+1.6L'], 'kip')
print('Right Support Reacton:', SimpleBeam.GetNode('N2').RxnFY['1.2D+1.6L'], 'kip')
# Print the max/min shears and moments in the beam
print('Maximum Shear:', SimpleBeam.GetMember('M1').MaxShear('Fy', '1.2D+1.6L'), 'kip')
print('Minimum Shear:', SimpleBeam.GetMember('M1').MinShear('Fy', '1.2D+1.6L'), 'kip')
print('Maximum Moment:', SimpleBeam.GetMember('M1').MaxMoment('Mz', '1.2D+1.6L')/12, 'kip-ft')
print('Minimum Moment:', SimpleBeam.GetMember('M1').MinMoment('Mz', '1.2D+1.6L')/12, 'kip-ft')
# Print the max/min deflections in the beam
print('Maximum Deflection:', SimpleBeam.GetMember('M1').MaxDeflection('dy', '1.2D+1.6L'), 'in')
print('Minimum Deflection:', SimpleBeam.GetMember('M1').MinDeflection('dy', '1.2D+1.6L'), 'in') | Examples/Simple Beam - Point Load.py |
# Import `FEModel3D` from `PyNite`
from PyNite import FEModel3D
# Import 'Visualization' for rendering the model
from PyNite import Visualization
# Create a new finite element model
SimpleBeam = FEModel3D()
# Add nodes (14 ft apart)
SimpleBeam.AddNode('N1', 0, 0, 0)
SimpleBeam.AddNode('N2', 14*12, 0, 0)
# Add a beam with the following properties:
# E = 29000 ksi, G = 11400 ksi, Iy = 100 in^4, Iz = 150 in^4, J = 250 in^4, A = 20 in^2
SimpleBeam.AddMember('M1', 'N1', 'N2', 29000, 11400, 100, 150, 250, 20)
# Provide simple supports
SimpleBeam.DefineSupport('N1', True, True, True, True, False, False) # Constrained for torsion at 'N1'
SimpleBeam.DefineSupport('N2', True, True, True, False, False, False) # Not constrained for torsion at 'N2'
# Add a downward point load of 5 kips at the midspan of the beam
SimpleBeam.AddMemberPtLoad('M1', 'Fy', -5, 7*12, 'D') # 5 kips Dead load
SimpleBeam.AddMemberPtLoad('M1', 'Fy', -8, 7*12, 'L') # 8 kips Live load
# Add load combinations
SimpleBeam.AddLoadCombo('1.4D', {'D':1.0})
SimpleBeam.AddLoadCombo('1.2D+1.6L', {'D':1.2, 'L':1.6})
# Analyze the beam and perform a statics check
SimpleBeam.Analyze(check_statics=True)
Visualization.RenderModel(SimpleBeam, text_height=10, deformed_shape=True, deformed_scale=30, render_loads=True, combo_name='1.2D+1.6L',)
# Print the shear, moment, and deflection diagrams
SimpleBeam.GetMember('M1').PlotShear('Fy', '1.2D+1.6L')
SimpleBeam.GetMember('M1').PlotMoment('Mz', '1.2D+1.6L')
SimpleBeam.GetMember('M1').PlotDeflection('dy', '1.2D+1.6L')
# Print reactions at each end of the beam
print('Left Support Reaction:', SimpleBeam.GetNode('N1').RxnFY['1.2D+1.6L'], 'kip')
print('Right Support Reacton:', SimpleBeam.GetNode('N2').RxnFY['1.2D+1.6L'], 'kip')
# Print the max/min shears and moments in the beam
print('Maximum Shear:', SimpleBeam.GetMember('M1').MaxShear('Fy', '1.2D+1.6L'), 'kip')
print('Minimum Shear:', SimpleBeam.GetMember('M1').MinShear('Fy', '1.2D+1.6L'), 'kip')
print('Maximum Moment:', SimpleBeam.GetMember('M1').MaxMoment('Mz', '1.2D+1.6L')/12, 'kip-ft')
print('Minimum Moment:', SimpleBeam.GetMember('M1').MinMoment('Mz', '1.2D+1.6L')/12, 'kip-ft')
# Print the max/min deflections in the beam
print('Maximum Deflection:', SimpleBeam.GetMember('M1').MaxDeflection('dy', '1.2D+1.6L'), 'in')
print('Minimum Deflection:', SimpleBeam.GetMember('M1').MinDeflection('dy', '1.2D+1.6L'), 'in') | 0.798344 | 0.6508 |
import gi
try:
gi.require_version('Gtk', '3.0')
gi.require_version('Gdk', '3.0')
except Exception as e:
print(e)
exit(-1)
from gi.repository import Gtk
from gi.repository import Gdk
import sys
import importlib
import comun
from config import Configuration
from croni import Croni
from autostart import Autostart
from dwdownloader import change_wallpaper
from fsync import async_function
from comun import get_modules
from comun import _
from singleton import listen_for_activation, activate_if_already_running
sys.path.insert(1, comun.DAILIESDIR)
sys.path.insert(1, comun.USERDAILIESDIR)
def select_value_in_combo(combo, value):
model = combo.get_model()
for i, item in enumerate(model):
if value == item[1]:
combo.set_active(i)
return
combo.set_active(0)
def get_selected_value_in_combo(combo):
model = combo.get_model()
return model.get_value(combo.get_active_iter(), 1)
class DWW(Gtk.Window):
def __init__(self):
Gtk.Window.__init__(self)
self.set_title(_('Daily Wallpaper'))
self.set_modal(True)
self.set_destroy_with_parent(True)
self.set_size_request(370, 80)
self.set_icon_from_file(comun.ICON)
self.connect('realize', self.on_realize)
self.connect('destroy', self.close_application)
self.croni = Croni()
self.autostart = Autostart()
grid = Gtk.Grid()
grid.set_row_spacing(10)
grid.set_column_spacing(10)
grid.set_border_width(10)
self.add(grid)
label10 = Gtk.Label.new(_('Change wallpaper automatically?'))
label10.set_halign(True)
grid.add(label10)
self.switch = Gtk.Switch.new()
self.switch.set_halign(True)
self.switch.set_active(self.croni.is_enabled())
grid.attach(self.switch, 1, 0, 1, 1)
label20 = Gtk.Label.new(_('Random source?'))
label20.set_halign(True)
grid.attach(label20, 0, 1, 1, 1)
self.switch_random = Gtk.Switch.new()
self.switch_random.set_halign(True)
self.switch_random.set_active(True)
self.switch_random.connect('state-set', self.on_switch_random_changed)
grid.attach(self.switch_random, 1, 1, 1, 1)
self.label30 = Gtk.Label.new(_('Select backgrounds source:'))
self.label30.set_halign(True)
grid.attach(self.label30, 0, 2, 1, 1)
source_store = Gtk.ListStore(str, str)
source_store.set_sort_func(0, self.tree_compare_func, None)
for module_name in get_modules():
module = importlib.import_module(module_name)
daily = module.get_daily()
source_store.append([daily.get_name(), daily.get_id()])
self.combobox_source = Gtk.ComboBox.new()
self.combobox_source.set_model(source_store)
cell1 = Gtk.CellRendererText()
self.combobox_source.pack_start(cell1, True)
self.combobox_source.add_attribute(cell1, 'text', 0)
grid.attach(self.combobox_source, 1, 2, 1, 1)
button = Gtk.Button.new_with_label(_('Change now'))
button.set_halign(Gtk.Align.CENTER)
button.connect('clicked', self.button_pressed)
grid.attach(button, 0, 3, 2, 1)
hb = Gtk.HeaderBar()
self.set_titlebar(hb)
hb.set_show_close_button(True)
hb.props.title = comun.APP
button_cancel = Gtk.Button.new_with_label(_('Cancel'))
button_cancel.get_style_context().add_class(
Gtk.STYLE_CLASS_DESTRUCTIVE_ACTION)
button_cancel.set_halign(Gtk.Align.START)
button_cancel.connect('clicked', self.on_button_cancel_clicked)
hb.pack_start(button_cancel)
button_ok = Gtk.Button.new_with_label(_('Ok'))
button_ok.get_style_context().add_class(
Gtk.STYLE_CLASS_SUGGESTED_ACTION)
button_ok.set_halign(Gtk.Align.END)
button_ok.connect('clicked', self.on_button_ok_clicked)
hb.pack_end(button_ok)
self.load_preferences()
self.show_all()
def tree_compare_func(self, row1, row2):
"""
a negative integer, zero or a positive integer depending on whether a
sorts before, with or after b
"""
print(type(row1), row1)
if row1 < row2:
return -1
elif row1 > row2:
return 1
return 0
def on_button_ok_clicked(self, widget):
self.hide()
self.set_autostart_activate()
self.save_preferences()
self.destroy()
def on_button_cancel_clicked(self, widget):
self.destroy()
def set_source_state(self, state):
self.label30.set_sensitive(state)
self.combobox_source.set_sensitive(state)
def on_switch_random_changed(self, widget, state):
state = self.switch_random.get_active()
self.set_source_state(not state)
def set_autostart_activate(self):
if self.switch.get_active():
self.croni.set_jobs()
self.autostart.set_autostart(True)
else:
self.croni.unset_jobs()
self.autostart.set_autostart(False)
def button_pressed(self, widget):
self.change_wallpaper_async()
def close_application(self, widget, data=None):
exit(0)
def load_preferences(self):
config = Configuration()
select_value_in_combo(self.combobox_source, config.get('source'))
self.switch_random.set_active(config.get('random'))
self.set_source_state(not config.get('random'))
def save_preferences(self):
config = Configuration()
config.set('source', get_selected_value_in_combo(self.combobox_source))
config.set('random', self.switch_random.get_active())
config.save()
def change_wallpaper_async(self):
def on_change_wallpaper_done(result, error):
self.get_window().set_cursor(None)
@async_function(on_done=on_change_wallpaper_done)
def do_change_wallpaper_in_thread():
self.save_preferences()
change_wallpaper()
return True
self.get_window().set_cursor(Gdk.Cursor(Gdk.CursorType.WATCH))
do_change_wallpaper_in_thread()
def on_realize(self, *_):
monitor = Gdk.Display.get_primary_monitor(Gdk.Display.get_default())
scale = monitor.get_scale_factor()
monitor_width = monitor.get_geometry().width / scale
monitor_height = monitor.get_geometry().height / scale
width = self.get_preferred_width()[0]
height = self.get_preferred_height()[0]
self.move((monitor_width - width)/2, (monitor_height - height)/2)
def main():
"""TODO: Docstring for main.
:returns: TODO
"""
APP_ID = 'es.atareao.daily_wallpaper'
activated = activate_if_already_running(APP_ID)
if activated:
sys.exit(0)
dww = DWW()
listen_for_activation(APP_ID, dww)
Gtk.main()
if __name__ == '__main__':
main() | src/main.py |
import gi
try:
gi.require_version('Gtk', '3.0')
gi.require_version('Gdk', '3.0')
except Exception as e:
print(e)
exit(-1)
from gi.repository import Gtk
from gi.repository import Gdk
import sys
import importlib
import comun
from config import Configuration
from croni import Croni
from autostart import Autostart
from dwdownloader import change_wallpaper
from fsync import async_function
from comun import get_modules
from comun import _
from singleton import listen_for_activation, activate_if_already_running
sys.path.insert(1, comun.DAILIESDIR)
sys.path.insert(1, comun.USERDAILIESDIR)
def select_value_in_combo(combo, value):
model = combo.get_model()
for i, item in enumerate(model):
if value == item[1]:
combo.set_active(i)
return
combo.set_active(0)
def get_selected_value_in_combo(combo):
model = combo.get_model()
return model.get_value(combo.get_active_iter(), 1)
class DWW(Gtk.Window):
def __init__(self):
Gtk.Window.__init__(self)
self.set_title(_('Daily Wallpaper'))
self.set_modal(True)
self.set_destroy_with_parent(True)
self.set_size_request(370, 80)
self.set_icon_from_file(comun.ICON)
self.connect('realize', self.on_realize)
self.connect('destroy', self.close_application)
self.croni = Croni()
self.autostart = Autostart()
grid = Gtk.Grid()
grid.set_row_spacing(10)
grid.set_column_spacing(10)
grid.set_border_width(10)
self.add(grid)
label10 = Gtk.Label.new(_('Change wallpaper automatically?'))
label10.set_halign(True)
grid.add(label10)
self.switch = Gtk.Switch.new()
self.switch.set_halign(True)
self.switch.set_active(self.croni.is_enabled())
grid.attach(self.switch, 1, 0, 1, 1)
label20 = Gtk.Label.new(_('Random source?'))
label20.set_halign(True)
grid.attach(label20, 0, 1, 1, 1)
self.switch_random = Gtk.Switch.new()
self.switch_random.set_halign(True)
self.switch_random.set_active(True)
self.switch_random.connect('state-set', self.on_switch_random_changed)
grid.attach(self.switch_random, 1, 1, 1, 1)
self.label30 = Gtk.Label.new(_('Select backgrounds source:'))
self.label30.set_halign(True)
grid.attach(self.label30, 0, 2, 1, 1)
source_store = Gtk.ListStore(str, str)
source_store.set_sort_func(0, self.tree_compare_func, None)
for module_name in get_modules():
module = importlib.import_module(module_name)
daily = module.get_daily()
source_store.append([daily.get_name(), daily.get_id()])
self.combobox_source = Gtk.ComboBox.new()
self.combobox_source.set_model(source_store)
cell1 = Gtk.CellRendererText()
self.combobox_source.pack_start(cell1, True)
self.combobox_source.add_attribute(cell1, 'text', 0)
grid.attach(self.combobox_source, 1, 2, 1, 1)
button = Gtk.Button.new_with_label(_('Change now'))
button.set_halign(Gtk.Align.CENTER)
button.connect('clicked', self.button_pressed)
grid.attach(button, 0, 3, 2, 1)
hb = Gtk.HeaderBar()
self.set_titlebar(hb)
hb.set_show_close_button(True)
hb.props.title = comun.APP
button_cancel = Gtk.Button.new_with_label(_('Cancel'))
button_cancel.get_style_context().add_class(
Gtk.STYLE_CLASS_DESTRUCTIVE_ACTION)
button_cancel.set_halign(Gtk.Align.START)
button_cancel.connect('clicked', self.on_button_cancel_clicked)
hb.pack_start(button_cancel)
button_ok = Gtk.Button.new_with_label(_('Ok'))
button_ok.get_style_context().add_class(
Gtk.STYLE_CLASS_SUGGESTED_ACTION)
button_ok.set_halign(Gtk.Align.END)
button_ok.connect('clicked', self.on_button_ok_clicked)
hb.pack_end(button_ok)
self.load_preferences()
self.show_all()
def tree_compare_func(self, row1, row2):
"""
a negative integer, zero or a positive integer depending on whether a
sorts before, with or after b
"""
print(type(row1), row1)
if row1 < row2:
return -1
elif row1 > row2:
return 1
return 0
def on_button_ok_clicked(self, widget):
self.hide()
self.set_autostart_activate()
self.save_preferences()
self.destroy()
def on_button_cancel_clicked(self, widget):
self.destroy()
def set_source_state(self, state):
self.label30.set_sensitive(state)
self.combobox_source.set_sensitive(state)
def on_switch_random_changed(self, widget, state):
state = self.switch_random.get_active()
self.set_source_state(not state)
def set_autostart_activate(self):
if self.switch.get_active():
self.croni.set_jobs()
self.autostart.set_autostart(True)
else:
self.croni.unset_jobs()
self.autostart.set_autostart(False)
def button_pressed(self, widget):
self.change_wallpaper_async()
def close_application(self, widget, data=None):
exit(0)
def load_preferences(self):
config = Configuration()
select_value_in_combo(self.combobox_source, config.get('source'))
self.switch_random.set_active(config.get('random'))
self.set_source_state(not config.get('random'))
def save_preferences(self):
config = Configuration()
config.set('source', get_selected_value_in_combo(self.combobox_source))
config.set('random', self.switch_random.get_active())
config.save()
def change_wallpaper_async(self):
def on_change_wallpaper_done(result, error):
self.get_window().set_cursor(None)
@async_function(on_done=on_change_wallpaper_done)
def do_change_wallpaper_in_thread():
self.save_preferences()
change_wallpaper()
return True
self.get_window().set_cursor(Gdk.Cursor(Gdk.CursorType.WATCH))
do_change_wallpaper_in_thread()
def on_realize(self, *_):
monitor = Gdk.Display.get_primary_monitor(Gdk.Display.get_default())
scale = monitor.get_scale_factor()
monitor_width = monitor.get_geometry().width / scale
monitor_height = monitor.get_geometry().height / scale
width = self.get_preferred_width()[0]
height = self.get_preferred_height()[0]
self.move((monitor_width - width)/2, (monitor_height - height)/2)
def main():
"""TODO: Docstring for main.
:returns: TODO
"""
APP_ID = 'es.atareao.daily_wallpaper'
activated = activate_if_already_running(APP_ID)
if activated:
sys.exit(0)
dww = DWW()
listen_for_activation(APP_ID, dww)
Gtk.main()
if __name__ == '__main__':
main() | 0.31237 | 0.13707 |
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('application', '0049_auto_20201119_0924'),
]
operations = [
migrations.RemoveField(
model_name='landingpages',
name='button_text_en',
),
migrations.RemoveField(
model_name='landingpages',
name='button_text_fi',
),
migrations.RemoveField(
model_name='landingpages',
name='button_text_sv',
),
migrations.RemoveField(
model_name='landingpages',
name='button_url_en',
),
migrations.RemoveField(
model_name='landingpages',
name='button_url_fi',
),
migrations.RemoveField(
model_name='landingpages',
name='button_url_sv',
),
migrations.RemoveField(
model_name='landingpages',
name='description_en',
),
migrations.RemoveField(
model_name='landingpages',
name='description_fi',
),
migrations.RemoveField(
model_name='landingpages',
name='description_sv',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_background_image_color_en',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_background_image_color_fi',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_background_image_color_sv',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_background_image_en',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_background_image_fi',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_background_image_mobile_en',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_background_image_mobile_fi',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_background_image_mobile_sv',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_background_image_sv',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_top_layer_image_en',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_top_layer_image_fi',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_top_layer_image_sv',
),
migrations.RemoveField(
model_name='landingpages',
name='social_media_image_en',
),
migrations.RemoveField(
model_name='landingpages',
name='social_media_image_fi',
),
migrations.RemoveField(
model_name='landingpages',
name='social_media_image_sv',
),
migrations.RemoveField(
model_name='landingpages',
name='title_and_description_color_en',
),
migrations.RemoveField(
model_name='landingpages',
name='title_and_description_color_fi',
),
migrations.RemoveField(
model_name='landingpages',
name='title_and_description_color_sv',
),
migrations.RemoveField(
model_name='landingpages',
name='title_en',
),
migrations.RemoveField(
model_name='landingpages',
name='title_fi',
),
migrations.RemoveField(
model_name='landingpages',
name='title_sv',
),
] | application/migrations/0050_auto_20201222_1046.py |
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('application', '0049_auto_20201119_0924'),
]
operations = [
migrations.RemoveField(
model_name='landingpages',
name='button_text_en',
),
migrations.RemoveField(
model_name='landingpages',
name='button_text_fi',
),
migrations.RemoveField(
model_name='landingpages',
name='button_text_sv',
),
migrations.RemoveField(
model_name='landingpages',
name='button_url_en',
),
migrations.RemoveField(
model_name='landingpages',
name='button_url_fi',
),
migrations.RemoveField(
model_name='landingpages',
name='button_url_sv',
),
migrations.RemoveField(
model_name='landingpages',
name='description_en',
),
migrations.RemoveField(
model_name='landingpages',
name='description_fi',
),
migrations.RemoveField(
model_name='landingpages',
name='description_sv',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_background_image_color_en',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_background_image_color_fi',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_background_image_color_sv',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_background_image_en',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_background_image_fi',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_background_image_mobile_en',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_background_image_mobile_fi',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_background_image_mobile_sv',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_background_image_sv',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_top_layer_image_en',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_top_layer_image_fi',
),
migrations.RemoveField(
model_name='landingpages',
name='hero_top_layer_image_sv',
),
migrations.RemoveField(
model_name='landingpages',
name='social_media_image_en',
),
migrations.RemoveField(
model_name='landingpages',
name='social_media_image_fi',
),
migrations.RemoveField(
model_name='landingpages',
name='social_media_image_sv',
),
migrations.RemoveField(
model_name='landingpages',
name='title_and_description_color_en',
),
migrations.RemoveField(
model_name='landingpages',
name='title_and_description_color_fi',
),
migrations.RemoveField(
model_name='landingpages',
name='title_and_description_color_sv',
),
migrations.RemoveField(
model_name='landingpages',
name='title_en',
),
migrations.RemoveField(
model_name='landingpages',
name='title_fi',
),
migrations.RemoveField(
model_name='landingpages',
name='title_sv',
),
] | 0.594904 | 0.097347 |
import argparse
import logging
import os
import random
import socket
import sys
import traceback
import numpy as np
import psutil
import setproctitle
import torch
import wandb
from mpi4py import MPI
# add the FedML root directory to the python path
sys.path.insert(0, os.path.abspath(os.path.join(os.getcwd(), "../../../")))
from fedml_api.distributed.utils.gpu_mapping import mapping_processes_to_gpu_device_from_yaml_file
from fedml_api.data_preprocessing.FederatedEMNIST.data_loader import load_partition_data_federated_emnist
from fedml_api.data_preprocessing.fed_cifar100.data_loader import load_partition_data_federated_cifar100
from fedml_api.data_preprocessing.fed_shakespeare.data_loader import load_partition_data_federated_shakespeare
from fedml_api.data_preprocessing.shakespeare.data_loader import load_partition_data_shakespeare
from fedml_api.data_preprocessing.stackoverflow_lr.data_loader import load_partition_data_federated_stackoverflow_lr
from fedml_api.data_preprocessing.stackoverflow_nwp.data_loader import load_partition_data_federated_stackoverflow_nwp
from fedml_api.data_preprocessing.MNIST.data_loader import load_partition_data_mnist
from fedml_api.data_preprocessing.ImageNet.data_loader import load_partition_data_ImageNet
from fedml_api.data_preprocessing.Landmarks.data_loader import load_partition_data_landmarks
from fedml_api.data_preprocessing.cifar10.data_loader import load_partition_data_cifar10
from fedml_api.data_preprocessing.cifar100.data_loader import load_partition_data_cifar100
from fedml_api.data_preprocessing.cinic10.data_loader import load_partition_data_cinic10
from fedml_api.model.cv.cnn import CNN_DropOut
from fedml_api.model.cv.resnet_gn import resnet18
from fedml_api.model.cv.mobilenet import mobilenet
from fedml_api.model.cv.resnet import resnet56
from fedml_api.model.nlp.rnn import RNN_OriginalFedAvg, RNN_StackOverFlow
from fedml_api.model.linear.lr import LogisticRegression
from fedml_api.model.cv.mobilenet_v3 import MobileNetV3
from fedml_api.model.cv.efficientnet import EfficientNet
from fedml_api.distributed.fedavg.FedAvgAPI import FedML_init, FedML_FedAvg_distributed
def add_args(parser):
"""
parser : argparse.ArgumentParser
return a parser added with args required by fit
"""
# Training settings
parser.add_argument('--model', type=str, default='mobilenet', metavar='N',
help='neural network used in training')
parser.add_argument('--dataset', type=str, default='cifar10', metavar='N',
help='dataset used for training')
parser.add_argument('--data_dir', type=str, default='./../../../data/cifar10',
help='data directory')
parser.add_argument('--partition_method', type=str, default='hetero', metavar='N',
help='how to partition the dataset on local workers')
parser.add_argument('--partition_alpha', type=float, default=0.5, metavar='PA',
help='partition alpha (default: 0.5)')
parser.add_argument('--client_num_in_total', type=int, default=1000, metavar='NN',
help='number of workers in a distributed cluster')
parser.add_argument('--client_num_per_round', type=int, default=4, metavar='NN',
help='number of workers')
parser.add_argument('--batch_size', type=int, default=64, metavar='N',
help='input batch size for training (default: 64)')
parser.add_argument('--client_optimizer', type=str, default='adam',
help='SGD with momentum; adam')
parser.add_argument('--lr', type=float, default=0.001, metavar='LR',
help='learning rate (default: 0.001)')
parser.add_argument('--wd', help='weight decay parameter;', type=float, default=0.001)
parser.add_argument('--epochs', type=int, default=5, metavar='EP',
help='how many epochs will be trained locally')
parser.add_argument('--comm_round', type=int, default=10,
help='how many round of communications we shoud use')
parser.add_argument('--is_mobile', type=int, default=0,
help='whether the program is running on the FedML-Mobile server side')
parser.add_argument('--frequency_of_the_test', type=int, default=1,
help='the frequency of the algorithms')
parser.add_argument('--gpu_server_num', type=int, default=1,
help='gpu_server_num')
parser.add_argument('--gpu_num_per_server', type=int, default=4,
help='gpu_num_per_server')
parser.add_argument('--gpu_mapping_file', type=str, default="gpu_mapping.yaml",
help='the gpu utilization file for servers and clients. If there is no \
gpu_util_file, gpu will not be used.')
parser.add_argument('--gpu_mapping_key', type=str, default="mapping_default",
help='the key in gpu utilization file')
parser.add_argument('--ci', type=int, default=0,
help='CI')
args = parser.parse_args()
return args
def load_data(args, dataset_name):
if dataset_name == "mnist":
logging.info("load_data. dataset_name = %s" % dataset_name)
client_num, train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = load_partition_data_mnist(args.batch_size)
"""
For shallow NN or linear models,
we uniformly sample a fraction of clients each round (as the original FedAvg paper)
"""
args.client_num_in_total = client_num
elif dataset_name == "femnist":
logging.info("load_data. dataset_name = %s" % dataset_name)
client_num, train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = load_partition_data_federated_emnist(args.dataset, args.data_dir)
args.client_num_in_total = client_num
elif dataset_name == "shakespeare":
logging.info("load_data. dataset_name = %s" % dataset_name)
client_num, train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = load_partition_data_shakespeare(args.batch_size)
args.client_num_in_total = client_num
elif dataset_name == "fed_shakespeare":
logging.info("load_data. dataset_name = %s" % dataset_name)
client_num, train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = load_partition_data_federated_shakespeare(args.dataset, args.data_dir)
args.client_num_in_total = client_num
elif dataset_name == "fed_cifar100":
logging.info("load_data. dataset_name = %s" % dataset_name)
client_num, train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = load_partition_data_federated_cifar100(args.dataset, args.data_dir)
args.client_num_in_total = client_num
elif dataset_name == "stackoverflow_lr":
logging.info("load_data. dataset_name = %s" % dataset_name)
client_num, train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = load_partition_data_federated_stackoverflow_lr(args.dataset, args.data_dir)
args.client_num_in_total = client_num
elif dataset_name == "stackoverflow_nwp":
logging.info("load_data. dataset_name = %s" % dataset_name)
client_num, train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = load_partition_data_federated_stackoverflow_nwp(args.dataset, args.data_dir)
args.client_num_in_total = client_num
elif dataset_name == "ILSVRC2012":
logging.info("load_data. dataset_name = %s" % dataset_name)
train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = load_partition_data_ImageNet(dataset=dataset_name, data_dir=args.data_dir,
partition_method=None, partition_alpha=None,
client_number=args.client_num_in_total, batch_size=args.batch_size)
elif dataset_name == "gld23k":
logging.info("load_data. dataset_name = %s" % dataset_name)
args.client_num_in_total = 233
fed_train_map_file = os.path.join(args.data_dir, 'mini_gld_train_split.csv')
fed_test_map_file = os.path.join(args.data_dir, 'mini_gld_test.csv')
args.data_dir = os.path.join(args.data_dir, 'images')
train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = load_partition_data_landmarks(dataset=dataset_name, data_dir=args.data_dir,
fed_train_map_file=fed_train_map_file,
fed_test_map_file=fed_test_map_file,
partition_method=None, partition_alpha=None,
client_number=args.client_num_in_total, batch_size=args.batch_size)
elif dataset_name == "gld160k":
logging.info("load_data. dataset_name = %s" % dataset_name)
args.client_num_in_total = 1262
fed_train_map_file = os.path.join(args.data_dir, 'federated_train.csv')
fed_test_map_file = os.path.join(args.data_dir, 'test.csv')
args.data_dir = os.path.join(args.data_dir, 'images')
train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = load_partition_data_landmarks(dataset=dataset_name, data_dir=args.data_dir,
fed_train_map_file=fed_train_map_file,
fed_test_map_file=fed_test_map_file,
partition_method=None, partition_alpha=None,
client_number=args.client_num_in_total, batch_size=args.batch_size)
else:
if dataset_name == "cifar10":
data_loader = load_partition_data_cifar10
elif dataset_name == "cifar100":
data_loader = load_partition_data_cifar100
elif dataset_name == "cinic10":
data_loader = load_partition_data_cinic10
else:
data_loader = load_partition_data_cifar10
train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = data_loader(args.dataset, args.data_dir, args.partition_method,
args.partition_alpha, args.client_num_in_total, args.batch_size)
dataset = [train_data_num, test_data_num, train_data_global, test_data_global,
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, class_num]
return dataset
def create_model(args, model_name, output_dim):
logging.info("create_model. model_name = %s, output_dim = %s" % (model_name, output_dim))
model = None
if model_name == "lr" and args.dataset == "mnist":
logging.info("LogisticRegression + MNIST")
model = LogisticRegression(28 * 28, output_dim)
elif model_name == "rnn" and args.dataset == "shakespeare":
logging.info("RNN + shakespeare")
model = RNN_OriginalFedAvg()
elif model_name == "cnn" and args.dataset == "femnist":
logging.info("CNN + FederatedEMNIST")
model = CNN_DropOut(False)
elif model_name == "resnet18_gn" and args.dataset == "fed_cifar100":
logging.info("ResNet18_GN + Federated_CIFAR100")
model = resnet18()
elif model_name == "rnn" and args.dataset == "fed_shakespeare":
logging.info("RNN + fed_shakespeare")
model = RNN_OriginalFedAvg()
elif model_name == "lr" and args.dataset == "stackoverflow_lr":
logging.info("lr + stackoverflow_lr")
model = LogisticRegression(10004, output_dim)
elif model_name == "rnn" and args.dataset == "stackoverflow_nwp":
logging.info("CNN + stackoverflow_nwp")
model = RNN_StackOverFlow()
elif model_name == "resnet56":
model = resnet56(class_num=output_dim)
elif model_name == "mobilenet":
model = mobilenet(class_num=output_dim)
# TODO
elif model_name == 'mobilenet_v3':
'''model_mode \in {LARGE: 5.15M, SMALL: 2.94M}'''
model = MobileNetV3(model_mode='LARGE')
elif model_name == 'efficientnet':
model = EfficientNet()
return model
if __name__ == "__main__":
# initialize distributed computing (MPI)
comm, process_id, worker_number = FedML_init()
# parse python script input parameters
parser = argparse.ArgumentParser()
args = add_args(parser)
logging.info(args)
# customize the process name
str_process_name = "FedAvg (distributed):" + str(process_id)
setproctitle.setproctitle(str_process_name)
# customize the log format
# logging.basicConfig(level=logging.INFO,
logging.basicConfig(level=logging.DEBUG,
format=str(
process_id) + ' - %(asctime)s %(filename)s[line:%(lineno)d] %(levelname)s %(message)s',
datefmt='%a, %d %b %Y %H:%M:%S')
hostname = socket.gethostname()
logging.info("#############process ID = " + str(process_id) +
", host name = " + hostname + "########" +
", process ID = " + str(os.getpid()) +
", process Name = " + str(psutil.Process(os.getpid())))
# initialize the wandb machine learning experimental tracking platform (https://www.wandb.com/).
if process_id == 0:
wandb.init(
# project="federated_nas",
project="fedml",
name="FedAVG(d)" + str(args.partition_method) + "r" + str(args.comm_round) + "-e" + str(
args.epochs) + "-lr" + str(
args.lr),
config=args
)
# Set the random seed. The np.random seed determines the dataset partition.
# The torch_manual_seed determines the initial weight.
# We fix these two, so that we can reproduce the result.
random.seed(0)
np.random.seed(0)
torch.manual_seed(0)
torch.cuda.manual_seed_all(0)
# Please check "GPU_MAPPING.md" to see how to define the topology
logging.info("process_id = %d, size = %d" % (process_id, worker_number))
device = mapping_processes_to_gpu_device_from_yaml_file(process_id, worker_number, args.gpu_mapping_file, args.gpu_mapping_key)
# load data
dataset = load_data(args, args.dataset)
[train_data_num, test_data_num, train_data_global, test_data_global,
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, class_num] = dataset
# create model.
# Note if the model is DNN (e.g., ResNet), the training will be very slow.
# In this case, please use our FedML distributed version (./fedml_experiments/distributed_fedavg)
model = create_model(args, model_name=args.model, output_dim=dataset[7])
try:
# start "federated averaging (FedAvg)"
FedML_FedAvg_distributed(process_id, worker_number, device, comm,
model, train_data_num, train_data_global, test_data_global,
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, args)
except Exception as e:
print(e)
logging.info('traceback.format_exc():\n%s' % traceback.format_exc())
MPI.COMM_WORLD.Abort() | fedml_experiments/distributed/fedavg/main_fedavg.py | import argparse
import logging
import os
import random
import socket
import sys
import traceback
import numpy as np
import psutil
import setproctitle
import torch
import wandb
from mpi4py import MPI
# add the FedML root directory to the python path
sys.path.insert(0, os.path.abspath(os.path.join(os.getcwd(), "../../../")))
from fedml_api.distributed.utils.gpu_mapping import mapping_processes_to_gpu_device_from_yaml_file
from fedml_api.data_preprocessing.FederatedEMNIST.data_loader import load_partition_data_federated_emnist
from fedml_api.data_preprocessing.fed_cifar100.data_loader import load_partition_data_federated_cifar100
from fedml_api.data_preprocessing.fed_shakespeare.data_loader import load_partition_data_federated_shakespeare
from fedml_api.data_preprocessing.shakespeare.data_loader import load_partition_data_shakespeare
from fedml_api.data_preprocessing.stackoverflow_lr.data_loader import load_partition_data_federated_stackoverflow_lr
from fedml_api.data_preprocessing.stackoverflow_nwp.data_loader import load_partition_data_federated_stackoverflow_nwp
from fedml_api.data_preprocessing.MNIST.data_loader import load_partition_data_mnist
from fedml_api.data_preprocessing.ImageNet.data_loader import load_partition_data_ImageNet
from fedml_api.data_preprocessing.Landmarks.data_loader import load_partition_data_landmarks
from fedml_api.data_preprocessing.cifar10.data_loader import load_partition_data_cifar10
from fedml_api.data_preprocessing.cifar100.data_loader import load_partition_data_cifar100
from fedml_api.data_preprocessing.cinic10.data_loader import load_partition_data_cinic10
from fedml_api.model.cv.cnn import CNN_DropOut
from fedml_api.model.cv.resnet_gn import resnet18
from fedml_api.model.cv.mobilenet import mobilenet
from fedml_api.model.cv.resnet import resnet56
from fedml_api.model.nlp.rnn import RNN_OriginalFedAvg, RNN_StackOverFlow
from fedml_api.model.linear.lr import LogisticRegression
from fedml_api.model.cv.mobilenet_v3 import MobileNetV3
from fedml_api.model.cv.efficientnet import EfficientNet
from fedml_api.distributed.fedavg.FedAvgAPI import FedML_init, FedML_FedAvg_distributed
def add_args(parser):
"""
parser : argparse.ArgumentParser
return a parser added with args required by fit
"""
# Training settings
parser.add_argument('--model', type=str, default='mobilenet', metavar='N',
help='neural network used in training')
parser.add_argument('--dataset', type=str, default='cifar10', metavar='N',
help='dataset used for training')
parser.add_argument('--data_dir', type=str, default='./../../../data/cifar10',
help='data directory')
parser.add_argument('--partition_method', type=str, default='hetero', metavar='N',
help='how to partition the dataset on local workers')
parser.add_argument('--partition_alpha', type=float, default=0.5, metavar='PA',
help='partition alpha (default: 0.5)')
parser.add_argument('--client_num_in_total', type=int, default=1000, metavar='NN',
help='number of workers in a distributed cluster')
parser.add_argument('--client_num_per_round', type=int, default=4, metavar='NN',
help='number of workers')
parser.add_argument('--batch_size', type=int, default=64, metavar='N',
help='input batch size for training (default: 64)')
parser.add_argument('--client_optimizer', type=str, default='adam',
help='SGD with momentum; adam')
parser.add_argument('--lr', type=float, default=0.001, metavar='LR',
help='learning rate (default: 0.001)')
parser.add_argument('--wd', help='weight decay parameter;', type=float, default=0.001)
parser.add_argument('--epochs', type=int, default=5, metavar='EP',
help='how many epochs will be trained locally')
parser.add_argument('--comm_round', type=int, default=10,
help='how many round of communications we shoud use')
parser.add_argument('--is_mobile', type=int, default=0,
help='whether the program is running on the FedML-Mobile server side')
parser.add_argument('--frequency_of_the_test', type=int, default=1,
help='the frequency of the algorithms')
parser.add_argument('--gpu_server_num', type=int, default=1,
help='gpu_server_num')
parser.add_argument('--gpu_num_per_server', type=int, default=4,
help='gpu_num_per_server')
parser.add_argument('--gpu_mapping_file', type=str, default="gpu_mapping.yaml",
help='the gpu utilization file for servers and clients. If there is no \
gpu_util_file, gpu will not be used.')
parser.add_argument('--gpu_mapping_key', type=str, default="mapping_default",
help='the key in gpu utilization file')
parser.add_argument('--ci', type=int, default=0,
help='CI')
args = parser.parse_args()
return args
def load_data(args, dataset_name):
if dataset_name == "mnist":
logging.info("load_data. dataset_name = %s" % dataset_name)
client_num, train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = load_partition_data_mnist(args.batch_size)
"""
For shallow NN or linear models,
we uniformly sample a fraction of clients each round (as the original FedAvg paper)
"""
args.client_num_in_total = client_num
elif dataset_name == "femnist":
logging.info("load_data. dataset_name = %s" % dataset_name)
client_num, train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = load_partition_data_federated_emnist(args.dataset, args.data_dir)
args.client_num_in_total = client_num
elif dataset_name == "shakespeare":
logging.info("load_data. dataset_name = %s" % dataset_name)
client_num, train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = load_partition_data_shakespeare(args.batch_size)
args.client_num_in_total = client_num
elif dataset_name == "fed_shakespeare":
logging.info("load_data. dataset_name = %s" % dataset_name)
client_num, train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = load_partition_data_federated_shakespeare(args.dataset, args.data_dir)
args.client_num_in_total = client_num
elif dataset_name == "fed_cifar100":
logging.info("load_data. dataset_name = %s" % dataset_name)
client_num, train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = load_partition_data_federated_cifar100(args.dataset, args.data_dir)
args.client_num_in_total = client_num
elif dataset_name == "stackoverflow_lr":
logging.info("load_data. dataset_name = %s" % dataset_name)
client_num, train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = load_partition_data_federated_stackoverflow_lr(args.dataset, args.data_dir)
args.client_num_in_total = client_num
elif dataset_name == "stackoverflow_nwp":
logging.info("load_data. dataset_name = %s" % dataset_name)
client_num, train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = load_partition_data_federated_stackoverflow_nwp(args.dataset, args.data_dir)
args.client_num_in_total = client_num
elif dataset_name == "ILSVRC2012":
logging.info("load_data. dataset_name = %s" % dataset_name)
train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = load_partition_data_ImageNet(dataset=dataset_name, data_dir=args.data_dir,
partition_method=None, partition_alpha=None,
client_number=args.client_num_in_total, batch_size=args.batch_size)
elif dataset_name == "gld23k":
logging.info("load_data. dataset_name = %s" % dataset_name)
args.client_num_in_total = 233
fed_train_map_file = os.path.join(args.data_dir, 'mini_gld_train_split.csv')
fed_test_map_file = os.path.join(args.data_dir, 'mini_gld_test.csv')
args.data_dir = os.path.join(args.data_dir, 'images')
train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = load_partition_data_landmarks(dataset=dataset_name, data_dir=args.data_dir,
fed_train_map_file=fed_train_map_file,
fed_test_map_file=fed_test_map_file,
partition_method=None, partition_alpha=None,
client_number=args.client_num_in_total, batch_size=args.batch_size)
elif dataset_name == "gld160k":
logging.info("load_data. dataset_name = %s" % dataset_name)
args.client_num_in_total = 1262
fed_train_map_file = os.path.join(args.data_dir, 'federated_train.csv')
fed_test_map_file = os.path.join(args.data_dir, 'test.csv')
args.data_dir = os.path.join(args.data_dir, 'images')
train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = load_partition_data_landmarks(dataset=dataset_name, data_dir=args.data_dir,
fed_train_map_file=fed_train_map_file,
fed_test_map_file=fed_test_map_file,
partition_method=None, partition_alpha=None,
client_number=args.client_num_in_total, batch_size=args.batch_size)
else:
if dataset_name == "cifar10":
data_loader = load_partition_data_cifar10
elif dataset_name == "cifar100":
data_loader = load_partition_data_cifar100
elif dataset_name == "cinic10":
data_loader = load_partition_data_cinic10
else:
data_loader = load_partition_data_cifar10
train_data_num, test_data_num, train_data_global, test_data_global, \
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, \
class_num = data_loader(args.dataset, args.data_dir, args.partition_method,
args.partition_alpha, args.client_num_in_total, args.batch_size)
dataset = [train_data_num, test_data_num, train_data_global, test_data_global,
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, class_num]
return dataset
def create_model(args, model_name, output_dim):
logging.info("create_model. model_name = %s, output_dim = %s" % (model_name, output_dim))
model = None
if model_name == "lr" and args.dataset == "mnist":
logging.info("LogisticRegression + MNIST")
model = LogisticRegression(28 * 28, output_dim)
elif model_name == "rnn" and args.dataset == "shakespeare":
logging.info("RNN + shakespeare")
model = RNN_OriginalFedAvg()
elif model_name == "cnn" and args.dataset == "femnist":
logging.info("CNN + FederatedEMNIST")
model = CNN_DropOut(False)
elif model_name == "resnet18_gn" and args.dataset == "fed_cifar100":
logging.info("ResNet18_GN + Federated_CIFAR100")
model = resnet18()
elif model_name == "rnn" and args.dataset == "fed_shakespeare":
logging.info("RNN + fed_shakespeare")
model = RNN_OriginalFedAvg()
elif model_name == "lr" and args.dataset == "stackoverflow_lr":
logging.info("lr + stackoverflow_lr")
model = LogisticRegression(10004, output_dim)
elif model_name == "rnn" and args.dataset == "stackoverflow_nwp":
logging.info("CNN + stackoverflow_nwp")
model = RNN_StackOverFlow()
elif model_name == "resnet56":
model = resnet56(class_num=output_dim)
elif model_name == "mobilenet":
model = mobilenet(class_num=output_dim)
# TODO
elif model_name == 'mobilenet_v3':
'''model_mode \in {LARGE: 5.15M, SMALL: 2.94M}'''
model = MobileNetV3(model_mode='LARGE')
elif model_name == 'efficientnet':
model = EfficientNet()
return model
if __name__ == "__main__":
# initialize distributed computing (MPI)
comm, process_id, worker_number = FedML_init()
# parse python script input parameters
parser = argparse.ArgumentParser()
args = add_args(parser)
logging.info(args)
# customize the process name
str_process_name = "FedAvg (distributed):" + str(process_id)
setproctitle.setproctitle(str_process_name)
# customize the log format
# logging.basicConfig(level=logging.INFO,
logging.basicConfig(level=logging.DEBUG,
format=str(
process_id) + ' - %(asctime)s %(filename)s[line:%(lineno)d] %(levelname)s %(message)s',
datefmt='%a, %d %b %Y %H:%M:%S')
hostname = socket.gethostname()
logging.info("#############process ID = " + str(process_id) +
", host name = " + hostname + "########" +
", process ID = " + str(os.getpid()) +
", process Name = " + str(psutil.Process(os.getpid())))
# initialize the wandb machine learning experimental tracking platform (https://www.wandb.com/).
if process_id == 0:
wandb.init(
# project="federated_nas",
project="fedml",
name="FedAVG(d)" + str(args.partition_method) + "r" + str(args.comm_round) + "-e" + str(
args.epochs) + "-lr" + str(
args.lr),
config=args
)
# Set the random seed. The np.random seed determines the dataset partition.
# The torch_manual_seed determines the initial weight.
# We fix these two, so that we can reproduce the result.
random.seed(0)
np.random.seed(0)
torch.manual_seed(0)
torch.cuda.manual_seed_all(0)
# Please check "GPU_MAPPING.md" to see how to define the topology
logging.info("process_id = %d, size = %d" % (process_id, worker_number))
device = mapping_processes_to_gpu_device_from_yaml_file(process_id, worker_number, args.gpu_mapping_file, args.gpu_mapping_key)
# load data
dataset = load_data(args, args.dataset)
[train_data_num, test_data_num, train_data_global, test_data_global,
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, class_num] = dataset
# create model.
# Note if the model is DNN (e.g., ResNet), the training will be very slow.
# In this case, please use our FedML distributed version (./fedml_experiments/distributed_fedavg)
model = create_model(args, model_name=args.model, output_dim=dataset[7])
try:
# start "federated averaging (FedAvg)"
FedML_FedAvg_distributed(process_id, worker_number, device, comm,
model, train_data_num, train_data_global, test_data_global,
train_data_local_num_dict, train_data_local_dict, test_data_local_dict, args)
except Exception as e:
print(e)
logging.info('traceback.format_exc():\n%s' % traceback.format_exc())
MPI.COMM_WORLD.Abort() | 0.441432 | 0.173113 |
"""End-to-end tests for federated trainer tasks."""
import collections
import os.path
from absl.testing import parameterized
import tensorflow as tf
import tensorflow_federated as tff
from optimization.cifar100 import federated_cifar100
from optimization.emnist import federated_emnist
from optimization.emnist_ae import federated_emnist_ae
from optimization.shakespeare import federated_shakespeare
from optimization.shared import fed_avg_schedule
from optimization.stackoverflow import federated_stackoverflow
from optimization.stackoverflow_lr import federated_stackoverflow_lr
def iterative_process_builder(model_fn, client_weight_fn=None):
return fed_avg_schedule.build_fed_avg_process(
model_fn=model_fn,
client_optimizer_fn=tf.keras.optimizers.SGD,
client_lr=0.1,
server_optimizer_fn=tf.keras.optimizers.SGD,
server_lr=1.0,
client_weight_fn=client_weight_fn)
class FederatedTasksTest(tf.test.TestCase, parameterized.TestCase):
@parameterized.named_parameters(
('cifar100', federated_cifar100.run_federated),
('emnist_cr', federated_emnist.run_federated),
('emnist_ae', federated_emnist_ae.run_federated),
('shakespeare', federated_shakespeare.run_federated),
('stackoverflow_nwp', federated_stackoverflow.run_federated),
('stackoverflow_lr', federated_stackoverflow_lr.run_federated),
)
def test_run_federated(self, run_federated_fn):
total_rounds = 1
shared_args = collections.OrderedDict(
client_epochs_per_round=1,
client_batch_size=10,
clients_per_round=1,
client_datasets_random_seed=1,
total_rounds=total_rounds,
iterative_process_builder=iterative_process_builder,
rounds_per_checkpoint=10,
rounds_per_eval=10)
root_output_dir = self.get_temp_dir()
exp_name = 'test_run_federated'
shared_args['root_output_dir'] = root_output_dir
shared_args['experiment_name'] = exp_name
run_federated_fn(**shared_args)
results_dir = os.path.join(root_output_dir, 'results', exp_name)
self.assertTrue(tf.io.gfile.exists(results_dir))
scalar_manager = tff.simulation.CSVMetricsManager(
os.path.join(results_dir, 'experiment.metrics.csv'))
fieldnames, metrics = scalar_manager.get_metrics()
self.assertIn(
'train/loss',
fieldnames,
msg='The output metrics should have a `train/loss` column if training '
'is successful.')
self.assertIn(
'eval/loss',
fieldnames,
msg='The output metrics should have a `train/loss` column if validation'
' metrics computation is successful.')
self.assertIn(
'test/loss',
fieldnames,
msg='The output metrics should have a `test/loss` column if test '
'metrics computation is successful.')
self.assertLen(
metrics,
total_rounds + 1,
msg='The number of rows in the metrics CSV should be the number of '
'training rounds + 1 (as there is an extra row for validation/test set'
'metrics after training has completed.')
if __name__ == '__main__':
tf.test.main() | optimization/main/federated_tasks_test.py | """End-to-end tests for federated trainer tasks."""
import collections
import os.path
from absl.testing import parameterized
import tensorflow as tf
import tensorflow_federated as tff
from optimization.cifar100 import federated_cifar100
from optimization.emnist import federated_emnist
from optimization.emnist_ae import federated_emnist_ae
from optimization.shakespeare import federated_shakespeare
from optimization.shared import fed_avg_schedule
from optimization.stackoverflow import federated_stackoverflow
from optimization.stackoverflow_lr import federated_stackoverflow_lr
def iterative_process_builder(model_fn, client_weight_fn=None):
return fed_avg_schedule.build_fed_avg_process(
model_fn=model_fn,
client_optimizer_fn=tf.keras.optimizers.SGD,
client_lr=0.1,
server_optimizer_fn=tf.keras.optimizers.SGD,
server_lr=1.0,
client_weight_fn=client_weight_fn)
class FederatedTasksTest(tf.test.TestCase, parameterized.TestCase):
@parameterized.named_parameters(
('cifar100', federated_cifar100.run_federated),
('emnist_cr', federated_emnist.run_federated),
('emnist_ae', federated_emnist_ae.run_federated),
('shakespeare', federated_shakespeare.run_federated),
('stackoverflow_nwp', federated_stackoverflow.run_federated),
('stackoverflow_lr', federated_stackoverflow_lr.run_federated),
)
def test_run_federated(self, run_federated_fn):
total_rounds = 1
shared_args = collections.OrderedDict(
client_epochs_per_round=1,
client_batch_size=10,
clients_per_round=1,
client_datasets_random_seed=1,
total_rounds=total_rounds,
iterative_process_builder=iterative_process_builder,
rounds_per_checkpoint=10,
rounds_per_eval=10)
root_output_dir = self.get_temp_dir()
exp_name = 'test_run_federated'
shared_args['root_output_dir'] = root_output_dir
shared_args['experiment_name'] = exp_name
run_federated_fn(**shared_args)
results_dir = os.path.join(root_output_dir, 'results', exp_name)
self.assertTrue(tf.io.gfile.exists(results_dir))
scalar_manager = tff.simulation.CSVMetricsManager(
os.path.join(results_dir, 'experiment.metrics.csv'))
fieldnames, metrics = scalar_manager.get_metrics()
self.assertIn(
'train/loss',
fieldnames,
msg='The output metrics should have a `train/loss` column if training '
'is successful.')
self.assertIn(
'eval/loss',
fieldnames,
msg='The output metrics should have a `train/loss` column if validation'
' metrics computation is successful.')
self.assertIn(
'test/loss',
fieldnames,
msg='The output metrics should have a `test/loss` column if test '
'metrics computation is successful.')
self.assertLen(
metrics,
total_rounds + 1,
msg='The number of rows in the metrics CSV should be the number of '
'training rounds + 1 (as there is an extra row for validation/test set'
'metrics after training has completed.')
if __name__ == '__main__':
tf.test.main() | 0.838944 | 0.402627 |
import re # noqa: F401
from xero_python.models import BaseModel
class EmployeeLeaveBalance(BaseModel):
"""NOTE: This class is auto generated by OpenAPI Generator.
Ref: https://openapi-generator.tech
Do not edit the class manually.
"""
"""
Attributes:
openapi_types (dict): The key is attribute name
and the value is attribute type.
attribute_map (dict): The key is attribute name
and the value is json key in definition.
"""
openapi_types = {
"name": "str",
"leave_type_id": "str",
"balance": "float",
"type_of_units": "str",
}
attribute_map = {
"name": "name",
"leave_type_id": "leaveTypeID",
"balance": "balance",
"type_of_units": "typeOfUnits",
}
def __init__(
self, name=None, leave_type_id=None, balance=None, type_of_units=None
): # noqa: E501
"""EmployeeLeaveBalance - a model defined in OpenAPI""" # noqa: E501
self._name = None
self._leave_type_id = None
self._balance = None
self._type_of_units = None
self.discriminator = None
if name is not None:
self.name = name
if leave_type_id is not None:
self.leave_type_id = leave_type_id
if balance is not None:
self.balance = balance
if type_of_units is not None:
self.type_of_units = type_of_units
@property
def name(self):
"""Gets the name of this EmployeeLeaveBalance. # noqa: E501
Name of the leave type. # noqa: E501
:return: The name of this EmployeeLeaveBalance. # noqa: E501
:rtype: str
"""
return self._name
@name.setter
def name(self, name):
"""Sets the name of this EmployeeLeaveBalance.
Name of the leave type. # noqa: E501
:param name: The name of this EmployeeLeaveBalance. # noqa: E501
:type: str
"""
self._name = name
@property
def leave_type_id(self):
"""Gets the leave_type_id of this EmployeeLeaveBalance. # noqa: E501
The Xero identifier for leave type # noqa: E501
:return: The leave_type_id of this EmployeeLeaveBalance. # noqa: E501
:rtype: str
"""
return self._leave_type_id
@leave_type_id.setter
def leave_type_id(self, leave_type_id):
"""Sets the leave_type_id of this EmployeeLeaveBalance.
The Xero identifier for leave type # noqa: E501
:param leave_type_id: The leave_type_id of this EmployeeLeaveBalance. # noqa: E501
:type: str
"""
self._leave_type_id = leave_type_id
@property
def balance(self):
"""Gets the balance of this EmployeeLeaveBalance. # noqa: E501
The employees current balance for the corresponding leave type. # noqa: E501
:return: The balance of this EmployeeLeaveBalance. # noqa: E501
:rtype: float
"""
return self._balance
@balance.setter
def balance(self, balance):
"""Sets the balance of this EmployeeLeaveBalance.
The employees current balance for the corresponding leave type. # noqa: E501
:param balance: The balance of this EmployeeLeaveBalance. # noqa: E501
:type: float
"""
self._balance = balance
@property
def type_of_units(self):
"""Gets the type_of_units of this EmployeeLeaveBalance. # noqa: E501
The type of the units of the leave. # noqa: E501
:return: The type_of_units of this EmployeeLeaveBalance. # noqa: E501
:rtype: str
"""
return self._type_of_units
@type_of_units.setter
def type_of_units(self, type_of_units):
"""Sets the type_of_units of this EmployeeLeaveBalance.
The type of the units of the leave. # noqa: E501
:param type_of_units: The type_of_units of this EmployeeLeaveBalance. # noqa: E501
:type: str
"""
self._type_of_units = type_of_units | xero_python/payrolluk/models/employee_leave_balance.py | import re # noqa: F401
from xero_python.models import BaseModel
class EmployeeLeaveBalance(BaseModel):
"""NOTE: This class is auto generated by OpenAPI Generator.
Ref: https://openapi-generator.tech
Do not edit the class manually.
"""
"""
Attributes:
openapi_types (dict): The key is attribute name
and the value is attribute type.
attribute_map (dict): The key is attribute name
and the value is json key in definition.
"""
openapi_types = {
"name": "str",
"leave_type_id": "str",
"balance": "float",
"type_of_units": "str",
}
attribute_map = {
"name": "name",
"leave_type_id": "leaveTypeID",
"balance": "balance",
"type_of_units": "typeOfUnits",
}
def __init__(
self, name=None, leave_type_id=None, balance=None, type_of_units=None
): # noqa: E501
"""EmployeeLeaveBalance - a model defined in OpenAPI""" # noqa: E501
self._name = None
self._leave_type_id = None
self._balance = None
self._type_of_units = None
self.discriminator = None
if name is not None:
self.name = name
if leave_type_id is not None:
self.leave_type_id = leave_type_id
if balance is not None:
self.balance = balance
if type_of_units is not None:
self.type_of_units = type_of_units
@property
def name(self):
"""Gets the name of this EmployeeLeaveBalance. # noqa: E501
Name of the leave type. # noqa: E501
:return: The name of this EmployeeLeaveBalance. # noqa: E501
:rtype: str
"""
return self._name
@name.setter
def name(self, name):
"""Sets the name of this EmployeeLeaveBalance.
Name of the leave type. # noqa: E501
:param name: The name of this EmployeeLeaveBalance. # noqa: E501
:type: str
"""
self._name = name
@property
def leave_type_id(self):
"""Gets the leave_type_id of this EmployeeLeaveBalance. # noqa: E501
The Xero identifier for leave type # noqa: E501
:return: The leave_type_id of this EmployeeLeaveBalance. # noqa: E501
:rtype: str
"""
return self._leave_type_id
@leave_type_id.setter
def leave_type_id(self, leave_type_id):
"""Sets the leave_type_id of this EmployeeLeaveBalance.
The Xero identifier for leave type # noqa: E501
:param leave_type_id: The leave_type_id of this EmployeeLeaveBalance. # noqa: E501
:type: str
"""
self._leave_type_id = leave_type_id
@property
def balance(self):
"""Gets the balance of this EmployeeLeaveBalance. # noqa: E501
The employees current balance for the corresponding leave type. # noqa: E501
:return: The balance of this EmployeeLeaveBalance. # noqa: E501
:rtype: float
"""
return self._balance
@balance.setter
def balance(self, balance):
"""Sets the balance of this EmployeeLeaveBalance.
The employees current balance for the corresponding leave type. # noqa: E501
:param balance: The balance of this EmployeeLeaveBalance. # noqa: E501
:type: float
"""
self._balance = balance
@property
def type_of_units(self):
"""Gets the type_of_units of this EmployeeLeaveBalance. # noqa: E501
The type of the units of the leave. # noqa: E501
:return: The type_of_units of this EmployeeLeaveBalance. # noqa: E501
:rtype: str
"""
return self._type_of_units
@type_of_units.setter
def type_of_units(self, type_of_units):
"""Sets the type_of_units of this EmployeeLeaveBalance.
The type of the units of the leave. # noqa: E501
:param type_of_units: The type_of_units of this EmployeeLeaveBalance. # noqa: E501
:type: str
"""
self._type_of_units = type_of_units | 0.784773 | 0.140631 |
import numpy as np
import scipy.linalg as spla
from scipy.spatial.distance import cdist
def chol2inv(chol):
return spla.cho_solve((chol, False), np.eye(chol.shape[ 0 ]))
def matrixInverse(M):
return chol2inv(spla.cholesky(M, lower=False))
def compute_kernel(lls, lsf, x, z):
ls = np.exp(lls)
sf = np.exp(lsf)
if x.ndim == 1:
x= x[ None, : ]
if z.ndim == 1:
z= z[ None, : ]
r2 = cdist(x, z, 'seuclidean', V = ls)**2.0
k = sf * np.exp(-0.5*r2)
return k
def compute_psi1(lls, lsf, xmean, xvar, z):
if xmean.ndim == 1:
xmean = xmean[ None, : ]
ls = np.exp(lls)
sf = np.exp(lsf)
lspxvar = ls + xvar
constterm1 = ls / lspxvar
constterm2 = np.prod(np.sqrt(constterm1))
r2_psi1 = cdist(xmean, z, 'seuclidean', V = lspxvar)**2.0
psi1 = sf*constterm2*np.exp(-0.5*r2_psi1)
return psi1
def compute_psi2(lls, lsf, xmean, xvar, z):
ls = np.exp(lls)
sf = np.exp(lsf)
lsp2xvar = ls + 2.0 * xvar
constterm1 = ls / lsp2xvar
constterm2 = np.prod(np.sqrt(constterm1))
n_psi = z.shape[ 0 ]
v_ones_n_psi = np.ones(n_psi)
v_ones_dim = np.ones(z.shape[ 1 ])
D = ls
Dnew = ls / 2.0
Btilde = 1.0 / (Dnew + xvar)
Vtilde = Btilde - 1.0 / Dnew
Qtilde = 1.0 / D + 0.25 * Vtilde
T1 = -0.5 * np.outer(np.dot((z**2) * np.outer(v_ones_n_psi, Qtilde), v_ones_dim), v_ones_n_psi)
T2 = +0.5 * np.outer(np.dot(z, xmean * Btilde), v_ones_n_psi)
T3 = -0.25 * np.dot(z * np.outer(v_ones_n_psi, Vtilde), z.T)
T4 = -0.5 * np.sum((xmean**2) * Btilde)
M = T1 + T1.T + T2 + T2.T + T3 + T4
psi2 = sf**2.0 * constterm2 * np.exp(M)
return psi2
def d_trace_MKzz_dhypers(lls, lsf, z, M, Kzz):
dKzz_dlsf = Kzz
ls = np.exp(lls)
# This is extracted from the R-code of Scalable EP for GP Classification by DHL and JMHL
gr_lsf = np.sum(M * dKzz_dlsf)
# This uses the vact that the distance is v^21^T - vv^T + 1v^2^T, where v is a vector with the l-dimension
# of the inducing points.
Ml = 0.5 * M * Kzz
Xl = z * np.outer(np.ones(z.shape[ 0 ]), 1.0 / np.sqrt(ls))
gr_lls = np.dot(np.ones(Ml.shape[ 0 ]), np.dot(Ml.T, Xl**2)) + np.dot(np.ones(Ml.shape[ 0 ]), np.dot(Ml, Xl**2)) \
- 2.0 * np.dot(np.ones(Xl.shape[ 0 ]), (Xl * np.dot(Ml, Xl)))
Xbar = z * np.outer(np.ones(z.shape[ 0 ]), 1.0 / ls)
Mbar1 = - M.T * Kzz
Mbar2 = - M * Kzz
gr_z = (Xbar * np.outer(np.dot(np.ones(Mbar1.shape[ 0 ]) , Mbar1), np.ones(Xbar.shape[ 1 ])) - np.dot(Mbar1, Xbar)) +\
(Xbar * np.outer(np.dot(np.ones(Mbar2.shape[ 0 ]) , Mbar2), np.ones(Xbar.shape[ 1 ])) - np.dot(Mbar2, Xbar))
# The cost of this function is dominated by five matrix multiplications with cost M^2 * D each where D is
# the dimensionality of the data!!!
return gr_lsf, gr_lls, gr_z | numpy/deepgp_approxep/EQ_kernel.py | import numpy as np
import scipy.linalg as spla
from scipy.spatial.distance import cdist
def chol2inv(chol):
return spla.cho_solve((chol, False), np.eye(chol.shape[ 0 ]))
def matrixInverse(M):
return chol2inv(spla.cholesky(M, lower=False))
def compute_kernel(lls, lsf, x, z):
ls = np.exp(lls)
sf = np.exp(lsf)
if x.ndim == 1:
x= x[ None, : ]
if z.ndim == 1:
z= z[ None, : ]
r2 = cdist(x, z, 'seuclidean', V = ls)**2.0
k = sf * np.exp(-0.5*r2)
return k
def compute_psi1(lls, lsf, xmean, xvar, z):
if xmean.ndim == 1:
xmean = xmean[ None, : ]
ls = np.exp(lls)
sf = np.exp(lsf)
lspxvar = ls + xvar
constterm1 = ls / lspxvar
constterm2 = np.prod(np.sqrt(constterm1))
r2_psi1 = cdist(xmean, z, 'seuclidean', V = lspxvar)**2.0
psi1 = sf*constterm2*np.exp(-0.5*r2_psi1)
return psi1
def compute_psi2(lls, lsf, xmean, xvar, z):
ls = np.exp(lls)
sf = np.exp(lsf)
lsp2xvar = ls + 2.0 * xvar
constterm1 = ls / lsp2xvar
constterm2 = np.prod(np.sqrt(constterm1))
n_psi = z.shape[ 0 ]
v_ones_n_psi = np.ones(n_psi)
v_ones_dim = np.ones(z.shape[ 1 ])
D = ls
Dnew = ls / 2.0
Btilde = 1.0 / (Dnew + xvar)
Vtilde = Btilde - 1.0 / Dnew
Qtilde = 1.0 / D + 0.25 * Vtilde
T1 = -0.5 * np.outer(np.dot((z**2) * np.outer(v_ones_n_psi, Qtilde), v_ones_dim), v_ones_n_psi)
T2 = +0.5 * np.outer(np.dot(z, xmean * Btilde), v_ones_n_psi)
T3 = -0.25 * np.dot(z * np.outer(v_ones_n_psi, Vtilde), z.T)
T4 = -0.5 * np.sum((xmean**2) * Btilde)
M = T1 + T1.T + T2 + T2.T + T3 + T4
psi2 = sf**2.0 * constterm2 * np.exp(M)
return psi2
def d_trace_MKzz_dhypers(lls, lsf, z, M, Kzz):
dKzz_dlsf = Kzz
ls = np.exp(lls)
# This is extracted from the R-code of Scalable EP for GP Classification by DHL and JMHL
gr_lsf = np.sum(M * dKzz_dlsf)
# This uses the vact that the distance is v^21^T - vv^T + 1v^2^T, where v is a vector with the l-dimension
# of the inducing points.
Ml = 0.5 * M * Kzz
Xl = z * np.outer(np.ones(z.shape[ 0 ]), 1.0 / np.sqrt(ls))
gr_lls = np.dot(np.ones(Ml.shape[ 0 ]), np.dot(Ml.T, Xl**2)) + np.dot(np.ones(Ml.shape[ 0 ]), np.dot(Ml, Xl**2)) \
- 2.0 * np.dot(np.ones(Xl.shape[ 0 ]), (Xl * np.dot(Ml, Xl)))
Xbar = z * np.outer(np.ones(z.shape[ 0 ]), 1.0 / ls)
Mbar1 = - M.T * Kzz
Mbar2 = - M * Kzz
gr_z = (Xbar * np.outer(np.dot(np.ones(Mbar1.shape[ 0 ]) , Mbar1), np.ones(Xbar.shape[ 1 ])) - np.dot(Mbar1, Xbar)) +\
(Xbar * np.outer(np.dot(np.ones(Mbar2.shape[ 0 ]) , Mbar2), np.ones(Xbar.shape[ 1 ])) - np.dot(Mbar2, Xbar))
# The cost of this function is dominated by five matrix multiplications with cost M^2 * D each where D is
# the dimensionality of the data!!!
return gr_lsf, gr_lls, gr_z | 0.579638 | 0.640833 |
# pylint: disable-msg=C6310
"""Channel Tic Tac Toe
This module demonstrates the App Engine Channel API by implementing a
simple tic-tac-toe game.
"""
import datetime
import logging
import os
import random
import re
import uuid
import sys
from django.utils import simplejson
from google.appengine.api import channel
from google.appengine.ext import db
from google.appengine.ext import webapp
from google.appengine.ext.webapp import template
from google.appengine.ext.webapp.util import run_wsgi_app
class Game(db.Model):
"""All the data we store for a game"""
userX = db.StringProperty()
userO = db.StringProperty()
board = db.StringProperty()
moveX = db.BooleanProperty()
winner = db.StringProperty()
winning_board = db.StringProperty()
class Wins():
x_win_patterns = ['XXX......',
'...XXX...',
'......XXX',
'X..X..X..',
'.X..X..X.',
'..X..X..X',
'X...X...X',
'..X.X.X..']
o_win_patterns = map(lambda s: s.replace('X','O'), x_win_patterns)
x_wins = map(lambda s: re.compile(s), x_win_patterns)
o_wins = map(lambda s: re.compile(s), o_win_patterns)
class GameUpdater():
game = None
def __init__(self, game):
self.game = game
def get_game_message(self):
gameUpdate = {
'board': self.game.board,
'userX': self.game.userX,
'userO': '' if not self.game.userO else self.game.userO,
'moveX': self.game.moveX,
'winner': self.game.winner,
'winningBoard': self.game.winning_board
}
return simplejson.dumps(gameUpdate)
def send_update(self):
message = self.get_game_message()
channel.send_message(self.game.userX + self.game.key().id_or_name(), message)
if self.game.userO:
channel.send_message(self.game.userO + self.game.key().id_or_name(), message)
def check_win(self):
if self.game.moveX:
# O just moved, check for O wins
wins = Wins().o_wins
potential_winner = self.game.userO
else:
# X just moved, check for X wins
wins = Wins().x_wins
potential_winner = self.game.userX
for win in wins:
if win.match(self.game.board):
self.game.winner = potential_winner
self.game.winning_board = win.pattern
return
def make_move(self, position, user):
if position >= 0 and user == self.game.userX or user == self.game.userO:
if self.game.moveX == (user == self.game.userX):
boardList = list(self.game.board)
if (boardList[position] == ' '):
boardList[position] = 'X' if self.game.moveX else 'O'
self.game.board = "".join(boardList)
self.game.moveX = not self.game.moveX
self.check_win()
self.game.put()
self.send_update()
return
class GameFromRequest():
game = None;
user = None;
def __init__(self, request):
self.user = request.get('u')
game_key = request.get('g')
if game_key:
self.game = Game.get_by_key_name(game_key)
def get_game_data(self):
return ( self.game, self.user )
class MovePage(webapp.RequestHandler):
def post(self):
(game, user) = GameFromRequest(self.request).get_game_data()
if game and user:
id = int(self.request.get('i'))
GameUpdater(game).make_move(id, user)
class OpenedPage(webapp.RequestHandler):
def post(self):
(game, user) = GameFromRequest(self.request).get_game_data()
GameUpdater(game).send_update()
class MainPage(webapp.RequestHandler):
"""The main UI page, renders the 'index.html' template."""
def get(self):
"""Renders the main page. When this page is shown, we create a new
channel to push asynchronous updates to the client."""
game_key = self.request.get('g')
game = None
user = None
if game_key:
game = Game.get_by_key_name(game_key)
if game:
user = game.userO
if not user:
user = uuid.uuid4().hex
game.userO = user
game.put()
if not game:
game_key = <KEY>
user = uuid.uuid4().hex
game = Game(key_name = game_key,
moveX = True,
userX = user,
complete = False,
board = ' ')
game.put()
game_link = 'http://localhost:8080/?g=' + game_key
if game:
token = channel.create_channel(user + game_key)
values = {'token': token,
'me': user,
'game_key': game_key,
'game_link': game_link,
'initial_message': GameUpdater(game).get_game_message()
}
self.response.out.write(simplejson.dumps(values))
else:
self.response.out.write(simplejson.dumps({'error': 'No such game'}))
application = webapp.WSGIApplication([
('/', MainPage),
('/opened', OpenedPage),
('/move', MovePage)], debug=True)
def main():
run_wsgi_app(application)
if __name__ == "__main__":
main() | apps/samples/appengine-channelapi/appengine/chatactoe.py |
# pylint: disable-msg=C6310
"""Channel Tic Tac Toe
This module demonstrates the App Engine Channel API by implementing a
simple tic-tac-toe game.
"""
import datetime
import logging
import os
import random
import re
import uuid
import sys
from django.utils import simplejson
from google.appengine.api import channel
from google.appengine.ext import db
from google.appengine.ext import webapp
from google.appengine.ext.webapp import template
from google.appengine.ext.webapp.util import run_wsgi_app
class Game(db.Model):
"""All the data we store for a game"""
userX = db.StringProperty()
userO = db.StringProperty()
board = db.StringProperty()
moveX = db.BooleanProperty()
winner = db.StringProperty()
winning_board = db.StringProperty()
class Wins():
x_win_patterns = ['XXX......',
'...XXX...',
'......XXX',
'X..X..X..',
'.X..X..X.',
'..X..X..X',
'X...X...X',
'..X.X.X..']
o_win_patterns = map(lambda s: s.replace('X','O'), x_win_patterns)
x_wins = map(lambda s: re.compile(s), x_win_patterns)
o_wins = map(lambda s: re.compile(s), o_win_patterns)
class GameUpdater():
game = None
def __init__(self, game):
self.game = game
def get_game_message(self):
gameUpdate = {
'board': self.game.board,
'userX': self.game.userX,
'userO': '' if not self.game.userO else self.game.userO,
'moveX': self.game.moveX,
'winner': self.game.winner,
'winningBoard': self.game.winning_board
}
return simplejson.dumps(gameUpdate)
def send_update(self):
message = self.get_game_message()
channel.send_message(self.game.userX + self.game.key().id_or_name(), message)
if self.game.userO:
channel.send_message(self.game.userO + self.game.key().id_or_name(), message)
def check_win(self):
if self.game.moveX:
# O just moved, check for O wins
wins = Wins().o_wins
potential_winner = self.game.userO
else:
# X just moved, check for X wins
wins = Wins().x_wins
potential_winner = self.game.userX
for win in wins:
if win.match(self.game.board):
self.game.winner = potential_winner
self.game.winning_board = win.pattern
return
def make_move(self, position, user):
if position >= 0 and user == self.game.userX or user == self.game.userO:
if self.game.moveX == (user == self.game.userX):
boardList = list(self.game.board)
if (boardList[position] == ' '):
boardList[position] = 'X' if self.game.moveX else 'O'
self.game.board = "".join(boardList)
self.game.moveX = not self.game.moveX
self.check_win()
self.game.put()
self.send_update()
return
class GameFromRequest():
game = None;
user = None;
def __init__(self, request):
self.user = request.get('u')
game_key = request.get('g')
if game_key:
self.game = Game.get_by_key_name(game_key)
def get_game_data(self):
return ( self.game, self.user )
class MovePage(webapp.RequestHandler):
def post(self):
(game, user) = GameFromRequest(self.request).get_game_data()
if game and user:
id = int(self.request.get('i'))
GameUpdater(game).make_move(id, user)
class OpenedPage(webapp.RequestHandler):
def post(self):
(game, user) = GameFromRequest(self.request).get_game_data()
GameUpdater(game).send_update()
class MainPage(webapp.RequestHandler):
"""The main UI page, renders the 'index.html' template."""
def get(self):
"""Renders the main page. When this page is shown, we create a new
channel to push asynchronous updates to the client."""
game_key = self.request.get('g')
game = None
user = None
if game_key:
game = Game.get_by_key_name(game_key)
if game:
user = game.userO
if not user:
user = uuid.uuid4().hex
game.userO = user
game.put()
if not game:
game_key = <KEY>
user = uuid.uuid4().hex
game = Game(key_name = game_key,
moveX = True,
userX = user,
complete = False,
board = ' ')
game.put()
game_link = 'http://localhost:8080/?g=' + game_key
if game:
token = channel.create_channel(user + game_key)
values = {'token': token,
'me': user,
'game_key': game_key,
'game_link': game_link,
'initial_message': GameUpdater(game).get_game_message()
}
self.response.out.write(simplejson.dumps(values))
else:
self.response.out.write(simplejson.dumps({'error': 'No such game'}))
application = webapp.WSGIApplication([
('/', MainPage),
('/opened', OpenedPage),
('/move', MovePage)], debug=True)
def main():
run_wsgi_app(application)
if __name__ == "__main__":
main() | 0.480722 | 0.081703 |
from jumpscale import j
from zerorobot.template.base import TemplateBase
from zerorobot.template.state import StateCheckError
from zerorobot.service_collection import ServiceNotFoundError
ZERODB_TEMPLATE_UID = 'github.com/threefoldtech/0-templates/zerodb/0.0.1'
NODE_CLIENT = 'local'
class Vdisk(TemplateBase):
version = '0.0.1'
template_name = "vdisk"
def __init__(self, name=None, guid=None, data=None):
super().__init__(name=name, guid=guid, data=data)
self.add_delete_callback(self.uninstall)
self.recurring_action('_monitor', 10)
if not self.data.get('password'):
self.data['password'] = <PASSWORD>(32)
def validate(self):
try:
# ensure that a node service exists
node = self.api.services.get(template_account='threefoldtech', template_name='node')
node.state.check('actions', 'install', 'ok')
except:
raise RuntimeError("not node service found, can't install the namespace")
for param in ['diskType', 'size', 'label']:
if not self.data.get(param):
raise ValueError("parameter '%s' not valid: %s" % (param, str(self.data[param])))
@property
def _node_sal(self):
"""
connection to the node
"""
return j.clients.zos.get(NODE_CLIENT)
@property
def _zerodb(self):
return self.api.services.get(template_uid=ZERODB_TEMPLATE_UID, name=self.data['zerodb'])
def _monitor(self):
self.state.check('actions', 'install', 'ok')
try:
self._zerodb.state.check('status', 'running', 'ok')
self.state.set('status', 'running', 'ok')
except StateCheckError:
data = {
'attributes': {},
'resource': self.guid,
'text': 'Failed to start vdisk {}'.format(self.name),
'environment': 'Production',
'severity': 'critical',
'event': 'Hardware',
'tags': [],
'service': ['vdisk']
}
alertas = self.api.services.find(template_uid='github.com/threefoldtech/0-templates/alerta/0.0.1')
for alerta in alertas:
alerta.schedule_action('send_alert', args={'data': data})
self.state.delete('status', 'running')
def install(self):
try:
# no op is already installed
self.state.check('actions', 'install', 'ok')
return
except StateCheckError:
pass
node = self.api.services.get(template_account='threefoldtech', template_name='node')
kwargs = {
'disktype': self.data['diskType'],
'mode': 'user',
'password': <PASSWORD>['password'],
'public': False,
'ns_size': int(self.data['size']),
}
# use the method on the node service to create the zdb and the namespace.
# this action hold the logic of the capacity planning for the zdb and namespaces
self.data['zerodb'], self.data['nsName'] = node.schedule_action('create_zdb_namespace', kwargs).wait(die=True).result
zerodb_data = self._zerodb.data.copy()
zerodb_data['name'] = self._zerodb.name
zerodb_sal = self._node_sal.primitives.from_dict('zerodb', zerodb_data)
disk = self._node_sal.primitives.create_disk(self.data['nsName'],
zerodb_sal,
mountpoint=self.data['mountPoint'] or None,
filesystem=self.data['filesystem'] or None,
size=int(self.data['size']),
label=self.data['label'])
disk.deploy()
self.state.set('actions', 'install', 'ok')
self.state.set('status', 'running', 'ok')
def info(self):
self.state.check('actions', 'install', 'ok')
return self._zerodb.schedule_action('namespace_info', args={'name': self.data['nsName']}).wait(die=True).result
def url(self):
self.state.check('actions', 'install', 'ok')
return self._zerodb.schedule_action('namespace_url', args={'name': self.data['nsName']}).wait(die=True).result
def private_url(self):
self.state.check('actions', 'install', 'ok')
return self._zerodb.schedule_action('namespace_private_url', args={'name': self.data['nsName']}).wait(die=True).result
def uninstall(self):
self._zerodb.schedule_action('namespace_delete', args={'name': self.data['nsName']}).wait(die=True)
self.state.delete('actions', 'install')
self.state.delete('status', 'running') | templates/vdisk/vdisk.py | from jumpscale import j
from zerorobot.template.base import TemplateBase
from zerorobot.template.state import StateCheckError
from zerorobot.service_collection import ServiceNotFoundError
ZERODB_TEMPLATE_UID = 'github.com/threefoldtech/0-templates/zerodb/0.0.1'
NODE_CLIENT = 'local'
class Vdisk(TemplateBase):
version = '0.0.1'
template_name = "vdisk"
def __init__(self, name=None, guid=None, data=None):
super().__init__(name=name, guid=guid, data=data)
self.add_delete_callback(self.uninstall)
self.recurring_action('_monitor', 10)
if not self.data.get('password'):
self.data['password'] = <PASSWORD>(32)
def validate(self):
try:
# ensure that a node service exists
node = self.api.services.get(template_account='threefoldtech', template_name='node')
node.state.check('actions', 'install', 'ok')
except:
raise RuntimeError("not node service found, can't install the namespace")
for param in ['diskType', 'size', 'label']:
if not self.data.get(param):
raise ValueError("parameter '%s' not valid: %s" % (param, str(self.data[param])))
@property
def _node_sal(self):
"""
connection to the node
"""
return j.clients.zos.get(NODE_CLIENT)
@property
def _zerodb(self):
return self.api.services.get(template_uid=ZERODB_TEMPLATE_UID, name=self.data['zerodb'])
def _monitor(self):
self.state.check('actions', 'install', 'ok')
try:
self._zerodb.state.check('status', 'running', 'ok')
self.state.set('status', 'running', 'ok')
except StateCheckError:
data = {
'attributes': {},
'resource': self.guid,
'text': 'Failed to start vdisk {}'.format(self.name),
'environment': 'Production',
'severity': 'critical',
'event': 'Hardware',
'tags': [],
'service': ['vdisk']
}
alertas = self.api.services.find(template_uid='github.com/threefoldtech/0-templates/alerta/0.0.1')
for alerta in alertas:
alerta.schedule_action('send_alert', args={'data': data})
self.state.delete('status', 'running')
def install(self):
try:
# no op is already installed
self.state.check('actions', 'install', 'ok')
return
except StateCheckError:
pass
node = self.api.services.get(template_account='threefoldtech', template_name='node')
kwargs = {
'disktype': self.data['diskType'],
'mode': 'user',
'password': <PASSWORD>['password'],
'public': False,
'ns_size': int(self.data['size']),
}
# use the method on the node service to create the zdb and the namespace.
# this action hold the logic of the capacity planning for the zdb and namespaces
self.data['zerodb'], self.data['nsName'] = node.schedule_action('create_zdb_namespace', kwargs).wait(die=True).result
zerodb_data = self._zerodb.data.copy()
zerodb_data['name'] = self._zerodb.name
zerodb_sal = self._node_sal.primitives.from_dict('zerodb', zerodb_data)
disk = self._node_sal.primitives.create_disk(self.data['nsName'],
zerodb_sal,
mountpoint=self.data['mountPoint'] or None,
filesystem=self.data['filesystem'] or None,
size=int(self.data['size']),
label=self.data['label'])
disk.deploy()
self.state.set('actions', 'install', 'ok')
self.state.set('status', 'running', 'ok')
def info(self):
self.state.check('actions', 'install', 'ok')
return self._zerodb.schedule_action('namespace_info', args={'name': self.data['nsName']}).wait(die=True).result
def url(self):
self.state.check('actions', 'install', 'ok')
return self._zerodb.schedule_action('namespace_url', args={'name': self.data['nsName']}).wait(die=True).result
def private_url(self):
self.state.check('actions', 'install', 'ok')
return self._zerodb.schedule_action('namespace_private_url', args={'name': self.data['nsName']}).wait(die=True).result
def uninstall(self):
self._zerodb.schedule_action('namespace_delete', args={'name': self.data['nsName']}).wait(die=True)
self.state.delete('actions', 'install')
self.state.delete('status', 'running') | 0.591015 | 0.138666 |
import logging
SUPPORTED_SCALING_FACTORS = [(7, 8), (3, 4), (5, 8), (1, 2), (3, 8), (1, 4), (1, 8)]
_LOGGER = logging.getLogger(__name__)
def scale_jpeg_camera_image(cam_image, width, height):
"""Scale a camera image as close as possible to one of the supported scaling factors."""
turbo_jpeg = TurboJPEGSingleton.instance()
if not turbo_jpeg:
return cam_image.content
(current_width, current_height, _, _) = turbo_jpeg.decode_header(cam_image.content)
if current_width <= width or current_height <= height:
return cam_image.content
ratio = width / current_width
scaling_factor = SUPPORTED_SCALING_FACTORS[-1]
for supported_sf in SUPPORTED_SCALING_FACTORS:
if ratio >= (supported_sf[0] / supported_sf[1]):
scaling_factor = supported_sf
break
return turbo_jpeg.scale_with_quality(
cam_image.content,
scaling_factor=scaling_factor,
quality=75,
)
class TurboJPEGSingleton:
"""
Load TurboJPEG only once.
Ensures we do not log load failures each snapshot
since camera image fetches happen every few
seconds.
"""
__instance = None
@staticmethod
def instance():
"""Singleton for TurboJPEG."""
if TurboJPEGSingleton.__instance is None:
TurboJPEGSingleton()
return TurboJPEGSingleton.__instance
def __init__(self):
"""Try to create TurboJPEG only once."""
try:
# TurboJPEG checks for libturbojpeg
# when its created, but it imports
# numpy which may or may not work so
# we have to guard the import here.
from turbojpeg import TurboJPEG # pylint: disable=import-outside-toplevel
TurboJPEGSingleton.__instance = TurboJPEG()
except Exception: # pylint: disable=broad-except
_LOGGER.exception(
"Error loading libturbojpeg; Cameras may impact HomeKit performance"
)
TurboJPEGSingleton.__instance = False | homeassistant/components/homekit/img_util.py |
import logging
SUPPORTED_SCALING_FACTORS = [(7, 8), (3, 4), (5, 8), (1, 2), (3, 8), (1, 4), (1, 8)]
_LOGGER = logging.getLogger(__name__)
def scale_jpeg_camera_image(cam_image, width, height):
"""Scale a camera image as close as possible to one of the supported scaling factors."""
turbo_jpeg = TurboJPEGSingleton.instance()
if not turbo_jpeg:
return cam_image.content
(current_width, current_height, _, _) = turbo_jpeg.decode_header(cam_image.content)
if current_width <= width or current_height <= height:
return cam_image.content
ratio = width / current_width
scaling_factor = SUPPORTED_SCALING_FACTORS[-1]
for supported_sf in SUPPORTED_SCALING_FACTORS:
if ratio >= (supported_sf[0] / supported_sf[1]):
scaling_factor = supported_sf
break
return turbo_jpeg.scale_with_quality(
cam_image.content,
scaling_factor=scaling_factor,
quality=75,
)
class TurboJPEGSingleton:
"""
Load TurboJPEG only once.
Ensures we do not log load failures each snapshot
since camera image fetches happen every few
seconds.
"""
__instance = None
@staticmethod
def instance():
"""Singleton for TurboJPEG."""
if TurboJPEGSingleton.__instance is None:
TurboJPEGSingleton()
return TurboJPEGSingleton.__instance
def __init__(self):
"""Try to create TurboJPEG only once."""
try:
# TurboJPEG checks for libturbojpeg
# when its created, but it imports
# numpy which may or may not work so
# we have to guard the import here.
from turbojpeg import TurboJPEG # pylint: disable=import-outside-toplevel
TurboJPEGSingleton.__instance = TurboJPEG()
except Exception: # pylint: disable=broad-except
_LOGGER.exception(
"Error loading libturbojpeg; Cameras may impact HomeKit performance"
)
TurboJPEGSingleton.__instance = False | 0.803135 | 0.201401 |
from hangulize import *
class Dutch(Language):
"""For transcribing Dutch."""
__iso639__ = {1: 'nl', 2: 'dut', 3: 'nld'}
__tmp__ = '%,;&'
vowels = 'aeEioOuUyQ'
cs = 'b', 'B', 'c', 'C', 'd', 'D', 'f', 'F', 'g', 'G', 'h', 'j', 'J', \
'k', 'K', 'l', 'm', 'n', 'N', 'p', 'P', 'q', 'r', 's', 't', 'T', \
'v', 'w', 'x', 'X', 'z', '%' # consonants
son = 'lmnNrw' # sonorants
short = 'aeEiouU' # short vowels
notation = Notation([
(u'’', '\''),
(' aan ', '/aan/'),
('^aan ', 'aan/'),
(' bij ', '/bij/'),
('^bij ', 'bij/'),
(' boven ', '/boven/'),
('^boven ', 'boven/'),
(' en ', '/en/'),
('^en ', 'en/'),
(' in ', '/in/'),
('^in ', 'in/'),
(' op ', '/op/'),
('^op ', 'op/'),
(' over ', '/over/'),
('^over ', 'over/'),
(' of ', '/of/'),
('^de ', 'de/'),
('^den ', 'den/'),
('^der ', 'der/'),
('^des ', 'des/'),
('^di ', 'di/'),
('^het ', 'het/'),
('^onder ', 'onder/'),
('^sint ', 'sint/'),
('^te ', 'te/'),
('^ten ', 'ten/'),
('^ter ', 'ter/'),
('^thoe ', 'thoe/'),
('^tot ', 'tot/'),
('^uit ', 'uit/'),
('^uijt ', 'uijt/'),
('^van ', 'van/'),
('^ver ', 'ver/'),
('^voor ', 'voor/'),
('-', '/'),
('^\'s ', 's/'),
('^\'t ', 'Qt,/'),
('^\'t', 'Qt,'),
('hoek van/holland', 'hoek/van/holland'),
('hof van/twente', 'hof/van/twente'),
('ronde venen', 'ronde/venen'),
('^midden ', 'midden/'),
('^neder ', 'neder/'),
('^nieuw ', 'nieuw/'),
('^nieuwe ', 'nieuwe/'),
('^noord ', 'noord/'),
('^oost ', 'oost/'),
('^west ', 'west/'),
('^zuid ', 'zuid/'),
(u'aimé', u'emé'),
(u'curaçao', 'curaso'),
('curacao', 'curaso'),
(u'française', 'frangsEzY'),
('francaise', 'frangsEzY'),
(u'français', 'frangsE'),
('francais', 'frangsE'),
(u'françoise', 'frangsoeazY'),
('francoise', 'frangsoeazY'),
(u'françois', 'frangsoea'),
('francois', 'frangsoea'),
(u'ç', 's'),
(u'{@}ä{@}', '%a%'),
(u'{@}ä', '%a'),
(u'ä{@}', 'a%'),
(u'ä', 'e'),
(u'{@}ë{@}', '%e%'),
(u'{@}ë', '%e'),
(u'ë{@}', 'e%'),
(u'ë', 'E'),
(u'ée', 'ee'),
(u'é', 'E'),
(u'{@}ï{@}', '%i%'),
(u'{@}ï', '%i'),
(u'ï{@}', 'i%'),
(u'ï', 'i'),
(u'{@}ö{@}', '%o%'),
(u'{@}ö', '%o'),
(u'ö{@}', 'o%'),
(u'ö', 'eu'),
(u'{@}ü{@}', '%u%'),
(u'{@}ü', '%u'),
(u'ü{@}', 'u%'),
(u'ü', 'u'),
('^{<cs>}ig', 'igg'),
('^{(<cs>)(<cs>)}ig', 'igg'),
('^{(<cs>)(<cs>)(<cs>)}ig', 'igg'),
('aalbes', 'aalbEs'),
('^aang', 'aan-g'),
('aapmens', 'aapmEns'),
('^abc$', 'abece'),
('adelbert', 'adelbErt'),
('ademtest', 'ademtEst'),
('adres', 'adrEs'),
('adrien', 'adriEn'),
('advocaat', 'aDvocaat'),
('aequo', 'equo'),
('aftershave', 'aftQrsjeev'),
('afvalrace', 'afvalrees'),
('agaath', 'agaat'),
('agath', 'agat'),
('ageeth', 'ageet'),
('ageth', 'aget'),
('^aim{e|ee}', 'em'),
('allerbest', 'allerbEst'),
('altsaxo', 'altYsaxo'),
('amanuens', 'amanu%ens'),
('amulet', 'amulEt'),
('ancien', 'anciEn'),
('andelst', 'andElst'),
('angina', 'anggina'),
('angli{c|st}', 'anggli'),
('angol{a|ees}', 'anggol'),
('anouk', 'anoek'),
('anthon', 'anton'),
('apothe{ek|k}', 'apote'),
('^apropos$', 'apropo'),
('^a propos$', 'apropo'),
('aquarel', 'aquarEl'),
('archipel', 'archipEl'),
('architect', 'architEct'),
('arrest', 'arrEst'),
('aspect', 'aspEct'),
('asbest', 'asbEst'),
('autorace', 'autorees'),
('baby', 'beeby'),
('badge', 'bezi'),
('badminton', 'bedminton'),
('bagage', 'bagaze'),
('bagatel', 'bagatEl'),
('bajonet', 'bajonEt'),
('^balpen', 'balpEn'),
('balth', 'balt'),
('banket', 'bankEt'),
('bankstel', 'bankstEl'),
('baret', 'barEt'),
('barkeep', 'barkip'),
('barones', 'baronEs'),
('barrage', 'barraze'),
('barthol', 'bartol'),
('baseball', 'beesbol'),
('bassin', 'bassEng'),
('beautycase', 'bJoetykees'),
('bed', 'bEd'),
('bEdekt', 'bedEkt'),
('beige', 'beize'),
('^beken', 'bekEn'),
('bekend', 'bekEnd'),
('berg', 'bErg'),
('besef', 'besEf'),
('besmet', 'besmEt'),
('beste{k|l|m}', 'bestE'),
('bevlek', 'bevlEk'),
('bijec', 'bi-jec'),
('bijou', 'bizoe'),
('biljet', 'biljEt'),
('bingo', 'bingGo'),
('biscuit', 'biscu%i'),
('bordes', 'bordEs'),
('bosbes', 'bosbEs'),
('boudier', 'boediE'),
('boulevard', 'boelevar'),
('bourgogne', 'boergonje'),
('bourgond', 'boergond'),
('bouvier', 'boeviE'),
('bowl', 'bol'),
('braille', 'braje'),
('brek', 'brEk'),
('breng', 'brEng'),
('budget', 'buzEt'),
('buffet', 'buffEt'),
('bungalowtent', 'bungalowtEnt'),
('bungalow', 'bungGalo'),
('cabaretier', 'cabarEtiE'),
('cabaret', 'cabarE'),
('cabriolet', 'cabriolEt'),
('cadet', 'cadEt'),
('caissiEre', 'cassiEre'),
('cake', 'keek'),
('cahier', 'cajE'),
('camouflage', 'camoeflaze'),
('campagne', 'campanje'),
('cantharel', 'cantarEl'),
('capuchon', 'capusjon'),
('cari%es', 'cariEs'),
('carillon', 'cariljon'),
('cashew', 'kesjoe'),
('cash', 'kesj'),
('castagnet', 'castanjet'),
('catheter', 'cateter'),
('^cees', 'kees'),
('chalet', 'sjalE'),
('champagne', 'sjampanje'),
('champignon', 'sjampinjon'),
('chantage', 'sjantaze'),
('chante{er|re}', 'sjante'),
('chaperon', 'sjaperon'),
('charcuterie', 'sjarcuterie'),
('charles', 'sjarl'),
('^charl', 'sjarl'),
('charmant', 'sjarmant'),
('chauffeur', 'sjoffeur'),
('cheque', 'sjEk'),
('cheryl', 'sjeryl'),
('chris', 'kris'),
('cologne', 'colonje'),
('compagn{i|y}', 'compan'),
('compagn', 'companj'),
('concertza{al|l}', 'concert-za'),
('conci%erge', 'conciErze'),
('concours', 'concoer'),
('concurrent', 'concurrEnt'),
('condens', 'condEns'),
('conferencier', 'conferangsiE'),
('conference', 'conferangs'),
('congres', 'conggrEs'),
('consequent', 'consequEnt'),
('consignatie', 'consinjatie'),
('contactlens', 'contactlEns'),
('container', 'conteener'),
('continue{er|r}', 'continu%e'),
('contour', 'contoer'),
('copyright', 'copyrajt'),
('cornedbeef', 'cornedbif'),
('corps', 'cor'),
('correct', 'corrEct'),
('corrige', 'corrize'),
('corsage', 'corsaze'),
('coulant', 'coelant'),
('coulisse', 'coelisse'),
('coup', 'coep'),
('courant', 'coerant'),
('coureur', 'coereur'),
('courgette', 'coerzette'),
('courtage', 'coertaze'),
('couture', 'coeture'),
('couturier', 'coeturiE'),
('couveuse', 'coeveuse'),
('cowboy', 'cauboy'),
('crash', 'crEsj'),
('crawl', 'crol'),
('crEche', 'crEsj'),
('crEme', 'crEm'),
('crime', 'crim'),
('croissant', 'croeassang'),
('croque', 'crok'),
('cursusjaar', 'cursusYjaar'),
('damhert', 'damhErt'),
('daniel', 'daniEl'),
('dani%el', 'daniEl'),
('dashboard', 'desjbord'),
('davidster', 'davit,ster'),
('debet', 'debEt'),
('decadent', 'decadEnt'),
('decibel', 'decibEl'),
('defect', 'defEct'),
('depot$', 'depo'),
('depots', 'depos'),
('dessert', 'dessEr'),
('dessin', 'dessEng'),
('detaillist', 'detajist'),
('detail', 'detaj'),
('detective', 'ditectiv'),
('diligence', 'dilizangce'),
('direct', 'dirEct'),
('discothe', 'discote'),
('discretie', 'discreti'),
('display', 'displey'),
('divers', 'divErs'),
('dividend', 'dividEnd'),
('doodstraf', 'dood%straf'),
('doodziek', 'dood%ziek'),
('doodzonde', 'dood%zonde'),
('doroth', 'dorot'),
('dossier', 'dossiE'),
('douan{e|i}', 'doean'),
('doubl', 'doebl'),
('douche$', 'doesj'),
('douche', 'doesje'),
('drenthe', 'drente'),
('drinkyoghurt', 'drinkYJoghurt'),
('drukpers', 'drukpErs'),
('drumstel', 'drumstEl'),
('^dumas$', 'duma'),
('dyk', 'dijk'),
('eerhestel', 'eerhestEl'),
('effect', 'effEct'),
('eicel', 'eicEl'),
('eindhoven', 'einthoven'),
('elektricien', 'elektriciEng'),
('^eljero', 'elzero'),
('employE', 'amploeajE'),
('enschede', 'enschedE'),
('ernst', 'Ernst'),
('erwt', 'Ert'),
('esther', 'ester'),
('etage', 'etaze'),
('etalage', 'etalaze'),
('ether', 'eter'),
('ethiek', 'etiek'),
('ethiop', 'etiop'),
('ethisch', 'etisch'),
('eugene', 'euzEn'),
('eurocent', 'eurocEnt'),
('euthanas', 'eutanas'),
('evacue{er|r}', 'evacu%e'),
('evangel', 'evanggel'),
('evengoed', 'even-goed'),
('examengeld', 'examen-gEld'),
('exces', 'excEs'),
('{~@}ex', 'Ex'),
('floret', 'florEt'),
('foetus', 'feutus'),
('forel', 'forEl'),
('forfait', 'forfE'),
('fokstier', 'fokstir'),
('formulier', 'formulir'),
('foyer', 'foeajE'),
('franchise', 'fransjize'),
('frangipane', 'frangzipane'),
('freak', 'fri-k'),
('freelancer', 'frilangcer'),
('freelance', 'frilangs'),
('freudia', 'froidia'),
('frikadel', 'frikadEl'),
('frou-frou', 'froe-froe'),
('fulltime', 'foeltajm'),
('funest', 'funEst'),
('gabriel', 'GabriEl'),
('gabri%el', 'GabriEl'),
('^game$', 'Geem'),
('^games$', 'Geems'),
('gameboy', 'Geemboy'),
('gebrek', 'gebrEk'),
('gelukwens', 'gelukwEns'),
('gemenebest', 'gemenebEst'),
('gemengd', 'gemEngd'),
('gEnant', 'zEnant'),
('gendarme', 'zangdarme'),
('genEve', 'zenEve'),
('genie$', 'zenie'),
('genie{%en|tj}', 'zenie'),
('genre', 'zangrY'),
('^giovan', 'zovan'),
('gogh', 'Gogh'),
('grens', 'grEns'),
('greth{a|e}', 'gret'),
('^guido', 'gido'),
('^hamel', 'hamEl'),
('hef', 'hEf'),
('hek', 'hEk'),
('hengst', 'hEngst'),
('ijssel', 'ijssQl'),
('israel', 'israEl'),
('isra%el', 'israEl'),
('jacques', 'zaak'),
('jeanette', 'zaanEt'),
('jeanet', 'zaanEt'),
('jeanne$', 'zaan'),
('jockey', 'zoki'),
('johannes', 'johannEs'),
('^john$', 'zon'),
('jozef', 'jozEf'),
('^beken', 'bekEn'),
('beken{d|t}', 'bekEn'),
('^erken', 'erkEn'),
('erken{d|t}', 'erkEn'),
('^herken', 'herkEn'),
('^ontken', 'ontkEn'),
('ontken{d|t}', 'ontkEn'),
('^toeken', 'toekEn'),
('toeken{d|t}', 'toekEn'),
('^verken', 'verkEn'),
('klem{d|t}', 'klEm'),
('korthal', 'kortal'),
('leg{d|t}', 'lEg'),
('lingerie', 'lengzerie'),
('lingu%ist', 'linggu%ist'),
('^louis$', 'loei'),
('^louis', 'loeis'),
('lyonnet', 'lyonnE'),
('manuel', 'manuEl'),
('^margot$', 'margo'),
('^mari%e', 'mariE'),
('marth', 'mart'),
('^mary$', 'mery'),
('mathild', 'matild'),
('melk', 'mElk'),
('merk', 'mErk'),
('michael', 'mikaEl'),
('micha%el', 'mikaEl'),
('^michel$', 'misjEl'),
('michiel', 'mikiEl'),
('michi%el', 'mikiEl'),
('model', 'modEl'),
('monsieur', 'mQsieu'),
('nerf', 'nErf'),
('^nigel', 'naizel'),
('^no%e', 'noE'),
('ongerust', 'onggerust'),
('orkest', 'orkEst'),
('pech', 'pEch'),
('persoonsbed', 'persoonsbEd'),
('pierre', 'piEr'),
('pincher', 'pinsjer'),
('posthum', 'postum'),
('rafael', 'rafaEl'),
('rafa%el', 'rafaEl'),
('recept', 'recEpt'),
('reinier', 'reini%er'),
('rhijn', 'rijn'),
('richard', 'rikard'),
('rogier', 'rogi%er'),
('ryan', 'raien'),
('scherm', 'schErm'),
('sharon', 'sjaron'),
('spel', 'spEl'),
('spionage', 'spionaze'),
('streng', 'strEng'),
('student', 'studEnt'),
('term', 'tErm'),
('the{a|o}', 'te'),
('thierry', 'tiErry'),
('thijs', 'tijs'),
('thys', 'tys'),
('timoth', 'timot'),
('toilette', 'toealEt'),
('toilet', 'toealEt'),
('tref', 'trEf'),
('trek', 'trEk'),
('van/Gogh', 'wan/Gogh'),
('vel{d|t}', 'vEl'),
('vEldhoven', 'vEld/hoven'),
('^vera$', 'wera'),
('veroni', 'weroni'),
('victor', 'wictor'),
('vincent', 'wincEnt'),
('viol', 'wiol'),
('vlek', 'vlEk'),
('weg', 'wEg'),
('wenst', 'wEnst'),
('^wens', 'wEns'),
('werk', 'wErk'),
('wesley', 'wesly'),
('wet', 'wEt'),
('^wt', 'uwt'),
('zet', 'zEt'),
('szoon', 's/zoon'),
('echt', 'Echt'),
('egd', 'Egd'),
('ent', 'Ent'),
('eau', 'o'), # common French spellings
('%e{l|ls|t|ts|tt|tts}$', 'E'),
('air', 'Er'),
('oir$', 'oear'),
('^ti', 'tiF'),
('tie{f|k}', 'ti'),
('tie$', 'sie'),
('tieus', 'sieus'),
('{n|r}tie$', 'sie'),
('ti{eel|%el}', 'si'),
('ti{aal|al}', 'si'),
('tion$', 'sjon'),
('tion{eel|%el}', 'sjon'),
('tione{er|r}', 'sjone'),
('tion{ne|s}', 'sjon'),
('tium', 'sium'),
('F', None),
('{<cs>}ig$', 'Qg'),
('{<cs>}igd$', 'Qgd'),
('{<cs>}igde$', 'Qgde'),
('{<cs>}ige$', 'Qge'),
('{<cs>}igen$', 'Qgen'),
('{<cs>}igheid$', 'Qgheid'),
('{<cs>}iging$', 'Qging'),
('^over', 'ovQr'),
('sch{@}', 'sX'),
('sch', 's'),
('ch', 'X'),
('c{e|E|i|y}', 's'),
('c', 'k'),
('qq', 'q'),
('qu', 'kw'),
('q', 'k'),
('x', 'ks'),
('ng', 'N'),
('nk', 'Nk'),
('dt$', 't'),
('dt{<cs>}', 't'),
('gh', 'g'),
('ph', 'p'),
('^th', 't'),
('^kh', 'k'),
('h{<cs>}', None),
('h$', None),
('sj{@}', 'sJ'),
('sj', 'si'),
('sz$', 's'),
('sz{<cs>}', 's'),
('ts', 'C'),
('tz', 'C'),
('^v', 'f'),
('uw', 'uW'),
('v$', 'f'),
('^y{@}', 'j'),
('y', 'i%'),
('z$', 's'),
('bb', 'b'),
('dd', 'd'),
('ff', 'f'),
('fv', 'f'),
('gg', 'g'),
('hh', 'h'),
('kk', 'k'),
('ll', 'l'),
('mm', 'm'),
('nn', 'n'),
('pp', 'p'),
('rr', 'r'),
('ss', 's'),
('tt', 't'),
('mbt', 'mt'),
('mpt', 'mt'),
('b$', '-p'),
('d$', '-t'),
('ds{~@}', 'C'),
('ds$', 'C'),
('dz{~@}', 'C'),
('dz$', 'C'),
('^ie{<cs>}', 'i'),
('{<cs>}ie{<cs>}', 'i'),
('^oe{<cs>}', 'U'),
('{<cs>}oe{<cs>}', 'U'),
('b{@|<son>|j}', 'B'),
('{<son>}b', 'B'),
('^{(<short>)}b{<cs>}', 'P'),
('{(<cs>)(<short>)}b{<cs>}', 'P'),
('B', 'b'),
('d{@|<son>|j}', 'D'),
('{<son>}d', 'D'),
('^{(<short>)}d{<cs>}', 'T'),
('{(<cs>)(<short>)}d{<cs>}', 'T'),
('D', 'd'),
('p{@|<son>|j}', 'F'),
('{<son>}p', 'F'),
('^{(<short>)}p{<cs>}', 'P'),
('{(<cs>)(<short>)}p{<cs>}', 'P'),
('^{(<short>)}p$', 'P'),
('{(<cs>)(<short>)}p$', 'P'),
('F', 'p'),
('t{@|<son>|j}', 'F'),
('{<son>}t', 'F'),
('^{(<short)>}t{<cs>}', 'T'),
('{(<cs>)(<short>)}t{<cs>}', 'T'),
('^{(<short>)}t$', 'T'),
('{(<cs>)(<short>)}t$', 'T'),
('F', 't'),
('k{@|<son>|j|v}', 'F'),
('{<son>}k', 'F'),
('^{(<short>)}k{<cs>}', 'K'),
('{(<cs>)(<short>)}k{<cs>}', 'K'),
('^{(<short>)}k$', 'K'),
('{(<cs>)(<short>)}k$', 'K'),
('F', 'k'),
('{~@}bj', 'bi%'),
('^bj', 'bi%'),
('{~@}dj', 'di%'),
('^dj', 'di%'),
('{~@}pj', 'pi%'),
('^pj', 'pi%'),
('{~@}tj', 'ti%'),
('^tj', 'ti%'),
('{~@}kj', 'ki%'),
('^kj', 'ki%'),
('{~@}rj', 'ri%'),
('^rj', 'ri%'),
('{b|d|p|t|k|r}j', 'Yj'),
('{@}ie', 'i%e'),
('w', 'v'),
('ae', 'aa'),
('aa', 'a'),
('auW', 'aU%'),
('au', 'aU%'),
('ouW', 'aU%'),
('ou', 'aU%'),
('{@}iji', 'i'),
('{@}ij{@}', 'i%j'),
('{@}ij', 'i%'),
('ij', 'ei'),
('eeuW', 'eiU%'),
('ieuW', 'iU%'),
('euW', 'e-u%'),
('iee', 'i%ee'),
('ee', 'ei'),
('oo', 'o'),
('ui', 'au%'),
('uy', 'au%'),
('eu', 'O%'),
('uee', 'u%ee'),
('ue', 'uu'),
('uW', 'uu%'),
('uu', 'u'),
('i%i', 'i'),
('ie', 'i'),
('ii', 'i'),
('oe', 'U'),
('-', None),
('e$', 'Q'),
('^e{(<cs>)}$', 'E'),
('^{(<cs>)}e{(<cs>)}$', 'E'),
('^{(<cs>)(<cs>)}e{(<cs>)}$', 'E'),
('^{(<cs>)(<cs>)(<cs>)}e{(<cs>)}$', 'E'),
('^e{(<cs>)(<cs>)}$', 'E'),
('^{(<cs>)}e{(<cs>)(<cs>)}$', 'E'),
('^{(<cs>)(<cs>)}e{(<cs>)(<cs>)}$', 'E'),
('^{(<cs>)(<cs>)(<cs>)}e{(<cs>)(<cs>)}$', 'E'),
('^e{(<cs>)(<cs>)(<cs>)}$', 'E'),
('^{(<cs>)}e{(<cs>)(<cs>)(<cs>)}$', 'E'),
('^{(<cs>)(<cs>)}e{(<cs>)(<cs>)(<cs>)}$', 'E'),
('^{(<cs>)(<cs>)(<cs>)}e{(<cs>)(<cs>)(<cs>)}$', 'E'),
('^e{(<cs>)(<cs>)(<cs>)(<cs>)}$', 'E'),
('^{(<cs>)}e{(<cs>)(<cs>)(<cs>)(<cs>)}$', 'E'),
('^{(<cs>)(<cs>)}e{(<cs>)(<cs>)(<cs>)(<cs>)}$', 'E'),
('^{(<cs>)(<cs>)(<cs>)}e{(<cs>)(<cs>)(<cs>)(<cs>)}$', 'E'),
('{<cs>}e{(<cs>)}$', 'Q'),
('{<cs>}e{(<cs>)(<cs>)}$', 'Q'),
('{<cs>}e{(<cs>)(<cs>)(<cs>)}$', 'Q'),
('{<cs>}e{(<cs>)(<cs>)(<cs>)(<cs>)}$', 'Q'),
('E', 'e'),
('P', 'p,'),
('T', 't,'),
('K', 'k,'),
('j{@}', 'J'),
('j', 'i'),
('{C|z}J', None),
('^l', 'l;'),
('^m', 'm;'),
('^n', 'n;'),
('l$', 'l,'),
('m$', 'm,'),
('n$', 'n,'),
('l{@|m,|n,|N}', 'l;'),
('{,}l', 'l;'),
('m{@}', 'm;'),
('n{@}', 'n;'),
('l', 'l,'),
('m', 'm,'),
('n', 'n,'),
('N', 'N,'),
(',,', ','),
(',;', None),
(',l,', 'l,'),
(',m,', 'm,'),
(',n,', 'n,'),
(',N,', 'N,'),
('l{m;|n;}', 'l,'),
(';', None),
('^a', '&a'),
('^e', '&e'),
('^i', '&i'),
('^o', '&o'),
('^O', '&O'),
('^u', '&u'),
('^U', '&U'),
('^Q', '&Q'),
('^J', '&J'),
('b', Choseong(B)),
('C', Choseong(C)),
('d', Choseong(D)),
('f', Choseong(P)),
('g', Choseong(H)),
('G', Choseong(G)),
('h', Choseong(H)),
('k,', Jongseong(G)),
('k', Choseong(K)),
('^l', Choseong(L)),
('{,}l', Choseong(L)),
('l,', Jongseong(L)),
('l', Jongseong(L), Choseong(L)),
('m,', Jongseong(M)),
('m', Choseong(M)),
('n,', Jongseong(N)),
('n', Choseong(N)),
('N', Jongseong(NG)),
('p,', Jongseong(B)),
('p', Choseong(P)),
('r', Choseong(L)),
('s', Choseong(S)),
('t,', Jongseong(S)),
('t', Choseong(T)),
('v', Choseong(B)),
('X', Choseong(H)),
('z', Choseong(J)),
('&', Choseong(NG)),
('Ja', Jungseong(YA)),
('Je', Jungseong(YE)),
('Ji', Jungseong(I)),
('Jo', Jungseong(YO)),
('JO', Jungseong(YE)),
('Ju', Jungseong(YU)),
('JU', Jungseong(YU)),
('JQ', Jungseong(YEO)),
('a', Jungseong(A)),
('e', Jungseong(E)),
('i', Jungseong(I)),
('o', Jungseong(O)),
('O', Jungseong(OE)),
('u', Jungseong(WI)),
('U', Jungseong(U)),
('Q', Jungseong(EO)),
('Y', Jungseong(EU)),
])
def normalize(self, string):
return normalize_roman(string, {
u'Ä': u'ä', u'Ç': u'ç', u'Ë': u'ë', u'É': u'é', u'È': u'é',
u'è': u'é', u'Ê': u'é', u'ê': u'é', u'Ï': u'ï', u'Ḯ': u'ï',
u'Ḯ': u'ï', u'Ö': u'ö', u'IJ': u'ij', u'ij': u'ij', u'Ü': u'ü',
u'Ÿ': u'ij', u'ÿ': u'ij'
})
__lang__ = Dutch | hangulize/langs/nld/__init__.py | from hangulize import *
class Dutch(Language):
"""For transcribing Dutch."""
__iso639__ = {1: 'nl', 2: 'dut', 3: 'nld'}
__tmp__ = '%,;&'
vowels = 'aeEioOuUyQ'
cs = 'b', 'B', 'c', 'C', 'd', 'D', 'f', 'F', 'g', 'G', 'h', 'j', 'J', \
'k', 'K', 'l', 'm', 'n', 'N', 'p', 'P', 'q', 'r', 's', 't', 'T', \
'v', 'w', 'x', 'X', 'z', '%' # consonants
son = 'lmnNrw' # sonorants
short = 'aeEiouU' # short vowels
notation = Notation([
(u'’', '\''),
(' aan ', '/aan/'),
('^aan ', 'aan/'),
(' bij ', '/bij/'),
('^bij ', 'bij/'),
(' boven ', '/boven/'),
('^boven ', 'boven/'),
(' en ', '/en/'),
('^en ', 'en/'),
(' in ', '/in/'),
('^in ', 'in/'),
(' op ', '/op/'),
('^op ', 'op/'),
(' over ', '/over/'),
('^over ', 'over/'),
(' of ', '/of/'),
('^de ', 'de/'),
('^den ', 'den/'),
('^der ', 'der/'),
('^des ', 'des/'),
('^di ', 'di/'),
('^het ', 'het/'),
('^onder ', 'onder/'),
('^sint ', 'sint/'),
('^te ', 'te/'),
('^ten ', 'ten/'),
('^ter ', 'ter/'),
('^thoe ', 'thoe/'),
('^tot ', 'tot/'),
('^uit ', 'uit/'),
('^uijt ', 'uijt/'),
('^van ', 'van/'),
('^ver ', 'ver/'),
('^voor ', 'voor/'),
('-', '/'),
('^\'s ', 's/'),
('^\'t ', 'Qt,/'),
('^\'t', 'Qt,'),
('hoek van/holland', 'hoek/van/holland'),
('hof van/twente', 'hof/van/twente'),
('ronde venen', 'ronde/venen'),
('^midden ', 'midden/'),
('^neder ', 'neder/'),
('^nieuw ', 'nieuw/'),
('^nieuwe ', 'nieuwe/'),
('^noord ', 'noord/'),
('^oost ', 'oost/'),
('^west ', 'west/'),
('^zuid ', 'zuid/'),
(u'aimé', u'emé'),
(u'curaçao', 'curaso'),
('curacao', 'curaso'),
(u'française', 'frangsEzY'),
('francaise', 'frangsEzY'),
(u'français', 'frangsE'),
('francais', 'frangsE'),
(u'françoise', 'frangsoeazY'),
('francoise', 'frangsoeazY'),
(u'françois', 'frangsoea'),
('francois', 'frangsoea'),
(u'ç', 's'),
(u'{@}ä{@}', '%a%'),
(u'{@}ä', '%a'),
(u'ä{@}', 'a%'),
(u'ä', 'e'),
(u'{@}ë{@}', '%e%'),
(u'{@}ë', '%e'),
(u'ë{@}', 'e%'),
(u'ë', 'E'),
(u'ée', 'ee'),
(u'é', 'E'),
(u'{@}ï{@}', '%i%'),
(u'{@}ï', '%i'),
(u'ï{@}', 'i%'),
(u'ï', 'i'),
(u'{@}ö{@}', '%o%'),
(u'{@}ö', '%o'),
(u'ö{@}', 'o%'),
(u'ö', 'eu'),
(u'{@}ü{@}', '%u%'),
(u'{@}ü', '%u'),
(u'ü{@}', 'u%'),
(u'ü', 'u'),
('^{<cs>}ig', 'igg'),
('^{(<cs>)(<cs>)}ig', 'igg'),
('^{(<cs>)(<cs>)(<cs>)}ig', 'igg'),
('aalbes', 'aalbEs'),
('^aang', 'aan-g'),
('aapmens', 'aapmEns'),
('^abc$', 'abece'),
('adelbert', 'adelbErt'),
('ademtest', 'ademtEst'),
('adres', 'adrEs'),
('adrien', 'adriEn'),
('advocaat', 'aDvocaat'),
('aequo', 'equo'),
('aftershave', 'aftQrsjeev'),
('afvalrace', 'afvalrees'),
('agaath', 'agaat'),
('agath', 'agat'),
('ageeth', 'ageet'),
('ageth', 'aget'),
('^aim{e|ee}', 'em'),
('allerbest', 'allerbEst'),
('altsaxo', 'altYsaxo'),
('amanuens', 'amanu%ens'),
('amulet', 'amulEt'),
('ancien', 'anciEn'),
('andelst', 'andElst'),
('angina', 'anggina'),
('angli{c|st}', 'anggli'),
('angol{a|ees}', 'anggol'),
('anouk', 'anoek'),
('anthon', 'anton'),
('apothe{ek|k}', 'apote'),
('^apropos$', 'apropo'),
('^a propos$', 'apropo'),
('aquarel', 'aquarEl'),
('archipel', 'archipEl'),
('architect', 'architEct'),
('arrest', 'arrEst'),
('aspect', 'aspEct'),
('asbest', 'asbEst'),
('autorace', 'autorees'),
('baby', 'beeby'),
('badge', 'bezi'),
('badminton', 'bedminton'),
('bagage', 'bagaze'),
('bagatel', 'bagatEl'),
('bajonet', 'bajonEt'),
('^balpen', 'balpEn'),
('balth', 'balt'),
('banket', 'bankEt'),
('bankstel', 'bankstEl'),
('baret', 'barEt'),
('barkeep', 'barkip'),
('barones', 'baronEs'),
('barrage', 'barraze'),
('barthol', 'bartol'),
('baseball', 'beesbol'),
('bassin', 'bassEng'),
('beautycase', 'bJoetykees'),
('bed', 'bEd'),
('bEdekt', 'bedEkt'),
('beige', 'beize'),
('^beken', 'bekEn'),
('bekend', 'bekEnd'),
('berg', 'bErg'),
('besef', 'besEf'),
('besmet', 'besmEt'),
('beste{k|l|m}', 'bestE'),
('bevlek', 'bevlEk'),
('bijec', 'bi-jec'),
('bijou', 'bizoe'),
('biljet', 'biljEt'),
('bingo', 'bingGo'),
('biscuit', 'biscu%i'),
('bordes', 'bordEs'),
('bosbes', 'bosbEs'),
('boudier', 'boediE'),
('boulevard', 'boelevar'),
('bourgogne', 'boergonje'),
('bourgond', 'boergond'),
('bouvier', 'boeviE'),
('bowl', 'bol'),
('braille', 'braje'),
('brek', 'brEk'),
('breng', 'brEng'),
('budget', 'buzEt'),
('buffet', 'buffEt'),
('bungalowtent', 'bungalowtEnt'),
('bungalow', 'bungGalo'),
('cabaretier', 'cabarEtiE'),
('cabaret', 'cabarE'),
('cabriolet', 'cabriolEt'),
('cadet', 'cadEt'),
('caissiEre', 'cassiEre'),
('cake', 'keek'),
('cahier', 'cajE'),
('camouflage', 'camoeflaze'),
('campagne', 'campanje'),
('cantharel', 'cantarEl'),
('capuchon', 'capusjon'),
('cari%es', 'cariEs'),
('carillon', 'cariljon'),
('cashew', 'kesjoe'),
('cash', 'kesj'),
('castagnet', 'castanjet'),
('catheter', 'cateter'),
('^cees', 'kees'),
('chalet', 'sjalE'),
('champagne', 'sjampanje'),
('champignon', 'sjampinjon'),
('chantage', 'sjantaze'),
('chante{er|re}', 'sjante'),
('chaperon', 'sjaperon'),
('charcuterie', 'sjarcuterie'),
('charles', 'sjarl'),
('^charl', 'sjarl'),
('charmant', 'sjarmant'),
('chauffeur', 'sjoffeur'),
('cheque', 'sjEk'),
('cheryl', 'sjeryl'),
('chris', 'kris'),
('cologne', 'colonje'),
('compagn{i|y}', 'compan'),
('compagn', 'companj'),
('concertza{al|l}', 'concert-za'),
('conci%erge', 'conciErze'),
('concours', 'concoer'),
('concurrent', 'concurrEnt'),
('condens', 'condEns'),
('conferencier', 'conferangsiE'),
('conference', 'conferangs'),
('congres', 'conggrEs'),
('consequent', 'consequEnt'),
('consignatie', 'consinjatie'),
('contactlens', 'contactlEns'),
('container', 'conteener'),
('continue{er|r}', 'continu%e'),
('contour', 'contoer'),
('copyright', 'copyrajt'),
('cornedbeef', 'cornedbif'),
('corps', 'cor'),
('correct', 'corrEct'),
('corrige', 'corrize'),
('corsage', 'corsaze'),
('coulant', 'coelant'),
('coulisse', 'coelisse'),
('coup', 'coep'),
('courant', 'coerant'),
('coureur', 'coereur'),
('courgette', 'coerzette'),
('courtage', 'coertaze'),
('couture', 'coeture'),
('couturier', 'coeturiE'),
('couveuse', 'coeveuse'),
('cowboy', 'cauboy'),
('crash', 'crEsj'),
('crawl', 'crol'),
('crEche', 'crEsj'),
('crEme', 'crEm'),
('crime', 'crim'),
('croissant', 'croeassang'),
('croque', 'crok'),
('cursusjaar', 'cursusYjaar'),
('damhert', 'damhErt'),
('daniel', 'daniEl'),
('dani%el', 'daniEl'),
('dashboard', 'desjbord'),
('davidster', 'davit,ster'),
('debet', 'debEt'),
('decadent', 'decadEnt'),
('decibel', 'decibEl'),
('defect', 'defEct'),
('depot$', 'depo'),
('depots', 'depos'),
('dessert', 'dessEr'),
('dessin', 'dessEng'),
('detaillist', 'detajist'),
('detail', 'detaj'),
('detective', 'ditectiv'),
('diligence', 'dilizangce'),
('direct', 'dirEct'),
('discothe', 'discote'),
('discretie', 'discreti'),
('display', 'displey'),
('divers', 'divErs'),
('dividend', 'dividEnd'),
('doodstraf', 'dood%straf'),
('doodziek', 'dood%ziek'),
('doodzonde', 'dood%zonde'),
('doroth', 'dorot'),
('dossier', 'dossiE'),
('douan{e|i}', 'doean'),
('doubl', 'doebl'),
('douche$', 'doesj'),
('douche', 'doesje'),
('drenthe', 'drente'),
('drinkyoghurt', 'drinkYJoghurt'),
('drukpers', 'drukpErs'),
('drumstel', 'drumstEl'),
('^dumas$', 'duma'),
('dyk', 'dijk'),
('eerhestel', 'eerhestEl'),
('effect', 'effEct'),
('eicel', 'eicEl'),
('eindhoven', 'einthoven'),
('elektricien', 'elektriciEng'),
('^eljero', 'elzero'),
('employE', 'amploeajE'),
('enschede', 'enschedE'),
('ernst', 'Ernst'),
('erwt', 'Ert'),
('esther', 'ester'),
('etage', 'etaze'),
('etalage', 'etalaze'),
('ether', 'eter'),
('ethiek', 'etiek'),
('ethiop', 'etiop'),
('ethisch', 'etisch'),
('eugene', 'euzEn'),
('eurocent', 'eurocEnt'),
('euthanas', 'eutanas'),
('evacue{er|r}', 'evacu%e'),
('evangel', 'evanggel'),
('evengoed', 'even-goed'),
('examengeld', 'examen-gEld'),
('exces', 'excEs'),
('{~@}ex', 'Ex'),
('floret', 'florEt'),
('foetus', 'feutus'),
('forel', 'forEl'),
('forfait', 'forfE'),
('fokstier', 'fokstir'),
('formulier', 'formulir'),
('foyer', 'foeajE'),
('franchise', 'fransjize'),
('frangipane', 'frangzipane'),
('freak', 'fri-k'),
('freelancer', 'frilangcer'),
('freelance', 'frilangs'),
('freudia', 'froidia'),
('frikadel', 'frikadEl'),
('frou-frou', 'froe-froe'),
('fulltime', 'foeltajm'),
('funest', 'funEst'),
('gabriel', 'GabriEl'),
('gabri%el', 'GabriEl'),
('^game$', 'Geem'),
('^games$', 'Geems'),
('gameboy', 'Geemboy'),
('gebrek', 'gebrEk'),
('gelukwens', 'gelukwEns'),
('gemenebest', 'gemenebEst'),
('gemengd', 'gemEngd'),
('gEnant', 'zEnant'),
('gendarme', 'zangdarme'),
('genEve', 'zenEve'),
('genie$', 'zenie'),
('genie{%en|tj}', 'zenie'),
('genre', 'zangrY'),
('^giovan', 'zovan'),
('gogh', 'Gogh'),
('grens', 'grEns'),
('greth{a|e}', 'gret'),
('^guido', 'gido'),
('^hamel', 'hamEl'),
('hef', 'hEf'),
('hek', 'hEk'),
('hengst', 'hEngst'),
('ijssel', 'ijssQl'),
('israel', 'israEl'),
('isra%el', 'israEl'),
('jacques', 'zaak'),
('jeanette', 'zaanEt'),
('jeanet', 'zaanEt'),
('jeanne$', 'zaan'),
('jockey', 'zoki'),
('johannes', 'johannEs'),
('^john$', 'zon'),
('jozef', 'jozEf'),
('^beken', 'bekEn'),
('beken{d|t}', 'bekEn'),
('^erken', 'erkEn'),
('erken{d|t}', 'erkEn'),
('^herken', 'herkEn'),
('^ontken', 'ontkEn'),
('ontken{d|t}', 'ontkEn'),
('^toeken', 'toekEn'),
('toeken{d|t}', 'toekEn'),
('^verken', 'verkEn'),
('klem{d|t}', 'klEm'),
('korthal', 'kortal'),
('leg{d|t}', 'lEg'),
('lingerie', 'lengzerie'),
('lingu%ist', 'linggu%ist'),
('^louis$', 'loei'),
('^louis', 'loeis'),
('lyonnet', 'lyonnE'),
('manuel', 'manuEl'),
('^margot$', 'margo'),
('^mari%e', 'mariE'),
('marth', 'mart'),
('^mary$', 'mery'),
('mathild', 'matild'),
('melk', 'mElk'),
('merk', 'mErk'),
('michael', 'mikaEl'),
('micha%el', 'mikaEl'),
('^michel$', 'misjEl'),
('michiel', 'mikiEl'),
('michi%el', 'mikiEl'),
('model', 'modEl'),
('monsieur', 'mQsieu'),
('nerf', 'nErf'),
('^nigel', 'naizel'),
('^no%e', 'noE'),
('ongerust', 'onggerust'),
('orkest', 'orkEst'),
('pech', 'pEch'),
('persoonsbed', 'persoonsbEd'),
('pierre', 'piEr'),
('pincher', 'pinsjer'),
('posthum', 'postum'),
('rafael', 'rafaEl'),
('rafa%el', 'rafaEl'),
('recept', 'recEpt'),
('reinier', 'reini%er'),
('rhijn', 'rijn'),
('richard', 'rikard'),
('rogier', 'rogi%er'),
('ryan', 'raien'),
('scherm', 'schErm'),
('sharon', 'sjaron'),
('spel', 'spEl'),
('spionage', 'spionaze'),
('streng', 'strEng'),
('student', 'studEnt'),
('term', 'tErm'),
('the{a|o}', 'te'),
('thierry', 'tiErry'),
('thijs', 'tijs'),
('thys', 'tys'),
('timoth', 'timot'),
('toilette', 'toealEt'),
('toilet', 'toealEt'),
('tref', 'trEf'),
('trek', 'trEk'),
('van/Gogh', 'wan/Gogh'),
('vel{d|t}', 'vEl'),
('vEldhoven', 'vEld/hoven'),
('^vera$', 'wera'),
('veroni', 'weroni'),
('victor', 'wictor'),
('vincent', 'wincEnt'),
('viol', 'wiol'),
('vlek', 'vlEk'),
('weg', 'wEg'),
('wenst', 'wEnst'),
('^wens', 'wEns'),
('werk', 'wErk'),
('wesley', 'wesly'),
('wet', 'wEt'),
('^wt', 'uwt'),
('zet', 'zEt'),
('szoon', 's/zoon'),
('echt', 'Echt'),
('egd', 'Egd'),
('ent', 'Ent'),
('eau', 'o'), # common French spellings
('%e{l|ls|t|ts|tt|tts}$', 'E'),
('air', 'Er'),
('oir$', 'oear'),
('^ti', 'tiF'),
('tie{f|k}', 'ti'),
('tie$', 'sie'),
('tieus', 'sieus'),
('{n|r}tie$', 'sie'),
('ti{eel|%el}', 'si'),
('ti{aal|al}', 'si'),
('tion$', 'sjon'),
('tion{eel|%el}', 'sjon'),
('tione{er|r}', 'sjone'),
('tion{ne|s}', 'sjon'),
('tium', 'sium'),
('F', None),
('{<cs>}ig$', 'Qg'),
('{<cs>}igd$', 'Qgd'),
('{<cs>}igde$', 'Qgde'),
('{<cs>}ige$', 'Qge'),
('{<cs>}igen$', 'Qgen'),
('{<cs>}igheid$', 'Qgheid'),
('{<cs>}iging$', 'Qging'),
('^over', 'ovQr'),
('sch{@}', 'sX'),
('sch', 's'),
('ch', 'X'),
('c{e|E|i|y}', 's'),
('c', 'k'),
('qq', 'q'),
('qu', 'kw'),
('q', 'k'),
('x', 'ks'),
('ng', 'N'),
('nk', 'Nk'),
('dt$', 't'),
('dt{<cs>}', 't'),
('gh', 'g'),
('ph', 'p'),
('^th', 't'),
('^kh', 'k'),
('h{<cs>}', None),
('h$', None),
('sj{@}', 'sJ'),
('sj', 'si'),
('sz$', 's'),
('sz{<cs>}', 's'),
('ts', 'C'),
('tz', 'C'),
('^v', 'f'),
('uw', 'uW'),
('v$', 'f'),
('^y{@}', 'j'),
('y', 'i%'),
('z$', 's'),
('bb', 'b'),
('dd', 'd'),
('ff', 'f'),
('fv', 'f'),
('gg', 'g'),
('hh', 'h'),
('kk', 'k'),
('ll', 'l'),
('mm', 'm'),
('nn', 'n'),
('pp', 'p'),
('rr', 'r'),
('ss', 's'),
('tt', 't'),
('mbt', 'mt'),
('mpt', 'mt'),
('b$', '-p'),
('d$', '-t'),
('ds{~@}', 'C'),
('ds$', 'C'),
('dz{~@}', 'C'),
('dz$', 'C'),
('^ie{<cs>}', 'i'),
('{<cs>}ie{<cs>}', 'i'),
('^oe{<cs>}', 'U'),
('{<cs>}oe{<cs>}', 'U'),
('b{@|<son>|j}', 'B'),
('{<son>}b', 'B'),
('^{(<short>)}b{<cs>}', 'P'),
('{(<cs>)(<short>)}b{<cs>}', 'P'),
('B', 'b'),
('d{@|<son>|j}', 'D'),
('{<son>}d', 'D'),
('^{(<short>)}d{<cs>}', 'T'),
('{(<cs>)(<short>)}d{<cs>}', 'T'),
('D', 'd'),
('p{@|<son>|j}', 'F'),
('{<son>}p', 'F'),
('^{(<short>)}p{<cs>}', 'P'),
('{(<cs>)(<short>)}p{<cs>}', 'P'),
('^{(<short>)}p$', 'P'),
('{(<cs>)(<short>)}p$', 'P'),
('F', 'p'),
('t{@|<son>|j}', 'F'),
('{<son>}t', 'F'),
('^{(<short)>}t{<cs>}', 'T'),
('{(<cs>)(<short>)}t{<cs>}', 'T'),
('^{(<short>)}t$', 'T'),
('{(<cs>)(<short>)}t$', 'T'),
('F', 't'),
('k{@|<son>|j|v}', 'F'),
('{<son>}k', 'F'),
('^{(<short>)}k{<cs>}', 'K'),
('{(<cs>)(<short>)}k{<cs>}', 'K'),
('^{(<short>)}k$', 'K'),
('{(<cs>)(<short>)}k$', 'K'),
('F', 'k'),
('{~@}bj', 'bi%'),
('^bj', 'bi%'),
('{~@}dj', 'di%'),
('^dj', 'di%'),
('{~@}pj', 'pi%'),
('^pj', 'pi%'),
('{~@}tj', 'ti%'),
('^tj', 'ti%'),
('{~@}kj', 'ki%'),
('^kj', 'ki%'),
('{~@}rj', 'ri%'),
('^rj', 'ri%'),
('{b|d|p|t|k|r}j', 'Yj'),
('{@}ie', 'i%e'),
('w', 'v'),
('ae', 'aa'),
('aa', 'a'),
('auW', 'aU%'),
('au', 'aU%'),
('ouW', 'aU%'),
('ou', 'aU%'),
('{@}iji', 'i'),
('{@}ij{@}', 'i%j'),
('{@}ij', 'i%'),
('ij', 'ei'),
('eeuW', 'eiU%'),
('ieuW', 'iU%'),
('euW', 'e-u%'),
('iee', 'i%ee'),
('ee', 'ei'),
('oo', 'o'),
('ui', 'au%'),
('uy', 'au%'),
('eu', 'O%'),
('uee', 'u%ee'),
('ue', 'uu'),
('uW', 'uu%'),
('uu', 'u'),
('i%i', 'i'),
('ie', 'i'),
('ii', 'i'),
('oe', 'U'),
('-', None),
('e$', 'Q'),
('^e{(<cs>)}$', 'E'),
('^{(<cs>)}e{(<cs>)}$', 'E'),
('^{(<cs>)(<cs>)}e{(<cs>)}$', 'E'),
('^{(<cs>)(<cs>)(<cs>)}e{(<cs>)}$', 'E'),
('^e{(<cs>)(<cs>)}$', 'E'),
('^{(<cs>)}e{(<cs>)(<cs>)}$', 'E'),
('^{(<cs>)(<cs>)}e{(<cs>)(<cs>)}$', 'E'),
('^{(<cs>)(<cs>)(<cs>)}e{(<cs>)(<cs>)}$', 'E'),
('^e{(<cs>)(<cs>)(<cs>)}$', 'E'),
('^{(<cs>)}e{(<cs>)(<cs>)(<cs>)}$', 'E'),
('^{(<cs>)(<cs>)}e{(<cs>)(<cs>)(<cs>)}$', 'E'),
('^{(<cs>)(<cs>)(<cs>)}e{(<cs>)(<cs>)(<cs>)}$', 'E'),
('^e{(<cs>)(<cs>)(<cs>)(<cs>)}$', 'E'),
('^{(<cs>)}e{(<cs>)(<cs>)(<cs>)(<cs>)}$', 'E'),
('^{(<cs>)(<cs>)}e{(<cs>)(<cs>)(<cs>)(<cs>)}$', 'E'),
('^{(<cs>)(<cs>)(<cs>)}e{(<cs>)(<cs>)(<cs>)(<cs>)}$', 'E'),
('{<cs>}e{(<cs>)}$', 'Q'),
('{<cs>}e{(<cs>)(<cs>)}$', 'Q'),
('{<cs>}e{(<cs>)(<cs>)(<cs>)}$', 'Q'),
('{<cs>}e{(<cs>)(<cs>)(<cs>)(<cs>)}$', 'Q'),
('E', 'e'),
('P', 'p,'),
('T', 't,'),
('K', 'k,'),
('j{@}', 'J'),
('j', 'i'),
('{C|z}J', None),
('^l', 'l;'),
('^m', 'm;'),
('^n', 'n;'),
('l$', 'l,'),
('m$', 'm,'),
('n$', 'n,'),
('l{@|m,|n,|N}', 'l;'),
('{,}l', 'l;'),
('m{@}', 'm;'),
('n{@}', 'n;'),
('l', 'l,'),
('m', 'm,'),
('n', 'n,'),
('N', 'N,'),
(',,', ','),
(',;', None),
(',l,', 'l,'),
(',m,', 'm,'),
(',n,', 'n,'),
(',N,', 'N,'),
('l{m;|n;}', 'l,'),
(';', None),
('^a', '&a'),
('^e', '&e'),
('^i', '&i'),
('^o', '&o'),
('^O', '&O'),
('^u', '&u'),
('^U', '&U'),
('^Q', '&Q'),
('^J', '&J'),
('b', Choseong(B)),
('C', Choseong(C)),
('d', Choseong(D)),
('f', Choseong(P)),
('g', Choseong(H)),
('G', Choseong(G)),
('h', Choseong(H)),
('k,', Jongseong(G)),
('k', Choseong(K)),
('^l', Choseong(L)),
('{,}l', Choseong(L)),
('l,', Jongseong(L)),
('l', Jongseong(L), Choseong(L)),
('m,', Jongseong(M)),
('m', Choseong(M)),
('n,', Jongseong(N)),
('n', Choseong(N)),
('N', Jongseong(NG)),
('p,', Jongseong(B)),
('p', Choseong(P)),
('r', Choseong(L)),
('s', Choseong(S)),
('t,', Jongseong(S)),
('t', Choseong(T)),
('v', Choseong(B)),
('X', Choseong(H)),
('z', Choseong(J)),
('&', Choseong(NG)),
('Ja', Jungseong(YA)),
('Je', Jungseong(YE)),
('Ji', Jungseong(I)),
('Jo', Jungseong(YO)),
('JO', Jungseong(YE)),
('Ju', Jungseong(YU)),
('JU', Jungseong(YU)),
('JQ', Jungseong(YEO)),
('a', Jungseong(A)),
('e', Jungseong(E)),
('i', Jungseong(I)),
('o', Jungseong(O)),
('O', Jungseong(OE)),
('u', Jungseong(WI)),
('U', Jungseong(U)),
('Q', Jungseong(EO)),
('Y', Jungseong(EU)),
])
def normalize(self, string):
return normalize_roman(string, {
u'Ä': u'ä', u'Ç': u'ç', u'Ë': u'ë', u'É': u'é', u'È': u'é',
u'è': u'é', u'Ê': u'é', u'ê': u'é', u'Ï': u'ï', u'Ḯ': u'ï',
u'Ḯ': u'ï', u'Ö': u'ö', u'IJ': u'ij', u'ij': u'ij', u'Ü': u'ü',
u'Ÿ': u'ij', u'ÿ': u'ij'
})
__lang__ = Dutch | 0.316369 | 0.221656 |
from units import unit
from items import item
import time
going = True
coins = 10
player_score = 0
player_round = 0
n_shop_items = 2
n_shop_units = 4
n_roster = 5
roster = []
for i in range(n_roster):
roster.append(0)
shop_units = []
shop_items = []
shop_units = []
for i in range(n_shop_units):
shop_units.append(unit.random_unit())
shop_items = []
for i in range(n_shop_items):
shop_items.append(item.random_item())
print("Coins: "+str(coins))
while going:
time.sleep(0.1)
action = input("Action: ")
if action == "q":
print("Exit")
going = False
elif action == "u":
myunit = unit.Unit("Cow", 2, 3, 5, 2)
print(myunit.to_str())
elif action == "i":
myitem = item.Item("Revolver", 3, 1, 0, 3)
print(myitem.to_str())
elif action == "rsi":
shop_items = []
for i in range(n_shop_items):
shop_items.append(item.random_item())
elif action == "rsu":
shop_units = []
for i in range(n_shop_units):
shop_units.append(unit.random_unit())
elif action == "lsi":
for i in range(len(shop_items)):
if shop_items[i] == 0:
print(" - "+str(i)+" empty")
else:
print(" - "+str(i)+" "+shop_items[i].to_str())
elif action == "lsu":
for i in range(len(shop_units)):
if shop_units[i] == 0:
print(" - "+str(i)+" empty")
else:
print(" - "+str(i)+" "+shop_units[i].to_str())
elif action == "r":
for i in range(n_roster):
if roster[i] != 0:
print(str(i)+" "+roster[i].to_str())
else:
print(str(i)+" empty")
elif action == "c":
print("Coins: "+str(coins))
elif action == "bi":
print("Item store")
for i in range(len(shop_items)):
if shop_items[i] == 0:
print(" - "+str(i)+" empty")
else:
print(" - "+str(i)+" "+shop_items[i].to_str())
item_buy = input("Buy item: ")
if item_buy == "q":
continue
elif shop_items[int(item_buy)] != 0:
if int(item_buy) >= 0 and int(item_buy) < len(shop_items) and coins >= shop_items[int(item_buy)].cost:
for i in range(n_roster):
if roster[i] != 0:
print(str(i)+" "+roster[i].to_str())
else:
print(str(i)+" empty")
action = int(input("Equip: "))
if roster[action] != 0:
coins -= shop_items[int(item_buy)].cost
print("equip")
roster[action].equip(shop_items[int(item_buy)])
shop_items[int(item_buy)] = 0
elif action == "bu":
print("Unit store")
for i in range(len(shop_units)):
if shop_units[i] == 0:
print(" - "+str(i)+" empty")
else:
print(" - "+str(i)+" "+shop_units[i].to_str())
unit_buy = input("Buy unit: ")
if unit_buy == "q":
continue
elif int(unit_buy) >=0 and int(unit_buy) < len(shop_units) and coins >= shop_units[int(unit_buy)].cost:
for i in range(n_roster):
if roster[i] != 0:
print(str(i)+" "+roster[i].to_str())
else:
print(str(i)+" empty")
action = int(input("Place: "))
if roster[action] == 0:
coins -= shop_units[int(unit_buy)].cost
roster[action] = shop_units[int(unit_buy)]
shop_units[int(unit_buy)] = 0 | main.py | from units import unit
from items import item
import time
going = True
coins = 10
player_score = 0
player_round = 0
n_shop_items = 2
n_shop_units = 4
n_roster = 5
roster = []
for i in range(n_roster):
roster.append(0)
shop_units = []
shop_items = []
shop_units = []
for i in range(n_shop_units):
shop_units.append(unit.random_unit())
shop_items = []
for i in range(n_shop_items):
shop_items.append(item.random_item())
print("Coins: "+str(coins))
while going:
time.sleep(0.1)
action = input("Action: ")
if action == "q":
print("Exit")
going = False
elif action == "u":
myunit = unit.Unit("Cow", 2, 3, 5, 2)
print(myunit.to_str())
elif action == "i":
myitem = item.Item("Revolver", 3, 1, 0, 3)
print(myitem.to_str())
elif action == "rsi":
shop_items = []
for i in range(n_shop_items):
shop_items.append(item.random_item())
elif action == "rsu":
shop_units = []
for i in range(n_shop_units):
shop_units.append(unit.random_unit())
elif action == "lsi":
for i in range(len(shop_items)):
if shop_items[i] == 0:
print(" - "+str(i)+" empty")
else:
print(" - "+str(i)+" "+shop_items[i].to_str())
elif action == "lsu":
for i in range(len(shop_units)):
if shop_units[i] == 0:
print(" - "+str(i)+" empty")
else:
print(" - "+str(i)+" "+shop_units[i].to_str())
elif action == "r":
for i in range(n_roster):
if roster[i] != 0:
print(str(i)+" "+roster[i].to_str())
else:
print(str(i)+" empty")
elif action == "c":
print("Coins: "+str(coins))
elif action == "bi":
print("Item store")
for i in range(len(shop_items)):
if shop_items[i] == 0:
print(" - "+str(i)+" empty")
else:
print(" - "+str(i)+" "+shop_items[i].to_str())
item_buy = input("Buy item: ")
if item_buy == "q":
continue
elif shop_items[int(item_buy)] != 0:
if int(item_buy) >= 0 and int(item_buy) < len(shop_items) and coins >= shop_items[int(item_buy)].cost:
for i in range(n_roster):
if roster[i] != 0:
print(str(i)+" "+roster[i].to_str())
else:
print(str(i)+" empty")
action = int(input("Equip: "))
if roster[action] != 0:
coins -= shop_items[int(item_buy)].cost
print("equip")
roster[action].equip(shop_items[int(item_buy)])
shop_items[int(item_buy)] = 0
elif action == "bu":
print("Unit store")
for i in range(len(shop_units)):
if shop_units[i] == 0:
print(" - "+str(i)+" empty")
else:
print(" - "+str(i)+" "+shop_units[i].to_str())
unit_buy = input("Buy unit: ")
if unit_buy == "q":
continue
elif int(unit_buy) >=0 and int(unit_buy) < len(shop_units) and coins >= shop_units[int(unit_buy)].cost:
for i in range(n_roster):
if roster[i] != 0:
print(str(i)+" "+roster[i].to_str())
else:
print(str(i)+" empty")
action = int(input("Place: "))
if roster[action] == 0:
coins -= shop_units[int(unit_buy)].cost
roster[action] = shop_units[int(unit_buy)]
shop_units[int(unit_buy)] = 0 | 0.087474 | 0.238517 |
import pandas as pd
import os
# creating a class named Song
class Song:
def __init__(self, song_name, path): # initializing object
self.song_name = song_name
self.path = path
# defining the function to return song info
def getinfo(self):
#handling none input type
if self.song_name is None:
return("None input type not accepted." +
"\nPlease provide a string input.")
song_name = self.song_name.lower().strip()
# assigning the database to the variable "db"
db = pd.read_csv(self.path)
# creating a list with all song titles
titles = list(db["track_name"].str.lower())
if song_name in titles:
# assinging the index number to variable i
i = titles.index(song_name)
# returning info
return ("\nThe song: '" + db.track_name[i] + "' is made by '" +
db.track_artist[i] + "'.\nIt was released in the album '" +
db.track_album_name[i] + "', in the date " +
db.track_album_release_date[i] + ", and it appeared" +
" in the spotify playlist named " +
db.playlist_name[i] + ", with other song of genre " +
db.playlist_genre[i] + ", and subgenre " +
db.playlist_subgenre[i] + ".\nThe song has " +
str(round(db.tempo[i])) + " bpm and it lasts " +
str(round(db.duration_ms[i] / 1000)) + " seconds.\n")
else:
return (" The song you're looking for" +
" is not present in our database. " +
" Here you are some recommended songs we have:\n " +
" 'Party Rock Anthem',\n " +
" 'Symphony Of Destruction',\n " +
" 'Some Nights'! ")
# defining the function to create a karaoke
def karaoke(self):
#handling none input type
if self.song_name is None:
return("None input type not accepted." +
"\nPlease provide a string input.")
song_name = self.song_name.lower().strip()
db = pd.read_csv(self.path)
# creating a list with all song titles
titles = list(db["track_name"].str.lower())
if song_name in titles:
# assinging the index number to variable i
i = titles.index(song_name)
# returning song URL and song lyrics
return (" \nType this in your favourite browser: 'spotify:track:" +
str(db.track_id[i]) + "' and sing with our lyrics!\n\n " +
db.track_name[i].upper() +
" - " + db.track_artist[i].upper() +
"\n\n" +
str(db.lyrics[i]))
else:
# returning recommendations, if song not present
return ("Not found!\nHere you are" +
" some recommended songs we have:\n" +
"'Party Rock Anthem',\n" +
"'Symphony Of Destruction',\n" +
"'Some Nights'!") | modules/getinfo.py | import pandas as pd
import os
# creating a class named Song
class Song:
def __init__(self, song_name, path): # initializing object
self.song_name = song_name
self.path = path
# defining the function to return song info
def getinfo(self):
#handling none input type
if self.song_name is None:
return("None input type not accepted." +
"\nPlease provide a string input.")
song_name = self.song_name.lower().strip()
# assigning the database to the variable "db"
db = pd.read_csv(self.path)
# creating a list with all song titles
titles = list(db["track_name"].str.lower())
if song_name in titles:
# assinging the index number to variable i
i = titles.index(song_name)
# returning info
return ("\nThe song: '" + db.track_name[i] + "' is made by '" +
db.track_artist[i] + "'.\nIt was released in the album '" +
db.track_album_name[i] + "', in the date " +
db.track_album_release_date[i] + ", and it appeared" +
" in the spotify playlist named " +
db.playlist_name[i] + ", with other song of genre " +
db.playlist_genre[i] + ", and subgenre " +
db.playlist_subgenre[i] + ".\nThe song has " +
str(round(db.tempo[i])) + " bpm and it lasts " +
str(round(db.duration_ms[i] / 1000)) + " seconds.\n")
else:
return (" The song you're looking for" +
" is not present in our database. " +
" Here you are some recommended songs we have:\n " +
" 'Party Rock Anthem',\n " +
" 'Symphony Of Destruction',\n " +
" 'Some Nights'! ")
# defining the function to create a karaoke
def karaoke(self):
#handling none input type
if self.song_name is None:
return("None input type not accepted." +
"\nPlease provide a string input.")
song_name = self.song_name.lower().strip()
db = pd.read_csv(self.path)
# creating a list with all song titles
titles = list(db["track_name"].str.lower())
if song_name in titles:
# assinging the index number to variable i
i = titles.index(song_name)
# returning song URL and song lyrics
return (" \nType this in your favourite browser: 'spotify:track:" +
str(db.track_id[i]) + "' and sing with our lyrics!\n\n " +
db.track_name[i].upper() +
" - " + db.track_artist[i].upper() +
"\n\n" +
str(db.lyrics[i]))
else:
# returning recommendations, if song not present
return ("Not found!\nHere you are" +
" some recommended songs we have:\n" +
"'Party Rock Anthem',\n" +
"'Symphony Of Destruction',\n" +
"'Some Nights'!") | 0.222109 | 0.120129 |
import os
from distutils.util import convert_path
from fnmatch import fnmatchcase
from setuptools import find_packages, setup
standard_exclude = ('*.pyc', '*~', '.*', '*.bak', '*.swp*')
standard_exclude_directories = (
'.*', 'CVS', '_darcs', './build', './dist', 'EGG-INFO', '*.egg-info')
def long_description():
this_directory = os.path.abspath(os.path.dirname(__file__))
with open(os.path.join(this_directory, "README.md"), encoding="utf-8") as f:
return f.read()
def find_package_data(where='.', package='', exclude=standard_exclude,
exclude_directories=standard_exclude_directories):
out = {}
stack = [(convert_path(where), '', package)]
while stack:
where, prefix, package = stack.pop(0)
for name in os.listdir(where):
fn = os.path.join(where, name)
if os.path.isdir(fn):
bad_name = False
for pattern in exclude_directories:
if (fnmatchcase(name, pattern)
or fn.lower() == pattern.lower()):
bad_name = True
break
if bad_name:
continue
if os.path.isfile(os.path.join(fn, '__init__.py')):
if not package:
new_package = name
else:
new_package = package + '.' + name
stack.append((fn, '', new_package))
else:
stack.append((fn, prefix + name + '/', package))
else:
bad_name = False
for pattern in exclude:
if (fnmatchcase(name, pattern)
or fn.lower() == pattern.lower()):
bad_name = True
break
if bad_name:
continue
out.setdefault(package, []).append(prefix + name)
return out
setup(
name='docassemble.lmrhh',
version='2.0.2',
description=__doc__,
long_description=long_description(),
long_description_content_type='text/markdown',
author='<NAME>',
author_email='<EMAIL>',
license='The MIT License (MIT)',
url='https://github.com/lmr-hamburg/docassemble-lmrhh',
packages=find_packages(),
namespace_packages=['docassemble'],
install_requires=[
'requests',
'Flask-Mail',
'google-api-python-client',
'google-auth-oauthlib'
],
zip_safe=False,
package_data=find_package_data(where='docassemble/lmrhh/',
package='docassemble.lmrhh'),
) | setup.py |
import os
from distutils.util import convert_path
from fnmatch import fnmatchcase
from setuptools import find_packages, setup
standard_exclude = ('*.pyc', '*~', '.*', '*.bak', '*.swp*')
standard_exclude_directories = (
'.*', 'CVS', '_darcs', './build', './dist', 'EGG-INFO', '*.egg-info')
def long_description():
this_directory = os.path.abspath(os.path.dirname(__file__))
with open(os.path.join(this_directory, "README.md"), encoding="utf-8") as f:
return f.read()
def find_package_data(where='.', package='', exclude=standard_exclude,
exclude_directories=standard_exclude_directories):
out = {}
stack = [(convert_path(where), '', package)]
while stack:
where, prefix, package = stack.pop(0)
for name in os.listdir(where):
fn = os.path.join(where, name)
if os.path.isdir(fn):
bad_name = False
for pattern in exclude_directories:
if (fnmatchcase(name, pattern)
or fn.lower() == pattern.lower()):
bad_name = True
break
if bad_name:
continue
if os.path.isfile(os.path.join(fn, '__init__.py')):
if not package:
new_package = name
else:
new_package = package + '.' + name
stack.append((fn, '', new_package))
else:
stack.append((fn, prefix + name + '/', package))
else:
bad_name = False
for pattern in exclude:
if (fnmatchcase(name, pattern)
or fn.lower() == pattern.lower()):
bad_name = True
break
if bad_name:
continue
out.setdefault(package, []).append(prefix + name)
return out
setup(
name='docassemble.lmrhh',
version='2.0.2',
description=__doc__,
long_description=long_description(),
long_description_content_type='text/markdown',
author='<NAME>',
author_email='<EMAIL>',
license='The MIT License (MIT)',
url='https://github.com/lmr-hamburg/docassemble-lmrhh',
packages=find_packages(),
namespace_packages=['docassemble'],
install_requires=[
'requests',
'Flask-Mail',
'google-api-python-client',
'google-auth-oauthlib'
],
zip_safe=False,
package_data=find_package_data(where='docassemble/lmrhh/',
package='docassemble.lmrhh'),
) | 0.329392 | 0.120206 |
### Python imports
import pathlib
### Third Party imports
import numpy as np
import pandas as pd
import pytest
### Project imports
from t4.formats import FormatRegistry
from t4.util import QuiltException
### Constants
### Code
def test_buggy_parquet():
"""
Test that T4 avoids crashing on bad Pandas metadata from
old pyarrow libaries.
"""
path = pathlib.Path(__file__).parent
for parquet_handler in FormatRegistry.for_format('parquet'):
with open(path / 'data' / 'buggy_parquet.parquet', 'rb') as bad_parq:
# Make sure this doesn't crash.
parquet_handler.deserialize(bad_parq.read())
def test_formats_for_obj():
arr = np.ndarray(3)
fmt = FormatRegistry.for_obj(arr)[0]
assert 'npz' in fmt.handled_extensions
assert FormatRegistry.for_ext('npy')[0] is fmt
expected_string_fmt_names = ['utf-8', 'unicode', 'json']
found_string_fmt_names = list(f.name for f in FormatRegistry.for_obj('blah'))
assert found_string_fmt_names == expected_string_fmt_names
bytes_obj = fmt.serialize(arr)[0]
assert np.array_equal(fmt.deserialize(bytes_obj, ), arr)
def test_formats_for_ext():
fmt = FormatRegistry.for_ext('json')[0]
assert fmt.serialize({'blah': 'blah'})[0] == b'{"blah": "blah"}'
assert fmt.deserialize(b'{"meow": "mix"}', ) == {'meow': 'mix'}
def test_formats_for_meta():
bytes_fmt = FormatRegistry.for_meta({'target': 'bytes'})[0]
json_fmt = FormatRegistry.for_meta({'target': 'json'})[0]
some_bytes = b'["phlipper", "piglet"]'
assert bytes_fmt.serialize(some_bytes)[0] == some_bytes
assert json_fmt.deserialize(some_bytes) == ['phlipper', 'piglet']
def test_formats_for_format():
bytes_fmt = FormatRegistry.for_format('bytes')[0]
json_fmt = FormatRegistry.for_format('json')[0]
some_bytes = b'["phlipper", "piglet"]'
assert bytes_fmt.serialize(some_bytes)[0] == some_bytes
assert json_fmt.deserialize(some_bytes) == ['phlipper', 'piglet']
def test_formats_serdes():
objects = [
{'blah': 'foo'},
b'blather',
'blip',
]
metadata = [{} for o in objects]
for obj, meta in zip(objects, metadata):
data, format_meta = FormatRegistry.serialize(obj, meta)
meta.update(format_meta)
assert FormatRegistry.deserialize(data, meta) == obj
meta = {}
df1 = pd.DataFrame([[1, 2], [3, 4]])
data, format_meta = FormatRegistry.serialize(df1, meta)
meta.update(format_meta)
df2 = FormatRegistry.deserialize(data, meta)
# we can't really get around this nicely -- if header is used, and header names are numeric,
# once loaded from CSV, header names are now strings. This causes a bad comparison, so we
# cast to int again.
df2.columns = df2.columns.astype(int, copy=False)
assert df1.equals(df2)
def test_formats_csv_read():
csv_file = pathlib.Path(__file__).parent / 'data' / 'csv.csv'
meta = {'format': {'name': 'csv'}}
expected_bytes = b'a,b,c,d\n1,2,3,4\n5,6,7,8\n'
expected_df = FormatRegistry.deserialize(expected_bytes, meta)
df = FormatRegistry.deserialize(csv_file.read_bytes(), meta)
assert df.equals(expected_df)
assert expected_bytes == FormatRegistry.serialize(df, meta)[0]
def test_formats_csv_roundtrip():
test_data = b'9,2,5\n7,2,6\n1,0,1\n'
# roundtrip defaults.
meta = {'format': {'name': 'csv'}}
df1 = FormatRegistry.deserialize(test_data, meta)
bin, format_meta = FormatRegistry.serialize(df1, meta)
meta.update(format_meta)
df2 = FormatRegistry.deserialize(bin, meta)
assert test_data == bin
assert df1.equals(df2)
# interpret first row as header
meta = {'format': {'name': 'csv', 'opts': {'use_header': True}}}
df1 = FormatRegistry.deserialize(test_data, meta)
bin, format_meta = FormatRegistry.serialize(df1, meta)
meta.update(format_meta)
df2 = FormatRegistry.deserialize(bin, meta)
assert test_data == bin
assert df1.equals(df2)
# interpret first column as index
meta = {'format': {'name': 'csv', 'opts': {'use_index': True}}}
df1 = FormatRegistry.deserialize(test_data, meta)
bin, format_meta = FormatRegistry.serialize(df1, meta)
meta.update(format_meta)
df2 = FormatRegistry.deserialize(bin, meta)
assert test_data == bin
assert df1.equals(df2)
# interpret first row as header, and first column as index
meta = {'format': {'name': 'csv', 'opts': {'use_index': True, 'use_header': True}}}
df1 = FormatRegistry.deserialize(test_data, meta)
bin, format_meta = FormatRegistry.serialize(df1, meta)
meta.update(format_meta)
df2 = FormatRegistry.deserialize(bin, meta)
assert test_data == bin
assert df1.equals(df2)
def test_formats_search_fail_notfound():
# a search that finds nothing should raise with an explanation.
class Foo:
pass
bad_kwargs = [
dict(obj_type=Foo, meta=None, ext=None),
dict(obj_type=None, meta={}, ext=None),
dict(obj_type=None, meta=None, ext='.fizz'),
]
for args in bad_kwargs:
with pytest.raises(QuiltException):
FormatRegistry.search(**args) | api/python/tests/test_formats.py |
### Python imports
import pathlib
### Third Party imports
import numpy as np
import pandas as pd
import pytest
### Project imports
from t4.formats import FormatRegistry
from t4.util import QuiltException
### Constants
### Code
def test_buggy_parquet():
"""
Test that T4 avoids crashing on bad Pandas metadata from
old pyarrow libaries.
"""
path = pathlib.Path(__file__).parent
for parquet_handler in FormatRegistry.for_format('parquet'):
with open(path / 'data' / 'buggy_parquet.parquet', 'rb') as bad_parq:
# Make sure this doesn't crash.
parquet_handler.deserialize(bad_parq.read())
def test_formats_for_obj():
arr = np.ndarray(3)
fmt = FormatRegistry.for_obj(arr)[0]
assert 'npz' in fmt.handled_extensions
assert FormatRegistry.for_ext('npy')[0] is fmt
expected_string_fmt_names = ['utf-8', 'unicode', 'json']
found_string_fmt_names = list(f.name for f in FormatRegistry.for_obj('blah'))
assert found_string_fmt_names == expected_string_fmt_names
bytes_obj = fmt.serialize(arr)[0]
assert np.array_equal(fmt.deserialize(bytes_obj, ), arr)
def test_formats_for_ext():
fmt = FormatRegistry.for_ext('json')[0]
assert fmt.serialize({'blah': 'blah'})[0] == b'{"blah": "blah"}'
assert fmt.deserialize(b'{"meow": "mix"}', ) == {'meow': 'mix'}
def test_formats_for_meta():
bytes_fmt = FormatRegistry.for_meta({'target': 'bytes'})[0]
json_fmt = FormatRegistry.for_meta({'target': 'json'})[0]
some_bytes = b'["phlipper", "piglet"]'
assert bytes_fmt.serialize(some_bytes)[0] == some_bytes
assert json_fmt.deserialize(some_bytes) == ['phlipper', 'piglet']
def test_formats_for_format():
bytes_fmt = FormatRegistry.for_format('bytes')[0]
json_fmt = FormatRegistry.for_format('json')[0]
some_bytes = b'["phlipper", "piglet"]'
assert bytes_fmt.serialize(some_bytes)[0] == some_bytes
assert json_fmt.deserialize(some_bytes) == ['phlipper', 'piglet']
def test_formats_serdes():
objects = [
{'blah': 'foo'},
b'blather',
'blip',
]
metadata = [{} for o in objects]
for obj, meta in zip(objects, metadata):
data, format_meta = FormatRegistry.serialize(obj, meta)
meta.update(format_meta)
assert FormatRegistry.deserialize(data, meta) == obj
meta = {}
df1 = pd.DataFrame([[1, 2], [3, 4]])
data, format_meta = FormatRegistry.serialize(df1, meta)
meta.update(format_meta)
df2 = FormatRegistry.deserialize(data, meta)
# we can't really get around this nicely -- if header is used, and header names are numeric,
# once loaded from CSV, header names are now strings. This causes a bad comparison, so we
# cast to int again.
df2.columns = df2.columns.astype(int, copy=False)
assert df1.equals(df2)
def test_formats_csv_read():
csv_file = pathlib.Path(__file__).parent / 'data' / 'csv.csv'
meta = {'format': {'name': 'csv'}}
expected_bytes = b'a,b,c,d\n1,2,3,4\n5,6,7,8\n'
expected_df = FormatRegistry.deserialize(expected_bytes, meta)
df = FormatRegistry.deserialize(csv_file.read_bytes(), meta)
assert df.equals(expected_df)
assert expected_bytes == FormatRegistry.serialize(df, meta)[0]
def test_formats_csv_roundtrip():
test_data = b'9,2,5\n7,2,6\n1,0,1\n'
# roundtrip defaults.
meta = {'format': {'name': 'csv'}}
df1 = FormatRegistry.deserialize(test_data, meta)
bin, format_meta = FormatRegistry.serialize(df1, meta)
meta.update(format_meta)
df2 = FormatRegistry.deserialize(bin, meta)
assert test_data == bin
assert df1.equals(df2)
# interpret first row as header
meta = {'format': {'name': 'csv', 'opts': {'use_header': True}}}
df1 = FormatRegistry.deserialize(test_data, meta)
bin, format_meta = FormatRegistry.serialize(df1, meta)
meta.update(format_meta)
df2 = FormatRegistry.deserialize(bin, meta)
assert test_data == bin
assert df1.equals(df2)
# interpret first column as index
meta = {'format': {'name': 'csv', 'opts': {'use_index': True}}}
df1 = FormatRegistry.deserialize(test_data, meta)
bin, format_meta = FormatRegistry.serialize(df1, meta)
meta.update(format_meta)
df2 = FormatRegistry.deserialize(bin, meta)
assert test_data == bin
assert df1.equals(df2)
# interpret first row as header, and first column as index
meta = {'format': {'name': 'csv', 'opts': {'use_index': True, 'use_header': True}}}
df1 = FormatRegistry.deserialize(test_data, meta)
bin, format_meta = FormatRegistry.serialize(df1, meta)
meta.update(format_meta)
df2 = FormatRegistry.deserialize(bin, meta)
assert test_data == bin
assert df1.equals(df2)
def test_formats_search_fail_notfound():
# a search that finds nothing should raise with an explanation.
class Foo:
pass
bad_kwargs = [
dict(obj_type=Foo, meta=None, ext=None),
dict(obj_type=None, meta={}, ext=None),
dict(obj_type=None, meta=None, ext='.fizz'),
]
for args in bad_kwargs:
with pytest.raises(QuiltException):
FormatRegistry.search(**args) | 0.672224 | 0.44071 |
class parser:
"""Parser for OpenFlow packets
(C) Copyright Stanford University
Date October 2009
Created by ykk
"""
def __init__(self, messages):
"""Initialize
"""
##Internal reference to OpenFlow messages
self.__messages = messages
def describe(self, packet):
"""Parse OpenFlow packet and return string description
"""
dic = self.__messages.peek_from_front("ofp_header", packet)
desc = self.header_describe(dic)
if (dic["type"][0] == self.__messages.get_value("OFPT_HELLO")):
pass
elif (dic["type"][0] == self.__messages.get_value("OFPT_SET_CONFIG")):
desc += "\n\t"+self.switch_config_describe(packet)
elif (dic["type"][0] == self.__messages.get_value("OFPT_FLOW_MOD")):
(fmdic, remaining) = self.__messages.unpack_from_front("ofp_flow_mod", packet)
desc += self.flow_mod_describe(fmdic, "\n\t")
desc += "\n\twith remaining "+str(len(remaining))+" bytes"
else:
desc += "\n\tUnparsed..."
return desc
def flow_mod_describe(self, packet, prefix=""):
"""Parse flow mod and return description
"""
dic = self.__assert_dic(packet, "ofp_flow_mod")
if (dic == None):
return ""
return prefix+\
"Flow_mod of command "+self.__messages.get_enum_name("ofp_flow_mod_command", dic["command"][0])+\
" idle/hard timeout:"+str(dic["idle_timeout"][0])+"/"+str(dic["hard_timeout"][0])+\
self.match_describe(dic, "match.", "\n\t")+\
prefix+\
"(priority:"+str(dic["priority"][0])+\
"/buffer id:"+str(dic["buffer_id"][0])+\
"/out port:"+str(dic["out_port"][0])+")"
def match_describe(self, dic, nameprefix="", prefix=""):
"""Return description for ofp match
"""
return prefix+"match wildcards:%x" % dic[nameprefix+"wildcards"][0]+\
" inport="+str(dic[nameprefix+"in_port"][0])+\
prefix+" "+\
" ethertype="+str(dic[nameprefix+"dl_type"][0])+\
" vlan="+str(dic[nameprefix+"dl_vlan"][0])+\
" "+self.eth_describe(dic[nameprefix+"dl_src"])+"->"+\
self.eth_describe(dic[nameprefix+"dl_dst"])+\
prefix+" "+\
" ipproto="+str(dic[nameprefix+"nw_proto"][0])+\
" "+self.ip_describe(dic[nameprefix+"nw_src"][0])+\
"->"+self.ip_describe(dic[nameprefix+"nw_src"][0])+\
prefix+" "+\
" transport "+str(dic[nameprefix+"tp_src"][0])+\
"->"+str(dic[nameprefix+"tp_dst"][0])
def switch_config_describe(self, packet):
"""Parse OpenFlow switch config and return description
"""
dic = self.__assert_dic(packet, "ofp_switch_config")
if (dic == None):
return ""
return "with flag "+str(self.__messages.get_enum_name("ofp_config_flags", dic["flags"][0]))+\
" and miss send length "+str(dic["miss_send_len"][0])
def header_describe(self, packet):
"""Parse OpenFlow header and return string description
"""
dic = self.__assert_dic(packet, "ofp_header")
if (dic == None):
return ""
return self.__messages.get_enum_name("ofp_type", dic["type"][0])+" packet "+\
"(length:"+str(dic["length"][0])+\
"/xid:"+str(dic["xid"][0])+")"
def ip_describe(self, value):
"""Return string for ip address
"""
desc = ""
for i in range(0,4):
(value, cv) = divmod(value, 256)
desc = str(cv).strip() +"." + desc
return desc
def eth_describe(self, etheraddr):
"""Return string for ethernet address
"""
desc = ""
for value in etheraddr:
desc += ":"+("%x" % value).zfill(2)
return desc[1:]
def __assert_dic(self, packet, typename):
"""Assert and ensure dictionary is given
"""
dic = None
if (isinstance(packet, str)):
dic = self.__messages.peek_from_front(typename, packet)
elif (isinstance(packet, dict)):
dic = packet
return dic | utils/demo/pylibopenflow/of/msg.py | class parser:
"""Parser for OpenFlow packets
(C) Copyright Stanford University
Date October 2009
Created by ykk
"""
def __init__(self, messages):
"""Initialize
"""
##Internal reference to OpenFlow messages
self.__messages = messages
def describe(self, packet):
"""Parse OpenFlow packet and return string description
"""
dic = self.__messages.peek_from_front("ofp_header", packet)
desc = self.header_describe(dic)
if (dic["type"][0] == self.__messages.get_value("OFPT_HELLO")):
pass
elif (dic["type"][0] == self.__messages.get_value("OFPT_SET_CONFIG")):
desc += "\n\t"+self.switch_config_describe(packet)
elif (dic["type"][0] == self.__messages.get_value("OFPT_FLOW_MOD")):
(fmdic, remaining) = self.__messages.unpack_from_front("ofp_flow_mod", packet)
desc += self.flow_mod_describe(fmdic, "\n\t")
desc += "\n\twith remaining "+str(len(remaining))+" bytes"
else:
desc += "\n\tUnparsed..."
return desc
def flow_mod_describe(self, packet, prefix=""):
"""Parse flow mod and return description
"""
dic = self.__assert_dic(packet, "ofp_flow_mod")
if (dic == None):
return ""
return prefix+\
"Flow_mod of command "+self.__messages.get_enum_name("ofp_flow_mod_command", dic["command"][0])+\
" idle/hard timeout:"+str(dic["idle_timeout"][0])+"/"+str(dic["hard_timeout"][0])+\
self.match_describe(dic, "match.", "\n\t")+\
prefix+\
"(priority:"+str(dic["priority"][0])+\
"/buffer id:"+str(dic["buffer_id"][0])+\
"/out port:"+str(dic["out_port"][0])+")"
def match_describe(self, dic, nameprefix="", prefix=""):
"""Return description for ofp match
"""
return prefix+"match wildcards:%x" % dic[nameprefix+"wildcards"][0]+\
" inport="+str(dic[nameprefix+"in_port"][0])+\
prefix+" "+\
" ethertype="+str(dic[nameprefix+"dl_type"][0])+\
" vlan="+str(dic[nameprefix+"dl_vlan"][0])+\
" "+self.eth_describe(dic[nameprefix+"dl_src"])+"->"+\
self.eth_describe(dic[nameprefix+"dl_dst"])+\
prefix+" "+\
" ipproto="+str(dic[nameprefix+"nw_proto"][0])+\
" "+self.ip_describe(dic[nameprefix+"nw_src"][0])+\
"->"+self.ip_describe(dic[nameprefix+"nw_src"][0])+\
prefix+" "+\
" transport "+str(dic[nameprefix+"tp_src"][0])+\
"->"+str(dic[nameprefix+"tp_dst"][0])
def switch_config_describe(self, packet):
"""Parse OpenFlow switch config and return description
"""
dic = self.__assert_dic(packet, "ofp_switch_config")
if (dic == None):
return ""
return "with flag "+str(self.__messages.get_enum_name("ofp_config_flags", dic["flags"][0]))+\
" and miss send length "+str(dic["miss_send_len"][0])
def header_describe(self, packet):
"""Parse OpenFlow header and return string description
"""
dic = self.__assert_dic(packet, "ofp_header")
if (dic == None):
return ""
return self.__messages.get_enum_name("ofp_type", dic["type"][0])+" packet "+\
"(length:"+str(dic["length"][0])+\
"/xid:"+str(dic["xid"][0])+")"
def ip_describe(self, value):
"""Return string for ip address
"""
desc = ""
for i in range(0,4):
(value, cv) = divmod(value, 256)
desc = str(cv).strip() +"." + desc
return desc
def eth_describe(self, etheraddr):
"""Return string for ethernet address
"""
desc = ""
for value in etheraddr:
desc += ":"+("%x" % value).zfill(2)
return desc[1:]
def __assert_dic(self, packet, typename):
"""Assert and ensure dictionary is given
"""
dic = None
if (isinstance(packet, str)):
dic = self.__messages.peek_from_front(typename, packet)
elif (isinstance(packet, dict)):
dic = packet
return dic | 0.459804 | 0.331661 |
import inspect
import os
import random
import string
import time
import pytest
from fixedrec import RecordFile, RecordFileError
DATADIR = os.path.join(os.path.split(__file__)[0], 'data') + '/blockfile-'
def fname(d):
fn_name = inspect.currentframe().f_back.f_code.co_name
return d / fn_name
def test_open(tmpdir):
name = fname(tmpdir)
ks = RecordFile(name, overwrite=True)
assert len(ks) == 0
assert os.stat(name.strpath).st_size == 0
def test_open_small_block(tmpdir):
name = fname(tmpdir)
with pytest.raises(RecordFileError):
RecordFile(name, blocksize=1, overwrite=True)
def test_write(tmpdir):
name = fname(tmpdir)
bf = RecordFile(name, blocksize=4, overwrite=True)
bf[-1] = 'aaaa'
assert bf[0] == 'aaaa'
def test_repr(tmpdir):
name = fname(tmpdir)
fp = RecordFile(name, blocksize=4, overwrite=True)
fp[-1] = 'aaaa'
fp[-1] = 'bbbb'
assert repr(fp) == 'aaaa\nbbbb'
assert str(fp) == 'aaaabbbb'
def test_truncate(tmpdir):
name = fname(tmpdir)
fp = RecordFile(name, blocksize=4, overwrite=True)
fp[-1] = 'aaaa'
fp[-1] = 'bbbb'
fp[-1] = 'cccc'
fp.truncate(1)
assert str(fp) == 'aaaa'
def test_goto_recnum_relative(tmpdir):
name = fname(tmpdir)
fp = RecordFile(name, blocksize=4, overwrite=True)
fp[-1] = 'aaaa'
fp[-1] = 'bbbb'
fp[-1] = 'cccc'
fp.goto_recnum(1)
fp.goto_recnum_relative(1)
assert fp.read() == 'cccc'
fp.goto_recnum(1)
fp.goto_recnum_relative(-1)
assert fp.read() == 'aaaa'
fp.goto_last_record()
fp.goto_recnum_relative(-1)
assert fp.read() == 'bbbb'
def test_swap(tmpdir):
name = fname(tmpdir)
fp = RecordFile(name, blocksize=4, overwrite=True)
fp[-1] = 'aaaa'
fp[-1] = 'bbbb'
fp[-1] = 'cccc'
fp.swap(0, 2)
assert str(fp) == 'ccccbbbbaaaa'
def test_delete(tmpdir):
name = fname(tmpdir)
fp = RecordFile(name, blocksize=4, overwrite=True)
fp[-1] = 'aaaa'
fp[-1] = 'bbbb'
fp[-1] = 'cccc'
del fp[1]
assert str(fp) == 'aaaacccc'
def test_read(tmpdir):
name = fname(tmpdir)
with RecordFile(name, blocksize=4, overwrite=True) as bf:
bf[0] = 'aaaa'
bf[1] = 'bbbb'
bf[2] = 'cccc'
bf[1] = 'xxxx'
with RecordFile(name, blocksize=4) as b:
assert b[0] == 'aaaa'
assert b[1] == 'xxxx'
assert b[2] == 'cccc'
assert len(b) == 3
with RecordFile(name, blocksize=4) as c:
assert list(c) == ['aaaa', 'xxxx', 'cccc']
def test_open_missing_file(tmpdir):
name = fname(tmpdir)
bf = RecordFile(name)
assert os.path.exists(name.strpath)
def test_out_of_bounds_write(tmpdir):
name = fname(tmpdir)
bf = RecordFile(name)
bf[5] = 'abcd'
assert bf[5] == 'abcd'
assert len(bf) == 6
def test_err_blocksize(tmpdir):
name = fname(tmpdir)
with pytest.raises(RecordFileError) as e:
bf = RecordFile(name, blocksize=4, overwrite=True)
bf[-1] = 'a' * 5
assert "didn't fit" in e.value.message
def test_err_no_filename():
with pytest.raises(RecordFileError) as e:
bf = RecordFile("")
assert e.value.message == 'Missing file name.'
@pytest.mark.skipif("1") # skip if running coverage..?
def test_speed(tmpdir): # pragma: no cover
name = fname(tmpdir)
start = time.time()
blocksize = 250
records = 500
randpos = [random.randrange(0, records) for _i in range(100000)]
bf = RecordFile(name, blocksize=blocksize)
data = []
for i in range(blocksize * records):
data.append(random.choice(string.letters))
data = ''.join(data)
created = time.time()
create_step = created - start
assert create_step < 0.5
for i in range(records):
bf[i] = data[i * blocksize:(i + 1) * blocksize]
filled = time.time()
filled_step = filled - created
assert filled_step < 0.02
for i, p in enumerate(randpos[:10000]):
n = i % records
bf[p] = data[n * blocksize:(n + 1) * blocksize]
writet = time.time()
write_step = writet - filled
assert write_step < 0.08 # 125K writes/sec
for i, p in enumerate(randpos):
v = bf[p]
readt = time.time()
read_step = readt - writet
assert read_step < 0.55 # 180K+ reads/sec | tests/test_recordfile.py | import inspect
import os
import random
import string
import time
import pytest
from fixedrec import RecordFile, RecordFileError
DATADIR = os.path.join(os.path.split(__file__)[0], 'data') + '/blockfile-'
def fname(d):
fn_name = inspect.currentframe().f_back.f_code.co_name
return d / fn_name
def test_open(tmpdir):
name = fname(tmpdir)
ks = RecordFile(name, overwrite=True)
assert len(ks) == 0
assert os.stat(name.strpath).st_size == 0
def test_open_small_block(tmpdir):
name = fname(tmpdir)
with pytest.raises(RecordFileError):
RecordFile(name, blocksize=1, overwrite=True)
def test_write(tmpdir):
name = fname(tmpdir)
bf = RecordFile(name, blocksize=4, overwrite=True)
bf[-1] = 'aaaa'
assert bf[0] == 'aaaa'
def test_repr(tmpdir):
name = fname(tmpdir)
fp = RecordFile(name, blocksize=4, overwrite=True)
fp[-1] = 'aaaa'
fp[-1] = 'bbbb'
assert repr(fp) == 'aaaa\nbbbb'
assert str(fp) == 'aaaabbbb'
def test_truncate(tmpdir):
name = fname(tmpdir)
fp = RecordFile(name, blocksize=4, overwrite=True)
fp[-1] = 'aaaa'
fp[-1] = 'bbbb'
fp[-1] = 'cccc'
fp.truncate(1)
assert str(fp) == 'aaaa'
def test_goto_recnum_relative(tmpdir):
name = fname(tmpdir)
fp = RecordFile(name, blocksize=4, overwrite=True)
fp[-1] = 'aaaa'
fp[-1] = 'bbbb'
fp[-1] = 'cccc'
fp.goto_recnum(1)
fp.goto_recnum_relative(1)
assert fp.read() == 'cccc'
fp.goto_recnum(1)
fp.goto_recnum_relative(-1)
assert fp.read() == 'aaaa'
fp.goto_last_record()
fp.goto_recnum_relative(-1)
assert fp.read() == 'bbbb'
def test_swap(tmpdir):
name = fname(tmpdir)
fp = RecordFile(name, blocksize=4, overwrite=True)
fp[-1] = 'aaaa'
fp[-1] = 'bbbb'
fp[-1] = 'cccc'
fp.swap(0, 2)
assert str(fp) == 'ccccbbbbaaaa'
def test_delete(tmpdir):
name = fname(tmpdir)
fp = RecordFile(name, blocksize=4, overwrite=True)
fp[-1] = 'aaaa'
fp[-1] = 'bbbb'
fp[-1] = 'cccc'
del fp[1]
assert str(fp) == 'aaaacccc'
def test_read(tmpdir):
name = fname(tmpdir)
with RecordFile(name, blocksize=4, overwrite=True) as bf:
bf[0] = 'aaaa'
bf[1] = 'bbbb'
bf[2] = 'cccc'
bf[1] = 'xxxx'
with RecordFile(name, blocksize=4) as b:
assert b[0] == 'aaaa'
assert b[1] == 'xxxx'
assert b[2] == 'cccc'
assert len(b) == 3
with RecordFile(name, blocksize=4) as c:
assert list(c) == ['aaaa', 'xxxx', 'cccc']
def test_open_missing_file(tmpdir):
name = fname(tmpdir)
bf = RecordFile(name)
assert os.path.exists(name.strpath)
def test_out_of_bounds_write(tmpdir):
name = fname(tmpdir)
bf = RecordFile(name)
bf[5] = 'abcd'
assert bf[5] == 'abcd'
assert len(bf) == 6
def test_err_blocksize(tmpdir):
name = fname(tmpdir)
with pytest.raises(RecordFileError) as e:
bf = RecordFile(name, blocksize=4, overwrite=True)
bf[-1] = 'a' * 5
assert "didn't fit" in e.value.message
def test_err_no_filename():
with pytest.raises(RecordFileError) as e:
bf = RecordFile("")
assert e.value.message == 'Missing file name.'
@pytest.mark.skipif("1") # skip if running coverage..?
def test_speed(tmpdir): # pragma: no cover
name = fname(tmpdir)
start = time.time()
blocksize = 250
records = 500
randpos = [random.randrange(0, records) for _i in range(100000)]
bf = RecordFile(name, blocksize=blocksize)
data = []
for i in range(blocksize * records):
data.append(random.choice(string.letters))
data = ''.join(data)
created = time.time()
create_step = created - start
assert create_step < 0.5
for i in range(records):
bf[i] = data[i * blocksize:(i + 1) * blocksize]
filled = time.time()
filled_step = filled - created
assert filled_step < 0.02
for i, p in enumerate(randpos[:10000]):
n = i % records
bf[p] = data[n * blocksize:(n + 1) * blocksize]
writet = time.time()
write_step = writet - filled
assert write_step < 0.08 # 125K writes/sec
for i, p in enumerate(randpos):
v = bf[p]
readt = time.time()
read_step = readt - writet
assert read_step < 0.55 # 180K+ reads/sec | 0.231875 | 0.40987 |
from inspect import cleandoc
from testfixtures import compare
from mlinspect._pipeline_inspector import PipelineInspector
from mlinspect.inspections import CompletenessOfColumns
def test_completeness_merge():
"""
Tests whether CompletenessOfColumns works for joins
"""
test_code = cleandoc("""
import numpy as np
import pandas as pd
df_a = pd.DataFrame({'A': ['cat_a', None, 'cat_a', 'cat_c', None], 'B': [1, 2, 4, 5, 7]})
df_b = pd.DataFrame({'B': [1, 2, 3, 4, np.nan], 'C': [1, 5, 4, 11, None]})
df_merged = df_a.merge(df_b, on='B')
""")
inspector_result = PipelineInspector \
.on_pipeline_from_string(test_code) \
.add_required_inspection(CompletenessOfColumns(['A', 'B'])) \
.execute()
inspection_results = list(inspector_result.dag_node_to_inspection_results.values())
completeness_output = inspection_results[0][CompletenessOfColumns(['A', 'B'])]
expected_completeness = {'A': 0.6, 'B': 1.0}
compare(completeness_output, expected_completeness)
completeness_output = inspection_results[1][CompletenessOfColumns(['A', 'B'])]
expected_completeness = {'B': 0.8}
compare(completeness_output, expected_completeness)
completeness_output = inspection_results[2][CompletenessOfColumns(['A', 'B'])]
expected_completeness = {'A': 2/3, 'B': 1.0}
compare(completeness_output, expected_completeness)
def test_completeness_projection():
"""
Tests whether CompletenessOfColumns works for projections
"""
test_code = cleandoc("""
import pandas as pd
import numpy as np
pandas_df = pd.DataFrame({'A': ['cat_a', 'cat_b', None, 'cat_c', 'cat_b'],
'B': [1, None, np.nan, None, 7], 'C': [2, 2, 10, 5, 7]})
pandas_df = pandas_df[['B', 'C']]
pandas_df = pandas_df[['C']]
""")
inspector_result = PipelineInspector \
.on_pipeline_from_string(test_code) \
.add_required_inspection(CompletenessOfColumns(['A', 'B'])) \
.execute()
inspection_results = list(inspector_result.dag_node_to_inspection_results.values())
completeness_output = inspection_results[0][CompletenessOfColumns(['A', 'B'])]
expected_completeness = {'A': 0.8, 'B': 0.4}
compare(completeness_output, expected_completeness)
completeness_output = inspection_results[1][CompletenessOfColumns(['A', 'B'])]
expected_completeness = {'B': 0.4}
compare(completeness_output, expected_completeness)
completeness_output = inspection_results[2][CompletenessOfColumns(['A', 'B'])]
expected_completeness = {}
compare(completeness_output, expected_completeness) | test/inspections/test_completeness_of_columns.py | from inspect import cleandoc
from testfixtures import compare
from mlinspect._pipeline_inspector import PipelineInspector
from mlinspect.inspections import CompletenessOfColumns
def test_completeness_merge():
"""
Tests whether CompletenessOfColumns works for joins
"""
test_code = cleandoc("""
import numpy as np
import pandas as pd
df_a = pd.DataFrame({'A': ['cat_a', None, 'cat_a', 'cat_c', None], 'B': [1, 2, 4, 5, 7]})
df_b = pd.DataFrame({'B': [1, 2, 3, 4, np.nan], 'C': [1, 5, 4, 11, None]})
df_merged = df_a.merge(df_b, on='B')
""")
inspector_result = PipelineInspector \
.on_pipeline_from_string(test_code) \
.add_required_inspection(CompletenessOfColumns(['A', 'B'])) \
.execute()
inspection_results = list(inspector_result.dag_node_to_inspection_results.values())
completeness_output = inspection_results[0][CompletenessOfColumns(['A', 'B'])]
expected_completeness = {'A': 0.6, 'B': 1.0}
compare(completeness_output, expected_completeness)
completeness_output = inspection_results[1][CompletenessOfColumns(['A', 'B'])]
expected_completeness = {'B': 0.8}
compare(completeness_output, expected_completeness)
completeness_output = inspection_results[2][CompletenessOfColumns(['A', 'B'])]
expected_completeness = {'A': 2/3, 'B': 1.0}
compare(completeness_output, expected_completeness)
def test_completeness_projection():
"""
Tests whether CompletenessOfColumns works for projections
"""
test_code = cleandoc("""
import pandas as pd
import numpy as np
pandas_df = pd.DataFrame({'A': ['cat_a', 'cat_b', None, 'cat_c', 'cat_b'],
'B': [1, None, np.nan, None, 7], 'C': [2, 2, 10, 5, 7]})
pandas_df = pandas_df[['B', 'C']]
pandas_df = pandas_df[['C']]
""")
inspector_result = PipelineInspector \
.on_pipeline_from_string(test_code) \
.add_required_inspection(CompletenessOfColumns(['A', 'B'])) \
.execute()
inspection_results = list(inspector_result.dag_node_to_inspection_results.values())
completeness_output = inspection_results[0][CompletenessOfColumns(['A', 'B'])]
expected_completeness = {'A': 0.8, 'B': 0.4}
compare(completeness_output, expected_completeness)
completeness_output = inspection_results[1][CompletenessOfColumns(['A', 'B'])]
expected_completeness = {'B': 0.4}
compare(completeness_output, expected_completeness)
completeness_output = inspection_results[2][CompletenessOfColumns(['A', 'B'])]
expected_completeness = {}
compare(completeness_output, expected_completeness) | 0.660172 | 0.467879 |
import os, sys
from pip.req import InstallRequirement, RequirementSet
from pip.req import parse_requirements
from pip.log import logger
from pip.locations import build_prefix, src_prefix
from pip.basecommand import Command
from pip.index import PackageFinder
from pip.exceptions import InstallationError
class InstallCommand(Command):
name = 'install'
usage = '%prog [OPTIONS] PACKAGE_NAMES...'
summary = 'Install packages'
bundle = False
def __init__(self):
super(InstallCommand, self).__init__()
self.parser.add_option(
'-e', '--editable',
dest='editables',
action='append',
default=[],
metavar='VCS+REPOS_URL[@REV]#egg=PACKAGE',
help='Install a package directly from a checkout. Source will be checked '
'out into src/PACKAGE (lower-case) and installed in-place (using '
'setup.py develop). You can run this on an existing directory/checkout (like '
'pip install -e src/mycheckout). This option may be provided multiple times. '
'Possible values for VCS are: svn, git, hg and bzr.')
self.parser.add_option(
'-r', '--requirement',
dest='requirements',
action='append',
default=[],
metavar='FILENAME',
help='Install all the packages listed in the given requirements file. '
'This option can be used multiple times.')
self.parser.add_option(
'-f', '--find-links',
dest='find_links',
action='append',
default=[],
metavar='URL',
help='URL to look for packages at')
self.parser.add_option(
'-i', '--index-url', '--pypi-url',
dest='index_url',
metavar='URL',
default='http://pypi.python.org/simple/',
help='Base URL of Python Package Index (default %default)')
self.parser.add_option(
'--extra-index-url',
dest='extra_index_urls',
metavar='URL',
action='append',
default=[],
help='Extra URLs of package indexes to use in addition to --index-url')
self.parser.add_option(
'--no-index',
dest='no_index',
action='store_true',
default=False,
help='Ignore package index (only looking at --find-links URLs instead)')
self.parser.add_option(
'-M', '--use-mirrors',
dest='use_mirrors',
action='store_true',
default=False,
help='Use the PyPI mirrors as a fallback in case the main index is down.')
self.parser.add_option(
'--mirrors',
dest='mirrors',
metavar='URL',
action='append',
default=[],
help='Specific mirror URLs to query when --use-mirrors is used')
self.parser.add_option(
'-b', '--build', '--build-dir', '--build-directory',
dest='build_dir',
metavar='DIR',
default=None,
help='Unpack packages into DIR (default %s) and build from there' % build_prefix)
self.parser.add_option(
'-d', '--download', '--download-dir', '--download-directory',
dest='download_dir',
metavar='DIR',
default=None,
help='Download packages into DIR instead of installing them')
self.parser.add_option(
'--download-cache',
dest='download_cache',
metavar='DIR',
default=None,
help='Cache downloaded packages in DIR')
self.parser.add_option(
'--src', '--source', '--source-dir', '--source-directory',
dest='src_dir',
metavar='DIR',
default=None,
help='Check out --editable packages into DIR (default %s)' % src_prefix)
self.parser.add_option(
'-U', '--upgrade',
dest='upgrade',
action='store_true',
help='Upgrade all packages to the newest available version')
self.parser.add_option(
'-I', '--ignore-installed',
dest='ignore_installed',
action='store_true',
help='Ignore the installed packages (reinstalling instead)')
self.parser.add_option(
'--no-deps', '--no-dependencies',
dest='ignore_dependencies',
action='store_true',
default=False,
help='Ignore package dependencies')
self.parser.add_option(
'--no-install',
dest='no_install',
action='store_true',
help="Download and unpack all packages, but don't actually install them")
self.parser.add_option(
'--no-download',
dest='no_download',
action="store_true",
help="Don't download any packages, just install the ones already downloaded "
"(completes an install run with --no-install)")
self.parser.add_option(
'--install-option',
dest='install_options',
action='append',
help="Extra arguments to be supplied to the setup.py install "
"command (use like --install-option=\"--install-scripts=/usr/local/bin\"). "
"Use multiple --install-option options to pass multiple options to setup.py install. "
"If you are using an option with a directory path, be sure to use absolute path.")
self.parser.add_option(
'--global-option',
dest='global_options',
action='append',
help="Extra global options to be supplied to the setup.py"
"call before the install command")
self.parser.add_option(
'--user',
dest='use_user_site',
action='store_true',
help='Install to user-site')
def _build_package_finder(self, options, index_urls):
"""
Create a package finder appropriate to this install command.
This method is meant to be overridden by subclasses, not
called directly.
"""
return PackageFinder(find_links=options.find_links,
index_urls=index_urls,
use_mirrors=options.use_mirrors,
mirrors=options.mirrors)
def run(self, options, args):
if not options.build_dir:
options.build_dir = build_prefix
if not options.src_dir:
options.src_dir = src_prefix
if options.download_dir:
options.no_install = True
options.ignore_installed = True
options.build_dir = os.path.abspath(options.build_dir)
options.src_dir = os.path.abspath(options.src_dir)
install_options = options.install_options or []
if options.use_user_site:
install_options.append('--user')
global_options = options.global_options or []
index_urls = [options.index_url] + options.extra_index_urls
if options.no_index:
logger.notify('Ignoring indexes: %s' % ','.join(index_urls))
index_urls = []
finder = self._build_package_finder(options, index_urls)
requirement_set = RequirementSet(
build_dir=options.build_dir,
src_dir=options.src_dir,
download_dir=options.download_dir,
download_cache=options.download_cache,
upgrade=options.upgrade,
ignore_installed=options.ignore_installed,
ignore_dependencies=options.ignore_dependencies)
for name in args:
requirement_set.add_requirement(
InstallRequirement.from_line(name, None))
for name in options.editables:
requirement_set.add_requirement(
InstallRequirement.from_editable(name, default_vcs=options.default_vcs))
for filename in options.requirements:
for req in parse_requirements(filename, finder=finder, options=options):
requirement_set.add_requirement(req)
if not requirement_set.has_requirements:
if options.find_links:
raise InstallationError('You must give at least one '
'requirement to %s (maybe you meant "pip install %s"?)'
% (self.name, " ".join(options.find_links)))
raise InstallationError('You must give at least one requirement '
'to %(name)s (see "pip help %(name)s")' % dict(name=self.name))
if (options.use_user_site and
sys.version_info < (2, 6)):
raise InstallationError('--user is only supported in Python version 2.6 and newer')
import setuptools
if (options.use_user_site and
requirement_set.has_editables and
not getattr(setuptools, '_distribute', False)):
raise InstallationError('--user --editable not supported with setuptools, use distribute')
if not options.no_download:
requirement_set.prepare_files(finder, force_root_egg_info=self.bundle, bundle=self.bundle)
else:
requirement_set.locate_files()
if not options.no_install and not self.bundle:
requirement_set.install(install_options, global_options)
installed = ' '.join([req.name for req in
requirement_set.successfully_installed])
if installed:
logger.notify('Successfully installed %s' % installed)
elif not self.bundle:
downloaded = ' '.join([req.name for req in
requirement_set.successfully_downloaded])
if downloaded:
logger.notify('Successfully downloaded %s' % downloaded)
elif self.bundle:
requirement_set.create_bundle(self.bundle_filename)
logger.notify('Created bundle in %s' % self.bundle_filename)
# Clean up
if not options.no_install:
requirement_set.cleanup_files(bundle=self.bundle)
return requirement_set
InstallCommand() | docs/docs_env/Lib/site-packages/pip-1.0-py2.5.egg/pip/commands/install.py | import os, sys
from pip.req import InstallRequirement, RequirementSet
from pip.req import parse_requirements
from pip.log import logger
from pip.locations import build_prefix, src_prefix
from pip.basecommand import Command
from pip.index import PackageFinder
from pip.exceptions import InstallationError
class InstallCommand(Command):
name = 'install'
usage = '%prog [OPTIONS] PACKAGE_NAMES...'
summary = 'Install packages'
bundle = False
def __init__(self):
super(InstallCommand, self).__init__()
self.parser.add_option(
'-e', '--editable',
dest='editables',
action='append',
default=[],
metavar='VCS+REPOS_URL[@REV]#egg=PACKAGE',
help='Install a package directly from a checkout. Source will be checked '
'out into src/PACKAGE (lower-case) and installed in-place (using '
'setup.py develop). You can run this on an existing directory/checkout (like '
'pip install -e src/mycheckout). This option may be provided multiple times. '
'Possible values for VCS are: svn, git, hg and bzr.')
self.parser.add_option(
'-r', '--requirement',
dest='requirements',
action='append',
default=[],
metavar='FILENAME',
help='Install all the packages listed in the given requirements file. '
'This option can be used multiple times.')
self.parser.add_option(
'-f', '--find-links',
dest='find_links',
action='append',
default=[],
metavar='URL',
help='URL to look for packages at')
self.parser.add_option(
'-i', '--index-url', '--pypi-url',
dest='index_url',
metavar='URL',
default='http://pypi.python.org/simple/',
help='Base URL of Python Package Index (default %default)')
self.parser.add_option(
'--extra-index-url',
dest='extra_index_urls',
metavar='URL',
action='append',
default=[],
help='Extra URLs of package indexes to use in addition to --index-url')
self.parser.add_option(
'--no-index',
dest='no_index',
action='store_true',
default=False,
help='Ignore package index (only looking at --find-links URLs instead)')
self.parser.add_option(
'-M', '--use-mirrors',
dest='use_mirrors',
action='store_true',
default=False,
help='Use the PyPI mirrors as a fallback in case the main index is down.')
self.parser.add_option(
'--mirrors',
dest='mirrors',
metavar='URL',
action='append',
default=[],
help='Specific mirror URLs to query when --use-mirrors is used')
self.parser.add_option(
'-b', '--build', '--build-dir', '--build-directory',
dest='build_dir',
metavar='DIR',
default=None,
help='Unpack packages into DIR (default %s) and build from there' % build_prefix)
self.parser.add_option(
'-d', '--download', '--download-dir', '--download-directory',
dest='download_dir',
metavar='DIR',
default=None,
help='Download packages into DIR instead of installing them')
self.parser.add_option(
'--download-cache',
dest='download_cache',
metavar='DIR',
default=None,
help='Cache downloaded packages in DIR')
self.parser.add_option(
'--src', '--source', '--source-dir', '--source-directory',
dest='src_dir',
metavar='DIR',
default=None,
help='Check out --editable packages into DIR (default %s)' % src_prefix)
self.parser.add_option(
'-U', '--upgrade',
dest='upgrade',
action='store_true',
help='Upgrade all packages to the newest available version')
self.parser.add_option(
'-I', '--ignore-installed',
dest='ignore_installed',
action='store_true',
help='Ignore the installed packages (reinstalling instead)')
self.parser.add_option(
'--no-deps', '--no-dependencies',
dest='ignore_dependencies',
action='store_true',
default=False,
help='Ignore package dependencies')
self.parser.add_option(
'--no-install',
dest='no_install',
action='store_true',
help="Download and unpack all packages, but don't actually install them")
self.parser.add_option(
'--no-download',
dest='no_download',
action="store_true",
help="Don't download any packages, just install the ones already downloaded "
"(completes an install run with --no-install)")
self.parser.add_option(
'--install-option',
dest='install_options',
action='append',
help="Extra arguments to be supplied to the setup.py install "
"command (use like --install-option=\"--install-scripts=/usr/local/bin\"). "
"Use multiple --install-option options to pass multiple options to setup.py install. "
"If you are using an option with a directory path, be sure to use absolute path.")
self.parser.add_option(
'--global-option',
dest='global_options',
action='append',
help="Extra global options to be supplied to the setup.py"
"call before the install command")
self.parser.add_option(
'--user',
dest='use_user_site',
action='store_true',
help='Install to user-site')
def _build_package_finder(self, options, index_urls):
"""
Create a package finder appropriate to this install command.
This method is meant to be overridden by subclasses, not
called directly.
"""
return PackageFinder(find_links=options.find_links,
index_urls=index_urls,
use_mirrors=options.use_mirrors,
mirrors=options.mirrors)
def run(self, options, args):
if not options.build_dir:
options.build_dir = build_prefix
if not options.src_dir:
options.src_dir = src_prefix
if options.download_dir:
options.no_install = True
options.ignore_installed = True
options.build_dir = os.path.abspath(options.build_dir)
options.src_dir = os.path.abspath(options.src_dir)
install_options = options.install_options or []
if options.use_user_site:
install_options.append('--user')
global_options = options.global_options or []
index_urls = [options.index_url] + options.extra_index_urls
if options.no_index:
logger.notify('Ignoring indexes: %s' % ','.join(index_urls))
index_urls = []
finder = self._build_package_finder(options, index_urls)
requirement_set = RequirementSet(
build_dir=options.build_dir,
src_dir=options.src_dir,
download_dir=options.download_dir,
download_cache=options.download_cache,
upgrade=options.upgrade,
ignore_installed=options.ignore_installed,
ignore_dependencies=options.ignore_dependencies)
for name in args:
requirement_set.add_requirement(
InstallRequirement.from_line(name, None))
for name in options.editables:
requirement_set.add_requirement(
InstallRequirement.from_editable(name, default_vcs=options.default_vcs))
for filename in options.requirements:
for req in parse_requirements(filename, finder=finder, options=options):
requirement_set.add_requirement(req)
if not requirement_set.has_requirements:
if options.find_links:
raise InstallationError('You must give at least one '
'requirement to %s (maybe you meant "pip install %s"?)'
% (self.name, " ".join(options.find_links)))
raise InstallationError('You must give at least one requirement '
'to %(name)s (see "pip help %(name)s")' % dict(name=self.name))
if (options.use_user_site and
sys.version_info < (2, 6)):
raise InstallationError('--user is only supported in Python version 2.6 and newer')
import setuptools
if (options.use_user_site and
requirement_set.has_editables and
not getattr(setuptools, '_distribute', False)):
raise InstallationError('--user --editable not supported with setuptools, use distribute')
if not options.no_download:
requirement_set.prepare_files(finder, force_root_egg_info=self.bundle, bundle=self.bundle)
else:
requirement_set.locate_files()
if not options.no_install and not self.bundle:
requirement_set.install(install_options, global_options)
installed = ' '.join([req.name for req in
requirement_set.successfully_installed])
if installed:
logger.notify('Successfully installed %s' % installed)
elif not self.bundle:
downloaded = ' '.join([req.name for req in
requirement_set.successfully_downloaded])
if downloaded:
logger.notify('Successfully downloaded %s' % downloaded)
elif self.bundle:
requirement_set.create_bundle(self.bundle_filename)
logger.notify('Created bundle in %s' % self.bundle_filename)
# Clean up
if not options.no_install:
requirement_set.cleanup_files(bundle=self.bundle)
return requirement_set
InstallCommand() | 0.341253 | 0.069795 |
from __future__ import absolute_import
import bson
import mock
from st2common.constants.triggers import TIMER_TRIGGER_TYPES
from st2common.models.db.trigger import TriggerDB
from st2common.models.system.common import ResourceReference
from st2common.persistence.trigger import TriggerType
from st2common.persistence.trigger import Trigger
from st2reactor.timer.base import St2Timer
from st2tests.base import CleanDbTestCase
class St2TimerTestCase(CleanDbTestCase):
def test_trigger_types_are_registered_on_start(self):
timer = St2Timer()
timer._scheduler = mock.Mock()
# Verify there are no TriggerType in the db when we start
self.assertItemsEqual(TriggerType.get_all(), [])
timer.start()
# Verify TriggerType objects have been created
trigger_type_dbs = TriggerType.get_all()
self.assertEqual(len(trigger_type_dbs), len(TIMER_TRIGGER_TYPES))
timer_trigger_type_refs = list(TIMER_TRIGGER_TYPES.keys())
for trigger_type in trigger_type_dbs:
ref = ResourceReference(pack=trigger_type.pack, name=trigger_type.name).ref
self.assertIn(ref, timer_trigger_type_refs)
def test_existing_rules_are_loaded_on_start(self):
# Assert that we dispatch message for every existing Trigger object
St2Timer._handle_create_trigger = mock.Mock()
timer = St2Timer()
timer._scheduler = mock.Mock()
timer._trigger_watcher.run = mock.Mock()
# Verify there are no Trigger and TriggerType in the db wh:w
self.assertItemsEqual(Trigger.get_all(), [])
self.assertItemsEqual(TriggerType.get_all(), [])
# Add a dummy timer Trigger object
type_ = list(TIMER_TRIGGER_TYPES.keys())[0]
parameters = {'unit': 'seconds', 'delta': 1000}
trigger_db = TriggerDB(id=bson.ObjectId(), name='test_trigger_1', pack='dummy',
type=type_, parameters=parameters)
trigger_db = Trigger.add_or_update(trigger_db)
# Verify object has been added
self.assertEqual(len(Trigger.get_all()), 1)
timer.start()
timer._trigger_watcher._load_thread.wait()
# Verify handlers are called
timer._handle_create_trigger.assert_called_with(trigger_db)
@mock.patch('st2common.transport.reactor.TriggerDispatcher.dispatch')
def test_timer_trace_tag_creation(self, dispatch_mock):
timer = St2Timer()
timer._scheduler = mock.Mock()
timer._trigger_watcher = mock.Mock()
# Add a dummy timer Trigger object
type_ = list(TIMER_TRIGGER_TYPES.keys())[0]
parameters = {'unit': 'seconds', 'delta': 1}
trigger_db = TriggerDB(name='test_trigger_1', pack='dummy', type=type_,
parameters=parameters)
timer.add_trigger(trigger_db)
timer._emit_trigger_instance(trigger=trigger_db.to_serializable_dict())
self.assertEqual(dispatch_mock.call_args[1]['trace_context'].trace_tag,
'%s-%s' % (TIMER_TRIGGER_TYPES[type_]['name'], trigger_db.name)) | st2reactor/tests/unit/test_timer.py |
from __future__ import absolute_import
import bson
import mock
from st2common.constants.triggers import TIMER_TRIGGER_TYPES
from st2common.models.db.trigger import TriggerDB
from st2common.models.system.common import ResourceReference
from st2common.persistence.trigger import TriggerType
from st2common.persistence.trigger import Trigger
from st2reactor.timer.base import St2Timer
from st2tests.base import CleanDbTestCase
class St2TimerTestCase(CleanDbTestCase):
def test_trigger_types_are_registered_on_start(self):
timer = St2Timer()
timer._scheduler = mock.Mock()
# Verify there are no TriggerType in the db when we start
self.assertItemsEqual(TriggerType.get_all(), [])
timer.start()
# Verify TriggerType objects have been created
trigger_type_dbs = TriggerType.get_all()
self.assertEqual(len(trigger_type_dbs), len(TIMER_TRIGGER_TYPES))
timer_trigger_type_refs = list(TIMER_TRIGGER_TYPES.keys())
for trigger_type in trigger_type_dbs:
ref = ResourceReference(pack=trigger_type.pack, name=trigger_type.name).ref
self.assertIn(ref, timer_trigger_type_refs)
def test_existing_rules_are_loaded_on_start(self):
# Assert that we dispatch message for every existing Trigger object
St2Timer._handle_create_trigger = mock.Mock()
timer = St2Timer()
timer._scheduler = mock.Mock()
timer._trigger_watcher.run = mock.Mock()
# Verify there are no Trigger and TriggerType in the db wh:w
self.assertItemsEqual(Trigger.get_all(), [])
self.assertItemsEqual(TriggerType.get_all(), [])
# Add a dummy timer Trigger object
type_ = list(TIMER_TRIGGER_TYPES.keys())[0]
parameters = {'unit': 'seconds', 'delta': 1000}
trigger_db = TriggerDB(id=bson.ObjectId(), name='test_trigger_1', pack='dummy',
type=type_, parameters=parameters)
trigger_db = Trigger.add_or_update(trigger_db)
# Verify object has been added
self.assertEqual(len(Trigger.get_all()), 1)
timer.start()
timer._trigger_watcher._load_thread.wait()
# Verify handlers are called
timer._handle_create_trigger.assert_called_with(trigger_db)
@mock.patch('st2common.transport.reactor.TriggerDispatcher.dispatch')
def test_timer_trace_tag_creation(self, dispatch_mock):
timer = St2Timer()
timer._scheduler = mock.Mock()
timer._trigger_watcher = mock.Mock()
# Add a dummy timer Trigger object
type_ = list(TIMER_TRIGGER_TYPES.keys())[0]
parameters = {'unit': 'seconds', 'delta': 1}
trigger_db = TriggerDB(name='test_trigger_1', pack='dummy', type=type_,
parameters=parameters)
timer.add_trigger(trigger_db)
timer._emit_trigger_instance(trigger=trigger_db.to_serializable_dict())
self.assertEqual(dispatch_mock.call_args[1]['trace_context'].trace_tag,
'%s-%s' % (TIMER_TRIGGER_TYPES[type_]['name'], trigger_db.name)) | 0.758332 | 0.267996 |
from django.conf import settings
from django.shortcuts import redirect
from django.urls import reverse, reverse_lazy
from django.utils.http import is_safe_url
from django.utils.translation import gettext_lazy as _
from django.views.generic import FormView, TemplateView
from mtp_common.auth.api_client import get_api_session
from security import hmpps_employee_flag, not_hmpps_employee_flag
from security.forms.eligibility import HMPPSEmployeeForm
from security.utils import save_user_flags
class HMPPSEmployeeView(FormView):
title = _('Confirm your eligibility')
template_name = 'hmpps-employee.html'
form_class = HMPPSEmployeeForm
success_url = reverse_lazy(settings.LOGIN_REDIRECT_URL)
not_employee_url = reverse_lazy('security:not_hmpps_employee')
def dispatch(self, request, *args, **kwargs):
if not request.can_access_security:
return redirect(self.success_url)
flags = request.user.user_data.get('flags') or []
if hmpps_employee_flag in flags:
return redirect(self.success_url)
if not_hmpps_employee_flag in flags:
return redirect(self.not_employee_url)
request.cannot_navigate_away = True
return super().dispatch(request, *args, **kwargs)
def get_initial(self):
initial = super().get_initial()
initial['next'] = self.request.META.get('HTTP_REFERER', '')
return initial
def form_valid(self, form):
api_session = get_api_session(self.request)
confirmation = form.cleaned_data['confirmation']
if confirmation == 'yes':
save_user_flags(self.request, hmpps_employee_flag, api_session)
success_url = form.cleaned_data['next']
if success_url and is_safe_url(success_url, allowed_hosts=self.request.get_host()):
self.success_url = success_url
return super().form_valid(form)
else:
save_user_flags(self.request, not_hmpps_employee_flag, api_session)
api_session.delete('/users/%s/' % self.request.user.username)
self.request.session.flush()
return redirect(self.not_employee_url)
class NotHMPPSEmployeeView(TemplateView):
title = _('You can’t use this tool')
template_name = 'not-hmpps-employee.html'
def dispatch(self, request, *args, **kwargs):
flags = request.user.user_data.get('flags') or []
if request.user.is_authenticated and not_hmpps_employee_flag not in flags:
return redirect(reverse(settings.LOGIN_REDIRECT_URL))
request.cannot_navigate_away = True
return super().dispatch(request, *args, **kwargs) | mtp_noms_ops/apps/security/views/eligibility.py | from django.conf import settings
from django.shortcuts import redirect
from django.urls import reverse, reverse_lazy
from django.utils.http import is_safe_url
from django.utils.translation import gettext_lazy as _
from django.views.generic import FormView, TemplateView
from mtp_common.auth.api_client import get_api_session
from security import hmpps_employee_flag, not_hmpps_employee_flag
from security.forms.eligibility import HMPPSEmployeeForm
from security.utils import save_user_flags
class HMPPSEmployeeView(FormView):
title = _('Confirm your eligibility')
template_name = 'hmpps-employee.html'
form_class = HMPPSEmployeeForm
success_url = reverse_lazy(settings.LOGIN_REDIRECT_URL)
not_employee_url = reverse_lazy('security:not_hmpps_employee')
def dispatch(self, request, *args, **kwargs):
if not request.can_access_security:
return redirect(self.success_url)
flags = request.user.user_data.get('flags') or []
if hmpps_employee_flag in flags:
return redirect(self.success_url)
if not_hmpps_employee_flag in flags:
return redirect(self.not_employee_url)
request.cannot_navigate_away = True
return super().dispatch(request, *args, **kwargs)
def get_initial(self):
initial = super().get_initial()
initial['next'] = self.request.META.get('HTTP_REFERER', '')
return initial
def form_valid(self, form):
api_session = get_api_session(self.request)
confirmation = form.cleaned_data['confirmation']
if confirmation == 'yes':
save_user_flags(self.request, hmpps_employee_flag, api_session)
success_url = form.cleaned_data['next']
if success_url and is_safe_url(success_url, allowed_hosts=self.request.get_host()):
self.success_url = success_url
return super().form_valid(form)
else:
save_user_flags(self.request, not_hmpps_employee_flag, api_session)
api_session.delete('/users/%s/' % self.request.user.username)
self.request.session.flush()
return redirect(self.not_employee_url)
class NotHMPPSEmployeeView(TemplateView):
title = _('You can’t use this tool')
template_name = 'not-hmpps-employee.html'
def dispatch(self, request, *args, **kwargs):
flags = request.user.user_data.get('flags') or []
if request.user.is_authenticated and not_hmpps_employee_flag not in flags:
return redirect(reverse(settings.LOGIN_REDIRECT_URL))
request.cannot_navigate_away = True
return super().dispatch(request, *args, **kwargs) | 0.393152 | 0.064271 |
import os
import urllib.request
from PIL import Image
import numpy as np
import tensorflow as tf
import tensorflow_hub as hub
import config
def save_image_from_message(message, telbot):
cid = message.chat.id
image_id = get_image_id_from_message(message)
# prepare image for downloading
file_path = telbot.get_file(image_id).file_path
# generate image download url
image_url = "https://api.telegram.org/file/bot{0}/{1}".format(config.TOKEN, file_path)
# create folder to store image temporary, if it doesnt exist
if not os.path.exists(config.result_storage_path):
os.makedirs(config.result_storage_path)
# retrieve and save image
image_name = "{0}.jpg".format(image_id)
urllib.request.urlretrieve(image_url, "{0}/{1}".format(config.result_storage_path, image_name))
return image_name
def get_image_id_from_message(message):
# there are multiple array of images, check the biggest
return message.photo[len(message.photo) - 1].file_id
def handle_image(image_name, cid):
if config.dict_styles_established[cid] == 'standard style established':
style_number = config.dict_styles[cid]
del config.dict_styles[cid]
style_image_name = "handled_style{0}.jpg".format(style_number)
style_image = Image.open("{0}/{1}".format(config.result_storage_path, style_image_name))
else:
style_image_name = config.dict_styles_established[cid]
style_image = Image.open("{0}/{1}".format(config.result_storage_path, style_image_name))
style_image = image_to_square(style_image, 256)
style_img = np.array(style_image)
style_img = style_img.astype(np.float32)[np.newaxis, ...] / 255.
content_image = Image.open("{0}/{1}".format(config.result_storage_path, image_name))
image_resized = image_reduce(content_image, 384)
content_img = np.array(image_resized)
content_img = content_img.astype(np.float32)[np.newaxis, ...] / 255.
hub_module = hub.load('https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2')
outputs = hub_module(tf.constant(content_img), tf.constant(style_img))
stylized_image = outputs[0]
result_img = tf.squeeze(stylized_image)
result_im = tf.cast(result_img * 255, tf.uint8)
result_img_pillow = Image.fromarray(result_im.numpy())
image_name_new = "handled_image_" + image_name
result_img_pillow.save("{0}/{1}".format(config.result_storage_path, image_name_new))
return image_name_new
def cleanup_remove_images(image_name, image_name_new, style_image_name):
os.remove('{0}/{1}'.format(config.result_storage_path, image_name))
os.remove('{0}/{1}'.format(config.result_storage_path, image_name_new))
if style_image_name != 'standard style established':
os.remove('{0}/{1}'.format(config.result_storage_path, style_image_name))
def get_save_style_image(number):
# create folder to store image temporary, if it doesnt exist
if not os.path.exists(config.result_storage_path):
os.makedirs(config.result_storage_path)
if not os.path.exists("{0}/handled_style{1}.jpg".format(config.result_storage_path, number)):
image_mame = "style{0}.jpg".format(number)
image_path = "static/" + image_mame
style_image = Image.open(image_path)
image_square_resized = image_to_square(style_image, 256)
style_image_name = "handled_" + image_mame
image_square_resized.save("{0}/{1}".format(config.result_storage_path, style_image_name))
else:
style_image_name = "handled_style{0}.jpg".format(number)
return style_image_name
def image_to_square(image_name, image_size):
width = image_name.width
height = image_name.height
if width == height:
image_square_resized = image_name.resize((image_size, image_size))
elif width > height:
image_crop = image_name.crop(((width // 2 - height // 2), 0, (width // 2 - height // 2) + height, height))
image_square_resized = image_crop.resize((image_size, image_size))
else:
image_crop = image_name.crop((0, (height // 2 - width // 2), width, (height // 2 - width // 2) + width))
image_square_resized = image_crop.resize((image_size, image_size))
return image_square_resized
def image_reduce(image_name, width_size):
width = image_name.width
height = image_name.height
if width == height & width > width_size:
image_resized = image_name.resize((width_size, width_size))
elif width > width_size:
factor = width / width_size
image_resized = image_name.resize((width_size, round(height / factor)))
else:
image_resized = image_name
return image_resized | image_utils.py | import os
import urllib.request
from PIL import Image
import numpy as np
import tensorflow as tf
import tensorflow_hub as hub
import config
def save_image_from_message(message, telbot):
cid = message.chat.id
image_id = get_image_id_from_message(message)
# prepare image for downloading
file_path = telbot.get_file(image_id).file_path
# generate image download url
image_url = "https://api.telegram.org/file/bot{0}/{1}".format(config.TOKEN, file_path)
# create folder to store image temporary, if it doesnt exist
if not os.path.exists(config.result_storage_path):
os.makedirs(config.result_storage_path)
# retrieve and save image
image_name = "{0}.jpg".format(image_id)
urllib.request.urlretrieve(image_url, "{0}/{1}".format(config.result_storage_path, image_name))
return image_name
def get_image_id_from_message(message):
# there are multiple array of images, check the biggest
return message.photo[len(message.photo) - 1].file_id
def handle_image(image_name, cid):
if config.dict_styles_established[cid] == 'standard style established':
style_number = config.dict_styles[cid]
del config.dict_styles[cid]
style_image_name = "handled_style{0}.jpg".format(style_number)
style_image = Image.open("{0}/{1}".format(config.result_storage_path, style_image_name))
else:
style_image_name = config.dict_styles_established[cid]
style_image = Image.open("{0}/{1}".format(config.result_storage_path, style_image_name))
style_image = image_to_square(style_image, 256)
style_img = np.array(style_image)
style_img = style_img.astype(np.float32)[np.newaxis, ...] / 255.
content_image = Image.open("{0}/{1}".format(config.result_storage_path, image_name))
image_resized = image_reduce(content_image, 384)
content_img = np.array(image_resized)
content_img = content_img.astype(np.float32)[np.newaxis, ...] / 255.
hub_module = hub.load('https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2')
outputs = hub_module(tf.constant(content_img), tf.constant(style_img))
stylized_image = outputs[0]
result_img = tf.squeeze(stylized_image)
result_im = tf.cast(result_img * 255, tf.uint8)
result_img_pillow = Image.fromarray(result_im.numpy())
image_name_new = "handled_image_" + image_name
result_img_pillow.save("{0}/{1}".format(config.result_storage_path, image_name_new))
return image_name_new
def cleanup_remove_images(image_name, image_name_new, style_image_name):
os.remove('{0}/{1}'.format(config.result_storage_path, image_name))
os.remove('{0}/{1}'.format(config.result_storage_path, image_name_new))
if style_image_name != 'standard style established':
os.remove('{0}/{1}'.format(config.result_storage_path, style_image_name))
def get_save_style_image(number):
# create folder to store image temporary, if it doesnt exist
if not os.path.exists(config.result_storage_path):
os.makedirs(config.result_storage_path)
if not os.path.exists("{0}/handled_style{1}.jpg".format(config.result_storage_path, number)):
image_mame = "style{0}.jpg".format(number)
image_path = "static/" + image_mame
style_image = Image.open(image_path)
image_square_resized = image_to_square(style_image, 256)
style_image_name = "handled_" + image_mame
image_square_resized.save("{0}/{1}".format(config.result_storage_path, style_image_name))
else:
style_image_name = "handled_style{0}.jpg".format(number)
return style_image_name
def image_to_square(image_name, image_size):
width = image_name.width
height = image_name.height
if width == height:
image_square_resized = image_name.resize((image_size, image_size))
elif width > height:
image_crop = image_name.crop(((width // 2 - height // 2), 0, (width // 2 - height // 2) + height, height))
image_square_resized = image_crop.resize((image_size, image_size))
else:
image_crop = image_name.crop((0, (height // 2 - width // 2), width, (height // 2 - width // 2) + width))
image_square_resized = image_crop.resize((image_size, image_size))
return image_square_resized
def image_reduce(image_name, width_size):
width = image_name.width
height = image_name.height
if width == height & width > width_size:
image_resized = image_name.resize((width_size, width_size))
elif width > width_size:
factor = width / width_size
image_resized = image_name.resize((width_size, round(height / factor)))
else:
image_resized = image_name
return image_resized | 0.385953 | 0.166743 |
import datetime
from unittest import mock
from django.db import (
IntegrityError, NotSupportedError, connection, transaction,
)
from django.db.models import (
CheckConstraint, Deferrable, F, Func, Q, UniqueConstraint,
)
from django.db.models.fields.json import KeyTextTransform
from django.db.models.functions import Left
from django.test import skipUnlessDBFeature
from django.utils import timezone
from . import PostgreSQLTestCase
from .models import HotelReservation, RangesModel, Room, Scene
try:
from psycopg2.extras import DateRange, NumericRange
from django.contrib.postgres.constraints import ExclusionConstraint
from django.contrib.postgres.fields import (
DateTimeRangeField, RangeBoundary, RangeOperators,
)
except ImportError:
pass
class SchemaTests(PostgreSQLTestCase):
get_opclass_query = '''
SELECT opcname, c.relname FROM pg_opclass AS oc
JOIN pg_index as i on oc.oid = ANY(i.indclass)
JOIN pg_class as c on c.oid = i.indexrelid
WHERE c.relname = %s
'''
def get_constraints(self, table):
"""Get the constraints on the table using a new cursor."""
with connection.cursor() as cursor:
return connection.introspection.get_constraints(cursor, table)
def test_check_constraint_range_value(self):
constraint_name = 'ints_between'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = CheckConstraint(
check=Q(ints__contained_by=NumericRange(10, 30)),
name=constraint_name,
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
with self.assertRaises(IntegrityError), transaction.atomic():
RangesModel.objects.create(ints=(20, 50))
RangesModel.objects.create(ints=(10, 30))
def test_check_constraint_daterange_contains(self):
constraint_name = 'dates_contains'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = CheckConstraint(
check=Q(dates__contains=F('dates_inner')),
name=constraint_name,
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
date_1 = datetime.date(2016, 1, 1)
date_2 = datetime.date(2016, 1, 4)
with self.assertRaises(IntegrityError), transaction.atomic():
RangesModel.objects.create(
dates=(date_1, date_2),
dates_inner=(date_1, date_2.replace(day=5)),
)
RangesModel.objects.create(
dates=(date_1, date_2),
dates_inner=(date_1, date_2),
)
def test_check_constraint_datetimerange_contains(self):
constraint_name = 'timestamps_contains'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = CheckConstraint(
check=Q(timestamps__contains=F('timestamps_inner')),
name=constraint_name,
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
datetime_1 = datetime.datetime(2016, 1, 1)
datetime_2 = datetime.datetime(2016, 1, 2, 12)
with self.assertRaises(IntegrityError), transaction.atomic():
RangesModel.objects.create(
timestamps=(datetime_1, datetime_2),
timestamps_inner=(datetime_1, datetime_2.replace(hour=13)),
)
RangesModel.objects.create(
timestamps=(datetime_1, datetime_2),
timestamps_inner=(datetime_1, datetime_2),
)
def test_opclass(self):
constraint = UniqueConstraint(
name='test_opclass',
fields=['scene'],
opclasses=['varchar_pattern_ops'],
)
with connection.schema_editor() as editor:
editor.add_constraint(Scene, constraint)
self.assertIn(constraint.name, self.get_constraints(Scene._meta.db_table))
with editor.connection.cursor() as cursor:
cursor.execute(self.get_opclass_query, [constraint.name])
self.assertEqual(
cursor.fetchall(),
[('varchar_pattern_ops', constraint.name)],
)
# Drop the constraint.
with connection.schema_editor() as editor:
editor.remove_constraint(Scene, constraint)
self.assertNotIn(constraint.name, self.get_constraints(Scene._meta.db_table))
def test_opclass_multiple_columns(self):
constraint = UniqueConstraint(
name='test_opclass_multiple',
fields=['scene', 'setting'],
opclasses=['varchar_pattern_ops', 'text_pattern_ops'],
)
with connection.schema_editor() as editor:
editor.add_constraint(Scene, constraint)
with editor.connection.cursor() as cursor:
cursor.execute(self.get_opclass_query, [constraint.name])
expected_opclasses = (
('varchar_pattern_ops', constraint.name),
('text_pattern_ops', constraint.name),
)
self.assertCountEqual(cursor.fetchall(), expected_opclasses)
def test_opclass_partial(self):
constraint = UniqueConstraint(
name='test_opclass_partial',
fields=['scene'],
opclasses=['varchar_pattern_ops'],
condition=Q(setting__contains="Sir Bedemir's Castle"),
)
with connection.schema_editor() as editor:
editor.add_constraint(Scene, constraint)
with editor.connection.cursor() as cursor:
cursor.execute(self.get_opclass_query, [constraint.name])
self.assertCountEqual(
cursor.fetchall(),
[('varchar_pattern_ops', constraint.name)],
)
@skipUnlessDBFeature('supports_covering_indexes')
def test_opclass_include(self):
constraint = UniqueConstraint(
name='test_opclass_include',
fields=['scene'],
opclasses=['varchar_pattern_ops'],
include=['setting'],
)
with connection.schema_editor() as editor:
editor.add_constraint(Scene, constraint)
with editor.connection.cursor() as cursor:
cursor.execute(self.get_opclass_query, [constraint.name])
self.assertCountEqual(
cursor.fetchall(),
[('varchar_pattern_ops', constraint.name)],
)
class ExclusionConstraintTests(PostgreSQLTestCase):
def get_constraints(self, table):
"""Get the constraints on the table using a new cursor."""
with connection.cursor() as cursor:
return connection.introspection.get_constraints(cursor, table)
def test_invalid_condition(self):
msg = 'ExclusionConstraint.condition must be a Q instance.'
with self.assertRaisesMessage(ValueError, msg):
ExclusionConstraint(
index_type='GIST',
name='exclude_invalid_condition',
expressions=[(F('datespan'), RangeOperators.OVERLAPS)],
condition=F('invalid'),
)
def test_invalid_index_type(self):
msg = 'Exclusion constraints only support GiST or SP-GiST indexes.'
with self.assertRaisesMessage(ValueError, msg):
ExclusionConstraint(
index_type='gin',
name='exclude_invalid_index_type',
expressions=[(F('datespan'), RangeOperators.OVERLAPS)],
)
def test_invalid_expressions(self):
msg = 'The expressions must be a list of 2-tuples.'
for expressions in (['foo'], [('foo')], [('foo_1', 'foo_2', 'foo_3')]):
with self.subTest(expressions), self.assertRaisesMessage(ValueError, msg):
ExclusionConstraint(
index_type='GIST',
name='exclude_invalid_expressions',
expressions=expressions,
)
def test_empty_expressions(self):
msg = 'At least one expression is required to define an exclusion constraint.'
for empty_expressions in (None, []):
with self.subTest(empty_expressions), self.assertRaisesMessage(ValueError, msg):
ExclusionConstraint(
index_type='GIST',
name='exclude_empty_expressions',
expressions=empty_expressions,
)
def test_invalid_deferrable(self):
msg = 'ExclusionConstraint.deferrable must be a Deferrable instance.'
with self.assertRaisesMessage(ValueError, msg):
ExclusionConstraint(
name='exclude_invalid_deferrable',
expressions=[(F('datespan'), RangeOperators.OVERLAPS)],
deferrable='invalid',
)
def test_deferrable_with_condition(self):
msg = 'ExclusionConstraint with conditions cannot be deferred.'
with self.assertRaisesMessage(ValueError, msg):
ExclusionConstraint(
name='exclude_invalid_condition',
expressions=[(F('datespan'), RangeOperators.OVERLAPS)],
condition=Q(cancelled=False),
deferrable=Deferrable.DEFERRED,
)
def test_invalid_include_type(self):
msg = 'ExclusionConstraint.include must be a list or tuple.'
with self.assertRaisesMessage(ValueError, msg):
ExclusionConstraint(
name='exclude_invalid_include',
expressions=[(F('datespan'), RangeOperators.OVERLAPS)],
include='invalid',
)
def test_invalid_include_index_type(self):
msg = 'Covering exclusion constraints only support GiST indexes.'
with self.assertRaisesMessage(ValueError, msg):
ExclusionConstraint(
name='exclude_invalid_index_type',
expressions=[(F('datespan'), RangeOperators.OVERLAPS)],
include=['cancelled'],
index_type='spgist',
)
def test_invalid_opclasses_type(self):
msg = 'ExclusionConstraint.opclasses must be a list or tuple.'
with self.assertRaisesMessage(ValueError, msg):
ExclusionConstraint(
name='exclude_invalid_opclasses',
expressions=[(F('datespan'), RangeOperators.OVERLAPS)],
opclasses='invalid',
)
def test_opclasses_and_expressions_same_length(self):
msg = (
'ExclusionConstraint.expressions and '
'ExclusionConstraint.opclasses must have the same number of '
'elements.'
)
with self.assertRaisesMessage(ValueError, msg):
ExclusionConstraint(
name='exclude_invalid_expressions_opclasses_length',
expressions=[(F('datespan'), RangeOperators.OVERLAPS)],
opclasses=['foo', 'bar'],
)
def test_repr(self):
constraint = ExclusionConstraint(
name='exclude_overlapping',
expressions=[
(F('datespan'), RangeOperators.OVERLAPS),
(F('room'), RangeOperators.EQUAL),
],
)
self.assertEqual(
repr(constraint),
"<ExclusionConstraint: index_type=GIST, expressions=["
"(F(datespan), '&&'), (F(room), '=')]>",
)
constraint = ExclusionConstraint(
name='exclude_overlapping',
expressions=[(F('datespan'), RangeOperators.ADJACENT_TO)],
condition=Q(cancelled=False),
index_type='SPGiST',
)
self.assertEqual(
repr(constraint),
"<ExclusionConstraint: index_type=SPGiST, expressions=["
"(F(datespan), '-|-')], condition=(AND: ('cancelled', False))>",
)
constraint = ExclusionConstraint(
name='exclude_overlapping',
expressions=[(F('datespan'), RangeOperators.ADJACENT_TO)],
deferrable=Deferrable.IMMEDIATE,
)
self.assertEqual(
repr(constraint),
"<ExclusionConstraint: index_type=GIST, expressions=["
"(F(datespan), '-|-')], deferrable=Deferrable.IMMEDIATE>",
)
constraint = ExclusionConstraint(
name='exclude_overlapping',
expressions=[(F('datespan'), RangeOperators.ADJACENT_TO)],
include=['cancelled', 'room'],
)
self.assertEqual(
repr(constraint),
"<ExclusionConstraint: index_type=GIST, expressions=["
"(F(datespan), '-|-')], include=('cancelled', 'room')>",
)
constraint = ExclusionConstraint(
name='exclude_overlapping',
expressions=[(F('datespan'), RangeOperators.ADJACENT_TO)],
opclasses=['range_ops'],
)
self.assertEqual(
repr(constraint),
"<ExclusionConstraint: index_type=GIST, expressions=["
"(F(datespan), '-|-')], opclasses=['range_ops']>",
)
def test_eq(self):
constraint_1 = ExclusionConstraint(
name='exclude_overlapping',
expressions=[
(F('datespan'), RangeOperators.OVERLAPS),
(F('room'), RangeOperators.EQUAL),
],
condition=Q(cancelled=False),
)
constraint_2 = ExclusionConstraint(
name='exclude_overlapping',
expressions=[
('datespan', RangeOperators.OVERLAPS),
('room', RangeOperators.EQUAL),
],
)
constraint_3 = ExclusionConstraint(
name='exclude_overlapping',
expressions=[('datespan', RangeOperators.OVERLAPS)],
condition=Q(cancelled=False),
)
constraint_4 = ExclusionConstraint(
name='exclude_overlapping',
expressions=[
('datespan', RangeOperators.OVERLAPS),
('room', RangeOperators.EQUAL),
],
deferrable=Deferrable.DEFERRED,
)
constraint_5 = ExclusionConstraint(
name='exclude_overlapping',
expressions=[
('datespan', RangeOperators.OVERLAPS),
('room', RangeOperators.EQUAL),
],
deferrable=Deferrable.IMMEDIATE,
)
constraint_6 = ExclusionConstraint(
name='exclude_overlapping',
expressions=[
('datespan', RangeOperators.OVERLAPS),
('room', RangeOperators.EQUAL),
],
deferrable=Deferrable.IMMEDIATE,
include=['cancelled'],
)
constraint_7 = ExclusionConstraint(
name='exclude_overlapping',
expressions=[
('datespan', RangeOperators.OVERLAPS),
('room', RangeOperators.EQUAL),
],
include=['cancelled'],
)
constraint_8 = ExclusionConstraint(
name='exclude_overlapping',
expressions=[
('datespan', RangeOperators.OVERLAPS),
('room', RangeOperators.EQUAL),
],
include=['cancelled'],
opclasses=['range_ops', 'range_ops']
)
constraint_9 = ExclusionConstraint(
name='exclude_overlapping',
expressions=[
('datespan', RangeOperators.OVERLAPS),
('room', RangeOperators.EQUAL),
],
opclasses=['range_ops', 'range_ops']
)
self.assertEqual(constraint_1, constraint_1)
self.assertEqual(constraint_1, mock.ANY)
self.assertNotEqual(constraint_1, constraint_2)
self.assertNotEqual(constraint_1, constraint_3)
self.assertNotEqual(constraint_1, constraint_4)
self.assertNotEqual(constraint_2, constraint_3)
self.assertNotEqual(constraint_2, constraint_4)
self.assertNotEqual(constraint_2, constraint_7)
self.assertNotEqual(constraint_2, constraint_9)
self.assertNotEqual(constraint_4, constraint_5)
self.assertNotEqual(constraint_5, constraint_6)
self.assertNotEqual(constraint_7, constraint_8)
self.assertNotEqual(constraint_1, object())
def test_deconstruct(self):
constraint = ExclusionConstraint(
name='exclude_overlapping',
expressions=[('datespan', RangeOperators.OVERLAPS), ('room', RangeOperators.EQUAL)],
)
path, args, kwargs = constraint.deconstruct()
self.assertEqual(path, 'django.contrib.postgres.constraints.ExclusionConstraint')
self.assertEqual(args, ())
self.assertEqual(kwargs, {
'name': 'exclude_overlapping',
'expressions': [('datespan', RangeOperators.OVERLAPS), ('room', RangeOperators.EQUAL)],
})
def test_deconstruct_index_type(self):
constraint = ExclusionConstraint(
name='exclude_overlapping',
index_type='SPGIST',
expressions=[('datespan', RangeOperators.OVERLAPS), ('room', RangeOperators.EQUAL)],
)
path, args, kwargs = constraint.deconstruct()
self.assertEqual(path, 'django.contrib.postgres.constraints.ExclusionConstraint')
self.assertEqual(args, ())
self.assertEqual(kwargs, {
'name': 'exclude_overlapping',
'index_type': 'SPGIST',
'expressions': [('datespan', RangeOperators.OVERLAPS), ('room', RangeOperators.EQUAL)],
})
def test_deconstruct_condition(self):
constraint = ExclusionConstraint(
name='exclude_overlapping',
expressions=[('datespan', RangeOperators.OVERLAPS), ('room', RangeOperators.EQUAL)],
condition=Q(cancelled=False),
)
path, args, kwargs = constraint.deconstruct()
self.assertEqual(path, 'django.contrib.postgres.constraints.ExclusionConstraint')
self.assertEqual(args, ())
self.assertEqual(kwargs, {
'name': 'exclude_overlapping',
'expressions': [('datespan', RangeOperators.OVERLAPS), ('room', RangeOperators.EQUAL)],
'condition': Q(cancelled=False),
})
def test_deconstruct_deferrable(self):
constraint = ExclusionConstraint(
name='exclude_overlapping',
expressions=[('datespan', RangeOperators.OVERLAPS)],
deferrable=Deferrable.DEFERRED,
)
path, args, kwargs = constraint.deconstruct()
self.assertEqual(path, 'django.contrib.postgres.constraints.ExclusionConstraint')
self.assertEqual(args, ())
self.assertEqual(kwargs, {
'name': 'exclude_overlapping',
'expressions': [('datespan', RangeOperators.OVERLAPS)],
'deferrable': Deferrable.DEFERRED,
})
def test_deconstruct_include(self):
constraint = ExclusionConstraint(
name='exclude_overlapping',
expressions=[('datespan', RangeOperators.OVERLAPS)],
include=['cancelled', 'room'],
)
path, args, kwargs = constraint.deconstruct()
self.assertEqual(path, 'django.contrib.postgres.constraints.ExclusionConstraint')
self.assertEqual(args, ())
self.assertEqual(kwargs, {
'name': 'exclude_overlapping',
'expressions': [('datespan', RangeOperators.OVERLAPS)],
'include': ('cancelled', 'room'),
})
def test_deconstruct_opclasses(self):
constraint = ExclusionConstraint(
name='exclude_overlapping',
expressions=[('datespan', RangeOperators.OVERLAPS)],
opclasses=['range_ops'],
)
path, args, kwargs = constraint.deconstruct()
self.assertEqual(path, 'django.contrib.postgres.constraints.ExclusionConstraint')
self.assertEqual(args, ())
self.assertEqual(kwargs, {
'name': 'exclude_overlapping',
'expressions': [('datespan', RangeOperators.OVERLAPS)],
'opclasses': ['range_ops'],
})
def _test_range_overlaps(self, constraint):
# Create exclusion constraint.
self.assertNotIn(constraint.name, self.get_constraints(HotelReservation._meta.db_table))
with connection.schema_editor() as editor:
editor.add_constraint(HotelReservation, constraint)
self.assertIn(constraint.name, self.get_constraints(HotelReservation._meta.db_table))
# Add initial reservations.
room101 = Room.objects.create(number=101)
room102 = Room.objects.create(number=102)
datetimes = [
timezone.datetime(2018, 6, 20),
timezone.datetime(2018, 6, 24),
timezone.datetime(2018, 6, 26),
timezone.datetime(2018, 6, 28),
timezone.datetime(2018, 6, 29),
]
HotelReservation.objects.create(
datespan=DateRange(datetimes[0].date(), datetimes[1].date()),
start=datetimes[0],
end=datetimes[1],
room=room102,
)
HotelReservation.objects.create(
datespan=DateRange(datetimes[1].date(), datetimes[3].date()),
start=datetimes[1],
end=datetimes[3],
room=room102,
)
# Overlap dates.
with self.assertRaises(IntegrityError), transaction.atomic():
reservation = HotelReservation(
datespan=(datetimes[1].date(), datetimes[2].date()),
start=datetimes[1],
end=datetimes[2],
room=room102,
)
reservation.save()
# Valid range.
HotelReservation.objects.bulk_create([
# Other room.
HotelReservation(
datespan=(datetimes[1].date(), datetimes[2].date()),
start=datetimes[1],
end=datetimes[2],
room=room101,
),
# Cancelled reservation.
HotelReservation(
datespan=(datetimes[1].date(), datetimes[1].date()),
start=datetimes[1],
end=datetimes[2],
room=room102,
cancelled=True,
),
# Other adjacent dates.
HotelReservation(
datespan=(datetimes[3].date(), datetimes[4].date()),
start=datetimes[3],
end=datetimes[4],
room=room102,
),
])
def test_range_overlaps_custom(self):
class TsTzRange(Func):
function = 'TSTZRANGE'
output_field = DateTimeRangeField()
constraint = ExclusionConstraint(
name='exclude_overlapping_reservations_custom',
expressions=[
(TsTzRange('start', 'end', RangeBoundary()), RangeOperators.OVERLAPS),
('room', RangeOperators.EQUAL)
],
condition=Q(cancelled=False),
opclasses=['range_ops', 'gist_int4_ops'],
)
self._test_range_overlaps(constraint)
def test_range_overlaps(self):
constraint = ExclusionConstraint(
name='exclude_overlapping_reservations',
expressions=[
(F('datespan'), RangeOperators.OVERLAPS),
('room', RangeOperators.EQUAL)
],
condition=Q(cancelled=False),
)
self._test_range_overlaps(constraint)
def test_range_adjacent(self):
constraint_name = 'ints_adjacent'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[('ints', RangeOperators.ADJACENT_TO)],
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
RangesModel.objects.create(ints=(20, 50))
with self.assertRaises(IntegrityError), transaction.atomic():
RangesModel.objects.create(ints=(10, 20))
RangesModel.objects.create(ints=(10, 19))
RangesModel.objects.create(ints=(51, 60))
# Drop the constraint.
with connection.schema_editor() as editor:
editor.remove_constraint(RangesModel, constraint)
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
def test_expressions_with_params(self):
constraint_name = 'scene_left_equal'
self.assertNotIn(constraint_name, self.get_constraints(Scene._meta.db_table))
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[(Left('scene', 4), RangeOperators.EQUAL)],
)
with connection.schema_editor() as editor:
editor.add_constraint(Scene, constraint)
self.assertIn(constraint_name, self.get_constraints(Scene._meta.db_table))
def test_expressions_with_key_transform(self):
constraint_name = 'exclude_overlapping_reservations_smoking'
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[
(F('datespan'), RangeOperators.OVERLAPS),
(KeyTextTransform('smoking', 'requirements'), RangeOperators.EQUAL),
],
)
with connection.schema_editor() as editor:
editor.add_constraint(HotelReservation, constraint)
self.assertIn(
constraint_name,
self.get_constraints(HotelReservation._meta.db_table),
)
def test_range_adjacent_initially_deferred(self):
constraint_name = 'ints_adjacent_deferred'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[('ints', RangeOperators.ADJACENT_TO)],
deferrable=Deferrable.DEFERRED,
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
RangesModel.objects.create(ints=(20, 50))
adjacent_range = RangesModel.objects.create(ints=(10, 20))
# Constraint behavior can be changed with SET CONSTRAINTS.
with self.assertRaises(IntegrityError):
with transaction.atomic(), connection.cursor() as cursor:
quoted_name = connection.ops.quote_name(constraint_name)
cursor.execute('SET CONSTRAINTS %s IMMEDIATE' % quoted_name)
# Remove adjacent range before the end of transaction.
adjacent_range.delete()
RangesModel.objects.create(ints=(10, 19))
RangesModel.objects.create(ints=(51, 60))
@skipUnlessDBFeature('supports_covering_gist_indexes')
def test_range_adjacent_include(self):
constraint_name = 'ints_adjacent_include'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[('ints', RangeOperators.ADJACENT_TO)],
include=['decimals', 'ints'],
index_type='gist',
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
RangesModel.objects.create(ints=(20, 50))
with self.assertRaises(IntegrityError), transaction.atomic():
RangesModel.objects.create(ints=(10, 20))
RangesModel.objects.create(ints=(10, 19))
RangesModel.objects.create(ints=(51, 60))
@skipUnlessDBFeature('supports_covering_gist_indexes')
def test_range_adjacent_include_condition(self):
constraint_name = 'ints_adjacent_include_condition'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[('ints', RangeOperators.ADJACENT_TO)],
include=['decimals'],
condition=Q(id__gte=100),
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
@skipUnlessDBFeature('supports_covering_gist_indexes')
def test_range_adjacent_include_deferrable(self):
constraint_name = 'ints_adjacent_include_deferrable'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[('ints', RangeOperators.ADJACENT_TO)],
include=['decimals'],
deferrable=Deferrable.DEFERRED,
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
def test_include_not_supported(self):
constraint_name = 'ints_adjacent_include_not_supported'
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[('ints', RangeOperators.ADJACENT_TO)],
include=['id'],
)
msg = 'Covering exclusion constraints requires PostgreSQL 12+.'
with connection.schema_editor() as editor:
with mock.patch(
'django.db.backends.postgresql.features.DatabaseFeatures.supports_covering_gist_indexes',
False,
):
with self.assertRaisesMessage(NotSupportedError, msg):
editor.add_constraint(RangesModel, constraint)
def test_range_adjacent_opclasses(self):
constraint_name = 'ints_adjacent_opclasses'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[('ints', RangeOperators.ADJACENT_TO)],
opclasses=['range_ops'],
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
RangesModel.objects.create(ints=(20, 50))
with self.assertRaises(IntegrityError), transaction.atomic():
RangesModel.objects.create(ints=(10, 20))
RangesModel.objects.create(ints=(10, 19))
RangesModel.objects.create(ints=(51, 60))
# Drop the constraint.
with connection.schema_editor() as editor:
editor.remove_constraint(RangesModel, constraint)
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
def test_range_adjacent_opclasses_condition(self):
constraint_name = 'ints_adjacent_opclasses_condition'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[('ints', RangeOperators.ADJACENT_TO)],
opclasses=['range_ops'],
condition=Q(id__gte=100),
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
def test_range_adjacent_opclasses_deferrable(self):
constraint_name = 'ints_adjacent_opclasses_deferrable'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[('ints', RangeOperators.ADJACENT_TO)],
opclasses=['range_ops'],
deferrable=Deferrable.DEFERRED,
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
@skipUnlessDBFeature('supports_covering_gist_indexes')
def test_range_adjacent_opclasses_include(self):
constraint_name = 'ints_adjacent_opclasses_include'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[('ints', RangeOperators.ADJACENT_TO)],
opclasses=['range_ops'],
include=['decimals'],
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table)) | tests/postgres_tests/test_constraints.py | import datetime
from unittest import mock
from django.db import (
IntegrityError, NotSupportedError, connection, transaction,
)
from django.db.models import (
CheckConstraint, Deferrable, F, Func, Q, UniqueConstraint,
)
from django.db.models.fields.json import KeyTextTransform
from django.db.models.functions import Left
from django.test import skipUnlessDBFeature
from django.utils import timezone
from . import PostgreSQLTestCase
from .models import HotelReservation, RangesModel, Room, Scene
try:
from psycopg2.extras import DateRange, NumericRange
from django.contrib.postgres.constraints import ExclusionConstraint
from django.contrib.postgres.fields import (
DateTimeRangeField, RangeBoundary, RangeOperators,
)
except ImportError:
pass
class SchemaTests(PostgreSQLTestCase):
get_opclass_query = '''
SELECT opcname, c.relname FROM pg_opclass AS oc
JOIN pg_index as i on oc.oid = ANY(i.indclass)
JOIN pg_class as c on c.oid = i.indexrelid
WHERE c.relname = %s
'''
def get_constraints(self, table):
"""Get the constraints on the table using a new cursor."""
with connection.cursor() as cursor:
return connection.introspection.get_constraints(cursor, table)
def test_check_constraint_range_value(self):
constraint_name = 'ints_between'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = CheckConstraint(
check=Q(ints__contained_by=NumericRange(10, 30)),
name=constraint_name,
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
with self.assertRaises(IntegrityError), transaction.atomic():
RangesModel.objects.create(ints=(20, 50))
RangesModel.objects.create(ints=(10, 30))
def test_check_constraint_daterange_contains(self):
constraint_name = 'dates_contains'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = CheckConstraint(
check=Q(dates__contains=F('dates_inner')),
name=constraint_name,
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
date_1 = datetime.date(2016, 1, 1)
date_2 = datetime.date(2016, 1, 4)
with self.assertRaises(IntegrityError), transaction.atomic():
RangesModel.objects.create(
dates=(date_1, date_2),
dates_inner=(date_1, date_2.replace(day=5)),
)
RangesModel.objects.create(
dates=(date_1, date_2),
dates_inner=(date_1, date_2),
)
def test_check_constraint_datetimerange_contains(self):
constraint_name = 'timestamps_contains'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = CheckConstraint(
check=Q(timestamps__contains=F('timestamps_inner')),
name=constraint_name,
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
datetime_1 = datetime.datetime(2016, 1, 1)
datetime_2 = datetime.datetime(2016, 1, 2, 12)
with self.assertRaises(IntegrityError), transaction.atomic():
RangesModel.objects.create(
timestamps=(datetime_1, datetime_2),
timestamps_inner=(datetime_1, datetime_2.replace(hour=13)),
)
RangesModel.objects.create(
timestamps=(datetime_1, datetime_2),
timestamps_inner=(datetime_1, datetime_2),
)
def test_opclass(self):
constraint = UniqueConstraint(
name='test_opclass',
fields=['scene'],
opclasses=['varchar_pattern_ops'],
)
with connection.schema_editor() as editor:
editor.add_constraint(Scene, constraint)
self.assertIn(constraint.name, self.get_constraints(Scene._meta.db_table))
with editor.connection.cursor() as cursor:
cursor.execute(self.get_opclass_query, [constraint.name])
self.assertEqual(
cursor.fetchall(),
[('varchar_pattern_ops', constraint.name)],
)
# Drop the constraint.
with connection.schema_editor() as editor:
editor.remove_constraint(Scene, constraint)
self.assertNotIn(constraint.name, self.get_constraints(Scene._meta.db_table))
def test_opclass_multiple_columns(self):
constraint = UniqueConstraint(
name='test_opclass_multiple',
fields=['scene', 'setting'],
opclasses=['varchar_pattern_ops', 'text_pattern_ops'],
)
with connection.schema_editor() as editor:
editor.add_constraint(Scene, constraint)
with editor.connection.cursor() as cursor:
cursor.execute(self.get_opclass_query, [constraint.name])
expected_opclasses = (
('varchar_pattern_ops', constraint.name),
('text_pattern_ops', constraint.name),
)
self.assertCountEqual(cursor.fetchall(), expected_opclasses)
def test_opclass_partial(self):
constraint = UniqueConstraint(
name='test_opclass_partial',
fields=['scene'],
opclasses=['varchar_pattern_ops'],
condition=Q(setting__contains="Sir Bedemir's Castle"),
)
with connection.schema_editor() as editor:
editor.add_constraint(Scene, constraint)
with editor.connection.cursor() as cursor:
cursor.execute(self.get_opclass_query, [constraint.name])
self.assertCountEqual(
cursor.fetchall(),
[('varchar_pattern_ops', constraint.name)],
)
@skipUnlessDBFeature('supports_covering_indexes')
def test_opclass_include(self):
constraint = UniqueConstraint(
name='test_opclass_include',
fields=['scene'],
opclasses=['varchar_pattern_ops'],
include=['setting'],
)
with connection.schema_editor() as editor:
editor.add_constraint(Scene, constraint)
with editor.connection.cursor() as cursor:
cursor.execute(self.get_opclass_query, [constraint.name])
self.assertCountEqual(
cursor.fetchall(),
[('varchar_pattern_ops', constraint.name)],
)
class ExclusionConstraintTests(PostgreSQLTestCase):
def get_constraints(self, table):
"""Get the constraints on the table using a new cursor."""
with connection.cursor() as cursor:
return connection.introspection.get_constraints(cursor, table)
def test_invalid_condition(self):
msg = 'ExclusionConstraint.condition must be a Q instance.'
with self.assertRaisesMessage(ValueError, msg):
ExclusionConstraint(
index_type='GIST',
name='exclude_invalid_condition',
expressions=[(F('datespan'), RangeOperators.OVERLAPS)],
condition=F('invalid'),
)
def test_invalid_index_type(self):
msg = 'Exclusion constraints only support GiST or SP-GiST indexes.'
with self.assertRaisesMessage(ValueError, msg):
ExclusionConstraint(
index_type='gin',
name='exclude_invalid_index_type',
expressions=[(F('datespan'), RangeOperators.OVERLAPS)],
)
def test_invalid_expressions(self):
msg = 'The expressions must be a list of 2-tuples.'
for expressions in (['foo'], [('foo')], [('foo_1', 'foo_2', 'foo_3')]):
with self.subTest(expressions), self.assertRaisesMessage(ValueError, msg):
ExclusionConstraint(
index_type='GIST',
name='exclude_invalid_expressions',
expressions=expressions,
)
def test_empty_expressions(self):
msg = 'At least one expression is required to define an exclusion constraint.'
for empty_expressions in (None, []):
with self.subTest(empty_expressions), self.assertRaisesMessage(ValueError, msg):
ExclusionConstraint(
index_type='GIST',
name='exclude_empty_expressions',
expressions=empty_expressions,
)
def test_invalid_deferrable(self):
msg = 'ExclusionConstraint.deferrable must be a Deferrable instance.'
with self.assertRaisesMessage(ValueError, msg):
ExclusionConstraint(
name='exclude_invalid_deferrable',
expressions=[(F('datespan'), RangeOperators.OVERLAPS)],
deferrable='invalid',
)
def test_deferrable_with_condition(self):
msg = 'ExclusionConstraint with conditions cannot be deferred.'
with self.assertRaisesMessage(ValueError, msg):
ExclusionConstraint(
name='exclude_invalid_condition',
expressions=[(F('datespan'), RangeOperators.OVERLAPS)],
condition=Q(cancelled=False),
deferrable=Deferrable.DEFERRED,
)
def test_invalid_include_type(self):
msg = 'ExclusionConstraint.include must be a list or tuple.'
with self.assertRaisesMessage(ValueError, msg):
ExclusionConstraint(
name='exclude_invalid_include',
expressions=[(F('datespan'), RangeOperators.OVERLAPS)],
include='invalid',
)
def test_invalid_include_index_type(self):
msg = 'Covering exclusion constraints only support GiST indexes.'
with self.assertRaisesMessage(ValueError, msg):
ExclusionConstraint(
name='exclude_invalid_index_type',
expressions=[(F('datespan'), RangeOperators.OVERLAPS)],
include=['cancelled'],
index_type='spgist',
)
def test_invalid_opclasses_type(self):
msg = 'ExclusionConstraint.opclasses must be a list or tuple.'
with self.assertRaisesMessage(ValueError, msg):
ExclusionConstraint(
name='exclude_invalid_opclasses',
expressions=[(F('datespan'), RangeOperators.OVERLAPS)],
opclasses='invalid',
)
def test_opclasses_and_expressions_same_length(self):
msg = (
'ExclusionConstraint.expressions and '
'ExclusionConstraint.opclasses must have the same number of '
'elements.'
)
with self.assertRaisesMessage(ValueError, msg):
ExclusionConstraint(
name='exclude_invalid_expressions_opclasses_length',
expressions=[(F('datespan'), RangeOperators.OVERLAPS)],
opclasses=['foo', 'bar'],
)
def test_repr(self):
constraint = ExclusionConstraint(
name='exclude_overlapping',
expressions=[
(F('datespan'), RangeOperators.OVERLAPS),
(F('room'), RangeOperators.EQUAL),
],
)
self.assertEqual(
repr(constraint),
"<ExclusionConstraint: index_type=GIST, expressions=["
"(F(datespan), '&&'), (F(room), '=')]>",
)
constraint = ExclusionConstraint(
name='exclude_overlapping',
expressions=[(F('datespan'), RangeOperators.ADJACENT_TO)],
condition=Q(cancelled=False),
index_type='SPGiST',
)
self.assertEqual(
repr(constraint),
"<ExclusionConstraint: index_type=SPGiST, expressions=["
"(F(datespan), '-|-')], condition=(AND: ('cancelled', False))>",
)
constraint = ExclusionConstraint(
name='exclude_overlapping',
expressions=[(F('datespan'), RangeOperators.ADJACENT_TO)],
deferrable=Deferrable.IMMEDIATE,
)
self.assertEqual(
repr(constraint),
"<ExclusionConstraint: index_type=GIST, expressions=["
"(F(datespan), '-|-')], deferrable=Deferrable.IMMEDIATE>",
)
constraint = ExclusionConstraint(
name='exclude_overlapping',
expressions=[(F('datespan'), RangeOperators.ADJACENT_TO)],
include=['cancelled', 'room'],
)
self.assertEqual(
repr(constraint),
"<ExclusionConstraint: index_type=GIST, expressions=["
"(F(datespan), '-|-')], include=('cancelled', 'room')>",
)
constraint = ExclusionConstraint(
name='exclude_overlapping',
expressions=[(F('datespan'), RangeOperators.ADJACENT_TO)],
opclasses=['range_ops'],
)
self.assertEqual(
repr(constraint),
"<ExclusionConstraint: index_type=GIST, expressions=["
"(F(datespan), '-|-')], opclasses=['range_ops']>",
)
def test_eq(self):
constraint_1 = ExclusionConstraint(
name='exclude_overlapping',
expressions=[
(F('datespan'), RangeOperators.OVERLAPS),
(F('room'), RangeOperators.EQUAL),
],
condition=Q(cancelled=False),
)
constraint_2 = ExclusionConstraint(
name='exclude_overlapping',
expressions=[
('datespan', RangeOperators.OVERLAPS),
('room', RangeOperators.EQUAL),
],
)
constraint_3 = ExclusionConstraint(
name='exclude_overlapping',
expressions=[('datespan', RangeOperators.OVERLAPS)],
condition=Q(cancelled=False),
)
constraint_4 = ExclusionConstraint(
name='exclude_overlapping',
expressions=[
('datespan', RangeOperators.OVERLAPS),
('room', RangeOperators.EQUAL),
],
deferrable=Deferrable.DEFERRED,
)
constraint_5 = ExclusionConstraint(
name='exclude_overlapping',
expressions=[
('datespan', RangeOperators.OVERLAPS),
('room', RangeOperators.EQUAL),
],
deferrable=Deferrable.IMMEDIATE,
)
constraint_6 = ExclusionConstraint(
name='exclude_overlapping',
expressions=[
('datespan', RangeOperators.OVERLAPS),
('room', RangeOperators.EQUAL),
],
deferrable=Deferrable.IMMEDIATE,
include=['cancelled'],
)
constraint_7 = ExclusionConstraint(
name='exclude_overlapping',
expressions=[
('datespan', RangeOperators.OVERLAPS),
('room', RangeOperators.EQUAL),
],
include=['cancelled'],
)
constraint_8 = ExclusionConstraint(
name='exclude_overlapping',
expressions=[
('datespan', RangeOperators.OVERLAPS),
('room', RangeOperators.EQUAL),
],
include=['cancelled'],
opclasses=['range_ops', 'range_ops']
)
constraint_9 = ExclusionConstraint(
name='exclude_overlapping',
expressions=[
('datespan', RangeOperators.OVERLAPS),
('room', RangeOperators.EQUAL),
],
opclasses=['range_ops', 'range_ops']
)
self.assertEqual(constraint_1, constraint_1)
self.assertEqual(constraint_1, mock.ANY)
self.assertNotEqual(constraint_1, constraint_2)
self.assertNotEqual(constraint_1, constraint_3)
self.assertNotEqual(constraint_1, constraint_4)
self.assertNotEqual(constraint_2, constraint_3)
self.assertNotEqual(constraint_2, constraint_4)
self.assertNotEqual(constraint_2, constraint_7)
self.assertNotEqual(constraint_2, constraint_9)
self.assertNotEqual(constraint_4, constraint_5)
self.assertNotEqual(constraint_5, constraint_6)
self.assertNotEqual(constraint_7, constraint_8)
self.assertNotEqual(constraint_1, object())
def test_deconstruct(self):
constraint = ExclusionConstraint(
name='exclude_overlapping',
expressions=[('datespan', RangeOperators.OVERLAPS), ('room', RangeOperators.EQUAL)],
)
path, args, kwargs = constraint.deconstruct()
self.assertEqual(path, 'django.contrib.postgres.constraints.ExclusionConstraint')
self.assertEqual(args, ())
self.assertEqual(kwargs, {
'name': 'exclude_overlapping',
'expressions': [('datespan', RangeOperators.OVERLAPS), ('room', RangeOperators.EQUAL)],
})
def test_deconstruct_index_type(self):
constraint = ExclusionConstraint(
name='exclude_overlapping',
index_type='SPGIST',
expressions=[('datespan', RangeOperators.OVERLAPS), ('room', RangeOperators.EQUAL)],
)
path, args, kwargs = constraint.deconstruct()
self.assertEqual(path, 'django.contrib.postgres.constraints.ExclusionConstraint')
self.assertEqual(args, ())
self.assertEqual(kwargs, {
'name': 'exclude_overlapping',
'index_type': 'SPGIST',
'expressions': [('datespan', RangeOperators.OVERLAPS), ('room', RangeOperators.EQUAL)],
})
def test_deconstruct_condition(self):
constraint = ExclusionConstraint(
name='exclude_overlapping',
expressions=[('datespan', RangeOperators.OVERLAPS), ('room', RangeOperators.EQUAL)],
condition=Q(cancelled=False),
)
path, args, kwargs = constraint.deconstruct()
self.assertEqual(path, 'django.contrib.postgres.constraints.ExclusionConstraint')
self.assertEqual(args, ())
self.assertEqual(kwargs, {
'name': 'exclude_overlapping',
'expressions': [('datespan', RangeOperators.OVERLAPS), ('room', RangeOperators.EQUAL)],
'condition': Q(cancelled=False),
})
def test_deconstruct_deferrable(self):
constraint = ExclusionConstraint(
name='exclude_overlapping',
expressions=[('datespan', RangeOperators.OVERLAPS)],
deferrable=Deferrable.DEFERRED,
)
path, args, kwargs = constraint.deconstruct()
self.assertEqual(path, 'django.contrib.postgres.constraints.ExclusionConstraint')
self.assertEqual(args, ())
self.assertEqual(kwargs, {
'name': 'exclude_overlapping',
'expressions': [('datespan', RangeOperators.OVERLAPS)],
'deferrable': Deferrable.DEFERRED,
})
def test_deconstruct_include(self):
constraint = ExclusionConstraint(
name='exclude_overlapping',
expressions=[('datespan', RangeOperators.OVERLAPS)],
include=['cancelled', 'room'],
)
path, args, kwargs = constraint.deconstruct()
self.assertEqual(path, 'django.contrib.postgres.constraints.ExclusionConstraint')
self.assertEqual(args, ())
self.assertEqual(kwargs, {
'name': 'exclude_overlapping',
'expressions': [('datespan', RangeOperators.OVERLAPS)],
'include': ('cancelled', 'room'),
})
def test_deconstruct_opclasses(self):
constraint = ExclusionConstraint(
name='exclude_overlapping',
expressions=[('datespan', RangeOperators.OVERLAPS)],
opclasses=['range_ops'],
)
path, args, kwargs = constraint.deconstruct()
self.assertEqual(path, 'django.contrib.postgres.constraints.ExclusionConstraint')
self.assertEqual(args, ())
self.assertEqual(kwargs, {
'name': 'exclude_overlapping',
'expressions': [('datespan', RangeOperators.OVERLAPS)],
'opclasses': ['range_ops'],
})
def _test_range_overlaps(self, constraint):
# Create exclusion constraint.
self.assertNotIn(constraint.name, self.get_constraints(HotelReservation._meta.db_table))
with connection.schema_editor() as editor:
editor.add_constraint(HotelReservation, constraint)
self.assertIn(constraint.name, self.get_constraints(HotelReservation._meta.db_table))
# Add initial reservations.
room101 = Room.objects.create(number=101)
room102 = Room.objects.create(number=102)
datetimes = [
timezone.datetime(2018, 6, 20),
timezone.datetime(2018, 6, 24),
timezone.datetime(2018, 6, 26),
timezone.datetime(2018, 6, 28),
timezone.datetime(2018, 6, 29),
]
HotelReservation.objects.create(
datespan=DateRange(datetimes[0].date(), datetimes[1].date()),
start=datetimes[0],
end=datetimes[1],
room=room102,
)
HotelReservation.objects.create(
datespan=DateRange(datetimes[1].date(), datetimes[3].date()),
start=datetimes[1],
end=datetimes[3],
room=room102,
)
# Overlap dates.
with self.assertRaises(IntegrityError), transaction.atomic():
reservation = HotelReservation(
datespan=(datetimes[1].date(), datetimes[2].date()),
start=datetimes[1],
end=datetimes[2],
room=room102,
)
reservation.save()
# Valid range.
HotelReservation.objects.bulk_create([
# Other room.
HotelReservation(
datespan=(datetimes[1].date(), datetimes[2].date()),
start=datetimes[1],
end=datetimes[2],
room=room101,
),
# Cancelled reservation.
HotelReservation(
datespan=(datetimes[1].date(), datetimes[1].date()),
start=datetimes[1],
end=datetimes[2],
room=room102,
cancelled=True,
),
# Other adjacent dates.
HotelReservation(
datespan=(datetimes[3].date(), datetimes[4].date()),
start=datetimes[3],
end=datetimes[4],
room=room102,
),
])
def test_range_overlaps_custom(self):
class TsTzRange(Func):
function = 'TSTZRANGE'
output_field = DateTimeRangeField()
constraint = ExclusionConstraint(
name='exclude_overlapping_reservations_custom',
expressions=[
(TsTzRange('start', 'end', RangeBoundary()), RangeOperators.OVERLAPS),
('room', RangeOperators.EQUAL)
],
condition=Q(cancelled=False),
opclasses=['range_ops', 'gist_int4_ops'],
)
self._test_range_overlaps(constraint)
def test_range_overlaps(self):
constraint = ExclusionConstraint(
name='exclude_overlapping_reservations',
expressions=[
(F('datespan'), RangeOperators.OVERLAPS),
('room', RangeOperators.EQUAL)
],
condition=Q(cancelled=False),
)
self._test_range_overlaps(constraint)
def test_range_adjacent(self):
constraint_name = 'ints_adjacent'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[('ints', RangeOperators.ADJACENT_TO)],
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
RangesModel.objects.create(ints=(20, 50))
with self.assertRaises(IntegrityError), transaction.atomic():
RangesModel.objects.create(ints=(10, 20))
RangesModel.objects.create(ints=(10, 19))
RangesModel.objects.create(ints=(51, 60))
# Drop the constraint.
with connection.schema_editor() as editor:
editor.remove_constraint(RangesModel, constraint)
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
def test_expressions_with_params(self):
constraint_name = 'scene_left_equal'
self.assertNotIn(constraint_name, self.get_constraints(Scene._meta.db_table))
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[(Left('scene', 4), RangeOperators.EQUAL)],
)
with connection.schema_editor() as editor:
editor.add_constraint(Scene, constraint)
self.assertIn(constraint_name, self.get_constraints(Scene._meta.db_table))
def test_expressions_with_key_transform(self):
constraint_name = 'exclude_overlapping_reservations_smoking'
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[
(F('datespan'), RangeOperators.OVERLAPS),
(KeyTextTransform('smoking', 'requirements'), RangeOperators.EQUAL),
],
)
with connection.schema_editor() as editor:
editor.add_constraint(HotelReservation, constraint)
self.assertIn(
constraint_name,
self.get_constraints(HotelReservation._meta.db_table),
)
def test_range_adjacent_initially_deferred(self):
constraint_name = 'ints_adjacent_deferred'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[('ints', RangeOperators.ADJACENT_TO)],
deferrable=Deferrable.DEFERRED,
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
RangesModel.objects.create(ints=(20, 50))
adjacent_range = RangesModel.objects.create(ints=(10, 20))
# Constraint behavior can be changed with SET CONSTRAINTS.
with self.assertRaises(IntegrityError):
with transaction.atomic(), connection.cursor() as cursor:
quoted_name = connection.ops.quote_name(constraint_name)
cursor.execute('SET CONSTRAINTS %s IMMEDIATE' % quoted_name)
# Remove adjacent range before the end of transaction.
adjacent_range.delete()
RangesModel.objects.create(ints=(10, 19))
RangesModel.objects.create(ints=(51, 60))
@skipUnlessDBFeature('supports_covering_gist_indexes')
def test_range_adjacent_include(self):
constraint_name = 'ints_adjacent_include'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[('ints', RangeOperators.ADJACENT_TO)],
include=['decimals', 'ints'],
index_type='gist',
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
RangesModel.objects.create(ints=(20, 50))
with self.assertRaises(IntegrityError), transaction.atomic():
RangesModel.objects.create(ints=(10, 20))
RangesModel.objects.create(ints=(10, 19))
RangesModel.objects.create(ints=(51, 60))
@skipUnlessDBFeature('supports_covering_gist_indexes')
def test_range_adjacent_include_condition(self):
constraint_name = 'ints_adjacent_include_condition'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[('ints', RangeOperators.ADJACENT_TO)],
include=['decimals'],
condition=Q(id__gte=100),
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
@skipUnlessDBFeature('supports_covering_gist_indexes')
def test_range_adjacent_include_deferrable(self):
constraint_name = 'ints_adjacent_include_deferrable'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[('ints', RangeOperators.ADJACENT_TO)],
include=['decimals'],
deferrable=Deferrable.DEFERRED,
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
def test_include_not_supported(self):
constraint_name = 'ints_adjacent_include_not_supported'
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[('ints', RangeOperators.ADJACENT_TO)],
include=['id'],
)
msg = 'Covering exclusion constraints requires PostgreSQL 12+.'
with connection.schema_editor() as editor:
with mock.patch(
'django.db.backends.postgresql.features.DatabaseFeatures.supports_covering_gist_indexes',
False,
):
with self.assertRaisesMessage(NotSupportedError, msg):
editor.add_constraint(RangesModel, constraint)
def test_range_adjacent_opclasses(self):
constraint_name = 'ints_adjacent_opclasses'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[('ints', RangeOperators.ADJACENT_TO)],
opclasses=['range_ops'],
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
RangesModel.objects.create(ints=(20, 50))
with self.assertRaises(IntegrityError), transaction.atomic():
RangesModel.objects.create(ints=(10, 20))
RangesModel.objects.create(ints=(10, 19))
RangesModel.objects.create(ints=(51, 60))
# Drop the constraint.
with connection.schema_editor() as editor:
editor.remove_constraint(RangesModel, constraint)
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
def test_range_adjacent_opclasses_condition(self):
constraint_name = 'ints_adjacent_opclasses_condition'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[('ints', RangeOperators.ADJACENT_TO)],
opclasses=['range_ops'],
condition=Q(id__gte=100),
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
def test_range_adjacent_opclasses_deferrable(self):
constraint_name = 'ints_adjacent_opclasses_deferrable'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[('ints', RangeOperators.ADJACENT_TO)],
opclasses=['range_ops'],
deferrable=Deferrable.DEFERRED,
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
@skipUnlessDBFeature('supports_covering_gist_indexes')
def test_range_adjacent_opclasses_include(self):
constraint_name = 'ints_adjacent_opclasses_include'
self.assertNotIn(constraint_name, self.get_constraints(RangesModel._meta.db_table))
constraint = ExclusionConstraint(
name=constraint_name,
expressions=[('ints', RangeOperators.ADJACENT_TO)],
opclasses=['range_ops'],
include=['decimals'],
)
with connection.schema_editor() as editor:
editor.add_constraint(RangesModel, constraint)
self.assertIn(constraint_name, self.get_constraints(RangesModel._meta.db_table)) | 0.645232 | 0.34679 |
import time
import logging
import json
from sjsclient import client
logging.basicConfig()
logger = logging.getLogger()
logger.setLevel(logging.INFO)
sjs = client.Client("http://jobserver.ml-test-blog.internal:8090")
myApp = sjs.apps.get("ml")
myContext = sjs.contexts.get("ml-context")
def testHandler(event, context):
logger.info('got event{}'.format(event))
s3DataLocProtocol = "\"s3://{}\"".format(event['s3DataLoc'])
s3ModelLocProtocol = "\"s3://{}\"".format(event['s3ModelLoc'])
conf = '{'+'s3DataLoc:{},s3ModelLoc:{}'.format(s3DataLocProtocol,s3ModelLocProtocol)+'}'
class_path = "com.amazonaws.proserv.ml.TestParams"
myJob = sjs.jobs.create(myApp, class_path, conf = conf, ctx = myContext)
myId = myJob.jobId
while myJob.status != "FINISHED":
time.sleep(2)
myJob = sjs.jobs.get(myId)
return {
'result' : sjs.jobs.get(myId).result
}
def loadHandler(event, context):
logger.info('got event{}'.format(event))
s3DataLocProtocol = "\"s3://{}\"".format(event['s3DataLoc'])
s3ModelLocProtocol = "\"s3://{}\"".format(event['s3ModelLoc'])
conf = '{'+'s3DataLoc:{},s3ModelLoc:{}'.format(s3DataLocProtocol,s3ModelLocProtocol)+'}'
class_path = "com.amazonaws.proserv.ml.LoadModelAndData"
myJob = sjs.jobs.create(myApp, class_path, conf = conf, ctx = myContext)
myId = myJob.jobId
return {
'result' : 'Request Submitted with ID '+myJob.jobId+'. It should be ready shortly.'
}
def recommenderHandler(event, context):
logger.info('got event{}'.format(event))
userId = event['userId']
conf = '{'+'userId:{}'.format(userId)+'}'
class_path = "com.amazonaws.proserv.ml.MoviesRec"
myJob = sjs.jobs.create(myApp, class_path, conf = conf, ctx = myContext)
myId = myJob.jobId
while myJob.status != "FINISHED":
time.sleep(2)
myJob = sjs.jobs.get(myId)
return {
'result' : sjs.jobs.get(myId).result
}
def genreHandler(event, context):
logger.info('got event{}'.format(event))
userId = event['userId']
genre = event['genre']
conf = '{'+'userId:{},genre:{}'.format(userId,genre)+'}'
class_path = "com.amazonaws.proserv.ml.MoviesRecByGenre"
myJob = sjs.jobs.create(myApp, class_path, conf = conf, ctx = myContext)
myId = myJob.jobId
while myJob.status != "FINISHED":
time.sleep(2)
myJob = sjs.jobs.get(myId)
return {
'result' : sjs.jobs.get(myId).result,
}
if __name__ == '__main__':
event = 'none'
context = 'none'
#Uncomment the follwing lines to test...one at a time
#print(testHandler(event, context))
#print(loadHandler(event, context))
#print(recommenderHandler(event, context))
#print(genreHandler(event, context)) | aws-blog-jobserver-emr/python_lambda/models.py | import time
import logging
import json
from sjsclient import client
logging.basicConfig()
logger = logging.getLogger()
logger.setLevel(logging.INFO)
sjs = client.Client("http://jobserver.ml-test-blog.internal:8090")
myApp = sjs.apps.get("ml")
myContext = sjs.contexts.get("ml-context")
def testHandler(event, context):
logger.info('got event{}'.format(event))
s3DataLocProtocol = "\"s3://{}\"".format(event['s3DataLoc'])
s3ModelLocProtocol = "\"s3://{}\"".format(event['s3ModelLoc'])
conf = '{'+'s3DataLoc:{},s3ModelLoc:{}'.format(s3DataLocProtocol,s3ModelLocProtocol)+'}'
class_path = "com.amazonaws.proserv.ml.TestParams"
myJob = sjs.jobs.create(myApp, class_path, conf = conf, ctx = myContext)
myId = myJob.jobId
while myJob.status != "FINISHED":
time.sleep(2)
myJob = sjs.jobs.get(myId)
return {
'result' : sjs.jobs.get(myId).result
}
def loadHandler(event, context):
logger.info('got event{}'.format(event))
s3DataLocProtocol = "\"s3://{}\"".format(event['s3DataLoc'])
s3ModelLocProtocol = "\"s3://{}\"".format(event['s3ModelLoc'])
conf = '{'+'s3DataLoc:{},s3ModelLoc:{}'.format(s3DataLocProtocol,s3ModelLocProtocol)+'}'
class_path = "com.amazonaws.proserv.ml.LoadModelAndData"
myJob = sjs.jobs.create(myApp, class_path, conf = conf, ctx = myContext)
myId = myJob.jobId
return {
'result' : 'Request Submitted with ID '+myJob.jobId+'. It should be ready shortly.'
}
def recommenderHandler(event, context):
logger.info('got event{}'.format(event))
userId = event['userId']
conf = '{'+'userId:{}'.format(userId)+'}'
class_path = "com.amazonaws.proserv.ml.MoviesRec"
myJob = sjs.jobs.create(myApp, class_path, conf = conf, ctx = myContext)
myId = myJob.jobId
while myJob.status != "FINISHED":
time.sleep(2)
myJob = sjs.jobs.get(myId)
return {
'result' : sjs.jobs.get(myId).result
}
def genreHandler(event, context):
logger.info('got event{}'.format(event))
userId = event['userId']
genre = event['genre']
conf = '{'+'userId:{},genre:{}'.format(userId,genre)+'}'
class_path = "com.amazonaws.proserv.ml.MoviesRecByGenre"
myJob = sjs.jobs.create(myApp, class_path, conf = conf, ctx = myContext)
myId = myJob.jobId
while myJob.status != "FINISHED":
time.sleep(2)
myJob = sjs.jobs.get(myId)
return {
'result' : sjs.jobs.get(myId).result,
}
if __name__ == '__main__':
event = 'none'
context = 'none'
#Uncomment the follwing lines to test...one at a time
#print(testHandler(event, context))
#print(loadHandler(event, context))
#print(recommenderHandler(event, context))
#print(genreHandler(event, context)) | 0.158695 | 0.049543 |
WIDTH = 8
HEIGHT = 8
FIRST = 0x20
LAST = 0x7f
_FONT =\
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b'\x00\x10\x38\x6c\xc6\xc6\xfe\x00'\
FONT = memoryview(_FONT) | fonts/diamonstealth64_8x8.py | WIDTH = 8
HEIGHT = 8
FIRST = 0x20
LAST = 0x7f
_FONT =\
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b'\x70\x30\x30\x30\x30\x30\x78\x00'\
b'\x00\x00\xcc\xfe\xfe\xd6\xd6\x00'\
b'\x00\x00\xb8\xcc\xcc\xcc\xcc\x00'\
b'\x00\x00\x78\xcc\xcc\xcc\x78\x00'\
b'\x00\x00\xdc\x66\x66\x7c\x60\xf0'\
b'\x00\x00\x76\xcc\xcc\x7c\x0c\x1e'\
b'\x00\x00\xdc\x76\x62\x60\xf0\x00'\
b'\x00\x00\x7c\xc0\x70\x1c\xf8\x00'\
b'\x10\x30\xfc\x30\x30\x34\x18\x00'\
b'\x00\x00\xcc\xcc\xcc\xcc\x76\x00'\
b'\x00\x00\xcc\xcc\xcc\x78\x30\x00'\
b'\x00\x00\xc6\xc6\xd6\xfe\x6c\x00'\
b'\x00\x00\xc6\x6c\x38\x6c\xc6\x00'\
b'\x00\x00\xcc\xcc\xcc\x7c\x0c\xf8'\
b'\x00\x00\xfc\x98\x30\x64\xfc\x00'\
b'\x1c\x30\x30\xe0\x30\x30\x1c\x00'\
b'\x18\x18\x18\x00\x18\x18\x18\x00'\
b'\xe0\x30\x30\x1c\x30\x30\xe0\x00'\
b'\x76\xdc\x00\x00\x00\x00\x00\x00'\
b'\x00\x10\x38\x6c\xc6\xc6\xfe\x00'\
FONT = memoryview(_FONT) | 0.130161 | 0.462109 |
import click
from tripaille.cli import pass_context
from tripaille.decorators import custom_exception, str_output
@click.command('load_blast')
@click.argument("name", type=str)
@click.argument("program", type=str)
@click.argument("programversion", type=str)
@click.argument("sourcename", type=str)
@click.argument("blast_output", type=str)
@click.option(
"--blast_ext",
help="If looking for files in a directory, extension of the blast result files",
type=str
)
@click.option(
"--blastdb",
help="Name of the database blasted against (must be in the Chado db table)",
type=str
)
@click.option(
"--blastdb_id",
help="ID of the database blasted against (must be in the Chado db table)",
type=str
)
@click.option(
"--blast_parameters",
help="Blast parameters used to produce these results",
type=str
)
@click.option(
"--query_re",
help="The regular expression that can uniquely identify the query name. This parameters is required if the feature name is not the first word in the blast query name.",
type=str
)
@click.option(
"--query_type",
help="The feature type (e.g. 'gene', 'mRNA', 'contig') of the query. It must be a valid Sequence Ontology term.",
type=str
)
@click.option(
"--query_uniquename",
help="Use this if the --query-re regular expression matches unique names instead of names in the database.",
is_flag=True
)
@click.option(
"--is_concat",
help="If the blast result file is simply a list of concatenated blast results.",
is_flag=True
)
@click.option(
"--search_keywords",
help="Extract keywords for Tripal search",
is_flag=True
)
@click.option(
"--no_parsed",
help="Maximum number of hits to parse per feature. Default=all",
default="all",
show_default=True,
type=str
)
@click.option(
"--no_wait",
help="Do not wait for job to complete",
is_flag=True
)
@click.option(
"--algorithm",
help="analysis algorithm",
type=str
)
@click.option(
"--sourceversion",
help="analysis sourceversion",
type=str
)
@click.option(
"--sourceuri",
help="analysis sourceuri",
type=str
)
@click.option(
"--description",
help="analysis description",
type=str
)
@click.option(
"--date_executed",
help="analysis date_executed (yyyy-mm-dd)",
type=str
)
@pass_context
@custom_exception
@str_output
def cli(ctx, name, program, programversion, sourcename, blast_output, blast_ext="", blastdb="", blastdb_id="", blast_parameters="", query_re="", query_type="", query_uniquename=False, is_concat=False, search_keywords=False, no_parsed="all", no_wait=False, algorithm="", sourceversion="", sourceuri="", description="", date_executed=""):
"""Create a Blast analysis
Output:
Loading information
"""
return ctx.gi.analysis.load_blast(name, program, programversion, sourcename, blast_output, blast_ext=blast_ext, blastdb=blastdb, blastdb_id=blastdb_id, blast_parameters=blast_parameters, query_re=query_re, query_type=query_type, query_uniquename=query_uniquename, is_concat=is_concat, search_keywords=search_keywords, no_parsed=no_parsed, no_wait=no_wait, algorithm=algorithm, sourceversion=sourceversion, sourceuri=sourceuri, description=description, date_executed=date_executed) | tripaille/commands/analysis/load_blast.py | import click
from tripaille.cli import pass_context
from tripaille.decorators import custom_exception, str_output
@click.command('load_blast')
@click.argument("name", type=str)
@click.argument("program", type=str)
@click.argument("programversion", type=str)
@click.argument("sourcename", type=str)
@click.argument("blast_output", type=str)
@click.option(
"--blast_ext",
help="If looking for files in a directory, extension of the blast result files",
type=str
)
@click.option(
"--blastdb",
help="Name of the database blasted against (must be in the Chado db table)",
type=str
)
@click.option(
"--blastdb_id",
help="ID of the database blasted against (must be in the Chado db table)",
type=str
)
@click.option(
"--blast_parameters",
help="Blast parameters used to produce these results",
type=str
)
@click.option(
"--query_re",
help="The regular expression that can uniquely identify the query name. This parameters is required if the feature name is not the first word in the blast query name.",
type=str
)
@click.option(
"--query_type",
help="The feature type (e.g. 'gene', 'mRNA', 'contig') of the query. It must be a valid Sequence Ontology term.",
type=str
)
@click.option(
"--query_uniquename",
help="Use this if the --query-re regular expression matches unique names instead of names in the database.",
is_flag=True
)
@click.option(
"--is_concat",
help="If the blast result file is simply a list of concatenated blast results.",
is_flag=True
)
@click.option(
"--search_keywords",
help="Extract keywords for Tripal search",
is_flag=True
)
@click.option(
"--no_parsed",
help="Maximum number of hits to parse per feature. Default=all",
default="all",
show_default=True,
type=str
)
@click.option(
"--no_wait",
help="Do not wait for job to complete",
is_flag=True
)
@click.option(
"--algorithm",
help="analysis algorithm",
type=str
)
@click.option(
"--sourceversion",
help="analysis sourceversion",
type=str
)
@click.option(
"--sourceuri",
help="analysis sourceuri",
type=str
)
@click.option(
"--description",
help="analysis description",
type=str
)
@click.option(
"--date_executed",
help="analysis date_executed (yyyy-mm-dd)",
type=str
)
@pass_context
@custom_exception
@str_output
def cli(ctx, name, program, programversion, sourcename, blast_output, blast_ext="", blastdb="", blastdb_id="", blast_parameters="", query_re="", query_type="", query_uniquename=False, is_concat=False, search_keywords=False, no_parsed="all", no_wait=False, algorithm="", sourceversion="", sourceuri="", description="", date_executed=""):
"""Create a Blast analysis
Output:
Loading information
"""
return ctx.gi.analysis.load_blast(name, program, programversion, sourcename, blast_output, blast_ext=blast_ext, blastdb=blastdb, blastdb_id=blastdb_id, blast_parameters=blast_parameters, query_re=query_re, query_type=query_type, query_uniquename=query_uniquename, is_concat=is_concat, search_keywords=search_keywords, no_parsed=no_parsed, no_wait=no_wait, algorithm=algorithm, sourceversion=sourceversion, sourceuri=sourceuri, description=description, date_executed=date_executed) | 0.577138 | 0.181173 |
from .abstract_data_operation_config import AbstractDataOperationConfig
from oci.util import formatted_flat_dict, NONE_SENTINEL, value_allowed_none_or_none_sentinel # noqa: F401
from oci.decorators import init_model_state_from_kwargs
@init_model_state_from_kwargs
class ReadOperationConfig(AbstractDataOperationConfig):
"""
The information about the read operation.
"""
def __init__(self, **kwargs):
"""
Initializes a new ReadOperationConfig object with values from keyword arguments. The default value of the :py:attr:`~oci.data_integration.models.ReadOperationConfig.model_type` attribute
of this class is ``READ_OPERATION_CONFIG`` and it should not be changed.
The following keyword arguments are supported (corresponding to the getters/setters of this class):
:param model_type:
The value to assign to the model_type property of this ReadOperationConfig.
Allowed values for this property are: "READ_OPERATION_CONFIG", "WRITE_OPERATION_CONFIG", 'UNKNOWN_ENUM_VALUE'.
Any unrecognized values returned by a service will be mapped to 'UNKNOWN_ENUM_VALUE'.
:type model_type: str
:param key:
The value to assign to the key property of this ReadOperationConfig.
:type key: str
:param model_version:
The value to assign to the model_version property of this ReadOperationConfig.
:type model_version: str
:param parent_ref:
The value to assign to the parent_ref property of this ReadOperationConfig.
:type parent_ref: oci.data_integration.models.ParentReference
:param operations:
The value to assign to the operations property of this ReadOperationConfig.
:type operations: list[oci.data_integration.models.PushDownOperation]
:param data_format:
The value to assign to the data_format property of this ReadOperationConfig.
:type data_format: oci.data_integration.models.DataFormat
:param partition_config:
The value to assign to the partition_config property of this ReadOperationConfig.
:type partition_config: oci.data_integration.models.PartitionConfig
:param read_attribute:
The value to assign to the read_attribute property of this ReadOperationConfig.
:type read_attribute: oci.data_integration.models.AbstractReadAttribute
:param object_status:
The value to assign to the object_status property of this ReadOperationConfig.
:type object_status: int
"""
self.swagger_types = {
'model_type': 'str',
'key': 'str',
'model_version': 'str',
'parent_ref': 'ParentReference',
'operations': 'list[PushDownOperation]',
'data_format': 'DataFormat',
'partition_config': 'PartitionConfig',
'read_attribute': 'AbstractReadAttribute',
'object_status': 'int'
}
self.attribute_map = {
'model_type': 'modelType',
'key': 'key',
'model_version': 'modelVersion',
'parent_ref': 'parentRef',
'operations': 'operations',
'data_format': 'dataFormat',
'partition_config': 'partitionConfig',
'read_attribute': 'readAttribute',
'object_status': 'objectStatus'
}
self._model_type = None
self._key = None
self._model_version = None
self._parent_ref = None
self._operations = None
self._data_format = None
self._partition_config = None
self._read_attribute = None
self._object_status = None
self._model_type = 'READ_OPERATION_CONFIG'
@property
def key(self):
"""
Gets the key of this ReadOperationConfig.
The object key.
:return: The key of this ReadOperationConfig.
:rtype: str
"""
return self._key
@key.setter
def key(self, key):
"""
Sets the key of this ReadOperationConfig.
The object key.
:param key: The key of this ReadOperationConfig.
:type: str
"""
self._key = key
@property
def model_version(self):
"""
Gets the model_version of this ReadOperationConfig.
The object's model version.
:return: The model_version of this ReadOperationConfig.
:rtype: str
"""
return self._model_version
@model_version.setter
def model_version(self, model_version):
"""
Sets the model_version of this ReadOperationConfig.
The object's model version.
:param model_version: The model_version of this ReadOperationConfig.
:type: str
"""
self._model_version = model_version
@property
def parent_ref(self):
"""
Gets the parent_ref of this ReadOperationConfig.
:return: The parent_ref of this ReadOperationConfig.
:rtype: oci.data_integration.models.ParentReference
"""
return self._parent_ref
@parent_ref.setter
def parent_ref(self, parent_ref):
"""
Sets the parent_ref of this ReadOperationConfig.
:param parent_ref: The parent_ref of this ReadOperationConfig.
:type: oci.data_integration.models.ParentReference
"""
self._parent_ref = parent_ref
@property
def operations(self):
"""
Gets the operations of this ReadOperationConfig.
An array of operations.
:return: The operations of this ReadOperationConfig.
:rtype: list[oci.data_integration.models.PushDownOperation]
"""
return self._operations
@operations.setter
def operations(self, operations):
"""
Sets the operations of this ReadOperationConfig.
An array of operations.
:param operations: The operations of this ReadOperationConfig.
:type: list[oci.data_integration.models.PushDownOperation]
"""
self._operations = operations
@property
def data_format(self):
"""
Gets the data_format of this ReadOperationConfig.
:return: The data_format of this ReadOperationConfig.
:rtype: oci.data_integration.models.DataFormat
"""
return self._data_format
@data_format.setter
def data_format(self, data_format):
"""
Sets the data_format of this ReadOperationConfig.
:param data_format: The data_format of this ReadOperationConfig.
:type: oci.data_integration.models.DataFormat
"""
self._data_format = data_format
@property
def partition_config(self):
"""
Gets the partition_config of this ReadOperationConfig.
:return: The partition_config of this ReadOperationConfig.
:rtype: oci.data_integration.models.PartitionConfig
"""
return self._partition_config
@partition_config.setter
def partition_config(self, partition_config):
"""
Sets the partition_config of this ReadOperationConfig.
:param partition_config: The partition_config of this ReadOperationConfig.
:type: oci.data_integration.models.PartitionConfig
"""
self._partition_config = partition_config
@property
def read_attribute(self):
"""
Gets the read_attribute of this ReadOperationConfig.
:return: The read_attribute of this ReadOperationConfig.
:rtype: oci.data_integration.models.AbstractReadAttribute
"""
return self._read_attribute
@read_attribute.setter
def read_attribute(self, read_attribute):
"""
Sets the read_attribute of this ReadOperationConfig.
:param read_attribute: The read_attribute of this ReadOperationConfig.
:type: oci.data_integration.models.AbstractReadAttribute
"""
self._read_attribute = read_attribute
@property
def object_status(self):
"""
Gets the object_status of this ReadOperationConfig.
The status of an object that can be set to value 1 for shallow references across objects, other values reserved.
:return: The object_status of this ReadOperationConfig.
:rtype: int
"""
return self._object_status
@object_status.setter
def object_status(self, object_status):
"""
Sets the object_status of this ReadOperationConfig.
The status of an object that can be set to value 1 for shallow references across objects, other values reserved.
:param object_status: The object_status of this ReadOperationConfig.
:type: int
"""
self._object_status = object_status
def __repr__(self):
return formatted_flat_dict(self)
def __eq__(self, other):
if other is None:
return False
return self.__dict__ == other.__dict__
def __ne__(self, other):
return not self == other | src/oci/data_integration/models/read_operation_config.py |
from .abstract_data_operation_config import AbstractDataOperationConfig
from oci.util import formatted_flat_dict, NONE_SENTINEL, value_allowed_none_or_none_sentinel # noqa: F401
from oci.decorators import init_model_state_from_kwargs
@init_model_state_from_kwargs
class ReadOperationConfig(AbstractDataOperationConfig):
"""
The information about the read operation.
"""
def __init__(self, **kwargs):
"""
Initializes a new ReadOperationConfig object with values from keyword arguments. The default value of the :py:attr:`~oci.data_integration.models.ReadOperationConfig.model_type` attribute
of this class is ``READ_OPERATION_CONFIG`` and it should not be changed.
The following keyword arguments are supported (corresponding to the getters/setters of this class):
:param model_type:
The value to assign to the model_type property of this ReadOperationConfig.
Allowed values for this property are: "READ_OPERATION_CONFIG", "WRITE_OPERATION_CONFIG", 'UNKNOWN_ENUM_VALUE'.
Any unrecognized values returned by a service will be mapped to 'UNKNOWN_ENUM_VALUE'.
:type model_type: str
:param key:
The value to assign to the key property of this ReadOperationConfig.
:type key: str
:param model_version:
The value to assign to the model_version property of this ReadOperationConfig.
:type model_version: str
:param parent_ref:
The value to assign to the parent_ref property of this ReadOperationConfig.
:type parent_ref: oci.data_integration.models.ParentReference
:param operations:
The value to assign to the operations property of this ReadOperationConfig.
:type operations: list[oci.data_integration.models.PushDownOperation]
:param data_format:
The value to assign to the data_format property of this ReadOperationConfig.
:type data_format: oci.data_integration.models.DataFormat
:param partition_config:
The value to assign to the partition_config property of this ReadOperationConfig.
:type partition_config: oci.data_integration.models.PartitionConfig
:param read_attribute:
The value to assign to the read_attribute property of this ReadOperationConfig.
:type read_attribute: oci.data_integration.models.AbstractReadAttribute
:param object_status:
The value to assign to the object_status property of this ReadOperationConfig.
:type object_status: int
"""
self.swagger_types = {
'model_type': 'str',
'key': 'str',
'model_version': 'str',
'parent_ref': 'ParentReference',
'operations': 'list[PushDownOperation]',
'data_format': 'DataFormat',
'partition_config': 'PartitionConfig',
'read_attribute': 'AbstractReadAttribute',
'object_status': 'int'
}
self.attribute_map = {
'model_type': 'modelType',
'key': 'key',
'model_version': 'modelVersion',
'parent_ref': 'parentRef',
'operations': 'operations',
'data_format': 'dataFormat',
'partition_config': 'partitionConfig',
'read_attribute': 'readAttribute',
'object_status': 'objectStatus'
}
self._model_type = None
self._key = None
self._model_version = None
self._parent_ref = None
self._operations = None
self._data_format = None
self._partition_config = None
self._read_attribute = None
self._object_status = None
self._model_type = 'READ_OPERATION_CONFIG'
@property
def key(self):
"""
Gets the key of this ReadOperationConfig.
The object key.
:return: The key of this ReadOperationConfig.
:rtype: str
"""
return self._key
@key.setter
def key(self, key):
"""
Sets the key of this ReadOperationConfig.
The object key.
:param key: The key of this ReadOperationConfig.
:type: str
"""
self._key = key
@property
def model_version(self):
"""
Gets the model_version of this ReadOperationConfig.
The object's model version.
:return: The model_version of this ReadOperationConfig.
:rtype: str
"""
return self._model_version
@model_version.setter
def model_version(self, model_version):
"""
Sets the model_version of this ReadOperationConfig.
The object's model version.
:param model_version: The model_version of this ReadOperationConfig.
:type: str
"""
self._model_version = model_version
@property
def parent_ref(self):
"""
Gets the parent_ref of this ReadOperationConfig.
:return: The parent_ref of this ReadOperationConfig.
:rtype: oci.data_integration.models.ParentReference
"""
return self._parent_ref
@parent_ref.setter
def parent_ref(self, parent_ref):
"""
Sets the parent_ref of this ReadOperationConfig.
:param parent_ref: The parent_ref of this ReadOperationConfig.
:type: oci.data_integration.models.ParentReference
"""
self._parent_ref = parent_ref
@property
def operations(self):
"""
Gets the operations of this ReadOperationConfig.
An array of operations.
:return: The operations of this ReadOperationConfig.
:rtype: list[oci.data_integration.models.PushDownOperation]
"""
return self._operations
@operations.setter
def operations(self, operations):
"""
Sets the operations of this ReadOperationConfig.
An array of operations.
:param operations: The operations of this ReadOperationConfig.
:type: list[oci.data_integration.models.PushDownOperation]
"""
self._operations = operations
@property
def data_format(self):
"""
Gets the data_format of this ReadOperationConfig.
:return: The data_format of this ReadOperationConfig.
:rtype: oci.data_integration.models.DataFormat
"""
return self._data_format
@data_format.setter
def data_format(self, data_format):
"""
Sets the data_format of this ReadOperationConfig.
:param data_format: The data_format of this ReadOperationConfig.
:type: oci.data_integration.models.DataFormat
"""
self._data_format = data_format
@property
def partition_config(self):
"""
Gets the partition_config of this ReadOperationConfig.
:return: The partition_config of this ReadOperationConfig.
:rtype: oci.data_integration.models.PartitionConfig
"""
return self._partition_config
@partition_config.setter
def partition_config(self, partition_config):
"""
Sets the partition_config of this ReadOperationConfig.
:param partition_config: The partition_config of this ReadOperationConfig.
:type: oci.data_integration.models.PartitionConfig
"""
self._partition_config = partition_config
@property
def read_attribute(self):
"""
Gets the read_attribute of this ReadOperationConfig.
:return: The read_attribute of this ReadOperationConfig.
:rtype: oci.data_integration.models.AbstractReadAttribute
"""
return self._read_attribute
@read_attribute.setter
def read_attribute(self, read_attribute):
"""
Sets the read_attribute of this ReadOperationConfig.
:param read_attribute: The read_attribute of this ReadOperationConfig.
:type: oci.data_integration.models.AbstractReadAttribute
"""
self._read_attribute = read_attribute
@property
def object_status(self):
"""
Gets the object_status of this ReadOperationConfig.
The status of an object that can be set to value 1 for shallow references across objects, other values reserved.
:return: The object_status of this ReadOperationConfig.
:rtype: int
"""
return self._object_status
@object_status.setter
def object_status(self, object_status):
"""
Sets the object_status of this ReadOperationConfig.
The status of an object that can be set to value 1 for shallow references across objects, other values reserved.
:param object_status: The object_status of this ReadOperationConfig.
:type: int
"""
self._object_status = object_status
def __repr__(self):
return formatted_flat_dict(self)
def __eq__(self, other):
if other is None:
return False
return self.__dict__ == other.__dict__
def __ne__(self, other):
return not self == other | 0.812793 | 0.302436 |
import hashlib
import json
import pathlib
from unittest import mock
from gs_quant.api.gs.risk import GsRiskApi
from gs_quant.json_encoder import JSONEncoder
from gs_quant.markets import PricingContext
from gs_quant.session import Environment, GsSession
def _remove_unwanted(json_text):
json_dict = json.loads(json_text)
if "asOfTime" in json_dict:
del json_dict["asOfTime"]
return json_dict
def load_json_from_resource(test_file_name, json_file_name):
with open(pathlib.Path(__file__).parents[1] / f'resources/{test_file_name}/{json_file_name}') as json_data:
return json.load(json_data)
def mock_request(method, path, payload, test_file_name):
queries = {
'assetsDataGSNWithRic':
'{"asOfTime": "2019-05-16T21:18:18.294Z", "limit": 4, "where": {"ric": ["GS.N"]}, "fields": ["ric", "id"]}',
'assetsDataGSNWithId':
'{"limit": 4, "fields": ["id", "ric"], "where": {"id": ["123456MW5E27U123456"]}}',
'assetsDataSPXWithRic':
'{"where": {"ric": [".SPX"]}, "limit": 4, "fields": ["ric", "id"]}',
'assetsDataSPXWithId':
'{"limit": 4, "fields": ["id", "ric"], "where": {"id": ["456123MW5E27U123456"]}}',
'dataQueryRic':
'{"fields": ["adjustedTradePrice"],'
' "format": "MessagePack", "where": {"assetId": ["123456MW5E27U123456"]}}',
'dataQuerySPX':
'{"fields": ["adjustedTradePrice"], "format": "MessagePack", "where": {"assetId": ["456123MW5E27U123456"]}}'
}
payload = _remove_unwanted(json.dumps(payload, cls=JSONEncoder) if payload else '{}')
if method == 'GET':
if path == '/data/datasets/TREOD':
return load_json_from_resource(test_file_name, 'datasets_treod_response.json')
elif method == 'POST':
if path == '/assets/data/query':
if payload == _remove_unwanted(queries['assetsDataGSNWithRic']) or \
payload == _remove_unwanted(queries['assetsDataGSNWithId']):
return load_json_from_resource(test_file_name, 'assets_data_query_response_gsn.json')
elif payload == _remove_unwanted(queries['assetsDataSPXWithRic']) or \
payload == _remove_unwanted(queries['assetsDataSPXWithId']):
return load_json_from_resource(test_file_name, 'assets_data_query_response_spx.json')
elif path == '/data/TREOD/query':
if payload == _remove_unwanted(queries['dataQueryRic']):
return load_json_from_resource(test_file_name, 'treod_query_response_gsn.json')
elif payload == _remove_unwanted(queries['dataQuerySPX']):
return load_json_from_resource(test_file_name, 'treod_query_response_spx.json')
raise Exception(f'Unhandled request. Method: {method}, Path: {path}, payload: {payload} not recognized.')
gs_risk_api_exec = GsRiskApi._exec
def get_risk_request_id(requests):
"""
This is not a formal equality of the risk request as it covers only the names of core components. When a formal
eq function is provided on risk_request then this should be replaced with something derived from that.
:param requests: a collection of RiskRequests
:type requests: tuple of RiskRequest
:return: hash
:rtype: str
"""
identifier = str(len(requests))
for request in requests:
identifier += '_'
identifier += '-'.join([pos.instrument.name for pos in request.positions])
identifier += '-'.join([r.__repr__() for r in request.measures])
date = request.pricing_and_market_data_as_of[0].pricing_date.strftime('%Y%b%d')
today = PricingContext().pricing_date.strftime('%Y%b%d')
identifier += 'today' if date == today else date
if request.scenario is not None:
scenario_identifier = []
for k, v in request.scenario.scenario.as_dict().items():
if k != 'shocks':
scenario_identifier.append(str(k) + "=" + str(v))
else:
shock_value = 'shock_value' + "=" + str(v[0].shock.value)
pattern = v[0].pattern
shock_pattern = 'shock_pattern' + "=" + '-'.join(
[str(m) for m in [pattern.mkt_type, pattern.mkt_asset, pattern.mkt_class]])
scenario_identifier.append(shock_value + "+" + shock_pattern)
identifier += '+'.join(sorted(scenario_identifier))
return hashlib.md5(identifier.encode('utf-8')).hexdigest()
class MockCalc:
def __init__(self, mocker, save_files=False, paths=pathlib.Path(__file__).parents[1], application='gs-quant'):
# do not save tests with save_files = True
self.save_files = save_files
self.mocker = mocker
self.paths = paths
self.application = application
def __enter__(self):
if self.save_files:
GsSession.use(Environment.PROD, None, None, application=self.application)
self.mocker.patch.object(GsRiskApi, '_exec', side_effect=self.mock_calc_create_files)
else:
from gs_quant.session import OAuth2Session
OAuth2Session.init = mock.MagicMock(return_value=None)
GsSession.use(Environment.PROD, 'fake_client_id', 'fake_secret', application=self.application)
self.mocker.patch.object(GsRiskApi, '_exec', side_effect=self.mock_calc)
def mock_calc(self, *args, **kwargs):
request = kwargs.get('request') or args[0]
with open(self.paths / f'calc_cache/request{get_risk_request_id(request)}.json') \
as json_data:
return json.load(json_data)
def mock_calc_create_files(self, *args, **kwargs):
# never leave a side_effect calling this function. Call it once to create the files, check them in
# and switch to mock_calc
def get_json(*i_args, **i_kwargs):
this_json = gs_risk_api_exec(*i_args, **i_kwargs)
return this_json
result_json = get_json(*args, **kwargs)
request = kwargs.get('request') or args[0]
with open(self.paths / f'calc_cache/request{get_risk_request_id(request)}.json',
'w') as json_data:
json.dump(result_json, json_data)
return result_json
def __exit__(self, exc_type, exc_val, exc_tb):
pass | gs_quant/test/utils/test_utils.py | import hashlib
import json
import pathlib
from unittest import mock
from gs_quant.api.gs.risk import GsRiskApi
from gs_quant.json_encoder import JSONEncoder
from gs_quant.markets import PricingContext
from gs_quant.session import Environment, GsSession
def _remove_unwanted(json_text):
json_dict = json.loads(json_text)
if "asOfTime" in json_dict:
del json_dict["asOfTime"]
return json_dict
def load_json_from_resource(test_file_name, json_file_name):
with open(pathlib.Path(__file__).parents[1] / f'resources/{test_file_name}/{json_file_name}') as json_data:
return json.load(json_data)
def mock_request(method, path, payload, test_file_name):
queries = {
'assetsDataGSNWithRic':
'{"asOfTime": "2019-05-16T21:18:18.294Z", "limit": 4, "where": {"ric": ["GS.N"]}, "fields": ["ric", "id"]}',
'assetsDataGSNWithId':
'{"limit": 4, "fields": ["id", "ric"], "where": {"id": ["123456MW5E27U123456"]}}',
'assetsDataSPXWithRic':
'{"where": {"ric": [".SPX"]}, "limit": 4, "fields": ["ric", "id"]}',
'assetsDataSPXWithId':
'{"limit": 4, "fields": ["id", "ric"], "where": {"id": ["456123MW5E27U123456"]}}',
'dataQueryRic':
'{"fields": ["adjustedTradePrice"],'
' "format": "MessagePack", "where": {"assetId": ["123456MW5E27U123456"]}}',
'dataQuerySPX':
'{"fields": ["adjustedTradePrice"], "format": "MessagePack", "where": {"assetId": ["456123MW5E27U123456"]}}'
}
payload = _remove_unwanted(json.dumps(payload, cls=JSONEncoder) if payload else '{}')
if method == 'GET':
if path == '/data/datasets/TREOD':
return load_json_from_resource(test_file_name, 'datasets_treod_response.json')
elif method == 'POST':
if path == '/assets/data/query':
if payload == _remove_unwanted(queries['assetsDataGSNWithRic']) or \
payload == _remove_unwanted(queries['assetsDataGSNWithId']):
return load_json_from_resource(test_file_name, 'assets_data_query_response_gsn.json')
elif payload == _remove_unwanted(queries['assetsDataSPXWithRic']) or \
payload == _remove_unwanted(queries['assetsDataSPXWithId']):
return load_json_from_resource(test_file_name, 'assets_data_query_response_spx.json')
elif path == '/data/TREOD/query':
if payload == _remove_unwanted(queries['dataQueryRic']):
return load_json_from_resource(test_file_name, 'treod_query_response_gsn.json')
elif payload == _remove_unwanted(queries['dataQuerySPX']):
return load_json_from_resource(test_file_name, 'treod_query_response_spx.json')
raise Exception(f'Unhandled request. Method: {method}, Path: {path}, payload: {payload} not recognized.')
gs_risk_api_exec = GsRiskApi._exec
def get_risk_request_id(requests):
"""
This is not a formal equality of the risk request as it covers only the names of core components. When a formal
eq function is provided on risk_request then this should be replaced with something derived from that.
:param requests: a collection of RiskRequests
:type requests: tuple of RiskRequest
:return: hash
:rtype: str
"""
identifier = str(len(requests))
for request in requests:
identifier += '_'
identifier += '-'.join([pos.instrument.name for pos in request.positions])
identifier += '-'.join([r.__repr__() for r in request.measures])
date = request.pricing_and_market_data_as_of[0].pricing_date.strftime('%Y%b%d')
today = PricingContext().pricing_date.strftime('%Y%b%d')
identifier += 'today' if date == today else date
if request.scenario is not None:
scenario_identifier = []
for k, v in request.scenario.scenario.as_dict().items():
if k != 'shocks':
scenario_identifier.append(str(k) + "=" + str(v))
else:
shock_value = 'shock_value' + "=" + str(v[0].shock.value)
pattern = v[0].pattern
shock_pattern = 'shock_pattern' + "=" + '-'.join(
[str(m) for m in [pattern.mkt_type, pattern.mkt_asset, pattern.mkt_class]])
scenario_identifier.append(shock_value + "+" + shock_pattern)
identifier += '+'.join(sorted(scenario_identifier))
return hashlib.md5(identifier.encode('utf-8')).hexdigest()
class MockCalc:
def __init__(self, mocker, save_files=False, paths=pathlib.Path(__file__).parents[1], application='gs-quant'):
# do not save tests with save_files = True
self.save_files = save_files
self.mocker = mocker
self.paths = paths
self.application = application
def __enter__(self):
if self.save_files:
GsSession.use(Environment.PROD, None, None, application=self.application)
self.mocker.patch.object(GsRiskApi, '_exec', side_effect=self.mock_calc_create_files)
else:
from gs_quant.session import OAuth2Session
OAuth2Session.init = mock.MagicMock(return_value=None)
GsSession.use(Environment.PROD, 'fake_client_id', 'fake_secret', application=self.application)
self.mocker.patch.object(GsRiskApi, '_exec', side_effect=self.mock_calc)
def mock_calc(self, *args, **kwargs):
request = kwargs.get('request') or args[0]
with open(self.paths / f'calc_cache/request{get_risk_request_id(request)}.json') \
as json_data:
return json.load(json_data)
def mock_calc_create_files(self, *args, **kwargs):
# never leave a side_effect calling this function. Call it once to create the files, check them in
# and switch to mock_calc
def get_json(*i_args, **i_kwargs):
this_json = gs_risk_api_exec(*i_args, **i_kwargs)
return this_json
result_json = get_json(*args, **kwargs)
request = kwargs.get('request') or args[0]
with open(self.paths / f'calc_cache/request{get_risk_request_id(request)}.json',
'w') as json_data:
json.dump(result_json, json_data)
return result_json
def __exit__(self, exc_type, exc_val, exc_tb):
pass | 0.441673 | 0.211722 |
import yaml
import os
try:
from yaml import CLoader as Loader
except ImportError:
from yaml import Loader
def load_config(config_file):
"""Load config file with yaml.
Args:
config_file: config_file
Returns:
config file
"""
with open(config_file, 'r') as stream:
config = yaml.load(stream, Loader=Loader)
return config
def get_strict_filter_parameters(config_file):
"""Get strict filter from config file.
Args:
config_file: config_file
Returns:
strict filter
"""
config = load_config(config_file)
return config['strict_filter']
def get_loose_filter_parameters(config_file):
"""Get loose filter from config file.
Args:
config_file: config_file
Returns:
loose filter
"""
config = load_config(config_file)
return config['loose_filter']
def get_sample_ids(config_file):
"""Get sample ids from config file.
Args:
config_file: config_file
Returns:
sample ids
"""
config = load_config(config_file)
return config['samples'].keys()
def get_result_dir(config_file):
"""Get path to results directory from config file.
Args:
config_file: config_file
Returns:
results directory
"""
config = load_config(config_file)
return os.path.join(config['working_dir'], config['results_dir'])
def get_vcf_files(config_file):
"""Get path to vcf files from config file.
Args:
config_file: config_file
Returns:
path to vcf files
"""
vcf_files = {}
config = load_config(config_file)
for sample_id in get_sample_ids(config_file):
if os.path.exists(config['samples'][sample_id]['vcf_file']):
vcf_files[sample_id] = config['samples'][sample_id]['vcf_file']
else:
vcf_files[sample_id] = os.path.join(config['working_dir'], config['samples'][sample_id]['vcf_file'])
return vcf_files
def get_maf_files(config_file):
"""Get path to maf files from config file.
Args:
config_file: config_file
Returns:
path to maf files
"""
maf_files = {}
config = load_config(config_file)
for sample_id in get_sample_ids(config_file):
if os.path.exists(config['samples'][sample_id]['maf_file']):
maf_files[sample_id] = config['samples'][sample_id]['maf_file']
else:
maf_files[sample_id] = os.path.join(config['working_dir'], config['samples'][sample_id]['maf_file'])
return maf_files
def get_type(config_file):
"""Get sampel types from config file.
Args:
config_file: config_file
Returns:
sample types
"""
types = {}
config = load_config(config_file)
for sample_id in get_sample_ids(config_file):
types[sample_id] = config['samples'][sample_id]['type']
return types | src/parameters.py | import yaml
import os
try:
from yaml import CLoader as Loader
except ImportError:
from yaml import Loader
def load_config(config_file):
"""Load config file with yaml.
Args:
config_file: config_file
Returns:
config file
"""
with open(config_file, 'r') as stream:
config = yaml.load(stream, Loader=Loader)
return config
def get_strict_filter_parameters(config_file):
"""Get strict filter from config file.
Args:
config_file: config_file
Returns:
strict filter
"""
config = load_config(config_file)
return config['strict_filter']
def get_loose_filter_parameters(config_file):
"""Get loose filter from config file.
Args:
config_file: config_file
Returns:
loose filter
"""
config = load_config(config_file)
return config['loose_filter']
def get_sample_ids(config_file):
"""Get sample ids from config file.
Args:
config_file: config_file
Returns:
sample ids
"""
config = load_config(config_file)
return config['samples'].keys()
def get_result_dir(config_file):
"""Get path to results directory from config file.
Args:
config_file: config_file
Returns:
results directory
"""
config = load_config(config_file)
return os.path.join(config['working_dir'], config['results_dir'])
def get_vcf_files(config_file):
"""Get path to vcf files from config file.
Args:
config_file: config_file
Returns:
path to vcf files
"""
vcf_files = {}
config = load_config(config_file)
for sample_id in get_sample_ids(config_file):
if os.path.exists(config['samples'][sample_id]['vcf_file']):
vcf_files[sample_id] = config['samples'][sample_id]['vcf_file']
else:
vcf_files[sample_id] = os.path.join(config['working_dir'], config['samples'][sample_id]['vcf_file'])
return vcf_files
def get_maf_files(config_file):
"""Get path to maf files from config file.
Args:
config_file: config_file
Returns:
path to maf files
"""
maf_files = {}
config = load_config(config_file)
for sample_id in get_sample_ids(config_file):
if os.path.exists(config['samples'][sample_id]['maf_file']):
maf_files[sample_id] = config['samples'][sample_id]['maf_file']
else:
maf_files[sample_id] = os.path.join(config['working_dir'], config['samples'][sample_id]['maf_file'])
return maf_files
def get_type(config_file):
"""Get sampel types from config file.
Args:
config_file: config_file
Returns:
sample types
"""
types = {}
config = load_config(config_file)
for sample_id in get_sample_ids(config_file):
types[sample_id] = config['samples'][sample_id]['type']
return types | 0.579995 | 0.144179 |
from os import listdir
from os.path import exists, join, isfile
from argparse import ArgumentParser
from tqdm import tqdm
def load_label_map(file_path):
action_names = []
with open(file_path) as input_stream:
for line in input_stream:
line_parts = line.strip().split(';')
if len(line_parts) != 1:
continue
action_name = line_parts[0]
action_names.append(action_name)
assert len(action_names) > 0
unique_names = set(action_names)
assert len(unique_names) == len(action_names)
out_data = {name: label for label, name in enumerate(action_names)}
return out_data
def load_annotation(annot_path, label_map):
out_data = []
with open(annot_path) as input_stream:
for line in input_stream:
line_parts = line.strip().split(';')
if len(line_parts) != 2:
continue
rel_path, action_name = line_parts
assert action_name in label_map
action_id = label_map[action_name]
out_data.append((rel_path, action_id))
return out_data
def convert_annotation(src_annot, images_root, continuous_format):
out_data = []
for rel_path, action_id in tqdm(src_annot):
images_dir = join(images_root, rel_path)
if not exists(images_dir):
continue
files = [f for f in listdir(images_dir) if isfile(join(images_dir, f))]
if len(files) <= 1:
continue
frame_ids = [int(f.split('.')[0]) for f in files]
assert min(frame_ids) == 1
assert len(frame_ids) == max(frame_ids)
num_frames = len(frame_ids)
if continuous_format:
out_data.append((rel_path, action_id, 0, num_frames - 1, 0, num_frames - 1, 30.0))
else:
out_data.append((rel_path, num_frames, action_id))
return out_data
def dump_annotation(annot, out_path):
with open(out_path, 'w') as output_stream:
for record in annot:
output_stream.write(' '.join([str(r) for r in record]) + '\n')
def main():
parser = ArgumentParser()
parser.add_argument('--label_map', '-lm', type=str, required=True)
parser.add_argument('--images_root', '-im', type=str, required=True)
parser.add_argument('--input_annot', '-ia', type=str, required=True)
parser.add_argument('--out_annot', '-oa', type=str, required=True)
args = parser.parse_args()
assert exists(args.label_map)
assert exists(args.images_root)
assert exists(args.input_annot)
label_map = load_label_map(args.label_map)
print('Loaded names for {} labels'.format(len(label_map)))
annot = load_annotation(args.input_annot, label_map)
print('Found {} records'.format(len(annot)))
converted_annot = convert_annotation(annot, args.images_root, continuous_format=True)
print('Converted {} / {} records'.format(len(converted_annot), len(annot)))
dump_annotation(converted_annot, args.out_annot)
print('Converted annotation is stored at: {}'.format(args.out_annot))
if __name__ == '__main__':
main() | models/action_recognition/model_templates/gesture-recognition/tools/data/prepare_jester_annot.py | from os import listdir
from os.path import exists, join, isfile
from argparse import ArgumentParser
from tqdm import tqdm
def load_label_map(file_path):
action_names = []
with open(file_path) as input_stream:
for line in input_stream:
line_parts = line.strip().split(';')
if len(line_parts) != 1:
continue
action_name = line_parts[0]
action_names.append(action_name)
assert len(action_names) > 0
unique_names = set(action_names)
assert len(unique_names) == len(action_names)
out_data = {name: label for label, name in enumerate(action_names)}
return out_data
def load_annotation(annot_path, label_map):
out_data = []
with open(annot_path) as input_stream:
for line in input_stream:
line_parts = line.strip().split(';')
if len(line_parts) != 2:
continue
rel_path, action_name = line_parts
assert action_name in label_map
action_id = label_map[action_name]
out_data.append((rel_path, action_id))
return out_data
def convert_annotation(src_annot, images_root, continuous_format):
out_data = []
for rel_path, action_id in tqdm(src_annot):
images_dir = join(images_root, rel_path)
if not exists(images_dir):
continue
files = [f for f in listdir(images_dir) if isfile(join(images_dir, f))]
if len(files) <= 1:
continue
frame_ids = [int(f.split('.')[0]) for f in files]
assert min(frame_ids) == 1
assert len(frame_ids) == max(frame_ids)
num_frames = len(frame_ids)
if continuous_format:
out_data.append((rel_path, action_id, 0, num_frames - 1, 0, num_frames - 1, 30.0))
else:
out_data.append((rel_path, num_frames, action_id))
return out_data
def dump_annotation(annot, out_path):
with open(out_path, 'w') as output_stream:
for record in annot:
output_stream.write(' '.join([str(r) for r in record]) + '\n')
def main():
parser = ArgumentParser()
parser.add_argument('--label_map', '-lm', type=str, required=True)
parser.add_argument('--images_root', '-im', type=str, required=True)
parser.add_argument('--input_annot', '-ia', type=str, required=True)
parser.add_argument('--out_annot', '-oa', type=str, required=True)
args = parser.parse_args()
assert exists(args.label_map)
assert exists(args.images_root)
assert exists(args.input_annot)
label_map = load_label_map(args.label_map)
print('Loaded names for {} labels'.format(len(label_map)))
annot = load_annotation(args.input_annot, label_map)
print('Found {} records'.format(len(annot)))
converted_annot = convert_annotation(annot, args.images_root, continuous_format=True)
print('Converted {} / {} records'.format(len(converted_annot), len(annot)))
dump_annotation(converted_annot, args.out_annot)
print('Converted annotation is stored at: {}'.format(args.out_annot))
if __name__ == '__main__':
main() | 0.454956 | 0.35928 |
import numpy as np
def load_streamflow(path):
"""load streamflow into memory
Args:
path (str|DataFrame): path of streamflow csv file, or pandas DataFrame
Returns:
tuple: (date of np.datetime64, streamflow of float)
"""
if isinstance(path, str):
date, Q = np.loadtxt(
path,
delimiter=",",
skiprows=1,
unpack=True,
dtype=[("date", "datetime64[D]"), ("Q", float)],
converters={0: np.datetime64},
encoding="utf8",
)
year = date.astype("datetime64[Y]").astype(int) + int(
str(np.datetime64(0, "Y"))
)
month = date.astype("datetime64[M]").astype(int) % 12 + 1
day = (date - date.astype("datetime64[M]")).astype(int) + 1
date = np.rec.fromarrays(
[year, month, day], dtype=[("Y", "i4"), ("M", "i4"), ("D", "i4")]
)
else:
df_date = path.iloc[:, 0].astype("datetime64")
date = np.rec.fromarrays(
[df_date.dt.year, df_date.dt.month, df_date.dt.day],
dtype=[("Y", "i4"), ("M", "i4"), ("D", "i4")],
)
Q = path.iloc[:, 1].values.astype(float)
return clean_streamflow(date, Q)
def clean_streamflow(date, Q):
Q[np.isnan(Q)] = 0
Q = np.abs(Q)
year = date["Y"]
year_unique = np.unique(year)
year_delete = clean_streamflow_jit(year, year_unique, Q)
idx_delete = np.isin(year, year_delete)
return Q[~idx_delete], date[~idx_delete]
def clean_streamflow_jit(year, year_unique, Q):
year_delete = []
for y in year_unique:
if (Q[year == y] >= 0).sum() < 120:
year_delete.append(y)
return year_delete
def moving_average(x, w):
res = np.convolve(x, np.ones(w)) / w
return res[w - 1 : -w + 1]
def multi_arange_steps(starts, stops, steps):
pos = 0
cnt = np.sum((stops - starts + steps - np.sign(steps)) // steps, dtype=np.int64)
res = np.zeros((cnt,), dtype=np.int64)
for i in range(starts.size):
v, stop, step = starts[i], stops[i], steps[i]
if step > 0:
while v < stop:
res[pos] = v
pos += 1
v += step
elif step < 0:
while v > stop:
res[pos] = v
pos += 1
v += step
assert pos == cnt
return res
def multi_arange(starts, stops):
pos = 0
cnt = np.sum(stops - starts, dtype=np.int64)
res = np.zeros((cnt,), dtype=np.int64)
for i in range(starts.size):
num = stops[i] - starts[i]
res[pos : pos + num] = np.arange(starts[i], stops[i])
pos += num
return res
def NSE(Q_obs, Q_sim):
SS_res = np.sum(np.square(Q_obs - Q_sim))
SS_tot = np.sum(np.square(Q_obs - np.mean(Q_obs)))
return (1 - SS_res / (SS_tot + 1e-10)) - 1e-10 | src/hydrotoolbox/baseflow/utils.py | import numpy as np
def load_streamflow(path):
"""load streamflow into memory
Args:
path (str|DataFrame): path of streamflow csv file, or pandas DataFrame
Returns:
tuple: (date of np.datetime64, streamflow of float)
"""
if isinstance(path, str):
date, Q = np.loadtxt(
path,
delimiter=",",
skiprows=1,
unpack=True,
dtype=[("date", "datetime64[D]"), ("Q", float)],
converters={0: np.datetime64},
encoding="utf8",
)
year = date.astype("datetime64[Y]").astype(int) + int(
str(np.datetime64(0, "Y"))
)
month = date.astype("datetime64[M]").astype(int) % 12 + 1
day = (date - date.astype("datetime64[M]")).astype(int) + 1
date = np.rec.fromarrays(
[year, month, day], dtype=[("Y", "i4"), ("M", "i4"), ("D", "i4")]
)
else:
df_date = path.iloc[:, 0].astype("datetime64")
date = np.rec.fromarrays(
[df_date.dt.year, df_date.dt.month, df_date.dt.day],
dtype=[("Y", "i4"), ("M", "i4"), ("D", "i4")],
)
Q = path.iloc[:, 1].values.astype(float)
return clean_streamflow(date, Q)
def clean_streamflow(date, Q):
Q[np.isnan(Q)] = 0
Q = np.abs(Q)
year = date["Y"]
year_unique = np.unique(year)
year_delete = clean_streamflow_jit(year, year_unique, Q)
idx_delete = np.isin(year, year_delete)
return Q[~idx_delete], date[~idx_delete]
def clean_streamflow_jit(year, year_unique, Q):
year_delete = []
for y in year_unique:
if (Q[year == y] >= 0).sum() < 120:
year_delete.append(y)
return year_delete
def moving_average(x, w):
res = np.convolve(x, np.ones(w)) / w
return res[w - 1 : -w + 1]
def multi_arange_steps(starts, stops, steps):
pos = 0
cnt = np.sum((stops - starts + steps - np.sign(steps)) // steps, dtype=np.int64)
res = np.zeros((cnt,), dtype=np.int64)
for i in range(starts.size):
v, stop, step = starts[i], stops[i], steps[i]
if step > 0:
while v < stop:
res[pos] = v
pos += 1
v += step
elif step < 0:
while v > stop:
res[pos] = v
pos += 1
v += step
assert pos == cnt
return res
def multi_arange(starts, stops):
pos = 0
cnt = np.sum(stops - starts, dtype=np.int64)
res = np.zeros((cnt,), dtype=np.int64)
for i in range(starts.size):
num = stops[i] - starts[i]
res[pos : pos + num] = np.arange(starts[i], stops[i])
pos += num
return res
def NSE(Q_obs, Q_sim):
SS_res = np.sum(np.square(Q_obs - Q_sim))
SS_tot = np.sum(np.square(Q_obs - np.mean(Q_obs)))
return (1 - SS_res / (SS_tot + 1e-10)) - 1e-10 | 0.741487 | 0.582669 |
import numpy as np
import pytest
import autogalaxy as ag
from autoarray.inversion import inversions
from autogalaxy.mock.mock import MockLightProfile
class MockFitImaging:
def __init__(self, model_images_of_galaxies):
self.model_images_of_galaxies = model_images_of_galaxies
class TestFitImaging:
class TestLikelihood:
def test__1x2_image__no_psf_blurring__plane_fits_data_with_chi_sq_5(self):
# The image plane image generated by the galaxy is [1.0, 1.0]
# Thus the chi squared is 4.0**2.0 + 3.0**2.0 = 25.0
psf = ag.Kernel2D.manual_native(
array=[[0.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 0.0]],
pixel_scales=1.0,
)
imaging = ag.Imaging(
image=5.0 * ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
psf=psf,
noise_map=ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
)
imaging.image[6] = 4.0
mask = ag.Mask2D.manual(
mask=[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
],
pixel_scales=1.0,
)
masked_imaging_7x7 = ag.MaskedImaging(
imaging=imaging,
mask=mask,
settings=ag.SettingsMaskedImaging(grid_class=ag.Grid2D, sub_size=1),
)
# Setup as a ray trace instance, using a light profile for the galaxy
g0 = ag.Galaxy(
redshift=0.5, light_profile=MockLightProfile(value=1.0, size=2)
)
plane = ag.Plane(galaxies=[g0])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
assert (
fit.mask
== np.array(
[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
]
)
).all()
assert (
fit.image.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 5.0, 4.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.noise_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 1.0, 1.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.model_image.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 1.0, 1.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.residual_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 4.0, 3.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.normalized_residual_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 4.0, 3.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.chi_squared_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 16.0, 9.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert fit.chi_squared == 25.0
assert fit.reduced_chi_squared == 25.0 / 2.0
assert fit.noise_normalization == (2.0 * np.log(2 * np.pi * 1.0 ** 2.0))
assert fit.log_likelihood == -0.5 * (
25.0 + 2.0 * np.log(2 * np.pi * 1.0 ** 2.0)
)
def test__1x2_image__include_psf_blurring__plane_fits_data_with_chi_sq_4(self):
# This PSF changes the blurred image plane image from [1.0, 1.0] to [1.0, 5.0]
# Thus, the chi squared is 4.0**2.0 + 0.0**2.0 = 16.0
psf = ag.Kernel2D.manual_native(
array=[[0.0, 0.0, 0.0], [0.0, 1.0, 3.0], [0.0, 0.0, 0.0]],
pixel_scales=1.0,
renormalize=False,
)
imaging = ag.Imaging(
image=5.0 * ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
psf=psf,
noise_map=ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
)
imaging.image[6] = 4.0
mask = ag.Mask2D.manual(
mask=[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
],
pixel_scales=1.0,
)
masked_imaging_7x7 = ag.MaskedImaging(
imaging=imaging,
mask=mask,
settings=ag.SettingsMaskedImaging(
grid_class=ag.Grid2D, renormalize_psf=False, sub_size=1
),
)
# Setup as a ray trace instance, using a light profile for the galaxy
g0 = ag.Galaxy(
redshift=0.5, light_profile=MockLightProfile(value=1.0, size=2)
)
plane = ag.Plane(galaxies=[g0])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
assert (
fit.mask
== np.array(
[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
]
)
).all()
assert (
fit.image.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 5.0, 4.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.noise_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 1.0, 1.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.model_image.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 1.0, 4.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.residual_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 4.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.normalized_residual_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 4.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.chi_squared_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 16.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert fit.chi_squared == 16.0
assert fit.reduced_chi_squared == 16.0 / 2.0
assert fit.noise_normalization == (2.0 * np.log(2 * np.pi * 1.0 ** 2.0))
assert fit.log_likelihood == -0.5 * (
16.0 + 2.0 * np.log(2 * np.pi * 1.0 ** 2.0)
)
def test__hyper_galaxy_changes_noise_above_from_1_to_2__reflected_in_likelihood(
self,
):
# This PSF changes the blurred image plane image from [1.0, 1.0] to [1.0, 5.0]
# Thus, the chi squared is 4.0**2.0 + 0.0**2.0 = 16.0
# The hyper_galaxies galaxy increases the noise in both pixels by 1.0, to 2.0.
# This reduces the chi squared to 2.0 instead of 4.0
psf = ag.Kernel2D.manual_native(
array=[[0.0, 0.0, 0.0], [0.0, 1.0, 3.0], [0.0, 0.0, 0.0]],
pixel_scales=1.0,
)
imaging = ag.Imaging(
image=5.0 * ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
psf=psf,
noise_map=ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
)
imaging.image[6] = 4.0
mask = ag.Mask2D.manual(
mask=[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
],
pixel_scales=1.0,
)
masked_imaging_7x7 = ag.MaskedImaging(
imaging=imaging,
mask=mask,
settings=ag.SettingsMaskedImaging(
grid_class=ag.Grid2D, renormalize_psf=False, sub_size=1
),
)
# Setup as a ray trace instance, using a light profile for the galaxy
g0 = ag.Galaxy(
redshift=0.5,
light_profile=MockLightProfile(value=1.0, size=2),
hyper_galaxy=ag.HyperGalaxy(
contribution_factor=1.0, noise_factor=1.0, noise_power=1.0
),
hyper_model_image=ag.Array2D.ones(
shape_native=(1, 2), pixel_scales=1.0
),
hyper_galaxy_image=ag.Array2D.ones(
shape_native=(1, 2), pixel_scales=1.0
),
hyper_minimum_value=0.0,
)
plane = ag.Plane(galaxies=[g0])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
assert (
fit.noise_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 2.0, 2.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.chi_squared_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 4.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert fit.chi_squared == 4.0
assert fit.reduced_chi_squared == 4.0 / 2.0
assert fit.noise_normalization == (2.0 * np.log(2 * np.pi * 2.0 ** 2.0))
assert fit.log_likelihood == -0.5 * (
4.0 + 2.0 * np.log(2 * np.pi * 2.0 ** 2.0)
)
def test__hyper_image_changes_background_sky__reflected_in_likelihood(self):
psf = ag.Kernel2D.manual_native(
array=[[0.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 0.0]],
pixel_scales=1.0,
)
imaging = ag.Imaging(
image=ag.Array2D.full(
fill_value=4.0, shape_native=(3, 4), pixel_scales=1.0
),
psf=psf,
noise_map=ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
)
imaging.image[5] = 5.0
mask = ag.Mask2D.manual(
mask=[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
],
pixel_scales=1.0,
)
masked_imaging_7x7 = ag.MaskedImaging(
imaging=imaging,
mask=mask,
settings=ag.SettingsMaskedImaging(grid_class=ag.Grid2D, sub_size=1),
)
# Setup as a ray trace instance, using a light profile for the galaxy
g0 = ag.Galaxy(
redshift=0.5, light_profile=MockLightProfile(value=1.0, size=2)
)
plane = ag.Plane(galaxies=[g0])
hyper_image_sky = ag.hyper_data.HyperImageSky(sky_scale=1.0)
fit = ag.FitImaging(
masked_imaging=masked_imaging_7x7,
plane=plane,
hyper_image_sky=hyper_image_sky,
)
assert (
fit.mask
== np.array(
[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
]
)
).all()
assert (
fit.image.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 6.0, 5.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.chi_squared_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 25.0, 16.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert fit.chi_squared == 41.0
assert fit.reduced_chi_squared == 41.0 / 2.0
assert fit.noise_normalization == (2.0 * np.log(2 * np.pi * 1.0 ** 2.0))
assert fit.log_likelihood == -0.5 * (
41.0 + 2.0 * np.log(2 * np.pi * 1.0 ** 2.0)
)
def test__hyper_background_changes_background_noise_map__reflected_in_likelihood(
self,
):
psf = ag.Kernel2D.manual_native(
array=[[0.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 0.0]],
pixel_scales=1.0,
)
imaging = ag.Imaging(
image=5.0 * ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
psf=psf,
noise_map=ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
)
imaging.image[6] = 4.0
mask = ag.Mask2D.manual(
mask=[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
],
pixel_scales=1.0,
)
masked_imaging_7x7 = ag.MaskedImaging(
imaging=imaging,
mask=mask,
settings=ag.SettingsMaskedImaging(grid_class=ag.Grid2D, sub_size=1),
)
# Setup as a ray trace instance, using a light profile for the galaxy
g0 = ag.Galaxy(
redshift=0.5, light_profile=MockLightProfile(value=1.0, size=2)
)
plane = ag.Plane(galaxies=[g0])
hyper_background_noise = ag.hyper_data.HyperBackgroundNoise(noise_scale=1.0)
fit = ag.FitImaging(
masked_imaging=masked_imaging_7x7,
plane=plane,
hyper_background_noise=hyper_background_noise,
)
assert (
fit.noise_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 2.0, 2.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert fit.chi_squared == 6.25
assert fit.reduced_chi_squared == 6.25 / 2.0
assert fit.noise_normalization == (2.0 * np.log(2 * np.pi * 2.0 ** 2.0))
assert fit.log_likelihood == -0.5 * (
6.25 + 2.0 * np.log(2 * np.pi * 2.0 ** 2.0)
)
def test__hyper_galaxy_changes_noise_above_hyper_noise_limit__rounded_down_to_limit(
self,
):
# This PSF changes the blurred image plane image from [1.0, 1.0] to [1.0, 5.0]
# Thus, the chi squared is 4.0**2.0 + 0.0**2.0 = 16.0
# The hyper_galaxies galaxy increases the noise in both pixels by 1.0, to 2.0.
# This reduces the chi squared to 2.0 instead of 4.0
psf = ag.Kernel2D.manual_native(
array=[[0.0, 0.0, 0.0], [0.0, 1.0, 3.0], [0.0, 0.0, 0.0]],
pixel_scales=1.0,
)
imaging = ag.Imaging(
image=5.0 * ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
psf=psf,
noise_map=ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
)
imaging.image[6] = 4.0
mask = ag.Mask2D.manual(
mask=[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
],
pixel_scales=1.0,
)
masked_imaging_7x7 = ag.MaskedImaging(
imaging=imaging,
mask=mask,
settings=ag.SettingsMaskedImaging(
grid_class=ag.Grid2D, renormalize_psf=False, sub_size=1
),
)
# Setup as a ray trace instance, using a light profile for the galaxy
g0 = ag.Galaxy(
redshift=0.5,
light_profile=MockLightProfile(value=1.0, size=2),
hyper_galaxy=ag.HyperGalaxy(
contribution_factor=1.0, noise_factor=1.0e9, noise_power=1.0
),
hyper_model_image=ag.Array2D.ones(
shape_native=(1, 2), pixel_scales=1.0
),
hyper_galaxy_image=ag.Array2D.ones(
shape_native=(1, 2), pixel_scales=1.0
),
hyper_minimum_value=0.0,
)
plane = ag.Plane(galaxies=[g0])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
assert (
fit.noise_map.native
== np.array(
[
[0.0, 0.0, 0.0, 0.0],
[0.0, 1.0e8, 1.0e8, 0.0],
[0.0, 0.0, 0.0, 0.0],
]
)
).all()
class TestCompareToManualProfilesOnly:
def test___all_fit_quantities__no_hyper_methods(self, masked_imaging_7x7):
g0 = ag.Galaxy(
redshift=0.5,
light_profile=ag.lp.EllipticalSersic(intensity=1.0),
mass_profile=ag.mp.SphericalIsothermal(einstein_radius=1.0),
)
g1 = ag.Galaxy(
redshift=1.0, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
assert masked_imaging_7x7.noise_map.native == pytest.approx(
fit.noise_map.native
)
model_image = plane.blurred_image_from_grid_and_convolver(
grid=masked_imaging_7x7.grid,
convolver=masked_imaging_7x7.convolver,
blurring_grid=masked_imaging_7x7.blurring_grid,
)
assert model_image.native == pytest.approx(fit.model_image.native)
residual_map = ag.util.fit.residual_map_from(
data=masked_imaging_7x7.image, model_data=model_image
)
assert residual_map.native == pytest.approx(fit.residual_map.native)
normalized_residual_map = ag.util.fit.normalized_residual_map_from(
residual_map=residual_map, noise_map=masked_imaging_7x7.noise_map
)
assert normalized_residual_map.native == pytest.approx(
fit.normalized_residual_map.native
)
chi_squared_map = ag.util.fit.chi_squared_map_from(
residual_map=residual_map, noise_map=masked_imaging_7x7.noise_map
)
assert chi_squared_map.native == pytest.approx(fit.chi_squared_map.native)
chi_squared = ag.util.fit.chi_squared_from(chi_squared_map=chi_squared_map)
noise_normalization = ag.util.fit.noise_normalization_from(
noise_map=masked_imaging_7x7.noise_map
)
log_likelihood = ag.util.fit.log_likelihood_from(
chi_squared=chi_squared, noise_normalization=noise_normalization
)
assert log_likelihood == pytest.approx(fit.log_likelihood, 1e-4)
assert log_likelihood == fit.figure_of_merit
def test___fit_galaxy_model_image_dict__corresponds_to_blurred_galaxy_images(
self, masked_imaging_7x7
):
g0 = ag.Galaxy(
redshift=0.5,
light_profile=ag.lp.EllipticalSersic(intensity=1.0),
mass_profile=ag.mp.SphericalIsothermal(einstein_radius=1.0),
)
g1 = ag.Galaxy(
redshift=1.0, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
g2 = ag.Galaxy(redshift=1.0)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1, g2])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
g0_blurred_image = g0.blurred_image_from_grid_and_convolver(
grid=masked_imaging_7x7.grid,
blurring_grid=masked_imaging_7x7.blurring_grid,
convolver=masked_imaging_7x7.convolver,
)
g1_blurred_image = g1.blurred_image_from_grid_and_convolver(
grid=masked_imaging_7x7.grid,
blurring_grid=masked_imaging_7x7.blurring_grid,
convolver=masked_imaging_7x7.convolver,
)
assert fit.galaxy_model_image_dict[g0] == pytest.approx(
g0_blurred_image, 1.0e-4
)
assert fit.galaxy_model_image_dict[g1] == pytest.approx(
g1_blurred_image, 1.0e-4
)
assert (fit.galaxy_model_image_dict[g2].slim == np.zeros(9)).all()
assert fit.model_image.native == pytest.approx(
fit.galaxy_model_image_dict[g0].native
+ fit.galaxy_model_image_dict[g1].native,
1.0e-4,
)
def test___all_fit_quantities__including_hyper_methods(
self, masked_imaging_7x7
):
hyper_image_sky = ag.hyper_data.HyperImageSky(sky_scale=1.0)
hyper_background_noise = ag.hyper_data.HyperBackgroundNoise(noise_scale=1.0)
image = hyper_image_sky.hyper_image_from_image(
image=masked_imaging_7x7.image
)
g0 = ag.Galaxy(
redshift=0.5,
light_profile=ag.lp.EllipticalSersic(intensity=1.0),
mass_profile=ag.mp.SphericalIsothermal(einstein_radius=1.0),
hyper_galaxy=ag.HyperGalaxy(
contribution_factor=1.0, noise_factor=1.0, noise_power=1.0
),
hyper_model_image=np.ones(9),
hyper_galaxy_image=np.ones(9),
hyper_minimum_value=0.0,
)
g1 = ag.Galaxy(
redshift=1.0, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1])
fit = ag.FitImaging(
masked_imaging=masked_imaging_7x7,
plane=plane,
hyper_image_sky=hyper_image_sky,
hyper_background_noise=hyper_background_noise,
)
hyper_noise_map_background = hyper_background_noise.hyper_noise_map_from_noise_map(
noise_map=masked_imaging_7x7.noise_map
)
hyper_noise = plane.hyper_noise_map_from_noise_map(
noise_map=masked_imaging_7x7.noise_map
)
hyper_noise_map = hyper_noise_map_background + hyper_noise
assert hyper_noise_map.native == pytest.approx(fit.noise_map.native)
model_image = plane.blurred_image_from_grid_and_convolver(
grid=masked_imaging_7x7.grid,
convolver=masked_imaging_7x7.convolver,
blurring_grid=masked_imaging_7x7.blurring_grid,
)
assert model_image.native == pytest.approx(fit.model_image.native)
residual_map = ag.util.fit.residual_map_from(
data=image, model_data=model_image
)
assert residual_map.native == pytest.approx(fit.residual_map.native)
normalized_residual_map = ag.util.fit.normalized_residual_map_from(
residual_map=residual_map, noise_map=hyper_noise_map
)
assert normalized_residual_map.native == pytest.approx(
fit.normalized_residual_map.native
)
chi_squared_map = ag.util.fit.chi_squared_map_from(
residual_map=residual_map, noise_map=hyper_noise_map
)
assert chi_squared_map.native == pytest.approx(fit.chi_squared_map.native)
chi_squared = ag.util.fit.chi_squared_from(chi_squared_map=chi_squared_map)
noise_normalization = ag.util.fit.noise_normalization_from(
noise_map=hyper_noise_map
)
log_likelihood = ag.util.fit.log_likelihood_from(
chi_squared=chi_squared, noise_normalization=noise_normalization
)
assert log_likelihood == pytest.approx(fit.log_likelihood, 1e-4)
assert log_likelihood == fit.figure_of_merit
fit = ag.FitImaging(
masked_imaging=masked_imaging_7x7,
plane=plane,
hyper_image_sky=hyper_image_sky,
hyper_background_noise=hyper_background_noise,
use_hyper_scalings=False,
)
assert fit.image == pytest.approx(masked_imaging_7x7.image, 1.0e-4)
assert fit.noise_map == pytest.approx(masked_imaging_7x7.noise_map, 1.0e-4)
def test___blurred_and_model_images_of_galaxies_and_unmasked_blurred_image_properties(
self, masked_imaging_7x7
):
g0 = ag.Galaxy(
redshift=0.5,
light_profile=ag.lp.EllipticalSersic(intensity=1.0),
mass_profile=ag.mp.SphericalIsothermal(einstein_radius=1.0),
)
g1 = ag.Galaxy(
redshift=1.0, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
blurred_images_of_galaxies = plane.blurred_images_of_galaxies_from_grid_and_convolver(
grid=masked_imaging_7x7.grid,
convolver=masked_imaging_7x7.convolver,
blurring_grid=masked_imaging_7x7.blurring_grid,
)
assert blurred_images_of_galaxies[0].native == pytest.approx(
fit.model_images_of_galaxies[0].native, 1.0e-4
)
assert blurred_images_of_galaxies[1].native == pytest.approx(
fit.model_images_of_galaxies[1].native, 1.0e-4
)
unmasked_blurred_image = plane.unmasked_blurred_image_from_grid_and_psf(
grid=masked_imaging_7x7.grid, psf=masked_imaging_7x7.psf
)
assert (unmasked_blurred_image == fit.unmasked_blurred_image).all()
unmasked_blurred_image_of_galaxies = plane.unmasked_blurred_image_of_galaxies_from_grid_and_psf(
grid=masked_imaging_7x7.grid, psf=masked_imaging_7x7.psf
)
assert (
unmasked_blurred_image_of_galaxies[0]
== fit.unmasked_blurred_image_of_galaxies[0]
).all()
assert (
unmasked_blurred_image_of_galaxies[1]
== fit.unmasked_blurred_image_of_galaxies[1]
).all()
class TestCompareToManualInversionOnly:
def test___all_quantities__no_hyper_methods(self, masked_imaging_7x7):
# Ensures the inversion grid is used, as this would cause the test to fail.
masked_imaging_7x7.grid[0, 0] = -100.0
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
g0 = ag.Galaxy(redshift=0.5, pixelization=pix, regularization=reg)
plane = ag.Plane(galaxies=[ag.Galaxy(redshift=0.5), g0])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_imaging_7x7.grid_inversion, sparse_grid=None
)
inversion = inversions.InversionImagingMatrix.from_data_mapper_and_regularization(
mapper=mapper,
regularization=reg,
image=masked_imaging_7x7.image,
noise_map=masked_imaging_7x7.noise_map,
convolver=masked_imaging_7x7.convolver,
)
assert inversion.mapped_reconstructed_image.native == pytest.approx(
fit.model_image.native, 1.0e-4
)
residual_map = ag.util.fit.residual_map_from(
data=masked_imaging_7x7.image,
model_data=inversion.mapped_reconstructed_image,
)
assert residual_map.native == pytest.approx(fit.residual_map.native, 1.0e-4)
normalized_residual_map = ag.util.fit.normalized_residual_map_from(
residual_map=residual_map, noise_map=masked_imaging_7x7.noise_map
)
assert normalized_residual_map.native == pytest.approx(
fit.normalized_residual_map.native, 1.0e-4
)
chi_squared_map = ag.util.fit.chi_squared_map_from(
residual_map=residual_map, noise_map=masked_imaging_7x7.noise_map
)
assert chi_squared_map.native == pytest.approx(
fit.chi_squared_map.native, 1.0e-4
)
chi_squared = ag.util.fit.chi_squared_from(chi_squared_map=chi_squared_map)
noise_normalization = ag.util.fit.noise_normalization_from(
noise_map=masked_imaging_7x7.noise_map
)
log_likelihood = ag.util.fit.log_likelihood_from(
chi_squared=chi_squared, noise_normalization=noise_normalization
)
assert log_likelihood == pytest.approx(fit.log_likelihood, 1e-4)
log_likelihood_with_regularization = ag.util.fit.log_likelihood_with_regularization_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
noise_normalization=noise_normalization,
)
assert log_likelihood_with_regularization == pytest.approx(
fit.log_likelihood_with_regularization, 1e-4
)
log_evidence = ag.util.fit.log_evidence_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
log_curvature_regularization_term=inversion.log_det_curvature_reg_matrix_term,
log_regularization_term=inversion.log_det_regularization_matrix_term,
noise_normalization=noise_normalization,
)
assert log_evidence == fit.log_evidence
assert log_evidence == fit.figure_of_merit
def test___fit_galaxy_model_image_dict__has_inversion_mapped_reconstructed_image(
self, masked_imaging_7x7
):
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
g0 = ag.Galaxy(redshift=0.5)
g1 = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_imaging_7x7.grid, sparse_grid=None
)
inversion = inversions.InversionImagingMatrix.from_data_mapper_and_regularization(
mapper=mapper,
regularization=reg,
image=masked_imaging_7x7.image,
noise_map=masked_imaging_7x7.noise_map,
convolver=masked_imaging_7x7.convolver,
)
assert (fit.galaxy_model_image_dict[g0] == np.zeros(9)).all()
assert fit.galaxy_model_image_dict[g1].native == pytest.approx(
inversion.mapped_reconstructed_image.native, 1.0e-4
)
assert fit.model_image.native == pytest.approx(
fit.galaxy_model_image_dict[g1].native, 1.0e-4
)
def test___all_fit_quantities__include_hyper_methods(self, masked_imaging_7x7):
hyper_image_sky = ag.hyper_data.HyperImageSky(sky_scale=1.0)
hyper_background_noise = ag.hyper_data.HyperBackgroundNoise(noise_scale=1.0)
image = hyper_image_sky.hyper_image_from_image(
image=masked_imaging_7x7.image
)
hyper_noise_map_background = hyper_background_noise.hyper_noise_map_from_noise_map(
noise_map=masked_imaging_7x7.noise_map
)
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
g0 = ag.Galaxy(
redshift=0.5,
pixelization=pix,
regularization=reg,
hyper_galaxy=ag.HyperGalaxy(
contribution_factor=1.0, noise_factor=1.0, noise_power=1.0
),
hyper_model_image=np.ones(9),
hyper_galaxy_image=np.ones(9),
hyper_minimum_value=0.0,
)
plane = ag.Plane(galaxies=[ag.Galaxy(redshift=0.5), g0])
fit = ag.FitImaging(
masked_imaging=masked_imaging_7x7,
plane=plane,
hyper_image_sky=hyper_image_sky,
hyper_background_noise=hyper_background_noise,
)
hyper_noise = plane.hyper_noise_map_from_noise_map(
noise_map=masked_imaging_7x7.noise_map
)
hyper_noise_map = hyper_noise_map_background + hyper_noise
assert hyper_noise_map.native == pytest.approx(fit.noise_map.native)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_imaging_7x7.grid,
settings=ag.SettingsPixelization(use_border=False),
)
inversion = inversions.InversionImagingMatrix.from_data_mapper_and_regularization(
mapper=mapper,
regularization=reg,
image=image,
noise_map=hyper_noise_map,
convolver=masked_imaging_7x7.convolver,
)
assert inversion.mapped_reconstructed_image.native == pytest.approx(
fit.model_image.native, 1.0e-4
)
residual_map = ag.util.fit.residual_map_from(
data=image, model_data=inversion.mapped_reconstructed_image
)
assert residual_map.native == pytest.approx(fit.residual_map.native)
normalized_residual_map = ag.util.fit.normalized_residual_map_from(
residual_map=residual_map, noise_map=hyper_noise_map
)
assert normalized_residual_map.native == pytest.approx(
fit.normalized_residual_map.native
)
chi_squared_map = ag.util.fit.chi_squared_map_from(
residual_map=residual_map, noise_map=hyper_noise_map
)
assert chi_squared_map.native == pytest.approx(fit.chi_squared_map.native)
chi_squared = ag.util.fit.chi_squared_from(chi_squared_map=chi_squared_map)
noise_normalization = ag.util.fit.noise_normalization_from(
noise_map=hyper_noise_map
)
log_likelihood = ag.util.fit.log_likelihood_from(
chi_squared=chi_squared, noise_normalization=noise_normalization
)
assert log_likelihood == pytest.approx(fit.log_likelihood, 1e-4)
log_likelihood_with_regularization = ag.util.fit.log_likelihood_with_regularization_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
noise_normalization=noise_normalization,
)
assert log_likelihood_with_regularization == pytest.approx(
fit.log_likelihood_with_regularization, 1e-4
)
log_evidence = ag.util.fit.log_evidence_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
log_curvature_regularization_term=inversion.log_det_curvature_reg_matrix_term,
log_regularization_term=inversion.log_det_regularization_matrix_term,
noise_normalization=noise_normalization,
)
assert log_evidence == fit.log_evidence
assert log_evidence == fit.figure_of_merit
def test___blurred_and_model_images_of_galaxies_and_unmasked_blurred_image_properties(
self, masked_imaging_7x7
):
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
g0 = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[ag.Galaxy(redshift=0.5), g0])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_imaging_7x7.grid,
settings=ag.SettingsPixelization(use_border=False),
)
inversion = inversions.InversionImagingMatrix.from_data_mapper_and_regularization(
mapper=mapper,
regularization=reg,
image=masked_imaging_7x7.image,
noise_map=masked_imaging_7x7.noise_map,
convolver=masked_imaging_7x7.convolver,
)
assert (fit.model_images_of_galaxies[0].native == np.zeros((7, 7))).all()
assert inversion.mapped_reconstructed_image.native == pytest.approx(
fit.model_images_of_galaxies[1].native, 1.0e-4
)
class TestCompareToManualProfilesAndInversion:
def test___all_fit_quantities__no_hyper_methods(self, masked_imaging_7x7):
galaxy_light = ag.Galaxy(
redshift=0.5, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
galaxy_pix = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[galaxy_light, galaxy_pix])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
blurred_image = plane.blurred_image_from_grid_and_convolver(
grid=masked_imaging_7x7.grid,
convolver=masked_imaging_7x7.convolver,
blurring_grid=masked_imaging_7x7.blurring_grid,
)
assert blurred_image.native == pytest.approx(fit.blurred_image.native)
profile_subtracted_image = masked_imaging_7x7.image - blurred_image
assert profile_subtracted_image.native == pytest.approx(
fit.profile_subtracted_image.native
)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_imaging_7x7.grid,
settings=ag.SettingsPixelization(use_border=False),
)
inversion = inversions.InversionImagingMatrix.from_data_mapper_and_regularization(
image=profile_subtracted_image,
noise_map=masked_imaging_7x7.noise_map,
convolver=masked_imaging_7x7.convolver,
mapper=mapper,
regularization=reg,
)
model_image = blurred_image + inversion.mapped_reconstructed_image
assert model_image.native == pytest.approx(fit.model_image.native)
residual_map = ag.util.fit.residual_map_from(
data=masked_imaging_7x7.image, model_data=model_image
)
assert residual_map.native == pytest.approx(fit.residual_map.native)
normalized_residual_map = ag.util.fit.normalized_residual_map_from(
residual_map=residual_map, noise_map=masked_imaging_7x7.noise_map
)
assert normalized_residual_map.native == pytest.approx(
fit.normalized_residual_map.native
)
chi_squared_map = ag.util.fit.chi_squared_map_from(
residual_map=residual_map, noise_map=masked_imaging_7x7.noise_map
)
assert chi_squared_map.native == pytest.approx(fit.chi_squared_map.native)
chi_squared = ag.util.fit.chi_squared_from(chi_squared_map=chi_squared_map)
noise_normalization = ag.util.fit.noise_normalization_from(
noise_map=masked_imaging_7x7.noise_map
)
log_likelihood = ag.util.fit.log_likelihood_from(
chi_squared=chi_squared, noise_normalization=noise_normalization
)
assert log_likelihood == pytest.approx(fit.log_likelihood, 1e-4)
log_likelihood_with_regularization = ag.util.fit.log_likelihood_with_regularization_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
noise_normalization=noise_normalization,
)
assert log_likelihood_with_regularization == pytest.approx(
fit.log_likelihood_with_regularization, 1e-4
)
log_evidence = ag.util.fit.log_evidence_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
log_curvature_regularization_term=inversion.log_det_curvature_reg_matrix_term,
log_regularization_term=inversion.log_det_regularization_matrix_term,
noise_normalization=noise_normalization,
)
assert log_evidence == fit.log_evidence
assert log_evidence == fit.figure_of_merit
def test___fit_galaxy_model_image_dict__has_blurred_images_and_inversion_mapped_reconstructed_image(
self, masked_imaging_7x7
):
g0 = ag.Galaxy(
redshift=0.5, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
g1 = ag.Galaxy(
redshift=0.5, light_profile=ag.lp.EllipticalSersic(intensity=2.0)
)
g2 = ag.Galaxy(redshift=0.5)
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
galaxy_pix = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1, g2, galaxy_pix])
masked_imaging_7x7.image[0] = 3.0
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
g0_blurred_image = g0.blurred_image_from_grid_and_convolver(
grid=masked_imaging_7x7.grid,
convolver=masked_imaging_7x7.convolver,
blurring_grid=masked_imaging_7x7.blurring_grid,
)
g1_blurred_image = g1.blurred_image_from_grid_and_convolver(
grid=masked_imaging_7x7.grid,
convolver=masked_imaging_7x7.convolver,
blurring_grid=masked_imaging_7x7.blurring_grid,
)
blurred_image = g0_blurred_image + g1_blurred_image
profile_subtracted_image = masked_imaging_7x7.image - blurred_image
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_imaging_7x7.grid,
settings=ag.SettingsPixelization(use_border=False),
)
inversion = inversions.InversionImagingMatrix.from_data_mapper_and_regularization(
image=profile_subtracted_image,
noise_map=masked_imaging_7x7.noise_map,
convolver=masked_imaging_7x7.convolver,
mapper=mapper,
regularization=reg,
)
assert (fit.galaxy_model_image_dict[g2] == np.zeros(9)).all()
assert fit.galaxy_model_image_dict[g0].native == pytest.approx(
g0_blurred_image.native, 1.0e-4
)
assert fit.galaxy_model_image_dict[g1].native == pytest.approx(
g1_blurred_image.native, 1.0e-4
)
assert fit.galaxy_model_image_dict[galaxy_pix].native == pytest.approx(
inversion.mapped_reconstructed_image.native, 1.0e-4
)
assert fit.model_image.native == pytest.approx(
fit.galaxy_model_image_dict[g0].native
+ fit.galaxy_model_image_dict[g1].native
+ inversion.mapped_reconstructed_image.native,
1.0e-4,
)
def test___all_fit_quantities__include_hyper_methods(self, masked_imaging_7x7):
hyper_image_sky = ag.hyper_data.HyperImageSky(sky_scale=1.0)
hyper_background_noise = ag.hyper_data.HyperBackgroundNoise(noise_scale=1.0)
image = hyper_image_sky.hyper_image_from_image(
image=masked_imaging_7x7.image
)
hyper_noise_map_background = hyper_background_noise.hyper_noise_map_from_noise_map(
noise_map=masked_imaging_7x7.noise_map
)
galaxy_light = ag.Galaxy(
redshift=0.5,
light_profile=ag.lp.EllipticalSersic(intensity=1.0),
hyper_galaxy=ag.HyperGalaxy(
contribution_factor=1.0, noise_factor=1.0, noise_power=1.0
),
hyper_model_image=ag.Array2D.ones(
shape_native=(3, 3), pixel_scales=1.0
),
hyper_galaxy_image=ag.Array2D.ones(
shape_native=(3, 3), pixel_scales=1.0
),
hyper_minimum_value=0.0,
)
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
galaxy_pix = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[galaxy_light, galaxy_pix])
fit = ag.FitImaging(
masked_imaging=masked_imaging_7x7,
plane=plane,
hyper_image_sky=hyper_image_sky,
hyper_background_noise=hyper_background_noise,
)
hyper_noise = plane.hyper_noise_map_from_noise_map(
noise_map=masked_imaging_7x7.noise_map
)
hyper_noise_map = hyper_noise_map_background + hyper_noise
assert hyper_noise_map.native == pytest.approx(fit.noise_map.native, 1.0e-4)
blurred_image = plane.blurred_image_from_grid_and_convolver(
grid=masked_imaging_7x7.grid,
convolver=masked_imaging_7x7.convolver,
blurring_grid=masked_imaging_7x7.blurring_grid,
)
assert blurred_image.native == pytest.approx(fit.blurred_image.native)
profile_subtracted_image = image - blurred_image
assert profile_subtracted_image.native == pytest.approx(
fit.profile_subtracted_image.native
)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_imaging_7x7.grid,
settings=ag.SettingsPixelization(use_border=False),
)
inversion = inversions.InversionImagingMatrix.from_data_mapper_and_regularization(
image=profile_subtracted_image,
noise_map=hyper_noise_map,
convolver=masked_imaging_7x7.convolver,
mapper=mapper,
regularization=reg,
)
model_image = blurred_image + inversion.mapped_reconstructed_image
assert model_image.native == pytest.approx(fit.model_image.native, 1.0e-4)
residual_map = ag.util.fit.residual_map_from(
data=image, model_data=model_image
)
assert residual_map.native == pytest.approx(fit.residual_map.native, 1.0e-4)
normalized_residual_map = ag.util.fit.normalized_residual_map_from(
residual_map=residual_map, noise_map=hyper_noise_map
)
assert normalized_residual_map.native == pytest.approx(
fit.normalized_residual_map.native, 1.0e-4
)
chi_squared_map = ag.util.fit.chi_squared_map_from(
residual_map=residual_map, noise_map=hyper_noise_map
)
assert chi_squared_map.native == pytest.approx(
fit.chi_squared_map.native, 1.0e-4
)
chi_squared = ag.util.fit.chi_squared_from(chi_squared_map=chi_squared_map)
noise_normalization = ag.util.fit.noise_normalization_from(
noise_map=hyper_noise_map
)
log_likelihood = ag.util.fit.log_likelihood_from(
chi_squared=chi_squared, noise_normalization=noise_normalization
)
assert log_likelihood == pytest.approx(fit.log_likelihood, 1e-4)
log_likelihood_with_regularization = ag.util.fit.log_likelihood_with_regularization_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
noise_normalization=noise_normalization,
)
assert log_likelihood_with_regularization == pytest.approx(
fit.log_likelihood_with_regularization, 1e-4
)
log_evidence = ag.util.fit.log_evidence_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
log_curvature_regularization_term=inversion.log_det_curvature_reg_matrix_term,
log_regularization_term=inversion.log_det_regularization_matrix_term,
noise_normalization=noise_normalization,
)
assert log_evidence == fit.log_evidence
assert log_evidence == fit.figure_of_merit
def test___blurred_and_model_images_of_galaxies_and_unmasked_blurred_image_properties(
self, masked_imaging_7x7
):
galaxy_light = ag.Galaxy(
redshift=0.5, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
galaxy_pix = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[galaxy_light, galaxy_pix])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
blurred_image = plane.blurred_image_from_grid_and_convolver(
grid=masked_imaging_7x7.grid,
convolver=masked_imaging_7x7.convolver,
blurring_grid=masked_imaging_7x7.blurring_grid,
)
profile_subtracted_image = masked_imaging_7x7.image - blurred_image
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_imaging_7x7.grid,
settings=ag.SettingsPixelization(use_border=False),
)
inversion = inversions.InversionImagingMatrix.from_data_mapper_and_regularization(
image=profile_subtracted_image,
noise_map=masked_imaging_7x7.noise_map,
convolver=masked_imaging_7x7.convolver,
mapper=mapper,
regularization=reg,
)
assert blurred_image.native == pytest.approx(
fit.model_images_of_galaxies[0].native, 1.0e-4
)
assert inversion.mapped_reconstructed_image.native == pytest.approx(
fit.model_images_of_galaxies[1].native, 1.0e-4
)
class TestAttributes:
def test__subtracted_images_of_galaxies(self, masked_imaging_no_blur_7x7):
g0 = ag.Galaxy(redshift=0.5, light_profile=MockLightProfile(value=1.0))
g1 = ag.Galaxy(redshift=1.0, light_profile=MockLightProfile(value=2.0))
g2 = ag.Galaxy(redshift=1.0, light_profile=MockLightProfile(value=3.0))
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1, g2])
fit = ag.FitImaging(masked_imaging=masked_imaging_no_blur_7x7, plane=plane)
assert fit.subtracted_images_of_galaxies[0].slim[0] == -4.0
assert fit.subtracted_images_of_galaxies[1].slim[0] == -3.0
assert fit.subtracted_images_of_galaxies[2].slim[0] == -2.0
g0 = ag.Galaxy(redshift=0.5, light_profile=MockLightProfile(value=1.0))
g1 = ag.Galaxy(redshift=0.5)
g2 = ag.Galaxy(redshift=1.0, light_profile=MockLightProfile(value=3.0))
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1, g2])
fit = ag.FitImaging(masked_imaging=masked_imaging_no_blur_7x7, plane=plane)
assert fit.subtracted_images_of_galaxies[0].slim[0] == -2.0
assert fit.subtracted_images_of_galaxies[1].slim[0] == -3.0
assert fit.subtracted_images_of_galaxies[2].slim[0] == 0.0
class TestFitInterferometer:
class TestLikelihood:
def test__1x2_image__1x2_visibilities__simple_fourier_transform(self):
# The image plane image generated by the galaxy is [1.0, 1.0]
# Thus the chi squared is 4.0**2.0 + 3.0**2.0 = 25.0
interferometer = ag.Interferometer(
visibilities=ag.Visibilities.full(fill_value=5.0, shape_slim=(1,)),
noise_map=ag.Visibilities.ones(shape_slim=(1,)),
uv_wavelengths=np.array([[0.0, 0.0]]),
)
interferometer.visibilities[0] = 5.0 + 4.0j
visibilities_mask = np.full(fill_value=False, shape=(1,))
real_space_mask = ag.Mask2D.manual(
mask=[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
],
pixel_scales=1.0,
)
masked_interferometer = ag.MaskedInterferometer(
interferometer=interferometer,
visibilities_mask=visibilities_mask,
real_space_mask=real_space_mask,
settings=ag.SettingsMaskedInterferometer(
grid_class=ag.Grid2D,
sub_size=1,
transformer_class=ag.TransformerDFT,
),
)
# Setup as a ray trace instance, using a light profile for the galaxy
g0 = ag.Galaxy(
redshift=0.5, light_profile=MockLightProfile(value=1.0, size=2)
)
plane = ag.Plane(galaxies=[g0])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer, plane=plane
)
assert (fit.visibilities_mask == np.array([False])).all()
assert (fit.visibilities.slim == np.array([5.0 + 4.0j])).all()
assert (fit.noise_map.slim == np.array([1.0 + 1.0j])).all()
assert (fit.model_visibilities.slim == np.array([2.0 + 0.0j])).all()
assert (fit.residual_map.slim == np.array([3.0 + 4.0j])).all()
assert (fit.normalized_residual_map.slim == np.array([3.0 + 4.0j])).all()
assert (fit.chi_squared_map.slim == np.array([9.0 + 16.0j])).all()
assert fit.chi_squared == 25.0
assert fit.noise_normalization == (2.0 * np.log(2 * np.pi * 1.0 ** 2.0))
assert fit.log_likelihood == -0.5 * (
25.0 + 2.0 * np.log(2 * np.pi * 1.0 ** 2.0)
)
def test__hyper_background_changes_background_sky__reflected_in_likelihood(
self,
):
uv_wavelengths = np.array([[1.0, 0.0], [1.0, 1.0], [2.0, 2.0]])
interferometer = ag.Interferometer(
visibilities=ag.Visibilities.full(fill_value=5.0, shape_slim=(3,)),
noise_map=ag.Visibilities.full(fill_value=2.0, shape_slim=(3,)),
uv_wavelengths=uv_wavelengths,
)
visibilities_mask = np.full(fill_value=False, shape=(1,))
real_space_mask = ag.Mask2D.manual(
mask=[
[True, True, True, True, True],
[True, False, False, False, True],
[True, True, True, True, True],
],
pixel_scales=1.0,
)
masked_interferometer = ag.MaskedInterferometer(
interferometer=interferometer,
visibilities_mask=visibilities_mask,
real_space_mask=real_space_mask,
settings=ag.SettingsMaskedInterferometer(
grid_class=ag.Grid2D, sub_size=1
),
)
# Setup as a ray trace instance, using a light profile for the galaxy
g0 = ag.Galaxy(
redshift=0.5, light_profile=MockLightProfile(value=1.0, size=2)
)
plane = ag.Plane(galaxies=[g0])
hyper_background_noise = ag.hyper_data.HyperBackgroundNoise(noise_scale=1.0)
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer,
plane=plane,
hyper_background_noise=hyper_background_noise,
)
assert (
fit.visibilities.slim == np.array([5.0 + 5.0j, 5.0 + 5.0j, 5.0 + 5.0j])
).all()
assert (
fit.noise_map.slim == np.array([3.0 + 3.0j, 3.0 + 3.0j, 3.0 + 3.0j])
).all()
class TestCompareToManualProfilesOnly:
def test___all_fit_quantities__no_hyper_methods(self, masked_interferometer_7):
g0 = ag.Galaxy(
redshift=0.5,
light_profile=ag.lp.EllipticalSersic(intensity=1.0),
mass_profile=ag.mp.SphericalIsothermal(einstein_radius=1.0),
)
g1 = ag.Galaxy(
redshift=1.0, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7, plane=plane
)
assert masked_interferometer_7.noise_map == pytest.approx(fit.noise_map)
model_visibilities = plane.profile_visibilities_from_grid_and_transformer(
grid=masked_interferometer_7.grid,
transformer=masked_interferometer_7.transformer,
)
assert model_visibilities == pytest.approx(fit.model_visibilities, 1e-4)
residual_map = ag.util.fit.residual_map_from(
data=masked_interferometer_7.visibilities, model_data=model_visibilities
)
assert residual_map == pytest.approx(fit.residual_map, 1e-4)
normalized_residual_map = ag.util.fit.normalized_residual_map_complex_from(
residual_map=residual_map, noise_map=masked_interferometer_7.noise_map
)
assert normalized_residual_map == pytest.approx(
fit.normalized_residual_map, 1e-4
)
chi_squared_map = ag.util.fit.chi_squared_map_complex_from(
residual_map=residual_map, noise_map=masked_interferometer_7.noise_map
)
assert chi_squared_map == pytest.approx(fit.chi_squared_map, 1e-4)
chi_squared = ag.util.fit.chi_squared_complex_from(
chi_squared_map=fit.chi_squared_map
)
noise_normalization = ag.util.fit.noise_normalization_complex_from(
noise_map=masked_interferometer_7.noise_map
)
log_likelihood = ag.util.fit.log_likelihood_from(
chi_squared=chi_squared, noise_normalization=noise_normalization
)
assert log_likelihood == pytest.approx(fit.log_likelihood, 1e-4)
assert log_likelihood == fit.figure_of_merit
def test___fit_galaxy_model_image_dict__corresponds_to_profile_galaxy_images(
self, masked_interferometer_7
):
g0 = ag.Galaxy(
redshift=0.5,
light_profile=ag.lp.EllipticalSersic(intensity=1.0),
mass_profile=ag.mp.SphericalIsothermal(einstein_radius=1.0),
)
g1 = ag.Galaxy(
redshift=1.0, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7, plane=plane
)
g0_image = g0.image_from_grid(grid=masked_interferometer_7.grid)
g1_image = g1.image_from_grid(grid=masked_interferometer_7.grid)
assert fit.galaxy_model_image_dict[g0].slim == pytest.approx(
g0_image, 1.0e-4
)
assert fit.galaxy_model_image_dict[g1].slim == pytest.approx(
g1_image, 1.0e-4
)
def test___fit_galaxy_visibilities_dict__corresponds_to_galaxy_visibilities(
self, masked_interferometer_7
):
g0 = ag.Galaxy(
redshift=0.5,
light_profile=ag.lp.EllipticalSersic(intensity=1.0),
mass_profile=ag.mp.SphericalIsothermal(einstein_radius=1.0),
)
g1 = ag.Galaxy(
redshift=1.0, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7, plane=plane
)
g0_profile_visibilities = g0.profile_visibilities_from_grid_and_transformer(
grid=masked_interferometer_7.grid,
transformer=masked_interferometer_7.transformer,
)
g1_profile_visibilities = g1.profile_visibilities_from_grid_and_transformer(
grid=masked_interferometer_7.grid,
transformer=masked_interferometer_7.transformer,
)
assert fit.galaxy_model_visibilities_dict[g0].slim == pytest.approx(
g0_profile_visibilities, 1.0e-4
)
assert fit.galaxy_model_visibilities_dict[g1].slim == pytest.approx(
g1_profile_visibilities, 1.0e-4
)
assert fit.model_visibilities.slim == pytest.approx(
fit.galaxy_model_visibilities_dict[g0].slim
+ fit.galaxy_model_visibilities_dict[g1].slim,
1.0e-4,
)
def test___all_fit_quantities__hyper_background_noise(
self, masked_interferometer_7
):
hyper_background_noise = ag.hyper_data.HyperBackgroundNoise(noise_scale=1.0)
hyper_noise_map = hyper_background_noise.hyper_noise_map_from_complex_noise_map(
noise_map=masked_interferometer_7.noise_map
)
g0 = ag.Galaxy(
redshift=0.5,
light_profile=ag.lp.EllipticalSersic(intensity=1.0),
mass_profile=ag.mp.SphericalIsothermal(einstein_radius=1.0),
)
g1 = ag.Galaxy(
redshift=1.0, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7,
plane=plane,
hyper_background_noise=hyper_background_noise,
)
assert hyper_noise_map.slim == pytest.approx(fit.noise_map.slim)
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7,
plane=plane,
hyper_background_noise=hyper_background_noise,
use_hyper_scalings=False,
)
assert fit.noise_map == pytest.approx(
masked_interferometer_7.noise_map, 1.0e-4
)
assert fit.noise_map != pytest.approx(hyper_noise_map.slim, 1.0e-4)
class TestCompareToManualInversionOnly:
def test___all_fit_quantities__no_hyper_methods(self, masked_interferometer_7):
# Ensures the inversion grid is used, as this would cause the test to fail.
masked_interferometer_7.grid[0, 0] = -100.0
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=0.01)
g0 = ag.Galaxy(redshift=0.5, pixelization=pix, regularization=reg)
plane = ag.Plane(galaxies=[ag.Galaxy(redshift=0.5), g0])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7, plane=plane
)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_interferometer_7.grid_inversion, sparse_grid=None
)
inversion = inversions.InversionInterferometerMatrix.from_data_mapper_and_regularization(
mapper=mapper,
regularization=reg,
visibilities=masked_interferometer_7.visibilities,
noise_map=masked_interferometer_7.noise_map,
transformer=masked_interferometer_7.transformer,
)
assert inversion.mapped_reconstructed_visibilities == pytest.approx(
fit.model_visibilities, 1.0e-4
)
residual_map = ag.util.fit.residual_map_from(
data=masked_interferometer_7.visibilities,
model_data=inversion.mapped_reconstructed_visibilities,
)
assert residual_map.slim == pytest.approx(fit.residual_map.slim, 1.0e-4)
normalized_residual_map = ag.util.fit.normalized_residual_map_complex_from(
residual_map=residual_map, noise_map=masked_interferometer_7.noise_map
)
assert normalized_residual_map.slim == pytest.approx(
fit.normalized_residual_map.slim, 1.0e-4
)
chi_squared_map = ag.util.fit.chi_squared_map_complex_from(
residual_map=residual_map, noise_map=masked_interferometer_7.noise_map
)
assert chi_squared_map.slim == pytest.approx(
fit.chi_squared_map.slim, 1.0e-4
)
chi_squared = ag.util.fit.chi_squared_complex_from(
chi_squared_map=chi_squared_map
)
noise_normalization = ag.util.fit.noise_normalization_complex_from(
noise_map=masked_interferometer_7.noise_map
)
log_likelihood = ag.util.fit.log_likelihood_from(
chi_squared=chi_squared, noise_normalization=noise_normalization
)
assert log_likelihood == pytest.approx(fit.log_likelihood, 1e-4)
log_likelihood_with_regularization = ag.util.fit.log_likelihood_with_regularization_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
noise_normalization=noise_normalization,
)
assert log_likelihood_with_regularization == pytest.approx(
fit.log_likelihood_with_regularization, 1e-4
)
log_evidence = ag.util.fit.log_evidence_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
log_curvature_regularization_term=inversion.log_det_curvature_reg_matrix_term,
log_regularization_term=inversion.log_det_regularization_matrix_term,
noise_normalization=noise_normalization,
)
assert log_evidence == fit.log_evidence
assert log_evidence == fit.figure_of_merit
mapped_reconstructed_image = ag.util.inversion.mapped_reconstructed_data_from(
mapping_matrix=fit.inversion.mapper.mapping_matrix,
reconstruction=fit.inversion.reconstruction,
)
assert (
fit.inversion.mapped_reconstructed_image.slim
== mapped_reconstructed_image
).all()
def test___fit_galaxy_model_image_dict__images_and_inversion_mapped_reconstructed_image(
self, masked_interferometer_7
):
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
g0 = ag.Galaxy(redshift=0.5)
g1 = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7, plane=plane
)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_interferometer_7.grid, sparse_grid=None
)
inversion = inversions.InversionInterferometerMatrix.from_data_mapper_and_regularization(
mapper=mapper,
regularization=reg,
visibilities=masked_interferometer_7.visibilities,
noise_map=masked_interferometer_7.noise_map,
transformer=masked_interferometer_7.transformer,
)
assert (fit.galaxy_model_image_dict[g0].native == np.zeros((7, 7))).all()
assert fit.galaxy_model_image_dict[g1].slim == pytest.approx(
inversion.mapped_reconstructed_image.slim, 1.0e-4
)
def test___fit_galaxy_model_visibilities_dict__has_inversion_mapped_reconstructed_visibilities(
self, masked_interferometer_7
):
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
g0 = ag.Galaxy(redshift=0.5)
g1 = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7, plane=plane
)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_interferometer_7.grid, sparse_grid=None
)
inversion = inversions.InversionInterferometerMatrix.from_data_mapper_and_regularization(
mapper=mapper,
regularization=reg,
visibilities=masked_interferometer_7.visibilities,
noise_map=masked_interferometer_7.noise_map,
transformer=masked_interferometer_7.transformer,
)
assert (
fit.galaxy_model_visibilities_dict[g0] == 0.0 + 0.0j * np.zeros((7,))
).all()
assert fit.galaxy_model_visibilities_dict[g1].slim == pytest.approx(
inversion.mapped_reconstructed_visibilities.slim, 1.0e-4
)
assert fit.model_visibilities.slim == pytest.approx(
fit.galaxy_model_visibilities_dict[g1].slim, 1.0e-4
)
def test___all_fit_quantities__hyper_background_noise(
self, masked_interferometer_7
):
hyper_background_noise = ag.hyper_data.HyperBackgroundNoise(noise_scale=1.0)
hyper_noise_map = hyper_background_noise.hyper_noise_map_from_complex_noise_map(
noise_map=masked_interferometer_7.noise_map
)
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=0.01)
g0 = ag.Galaxy(redshift=0.5, pixelization=pix, regularization=reg)
plane = ag.Plane(galaxies=[ag.Galaxy(redshift=0.5), g0])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7,
plane=plane,
hyper_background_noise=hyper_background_noise,
)
assert hyper_noise_map.slim == pytest.approx(
fit.inversion.noise_map, 1.0e-4
)
assert hyper_noise_map.slim == pytest.approx(fit.noise_map.slim)
def test___all_fit_quantities__uses_linear_operator_inversion(
self, masked_interferometer_7_lop
):
# Ensures the inversion grid is used, as this would cause the test to fail.
masked_interferometer_7_lop.grid[0, 0] = -100.0
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=0.01)
g0 = ag.Galaxy(redshift=0.5, pixelization=pix, regularization=reg)
plane = ag.Plane(galaxies=[ag.Galaxy(redshift=0.5), g0])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7_lop,
plane=plane,
settings_inversion=ag.SettingsInversion(use_linear_operators=True),
)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_interferometer_7_lop.grid_inversion, sparse_grid=None
)
inversion = inversions.InversionInterferometerLinearOperator.from_data_mapper_and_regularization(
mapper=mapper,
regularization=reg,
visibilities=masked_interferometer_7_lop.visibilities,
noise_map=masked_interferometer_7_lop.noise_map,
transformer=masked_interferometer_7_lop.transformer,
settings=ag.SettingsInversion(use_linear_operators=True),
)
assert inversion.mapped_reconstructed_visibilities == pytest.approx(
fit.model_visibilities, 1.0e-4
)
residual_map = ag.util.fit.residual_map_from(
data=masked_interferometer_7_lop.visibilities,
model_data=inversion.mapped_reconstructed_visibilities,
)
assert residual_map.slim == pytest.approx(fit.residual_map.slim, 1.0e-4)
normalized_residual_map = ag.util.fit.normalized_residual_map_complex_from(
residual_map=residual_map,
noise_map=masked_interferometer_7_lop.noise_map,
)
assert normalized_residual_map.slim == pytest.approx(
fit.normalized_residual_map.slim, 1.0e-4
)
chi_squared_map = ag.util.fit.chi_squared_map_complex_from(
residual_map=residual_map,
noise_map=masked_interferometer_7_lop.noise_map,
)
assert chi_squared_map.slim == pytest.approx(
fit.chi_squared_map.slim, 1.0e-4
)
chi_squared = ag.util.fit.chi_squared_complex_from(
chi_squared_map=chi_squared_map
)
noise_normalization = ag.util.fit.noise_normalization_complex_from(
noise_map=masked_interferometer_7_lop.noise_map
)
log_likelihood = ag.util.fit.log_likelihood_from(
chi_squared=chi_squared, noise_normalization=noise_normalization
)
assert log_likelihood == pytest.approx(fit.log_likelihood, 1e-4)
log_likelihood_with_regularization = ag.util.fit.log_likelihood_with_regularization_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
noise_normalization=noise_normalization,
)
assert log_likelihood_with_regularization == pytest.approx(
fit.log_likelihood_with_regularization, 1e-4
)
log_evidence = ag.util.fit.log_evidence_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
log_curvature_regularization_term=inversion.log_det_curvature_reg_matrix_term,
log_regularization_term=inversion.log_det_regularization_matrix_term,
noise_normalization=noise_normalization,
)
assert log_evidence == fit.log_evidence
assert log_evidence == fit.figure_of_merit
mapped_reconstructed_image = ag.util.inversion.mapped_reconstructed_data_from(
mapping_matrix=fit.inversion.mapper.mapping_matrix,
reconstruction=fit.inversion.reconstruction,
)
assert (
fit.inversion.mapped_reconstructed_image.slim
== mapped_reconstructed_image
).all()
class TestCompareToManualProfilesAndInversion:
def test___all_fit_quantities__no_hyper_methods(self, masked_interferometer_7):
galaxy_light = ag.Galaxy(
redshift=0.5, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
galaxy_pix = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[galaxy_light, galaxy_pix])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7, plane=plane
)
profile_visibilities = plane.profile_visibilities_from_grid_and_transformer(
grid=masked_interferometer_7.grid,
transformer=masked_interferometer_7.transformer,
)
assert profile_visibilities.slim == pytest.approx(
fit.profile_visibilities.slim
)
profile_subtracted_visibilities = (
masked_interferometer_7.visibilities - profile_visibilities
)
assert profile_subtracted_visibilities.slim == pytest.approx(
fit.profile_subtracted_visibilities.slim
)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_interferometer_7.grid,
settings=ag.SettingsPixelization(use_border=False),
)
inversion = inversions.InversionInterferometerMatrix.from_data_mapper_and_regularization(
visibilities=profile_subtracted_visibilities,
noise_map=masked_interferometer_7.noise_map,
transformer=masked_interferometer_7.transformer,
mapper=mapper,
regularization=reg,
)
model_visibilities = (
profile_visibilities + inversion.mapped_reconstructed_visibilities
)
assert model_visibilities.slim == pytest.approx(fit.model_visibilities.slim)
residual_map = ag.util.fit.residual_map_from(
data=masked_interferometer_7.visibilities, model_data=model_visibilities
)
assert residual_map.slim == pytest.approx(fit.residual_map.slim)
normalized_residual_map = ag.util.fit.normalized_residual_map_complex_from(
residual_map=residual_map, noise_map=masked_interferometer_7.noise_map
)
assert normalized_residual_map.slim == pytest.approx(
fit.normalized_residual_map.slim
)
chi_squared_map = ag.util.fit.chi_squared_map_complex_from(
residual_map=residual_map, noise_map=masked_interferometer_7.noise_map
)
assert chi_squared_map.slim == pytest.approx(fit.chi_squared_map.slim)
chi_squared = ag.util.fit.chi_squared_complex_from(
chi_squared_map=chi_squared_map
)
noise_normalization = ag.util.fit.noise_normalization_complex_from(
noise_map=masked_interferometer_7.noise_map
)
log_likelihood = ag.util.fit.log_likelihood_from(
chi_squared=chi_squared, noise_normalization=noise_normalization
)
assert log_likelihood == pytest.approx(fit.log_likelihood, 1e-4)
log_likelihood_with_regularization = ag.util.fit.log_likelihood_with_regularization_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
noise_normalization=noise_normalization,
)
assert log_likelihood_with_regularization == pytest.approx(
fit.log_likelihood_with_regularization, 1e-4
)
log_evidence = ag.util.fit.log_evidence_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
log_curvature_regularization_term=inversion.log_det_curvature_reg_matrix_term,
log_regularization_term=inversion.log_det_regularization_matrix_term,
noise_normalization=noise_normalization,
)
assert log_evidence == fit.log_evidence
assert log_evidence == fit.figure_of_merit
mapped_reconstructed_image = ag.util.inversion.mapped_reconstructed_data_from(
mapping_matrix=fit.inversion.mapper.mapping_matrix,
reconstruction=fit.inversion.reconstruction,
)
assert (
fit.inversion.mapped_reconstructed_image.slim
== mapped_reconstructed_image
).all()
def test___fit_galaxy_model_visibilities_dict__has_image_and_inversion_mapped_reconstructed_image(
self, masked_interferometer_7
):
g0 = ag.Galaxy(
redshift=0.5, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
g1 = ag.Galaxy(
redshift=0.5, light_profile=ag.lp.EllipticalSersic(intensity=2.0)
)
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
galaxy_pix = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1, galaxy_pix])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7, plane=plane
)
g0_visibilities = g0.profile_visibilities_from_grid_and_transformer(
grid=masked_interferometer_7.grid,
transformer=masked_interferometer_7.transformer,
)
g1_visibilities = g1.profile_visibilities_from_grid_and_transformer(
grid=masked_interferometer_7.grid,
transformer=masked_interferometer_7.transformer,
)
profile_visibilities = g0_visibilities + g1_visibilities
profile_subtracted_visibilities = (
masked_interferometer_7.visibilities - profile_visibilities
)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_interferometer_7.grid,
settings=ag.SettingsPixelization(use_border=False),
)
inversion = inversions.InversionInterferometerMatrix.from_data_mapper_and_regularization(
visibilities=profile_subtracted_visibilities,
noise_map=masked_interferometer_7.noise_map,
transformer=masked_interferometer_7.transformer,
mapper=mapper,
regularization=reg,
)
g0_image = g0.image_from_grid(grid=masked_interferometer_7.grid)
g1_image = g1.image_from_grid(grid=masked_interferometer_7.grid)
assert fit.galaxy_model_image_dict[g0].slim == pytest.approx(
g0_image.slim, 1.0e-4
)
assert fit.galaxy_model_image_dict[g1].slim == pytest.approx(
g1_image.slim, 1.0e-4
)
assert fit.galaxy_model_image_dict[galaxy_pix].slim == pytest.approx(
inversion.mapped_reconstructed_image.slim, 1.0e-4
)
def test___fit_galaxy_model_visibilities_dict__has_profile_visibilitiess_and_inversion_mapped_reconstructed_visibilities(
self, masked_interferometer_7
):
g0 = ag.Galaxy(
redshift=0.5, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
g1 = ag.Galaxy(
redshift=0.5, light_profile=ag.lp.EllipticalSersic(intensity=2.0)
)
g2 = ag.Galaxy(redshift=0.5)
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
galaxy_pix = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1, g2, galaxy_pix])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7, plane=plane
)
g0_visibilities = g0.profile_visibilities_from_grid_and_transformer(
grid=masked_interferometer_7.grid,
transformer=masked_interferometer_7.transformer,
)
g1_visibilities = g1.profile_visibilities_from_grid_and_transformer(
grid=masked_interferometer_7.grid,
transformer=masked_interferometer_7.transformer,
)
profile_visibilities = g0_visibilities + g1_visibilities
profile_subtracted_visibilities = (
masked_interferometer_7.visibilities - profile_visibilities
)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_interferometer_7.grid,
settings=ag.SettingsPixelization(use_border=False),
)
inversion = inversions.InversionInterferometerMatrix.from_data_mapper_and_regularization(
visibilities=profile_subtracted_visibilities,
noise_map=masked_interferometer_7.noise_map,
transformer=masked_interferometer_7.transformer,
mapper=mapper,
regularization=reg,
)
assert (
fit.galaxy_model_visibilities_dict[g2] == 0.0 + 0.0j * np.zeros((7,))
).all()
assert fit.galaxy_model_visibilities_dict[g0].slim == pytest.approx(
g0_visibilities.slim, 1.0e-4
)
assert fit.galaxy_model_visibilities_dict[g1].slim == pytest.approx(
g1_visibilities.slim, 1.0e-4
)
assert fit.galaxy_model_visibilities_dict[galaxy_pix].slim == pytest.approx(
inversion.mapped_reconstructed_visibilities.slim, 1.0e-4
)
assert fit.model_visibilities.slim == pytest.approx(
fit.galaxy_model_visibilities_dict[g0].slim
+ fit.galaxy_model_visibilities_dict[g1].slim
+ inversion.mapped_reconstructed_visibilities.slim,
1.0e-4,
)
def test___all_fit_quantities__hyper_background_noise(
self, masked_interferometer_7
):
hyper_background_noise = ag.hyper_data.HyperBackgroundNoise(noise_scale=1.0)
hyper_noise_map = hyper_background_noise.hyper_noise_map_from_complex_noise_map(
noise_map=masked_interferometer_7.noise_map
)
galaxy_light = ag.Galaxy(
redshift=0.5, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
galaxy_pix = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[galaxy_light, galaxy_pix])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7,
plane=plane,
hyper_background_noise=hyper_background_noise,
)
assert hyper_noise_map.slim == pytest.approx(
fit.inversion.noise_map, 1.0e-4
)
assert hyper_noise_map.slim == pytest.approx(fit.noise_map.slim) | test_autogalaxy/unit/fit/test_fit.py | import numpy as np
import pytest
import autogalaxy as ag
from autoarray.inversion import inversions
from autogalaxy.mock.mock import MockLightProfile
class MockFitImaging:
def __init__(self, model_images_of_galaxies):
self.model_images_of_galaxies = model_images_of_galaxies
class TestFitImaging:
class TestLikelihood:
def test__1x2_image__no_psf_blurring__plane_fits_data_with_chi_sq_5(self):
# The image plane image generated by the galaxy is [1.0, 1.0]
# Thus the chi squared is 4.0**2.0 + 3.0**2.0 = 25.0
psf = ag.Kernel2D.manual_native(
array=[[0.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 0.0]],
pixel_scales=1.0,
)
imaging = ag.Imaging(
image=5.0 * ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
psf=psf,
noise_map=ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
)
imaging.image[6] = 4.0
mask = ag.Mask2D.manual(
mask=[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
],
pixel_scales=1.0,
)
masked_imaging_7x7 = ag.MaskedImaging(
imaging=imaging,
mask=mask,
settings=ag.SettingsMaskedImaging(grid_class=ag.Grid2D, sub_size=1),
)
# Setup as a ray trace instance, using a light profile for the galaxy
g0 = ag.Galaxy(
redshift=0.5, light_profile=MockLightProfile(value=1.0, size=2)
)
plane = ag.Plane(galaxies=[g0])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
assert (
fit.mask
== np.array(
[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
]
)
).all()
assert (
fit.image.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 5.0, 4.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.noise_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 1.0, 1.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.model_image.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 1.0, 1.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.residual_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 4.0, 3.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.normalized_residual_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 4.0, 3.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.chi_squared_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 16.0, 9.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert fit.chi_squared == 25.0
assert fit.reduced_chi_squared == 25.0 / 2.0
assert fit.noise_normalization == (2.0 * np.log(2 * np.pi * 1.0 ** 2.0))
assert fit.log_likelihood == -0.5 * (
25.0 + 2.0 * np.log(2 * np.pi * 1.0 ** 2.0)
)
def test__1x2_image__include_psf_blurring__plane_fits_data_with_chi_sq_4(self):
# This PSF changes the blurred image plane image from [1.0, 1.0] to [1.0, 5.0]
# Thus, the chi squared is 4.0**2.0 + 0.0**2.0 = 16.0
psf = ag.Kernel2D.manual_native(
array=[[0.0, 0.0, 0.0], [0.0, 1.0, 3.0], [0.0, 0.0, 0.0]],
pixel_scales=1.0,
renormalize=False,
)
imaging = ag.Imaging(
image=5.0 * ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
psf=psf,
noise_map=ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
)
imaging.image[6] = 4.0
mask = ag.Mask2D.manual(
mask=[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
],
pixel_scales=1.0,
)
masked_imaging_7x7 = ag.MaskedImaging(
imaging=imaging,
mask=mask,
settings=ag.SettingsMaskedImaging(
grid_class=ag.Grid2D, renormalize_psf=False, sub_size=1
),
)
# Setup as a ray trace instance, using a light profile for the galaxy
g0 = ag.Galaxy(
redshift=0.5, light_profile=MockLightProfile(value=1.0, size=2)
)
plane = ag.Plane(galaxies=[g0])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
assert (
fit.mask
== np.array(
[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
]
)
).all()
assert (
fit.image.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 5.0, 4.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.noise_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 1.0, 1.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.model_image.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 1.0, 4.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.residual_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 4.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.normalized_residual_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 4.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.chi_squared_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 16.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert fit.chi_squared == 16.0
assert fit.reduced_chi_squared == 16.0 / 2.0
assert fit.noise_normalization == (2.0 * np.log(2 * np.pi * 1.0 ** 2.0))
assert fit.log_likelihood == -0.5 * (
16.0 + 2.0 * np.log(2 * np.pi * 1.0 ** 2.0)
)
def test__hyper_galaxy_changes_noise_above_from_1_to_2__reflected_in_likelihood(
self,
):
# This PSF changes the blurred image plane image from [1.0, 1.0] to [1.0, 5.0]
# Thus, the chi squared is 4.0**2.0 + 0.0**2.0 = 16.0
# The hyper_galaxies galaxy increases the noise in both pixels by 1.0, to 2.0.
# This reduces the chi squared to 2.0 instead of 4.0
psf = ag.Kernel2D.manual_native(
array=[[0.0, 0.0, 0.0], [0.0, 1.0, 3.0], [0.0, 0.0, 0.0]],
pixel_scales=1.0,
)
imaging = ag.Imaging(
image=5.0 * ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
psf=psf,
noise_map=ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
)
imaging.image[6] = 4.0
mask = ag.Mask2D.manual(
mask=[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
],
pixel_scales=1.0,
)
masked_imaging_7x7 = ag.MaskedImaging(
imaging=imaging,
mask=mask,
settings=ag.SettingsMaskedImaging(
grid_class=ag.Grid2D, renormalize_psf=False, sub_size=1
),
)
# Setup as a ray trace instance, using a light profile for the galaxy
g0 = ag.Galaxy(
redshift=0.5,
light_profile=MockLightProfile(value=1.0, size=2),
hyper_galaxy=ag.HyperGalaxy(
contribution_factor=1.0, noise_factor=1.0, noise_power=1.0
),
hyper_model_image=ag.Array2D.ones(
shape_native=(1, 2), pixel_scales=1.0
),
hyper_galaxy_image=ag.Array2D.ones(
shape_native=(1, 2), pixel_scales=1.0
),
hyper_minimum_value=0.0,
)
plane = ag.Plane(galaxies=[g0])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
assert (
fit.noise_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 2.0, 2.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.chi_squared_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 4.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert fit.chi_squared == 4.0
assert fit.reduced_chi_squared == 4.0 / 2.0
assert fit.noise_normalization == (2.0 * np.log(2 * np.pi * 2.0 ** 2.0))
assert fit.log_likelihood == -0.5 * (
4.0 + 2.0 * np.log(2 * np.pi * 2.0 ** 2.0)
)
def test__hyper_image_changes_background_sky__reflected_in_likelihood(self):
psf = ag.Kernel2D.manual_native(
array=[[0.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 0.0]],
pixel_scales=1.0,
)
imaging = ag.Imaging(
image=ag.Array2D.full(
fill_value=4.0, shape_native=(3, 4), pixel_scales=1.0
),
psf=psf,
noise_map=ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
)
imaging.image[5] = 5.0
mask = ag.Mask2D.manual(
mask=[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
],
pixel_scales=1.0,
)
masked_imaging_7x7 = ag.MaskedImaging(
imaging=imaging,
mask=mask,
settings=ag.SettingsMaskedImaging(grid_class=ag.Grid2D, sub_size=1),
)
# Setup as a ray trace instance, using a light profile for the galaxy
g0 = ag.Galaxy(
redshift=0.5, light_profile=MockLightProfile(value=1.0, size=2)
)
plane = ag.Plane(galaxies=[g0])
hyper_image_sky = ag.hyper_data.HyperImageSky(sky_scale=1.0)
fit = ag.FitImaging(
masked_imaging=masked_imaging_7x7,
plane=plane,
hyper_image_sky=hyper_image_sky,
)
assert (
fit.mask
== np.array(
[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
]
)
).all()
assert (
fit.image.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 6.0, 5.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert (
fit.chi_squared_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 25.0, 16.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert fit.chi_squared == 41.0
assert fit.reduced_chi_squared == 41.0 / 2.0
assert fit.noise_normalization == (2.0 * np.log(2 * np.pi * 1.0 ** 2.0))
assert fit.log_likelihood == -0.5 * (
41.0 + 2.0 * np.log(2 * np.pi * 1.0 ** 2.0)
)
def test__hyper_background_changes_background_noise_map__reflected_in_likelihood(
self,
):
psf = ag.Kernel2D.manual_native(
array=[[0.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 0.0]],
pixel_scales=1.0,
)
imaging = ag.Imaging(
image=5.0 * ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
psf=psf,
noise_map=ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
)
imaging.image[6] = 4.0
mask = ag.Mask2D.manual(
mask=[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
],
pixel_scales=1.0,
)
masked_imaging_7x7 = ag.MaskedImaging(
imaging=imaging,
mask=mask,
settings=ag.SettingsMaskedImaging(grid_class=ag.Grid2D, sub_size=1),
)
# Setup as a ray trace instance, using a light profile for the galaxy
g0 = ag.Galaxy(
redshift=0.5, light_profile=MockLightProfile(value=1.0, size=2)
)
plane = ag.Plane(galaxies=[g0])
hyper_background_noise = ag.hyper_data.HyperBackgroundNoise(noise_scale=1.0)
fit = ag.FitImaging(
masked_imaging=masked_imaging_7x7,
plane=plane,
hyper_background_noise=hyper_background_noise,
)
assert (
fit.noise_map.native
== np.array(
[[0.0, 0.0, 0.0, 0.0], [0.0, 2.0, 2.0, 0.0], [0.0, 0.0, 0.0, 0.0]]
)
).all()
assert fit.chi_squared == 6.25
assert fit.reduced_chi_squared == 6.25 / 2.0
assert fit.noise_normalization == (2.0 * np.log(2 * np.pi * 2.0 ** 2.0))
assert fit.log_likelihood == -0.5 * (
6.25 + 2.0 * np.log(2 * np.pi * 2.0 ** 2.0)
)
def test__hyper_galaxy_changes_noise_above_hyper_noise_limit__rounded_down_to_limit(
self,
):
# This PSF changes the blurred image plane image from [1.0, 1.0] to [1.0, 5.0]
# Thus, the chi squared is 4.0**2.0 + 0.0**2.0 = 16.0
# The hyper_galaxies galaxy increases the noise in both pixels by 1.0, to 2.0.
# This reduces the chi squared to 2.0 instead of 4.0
psf = ag.Kernel2D.manual_native(
array=[[0.0, 0.0, 0.0], [0.0, 1.0, 3.0], [0.0, 0.0, 0.0]],
pixel_scales=1.0,
)
imaging = ag.Imaging(
image=5.0 * ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
psf=psf,
noise_map=ag.Array2D.ones(shape_native=(3, 4), pixel_scales=1.0),
)
imaging.image[6] = 4.0
mask = ag.Mask2D.manual(
mask=[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
],
pixel_scales=1.0,
)
masked_imaging_7x7 = ag.MaskedImaging(
imaging=imaging,
mask=mask,
settings=ag.SettingsMaskedImaging(
grid_class=ag.Grid2D, renormalize_psf=False, sub_size=1
),
)
# Setup as a ray trace instance, using a light profile for the galaxy
g0 = ag.Galaxy(
redshift=0.5,
light_profile=MockLightProfile(value=1.0, size=2),
hyper_galaxy=ag.HyperGalaxy(
contribution_factor=1.0, noise_factor=1.0e9, noise_power=1.0
),
hyper_model_image=ag.Array2D.ones(
shape_native=(1, 2), pixel_scales=1.0
),
hyper_galaxy_image=ag.Array2D.ones(
shape_native=(1, 2), pixel_scales=1.0
),
hyper_minimum_value=0.0,
)
plane = ag.Plane(galaxies=[g0])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
assert (
fit.noise_map.native
== np.array(
[
[0.0, 0.0, 0.0, 0.0],
[0.0, 1.0e8, 1.0e8, 0.0],
[0.0, 0.0, 0.0, 0.0],
]
)
).all()
class TestCompareToManualProfilesOnly:
def test___all_fit_quantities__no_hyper_methods(self, masked_imaging_7x7):
g0 = ag.Galaxy(
redshift=0.5,
light_profile=ag.lp.EllipticalSersic(intensity=1.0),
mass_profile=ag.mp.SphericalIsothermal(einstein_radius=1.0),
)
g1 = ag.Galaxy(
redshift=1.0, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
assert masked_imaging_7x7.noise_map.native == pytest.approx(
fit.noise_map.native
)
model_image = plane.blurred_image_from_grid_and_convolver(
grid=masked_imaging_7x7.grid,
convolver=masked_imaging_7x7.convolver,
blurring_grid=masked_imaging_7x7.blurring_grid,
)
assert model_image.native == pytest.approx(fit.model_image.native)
residual_map = ag.util.fit.residual_map_from(
data=masked_imaging_7x7.image, model_data=model_image
)
assert residual_map.native == pytest.approx(fit.residual_map.native)
normalized_residual_map = ag.util.fit.normalized_residual_map_from(
residual_map=residual_map, noise_map=masked_imaging_7x7.noise_map
)
assert normalized_residual_map.native == pytest.approx(
fit.normalized_residual_map.native
)
chi_squared_map = ag.util.fit.chi_squared_map_from(
residual_map=residual_map, noise_map=masked_imaging_7x7.noise_map
)
assert chi_squared_map.native == pytest.approx(fit.chi_squared_map.native)
chi_squared = ag.util.fit.chi_squared_from(chi_squared_map=chi_squared_map)
noise_normalization = ag.util.fit.noise_normalization_from(
noise_map=masked_imaging_7x7.noise_map
)
log_likelihood = ag.util.fit.log_likelihood_from(
chi_squared=chi_squared, noise_normalization=noise_normalization
)
assert log_likelihood == pytest.approx(fit.log_likelihood, 1e-4)
assert log_likelihood == fit.figure_of_merit
def test___fit_galaxy_model_image_dict__corresponds_to_blurred_galaxy_images(
self, masked_imaging_7x7
):
g0 = ag.Galaxy(
redshift=0.5,
light_profile=ag.lp.EllipticalSersic(intensity=1.0),
mass_profile=ag.mp.SphericalIsothermal(einstein_radius=1.0),
)
g1 = ag.Galaxy(
redshift=1.0, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
g2 = ag.Galaxy(redshift=1.0)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1, g2])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
g0_blurred_image = g0.blurred_image_from_grid_and_convolver(
grid=masked_imaging_7x7.grid,
blurring_grid=masked_imaging_7x7.blurring_grid,
convolver=masked_imaging_7x7.convolver,
)
g1_blurred_image = g1.blurred_image_from_grid_and_convolver(
grid=masked_imaging_7x7.grid,
blurring_grid=masked_imaging_7x7.blurring_grid,
convolver=masked_imaging_7x7.convolver,
)
assert fit.galaxy_model_image_dict[g0] == pytest.approx(
g0_blurred_image, 1.0e-4
)
assert fit.galaxy_model_image_dict[g1] == pytest.approx(
g1_blurred_image, 1.0e-4
)
assert (fit.galaxy_model_image_dict[g2].slim == np.zeros(9)).all()
assert fit.model_image.native == pytest.approx(
fit.galaxy_model_image_dict[g0].native
+ fit.galaxy_model_image_dict[g1].native,
1.0e-4,
)
def test___all_fit_quantities__including_hyper_methods(
self, masked_imaging_7x7
):
hyper_image_sky = ag.hyper_data.HyperImageSky(sky_scale=1.0)
hyper_background_noise = ag.hyper_data.HyperBackgroundNoise(noise_scale=1.0)
image = hyper_image_sky.hyper_image_from_image(
image=masked_imaging_7x7.image
)
g0 = ag.Galaxy(
redshift=0.5,
light_profile=ag.lp.EllipticalSersic(intensity=1.0),
mass_profile=ag.mp.SphericalIsothermal(einstein_radius=1.0),
hyper_galaxy=ag.HyperGalaxy(
contribution_factor=1.0, noise_factor=1.0, noise_power=1.0
),
hyper_model_image=np.ones(9),
hyper_galaxy_image=np.ones(9),
hyper_minimum_value=0.0,
)
g1 = ag.Galaxy(
redshift=1.0, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1])
fit = ag.FitImaging(
masked_imaging=masked_imaging_7x7,
plane=plane,
hyper_image_sky=hyper_image_sky,
hyper_background_noise=hyper_background_noise,
)
hyper_noise_map_background = hyper_background_noise.hyper_noise_map_from_noise_map(
noise_map=masked_imaging_7x7.noise_map
)
hyper_noise = plane.hyper_noise_map_from_noise_map(
noise_map=masked_imaging_7x7.noise_map
)
hyper_noise_map = hyper_noise_map_background + hyper_noise
assert hyper_noise_map.native == pytest.approx(fit.noise_map.native)
model_image = plane.blurred_image_from_grid_and_convolver(
grid=masked_imaging_7x7.grid,
convolver=masked_imaging_7x7.convolver,
blurring_grid=masked_imaging_7x7.blurring_grid,
)
assert model_image.native == pytest.approx(fit.model_image.native)
residual_map = ag.util.fit.residual_map_from(
data=image, model_data=model_image
)
assert residual_map.native == pytest.approx(fit.residual_map.native)
normalized_residual_map = ag.util.fit.normalized_residual_map_from(
residual_map=residual_map, noise_map=hyper_noise_map
)
assert normalized_residual_map.native == pytest.approx(
fit.normalized_residual_map.native
)
chi_squared_map = ag.util.fit.chi_squared_map_from(
residual_map=residual_map, noise_map=hyper_noise_map
)
assert chi_squared_map.native == pytest.approx(fit.chi_squared_map.native)
chi_squared = ag.util.fit.chi_squared_from(chi_squared_map=chi_squared_map)
noise_normalization = ag.util.fit.noise_normalization_from(
noise_map=hyper_noise_map
)
log_likelihood = ag.util.fit.log_likelihood_from(
chi_squared=chi_squared, noise_normalization=noise_normalization
)
assert log_likelihood == pytest.approx(fit.log_likelihood, 1e-4)
assert log_likelihood == fit.figure_of_merit
fit = ag.FitImaging(
masked_imaging=masked_imaging_7x7,
plane=plane,
hyper_image_sky=hyper_image_sky,
hyper_background_noise=hyper_background_noise,
use_hyper_scalings=False,
)
assert fit.image == pytest.approx(masked_imaging_7x7.image, 1.0e-4)
assert fit.noise_map == pytest.approx(masked_imaging_7x7.noise_map, 1.0e-4)
def test___blurred_and_model_images_of_galaxies_and_unmasked_blurred_image_properties(
self, masked_imaging_7x7
):
g0 = ag.Galaxy(
redshift=0.5,
light_profile=ag.lp.EllipticalSersic(intensity=1.0),
mass_profile=ag.mp.SphericalIsothermal(einstein_radius=1.0),
)
g1 = ag.Galaxy(
redshift=1.0, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
blurred_images_of_galaxies = plane.blurred_images_of_galaxies_from_grid_and_convolver(
grid=masked_imaging_7x7.grid,
convolver=masked_imaging_7x7.convolver,
blurring_grid=masked_imaging_7x7.blurring_grid,
)
assert blurred_images_of_galaxies[0].native == pytest.approx(
fit.model_images_of_galaxies[0].native, 1.0e-4
)
assert blurred_images_of_galaxies[1].native == pytest.approx(
fit.model_images_of_galaxies[1].native, 1.0e-4
)
unmasked_blurred_image = plane.unmasked_blurred_image_from_grid_and_psf(
grid=masked_imaging_7x7.grid, psf=masked_imaging_7x7.psf
)
assert (unmasked_blurred_image == fit.unmasked_blurred_image).all()
unmasked_blurred_image_of_galaxies = plane.unmasked_blurred_image_of_galaxies_from_grid_and_psf(
grid=masked_imaging_7x7.grid, psf=masked_imaging_7x7.psf
)
assert (
unmasked_blurred_image_of_galaxies[0]
== fit.unmasked_blurred_image_of_galaxies[0]
).all()
assert (
unmasked_blurred_image_of_galaxies[1]
== fit.unmasked_blurred_image_of_galaxies[1]
).all()
class TestCompareToManualInversionOnly:
def test___all_quantities__no_hyper_methods(self, masked_imaging_7x7):
# Ensures the inversion grid is used, as this would cause the test to fail.
masked_imaging_7x7.grid[0, 0] = -100.0
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
g0 = ag.Galaxy(redshift=0.5, pixelization=pix, regularization=reg)
plane = ag.Plane(galaxies=[ag.Galaxy(redshift=0.5), g0])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_imaging_7x7.grid_inversion, sparse_grid=None
)
inversion = inversions.InversionImagingMatrix.from_data_mapper_and_regularization(
mapper=mapper,
regularization=reg,
image=masked_imaging_7x7.image,
noise_map=masked_imaging_7x7.noise_map,
convolver=masked_imaging_7x7.convolver,
)
assert inversion.mapped_reconstructed_image.native == pytest.approx(
fit.model_image.native, 1.0e-4
)
residual_map = ag.util.fit.residual_map_from(
data=masked_imaging_7x7.image,
model_data=inversion.mapped_reconstructed_image,
)
assert residual_map.native == pytest.approx(fit.residual_map.native, 1.0e-4)
normalized_residual_map = ag.util.fit.normalized_residual_map_from(
residual_map=residual_map, noise_map=masked_imaging_7x7.noise_map
)
assert normalized_residual_map.native == pytest.approx(
fit.normalized_residual_map.native, 1.0e-4
)
chi_squared_map = ag.util.fit.chi_squared_map_from(
residual_map=residual_map, noise_map=masked_imaging_7x7.noise_map
)
assert chi_squared_map.native == pytest.approx(
fit.chi_squared_map.native, 1.0e-4
)
chi_squared = ag.util.fit.chi_squared_from(chi_squared_map=chi_squared_map)
noise_normalization = ag.util.fit.noise_normalization_from(
noise_map=masked_imaging_7x7.noise_map
)
log_likelihood = ag.util.fit.log_likelihood_from(
chi_squared=chi_squared, noise_normalization=noise_normalization
)
assert log_likelihood == pytest.approx(fit.log_likelihood, 1e-4)
log_likelihood_with_regularization = ag.util.fit.log_likelihood_with_regularization_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
noise_normalization=noise_normalization,
)
assert log_likelihood_with_regularization == pytest.approx(
fit.log_likelihood_with_regularization, 1e-4
)
log_evidence = ag.util.fit.log_evidence_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
log_curvature_regularization_term=inversion.log_det_curvature_reg_matrix_term,
log_regularization_term=inversion.log_det_regularization_matrix_term,
noise_normalization=noise_normalization,
)
assert log_evidence == fit.log_evidence
assert log_evidence == fit.figure_of_merit
def test___fit_galaxy_model_image_dict__has_inversion_mapped_reconstructed_image(
self, masked_imaging_7x7
):
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
g0 = ag.Galaxy(redshift=0.5)
g1 = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_imaging_7x7.grid, sparse_grid=None
)
inversion = inversions.InversionImagingMatrix.from_data_mapper_and_regularization(
mapper=mapper,
regularization=reg,
image=masked_imaging_7x7.image,
noise_map=masked_imaging_7x7.noise_map,
convolver=masked_imaging_7x7.convolver,
)
assert (fit.galaxy_model_image_dict[g0] == np.zeros(9)).all()
assert fit.galaxy_model_image_dict[g1].native == pytest.approx(
inversion.mapped_reconstructed_image.native, 1.0e-4
)
assert fit.model_image.native == pytest.approx(
fit.galaxy_model_image_dict[g1].native, 1.0e-4
)
def test___all_fit_quantities__include_hyper_methods(self, masked_imaging_7x7):
hyper_image_sky = ag.hyper_data.HyperImageSky(sky_scale=1.0)
hyper_background_noise = ag.hyper_data.HyperBackgroundNoise(noise_scale=1.0)
image = hyper_image_sky.hyper_image_from_image(
image=masked_imaging_7x7.image
)
hyper_noise_map_background = hyper_background_noise.hyper_noise_map_from_noise_map(
noise_map=masked_imaging_7x7.noise_map
)
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
g0 = ag.Galaxy(
redshift=0.5,
pixelization=pix,
regularization=reg,
hyper_galaxy=ag.HyperGalaxy(
contribution_factor=1.0, noise_factor=1.0, noise_power=1.0
),
hyper_model_image=np.ones(9),
hyper_galaxy_image=np.ones(9),
hyper_minimum_value=0.0,
)
plane = ag.Plane(galaxies=[ag.Galaxy(redshift=0.5), g0])
fit = ag.FitImaging(
masked_imaging=masked_imaging_7x7,
plane=plane,
hyper_image_sky=hyper_image_sky,
hyper_background_noise=hyper_background_noise,
)
hyper_noise = plane.hyper_noise_map_from_noise_map(
noise_map=masked_imaging_7x7.noise_map
)
hyper_noise_map = hyper_noise_map_background + hyper_noise
assert hyper_noise_map.native == pytest.approx(fit.noise_map.native)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_imaging_7x7.grid,
settings=ag.SettingsPixelization(use_border=False),
)
inversion = inversions.InversionImagingMatrix.from_data_mapper_and_regularization(
mapper=mapper,
regularization=reg,
image=image,
noise_map=hyper_noise_map,
convolver=masked_imaging_7x7.convolver,
)
assert inversion.mapped_reconstructed_image.native == pytest.approx(
fit.model_image.native, 1.0e-4
)
residual_map = ag.util.fit.residual_map_from(
data=image, model_data=inversion.mapped_reconstructed_image
)
assert residual_map.native == pytest.approx(fit.residual_map.native)
normalized_residual_map = ag.util.fit.normalized_residual_map_from(
residual_map=residual_map, noise_map=hyper_noise_map
)
assert normalized_residual_map.native == pytest.approx(
fit.normalized_residual_map.native
)
chi_squared_map = ag.util.fit.chi_squared_map_from(
residual_map=residual_map, noise_map=hyper_noise_map
)
assert chi_squared_map.native == pytest.approx(fit.chi_squared_map.native)
chi_squared = ag.util.fit.chi_squared_from(chi_squared_map=chi_squared_map)
noise_normalization = ag.util.fit.noise_normalization_from(
noise_map=hyper_noise_map
)
log_likelihood = ag.util.fit.log_likelihood_from(
chi_squared=chi_squared, noise_normalization=noise_normalization
)
assert log_likelihood == pytest.approx(fit.log_likelihood, 1e-4)
log_likelihood_with_regularization = ag.util.fit.log_likelihood_with_regularization_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
noise_normalization=noise_normalization,
)
assert log_likelihood_with_regularization == pytest.approx(
fit.log_likelihood_with_regularization, 1e-4
)
log_evidence = ag.util.fit.log_evidence_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
log_curvature_regularization_term=inversion.log_det_curvature_reg_matrix_term,
log_regularization_term=inversion.log_det_regularization_matrix_term,
noise_normalization=noise_normalization,
)
assert log_evidence == fit.log_evidence
assert log_evidence == fit.figure_of_merit
def test___blurred_and_model_images_of_galaxies_and_unmasked_blurred_image_properties(
self, masked_imaging_7x7
):
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
g0 = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[ag.Galaxy(redshift=0.5), g0])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_imaging_7x7.grid,
settings=ag.SettingsPixelization(use_border=False),
)
inversion = inversions.InversionImagingMatrix.from_data_mapper_and_regularization(
mapper=mapper,
regularization=reg,
image=masked_imaging_7x7.image,
noise_map=masked_imaging_7x7.noise_map,
convolver=masked_imaging_7x7.convolver,
)
assert (fit.model_images_of_galaxies[0].native == np.zeros((7, 7))).all()
assert inversion.mapped_reconstructed_image.native == pytest.approx(
fit.model_images_of_galaxies[1].native, 1.0e-4
)
class TestCompareToManualProfilesAndInversion:
def test___all_fit_quantities__no_hyper_methods(self, masked_imaging_7x7):
galaxy_light = ag.Galaxy(
redshift=0.5, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
galaxy_pix = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[galaxy_light, galaxy_pix])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
blurred_image = plane.blurred_image_from_grid_and_convolver(
grid=masked_imaging_7x7.grid,
convolver=masked_imaging_7x7.convolver,
blurring_grid=masked_imaging_7x7.blurring_grid,
)
assert blurred_image.native == pytest.approx(fit.blurred_image.native)
profile_subtracted_image = masked_imaging_7x7.image - blurred_image
assert profile_subtracted_image.native == pytest.approx(
fit.profile_subtracted_image.native
)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_imaging_7x7.grid,
settings=ag.SettingsPixelization(use_border=False),
)
inversion = inversions.InversionImagingMatrix.from_data_mapper_and_regularization(
image=profile_subtracted_image,
noise_map=masked_imaging_7x7.noise_map,
convolver=masked_imaging_7x7.convolver,
mapper=mapper,
regularization=reg,
)
model_image = blurred_image + inversion.mapped_reconstructed_image
assert model_image.native == pytest.approx(fit.model_image.native)
residual_map = ag.util.fit.residual_map_from(
data=masked_imaging_7x7.image, model_data=model_image
)
assert residual_map.native == pytest.approx(fit.residual_map.native)
normalized_residual_map = ag.util.fit.normalized_residual_map_from(
residual_map=residual_map, noise_map=masked_imaging_7x7.noise_map
)
assert normalized_residual_map.native == pytest.approx(
fit.normalized_residual_map.native
)
chi_squared_map = ag.util.fit.chi_squared_map_from(
residual_map=residual_map, noise_map=masked_imaging_7x7.noise_map
)
assert chi_squared_map.native == pytest.approx(fit.chi_squared_map.native)
chi_squared = ag.util.fit.chi_squared_from(chi_squared_map=chi_squared_map)
noise_normalization = ag.util.fit.noise_normalization_from(
noise_map=masked_imaging_7x7.noise_map
)
log_likelihood = ag.util.fit.log_likelihood_from(
chi_squared=chi_squared, noise_normalization=noise_normalization
)
assert log_likelihood == pytest.approx(fit.log_likelihood, 1e-4)
log_likelihood_with_regularization = ag.util.fit.log_likelihood_with_regularization_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
noise_normalization=noise_normalization,
)
assert log_likelihood_with_regularization == pytest.approx(
fit.log_likelihood_with_regularization, 1e-4
)
log_evidence = ag.util.fit.log_evidence_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
log_curvature_regularization_term=inversion.log_det_curvature_reg_matrix_term,
log_regularization_term=inversion.log_det_regularization_matrix_term,
noise_normalization=noise_normalization,
)
assert log_evidence == fit.log_evidence
assert log_evidence == fit.figure_of_merit
def test___fit_galaxy_model_image_dict__has_blurred_images_and_inversion_mapped_reconstructed_image(
self, masked_imaging_7x7
):
g0 = ag.Galaxy(
redshift=0.5, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
g1 = ag.Galaxy(
redshift=0.5, light_profile=ag.lp.EllipticalSersic(intensity=2.0)
)
g2 = ag.Galaxy(redshift=0.5)
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
galaxy_pix = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1, g2, galaxy_pix])
masked_imaging_7x7.image[0] = 3.0
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
g0_blurred_image = g0.blurred_image_from_grid_and_convolver(
grid=masked_imaging_7x7.grid,
convolver=masked_imaging_7x7.convolver,
blurring_grid=masked_imaging_7x7.blurring_grid,
)
g1_blurred_image = g1.blurred_image_from_grid_and_convolver(
grid=masked_imaging_7x7.grid,
convolver=masked_imaging_7x7.convolver,
blurring_grid=masked_imaging_7x7.blurring_grid,
)
blurred_image = g0_blurred_image + g1_blurred_image
profile_subtracted_image = masked_imaging_7x7.image - blurred_image
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_imaging_7x7.grid,
settings=ag.SettingsPixelization(use_border=False),
)
inversion = inversions.InversionImagingMatrix.from_data_mapper_and_regularization(
image=profile_subtracted_image,
noise_map=masked_imaging_7x7.noise_map,
convolver=masked_imaging_7x7.convolver,
mapper=mapper,
regularization=reg,
)
assert (fit.galaxy_model_image_dict[g2] == np.zeros(9)).all()
assert fit.galaxy_model_image_dict[g0].native == pytest.approx(
g0_blurred_image.native, 1.0e-4
)
assert fit.galaxy_model_image_dict[g1].native == pytest.approx(
g1_blurred_image.native, 1.0e-4
)
assert fit.galaxy_model_image_dict[galaxy_pix].native == pytest.approx(
inversion.mapped_reconstructed_image.native, 1.0e-4
)
assert fit.model_image.native == pytest.approx(
fit.galaxy_model_image_dict[g0].native
+ fit.galaxy_model_image_dict[g1].native
+ inversion.mapped_reconstructed_image.native,
1.0e-4,
)
def test___all_fit_quantities__include_hyper_methods(self, masked_imaging_7x7):
hyper_image_sky = ag.hyper_data.HyperImageSky(sky_scale=1.0)
hyper_background_noise = ag.hyper_data.HyperBackgroundNoise(noise_scale=1.0)
image = hyper_image_sky.hyper_image_from_image(
image=masked_imaging_7x7.image
)
hyper_noise_map_background = hyper_background_noise.hyper_noise_map_from_noise_map(
noise_map=masked_imaging_7x7.noise_map
)
galaxy_light = ag.Galaxy(
redshift=0.5,
light_profile=ag.lp.EllipticalSersic(intensity=1.0),
hyper_galaxy=ag.HyperGalaxy(
contribution_factor=1.0, noise_factor=1.0, noise_power=1.0
),
hyper_model_image=ag.Array2D.ones(
shape_native=(3, 3), pixel_scales=1.0
),
hyper_galaxy_image=ag.Array2D.ones(
shape_native=(3, 3), pixel_scales=1.0
),
hyper_minimum_value=0.0,
)
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
galaxy_pix = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[galaxy_light, galaxy_pix])
fit = ag.FitImaging(
masked_imaging=masked_imaging_7x7,
plane=plane,
hyper_image_sky=hyper_image_sky,
hyper_background_noise=hyper_background_noise,
)
hyper_noise = plane.hyper_noise_map_from_noise_map(
noise_map=masked_imaging_7x7.noise_map
)
hyper_noise_map = hyper_noise_map_background + hyper_noise
assert hyper_noise_map.native == pytest.approx(fit.noise_map.native, 1.0e-4)
blurred_image = plane.blurred_image_from_grid_and_convolver(
grid=masked_imaging_7x7.grid,
convolver=masked_imaging_7x7.convolver,
blurring_grid=masked_imaging_7x7.blurring_grid,
)
assert blurred_image.native == pytest.approx(fit.blurred_image.native)
profile_subtracted_image = image - blurred_image
assert profile_subtracted_image.native == pytest.approx(
fit.profile_subtracted_image.native
)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_imaging_7x7.grid,
settings=ag.SettingsPixelization(use_border=False),
)
inversion = inversions.InversionImagingMatrix.from_data_mapper_and_regularization(
image=profile_subtracted_image,
noise_map=hyper_noise_map,
convolver=masked_imaging_7x7.convolver,
mapper=mapper,
regularization=reg,
)
model_image = blurred_image + inversion.mapped_reconstructed_image
assert model_image.native == pytest.approx(fit.model_image.native, 1.0e-4)
residual_map = ag.util.fit.residual_map_from(
data=image, model_data=model_image
)
assert residual_map.native == pytest.approx(fit.residual_map.native, 1.0e-4)
normalized_residual_map = ag.util.fit.normalized_residual_map_from(
residual_map=residual_map, noise_map=hyper_noise_map
)
assert normalized_residual_map.native == pytest.approx(
fit.normalized_residual_map.native, 1.0e-4
)
chi_squared_map = ag.util.fit.chi_squared_map_from(
residual_map=residual_map, noise_map=hyper_noise_map
)
assert chi_squared_map.native == pytest.approx(
fit.chi_squared_map.native, 1.0e-4
)
chi_squared = ag.util.fit.chi_squared_from(chi_squared_map=chi_squared_map)
noise_normalization = ag.util.fit.noise_normalization_from(
noise_map=hyper_noise_map
)
log_likelihood = ag.util.fit.log_likelihood_from(
chi_squared=chi_squared, noise_normalization=noise_normalization
)
assert log_likelihood == pytest.approx(fit.log_likelihood, 1e-4)
log_likelihood_with_regularization = ag.util.fit.log_likelihood_with_regularization_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
noise_normalization=noise_normalization,
)
assert log_likelihood_with_regularization == pytest.approx(
fit.log_likelihood_with_regularization, 1e-4
)
log_evidence = ag.util.fit.log_evidence_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
log_curvature_regularization_term=inversion.log_det_curvature_reg_matrix_term,
log_regularization_term=inversion.log_det_regularization_matrix_term,
noise_normalization=noise_normalization,
)
assert log_evidence == fit.log_evidence
assert log_evidence == fit.figure_of_merit
def test___blurred_and_model_images_of_galaxies_and_unmasked_blurred_image_properties(
self, masked_imaging_7x7
):
galaxy_light = ag.Galaxy(
redshift=0.5, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
galaxy_pix = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[galaxy_light, galaxy_pix])
fit = ag.FitImaging(masked_imaging=masked_imaging_7x7, plane=plane)
blurred_image = plane.blurred_image_from_grid_and_convolver(
grid=masked_imaging_7x7.grid,
convolver=masked_imaging_7x7.convolver,
blurring_grid=masked_imaging_7x7.blurring_grid,
)
profile_subtracted_image = masked_imaging_7x7.image - blurred_image
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_imaging_7x7.grid,
settings=ag.SettingsPixelization(use_border=False),
)
inversion = inversions.InversionImagingMatrix.from_data_mapper_and_regularization(
image=profile_subtracted_image,
noise_map=masked_imaging_7x7.noise_map,
convolver=masked_imaging_7x7.convolver,
mapper=mapper,
regularization=reg,
)
assert blurred_image.native == pytest.approx(
fit.model_images_of_galaxies[0].native, 1.0e-4
)
assert inversion.mapped_reconstructed_image.native == pytest.approx(
fit.model_images_of_galaxies[1].native, 1.0e-4
)
class TestAttributes:
def test__subtracted_images_of_galaxies(self, masked_imaging_no_blur_7x7):
g0 = ag.Galaxy(redshift=0.5, light_profile=MockLightProfile(value=1.0))
g1 = ag.Galaxy(redshift=1.0, light_profile=MockLightProfile(value=2.0))
g2 = ag.Galaxy(redshift=1.0, light_profile=MockLightProfile(value=3.0))
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1, g2])
fit = ag.FitImaging(masked_imaging=masked_imaging_no_blur_7x7, plane=plane)
assert fit.subtracted_images_of_galaxies[0].slim[0] == -4.0
assert fit.subtracted_images_of_galaxies[1].slim[0] == -3.0
assert fit.subtracted_images_of_galaxies[2].slim[0] == -2.0
g0 = ag.Galaxy(redshift=0.5, light_profile=MockLightProfile(value=1.0))
g1 = ag.Galaxy(redshift=0.5)
g2 = ag.Galaxy(redshift=1.0, light_profile=MockLightProfile(value=3.0))
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1, g2])
fit = ag.FitImaging(masked_imaging=masked_imaging_no_blur_7x7, plane=plane)
assert fit.subtracted_images_of_galaxies[0].slim[0] == -2.0
assert fit.subtracted_images_of_galaxies[1].slim[0] == -3.0
assert fit.subtracted_images_of_galaxies[2].slim[0] == 0.0
class TestFitInterferometer:
class TestLikelihood:
def test__1x2_image__1x2_visibilities__simple_fourier_transform(self):
# The image plane image generated by the galaxy is [1.0, 1.0]
# Thus the chi squared is 4.0**2.0 + 3.0**2.0 = 25.0
interferometer = ag.Interferometer(
visibilities=ag.Visibilities.full(fill_value=5.0, shape_slim=(1,)),
noise_map=ag.Visibilities.ones(shape_slim=(1,)),
uv_wavelengths=np.array([[0.0, 0.0]]),
)
interferometer.visibilities[0] = 5.0 + 4.0j
visibilities_mask = np.full(fill_value=False, shape=(1,))
real_space_mask = ag.Mask2D.manual(
mask=[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
],
pixel_scales=1.0,
)
masked_interferometer = ag.MaskedInterferometer(
interferometer=interferometer,
visibilities_mask=visibilities_mask,
real_space_mask=real_space_mask,
settings=ag.SettingsMaskedInterferometer(
grid_class=ag.Grid2D,
sub_size=1,
transformer_class=ag.TransformerDFT,
),
)
# Setup as a ray trace instance, using a light profile for the galaxy
g0 = ag.Galaxy(
redshift=0.5, light_profile=MockLightProfile(value=1.0, size=2)
)
plane = ag.Plane(galaxies=[g0])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer, plane=plane
)
assert (fit.visibilities_mask == np.array([False])).all()
assert (fit.visibilities.slim == np.array([5.0 + 4.0j])).all()
assert (fit.noise_map.slim == np.array([1.0 + 1.0j])).all()
assert (fit.model_visibilities.slim == np.array([2.0 + 0.0j])).all()
assert (fit.residual_map.slim == np.array([3.0 + 4.0j])).all()
assert (fit.normalized_residual_map.slim == np.array([3.0 + 4.0j])).all()
assert (fit.chi_squared_map.slim == np.array([9.0 + 16.0j])).all()
assert fit.chi_squared == 25.0
assert fit.noise_normalization == (2.0 * np.log(2 * np.pi * 1.0 ** 2.0))
assert fit.log_likelihood == -0.5 * (
25.0 + 2.0 * np.log(2 * np.pi * 1.0 ** 2.0)
)
def test__hyper_background_changes_background_sky__reflected_in_likelihood(
self,
):
uv_wavelengths = np.array([[1.0, 0.0], [1.0, 1.0], [2.0, 2.0]])
interferometer = ag.Interferometer(
visibilities=ag.Visibilities.full(fill_value=5.0, shape_slim=(3,)),
noise_map=ag.Visibilities.full(fill_value=2.0, shape_slim=(3,)),
uv_wavelengths=uv_wavelengths,
)
visibilities_mask = np.full(fill_value=False, shape=(1,))
real_space_mask = ag.Mask2D.manual(
mask=[
[True, True, True, True, True],
[True, False, False, False, True],
[True, True, True, True, True],
],
pixel_scales=1.0,
)
masked_interferometer = ag.MaskedInterferometer(
interferometer=interferometer,
visibilities_mask=visibilities_mask,
real_space_mask=real_space_mask,
settings=ag.SettingsMaskedInterferometer(
grid_class=ag.Grid2D, sub_size=1
),
)
# Setup as a ray trace instance, using a light profile for the galaxy
g0 = ag.Galaxy(
redshift=0.5, light_profile=MockLightProfile(value=1.0, size=2)
)
plane = ag.Plane(galaxies=[g0])
hyper_background_noise = ag.hyper_data.HyperBackgroundNoise(noise_scale=1.0)
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer,
plane=plane,
hyper_background_noise=hyper_background_noise,
)
assert (
fit.visibilities.slim == np.array([5.0 + 5.0j, 5.0 + 5.0j, 5.0 + 5.0j])
).all()
assert (
fit.noise_map.slim == np.array([3.0 + 3.0j, 3.0 + 3.0j, 3.0 + 3.0j])
).all()
class TestCompareToManualProfilesOnly:
def test___all_fit_quantities__no_hyper_methods(self, masked_interferometer_7):
g0 = ag.Galaxy(
redshift=0.5,
light_profile=ag.lp.EllipticalSersic(intensity=1.0),
mass_profile=ag.mp.SphericalIsothermal(einstein_radius=1.0),
)
g1 = ag.Galaxy(
redshift=1.0, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7, plane=plane
)
assert masked_interferometer_7.noise_map == pytest.approx(fit.noise_map)
model_visibilities = plane.profile_visibilities_from_grid_and_transformer(
grid=masked_interferometer_7.grid,
transformer=masked_interferometer_7.transformer,
)
assert model_visibilities == pytest.approx(fit.model_visibilities, 1e-4)
residual_map = ag.util.fit.residual_map_from(
data=masked_interferometer_7.visibilities, model_data=model_visibilities
)
assert residual_map == pytest.approx(fit.residual_map, 1e-4)
normalized_residual_map = ag.util.fit.normalized_residual_map_complex_from(
residual_map=residual_map, noise_map=masked_interferometer_7.noise_map
)
assert normalized_residual_map == pytest.approx(
fit.normalized_residual_map, 1e-4
)
chi_squared_map = ag.util.fit.chi_squared_map_complex_from(
residual_map=residual_map, noise_map=masked_interferometer_7.noise_map
)
assert chi_squared_map == pytest.approx(fit.chi_squared_map, 1e-4)
chi_squared = ag.util.fit.chi_squared_complex_from(
chi_squared_map=fit.chi_squared_map
)
noise_normalization = ag.util.fit.noise_normalization_complex_from(
noise_map=masked_interferometer_7.noise_map
)
log_likelihood = ag.util.fit.log_likelihood_from(
chi_squared=chi_squared, noise_normalization=noise_normalization
)
assert log_likelihood == pytest.approx(fit.log_likelihood, 1e-4)
assert log_likelihood == fit.figure_of_merit
def test___fit_galaxy_model_image_dict__corresponds_to_profile_galaxy_images(
self, masked_interferometer_7
):
g0 = ag.Galaxy(
redshift=0.5,
light_profile=ag.lp.EllipticalSersic(intensity=1.0),
mass_profile=ag.mp.SphericalIsothermal(einstein_radius=1.0),
)
g1 = ag.Galaxy(
redshift=1.0, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7, plane=plane
)
g0_image = g0.image_from_grid(grid=masked_interferometer_7.grid)
g1_image = g1.image_from_grid(grid=masked_interferometer_7.grid)
assert fit.galaxy_model_image_dict[g0].slim == pytest.approx(
g0_image, 1.0e-4
)
assert fit.galaxy_model_image_dict[g1].slim == pytest.approx(
g1_image, 1.0e-4
)
def test___fit_galaxy_visibilities_dict__corresponds_to_galaxy_visibilities(
self, masked_interferometer_7
):
g0 = ag.Galaxy(
redshift=0.5,
light_profile=ag.lp.EllipticalSersic(intensity=1.0),
mass_profile=ag.mp.SphericalIsothermal(einstein_radius=1.0),
)
g1 = ag.Galaxy(
redshift=1.0, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7, plane=plane
)
g0_profile_visibilities = g0.profile_visibilities_from_grid_and_transformer(
grid=masked_interferometer_7.grid,
transformer=masked_interferometer_7.transformer,
)
g1_profile_visibilities = g1.profile_visibilities_from_grid_and_transformer(
grid=masked_interferometer_7.grid,
transformer=masked_interferometer_7.transformer,
)
assert fit.galaxy_model_visibilities_dict[g0].slim == pytest.approx(
g0_profile_visibilities, 1.0e-4
)
assert fit.galaxy_model_visibilities_dict[g1].slim == pytest.approx(
g1_profile_visibilities, 1.0e-4
)
assert fit.model_visibilities.slim == pytest.approx(
fit.galaxy_model_visibilities_dict[g0].slim
+ fit.galaxy_model_visibilities_dict[g1].slim,
1.0e-4,
)
def test___all_fit_quantities__hyper_background_noise(
self, masked_interferometer_7
):
hyper_background_noise = ag.hyper_data.HyperBackgroundNoise(noise_scale=1.0)
hyper_noise_map = hyper_background_noise.hyper_noise_map_from_complex_noise_map(
noise_map=masked_interferometer_7.noise_map
)
g0 = ag.Galaxy(
redshift=0.5,
light_profile=ag.lp.EllipticalSersic(intensity=1.0),
mass_profile=ag.mp.SphericalIsothermal(einstein_radius=1.0),
)
g1 = ag.Galaxy(
redshift=1.0, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7,
plane=plane,
hyper_background_noise=hyper_background_noise,
)
assert hyper_noise_map.slim == pytest.approx(fit.noise_map.slim)
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7,
plane=plane,
hyper_background_noise=hyper_background_noise,
use_hyper_scalings=False,
)
assert fit.noise_map == pytest.approx(
masked_interferometer_7.noise_map, 1.0e-4
)
assert fit.noise_map != pytest.approx(hyper_noise_map.slim, 1.0e-4)
class TestCompareToManualInversionOnly:
def test___all_fit_quantities__no_hyper_methods(self, masked_interferometer_7):
# Ensures the inversion grid is used, as this would cause the test to fail.
masked_interferometer_7.grid[0, 0] = -100.0
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=0.01)
g0 = ag.Galaxy(redshift=0.5, pixelization=pix, regularization=reg)
plane = ag.Plane(galaxies=[ag.Galaxy(redshift=0.5), g0])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7, plane=plane
)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_interferometer_7.grid_inversion, sparse_grid=None
)
inversion = inversions.InversionInterferometerMatrix.from_data_mapper_and_regularization(
mapper=mapper,
regularization=reg,
visibilities=masked_interferometer_7.visibilities,
noise_map=masked_interferometer_7.noise_map,
transformer=masked_interferometer_7.transformer,
)
assert inversion.mapped_reconstructed_visibilities == pytest.approx(
fit.model_visibilities, 1.0e-4
)
residual_map = ag.util.fit.residual_map_from(
data=masked_interferometer_7.visibilities,
model_data=inversion.mapped_reconstructed_visibilities,
)
assert residual_map.slim == pytest.approx(fit.residual_map.slim, 1.0e-4)
normalized_residual_map = ag.util.fit.normalized_residual_map_complex_from(
residual_map=residual_map, noise_map=masked_interferometer_7.noise_map
)
assert normalized_residual_map.slim == pytest.approx(
fit.normalized_residual_map.slim, 1.0e-4
)
chi_squared_map = ag.util.fit.chi_squared_map_complex_from(
residual_map=residual_map, noise_map=masked_interferometer_7.noise_map
)
assert chi_squared_map.slim == pytest.approx(
fit.chi_squared_map.slim, 1.0e-4
)
chi_squared = ag.util.fit.chi_squared_complex_from(
chi_squared_map=chi_squared_map
)
noise_normalization = ag.util.fit.noise_normalization_complex_from(
noise_map=masked_interferometer_7.noise_map
)
log_likelihood = ag.util.fit.log_likelihood_from(
chi_squared=chi_squared, noise_normalization=noise_normalization
)
assert log_likelihood == pytest.approx(fit.log_likelihood, 1e-4)
log_likelihood_with_regularization = ag.util.fit.log_likelihood_with_regularization_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
noise_normalization=noise_normalization,
)
assert log_likelihood_with_regularization == pytest.approx(
fit.log_likelihood_with_regularization, 1e-4
)
log_evidence = ag.util.fit.log_evidence_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
log_curvature_regularization_term=inversion.log_det_curvature_reg_matrix_term,
log_regularization_term=inversion.log_det_regularization_matrix_term,
noise_normalization=noise_normalization,
)
assert log_evidence == fit.log_evidence
assert log_evidence == fit.figure_of_merit
mapped_reconstructed_image = ag.util.inversion.mapped_reconstructed_data_from(
mapping_matrix=fit.inversion.mapper.mapping_matrix,
reconstruction=fit.inversion.reconstruction,
)
assert (
fit.inversion.mapped_reconstructed_image.slim
== mapped_reconstructed_image
).all()
def test___fit_galaxy_model_image_dict__images_and_inversion_mapped_reconstructed_image(
self, masked_interferometer_7
):
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
g0 = ag.Galaxy(redshift=0.5)
g1 = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7, plane=plane
)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_interferometer_7.grid, sparse_grid=None
)
inversion = inversions.InversionInterferometerMatrix.from_data_mapper_and_regularization(
mapper=mapper,
regularization=reg,
visibilities=masked_interferometer_7.visibilities,
noise_map=masked_interferometer_7.noise_map,
transformer=masked_interferometer_7.transformer,
)
assert (fit.galaxy_model_image_dict[g0].native == np.zeros((7, 7))).all()
assert fit.galaxy_model_image_dict[g1].slim == pytest.approx(
inversion.mapped_reconstructed_image.slim, 1.0e-4
)
def test___fit_galaxy_model_visibilities_dict__has_inversion_mapped_reconstructed_visibilities(
self, masked_interferometer_7
):
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
g0 = ag.Galaxy(redshift=0.5)
g1 = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7, plane=plane
)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_interferometer_7.grid, sparse_grid=None
)
inversion = inversions.InversionInterferometerMatrix.from_data_mapper_and_regularization(
mapper=mapper,
regularization=reg,
visibilities=masked_interferometer_7.visibilities,
noise_map=masked_interferometer_7.noise_map,
transformer=masked_interferometer_7.transformer,
)
assert (
fit.galaxy_model_visibilities_dict[g0] == 0.0 + 0.0j * np.zeros((7,))
).all()
assert fit.galaxy_model_visibilities_dict[g1].slim == pytest.approx(
inversion.mapped_reconstructed_visibilities.slim, 1.0e-4
)
assert fit.model_visibilities.slim == pytest.approx(
fit.galaxy_model_visibilities_dict[g1].slim, 1.0e-4
)
def test___all_fit_quantities__hyper_background_noise(
self, masked_interferometer_7
):
hyper_background_noise = ag.hyper_data.HyperBackgroundNoise(noise_scale=1.0)
hyper_noise_map = hyper_background_noise.hyper_noise_map_from_complex_noise_map(
noise_map=masked_interferometer_7.noise_map
)
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=0.01)
g0 = ag.Galaxy(redshift=0.5, pixelization=pix, regularization=reg)
plane = ag.Plane(galaxies=[ag.Galaxy(redshift=0.5), g0])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7,
plane=plane,
hyper_background_noise=hyper_background_noise,
)
assert hyper_noise_map.slim == pytest.approx(
fit.inversion.noise_map, 1.0e-4
)
assert hyper_noise_map.slim == pytest.approx(fit.noise_map.slim)
def test___all_fit_quantities__uses_linear_operator_inversion(
self, masked_interferometer_7_lop
):
# Ensures the inversion grid is used, as this would cause the test to fail.
masked_interferometer_7_lop.grid[0, 0] = -100.0
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=0.01)
g0 = ag.Galaxy(redshift=0.5, pixelization=pix, regularization=reg)
plane = ag.Plane(galaxies=[ag.Galaxy(redshift=0.5), g0])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7_lop,
plane=plane,
settings_inversion=ag.SettingsInversion(use_linear_operators=True),
)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_interferometer_7_lop.grid_inversion, sparse_grid=None
)
inversion = inversions.InversionInterferometerLinearOperator.from_data_mapper_and_regularization(
mapper=mapper,
regularization=reg,
visibilities=masked_interferometer_7_lop.visibilities,
noise_map=masked_interferometer_7_lop.noise_map,
transformer=masked_interferometer_7_lop.transformer,
settings=ag.SettingsInversion(use_linear_operators=True),
)
assert inversion.mapped_reconstructed_visibilities == pytest.approx(
fit.model_visibilities, 1.0e-4
)
residual_map = ag.util.fit.residual_map_from(
data=masked_interferometer_7_lop.visibilities,
model_data=inversion.mapped_reconstructed_visibilities,
)
assert residual_map.slim == pytest.approx(fit.residual_map.slim, 1.0e-4)
normalized_residual_map = ag.util.fit.normalized_residual_map_complex_from(
residual_map=residual_map,
noise_map=masked_interferometer_7_lop.noise_map,
)
assert normalized_residual_map.slim == pytest.approx(
fit.normalized_residual_map.slim, 1.0e-4
)
chi_squared_map = ag.util.fit.chi_squared_map_complex_from(
residual_map=residual_map,
noise_map=masked_interferometer_7_lop.noise_map,
)
assert chi_squared_map.slim == pytest.approx(
fit.chi_squared_map.slim, 1.0e-4
)
chi_squared = ag.util.fit.chi_squared_complex_from(
chi_squared_map=chi_squared_map
)
noise_normalization = ag.util.fit.noise_normalization_complex_from(
noise_map=masked_interferometer_7_lop.noise_map
)
log_likelihood = ag.util.fit.log_likelihood_from(
chi_squared=chi_squared, noise_normalization=noise_normalization
)
assert log_likelihood == pytest.approx(fit.log_likelihood, 1e-4)
log_likelihood_with_regularization = ag.util.fit.log_likelihood_with_regularization_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
noise_normalization=noise_normalization,
)
assert log_likelihood_with_regularization == pytest.approx(
fit.log_likelihood_with_regularization, 1e-4
)
log_evidence = ag.util.fit.log_evidence_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
log_curvature_regularization_term=inversion.log_det_curvature_reg_matrix_term,
log_regularization_term=inversion.log_det_regularization_matrix_term,
noise_normalization=noise_normalization,
)
assert log_evidence == fit.log_evidence
assert log_evidence == fit.figure_of_merit
mapped_reconstructed_image = ag.util.inversion.mapped_reconstructed_data_from(
mapping_matrix=fit.inversion.mapper.mapping_matrix,
reconstruction=fit.inversion.reconstruction,
)
assert (
fit.inversion.mapped_reconstructed_image.slim
== mapped_reconstructed_image
).all()
class TestCompareToManualProfilesAndInversion:
def test___all_fit_quantities__no_hyper_methods(self, masked_interferometer_7):
galaxy_light = ag.Galaxy(
redshift=0.5, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
galaxy_pix = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[galaxy_light, galaxy_pix])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7, plane=plane
)
profile_visibilities = plane.profile_visibilities_from_grid_and_transformer(
grid=masked_interferometer_7.grid,
transformer=masked_interferometer_7.transformer,
)
assert profile_visibilities.slim == pytest.approx(
fit.profile_visibilities.slim
)
profile_subtracted_visibilities = (
masked_interferometer_7.visibilities - profile_visibilities
)
assert profile_subtracted_visibilities.slim == pytest.approx(
fit.profile_subtracted_visibilities.slim
)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_interferometer_7.grid,
settings=ag.SettingsPixelization(use_border=False),
)
inversion = inversions.InversionInterferometerMatrix.from_data_mapper_and_regularization(
visibilities=profile_subtracted_visibilities,
noise_map=masked_interferometer_7.noise_map,
transformer=masked_interferometer_7.transformer,
mapper=mapper,
regularization=reg,
)
model_visibilities = (
profile_visibilities + inversion.mapped_reconstructed_visibilities
)
assert model_visibilities.slim == pytest.approx(fit.model_visibilities.slim)
residual_map = ag.util.fit.residual_map_from(
data=masked_interferometer_7.visibilities, model_data=model_visibilities
)
assert residual_map.slim == pytest.approx(fit.residual_map.slim)
normalized_residual_map = ag.util.fit.normalized_residual_map_complex_from(
residual_map=residual_map, noise_map=masked_interferometer_7.noise_map
)
assert normalized_residual_map.slim == pytest.approx(
fit.normalized_residual_map.slim
)
chi_squared_map = ag.util.fit.chi_squared_map_complex_from(
residual_map=residual_map, noise_map=masked_interferometer_7.noise_map
)
assert chi_squared_map.slim == pytest.approx(fit.chi_squared_map.slim)
chi_squared = ag.util.fit.chi_squared_complex_from(
chi_squared_map=chi_squared_map
)
noise_normalization = ag.util.fit.noise_normalization_complex_from(
noise_map=masked_interferometer_7.noise_map
)
log_likelihood = ag.util.fit.log_likelihood_from(
chi_squared=chi_squared, noise_normalization=noise_normalization
)
assert log_likelihood == pytest.approx(fit.log_likelihood, 1e-4)
log_likelihood_with_regularization = ag.util.fit.log_likelihood_with_regularization_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
noise_normalization=noise_normalization,
)
assert log_likelihood_with_regularization == pytest.approx(
fit.log_likelihood_with_regularization, 1e-4
)
log_evidence = ag.util.fit.log_evidence_from(
chi_squared=chi_squared,
regularization_term=inversion.regularization_term,
log_curvature_regularization_term=inversion.log_det_curvature_reg_matrix_term,
log_regularization_term=inversion.log_det_regularization_matrix_term,
noise_normalization=noise_normalization,
)
assert log_evidence == fit.log_evidence
assert log_evidence == fit.figure_of_merit
mapped_reconstructed_image = ag.util.inversion.mapped_reconstructed_data_from(
mapping_matrix=fit.inversion.mapper.mapping_matrix,
reconstruction=fit.inversion.reconstruction,
)
assert (
fit.inversion.mapped_reconstructed_image.slim
== mapped_reconstructed_image
).all()
def test___fit_galaxy_model_visibilities_dict__has_image_and_inversion_mapped_reconstructed_image(
self, masked_interferometer_7
):
g0 = ag.Galaxy(
redshift=0.5, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
g1 = ag.Galaxy(
redshift=0.5, light_profile=ag.lp.EllipticalSersic(intensity=2.0)
)
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
galaxy_pix = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1, galaxy_pix])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7, plane=plane
)
g0_visibilities = g0.profile_visibilities_from_grid_and_transformer(
grid=masked_interferometer_7.grid,
transformer=masked_interferometer_7.transformer,
)
g1_visibilities = g1.profile_visibilities_from_grid_and_transformer(
grid=masked_interferometer_7.grid,
transformer=masked_interferometer_7.transformer,
)
profile_visibilities = g0_visibilities + g1_visibilities
profile_subtracted_visibilities = (
masked_interferometer_7.visibilities - profile_visibilities
)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_interferometer_7.grid,
settings=ag.SettingsPixelization(use_border=False),
)
inversion = inversions.InversionInterferometerMatrix.from_data_mapper_and_regularization(
visibilities=profile_subtracted_visibilities,
noise_map=masked_interferometer_7.noise_map,
transformer=masked_interferometer_7.transformer,
mapper=mapper,
regularization=reg,
)
g0_image = g0.image_from_grid(grid=masked_interferometer_7.grid)
g1_image = g1.image_from_grid(grid=masked_interferometer_7.grid)
assert fit.galaxy_model_image_dict[g0].slim == pytest.approx(
g0_image.slim, 1.0e-4
)
assert fit.galaxy_model_image_dict[g1].slim == pytest.approx(
g1_image.slim, 1.0e-4
)
assert fit.galaxy_model_image_dict[galaxy_pix].slim == pytest.approx(
inversion.mapped_reconstructed_image.slim, 1.0e-4
)
def test___fit_galaxy_model_visibilities_dict__has_profile_visibilitiess_and_inversion_mapped_reconstructed_visibilities(
self, masked_interferometer_7
):
g0 = ag.Galaxy(
redshift=0.5, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
g1 = ag.Galaxy(
redshift=0.5, light_profile=ag.lp.EllipticalSersic(intensity=2.0)
)
g2 = ag.Galaxy(redshift=0.5)
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
galaxy_pix = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[g0, g1, g2, galaxy_pix])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7, plane=plane
)
g0_visibilities = g0.profile_visibilities_from_grid_and_transformer(
grid=masked_interferometer_7.grid,
transformer=masked_interferometer_7.transformer,
)
g1_visibilities = g1.profile_visibilities_from_grid_and_transformer(
grid=masked_interferometer_7.grid,
transformer=masked_interferometer_7.transformer,
)
profile_visibilities = g0_visibilities + g1_visibilities
profile_subtracted_visibilities = (
masked_interferometer_7.visibilities - profile_visibilities
)
mapper = pix.mapper_from_grid_and_sparse_grid(
grid=masked_interferometer_7.grid,
settings=ag.SettingsPixelization(use_border=False),
)
inversion = inversions.InversionInterferometerMatrix.from_data_mapper_and_regularization(
visibilities=profile_subtracted_visibilities,
noise_map=masked_interferometer_7.noise_map,
transformer=masked_interferometer_7.transformer,
mapper=mapper,
regularization=reg,
)
assert (
fit.galaxy_model_visibilities_dict[g2] == 0.0 + 0.0j * np.zeros((7,))
).all()
assert fit.galaxy_model_visibilities_dict[g0].slim == pytest.approx(
g0_visibilities.slim, 1.0e-4
)
assert fit.galaxy_model_visibilities_dict[g1].slim == pytest.approx(
g1_visibilities.slim, 1.0e-4
)
assert fit.galaxy_model_visibilities_dict[galaxy_pix].slim == pytest.approx(
inversion.mapped_reconstructed_visibilities.slim, 1.0e-4
)
assert fit.model_visibilities.slim == pytest.approx(
fit.galaxy_model_visibilities_dict[g0].slim
+ fit.galaxy_model_visibilities_dict[g1].slim
+ inversion.mapped_reconstructed_visibilities.slim,
1.0e-4,
)
def test___all_fit_quantities__hyper_background_noise(
self, masked_interferometer_7
):
hyper_background_noise = ag.hyper_data.HyperBackgroundNoise(noise_scale=1.0)
hyper_noise_map = hyper_background_noise.hyper_noise_map_from_complex_noise_map(
noise_map=masked_interferometer_7.noise_map
)
galaxy_light = ag.Galaxy(
redshift=0.5, light_profile=ag.lp.EllipticalSersic(intensity=1.0)
)
pix = ag.pix.Rectangular(shape=(3, 3))
reg = ag.reg.Constant(coefficient=1.0)
galaxy_pix = ag.Galaxy(redshift=1.0, pixelization=pix, regularization=reg)
plane = ag.Plane(redshift=0.75, galaxies=[galaxy_light, galaxy_pix])
fit = ag.FitInterferometer(
masked_interferometer=masked_interferometer_7,
plane=plane,
hyper_background_noise=hyper_background_noise,
)
assert hyper_noise_map.slim == pytest.approx(
fit.inversion.noise_map, 1.0e-4
)
assert hyper_noise_map.slim == pytest.approx(fit.noise_map.slim) | 0.799677 | 0.590484 |
import numpy as np
import networkx as nx
from networkx.utils import np_random_state
def _process_params(G, center):
if not isinstance(G, nx.Graph):
empty_graph = nx.Graph()
empty_graph.add_nodes_from(G)
G = empty_graph
center = np.zeros(2) if center is None else np.asarray(center)
return G, center
def spring_layout(
G,
k=None,
pos=None,
fixed=None,
iterations=50,
threshold=1e-4,
weight="weight",
scale=1,
center=None,
):
"""Position nodes using Fruchterman-Reingold force-directed algorithm.
The algorithm simulates a force-directed representation of the network
treating edges as springs holding nodes close, while treating nodes
as repelling objects, sometimes called an anti-gravity force.
Simulation continues until the positions are close to an equilibrium.
There are some hard-coded values: minimal distance between
nodes (0.01) and "temperature" of 0.1 to ensure nodes don't fly away.
During the simulation, `k` helps determine the distance between nodes,
though `scale` and `center` determine the size and place after
rescaling occurs at the end of the simulation.
Fixing some nodes doesn't allow them to move in the simulation.
It also turns off the rescaling feature at the simulation's end.
In addition, setting `scale` to `None` turns off rescaling.
Parameters
----------
G : NetworkX graph or list of nodes
A position will be assigned to every node in G.
k : float (default=None)
Optimal distance between nodes. If None the distance is set to
1/sqrt(n) where n is the number of nodes. Increase this value
to move nodes farther apart.
pos : dict or None optional (default=None)
Initial positions for nodes as a dictionary with node as keys
and values as a coordinate list or tuple. If None, then use
random initial positions.
fixed : list or None optional (default=None)
Nodes to keep fixed at initial position.
Nodes not in ``G.nodes`` are ignored.
ValueError raised if `fixed` specified and `pos` not.
iterations : int optional (default=50)
Maximum number of iterations taken
threshold: float optional (default = 1e-4)
Threshold for relative error in node position changes.
The iteration stops if the error is below this threshold.
weight : string or None optional (default='weight')
The edge attribute that holds the numerical value used for
the edge weight. Larger means a stronger attractive force.
If None, then all edge weights are 1.
scale : number or None (default: 1)
Scale factor for positions. Not used unless `fixed is None`.
If scale is None, no rescaling is performed.
center : array-like or None
Coordinate pair around which to center the layout.
Not used unless `fixed is None`.
Returns
-------
pos : dict
A dictionary of positions keyed by node
Examples
--------
>>> G = nx.path_graph(4)
>>> pos = nx.spring_layout(G)
# The same using longer but equivalent function name
>>> pos = nx.fruchterman_reingold_layout(G)
"""
G, center = _process_params(G, center)
if fixed is not None:
if pos is None:
raise ValueError("nodes are fixed without positions given")
for node in fixed:
if node not in pos:
raise ValueError("nodes are fixed without positions given")
nfixed = {node: i for i, node in enumerate(G)}
fixed = np.asarray([nfixed[node] for node in fixed if node in nfixed])
if pos is not None:
# Determine size of existing domain to adjust initial positions
dom_size = max(coord for pos_tup in pos.values() for coord in pos_tup)
if dom_size == 0:
dom_size = 1
pos_arr = seed.rand(len(G), 2) * dom_size + center
for i, n in enumerate(G):
if n in pos:
pos_arr[i] = np.asarray(pos[n])
else:
pos_arr = None
dom_size = 1
if len(G) == 0:
return {}
if len(G) == 1:
return {nx.utils.arbitrary_element(G.nodes()): center}
A = nx.to_numpy_array(G, weight=weight) # adjacency matrix, weighted if edges have 'weight' attribute
if k is None and fixed is not None:
# We must adjust k by domain size for layouts not near 1x1
nnodes, _ = A.shape
k = dom_size / np.sqrt(nnodes)
pos = _fruchterman_reingold(
A, k, pos_arr, fixed, iterations, threshold, 2, 4
)
if fixed is None and scale is not None:
pos = rescale_layout(pos, scale=scale) + center
pos = dict(zip(G, pos))
return pos
def rescale_layout(pos, scale=1):
"""Returns scaled position array to (-scale, scale) in all axes.
The function acts on NumPy arrays which hold position information.
Each position is one row of the array. The dimension of the space
equals the number of columns. Each coordinate in one column.
To rescale, the mean (center) is subtracted from each axis separately.
Then all values are scaled so that the largest magnitude value
from all axes equals `scale` (thus, the aspect ratio is preserved).
The resulting NumPy Array is returned (order of rows unchanged).
Parameters
----------
pos : numpy array
positions to be scaled. Each row is a position.
scale : number (default: 1)
The size of the resulting extent in all directions.
Returns
-------
pos : numpy array
scaled positions. Each row is a position.
See Also
--------
rescale_layout_dict
"""
# Find max length over all dimensions
lim = 0 # max coordinate for all axes
for i in range(pos.shape[1]):
pos[:, i] -= pos[:, i].mean()
lim = max(abs(pos[:, i]).max(), lim)
# rescale to (-scale, scale) in all directions, preserves aspect
if lim > 0:
for i in range(pos.shape[1]):
pos[:,i] *= scale / lim
return pos
# Position nodes in adjacency matrix A using Fruchterman-Reingold
# Entry point for NetworkX graph is fruchterman_reingold_layout()
@np_random_state(7)
def _fruchterman_reingold(
A, k=None, pos=None, fixed=None, iterations=50, threshold=1e-4, dim=2, seed=None
):
assert isinstance(A, np.ndarray), "fruchterman_reingold() takes an adjacency matrix as input"
nnodes, _ = A.shape
# random initial positions; make sure positions are of same type as matrix
pos = np.asarray(seed.rand(nnodes, dim), dtype=A.dtype) if pos is None else pos.astype(A.dtype)
# optimal distance between nodes
if k is None:
k = np.sqrt(1.0 / nnodes)
# the initial "temperature" is about .1 of domain area (=1x1) <=> the largest step allowed in the dynamics.
# This is needed in case the fixed positions force our domain to be much bigger than 1x1
t = max(max(pos.T[0]) - min(pos.T[0]), max(pos.T[1]) - min(pos.T[1])) * 0.1
# simple cooling scheme.
# linearly step down by dt on each iteration so last iteration is size dt.
dt = t / float(iterations + 1)
delta = np.zeros((pos.shape[0], pos.shape[0], pos.shape[1]), dtype=A.dtype)
for iteration in range(iterations):
# matrix of difference between points
delta = pos[:, np.newaxis, :] - pos[np.newaxis, :, :]
# distance between points
distance = np.linalg.norm(delta, axis=-1)
# enforce minimum distance of 0.01
np.clip(distance, 0.01, None, out=distance)
# displacement "force"
displacement = np.einsum(
"ijk,ij->ik", delta, (k * k / distance ** 2 - A * distance / k)
)
# update positions
length = np.linalg.norm(displacement, axis=-1)
length = np.where(length < 0.01, 0.1, length)
delta_pos = np.einsum("ij,i->ij", displacement, t / length)
if fixed is not None:
# don't change positions of fixed nodes
delta_pos[fixed] = 0.0
pos += delta_pos
# cool temperature
t -= dt
err = np.linalg.norm(delta_pos) / nnodes
if err < threshold:
break
return pos
class ForceLayout():
def __init__(self, graph, k = None, pos = None, fixed = None):
assert isinstance(graph, nx.classes.graph.Graph)
self.graph = graph
self.nv = graph.number_of_nodes()
self.fixed = fixed
## Adjacency matrix, positions, and difference, preallocated
self._A = nx.to_numpy_array(self.graph, weight='weight') # adjacency matrix
self._pos = np.asarray(np.random.uniform(size=(self.nv, 2)), dtype=self._A.dtype) if pos is None else pos.astype(self._A.dtype)
self._delta = np.zeros((self.nv, self.nv, 2), dtype=self._A.dtype)
# # optimal distance between nodes
self.k = np.sqrt(1.0 / self.nv) if k is None else k
# the initial "temperature" is about .1 of domain area (=1x1) <=> the largest step allowed in the dynamics.
# This is needed in case the fixed positions force our domain to be much bigger than 1x1
self.temp = max(max(self._pos.T[0]) - min(self._pos.T[0]), max(self._pos.T[1]) - min(self._pos.T[1])) * 0.1
# Linear cooling scheme -- decrease temp by dt on each iteration so last iteration is size dt.
self.dt = self.temp / float(250)
# Informational
self.error = np.inf
def step_force(self, n_iter: int = 1, threshold = "default"):
if self.temp < 1e-6 or isinstance(threshold, str) and self.error < 1e-6:
return(self._pos)
else:
for iteration in range(n_iter):
# matrix of difference between points
delta = self._pos[:, np.newaxis, :] - self._pos[np.newaxis, :, :] # n x n x d
# distance between points
distance = np.linalg.norm(delta, axis=-1) # n x n
np.clip(distance, 0.001, None, out=distance) # enforce minimum distance of 0.01
# displacement "force"
displacement = np.einsum(
"ijk,ij->ik", delta, (self.k * self.k / distance ** 2 - self._A * distance / self.k)
)
# update positions
length = np.linalg.norm(displacement, axis=-1)
length = np.where(length < 1.0, 0.5, length)
delta_pos = np.einsum("ij,i->ij", displacement, self.temp / length)
if self.fixed is not None:
delta_pos[self.fixed] = 0.0 # don't change positions of fixed nodes
self._pos += delta_pos
# cool temperature
self.temp -= self.dt
self.error = np.linalg.norm(delta_pos) / self.nv | fr_nx.py | import numpy as np
import networkx as nx
from networkx.utils import np_random_state
def _process_params(G, center):
if not isinstance(G, nx.Graph):
empty_graph = nx.Graph()
empty_graph.add_nodes_from(G)
G = empty_graph
center = np.zeros(2) if center is None else np.asarray(center)
return G, center
def spring_layout(
G,
k=None,
pos=None,
fixed=None,
iterations=50,
threshold=1e-4,
weight="weight",
scale=1,
center=None,
):
"""Position nodes using Fruchterman-Reingold force-directed algorithm.
The algorithm simulates a force-directed representation of the network
treating edges as springs holding nodes close, while treating nodes
as repelling objects, sometimes called an anti-gravity force.
Simulation continues until the positions are close to an equilibrium.
There are some hard-coded values: minimal distance between
nodes (0.01) and "temperature" of 0.1 to ensure nodes don't fly away.
During the simulation, `k` helps determine the distance between nodes,
though `scale` and `center` determine the size and place after
rescaling occurs at the end of the simulation.
Fixing some nodes doesn't allow them to move in the simulation.
It also turns off the rescaling feature at the simulation's end.
In addition, setting `scale` to `None` turns off rescaling.
Parameters
----------
G : NetworkX graph or list of nodes
A position will be assigned to every node in G.
k : float (default=None)
Optimal distance between nodes. If None the distance is set to
1/sqrt(n) where n is the number of nodes. Increase this value
to move nodes farther apart.
pos : dict or None optional (default=None)
Initial positions for nodes as a dictionary with node as keys
and values as a coordinate list or tuple. If None, then use
random initial positions.
fixed : list or None optional (default=None)
Nodes to keep fixed at initial position.
Nodes not in ``G.nodes`` are ignored.
ValueError raised if `fixed` specified and `pos` not.
iterations : int optional (default=50)
Maximum number of iterations taken
threshold: float optional (default = 1e-4)
Threshold for relative error in node position changes.
The iteration stops if the error is below this threshold.
weight : string or None optional (default='weight')
The edge attribute that holds the numerical value used for
the edge weight. Larger means a stronger attractive force.
If None, then all edge weights are 1.
scale : number or None (default: 1)
Scale factor for positions. Not used unless `fixed is None`.
If scale is None, no rescaling is performed.
center : array-like or None
Coordinate pair around which to center the layout.
Not used unless `fixed is None`.
Returns
-------
pos : dict
A dictionary of positions keyed by node
Examples
--------
>>> G = nx.path_graph(4)
>>> pos = nx.spring_layout(G)
# The same using longer but equivalent function name
>>> pos = nx.fruchterman_reingold_layout(G)
"""
G, center = _process_params(G, center)
if fixed is not None:
if pos is None:
raise ValueError("nodes are fixed without positions given")
for node in fixed:
if node not in pos:
raise ValueError("nodes are fixed without positions given")
nfixed = {node: i for i, node in enumerate(G)}
fixed = np.asarray([nfixed[node] for node in fixed if node in nfixed])
if pos is not None:
# Determine size of existing domain to adjust initial positions
dom_size = max(coord for pos_tup in pos.values() for coord in pos_tup)
if dom_size == 0:
dom_size = 1
pos_arr = seed.rand(len(G), 2) * dom_size + center
for i, n in enumerate(G):
if n in pos:
pos_arr[i] = np.asarray(pos[n])
else:
pos_arr = None
dom_size = 1
if len(G) == 0:
return {}
if len(G) == 1:
return {nx.utils.arbitrary_element(G.nodes()): center}
A = nx.to_numpy_array(G, weight=weight) # adjacency matrix, weighted if edges have 'weight' attribute
if k is None and fixed is not None:
# We must adjust k by domain size for layouts not near 1x1
nnodes, _ = A.shape
k = dom_size / np.sqrt(nnodes)
pos = _fruchterman_reingold(
A, k, pos_arr, fixed, iterations, threshold, 2, 4
)
if fixed is None and scale is not None:
pos = rescale_layout(pos, scale=scale) + center
pos = dict(zip(G, pos))
return pos
def rescale_layout(pos, scale=1):
"""Returns scaled position array to (-scale, scale) in all axes.
The function acts on NumPy arrays which hold position information.
Each position is one row of the array. The dimension of the space
equals the number of columns. Each coordinate in one column.
To rescale, the mean (center) is subtracted from each axis separately.
Then all values are scaled so that the largest magnitude value
from all axes equals `scale` (thus, the aspect ratio is preserved).
The resulting NumPy Array is returned (order of rows unchanged).
Parameters
----------
pos : numpy array
positions to be scaled. Each row is a position.
scale : number (default: 1)
The size of the resulting extent in all directions.
Returns
-------
pos : numpy array
scaled positions. Each row is a position.
See Also
--------
rescale_layout_dict
"""
# Find max length over all dimensions
lim = 0 # max coordinate for all axes
for i in range(pos.shape[1]):
pos[:, i] -= pos[:, i].mean()
lim = max(abs(pos[:, i]).max(), lim)
# rescale to (-scale, scale) in all directions, preserves aspect
if lim > 0:
for i in range(pos.shape[1]):
pos[:,i] *= scale / lim
return pos
# Position nodes in adjacency matrix A using Fruchterman-Reingold
# Entry point for NetworkX graph is fruchterman_reingold_layout()
@np_random_state(7)
def _fruchterman_reingold(
A, k=None, pos=None, fixed=None, iterations=50, threshold=1e-4, dim=2, seed=None
):
assert isinstance(A, np.ndarray), "fruchterman_reingold() takes an adjacency matrix as input"
nnodes, _ = A.shape
# random initial positions; make sure positions are of same type as matrix
pos = np.asarray(seed.rand(nnodes, dim), dtype=A.dtype) if pos is None else pos.astype(A.dtype)
# optimal distance between nodes
if k is None:
k = np.sqrt(1.0 / nnodes)
# the initial "temperature" is about .1 of domain area (=1x1) <=> the largest step allowed in the dynamics.
# This is needed in case the fixed positions force our domain to be much bigger than 1x1
t = max(max(pos.T[0]) - min(pos.T[0]), max(pos.T[1]) - min(pos.T[1])) * 0.1
# simple cooling scheme.
# linearly step down by dt on each iteration so last iteration is size dt.
dt = t / float(iterations + 1)
delta = np.zeros((pos.shape[0], pos.shape[0], pos.shape[1]), dtype=A.dtype)
for iteration in range(iterations):
# matrix of difference between points
delta = pos[:, np.newaxis, :] - pos[np.newaxis, :, :]
# distance between points
distance = np.linalg.norm(delta, axis=-1)
# enforce minimum distance of 0.01
np.clip(distance, 0.01, None, out=distance)
# displacement "force"
displacement = np.einsum(
"ijk,ij->ik", delta, (k * k / distance ** 2 - A * distance / k)
)
# update positions
length = np.linalg.norm(displacement, axis=-1)
length = np.where(length < 0.01, 0.1, length)
delta_pos = np.einsum("ij,i->ij", displacement, t / length)
if fixed is not None:
# don't change positions of fixed nodes
delta_pos[fixed] = 0.0
pos += delta_pos
# cool temperature
t -= dt
err = np.linalg.norm(delta_pos) / nnodes
if err < threshold:
break
return pos
class ForceLayout():
def __init__(self, graph, k = None, pos = None, fixed = None):
assert isinstance(graph, nx.classes.graph.Graph)
self.graph = graph
self.nv = graph.number_of_nodes()
self.fixed = fixed
## Adjacency matrix, positions, and difference, preallocated
self._A = nx.to_numpy_array(self.graph, weight='weight') # adjacency matrix
self._pos = np.asarray(np.random.uniform(size=(self.nv, 2)), dtype=self._A.dtype) if pos is None else pos.astype(self._A.dtype)
self._delta = np.zeros((self.nv, self.nv, 2), dtype=self._A.dtype)
# # optimal distance between nodes
self.k = np.sqrt(1.0 / self.nv) if k is None else k
# the initial "temperature" is about .1 of domain area (=1x1) <=> the largest step allowed in the dynamics.
# This is needed in case the fixed positions force our domain to be much bigger than 1x1
self.temp = max(max(self._pos.T[0]) - min(self._pos.T[0]), max(self._pos.T[1]) - min(self._pos.T[1])) * 0.1
# Linear cooling scheme -- decrease temp by dt on each iteration so last iteration is size dt.
self.dt = self.temp / float(250)
# Informational
self.error = np.inf
def step_force(self, n_iter: int = 1, threshold = "default"):
if self.temp < 1e-6 or isinstance(threshold, str) and self.error < 1e-6:
return(self._pos)
else:
for iteration in range(n_iter):
# matrix of difference between points
delta = self._pos[:, np.newaxis, :] - self._pos[np.newaxis, :, :] # n x n x d
# distance between points
distance = np.linalg.norm(delta, axis=-1) # n x n
np.clip(distance, 0.001, None, out=distance) # enforce minimum distance of 0.01
# displacement "force"
displacement = np.einsum(
"ijk,ij->ik", delta, (self.k * self.k / distance ** 2 - self._A * distance / self.k)
)
# update positions
length = np.linalg.norm(displacement, axis=-1)
length = np.where(length < 1.0, 0.5, length)
delta_pos = np.einsum("ij,i->ij", displacement, self.temp / length)
if self.fixed is not None:
delta_pos[self.fixed] = 0.0 # don't change positions of fixed nodes
self._pos += delta_pos
# cool temperature
self.temp -= self.dt
self.error = np.linalg.norm(delta_pos) / self.nv | 0.79542 | 0.676112 |
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union
from ... import _utilities, _tables
from . import outputs
__all__ = [
'GetVirtualMachineScaleSetResult',
'AwaitableGetVirtualMachineScaleSetResult',
'get_virtual_machine_scale_set',
]
@pulumi.output_type
class GetVirtualMachineScaleSetResult:
"""
Describes a Virtual Machine Scale Set.
"""
def __init__(__self__, identity=None, location=None, name=None, over_provision=None, provisioning_state=None, sku=None, tags=None, type=None, upgrade_policy=None, virtual_machine_profile=None):
if identity and not isinstance(identity, dict):
raise TypeError("Expected argument 'identity' to be a dict")
pulumi.set(__self__, "identity", identity)
if location and not isinstance(location, str):
raise TypeError("Expected argument 'location' to be a str")
pulumi.set(__self__, "location", location)
if name and not isinstance(name, str):
raise TypeError("Expected argument 'name' to be a str")
pulumi.set(__self__, "name", name)
if over_provision and not isinstance(over_provision, bool):
raise TypeError("Expected argument 'over_provision' to be a bool")
pulumi.set(__self__, "over_provision", over_provision)
if provisioning_state and not isinstance(provisioning_state, str):
raise TypeError("Expected argument 'provisioning_state' to be a str")
pulumi.set(__self__, "provisioning_state", provisioning_state)
if sku and not isinstance(sku, dict):
raise TypeError("Expected argument 'sku' to be a dict")
pulumi.set(__self__, "sku", sku)
if tags and not isinstance(tags, dict):
raise TypeError("Expected argument 'tags' to be a dict")
pulumi.set(__self__, "tags", tags)
if type and not isinstance(type, str):
raise TypeError("Expected argument 'type' to be a str")
pulumi.set(__self__, "type", type)
if upgrade_policy and not isinstance(upgrade_policy, dict):
raise TypeError("Expected argument 'upgrade_policy' to be a dict")
pulumi.set(__self__, "upgrade_policy", upgrade_policy)
if virtual_machine_profile and not isinstance(virtual_machine_profile, dict):
raise TypeError("Expected argument 'virtual_machine_profile' to be a dict")
pulumi.set(__self__, "virtual_machine_profile", virtual_machine_profile)
@property
@pulumi.getter
def identity(self) -> Optional['outputs.VirtualMachineScaleSetIdentityResponse']:
"""
The identity of the virtual machine scale set, if configured.
"""
return pulumi.get(self, "identity")
@property
@pulumi.getter
def location(self) -> str:
"""
Resource location
"""
return pulumi.get(self, "location")
@property
@pulumi.getter
def name(self) -> str:
"""
Resource name
"""
return pulumi.get(self, "name")
@property
@pulumi.getter(name="overProvision")
def over_provision(self) -> Optional[bool]:
"""
Specifies whether the Virtual Machine Scale Set should be overprovisioned.
"""
return pulumi.get(self, "over_provision")
@property
@pulumi.getter(name="provisioningState")
def provisioning_state(self) -> str:
"""
The provisioning state, which only appears in the response.
"""
return pulumi.get(self, "provisioning_state")
@property
@pulumi.getter
def sku(self) -> Optional['outputs.SkuResponse']:
"""
The virtual machine scale set sku.
"""
return pulumi.get(self, "sku")
@property
@pulumi.getter
def tags(self) -> Optional[Mapping[str, str]]:
"""
Resource tags
"""
return pulumi.get(self, "tags")
@property
@pulumi.getter
def type(self) -> str:
"""
Resource type
"""
return pulumi.get(self, "type")
@property
@pulumi.getter(name="upgradePolicy")
def upgrade_policy(self) -> Optional['outputs.UpgradePolicyResponse']:
"""
The upgrade policy.
"""
return pulumi.get(self, "upgrade_policy")
@property
@pulumi.getter(name="virtualMachineProfile")
def virtual_machine_profile(self) -> Optional['outputs.VirtualMachineScaleSetVMProfileResponse']:
"""
The virtual machine profile.
"""
return pulumi.get(self, "virtual_machine_profile")
class AwaitableGetVirtualMachineScaleSetResult(GetVirtualMachineScaleSetResult):
# pylint: disable=using-constant-test
def __await__(self):
if False:
yield self
return GetVirtualMachineScaleSetResult(
identity=self.identity,
location=self.location,
name=self.name,
over_provision=self.over_provision,
provisioning_state=self.provisioning_state,
sku=self.sku,
tags=self.tags,
type=self.type,
upgrade_policy=self.upgrade_policy,
virtual_machine_profile=self.virtual_machine_profile)
def get_virtual_machine_scale_set(resource_group_name: Optional[str] = None,
vm_scale_set_name: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetVirtualMachineScaleSetResult:
"""
Use this data source to access information about an existing resource.
:param str resource_group_name: The name of the resource group.
:param str vm_scale_set_name: The name of the VM scale set.
"""
__args__ = dict()
__args__['resourceGroupName'] = resource_group_name
__args__['vmScaleSetName'] = vm_scale_set_name
if opts is None:
opts = pulumi.InvokeOptions()
if opts.version is None:
opts.version = _utilities.get_version()
__ret__ = pulumi.runtime.invoke('azure-nextgen:compute/v20160330:getVirtualMachineScaleSet', __args__, opts=opts, typ=GetVirtualMachineScaleSetResult).value
return AwaitableGetVirtualMachineScaleSetResult(
identity=__ret__.identity,
location=__ret__.location,
name=__ret__.name,
over_provision=__ret__.over_provision,
provisioning_state=__ret__.provisioning_state,
sku=__ret__.sku,
tags=__ret__.tags,
type=__ret__.type,
upgrade_policy=__ret__.upgrade_policy,
virtual_machine_profile=__ret__.virtual_machine_profile) | sdk/python/pulumi_azure_nextgen/compute/v20160330/get_virtual_machine_scale_set.py |
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union
from ... import _utilities, _tables
from . import outputs
__all__ = [
'GetVirtualMachineScaleSetResult',
'AwaitableGetVirtualMachineScaleSetResult',
'get_virtual_machine_scale_set',
]
@pulumi.output_type
class GetVirtualMachineScaleSetResult:
"""
Describes a Virtual Machine Scale Set.
"""
def __init__(__self__, identity=None, location=None, name=None, over_provision=None, provisioning_state=None, sku=None, tags=None, type=None, upgrade_policy=None, virtual_machine_profile=None):
if identity and not isinstance(identity, dict):
raise TypeError("Expected argument 'identity' to be a dict")
pulumi.set(__self__, "identity", identity)
if location and not isinstance(location, str):
raise TypeError("Expected argument 'location' to be a str")
pulumi.set(__self__, "location", location)
if name and not isinstance(name, str):
raise TypeError("Expected argument 'name' to be a str")
pulumi.set(__self__, "name", name)
if over_provision and not isinstance(over_provision, bool):
raise TypeError("Expected argument 'over_provision' to be a bool")
pulumi.set(__self__, "over_provision", over_provision)
if provisioning_state and not isinstance(provisioning_state, str):
raise TypeError("Expected argument 'provisioning_state' to be a str")
pulumi.set(__self__, "provisioning_state", provisioning_state)
if sku and not isinstance(sku, dict):
raise TypeError("Expected argument 'sku' to be a dict")
pulumi.set(__self__, "sku", sku)
if tags and not isinstance(tags, dict):
raise TypeError("Expected argument 'tags' to be a dict")
pulumi.set(__self__, "tags", tags)
if type and not isinstance(type, str):
raise TypeError("Expected argument 'type' to be a str")
pulumi.set(__self__, "type", type)
if upgrade_policy and not isinstance(upgrade_policy, dict):
raise TypeError("Expected argument 'upgrade_policy' to be a dict")
pulumi.set(__self__, "upgrade_policy", upgrade_policy)
if virtual_machine_profile and not isinstance(virtual_machine_profile, dict):
raise TypeError("Expected argument 'virtual_machine_profile' to be a dict")
pulumi.set(__self__, "virtual_machine_profile", virtual_machine_profile)
@property
@pulumi.getter
def identity(self) -> Optional['outputs.VirtualMachineScaleSetIdentityResponse']:
"""
The identity of the virtual machine scale set, if configured.
"""
return pulumi.get(self, "identity")
@property
@pulumi.getter
def location(self) -> str:
"""
Resource location
"""
return pulumi.get(self, "location")
@property
@pulumi.getter
def name(self) -> str:
"""
Resource name
"""
return pulumi.get(self, "name")
@property
@pulumi.getter(name="overProvision")
def over_provision(self) -> Optional[bool]:
"""
Specifies whether the Virtual Machine Scale Set should be overprovisioned.
"""
return pulumi.get(self, "over_provision")
@property
@pulumi.getter(name="provisioningState")
def provisioning_state(self) -> str:
"""
The provisioning state, which only appears in the response.
"""
return pulumi.get(self, "provisioning_state")
@property
@pulumi.getter
def sku(self) -> Optional['outputs.SkuResponse']:
"""
The virtual machine scale set sku.
"""
return pulumi.get(self, "sku")
@property
@pulumi.getter
def tags(self) -> Optional[Mapping[str, str]]:
"""
Resource tags
"""
return pulumi.get(self, "tags")
@property
@pulumi.getter
def type(self) -> str:
"""
Resource type
"""
return pulumi.get(self, "type")
@property
@pulumi.getter(name="upgradePolicy")
def upgrade_policy(self) -> Optional['outputs.UpgradePolicyResponse']:
"""
The upgrade policy.
"""
return pulumi.get(self, "upgrade_policy")
@property
@pulumi.getter(name="virtualMachineProfile")
def virtual_machine_profile(self) -> Optional['outputs.VirtualMachineScaleSetVMProfileResponse']:
"""
The virtual machine profile.
"""
return pulumi.get(self, "virtual_machine_profile")
class AwaitableGetVirtualMachineScaleSetResult(GetVirtualMachineScaleSetResult):
# pylint: disable=using-constant-test
def __await__(self):
if False:
yield self
return GetVirtualMachineScaleSetResult(
identity=self.identity,
location=self.location,
name=self.name,
over_provision=self.over_provision,
provisioning_state=self.provisioning_state,
sku=self.sku,
tags=self.tags,
type=self.type,
upgrade_policy=self.upgrade_policy,
virtual_machine_profile=self.virtual_machine_profile)
def get_virtual_machine_scale_set(resource_group_name: Optional[str] = None,
vm_scale_set_name: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetVirtualMachineScaleSetResult:
"""
Use this data source to access information about an existing resource.
:param str resource_group_name: The name of the resource group.
:param str vm_scale_set_name: The name of the VM scale set.
"""
__args__ = dict()
__args__['resourceGroupName'] = resource_group_name
__args__['vmScaleSetName'] = vm_scale_set_name
if opts is None:
opts = pulumi.InvokeOptions()
if opts.version is None:
opts.version = _utilities.get_version()
__ret__ = pulumi.runtime.invoke('azure-nextgen:compute/v20160330:getVirtualMachineScaleSet', __args__, opts=opts, typ=GetVirtualMachineScaleSetResult).value
return AwaitableGetVirtualMachineScaleSetResult(
identity=__ret__.identity,
location=__ret__.location,
name=__ret__.name,
over_provision=__ret__.over_provision,
provisioning_state=__ret__.provisioning_state,
sku=__ret__.sku,
tags=__ret__.tags,
type=__ret__.type,
upgrade_policy=__ret__.upgrade_policy,
virtual_machine_profile=__ret__.virtual_machine_profile) | 0.833155 | 0.074467 |
from tkinter import ttk
from tkinter import filedialog
from tkinter import messagebox
import tkinter as tk
from main import main, conversion
import math
import sys
from onefile import *
import os
print (os.getcwd())
def center_window(win, width=300, height=200):
# get screen width and height
screen_width = root.winfo_screenwidth()
screen_height = root.winfo_screenheight()
# calculate position x and y coordinates
x = (screen_width/2) - (width/2)
y = (screen_height/2) - (height/2)
win.geometry('%dx%d+%d+%d' % (width, height, x, y))
def selectRes():
root.withdraw()
def convertionStart():
res_win.withdraw()
conversion(res_r.get())
root.deiconify()
center_window(root, 270, 120)
messagebox.showinfo(title='success', message='Conversion is Done!')
def selectPack():
global pack
pack = filedialog.askopenfilename(initialdir = "./",title = "Select Pack",filetypes = (("resource pack","*.zip"),("all files","*.*")))
if(pack):
root.withdraw()
convert = main(pack[:-4])
if(convert == -1):
print ("this pack is already compatible with 1.13")
root.deiconify()
center_window(root, 270, 120)
messagebox.showwarning(title='warning', message="This pack is already compatible with 1.13, please select other!")
elif(convert == 0):
print ("please set it manually")
res_win.deiconify()
center_window(res_win, 270, 80)
messagebox.showwarning(title='warning', message="Fail to detect the pack's resolution, please set it manually!")
else:
print ("next one?")
root.deiconify()
center_window(root, 270, 120)
messagebox.showinfo(title='success', message='Conversion is Done!')
return False
else:
print ('select pack to start conversion')
def show_values(value=None):
slider_label['text'] = text='resolution: '+ str(int(16 * math.pow(2, res_r.get()-1))) + 'X'
#print (res_r.get())
root = tk.Tk()
root.title("Resource Pack Converter")
#root.geometry('500x300+500+200')
root.iconbitmap(resource_path('favicon.ico'))
root.resizable(width=False, height=False)
center_window(root, 270, 120)
btn_select = tk.Button(
root,
text='Select Pack',
width=50,
height=50,
command=selectPack
)
btn_select.pack()
res_win = tk.Toplevel(root)
res_win.title("Set Resolution")
res_win.iconbitmap(resource_path('favicon.ico'))
res_win.resizable(width=False, height=False)
center_window(res_win, 270, 80)
''' resolution ratio set'''
res_r = tk.IntVar()
res_r.set(1)
slider_res = tk.PanedWindow(res_win)
slider_res.pack(fill = tk.BOTH, expand = 1)
slider_label = tk.Label(res_win, text='resolution: 16X')
slider_scale = tk.Scale(
res_win,
from_=0,
to=6,
orient=tk.HORIZONTAL,
variable = res_r,
command=show_values
)
slider_res.add(slider_label)
slider_res.add(slider_scale)
btn_start = tk.Button(
res_win,
text='Confirm',
width=60,
command=convertionStart
)
btn_start.pack()
res_win.withdraw()
root.mainloop() | src/convert_tool.py | from tkinter import ttk
from tkinter import filedialog
from tkinter import messagebox
import tkinter as tk
from main import main, conversion
import math
import sys
from onefile import *
import os
print (os.getcwd())
def center_window(win, width=300, height=200):
# get screen width and height
screen_width = root.winfo_screenwidth()
screen_height = root.winfo_screenheight()
# calculate position x and y coordinates
x = (screen_width/2) - (width/2)
y = (screen_height/2) - (height/2)
win.geometry('%dx%d+%d+%d' % (width, height, x, y))
def selectRes():
root.withdraw()
def convertionStart():
res_win.withdraw()
conversion(res_r.get())
root.deiconify()
center_window(root, 270, 120)
messagebox.showinfo(title='success', message='Conversion is Done!')
def selectPack():
global pack
pack = filedialog.askopenfilename(initialdir = "./",title = "Select Pack",filetypes = (("resource pack","*.zip"),("all files","*.*")))
if(pack):
root.withdraw()
convert = main(pack[:-4])
if(convert == -1):
print ("this pack is already compatible with 1.13")
root.deiconify()
center_window(root, 270, 120)
messagebox.showwarning(title='warning', message="This pack is already compatible with 1.13, please select other!")
elif(convert == 0):
print ("please set it manually")
res_win.deiconify()
center_window(res_win, 270, 80)
messagebox.showwarning(title='warning', message="Fail to detect the pack's resolution, please set it manually!")
else:
print ("next one?")
root.deiconify()
center_window(root, 270, 120)
messagebox.showinfo(title='success', message='Conversion is Done!')
return False
else:
print ('select pack to start conversion')
def show_values(value=None):
slider_label['text'] = text='resolution: '+ str(int(16 * math.pow(2, res_r.get()-1))) + 'X'
#print (res_r.get())
root = tk.Tk()
root.title("Resource Pack Converter")
#root.geometry('500x300+500+200')
root.iconbitmap(resource_path('favicon.ico'))
root.resizable(width=False, height=False)
center_window(root, 270, 120)
btn_select = tk.Button(
root,
text='Select Pack',
width=50,
height=50,
command=selectPack
)
btn_select.pack()
res_win = tk.Toplevel(root)
res_win.title("Set Resolution")
res_win.iconbitmap(resource_path('favicon.ico'))
res_win.resizable(width=False, height=False)
center_window(res_win, 270, 80)
''' resolution ratio set'''
res_r = tk.IntVar()
res_r.set(1)
slider_res = tk.PanedWindow(res_win)
slider_res.pack(fill = tk.BOTH, expand = 1)
slider_label = tk.Label(res_win, text='resolution: 16X')
slider_scale = tk.Scale(
res_win,
from_=0,
to=6,
orient=tk.HORIZONTAL,
variable = res_r,
command=show_values
)
slider_res.add(slider_label)
slider_res.add(slider_scale)
btn_start = tk.Button(
res_win,
text='Confirm',
width=60,
command=convertionStart
)
btn_start.pack()
res_win.withdraw()
root.mainloop() | 0.181118 | 0.088978 |
import logging
from base64 import b64decode
from pyramid.view import view_config
from pyramid.security import NO_PERMISSION_REQUIRED
from pyramid.security import authenticated_userid
from pyramid.security import Authenticated
from pyramid.httpexceptions import HTTPFound
from six.moves.urllib.parse import urlparse
from six.moves.urllib.parse import parse_qsl
from six.moves.urllib.parse import ParseResult
from six.moves.urllib.parse import urlencode
from cryptography.hazmat.primitives.kdf.scrypt import Scrypt
from cryptography.exceptions import InvalidKey
from .models import DBSession as db
from .models import Oauth2Token
from .models import Oauth2Code
from .models import Oauth2RedirectUri
from .models import Oauth2Client
from .models import backend
from .errors import InvalidToken
from .errors import InvalidClient
from .errors import InvalidRequest
from .errors import UnsupportedGrantType
from .util import oauth2_settings
from .util import getClientCredentials
from .interfaces import IAuthCheck
from .jsonerrors import HTTPBadRequest
from .jsonerrors import HTTPUnauthorized
from .jsonerrors import HTTPMethodNotAllowed
def require_https(handler):
"""
This check should be taken care of via the authorization policy, but in
case someone has configured a different policy, check again. HTTPS is
required for all Oauth2 authenticated requests to ensure the security of
client credentials and authorization tokens.
"""
def wrapped(request):
if (request.scheme != 'https' and
oauth2_settings('require_ssl', default=True)):
log.info('rejected request due to unsupported scheme: %s'
% request.scheme)
return HTTPBadRequest(InvalidRequest(
error_description='Oauth2 requires all requests'
' to be made via HTTPS.'))
return handler(request)
return wrapped
log = logging.getLogger('pyramid_oauth2_provider.views')
@view_config(route_name='oauth2_provider_authorize', renderer='json',
permission=Authenticated)
@require_https
def oauth2_authorize(request):
"""
* In the case of a 'code' authorize request a GET or POST is made
with the following structure.
GET /authorize?response_type=code&client_id=aoiuer HTTP/1.1
Host: server.example.com
POST /authorize HTTP/1.1
Host: server.example.com
Content-Type: application/x-www-form-urlencoded
response_type=code&client_id=aoiuer
The response_type and client_id are required parameters. A redirect_uri
and state parameters may also be supplied. The redirect_uri will be
validated against the URI's registered for the client. The state is an
opaque value that is simply passed through for security on the client's
end.
The response to a 'code' request will be a redirect to a registered URI
with the authorization code and optional state values as query
parameters.
HTTP/1.1 302 Found
Location: https://client.example.com/cb?code=AverTaer&state=efg
"""
request.client_id = request.params.get('client_id')
client = db.query(Oauth2Client).filter_by(
client_id=request.client_id).first()
if not client:
log.info('received invalid client credentials')
return HTTPBadRequest(InvalidRequest(
error_description='Invalid client credentials'))
redirect_uri = request.params.get('redirect_uri')
redirection_uri = None
if len(client.redirect_uris) == 1 and (
not redirect_uri or redirect_uri == client.redirect_uris[0]):
redirection_uri = client.redirect_uris[0]
elif len(client.redirect_uris) > 0:
redirection_uri = db.query(Oauth2RedirectUri)\
.filter_by(client_id=client.id, uri=redirect_uri).first()
if redirection_uri is None:
return HTTPBadRequest(InvalidRequest(
error_description='Redirection URI validation failed'))
resp = None
response_type = request.params.get('response_type')
state = request.params.get('state')
if 'code' == response_type:
resp = handle_authcode(request, client, redirection_uri, state)
elif 'token' == response_type:
resp = handle_implicit(request, client, redirection_uri, state)
else:
log.info('received invalid response_type %s')
resp = HTTPBadRequest(InvalidRequest(error_description='Oauth2 unknown '
'response_type not supported'))
return resp
def handle_authcode(request, client, redirection_uri, state=None):
parts = urlparse(redirection_uri.uri)
qparams = dict(parse_qsl(parts.query))
user_id = authenticated_userid(request)
auth_code = Oauth2Code(client, user_id)
db.add(auth_code)
db.flush()
qparams['code'] = auth_code.authcode
if state:
qparams['state'] = state
parts = ParseResult(
parts.scheme, parts.netloc, parts.path, parts.params,
urlencode(qparams), '')
return HTTPFound(location=parts.geturl())
def handle_implicit(request, client, redirection_uri, state=None):
return HTTPBadRequest(InvalidRequest(error_description='Oauth2 '
'response_type "implicit" not supported'))
@view_config(route_name='oauth2_provider_token', renderer='json',
permission=NO_PERMISSION_REQUIRED)
@require_https
def oauth2_token(request):
"""
* In the case of an incoming authentication request a POST is made
with the following structure.
POST /token HTTP/1.1
Host: server.example.com
Authorization: Basic czZCaGRSa3F0MzpnWDFmQmF0M2JW
Content-Type: application/x-www-form-urlencoded
grant_type=password&username=johndoe&password=<PASSWORD>
The basic auth header contains the client_id:client_secret base64
encoded for client authentication.
The username and password are form encoded as part of the body. This
request *must* be made over https.
The response to this request will be, assuming no error:
HTTP/1.1 200 OK
Content-Type: application/json;charset=UTF-8
Cache-Control: no-store
Pragma: no-cache
{
"access_token":"<KEY>",
"token_type":"bearer",
"expires_in":3600,
"refresh_token":"tGzv3JOkF0XG5Qx2TlKW",
"user_id":1234,
}
* In the case of a token refresh request a POST with the following
structure is required:
POST /token HTTP/1.1
Host: server.example.com
Authorization: Basic czZCaGRSa3F0MzpnWDFmQmF0M2JW
Content-Type: application/x-www-form-urlencoded
grant_type=refresh_token&refresh_token=tGzv3JOkF0XG5Qx2TlKW&user_id=1234
The response will be the same as above with a new access_token and
refresh_token.
"""
# Make sure this is a POST.
if request.method != 'POST':
log.info('rejected request due to invalid method: %s' % request.method)
return HTTPMethodNotAllowed(
'This endpoint only supports the POST method.')
getClientCredentials(request)
# Make sure we got a client_id and secret through the authorization
# policy. Note that you should only get here if not using the Oauth2
# authorization policy or access was granted through the AuthTKt policy.
if (not hasattr(request, 'client_id') or
not hasattr(request, 'client_secret')):
log.info('did not receive client credentials')
return HTTPUnauthorized('Invalid client credentials')
client = db.query(Oauth2Client).filter_by(
client_id=request.client_id).first()
# Again, the authorization policy should catch this, but check again.
if not oauth2_settings('salt'):
raise ValueError('oauth2_provider.salt configuration required.')
salt = b64decode(oauth2_settings('salt').encode('utf-8'))
kdf = Scrypt(
salt=salt,
length=64,
n=2 ** 14,
r=8,
p=1,
backend=backend
)
try:
client_secret = request.client_secret
try:
client_secret = bytes(client_secret, 'utf-8')
except TypeError:
client_secret = client_secret.encode('utf-8')
kdf.verify(client_secret, client.client_secret)
bad_secret = False
except (AttributeError, InvalidKey):
bad_secret = True
if not client or bad_secret:
log.info('received invalid client credentials')
return HTTPBadRequest(InvalidRequest(
error_description='Invalid client credentials'))
# Check for supported grant type. This is a required field of the form
# submission.
resp = None
grant_type = request.POST.get('grant_type')
if grant_type == 'password':
resp = handle_password(request, client)
elif grant_type == 'refresh_token':
resp = handle_refresh_token(request, client)
else:
log.info('invalid grant type: %s' % grant_type)
return HTTPBadRequest(UnsupportedGrantType(error_description='Only '
'password and refresh_token grant types are supported by this '
'authentication server'))
add_cache_headers(request)
return resp
def handle_password(request, client):
if 'username' not in request.POST or 'password' not in request.POST:
log.info('missing username or password')
return HTTPBadRequest(InvalidRequest(error_description='Both username '
'and password are required to obtain a password based grant.'))
auth_check = request.registry.queryUtility(IAuthCheck)
user_id = auth_check().checkauth(request.POST.get('username'),
request.POST.get('password'))
if not user_id:
log.info('could not validate user credentials')
return HTTPUnauthorized(InvalidClient(error_description='Username and '
'password are invalid.'))
auth_token = Oauth2Token(client, user_id)
db.add(auth_token)
db.flush()
return auth_token.asJSON(token_type='bearer')
def handle_refresh_token(request, client):
if 'refresh_token' not in request.POST:
log.info('refresh_token field missing')
return HTTPBadRequest(InvalidRequest(error_description='refresh_token '
'field required'))
if 'user_id' not in request.POST:
log.info('user_id field missing')
return HTTPBadRequest(InvalidRequest(error_description='user_id '
'field required'))
auth_token = db.query(Oauth2Token).filter_by(
refresh_token=request.POST.get('refresh_token')).first()
if not auth_token:
log.info('invalid refresh_token')
return HTTPUnauthorized(InvalidToken(error_description='Provided '
'refresh_token is not valid.'))
if auth_token.client.client_id != client.client_id:
log.info('invalid client_id')
return HTTPBadRequest(InvalidClient(error_description='Client does '
'not own this refresh_token.'))
if str(auth_token.user_id) != request.POST.get('user_id'):
log.info('invalid user_id')
return HTTPBadRequest(InvalidClient(error_description='The given '
'user_id does not match the given refresh_token.'))
new_token = auth_token.refresh()
db.add(new_token)
db.flush()
return new_token.asJSON(token_type='bearer')
def add_cache_headers(request):
"""
The Oauth2 draft spec requires that all token endpoint traffic be marked
as uncacheable.
"""
resp = request.response
resp.headerlist.append(('Cache-Control', 'no-store'))
resp.headerlist.append(('Pragma', 'no-cache'))
return request | pyramid_oauth2_provider/views.py |
import logging
from base64 import b64decode
from pyramid.view import view_config
from pyramid.security import NO_PERMISSION_REQUIRED
from pyramid.security import authenticated_userid
from pyramid.security import Authenticated
from pyramid.httpexceptions import HTTPFound
from six.moves.urllib.parse import urlparse
from six.moves.urllib.parse import parse_qsl
from six.moves.urllib.parse import ParseResult
from six.moves.urllib.parse import urlencode
from cryptography.hazmat.primitives.kdf.scrypt import Scrypt
from cryptography.exceptions import InvalidKey
from .models import DBSession as db
from .models import Oauth2Token
from .models import Oauth2Code
from .models import Oauth2RedirectUri
from .models import Oauth2Client
from .models import backend
from .errors import InvalidToken
from .errors import InvalidClient
from .errors import InvalidRequest
from .errors import UnsupportedGrantType
from .util import oauth2_settings
from .util import getClientCredentials
from .interfaces import IAuthCheck
from .jsonerrors import HTTPBadRequest
from .jsonerrors import HTTPUnauthorized
from .jsonerrors import HTTPMethodNotAllowed
def require_https(handler):
"""
This check should be taken care of via the authorization policy, but in
case someone has configured a different policy, check again. HTTPS is
required for all Oauth2 authenticated requests to ensure the security of
client credentials and authorization tokens.
"""
def wrapped(request):
if (request.scheme != 'https' and
oauth2_settings('require_ssl', default=True)):
log.info('rejected request due to unsupported scheme: %s'
% request.scheme)
return HTTPBadRequest(InvalidRequest(
error_description='Oauth2 requires all requests'
' to be made via HTTPS.'))
return handler(request)
return wrapped
log = logging.getLogger('pyramid_oauth2_provider.views')
@view_config(route_name='oauth2_provider_authorize', renderer='json',
permission=Authenticated)
@require_https
def oauth2_authorize(request):
"""
* In the case of a 'code' authorize request a GET or POST is made
with the following structure.
GET /authorize?response_type=code&client_id=aoiuer HTTP/1.1
Host: server.example.com
POST /authorize HTTP/1.1
Host: server.example.com
Content-Type: application/x-www-form-urlencoded
response_type=code&client_id=aoiuer
The response_type and client_id are required parameters. A redirect_uri
and state parameters may also be supplied. The redirect_uri will be
validated against the URI's registered for the client. The state is an
opaque value that is simply passed through for security on the client's
end.
The response to a 'code' request will be a redirect to a registered URI
with the authorization code and optional state values as query
parameters.
HTTP/1.1 302 Found
Location: https://client.example.com/cb?code=AverTaer&state=efg
"""
request.client_id = request.params.get('client_id')
client = db.query(Oauth2Client).filter_by(
client_id=request.client_id).first()
if not client:
log.info('received invalid client credentials')
return HTTPBadRequest(InvalidRequest(
error_description='Invalid client credentials'))
redirect_uri = request.params.get('redirect_uri')
redirection_uri = None
if len(client.redirect_uris) == 1 and (
not redirect_uri or redirect_uri == client.redirect_uris[0]):
redirection_uri = client.redirect_uris[0]
elif len(client.redirect_uris) > 0:
redirection_uri = db.query(Oauth2RedirectUri)\
.filter_by(client_id=client.id, uri=redirect_uri).first()
if redirection_uri is None:
return HTTPBadRequest(InvalidRequest(
error_description='Redirection URI validation failed'))
resp = None
response_type = request.params.get('response_type')
state = request.params.get('state')
if 'code' == response_type:
resp = handle_authcode(request, client, redirection_uri, state)
elif 'token' == response_type:
resp = handle_implicit(request, client, redirection_uri, state)
else:
log.info('received invalid response_type %s')
resp = HTTPBadRequest(InvalidRequest(error_description='Oauth2 unknown '
'response_type not supported'))
return resp
def handle_authcode(request, client, redirection_uri, state=None):
parts = urlparse(redirection_uri.uri)
qparams = dict(parse_qsl(parts.query))
user_id = authenticated_userid(request)
auth_code = Oauth2Code(client, user_id)
db.add(auth_code)
db.flush()
qparams['code'] = auth_code.authcode
if state:
qparams['state'] = state
parts = ParseResult(
parts.scheme, parts.netloc, parts.path, parts.params,
urlencode(qparams), '')
return HTTPFound(location=parts.geturl())
def handle_implicit(request, client, redirection_uri, state=None):
return HTTPBadRequest(InvalidRequest(error_description='Oauth2 '
'response_type "implicit" not supported'))
@view_config(route_name='oauth2_provider_token', renderer='json',
permission=NO_PERMISSION_REQUIRED)
@require_https
def oauth2_token(request):
"""
* In the case of an incoming authentication request a POST is made
with the following structure.
POST /token HTTP/1.1
Host: server.example.com
Authorization: Basic czZCaGRSa3F0MzpnWDFmQmF0M2JW
Content-Type: application/x-www-form-urlencoded
grant_type=password&username=johndoe&password=<PASSWORD>
The basic auth header contains the client_id:client_secret base64
encoded for client authentication.
The username and password are form encoded as part of the body. This
request *must* be made over https.
The response to this request will be, assuming no error:
HTTP/1.1 200 OK
Content-Type: application/json;charset=UTF-8
Cache-Control: no-store
Pragma: no-cache
{
"access_token":"<KEY>",
"token_type":"bearer",
"expires_in":3600,
"refresh_token":"tGzv3JOkF0XG5Qx2TlKW",
"user_id":1234,
}
* In the case of a token refresh request a POST with the following
structure is required:
POST /token HTTP/1.1
Host: server.example.com
Authorization: Basic czZCaGRSa3F0MzpnWDFmQmF0M2JW
Content-Type: application/x-www-form-urlencoded
grant_type=refresh_token&refresh_token=tGzv3JOkF0XG5Qx2TlKW&user_id=1234
The response will be the same as above with a new access_token and
refresh_token.
"""
# Make sure this is a POST.
if request.method != 'POST':
log.info('rejected request due to invalid method: %s' % request.method)
return HTTPMethodNotAllowed(
'This endpoint only supports the POST method.')
getClientCredentials(request)
# Make sure we got a client_id and secret through the authorization
# policy. Note that you should only get here if not using the Oauth2
# authorization policy or access was granted through the AuthTKt policy.
if (not hasattr(request, 'client_id') or
not hasattr(request, 'client_secret')):
log.info('did not receive client credentials')
return HTTPUnauthorized('Invalid client credentials')
client = db.query(Oauth2Client).filter_by(
client_id=request.client_id).first()
# Again, the authorization policy should catch this, but check again.
if not oauth2_settings('salt'):
raise ValueError('oauth2_provider.salt configuration required.')
salt = b64decode(oauth2_settings('salt').encode('utf-8'))
kdf = Scrypt(
salt=salt,
length=64,
n=2 ** 14,
r=8,
p=1,
backend=backend
)
try:
client_secret = request.client_secret
try:
client_secret = bytes(client_secret, 'utf-8')
except TypeError:
client_secret = client_secret.encode('utf-8')
kdf.verify(client_secret, client.client_secret)
bad_secret = False
except (AttributeError, InvalidKey):
bad_secret = True
if not client or bad_secret:
log.info('received invalid client credentials')
return HTTPBadRequest(InvalidRequest(
error_description='Invalid client credentials'))
# Check for supported grant type. This is a required field of the form
# submission.
resp = None
grant_type = request.POST.get('grant_type')
if grant_type == 'password':
resp = handle_password(request, client)
elif grant_type == 'refresh_token':
resp = handle_refresh_token(request, client)
else:
log.info('invalid grant type: %s' % grant_type)
return HTTPBadRequest(UnsupportedGrantType(error_description='Only '
'password and refresh_token grant types are supported by this '
'authentication server'))
add_cache_headers(request)
return resp
def handle_password(request, client):
if 'username' not in request.POST or 'password' not in request.POST:
log.info('missing username or password')
return HTTPBadRequest(InvalidRequest(error_description='Both username '
'and password are required to obtain a password based grant.'))
auth_check = request.registry.queryUtility(IAuthCheck)
user_id = auth_check().checkauth(request.POST.get('username'),
request.POST.get('password'))
if not user_id:
log.info('could not validate user credentials')
return HTTPUnauthorized(InvalidClient(error_description='Username and '
'password are invalid.'))
auth_token = Oauth2Token(client, user_id)
db.add(auth_token)
db.flush()
return auth_token.asJSON(token_type='bearer')
def handle_refresh_token(request, client):
if 'refresh_token' not in request.POST:
log.info('refresh_token field missing')
return HTTPBadRequest(InvalidRequest(error_description='refresh_token '
'field required'))
if 'user_id' not in request.POST:
log.info('user_id field missing')
return HTTPBadRequest(InvalidRequest(error_description='user_id '
'field required'))
auth_token = db.query(Oauth2Token).filter_by(
refresh_token=request.POST.get('refresh_token')).first()
if not auth_token:
log.info('invalid refresh_token')
return HTTPUnauthorized(InvalidToken(error_description='Provided '
'refresh_token is not valid.'))
if auth_token.client.client_id != client.client_id:
log.info('invalid client_id')
return HTTPBadRequest(InvalidClient(error_description='Client does '
'not own this refresh_token.'))
if str(auth_token.user_id) != request.POST.get('user_id'):
log.info('invalid user_id')
return HTTPBadRequest(InvalidClient(error_description='The given '
'user_id does not match the given refresh_token.'))
new_token = auth_token.refresh()
db.add(new_token)
db.flush()
return new_token.asJSON(token_type='bearer')
def add_cache_headers(request):
"""
The Oauth2 draft spec requires that all token endpoint traffic be marked
as uncacheable.
"""
resp = request.response
resp.headerlist.append(('Cache-Control', 'no-store'))
resp.headerlist.append(('Pragma', 'no-cache'))
return request | 0.752649 | 0.118385 |
from chainer.training import extension
from chainer.training import trigger as trigger_module
class LossSplit(extension.Extension):
def __init__(self, trigger=(10000, 'iteration'), postprocess=None,
segmentation_loss_key='main/loss/mask',
detection_loss_loc_key='main/loss/loc', detection_loss_conf_key='main/loss/conf', smooth_alpha=0.85,
split_alpha=0.15):
# conduct the action of loss division
self._trigger = trigger_module.get_trigger(trigger)
self.alpha = smooth_alpha
self.split_alpha = split_alpha
self._postprocess = postprocess
self._segmentation_loss_key = segmentation_loss_key
self._detection_loss_conf_key = detection_loss_conf_key
self._detection_loss_loc_key = detection_loss_loc_key
self._max_loss_seg = None
self._current_loss_seg = None
self._max_loss_det_loc = None
self._current_loss_det_loc = None
self._max_loss_det_conf = None
self._current_loss_det_conf = None
self._current_loss_split = None
def __call__(self, trainer):
observation = trainer.observation
current_loss_seg = observation[self._segmentation_loss_key].data
current_loss_det_conf = observation[self._detection_loss_conf_key].data
current_loss_det_loc = observation[self._detection_loss_loc_key].data
if self._max_loss_seg is None:
self._max_loss_seg = current_loss_seg
if self._max_loss_det_conf is None:
self._max_loss_det_conf = current_loss_det_conf
if self._max_loss_det_loc is None:
self._max_loss_det_loc = current_loss_det_loc
self._current_loss_seg = self.__smooth(self._current_loss_seg, current_loss_seg)
self._current_loss_det_conf = self.__smooth(self._current_loss_det_conf, current_loss_det_conf)
self._current_loss_det_loc = self.__smooth(self._current_loss_det_loc, current_loss_det_loc)
if self._trigger(trainer):
# compute the rewward and modify the loss split
reward_det, reward_seg = self._reward()
loss_split = self._loss_split(reward_det, reward_seg)
self._current_loss_split = self.__smooth(self._current_loss_split, loss_split, self.split_alpha)
trainer.updater._optimizers['main'].target.loss_split = self._current_loss_split
self._max_loss_seg = current_loss_seg
self._max_loss_det_conf = current_loss_det_conf
self._max_loss_det_loc = current_loss_det_loc
# trainer
def _focal_function(self, p, r):
'''
-(1-p)**r*np.log(p)
:param p:
:param r:
:return:
'''
import numpy as np
return -(1 - p) ** r * np.log(p)
def _reward(self):
loss_det_current = self._current_loss_det_conf + self._current_loss_det_loc
loss_det_max = self._max_loss_det_conf + self._max_loss_det_loc
reward_det = (loss_det_max - loss_det_current) / loss_det_max
reward_seg = (self._max_loss_seg - self._current_loss_seg) / self._max_loss_seg
return reward_det, reward_seg
def _loss_split(self, reward_det, reward_seg):
import numpy as np
return np.round(np.exp(reward_seg) / (np.exp(reward_seg) + np.exp(reward_det)), 4)
def __smooth(self, previous, current, alpha=None):
if alpha is None:
alpha = self.alpha
if previous is None:
return current
else:
return previous * alpha + current * (1 - alpha) | multi_task/extensions/loss_split.py | from chainer.training import extension
from chainer.training import trigger as trigger_module
class LossSplit(extension.Extension):
def __init__(self, trigger=(10000, 'iteration'), postprocess=None,
segmentation_loss_key='main/loss/mask',
detection_loss_loc_key='main/loss/loc', detection_loss_conf_key='main/loss/conf', smooth_alpha=0.85,
split_alpha=0.15):
# conduct the action of loss division
self._trigger = trigger_module.get_trigger(trigger)
self.alpha = smooth_alpha
self.split_alpha = split_alpha
self._postprocess = postprocess
self._segmentation_loss_key = segmentation_loss_key
self._detection_loss_conf_key = detection_loss_conf_key
self._detection_loss_loc_key = detection_loss_loc_key
self._max_loss_seg = None
self._current_loss_seg = None
self._max_loss_det_loc = None
self._current_loss_det_loc = None
self._max_loss_det_conf = None
self._current_loss_det_conf = None
self._current_loss_split = None
def __call__(self, trainer):
observation = trainer.observation
current_loss_seg = observation[self._segmentation_loss_key].data
current_loss_det_conf = observation[self._detection_loss_conf_key].data
current_loss_det_loc = observation[self._detection_loss_loc_key].data
if self._max_loss_seg is None:
self._max_loss_seg = current_loss_seg
if self._max_loss_det_conf is None:
self._max_loss_det_conf = current_loss_det_conf
if self._max_loss_det_loc is None:
self._max_loss_det_loc = current_loss_det_loc
self._current_loss_seg = self.__smooth(self._current_loss_seg, current_loss_seg)
self._current_loss_det_conf = self.__smooth(self._current_loss_det_conf, current_loss_det_conf)
self._current_loss_det_loc = self.__smooth(self._current_loss_det_loc, current_loss_det_loc)
if self._trigger(trainer):
# compute the rewward and modify the loss split
reward_det, reward_seg = self._reward()
loss_split = self._loss_split(reward_det, reward_seg)
self._current_loss_split = self.__smooth(self._current_loss_split, loss_split, self.split_alpha)
trainer.updater._optimizers['main'].target.loss_split = self._current_loss_split
self._max_loss_seg = current_loss_seg
self._max_loss_det_conf = current_loss_det_conf
self._max_loss_det_loc = current_loss_det_loc
# trainer
def _focal_function(self, p, r):
'''
-(1-p)**r*np.log(p)
:param p:
:param r:
:return:
'''
import numpy as np
return -(1 - p) ** r * np.log(p)
def _reward(self):
loss_det_current = self._current_loss_det_conf + self._current_loss_det_loc
loss_det_max = self._max_loss_det_conf + self._max_loss_det_loc
reward_det = (loss_det_max - loss_det_current) / loss_det_max
reward_seg = (self._max_loss_seg - self._current_loss_seg) / self._max_loss_seg
return reward_det, reward_seg
def _loss_split(self, reward_det, reward_seg):
import numpy as np
return np.round(np.exp(reward_seg) / (np.exp(reward_seg) + np.exp(reward_det)), 4)
def __smooth(self, previous, current, alpha=None):
if alpha is None:
alpha = self.alpha
if previous is None:
return current
else:
return previous * alpha + current * (1 - alpha) | 0.925048 | 0.133472 |
from __future__ import absolute_import
from __future__ import unicode_literals
from pyramid.view import view_config
from schematizer.api.decorators import log_api
from schematizer.api.decorators import transform_api_response
from schematizer.api.exceptions import exceptions_v1
from schematizer.api.requests import requests_v1
from schematizer.api.responses import responses_v1
from schematizer.logic import doc_tool
from schematizer.logic import schema_repository
from schematizer.models.note import ReferenceTypeEnum
@view_config(
route_name='api.v1.create_note',
request_method='POST',
renderer='json'
)
@transform_api_response()
@log_api()
def create_note(request):
req = requests_v1.CreateNoteRequest(**request.json_body)
assert_reference_exists(req.reference_type, req.reference_id)
note = doc_tool.create_note(
reference_type=req.reference_type,
reference_id=req.reference_id,
note_text=req.note,
last_updated_by=req.last_updated_by
)
return responses_v1.get_note_response_from_note(note)
def assert_reference_exists(reference_type, reference_id):
"""Checks to make sure that the reference for this note exists.
If it does not, raise an exception
"""
if (
reference_type == ReferenceTypeEnum.SCHEMA and
schema_repository.get_schema_by_id(reference_id) is not None
) or (
reference_type == ReferenceTypeEnum.SCHEMA_ELEMENT and
schema_repository.get_schema_element_by_id(reference_id) is not None
):
# Valid. Do nothing
return
raise exceptions_v1.reference_not_found_exception()
@view_config(
route_name='api.v1.update_note',
request_method='POST',
renderer='json'
)
@transform_api_response()
@log_api()
def update_note(request):
req = requests_v1.UpdateNoteRequest(**request.json_body)
note_id_str = request.matchdict.get('note_id')
note_id = int(note_id_str)
note = doc_tool.get_note_by_id(note_id)
# Raise an exception if the note cannot be found
if note is None:
raise exceptions_v1.note_not_found_exception()
doc_tool.update_note(
id=note_id,
note_text=req.note,
last_updated_by=req.last_updated_by
)
return responses_v1.get_note_response_from_note(note) | schematizer/views/notes.py | from __future__ import absolute_import
from __future__ import unicode_literals
from pyramid.view import view_config
from schematizer.api.decorators import log_api
from schematizer.api.decorators import transform_api_response
from schematizer.api.exceptions import exceptions_v1
from schematizer.api.requests import requests_v1
from schematizer.api.responses import responses_v1
from schematizer.logic import doc_tool
from schematizer.logic import schema_repository
from schematizer.models.note import ReferenceTypeEnum
@view_config(
route_name='api.v1.create_note',
request_method='POST',
renderer='json'
)
@transform_api_response()
@log_api()
def create_note(request):
req = requests_v1.CreateNoteRequest(**request.json_body)
assert_reference_exists(req.reference_type, req.reference_id)
note = doc_tool.create_note(
reference_type=req.reference_type,
reference_id=req.reference_id,
note_text=req.note,
last_updated_by=req.last_updated_by
)
return responses_v1.get_note_response_from_note(note)
def assert_reference_exists(reference_type, reference_id):
"""Checks to make sure that the reference for this note exists.
If it does not, raise an exception
"""
if (
reference_type == ReferenceTypeEnum.SCHEMA and
schema_repository.get_schema_by_id(reference_id) is not None
) or (
reference_type == ReferenceTypeEnum.SCHEMA_ELEMENT and
schema_repository.get_schema_element_by_id(reference_id) is not None
):
# Valid. Do nothing
return
raise exceptions_v1.reference_not_found_exception()
@view_config(
route_name='api.v1.update_note',
request_method='POST',
renderer='json'
)
@transform_api_response()
@log_api()
def update_note(request):
req = requests_v1.UpdateNoteRequest(**request.json_body)
note_id_str = request.matchdict.get('note_id')
note_id = int(note_id_str)
note = doc_tool.get_note_by_id(note_id)
# Raise an exception if the note cannot be found
if note is None:
raise exceptions_v1.note_not_found_exception()
doc_tool.update_note(
id=note_id,
note_text=req.note,
last_updated_by=req.last_updated_by
)
return responses_v1.get_note_response_from_note(note) | 0.663124 | 0.109658 |
import click
import sys
import traceback
import os
import opencc
from lightnovel import LightNovel
from utils import echo
from provider import lk_new
from provider import wenku8
from provider import lk_mobile
echo.init_subroutine()
@click.group()
def cli():
pass
@cli.command()
# general options
@click.option('--dump-path', type=click.Path(), default='./dump',
help='directory for dumping files and caches')
@click.option('--title', default=None,
help='title of light novel')
@click.option('--authors', default=None,
help='authors\' names, separated by comma (,)')
@click.option('--identifier', default=None,
help='identifier of light novel')
@click.option('--cover-link', default=None,
help='cover link of light novel. cover link can either be web link or file path. if it is not beginned with "http", it would be recognized as file path. if nothing was given, then it will use the first picture of webpage.')
@click.option('--cvt', default=None,
help='OpenCC conversion configuration, used to convert between different Chinese characters. you can choose the value from "s2t", "t2s", "s2tw", "tw2s", "s2hk", "hk2s", "s2twp", "tw2sp", "t2tw", "hk2t", "t2hk", "t2jp", "jp2t", "tw2t". if nothing is provided, no conversion would be performed. for more information, please visit: https://github.com/BYVoid/OpenCC')
@click.option('--path', type=click.Path(exists=True), default='./',
help='directory for saving the light novel')
# lightnovel.us
@click.option('--lk-html-dump', type=click.Path(exists=True), default=None,
help='(lightnovel.us) html content dump file path')
# wenku8.net
@click.option('--wenku8-volume', default=-1,
help='(wenku8.net) identify the index of the volume to generate. -1 means every volume, which is also the default option. index starts from 1.')
# lk mobile
@click.option('--lk-mobile-top-area-height', default=325,
help='(lk mobile) the height of the top area')
@click.option('--lk-mobile-bottom-area-height', default=200,
help='(lk mobile) the height of the bottom area')
@click.option('--lk-mobile-image-equal-threshold', default=1,
help='(lk mobile) the threshold of judging whether two images are equal')
@click.option('--lk-mobile-safe-area-padding', default=20,
help='(lk mobile) the padding of the safe area')
@click.option('--lk-mobile-vert-dump', type=click.Path(exists=True), default=None,
help='(lk mobile) vertical content dump file path')
@click.option('--lk-mobile-horz-dump', type=click.Path(exists=True), default=None,
help='(lk mobile) horizontal content dump file path')
@click.option('--lk-mobile-html-dump', type=click.Path(exists=True), default=None,
help='(lk mobile) html content dump file path')
@click.option('--lk-mobile-conflict-mode', type=bool, default=False,
help='(lk mobile) whether to resolve conflict manually')
@click.option('--lk-mobile-ignore-newline', type=bool, default=True,
help='(lk mobile) whether to ignore newline')
# general arguments
@click.argument('url')
def download(
dump_path,
title: str,
authors: str,
identifier: str,
cover_link: str,
cvt: str,
path: str,
lk_html_dump,
wenku8_volume: int,
lk_mobile_top_area_height: int,
lk_mobile_bottom_area_height: int,
lk_mobile_image_equal_threshold: int,
lk_mobile_safe_area_padding: int,
lk_mobile_vert_dump,
lk_mobile_horz_dump,
lk_mobile_html_dump,
lk_mobile_conflict_mode: bool,
lk_mobile_ignore_newline: bool,
url: str):
'''
download the light novel
ARGUMENTS:
* URL: url of light novel to download
'''
def convert_str(content, cvt):
# chinese conversion
if cvt in ["s2t", "t2s", "s2tw", "tw2s", "s2hk", "hk2s", "s2twp", "tw2sp", "t2tw", "hk2t", "t2hk", "t2jp", "jp2t", "tw2t"]:
converter = opencc.OpenCC(f'{cvt}.json')
return converter.convert(content)
return content
echo.push_subroutine(sys._getframe().f_code.co_name)
try:
# init directory
if not os.path.exists(dump_path):
os.mkdir(dump_path)
if cover_link is None:
cover_link = input('(Optional) Input cover_link of light novel (see --help for further explanation): ')
if url.startswith('https://www.lightnovel.us/'):
contents = lk_new.get_contents(url, dump_path, lk_html_dump)
cover_link = lk_new.get_cover(cover_link, dump_path) if cover_link.startswith('http') else cover_link
elif url.startswith('https://www.wenku8.net/'):
source, authors, identifier, title, books, contents = wenku8.get_contents(url, dump_path, wenku8_volume)
cover_link = wenku8.get_cover(cover_link, dump_path) if cover_link.startswith('http') else cover_link
elif url == 'lk-mobile':
contents = lk_mobile.get_contents(lk_mobile_top_area_height, lk_mobile_bottom_area_height, lk_mobile_image_equal_threshold, lk_mobile_safe_area_padding, dump_path, lk_mobile_vert_dump, lk_mobile_horz_dump, lk_mobile_html_dump, lk_mobile_conflict_mode, lk_mobile_ignore_newline)
cover_link = lk_mobile.get_cover(cover_link, dump_path) if cover_link.startswith('http') else cover_link
url = '轻之国度 APP'
else:
echo.cexit('unsupported url')
if type(contents) == str:
contents = convert_str(contents, cvt)
elif type(contents) == list:
for content in contents:
content['title'] = convert_str(content['title'], cvt)
content['content'] = convert_str(content['content'], cvt)
else:
echo.cexit('CONTENTS MUST BE STRING OR LIST')
TITLE_INPUT_HINT = 'Input title of light novel: '
AUTHOR_INPUT_HINT = '(Optional) Input authors\' names, separated by comma (,): '
IDENTIFIER_INPUT_HINT = '(Optional) Input identifier of light novel: '
def isempty(instr) -> bool:
if instr is None:
return True
if len(instr) == 0 or str.isspace(instr):
return True
return False
if isempty(title):
title = input(TITLE_INPUT_HINT)
else:
user_title = input(f'Current Title: {title}. (Optional) {TITLE_INPUT_HINT}')
title = title if isempty(user_title) else user_title
if isempty(authors):
authors = input(AUTHOR_INPUT_HINT)
else:
user_authors = input(f'Current Authors: {authors}. {AUTHOR_INPUT_HINT}')
authors = authors if isempty(user_authors) else user_authors
if isempty(identifier):
identifier = input(IDENTIFIER_INPUT_HINT)
else:
user_identifier = input(f'Current identifier: {identifier}. {IDENTIFIER_INPUT_HINT}')
identifier = identifier if isempty(user_identifier) else user_identifier
novel = LightNovel(source=url, authors=authors.split(','), identifier=identifier, title=title, cover_link=cover_link)
novel.contents = contents
novel.write_epub(path)
except Exception as e:
echo.cerr(f'Error: {repr(e)}')
traceback.print_exc()
echo.cexit('DOWNLOAD LIGHTNOVEL FAILED')
finally:
echo.pop_subroutine()
if __name__ == '__main__':
cli() | cli.py | import click
import sys
import traceback
import os
import opencc
from lightnovel import LightNovel
from utils import echo
from provider import lk_new
from provider import wenku8
from provider import lk_mobile
echo.init_subroutine()
@click.group()
def cli():
pass
@cli.command()
# general options
@click.option('--dump-path', type=click.Path(), default='./dump',
help='directory for dumping files and caches')
@click.option('--title', default=None,
help='title of light novel')
@click.option('--authors', default=None,
help='authors\' names, separated by comma (,)')
@click.option('--identifier', default=None,
help='identifier of light novel')
@click.option('--cover-link', default=None,
help='cover link of light novel. cover link can either be web link or file path. if it is not beginned with "http", it would be recognized as file path. if nothing was given, then it will use the first picture of webpage.')
@click.option('--cvt', default=None,
help='OpenCC conversion configuration, used to convert between different Chinese characters. you can choose the value from "s2t", "t2s", "s2tw", "tw2s", "s2hk", "hk2s", "s2twp", "tw2sp", "t2tw", "hk2t", "t2hk", "t2jp", "jp2t", "tw2t". if nothing is provided, no conversion would be performed. for more information, please visit: https://github.com/BYVoid/OpenCC')
@click.option('--path', type=click.Path(exists=True), default='./',
help='directory for saving the light novel')
# lightnovel.us
@click.option('--lk-html-dump', type=click.Path(exists=True), default=None,
help='(lightnovel.us) html content dump file path')
# wenku8.net
@click.option('--wenku8-volume', default=-1,
help='(wenku8.net) identify the index of the volume to generate. -1 means every volume, which is also the default option. index starts from 1.')
# lk mobile
@click.option('--lk-mobile-top-area-height', default=325,
help='(lk mobile) the height of the top area')
@click.option('--lk-mobile-bottom-area-height', default=200,
help='(lk mobile) the height of the bottom area')
@click.option('--lk-mobile-image-equal-threshold', default=1,
help='(lk mobile) the threshold of judging whether two images are equal')
@click.option('--lk-mobile-safe-area-padding', default=20,
help='(lk mobile) the padding of the safe area')
@click.option('--lk-mobile-vert-dump', type=click.Path(exists=True), default=None,
help='(lk mobile) vertical content dump file path')
@click.option('--lk-mobile-horz-dump', type=click.Path(exists=True), default=None,
help='(lk mobile) horizontal content dump file path')
@click.option('--lk-mobile-html-dump', type=click.Path(exists=True), default=None,
help='(lk mobile) html content dump file path')
@click.option('--lk-mobile-conflict-mode', type=bool, default=False,
help='(lk mobile) whether to resolve conflict manually')
@click.option('--lk-mobile-ignore-newline', type=bool, default=True,
help='(lk mobile) whether to ignore newline')
# general arguments
@click.argument('url')
def download(
dump_path,
title: str,
authors: str,
identifier: str,
cover_link: str,
cvt: str,
path: str,
lk_html_dump,
wenku8_volume: int,
lk_mobile_top_area_height: int,
lk_mobile_bottom_area_height: int,
lk_mobile_image_equal_threshold: int,
lk_mobile_safe_area_padding: int,
lk_mobile_vert_dump,
lk_mobile_horz_dump,
lk_mobile_html_dump,
lk_mobile_conflict_mode: bool,
lk_mobile_ignore_newline: bool,
url: str):
'''
download the light novel
ARGUMENTS:
* URL: url of light novel to download
'''
def convert_str(content, cvt):
# chinese conversion
if cvt in ["s2t", "t2s", "s2tw", "tw2s", "s2hk", "hk2s", "s2twp", "tw2sp", "t2tw", "hk2t", "t2hk", "t2jp", "jp2t", "tw2t"]:
converter = opencc.OpenCC(f'{cvt}.json')
return converter.convert(content)
return content
echo.push_subroutine(sys._getframe().f_code.co_name)
try:
# init directory
if not os.path.exists(dump_path):
os.mkdir(dump_path)
if cover_link is None:
cover_link = input('(Optional) Input cover_link of light novel (see --help for further explanation): ')
if url.startswith('https://www.lightnovel.us/'):
contents = lk_new.get_contents(url, dump_path, lk_html_dump)
cover_link = lk_new.get_cover(cover_link, dump_path) if cover_link.startswith('http') else cover_link
elif url.startswith('https://www.wenku8.net/'):
source, authors, identifier, title, books, contents = wenku8.get_contents(url, dump_path, wenku8_volume)
cover_link = wenku8.get_cover(cover_link, dump_path) if cover_link.startswith('http') else cover_link
elif url == 'lk-mobile':
contents = lk_mobile.get_contents(lk_mobile_top_area_height, lk_mobile_bottom_area_height, lk_mobile_image_equal_threshold, lk_mobile_safe_area_padding, dump_path, lk_mobile_vert_dump, lk_mobile_horz_dump, lk_mobile_html_dump, lk_mobile_conflict_mode, lk_mobile_ignore_newline)
cover_link = lk_mobile.get_cover(cover_link, dump_path) if cover_link.startswith('http') else cover_link
url = '轻之国度 APP'
else:
echo.cexit('unsupported url')
if type(contents) == str:
contents = convert_str(contents, cvt)
elif type(contents) == list:
for content in contents:
content['title'] = convert_str(content['title'], cvt)
content['content'] = convert_str(content['content'], cvt)
else:
echo.cexit('CONTENTS MUST BE STRING OR LIST')
TITLE_INPUT_HINT = 'Input title of light novel: '
AUTHOR_INPUT_HINT = '(Optional) Input authors\' names, separated by comma (,): '
IDENTIFIER_INPUT_HINT = '(Optional) Input identifier of light novel: '
def isempty(instr) -> bool:
if instr is None:
return True
if len(instr) == 0 or str.isspace(instr):
return True
return False
if isempty(title):
title = input(TITLE_INPUT_HINT)
else:
user_title = input(f'Current Title: {title}. (Optional) {TITLE_INPUT_HINT}')
title = title if isempty(user_title) else user_title
if isempty(authors):
authors = input(AUTHOR_INPUT_HINT)
else:
user_authors = input(f'Current Authors: {authors}. {AUTHOR_INPUT_HINT}')
authors = authors if isempty(user_authors) else user_authors
if isempty(identifier):
identifier = input(IDENTIFIER_INPUT_HINT)
else:
user_identifier = input(f'Current identifier: {identifier}. {IDENTIFIER_INPUT_HINT}')
identifier = identifier if isempty(user_identifier) else user_identifier
novel = LightNovel(source=url, authors=authors.split(','), identifier=identifier, title=title, cover_link=cover_link)
novel.contents = contents
novel.write_epub(path)
except Exception as e:
echo.cerr(f'Error: {repr(e)}')
traceback.print_exc()
echo.cexit('DOWNLOAD LIGHTNOVEL FAILED')
finally:
echo.pop_subroutine()
if __name__ == '__main__':
cli() | 0.193833 | 0.073696 |
from CodaClient import Client, Currency, CurrencyFormat
import os
import schedule
import time
import urllib3
import random
from requests.exceptions import ConnectionError
from prometheus_client import Counter, start_http_server
def getenv_default_map(env_var: str, f, default):
value = os.getenv(env_var)
if value == None:
return default
else:
return f(value)
def getenv_str(env_var: str, default: str) -> str:
return os.getenv(env_var, default).strip()
def getenv_int(env_var: str, default: int) -> int:
return getenv_default_map(env_var, int, default)
def getenv_currency(env_var: str, lower_bound: Currency, upper_bound: Currency) -> Currency:
return getenv_default_map(env_var, Currency, Currency.random(lower_bound, upper_bound))
CODA_PUBLIC_KEY = getenv_str("CODA_PUBLIC_KEY", "<KEY>")
MINA_PRIVKEY_PASS = getenv_str("MINA_PRIVKEY_PASS", "<PASSWORD>")
AGENT_MIN_FEE = getenv_currency("AGENT_MIN_FEE", Currency("0.06"), Currency("0.1"))
AGENT_MAX_FEE = getenv_currency("AGENT_MAX_FEE", AGENT_MIN_FEE, AGENT_MIN_FEE + Currency("0.2"))
AGENT_MIN_TX = getenv_currency("AGENT_MIN_TX", Currency("0.0015"), Currency("0.005"))
AGENT_MAX_TX = getenv_currency("AGENT_MAX_TX", AGENT_MIN_TX, AGENT_MIN_TX + Currency("0.01"))
AGENT_TX_BATCH_SIZE = getenv_int("AGENT_TX_BATCH_SIZE", 1)
AGENT_SEND_EVERY_MINS = getenv_int("AGENT_SEND_EVERY_MINS", random.randint(1, 5))
AGENT_METRICS_PORT = getenv_int("AGENT_METRICS_PORT", 8000)
CODA_CLIENT_ARGS = {
"graphql_host": getenv_str("CODA_HOST", "localhost"),
"graphql_port": getenv_str("CODA_PORT", "3085")
}
## Prometheus Metrics
TRANSACTIONS_SENT = Counter('transactions_sent', 'Number of transactions agent has sent since boot.')
TRANSACTION_ERRORS = Counter('transaction_errors', 'Number of errors that occurred while sending transactions.')
class Agent(object):
"""Represents a generic agent that operates on the coda blockchain"""
def __init__(self, client_args, public_key, privkey_pass, min_tx_amount=AGENT_MIN_TX, max_tx_amount=AGENT_MAX_TX, min_fee_amount=AGENT_MIN_FEE, max_fee_amount=AGENT_MAX_FEE):
self.coda = Client(**client_args)
self.public_key = public_key
self.privkey_pass = privkey_pass
self.min_tx_amount = min_tx_amount
self.max_tx_amount = max_tx_amount
self.min_fee_amount = min_fee_amount
self.max_fee_amount = max_fee_amount
self.to_account = None
def get_to_account(self):
if not self.to_account:
print("Getting new wallet to send to...")
response = self.coda.create_wallet(self.privkey_pass)
self.to_account = response["createAccount"]["publicKey"]
print("Public Key: {}".format(self.to_account))
return self.to_account
def unlock_wallet(self):
response = self.coda.unlock_wallet(self.public_key, self.privkey_pass)
print("Unlocked Wallet!")
return response
def send_transaction(self):
print("---Sending Transaction---")
try:
to_account = self.get_to_account()
print("Trying to unlock Wallet!")
self.unlock_wallet()
except ConnectionError:
print("Transaction Failed due to connection error... is the Daemon running?")
TRANSACTION_ERRORS.inc()
return None
except Exception as e:
print("Error unlocking wallet...")
print(e)
return None
tx_amount = Currency.random(self.min_tx_amount, self.max_tx_amount)
fee_amount = Currency.random(self.min_fee_amount, self.max_fee_amount)
try:
response = self.coda.send_payment(to_account, self.public_key, tx_amount, fee_amount, memo="BeepBoop")
except Exception as e:
print("Error sending transaction...", e)
TRANSACTION_ERRORS.inc()
return None
if not response.get("errors", None):
print("Sent a Transaction {}".format(response))
TRANSACTIONS_SENT.inc()
else:
print("Error sending transaction: Request: {} Response: {}".format(self.public_key, response))
TRANSACTION_ERRORS.inc()
return response
def send_transaction_batch(self):
responses = []
for i in range(AGENT_TX_BATCH_SIZE):
responses.append(self.send_transaction())
return responses
def main():
agent = Agent(CODA_CLIENT_ARGS, CODA_PUBLIC_KEY, MINA_PRIVKEY_PASS)
schedule.every(AGENT_SEND_EVERY_MINS).minutes.do(agent.send_transaction_batch)
print("Sending a transaction every {} minutes.".format(AGENT_SEND_EVERY_MINS))
while True:
schedule.run_pending()
sleep_time = 10
print("Sleeping for {} seconds...".format(sleep_time))
time.sleep(sleep_time)
if __name__ == "__main__":
print("Starting up...")
start_http_server(AGENT_METRICS_PORT)
print("Metrics on Port {}".format(AGENT_METRICS_PORT))
print("Sleeping for 20 minutes...")
time.sleep(60*20)
main() | automation/services/coda-user-agent/agent.py | from CodaClient import Client, Currency, CurrencyFormat
import os
import schedule
import time
import urllib3
import random
from requests.exceptions import ConnectionError
from prometheus_client import Counter, start_http_server
def getenv_default_map(env_var: str, f, default):
value = os.getenv(env_var)
if value == None:
return default
else:
return f(value)
def getenv_str(env_var: str, default: str) -> str:
return os.getenv(env_var, default).strip()
def getenv_int(env_var: str, default: int) -> int:
return getenv_default_map(env_var, int, default)
def getenv_currency(env_var: str, lower_bound: Currency, upper_bound: Currency) -> Currency:
return getenv_default_map(env_var, Currency, Currency.random(lower_bound, upper_bound))
CODA_PUBLIC_KEY = getenv_str("CODA_PUBLIC_KEY", "<KEY>")
MINA_PRIVKEY_PASS = getenv_str("MINA_PRIVKEY_PASS", "<PASSWORD>")
AGENT_MIN_FEE = getenv_currency("AGENT_MIN_FEE", Currency("0.06"), Currency("0.1"))
AGENT_MAX_FEE = getenv_currency("AGENT_MAX_FEE", AGENT_MIN_FEE, AGENT_MIN_FEE + Currency("0.2"))
AGENT_MIN_TX = getenv_currency("AGENT_MIN_TX", Currency("0.0015"), Currency("0.005"))
AGENT_MAX_TX = getenv_currency("AGENT_MAX_TX", AGENT_MIN_TX, AGENT_MIN_TX + Currency("0.01"))
AGENT_TX_BATCH_SIZE = getenv_int("AGENT_TX_BATCH_SIZE", 1)
AGENT_SEND_EVERY_MINS = getenv_int("AGENT_SEND_EVERY_MINS", random.randint(1, 5))
AGENT_METRICS_PORT = getenv_int("AGENT_METRICS_PORT", 8000)
CODA_CLIENT_ARGS = {
"graphql_host": getenv_str("CODA_HOST", "localhost"),
"graphql_port": getenv_str("CODA_PORT", "3085")
}
## Prometheus Metrics
TRANSACTIONS_SENT = Counter('transactions_sent', 'Number of transactions agent has sent since boot.')
TRANSACTION_ERRORS = Counter('transaction_errors', 'Number of errors that occurred while sending transactions.')
class Agent(object):
"""Represents a generic agent that operates on the coda blockchain"""
def __init__(self, client_args, public_key, privkey_pass, min_tx_amount=AGENT_MIN_TX, max_tx_amount=AGENT_MAX_TX, min_fee_amount=AGENT_MIN_FEE, max_fee_amount=AGENT_MAX_FEE):
self.coda = Client(**client_args)
self.public_key = public_key
self.privkey_pass = privkey_pass
self.min_tx_amount = min_tx_amount
self.max_tx_amount = max_tx_amount
self.min_fee_amount = min_fee_amount
self.max_fee_amount = max_fee_amount
self.to_account = None
def get_to_account(self):
if not self.to_account:
print("Getting new wallet to send to...")
response = self.coda.create_wallet(self.privkey_pass)
self.to_account = response["createAccount"]["publicKey"]
print("Public Key: {}".format(self.to_account))
return self.to_account
def unlock_wallet(self):
response = self.coda.unlock_wallet(self.public_key, self.privkey_pass)
print("Unlocked Wallet!")
return response
def send_transaction(self):
print("---Sending Transaction---")
try:
to_account = self.get_to_account()
print("Trying to unlock Wallet!")
self.unlock_wallet()
except ConnectionError:
print("Transaction Failed due to connection error... is the Daemon running?")
TRANSACTION_ERRORS.inc()
return None
except Exception as e:
print("Error unlocking wallet...")
print(e)
return None
tx_amount = Currency.random(self.min_tx_amount, self.max_tx_amount)
fee_amount = Currency.random(self.min_fee_amount, self.max_fee_amount)
try:
response = self.coda.send_payment(to_account, self.public_key, tx_amount, fee_amount, memo="BeepBoop")
except Exception as e:
print("Error sending transaction...", e)
TRANSACTION_ERRORS.inc()
return None
if not response.get("errors", None):
print("Sent a Transaction {}".format(response))
TRANSACTIONS_SENT.inc()
else:
print("Error sending transaction: Request: {} Response: {}".format(self.public_key, response))
TRANSACTION_ERRORS.inc()
return response
def send_transaction_batch(self):
responses = []
for i in range(AGENT_TX_BATCH_SIZE):
responses.append(self.send_transaction())
return responses
def main():
agent = Agent(CODA_CLIENT_ARGS, CODA_PUBLIC_KEY, MINA_PRIVKEY_PASS)
schedule.every(AGENT_SEND_EVERY_MINS).minutes.do(agent.send_transaction_batch)
print("Sending a transaction every {} minutes.".format(AGENT_SEND_EVERY_MINS))
while True:
schedule.run_pending()
sleep_time = 10
print("Sleeping for {} seconds...".format(sleep_time))
time.sleep(sleep_time)
if __name__ == "__main__":
print("Starting up...")
start_http_server(AGENT_METRICS_PORT)
print("Metrics on Port {}".format(AGENT_METRICS_PORT))
print("Sleeping for 20 minutes...")
time.sleep(60*20)
main() | 0.46393 | 0.111 |
from __future__ import absolute_import
from collections import namedtuple
from typing import (Any, Callable, Dict, # pylint: disable=unused-import
Generator, Iterable, List, Text, Union, cast)
from .errors import WorkflowException
MutationState = namedtuple("MutationTracker", ["generation", "readers", "stepname"])
_generation = "http://commonwl.org/cwltool#generation"
class MutationManager(object):
"""Lock manager for checking correctness of in-place update of files.
Used to validate that in-place file updates happen sequentially, and that a
file which is registered for in-place update cannot be read or updated by
any other steps.
"""
def __init__(self):
# type: () -> None
self.generations = {} # type: Dict[Text, MutationState]
def register_reader(self, stepname, obj):
# type: (Text, Dict[Text, Any]) -> None
loc = obj["location"]
current = self.generations.get(loc, MutationState(0, [], ""))
obj_generation = obj.get(_generation, 0)
if obj_generation != current.generation:
raise WorkflowException("[job %s] wants to read %s from generation %i but current generation is %s (last updated by %s)" % (
stepname, loc, obj_generation, current.generation, current.stepname))
current.readers.append(stepname)
self.generations[loc] = current
def release_reader(self, stepname, obj):
# type: (Text, Dict[Text, Any]) -> None
loc = obj["location"]
current = self.generations.get(loc, MutationState(0, [], ""))
obj_generation = obj.get(_generation, 0)
if obj_generation != current.generation:
raise WorkflowException("[job %s] wants to release reader on %s from generation %i but current generation is %s (last updated by %s)" % (
stepname, loc, obj_generation, current.generation, current.stepname))
self.generations[loc].readers.remove(stepname)
def register_mutation(self, stepname, obj):
# type: (Text, Dict[Text, Any]) -> None
loc = obj["location"]
current = self.generations.get(loc, MutationState(0,[], ""))
obj_generation = obj.get(_generation, 0)
if len(current.readers) > 0:
raise WorkflowException("[job %s] wants to modify %s but has readers: %s" % (
stepname, loc, current.readers))
if obj_generation != current.generation:
raise WorkflowException("[job %s] wants to modify %s from generation %i but current generation is %s (last updated by %s)" % (
stepname, loc, obj_generation, current.generation, current.stepname))
self.generations[loc] = MutationState(current.generation+1, current.readers, stepname)
def set_generation(self, obj):
# type: (Dict) -> None
loc = obj["location"]
current = self.generations.get(loc, MutationState(0,[], ""))
obj[_generation] = current.generation
def unset_generation(self, obj):
# type: (Dict) -> None
obj.pop(_generation, None) | cwltool/mutation.py | from __future__ import absolute_import
from collections import namedtuple
from typing import (Any, Callable, Dict, # pylint: disable=unused-import
Generator, Iterable, List, Text, Union, cast)
from .errors import WorkflowException
MutationState = namedtuple("MutationTracker", ["generation", "readers", "stepname"])
_generation = "http://commonwl.org/cwltool#generation"
class MutationManager(object):
"""Lock manager for checking correctness of in-place update of files.
Used to validate that in-place file updates happen sequentially, and that a
file which is registered for in-place update cannot be read or updated by
any other steps.
"""
def __init__(self):
# type: () -> None
self.generations = {} # type: Dict[Text, MutationState]
def register_reader(self, stepname, obj):
# type: (Text, Dict[Text, Any]) -> None
loc = obj["location"]
current = self.generations.get(loc, MutationState(0, [], ""))
obj_generation = obj.get(_generation, 0)
if obj_generation != current.generation:
raise WorkflowException("[job %s] wants to read %s from generation %i but current generation is %s (last updated by %s)" % (
stepname, loc, obj_generation, current.generation, current.stepname))
current.readers.append(stepname)
self.generations[loc] = current
def release_reader(self, stepname, obj):
# type: (Text, Dict[Text, Any]) -> None
loc = obj["location"]
current = self.generations.get(loc, MutationState(0, [], ""))
obj_generation = obj.get(_generation, 0)
if obj_generation != current.generation:
raise WorkflowException("[job %s] wants to release reader on %s from generation %i but current generation is %s (last updated by %s)" % (
stepname, loc, obj_generation, current.generation, current.stepname))
self.generations[loc].readers.remove(stepname)
def register_mutation(self, stepname, obj):
# type: (Text, Dict[Text, Any]) -> None
loc = obj["location"]
current = self.generations.get(loc, MutationState(0,[], ""))
obj_generation = obj.get(_generation, 0)
if len(current.readers) > 0:
raise WorkflowException("[job %s] wants to modify %s but has readers: %s" % (
stepname, loc, current.readers))
if obj_generation != current.generation:
raise WorkflowException("[job %s] wants to modify %s from generation %i but current generation is %s (last updated by %s)" % (
stepname, loc, obj_generation, current.generation, current.stepname))
self.generations[loc] = MutationState(current.generation+1, current.readers, stepname)
def set_generation(self, obj):
# type: (Dict) -> None
loc = obj["location"]
current = self.generations.get(loc, MutationState(0,[], ""))
obj[_generation] = current.generation
def unset_generation(self, obj):
# type: (Dict) -> None
obj.pop(_generation, None) | 0.692538 | 0.128662 |
from .input_components.OneChannel import OneChannel
from .input_components.TwoEmbChannel import TwoEmbChannel
from .input_components.SixChannel import SixChannel
from .input_components.OneChannel_DocLevel import OneChannel_DocLevel
from .middle_components.parallel_conv import NParallelConvOnePoolNFC
from .middle_components.parallel_size_joined_conv import NCrossSizeParallelConvNFC
from .middle_components.parallel_joined_conv import ParallelJoinedConv
from .middle_components.parallel_conv_DocLevel import NConvDocConvNFC
from .middle_components.inception_like import InceptionLike
from .middle_components.pure_rnn import PureRNN
from .output_components.pan_output import PANOutput
from .output_components.ml_output import MLOutput
class TextCNN:
"""
A CNN for text classification.
Uses an embedding layer, followed by a convolutional, max-pooling and softmax layer.
Works for both single label (PAN) and multilabel (ML) datasets
"""
def __init__(
self, data, document_length, sequence_length, num_classes, embedding_size, filter_sizes, num_filters,
input_component, middle_component,
l2_reg_lambda, dropout, batch_normalize, elu, fc):
word_vocab_size = len(data.vocab)
# input component
if input_component.endswith("One"):
self.input_comp = OneChannel(sequence_length, num_classes, word_vocab_size, embedding_size,
data.embed_matrix)
elif input_component.endswith("One_DocLevel"):
self.input_comp = OneChannel_DocLevel(document_length, sequence_length, num_classes, word_vocab_size,
embedding_size, data.embed_matrix)
elif input_component.endswith("2CH"):
self.input_comp = TwoEmbChannel(sequence_length, num_classes, word_vocab_size, embedding_size,
data.embed_matrix, data.embed_matrix_w2v)
elif input_component.endswith("Six"):
# self.input_comp = SixChannel(sequence_length, num_classes, word_vocab_size, embedding_size,
# pref2_vocab_size, pref3_vocab_size, suff2_vocab_size, suff3_vocab_size,
# pos_vocab_size,
# init_embedding_glv) # TODO
self.input_pref2 = self.input_comp.input_pref2
self.input_pref3 = self.input_comp.input_pref3
self.input_suff2 = self.input_comp.input_suff2
self.input_suff3 = self.input_comp.input_suff3
self.input_pos = self.input_comp.input_pos
elif input_component.endswith("PAN11"):
self.input_comp = TwoEmbChannel(sequence_length, num_classes, word_vocab_size, embedding_size,
data.embed_matrix, data.embed_matrix_w2v)
else:
raise NotImplementedError
self.input_x = self.input_comp.input_x
self.input_y = self.input_comp.input_y
self.dropout_keep_prob = self.input_comp.dropout_keep_prob
# middle component
if middle_component == 'NParallelConvOnePoolNFC':
self.middle_comp = NParallelConvOnePoolNFC(sequence_length, embedding_size, filter_sizes, num_filters,
previous_component=self.input_comp, dropout=dropout,
batch_normalize=batch_normalize, elu=elu, n_conv=n_conv, fc=fc)
elif middle_component == 'ParallelJoinedConv':
self.middle_comp = ParallelJoinedConv(sequence_length, embedding_size, filter_sizes, num_filters,
previous_component=self.input_comp, dropout=dropout,
batch_normalize=batch_normalize, elu=elu, n_conv=n_conv,
fc=fc)
elif middle_component == 'NCrossSizeParallelConvNFC':
self.middle_comp = NCrossSizeParallelConvNFC(sequence_length, embedding_size, filter_sizes, num_filters,
previous_component=self.input_comp, dropout=dropout,
batch_normalize=batch_normalize, elu=elu,
fc=fc, l2_reg_lambda=l2_reg_lambda)
elif middle_component == "NConvDocConvNFC":
self.middle_comp = NConvDocConvNFC(document_length, sequence_length, embedding_size, filter_sizes,
num_filters,
previous_component=self.input_comp, dropout=dropout,
batch_normalize=batch_normalize, elu=elu,
fc=fc)
elif middle_component == 'InceptionLike':
self.middle_comp = InceptionLike(sequence_length, embedding_size, filter_sizes, num_filters,
previous_component=self.input_comp, dropout=dropout,
batch_normalize=batch_normalize, elu=elu,
fc=fc)
elif middle_component == 'PureRNN':
self.middle_comp = PureRNN(sequence_length, embedding_size, previous_component=self.input_comp,
num_layers=1, bidirectional=False, attn_length=50, attn_size=50,
attn_vec_size=50)
else:
raise NotImplementedError
self.is_training = self.middle_comp.is_training
prev_layer, num_nodes = self.middle_comp.get_last_layer_info()
l2_sum = self.middle_comp.l2_sum
# output component
if "ML" in data.name:
output = MLOutput(self.input_comp.input_y, prev_layer, num_nodes, num_classes, l2_sum, l2_reg_lambda)
elif "PAN" in data.name:
output = PANOutput(self.input_comp.input_y, prev_layer, num_nodes, num_classes, l2_sum, l2_reg_lambda)
# self.rate_percentage = output.rate_percentage
else:
raise NotImplementedError
self.loss = output.loss
self.scores = output.scores
self.predictions = output.predictions
self.accuracy = output.accuracy | networks/cnn.py | from .input_components.OneChannel import OneChannel
from .input_components.TwoEmbChannel import TwoEmbChannel
from .input_components.SixChannel import SixChannel
from .input_components.OneChannel_DocLevel import OneChannel_DocLevel
from .middle_components.parallel_conv import NParallelConvOnePoolNFC
from .middle_components.parallel_size_joined_conv import NCrossSizeParallelConvNFC
from .middle_components.parallel_joined_conv import ParallelJoinedConv
from .middle_components.parallel_conv_DocLevel import NConvDocConvNFC
from .middle_components.inception_like import InceptionLike
from .middle_components.pure_rnn import PureRNN
from .output_components.pan_output import PANOutput
from .output_components.ml_output import MLOutput
class TextCNN:
"""
A CNN for text classification.
Uses an embedding layer, followed by a convolutional, max-pooling and softmax layer.
Works for both single label (PAN) and multilabel (ML) datasets
"""
def __init__(
self, data, document_length, sequence_length, num_classes, embedding_size, filter_sizes, num_filters,
input_component, middle_component,
l2_reg_lambda, dropout, batch_normalize, elu, fc):
word_vocab_size = len(data.vocab)
# input component
if input_component.endswith("One"):
self.input_comp = OneChannel(sequence_length, num_classes, word_vocab_size, embedding_size,
data.embed_matrix)
elif input_component.endswith("One_DocLevel"):
self.input_comp = OneChannel_DocLevel(document_length, sequence_length, num_classes, word_vocab_size,
embedding_size, data.embed_matrix)
elif input_component.endswith("2CH"):
self.input_comp = TwoEmbChannel(sequence_length, num_classes, word_vocab_size, embedding_size,
data.embed_matrix, data.embed_matrix_w2v)
elif input_component.endswith("Six"):
# self.input_comp = SixChannel(sequence_length, num_classes, word_vocab_size, embedding_size,
# pref2_vocab_size, pref3_vocab_size, suff2_vocab_size, suff3_vocab_size,
# pos_vocab_size,
# init_embedding_glv) # TODO
self.input_pref2 = self.input_comp.input_pref2
self.input_pref3 = self.input_comp.input_pref3
self.input_suff2 = self.input_comp.input_suff2
self.input_suff3 = self.input_comp.input_suff3
self.input_pos = self.input_comp.input_pos
elif input_component.endswith("PAN11"):
self.input_comp = TwoEmbChannel(sequence_length, num_classes, word_vocab_size, embedding_size,
data.embed_matrix, data.embed_matrix_w2v)
else:
raise NotImplementedError
self.input_x = self.input_comp.input_x
self.input_y = self.input_comp.input_y
self.dropout_keep_prob = self.input_comp.dropout_keep_prob
# middle component
if middle_component == 'NParallelConvOnePoolNFC':
self.middle_comp = NParallelConvOnePoolNFC(sequence_length, embedding_size, filter_sizes, num_filters,
previous_component=self.input_comp, dropout=dropout,
batch_normalize=batch_normalize, elu=elu, n_conv=n_conv, fc=fc)
elif middle_component == 'ParallelJoinedConv':
self.middle_comp = ParallelJoinedConv(sequence_length, embedding_size, filter_sizes, num_filters,
previous_component=self.input_comp, dropout=dropout,
batch_normalize=batch_normalize, elu=elu, n_conv=n_conv,
fc=fc)
elif middle_component == 'NCrossSizeParallelConvNFC':
self.middle_comp = NCrossSizeParallelConvNFC(sequence_length, embedding_size, filter_sizes, num_filters,
previous_component=self.input_comp, dropout=dropout,
batch_normalize=batch_normalize, elu=elu,
fc=fc, l2_reg_lambda=l2_reg_lambda)
elif middle_component == "NConvDocConvNFC":
self.middle_comp = NConvDocConvNFC(document_length, sequence_length, embedding_size, filter_sizes,
num_filters,
previous_component=self.input_comp, dropout=dropout,
batch_normalize=batch_normalize, elu=elu,
fc=fc)
elif middle_component == 'InceptionLike':
self.middle_comp = InceptionLike(sequence_length, embedding_size, filter_sizes, num_filters,
previous_component=self.input_comp, dropout=dropout,
batch_normalize=batch_normalize, elu=elu,
fc=fc)
elif middle_component == 'PureRNN':
self.middle_comp = PureRNN(sequence_length, embedding_size, previous_component=self.input_comp,
num_layers=1, bidirectional=False, attn_length=50, attn_size=50,
attn_vec_size=50)
else:
raise NotImplementedError
self.is_training = self.middle_comp.is_training
prev_layer, num_nodes = self.middle_comp.get_last_layer_info()
l2_sum = self.middle_comp.l2_sum
# output component
if "ML" in data.name:
output = MLOutput(self.input_comp.input_y, prev_layer, num_nodes, num_classes, l2_sum, l2_reg_lambda)
elif "PAN" in data.name:
output = PANOutput(self.input_comp.input_y, prev_layer, num_nodes, num_classes, l2_sum, l2_reg_lambda)
# self.rate_percentage = output.rate_percentage
else:
raise NotImplementedError
self.loss = output.loss
self.scores = output.scores
self.predictions = output.predictions
self.accuracy = output.accuracy | 0.675765 | 0.322046 |
from __future__ import absolute_import
from __future__ import unicode_literals
from __future__ import print_function
from __future__ import division
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import math
#https://github.com/ShichenLiu/CondenseNet
class LearnedGroupConv(nn.Module):
global_progress = 0.0
def __init__(self, in_channels, out_channels, kernel_size, stride=1,
padding=0, dilation=1, groups=1,
condense_factor=None, dropout_rate=0.):
super(LearnedGroupConv, self).__init__()
self.norm = nn.BatchNorm2d(in_channels)
self.relu = nn.ReLU(inplace=True)
self.dropout_rate = dropout_rate
if self.dropout_rate > 0:
self.drop = nn.Dropout(dropout_rate, inplace=False)
self.conv = nn.Conv2d(in_channels, out_channels, kernel_size, stride,
padding, dilation, groups=1, bias=False)
self.in_channels = in_channels
self.out_channels = out_channels
self.groups = groups
self.condense_factor = condense_factor
if self.condense_factor is None:
self.condense_factor = self.groups
### Parameters that should be carefully used
self.register_buffer('_count', torch.zeros(1))
self.register_buffer('_stage', torch.zeros(1))
self.register_buffer('_mask', torch.ones(self.conv.weight.size()))
### Check if arguments are valid
assert self.in_channels % self.groups == 0, "group number can not be divided by input channels"
assert self.in_channels % self.condense_factor == 0, "condensation factor can not be divided by input channels"
assert self.out_channels % self.groups == 0, "group number can not be divided by output channels"
def forward(self, x):
self._check_drop()
x = self.norm(x)
x = self.relu(x)
if self.dropout_rate > 0:
x = self.drop(x)
### Masked output
weight = self.conv.weight * self.mask
return F.conv2d(x, weight, None, self.conv.stride,
self.conv.padding, self.conv.dilation, 1)
def _check_drop(self):
progress = LearnedGroupConv.global_progress
delta = 0
### Get current stage
for i in range(self.condense_factor - 1):
if progress * 2 < (i + 1) / (self.condense_factor - 1):
stage = i
break
else:
stage = self.condense_factor - 1
### Check for dropping
if not self._reach_stage(stage):
self.stage = stage
delta = self.in_channels // self.condense_factor
if delta > 0:
self._dropping(delta)
return
def _dropping(self, delta):
weight = self.conv.weight * self.mask
### Sum up all kernels
### Assume only apply to 1x1 conv to speed up
assert weight.size()[-1] == 1
weight = weight.abs().squeeze()
assert weight.size()[0] == self.out_channels
assert weight.size()[1] == self.in_channels
d_out = self.out_channels // self.groups
### Shuffle weight
weight = weight.view(d_out, self.groups, self.in_channels)
weight = weight.transpose(0, 1).contiguous()
weight = weight.view(self.out_channels, self.in_channels)
### Sort and drop
for i in range(self.groups):
wi = weight[i * d_out:(i + 1) * d_out, :]
### Take corresponding delta index
di = wi.sum(0).sort()[1][self.count:self.count + delta]
for d in di.data:
self._mask[i::self.groups, d, :, :].fill_(0)
self.count = self.count + delta
@property
def count(self):
return int(self._count[0])
@count.setter
def count(self, val):
self._count.fill_(val)
@property
def stage(self):
return int(self._stage[0])
@stage.setter
def stage(self, val):
self._stage.fill_(val)
@property
def mask(self):
return Variable(self._mask)
def _reach_stage(self, stage):
return (self._stage >= stage).all()
@property
def lasso_loss(self):
if self._reach_stage(self.groups - 1):
return 0
weight = self.conv.weight * self.mask
### Assume only apply to 1x1 conv to speed up
assert weight.size()[-1] == 1
weight = weight.squeeze().pow(2)
d_out = self.out_channels // self.groups
### Shuffle weight
weight = weight.view(d_out, self.groups, self.in_channels)
weight = weight.sum(0).clamp(min=1e-6).sqrt()
return weight.sum()
def ShuffleLayer(x, groups):
batchsize, num_channels, height, width = x.data.size()
channels_per_group = num_channels // groups
### reshape
x = x.view(batchsize, groups,
channels_per_group, height, width)
### transpose
x = torch.transpose(x, 1, 2).contiguous()
### flatten
x = x.view(batchsize, -1, height, width)
return x
class CondensingLinear(nn.Module):
def __init__(self, model, drop_rate=0.5):
super(CondensingLinear, self).__init__()
self.in_features = int(model.in_features*drop_rate)
self.out_features = model.out_features
self.linear = nn.Linear(self.in_features, self.out_features)
self.register_buffer('index', torch.LongTensor(self.in_features))
_, index = model.weight.data.abs().sum(0).sort()
index = index[model.in_features-self.in_features:]
self.linear.bias.data = model.bias.data.clone()
for i in range(self.in_features):
self.index[i] = index[i]
self.linear.weight.data[:, i] = model.weight.data[:, index[i]]
def forward(self, x):
x = torch.index_select(x, 1, Variable(self.index))
x = self.linear(x)
return x
class CondensingConv(nn.Module):
def __init__(self, model):
super(CondensingConv, self).__init__()
self.in_channels = model.conv.in_channels \
* model.groups // model.condense_factor
self.out_channels = model.conv.out_channels
self.groups = model.groups
self.condense_factor = model.condense_factor
self.norm = nn.BatchNorm2d(self.in_channels)
self.relu = nn.ReLU(inplace=True)
self.conv = nn.Conv2d(self.in_channels, self.out_channels,
kernel_size=model.conv.kernel_size,
padding=model.conv.padding,
groups=self.groups,
bias=False,
stride=model.conv.stride)
self.register_buffer('index', torch.LongTensor(self.in_channels))
index = 0
mask = model._mask.mean(-1).mean(-1)
for i in range(self.groups):
for j in range(model.conv.in_channels):
if index < (self.in_channels // self.groups) * (i + 1) \
and mask[i, j] == 1:
for k in range(self.out_channels // self.groups):
idx_i = int(k + i * (self.out_channels // self.groups))
idx_j = index % (self.in_channels // self.groups)
self.conv.weight.data[idx_i, idx_j, :, :] = \
model.conv.weight.data[int(i + k * self.groups), j, :, :]
self.norm.weight.data[index] = model.norm.weight.data[j]
self.norm.bias.data[index] = model.norm.bias.data[j]
self.norm.running_mean[index] = model.norm.running_mean[j]
self.norm.running_var[index] = model.norm.running_var[j]
self.index[index] = j
index += 1
def forward(self, x):
x = torch.index_select(x, 1, Variable(self.index))
x = self.norm(x)
x = self.relu(x)
x = self.conv(x)
x = ShuffleLayer(x, self.groups)
return x
class CondenseLinear(nn.Module):
def __init__(self, in_features, out_features, drop_rate=0.5):
super(CondenseLinear, self).__init__()
self.in_features = int(in_features*drop_rate)
self.out_features = out_features
self.linear = nn.Linear(self.in_features, self.out_features)
self.register_buffer('index', torch.LongTensor(self.in_features))
def forward(self, x):
x = torch.index_select(x, 1, Variable(self.index))
x = self.linear(x)
return x
class CondenseConv(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size,
stride=1, padding=0, groups=1):
super(CondenseConv, self).__init__()
self.in_channels = in_channels
self.out_channels = out_channels
self.groups = groups
self.norm = nn.BatchNorm2d(self.in_channels)
self.relu = nn.ReLU(inplace=True)
self.conv = nn.Conv2d(self.in_channels, self.out_channels,
kernel_size=kernel_size,
stride=stride,
padding=padding,
groups=self.groups,
bias=False)
self.register_buffer('index', torch.LongTensor(self.in_channels))
self.index.fill_(0)
def forward(self, x):
x = torch.index_select(x, 1, Variable(self.index))
x = self.norm(x)
x = self.relu(x)
x = self.conv(x)
x = ShuffleLayer(x, self.groups)
return x
class Conv(nn.Sequential):
def __init__(self, in_channels, out_channels, kernel_size,
stride=1, padding=0, groups=1):
super(Conv, self).__init__()
self.add_module('norm', nn.BatchNorm2d(in_channels))
self.add_module('relu', nn.ReLU(inplace=True))
self.add_module('conv', nn.Conv2d(in_channels, out_channels,
kernel_size=kernel_size,
stride=stride,
padding=padding, bias=False,
groups=groups))
__all__ = ['CondenseNet']
class _DenseLayer(nn.Module):
def __init__(self, in_channels, growth_rate, args):
super(_DenseLayer, self).__init__()
self.group_1x1 = args.group_1x1
self.group_3x3 = args.group_3x3
### 1x1 conv i --> b*k
self.conv_1 = LearnedGroupConv(in_channels, args.bottleneck * growth_rate,
kernel_size=1, groups=self.group_1x1,
condense_factor=args.condense_factor,
dropout_rate=args.dropout_rate)
### 3x3 conv b*k --> k
self.conv_2 = Conv(args.bottleneck * growth_rate, growth_rate,
kernel_size=3, padding=1, groups=self.group_3x3)
def forward(self, x):
x_ = x
x = self.conv_1(x)
x = self.conv_2(x)
return torch.cat([x_, x], 1)
class _DenseBlock(nn.Sequential):
def __init__(self, num_layers, in_channels, growth_rate, args):
super(_DenseBlock, self).__init__()
for i in range(num_layers):
layer = _DenseLayer(in_channels + i * growth_rate, growth_rate, args)
self.add_module('denselayer_%d' % (i + 1), layer)
class _Transition(nn.Module):
def __init__(self, in_channels, args):
super(_Transition, self).__init__()
self.pool = nn.AvgPool2d(kernel_size=2, stride=2)
def forward(self, x):
x = self.pool(x)
return x
class CondenseNet(nn.Module):
def __init__(self, args):
super(CondenseNet, self).__init__()
self.stages = args.stages
self.growth = args.growth
assert len(self.stages) == len(self.growth)
self.args = args
self.progress = 0.0
if args.data in ['cifar10', 'cifar100']:
self.init_stride = 1
self.pool_size = 8
else:
self.init_stride = 2
self.pool_size = 7
self.features = nn.Sequential()
### Initial nChannels should be 3
self.num_features = 2 * self.growth[0]
### Dense-block 1 (224x224)
self.features.add_module('init_conv', nn.Conv2d(3, self.num_features,
kernel_size=3,
stride=self.init_stride,
padding=1,
bias=False))
for i in range(len(self.stages)):
### Dense-block i
self.add_block(i)
### Linear layer
self.classifier = nn.Linear(self.num_features, args.num_classes)
### initialize
for m in self.modules():
if isinstance(m, nn.Conv2d):
n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels
m.weight.data.normal_(0, math.sqrt(2. / n))
elif isinstance(m, nn.BatchNorm2d):
m.weight.data.fill_(1)
m.bias.data.zero_()
elif isinstance(m, nn.Linear):
m.bias.data.zero_()
return
def add_block(self, i):
### Check if ith is the last one
last = (i == len(self.stages) - 1)
block = _DenseBlock(
num_layers=self.stages[i],
in_channels=self.num_features,
growth_rate=self.growth[i],
args=self.args,
)
self.features.add_module('denseblock_%d' % (i + 1), block)
self.num_features += self.stages[i] * self.growth[i]
if not last:
trans = _Transition(in_channels=self.num_features,
args=self.args)
self.features.add_module('transition_%d' % (i + 1), trans)
else:
self.features.add_module('norm_last',
nn.BatchNorm2d(self.num_features))
self.features.add_module('relu_last',
nn.ReLU(inplace=True))
self.features.add_module('pool_last',
nn.AvgPool2d(self.pool_size))
def forward(self, x, progress=None):
if progress:
LearnedGroupConv.global_progress = progress
features = self.features(x)
out = features.view(features.size(0), -1)
out = self.classifier(out)
return out | modles/condensenet.py | from __future__ import absolute_import
from __future__ import unicode_literals
from __future__ import print_function
from __future__ import division
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import math
#https://github.com/ShichenLiu/CondenseNet
class LearnedGroupConv(nn.Module):
global_progress = 0.0
def __init__(self, in_channels, out_channels, kernel_size, stride=1,
padding=0, dilation=1, groups=1,
condense_factor=None, dropout_rate=0.):
super(LearnedGroupConv, self).__init__()
self.norm = nn.BatchNorm2d(in_channels)
self.relu = nn.ReLU(inplace=True)
self.dropout_rate = dropout_rate
if self.dropout_rate > 0:
self.drop = nn.Dropout(dropout_rate, inplace=False)
self.conv = nn.Conv2d(in_channels, out_channels, kernel_size, stride,
padding, dilation, groups=1, bias=False)
self.in_channels = in_channels
self.out_channels = out_channels
self.groups = groups
self.condense_factor = condense_factor
if self.condense_factor is None:
self.condense_factor = self.groups
### Parameters that should be carefully used
self.register_buffer('_count', torch.zeros(1))
self.register_buffer('_stage', torch.zeros(1))
self.register_buffer('_mask', torch.ones(self.conv.weight.size()))
### Check if arguments are valid
assert self.in_channels % self.groups == 0, "group number can not be divided by input channels"
assert self.in_channels % self.condense_factor == 0, "condensation factor can not be divided by input channels"
assert self.out_channels % self.groups == 0, "group number can not be divided by output channels"
def forward(self, x):
self._check_drop()
x = self.norm(x)
x = self.relu(x)
if self.dropout_rate > 0:
x = self.drop(x)
### Masked output
weight = self.conv.weight * self.mask
return F.conv2d(x, weight, None, self.conv.stride,
self.conv.padding, self.conv.dilation, 1)
def _check_drop(self):
progress = LearnedGroupConv.global_progress
delta = 0
### Get current stage
for i in range(self.condense_factor - 1):
if progress * 2 < (i + 1) / (self.condense_factor - 1):
stage = i
break
else:
stage = self.condense_factor - 1
### Check for dropping
if not self._reach_stage(stage):
self.stage = stage
delta = self.in_channels // self.condense_factor
if delta > 0:
self._dropping(delta)
return
def _dropping(self, delta):
weight = self.conv.weight * self.mask
### Sum up all kernels
### Assume only apply to 1x1 conv to speed up
assert weight.size()[-1] == 1
weight = weight.abs().squeeze()
assert weight.size()[0] == self.out_channels
assert weight.size()[1] == self.in_channels
d_out = self.out_channels // self.groups
### Shuffle weight
weight = weight.view(d_out, self.groups, self.in_channels)
weight = weight.transpose(0, 1).contiguous()
weight = weight.view(self.out_channels, self.in_channels)
### Sort and drop
for i in range(self.groups):
wi = weight[i * d_out:(i + 1) * d_out, :]
### Take corresponding delta index
di = wi.sum(0).sort()[1][self.count:self.count + delta]
for d in di.data:
self._mask[i::self.groups, d, :, :].fill_(0)
self.count = self.count + delta
@property
def count(self):
return int(self._count[0])
@count.setter
def count(self, val):
self._count.fill_(val)
@property
def stage(self):
return int(self._stage[0])
@stage.setter
def stage(self, val):
self._stage.fill_(val)
@property
def mask(self):
return Variable(self._mask)
def _reach_stage(self, stage):
return (self._stage >= stage).all()
@property
def lasso_loss(self):
if self._reach_stage(self.groups - 1):
return 0
weight = self.conv.weight * self.mask
### Assume only apply to 1x1 conv to speed up
assert weight.size()[-1] == 1
weight = weight.squeeze().pow(2)
d_out = self.out_channels // self.groups
### Shuffle weight
weight = weight.view(d_out, self.groups, self.in_channels)
weight = weight.sum(0).clamp(min=1e-6).sqrt()
return weight.sum()
def ShuffleLayer(x, groups):
batchsize, num_channels, height, width = x.data.size()
channels_per_group = num_channels // groups
### reshape
x = x.view(batchsize, groups,
channels_per_group, height, width)
### transpose
x = torch.transpose(x, 1, 2).contiguous()
### flatten
x = x.view(batchsize, -1, height, width)
return x
class CondensingLinear(nn.Module):
def __init__(self, model, drop_rate=0.5):
super(CondensingLinear, self).__init__()
self.in_features = int(model.in_features*drop_rate)
self.out_features = model.out_features
self.linear = nn.Linear(self.in_features, self.out_features)
self.register_buffer('index', torch.LongTensor(self.in_features))
_, index = model.weight.data.abs().sum(0).sort()
index = index[model.in_features-self.in_features:]
self.linear.bias.data = model.bias.data.clone()
for i in range(self.in_features):
self.index[i] = index[i]
self.linear.weight.data[:, i] = model.weight.data[:, index[i]]
def forward(self, x):
x = torch.index_select(x, 1, Variable(self.index))
x = self.linear(x)
return x
class CondensingConv(nn.Module):
def __init__(self, model):
super(CondensingConv, self).__init__()
self.in_channels = model.conv.in_channels \
* model.groups // model.condense_factor
self.out_channels = model.conv.out_channels
self.groups = model.groups
self.condense_factor = model.condense_factor
self.norm = nn.BatchNorm2d(self.in_channels)
self.relu = nn.ReLU(inplace=True)
self.conv = nn.Conv2d(self.in_channels, self.out_channels,
kernel_size=model.conv.kernel_size,
padding=model.conv.padding,
groups=self.groups,
bias=False,
stride=model.conv.stride)
self.register_buffer('index', torch.LongTensor(self.in_channels))
index = 0
mask = model._mask.mean(-1).mean(-1)
for i in range(self.groups):
for j in range(model.conv.in_channels):
if index < (self.in_channels // self.groups) * (i + 1) \
and mask[i, j] == 1:
for k in range(self.out_channels // self.groups):
idx_i = int(k + i * (self.out_channels // self.groups))
idx_j = index % (self.in_channels // self.groups)
self.conv.weight.data[idx_i, idx_j, :, :] = \
model.conv.weight.data[int(i + k * self.groups), j, :, :]
self.norm.weight.data[index] = model.norm.weight.data[j]
self.norm.bias.data[index] = model.norm.bias.data[j]
self.norm.running_mean[index] = model.norm.running_mean[j]
self.norm.running_var[index] = model.norm.running_var[j]
self.index[index] = j
index += 1
def forward(self, x):
x = torch.index_select(x, 1, Variable(self.index))
x = self.norm(x)
x = self.relu(x)
x = self.conv(x)
x = ShuffleLayer(x, self.groups)
return x
class CondenseLinear(nn.Module):
def __init__(self, in_features, out_features, drop_rate=0.5):
super(CondenseLinear, self).__init__()
self.in_features = int(in_features*drop_rate)
self.out_features = out_features
self.linear = nn.Linear(self.in_features, self.out_features)
self.register_buffer('index', torch.LongTensor(self.in_features))
def forward(self, x):
x = torch.index_select(x, 1, Variable(self.index))
x = self.linear(x)
return x
class CondenseConv(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size,
stride=1, padding=0, groups=1):
super(CondenseConv, self).__init__()
self.in_channels = in_channels
self.out_channels = out_channels
self.groups = groups
self.norm = nn.BatchNorm2d(self.in_channels)
self.relu = nn.ReLU(inplace=True)
self.conv = nn.Conv2d(self.in_channels, self.out_channels,
kernel_size=kernel_size,
stride=stride,
padding=padding,
groups=self.groups,
bias=False)
self.register_buffer('index', torch.LongTensor(self.in_channels))
self.index.fill_(0)
def forward(self, x):
x = torch.index_select(x, 1, Variable(self.index))
x = self.norm(x)
x = self.relu(x)
x = self.conv(x)
x = ShuffleLayer(x, self.groups)
return x
class Conv(nn.Sequential):
def __init__(self, in_channels, out_channels, kernel_size,
stride=1, padding=0, groups=1):
super(Conv, self).__init__()
self.add_module('norm', nn.BatchNorm2d(in_channels))
self.add_module('relu', nn.ReLU(inplace=True))
self.add_module('conv', nn.Conv2d(in_channels, out_channels,
kernel_size=kernel_size,
stride=stride,
padding=padding, bias=False,
groups=groups))
__all__ = ['CondenseNet']
class _DenseLayer(nn.Module):
def __init__(self, in_channels, growth_rate, args):
super(_DenseLayer, self).__init__()
self.group_1x1 = args.group_1x1
self.group_3x3 = args.group_3x3
### 1x1 conv i --> b*k
self.conv_1 = LearnedGroupConv(in_channels, args.bottleneck * growth_rate,
kernel_size=1, groups=self.group_1x1,
condense_factor=args.condense_factor,
dropout_rate=args.dropout_rate)
### 3x3 conv b*k --> k
self.conv_2 = Conv(args.bottleneck * growth_rate, growth_rate,
kernel_size=3, padding=1, groups=self.group_3x3)
def forward(self, x):
x_ = x
x = self.conv_1(x)
x = self.conv_2(x)
return torch.cat([x_, x], 1)
class _DenseBlock(nn.Sequential):
def __init__(self, num_layers, in_channels, growth_rate, args):
super(_DenseBlock, self).__init__()
for i in range(num_layers):
layer = _DenseLayer(in_channels + i * growth_rate, growth_rate, args)
self.add_module('denselayer_%d' % (i + 1), layer)
class _Transition(nn.Module):
def __init__(self, in_channels, args):
super(_Transition, self).__init__()
self.pool = nn.AvgPool2d(kernel_size=2, stride=2)
def forward(self, x):
x = self.pool(x)
return x
class CondenseNet(nn.Module):
def __init__(self, args):
super(CondenseNet, self).__init__()
self.stages = args.stages
self.growth = args.growth
assert len(self.stages) == len(self.growth)
self.args = args
self.progress = 0.0
if args.data in ['cifar10', 'cifar100']:
self.init_stride = 1
self.pool_size = 8
else:
self.init_stride = 2
self.pool_size = 7
self.features = nn.Sequential()
### Initial nChannels should be 3
self.num_features = 2 * self.growth[0]
### Dense-block 1 (224x224)
self.features.add_module('init_conv', nn.Conv2d(3, self.num_features,
kernel_size=3,
stride=self.init_stride,
padding=1,
bias=False))
for i in range(len(self.stages)):
### Dense-block i
self.add_block(i)
### Linear layer
self.classifier = nn.Linear(self.num_features, args.num_classes)
### initialize
for m in self.modules():
if isinstance(m, nn.Conv2d):
n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels
m.weight.data.normal_(0, math.sqrt(2. / n))
elif isinstance(m, nn.BatchNorm2d):
m.weight.data.fill_(1)
m.bias.data.zero_()
elif isinstance(m, nn.Linear):
m.bias.data.zero_()
return
def add_block(self, i):
### Check if ith is the last one
last = (i == len(self.stages) - 1)
block = _DenseBlock(
num_layers=self.stages[i],
in_channels=self.num_features,
growth_rate=self.growth[i],
args=self.args,
)
self.features.add_module('denseblock_%d' % (i + 1), block)
self.num_features += self.stages[i] * self.growth[i]
if not last:
trans = _Transition(in_channels=self.num_features,
args=self.args)
self.features.add_module('transition_%d' % (i + 1), trans)
else:
self.features.add_module('norm_last',
nn.BatchNorm2d(self.num_features))
self.features.add_module('relu_last',
nn.ReLU(inplace=True))
self.features.add_module('pool_last',
nn.AvgPool2d(self.pool_size))
def forward(self, x, progress=None):
if progress:
LearnedGroupConv.global_progress = progress
features = self.features(x)
out = features.view(features.size(0), -1)
out = self.classifier(out)
return out | 0.939157 | 0.36659 |
import random
import json
from pygame.locals import *
import os
import pygame
import pygameMenu
from pygameMenu.locals import *
WIDTH = 900
HEIGHT = 700
FPS = 60
pygame.init()
os.environ['SDL_VIDEO_CENTERED'] = '1'
pygame.mixer.init()
screen = pygame.display.set_mode((WIDTH, HEIGHT))
pygame.display.set_caption("The Defender")
clock = pygame.time.Clock()
font_name = pygame.font.match_font('arial')
def pontuacao(surf, text,size,x,y):
font = pygame.font.Font(font_name,size)
text_surface = font.render(text,True, (255,0,0))
text_rect = text_surface.get_rect()
text_rect.midtop = (x,y)
surf.blit(text_surface,text_rect)
class Score(pygame.sprite.Sprite):
def __init__(self):
pygame.sprite.Sprite.__init__(self)
self.score = 0
self.dificuldade =1
def update(self):
self.score += 1
if self.score ==10:
self.dificuldade = 4
print(self.dificuldade)
if self.score ==30:
self.dificuldade = 6
print(self.dificuldade)
if self.score == 70:
self.dificuldade = 8
print(self.dificuldade)
if self.score == 100:
self.dificuldade = 10
print(self.dificuldade)
if self.score == 130:
self.dificuldade = 14
print(self.dificuldade)
if self.score == 200:
self.dificuldade = 18
print(self.dificuldade)
class Player(pygame.sprite.Sprite):
def __init__(self):
pygame.sprite.Sprite.__init__(self)
self.image = pygame.image.load('oldplayer.PNG')
self.rect = self.image.get_rect()
self.rect.centerx = WIDTH / 2
self.rect.bottom = HEIGHT - 10
self.speedx = 0
self.col0 = 0
def update(self):
self.speedx = 0
keystate = pygame.key.get_pressed()
if keystate[pygame.K_LEFT]:
self.speedx = -8
if keystate[pygame.K_RIGHT]:
self.speedx = 8
self.rect.x += self.speedx
if self.rect.right > WIDTH:
self.rect.right = WIDTH
if self.rect.left < 0:
self.rect.left = 0
def shoot(self):
pts = Score()
if pts.score == 200:
if self.col0 == 0:
bullet = Bullet(self.rect.centerx, self.rect.top)
all_sprites.add(bullet)
bullets.add(bullet)
self.col0 = 100
else:
bullet = Bullet(self.rect.centerx, self.rect.top)
all_sprites.add(bullet)
bullets.add(bullet)
if self.col0 > 0 :
self.col0 -=1
class Mob(pygame.sprite.Sprite):
def __init__(self):
pygame.sprite.Sprite.__init__(self)
self.image = pygame.image.load('inimigo.PNG')
self.image= pygame .transform.scale(self.image,(120,80))
self.rect = self.image.get_rect()
self.rect.x = random.randrange(100 , 800)
self.rect.y = random.randrange(-100, -40)
self.speedy = random.randrange(1, 4)
if self.rect.x < WIDTH/2:
self.speedx = random.randrange(0, 1)
else:
self.speedx = random.randrange(-1, 0)
def update(self):
self.rect.x += self.speedx
self.rect.y += self.speedy
if self.rect.top > HEIGHT - 10 or self.rect.left < -25 or self.rect.right > WIDTH + 20:
self.rect.y = random.randrange(-100, -40)
self.speedy = random.randrange(1, 2)
class Bullet(pygame.sprite.Sprite):
def __init__(self, x, y):
pygame.sprite.Sprite.__init__(self)
self.image = pygame.image.load('tiro.PNG')
self.rect = self.image.get_rect()
self.rect.bottom = y
self.rect.centerx = x
self.speedy = -10
def update(self):
self.rect.y += self.speedy
if self.rect.bottom < 0:
self.kill()
audio=pygame.mixer.Sound('boom.wav')
audio_tiro= pygame.mixer.Sound('disparo.wav')
audio_jogo = pygame.mixer.Sound('tema.wav')
audio_gameOver = pygame.mixer.Sound('gameOver.wav')
font = pygame.font.get_default_font()
font2= pygame.font.SysFont(font,70)
pygame.font.init()
try:
abre=open('pontuação.json','r')
Mpts = json.load(abre)
abre.close()
except:
Mpts = 0
coracao = pygame.image.load('vida.PNG')
coracao = pygame.transform.scale(coracao,(30,20))
bg = pygame.image.load('fundo.PNG')
bg = pygame.transform.scale(bg,(WIDTH,HEIGHT))
all_sprites = pygame.sprite.Group()
mobs = pygame.sprite.Group()
bullets = pygame.sprite.Group()
player = Player()
all_sprites.add(player)
def jogo():
vida =3
score = 0
pts = Score()
running = True
col =0
col2 =0
audio_jogo.play(3)
while running:
if col2 == 0:
for i in range(pts.dificuldade):
m = Mob()
all_sprites.add(m)
mobs.add(m)
mobs.draw(screen)
col2 = 100
if pts.dificuldade == 8:
col2 = 150
if pts.dificuldade == 14:
col2 = 200
clock.tick(FPS)
for event in pygame.event.get():
if event.type == pygame.QUIT:
running = False
if pts.score == 200:
pygame.key.set_repeat(10,50)
press = pygame.key.get_pressed()
if col == 0:
if press[pygame.K_SPACE]:
audio_tiro.play()
player.shoot()
col = 1000
elif event.type == pygame.KEYDOWN:
if event.key == pygame.K_SPACE:
audio_tiro.play()
player.shoot()
all_sprites.update()
hits = pygame.sprite.groupcollide(mobs, bullets, True, True)
for hit in hits:
pts.update()
score = pts.score
hits = pygame.sprite.spritecollide(player, mobs, True)
for hit in hits:
audio.play()
if hits:
vida -= 1
if vida == 0:
if score > Mpts:
abre = open('pontuação.json','w')
abre.write(str(score))
abre.close()
running = False
audio_jogo.stop()
audio_gameOver.play(3)
show_go_screen(score,Mpts,)
if col >0:
col -=0.1
if col2 >0:
col2 -= 1
screen.blit(bg,(0,0))
screen.blit(coracao,(WIDTH/2 -400, 10))
all_sprites.draw(screen)
pontuacao(screen,"PONTUAÇÃO: ", 18, WIDTH/2 -100, 10)
pontuacao(screen, str(score),18,WIDTH/2 -30,10 )
pontuacao(screen,str(vida), 18, WIDTH/2 -360, 10)
pontuacao(screen,"MELHOR PONTUAÇÃO:", 18, WIDTH/2 +250, 10)
pontuacao(screen,str(Mpts), 18, WIDTH/2 +380, 10)
pygame.display.flip()
pygame.quit()
def draw_text(surf, text, size, x, y):
font = pygame.font.Font(font_name, size)
text_surface = font.render(text, True, (255,255,255))
text_rect = text_surface.get_rect()
text_rect.midtop = (x, y)
surf.blit(text_surface, text_rect)
def draw_gameOver(surf, text, size, x, y):
font = pygame.font.Font(font_name, size)
text_surface = font.render(text, True, (255,0,0))
text_rect = text_surface.get_rect()
text_rect.midtop = (x, y)
surf.blit(text_surface, text_rect)
def show_go_screen(score,Mpts):
screen.fill((0,0,0))
draw_gameOver(screen, 'Game Over',64,WIDTH/2,HEIGHT/4)
draw_text(screen, 'Pontuação',25,WIDTH/2 -100,HEIGHT/4 + 100)
draw_text(screen, str(score),25,WIDTH/2 -100,HEIGHT/4 + 150)
if score > Mpts:
draw_text(screen, 'Nova Melhor Pontuação',25,WIDTH/2 +100,HEIGHT/4 + 100)
draw_text(screen, str(score),25,WIDTH/2 +100,HEIGHT/4 + 150)
else:
draw_text(screen, 'Melhor Pontuação',25,WIDTH/2 +100,HEIGHT/4 + 100)
draw_text(screen, str(Mpts),25,WIDTH/2 +100,HEIGHT/4 + 150)
draw_text(screen, 'Precione Esc para sair!',18,WIDTH/2,HEIGHT/4 + 450)
draw_text(screen, 'Desenvolvido por: <NAME> e <NAME>',18,WIDTH/2 + 250,HEIGHT/4 + 500)
pygame.display.flip()
true = True
while true:
clock.tick(FPS)
for event in pygame.event.get():
if event.type == pygame.QUIT:
pygame.quit()
elif event.type == pygame.KEYDOWN:
if event.key == pygame.K_ESCAPE:
pygame.quit()
COLOR_BACKGROUND = (0, 0, 0)
COLOR_BLACK = (0, 0, 0)
COLOR_WHITE = (255, 255, 255)
FPS = 60.0
MENU_BACKGROUND_COLOR = (3, 64, 137)
WINDOW_SIZE = (WIDTH, HEIGHT)
# -----------------------------------------------------------------------------
# Init pygame
pygame.init()
os.environ['SDL_VIDEO_CENTERED'] = '1'
# Create pygame screen and objects
surface = pygame.display.set_mode(WINDOW_SIZE)
pygame.display.set_caption('MENU INICIAL')
clock = pygame.time.Clock()
dt = 1 / FPS
def play_function():
jogo()
main_menu.disable()
main_menu.reset(1)
while True:
clock.tick(60)
# Application events
events = pygame.event.get()
for e in events:
if e.type == QUIT:
exit()
elif e.type == KEYDOWN:
if e.key == K_ESCAPE and main_menu.is_disabled():
main_menu.enable()
return
main_menu.mainloop(events)
pygame.display.flip()
def main_background():
surface.fill(COLOR_BACKGROUND)
# PLAY MENU
play_menu= pygameMenu.Menu(surface,
bgfun=main_background,
color_selected=COLOR_WHITE,
font=pygameMenu.fonts.FONT_BEBAS,
font_color=COLOR_BLACK,
font_size=30,
menu_alpha=100,
menu_color=MENU_BACKGROUND_COLOR,
menu_height=int(WINDOW_SIZE[1]*1),
menu_width=int(WINDOW_SIZE[0] *1),
onclose=PYGAME_MENU_DISABLE_CLOSE,
option_shadow=False,
title='The defender',
window_height=WINDOW_SIZE[1],
window_width=WINDOW_SIZE[0]
)
play_menu.add_option('Iniciar', play_function)
play_menu.add_option('Retornar ao menu principal', PYGAME_MENU_BACK)
# MAIN MENU
main_menu = pygameMenu.Menu(surface,
bgfun=main_background,
color_selected=COLOR_WHITE,
font=pygameMenu.fonts.FONT_BEBAS,
font_color=COLOR_BLACK,
font_size=30,
menu_alpha=100,
menu_color=MENU_BACKGROUND_COLOR,
menu_height=int(WINDOW_SIZE[1] * 1),
menu_width=int(WINDOW_SIZE[0] * 1),
option_shadow= False,
title='The defender',
window_height=WINDOW_SIZE[1],
window_width=WINDOW_SIZE[0]
)
main_menu.add_option('Jogar', play_menu)
main_menu.add_option('Sair', PYGAME_MENU_EXIT)
# -----------------------------------------------------------------------------
# Main loop
def menu():
while True:
# Tick
clock.tick(60)
# Application events
events = pygame.event.get()
for event in events:
if event.type == QUIT:
exit()
# Main menu
main_menu.mainloop(events)
# Flip surface
pygame.display.flip()
menu() | The Defender.py | import random
import json
from pygame.locals import *
import os
import pygame
import pygameMenu
from pygameMenu.locals import *
WIDTH = 900
HEIGHT = 700
FPS = 60
pygame.init()
os.environ['SDL_VIDEO_CENTERED'] = '1'
pygame.mixer.init()
screen = pygame.display.set_mode((WIDTH, HEIGHT))
pygame.display.set_caption("The Defender")
clock = pygame.time.Clock()
font_name = pygame.font.match_font('arial')
def pontuacao(surf, text,size,x,y):
font = pygame.font.Font(font_name,size)
text_surface = font.render(text,True, (255,0,0))
text_rect = text_surface.get_rect()
text_rect.midtop = (x,y)
surf.blit(text_surface,text_rect)
class Score(pygame.sprite.Sprite):
def __init__(self):
pygame.sprite.Sprite.__init__(self)
self.score = 0
self.dificuldade =1
def update(self):
self.score += 1
if self.score ==10:
self.dificuldade = 4
print(self.dificuldade)
if self.score ==30:
self.dificuldade = 6
print(self.dificuldade)
if self.score == 70:
self.dificuldade = 8
print(self.dificuldade)
if self.score == 100:
self.dificuldade = 10
print(self.dificuldade)
if self.score == 130:
self.dificuldade = 14
print(self.dificuldade)
if self.score == 200:
self.dificuldade = 18
print(self.dificuldade)
class Player(pygame.sprite.Sprite):
def __init__(self):
pygame.sprite.Sprite.__init__(self)
self.image = pygame.image.load('oldplayer.PNG')
self.rect = self.image.get_rect()
self.rect.centerx = WIDTH / 2
self.rect.bottom = HEIGHT - 10
self.speedx = 0
self.col0 = 0
def update(self):
self.speedx = 0
keystate = pygame.key.get_pressed()
if keystate[pygame.K_LEFT]:
self.speedx = -8
if keystate[pygame.K_RIGHT]:
self.speedx = 8
self.rect.x += self.speedx
if self.rect.right > WIDTH:
self.rect.right = WIDTH
if self.rect.left < 0:
self.rect.left = 0
def shoot(self):
pts = Score()
if pts.score == 200:
if self.col0 == 0:
bullet = Bullet(self.rect.centerx, self.rect.top)
all_sprites.add(bullet)
bullets.add(bullet)
self.col0 = 100
else:
bullet = Bullet(self.rect.centerx, self.rect.top)
all_sprites.add(bullet)
bullets.add(bullet)
if self.col0 > 0 :
self.col0 -=1
class Mob(pygame.sprite.Sprite):
def __init__(self):
pygame.sprite.Sprite.__init__(self)
self.image = pygame.image.load('inimigo.PNG')
self.image= pygame .transform.scale(self.image,(120,80))
self.rect = self.image.get_rect()
self.rect.x = random.randrange(100 , 800)
self.rect.y = random.randrange(-100, -40)
self.speedy = random.randrange(1, 4)
if self.rect.x < WIDTH/2:
self.speedx = random.randrange(0, 1)
else:
self.speedx = random.randrange(-1, 0)
def update(self):
self.rect.x += self.speedx
self.rect.y += self.speedy
if self.rect.top > HEIGHT - 10 or self.rect.left < -25 or self.rect.right > WIDTH + 20:
self.rect.y = random.randrange(-100, -40)
self.speedy = random.randrange(1, 2)
class Bullet(pygame.sprite.Sprite):
def __init__(self, x, y):
pygame.sprite.Sprite.__init__(self)
self.image = pygame.image.load('tiro.PNG')
self.rect = self.image.get_rect()
self.rect.bottom = y
self.rect.centerx = x
self.speedy = -10
def update(self):
self.rect.y += self.speedy
if self.rect.bottom < 0:
self.kill()
audio=pygame.mixer.Sound('boom.wav')
audio_tiro= pygame.mixer.Sound('disparo.wav')
audio_jogo = pygame.mixer.Sound('tema.wav')
audio_gameOver = pygame.mixer.Sound('gameOver.wav')
font = pygame.font.get_default_font()
font2= pygame.font.SysFont(font,70)
pygame.font.init()
try:
abre=open('pontuação.json','r')
Mpts = json.load(abre)
abre.close()
except:
Mpts = 0
coracao = pygame.image.load('vida.PNG')
coracao = pygame.transform.scale(coracao,(30,20))
bg = pygame.image.load('fundo.PNG')
bg = pygame.transform.scale(bg,(WIDTH,HEIGHT))
all_sprites = pygame.sprite.Group()
mobs = pygame.sprite.Group()
bullets = pygame.sprite.Group()
player = Player()
all_sprites.add(player)
def jogo():
vida =3
score = 0
pts = Score()
running = True
col =0
col2 =0
audio_jogo.play(3)
while running:
if col2 == 0:
for i in range(pts.dificuldade):
m = Mob()
all_sprites.add(m)
mobs.add(m)
mobs.draw(screen)
col2 = 100
if pts.dificuldade == 8:
col2 = 150
if pts.dificuldade == 14:
col2 = 200
clock.tick(FPS)
for event in pygame.event.get():
if event.type == pygame.QUIT:
running = False
if pts.score == 200:
pygame.key.set_repeat(10,50)
press = pygame.key.get_pressed()
if col == 0:
if press[pygame.K_SPACE]:
audio_tiro.play()
player.shoot()
col = 1000
elif event.type == pygame.KEYDOWN:
if event.key == pygame.K_SPACE:
audio_tiro.play()
player.shoot()
all_sprites.update()
hits = pygame.sprite.groupcollide(mobs, bullets, True, True)
for hit in hits:
pts.update()
score = pts.score
hits = pygame.sprite.spritecollide(player, mobs, True)
for hit in hits:
audio.play()
if hits:
vida -= 1
if vida == 0:
if score > Mpts:
abre = open('pontuação.json','w')
abre.write(str(score))
abre.close()
running = False
audio_jogo.stop()
audio_gameOver.play(3)
show_go_screen(score,Mpts,)
if col >0:
col -=0.1
if col2 >0:
col2 -= 1
screen.blit(bg,(0,0))
screen.blit(coracao,(WIDTH/2 -400, 10))
all_sprites.draw(screen)
pontuacao(screen,"PONTUAÇÃO: ", 18, WIDTH/2 -100, 10)
pontuacao(screen, str(score),18,WIDTH/2 -30,10 )
pontuacao(screen,str(vida), 18, WIDTH/2 -360, 10)
pontuacao(screen,"MELHOR PONTUAÇÃO:", 18, WIDTH/2 +250, 10)
pontuacao(screen,str(Mpts), 18, WIDTH/2 +380, 10)
pygame.display.flip()
pygame.quit()
def draw_text(surf, text, size, x, y):
font = pygame.font.Font(font_name, size)
text_surface = font.render(text, True, (255,255,255))
text_rect = text_surface.get_rect()
text_rect.midtop = (x, y)
surf.blit(text_surface, text_rect)
def draw_gameOver(surf, text, size, x, y):
font = pygame.font.Font(font_name, size)
text_surface = font.render(text, True, (255,0,0))
text_rect = text_surface.get_rect()
text_rect.midtop = (x, y)
surf.blit(text_surface, text_rect)
def show_go_screen(score,Mpts):
screen.fill((0,0,0))
draw_gameOver(screen, 'Game Over',64,WIDTH/2,HEIGHT/4)
draw_text(screen, 'Pontuação',25,WIDTH/2 -100,HEIGHT/4 + 100)
draw_text(screen, str(score),25,WIDTH/2 -100,HEIGHT/4 + 150)
if score > Mpts:
draw_text(screen, 'Nova Melhor Pontuação',25,WIDTH/2 +100,HEIGHT/4 + 100)
draw_text(screen, str(score),25,WIDTH/2 +100,HEIGHT/4 + 150)
else:
draw_text(screen, 'Melhor Pontuação',25,WIDTH/2 +100,HEIGHT/4 + 100)
draw_text(screen, str(Mpts),25,WIDTH/2 +100,HEIGHT/4 + 150)
draw_text(screen, 'Precione Esc para sair!',18,WIDTH/2,HEIGHT/4 + 450)
draw_text(screen, 'Desenvolvido por: <NAME> e <NAME>',18,WIDTH/2 + 250,HEIGHT/4 + 500)
pygame.display.flip()
true = True
while true:
clock.tick(FPS)
for event in pygame.event.get():
if event.type == pygame.QUIT:
pygame.quit()
elif event.type == pygame.KEYDOWN:
if event.key == pygame.K_ESCAPE:
pygame.quit()
COLOR_BACKGROUND = (0, 0, 0)
COLOR_BLACK = (0, 0, 0)
COLOR_WHITE = (255, 255, 255)
FPS = 60.0
MENU_BACKGROUND_COLOR = (3, 64, 137)
WINDOW_SIZE = (WIDTH, HEIGHT)
# -----------------------------------------------------------------------------
# Init pygame
pygame.init()
os.environ['SDL_VIDEO_CENTERED'] = '1'
# Create pygame screen and objects
surface = pygame.display.set_mode(WINDOW_SIZE)
pygame.display.set_caption('MENU INICIAL')
clock = pygame.time.Clock()
dt = 1 / FPS
def play_function():
jogo()
main_menu.disable()
main_menu.reset(1)
while True:
clock.tick(60)
# Application events
events = pygame.event.get()
for e in events:
if e.type == QUIT:
exit()
elif e.type == KEYDOWN:
if e.key == K_ESCAPE and main_menu.is_disabled():
main_menu.enable()
return
main_menu.mainloop(events)
pygame.display.flip()
def main_background():
surface.fill(COLOR_BACKGROUND)
# PLAY MENU
play_menu= pygameMenu.Menu(surface,
bgfun=main_background,
color_selected=COLOR_WHITE,
font=pygameMenu.fonts.FONT_BEBAS,
font_color=COLOR_BLACK,
font_size=30,
menu_alpha=100,
menu_color=MENU_BACKGROUND_COLOR,
menu_height=int(WINDOW_SIZE[1]*1),
menu_width=int(WINDOW_SIZE[0] *1),
onclose=PYGAME_MENU_DISABLE_CLOSE,
option_shadow=False,
title='The defender',
window_height=WINDOW_SIZE[1],
window_width=WINDOW_SIZE[0]
)
play_menu.add_option('Iniciar', play_function)
play_menu.add_option('Retornar ao menu principal', PYGAME_MENU_BACK)
# MAIN MENU
main_menu = pygameMenu.Menu(surface,
bgfun=main_background,
color_selected=COLOR_WHITE,
font=pygameMenu.fonts.FONT_BEBAS,
font_color=COLOR_BLACK,
font_size=30,
menu_alpha=100,
menu_color=MENU_BACKGROUND_COLOR,
menu_height=int(WINDOW_SIZE[1] * 1),
menu_width=int(WINDOW_SIZE[0] * 1),
option_shadow= False,
title='The defender',
window_height=WINDOW_SIZE[1],
window_width=WINDOW_SIZE[0]
)
main_menu.add_option('Jogar', play_menu)
main_menu.add_option('Sair', PYGAME_MENU_EXIT)
# -----------------------------------------------------------------------------
# Main loop
def menu():
while True:
# Tick
clock.tick(60)
# Application events
events = pygame.event.get()
for event in events:
if event.type == QUIT:
exit()
# Main menu
main_menu.mainloop(events)
# Flip surface
pygame.display.flip()
menu() | 0.139338 | 0.116362 |
from flask import Flask
from {{cookiecutter.app_name}} import auth, api
from {{cookiecutter.app_name}}.extensions import db, jwt, migrate, apispec
{%- if cookiecutter.use_celery == "yes"%}, celery{% endif%}
def create_app(testing=False, cli=False):
"""Application factory, used to create application"""
app = Flask("{{cookiecutter.app_name}}")
app.config.from_object("{{cookiecutter.app_name}}.config")
if testing is True:
app.config["TESTING"] = True
configure_extensions(app, cli)
configure_apispec(app)
register_blueprints(app)
{%- if cookiecutter.use_celery == "yes" %}
init_celery(app)
{%- endif %}
return app
def configure_extensions(app, cli):
"""configure flask extensions"""
db.init_app(app)
jwt.init_app(app)
if cli is True:
migrate.init_app(app, db)
def configure_apispec(app):
"""Configure APISpec for swagger support"""
apispec.init_app(app, security=[{"jwt": []}])
apispec.spec.components.security_scheme(
"jwt", {"type": "http", "scheme": "bearer", "bearerFormat": "JWT"}
)
apispec.spec.components.schema(
"PaginatedResult",
{
"properties": {
"total": {"type": "integer"},
"pages": {"type": "integer"},
"next": {"type": "string"},
"prev": {"type": "string"},
}
},
)
def register_blueprints(app):
"""register all blueprints for application"""
app.register_blueprint(auth.views.blueprint)
app.register_blueprint(api.views.blueprint)
{%- if cookiecutter.use_celery == "yes" %}
def init_celery(app=None):
app = app or create_app()
celery.conf.update(app.config.get("CELERY", {}))
class ContextTask(celery.Task):
"""Make celery tasks work with Flask app context"""
def __call__(self, *args, **kwargs):
with app.app_context():
return self.run(*args, **kwargs)
celery.Task = ContextTask
return celery
{%- endif %} | {{cookiecutter.project_name}}/{{cookiecutter.app_name}}/app.py | from flask import Flask
from {{cookiecutter.app_name}} import auth, api
from {{cookiecutter.app_name}}.extensions import db, jwt, migrate, apispec
{%- if cookiecutter.use_celery == "yes"%}, celery{% endif%}
def create_app(testing=False, cli=False):
"""Application factory, used to create application"""
app = Flask("{{cookiecutter.app_name}}")
app.config.from_object("{{cookiecutter.app_name}}.config")
if testing is True:
app.config["TESTING"] = True
configure_extensions(app, cli)
configure_apispec(app)
register_blueprints(app)
{%- if cookiecutter.use_celery == "yes" %}
init_celery(app)
{%- endif %}
return app
def configure_extensions(app, cli):
"""configure flask extensions"""
db.init_app(app)
jwt.init_app(app)
if cli is True:
migrate.init_app(app, db)
def configure_apispec(app):
"""Configure APISpec for swagger support"""
apispec.init_app(app, security=[{"jwt": []}])
apispec.spec.components.security_scheme(
"jwt", {"type": "http", "scheme": "bearer", "bearerFormat": "JWT"}
)
apispec.spec.components.schema(
"PaginatedResult",
{
"properties": {
"total": {"type": "integer"},
"pages": {"type": "integer"},
"next": {"type": "string"},
"prev": {"type": "string"},
}
},
)
def register_blueprints(app):
"""register all blueprints for application"""
app.register_blueprint(auth.views.blueprint)
app.register_blueprint(api.views.blueprint)
{%- if cookiecutter.use_celery == "yes" %}
def init_celery(app=None):
app = app or create_app()
celery.conf.update(app.config.get("CELERY", {}))
class ContextTask(celery.Task):
"""Make celery tasks work with Flask app context"""
def __call__(self, *args, **kwargs):
with app.app_context():
return self.run(*args, **kwargs)
celery.Task = ContextTask
return celery
{%- endif %} | 0.532425 | 0.093347 |
import copy
from cinderclient import exceptions as cinder_exp
import mock
from oslo_config import cfg
import six
from heat.common import exception
from heat.common import template_format
from heat.engine.clients.os import cinder
from heat.engine.clients.os import nova
from heat.engine.resources.aws.ec2 import instance
from heat.engine.resources.aws.ec2 import volume as aws_vol
from heat.engine import rsrc_defn
from heat.engine import scheduler
from heat.tests.openstack.cinder import test_volume_utils as vt_base
from heat.tests.openstack.nova import fakes as fakes_nova
from heat.tests import utils
volume_template = '''
{
"AWSTemplateFormatVersion" : "2010-09-09",
"Description" : "Volume Test",
"Parameters" : {},
"Resources" : {
"WikiDatabase": {
"Type": "AWS::EC2::Instance",
"Properties": {
"ImageId" : "foo",
"InstanceType" : "m1.large",
"KeyName" : "test",
"UserData" : "some data"
}
},
"DataVolume" : {
"Type" : "AWS::EC2::Volume",
"Properties" : {
"Size" : "1",
"AvailabilityZone" : {"Fn::GetAtt": ["WikiDatabase",
"AvailabilityZone"]},
"Tags" : [{ "Key" : "Usage", "Value" : "Wiki Data Volume" }]
}
},
"MountPoint" : {
"Type" : "AWS::EC2::VolumeAttachment",
"Properties" : {
"InstanceId" : { "Ref" : "WikiDatabase" },
"VolumeId" : { "Ref" : "DataVolume" },
"Device" : "/dev/vdc"
}
}
}
}
'''
class VolumeTest(vt_base.VolumeTestCase):
def setUp(self):
super(VolumeTest, self).setUp()
self.t = template_format.parse(volume_template)
self.use_cinder = False
def _mock_create_volume(self, fv, stack_name, final_status='available',
mock_attachment=None):
self.vol_name = utils.PhysName(stack_name, 'DataVolume')
self.stack_name = stack_name
self.cinder_fc.volumes.create.return_value = vt_base.FakeVolume(fv)
fv_ready = vt_base.FakeVolume(final_status, id=fv.id)
if mock_attachment is not None:
results = [fv, fv_ready, mock_attachment]
else:
results = [fv, fv_ready, vt_base.FakeVolume('in-use')]
self.cinder_fc.volumes.get.side_effect = results
return fv_ready
def test_volume(self):
stack_name = 'test_volume_create_stack'
# create script
fv = self._mock_create_volume(vt_base.FakeVolume('creating'),
stack_name)
# delete script
self._mock_delete_volume(fv)
stack = utils.parse_stack(self.t, stack_name=stack_name)
rsrc = self.create_volume(self.t, stack, 'DataVolume')
# delete script
self._mock_delete_volume(fv)
ex = self.assertRaises(exception.ResourceFailure,
scheduler.TaskRunner(rsrc.destroy))
self.assertIn("Volume in use", six.text_type(ex))
self.cinder_fc.volumes.get.side_effect = [
vt_base.FakeVolume('available'), cinder_exp.NotFound('Not found')]
scheduler.TaskRunner(rsrc.destroy)()
def test_volume_default_az(self):
fv = vt_base.FakeVolume('creating')
stack_name = 'test_volume_defaultaz_stack'
# create script
self.patchobject(instance.Instance, 'handle_create')
self.patchobject(instance.Instance, 'check_create_complete',
return_value=True)
self.patchobject(instance.Instance, '_resolve_attribute',
return_value=None)
self.patchobject(aws_vol.VolumeAttachment, 'handle_create')
self.patchobject(aws_vol.VolumeAttachment,
'check_create_complete',
return_value=True)
cinder.CinderClientPlugin._create.return_value = self.cinder_fc
self.stub_ImageConstraint_validate()
self.stub_ServerConstraint_validate()
self.stub_VolumeConstraint_validate()
vol_name = utils.PhysName(stack_name, 'DataVolume')
self.cinder_fc.volumes.create.return_value = fv
fv_ready = vt_base.FakeVolume('available', id=fv.id)
self.cinder_fc.volumes.get.side_effect = [
fv, fv_ready, cinder_exp.NotFound('Not found')]
# delete script
cookie = object()
self.patchobject(instance.Instance, 'handle_delete')
self.patchobject(aws_vol.VolumeAttachment, 'handle_delete',
return_value=cookie)
self.patchobject(aws_vol.VolumeAttachment, 'check_delete_complete',
return_value=True)
stack = utils.parse_stack(self.t, stack_name=stack_name)
stack._update_all_resource_data(True, False)
rsrc = stack['DataVolume']
self.assertIsNone(rsrc.validate())
scheduler.TaskRunner(stack.create)()
self.assertEqual((rsrc.CREATE, rsrc.COMPLETE), rsrc.state)
scheduler.TaskRunner(stack.delete)()
instance.Instance._resolve_attribute.assert_called_with(
'AvailabilityZone')
self.cinder_fc.volumes.create.assert_called_once_with(
size=1, availability_zone=None,
description=vol_name,
name=vol_name,
metadata={u'Usage': u'Wiki Data Volume'})
self.cinder_fc.volumes.get.assert_called_with('vol-123')
aws_vol.VolumeAttachment.check_delete_complete.assert_called_once_with(
cookie)
def test_volume_create_error(self):
fv = vt_base.FakeVolume('creating')
stack_name = 'test_volume_create_error_stack'
cfg.CONF.set_override('action_retry_limit', 0)
self._mock_create_volume(fv, stack_name, final_status='error')
stack = utils.parse_stack(self.t, stack_name=stack_name)
ex = self.assertRaises(exception.ResourceFailure,
self.create_volume, self.t, stack, 'DataVolume')
self.assertIn('Went to status error due to "Unknown"',
six.text_type(ex))
def test_volume_bad_tags(self):
stack_name = 'test_volume_bad_tags_stack'
self.t['Resources']['DataVolume']['Properties'][
'Tags'] = [{'Foo': 'bar'}]
stack = utils.parse_stack(self.t, stack_name=stack_name)
ex = self.assertRaises(exception.StackValidationFailed,
self.create_volume, self.t, stack, 'DataVolume')
self.assertEqual("Property error: "
"Resources.DataVolume.Properties.Tags[0]: "
"Unknown Property Foo", six.text_type(ex))
def test_volume_attachment_error(self):
stack_name = 'test_volume_attach_error_stack'
mock_attachment = self._mock_create_server_volume_script(
vt_base.FakeVolume('attaching'), final_status='error')
self._mock_create_volume(vt_base.FakeVolume('creating'),
stack_name,
mock_attachment=mock_attachment
)
self.stub_VolumeConstraint_validate()
stack = utils.parse_stack(self.t, stack_name=stack_name)
self.create_volume(self.t, stack, 'DataVolume')
ex = self.assertRaises(exception.ResourceFailure,
self.create_attachment,
self.t, stack, 'MountPoint')
self.assertIn("Volume attachment failed - Unknown status error",
six.text_type(ex))
self.validate_mock_create_server_volume_script()
def test_volume_attachment(self):
stack_name = 'test_volume_attach_stack'
fva = self._mock_create_server_volume_script(
vt_base.FakeVolume('attaching'))
self._mock_create_volume(vt_base.FakeVolume('creating'),
stack_name, mock_attachment=fva)
self.stub_VolumeConstraint_validate()
stack = utils.parse_stack(self.t, stack_name=stack_name)
self.create_volume(self.t, stack, 'DataVolume')
rsrc = self.create_attachment(self.t, stack, 'MountPoint')
# delete script
fva = vt_base.FakeVolume('in-use')
self.cinder_fc.volumes.get.side_effect = [
fva, vt_base.FakeVolume('detaching', id=fva.id),
vt_base.FakeVolume('available', id=fva.id)
]
self.fc.volumes.delete_server_volume.return_value = None
self.fc.volumes.get_server_volume.side_effect = [
fva, fva, fakes_nova.fake_exception()]
scheduler.TaskRunner(rsrc.delete)()
self.fc.volumes.get_server_volume.assert_called_with(u'WikiDatabase',
'vol-123')
self.fc.volumes.delete_server_volume.assert_called_with(
'WikiDatabase', 'vol-123')
self.fc.volumes.get_server_volume.assert_called_with(
u'WikiDatabase', 'vol-123')
self.validate_mock_create_server_volume_script()
def test_volume_detachment_err(self):
stack_name = 'test_volume_detach_err_stack'
fva = self._mock_create_server_volume_script(
vt_base.FakeVolume('attaching'))
self._mock_create_volume(vt_base.FakeVolume('creating'),
stack_name, mock_attachment=fva)
self.stub_VolumeConstraint_validate()
stack = utils.parse_stack(self.t, stack_name=stack_name)
self.create_volume(self.t, stack, 'DataVolume')
rsrc = self.create_attachment(self.t, stack, 'MountPoint')
# delete script
fva = vt_base.FakeVolume('in-use')
self.fc.volumes.get_server_volume.side_effect = [
fva, fva, fakes_nova.fake_exception()]
self.cinder_fc.volumes.get.side_effect = [
fva, vt_base.FakeVolume('available', id=fva.id)]
exc = fakes_nova.fake_exception(400)
self.fc.volumes.delete_server_volume.side_effect = exc
scheduler.TaskRunner(rsrc.delete)()
self.fc.volumes.get_server_volume.assert_called_with(
u'WikiDatabase', 'vol-123')
self.fc.volumes.delete_server_volume.assert_called_once_with(
'WikiDatabase', 'vol-123')
self.validate_mock_create_server_volume_script()
def test_volume_detach_non_exist(self):
fv = vt_base.FakeVolume('creating')
fva = vt_base.FakeVolume('in-use')
stack_name = 'test_volume_detach_nonexist_stack'
mock_attachment = self._mock_create_server_volume_script(fva)
self._mock_create_volume(fv, stack_name,
mock_attachment=mock_attachment)
self.stub_VolumeConstraint_validate()
stack = utils.parse_stack(self.t, stack_name=stack_name)
self.create_volume(self.t, stack, 'DataVolume')
rsrc = self.create_attachment(self.t, stack, 'MountPoint')
# delete script
self.fc.volumes.delete_server_volume.return_value = None
self.cinder_fc.volumes.get.side_effect = cinder_exp.NotFound(
'Not found')
exc = fakes_nova.fake_exception()
self.fc.volumes.get_server_volume.side_effect = exc
scheduler.TaskRunner(rsrc.delete)()
self.fc.volumes.delete_server_volume.assert_called_once_with(
u'WikiDatabase', 'vol-123')
self.fc.volumes.get_server_volume.assert_called_with(
u'WikiDatabase', 'vol-123')
self.validate_mock_create_server_volume_script()
def test_volume_detach_deleting_volume(self):
fv = vt_base.FakeVolume('creating')
fva = vt_base.FakeVolume('deleting')
stack_name = 'test_volume_detach_deleting_volume_stack'
mock_attachment = self._mock_create_server_volume_script(fva)
self._mock_create_volume(fv, stack_name,
mock_attachment=mock_attachment)
self.stub_VolumeConstraint_validate()
stack = utils.parse_stack(self.t, stack_name=stack_name)
self.create_volume(self.t, stack, 'DataVolume')
rsrc = self.create_attachment(self.t, stack, 'MountPoint')
# delete script
self.cinder_fc.volumes.get.side_effect = [fva]
exc = fakes_nova.fake_exception()
self.fc.volumes.get_server_volume.side_effect = exc
scheduler.TaskRunner(rsrc.delete)()
self.fc.volumes.delete_server_volume.assert_called_once_with(
u'WikiDatabase', 'vol-123')
self.validate_mock_create_server_volume_script()
def test_volume_detach_with_latency(self):
stack_name = 'test_volume_detach_latency_stack'
fva = self._mock_create_server_volume_script(
vt_base.FakeVolume('attaching'))
self._mock_create_volume(vt_base.FakeVolume('creating'),
stack_name, mock_attachment=fva)
self.stub_VolumeConstraint_validate()
stack = utils.parse_stack(self.t, stack_name=stack_name)
self.create_volume(self.t, stack, 'DataVolume')
rsrc = self.create_attachment(self.t, stack, 'MountPoint')
# delete script
self.fc.volumes.get_server_volume.side_effect = [
fva, fva, fakes_nova.fake_exception()]
self.cinder_fc.volumes.get.side_effect = [
fva, vt_base.FakeVolume('in-use', id=fva.id),
vt_base.FakeVolume('detaching', id=fva.id),
vt_base.FakeVolume('available', id=fva.id)]
scheduler.TaskRunner(rsrc.delete)()
self.fc.volumes.delete_server_volume.assert_called_once_with(
u'WikiDatabase', 'vol-123')
self.fc.volumes.get_server_volume.assert_called_with(
u'WikiDatabase', 'vol-123')
self.validate_mock_create_server_volume_script()
def test_volume_detach_with_error(self):
stack_name = 'test_volume_detach_werr_stack'
fva = self._mock_create_server_volume_script(
vt_base.FakeVolume('attaching'))
self._mock_create_volume(vt_base.FakeVolume('creating'),
stack_name, mock_attachment=fva)
self.stub_VolumeConstraint_validate()
stack = utils.parse_stack(self.t, stack_name=stack_name)
self.create_volume(self.t, stack, 'DataVolume')
rsrc = self.create_attachment(self.t, stack, 'MountPoint')
# delete script
self.fc.volumes.delete_server_volume.return_value = None
fva = vt_base.FakeVolume('in-use')
self.cinder_fc.volumes.get.side_effect = [
vt_base.FakeVolume('error', id=fva.id)]
detach_task = scheduler.TaskRunner(rsrc.delete)
ex = self.assertRaises(exception.ResourceFailure, detach_task)
self.assertIn('Volume detachment failed - Unknown status error',
six.text_type(ex))
self.fc.volumes.delete_server_volume.assert_called_once_with(
u'WikiDatabase', 'vol-123')
self.validate_mock_create_server_volume_script()
def test_volume_delete(self):
stack_name = 'test_volume_delete_stack'
fv = vt_base.FakeVolume('creating')
self._mock_create_volume(fv, stack_name)
self.t['Resources']['DataVolume']['DeletionPolicy'] = 'Delete'
stack = utils.parse_stack(self.t, stack_name=stack_name)
rsrc = self.create_volume(self.t, stack, 'DataVolume')
m_hd = mock.Mock(return_value=None)
rsrc.handle_delete = m_hd
m_cdc = mock.Mock(return_value=True)
rsrc.check_delete_complete = m_cdc
scheduler.TaskRunner(rsrc.destroy)()
m_cdc.assert_called_with(None)
m_hd.assert_called_once_with()
def test_volume_deleting_delete(self):
vt_base.FakeVolume('creating')
stack_name = 'test_volume_deleting_stack'
self._mock_create_volume(vt_base.FakeVolume('creating'),
stack_name)
stack = utils.parse_stack(self.t, stack_name=stack_name)
rsrc = self.create_volume(self.t, stack, 'DataVolume')
self.assertEqual(2, self.cinder_fc.volumes.get.call_count)
# delete script
self.cinder_fc.volumes.get.side_effect = [
vt_base.FakeVolume('deleting'),
vt_base.FakeVolume('deleting'),
cinder_exp.NotFound('NotFound')]
scheduler.TaskRunner(rsrc.destroy)()
self.assertEqual(5, self.cinder_fc.volumes.get.call_count)
def test_volume_delete_error(self):
fv = vt_base.FakeVolume('creating')
stack_name = 'test_volume_deleting_stack'
fv = self._mock_create_volume(vt_base.FakeVolume('creating'),
stack_name)
stack = utils.parse_stack(self.t, stack_name=stack_name)
rsrc = self.create_volume(self.t, stack, 'DataVolume')
self.assertEqual(2, self.cinder_fc.volumes.get.call_count)
self.cinder_fc.volumes.get.side_effect = [
fv,
vt_base.FakeVolume('deleting'),
vt_base.FakeVolume('error_deleting')]
self.cinder_fc.volumes.delete.return_value = True
deleter = scheduler.TaskRunner(rsrc.destroy)
self.assertRaisesRegex(exception.ResourceFailure,
".*ResourceInError.*error_deleting.*delete",
deleter)
self.cinder_fc.volumes.delete.assert_called_once_with(fv.id)
self.assertEqual(5, self.cinder_fc.volumes.get.call_count)
def test_volume_update_not_supported(self):
stack_name = 'test_volume_updnotsup_stack'
fv = vt_base.FakeVolume('creating')
self._mock_create_volume(fv, stack_name)
t = template_format.parse(volume_template)
stack = utils.parse_stack(t, stack_name=stack_name)
rsrc = self.create_volume(t, stack, 'DataVolume')
props = copy.deepcopy(rsrc.properties.data)
props['Size'] = 2
props['Tags'] = None
props['AvailabilityZone'] = 'other'
after = rsrc_defn.ResourceDefinition(rsrc.name, rsrc.type(), props)
updater = scheduler.TaskRunner(rsrc.update, after)
ex = self.assertRaises(exception.ResourceFailure, updater)
self.assertIn("NotSupported: resources.DataVolume: "
"Update to properties "
"AvailabilityZone, Size, Tags of DataVolume "
"(AWS::EC2::Volume) is not supported",
six.text_type(ex))
self.assertEqual((rsrc.UPDATE, rsrc.FAILED), rsrc.state)
def test_volume_check(self):
stack = utils.parse_stack(self.t, stack_name='volume_check')
res = stack['DataVolume']
res.state_set(res.CREATE, res.COMPLETE)
fake_volume = vt_base.FakeVolume('available')
cinder = mock.Mock()
cinder.volumes.get.return_value = fake_volume
self.patchobject(res, 'client', return_value=cinder)
scheduler.TaskRunner(res.check)()
self.assertEqual((res.CHECK, res.COMPLETE), res.state)
fake_volume = vt_base.FakeVolume('in-use')
res.client().volumes.get.return_value = fake_volume
scheduler.TaskRunner(res.check)()
self.assertEqual((res.CHECK, res.COMPLETE), res.state)
def test_volume_check_not_available(self):
stack = utils.parse_stack(self.t, stack_name='volume_check_na')
res = stack['DataVolume']
res.state_set(res.CREATE, res.COMPLETE)
cinder = mock.Mock()
fake_volume = vt_base.FakeVolume('foobar')
cinder.volumes.get.return_value = fake_volume
self.patchobject(res, 'client', return_value=cinder)
self.assertRaises(exception.ResourceFailure,
scheduler.TaskRunner(res.check))
self.assertEqual((res.CHECK, res.FAILED), res.state)
self.assertIn('foobar', res.status_reason)
def test_volume_check_fail(self):
stack = utils.parse_stack(self.t, stack_name='volume_check_fail')
res = stack['DataVolume']
res.state_set(res.CREATE, res.COMPLETE)
cinder = mock.Mock()
cinder.volumes.get.side_effect = Exception('boom')
self.patchobject(res, 'client', return_value=cinder)
self.assertRaises(exception.ResourceFailure,
scheduler.TaskRunner(res.check))
self.assertEqual((res.CHECK, res.FAILED), res.state)
self.assertIn('boom', res.status_reason)
def test_snapshot(self):
stack_name = 'test_volume_snapshot_stack'
fv = vt_base.FakeVolume('creating')
fv_ready = vt_base.FakeVolume('available', id=fv.id)
fv = self._mock_create_volume(fv,
stack_name, mock_attachment=fv_ready)
# snapshot script
fb = vt_base.FakeBackup('available')
self.m_backups.create.return_value = fb
self.m_backups.get.return_value = fb
self._mock_delete_volume(fv)
self.t['Resources']['DataVolume']['DeletionPolicy'] = 'Snapshot'
stack = utils.parse_stack(self.t, stack_name=stack_name)
rsrc = self.create_volume(self.t, stack, 'DataVolume')
self.cinder_fc.volumes.get.side_effect = [
fv,
vt_base.FakeVolume('available'),
cinder_exp.NotFound('Not found')
]
scheduler.TaskRunner(rsrc.destroy)()
self.m_backups.create.assert_called_once_with(fv.id)
self.m_backups.get.assert_called_once_with(fb.id)
def test_snapshot_error(self):
stack_name = 'test_volume_snapshot_err_stack'
fv = self._mock_create_volume(vt_base.FakeVolume('creating'),
stack_name)
# snapshot script
fb = vt_base.FakeBackup('error')
self.m_backups.create.return_value = fb
self.m_backups.get.return_value = fb
self.t['Resources']['DataVolume']['DeletionPolicy'] = 'Snapshot'
stack = utils.parse_stack(self.t, stack_name=stack_name)
rsrc = self.create_volume(self.t, stack, 'DataVolume')
ex = self.assertRaises(exception.ResourceFailure,
scheduler.TaskRunner(rsrc.destroy))
self.assertIn('Unknown status error', six.text_type(ex))
self.m_backups.create.assert_called_once_with(fv.id)
self.m_backups.get.assert_called_once_with(fb.id)
def test_snapshot_no_volume(self):
"""Test that backup does not start for failed resource."""
stack_name = 'test_volume_snapshot_novol_stack'
cfg.CONF.set_override('action_retry_limit', 0)
fva = vt_base.FakeVolume('error')
fv = self._mock_create_volume(vt_base.FakeVolume('creating'),
stack_name,
final_status='error',
mock_attachment=fva)
self._mock_delete_volume(fv)
self.t['Resources']['DataVolume']['DeletionPolicy'] = 'Snapshot'
self.t['Resources']['DataVolume']['Properties'][
'AvailabilityZone'] = 'nova'
stack = utils.parse_stack(self.t, stack_name=stack_name)
resource_defns = stack.t.resource_definitions(stack)
rsrc = aws_vol.Volume('DataVolume',
resource_defns['DataVolume'],
stack)
create = scheduler.TaskRunner(rsrc.create)
ex = self.assertRaises(exception.ResourceFailure, create)
self.assertIn('Went to status error due to "Unknown"',
six.text_type(ex))
self.cinder_fc.volumes.get.side_effect = [
fva,
cinder_exp.NotFound('Not found')
]
scheduler.TaskRunner(rsrc.destroy)()
def test_create_from_snapshot(self):
stack_name = 'test_volume_create_from_snapshot_stack'
fv = vt_base.FakeVolume('restoring-backup')
fvbr = vt_base.FakeBackupRestore('vol-123')
# create script
cinder.CinderClientPlugin._create.return_value = self.cinder_fc
self.m_restore.return_value = fvbr
fv2 = vt_base.FakeVolume('available')
self.cinder_fc.volumes.get.side_effect = [fv, fv2]
vol_name = utils.PhysName(stack_name, 'DataVolume')
self.t['Resources']['DataVolume']['Properties'][
'SnapshotId'] = 'backup-123'
stack = utils.parse_stack(self.t, stack_name=stack_name)
self.create_volume(self.t, stack, 'DataVolume', no_create=True)
cinder.CinderClientPlugin._create.assert_called_once_with()
self.m_restore.assert_called_once_with('backup-123')
self.cinder_fc.volumes.get.assert_called_with('vol-123')
self.cinder_fc.volumes.update.assert_called_once_with(
'vol-123', description=vol_name, name=vol_name)
def test_create_from_snapshot_error(self):
stack_name = 'test_volume_create_from_snap_err_stack'
cfg.CONF.set_override('action_retry_limit', 0)
fv = vt_base.FakeVolume('restoring-backup')
fv2 = vt_base.FakeVolume('error')
fvbr = vt_base.FakeBackupRestore('vol-123')
# create script
cinder.CinderClientPlugin._create.return_value = self.cinder_fc
self.m_restore.return_value = fvbr
self.cinder_fc.volumes.get.side_effect = [fv, fv2]
vol_name = utils.PhysName(stack_name, 'DataVolume')
self.t['Resources']['DataVolume']['Properties'][
'SnapshotId'] = 'backup-123'
stack = utils.parse_stack(self.t, stack_name=stack_name)
ex = self.assertRaises(exception.ResourceFailure,
self.create_volume, self.t, stack, 'DataVolume')
self.assertIn('Went to status error due to "Unknown"',
six.text_type(ex))
cinder.CinderClientPlugin._create.assert_called_once_with()
self.m_restore.assert_called_once_with('backup-123')
self.cinder_fc.volumes.update.assert_called_once_with(
fv.id, description=vol_name, name=vol_name)
def test_volume_size_constraint(self):
self.t['Resources']['DataVolume']['Properties']['Size'] = '0'
stack = utils.parse_stack(self.t)
error = self.assertRaises(exception.StackValidationFailed,
self.create_volume,
self.t, stack, 'DataVolume')
self.assertEqual(
"Property error: Resources.DataVolume.Properties.Size: "
"0 is out of range (min: 1, max: None)", six.text_type(error))
def test_volume_attachment_updates_not_supported(self):
self.patchobject(nova.NovaClientPlugin, 'get_server')
fv = vt_base.FakeVolume('creating')
fva = vt_base.FakeVolume('attaching')
stack_name = 'test_volume_attach_updnotsup_stack'
mock_create_server_volume = self._mock_create_server_volume_script(fva)
self._mock_create_volume(fv, stack_name,
mock_attachment=mock_create_server_volume)
self.stub_VolumeConstraint_validate()
stack = utils.parse_stack(self.t, stack_name=stack_name)
self.create_volume(self.t, stack, 'DataVolume')
rsrc = self.create_attachment(self.t, stack, 'MountPoint')
props = copy.deepcopy(rsrc.properties.data)
props['InstanceId'] = 'some_other_instance_id'
props['VolumeId'] = 'some_other_volume_id'
props['Device'] = '/dev/vdz'
after = rsrc_defn.ResourceDefinition(rsrc.name, rsrc.type(), props)
update_task = scheduler.TaskRunner(rsrc.update, after)
ex = self.assertRaises(exception.ResourceFailure, update_task)
self.assertIn('NotSupported: resources.MountPoint: '
'Update to properties Device, InstanceId, '
'VolumeId of MountPoint (AWS::EC2::VolumeAttachment)',
six.text_type(ex))
self.assertEqual((rsrc.UPDATE, rsrc.FAILED), rsrc.state)
self.validate_mock_create_server_volume_script()
def test_validate_deletion_policy(self):
cfg.CONF.set_override('backups_enabled', False, group='volumes')
stack_name = 'test_volume_validate_deletion_policy'
self.t['Resources']['DataVolume']['DeletionPolicy'] = 'Snapshot'
stack = utils.parse_stack(self.t, stack_name=stack_name)
rsrc = self.get_volume(self.t, stack, 'DataVolume')
self.assertRaisesRegex(
exception.StackValidationFailed,
'volume backup service is not enabled',
rsrc.validate) | heat/tests/aws/test_volume.py |
import copy
from cinderclient import exceptions as cinder_exp
import mock
from oslo_config import cfg
import six
from heat.common import exception
from heat.common import template_format
from heat.engine.clients.os import cinder
from heat.engine.clients.os import nova
from heat.engine.resources.aws.ec2 import instance
from heat.engine.resources.aws.ec2 import volume as aws_vol
from heat.engine import rsrc_defn
from heat.engine import scheduler
from heat.tests.openstack.cinder import test_volume_utils as vt_base
from heat.tests.openstack.nova import fakes as fakes_nova
from heat.tests import utils
volume_template = '''
{
"AWSTemplateFormatVersion" : "2010-09-09",
"Description" : "Volume Test",
"Parameters" : {},
"Resources" : {
"WikiDatabase": {
"Type": "AWS::EC2::Instance",
"Properties": {
"ImageId" : "foo",
"InstanceType" : "m1.large",
"KeyName" : "test",
"UserData" : "some data"
}
},
"DataVolume" : {
"Type" : "AWS::EC2::Volume",
"Properties" : {
"Size" : "1",
"AvailabilityZone" : {"Fn::GetAtt": ["WikiDatabase",
"AvailabilityZone"]},
"Tags" : [{ "Key" : "Usage", "Value" : "Wiki Data Volume" }]
}
},
"MountPoint" : {
"Type" : "AWS::EC2::VolumeAttachment",
"Properties" : {
"InstanceId" : { "Ref" : "WikiDatabase" },
"VolumeId" : { "Ref" : "DataVolume" },
"Device" : "/dev/vdc"
}
}
}
}
'''
class VolumeTest(vt_base.VolumeTestCase):
def setUp(self):
super(VolumeTest, self).setUp()
self.t = template_format.parse(volume_template)
self.use_cinder = False
def _mock_create_volume(self, fv, stack_name, final_status='available',
mock_attachment=None):
self.vol_name = utils.PhysName(stack_name, 'DataVolume')
self.stack_name = stack_name
self.cinder_fc.volumes.create.return_value = vt_base.FakeVolume(fv)
fv_ready = vt_base.FakeVolume(final_status, id=fv.id)
if mock_attachment is not None:
results = [fv, fv_ready, mock_attachment]
else:
results = [fv, fv_ready, vt_base.FakeVolume('in-use')]
self.cinder_fc.volumes.get.side_effect = results
return fv_ready
def test_volume(self):
stack_name = 'test_volume_create_stack'
# create script
fv = self._mock_create_volume(vt_base.FakeVolume('creating'),
stack_name)
# delete script
self._mock_delete_volume(fv)
stack = utils.parse_stack(self.t, stack_name=stack_name)
rsrc = self.create_volume(self.t, stack, 'DataVolume')
# delete script
self._mock_delete_volume(fv)
ex = self.assertRaises(exception.ResourceFailure,
scheduler.TaskRunner(rsrc.destroy))
self.assertIn("Volume in use", six.text_type(ex))
self.cinder_fc.volumes.get.side_effect = [
vt_base.FakeVolume('available'), cinder_exp.NotFound('Not found')]
scheduler.TaskRunner(rsrc.destroy)()
def test_volume_default_az(self):
fv = vt_base.FakeVolume('creating')
stack_name = 'test_volume_defaultaz_stack'
# create script
self.patchobject(instance.Instance, 'handle_create')
self.patchobject(instance.Instance, 'check_create_complete',
return_value=True)
self.patchobject(instance.Instance, '_resolve_attribute',
return_value=None)
self.patchobject(aws_vol.VolumeAttachment, 'handle_create')
self.patchobject(aws_vol.VolumeAttachment,
'check_create_complete',
return_value=True)
cinder.CinderClientPlugin._create.return_value = self.cinder_fc
self.stub_ImageConstraint_validate()
self.stub_ServerConstraint_validate()
self.stub_VolumeConstraint_validate()
vol_name = utils.PhysName(stack_name, 'DataVolume')
self.cinder_fc.volumes.create.return_value = fv
fv_ready = vt_base.FakeVolume('available', id=fv.id)
self.cinder_fc.volumes.get.side_effect = [
fv, fv_ready, cinder_exp.NotFound('Not found')]
# delete script
cookie = object()
self.patchobject(instance.Instance, 'handle_delete')
self.patchobject(aws_vol.VolumeAttachment, 'handle_delete',
return_value=cookie)
self.patchobject(aws_vol.VolumeAttachment, 'check_delete_complete',
return_value=True)
stack = utils.parse_stack(self.t, stack_name=stack_name)
stack._update_all_resource_data(True, False)
rsrc = stack['DataVolume']
self.assertIsNone(rsrc.validate())
scheduler.TaskRunner(stack.create)()
self.assertEqual((rsrc.CREATE, rsrc.COMPLETE), rsrc.state)
scheduler.TaskRunner(stack.delete)()
instance.Instance._resolve_attribute.assert_called_with(
'AvailabilityZone')
self.cinder_fc.volumes.create.assert_called_once_with(
size=1, availability_zone=None,
description=vol_name,
name=vol_name,
metadata={u'Usage': u'Wiki Data Volume'})
self.cinder_fc.volumes.get.assert_called_with('vol-123')
aws_vol.VolumeAttachment.check_delete_complete.assert_called_once_with(
cookie)
def test_volume_create_error(self):
fv = vt_base.FakeVolume('creating')
stack_name = 'test_volume_create_error_stack'
cfg.CONF.set_override('action_retry_limit', 0)
self._mock_create_volume(fv, stack_name, final_status='error')
stack = utils.parse_stack(self.t, stack_name=stack_name)
ex = self.assertRaises(exception.ResourceFailure,
self.create_volume, self.t, stack, 'DataVolume')
self.assertIn('Went to status error due to "Unknown"',
six.text_type(ex))
def test_volume_bad_tags(self):
stack_name = 'test_volume_bad_tags_stack'
self.t['Resources']['DataVolume']['Properties'][
'Tags'] = [{'Foo': 'bar'}]
stack = utils.parse_stack(self.t, stack_name=stack_name)
ex = self.assertRaises(exception.StackValidationFailed,
self.create_volume, self.t, stack, 'DataVolume')
self.assertEqual("Property error: "
"Resources.DataVolume.Properties.Tags[0]: "
"Unknown Property Foo", six.text_type(ex))
def test_volume_attachment_error(self):
stack_name = 'test_volume_attach_error_stack'
mock_attachment = self._mock_create_server_volume_script(
vt_base.FakeVolume('attaching'), final_status='error')
self._mock_create_volume(vt_base.FakeVolume('creating'),
stack_name,
mock_attachment=mock_attachment
)
self.stub_VolumeConstraint_validate()
stack = utils.parse_stack(self.t, stack_name=stack_name)
self.create_volume(self.t, stack, 'DataVolume')
ex = self.assertRaises(exception.ResourceFailure,
self.create_attachment,
self.t, stack, 'MountPoint')
self.assertIn("Volume attachment failed - Unknown status error",
six.text_type(ex))
self.validate_mock_create_server_volume_script()
def test_volume_attachment(self):
stack_name = 'test_volume_attach_stack'
fva = self._mock_create_server_volume_script(
vt_base.FakeVolume('attaching'))
self._mock_create_volume(vt_base.FakeVolume('creating'),
stack_name, mock_attachment=fva)
self.stub_VolumeConstraint_validate()
stack = utils.parse_stack(self.t, stack_name=stack_name)
self.create_volume(self.t, stack, 'DataVolume')
rsrc = self.create_attachment(self.t, stack, 'MountPoint')
# delete script
fva = vt_base.FakeVolume('in-use')
self.cinder_fc.volumes.get.side_effect = [
fva, vt_base.FakeVolume('detaching', id=fva.id),
vt_base.FakeVolume('available', id=fva.id)
]
self.fc.volumes.delete_server_volume.return_value = None
self.fc.volumes.get_server_volume.side_effect = [
fva, fva, fakes_nova.fake_exception()]
scheduler.TaskRunner(rsrc.delete)()
self.fc.volumes.get_server_volume.assert_called_with(u'WikiDatabase',
'vol-123')
self.fc.volumes.delete_server_volume.assert_called_with(
'WikiDatabase', 'vol-123')
self.fc.volumes.get_server_volume.assert_called_with(
u'WikiDatabase', 'vol-123')
self.validate_mock_create_server_volume_script()
def test_volume_detachment_err(self):
stack_name = 'test_volume_detach_err_stack'
fva = self._mock_create_server_volume_script(
vt_base.FakeVolume('attaching'))
self._mock_create_volume(vt_base.FakeVolume('creating'),
stack_name, mock_attachment=fva)
self.stub_VolumeConstraint_validate()
stack = utils.parse_stack(self.t, stack_name=stack_name)
self.create_volume(self.t, stack, 'DataVolume')
rsrc = self.create_attachment(self.t, stack, 'MountPoint')
# delete script
fva = vt_base.FakeVolume('in-use')
self.fc.volumes.get_server_volume.side_effect = [
fva, fva, fakes_nova.fake_exception()]
self.cinder_fc.volumes.get.side_effect = [
fva, vt_base.FakeVolume('available', id=fva.id)]
exc = fakes_nova.fake_exception(400)
self.fc.volumes.delete_server_volume.side_effect = exc
scheduler.TaskRunner(rsrc.delete)()
self.fc.volumes.get_server_volume.assert_called_with(
u'WikiDatabase', 'vol-123')
self.fc.volumes.delete_server_volume.assert_called_once_with(
'WikiDatabase', 'vol-123')
self.validate_mock_create_server_volume_script()
def test_volume_detach_non_exist(self):
fv = vt_base.FakeVolume('creating')
fva = vt_base.FakeVolume('in-use')
stack_name = 'test_volume_detach_nonexist_stack'
mock_attachment = self._mock_create_server_volume_script(fva)
self._mock_create_volume(fv, stack_name,
mock_attachment=mock_attachment)
self.stub_VolumeConstraint_validate()
stack = utils.parse_stack(self.t, stack_name=stack_name)
self.create_volume(self.t, stack, 'DataVolume')
rsrc = self.create_attachment(self.t, stack, 'MountPoint')
# delete script
self.fc.volumes.delete_server_volume.return_value = None
self.cinder_fc.volumes.get.side_effect = cinder_exp.NotFound(
'Not found')
exc = fakes_nova.fake_exception()
self.fc.volumes.get_server_volume.side_effect = exc
scheduler.TaskRunner(rsrc.delete)()
self.fc.volumes.delete_server_volume.assert_called_once_with(
u'WikiDatabase', 'vol-123')
self.fc.volumes.get_server_volume.assert_called_with(
u'WikiDatabase', 'vol-123')
self.validate_mock_create_server_volume_script()
def test_volume_detach_deleting_volume(self):
fv = vt_base.FakeVolume('creating')
fva = vt_base.FakeVolume('deleting')
stack_name = 'test_volume_detach_deleting_volume_stack'
mock_attachment = self._mock_create_server_volume_script(fva)
self._mock_create_volume(fv, stack_name,
mock_attachment=mock_attachment)
self.stub_VolumeConstraint_validate()
stack = utils.parse_stack(self.t, stack_name=stack_name)
self.create_volume(self.t, stack, 'DataVolume')
rsrc = self.create_attachment(self.t, stack, 'MountPoint')
# delete script
self.cinder_fc.volumes.get.side_effect = [fva]
exc = fakes_nova.fake_exception()
self.fc.volumes.get_server_volume.side_effect = exc
scheduler.TaskRunner(rsrc.delete)()
self.fc.volumes.delete_server_volume.assert_called_once_with(
u'WikiDatabase', 'vol-123')
self.validate_mock_create_server_volume_script()
def test_volume_detach_with_latency(self):
stack_name = 'test_volume_detach_latency_stack'
fva = self._mock_create_server_volume_script(
vt_base.FakeVolume('attaching'))
self._mock_create_volume(vt_base.FakeVolume('creating'),
stack_name, mock_attachment=fva)
self.stub_VolumeConstraint_validate()
stack = utils.parse_stack(self.t, stack_name=stack_name)
self.create_volume(self.t, stack, 'DataVolume')
rsrc = self.create_attachment(self.t, stack, 'MountPoint')
# delete script
self.fc.volumes.get_server_volume.side_effect = [
fva, fva, fakes_nova.fake_exception()]
self.cinder_fc.volumes.get.side_effect = [
fva, vt_base.FakeVolume('in-use', id=fva.id),
vt_base.FakeVolume('detaching', id=fva.id),
vt_base.FakeVolume('available', id=fva.id)]
scheduler.TaskRunner(rsrc.delete)()
self.fc.volumes.delete_server_volume.assert_called_once_with(
u'WikiDatabase', 'vol-123')
self.fc.volumes.get_server_volume.assert_called_with(
u'WikiDatabase', 'vol-123')
self.validate_mock_create_server_volume_script()
def test_volume_detach_with_error(self):
stack_name = 'test_volume_detach_werr_stack'
fva = self._mock_create_server_volume_script(
vt_base.FakeVolume('attaching'))
self._mock_create_volume(vt_base.FakeVolume('creating'),
stack_name, mock_attachment=fva)
self.stub_VolumeConstraint_validate()
stack = utils.parse_stack(self.t, stack_name=stack_name)
self.create_volume(self.t, stack, 'DataVolume')
rsrc = self.create_attachment(self.t, stack, 'MountPoint')
# delete script
self.fc.volumes.delete_server_volume.return_value = None
fva = vt_base.FakeVolume('in-use')
self.cinder_fc.volumes.get.side_effect = [
vt_base.FakeVolume('error', id=fva.id)]
detach_task = scheduler.TaskRunner(rsrc.delete)
ex = self.assertRaises(exception.ResourceFailure, detach_task)
self.assertIn('Volume detachment failed - Unknown status error',
six.text_type(ex))
self.fc.volumes.delete_server_volume.assert_called_once_with(
u'WikiDatabase', 'vol-123')
self.validate_mock_create_server_volume_script()
def test_volume_delete(self):
stack_name = 'test_volume_delete_stack'
fv = vt_base.FakeVolume('creating')
self._mock_create_volume(fv, stack_name)
self.t['Resources']['DataVolume']['DeletionPolicy'] = 'Delete'
stack = utils.parse_stack(self.t, stack_name=stack_name)
rsrc = self.create_volume(self.t, stack, 'DataVolume')
m_hd = mock.Mock(return_value=None)
rsrc.handle_delete = m_hd
m_cdc = mock.Mock(return_value=True)
rsrc.check_delete_complete = m_cdc
scheduler.TaskRunner(rsrc.destroy)()
m_cdc.assert_called_with(None)
m_hd.assert_called_once_with()
def test_volume_deleting_delete(self):
vt_base.FakeVolume('creating')
stack_name = 'test_volume_deleting_stack'
self._mock_create_volume(vt_base.FakeVolume('creating'),
stack_name)
stack = utils.parse_stack(self.t, stack_name=stack_name)
rsrc = self.create_volume(self.t, stack, 'DataVolume')
self.assertEqual(2, self.cinder_fc.volumes.get.call_count)
# delete script
self.cinder_fc.volumes.get.side_effect = [
vt_base.FakeVolume('deleting'),
vt_base.FakeVolume('deleting'),
cinder_exp.NotFound('NotFound')]
scheduler.TaskRunner(rsrc.destroy)()
self.assertEqual(5, self.cinder_fc.volumes.get.call_count)
def test_volume_delete_error(self):
fv = vt_base.FakeVolume('creating')
stack_name = 'test_volume_deleting_stack'
fv = self._mock_create_volume(vt_base.FakeVolume('creating'),
stack_name)
stack = utils.parse_stack(self.t, stack_name=stack_name)
rsrc = self.create_volume(self.t, stack, 'DataVolume')
self.assertEqual(2, self.cinder_fc.volumes.get.call_count)
self.cinder_fc.volumes.get.side_effect = [
fv,
vt_base.FakeVolume('deleting'),
vt_base.FakeVolume('error_deleting')]
self.cinder_fc.volumes.delete.return_value = True
deleter = scheduler.TaskRunner(rsrc.destroy)
self.assertRaisesRegex(exception.ResourceFailure,
".*ResourceInError.*error_deleting.*delete",
deleter)
self.cinder_fc.volumes.delete.assert_called_once_with(fv.id)
self.assertEqual(5, self.cinder_fc.volumes.get.call_count)
def test_volume_update_not_supported(self):
stack_name = 'test_volume_updnotsup_stack'
fv = vt_base.FakeVolume('creating')
self._mock_create_volume(fv, stack_name)
t = template_format.parse(volume_template)
stack = utils.parse_stack(t, stack_name=stack_name)
rsrc = self.create_volume(t, stack, 'DataVolume')
props = copy.deepcopy(rsrc.properties.data)
props['Size'] = 2
props['Tags'] = None
props['AvailabilityZone'] = 'other'
after = rsrc_defn.ResourceDefinition(rsrc.name, rsrc.type(), props)
updater = scheduler.TaskRunner(rsrc.update, after)
ex = self.assertRaises(exception.ResourceFailure, updater)
self.assertIn("NotSupported: resources.DataVolume: "
"Update to properties "
"AvailabilityZone, Size, Tags of DataVolume "
"(AWS::EC2::Volume) is not supported",
six.text_type(ex))
self.assertEqual((rsrc.UPDATE, rsrc.FAILED), rsrc.state)
def test_volume_check(self):
stack = utils.parse_stack(self.t, stack_name='volume_check')
res = stack['DataVolume']
res.state_set(res.CREATE, res.COMPLETE)
fake_volume = vt_base.FakeVolume('available')
cinder = mock.Mock()
cinder.volumes.get.return_value = fake_volume
self.patchobject(res, 'client', return_value=cinder)
scheduler.TaskRunner(res.check)()
self.assertEqual((res.CHECK, res.COMPLETE), res.state)
fake_volume = vt_base.FakeVolume('in-use')
res.client().volumes.get.return_value = fake_volume
scheduler.TaskRunner(res.check)()
self.assertEqual((res.CHECK, res.COMPLETE), res.state)
def test_volume_check_not_available(self):
stack = utils.parse_stack(self.t, stack_name='volume_check_na')
res = stack['DataVolume']
res.state_set(res.CREATE, res.COMPLETE)
cinder = mock.Mock()
fake_volume = vt_base.FakeVolume('foobar')
cinder.volumes.get.return_value = fake_volume
self.patchobject(res, 'client', return_value=cinder)
self.assertRaises(exception.ResourceFailure,
scheduler.TaskRunner(res.check))
self.assertEqual((res.CHECK, res.FAILED), res.state)
self.assertIn('foobar', res.status_reason)
def test_volume_check_fail(self):
stack = utils.parse_stack(self.t, stack_name='volume_check_fail')
res = stack['DataVolume']
res.state_set(res.CREATE, res.COMPLETE)
cinder = mock.Mock()
cinder.volumes.get.side_effect = Exception('boom')
self.patchobject(res, 'client', return_value=cinder)
self.assertRaises(exception.ResourceFailure,
scheduler.TaskRunner(res.check))
self.assertEqual((res.CHECK, res.FAILED), res.state)
self.assertIn('boom', res.status_reason)
def test_snapshot(self):
stack_name = 'test_volume_snapshot_stack'
fv = vt_base.FakeVolume('creating')
fv_ready = vt_base.FakeVolume('available', id=fv.id)
fv = self._mock_create_volume(fv,
stack_name, mock_attachment=fv_ready)
# snapshot script
fb = vt_base.FakeBackup('available')
self.m_backups.create.return_value = fb
self.m_backups.get.return_value = fb
self._mock_delete_volume(fv)
self.t['Resources']['DataVolume']['DeletionPolicy'] = 'Snapshot'
stack = utils.parse_stack(self.t, stack_name=stack_name)
rsrc = self.create_volume(self.t, stack, 'DataVolume')
self.cinder_fc.volumes.get.side_effect = [
fv,
vt_base.FakeVolume('available'),
cinder_exp.NotFound('Not found')
]
scheduler.TaskRunner(rsrc.destroy)()
self.m_backups.create.assert_called_once_with(fv.id)
self.m_backups.get.assert_called_once_with(fb.id)
def test_snapshot_error(self):
stack_name = 'test_volume_snapshot_err_stack'
fv = self._mock_create_volume(vt_base.FakeVolume('creating'),
stack_name)
# snapshot script
fb = vt_base.FakeBackup('error')
self.m_backups.create.return_value = fb
self.m_backups.get.return_value = fb
self.t['Resources']['DataVolume']['DeletionPolicy'] = 'Snapshot'
stack = utils.parse_stack(self.t, stack_name=stack_name)
rsrc = self.create_volume(self.t, stack, 'DataVolume')
ex = self.assertRaises(exception.ResourceFailure,
scheduler.TaskRunner(rsrc.destroy))
self.assertIn('Unknown status error', six.text_type(ex))
self.m_backups.create.assert_called_once_with(fv.id)
self.m_backups.get.assert_called_once_with(fb.id)
def test_snapshot_no_volume(self):
"""Test that backup does not start for failed resource."""
stack_name = 'test_volume_snapshot_novol_stack'
cfg.CONF.set_override('action_retry_limit', 0)
fva = vt_base.FakeVolume('error')
fv = self._mock_create_volume(vt_base.FakeVolume('creating'),
stack_name,
final_status='error',
mock_attachment=fva)
self._mock_delete_volume(fv)
self.t['Resources']['DataVolume']['DeletionPolicy'] = 'Snapshot'
self.t['Resources']['DataVolume']['Properties'][
'AvailabilityZone'] = 'nova'
stack = utils.parse_stack(self.t, stack_name=stack_name)
resource_defns = stack.t.resource_definitions(stack)
rsrc = aws_vol.Volume('DataVolume',
resource_defns['DataVolume'],
stack)
create = scheduler.TaskRunner(rsrc.create)
ex = self.assertRaises(exception.ResourceFailure, create)
self.assertIn('Went to status error due to "Unknown"',
six.text_type(ex))
self.cinder_fc.volumes.get.side_effect = [
fva,
cinder_exp.NotFound('Not found')
]
scheduler.TaskRunner(rsrc.destroy)()
def test_create_from_snapshot(self):
stack_name = 'test_volume_create_from_snapshot_stack'
fv = vt_base.FakeVolume('restoring-backup')
fvbr = vt_base.FakeBackupRestore('vol-123')
# create script
cinder.CinderClientPlugin._create.return_value = self.cinder_fc
self.m_restore.return_value = fvbr
fv2 = vt_base.FakeVolume('available')
self.cinder_fc.volumes.get.side_effect = [fv, fv2]
vol_name = utils.PhysName(stack_name, 'DataVolume')
self.t['Resources']['DataVolume']['Properties'][
'SnapshotId'] = 'backup-123'
stack = utils.parse_stack(self.t, stack_name=stack_name)
self.create_volume(self.t, stack, 'DataVolume', no_create=True)
cinder.CinderClientPlugin._create.assert_called_once_with()
self.m_restore.assert_called_once_with('backup-123')
self.cinder_fc.volumes.get.assert_called_with('vol-123')
self.cinder_fc.volumes.update.assert_called_once_with(
'vol-123', description=vol_name, name=vol_name)
def test_create_from_snapshot_error(self):
stack_name = 'test_volume_create_from_snap_err_stack'
cfg.CONF.set_override('action_retry_limit', 0)
fv = vt_base.FakeVolume('restoring-backup')
fv2 = vt_base.FakeVolume('error')
fvbr = vt_base.FakeBackupRestore('vol-123')
# create script
cinder.CinderClientPlugin._create.return_value = self.cinder_fc
self.m_restore.return_value = fvbr
self.cinder_fc.volumes.get.side_effect = [fv, fv2]
vol_name = utils.PhysName(stack_name, 'DataVolume')
self.t['Resources']['DataVolume']['Properties'][
'SnapshotId'] = 'backup-123'
stack = utils.parse_stack(self.t, stack_name=stack_name)
ex = self.assertRaises(exception.ResourceFailure,
self.create_volume, self.t, stack, 'DataVolume')
self.assertIn('Went to status error due to "Unknown"',
six.text_type(ex))
cinder.CinderClientPlugin._create.assert_called_once_with()
self.m_restore.assert_called_once_with('backup-123')
self.cinder_fc.volumes.update.assert_called_once_with(
fv.id, description=vol_name, name=vol_name)
def test_volume_size_constraint(self):
self.t['Resources']['DataVolume']['Properties']['Size'] = '0'
stack = utils.parse_stack(self.t)
error = self.assertRaises(exception.StackValidationFailed,
self.create_volume,
self.t, stack, 'DataVolume')
self.assertEqual(
"Property error: Resources.DataVolume.Properties.Size: "
"0 is out of range (min: 1, max: None)", six.text_type(error))
def test_volume_attachment_updates_not_supported(self):
self.patchobject(nova.NovaClientPlugin, 'get_server')
fv = vt_base.FakeVolume('creating')
fva = vt_base.FakeVolume('attaching')
stack_name = 'test_volume_attach_updnotsup_stack'
mock_create_server_volume = self._mock_create_server_volume_script(fva)
self._mock_create_volume(fv, stack_name,
mock_attachment=mock_create_server_volume)
self.stub_VolumeConstraint_validate()
stack = utils.parse_stack(self.t, stack_name=stack_name)
self.create_volume(self.t, stack, 'DataVolume')
rsrc = self.create_attachment(self.t, stack, 'MountPoint')
props = copy.deepcopy(rsrc.properties.data)
props['InstanceId'] = 'some_other_instance_id'
props['VolumeId'] = 'some_other_volume_id'
props['Device'] = '/dev/vdz'
after = rsrc_defn.ResourceDefinition(rsrc.name, rsrc.type(), props)
update_task = scheduler.TaskRunner(rsrc.update, after)
ex = self.assertRaises(exception.ResourceFailure, update_task)
self.assertIn('NotSupported: resources.MountPoint: '
'Update to properties Device, InstanceId, '
'VolumeId of MountPoint (AWS::EC2::VolumeAttachment)',
six.text_type(ex))
self.assertEqual((rsrc.UPDATE, rsrc.FAILED), rsrc.state)
self.validate_mock_create_server_volume_script()
def test_validate_deletion_policy(self):
cfg.CONF.set_override('backups_enabled', False, group='volumes')
stack_name = 'test_volume_validate_deletion_policy'
self.t['Resources']['DataVolume']['DeletionPolicy'] = 'Snapshot'
stack = utils.parse_stack(self.t, stack_name=stack_name)
rsrc = self.get_volume(self.t, stack, 'DataVolume')
self.assertRaisesRegex(
exception.StackValidationFailed,
'volume backup service is not enabled',
rsrc.validate) | 0.485112 | 0.25682 |
import collections
import itertools
from textwrap import dedent
import pytest
import pytablewriter as ptw
from ..._common import print_test_result
from ...data import (
float_header_list,
float_value_matrix,
headers,
mix_header_list,
mix_value_matrix,
value_matrix,
value_matrix_iter,
value_matrix_with_none,
)
Data = collections.namedtuple("Data", "col_delim header value expected")
normal_test_data_list = [
Data(
col_delim=",",
header=headers,
value=value_matrix,
expected=dedent(
"""\
"a","b","c","dd","e"
1,123.1,"a",1,1
2,2.2,"bb",2.2,2.2
3,3.3,"ccc",3,"cccc"
"""
),
),
Data(
col_delim=",",
header=headers,
value=[],
expected=dedent(
"""\
"a","b","c","dd","e"
"""
),
),
Data(
col_delim=",",
header=[],
value=value_matrix,
expected=dedent(
"""\
1,123.1,"a",1,1
2,2.2,"bb",2.2,2.2
3,3.3,"ccc",3,"cccc"
"""
),
),
Data(
col_delim="\t",
header=None,
value=value_matrix,
expected=dedent(
"""\
1\t123.1\t"a"\t1\t1
2\t2.2\t"bb"\t2.2\t2.2
3\t3.3\t"ccc"\t3\t"cccc"
"""
),
),
Data(
col_delim=",",
header=headers,
value=value_matrix_with_none,
expected=dedent(
"""\
"a","b","c","dd","e"
1,,"a",1,
,2.2,,2.2,2.2
3,3.3,"ccc",,"cccc"
,,,,
"""
),
),
Data(
col_delim=",",
header=mix_header_list,
value=mix_value_matrix,
expected=dedent(
"""\
"i","f","c","if","ifc","bool","inf","nan","mix_num","time"
1,1.1,"aa",1,1,True,Infinity,NaN,1,"2017-01-01T00:00:00"
2,2.2,"bbb",2.2,2.2,False,Infinity,NaN,Infinity,"2017-01-02 03:04:05+09:00"
3,3.33,"cccc",-3,"ccc",True,Infinity,NaN,NaN,"2017-01-01T00:00:00"
"""
),
),
Data(
col_delim=",",
header=float_header_list,
value=float_value_matrix,
expected=dedent(
"""\
"a","b","c"
0.01,0.00125,0
1,99.9,0.01
1.2,999999.123,0.001
"""
),
),
Data(
col_delim=",",
header=["a\nb", "c\n\nd", "e\r\nf"],
value=[["v1\nv1", "v2\n\nv2", "v3\r\nv3"]],
expected=dedent(
"""\
"a b","c d","e f"
"v1 v1","v2 v2","v3 v3"
"""
),
),
]
exception_test_data_list = [
Data(col_delim=",", header=header, value=value, expected=ptw.EmptyTableDataError)
for header, value in itertools.product([None, [], ""], [None, [], ""])
]
table_writer_class = ptw.CsvTableWriter
class Test_CsvTableWriter_table_format:
def test_normal(self):
assert table_writer_class().table_format is ptw.TableFormat.CSV
class Test_CsvTableWriter_write_new_line:
def test_normal(self, capsys):
writer = table_writer_class()
writer.write_null_line()
out, _err = capsys.readouterr()
assert out == "\n"
class Test_CsvTableWriter_from_csv:
__CSV_TEXT_INPUT = dedent(
"""\
"a","b","c","dd","e"
1,1.1,"a",1.0,
2,2.2,,2.2,"2.2"
3,3.3,"ccc",,"cc\ncc"
"""
)
__CSV_EXPECTED = dedent(
"""\
"a","b","c","dd","e"
1,1.1,"a",1,
2,2.2,,2.2,2.2
3,3.3,"ccc",,"cc cc"
"""
)
def test_normal_from_text(self, capsys):
writer = table_writer_class()
writer.from_csv(self.__CSV_TEXT_INPUT)
writer.write_table()
out, _err = capsys.readouterr()
assert writer.table_name == ""
assert writer.headers == ["a", "b", "c", "dd", "e"]
print_test_result(expected=self.__CSV_EXPECTED, actual=out)
assert out == self.__CSV_EXPECTED
def test_normal_from_file(self, capsys, tmpdir):
file_path = str(tmpdir.join("test_data.csv"))
with open(file_path, "w", encoding="utf-8") as f:
f.write(self.__CSV_TEXT_INPUT)
writer = table_writer_class()
writer.from_csv(file_path)
writer.write_table()
out, _err = capsys.readouterr()
assert writer.table_name == "test_data"
assert writer.headers == ["a", "b", "c", "dd", "e"]
print_test_result(expected=self.__CSV_EXPECTED, actual=out)
assert out == self.__CSV_EXPECTED
class Test_CsvTableWriter_write_table:
@pytest.mark.parametrize(
["col_delim", "header", "value", "expected"],
[
[data.col_delim, data.header, data.value, data.expected]
for data in normal_test_data_list
],
)
def test_normal(self, capsys, col_delim, header, value, expected):
writer = table_writer_class()
writer.column_delimiter = col_delim
writer.headers = header
writer.value_matrix = value
writer.write_table()
out, err = capsys.readouterr()
print_test_result(expected=expected, actual=out, error=err)
assert out == expected
assert writer.dumps() == expected
assert str(writer) == expected
def test_normal_escape_formula_injection(self, capsys):
writer = table_writer_class()
writer.headers = ["a", "b", "c", "d", "e"]
writer.value_matrix = [["a+b", "=a+b", "-a+b", "+a+b", "@a+b"]]
writer.update_preprocessor(is_escape_formula_injection=True)
writer.write_table()
expected = r""""a","b","c","d","e"
"a+b","\"=a+b","\"-a+b","\"+a+b","\"@a+b"
"""
out, err = capsys.readouterr()
print_test_result(expected=expected, actual=out, error=err)
assert out == expected
@pytest.mark.parametrize(
["header", "value", "expected"],
[[data.header, data.value, data.expected] for data in exception_test_data_list],
)
def test_exception(self, header, value, expected):
writer = table_writer_class()
writer.headers = header
writer.value_matrix = value
assert writer.dumps() == ""
assert str(writer) == ""
class Test_CsvTableWriter_write_table_iter:
@pytest.mark.parametrize(
["table", "header", "value", "expected"],
[
[
"tablename",
["ha", "hb", "hc"],
value_matrix_iter,
dedent(
"""\
"ha","hb","hc"
1,2,3
11,12,13
1,2,3
11,12,13
101,102,103
1001,1002,1003
"""
),
]
],
)
def test_normal(self, capsys, table, header, value, expected):
writer = table_writer_class()
writer.table_name = table
writer.headers = header
writer.value_matrix = value
writer.iteration_length = len(value)
writer.write_table_iter()
out, err = capsys.readouterr()
print_test_result(expected=expected, actual=out, error=err)
assert out == expected
@pytest.mark.parametrize(
["header", "value", "expected"],
[[data.header, data.value, data.expected] for data in exception_test_data_list],
)
def test_smoke_empty(self, header, value, expected):
writer = table_writer_class()
writer.headers = header
writer.value_matrix = value
writer.write_table_iter() | test/writer/text/test_csv_writer.py | import collections
import itertools
from textwrap import dedent
import pytest
import pytablewriter as ptw
from ..._common import print_test_result
from ...data import (
float_header_list,
float_value_matrix,
headers,
mix_header_list,
mix_value_matrix,
value_matrix,
value_matrix_iter,
value_matrix_with_none,
)
Data = collections.namedtuple("Data", "col_delim header value expected")
normal_test_data_list = [
Data(
col_delim=",",
header=headers,
value=value_matrix,
expected=dedent(
"""\
"a","b","c","dd","e"
1,123.1,"a",1,1
2,2.2,"bb",2.2,2.2
3,3.3,"ccc",3,"cccc"
"""
),
),
Data(
col_delim=",",
header=headers,
value=[],
expected=dedent(
"""\
"a","b","c","dd","e"
"""
),
),
Data(
col_delim=",",
header=[],
value=value_matrix,
expected=dedent(
"""\
1,123.1,"a",1,1
2,2.2,"bb",2.2,2.2
3,3.3,"ccc",3,"cccc"
"""
),
),
Data(
col_delim="\t",
header=None,
value=value_matrix,
expected=dedent(
"""\
1\t123.1\t"a"\t1\t1
2\t2.2\t"bb"\t2.2\t2.2
3\t3.3\t"ccc"\t3\t"cccc"
"""
),
),
Data(
col_delim=",",
header=headers,
value=value_matrix_with_none,
expected=dedent(
"""\
"a","b","c","dd","e"
1,,"a",1,
,2.2,,2.2,2.2
3,3.3,"ccc",,"cccc"
,,,,
"""
),
),
Data(
col_delim=",",
header=mix_header_list,
value=mix_value_matrix,
expected=dedent(
"""\
"i","f","c","if","ifc","bool","inf","nan","mix_num","time"
1,1.1,"aa",1,1,True,Infinity,NaN,1,"2017-01-01T00:00:00"
2,2.2,"bbb",2.2,2.2,False,Infinity,NaN,Infinity,"2017-01-02 03:04:05+09:00"
3,3.33,"cccc",-3,"ccc",True,Infinity,NaN,NaN,"2017-01-01T00:00:00"
"""
),
),
Data(
col_delim=",",
header=float_header_list,
value=float_value_matrix,
expected=dedent(
"""\
"a","b","c"
0.01,0.00125,0
1,99.9,0.01
1.2,999999.123,0.001
"""
),
),
Data(
col_delim=",",
header=["a\nb", "c\n\nd", "e\r\nf"],
value=[["v1\nv1", "v2\n\nv2", "v3\r\nv3"]],
expected=dedent(
"""\
"a b","c d","e f"
"v1 v1","v2 v2","v3 v3"
"""
),
),
]
exception_test_data_list = [
Data(col_delim=",", header=header, value=value, expected=ptw.EmptyTableDataError)
for header, value in itertools.product([None, [], ""], [None, [], ""])
]
table_writer_class = ptw.CsvTableWriter
class Test_CsvTableWriter_table_format:
def test_normal(self):
assert table_writer_class().table_format is ptw.TableFormat.CSV
class Test_CsvTableWriter_write_new_line:
def test_normal(self, capsys):
writer = table_writer_class()
writer.write_null_line()
out, _err = capsys.readouterr()
assert out == "\n"
class Test_CsvTableWriter_from_csv:
__CSV_TEXT_INPUT = dedent(
"""\
"a","b","c","dd","e"
1,1.1,"a",1.0,
2,2.2,,2.2,"2.2"
3,3.3,"ccc",,"cc\ncc"
"""
)
__CSV_EXPECTED = dedent(
"""\
"a","b","c","dd","e"
1,1.1,"a",1,
2,2.2,,2.2,2.2
3,3.3,"ccc",,"cc cc"
"""
)
def test_normal_from_text(self, capsys):
writer = table_writer_class()
writer.from_csv(self.__CSV_TEXT_INPUT)
writer.write_table()
out, _err = capsys.readouterr()
assert writer.table_name == ""
assert writer.headers == ["a", "b", "c", "dd", "e"]
print_test_result(expected=self.__CSV_EXPECTED, actual=out)
assert out == self.__CSV_EXPECTED
def test_normal_from_file(self, capsys, tmpdir):
file_path = str(tmpdir.join("test_data.csv"))
with open(file_path, "w", encoding="utf-8") as f:
f.write(self.__CSV_TEXT_INPUT)
writer = table_writer_class()
writer.from_csv(file_path)
writer.write_table()
out, _err = capsys.readouterr()
assert writer.table_name == "test_data"
assert writer.headers == ["a", "b", "c", "dd", "e"]
print_test_result(expected=self.__CSV_EXPECTED, actual=out)
assert out == self.__CSV_EXPECTED
class Test_CsvTableWriter_write_table:
@pytest.mark.parametrize(
["col_delim", "header", "value", "expected"],
[
[data.col_delim, data.header, data.value, data.expected]
for data in normal_test_data_list
],
)
def test_normal(self, capsys, col_delim, header, value, expected):
writer = table_writer_class()
writer.column_delimiter = col_delim
writer.headers = header
writer.value_matrix = value
writer.write_table()
out, err = capsys.readouterr()
print_test_result(expected=expected, actual=out, error=err)
assert out == expected
assert writer.dumps() == expected
assert str(writer) == expected
def test_normal_escape_formula_injection(self, capsys):
writer = table_writer_class()
writer.headers = ["a", "b", "c", "d", "e"]
writer.value_matrix = [["a+b", "=a+b", "-a+b", "+a+b", "@a+b"]]
writer.update_preprocessor(is_escape_formula_injection=True)
writer.write_table()
expected = r""""a","b","c","d","e"
"a+b","\"=a+b","\"-a+b","\"+a+b","\"@a+b"
"""
out, err = capsys.readouterr()
print_test_result(expected=expected, actual=out, error=err)
assert out == expected
@pytest.mark.parametrize(
["header", "value", "expected"],
[[data.header, data.value, data.expected] for data in exception_test_data_list],
)
def test_exception(self, header, value, expected):
writer = table_writer_class()
writer.headers = header
writer.value_matrix = value
assert writer.dumps() == ""
assert str(writer) == ""
class Test_CsvTableWriter_write_table_iter:
@pytest.mark.parametrize(
["table", "header", "value", "expected"],
[
[
"tablename",
["ha", "hb", "hc"],
value_matrix_iter,
dedent(
"""\
"ha","hb","hc"
1,2,3
11,12,13
1,2,3
11,12,13
101,102,103
1001,1002,1003
"""
),
]
],
)
def test_normal(self, capsys, table, header, value, expected):
writer = table_writer_class()
writer.table_name = table
writer.headers = header
writer.value_matrix = value
writer.iteration_length = len(value)
writer.write_table_iter()
out, err = capsys.readouterr()
print_test_result(expected=expected, actual=out, error=err)
assert out == expected
@pytest.mark.parametrize(
["header", "value", "expected"],
[[data.header, data.value, data.expected] for data in exception_test_data_list],
)
def test_smoke_empty(self, header, value, expected):
writer = table_writer_class()
writer.headers = header
writer.value_matrix = value
writer.write_table_iter() | 0.378115 | 0.445047 |
import argparse
import sys
from pathlib import Path
from typing import Callable, Dict
from determined.common.declarative_argparse import Arg, BoolOptArg, Cmd, Group
from . import cluster_utils
from .preflight import check_docker_install
def handle_cluster_up(args: argparse.Namespace) -> None:
if not args.no_preflight_checks:
check_docker_install()
cluster_utils.cluster_up(
num_agents=args.agents,
port=args.master_port,
master_config_path=args.master_config_path,
storage_host_path=args.storage_host_path,
cluster_name=args.cluster_name,
image_repo_prefix=args.image_repo_prefix,
version=args.det_version,
db_password=<PASSWORD>,
delete_db=args.delete_db,
gpu=args.gpu,
autorestart=(not args.no_autorestart),
auto_work_dir=args.auto_work_dir,
)
def handle_cluster_down(args: argparse.Namespace) -> None:
cluster_utils.cluster_down(cluster_name=args.cluster_name, delete_db=args.delete_db)
def handle_logs(args: argparse.Namespace) -> None:
cluster_utils.logs(cluster_name=args.cluster_name, no_follow=args.no_follow)
def handle_master_up(args: argparse.Namespace) -> None:
cluster_utils.master_up(
port=args.master_port,
master_config_path=args.master_config_path,
storage_host_path=args.storage_host_path,
master_name=args.master_name,
image_repo_prefix=args.image_repo_prefix,
version=args.det_version,
db_password=<PASSWORD>,
delete_db=args.delete_db,
autorestart=(not args.no_autorestart),
cluster_name=args.cluster_name,
auto_work_dir=args.auto_work_dir,
)
def handle_master_down(args: argparse.Namespace) -> None:
cluster_utils.master_down(master_name=args.master_name, delete_db=args.delete_db)
def handle_agent_up(args: argparse.Namespace) -> None:
cluster_utils.agent_up(
master_host=args.master_host,
master_port=args.master_port,
agent_config_path=args.agent_config_path,
gpu=args.gpu,
agent_name=args.agent_name,
agent_label=args.agent_label,
agent_resource_pool=args.agent_resource_pool,
image_repo_prefix=args.image_repo_prefix,
version=args.det_version,
labels=None,
autorestart=(not args.no_autorestart),
cluster_name=args.cluster_name,
)
def handle_agent_down(args: argparse.Namespace) -> None:
if args.all:
cluster_utils.stop_all_agents()
else:
cluster_utils.stop_agent(agent_name=args.agent_name)
def deploy_local(args: argparse.Namespace) -> None:
OPERATION_TO_FN = {
"agent-up": handle_agent_up,
"agent-down": handle_agent_down,
"cluster-up": handle_cluster_up,
"cluster-down": handle_cluster_down,
"logs": handle_logs,
"master-up": handle_master_up,
"master-down": handle_master_down,
} # type: Dict[str, Callable[[argparse.Namespace], None]]
OPERATION_TO_FN[args.command](args)
args_description = Cmd(
"local",
None,
"local help",
[
Cmd(
"cluster-up",
handle_cluster_up,
"Create a Determined cluster",
[
Group(
Arg(
"--master-config-path",
type=Path,
default=None,
help="path to master configuration",
),
Arg(
"--storage-host-path",
type=Path,
default=None,
help="Storage location for cluster data (e.g. checkpoints)",
),
),
Arg(
"--agents",
type=int,
default=1,
help="number of agents to start (on this machine)",
),
Arg(
"--master-port",
type=int,
default=cluster_utils.MASTER_PORT_DEFAULT,
help="port to expose master on",
),
Arg(
"--cluster-name",
type=str,
default="determined",
help="name for the cluster resources",
),
Arg("--det-version", type=str, default=None, help="version or commit to use"),
Arg(
"--db-password",
type=str,
default="<PASSWORD>",
help="password for master database",
),
Arg(
"--delete-db",
action="store_true",
help="remove current master database",
),
BoolOptArg(
"--gpu",
"--no-gpu",
dest="gpu",
default=("darwin" not in sys.platform),
true_help="enable GPU support for agent",
false_help="disable GPU support for agent",
),
Arg(
"--no-autorestart",
help="disable container auto-restart (recommended for local development)",
action="store_true",
),
Arg(
"--auto-work-dir",
type=Path,
default=None,
help="the default work dir, used for interactive jobs",
),
],
),
Cmd(
"cluster-down",
handle_cluster_down,
"Stop a Determined cluster",
[
Arg(
"--cluster-name",
type=str,
default="determined",
help="name for the cluster resources",
),
Arg(
"--delete-db",
action="store_true",
help="remove current master database",
),
],
),
Cmd(
"master-up",
handle_master_up,
"Start a Determined master",
[
Group(
Arg(
"--master-config-path",
type=Path,
default=None,
help="path to master configuration",
),
Arg(
"--storage-host-path",
type=Path,
default=None,
help="Storage location for cluster data (e.g. checkpoints)",
),
),
Arg(
"--master-port",
type=int,
default=cluster_utils.MASTER_PORT_DEFAULT,
help="port to expose master on",
),
Arg(
"--master-name",
type=str,
default="determined",
help="name for the cluster resources",
),
Arg("--det-version", type=str, default=None, help="version or commit to use"),
Arg(
"--db-password",
type=str,
default="<PASSWORD>",
help="password for master database",
),
Arg(
"--delete-db",
action="store_true",
help="remove current master database",
),
Arg(
"--no-autorestart",
help="disable container auto-restart (recommended for local development)",
action="store_true",
),
Arg(
"--cluster-name",
type=str,
default="determined",
help="name for the cluster resources",
),
Arg(
"--auto-work-dir",
type=Path,
default=None,
help="the default work dir, used for interactive jobs",
),
],
),
Cmd(
"master-down",
handle_master_down,
"Stop a Determined master",
[
Arg(
"--master-name",
type=str,
default="determined",
help="name for the cluster resources",
),
Arg(
"--delete-db",
action="store_true",
help="remove current master database",
),
Arg(
"--cluster-name",
type=str,
default="determined",
help="name for the cluster resources",
),
],
),
Cmd(
"logs",
handle_logs,
"Show the logs of a Determined cluster",
[
Arg(
"--cluster-name",
type=str,
default="determined",
help="name for the cluster resources",
),
Arg("--no-follow", help="disable following logs", action="store_true"),
],
),
Cmd(
"agent-up",
handle_agent_up,
"Start a Determined agent",
[
Arg("master_host", type=str, help="master hostname"),
Arg(
"--master-port",
type=int,
default=cluster_utils.MASTER_PORT_DEFAULT,
help="master port",
),
Arg(
"--agent-config-path",
type=Path,
default=None,
help="path to agent configuration",
),
Arg("--det-version", type=str, default=None, help="version or commit to use"),
Arg(
"--agent-name",
type=str,
default=cluster_utils.AGENT_NAME_DEFAULT,
help="agent name",
),
Arg("--agent-label", type=str, default=None, help="agent label"),
Arg("--agent-resource-pool", type=str, default=None, help="agent resource pool"),
BoolOptArg(
"--gpu",
"--no-gpu",
dest="gpu",
default=("darwin" not in sys.platform),
true_help="enable GPU support for agent",
false_help="disable GPU support for agent",
),
Arg(
"--no-autorestart",
help="disable container auto-restart (recommended for local development)",
action="store_true",
),
Arg(
"--cluster-name",
type=str,
default="determined",
help="name for the cluster resources",
),
],
),
Cmd(
"agent-down",
handle_agent_down,
"Stop a Determined agent",
[
Arg(
"--agent-name",
type=str,
default=cluster_utils.AGENT_NAME_DEFAULT,
help="agent name",
),
Arg("--all", help="stop all running agents", action="store_true"),
Arg(
"--cluster-name",
type=str,
default="determined",
help="name for the cluster resources",
),
],
),
],
) | harness/determined/deploy/local/cli.py | import argparse
import sys
from pathlib import Path
from typing import Callable, Dict
from determined.common.declarative_argparse import Arg, BoolOptArg, Cmd, Group
from . import cluster_utils
from .preflight import check_docker_install
def handle_cluster_up(args: argparse.Namespace) -> None:
if not args.no_preflight_checks:
check_docker_install()
cluster_utils.cluster_up(
num_agents=args.agents,
port=args.master_port,
master_config_path=args.master_config_path,
storage_host_path=args.storage_host_path,
cluster_name=args.cluster_name,
image_repo_prefix=args.image_repo_prefix,
version=args.det_version,
db_password=<PASSWORD>,
delete_db=args.delete_db,
gpu=args.gpu,
autorestart=(not args.no_autorestart),
auto_work_dir=args.auto_work_dir,
)
def handle_cluster_down(args: argparse.Namespace) -> None:
cluster_utils.cluster_down(cluster_name=args.cluster_name, delete_db=args.delete_db)
def handle_logs(args: argparse.Namespace) -> None:
cluster_utils.logs(cluster_name=args.cluster_name, no_follow=args.no_follow)
def handle_master_up(args: argparse.Namespace) -> None:
cluster_utils.master_up(
port=args.master_port,
master_config_path=args.master_config_path,
storage_host_path=args.storage_host_path,
master_name=args.master_name,
image_repo_prefix=args.image_repo_prefix,
version=args.det_version,
db_password=<PASSWORD>,
delete_db=args.delete_db,
autorestart=(not args.no_autorestart),
cluster_name=args.cluster_name,
auto_work_dir=args.auto_work_dir,
)
def handle_master_down(args: argparse.Namespace) -> None:
cluster_utils.master_down(master_name=args.master_name, delete_db=args.delete_db)
def handle_agent_up(args: argparse.Namespace) -> None:
cluster_utils.agent_up(
master_host=args.master_host,
master_port=args.master_port,
agent_config_path=args.agent_config_path,
gpu=args.gpu,
agent_name=args.agent_name,
agent_label=args.agent_label,
agent_resource_pool=args.agent_resource_pool,
image_repo_prefix=args.image_repo_prefix,
version=args.det_version,
labels=None,
autorestart=(not args.no_autorestart),
cluster_name=args.cluster_name,
)
def handle_agent_down(args: argparse.Namespace) -> None:
if args.all:
cluster_utils.stop_all_agents()
else:
cluster_utils.stop_agent(agent_name=args.agent_name)
def deploy_local(args: argparse.Namespace) -> None:
OPERATION_TO_FN = {
"agent-up": handle_agent_up,
"agent-down": handle_agent_down,
"cluster-up": handle_cluster_up,
"cluster-down": handle_cluster_down,
"logs": handle_logs,
"master-up": handle_master_up,
"master-down": handle_master_down,
} # type: Dict[str, Callable[[argparse.Namespace], None]]
OPERATION_TO_FN[args.command](args)
args_description = Cmd(
"local",
None,
"local help",
[
Cmd(
"cluster-up",
handle_cluster_up,
"Create a Determined cluster",
[
Group(
Arg(
"--master-config-path",
type=Path,
default=None,
help="path to master configuration",
),
Arg(
"--storage-host-path",
type=Path,
default=None,
help="Storage location for cluster data (e.g. checkpoints)",
),
),
Arg(
"--agents",
type=int,
default=1,
help="number of agents to start (on this machine)",
),
Arg(
"--master-port",
type=int,
default=cluster_utils.MASTER_PORT_DEFAULT,
help="port to expose master on",
),
Arg(
"--cluster-name",
type=str,
default="determined",
help="name for the cluster resources",
),
Arg("--det-version", type=str, default=None, help="version or commit to use"),
Arg(
"--db-password",
type=str,
default="<PASSWORD>",
help="password for master database",
),
Arg(
"--delete-db",
action="store_true",
help="remove current master database",
),
BoolOptArg(
"--gpu",
"--no-gpu",
dest="gpu",
default=("darwin" not in sys.platform),
true_help="enable GPU support for agent",
false_help="disable GPU support for agent",
),
Arg(
"--no-autorestart",
help="disable container auto-restart (recommended for local development)",
action="store_true",
),
Arg(
"--auto-work-dir",
type=Path,
default=None,
help="the default work dir, used for interactive jobs",
),
],
),
Cmd(
"cluster-down",
handle_cluster_down,
"Stop a Determined cluster",
[
Arg(
"--cluster-name",
type=str,
default="determined",
help="name for the cluster resources",
),
Arg(
"--delete-db",
action="store_true",
help="remove current master database",
),
],
),
Cmd(
"master-up",
handle_master_up,
"Start a Determined master",
[
Group(
Arg(
"--master-config-path",
type=Path,
default=None,
help="path to master configuration",
),
Arg(
"--storage-host-path",
type=Path,
default=None,
help="Storage location for cluster data (e.g. checkpoints)",
),
),
Arg(
"--master-port",
type=int,
default=cluster_utils.MASTER_PORT_DEFAULT,
help="port to expose master on",
),
Arg(
"--master-name",
type=str,
default="determined",
help="name for the cluster resources",
),
Arg("--det-version", type=str, default=None, help="version or commit to use"),
Arg(
"--db-password",
type=str,
default="<PASSWORD>",
help="password for master database",
),
Arg(
"--delete-db",
action="store_true",
help="remove current master database",
),
Arg(
"--no-autorestart",
help="disable container auto-restart (recommended for local development)",
action="store_true",
),
Arg(
"--cluster-name",
type=str,
default="determined",
help="name for the cluster resources",
),
Arg(
"--auto-work-dir",
type=Path,
default=None,
help="the default work dir, used for interactive jobs",
),
],
),
Cmd(
"master-down",
handle_master_down,
"Stop a Determined master",
[
Arg(
"--master-name",
type=str,
default="determined",
help="name for the cluster resources",
),
Arg(
"--delete-db",
action="store_true",
help="remove current master database",
),
Arg(
"--cluster-name",
type=str,
default="determined",
help="name for the cluster resources",
),
],
),
Cmd(
"logs",
handle_logs,
"Show the logs of a Determined cluster",
[
Arg(
"--cluster-name",
type=str,
default="determined",
help="name for the cluster resources",
),
Arg("--no-follow", help="disable following logs", action="store_true"),
],
),
Cmd(
"agent-up",
handle_agent_up,
"Start a Determined agent",
[
Arg("master_host", type=str, help="master hostname"),
Arg(
"--master-port",
type=int,
default=cluster_utils.MASTER_PORT_DEFAULT,
help="master port",
),
Arg(
"--agent-config-path",
type=Path,
default=None,
help="path to agent configuration",
),
Arg("--det-version", type=str, default=None, help="version or commit to use"),
Arg(
"--agent-name",
type=str,
default=cluster_utils.AGENT_NAME_DEFAULT,
help="agent name",
),
Arg("--agent-label", type=str, default=None, help="agent label"),
Arg("--agent-resource-pool", type=str, default=None, help="agent resource pool"),
BoolOptArg(
"--gpu",
"--no-gpu",
dest="gpu",
default=("darwin" not in sys.platform),
true_help="enable GPU support for agent",
false_help="disable GPU support for agent",
),
Arg(
"--no-autorestart",
help="disable container auto-restart (recommended for local development)",
action="store_true",
),
Arg(
"--cluster-name",
type=str,
default="determined",
help="name for the cluster resources",
),
],
),
Cmd(
"agent-down",
handle_agent_down,
"Stop a Determined agent",
[
Arg(
"--agent-name",
type=str,
default=cluster_utils.AGENT_NAME_DEFAULT,
help="agent name",
),
Arg("--all", help="stop all running agents", action="store_true"),
Arg(
"--cluster-name",
type=str,
default="determined",
help="name for the cluster resources",
),
],
),
],
) | 0.378 | 0.118207 |
from typing import Dict
from typing import Optional
from typing import Type
import asyncio
import time
import traceback
try:
from prometheus_client import Counter
from prometheus_client import Histogram
except ImportError:
Counter = Histogram = None
ERROR_NONE = "none"
ERROR_GENERAL_EXCEPTION = "exception"
class watch:
start: float
def __init__(
self,
*,
counter: Optional[Counter] = None,
histogram: Optional[Histogram] = None,
error_mappings: Dict[str, Type[BaseException]] = None,
labels: Optional[Dict[str, str]] = None,
):
self.counter = counter
self.histogram = histogram
self.labels = labels or {}
self.error_mappings = error_mappings or {}
def __enter__(self):
self.start = time.time()
return self
def __exit__(
self,
exc_type: Optional[Type[BaseException]],
exc_value: Optional[Exception],
exc_traceback: Optional[traceback.StackSummary],
):
if Counter is None:
return
error = ERROR_NONE
if self.histogram is not None:
finished = time.time()
if len(self.labels) > 0:
self.histogram.labels(**self.labels).observe(finished - self.start)
else:
self.histogram.observe(finished - self.start)
if self.counter is not None:
if exc_value is None:
error = ERROR_NONE
else:
for error_type, mapped_exc_type in self.error_mappings.items():
if isinstance(exc_value, mapped_exc_type):
error = error_type
break
else:
error = ERROR_GENERAL_EXCEPTION
self.counter.labels(error=error, **self.labels).inc()
class watch_lock:
def __init__(
self, histogram: Histogram, lock: asyncio.Lock, labels: Optional[Dict[str, str]] = None,
):
self.histogram = histogram
self.lock = lock
self.labels = labels or {}
async def __aenter__(self) -> None:
start = time.time()
await self.lock.acquire()
if self.histogram is not None:
finished = time.time()
if len(self.labels) > 0:
self.histogram.labels(**self.labels).observe(finished - start)
else:
self.histogram.observe(finished - start)
async def __aexit__(self, exc_type, exc, tb):
self.lock.release() | guillotina/metrics.py | from typing import Dict
from typing import Optional
from typing import Type
import asyncio
import time
import traceback
try:
from prometheus_client import Counter
from prometheus_client import Histogram
except ImportError:
Counter = Histogram = None
ERROR_NONE = "none"
ERROR_GENERAL_EXCEPTION = "exception"
class watch:
start: float
def __init__(
self,
*,
counter: Optional[Counter] = None,
histogram: Optional[Histogram] = None,
error_mappings: Dict[str, Type[BaseException]] = None,
labels: Optional[Dict[str, str]] = None,
):
self.counter = counter
self.histogram = histogram
self.labels = labels or {}
self.error_mappings = error_mappings or {}
def __enter__(self):
self.start = time.time()
return self
def __exit__(
self,
exc_type: Optional[Type[BaseException]],
exc_value: Optional[Exception],
exc_traceback: Optional[traceback.StackSummary],
):
if Counter is None:
return
error = ERROR_NONE
if self.histogram is not None:
finished = time.time()
if len(self.labels) > 0:
self.histogram.labels(**self.labels).observe(finished - self.start)
else:
self.histogram.observe(finished - self.start)
if self.counter is not None:
if exc_value is None:
error = ERROR_NONE
else:
for error_type, mapped_exc_type in self.error_mappings.items():
if isinstance(exc_value, mapped_exc_type):
error = error_type
break
else:
error = ERROR_GENERAL_EXCEPTION
self.counter.labels(error=error, **self.labels).inc()
class watch_lock:
def __init__(
self, histogram: Histogram, lock: asyncio.Lock, labels: Optional[Dict[str, str]] = None,
):
self.histogram = histogram
self.lock = lock
self.labels = labels or {}
async def __aenter__(self) -> None:
start = time.time()
await self.lock.acquire()
if self.histogram is not None:
finished = time.time()
if len(self.labels) > 0:
self.histogram.labels(**self.labels).observe(finished - start)
else:
self.histogram.observe(finished - start)
async def __aexit__(self, exc_type, exc, tb):
self.lock.release() | 0.795777 | 0.198763 |
import time
import logging
import requests
from .tor_proxy import TorProxy, TOR_SOCKS_PROXIES
from .free_proxy import FreeProxy
# Timeout for web server response (seconds)
TIMEOUT = 5
# Maximum retries count for executing request if an error occurred
MAX_RETRIES = 3
# The delay after executing an HTTP request (seconds)
# SLEEP_TIME = 1
SLEEP_TIME = 0.5
# HTTP headers for making the scraper more "human-like"
HEADERS = {
'User-Agent': ('Mozilla/5.0 (Windows NT 6.1; rv:88.0)'
' Gecko/20100101 Firefox/88.0'),
'Accept': '*/*',
}
ICANHAZIP_URL = 'http://icanhazip.com'
PROXY_TYPE_FREE = 'free'
PROXY_TYPE_TOR = 'tor'
class HttpRequest():
def __init__(self, headers: dict=HEADERS, max_retries: int=MAX_RETRIES,
timeout: float=TIMEOUT, sleep_time: float=SLEEP_TIME,
proxies=None, proxy_test_url: str=None):
# These attributes may be changed directly
self.headers = headers
self.max_retries = max_retries
self.timeout = timeout
self.sleep_time = sleep_time
self.proxies = proxies
self.proxy_test_url = proxy_test_url
# Don't change these atrributes from outside the class instance
self.tor_proxy = TorProxy()
self.free_proxy = FreeProxy()
self.proxy_index = -1
self.proxy = self._get_next_proxy()
def _get_next_proxy(self):
if self.proxies == None:
return None
elif isinstance(self.proxies, dict):
return self.proxies
elif isinstance(self.proxies, list):
self.proxy_index += 1
self.proxy_index = self.proxy_index % len(self.proxies)
return self.proxies[self.proxy_index]
elif self.proxies == PROXY_TYPE_FREE:
logging.info('Searching for free proxies.')
proxy = self.free_proxy.get_proxy(self.proxy_test_url)
return {'http': proxy, 'https': proxy}
elif self.proxies == PROXY_TYPE_TOR:
logging.info('Starting TOR.')
self.tor_proxy.restart()
return TOR_SOCKS_PROXIES
def rotate_proxy(self):
logging.info('Changing proxy (if possible).')
self.proxy = self._get_next_proxy()
logging.info('Now using IP: ' + self.get_ip())
def _request(self, func, **args) -> requests.Response:
args['headers'] = self.headers
args['timeout'] = self.timeout
args['proxies'] = self.proxy
for attempt in range(0, self.max_retries):
try:
r = func(**args)
except requests.exceptions.RequestException:
time.sleep(self.sleep_time)
else:
time.sleep(self.sleep_time)
if r.status_code != requests.codes.ok:
logging.error(f'Error {r.status_code} '
+ f'while accessing {args["url"]}.')
return None
return r
logging.error("Can't execute HTTP request while accessing "
+ args['url'])
return None
def get(self, url: str, params: dict=None):
args = {
'url': url,
'params': params,
}
func = requests.get
return self._request(func=func, **args)
def post(self, url: str, data: dict=None):
args = {
'url': url,
'data': data,
}
func = requests.post
return self._request(func=func, **args)
def get_ip(self) -> str:
ip = self.get(ICANHAZIP_URL)
if ip == None:
return None
return ip.text.strip()
# Retrieve an image from URL and save it to a file
def save_image(self, url: str, filename: str) -> bool:
r = self.get(url)
try:
with open(filename, 'wb') as f:
f.write(r.content)
except OSError:
logging.exception(f"Can't save the image to the file {filename}.")
return False
except Exception:
logging.exception(f'Failure while retrieving an image from {url}.')
return False
return True
# For testing
def main():
logging.basicConfig(level=logging.INFO)
request = HttpRequest(proxies=PROXY_TYPE_FREE)
print(request.get_ip())
if __name__ == '__main__':
main() | utils/http_request.py | import time
import logging
import requests
from .tor_proxy import TorProxy, TOR_SOCKS_PROXIES
from .free_proxy import FreeProxy
# Timeout for web server response (seconds)
TIMEOUT = 5
# Maximum retries count for executing request if an error occurred
MAX_RETRIES = 3
# The delay after executing an HTTP request (seconds)
# SLEEP_TIME = 1
SLEEP_TIME = 0.5
# HTTP headers for making the scraper more "human-like"
HEADERS = {
'User-Agent': ('Mozilla/5.0 (Windows NT 6.1; rv:88.0)'
' Gecko/20100101 Firefox/88.0'),
'Accept': '*/*',
}
ICANHAZIP_URL = 'http://icanhazip.com'
PROXY_TYPE_FREE = 'free'
PROXY_TYPE_TOR = 'tor'
class HttpRequest():
def __init__(self, headers: dict=HEADERS, max_retries: int=MAX_RETRIES,
timeout: float=TIMEOUT, sleep_time: float=SLEEP_TIME,
proxies=None, proxy_test_url: str=None):
# These attributes may be changed directly
self.headers = headers
self.max_retries = max_retries
self.timeout = timeout
self.sleep_time = sleep_time
self.proxies = proxies
self.proxy_test_url = proxy_test_url
# Don't change these atrributes from outside the class instance
self.tor_proxy = TorProxy()
self.free_proxy = FreeProxy()
self.proxy_index = -1
self.proxy = self._get_next_proxy()
def _get_next_proxy(self):
if self.proxies == None:
return None
elif isinstance(self.proxies, dict):
return self.proxies
elif isinstance(self.proxies, list):
self.proxy_index += 1
self.proxy_index = self.proxy_index % len(self.proxies)
return self.proxies[self.proxy_index]
elif self.proxies == PROXY_TYPE_FREE:
logging.info('Searching for free proxies.')
proxy = self.free_proxy.get_proxy(self.proxy_test_url)
return {'http': proxy, 'https': proxy}
elif self.proxies == PROXY_TYPE_TOR:
logging.info('Starting TOR.')
self.tor_proxy.restart()
return TOR_SOCKS_PROXIES
def rotate_proxy(self):
logging.info('Changing proxy (if possible).')
self.proxy = self._get_next_proxy()
logging.info('Now using IP: ' + self.get_ip())
def _request(self, func, **args) -> requests.Response:
args['headers'] = self.headers
args['timeout'] = self.timeout
args['proxies'] = self.proxy
for attempt in range(0, self.max_retries):
try:
r = func(**args)
except requests.exceptions.RequestException:
time.sleep(self.sleep_time)
else:
time.sleep(self.sleep_time)
if r.status_code != requests.codes.ok:
logging.error(f'Error {r.status_code} '
+ f'while accessing {args["url"]}.')
return None
return r
logging.error("Can't execute HTTP request while accessing "
+ args['url'])
return None
def get(self, url: str, params: dict=None):
args = {
'url': url,
'params': params,
}
func = requests.get
return self._request(func=func, **args)
def post(self, url: str, data: dict=None):
args = {
'url': url,
'data': data,
}
func = requests.post
return self._request(func=func, **args)
def get_ip(self) -> str:
ip = self.get(ICANHAZIP_URL)
if ip == None:
return None
return ip.text.strip()
# Retrieve an image from URL and save it to a file
def save_image(self, url: str, filename: str) -> bool:
r = self.get(url)
try:
with open(filename, 'wb') as f:
f.write(r.content)
except OSError:
logging.exception(f"Can't save the image to the file {filename}.")
return False
except Exception:
logging.exception(f'Failure while retrieving an image from {url}.')
return False
return True
# For testing
def main():
logging.basicConfig(level=logging.INFO)
request = HttpRequest(proxies=PROXY_TYPE_FREE)
print(request.get_ip())
if __name__ == '__main__':
main() | 0.568296 | 0.082143 |
from insights import CommandParser, parser
from insights.parsers import SkipException, parse_fixed_table
from insights.specs import Specs
class PodmanList(CommandParser):
"""
A general class for parsing tabular podman list information. Parsing
rules are:
* The first line is the header line.
* The other lines are data lines.
* All fields line up vertically.
* Fields are separated from each other by at least three spaces.
* Some fields can contain nothing, and this is shown as spaces, so we
need to catch that and turn it into None.
Why not just use hard-coded fields and columns? So that we can adapt to
different output lists.
Raises:
NotImplementedError: If `key_field` or `attr_name` is not defined
SkipException: If no data to parse
"""
key_field = ''
heading_ignore = []
attr_name = ''
substitutions = []
def parse_content(self, content):
if not (self.key_field and self.attr_name):
raise NotImplementedError("'key_field' or 'attr_name' is not defined")
self.rows = parse_fixed_table(content,
heading_ignore=self.heading_ignore,
header_substitute=self.substitutions)
if not self.rows:
raise SkipException('No data.')
data = {}
for row in self.rows:
k = row.get(self.key_field)
for sub in self.substitutions:
row[sub[0]] = row.pop(sub[1])
if k is not None and k != '<none>':
data[k] = row
setattr(self, self.attr_name, data)
@parser(Specs.podman_list_images)
class PodmanListImages(PodmanList):
"""
Handle the list of podman images using the PodmanList parser class.
Sample output of command ``podman images --all --no-trunc --digests``::
REPOSITORY TAG DIGEST IMAGE ID CREATED SIZE
rhel6_vsftpd latest <none> 412b684338a1178f0e5ad68a5fd00df01a10a18495959398b2cf92c2033d3d02 37 minutes ago 459.5 MB
rhel7_imagemagick latest <none> 882ab98aae5394aebe91fe6d8a4297fa0387c3cfd421b2d892bddf218ac373b2 4 days ago 785.4 MB
rhel6_nss-softokn latest <none> dd87dad2c7841a19263ae2dc96d32c501ee84a92f56aed75bb67f57efe4e48b5 5 days ago 449.7 MB
Attributes:
rows (list): List of row dictionaries.
images (dict): Dictionary keyed on the value of the "REPOSITORY" fileld
Examples:
>>> images.rows[0]['REPOSITORY']
'rhel6_vsftpd'
>>> images.rows[1]['SIZE']
'785.4 MB'
>>> images.images['rhel6_vsftpd']['CREATED']
'37 minutes ago'
"""
key_field = 'REPOSITORY'
heading_ignore = [key_field]
attr_name = 'images'
substitutions = [("IMAGE ID", "IMAGE_ID")]
@parser(Specs.podman_list_containers)
class PodmanListContainers(PodmanList):
"""
Handle the list of podman containers using the PodmanList parser class.
Sample output of command ``podman ps --all --no-trunc --size``::
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES SIZE
03e2861336a76e29155836113ff6560cb70780c32f95062642993b2b3d0fc216 rhel7_httpd "/usr/sbin/httpd -DFOREGROUND" 45 seconds ago Up 37 seconds 0.0.0.0:8080->80/tcp angry_saha 796 B (virtual 669.2 MB)
95516ea08b565e37e2a4bca3333af40a240c368131b77276da8dec629b7fe102 bd8638c869ea40a9269d87e9af6741574562af9ee013e03ac2745fb5f59e2478 "/bin/sh -c 'yum install -y vsftpd-2.2.2-6.el6'" 51 minutes ago Exited (137) 50 minutes ago tender_rosalind 4.751 MB (virtual 200.4 MB)
Attributes:
rows (list): List of row dictionaries.
containers(dict): Dictionary keyed on the value of the "NAMES" field
Examples:
>>> containers.rows[0]['NAMES']
'angry_saha'
>>> containers.rows[0]['STATUS']
'Up 37 seconds'
>>> containers.containers['tender_rosalind']['STATUS']
'Exited (137) 18 hours ago'
"""
key_field = 'NAMES'
heading_ignore = ['CONTAINER']
attr_name = 'containers'
substitutions = [("CONTAINER ID", "CONTAINER_ID")] | insights/parsers/podman_list.py | from insights import CommandParser, parser
from insights.parsers import SkipException, parse_fixed_table
from insights.specs import Specs
class PodmanList(CommandParser):
"""
A general class for parsing tabular podman list information. Parsing
rules are:
* The first line is the header line.
* The other lines are data lines.
* All fields line up vertically.
* Fields are separated from each other by at least three spaces.
* Some fields can contain nothing, and this is shown as spaces, so we
need to catch that and turn it into None.
Why not just use hard-coded fields and columns? So that we can adapt to
different output lists.
Raises:
NotImplementedError: If `key_field` or `attr_name` is not defined
SkipException: If no data to parse
"""
key_field = ''
heading_ignore = []
attr_name = ''
substitutions = []
def parse_content(self, content):
if not (self.key_field and self.attr_name):
raise NotImplementedError("'key_field' or 'attr_name' is not defined")
self.rows = parse_fixed_table(content,
heading_ignore=self.heading_ignore,
header_substitute=self.substitutions)
if not self.rows:
raise SkipException('No data.')
data = {}
for row in self.rows:
k = row.get(self.key_field)
for sub in self.substitutions:
row[sub[0]] = row.pop(sub[1])
if k is not None and k != '<none>':
data[k] = row
setattr(self, self.attr_name, data)
@parser(Specs.podman_list_images)
class PodmanListImages(PodmanList):
"""
Handle the list of podman images using the PodmanList parser class.
Sample output of command ``podman images --all --no-trunc --digests``::
REPOSITORY TAG DIGEST IMAGE ID CREATED SIZE
rhel6_vsftpd latest <none> 412b684338a1178f0e5ad68a5fd00df01a10a18495959398b2cf92c2033d3d02 37 minutes ago 459.5 MB
rhel7_imagemagick latest <none> 882ab98aae5394aebe91fe6d8a4297fa0387c3cfd421b2d892bddf218ac373b2 4 days ago 785.4 MB
rhel6_nss-softokn latest <none> dd87dad2c7841a19263ae2dc96d32c501ee84a92f56aed75bb67f57efe4e48b5 5 days ago 449.7 MB
Attributes:
rows (list): List of row dictionaries.
images (dict): Dictionary keyed on the value of the "REPOSITORY" fileld
Examples:
>>> images.rows[0]['REPOSITORY']
'rhel6_vsftpd'
>>> images.rows[1]['SIZE']
'785.4 MB'
>>> images.images['rhel6_vsftpd']['CREATED']
'37 minutes ago'
"""
key_field = 'REPOSITORY'
heading_ignore = [key_field]
attr_name = 'images'
substitutions = [("IMAGE ID", "IMAGE_ID")]
@parser(Specs.podman_list_containers)
class PodmanListContainers(PodmanList):
"""
Handle the list of podman containers using the PodmanList parser class.
Sample output of command ``podman ps --all --no-trunc --size``::
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES SIZE
03e2861336a76e29155836113ff6560cb70780c32f95062642993b2b3d0fc216 rhel7_httpd "/usr/sbin/httpd -DFOREGROUND" 45 seconds ago Up 37 seconds 0.0.0.0:8080->80/tcp angry_saha 796 B (virtual 669.2 MB)
95516ea08b565e37e2a4bca3333af40a240c368131b77276da8dec629b7fe102 bd8638c869ea40a9269d87e9af6741574562af9ee013e03ac2745fb5f59e2478 "/bin/sh -c 'yum install -y vsftpd-2.2.2-6.el6'" 51 minutes ago Exited (137) 50 minutes ago tender_rosalind 4.751 MB (virtual 200.4 MB)
Attributes:
rows (list): List of row dictionaries.
containers(dict): Dictionary keyed on the value of the "NAMES" field
Examples:
>>> containers.rows[0]['NAMES']
'angry_saha'
>>> containers.rows[0]['STATUS']
'Up 37 seconds'
>>> containers.containers['tender_rosalind']['STATUS']
'Exited (137) 18 hours ago'
"""
key_field = 'NAMES'
heading_ignore = ['CONTAINER']
attr_name = 'containers'
substitutions = [("CONTAINER ID", "CONTAINER_ID")] | 0.714429 | 0.445469 |
import os
from flask import Flask, render_template, request, url_for, abort, redirect
from flask_cloudy import Storage
import pandas as pd
import math
port = int(os.getenv('PORT', 8000))
curr_file = None
app = Flask(__name__)
app.config.update({
"STORAGE_PROVIDER": "LOCAL", # Can also be S3, GOOGLE_STORAGE, etc...
"STORAGE_KEY": "",
"STORAGE_SECRET": "",
"STORAGE_CONTAINER": "./files", # a directory path for local, bucket name of cloud
"STORAGE_SERVER": True,
"STORAGE_SERVER_URL": "/files" # The url endpoint to access files on LOCAL provider
})
# Setup storage
storage = Storage()
storage.init_app(app)
@app.route("/")
def index():
csv_obj, other_obj = [], []
for obj in storage:
fname = obj.name
if fname.split('.')[-1]=='csv':
csv_obj.append(obj)
else:
other_obj.append(obj)
return render_template("index.html", csv_obj=csv_obj, other_obj=other_obj)
@app.route("/view/<path:object_name>")
def view(object_name):
obj = storage.get(object_name)
f_type = obj.name.split('.')[-1]
if f_type=='csv':
df = pd.read_csv('.'+obj.url, engine='python')
global curr_file
curr_file = '.'+obj.url
img_list = df['Picture'].values.tolist()
names = df['Name'].values.tolist()
img_urls = ['./files/'+u for u in img_list if isinstance(u, str)]
info = df.values.tolist()
elif f_type=='jpg':
info, img_urls, names = None, None, None
else:
info, img_urls, names = None, None, None
return render_template("view.html", obj=obj, info=info, img_urls=img_urls, names=names)
@app.route("/upload", methods=["POST"])
def upload():
usr_file = request.files.get("file")
my_object = storage.upload(usr_file)
return redirect(url_for("view", object_name=my_object.name))
@app.route("/people_by_grade", methods=['POST'])
def search_people_by_grade():
low = request.form['low_grade']
high = request.form['high_grade']
df = pd.read_csv(curr_file, engine='python')
resp = []
for _, line in df.iterrows():
if line[1] != ' ' and not math.isnan(float(line[1])):
if int(low)<=int(line[1])<=int(high):
if isinstance(line[4], str):
resp.append([line[0], './files/'+line[4], line[3]])
return render_template("people_by_grade.html", grade_resp=resp)
@app.route("/people_by_room", methods=['POST'])
def search_people_by_room():
room_number = int(float(request.form['room_number']))
# print('daad', room_number, type(room_number))
df = pd.read_csv(curr_file, engine='python')
resp = []
for _, line in df.iterrows():
if not math.isnan(line[2]):
if int(line[2])==int(room_number):
if isinstance(line[4], str):
resp.append([line[0], './files/'+line[4]])
return render_template("people_by_room.html", people=resp)
@app.route("/change_info", methods=['POST'])
def change_people_info():
ppl = request.form['change_people']
area = request.form['change_area']
val = request.form['target_value']
df = pd.read_csv(curr_file, engine='python')
df.at[df['Name']==ppl, area] = int(val)
info = df.values.tolist()
df.to_csv(curr_file, index=False)
img_url = './files/'+ ppl + '.jpg'
return render_template("change_info.html", info=info, img_url=img_url)
if __name__ == '__main__':
app.run(host="0.0.0.0", port=port, debug=True) | quiz0/main.py | import os
from flask import Flask, render_template, request, url_for, abort, redirect
from flask_cloudy import Storage
import pandas as pd
import math
port = int(os.getenv('PORT', 8000))
curr_file = None
app = Flask(__name__)
app.config.update({
"STORAGE_PROVIDER": "LOCAL", # Can also be S3, GOOGLE_STORAGE, etc...
"STORAGE_KEY": "",
"STORAGE_SECRET": "",
"STORAGE_CONTAINER": "./files", # a directory path for local, bucket name of cloud
"STORAGE_SERVER": True,
"STORAGE_SERVER_URL": "/files" # The url endpoint to access files on LOCAL provider
})
# Setup storage
storage = Storage()
storage.init_app(app)
@app.route("/")
def index():
csv_obj, other_obj = [], []
for obj in storage:
fname = obj.name
if fname.split('.')[-1]=='csv':
csv_obj.append(obj)
else:
other_obj.append(obj)
return render_template("index.html", csv_obj=csv_obj, other_obj=other_obj)
@app.route("/view/<path:object_name>")
def view(object_name):
obj = storage.get(object_name)
f_type = obj.name.split('.')[-1]
if f_type=='csv':
df = pd.read_csv('.'+obj.url, engine='python')
global curr_file
curr_file = '.'+obj.url
img_list = df['Picture'].values.tolist()
names = df['Name'].values.tolist()
img_urls = ['./files/'+u for u in img_list if isinstance(u, str)]
info = df.values.tolist()
elif f_type=='jpg':
info, img_urls, names = None, None, None
else:
info, img_urls, names = None, None, None
return render_template("view.html", obj=obj, info=info, img_urls=img_urls, names=names)
@app.route("/upload", methods=["POST"])
def upload():
usr_file = request.files.get("file")
my_object = storage.upload(usr_file)
return redirect(url_for("view", object_name=my_object.name))
@app.route("/people_by_grade", methods=['POST'])
def search_people_by_grade():
low = request.form['low_grade']
high = request.form['high_grade']
df = pd.read_csv(curr_file, engine='python')
resp = []
for _, line in df.iterrows():
if line[1] != ' ' and not math.isnan(float(line[1])):
if int(low)<=int(line[1])<=int(high):
if isinstance(line[4], str):
resp.append([line[0], './files/'+line[4], line[3]])
return render_template("people_by_grade.html", grade_resp=resp)
@app.route("/people_by_room", methods=['POST'])
def search_people_by_room():
room_number = int(float(request.form['room_number']))
# print('daad', room_number, type(room_number))
df = pd.read_csv(curr_file, engine='python')
resp = []
for _, line in df.iterrows():
if not math.isnan(line[2]):
if int(line[2])==int(room_number):
if isinstance(line[4], str):
resp.append([line[0], './files/'+line[4]])
return render_template("people_by_room.html", people=resp)
@app.route("/change_info", methods=['POST'])
def change_people_info():
ppl = request.form['change_people']
area = request.form['change_area']
val = request.form['target_value']
df = pd.read_csv(curr_file, engine='python')
df.at[df['Name']==ppl, area] = int(val)
info = df.values.tolist()
df.to_csv(curr_file, index=False)
img_url = './files/'+ ppl + '.jpg'
return render_template("change_info.html", info=info, img_url=img_url)
if __name__ == '__main__':
app.run(host="0.0.0.0", port=port, debug=True) | 0.105498 | 0.065098 |
"""This file implements the functionalities of a minitaur using pybullet."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import collections
import copy
import math
import re
import numpy as np
from locomotion.robots import minitaur_constants
from locomotion.robots import minitaur_motor
from locomotion.robots import robot_config
from locomotion.robots import action_filter
from locomotion.robots import kinematics
INIT_POSITION = [0, 0, .2]
INIT_RACK_POSITION = [0, 0, 1]
INIT_ORIENTATION = [0, 0, 0, 1]
KNEE_CONSTRAINT_POINT_RIGHT = [0, 0.005, 0.2]
KNEE_CONSTRAINT_POINT_LEFT = [0, 0.01, 0.2]
OVERHEAT_SHUTDOWN_TORQUE = 2.45
OVERHEAT_SHUTDOWN_TIME = 1.0
LEG_POSITION = ["front_left", "back_left", "front_right", "back_right"]
MOTOR_NAMES = [
"motor_front_leftL_joint", "motor_front_leftR_joint",
"motor_back_leftL_joint", "motor_back_leftR_joint",
"motor_front_rightL_joint", "motor_front_rightR_joint",
"motor_back_rightL_joint", "motor_back_rightR_joint"
]
_CHASSIS_NAME_PATTERN = re.compile(r"chassis\D*center")
_MOTOR_NAME_PATTERN = re.compile(r"motor\D*joint")
_KNEE_NAME_PATTERN = re.compile(r"knee\D*")
_BRACKET_NAME_PATTERN = re.compile(r"motor\D*_bracket_joint")
_LEG_NAME_PATTERN1 = re.compile(r"hip\D*joint")
_LEG_NAME_PATTERN2 = re.compile(r"hip\D*link")
_LEG_NAME_PATTERN3 = re.compile(r"motor\D*link")
SENSOR_NOISE_STDDEV = (0.0, 0.0, 0.0, 0.0, 0.0)
MINITAUR_DEFAULT_MOTOR_DIRECTIONS = (-1, -1, -1, -1, 1, 1, 1, 1)
MINITAUR_DEFAULT_MOTOR_OFFSETS = (0, 0, 0, 0, 0, 0, 0, 0)
MINITAUR_NUM_MOTORS = 8
TWO_PI = 2 * math.pi
MINITAUR_DOFS_PER_LEG = 2
def MapToMinusPiToPi(angles):
"""Maps a list of angles to [-pi, pi].
Args:
angles: A list of angles in rad.
Returns:
A list of angle mapped to [-pi, pi].
"""
mapped_angles = copy.deepcopy(angles)
for i in range(len(angles)):
mapped_angles[i] = math.fmod(angles[i], TWO_PI)
if mapped_angles[i] >= math.pi:
mapped_angles[i] -= TWO_PI
elif mapped_angles[i] < -math.pi:
mapped_angles[i] += TWO_PI
return mapped_angles
class Minitaur(object):
"""The minitaur class that simulates a quadruped robot from Ghost Robotics."""
def __init__(self,
pybullet_client,
num_motors=MINITAUR_NUM_MOTORS,
dofs_per_leg=MINITAUR_DOFS_PER_LEG,
time_step=0.01,
action_repeat=1,
self_collision_enabled=False,
motor_control_mode=robot_config.MotorControlMode.POSITION,
motor_model_class=minitaur_motor.MotorModel,
motor_kp=1.0,
motor_kd=0.02,
motor_torque_limits=None,
pd_latency=0.0,
control_latency=0.0,
observation_noise_stdev=SENSOR_NOISE_STDDEV,
motor_overheat_protection=False,
motor_direction=MINITAUR_DEFAULT_MOTOR_DIRECTIONS,
motor_offset=MINITAUR_DEFAULT_MOTOR_OFFSETS,
on_rack=False,
reset_at_current_position=False,
sensors=None,
enable_action_interpolation=False,
enable_action_filter=False,
reset_time=-1):
"""Constructs a minitaur and reset it to the initial states.
Args:
pybullet_client: The instance of BulletClient to manage different
simulations.
num_motors: The number of the motors on the robot.
dofs_per_leg: The number of degrees of freedom for each leg.
time_step: The time step of the simulation.
action_repeat: The number of ApplyAction() for each control step.
self_collision_enabled: Whether to enable self collision.
motor_control_mode: Enum. Can either be POSITION, TORQUE, or HYBRID.
motor_model_class: We can choose from simple pd model to more accureate DC
motor models.
motor_kp: proportional gain for the motors.
motor_kd: derivative gain for the motors.
motor_torque_limits: Torque limits for the motors. Can be a single float
or a list of floats specifying different limits for different robots. If
not provided, the default limit of the robot is used.
pd_latency: The latency of the observations (in seconds) used to calculate
PD control. On the real hardware, it is the latency between the
microcontroller and the motor controller.
control_latency: The latency of the observations (in second) used to
calculate action. On the real hardware, it is the latency from the motor
controller, the microcontroller to the host (Nvidia TX2).
observation_noise_stdev: The standard deviation of a Gaussian noise model
for the sensor. It should be an array for separate sensors in the
following order [motor_angle, motor_velocity, motor_torque,
base_roll_pitch_yaw, base_angular_velocity]
motor_overheat_protection: Whether to shutdown the motor that has exerted
large torque (OVERHEAT_SHUTDOWN_TORQUE) for an extended amount of time
(OVERHEAT_SHUTDOWN_TIME). See ApplyAction() in minitaur.py for more
details.
motor_direction: A list of direction values, either 1 or -1, to compensate
the axis difference of motors between the simulation and the real robot.
motor_offset: A list of offset value for the motor angles. This is used to
compensate the angle difference between the simulation and the real
robot.
on_rack: Whether to place the minitaur on rack. This is only used to debug
the walking gait. In this mode, the minitaur's base is hanged midair so
that its walking gait is clearer to visualize.
reset_at_current_position: Whether to reset the minitaur at the current
position and orientation. This is for simulating the reset behavior in
the real world.
sensors: a list of sensors that are attached to the robot.
enable_action_interpolation: Whether to interpolate the current action
with the previous action in order to produce smoother motions
enable_action_filter: Boolean specifying if a lowpass filter should be
used to smooth actions.
"""
self.num_motors = num_motors
self.num_legs = self.num_motors // dofs_per_leg
self._pybullet_client = pybullet_client
self._action_repeat = action_repeat
self._self_collision_enabled = self_collision_enabled
self._motor_direction = motor_direction
self._motor_offset = motor_offset
self._observed_motor_torques = np.zeros(self.num_motors)
self._applied_motor_torques = np.zeros(self.num_motors)
self._max_force = 3.5
self._pd_latency = pd_latency
self._control_latency = control_latency
self._observation_noise_stdev = observation_noise_stdev
self._observation_history = collections.deque(maxlen=100)
self._control_observation = []
self._chassis_link_ids = [-1]
self._leg_link_ids = []
self._motor_link_ids = []
self._foot_link_ids = []
self._motor_overheat_protection = motor_overheat_protection
self._on_rack = on_rack
self._reset_at_current_position = reset_at_current_position
self.SetAllSensors(sensors if sensors is not None else list())
self._is_safe = True
self._enable_action_interpolation = enable_action_interpolation
self._enable_action_filter = enable_action_filter
self._last_action = None
if not motor_model_class:
raise ValueError("Must provide a motor model class!")
if self._on_rack and self._reset_at_current_position:
raise ValueError("on_rack and reset_at_current_position "
"cannot be enabled together")
if isinstance(motor_kp, (collections.Sequence, np.ndarray)):
self._motor_kps = np.asarray(motor_kp)
else:
self._motor_kps = np.full(num_motors, motor_kp)
if isinstance(motor_kd, (collections.Sequence, np.ndarray)):
self._motor_kds = np.asarray(motor_kd)
else:
self._motor_kds = np.full(num_motors, motor_kd)
if isinstance(motor_torque_limits, (collections.Sequence, np.ndarray)):
self._motor_torque_limits = np.asarray(motor_torque_limits)
elif motor_torque_limits is None:
self._motor_torque_limits = None
else:
self._motor_torque_limits = motor_torque_limits
self._motor_control_mode = motor_control_mode
self._motor_model = motor_model_class(
kp=motor_kp,
kd=motor_kd,
torque_limits=self._motor_torque_limits,
motor_control_mode=motor_control_mode)
self.time_step = time_step
self._step_counter = 0
# This also includes the time spent during the Reset motion.
self._state_action_counter = 0
_, self._init_orientation_inv = self._pybullet_client.invertTransform(
position=[0, 0, 0], orientation=self._GetDefaultInitOrientation())
if self._enable_action_filter:
self._action_filter = self._BuildActionFilter()
# reset_time=-1.0 means skipping the reset motion.
# See Reset for more details.
self.Reset(reset_time=reset_time)
self.ReceiveObservation()
def GetTimeSinceReset(self):
return self._step_counter * self.time_step
def _StepInternal(self, action, motor_control_mode=None):
self.ApplyAction(action, motor_control_mode)
self._pybullet_client.stepSimulation()
self.ReceiveObservation()
self._state_action_counter += 1
def Step(self, action, motor_control_mode=None):
"""Steps simulation."""
if self._enable_action_filter:
action = self._FilterAction(action)
for i in range(self._action_repeat):
proc_action = self.ProcessAction(action, i)
self._StepInternal(proc_action, motor_control_mode)
self._step_counter += 1
self._last_action = action
def Terminate(self):
pass
def GetFootLinkIDs(self):
"""Get list of IDs for all foot links."""
return self._foot_link_ids
def _RecordMassInfoFromURDF(self):
"""Records the mass information from the URDF file."""
self._base_mass_urdf = []
for chassis_id in self._chassis_link_ids:
self._base_mass_urdf.append(
self._pybullet_client.getDynamicsInfo(self.quadruped, chassis_id)[0])
self._leg_masses_urdf = []
for leg_id in self._leg_link_ids:
self._leg_masses_urdf.append(
self._pybullet_client.getDynamicsInfo(self.quadruped, leg_id)[0])
for motor_id in self._motor_link_ids:
self._leg_masses_urdf.append(
self._pybullet_client.getDynamicsInfo(self.quadruped, motor_id)[0])
def _RecordInertiaInfoFromURDF(self):
"""Record the inertia of each body from URDF file."""
self._link_urdf = []
num_bodies = self._pybullet_client.getNumJoints(self.quadruped)
for body_id in range(-1, num_bodies): # -1 is for the base link.
inertia = self._pybullet_client.getDynamicsInfo(self.quadruped,
body_id)[2]
self._link_urdf.append(inertia)
# We need to use id+1 to index self._link_urdf because it has the base
# (index = -1) at the first element.
self._base_inertia_urdf = [
self._link_urdf[chassis_id + 1]
for chassis_id in self._chassis_link_ids
]
self._leg_inertia_urdf = [
self._link_urdf[leg_id + 1] for leg_id in self._leg_link_ids
]
self._leg_inertia_urdf.extend(
[self._link_urdf[motor_id + 1] for motor_id in self._motor_link_ids])
def _BuildJointNameToIdDict(self):
num_joints = self._pybullet_client.getNumJoints(self.quadruped)
self._joint_name_to_id = {}
for i in range(num_joints):
joint_info = self._pybullet_client.getJointInfo(self.quadruped, i)
self._joint_name_to_id[joint_info[1].decode("UTF-8")] = joint_info[0]
def _BuildUrdfIds(self):
"""Build the link Ids from its name in the URDF file.
Raises:
ValueError: Unknown category of the joint name.
"""
num_joints = self._pybullet_client.getNumJoints(self.quadruped)
self._chassis_link_ids = [-1]
# The self._leg_link_ids include both the upper and lower links of the leg.
self._leg_link_ids = []
self._motor_link_ids = []
self._foot_link_ids = []
self._bracket_link_ids = []
for i in range(num_joints):
joint_info = self._pybullet_client.getJointInfo(self.quadruped, i)
joint_name = joint_info[1].decode("UTF-8")
joint_id = self._joint_name_to_id[joint_name]
if _CHASSIS_NAME_PATTERN.match(joint_name):
self._chassis_link_ids.append(joint_id)
elif _BRACKET_NAME_PATTERN.match(joint_name):
self._bracket_link_ids.append(joint_id)
elif _MOTOR_NAME_PATTERN.match(joint_name):
self._motor_link_ids.append(joint_id)
elif _KNEE_NAME_PATTERN.match(joint_name):
self._foot_link_ids.append(joint_id)
elif (_LEG_NAME_PATTERN1.match(joint_name)
or _LEG_NAME_PATTERN2.match(joint_name)
or _LEG_NAME_PATTERN3.match(joint_name)):
self._leg_link_ids.append(joint_id)
else:
raise ValueError("Unknown category of joint %s" % joint_name)
self._leg_link_ids.extend(self._foot_link_ids)
self._chassis_link_ids.sort()
self._motor_link_ids.sort()
self._foot_link_ids.sort()
self._leg_link_ids.sort()
self._bracket_link_ids.sort()
def _RemoveDefaultJointDamping(self):
num_joints = self._pybullet_client.getNumJoints(self.quadruped)
for i in range(num_joints):
joint_info = self._pybullet_client.getJointInfo(self.quadruped, i)
self._pybullet_client.changeDynamics(joint_info[0],
-1,
linearDamping=0,
angularDamping=0)
def _BuildMotorIdList(self):
self._motor_id_list = [
self._joint_name_to_id[motor_name]
for motor_name in self._GetMotorNames()
]
def _CreateRackConstraint(self, init_position, init_orientation):
"""Create a constraint that keeps the chassis at a fixed frame.
This frame is defined by init_position and init_orientation.
Args:
init_position: initial position of the fixed frame.
init_orientation: initial orientation of the fixed frame in quaternion
format [x,y,z,w].
Returns:
Return the constraint id.
"""
fixed_constraint = self._pybullet_client.createConstraint(
parentBodyUniqueId=self.quadruped,
parentLinkIndex=-1,
childBodyUniqueId=-1,
childLinkIndex=-1,
jointType=self._pybullet_client.JOINT_FIXED,
jointAxis=[0, 0, 0],
parentFramePosition=[0, 0, 0],
childFramePosition=init_position,
childFrameOrientation=init_orientation)
return fixed_constraint
def IsObservationValid(self):
"""Whether the observation is valid for the current time step.
In simulation, observations are always valid. In real hardware, it may not
be valid from time to time when communication error happens between the
Nvidia TX2 and the microcontroller.
Returns:
Whether the observation is valid for the current time step.
"""
return True
def Reset(self, reload_urdf=True, default_motor_angles=None, reset_time=3.0):
"""Reset the minitaur to its initial states.
Args:
reload_urdf: Whether to reload the urdf file. If not, Reset() just place
the minitaur back to its starting position.
default_motor_angles: The default motor angles. If it is None, minitaur
will hold a default pose (motor angle math.pi / 2) for 100 steps. In
torque control mode, the phase of holding the default pose is skipped.
reset_time: The duration (in seconds) to hold the default motor angles. If
reset_time <= 0 or in torque control mode, the phase of holding the
default pose is skipped.
"""
if reload_urdf:
self._LoadRobotURDF()
if self._on_rack:
self.rack_constraint = (self._CreateRackConstraint(
self._GetDefaultInitPosition(), self._GetDefaultInitOrientation()))
self._BuildJointNameToIdDict()
self._BuildUrdfIds()
self._RemoveDefaultJointDamping()
self._BuildMotorIdList()
self._RecordMassInfoFromURDF()
self._RecordInertiaInfoFromURDF()
self.ResetPose(add_constraint=True)
else:
self._pybullet_client.resetBasePositionAndOrientation(
self.quadruped, self._GetDefaultInitPosition(),
self._GetDefaultInitOrientation())
self._pybullet_client.resetBaseVelocity(self.quadruped, [0, 0, 0],
[0, 0, 0])
self.ResetPose(add_constraint=False)
self._overheat_counter = np.zeros(self.num_motors)
self._motor_enabled_list = [True] * self.num_motors
self._observation_history.clear()
self._step_counter = 0
self._state_action_counter = 0
self._is_safe = True
self._last_action = None
self._SettleDownForReset(default_motor_angles, reset_time)
if self._enable_action_filter:
self._ResetActionFilter()
def _LoadRobotURDF(self):
"""Loads the URDF file for the robot."""
urdf_file = self.GetURDFFile()
if self._self_collision_enabled:
self.quadruped = self._pybullet_client.loadURDF(
urdf_file,
self._GetDefaultInitPosition(),
self._GetDefaultInitOrientation(),
flags=self._pybullet_client.URDF_USE_SELF_COLLISION)
else:
self.quadruped = self._pybullet_client.loadURDF(
urdf_file, self._GetDefaultInitPosition(),
self._GetDefaultInitOrientation())
def _SettleDownForReset(self, default_motor_angles, reset_time):
"""Sets the default motor angles and waits for the robot to settle down.
The reset is skipped is reset_time is less than zereo.
Args:
default_motor_angles: A list of motor angles that the robot will achieve
at the end of the reset phase.
reset_time: The time duration for the reset phase.
"""
if reset_time <= 0:
return
# Important to fill the observation buffer.
self.ReceiveObservation()
for _ in range(100):
self._StepInternal(
[math.pi / 2] * self.num_motors,
motor_control_mode=robot_config.MotorControlMode.POSITION)
# Don't continue to reset if a safety error has occurred.
if not self._is_safe:
return
if default_motor_angles is None:
return
num_steps_to_reset = int(reset_time / self.time_step)
for _ in range(num_steps_to_reset):
self._StepInternal(
default_motor_angles,
motor_control_mode=robot_config.MotorControlMode.POSITION)
# Don't continue to reset if a safety error has occurred.
if not self._is_safe:
return
def _SetMotorTorqueById(self, motor_id, torque):
self._pybullet_client.setJointMotorControl2(
bodyIndex=self.quadruped,
jointIndex=motor_id,
controlMode=self._pybullet_client.TORQUE_CONTROL,
force=torque)
def _SetMotorTorqueByIds(self, motor_ids, torques):
self._pybullet_client.setJointMotorControlArray(
bodyIndex=self.quadruped,
jointIndices=motor_ids,
controlMode=self._pybullet_client.TORQUE_CONTROL,
forces=torques)
def _SetDesiredMotorAngleByName(self, motor_name, desired_angle):
self._SetDesiredMotorAngleById(self._joint_name_to_id[motor_name],
desired_angle)
def GetURDFFile(self):
return "quadruped/minitaur.urdf"
def ResetPose(self, add_constraint):
"""Reset the pose of the minitaur.
Args:
add_constraint: Whether to add a constraint at the joints of two feet.
"""
for i in range(self.num_legs):
self._ResetPoseForLeg(i, add_constraint)
def _ResetPoseForLeg(self, leg_id, add_constraint):
"""Reset the initial pose for the leg.
Args:
leg_id: It should be 0, 1, 2, or 3, which represents the leg at
front_left, back_left, front_right and back_right.
add_constraint: Whether to add a constraint at the joints of two feet.
"""
knee_friction_force = 0
half_pi = math.pi / 2.0
knee_angle = -2.1834
leg_position = LEG_POSITION[leg_id]
self._pybullet_client.resetJointState(
self.quadruped,
self._joint_name_to_id["motor_" + leg_position + "L_joint"],
self._motor_direction[2 * leg_id] * half_pi,
targetVelocity=0)
self._pybullet_client.resetJointState(
self.quadruped,
self._joint_name_to_id["knee_" + leg_position + "L_link"],
self._motor_direction[2 * leg_id] * knee_angle,
targetVelocity=0)
self._pybullet_client.resetJointState(
self.quadruped,
self._joint_name_to_id["motor_" + leg_position + "R_joint"],
self._motor_direction[2 * leg_id + 1] * half_pi,
targetVelocity=0)
self._pybullet_client.resetJointState(
self.quadruped,
self._joint_name_to_id["knee_" + leg_position + "R_link"],
self._motor_direction[2 * leg_id + 1] * knee_angle,
targetVelocity=0)
if add_constraint:
self._pybullet_client.createConstraint(
self.quadruped,
self._joint_name_to_id["knee_" + leg_position + "R_link"],
self.quadruped,
self._joint_name_to_id["knee_" + leg_position + "L_link"],
self._pybullet_client.JOINT_POINT2POINT, [0, 0, 0],
KNEE_CONSTRAINT_POINT_RIGHT, KNEE_CONSTRAINT_POINT_LEFT)
# Disable the default motor in pybullet.
self._pybullet_client.setJointMotorControl2(
bodyIndex=self.quadruped,
jointIndex=(self._joint_name_to_id["motor_" + leg_position +
"L_joint"]),
controlMode=self._pybullet_client.VELOCITY_CONTROL,
targetVelocity=0,
force=knee_friction_force)
self._pybullet_client.setJointMotorControl2(
bodyIndex=self.quadruped,
jointIndex=(self._joint_name_to_id["motor_" + leg_position +
"R_joint"]),
controlMode=self._pybullet_client.VELOCITY_CONTROL,
targetVelocity=0,
force=knee_friction_force)
self._pybullet_client.setJointMotorControl2(
bodyIndex=self.quadruped,
jointIndex=(self._joint_name_to_id["knee_" + leg_position + "L_link"]),
controlMode=self._pybullet_client.VELOCITY_CONTROL,
targetVelocity=0,
force=knee_friction_force)
self._pybullet_client.setJointMotorControl2(
bodyIndex=self.quadruped,
jointIndex=(self._joint_name_to_id["knee_" + leg_position + "R_link"]),
controlMode=self._pybullet_client.VELOCITY_CONTROL,
targetVelocity=0,
force=knee_friction_force)
def GetBasePosition(self):
"""Get the position of minitaur's base.
Returns:
The position of minitaur's base.
"""
return self._base_position
def GetBaseVelocity(self):
"""Get the linear velocity of minitaur's base.
Returns:
The velocity of minitaur's base.
"""
velocity, _ = self._pybullet_client.getBaseVelocity(self.quadruped)
return velocity
def GetTrueBaseRollPitchYaw(self):
"""Get minitaur's base orientation in euler angle in the world frame.
Returns:
A tuple (roll, pitch, yaw) of the base in world frame.
"""
orientation = self.GetTrueBaseOrientation()
roll_pitch_yaw = self._pybullet_client.getEulerFromQuaternion(orientation)
return np.asarray(roll_pitch_yaw)
def GetBaseRollPitchYaw(self):
"""Get minitaur's base orientation in euler angle in the world frame.
This function mimicks the noisy sensor reading and adds latency.
Returns:
A tuple (roll, pitch, yaw) of the base in world frame polluted by noise
and latency.
"""
delayed_orientation = np.array(
self._control_observation[3 * self.num_motors:3 * self.num_motors + 4])
delayed_roll_pitch_yaw = self._pybullet_client.getEulerFromQuaternion(
delayed_orientation)
roll_pitch_yaw = self._AddSensorNoise(np.array(delayed_roll_pitch_yaw),
self._observation_noise_stdev[3])
return roll_pitch_yaw
def GetHipPositionsInBaseFrame(self):
"""Get the hip joint positions of the robot within its base frame."""
raise NotImplementedError("Not implemented for Minitaur.")
def ComputeMotorAnglesFromFootLocalPosition(self, leg_id,
foot_local_position):
"""Use IK to compute the motor angles, given the foot link's local position.
Args:
leg_id: The leg index.
foot_local_position: The foot link's position in the base frame.
Returns:
A tuple. The position indices and the angles for all joints along the
leg. The position indices is consistent with the joint orders as returned
by GetMotorAngles API.
"""
assert len(self._foot_link_ids) == self.num_legs
toe_id = self._foot_link_ids[leg_id]
motors_per_leg = self.num_motors // self.num_legs
joint_position_idxs = list(
range(leg_id * motors_per_leg,
leg_id * motors_per_leg + motors_per_leg))
joint_angles = kinematics.joint_angles_from_link_position(
robot=self,
link_position=foot_local_position,
link_id=toe_id,
joint_ids=joint_position_idxs,
)
# Joint offset is necessary for Laikago.
joint_angles = np.multiply(
np.asarray(joint_angles) -
np.asarray(self._motor_offset)[joint_position_idxs],
self._motor_direction[joint_position_idxs])
# Return the joing index (the same as when calling GetMotorAngles) as well
# as the angles.
return joint_position_idxs, joint_angles.tolist()
def ComputeJacobian(self, leg_id):
"""Compute the Jacobian for a given leg."""
# Does not work for Minitaur which has the four bar mechanism for now.
assert len(self._foot_link_ids) == self.num_legs
full_jacobian = kinematics.compute_jacobian(
robot=self,
link_id=self._foot_link_ids[leg_id],
)
motors_per_leg = self.num_motors // self.num_legs
com_dof = 6
return full_jacobian[com_dof + leg_id * motors_per_leg:com_dof +
(leg_id + 1) * motors_per_leg]
def MapContactForceToJointTorques(self, leg_id, contact_force):
"""Maps the foot contact force to the leg joint torques."""
jv = self.ComputeJacobian(leg_id)
motor_torques_list = np.matmul(contact_force, jv)
motor_torques_dict = {}
motors_per_leg = self.num_motors // self.num_legs
for torque_id, joint_id in enumerate(
range(leg_id * motors_per_leg, (leg_id + 1) * motors_per_leg)):
motor_torques_dict[joint_id] = motor_torques_list[torque_id]
return motor_torques_dict
def GetFootContacts(self):
"""Get minitaur's foot contact situation with the ground.
Returns:
A list of 4 booleans. The ith boolean is True if leg i is in contact with
ground.
"""
contacts = []
for leg_idx in range(MINITAUR_NUM_MOTORS // 2):
link_id_1 = self._foot_link_ids[leg_idx * 2]
link_id_2 = self._foot_link_ids[leg_idx * 2 + 1]
contact_1 = bool(
self._pybullet_client.getContactPoints(bodyA=0,
bodyB=self.quadruped,
linkIndexA=-1,
linkIndexB=link_id_1))
contact_2 = bool(
self._pybullet_client.getContactPoints(bodyA=0,
bodyB=self.quadruped,
linkIndexA=-1,
linkIndexB=link_id_2))
contacts.append(contact_1 or contact_2)
return contacts
def GetFootPositionsInBaseFrame(self):
"""Get the robot's foot position in the base frame."""
assert len(self._foot_link_ids) == self.num_legs
foot_positions = []
for foot_id in self.GetFootLinkIDs():
foot_positions.append(
kinematics.link_position_in_base_frame(
robot=self,
link_id=foot_id,
))
return np.array(foot_positions)
def GetTrueMotorAngles(self):
"""Gets the eight motor angles at the current moment, mapped to [-pi, pi].
Returns:
Motor angles, mapped to [-pi, pi].
"""
motor_angles = [state[0] for state in self._joint_states]
motor_angles = np.multiply(
np.asarray(motor_angles) - np.asarray(self._motor_offset),
self._motor_direction)
return motor_angles
def GetMotorAngles(self):
"""Gets the eight motor angles.
This function mimicks the noisy sensor reading and adds latency. The motor
angles that are delayed, noise polluted, and mapped to [-pi, pi].
Returns:
Motor angles polluted by noise and latency, mapped to [-pi, pi].
"""
motor_angles = self._AddSensorNoise(
np.array(self._control_observation[0:self.num_motors]),
self._observation_noise_stdev[0])
return MapToMinusPiToPi(motor_angles)
def GetTrueMotorVelocities(self):
"""Get the velocity of all eight motors.
Returns:
Velocities of all eight motors.
"""
motor_velocities = [state[1] for state in self._joint_states]
motor_velocities = np.multiply(motor_velocities, self._motor_direction)
return motor_velocities
def GetMotorVelocities(self):
"""Get the velocity of all eight motors.
This function mimicks the noisy sensor reading and adds latency.
Returns:
Velocities of all eight motors polluted by noise and latency.
"""
return self._AddSensorNoise(
np.array(self._control_observation[self.num_motors:2 *
self.num_motors]),
self._observation_noise_stdev[1])
def GetTrueMotorTorques(self):
"""Get the amount of torque the motors are exerting.
Returns:
Motor torques of all eight motors.
"""
return self._observed_motor_torques
def GetMotorTorques(self):
"""Get the amount of torque the motors are exerting.
This function mimicks the noisy sensor reading and adds latency.
Returns:
Motor torques of all eight motors polluted by noise and latency.
"""
return self._AddSensorNoise(
np.array(self._control_observation[2 * self.num_motors:3 *
self.num_motors]),
self._observation_noise_stdev[2])
def GetEnergyConsumptionPerControlStep(self):
"""Get the amount of energy used in last one time step.
Returns:
Energy Consumption based on motor velocities and torques (Nm^2/s).
"""
return np.abs(np.dot(
self.GetMotorTorques(),
self.GetMotorVelocities())) * self.time_step * self._action_repeat
def GetTrueBaseOrientation(self):
"""Get the orientation of minitaur's base, represented as quaternion.
Returns:
The orientation of minitaur's base.
"""
return self._base_orientation
def GetBaseOrientation(self):
"""Get the orientation of minitaur's base, represented as quaternion.
This function mimicks the noisy sensor reading and adds latency.
Returns:
The orientation of minitaur's base polluted by noise and latency.
"""
return self._pybullet_client.getQuaternionFromEuler(
self.GetBaseRollPitchYaw())
def GetTrueBaseRollPitchYawRate(self):
"""Get the rate of orientation change of the minitaur's base in euler angle.
Returns:
rate of (roll, pitch, yaw) change of the minitaur's base.
"""
angular_velocity = self._pybullet_client.getBaseVelocity(self.quadruped)[1]
orientation = self.GetTrueBaseOrientation()
return self.TransformAngularVelocityToLocalFrame(angular_velocity,
orientation)
def TransformAngularVelocityToLocalFrame(self, angular_velocity,
orientation):
"""Transform the angular velocity from world frame to robot's frame.
Args:
angular_velocity: Angular velocity of the robot in world frame.
orientation: Orientation of the robot represented as a quaternion.
Returns:
angular velocity of based on the given orientation.
"""
# Treat angular velocity as a position vector, then transform based on the
# orientation given by dividing (or multiplying with inverse).
# Get inverse quaternion assuming the vector is at 0,0,0 origin.
_, orientation_inversed = self._pybullet_client.invertTransform(
[0, 0, 0], orientation)
# Transform the angular_velocity at neutral orientation using a neutral
# translation and reverse of the given orientation.
relative_velocity, _ = self._pybullet_client.multiplyTransforms(
[0, 0, 0], orientation_inversed, angular_velocity,
self._pybullet_client.getQuaternionFromEuler([0, 0, 0]))
return np.asarray(relative_velocity)
def GetBaseRollPitchYawRate(self):
"""Get the rate of orientation change of the minitaur's base in euler angle.
This function mimicks the noisy sensor reading and adds latency.
Returns:
rate of (roll, pitch, yaw) change of the minitaur's base polluted by noise
and latency.
"""
return self._AddSensorNoise(
np.array(self._control_observation[3 * self.num_motors +
4:3 * self.num_motors + 7]),
self._observation_noise_stdev[4])
def GetActionDimension(self):
"""Get the length of the action list.
Returns:
The length of the action list.
"""
return self.num_motors
def _ApplyOverheatProtection(self, actual_torque):
if self._motor_overheat_protection:
for i in range(self.num_motors):
if abs(actual_torque[i]) > OVERHEAT_SHUTDOWN_TORQUE:
self._overheat_counter[i] += 1
else:
self._overheat_counter[i] = 0
if (self._overheat_counter[i] >
OVERHEAT_SHUTDOWN_TIME / self.time_step):
self._motor_enabled_list[i] = False
def ApplyAction(self, motor_commands, motor_control_mode=None):
"""Apply the motor commands using the motor model.
Args:
motor_commands: np.array. Can be motor angles, torques, hybrid commands,
or motor pwms (for Minitaur only).
motor_control_mode: A MotorControlMode enum.
"""
self.last_action_time = self._state_action_counter * self.time_step
control_mode = motor_control_mode
if control_mode is None:
control_mode = self._motor_control_mode
motor_commands = np.asarray(motor_commands)
q, qdot = self._GetPDObservation()
qdot_true = self.GetTrueMotorVelocities()
actual_torque, observed_torque = self._motor_model.convert_to_torque(
motor_commands, q, qdot, qdot_true, control_mode)
# May turn off the motor
self._ApplyOverheatProtection(actual_torque)
# The torque is already in the observation space because we use
# GetMotorAngles and GetMotorVelocities.
self._observed_motor_torques = observed_torque
# Transform into the motor space when applying the torque.
self._applied_motor_torque = np.multiply(actual_torque,
self._motor_direction)
motor_ids = []
motor_torques = []
for motor_id, motor_torque, motor_enabled in zip(
self._motor_id_list, self._applied_motor_torque,
self._motor_enabled_list):
if motor_enabled:
motor_ids.append(motor_id)
motor_torques.append(motor_torque)
else:
motor_ids.append(motor_id)
motor_torques.append(0)
self._SetMotorTorqueByIds(motor_ids, motor_torques)
def ConvertFromLegModel(self, actions):
"""Convert the actions that use leg model to the real motor actions.
Args:
actions: The theta, phi of the leg model.
Returns:
The eight desired motor angles that can be used in ApplyActions().
"""
motor_angle = copy.deepcopy(actions)
scale_for_singularity = 1
offset_for_singularity = 1.5
half_num_motors = self.num_motors // 2
quater_pi = math.pi / 4
for i in range(self.num_motors):
action_idx = i // 2
forward_backward_component = (
-scale_for_singularity * quater_pi *
(actions[action_idx + half_num_motors] + offset_for_singularity))
extension_component = (-1)**i * quater_pi * actions[action_idx]
if i >= half_num_motors:
extension_component = -extension_component
motor_angle[i] = (math.pi + forward_backward_component +
extension_component)
return motor_angle
def GetBaseMassesFromURDF(self):
"""Get the mass of the base from the URDF file."""
return self._base_mass_urdf
def GetBaseInertiasFromURDF(self):
"""Get the inertia of the base from the URDF file."""
return self._base_inertia_urdf
def GetLegMassesFromURDF(self):
"""Get the mass of the legs from the URDF file."""
return self._leg_masses_urdf
def GetLegInertiasFromURDF(self):
"""Get the inertia of the legs from the URDF file."""
return self._leg_inertia_urdf
def SetBaseMasses(self, base_mass):
"""Set the mass of minitaur's base.
Args:
base_mass: A list of masses of each body link in CHASIS_LINK_IDS. The
length of this list should be the same as the length of CHASIS_LINK_IDS.
Raises:
ValueError: It is raised when the length of base_mass is not the same as
the length of self._chassis_link_ids.
"""
if len(base_mass) != len(self._chassis_link_ids):
raise ValueError(
"The length of base_mass {} and self._chassis_link_ids {} are not "
"the same.".format(len(base_mass), len(self._chassis_link_ids)))
for chassis_id, chassis_mass in zip(self._chassis_link_ids, base_mass):
self._pybullet_client.changeDynamics(self.quadruped,
chassis_id,
mass=chassis_mass)
def SetLegMasses(self, leg_masses):
"""Set the mass of the legs.
A leg includes leg_link and motor. 4 legs contain 16 links (4 links each)
and 8 motors. First 16 numbers correspond to link masses, last 8 correspond
to motor masses (24 total).
Args:
leg_masses: The leg and motor masses for all the leg links and motors.
Raises:
ValueError: It is raised when the length of masses is not equal to number
of links + motors.
"""
if len(leg_masses) != len(self._leg_link_ids) + len(self._motor_link_ids):
raise ValueError("The number of values passed to SetLegMasses are "
"different than number of leg links and motors.")
for leg_id, leg_mass in zip(self._leg_link_ids, leg_masses):
self._pybullet_client.changeDynamics(self.quadruped,
leg_id,
mass=leg_mass)
motor_masses = leg_masses[len(self._leg_link_ids):]
for link_id, motor_mass in zip(self._motor_link_ids, motor_masses):
self._pybullet_client.changeDynamics(self.quadruped,
link_id,
mass=motor_mass)
def SetBaseInertias(self, base_inertias):
"""Set the inertias of minitaur's base.
Args:
base_inertias: A list of inertias of each body link in CHASIS_LINK_IDS.
The length of this list should be the same as the length of
CHASIS_LINK_IDS.
Raises:
ValueError: It is raised when the length of base_inertias is not the same
as the length of self._chassis_link_ids and base_inertias contains
negative values.
"""
if len(base_inertias) != len(self._chassis_link_ids):
raise ValueError(
"The length of base_inertias {} and self._chassis_link_ids {} are "
"not the same.".format(len(base_inertias),
len(self._chassis_link_ids)))
for chassis_id, chassis_inertia in zip(self._chassis_link_ids,
base_inertias):
for inertia_value in chassis_inertia:
if (np.asarray(inertia_value) < 0).any():
raise ValueError("Values in inertia matrix should be non-negative.")
self._pybullet_client.changeDynamics(
self.quadruped, chassis_id, localInertiaDiagonal=chassis_inertia)
def SetLegInertias(self, leg_inertias):
"""Set the inertias of the legs.
A leg includes leg_link and motor. 4 legs contain 16 links (4 links each)
and 8 motors. First 16 numbers correspond to link inertia, last 8 correspond
to motor inertia (24 total).
Args:
leg_inertias: The leg and motor inertias for all the leg links and motors.
Raises:
ValueError: It is raised when the length of inertias is not equal to
the number of links + motors or leg_inertias contains negative values.
"""
if len(leg_inertias) != len(self._leg_link_ids) + len(
self._motor_link_ids):
raise ValueError("The number of values passed to SetLegMasses are "
"different than number of leg links and motors.")
for leg_id, leg_inertia in zip(self._leg_link_ids, leg_inertias):
for inertia_value in leg_inertias:
if (np.asarray(inertia_value) < 0).any():
raise ValueError("Values in inertia matrix should be non-negative.")
self._pybullet_client.changeDynamics(self.quadruped,
leg_id,
localInertiaDiagonal=leg_inertia)
motor_inertias = leg_inertias[len(self._leg_link_ids):]
for link_id, motor_inertia in zip(self._motor_link_ids, motor_inertias):
for inertia_value in motor_inertias:
if (np.asarray(inertia_value) < 0).any():
raise ValueError("Values in inertia matrix should be non-negative.")
self._pybullet_client.changeDynamics(self.quadruped,
link_id,
localInertiaDiagonal=motor_inertia)
def SetFootFriction(self, foot_friction):
"""Set the lateral friction of the feet.
Args:
foot_friction: The lateral friction coefficient of the foot. This value is
shared by all four feet.
"""
for link_id in self._foot_link_ids:
self._pybullet_client.changeDynamics(self.quadruped,
link_id,
lateralFriction=foot_friction)
def SetFootRestitution(self, foot_restitution):
"""Set the coefficient of restitution at the feet.
Args:
foot_restitution: The coefficient of restitution (bounciness) of the feet.
This value is shared by all four feet.
"""
for link_id in self._foot_link_ids:
self._pybullet_client.changeDynamics(self.quadruped,
link_id,
restitution=foot_restitution)
def SetJointFriction(self, joint_frictions):
for knee_joint_id, friction in zip(self._foot_link_ids, joint_frictions):
self._pybullet_client.setJointMotorControl2(
bodyIndex=self.quadruped,
jointIndex=knee_joint_id,
controlMode=self._pybullet_client.VELOCITY_CONTROL,
targetVelocity=0,
force=friction)
def GetNumKneeJoints(self):
return len(self._foot_link_ids)
def SetBatteryVoltage(self, voltage):
self._motor_model.set_voltage(voltage)
def SetMotorViscousDamping(self, viscous_damping):
self._motor_model.set_viscous_damping(viscous_damping)
def GetTrueObservation(self):
observation = []
observation.extend(self.GetTrueMotorAngles())
observation.extend(self.GetTrueMotorVelocities())
observation.extend(self.GetTrueMotorTorques())
observation.extend(self.GetTrueBaseOrientation())
observation.extend(self.GetTrueBaseRollPitchYawRate())
return observation
def ReceiveObservation(self):
"""Receive the observation from sensors.
This function is called once per step. The observations are only updated
when this function is called.
"""
self._joint_states = self._pybullet_client.getJointStates(
self.quadruped, self._motor_id_list)
self._base_position, orientation = (
self._pybullet_client.getBasePositionAndOrientation(self.quadruped))
# Computes the relative orientation relative to the robot's
# initial_orientation.
_, self._base_orientation = self._pybullet_client.multiplyTransforms(
positionA=[0, 0, 0],
orientationA=orientation,
positionB=[0, 0, 0],
orientationB=self._init_orientation_inv)
self._observation_history.appendleft(self.GetTrueObservation())
self._control_observation = self._GetControlObservation()
self.last_state_time = self._state_action_counter * self.time_step
def _GetDelayedObservation(self, latency):
"""Get observation that is delayed by the amount specified in latency.
Args:
latency: The latency (in seconds) of the delayed observation.
Returns:
observation: The observation which was actually latency seconds ago.
"""
if latency <= 0 or len(self._observation_history) == 1:
observation = self._observation_history[0]
else:
n_steps_ago = int(latency / self.time_step)
if n_steps_ago + 1 >= len(self._observation_history):
return self._observation_history[-1]
remaining_latency = latency - n_steps_ago * self.time_step
blend_alpha = remaining_latency / self.time_step
observation = (
(1.0 - blend_alpha) *
np.array(self._observation_history[n_steps_ago]) +
blend_alpha * np.array(self._observation_history[n_steps_ago + 1]))
return observation
def _GetPDObservation(self):
pd_delayed_observation = self._GetDelayedObservation(self._pd_latency)
q = pd_delayed_observation[0:self.num_motors]
qdot = pd_delayed_observation[self.num_motors:2 * self.num_motors]
return (np.array(q), np.array(qdot))
def _GetControlObservation(self):
control_delayed_observation = self._GetDelayedObservation(
self._control_latency)
return control_delayed_observation
def _AddSensorNoise(self, sensor_values, noise_stdev):
if noise_stdev <= 0:
return sensor_values
observation = sensor_values + np.random.normal(scale=noise_stdev,
size=sensor_values.shape)
return observation
def SetControlLatency(self, latency):
"""Set the latency of the control loop.
It measures the duration between sending an action from Nvidia TX2 and
receiving the observation from microcontroller.
Args:
latency: The latency (in seconds) of the control loop.
"""
self._control_latency = latency
def GetControlLatency(self):
"""Get the control latency.
Returns:
The latency (in seconds) between when the motor command is sent and when
the sensor measurements are reported back to the controller.
"""
return self._control_latency
def SetMotorGains(self, kp, kd):
"""Set the gains of all motors.
These gains are PD gains for motor positional control. kp is the
proportional gain and kd is the derivative gain.
Args:
kp: proportional gain(s) of the motors.
kd: derivative gain(s) of the motors.
"""
if isinstance(kp, (collections.Sequence, np.ndarray)):
self._motor_kps = np.asarray(kp)
else:
self._motor_kps = np.full(self.num_motors, kp)
if isinstance(kd, (collections.Sequence, np.ndarray)):
self._motor_kds = np.asarray(kd)
else:
self._motor_kds = np.full(self.num_motors, kd)
self._motor_model.set_motor_gains(kp, kd)
def GetMotorGains(self):
"""Get the gains of the motor.
Returns:
The proportional gain.
The derivative gain.
"""
return self._motor_kps, self._motor_kds
def GetMotorPositionGains(self):
"""Get the position gains of the motor.
Returns:
The proportional gain.
"""
return self._motor_kps
def GetMotorVelocityGains(self):
"""Get the velocity gains of the motor.
Returns:
The derivative gain.
"""
return self._motor_kds
def SetMotorStrengthRatio(self, ratio):
"""Set the strength of all motors relative to the default value.
Args:
ratio: The relative strength. A scalar range from 0.0 to 1.0.
"""
self._motor_model.set_strength_ratios([ratio] * self.num_motors)
def SetMotorStrengthRatios(self, ratios):
"""Set the strength of each motor relative to the default value.
Args:
ratios: The relative strength. A numpy array ranging from 0.0 to 1.0.
"""
self._motor_model.set_strength_ratios(ratios)
def SetTimeSteps(self, action_repeat, simulation_step):
"""Set the time steps of the control and simulation.
Args:
action_repeat: The number of simulation steps that the same action is
repeated.
simulation_step: The simulation time step.
"""
self.time_step = simulation_step
self._action_repeat = action_repeat
def _GetMotorNames(self):
return MOTOR_NAMES
def _GetDefaultInitPosition(self):
"""Returns the init position of the robot.
It can be either 1) origin (INIT_POSITION), 2) origin with a rack
(INIT_RACK_POSITION), or 3) the previous position.
"""
# If we want continuous resetting and is not the first episode.
if self._reset_at_current_position and self._observation_history:
x, y, _ = self.GetBasePosition()
_, _, z = INIT_POSITION
return [x, y, z]
if self._on_rack:
return INIT_RACK_POSITION
else:
return INIT_POSITION
def _GetDefaultInitOrientation(self):
"""Returns the init position of the robot.
It can be either 1) INIT_ORIENTATION or 2) the previous rotation in yaw.
"""
# If we want continuous resetting and is not the first episode.
if self._reset_at_current_position and self._observation_history:
_, _, yaw = self.GetBaseRollPitchYaw()
return self._pybullet_client.getQuaternionFromEuler([0.0, 0.0, yaw])
return INIT_ORIENTATION
@property
def chassis_link_ids(self):
return self._chassis_link_ids
def SetAllSensors(self, sensors):
"""set all sensors to this robot and move the ownership to this robot.
Args:
sensors: a list of sensors to this robot.
"""
for s in sensors:
s.set_robot(self)
self._sensors = sensors
def GetAllSensors(self):
"""get all sensors associated with this robot.
Returns:
sensors: a list of all sensors.
"""
return self._sensors
def GetSensor(self, name):
"""get the first sensor with the given name.
This function return None if a sensor with the given name does not exist.
Args:
name: the name of the sensor we are looking
Returns:
sensor: a sensor with the given name. None if not exists.
"""
for s in self._sensors:
if s.get_name() == name:
return s
return None
@property
def is_safe(self):
return self._is_safe
@property
def last_action(self):
return self._last_action
def ProcessAction(self, action, substep_count):
"""If enabled, interpolates between the current and previous actions.
Args:
action: current action.
substep_count: the step count should be between [0, self.__action_repeat).
Returns:
If interpolation is enabled, returns interpolated action depending on
the current action repeat substep.
"""
if self._enable_action_interpolation and self._last_action is not None:
lerp = float(substep_count + 1) / self._action_repeat
proc_action = self._last_action + lerp * (action - self._last_action)
else:
proc_action = action
return proc_action
def _BuildActionFilter(self):
sampling_rate = 1 / (self.time_step * self._action_repeat)
num_joints = self.GetActionDimension()
a_filter = action_filter.ActionFilterButter(sampling_rate=sampling_rate,
num_joints=num_joints)
return a_filter
def _ResetActionFilter(self):
self._action_filter.reset()
def _FilterAction(self, action):
# initialize the filter history, since resetting the filter will fill
# the history with zeros and this can cause sudden movements at the start
# of each episode
if self._step_counter == 0:
default_action = self.GetMotorAngles()
self._action_filter.init_history(default_action)
filtered_action = self._action_filter.filter(action)
return filtered_action
@property
def pybullet_client(self):
return self._pybullet_client
@property
def joint_states(self):
return self._joint_states
@classmethod
def GetConstants(cls):
del cls
return minitaur_constants | locomotion/robots/minitaur.py | """This file implements the functionalities of a minitaur using pybullet."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import collections
import copy
import math
import re
import numpy as np
from locomotion.robots import minitaur_constants
from locomotion.robots import minitaur_motor
from locomotion.robots import robot_config
from locomotion.robots import action_filter
from locomotion.robots import kinematics
INIT_POSITION = [0, 0, .2]
INIT_RACK_POSITION = [0, 0, 1]
INIT_ORIENTATION = [0, 0, 0, 1]
KNEE_CONSTRAINT_POINT_RIGHT = [0, 0.005, 0.2]
KNEE_CONSTRAINT_POINT_LEFT = [0, 0.01, 0.2]
OVERHEAT_SHUTDOWN_TORQUE = 2.45
OVERHEAT_SHUTDOWN_TIME = 1.0
LEG_POSITION = ["front_left", "back_left", "front_right", "back_right"]
MOTOR_NAMES = [
"motor_front_leftL_joint", "motor_front_leftR_joint",
"motor_back_leftL_joint", "motor_back_leftR_joint",
"motor_front_rightL_joint", "motor_front_rightR_joint",
"motor_back_rightL_joint", "motor_back_rightR_joint"
]
_CHASSIS_NAME_PATTERN = re.compile(r"chassis\D*center")
_MOTOR_NAME_PATTERN = re.compile(r"motor\D*joint")
_KNEE_NAME_PATTERN = re.compile(r"knee\D*")
_BRACKET_NAME_PATTERN = re.compile(r"motor\D*_bracket_joint")
_LEG_NAME_PATTERN1 = re.compile(r"hip\D*joint")
_LEG_NAME_PATTERN2 = re.compile(r"hip\D*link")
_LEG_NAME_PATTERN3 = re.compile(r"motor\D*link")
SENSOR_NOISE_STDDEV = (0.0, 0.0, 0.0, 0.0, 0.0)
MINITAUR_DEFAULT_MOTOR_DIRECTIONS = (-1, -1, -1, -1, 1, 1, 1, 1)
MINITAUR_DEFAULT_MOTOR_OFFSETS = (0, 0, 0, 0, 0, 0, 0, 0)
MINITAUR_NUM_MOTORS = 8
TWO_PI = 2 * math.pi
MINITAUR_DOFS_PER_LEG = 2
def MapToMinusPiToPi(angles):
"""Maps a list of angles to [-pi, pi].
Args:
angles: A list of angles in rad.
Returns:
A list of angle mapped to [-pi, pi].
"""
mapped_angles = copy.deepcopy(angles)
for i in range(len(angles)):
mapped_angles[i] = math.fmod(angles[i], TWO_PI)
if mapped_angles[i] >= math.pi:
mapped_angles[i] -= TWO_PI
elif mapped_angles[i] < -math.pi:
mapped_angles[i] += TWO_PI
return mapped_angles
class Minitaur(object):
"""The minitaur class that simulates a quadruped robot from Ghost Robotics."""
def __init__(self,
pybullet_client,
num_motors=MINITAUR_NUM_MOTORS,
dofs_per_leg=MINITAUR_DOFS_PER_LEG,
time_step=0.01,
action_repeat=1,
self_collision_enabled=False,
motor_control_mode=robot_config.MotorControlMode.POSITION,
motor_model_class=minitaur_motor.MotorModel,
motor_kp=1.0,
motor_kd=0.02,
motor_torque_limits=None,
pd_latency=0.0,
control_latency=0.0,
observation_noise_stdev=SENSOR_NOISE_STDDEV,
motor_overheat_protection=False,
motor_direction=MINITAUR_DEFAULT_MOTOR_DIRECTIONS,
motor_offset=MINITAUR_DEFAULT_MOTOR_OFFSETS,
on_rack=False,
reset_at_current_position=False,
sensors=None,
enable_action_interpolation=False,
enable_action_filter=False,
reset_time=-1):
"""Constructs a minitaur and reset it to the initial states.
Args:
pybullet_client: The instance of BulletClient to manage different
simulations.
num_motors: The number of the motors on the robot.
dofs_per_leg: The number of degrees of freedom for each leg.
time_step: The time step of the simulation.
action_repeat: The number of ApplyAction() for each control step.
self_collision_enabled: Whether to enable self collision.
motor_control_mode: Enum. Can either be POSITION, TORQUE, or HYBRID.
motor_model_class: We can choose from simple pd model to more accureate DC
motor models.
motor_kp: proportional gain for the motors.
motor_kd: derivative gain for the motors.
motor_torque_limits: Torque limits for the motors. Can be a single float
or a list of floats specifying different limits for different robots. If
not provided, the default limit of the robot is used.
pd_latency: The latency of the observations (in seconds) used to calculate
PD control. On the real hardware, it is the latency between the
microcontroller and the motor controller.
control_latency: The latency of the observations (in second) used to
calculate action. On the real hardware, it is the latency from the motor
controller, the microcontroller to the host (Nvidia TX2).
observation_noise_stdev: The standard deviation of a Gaussian noise model
for the sensor. It should be an array for separate sensors in the
following order [motor_angle, motor_velocity, motor_torque,
base_roll_pitch_yaw, base_angular_velocity]
motor_overheat_protection: Whether to shutdown the motor that has exerted
large torque (OVERHEAT_SHUTDOWN_TORQUE) for an extended amount of time
(OVERHEAT_SHUTDOWN_TIME). See ApplyAction() in minitaur.py for more
details.
motor_direction: A list of direction values, either 1 or -1, to compensate
the axis difference of motors between the simulation and the real robot.
motor_offset: A list of offset value for the motor angles. This is used to
compensate the angle difference between the simulation and the real
robot.
on_rack: Whether to place the minitaur on rack. This is only used to debug
the walking gait. In this mode, the minitaur's base is hanged midair so
that its walking gait is clearer to visualize.
reset_at_current_position: Whether to reset the minitaur at the current
position and orientation. This is for simulating the reset behavior in
the real world.
sensors: a list of sensors that are attached to the robot.
enable_action_interpolation: Whether to interpolate the current action
with the previous action in order to produce smoother motions
enable_action_filter: Boolean specifying if a lowpass filter should be
used to smooth actions.
"""
self.num_motors = num_motors
self.num_legs = self.num_motors // dofs_per_leg
self._pybullet_client = pybullet_client
self._action_repeat = action_repeat
self._self_collision_enabled = self_collision_enabled
self._motor_direction = motor_direction
self._motor_offset = motor_offset
self._observed_motor_torques = np.zeros(self.num_motors)
self._applied_motor_torques = np.zeros(self.num_motors)
self._max_force = 3.5
self._pd_latency = pd_latency
self._control_latency = control_latency
self._observation_noise_stdev = observation_noise_stdev
self._observation_history = collections.deque(maxlen=100)
self._control_observation = []
self._chassis_link_ids = [-1]
self._leg_link_ids = []
self._motor_link_ids = []
self._foot_link_ids = []
self._motor_overheat_protection = motor_overheat_protection
self._on_rack = on_rack
self._reset_at_current_position = reset_at_current_position
self.SetAllSensors(sensors if sensors is not None else list())
self._is_safe = True
self._enable_action_interpolation = enable_action_interpolation
self._enable_action_filter = enable_action_filter
self._last_action = None
if not motor_model_class:
raise ValueError("Must provide a motor model class!")
if self._on_rack and self._reset_at_current_position:
raise ValueError("on_rack and reset_at_current_position "
"cannot be enabled together")
if isinstance(motor_kp, (collections.Sequence, np.ndarray)):
self._motor_kps = np.asarray(motor_kp)
else:
self._motor_kps = np.full(num_motors, motor_kp)
if isinstance(motor_kd, (collections.Sequence, np.ndarray)):
self._motor_kds = np.asarray(motor_kd)
else:
self._motor_kds = np.full(num_motors, motor_kd)
if isinstance(motor_torque_limits, (collections.Sequence, np.ndarray)):
self._motor_torque_limits = np.asarray(motor_torque_limits)
elif motor_torque_limits is None:
self._motor_torque_limits = None
else:
self._motor_torque_limits = motor_torque_limits
self._motor_control_mode = motor_control_mode
self._motor_model = motor_model_class(
kp=motor_kp,
kd=motor_kd,
torque_limits=self._motor_torque_limits,
motor_control_mode=motor_control_mode)
self.time_step = time_step
self._step_counter = 0
# This also includes the time spent during the Reset motion.
self._state_action_counter = 0
_, self._init_orientation_inv = self._pybullet_client.invertTransform(
position=[0, 0, 0], orientation=self._GetDefaultInitOrientation())
if self._enable_action_filter:
self._action_filter = self._BuildActionFilter()
# reset_time=-1.0 means skipping the reset motion.
# See Reset for more details.
self.Reset(reset_time=reset_time)
self.ReceiveObservation()
def GetTimeSinceReset(self):
return self._step_counter * self.time_step
def _StepInternal(self, action, motor_control_mode=None):
self.ApplyAction(action, motor_control_mode)
self._pybullet_client.stepSimulation()
self.ReceiveObservation()
self._state_action_counter += 1
def Step(self, action, motor_control_mode=None):
"""Steps simulation."""
if self._enable_action_filter:
action = self._FilterAction(action)
for i in range(self._action_repeat):
proc_action = self.ProcessAction(action, i)
self._StepInternal(proc_action, motor_control_mode)
self._step_counter += 1
self._last_action = action
def Terminate(self):
pass
def GetFootLinkIDs(self):
"""Get list of IDs for all foot links."""
return self._foot_link_ids
def _RecordMassInfoFromURDF(self):
"""Records the mass information from the URDF file."""
self._base_mass_urdf = []
for chassis_id in self._chassis_link_ids:
self._base_mass_urdf.append(
self._pybullet_client.getDynamicsInfo(self.quadruped, chassis_id)[0])
self._leg_masses_urdf = []
for leg_id in self._leg_link_ids:
self._leg_masses_urdf.append(
self._pybullet_client.getDynamicsInfo(self.quadruped, leg_id)[0])
for motor_id in self._motor_link_ids:
self._leg_masses_urdf.append(
self._pybullet_client.getDynamicsInfo(self.quadruped, motor_id)[0])
def _RecordInertiaInfoFromURDF(self):
"""Record the inertia of each body from URDF file."""
self._link_urdf = []
num_bodies = self._pybullet_client.getNumJoints(self.quadruped)
for body_id in range(-1, num_bodies): # -1 is for the base link.
inertia = self._pybullet_client.getDynamicsInfo(self.quadruped,
body_id)[2]
self._link_urdf.append(inertia)
# We need to use id+1 to index self._link_urdf because it has the base
# (index = -1) at the first element.
self._base_inertia_urdf = [
self._link_urdf[chassis_id + 1]
for chassis_id in self._chassis_link_ids
]
self._leg_inertia_urdf = [
self._link_urdf[leg_id + 1] for leg_id in self._leg_link_ids
]
self._leg_inertia_urdf.extend(
[self._link_urdf[motor_id + 1] for motor_id in self._motor_link_ids])
def _BuildJointNameToIdDict(self):
num_joints = self._pybullet_client.getNumJoints(self.quadruped)
self._joint_name_to_id = {}
for i in range(num_joints):
joint_info = self._pybullet_client.getJointInfo(self.quadruped, i)
self._joint_name_to_id[joint_info[1].decode("UTF-8")] = joint_info[0]
def _BuildUrdfIds(self):
"""Build the link Ids from its name in the URDF file.
Raises:
ValueError: Unknown category of the joint name.
"""
num_joints = self._pybullet_client.getNumJoints(self.quadruped)
self._chassis_link_ids = [-1]
# The self._leg_link_ids include both the upper and lower links of the leg.
self._leg_link_ids = []
self._motor_link_ids = []
self._foot_link_ids = []
self._bracket_link_ids = []
for i in range(num_joints):
joint_info = self._pybullet_client.getJointInfo(self.quadruped, i)
joint_name = joint_info[1].decode("UTF-8")
joint_id = self._joint_name_to_id[joint_name]
if _CHASSIS_NAME_PATTERN.match(joint_name):
self._chassis_link_ids.append(joint_id)
elif _BRACKET_NAME_PATTERN.match(joint_name):
self._bracket_link_ids.append(joint_id)
elif _MOTOR_NAME_PATTERN.match(joint_name):
self._motor_link_ids.append(joint_id)
elif _KNEE_NAME_PATTERN.match(joint_name):
self._foot_link_ids.append(joint_id)
elif (_LEG_NAME_PATTERN1.match(joint_name)
or _LEG_NAME_PATTERN2.match(joint_name)
or _LEG_NAME_PATTERN3.match(joint_name)):
self._leg_link_ids.append(joint_id)
else:
raise ValueError("Unknown category of joint %s" % joint_name)
self._leg_link_ids.extend(self._foot_link_ids)
self._chassis_link_ids.sort()
self._motor_link_ids.sort()
self._foot_link_ids.sort()
self._leg_link_ids.sort()
self._bracket_link_ids.sort()
def _RemoveDefaultJointDamping(self):
num_joints = self._pybullet_client.getNumJoints(self.quadruped)
for i in range(num_joints):
joint_info = self._pybullet_client.getJointInfo(self.quadruped, i)
self._pybullet_client.changeDynamics(joint_info[0],
-1,
linearDamping=0,
angularDamping=0)
def _BuildMotorIdList(self):
self._motor_id_list = [
self._joint_name_to_id[motor_name]
for motor_name in self._GetMotorNames()
]
def _CreateRackConstraint(self, init_position, init_orientation):
"""Create a constraint that keeps the chassis at a fixed frame.
This frame is defined by init_position and init_orientation.
Args:
init_position: initial position of the fixed frame.
init_orientation: initial orientation of the fixed frame in quaternion
format [x,y,z,w].
Returns:
Return the constraint id.
"""
fixed_constraint = self._pybullet_client.createConstraint(
parentBodyUniqueId=self.quadruped,
parentLinkIndex=-1,
childBodyUniqueId=-1,
childLinkIndex=-1,
jointType=self._pybullet_client.JOINT_FIXED,
jointAxis=[0, 0, 0],
parentFramePosition=[0, 0, 0],
childFramePosition=init_position,
childFrameOrientation=init_orientation)
return fixed_constraint
def IsObservationValid(self):
"""Whether the observation is valid for the current time step.
In simulation, observations are always valid. In real hardware, it may not
be valid from time to time when communication error happens between the
Nvidia TX2 and the microcontroller.
Returns:
Whether the observation is valid for the current time step.
"""
return True
def Reset(self, reload_urdf=True, default_motor_angles=None, reset_time=3.0):
"""Reset the minitaur to its initial states.
Args:
reload_urdf: Whether to reload the urdf file. If not, Reset() just place
the minitaur back to its starting position.
default_motor_angles: The default motor angles. If it is None, minitaur
will hold a default pose (motor angle math.pi / 2) for 100 steps. In
torque control mode, the phase of holding the default pose is skipped.
reset_time: The duration (in seconds) to hold the default motor angles. If
reset_time <= 0 or in torque control mode, the phase of holding the
default pose is skipped.
"""
if reload_urdf:
self._LoadRobotURDF()
if self._on_rack:
self.rack_constraint = (self._CreateRackConstraint(
self._GetDefaultInitPosition(), self._GetDefaultInitOrientation()))
self._BuildJointNameToIdDict()
self._BuildUrdfIds()
self._RemoveDefaultJointDamping()
self._BuildMotorIdList()
self._RecordMassInfoFromURDF()
self._RecordInertiaInfoFromURDF()
self.ResetPose(add_constraint=True)
else:
self._pybullet_client.resetBasePositionAndOrientation(
self.quadruped, self._GetDefaultInitPosition(),
self._GetDefaultInitOrientation())
self._pybullet_client.resetBaseVelocity(self.quadruped, [0, 0, 0],
[0, 0, 0])
self.ResetPose(add_constraint=False)
self._overheat_counter = np.zeros(self.num_motors)
self._motor_enabled_list = [True] * self.num_motors
self._observation_history.clear()
self._step_counter = 0
self._state_action_counter = 0
self._is_safe = True
self._last_action = None
self._SettleDownForReset(default_motor_angles, reset_time)
if self._enable_action_filter:
self._ResetActionFilter()
def _LoadRobotURDF(self):
"""Loads the URDF file for the robot."""
urdf_file = self.GetURDFFile()
if self._self_collision_enabled:
self.quadruped = self._pybullet_client.loadURDF(
urdf_file,
self._GetDefaultInitPosition(),
self._GetDefaultInitOrientation(),
flags=self._pybullet_client.URDF_USE_SELF_COLLISION)
else:
self.quadruped = self._pybullet_client.loadURDF(
urdf_file, self._GetDefaultInitPosition(),
self._GetDefaultInitOrientation())
def _SettleDownForReset(self, default_motor_angles, reset_time):
"""Sets the default motor angles and waits for the robot to settle down.
The reset is skipped is reset_time is less than zereo.
Args:
default_motor_angles: A list of motor angles that the robot will achieve
at the end of the reset phase.
reset_time: The time duration for the reset phase.
"""
if reset_time <= 0:
return
# Important to fill the observation buffer.
self.ReceiveObservation()
for _ in range(100):
self._StepInternal(
[math.pi / 2] * self.num_motors,
motor_control_mode=robot_config.MotorControlMode.POSITION)
# Don't continue to reset if a safety error has occurred.
if not self._is_safe:
return
if default_motor_angles is None:
return
num_steps_to_reset = int(reset_time / self.time_step)
for _ in range(num_steps_to_reset):
self._StepInternal(
default_motor_angles,
motor_control_mode=robot_config.MotorControlMode.POSITION)
# Don't continue to reset if a safety error has occurred.
if not self._is_safe:
return
def _SetMotorTorqueById(self, motor_id, torque):
self._pybullet_client.setJointMotorControl2(
bodyIndex=self.quadruped,
jointIndex=motor_id,
controlMode=self._pybullet_client.TORQUE_CONTROL,
force=torque)
def _SetMotorTorqueByIds(self, motor_ids, torques):
self._pybullet_client.setJointMotorControlArray(
bodyIndex=self.quadruped,
jointIndices=motor_ids,
controlMode=self._pybullet_client.TORQUE_CONTROL,
forces=torques)
def _SetDesiredMotorAngleByName(self, motor_name, desired_angle):
self._SetDesiredMotorAngleById(self._joint_name_to_id[motor_name],
desired_angle)
def GetURDFFile(self):
return "quadruped/minitaur.urdf"
def ResetPose(self, add_constraint):
"""Reset the pose of the minitaur.
Args:
add_constraint: Whether to add a constraint at the joints of two feet.
"""
for i in range(self.num_legs):
self._ResetPoseForLeg(i, add_constraint)
def _ResetPoseForLeg(self, leg_id, add_constraint):
"""Reset the initial pose for the leg.
Args:
leg_id: It should be 0, 1, 2, or 3, which represents the leg at
front_left, back_left, front_right and back_right.
add_constraint: Whether to add a constraint at the joints of two feet.
"""
knee_friction_force = 0
half_pi = math.pi / 2.0
knee_angle = -2.1834
leg_position = LEG_POSITION[leg_id]
self._pybullet_client.resetJointState(
self.quadruped,
self._joint_name_to_id["motor_" + leg_position + "L_joint"],
self._motor_direction[2 * leg_id] * half_pi,
targetVelocity=0)
self._pybullet_client.resetJointState(
self.quadruped,
self._joint_name_to_id["knee_" + leg_position + "L_link"],
self._motor_direction[2 * leg_id] * knee_angle,
targetVelocity=0)
self._pybullet_client.resetJointState(
self.quadruped,
self._joint_name_to_id["motor_" + leg_position + "R_joint"],
self._motor_direction[2 * leg_id + 1] * half_pi,
targetVelocity=0)
self._pybullet_client.resetJointState(
self.quadruped,
self._joint_name_to_id["knee_" + leg_position + "R_link"],
self._motor_direction[2 * leg_id + 1] * knee_angle,
targetVelocity=0)
if add_constraint:
self._pybullet_client.createConstraint(
self.quadruped,
self._joint_name_to_id["knee_" + leg_position + "R_link"],
self.quadruped,
self._joint_name_to_id["knee_" + leg_position + "L_link"],
self._pybullet_client.JOINT_POINT2POINT, [0, 0, 0],
KNEE_CONSTRAINT_POINT_RIGHT, KNEE_CONSTRAINT_POINT_LEFT)
# Disable the default motor in pybullet.
self._pybullet_client.setJointMotorControl2(
bodyIndex=self.quadruped,
jointIndex=(self._joint_name_to_id["motor_" + leg_position +
"L_joint"]),
controlMode=self._pybullet_client.VELOCITY_CONTROL,
targetVelocity=0,
force=knee_friction_force)
self._pybullet_client.setJointMotorControl2(
bodyIndex=self.quadruped,
jointIndex=(self._joint_name_to_id["motor_" + leg_position +
"R_joint"]),
controlMode=self._pybullet_client.VELOCITY_CONTROL,
targetVelocity=0,
force=knee_friction_force)
self._pybullet_client.setJointMotorControl2(
bodyIndex=self.quadruped,
jointIndex=(self._joint_name_to_id["knee_" + leg_position + "L_link"]),
controlMode=self._pybullet_client.VELOCITY_CONTROL,
targetVelocity=0,
force=knee_friction_force)
self._pybullet_client.setJointMotorControl2(
bodyIndex=self.quadruped,
jointIndex=(self._joint_name_to_id["knee_" + leg_position + "R_link"]),
controlMode=self._pybullet_client.VELOCITY_CONTROL,
targetVelocity=0,
force=knee_friction_force)
def GetBasePosition(self):
"""Get the position of minitaur's base.
Returns:
The position of minitaur's base.
"""
return self._base_position
def GetBaseVelocity(self):
"""Get the linear velocity of minitaur's base.
Returns:
The velocity of minitaur's base.
"""
velocity, _ = self._pybullet_client.getBaseVelocity(self.quadruped)
return velocity
def GetTrueBaseRollPitchYaw(self):
"""Get minitaur's base orientation in euler angle in the world frame.
Returns:
A tuple (roll, pitch, yaw) of the base in world frame.
"""
orientation = self.GetTrueBaseOrientation()
roll_pitch_yaw = self._pybullet_client.getEulerFromQuaternion(orientation)
return np.asarray(roll_pitch_yaw)
def GetBaseRollPitchYaw(self):
"""Get minitaur's base orientation in euler angle in the world frame.
This function mimicks the noisy sensor reading and adds latency.
Returns:
A tuple (roll, pitch, yaw) of the base in world frame polluted by noise
and latency.
"""
delayed_orientation = np.array(
self._control_observation[3 * self.num_motors:3 * self.num_motors + 4])
delayed_roll_pitch_yaw = self._pybullet_client.getEulerFromQuaternion(
delayed_orientation)
roll_pitch_yaw = self._AddSensorNoise(np.array(delayed_roll_pitch_yaw),
self._observation_noise_stdev[3])
return roll_pitch_yaw
def GetHipPositionsInBaseFrame(self):
"""Get the hip joint positions of the robot within its base frame."""
raise NotImplementedError("Not implemented for Minitaur.")
def ComputeMotorAnglesFromFootLocalPosition(self, leg_id,
foot_local_position):
"""Use IK to compute the motor angles, given the foot link's local position.
Args:
leg_id: The leg index.
foot_local_position: The foot link's position in the base frame.
Returns:
A tuple. The position indices and the angles for all joints along the
leg. The position indices is consistent with the joint orders as returned
by GetMotorAngles API.
"""
assert len(self._foot_link_ids) == self.num_legs
toe_id = self._foot_link_ids[leg_id]
motors_per_leg = self.num_motors // self.num_legs
joint_position_idxs = list(
range(leg_id * motors_per_leg,
leg_id * motors_per_leg + motors_per_leg))
joint_angles = kinematics.joint_angles_from_link_position(
robot=self,
link_position=foot_local_position,
link_id=toe_id,
joint_ids=joint_position_idxs,
)
# Joint offset is necessary for Laikago.
joint_angles = np.multiply(
np.asarray(joint_angles) -
np.asarray(self._motor_offset)[joint_position_idxs],
self._motor_direction[joint_position_idxs])
# Return the joing index (the same as when calling GetMotorAngles) as well
# as the angles.
return joint_position_idxs, joint_angles.tolist()
def ComputeJacobian(self, leg_id):
"""Compute the Jacobian for a given leg."""
# Does not work for Minitaur which has the four bar mechanism for now.
assert len(self._foot_link_ids) == self.num_legs
full_jacobian = kinematics.compute_jacobian(
robot=self,
link_id=self._foot_link_ids[leg_id],
)
motors_per_leg = self.num_motors // self.num_legs
com_dof = 6
return full_jacobian[com_dof + leg_id * motors_per_leg:com_dof +
(leg_id + 1) * motors_per_leg]
def MapContactForceToJointTorques(self, leg_id, contact_force):
"""Maps the foot contact force to the leg joint torques."""
jv = self.ComputeJacobian(leg_id)
motor_torques_list = np.matmul(contact_force, jv)
motor_torques_dict = {}
motors_per_leg = self.num_motors // self.num_legs
for torque_id, joint_id in enumerate(
range(leg_id * motors_per_leg, (leg_id + 1) * motors_per_leg)):
motor_torques_dict[joint_id] = motor_torques_list[torque_id]
return motor_torques_dict
def GetFootContacts(self):
"""Get minitaur's foot contact situation with the ground.
Returns:
A list of 4 booleans. The ith boolean is True if leg i is in contact with
ground.
"""
contacts = []
for leg_idx in range(MINITAUR_NUM_MOTORS // 2):
link_id_1 = self._foot_link_ids[leg_idx * 2]
link_id_2 = self._foot_link_ids[leg_idx * 2 + 1]
contact_1 = bool(
self._pybullet_client.getContactPoints(bodyA=0,
bodyB=self.quadruped,
linkIndexA=-1,
linkIndexB=link_id_1))
contact_2 = bool(
self._pybullet_client.getContactPoints(bodyA=0,
bodyB=self.quadruped,
linkIndexA=-1,
linkIndexB=link_id_2))
contacts.append(contact_1 or contact_2)
return contacts
def GetFootPositionsInBaseFrame(self):
"""Get the robot's foot position in the base frame."""
assert len(self._foot_link_ids) == self.num_legs
foot_positions = []
for foot_id in self.GetFootLinkIDs():
foot_positions.append(
kinematics.link_position_in_base_frame(
robot=self,
link_id=foot_id,
))
return np.array(foot_positions)
def GetTrueMotorAngles(self):
"""Gets the eight motor angles at the current moment, mapped to [-pi, pi].
Returns:
Motor angles, mapped to [-pi, pi].
"""
motor_angles = [state[0] for state in self._joint_states]
motor_angles = np.multiply(
np.asarray(motor_angles) - np.asarray(self._motor_offset),
self._motor_direction)
return motor_angles
def GetMotorAngles(self):
"""Gets the eight motor angles.
This function mimicks the noisy sensor reading and adds latency. The motor
angles that are delayed, noise polluted, and mapped to [-pi, pi].
Returns:
Motor angles polluted by noise and latency, mapped to [-pi, pi].
"""
motor_angles = self._AddSensorNoise(
np.array(self._control_observation[0:self.num_motors]),
self._observation_noise_stdev[0])
return MapToMinusPiToPi(motor_angles)
def GetTrueMotorVelocities(self):
"""Get the velocity of all eight motors.
Returns:
Velocities of all eight motors.
"""
motor_velocities = [state[1] for state in self._joint_states]
motor_velocities = np.multiply(motor_velocities, self._motor_direction)
return motor_velocities
def GetMotorVelocities(self):
"""Get the velocity of all eight motors.
This function mimicks the noisy sensor reading and adds latency.
Returns:
Velocities of all eight motors polluted by noise and latency.
"""
return self._AddSensorNoise(
np.array(self._control_observation[self.num_motors:2 *
self.num_motors]),
self._observation_noise_stdev[1])
def GetTrueMotorTorques(self):
"""Get the amount of torque the motors are exerting.
Returns:
Motor torques of all eight motors.
"""
return self._observed_motor_torques
def GetMotorTorques(self):
"""Get the amount of torque the motors are exerting.
This function mimicks the noisy sensor reading and adds latency.
Returns:
Motor torques of all eight motors polluted by noise and latency.
"""
return self._AddSensorNoise(
np.array(self._control_observation[2 * self.num_motors:3 *
self.num_motors]),
self._observation_noise_stdev[2])
def GetEnergyConsumptionPerControlStep(self):
"""Get the amount of energy used in last one time step.
Returns:
Energy Consumption based on motor velocities and torques (Nm^2/s).
"""
return np.abs(np.dot(
self.GetMotorTorques(),
self.GetMotorVelocities())) * self.time_step * self._action_repeat
def GetTrueBaseOrientation(self):
"""Get the orientation of minitaur's base, represented as quaternion.
Returns:
The orientation of minitaur's base.
"""
return self._base_orientation
def GetBaseOrientation(self):
"""Get the orientation of minitaur's base, represented as quaternion.
This function mimicks the noisy sensor reading and adds latency.
Returns:
The orientation of minitaur's base polluted by noise and latency.
"""
return self._pybullet_client.getQuaternionFromEuler(
self.GetBaseRollPitchYaw())
def GetTrueBaseRollPitchYawRate(self):
"""Get the rate of orientation change of the minitaur's base in euler angle.
Returns:
rate of (roll, pitch, yaw) change of the minitaur's base.
"""
angular_velocity = self._pybullet_client.getBaseVelocity(self.quadruped)[1]
orientation = self.GetTrueBaseOrientation()
return self.TransformAngularVelocityToLocalFrame(angular_velocity,
orientation)
def TransformAngularVelocityToLocalFrame(self, angular_velocity,
orientation):
"""Transform the angular velocity from world frame to robot's frame.
Args:
angular_velocity: Angular velocity of the robot in world frame.
orientation: Orientation of the robot represented as a quaternion.
Returns:
angular velocity of based on the given orientation.
"""
# Treat angular velocity as a position vector, then transform based on the
# orientation given by dividing (or multiplying with inverse).
# Get inverse quaternion assuming the vector is at 0,0,0 origin.
_, orientation_inversed = self._pybullet_client.invertTransform(
[0, 0, 0], orientation)
# Transform the angular_velocity at neutral orientation using a neutral
# translation and reverse of the given orientation.
relative_velocity, _ = self._pybullet_client.multiplyTransforms(
[0, 0, 0], orientation_inversed, angular_velocity,
self._pybullet_client.getQuaternionFromEuler([0, 0, 0]))
return np.asarray(relative_velocity)
def GetBaseRollPitchYawRate(self):
"""Get the rate of orientation change of the minitaur's base in euler angle.
This function mimicks the noisy sensor reading and adds latency.
Returns:
rate of (roll, pitch, yaw) change of the minitaur's base polluted by noise
and latency.
"""
return self._AddSensorNoise(
np.array(self._control_observation[3 * self.num_motors +
4:3 * self.num_motors + 7]),
self._observation_noise_stdev[4])
def GetActionDimension(self):
"""Get the length of the action list.
Returns:
The length of the action list.
"""
return self.num_motors
def _ApplyOverheatProtection(self, actual_torque):
if self._motor_overheat_protection:
for i in range(self.num_motors):
if abs(actual_torque[i]) > OVERHEAT_SHUTDOWN_TORQUE:
self._overheat_counter[i] += 1
else:
self._overheat_counter[i] = 0
if (self._overheat_counter[i] >
OVERHEAT_SHUTDOWN_TIME / self.time_step):
self._motor_enabled_list[i] = False
def ApplyAction(self, motor_commands, motor_control_mode=None):
"""Apply the motor commands using the motor model.
Args:
motor_commands: np.array. Can be motor angles, torques, hybrid commands,
or motor pwms (for Minitaur only).
motor_control_mode: A MotorControlMode enum.
"""
self.last_action_time = self._state_action_counter * self.time_step
control_mode = motor_control_mode
if control_mode is None:
control_mode = self._motor_control_mode
motor_commands = np.asarray(motor_commands)
q, qdot = self._GetPDObservation()
qdot_true = self.GetTrueMotorVelocities()
actual_torque, observed_torque = self._motor_model.convert_to_torque(
motor_commands, q, qdot, qdot_true, control_mode)
# May turn off the motor
self._ApplyOverheatProtection(actual_torque)
# The torque is already in the observation space because we use
# GetMotorAngles and GetMotorVelocities.
self._observed_motor_torques = observed_torque
# Transform into the motor space when applying the torque.
self._applied_motor_torque = np.multiply(actual_torque,
self._motor_direction)
motor_ids = []
motor_torques = []
for motor_id, motor_torque, motor_enabled in zip(
self._motor_id_list, self._applied_motor_torque,
self._motor_enabled_list):
if motor_enabled:
motor_ids.append(motor_id)
motor_torques.append(motor_torque)
else:
motor_ids.append(motor_id)
motor_torques.append(0)
self._SetMotorTorqueByIds(motor_ids, motor_torques)
def ConvertFromLegModel(self, actions):
"""Convert the actions that use leg model to the real motor actions.
Args:
actions: The theta, phi of the leg model.
Returns:
The eight desired motor angles that can be used in ApplyActions().
"""
motor_angle = copy.deepcopy(actions)
scale_for_singularity = 1
offset_for_singularity = 1.5
half_num_motors = self.num_motors // 2
quater_pi = math.pi / 4
for i in range(self.num_motors):
action_idx = i // 2
forward_backward_component = (
-scale_for_singularity * quater_pi *
(actions[action_idx + half_num_motors] + offset_for_singularity))
extension_component = (-1)**i * quater_pi * actions[action_idx]
if i >= half_num_motors:
extension_component = -extension_component
motor_angle[i] = (math.pi + forward_backward_component +
extension_component)
return motor_angle
def GetBaseMassesFromURDF(self):
"""Get the mass of the base from the URDF file."""
return self._base_mass_urdf
def GetBaseInertiasFromURDF(self):
"""Get the inertia of the base from the URDF file."""
return self._base_inertia_urdf
def GetLegMassesFromURDF(self):
"""Get the mass of the legs from the URDF file."""
return self._leg_masses_urdf
def GetLegInertiasFromURDF(self):
"""Get the inertia of the legs from the URDF file."""
return self._leg_inertia_urdf
def SetBaseMasses(self, base_mass):
"""Set the mass of minitaur's base.
Args:
base_mass: A list of masses of each body link in CHASIS_LINK_IDS. The
length of this list should be the same as the length of CHASIS_LINK_IDS.
Raises:
ValueError: It is raised when the length of base_mass is not the same as
the length of self._chassis_link_ids.
"""
if len(base_mass) != len(self._chassis_link_ids):
raise ValueError(
"The length of base_mass {} and self._chassis_link_ids {} are not "
"the same.".format(len(base_mass), len(self._chassis_link_ids)))
for chassis_id, chassis_mass in zip(self._chassis_link_ids, base_mass):
self._pybullet_client.changeDynamics(self.quadruped,
chassis_id,
mass=chassis_mass)
def SetLegMasses(self, leg_masses):
"""Set the mass of the legs.
A leg includes leg_link and motor. 4 legs contain 16 links (4 links each)
and 8 motors. First 16 numbers correspond to link masses, last 8 correspond
to motor masses (24 total).
Args:
leg_masses: The leg and motor masses for all the leg links and motors.
Raises:
ValueError: It is raised when the length of masses is not equal to number
of links + motors.
"""
if len(leg_masses) != len(self._leg_link_ids) + len(self._motor_link_ids):
raise ValueError("The number of values passed to SetLegMasses are "
"different than number of leg links and motors.")
for leg_id, leg_mass in zip(self._leg_link_ids, leg_masses):
self._pybullet_client.changeDynamics(self.quadruped,
leg_id,
mass=leg_mass)
motor_masses = leg_masses[len(self._leg_link_ids):]
for link_id, motor_mass in zip(self._motor_link_ids, motor_masses):
self._pybullet_client.changeDynamics(self.quadruped,
link_id,
mass=motor_mass)
def SetBaseInertias(self, base_inertias):
"""Set the inertias of minitaur's base.
Args:
base_inertias: A list of inertias of each body link in CHASIS_LINK_IDS.
The length of this list should be the same as the length of
CHASIS_LINK_IDS.
Raises:
ValueError: It is raised when the length of base_inertias is not the same
as the length of self._chassis_link_ids and base_inertias contains
negative values.
"""
if len(base_inertias) != len(self._chassis_link_ids):
raise ValueError(
"The length of base_inertias {} and self._chassis_link_ids {} are "
"not the same.".format(len(base_inertias),
len(self._chassis_link_ids)))
for chassis_id, chassis_inertia in zip(self._chassis_link_ids,
base_inertias):
for inertia_value in chassis_inertia:
if (np.asarray(inertia_value) < 0).any():
raise ValueError("Values in inertia matrix should be non-negative.")
self._pybullet_client.changeDynamics(
self.quadruped, chassis_id, localInertiaDiagonal=chassis_inertia)
def SetLegInertias(self, leg_inertias):
"""Set the inertias of the legs.
A leg includes leg_link and motor. 4 legs contain 16 links (4 links each)
and 8 motors. First 16 numbers correspond to link inertia, last 8 correspond
to motor inertia (24 total).
Args:
leg_inertias: The leg and motor inertias for all the leg links and motors.
Raises:
ValueError: It is raised when the length of inertias is not equal to
the number of links + motors or leg_inertias contains negative values.
"""
if len(leg_inertias) != len(self._leg_link_ids) + len(
self._motor_link_ids):
raise ValueError("The number of values passed to SetLegMasses are "
"different than number of leg links and motors.")
for leg_id, leg_inertia in zip(self._leg_link_ids, leg_inertias):
for inertia_value in leg_inertias:
if (np.asarray(inertia_value) < 0).any():
raise ValueError("Values in inertia matrix should be non-negative.")
self._pybullet_client.changeDynamics(self.quadruped,
leg_id,
localInertiaDiagonal=leg_inertia)
motor_inertias = leg_inertias[len(self._leg_link_ids):]
for link_id, motor_inertia in zip(self._motor_link_ids, motor_inertias):
for inertia_value in motor_inertias:
if (np.asarray(inertia_value) < 0).any():
raise ValueError("Values in inertia matrix should be non-negative.")
self._pybullet_client.changeDynamics(self.quadruped,
link_id,
localInertiaDiagonal=motor_inertia)
def SetFootFriction(self, foot_friction):
"""Set the lateral friction of the feet.
Args:
foot_friction: The lateral friction coefficient of the foot. This value is
shared by all four feet.
"""
for link_id in self._foot_link_ids:
self._pybullet_client.changeDynamics(self.quadruped,
link_id,
lateralFriction=foot_friction)
def SetFootRestitution(self, foot_restitution):
"""Set the coefficient of restitution at the feet.
Args:
foot_restitution: The coefficient of restitution (bounciness) of the feet.
This value is shared by all four feet.
"""
for link_id in self._foot_link_ids:
self._pybullet_client.changeDynamics(self.quadruped,
link_id,
restitution=foot_restitution)
def SetJointFriction(self, joint_frictions):
for knee_joint_id, friction in zip(self._foot_link_ids, joint_frictions):
self._pybullet_client.setJointMotorControl2(
bodyIndex=self.quadruped,
jointIndex=knee_joint_id,
controlMode=self._pybullet_client.VELOCITY_CONTROL,
targetVelocity=0,
force=friction)
def GetNumKneeJoints(self):
return len(self._foot_link_ids)
def SetBatteryVoltage(self, voltage):
self._motor_model.set_voltage(voltage)
def SetMotorViscousDamping(self, viscous_damping):
self._motor_model.set_viscous_damping(viscous_damping)
def GetTrueObservation(self):
observation = []
observation.extend(self.GetTrueMotorAngles())
observation.extend(self.GetTrueMotorVelocities())
observation.extend(self.GetTrueMotorTorques())
observation.extend(self.GetTrueBaseOrientation())
observation.extend(self.GetTrueBaseRollPitchYawRate())
return observation
def ReceiveObservation(self):
"""Receive the observation from sensors.
This function is called once per step. The observations are only updated
when this function is called.
"""
self._joint_states = self._pybullet_client.getJointStates(
self.quadruped, self._motor_id_list)
self._base_position, orientation = (
self._pybullet_client.getBasePositionAndOrientation(self.quadruped))
# Computes the relative orientation relative to the robot's
# initial_orientation.
_, self._base_orientation = self._pybullet_client.multiplyTransforms(
positionA=[0, 0, 0],
orientationA=orientation,
positionB=[0, 0, 0],
orientationB=self._init_orientation_inv)
self._observation_history.appendleft(self.GetTrueObservation())
self._control_observation = self._GetControlObservation()
self.last_state_time = self._state_action_counter * self.time_step
def _GetDelayedObservation(self, latency):
"""Get observation that is delayed by the amount specified in latency.
Args:
latency: The latency (in seconds) of the delayed observation.
Returns:
observation: The observation which was actually latency seconds ago.
"""
if latency <= 0 or len(self._observation_history) == 1:
observation = self._observation_history[0]
else:
n_steps_ago = int(latency / self.time_step)
if n_steps_ago + 1 >= len(self._observation_history):
return self._observation_history[-1]
remaining_latency = latency - n_steps_ago * self.time_step
blend_alpha = remaining_latency / self.time_step
observation = (
(1.0 - blend_alpha) *
np.array(self._observation_history[n_steps_ago]) +
blend_alpha * np.array(self._observation_history[n_steps_ago + 1]))
return observation
def _GetPDObservation(self):
pd_delayed_observation = self._GetDelayedObservation(self._pd_latency)
q = pd_delayed_observation[0:self.num_motors]
qdot = pd_delayed_observation[self.num_motors:2 * self.num_motors]
return (np.array(q), np.array(qdot))
def _GetControlObservation(self):
control_delayed_observation = self._GetDelayedObservation(
self._control_latency)
return control_delayed_observation
def _AddSensorNoise(self, sensor_values, noise_stdev):
if noise_stdev <= 0:
return sensor_values
observation = sensor_values + np.random.normal(scale=noise_stdev,
size=sensor_values.shape)
return observation
def SetControlLatency(self, latency):
"""Set the latency of the control loop.
It measures the duration between sending an action from Nvidia TX2 and
receiving the observation from microcontroller.
Args:
latency: The latency (in seconds) of the control loop.
"""
self._control_latency = latency
def GetControlLatency(self):
"""Get the control latency.
Returns:
The latency (in seconds) between when the motor command is sent and when
the sensor measurements are reported back to the controller.
"""
return self._control_latency
def SetMotorGains(self, kp, kd):
"""Set the gains of all motors.
These gains are PD gains for motor positional control. kp is the
proportional gain and kd is the derivative gain.
Args:
kp: proportional gain(s) of the motors.
kd: derivative gain(s) of the motors.
"""
if isinstance(kp, (collections.Sequence, np.ndarray)):
self._motor_kps = np.asarray(kp)
else:
self._motor_kps = np.full(self.num_motors, kp)
if isinstance(kd, (collections.Sequence, np.ndarray)):
self._motor_kds = np.asarray(kd)
else:
self._motor_kds = np.full(self.num_motors, kd)
self._motor_model.set_motor_gains(kp, kd)
def GetMotorGains(self):
"""Get the gains of the motor.
Returns:
The proportional gain.
The derivative gain.
"""
return self._motor_kps, self._motor_kds
def GetMotorPositionGains(self):
"""Get the position gains of the motor.
Returns:
The proportional gain.
"""
return self._motor_kps
def GetMotorVelocityGains(self):
"""Get the velocity gains of the motor.
Returns:
The derivative gain.
"""
return self._motor_kds
def SetMotorStrengthRatio(self, ratio):
"""Set the strength of all motors relative to the default value.
Args:
ratio: The relative strength. A scalar range from 0.0 to 1.0.
"""
self._motor_model.set_strength_ratios([ratio] * self.num_motors)
def SetMotorStrengthRatios(self, ratios):
"""Set the strength of each motor relative to the default value.
Args:
ratios: The relative strength. A numpy array ranging from 0.0 to 1.0.
"""
self._motor_model.set_strength_ratios(ratios)
def SetTimeSteps(self, action_repeat, simulation_step):
"""Set the time steps of the control and simulation.
Args:
action_repeat: The number of simulation steps that the same action is
repeated.
simulation_step: The simulation time step.
"""
self.time_step = simulation_step
self._action_repeat = action_repeat
def _GetMotorNames(self):
return MOTOR_NAMES
def _GetDefaultInitPosition(self):
"""Returns the init position of the robot.
It can be either 1) origin (INIT_POSITION), 2) origin with a rack
(INIT_RACK_POSITION), or 3) the previous position.
"""
# If we want continuous resetting and is not the first episode.
if self._reset_at_current_position and self._observation_history:
x, y, _ = self.GetBasePosition()
_, _, z = INIT_POSITION
return [x, y, z]
if self._on_rack:
return INIT_RACK_POSITION
else:
return INIT_POSITION
def _GetDefaultInitOrientation(self):
"""Returns the init position of the robot.
It can be either 1) INIT_ORIENTATION or 2) the previous rotation in yaw.
"""
# If we want continuous resetting and is not the first episode.
if self._reset_at_current_position and self._observation_history:
_, _, yaw = self.GetBaseRollPitchYaw()
return self._pybullet_client.getQuaternionFromEuler([0.0, 0.0, yaw])
return INIT_ORIENTATION
@property
def chassis_link_ids(self):
return self._chassis_link_ids
def SetAllSensors(self, sensors):
"""set all sensors to this robot and move the ownership to this robot.
Args:
sensors: a list of sensors to this robot.
"""
for s in sensors:
s.set_robot(self)
self._sensors = sensors
def GetAllSensors(self):
"""get all sensors associated with this robot.
Returns:
sensors: a list of all sensors.
"""
return self._sensors
def GetSensor(self, name):
"""get the first sensor with the given name.
This function return None if a sensor with the given name does not exist.
Args:
name: the name of the sensor we are looking
Returns:
sensor: a sensor with the given name. None if not exists.
"""
for s in self._sensors:
if s.get_name() == name:
return s
return None
@property
def is_safe(self):
return self._is_safe
@property
def last_action(self):
return self._last_action
def ProcessAction(self, action, substep_count):
"""If enabled, interpolates between the current and previous actions.
Args:
action: current action.
substep_count: the step count should be between [0, self.__action_repeat).
Returns:
If interpolation is enabled, returns interpolated action depending on
the current action repeat substep.
"""
if self._enable_action_interpolation and self._last_action is not None:
lerp = float(substep_count + 1) / self._action_repeat
proc_action = self._last_action + lerp * (action - self._last_action)
else:
proc_action = action
return proc_action
def _BuildActionFilter(self):
sampling_rate = 1 / (self.time_step * self._action_repeat)
num_joints = self.GetActionDimension()
a_filter = action_filter.ActionFilterButter(sampling_rate=sampling_rate,
num_joints=num_joints)
return a_filter
def _ResetActionFilter(self):
self._action_filter.reset()
def _FilterAction(self, action):
# initialize the filter history, since resetting the filter will fill
# the history with zeros and this can cause sudden movements at the start
# of each episode
if self._step_counter == 0:
default_action = self.GetMotorAngles()
self._action_filter.init_history(default_action)
filtered_action = self._action_filter.filter(action)
return filtered_action
@property
def pybullet_client(self):
return self._pybullet_client
@property
def joint_states(self):
return self._joint_states
@classmethod
def GetConstants(cls):
del cls
return minitaur_constants | 0.937683 | 0.497253 |
import os
import sys
import glog as log
import json
import pkg_resources
import tempfile
import struct
import base64
import traceback
import avro.schema
from avro.datafile import DataFileReader, DataFileWriter
from avro.io import DatumReader, DatumWriter, BinaryDecoder, BinaryEncoder
from confluent_kafka.avro.cached_schema_registry_client import CachedSchemaRegistryClient
from confluent_kafka.avro.serializer.message_serializer import (
MessageSerializer,
ContextStringIO,
MAGIC_BYTE,
)
from confluent_kafka.avro.serializer import SerializerError
from multivitamin.data.response import config
class AvroIO:
def __init__(self, schema_registry_url=None):
"""Public interface for Avro IO functionality
Args:
use_schema_registry (bool): flag to use schema registry via client ID and registry URL
use_base64 (bool): encoding binary to base64
"""
self.impl = None
self.use_base64 = False
if schema_registry_url:
log.info(f"schema_registry_url: {schema_registry_url}")
self.impl = _AvroIORegistry(schema_registry_url)
else:
log.warning("registry_url is None, using local schema and serializing w/o magic byte")
self.impl = _AvroIOLocal()
def get_schema(self):
"""Return schema
Returns:
avro.schema.RecordSchema: schema
"""
return self.impl.schema
def get_schema_str(self):
"""Return schema as str
Returns:
str: schema as str
"""
return str(self.impl.schema).replace("\\", "")
def decode_binary_file(self, file_path):
"""Decode an Avro Binary using the schema
Args:
file_path (str) : avro binary file
Returns:
dict: avro document
"""
if not os.path.exists(file_path):
log.error("Missing: {}".format(file_path))
raise FileNotFoundError("Missing: {}".format(file_path))
log.info("Decoding file: {}".format(file_path))
return self.decode(open(file_path, "rb").read())
def decode(self, bytes, use_base64=False, binary_flag=True):
"""Decode an Avro Binary using the CV schema from bytes
Args:
bytes
use_base64
binary_flag
Returns:
dict:
"""
if use_base64:
bytes = base64.b64decode(bytes)
if binary_flag:
return self.impl.decode(bytes)
else:
return json.loads(str(bytes))
def write(self, doc, file, serialize=True, indent=None):
"""Write Avro doc
Args:
doc (dict): dict of the avro document
file_path (str): avro binary file output
serialize (bool): whether to serialize avro doc to a binary file
indent (int): if serialize=False, write json with indentation=indent
Returns:
bool: True if successfully wrote file
"""
if serialize:
try:
bytes = self.encode(doc)
with open(file, "wb") as wf:
wf.write(bytes)
except avro.io.AvroTypeException:
log.error("avro.io.AvroTypeException: the datum is not an example of the schema")
return False
log.info("Encoded doc to file: {}".format(file))
else:
if not self.is_valid_avro_doc(doc):
log.error("datum is not an example of schema")
return False
with open(file, "w") as wf:
json.dump(doc, wf, indent=indent)
return True
def encode(self, doc, use_base64=False):
"""Encode an avro doc to bytes
"""
bytes = self.impl.encode(doc)
if use_base64:
log.info(f"use_base64={use_base64}")
bytes = base64.b64encode(bytes)
return bytes
def is_valid_avro_doc(self, doc):
"""Boolean test to validate json against a schema
Args:
doc (dict): avro doc as a dict
Returns:
boolean: True if json is an example of schema
"""
try:
writer = DataFileWriter(tempfile.TemporaryFile(), DatumWriter(), self.impl.schema)
writer.append(doc)
writer.close()
except:
return False
return True
@staticmethod
def is_valid_avro_doc_static(doc, schema):
"""Boolean test to validate json against a schema
Args:
doc (dict): avro doc as a dict
schema (str or dict): schema as a string or dict
Returns:
boolean: True if json is an example of schema
"""
if isinstance(schema, str):
avro_schema = avro.schema.Parse(schema)
else:
avro_schema = schema
try:
writer = DataFileWriter(tempfile.TemporaryFile(), DatumWriter(), avro_schema)
writer.append(doc)
writer.close()
except:
return False
return True
class _AvroIOLocal:
def __init__(self):
"""Private implementation class for Avro IO of local files"""
local_schema_file = pkg_resources.resource_filename(
"multivitamin.data.response", config.SCHEMA_FILE
)
log.debug("Using local schema file {}".format(local_schema_file))
if not os.path.exists(local_schema_file):
raise FileNotFoundError("Schema file not found")
self.schema = avro.schema.Parse(open(local_schema_file).read())
def decode(self, bytes):
if len(bytes) <= 5:
raise SerializerError("Message is too small to decode")
with ContextStringIO(bytes) as payload:
magic, schema_id = struct.unpack(">bI", payload.read(5))
if magic != MAGIC_BYTE:
raise SerializerError("message does not start with magic byte")
curr_pos = payload.tell()
avro_reader = avro.io.DatumReader(self.schema)
def decoder(p):
bin_decoder = avro.io.BinaryDecoder(p)
return avro_reader.read(bin_decoder)
return decoder(payload)
def encode(self, record):
with ContextStringIO() as outf:
outf.write(struct.pack("b", MAGIC_BYTE))
outf.write(struct.pack(">I", config.SCHEMA_ID))
encoder = avro.io.BinaryEncoder(outf)
writer = avro.io.DatumWriter(self.schema)
writer.write(record, encoder)
return outf.getvalue()
class _AvroIORegistry:
def __init__(self, schema_registry_url):
"""Private implementation class for Avro IO using the registry"""
log.info(f"Using registry with schema_url/id {schema_registry_url}/{config.SCHEMA_ID}")
try:
self.client = CachedSchemaRegistryClient(url=schema_registry_url)
self.schema = self.client.get_by_id(config.SCHEMA_ID)
self.serializer = MessageSerializer(self.client)
except:
raise ValueError("Client id or schema id not found")
def decode(self, bytes):
return self.serializer.decode_message(bytes)
def encode(self, record):
return self.serializer.encode_record_with_schema_id(config.SCHEMA_ID, record) | multivitamin/data/response/io.py | import os
import sys
import glog as log
import json
import pkg_resources
import tempfile
import struct
import base64
import traceback
import avro.schema
from avro.datafile import DataFileReader, DataFileWriter
from avro.io import DatumReader, DatumWriter, BinaryDecoder, BinaryEncoder
from confluent_kafka.avro.cached_schema_registry_client import CachedSchemaRegistryClient
from confluent_kafka.avro.serializer.message_serializer import (
MessageSerializer,
ContextStringIO,
MAGIC_BYTE,
)
from confluent_kafka.avro.serializer import SerializerError
from multivitamin.data.response import config
class AvroIO:
def __init__(self, schema_registry_url=None):
"""Public interface for Avro IO functionality
Args:
use_schema_registry (bool): flag to use schema registry via client ID and registry URL
use_base64 (bool): encoding binary to base64
"""
self.impl = None
self.use_base64 = False
if schema_registry_url:
log.info(f"schema_registry_url: {schema_registry_url}")
self.impl = _AvroIORegistry(schema_registry_url)
else:
log.warning("registry_url is None, using local schema and serializing w/o magic byte")
self.impl = _AvroIOLocal()
def get_schema(self):
"""Return schema
Returns:
avro.schema.RecordSchema: schema
"""
return self.impl.schema
def get_schema_str(self):
"""Return schema as str
Returns:
str: schema as str
"""
return str(self.impl.schema).replace("\\", "")
def decode_binary_file(self, file_path):
"""Decode an Avro Binary using the schema
Args:
file_path (str) : avro binary file
Returns:
dict: avro document
"""
if not os.path.exists(file_path):
log.error("Missing: {}".format(file_path))
raise FileNotFoundError("Missing: {}".format(file_path))
log.info("Decoding file: {}".format(file_path))
return self.decode(open(file_path, "rb").read())
def decode(self, bytes, use_base64=False, binary_flag=True):
"""Decode an Avro Binary using the CV schema from bytes
Args:
bytes
use_base64
binary_flag
Returns:
dict:
"""
if use_base64:
bytes = base64.b64decode(bytes)
if binary_flag:
return self.impl.decode(bytes)
else:
return json.loads(str(bytes))
def write(self, doc, file, serialize=True, indent=None):
"""Write Avro doc
Args:
doc (dict): dict of the avro document
file_path (str): avro binary file output
serialize (bool): whether to serialize avro doc to a binary file
indent (int): if serialize=False, write json with indentation=indent
Returns:
bool: True if successfully wrote file
"""
if serialize:
try:
bytes = self.encode(doc)
with open(file, "wb") as wf:
wf.write(bytes)
except avro.io.AvroTypeException:
log.error("avro.io.AvroTypeException: the datum is not an example of the schema")
return False
log.info("Encoded doc to file: {}".format(file))
else:
if not self.is_valid_avro_doc(doc):
log.error("datum is not an example of schema")
return False
with open(file, "w") as wf:
json.dump(doc, wf, indent=indent)
return True
def encode(self, doc, use_base64=False):
"""Encode an avro doc to bytes
"""
bytes = self.impl.encode(doc)
if use_base64:
log.info(f"use_base64={use_base64}")
bytes = base64.b64encode(bytes)
return bytes
def is_valid_avro_doc(self, doc):
"""Boolean test to validate json against a schema
Args:
doc (dict): avro doc as a dict
Returns:
boolean: True if json is an example of schema
"""
try:
writer = DataFileWriter(tempfile.TemporaryFile(), DatumWriter(), self.impl.schema)
writer.append(doc)
writer.close()
except:
return False
return True
@staticmethod
def is_valid_avro_doc_static(doc, schema):
"""Boolean test to validate json against a schema
Args:
doc (dict): avro doc as a dict
schema (str or dict): schema as a string or dict
Returns:
boolean: True if json is an example of schema
"""
if isinstance(schema, str):
avro_schema = avro.schema.Parse(schema)
else:
avro_schema = schema
try:
writer = DataFileWriter(tempfile.TemporaryFile(), DatumWriter(), avro_schema)
writer.append(doc)
writer.close()
except:
return False
return True
class _AvroIOLocal:
def __init__(self):
"""Private implementation class for Avro IO of local files"""
local_schema_file = pkg_resources.resource_filename(
"multivitamin.data.response", config.SCHEMA_FILE
)
log.debug("Using local schema file {}".format(local_schema_file))
if not os.path.exists(local_schema_file):
raise FileNotFoundError("Schema file not found")
self.schema = avro.schema.Parse(open(local_schema_file).read())
def decode(self, bytes):
if len(bytes) <= 5:
raise SerializerError("Message is too small to decode")
with ContextStringIO(bytes) as payload:
magic, schema_id = struct.unpack(">bI", payload.read(5))
if magic != MAGIC_BYTE:
raise SerializerError("message does not start with magic byte")
curr_pos = payload.tell()
avro_reader = avro.io.DatumReader(self.schema)
def decoder(p):
bin_decoder = avro.io.BinaryDecoder(p)
return avro_reader.read(bin_decoder)
return decoder(payload)
def encode(self, record):
with ContextStringIO() as outf:
outf.write(struct.pack("b", MAGIC_BYTE))
outf.write(struct.pack(">I", config.SCHEMA_ID))
encoder = avro.io.BinaryEncoder(outf)
writer = avro.io.DatumWriter(self.schema)
writer.write(record, encoder)
return outf.getvalue()
class _AvroIORegistry:
def __init__(self, schema_registry_url):
"""Private implementation class for Avro IO using the registry"""
log.info(f"Using registry with schema_url/id {schema_registry_url}/{config.SCHEMA_ID}")
try:
self.client = CachedSchemaRegistryClient(url=schema_registry_url)
self.schema = self.client.get_by_id(config.SCHEMA_ID)
self.serializer = MessageSerializer(self.client)
except:
raise ValueError("Client id or schema id not found")
def decode(self, bytes):
return self.serializer.decode_message(bytes)
def encode(self, record):
return self.serializer.encode_record_with_schema_id(config.SCHEMA_ID, record) | 0.579281 | 0.111048 |
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _utilities
__all__ = [
'EndpointGroupEndpointConfigurationArgs',
'EndpointGroupPortOverridesArgs',
'ForwardingRuleRuleActionArgs',
'ForwardingRuleRuleActionForwardGroupConfigArgs',
'ForwardingRuleRuleActionForwardGroupConfigServerGroupTupleArgs',
'ForwardingRuleRuleConditionArgs',
'ForwardingRuleRuleConditionHostConfigArgs',
'ForwardingRuleRuleConditionPathConfigArgs',
'ListenerCertificateArgs',
'ListenerPortRangeArgs',
]
@pulumi.input_type
class EndpointGroupEndpointConfigurationArgs:
def __init__(__self__, *,
endpoint: pulumi.Input[str],
type: pulumi.Input[str],
weight: pulumi.Input[int],
enable_clientip_preservation: Optional[pulumi.Input[bool]] = None):
"""
:param pulumi.Input[str] endpoint: The IP address or domain name of Endpoint N in the endpoint group.
:param pulumi.Input[str] type: The type of Endpoint N in the endpoint group. Valid values: `Domain`: a custom domain name, `Ip`: a custom IP address, `PublicIp`: an Alibaba Cloud public IP address, `ECS`: an Alibaba Cloud Elastic Compute Service (ECS) instance, `SLB`: an Alibaba Cloud Server Load Balancer (SLB) instance.
:param pulumi.Input[int] weight: The weight of Endpoint N in the endpoint group. Valid value is 0 to 255.
:param pulumi.Input[bool] enable_clientip_preservation: Indicates whether client IP addresses are reserved. Valid values: `true`: Client IP addresses are reserved, `false`: Client IP addresses are not reserved. Default value is `false`.
"""
pulumi.set(__self__, "endpoint", endpoint)
pulumi.set(__self__, "type", type)
pulumi.set(__self__, "weight", weight)
if enable_clientip_preservation is not None:
pulumi.set(__self__, "enable_clientip_preservation", enable_clientip_preservation)
@property
@pulumi.getter
def endpoint(self) -> pulumi.Input[str]:
"""
The IP address or domain name of Endpoint N in the endpoint group.
"""
return pulumi.get(self, "endpoint")
@endpoint.setter
def endpoint(self, value: pulumi.Input[str]):
pulumi.set(self, "endpoint", value)
@property
@pulumi.getter
def type(self) -> pulumi.Input[str]:
"""
The type of Endpoint N in the endpoint group. Valid values: `Domain`: a custom domain name, `Ip`: a custom IP address, `PublicIp`: an Alibaba Cloud public IP address, `ECS`: an Alibaba Cloud Elastic Compute Service (ECS) instance, `SLB`: an Alibaba Cloud Server Load Balancer (SLB) instance.
"""
return pulumi.get(self, "type")
@type.setter
def type(self, value: pulumi.Input[str]):
pulumi.set(self, "type", value)
@property
@pulumi.getter
def weight(self) -> pulumi.Input[int]:
"""
The weight of Endpoint N in the endpoint group. Valid value is 0 to 255.
"""
return pulumi.get(self, "weight")
@weight.setter
def weight(self, value: pulumi.Input[int]):
pulumi.set(self, "weight", value)
@property
@pulumi.getter(name="enableClientipPreservation")
def enable_clientip_preservation(self) -> Optional[pulumi.Input[bool]]:
"""
Indicates whether client IP addresses are reserved. Valid values: `true`: Client IP addresses are reserved, `false`: Client IP addresses are not reserved. Default value is `false`.
"""
return pulumi.get(self, "enable_clientip_preservation")
@enable_clientip_preservation.setter
def enable_clientip_preservation(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "enable_clientip_preservation", value)
@pulumi.input_type
class EndpointGroupPortOverridesArgs:
def __init__(__self__, *,
endpoint_port: Optional[pulumi.Input[int]] = None,
listener_port: Optional[pulumi.Input[int]] = None):
"""
:param pulumi.Input[int] endpoint_port: Forwarding port.
:param pulumi.Input[int] listener_port: Listener port.
"""
if endpoint_port is not None:
pulumi.set(__self__, "endpoint_port", endpoint_port)
if listener_port is not None:
pulumi.set(__self__, "listener_port", listener_port)
@property
@pulumi.getter(name="endpointPort")
def endpoint_port(self) -> Optional[pulumi.Input[int]]:
"""
Forwarding port.
"""
return pulumi.get(self, "endpoint_port")
@endpoint_port.setter
def endpoint_port(self, value: Optional[pulumi.Input[int]]):
pulumi.set(self, "endpoint_port", value)
@property
@pulumi.getter(name="listenerPort")
def listener_port(self) -> Optional[pulumi.Input[int]]:
"""
Listener port.
"""
return pulumi.get(self, "listener_port")
@listener_port.setter
def listener_port(self, value: Optional[pulumi.Input[int]]):
pulumi.set(self, "listener_port", value)
@pulumi.input_type
class ForwardingRuleRuleActionArgs:
def __init__(__self__, *,
forward_group_config: pulumi.Input['ForwardingRuleRuleActionForwardGroupConfigArgs'],
order: pulumi.Input[int],
rule_action_type: pulumi.Input[str]):
"""
:param pulumi.Input['ForwardingRuleRuleActionForwardGroupConfigArgs'] forward_group_config: Forwarding configuration.
:param pulumi.Input[int] order: Forwarding priority.
:param pulumi.Input[str] rule_action_type: Forward action type. Default: forwardgroup.
"""
pulumi.set(__self__, "forward_group_config", forward_group_config)
pulumi.set(__self__, "order", order)
pulumi.set(__self__, "rule_action_type", rule_action_type)
@property
@pulumi.getter(name="forwardGroupConfig")
def forward_group_config(self) -> pulumi.Input['ForwardingRuleRuleActionForwardGroupConfigArgs']:
"""
Forwarding configuration.
"""
return pulumi.get(self, "forward_group_config")
@forward_group_config.setter
def forward_group_config(self, value: pulumi.Input['ForwardingRuleRuleActionForwardGroupConfigArgs']):
pulumi.set(self, "forward_group_config", value)
@property
@pulumi.getter
def order(self) -> pulumi.Input[int]:
"""
Forwarding priority.
"""
return pulumi.get(self, "order")
@order.setter
def order(self, value: pulumi.Input[int]):
pulumi.set(self, "order", value)
@property
@pulumi.getter(name="ruleActionType")
def rule_action_type(self) -> pulumi.Input[str]:
"""
Forward action type. Default: forwardgroup.
"""
return pulumi.get(self, "rule_action_type")
@rule_action_type.setter
def rule_action_type(self, value: pulumi.Input[str]):
pulumi.set(self, "rule_action_type", value)
@pulumi.input_type
class ForwardingRuleRuleActionForwardGroupConfigArgs:
def __init__(__self__, *,
server_group_tuples: pulumi.Input[Sequence[pulumi.Input['ForwardingRuleRuleActionForwardGroupConfigServerGroupTupleArgs']]]):
"""
:param pulumi.Input[Sequence[pulumi.Input['ForwardingRuleRuleActionForwardGroupConfigServerGroupTupleArgs']]] server_group_tuples: Terminal node group configuration.
"""
pulumi.set(__self__, "server_group_tuples", server_group_tuples)
@property
@pulumi.getter(name="serverGroupTuples")
def server_group_tuples(self) -> pulumi.Input[Sequence[pulumi.Input['ForwardingRuleRuleActionForwardGroupConfigServerGroupTupleArgs']]]:
"""
Terminal node group configuration.
"""
return pulumi.get(self, "server_group_tuples")
@server_group_tuples.setter
def server_group_tuples(self, value: pulumi.Input[Sequence[pulumi.Input['ForwardingRuleRuleActionForwardGroupConfigServerGroupTupleArgs']]]):
pulumi.set(self, "server_group_tuples", value)
@pulumi.input_type
class ForwardingRuleRuleActionForwardGroupConfigServerGroupTupleArgs:
def __init__(__self__, *,
endpoint_group_id: pulumi.Input[str]):
"""
:param pulumi.Input[str] endpoint_group_id: Terminal node group ID.
"""
pulumi.set(__self__, "endpoint_group_id", endpoint_group_id)
@property
@pulumi.getter(name="endpointGroupId")
def endpoint_group_id(self) -> pulumi.Input[str]:
"""
Terminal node group ID.
"""
return pulumi.get(self, "endpoint_group_id")
@endpoint_group_id.setter
def endpoint_group_id(self, value: pulumi.Input[str]):
pulumi.set(self, "endpoint_group_id", value)
@pulumi.input_type
class ForwardingRuleRuleConditionArgs:
def __init__(__self__, *,
rule_condition_type: pulumi.Input[str],
host_configs: Optional[pulumi.Input[Sequence[pulumi.Input['ForwardingRuleRuleConditionHostConfigArgs']]]] = None,
path_config: Optional[pulumi.Input['ForwardingRuleRuleConditionPathConfigArgs']] = None):
"""
:param pulumi.Input[str] rule_condition_type: Forwarding condition type. Valid value: `Host`, `Path`.
:param pulumi.Input[Sequence[pulumi.Input['ForwardingRuleRuleConditionHostConfigArgs']]] host_configs: Domain name configuration information.
:param pulumi.Input['ForwardingRuleRuleConditionPathConfigArgs'] path_config: Path configuration information.
"""
pulumi.set(__self__, "rule_condition_type", rule_condition_type)
if host_configs is not None:
pulumi.set(__self__, "host_configs", host_configs)
if path_config is not None:
pulumi.set(__self__, "path_config", path_config)
@property
@pulumi.getter(name="ruleConditionType")
def rule_condition_type(self) -> pulumi.Input[str]:
"""
Forwarding condition type. Valid value: `Host`, `Path`.
"""
return pulumi.get(self, "rule_condition_type")
@rule_condition_type.setter
def rule_condition_type(self, value: pulumi.Input[str]):
pulumi.set(self, "rule_condition_type", value)
@property
@pulumi.getter(name="hostConfigs")
def host_configs(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['ForwardingRuleRuleConditionHostConfigArgs']]]]:
"""
Domain name configuration information.
"""
return pulumi.get(self, "host_configs")
@host_configs.setter
def host_configs(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['ForwardingRuleRuleConditionHostConfigArgs']]]]):
pulumi.set(self, "host_configs", value)
@property
@pulumi.getter(name="pathConfig")
def path_config(self) -> Optional[pulumi.Input['ForwardingRuleRuleConditionPathConfigArgs']]:
"""
Path configuration information.
"""
return pulumi.get(self, "path_config")
@path_config.setter
def path_config(self, value: Optional[pulumi.Input['ForwardingRuleRuleConditionPathConfigArgs']]):
pulumi.set(self, "path_config", value)
@pulumi.input_type
class ForwardingRuleRuleConditionHostConfigArgs:
def __init__(__self__, *,
values: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None):
"""
:param pulumi.Input[Sequence[pulumi.Input[str]]] values: The domain name is 3-128 characters long, which can contain letters, numbers, dashes (-) and width period (.), and supports the use of asterisk (*) and width question mark (?) as wildcard characters.
"""
if values is not None:
pulumi.set(__self__, "values", values)
@property
@pulumi.getter
def values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
"""
The domain name is 3-128 characters long, which can contain letters, numbers, dashes (-) and width period (.), and supports the use of asterisk (*) and width question mark (?) as wildcard characters.
"""
return pulumi.get(self, "values")
@values.setter
def values(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]):
pulumi.set(self, "values", value)
@pulumi.input_type
class ForwardingRuleRuleConditionPathConfigArgs:
def __init__(__self__, *,
values: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None):
"""
:param pulumi.Input[Sequence[pulumi.Input[str]]] values: The domain name is 3-128 characters long, which can contain letters, numbers, dashes (-) and width period (.), and supports the use of asterisk (*) and width question mark (?) as wildcard characters.
"""
if values is not None:
pulumi.set(__self__, "values", values)
@property
@pulumi.getter
def values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
"""
The domain name is 3-128 characters long, which can contain letters, numbers, dashes (-) and width period (.), and supports the use of asterisk (*) and width question mark (?) as wildcard characters.
"""
return pulumi.get(self, "values")
@values.setter
def values(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]):
pulumi.set(self, "values", value)
@pulumi.input_type
class ListenerCertificateArgs:
def __init__(__self__, *,
id: Optional[pulumi.Input[str]] = None):
"""
:param pulumi.Input[str] id: The id of the certificate.
"""
if id is not None:
pulumi.set(__self__, "id", id)
@property
@pulumi.getter
def id(self) -> Optional[pulumi.Input[str]]:
"""
The id of the certificate.
"""
return pulumi.get(self, "id")
@id.setter
def id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "id", value)
@pulumi.input_type
class ListenerPortRangeArgs:
def __init__(__self__, *,
from_port: pulumi.Input[int],
to_port: pulumi.Input[int]):
"""
:param pulumi.Input[int] from_port: The initial listening port used to receive requests and forward them to terminal nodes.
:param pulumi.Input[int] to_port: The end listening port used to receive requests and forward them to terminal nodes.
"""
pulumi.set(__self__, "from_port", from_port)
pulumi.set(__self__, "to_port", to_port)
@property
@pulumi.getter(name="fromPort")
def from_port(self) -> pulumi.Input[int]:
"""
The initial listening port used to receive requests and forward them to terminal nodes.
"""
return pulumi.get(self, "from_port")
@from_port.setter
def from_port(self, value: pulumi.Input[int]):
pulumi.set(self, "from_port", value)
@property
@pulumi.getter(name="toPort")
def to_port(self) -> pulumi.Input[int]:
"""
The end listening port used to receive requests and forward them to terminal nodes.
"""
return pulumi.get(self, "to_port")
@to_port.setter
def to_port(self, value: pulumi.Input[int]):
pulumi.set(self, "to_port", value) | sdk/python/pulumi_alicloud/ga/_inputs.py |
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _utilities
__all__ = [
'EndpointGroupEndpointConfigurationArgs',
'EndpointGroupPortOverridesArgs',
'ForwardingRuleRuleActionArgs',
'ForwardingRuleRuleActionForwardGroupConfigArgs',
'ForwardingRuleRuleActionForwardGroupConfigServerGroupTupleArgs',
'ForwardingRuleRuleConditionArgs',
'ForwardingRuleRuleConditionHostConfigArgs',
'ForwardingRuleRuleConditionPathConfigArgs',
'ListenerCertificateArgs',
'ListenerPortRangeArgs',
]
@pulumi.input_type
class EndpointGroupEndpointConfigurationArgs:
def __init__(__self__, *,
endpoint: pulumi.Input[str],
type: pulumi.Input[str],
weight: pulumi.Input[int],
enable_clientip_preservation: Optional[pulumi.Input[bool]] = None):
"""
:param pulumi.Input[str] endpoint: The IP address or domain name of Endpoint N in the endpoint group.
:param pulumi.Input[str] type: The type of Endpoint N in the endpoint group. Valid values: `Domain`: a custom domain name, `Ip`: a custom IP address, `PublicIp`: an Alibaba Cloud public IP address, `ECS`: an Alibaba Cloud Elastic Compute Service (ECS) instance, `SLB`: an Alibaba Cloud Server Load Balancer (SLB) instance.
:param pulumi.Input[int] weight: The weight of Endpoint N in the endpoint group. Valid value is 0 to 255.
:param pulumi.Input[bool] enable_clientip_preservation: Indicates whether client IP addresses are reserved. Valid values: `true`: Client IP addresses are reserved, `false`: Client IP addresses are not reserved. Default value is `false`.
"""
pulumi.set(__self__, "endpoint", endpoint)
pulumi.set(__self__, "type", type)
pulumi.set(__self__, "weight", weight)
if enable_clientip_preservation is not None:
pulumi.set(__self__, "enable_clientip_preservation", enable_clientip_preservation)
@property
@pulumi.getter
def endpoint(self) -> pulumi.Input[str]:
"""
The IP address or domain name of Endpoint N in the endpoint group.
"""
return pulumi.get(self, "endpoint")
@endpoint.setter
def endpoint(self, value: pulumi.Input[str]):
pulumi.set(self, "endpoint", value)
@property
@pulumi.getter
def type(self) -> pulumi.Input[str]:
"""
The type of Endpoint N in the endpoint group. Valid values: `Domain`: a custom domain name, `Ip`: a custom IP address, `PublicIp`: an Alibaba Cloud public IP address, `ECS`: an Alibaba Cloud Elastic Compute Service (ECS) instance, `SLB`: an Alibaba Cloud Server Load Balancer (SLB) instance.
"""
return pulumi.get(self, "type")
@type.setter
def type(self, value: pulumi.Input[str]):
pulumi.set(self, "type", value)
@property
@pulumi.getter
def weight(self) -> pulumi.Input[int]:
"""
The weight of Endpoint N in the endpoint group. Valid value is 0 to 255.
"""
return pulumi.get(self, "weight")
@weight.setter
def weight(self, value: pulumi.Input[int]):
pulumi.set(self, "weight", value)
@property
@pulumi.getter(name="enableClientipPreservation")
def enable_clientip_preservation(self) -> Optional[pulumi.Input[bool]]:
"""
Indicates whether client IP addresses are reserved. Valid values: `true`: Client IP addresses are reserved, `false`: Client IP addresses are not reserved. Default value is `false`.
"""
return pulumi.get(self, "enable_clientip_preservation")
@enable_clientip_preservation.setter
def enable_clientip_preservation(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "enable_clientip_preservation", value)
@pulumi.input_type
class EndpointGroupPortOverridesArgs:
def __init__(__self__, *,
endpoint_port: Optional[pulumi.Input[int]] = None,
listener_port: Optional[pulumi.Input[int]] = None):
"""
:param pulumi.Input[int] endpoint_port: Forwarding port.
:param pulumi.Input[int] listener_port: Listener port.
"""
if endpoint_port is not None:
pulumi.set(__self__, "endpoint_port", endpoint_port)
if listener_port is not None:
pulumi.set(__self__, "listener_port", listener_port)
@property
@pulumi.getter(name="endpointPort")
def endpoint_port(self) -> Optional[pulumi.Input[int]]:
"""
Forwarding port.
"""
return pulumi.get(self, "endpoint_port")
@endpoint_port.setter
def endpoint_port(self, value: Optional[pulumi.Input[int]]):
pulumi.set(self, "endpoint_port", value)
@property
@pulumi.getter(name="listenerPort")
def listener_port(self) -> Optional[pulumi.Input[int]]:
"""
Listener port.
"""
return pulumi.get(self, "listener_port")
@listener_port.setter
def listener_port(self, value: Optional[pulumi.Input[int]]):
pulumi.set(self, "listener_port", value)
@pulumi.input_type
class ForwardingRuleRuleActionArgs:
def __init__(__self__, *,
forward_group_config: pulumi.Input['ForwardingRuleRuleActionForwardGroupConfigArgs'],
order: pulumi.Input[int],
rule_action_type: pulumi.Input[str]):
"""
:param pulumi.Input['ForwardingRuleRuleActionForwardGroupConfigArgs'] forward_group_config: Forwarding configuration.
:param pulumi.Input[int] order: Forwarding priority.
:param pulumi.Input[str] rule_action_type: Forward action type. Default: forwardgroup.
"""
pulumi.set(__self__, "forward_group_config", forward_group_config)
pulumi.set(__self__, "order", order)
pulumi.set(__self__, "rule_action_type", rule_action_type)
@property
@pulumi.getter(name="forwardGroupConfig")
def forward_group_config(self) -> pulumi.Input['ForwardingRuleRuleActionForwardGroupConfigArgs']:
"""
Forwarding configuration.
"""
return pulumi.get(self, "forward_group_config")
@forward_group_config.setter
def forward_group_config(self, value: pulumi.Input['ForwardingRuleRuleActionForwardGroupConfigArgs']):
pulumi.set(self, "forward_group_config", value)
@property
@pulumi.getter
def order(self) -> pulumi.Input[int]:
"""
Forwarding priority.
"""
return pulumi.get(self, "order")
@order.setter
def order(self, value: pulumi.Input[int]):
pulumi.set(self, "order", value)
@property
@pulumi.getter(name="ruleActionType")
def rule_action_type(self) -> pulumi.Input[str]:
"""
Forward action type. Default: forwardgroup.
"""
return pulumi.get(self, "rule_action_type")
@rule_action_type.setter
def rule_action_type(self, value: pulumi.Input[str]):
pulumi.set(self, "rule_action_type", value)
@pulumi.input_type
class ForwardingRuleRuleActionForwardGroupConfigArgs:
def __init__(__self__, *,
server_group_tuples: pulumi.Input[Sequence[pulumi.Input['ForwardingRuleRuleActionForwardGroupConfigServerGroupTupleArgs']]]):
"""
:param pulumi.Input[Sequence[pulumi.Input['ForwardingRuleRuleActionForwardGroupConfigServerGroupTupleArgs']]] server_group_tuples: Terminal node group configuration.
"""
pulumi.set(__self__, "server_group_tuples", server_group_tuples)
@property
@pulumi.getter(name="serverGroupTuples")
def server_group_tuples(self) -> pulumi.Input[Sequence[pulumi.Input['ForwardingRuleRuleActionForwardGroupConfigServerGroupTupleArgs']]]:
"""
Terminal node group configuration.
"""
return pulumi.get(self, "server_group_tuples")
@server_group_tuples.setter
def server_group_tuples(self, value: pulumi.Input[Sequence[pulumi.Input['ForwardingRuleRuleActionForwardGroupConfigServerGroupTupleArgs']]]):
pulumi.set(self, "server_group_tuples", value)
@pulumi.input_type
class ForwardingRuleRuleActionForwardGroupConfigServerGroupTupleArgs:
def __init__(__self__, *,
endpoint_group_id: pulumi.Input[str]):
"""
:param pulumi.Input[str] endpoint_group_id: Terminal node group ID.
"""
pulumi.set(__self__, "endpoint_group_id", endpoint_group_id)
@property
@pulumi.getter(name="endpointGroupId")
def endpoint_group_id(self) -> pulumi.Input[str]:
"""
Terminal node group ID.
"""
return pulumi.get(self, "endpoint_group_id")
@endpoint_group_id.setter
def endpoint_group_id(self, value: pulumi.Input[str]):
pulumi.set(self, "endpoint_group_id", value)
@pulumi.input_type
class ForwardingRuleRuleConditionArgs:
def __init__(__self__, *,
rule_condition_type: pulumi.Input[str],
host_configs: Optional[pulumi.Input[Sequence[pulumi.Input['ForwardingRuleRuleConditionHostConfigArgs']]]] = None,
path_config: Optional[pulumi.Input['ForwardingRuleRuleConditionPathConfigArgs']] = None):
"""
:param pulumi.Input[str] rule_condition_type: Forwarding condition type. Valid value: `Host`, `Path`.
:param pulumi.Input[Sequence[pulumi.Input['ForwardingRuleRuleConditionHostConfigArgs']]] host_configs: Domain name configuration information.
:param pulumi.Input['ForwardingRuleRuleConditionPathConfigArgs'] path_config: Path configuration information.
"""
pulumi.set(__self__, "rule_condition_type", rule_condition_type)
if host_configs is not None:
pulumi.set(__self__, "host_configs", host_configs)
if path_config is not None:
pulumi.set(__self__, "path_config", path_config)
@property
@pulumi.getter(name="ruleConditionType")
def rule_condition_type(self) -> pulumi.Input[str]:
"""
Forwarding condition type. Valid value: `Host`, `Path`.
"""
return pulumi.get(self, "rule_condition_type")
@rule_condition_type.setter
def rule_condition_type(self, value: pulumi.Input[str]):
pulumi.set(self, "rule_condition_type", value)
@property
@pulumi.getter(name="hostConfigs")
def host_configs(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['ForwardingRuleRuleConditionHostConfigArgs']]]]:
"""
Domain name configuration information.
"""
return pulumi.get(self, "host_configs")
@host_configs.setter
def host_configs(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['ForwardingRuleRuleConditionHostConfigArgs']]]]):
pulumi.set(self, "host_configs", value)
@property
@pulumi.getter(name="pathConfig")
def path_config(self) -> Optional[pulumi.Input['ForwardingRuleRuleConditionPathConfigArgs']]:
"""
Path configuration information.
"""
return pulumi.get(self, "path_config")
@path_config.setter
def path_config(self, value: Optional[pulumi.Input['ForwardingRuleRuleConditionPathConfigArgs']]):
pulumi.set(self, "path_config", value)
@pulumi.input_type
class ForwardingRuleRuleConditionHostConfigArgs:
def __init__(__self__, *,
values: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None):
"""
:param pulumi.Input[Sequence[pulumi.Input[str]]] values: The domain name is 3-128 characters long, which can contain letters, numbers, dashes (-) and width period (.), and supports the use of asterisk (*) and width question mark (?) as wildcard characters.
"""
if values is not None:
pulumi.set(__self__, "values", values)
@property
@pulumi.getter
def values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
"""
The domain name is 3-128 characters long, which can contain letters, numbers, dashes (-) and width period (.), and supports the use of asterisk (*) and width question mark (?) as wildcard characters.
"""
return pulumi.get(self, "values")
@values.setter
def values(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]):
pulumi.set(self, "values", value)
@pulumi.input_type
class ForwardingRuleRuleConditionPathConfigArgs:
def __init__(__self__, *,
values: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None):
"""
:param pulumi.Input[Sequence[pulumi.Input[str]]] values: The domain name is 3-128 characters long, which can contain letters, numbers, dashes (-) and width period (.), and supports the use of asterisk (*) and width question mark (?) as wildcard characters.
"""
if values is not None:
pulumi.set(__self__, "values", values)
@property
@pulumi.getter
def values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
"""
The domain name is 3-128 characters long, which can contain letters, numbers, dashes (-) and width period (.), and supports the use of asterisk (*) and width question mark (?) as wildcard characters.
"""
return pulumi.get(self, "values")
@values.setter
def values(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]):
pulumi.set(self, "values", value)
@pulumi.input_type
class ListenerCertificateArgs:
def __init__(__self__, *,
id: Optional[pulumi.Input[str]] = None):
"""
:param pulumi.Input[str] id: The id of the certificate.
"""
if id is not None:
pulumi.set(__self__, "id", id)
@property
@pulumi.getter
def id(self) -> Optional[pulumi.Input[str]]:
"""
The id of the certificate.
"""
return pulumi.get(self, "id")
@id.setter
def id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "id", value)
@pulumi.input_type
class ListenerPortRangeArgs:
def __init__(__self__, *,
from_port: pulumi.Input[int],
to_port: pulumi.Input[int]):
"""
:param pulumi.Input[int] from_port: The initial listening port used to receive requests and forward them to terminal nodes.
:param pulumi.Input[int] to_port: The end listening port used to receive requests and forward them to terminal nodes.
"""
pulumi.set(__self__, "from_port", from_port)
pulumi.set(__self__, "to_port", to_port)
@property
@pulumi.getter(name="fromPort")
def from_port(self) -> pulumi.Input[int]:
"""
The initial listening port used to receive requests and forward them to terminal nodes.
"""
return pulumi.get(self, "from_port")
@from_port.setter
def from_port(self, value: pulumi.Input[int]):
pulumi.set(self, "from_port", value)
@property
@pulumi.getter(name="toPort")
def to_port(self) -> pulumi.Input[int]:
"""
The end listening port used to receive requests and forward them to terminal nodes.
"""
return pulumi.get(self, "to_port")
@to_port.setter
def to_port(self, value: pulumi.Input[int]):
pulumi.set(self, "to_port", value) | 0.856453 | 0.080647 |
import webapp2
import jinja2
from google.appengine.ext import db
from google.appengine.api import users
from data.models import Monster, Profile, Vote, Product
import handlers.base
import configuration.site
import xml.etree.ElementTree as ET
from google.appengine.ext import blobstore
from google.appengine.ext.webapp import blobstore_handlers
import logging
class CreateHandler(handlers.base.LoggedInRequestHandler):
"""Creates a new product
Given the name of the product, create a new product with the current user as
the creator and a random access code."""
def get(self):
"""HTML GET handler.
Render a form that has all the data to make a product."""
template_values = self.build_template_values()
if not template_values[handlers.base.PROFILE_KEY]:
return self.forbidden()
elif not template_values[handlers.base.PROFILE_KEY].is_publisher:
return self.forbidden()
template = configuration.site.jinja_environment.get_template('product/create.html')
self.response.write(template.render(template_values))
def post(self):
"""HTML POST handler.
Check the query parameters for the name of the product, then make it."""
template_values = self.build_template_values()
if not template_values[handlers.base.PROFILE_KEY]:
return self.forbidden()
elif not template_values[handlers.base.PROFILE_KEY].is_publisher:
return self.forbidden()
name = self.request.get('name')
description = self.request.get('description')
link = self.request.get('link')
if (not name) or (not link) or (not description):
return self.forbidden()
product = Product()
product.creator = template_values[handlers.base.PROFILE_KEY]
product.name = name
product.link = link
product.description = description
product.generate_access_code()
product.put()
template_values[handlers.base.PROFILE_KEY].products.append(product.key().id())
template_values[handlers.base.PROFILE_KEY].put()
return self.redirect(self.uri_for('profile.edit'))
class ViewHandler(handlers.base.LoggedInRequestHandler):
"""Renders a single product view page.
Given the ID of a product to view, query for that prodict and display it
using the standard product template."""
def get(self, entity_id=None):
"""HTML GET handler.
Display the product with the specified ID"""
template_values = self.build_template_values()
if entity_id:
try:
product = Product.get_by_id(int(entity_id))
except ValueError:
return self.not_found()
if not product:
self.not_found()
return
template_values['product'] = product
else:
self.redirect(self.uri_for('product.home'))
return
template = configuration.site.jinja_environment.get_template('product/view.html')
self.response.write(template.render(template_values))
class UpdateHandler(handlers.base.LoggedInRequestHandler):
"""Updates the access code for a product.
Given the ID of a product to update, generate a new access code for it, then redirect to
the profile edit page."""
def get(self, entity_id=None):
"""HTML GET handler.
Update the product with the specified ID"""
template_values = self.build_template_values()
if entity_id:
try:
product = Product.get_by_id(int(entity_id))
except ValueError:
return self.not_found()
if not product:
self.not_found()
return
product.generate_access_code()
product.put()
else:
self.redirect(self.uri_for('product.home'))
return
return self.redirect(self.uri_for('profile.edit'))
class UploadHandler(handlers.base.LoggedInRequestHandler, blobstore_handlers.BlobstoreUploadHandler):
""""Uploads a file and parses it for monsters.
Templates used: upload.html"""
class CoreProduct(object):
name = "Core"
class FakeKey(object):
def id(self):
return -1
def key(self):
return self.FakeKey()
def get(self):
"""HTML GET handler.
Check the query parameters for the ID of the monster to be edited.
If found, display that monster for editing."""
template_values = self.build_template_values()
if not template_values[handlers.base.PROFILE_KEY].is_publisher:
return self.forbidden()
template_values['products'] = template_values[handlers.base.PROFILE_KEY].get_published_products()
template_values['upload_url'] = blobstore.create_upload_url(self.uri_for('product.upload'))
if users.is_current_user_admin():
template_values['products'].append(self.CoreProduct())
template = configuration.site.jinja_environment.get_template('product/upload.html')
self.response.write(template.render(template_values))
def post(self):
"""HTML POST handler.
Parse ALL THE MONSTERS."""
template_values = self.build_template_values()
if not template_values[handlers.base.PROFILE_KEY].is_publisher:
return self.forbidden()
upload_files = self.get_uploads('file_upload')
blob_info = upload_files[0]
blob_key = blob_info.key()
blob_reader = blobstore.BlobReader(blob_key)
root = ET.parse(blob_reader)
product = int(self.request.get('product'))
for upload_monster in root.iter('monster'):
monster = Monster()
if product == -1:
monster.is_core = True
else:
monster.product = product
monster.creator = template_values[handlers.base.PROFILE_KEY]
monster.name = upload_monster.findtext('name')
monster.description = upload_monster.findtext('description')
monster.instinct = upload_monster.findtext('instinct')
tags = upload_monster.find('tags')
if tags and len(tags):
for tag in tags:
monster.tags.append(tag.text.encode('utf-8'))
monster.damage = upload_monster.findtext('damage')
monster.hp = upload_monster.findtext('hp')
monster.armor = upload_monster.findtext('armor')
damage_tags = upload_monster.find('damage_tags')
if damage_tags and len(damage_tags):
for tag in damage_tags:
monster.damage_tags.append(tag.text)
special_qualities = upload_monster.find('special_qualities')
if special_qualities and len(special_qualities):
for special_quality in special_qualities:
monster.special_qualities.append(special_quality.text)
for move in upload_monster.find('moves'):
monster.moves.append(move.text)
try:
monster.put()
except:
print monster
raise
if product == -1:
return self.redirect(self.uri_for('home'))
self.redirect(self.uri_for('product', entity_id=product)) | handlers/product.py | import webapp2
import jinja2
from google.appengine.ext import db
from google.appengine.api import users
from data.models import Monster, Profile, Vote, Product
import handlers.base
import configuration.site
import xml.etree.ElementTree as ET
from google.appengine.ext import blobstore
from google.appengine.ext.webapp import blobstore_handlers
import logging
class CreateHandler(handlers.base.LoggedInRequestHandler):
"""Creates a new product
Given the name of the product, create a new product with the current user as
the creator and a random access code."""
def get(self):
"""HTML GET handler.
Render a form that has all the data to make a product."""
template_values = self.build_template_values()
if not template_values[handlers.base.PROFILE_KEY]:
return self.forbidden()
elif not template_values[handlers.base.PROFILE_KEY].is_publisher:
return self.forbidden()
template = configuration.site.jinja_environment.get_template('product/create.html')
self.response.write(template.render(template_values))
def post(self):
"""HTML POST handler.
Check the query parameters for the name of the product, then make it."""
template_values = self.build_template_values()
if not template_values[handlers.base.PROFILE_KEY]:
return self.forbidden()
elif not template_values[handlers.base.PROFILE_KEY].is_publisher:
return self.forbidden()
name = self.request.get('name')
description = self.request.get('description')
link = self.request.get('link')
if (not name) or (not link) or (not description):
return self.forbidden()
product = Product()
product.creator = template_values[handlers.base.PROFILE_KEY]
product.name = name
product.link = link
product.description = description
product.generate_access_code()
product.put()
template_values[handlers.base.PROFILE_KEY].products.append(product.key().id())
template_values[handlers.base.PROFILE_KEY].put()
return self.redirect(self.uri_for('profile.edit'))
class ViewHandler(handlers.base.LoggedInRequestHandler):
"""Renders a single product view page.
Given the ID of a product to view, query for that prodict and display it
using the standard product template."""
def get(self, entity_id=None):
"""HTML GET handler.
Display the product with the specified ID"""
template_values = self.build_template_values()
if entity_id:
try:
product = Product.get_by_id(int(entity_id))
except ValueError:
return self.not_found()
if not product:
self.not_found()
return
template_values['product'] = product
else:
self.redirect(self.uri_for('product.home'))
return
template = configuration.site.jinja_environment.get_template('product/view.html')
self.response.write(template.render(template_values))
class UpdateHandler(handlers.base.LoggedInRequestHandler):
"""Updates the access code for a product.
Given the ID of a product to update, generate a new access code for it, then redirect to
the profile edit page."""
def get(self, entity_id=None):
"""HTML GET handler.
Update the product with the specified ID"""
template_values = self.build_template_values()
if entity_id:
try:
product = Product.get_by_id(int(entity_id))
except ValueError:
return self.not_found()
if not product:
self.not_found()
return
product.generate_access_code()
product.put()
else:
self.redirect(self.uri_for('product.home'))
return
return self.redirect(self.uri_for('profile.edit'))
class UploadHandler(handlers.base.LoggedInRequestHandler, blobstore_handlers.BlobstoreUploadHandler):
""""Uploads a file and parses it for monsters.
Templates used: upload.html"""
class CoreProduct(object):
name = "Core"
class FakeKey(object):
def id(self):
return -1
def key(self):
return self.FakeKey()
def get(self):
"""HTML GET handler.
Check the query parameters for the ID of the monster to be edited.
If found, display that monster for editing."""
template_values = self.build_template_values()
if not template_values[handlers.base.PROFILE_KEY].is_publisher:
return self.forbidden()
template_values['products'] = template_values[handlers.base.PROFILE_KEY].get_published_products()
template_values['upload_url'] = blobstore.create_upload_url(self.uri_for('product.upload'))
if users.is_current_user_admin():
template_values['products'].append(self.CoreProduct())
template = configuration.site.jinja_environment.get_template('product/upload.html')
self.response.write(template.render(template_values))
def post(self):
"""HTML POST handler.
Parse ALL THE MONSTERS."""
template_values = self.build_template_values()
if not template_values[handlers.base.PROFILE_KEY].is_publisher:
return self.forbidden()
upload_files = self.get_uploads('file_upload')
blob_info = upload_files[0]
blob_key = blob_info.key()
blob_reader = blobstore.BlobReader(blob_key)
root = ET.parse(blob_reader)
product = int(self.request.get('product'))
for upload_monster in root.iter('monster'):
monster = Monster()
if product == -1:
monster.is_core = True
else:
monster.product = product
monster.creator = template_values[handlers.base.PROFILE_KEY]
monster.name = upload_monster.findtext('name')
monster.description = upload_monster.findtext('description')
monster.instinct = upload_monster.findtext('instinct')
tags = upload_monster.find('tags')
if tags and len(tags):
for tag in tags:
monster.tags.append(tag.text.encode('utf-8'))
monster.damage = upload_monster.findtext('damage')
monster.hp = upload_monster.findtext('hp')
monster.armor = upload_monster.findtext('armor')
damage_tags = upload_monster.find('damage_tags')
if damage_tags and len(damage_tags):
for tag in damage_tags:
monster.damage_tags.append(tag.text)
special_qualities = upload_monster.find('special_qualities')
if special_qualities and len(special_qualities):
for special_quality in special_qualities:
monster.special_qualities.append(special_quality.text)
for move in upload_monster.find('moves'):
monster.moves.append(move.text)
try:
monster.put()
except:
print monster
raise
if product == -1:
return self.redirect(self.uri_for('home'))
self.redirect(self.uri_for('product', entity_id=product)) | 0.403097 | 0.119974 |
import logging
import os
import subprocess
from patroni.exceptions import PostgresException
from patroni.utils import polling_loop
from six import string_types
from threading import Lock
logger = logging.getLogger(__name__)
class CancellableSubprocess(object):
def __init__(self):
self._is_cancelled = False
self._process = None
self._lock = Lock()
def call(self, *args, **kwargs):
for s in ('stdin', 'stdout', 'stderr'):
kwargs.pop(s, None)
communicate_input = 'communicate_input' in kwargs
if communicate_input:
input_data = kwargs.pop('communicate_input', None)
if not isinstance(input_data, string_types):
input_data = ''
if input_data and input_data[-1] != '\n':
input_data += '\n'
kwargs['stdin'] = subprocess.PIPE
kwargs['stdout'] = open(os.devnull, 'w')
kwargs['stderr'] = subprocess.STDOUT
try:
with self._lock:
if self._is_cancelled:
raise PostgresException('cancelled')
self._is_cancelled = False
self._process = subprocess.Popen(*args, **kwargs)
if communicate_input:
if input_data:
self._process.communicate(input_data)
self._process.stdin.close()
return self._process.wait()
finally:
with self._lock:
self._process = None
def reset_is_cancelled(self):
with self._lock:
self._is_cancelled = False
@property
def is_cancelled(self):
with self._lock:
return self._is_cancelled
def cancel(self):
with self._lock:
self._is_cancelled = True
if self._process is None or self._process.returncode is not None:
return
self._process.terminate()
for _ in polling_loop(10):
with self._lock:
if self._process is None or self._process.returncode is not None:
return
with self._lock:
if self._process is not None and self._process.returncode is None:
self._process.kill() | patroni/postgresql/cancellable.py | import logging
import os
import subprocess
from patroni.exceptions import PostgresException
from patroni.utils import polling_loop
from six import string_types
from threading import Lock
logger = logging.getLogger(__name__)
class CancellableSubprocess(object):
def __init__(self):
self._is_cancelled = False
self._process = None
self._lock = Lock()
def call(self, *args, **kwargs):
for s in ('stdin', 'stdout', 'stderr'):
kwargs.pop(s, None)
communicate_input = 'communicate_input' in kwargs
if communicate_input:
input_data = kwargs.pop('communicate_input', None)
if not isinstance(input_data, string_types):
input_data = ''
if input_data and input_data[-1] != '\n':
input_data += '\n'
kwargs['stdin'] = subprocess.PIPE
kwargs['stdout'] = open(os.devnull, 'w')
kwargs['stderr'] = subprocess.STDOUT
try:
with self._lock:
if self._is_cancelled:
raise PostgresException('cancelled')
self._is_cancelled = False
self._process = subprocess.Popen(*args, **kwargs)
if communicate_input:
if input_data:
self._process.communicate(input_data)
self._process.stdin.close()
return self._process.wait()
finally:
with self._lock:
self._process = None
def reset_is_cancelled(self):
with self._lock:
self._is_cancelled = False
@property
def is_cancelled(self):
with self._lock:
return self._is_cancelled
def cancel(self):
with self._lock:
self._is_cancelled = True
if self._process is None or self._process.returncode is not None:
return
self._process.terminate()
for _ in polling_loop(10):
with self._lock:
if self._process is None or self._process.returncode is not None:
return
with self._lock:
if self._process is not None and self._process.returncode is None:
self._process.kill() | 0.350755 | 0.04653 |
import struct
from typing import ClassVar, Optional
import attr
import marshmallow
from marshmallow import post_load
from elgas.parameters.enumerations import ParameterObjectType
from elgas.utils import pop_many, pretty_text
@attr.s(auto_attribs=True)
class ErrorCounter:
object_type: ClassVar[ParameterObjectType] = ParameterObjectType.ERROR_COUNTER
value_length: ClassVar[int] = 4
number: int
id: int
address_in_actual_values: int
address_in_data_archive_record: int
bit_control: int
in_data_archive: bool
in_daily_archive: bool
in_monthly_archive: bool
in_factory_archive: bool
is_metrological_quantity: bool
name: str
unit: str
digit: float
number_of_primary_counter: int
address_in_daily_archive_record: int
address_in_monthly_archive_record: int
address_in_billing_archive_record: int
decimals: Optional[int]
@classmethod
def from_bytes(cls, in_data: bytes):
data = bytearray(in_data)
number = int.from_bytes(pop_many(data, 2), "little")
id = int.from_bytes(pop_many(data, 2), "little")
address_in_actual_values = int.from_bytes(pop_many(data, 2), "little")
address_in_data_archive_record = int.from_bytes(pop_many(data, 2), "little")
bit_control = data.pop(0)
in_data_archive = bool(bit_control & 0b00000001)
in_daily_archive = bool(bit_control & 0b00000010)
in_monthly_archive = bool(bit_control & 0b00000100)
in_factory_archive = bool(bit_control & 0b00001000)
is_metrological_quantity = bool(bit_control & 0b00010000)
name = pretty_text(pop_many(data, 23))
unit = pretty_text(pop_many(data, 8))
digit = struct.unpack("<d", pop_many(data, 8))[0]
number_of_primary_counter = data.pop(0)
address_in_daily_archive_record = int.from_bytes(pop_many(data, 2), "little")
address_in_monthly_archive_record = int.from_bytes(pop_many(data, 2), "little")
address_in_billing_archive_record = int.from_bytes(pop_many(data, 2), "little")
if data:
decimals = data.pop(0)
else:
decimals = None
return cls(
number=number,
id=id,
address_in_actual_values=address_in_actual_values,
address_in_data_archive_record=address_in_data_archive_record,
bit_control=bit_control,
in_data_archive=in_data_archive,
in_daily_archive=in_daily_archive,
in_monthly_archive=in_monthly_archive,
in_factory_archive=in_factory_archive,
is_metrological_quantity=is_metrological_quantity,
name=name,
unit=unit,
digit=digit,
number_of_primary_counter=number_of_primary_counter,
address_in_daily_archive_record=address_in_daily_archive_record,
address_in_monthly_archive_record=address_in_monthly_archive_record,
address_in_billing_archive_record=address_in_billing_archive_record,
decimals=decimals,
)
class DoubleErrorCounter(ErrorCounter):
object_type: ClassVar[
ParameterObjectType
] = ParameterObjectType.DOUBLE_ERROR_COUNTER
value_length: ClassVar[int] = 8
class CorrectionCounter(ErrorCounter):
object_type: ClassVar[ParameterObjectType] = ParameterObjectType.CORRECTION_COUNTER
value_length: ClassVar[int] = 4
class ErrorCounterSchema(marshmallow.Schema):
number = marshmallow.fields.Integer(required=True)
id = marshmallow.fields.Integer(required=True)
address_in_actual_values = marshmallow.fields.Integer(required=True)
address_in_data_archive_record = marshmallow.fields.Integer(required=True)
bit_control = marshmallow.fields.Integer(required=True)
in_data_archive = marshmallow.fields.Boolean(required=True)
in_daily_archive = marshmallow.fields.Boolean(required=True)
in_monthly_archive = marshmallow.fields.Boolean(required=True)
in_factory_archive = marshmallow.fields.Boolean(required=True)
is_metrological_quantity = marshmallow.fields.Boolean(required=True)
name = marshmallow.fields.String(required=True)
unit = marshmallow.fields.String(required=True)
digit = marshmallow.fields.Float(required=True, as_string=True)
number_of_primary_counter = marshmallow.fields.Integer(required=True)
address_in_daily_archive_record = marshmallow.fields.Integer(required=True)
address_in_monthly_archive_record = marshmallow.fields.Integer(required=True)
address_in_billing_archive_record = marshmallow.fields.Integer(required=True)
decimals = marshmallow.fields.Integer(required=True, allow_none=True)
@post_load
def make_object(self, data, **kwargs):
return ErrorCounter(**data)
class DoubleErrorCounterSchema(ErrorCounterSchema):
@post_load
def make_object(self, data, **kwargs):
return DoubleErrorCounter(**data)
class CorrectionCounterSchema(ErrorCounterSchema):
@post_load
def make_object(self, data, **kwargs):
return CorrectionCounter(**data) | elgas/parameters/error_counter.py | import struct
from typing import ClassVar, Optional
import attr
import marshmallow
from marshmallow import post_load
from elgas.parameters.enumerations import ParameterObjectType
from elgas.utils import pop_many, pretty_text
@attr.s(auto_attribs=True)
class ErrorCounter:
object_type: ClassVar[ParameterObjectType] = ParameterObjectType.ERROR_COUNTER
value_length: ClassVar[int] = 4
number: int
id: int
address_in_actual_values: int
address_in_data_archive_record: int
bit_control: int
in_data_archive: bool
in_daily_archive: bool
in_monthly_archive: bool
in_factory_archive: bool
is_metrological_quantity: bool
name: str
unit: str
digit: float
number_of_primary_counter: int
address_in_daily_archive_record: int
address_in_monthly_archive_record: int
address_in_billing_archive_record: int
decimals: Optional[int]
@classmethod
def from_bytes(cls, in_data: bytes):
data = bytearray(in_data)
number = int.from_bytes(pop_many(data, 2), "little")
id = int.from_bytes(pop_many(data, 2), "little")
address_in_actual_values = int.from_bytes(pop_many(data, 2), "little")
address_in_data_archive_record = int.from_bytes(pop_many(data, 2), "little")
bit_control = data.pop(0)
in_data_archive = bool(bit_control & 0b00000001)
in_daily_archive = bool(bit_control & 0b00000010)
in_monthly_archive = bool(bit_control & 0b00000100)
in_factory_archive = bool(bit_control & 0b00001000)
is_metrological_quantity = bool(bit_control & 0b00010000)
name = pretty_text(pop_many(data, 23))
unit = pretty_text(pop_many(data, 8))
digit = struct.unpack("<d", pop_many(data, 8))[0]
number_of_primary_counter = data.pop(0)
address_in_daily_archive_record = int.from_bytes(pop_many(data, 2), "little")
address_in_monthly_archive_record = int.from_bytes(pop_many(data, 2), "little")
address_in_billing_archive_record = int.from_bytes(pop_many(data, 2), "little")
if data:
decimals = data.pop(0)
else:
decimals = None
return cls(
number=number,
id=id,
address_in_actual_values=address_in_actual_values,
address_in_data_archive_record=address_in_data_archive_record,
bit_control=bit_control,
in_data_archive=in_data_archive,
in_daily_archive=in_daily_archive,
in_monthly_archive=in_monthly_archive,
in_factory_archive=in_factory_archive,
is_metrological_quantity=is_metrological_quantity,
name=name,
unit=unit,
digit=digit,
number_of_primary_counter=number_of_primary_counter,
address_in_daily_archive_record=address_in_daily_archive_record,
address_in_monthly_archive_record=address_in_monthly_archive_record,
address_in_billing_archive_record=address_in_billing_archive_record,
decimals=decimals,
)
class DoubleErrorCounter(ErrorCounter):
object_type: ClassVar[
ParameterObjectType
] = ParameterObjectType.DOUBLE_ERROR_COUNTER
value_length: ClassVar[int] = 8
class CorrectionCounter(ErrorCounter):
object_type: ClassVar[ParameterObjectType] = ParameterObjectType.CORRECTION_COUNTER
value_length: ClassVar[int] = 4
class ErrorCounterSchema(marshmallow.Schema):
number = marshmallow.fields.Integer(required=True)
id = marshmallow.fields.Integer(required=True)
address_in_actual_values = marshmallow.fields.Integer(required=True)
address_in_data_archive_record = marshmallow.fields.Integer(required=True)
bit_control = marshmallow.fields.Integer(required=True)
in_data_archive = marshmallow.fields.Boolean(required=True)
in_daily_archive = marshmallow.fields.Boolean(required=True)
in_monthly_archive = marshmallow.fields.Boolean(required=True)
in_factory_archive = marshmallow.fields.Boolean(required=True)
is_metrological_quantity = marshmallow.fields.Boolean(required=True)
name = marshmallow.fields.String(required=True)
unit = marshmallow.fields.String(required=True)
digit = marshmallow.fields.Float(required=True, as_string=True)
number_of_primary_counter = marshmallow.fields.Integer(required=True)
address_in_daily_archive_record = marshmallow.fields.Integer(required=True)
address_in_monthly_archive_record = marshmallow.fields.Integer(required=True)
address_in_billing_archive_record = marshmallow.fields.Integer(required=True)
decimals = marshmallow.fields.Integer(required=True, allow_none=True)
@post_load
def make_object(self, data, **kwargs):
return ErrorCounter(**data)
class DoubleErrorCounterSchema(ErrorCounterSchema):
@post_load
def make_object(self, data, **kwargs):
return DoubleErrorCounter(**data)
class CorrectionCounterSchema(ErrorCounterSchema):
@post_load
def make_object(self, data, **kwargs):
return CorrectionCounter(**data) | 0.821295 | 0.33012 |
from mock import Mock, patch
@patch('cvm.services.VRouterPortService._port_needs_an_update', Mock(return_value=True))
def test_create_port(vrouter_port_service, database, vrouter_api_client, vmi_model):
database.ports_to_update.append(vmi_model)
vrouter_port_service.sync_ports()
vrouter_api_client.delete_port.assert_not_called()
vrouter_api_client.add_port.assert_called_once_with(vmi_model)
vrouter_api_client.enable_port.assert_called_once_with(vmi_model.uuid)
@patch('cvm.services.VRouterPortService._port_needs_an_update', Mock(return_value=False))
def test_no_update(vrouter_port_service, database, vrouter_api_client, vmi_model):
vrouter_api_client.read_port.return_value = {'dummy': 'dummy-value'}
database.ports_to_update.append(vmi_model)
vrouter_port_service.sync_ports()
vrouter_api_client.delete_port.assert_not_called()
vrouter_api_client.add_port.assert_not_called()
assert database.ports_to_update == []
def test_delete_port(vrouter_port_service, database, vrouter_api_client):
database.ports_to_delete.append('port-uuid')
vrouter_port_service.sync_ports()
vrouter_api_client.delete_port.assert_called_once_with('port-uuid')
@patch('cvm.services.VRouterPortService._port_needs_an_update', Mock(return_value=False))
def test_enable_port(vrouter_port_service, database, vrouter_api_client, vmi_model):
vmi_model.vm_model.update_power_state = True
database.ports_to_update.append(vmi_model)
vrouter_port_service.sync_ports()
vrouter_api_client.enable_port.assert_called_once_with(vmi_model.uuid)
vrouter_api_client.disable_port.assert_not_called()
@patch('cvm.services.VRouterPortService._port_needs_an_update', Mock(return_value=False))
def test_disable_port(vrouter_port_service, database, vrouter_api_client, vmi_model):
vmi_model.vm_model.update_power_state = False
database.ports_to_update.append(vmi_model)
vrouter_port_service.sync_ports()
vrouter_api_client.enable_port.assert_called_once_with(vmi_model.uuid)
vrouter_api_client.disable_port.assert_not_called() | tests/unit/services/test_vrouter_port_service.py | from mock import Mock, patch
@patch('cvm.services.VRouterPortService._port_needs_an_update', Mock(return_value=True))
def test_create_port(vrouter_port_service, database, vrouter_api_client, vmi_model):
database.ports_to_update.append(vmi_model)
vrouter_port_service.sync_ports()
vrouter_api_client.delete_port.assert_not_called()
vrouter_api_client.add_port.assert_called_once_with(vmi_model)
vrouter_api_client.enable_port.assert_called_once_with(vmi_model.uuid)
@patch('cvm.services.VRouterPortService._port_needs_an_update', Mock(return_value=False))
def test_no_update(vrouter_port_service, database, vrouter_api_client, vmi_model):
vrouter_api_client.read_port.return_value = {'dummy': 'dummy-value'}
database.ports_to_update.append(vmi_model)
vrouter_port_service.sync_ports()
vrouter_api_client.delete_port.assert_not_called()
vrouter_api_client.add_port.assert_not_called()
assert database.ports_to_update == []
def test_delete_port(vrouter_port_service, database, vrouter_api_client):
database.ports_to_delete.append('port-uuid')
vrouter_port_service.sync_ports()
vrouter_api_client.delete_port.assert_called_once_with('port-uuid')
@patch('cvm.services.VRouterPortService._port_needs_an_update', Mock(return_value=False))
def test_enable_port(vrouter_port_service, database, vrouter_api_client, vmi_model):
vmi_model.vm_model.update_power_state = True
database.ports_to_update.append(vmi_model)
vrouter_port_service.sync_ports()
vrouter_api_client.enable_port.assert_called_once_with(vmi_model.uuid)
vrouter_api_client.disable_port.assert_not_called()
@patch('cvm.services.VRouterPortService._port_needs_an_update', Mock(return_value=False))
def test_disable_port(vrouter_port_service, database, vrouter_api_client, vmi_model):
vmi_model.vm_model.update_power_state = False
database.ports_to_update.append(vmi_model)
vrouter_port_service.sync_ports()
vrouter_api_client.enable_port.assert_called_once_with(vmi_model.uuid)
vrouter_api_client.disable_port.assert_not_called() | 0.690455 | 0.150465 |
import sqlite3
import os
import re
import json
def all_files(d: str, ignore=None):
rv = list()
offset = len(os.path.dirname(d))
for root, subdirs, files in os.walk(d):
root = root[offset:]
root = root.lstrip('/')
files = [f'{root}/{f}' for f in files]
if ignore:
files = [f for f in files if not ignore.match(f)]
rv.extend(files)
return rv
def clean_db(db_path):
if os.path.exists(db_path):
os.remove(db_path)
with sqlite3.connect(db_path) as conn:
cursor = conn.cursor()
cursor.execute('CREATE TABLE Resources (ID INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT, Path TEXT NOT NULL UNIQUE, Data BLOB, MetaData TEXT);')
def pack_assets(db_path):
ase_json_undo = re.compile('.*\\.aseprite|.*~|.*\\.json')
asset_paths = all_files('assets', ignore = ase_json_undo)
with sqlite3.connect(db_path) as conn:
cursor = conn.cursor()
cmd = 'INSERT INTO Resources (Path,Data,MetaData) VALUES (?,?,?);'
cmd_nometa = 'INSERT INTO Resources (Path,Data) VALUES (?,?);'
for asset_path in asset_paths:
meta_path = asset_path+'.json'
meta = None
if os.path.exists(meta_path):
with open(meta_path, 'r') as f:
meta_json = json.load(f)
meta = json.dumps(meta_json, separators=(',',':'), indent=None)
with open(asset_path, 'rb') as f:
asset = f.read()
if meta:
cursor.execute(cmd, (asset_path,asset, meta))
print(f'Packed asset "{asset_path}" with its meta data.')
else:
cursor.execute(cmd_nometa, (asset_path,asset))
print(f'Packed asset "{asset_path}".')
def pack_rooms(db_path):
not_json = re.compile('.*(?<!.json)$')
room_paths = all_files('assets/rooms', ignore=not_json)
with sqlite3.connect(db_path) as conn:
cursor = conn.cursor()
cmd = 'INSERT INTO Resources (Path,MetaData) VALUES (?,?);'
for room_path in room_paths:
room_path = f'assets/{room_path}'
with open(room_path, 'r') as f:
room = f.read()
cursor.execute(cmd, (room_path, room))
print(f'Packed room "{room_path}".')
def pack_shaders(db_path):
undo = re.compile('.*~')
shader_paths = all_files('shaders', ignore=undo)
with sqlite3.connect(db_path) as conn:
cursor = conn.cursor()
cmd = 'INSERT INTO Resources (Path,Data) VALUES (?,?);'
for shader_path in shader_paths:
with open(shader_path, 'rb') as f:
shader = f.read()
cursor.execute(cmd, (shader_path,shader))
print(f'Packed shader "{shader_path}".')
if __name__ == '__main__':
db_path = 'geas_files.db'
clean_db(db_path)
pack_assets(db_path)
pack_rooms(db_path)
pack_shaders(db_path) | scripts/pack.py | import sqlite3
import os
import re
import json
def all_files(d: str, ignore=None):
rv = list()
offset = len(os.path.dirname(d))
for root, subdirs, files in os.walk(d):
root = root[offset:]
root = root.lstrip('/')
files = [f'{root}/{f}' for f in files]
if ignore:
files = [f for f in files if not ignore.match(f)]
rv.extend(files)
return rv
def clean_db(db_path):
if os.path.exists(db_path):
os.remove(db_path)
with sqlite3.connect(db_path) as conn:
cursor = conn.cursor()
cursor.execute('CREATE TABLE Resources (ID INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT, Path TEXT NOT NULL UNIQUE, Data BLOB, MetaData TEXT);')
def pack_assets(db_path):
ase_json_undo = re.compile('.*\\.aseprite|.*~|.*\\.json')
asset_paths = all_files('assets', ignore = ase_json_undo)
with sqlite3.connect(db_path) as conn:
cursor = conn.cursor()
cmd = 'INSERT INTO Resources (Path,Data,MetaData) VALUES (?,?,?);'
cmd_nometa = 'INSERT INTO Resources (Path,Data) VALUES (?,?);'
for asset_path in asset_paths:
meta_path = asset_path+'.json'
meta = None
if os.path.exists(meta_path):
with open(meta_path, 'r') as f:
meta_json = json.load(f)
meta = json.dumps(meta_json, separators=(',',':'), indent=None)
with open(asset_path, 'rb') as f:
asset = f.read()
if meta:
cursor.execute(cmd, (asset_path,asset, meta))
print(f'Packed asset "{asset_path}" with its meta data.')
else:
cursor.execute(cmd_nometa, (asset_path,asset))
print(f'Packed asset "{asset_path}".')
def pack_rooms(db_path):
not_json = re.compile('.*(?<!.json)$')
room_paths = all_files('assets/rooms', ignore=not_json)
with sqlite3.connect(db_path) as conn:
cursor = conn.cursor()
cmd = 'INSERT INTO Resources (Path,MetaData) VALUES (?,?);'
for room_path in room_paths:
room_path = f'assets/{room_path}'
with open(room_path, 'r') as f:
room = f.read()
cursor.execute(cmd, (room_path, room))
print(f'Packed room "{room_path}".')
def pack_shaders(db_path):
undo = re.compile('.*~')
shader_paths = all_files('shaders', ignore=undo)
with sqlite3.connect(db_path) as conn:
cursor = conn.cursor()
cmd = 'INSERT INTO Resources (Path,Data) VALUES (?,?);'
for shader_path in shader_paths:
with open(shader_path, 'rb') as f:
shader = f.read()
cursor.execute(cmd, (shader_path,shader))
print(f'Packed shader "{shader_path}".')
if __name__ == '__main__':
db_path = 'geas_files.db'
clean_db(db_path)
pack_assets(db_path)
pack_rooms(db_path)
pack_shaders(db_path) | 0.202917 | 0.084531 |
import json
import requests
import six
from six.moves import urllib
from firebase_admin import _auth_utils
from firebase_admin import _user_import
MAX_LIST_USERS_RESULTS = 1000
MAX_IMPORT_USERS_SIZE = 1000
class Sentinel(object):
def __init__(self, description):
self.description = description
DELETE_ATTRIBUTE = Sentinel('Value used to delete an attribute from a user profile')
class UserMetadata(object):
"""Contains additional metadata associated with a user account."""
def __init__(self, creation_timestamp=None, last_sign_in_timestamp=None):
self._creation_timestamp = _auth_utils.validate_timestamp(
creation_timestamp, 'creation_timestamp')
self._last_sign_in_timestamp = _auth_utils.validate_timestamp(
last_sign_in_timestamp, 'last_sign_in_timestamp')
@property
def creation_timestamp(self):
""" Creation timestamp in milliseconds since the epoch.
Returns:
integer: The user creation timestamp in milliseconds since the epoch.
"""
return self._creation_timestamp
@property
def last_sign_in_timestamp(self):
""" Last sign in timestamp in milliseconds since the epoch.
Returns:
integer: The last sign in timestamp in milliseconds since the epoch.
"""
return self._last_sign_in_timestamp
class UserInfo(object):
"""A collection of standard profile information for a user.
Used to expose profile information returned by an identity provider.
"""
@property
def uid(self):
"""Returns the user ID of this user."""
raise NotImplementedError
@property
def display_name(self):
"""Returns the display name of this user."""
raise NotImplementedError
@property
def email(self):
"""Returns the email address associated with this user."""
raise NotImplementedError
@property
def phone_number(self):
"""Returns the phone number associated with this user."""
raise NotImplementedError
@property
def photo_url(self):
"""Returns the photo URL of this user."""
raise NotImplementedError
@property
def provider_id(self):
"""Returns the ID of the identity provider.
This can be a short domain name (e.g. google.com), or the identity of an OpenID
identity provider.
"""
raise NotImplementedError
class UserRecord(UserInfo):
"""Contains metadata associated with a Firebase user account."""
def __init__(self, data):
super(UserRecord, self).__init__()
if not isinstance(data, dict):
raise ValueError('Invalid data argument: {0}. Must be a dictionary.'.format(data))
if not data.get('localId'):
raise ValueError('User ID must not be None or empty.')
self._data = data
@property
def uid(self):
"""Returns the user ID of this user.
Returns:
string: A user ID string. This value is never None or empty.
"""
return self._data.get('localId')
@property
def display_name(self):
"""Returns the display name of this user.
Returns:
string: A display name string or None.
"""
return self._data.get('displayName')
@property
def email(self):
"""Returns the email address associated with this user.
Returns:
string: An email address string or None.
"""
return self._data.get('email')
@property
def phone_number(self):
"""Returns the phone number associated with this user.
Returns:
string: A phone number string or None.
"""
return self._data.get('phoneNumber')
@property
def photo_url(self):
"""Returns the photo URL of this user.
Returns:
string: A URL string or None.
"""
return self._data.get('photoUrl')
@property
def provider_id(self):
"""Returns the provider ID of this user.
Returns:
string: A constant provider ID value.
"""
return 'firebase'
@property
def email_verified(self):
"""Returns whether the email address of this user has been verified.
Returns:
bool: True if the email has been verified, and False otherwise.
"""
return bool(self._data.get('emailVerified'))
@property
def disabled(self):
"""Returns whether this user account is disabled.
Returns:
bool: True if the user account is disabled, and False otherwise.
"""
return bool(self._data.get('disabled'))
@property
def tokens_valid_after_timestamp(self):
"""Returns the time, in milliseconds since the epoch, before which tokens are invalid.
Note: this is truncated to 1 second accuracy.
Returns:
int: Timestamp in milliseconds since the epoch, truncated to the second.
All tokens issued before that time are considered revoked.
"""
valid_since = self._data.get('validSince')
if valid_since is not None:
return 1000 * int(valid_since)
return 0
@property
def user_metadata(self):
"""Returns additional metadata associated with this user.
Returns:
UserMetadata: A UserMetadata instance. Does not return None.
"""
def _int_or_none(key):
if key in self._data:
return int(self._data[key])
return None
return UserMetadata(_int_or_none('createdAt'), _int_or_none('lastLoginAt'))
@property
def provider_data(self):
"""Returns a list of UserInfo instances.
Each object represents an identity from an identity provider that is linked to this user.
Returns:
list: A list of UserInfo objects, which may be empty.
"""
providers = self._data.get('providerUserInfo', [])
return [ProviderUserInfo(entry) for entry in providers]
@property
def custom_claims(self):
"""Returns any custom claims set on this user account.
Returns:
dict: A dictionary of claims or None.
"""
claims = self._data.get('customAttributes')
if claims:
parsed = json.loads(claims)
if parsed != {}:
return parsed
return None
class ExportedUserRecord(UserRecord):
"""Contains metadata associated with a user including password hash and salt."""
def __init__(self, data):
super(ExportedUserRecord, self).__init__(data)
@property
def password_hash(self):
"""The user's password hash as a base64-encoded string.
If the Firebase Auth hashing algorithm (SCRYPT) was used to create the user account, this
is the base64-encoded password hash of the user. If a different hashing algorithm was
used to create this user, as is typical when migrating from another Auth system, this
is an empty string. If no password is set, this is ``None``.
"""
return self._data.get('passwordHash')
@property
def password_salt(self):
"""The user's password salt as a base64-encoded string.
If the Firebase Auth hashing algorithm (SCRYPT) was used to create the user account, this
is the base64-encoded password salt of the user. If a different hashing algorithm was
used to create this user, as is typical when migrating from another Auth system, this is
an empty string. If no password is set, this is ``None``.
"""
return self._data.get('salt')
class ListUsersPage(object):
"""Represents a page of user records exported from a Firebase project.
Provides methods for traversing the user accounts included in this page, as well as retrieving
subsequent pages of users. The iterator returned by ``iterate_all()`` can be used to iterate
through all users in the Firebase project starting from this page.
"""
def __init__(self, download, page_token, max_results):
self._download = download
self._max_results = max_results
self._current = download(page_token, max_results)
@property
def users(self):
"""A list of ``ExportedUserRecord`` instances available in this page."""
return [ExportedUserRecord(user) for user in self._current.get('users', [])]
@property
def next_page_token(self):
"""Page token string for the next page (empty string indicates no more pages)."""
return self._current.get('nextPageToken', '')
@property
def has_next_page(self):
"""A boolean indicating whether more pages are available."""
return bool(self.next_page_token)
def get_next_page(self):
"""Retrieves the next page of user accounts, if available.
Returns:
ListUsersPage: Next page of users, or None if this is the last page.
"""
if self.has_next_page:
return ListUsersPage(self._download, self.next_page_token, self._max_results)
return None
def iterate_all(self):
"""Retrieves an iterator for user accounts.
Returned iterator will iterate through all the user accounts in the Firebase project
starting from this page. The iterator will never buffer more than one page of users
in memory at a time.
Returns:
iterator: An iterator of ExportedUserRecord instances.
"""
return _UserIterator(self)
class ProviderUserInfo(UserInfo):
"""Contains metadata regarding how a user is known by a particular identity provider."""
def __init__(self, data):
super(ProviderUserInfo, self).__init__()
if not isinstance(data, dict):
raise ValueError('Invalid data argument: {0}. Must be a dictionary.'.format(data))
if not data.get('rawId'):
raise ValueError('User ID must not be None or empty.')
self._data = data
@property
def uid(self):
return self._data.get('rawId')
@property
def display_name(self):
return self._data.get('displayName')
@property
def email(self):
return self._data.get('email')
@property
def phone_number(self):
return self._data.get('phoneNumber')
@property
def photo_url(self):
return self._data.get('photoUrl')
@property
def provider_id(self):
return self._data.get('providerId')
class ActionCodeSettings(object):
"""Contains required continue/state URL with optional Android and iOS settings.
Used when invoking the email action link generation APIs.
"""
def __init__(self, url, handle_code_in_app=None, dynamic_link_domain=None, ios_bundle_id=None,
android_package_name=None, android_install_app=None, android_minimum_version=None):
self.url = url
self.handle_code_in_app = handle_code_in_app
self.dynamic_link_domain = dynamic_link_domain
self.ios_bundle_id = ios_bundle_id
self.android_package_name = android_package_name
self.android_install_app = android_install_app
self.android_minimum_version = android_minimum_version
def encode_action_code_settings(settings):
""" Validates the provided action code settings for email link generation and
populates the REST api parameters.
settings - ``ActionCodeSettings`` object provided to be encoded
returns - dict of parameters to be passed for link gereration.
"""
parameters = {}
# url
if not settings.url:
raise ValueError("Dynamic action links url is mandatory")
try:
parsed = urllib.parse.urlparse(settings.url)
if not parsed.netloc:
raise ValueError('Malformed dynamic action links url: "{0}".'.format(settings.url))
parameters['continueUrl'] = settings.url
except Exception:
raise ValueError('Malformed dynamic action links url: "{0}".'.format(settings.url))
# handle_code_in_app
if settings.handle_code_in_app is not None:
if not isinstance(settings.handle_code_in_app, bool):
raise ValueError('Invalid value provided for handle_code_in_app: {0}'
.format(settings.handle_code_in_app))
parameters['canHandleCodeInApp'] = settings.handle_code_in_app
# dynamic_link_domain
if settings.dynamic_link_domain is not None:
if not isinstance(settings.dynamic_link_domain, six.string_types):
raise ValueError('Invalid value provided for dynamic_link_domain: {0}'
.format(settings.dynamic_link_domain))
parameters['dynamicLinkDomain'] = settings.dynamic_link_domain
# ios_bundle_id
if settings.ios_bundle_id is not None:
if not isinstance(settings.ios_bundle_id, six.string_types):
raise ValueError('Invalid value provided for ios_bundle_id: {0}'
.format(settings.ios_bundle_id))
parameters['iosBundleId'] = settings.ios_bundle_id
# android_* attributes
if (settings.android_minimum_version or settings.android_install_app) \
and not settings.android_package_name:
raise ValueError("Android package name is required when specifying other Android settings")
if settings.android_package_name is not None:
if not isinstance(settings.android_package_name, six.string_types):
raise ValueError('Invalid value provided for android_package_name: {0}'
.format(settings.android_package_name))
parameters['androidPackageName'] = settings.android_package_name
if settings.android_minimum_version is not None:
if not isinstance(settings.android_minimum_version, six.string_types):
raise ValueError('Invalid value provided for android_minimum_version: {0}'
.format(settings.android_minimum_version))
parameters['androidMinimumVersion'] = settings.android_minimum_version
if settings.android_install_app is not None:
if not isinstance(settings.android_install_app, bool):
raise ValueError('Invalid value provided for android_install_app: {0}'
.format(settings.android_install_app))
parameters['androidInstallApp'] = settings.android_install_app
return parameters
class UserManager(object):
"""Provides methods for interacting with the Google Identity Toolkit."""
def __init__(self, client):
self._client = client
def get_user(self, **kwargs):
"""Gets the user data corresponding to the provided key."""
if 'uid' in kwargs:
key, key_type = kwargs.pop('uid'), 'user ID'
payload = {'localId' : [_auth_utils.validate_uid(key, required=True)]}
elif 'email' in kwargs:
key, key_type = kwargs.pop('email'), 'email'
payload = {'email' : [_auth_utils.validate_email(key, required=True)]}
elif 'phone_number' in kwargs:
key, key_type = kwargs.pop('phone_number'), 'phone number'
payload = {'phoneNumber' : [_auth_utils.validate_phone(key, required=True)]}
else:
raise TypeError('Unsupported keyword arguments: {0}.'.format(kwargs))
try:
body, http_resp = self._client.body_and_response(
'post', '/accounts:lookup', json=payload)
except requests.exceptions.RequestException as error:
raise _auth_utils.handle_auth_backend_error(error)
else:
if not body or not body.get('users'):
raise _auth_utils.UserNotFoundError(
'No user record found for the provided {0}: {1}.'.format(key_type, key),
http_response=http_resp)
return body['users'][0]
def list_users(self, page_token=None, max_results=MAX_LIST_USERS_RESULTS):
"""Retrieves a batch of users."""
if page_token is not None:
if not isinstance(page_token, six.string_types) or not page_token:
raise ValueError('Page token must be a non-empty string.')
if not isinstance(max_results, int):
raise ValueError('Max results must be an integer.')
elif max_results < 1 or max_results > MAX_LIST_USERS_RESULTS:
raise ValueError(
'Max results must be a positive integer less than '
'{0}.'.format(MAX_LIST_USERS_RESULTS))
payload = {'maxResults': max_results}
if page_token:
payload['nextPageToken'] = page_token
try:
return self._client.body('get', '/accounts:batchGet', params=payload)
except requests.exceptions.RequestException as error:
raise _auth_utils.handle_auth_backend_error(error)
def create_user(self, uid=None, display_name=None, email=None, phone_number=None,
photo_url=None, password=<PASSWORD>, disabled=None, email_verified=None):
"""Creates a new user account with the specified properties."""
payload = {
'localId': _auth_utils.validate_uid(uid),
'displayName': _auth_utils.validate_display_name(display_name),
'email': _auth_utils.validate_email(email),
'phoneNumber': _auth_utils.validate_phone(phone_number),
'photoUrl': _auth_utils.validate_photo_url(photo_url),
'password': _auth_utils.validate_password(password),
'emailVerified': bool(email_verified) if email_verified is not None else None,
'disabled': bool(disabled) if disabled is not None else None,
}
payload = {k: v for k, v in payload.items() if v is not None}
try:
body, http_resp = self._client.body_and_response('post', '/accounts', json=payload)
except requests.exceptions.RequestException as error:
raise _auth_utils.handle_auth_backend_error(error)
else:
if not body or not body.get('localId'):
raise _auth_utils.UnexpectedResponseError(
'Failed to create new user.', http_response=http_resp)
return body.get('localId')
def update_user(self, uid, display_name=None, email=None, phone_number=None,
photo_url=None, password=<PASSWORD>, disabled=None, email_verified=None,
valid_since=None, custom_claims=None):
"""Updates an existing user account with the specified properties"""
payload = {
'localId': _auth_utils.validate_uid(uid, required=True),
'email': _auth_utils.validate_email(email),
'password': _auth_<PASSWORD>(password),
'validSince': _auth_utils.validate_timestamp(valid_since, 'valid_since'),
'emailVerified': bool(email_verified) if email_verified is not None else None,
'disableUser': bool(disabled) if disabled is not None else None,
}
remove = []
if display_name is not None:
if display_name is DELETE_ATTRIBUTE:
remove.append('DISPLAY_NAME')
else:
payload['displayName'] = _auth_utils.validate_display_name(display_name)
if photo_url is not None:
if photo_url is DELETE_ATTRIBUTE:
remove.append('PHOTO_URL')
else:
payload['photoUrl'] = _auth_utils.validate_photo_url(photo_url)
if remove:
payload['deleteAttribute'] = remove
if phone_number is not None:
if phone_number is DELETE_ATTRIBUTE:
payload['deleteProvider'] = ['phone']
else:
payload['phoneNumber'] = _auth_utils.validate_phone(phone_number)
if custom_claims is not None:
if custom_claims is DELETE_ATTRIBUTE:
custom_claims = {}
json_claims = json.dumps(custom_claims) if isinstance(
custom_claims, dict) else custom_claims
payload['customAttributes'] = _auth_utils.validate_custom_claims(json_claims)
payload = {k: v for k, v in payload.items() if v is not None}
try:
body, http_resp = self._client.body_and_response(
'post', '/accounts:update', json=payload)
except requests.exceptions.RequestException as error:
raise _auth_utils.handle_auth_backend_error(error)
else:
if not body or not body.get('localId'):
raise _auth_utils.UnexpectedResponseError(
'Failed to update user: {0}.'.format(uid), http_response=http_resp)
return body.get('localId')
def delete_user(self, uid):
"""Deletes the user identified by the specified user ID."""
_auth_utils.validate_uid(uid, required=True)
try:
body, http_resp = self._client.body_and_response(
'post', '/accounts:delete', json={'localId' : uid})
except requests.exceptions.RequestException as error:
raise _auth_utils.handle_auth_backend_error(error)
else:
if not body or not body.get('kind'):
raise _auth_utils.UnexpectedResponseError(
'Failed to delete user: {0}.'.format(uid), http_response=http_resp)
def import_users(self, users, hash_alg=None):
"""Imports the given list of users to Firebase Auth."""
try:
if not users or len(users) > MAX_IMPORT_USERS_SIZE:
raise ValueError(
'Users must be a non-empty list with no more than {0} elements.'.format(
MAX_IMPORT_USERS_SIZE))
if any([not isinstance(u, _user_import.ImportUserRecord) for u in users]):
raise ValueError('One or more user objects are invalid.')
except TypeError:
raise ValueError('users must be iterable')
payload = {'users': [u.to_dict() for u in users]}
if any(['passwordHash' in u for u in payload['users']]):
if not isinstance(hash_alg, _user_import.UserImportHash):
raise ValueError('A UserImportHash is required to import users with passwords.')
payload.update(hash_alg.to_dict())
try:
body, http_resp = self._client.body_and_response(
'post', '/accounts:batchCreate', json=payload)
except requests.exceptions.RequestException as error:
raise _auth_utils.handle_auth_backend_error(error)
else:
if not isinstance(body, dict):
raise _auth_utils.UnexpectedResponseError(
'Failed to import users.', http_response=http_resp)
return body
def generate_email_action_link(self, action_type, email, action_code_settings=None):
"""Fetches the email action links for types
Args:
action_type: String. Valid values ['VERIFY_EMAIL', 'EMAIL_SIGNIN', 'PASSWORD_RESET']
email: Email of the user for which the action is performed
action_code_settings: ``ActionCodeSettings`` object or dict (optional). Defines whether
the link is to be handled by a mobile app and the additional state information to be
passed in the deep link, etc.
Returns:
link_url: action url to be emailed to the user
Raises:
FirebaseError: If an error occurs while generating the link
ValueError: If the provided arguments are invalid
"""
payload = {
'requestType': _auth_utils.validate_action_type(action_type),
'email': _auth_utils.validate_email(email),
'returnOobLink': True
}
if action_code_settings:
payload.update(encode_action_code_settings(action_code_settings))
try:
body, http_resp = self._client.body_and_response(
'post', '/accounts:sendOobCode', json=payload)
except requests.exceptions.RequestException as error:
raise _auth_utils.handle_auth_backend_error(error)
else:
if not body or not body.get('oobLink'):
raise _auth_utils.UnexpectedResponseError(
'Failed to generate email action link.', http_response=http_resp)
return body.get('oobLink')
class _UserIterator(object):
"""An iterator that allows iterating over user accounts, one at a time.
This implementation loads a page of users into memory, and iterates on them. When the whole
page has been traversed, it loads another page. This class never keeps more than one page
of entries in memory.
"""
def __init__(self, current_page):
if not current_page:
raise ValueError('Current page must not be None.')
self._current_page = current_page
self._index = 0
def next(self):
if self._index == len(self._current_page.users):
if self._current_page.has_next_page:
self._current_page = self._current_page.get_next_page()
self._index = 0
if self._index < len(self._current_page.users):
result = self._current_page.users[self._index]
self._index += 1
return result
raise StopIteration
def __next__(self):
return self.next()
def __iter__(self):
return self | venv/lib/python3.7/site-packages/firebase_admin/_user_mgt.py | import json
import requests
import six
from six.moves import urllib
from firebase_admin import _auth_utils
from firebase_admin import _user_import
MAX_LIST_USERS_RESULTS = 1000
MAX_IMPORT_USERS_SIZE = 1000
class Sentinel(object):
def __init__(self, description):
self.description = description
DELETE_ATTRIBUTE = Sentinel('Value used to delete an attribute from a user profile')
class UserMetadata(object):
"""Contains additional metadata associated with a user account."""
def __init__(self, creation_timestamp=None, last_sign_in_timestamp=None):
self._creation_timestamp = _auth_utils.validate_timestamp(
creation_timestamp, 'creation_timestamp')
self._last_sign_in_timestamp = _auth_utils.validate_timestamp(
last_sign_in_timestamp, 'last_sign_in_timestamp')
@property
def creation_timestamp(self):
""" Creation timestamp in milliseconds since the epoch.
Returns:
integer: The user creation timestamp in milliseconds since the epoch.
"""
return self._creation_timestamp
@property
def last_sign_in_timestamp(self):
""" Last sign in timestamp in milliseconds since the epoch.
Returns:
integer: The last sign in timestamp in milliseconds since the epoch.
"""
return self._last_sign_in_timestamp
class UserInfo(object):
"""A collection of standard profile information for a user.
Used to expose profile information returned by an identity provider.
"""
@property
def uid(self):
"""Returns the user ID of this user."""
raise NotImplementedError
@property
def display_name(self):
"""Returns the display name of this user."""
raise NotImplementedError
@property
def email(self):
"""Returns the email address associated with this user."""
raise NotImplementedError
@property
def phone_number(self):
"""Returns the phone number associated with this user."""
raise NotImplementedError
@property
def photo_url(self):
"""Returns the photo URL of this user."""
raise NotImplementedError
@property
def provider_id(self):
"""Returns the ID of the identity provider.
This can be a short domain name (e.g. google.com), or the identity of an OpenID
identity provider.
"""
raise NotImplementedError
class UserRecord(UserInfo):
"""Contains metadata associated with a Firebase user account."""
def __init__(self, data):
super(UserRecord, self).__init__()
if not isinstance(data, dict):
raise ValueError('Invalid data argument: {0}. Must be a dictionary.'.format(data))
if not data.get('localId'):
raise ValueError('User ID must not be None or empty.')
self._data = data
@property
def uid(self):
"""Returns the user ID of this user.
Returns:
string: A user ID string. This value is never None or empty.
"""
return self._data.get('localId')
@property
def display_name(self):
"""Returns the display name of this user.
Returns:
string: A display name string or None.
"""
return self._data.get('displayName')
@property
def email(self):
"""Returns the email address associated with this user.
Returns:
string: An email address string or None.
"""
return self._data.get('email')
@property
def phone_number(self):
"""Returns the phone number associated with this user.
Returns:
string: A phone number string or None.
"""
return self._data.get('phoneNumber')
@property
def photo_url(self):
"""Returns the photo URL of this user.
Returns:
string: A URL string or None.
"""
return self._data.get('photoUrl')
@property
def provider_id(self):
"""Returns the provider ID of this user.
Returns:
string: A constant provider ID value.
"""
return 'firebase'
@property
def email_verified(self):
"""Returns whether the email address of this user has been verified.
Returns:
bool: True if the email has been verified, and False otherwise.
"""
return bool(self._data.get('emailVerified'))
@property
def disabled(self):
"""Returns whether this user account is disabled.
Returns:
bool: True if the user account is disabled, and False otherwise.
"""
return bool(self._data.get('disabled'))
@property
def tokens_valid_after_timestamp(self):
"""Returns the time, in milliseconds since the epoch, before which tokens are invalid.
Note: this is truncated to 1 second accuracy.
Returns:
int: Timestamp in milliseconds since the epoch, truncated to the second.
All tokens issued before that time are considered revoked.
"""
valid_since = self._data.get('validSince')
if valid_since is not None:
return 1000 * int(valid_since)
return 0
@property
def user_metadata(self):
"""Returns additional metadata associated with this user.
Returns:
UserMetadata: A UserMetadata instance. Does not return None.
"""
def _int_or_none(key):
if key in self._data:
return int(self._data[key])
return None
return UserMetadata(_int_or_none('createdAt'), _int_or_none('lastLoginAt'))
@property
def provider_data(self):
"""Returns a list of UserInfo instances.
Each object represents an identity from an identity provider that is linked to this user.
Returns:
list: A list of UserInfo objects, which may be empty.
"""
providers = self._data.get('providerUserInfo', [])
return [ProviderUserInfo(entry) for entry in providers]
@property
def custom_claims(self):
"""Returns any custom claims set on this user account.
Returns:
dict: A dictionary of claims or None.
"""
claims = self._data.get('customAttributes')
if claims:
parsed = json.loads(claims)
if parsed != {}:
return parsed
return None
class ExportedUserRecord(UserRecord):
"""Contains metadata associated with a user including password hash and salt."""
def __init__(self, data):
super(ExportedUserRecord, self).__init__(data)
@property
def password_hash(self):
"""The user's password hash as a base64-encoded string.
If the Firebase Auth hashing algorithm (SCRYPT) was used to create the user account, this
is the base64-encoded password hash of the user. If a different hashing algorithm was
used to create this user, as is typical when migrating from another Auth system, this
is an empty string. If no password is set, this is ``None``.
"""
return self._data.get('passwordHash')
@property
def password_salt(self):
"""The user's password salt as a base64-encoded string.
If the Firebase Auth hashing algorithm (SCRYPT) was used to create the user account, this
is the base64-encoded password salt of the user. If a different hashing algorithm was
used to create this user, as is typical when migrating from another Auth system, this is
an empty string. If no password is set, this is ``None``.
"""
return self._data.get('salt')
class ListUsersPage(object):
"""Represents a page of user records exported from a Firebase project.
Provides methods for traversing the user accounts included in this page, as well as retrieving
subsequent pages of users. The iterator returned by ``iterate_all()`` can be used to iterate
through all users in the Firebase project starting from this page.
"""
def __init__(self, download, page_token, max_results):
self._download = download
self._max_results = max_results
self._current = download(page_token, max_results)
@property
def users(self):
"""A list of ``ExportedUserRecord`` instances available in this page."""
return [ExportedUserRecord(user) for user in self._current.get('users', [])]
@property
def next_page_token(self):
"""Page token string for the next page (empty string indicates no more pages)."""
return self._current.get('nextPageToken', '')
@property
def has_next_page(self):
"""A boolean indicating whether more pages are available."""
return bool(self.next_page_token)
def get_next_page(self):
"""Retrieves the next page of user accounts, if available.
Returns:
ListUsersPage: Next page of users, or None if this is the last page.
"""
if self.has_next_page:
return ListUsersPage(self._download, self.next_page_token, self._max_results)
return None
def iterate_all(self):
"""Retrieves an iterator for user accounts.
Returned iterator will iterate through all the user accounts in the Firebase project
starting from this page. The iterator will never buffer more than one page of users
in memory at a time.
Returns:
iterator: An iterator of ExportedUserRecord instances.
"""
return _UserIterator(self)
class ProviderUserInfo(UserInfo):
"""Contains metadata regarding how a user is known by a particular identity provider."""
def __init__(self, data):
super(ProviderUserInfo, self).__init__()
if not isinstance(data, dict):
raise ValueError('Invalid data argument: {0}. Must be a dictionary.'.format(data))
if not data.get('rawId'):
raise ValueError('User ID must not be None or empty.')
self._data = data
@property
def uid(self):
return self._data.get('rawId')
@property
def display_name(self):
return self._data.get('displayName')
@property
def email(self):
return self._data.get('email')
@property
def phone_number(self):
return self._data.get('phoneNumber')
@property
def photo_url(self):
return self._data.get('photoUrl')
@property
def provider_id(self):
return self._data.get('providerId')
class ActionCodeSettings(object):
"""Contains required continue/state URL with optional Android and iOS settings.
Used when invoking the email action link generation APIs.
"""
def __init__(self, url, handle_code_in_app=None, dynamic_link_domain=None, ios_bundle_id=None,
android_package_name=None, android_install_app=None, android_minimum_version=None):
self.url = url
self.handle_code_in_app = handle_code_in_app
self.dynamic_link_domain = dynamic_link_domain
self.ios_bundle_id = ios_bundle_id
self.android_package_name = android_package_name
self.android_install_app = android_install_app
self.android_minimum_version = android_minimum_version
def encode_action_code_settings(settings):
""" Validates the provided action code settings for email link generation and
populates the REST api parameters.
settings - ``ActionCodeSettings`` object provided to be encoded
returns - dict of parameters to be passed for link gereration.
"""
parameters = {}
# url
if not settings.url:
raise ValueError("Dynamic action links url is mandatory")
try:
parsed = urllib.parse.urlparse(settings.url)
if not parsed.netloc:
raise ValueError('Malformed dynamic action links url: "{0}".'.format(settings.url))
parameters['continueUrl'] = settings.url
except Exception:
raise ValueError('Malformed dynamic action links url: "{0}".'.format(settings.url))
# handle_code_in_app
if settings.handle_code_in_app is not None:
if not isinstance(settings.handle_code_in_app, bool):
raise ValueError('Invalid value provided for handle_code_in_app: {0}'
.format(settings.handle_code_in_app))
parameters['canHandleCodeInApp'] = settings.handle_code_in_app
# dynamic_link_domain
if settings.dynamic_link_domain is not None:
if not isinstance(settings.dynamic_link_domain, six.string_types):
raise ValueError('Invalid value provided for dynamic_link_domain: {0}'
.format(settings.dynamic_link_domain))
parameters['dynamicLinkDomain'] = settings.dynamic_link_domain
# ios_bundle_id
if settings.ios_bundle_id is not None:
if not isinstance(settings.ios_bundle_id, six.string_types):
raise ValueError('Invalid value provided for ios_bundle_id: {0}'
.format(settings.ios_bundle_id))
parameters['iosBundleId'] = settings.ios_bundle_id
# android_* attributes
if (settings.android_minimum_version or settings.android_install_app) \
and not settings.android_package_name:
raise ValueError("Android package name is required when specifying other Android settings")
if settings.android_package_name is not None:
if not isinstance(settings.android_package_name, six.string_types):
raise ValueError('Invalid value provided for android_package_name: {0}'
.format(settings.android_package_name))
parameters['androidPackageName'] = settings.android_package_name
if settings.android_minimum_version is not None:
if not isinstance(settings.android_minimum_version, six.string_types):
raise ValueError('Invalid value provided for android_minimum_version: {0}'
.format(settings.android_minimum_version))
parameters['androidMinimumVersion'] = settings.android_minimum_version
if settings.android_install_app is not None:
if not isinstance(settings.android_install_app, bool):
raise ValueError('Invalid value provided for android_install_app: {0}'
.format(settings.android_install_app))
parameters['androidInstallApp'] = settings.android_install_app
return parameters
class UserManager(object):
"""Provides methods for interacting with the Google Identity Toolkit."""
def __init__(self, client):
self._client = client
def get_user(self, **kwargs):
"""Gets the user data corresponding to the provided key."""
if 'uid' in kwargs:
key, key_type = kwargs.pop('uid'), 'user ID'
payload = {'localId' : [_auth_utils.validate_uid(key, required=True)]}
elif 'email' in kwargs:
key, key_type = kwargs.pop('email'), 'email'
payload = {'email' : [_auth_utils.validate_email(key, required=True)]}
elif 'phone_number' in kwargs:
key, key_type = kwargs.pop('phone_number'), 'phone number'
payload = {'phoneNumber' : [_auth_utils.validate_phone(key, required=True)]}
else:
raise TypeError('Unsupported keyword arguments: {0}.'.format(kwargs))
try:
body, http_resp = self._client.body_and_response(
'post', '/accounts:lookup', json=payload)
except requests.exceptions.RequestException as error:
raise _auth_utils.handle_auth_backend_error(error)
else:
if not body or not body.get('users'):
raise _auth_utils.UserNotFoundError(
'No user record found for the provided {0}: {1}.'.format(key_type, key),
http_response=http_resp)
return body['users'][0]
def list_users(self, page_token=None, max_results=MAX_LIST_USERS_RESULTS):
"""Retrieves a batch of users."""
if page_token is not None:
if not isinstance(page_token, six.string_types) or not page_token:
raise ValueError('Page token must be a non-empty string.')
if not isinstance(max_results, int):
raise ValueError('Max results must be an integer.')
elif max_results < 1 or max_results > MAX_LIST_USERS_RESULTS:
raise ValueError(
'Max results must be a positive integer less than '
'{0}.'.format(MAX_LIST_USERS_RESULTS))
payload = {'maxResults': max_results}
if page_token:
payload['nextPageToken'] = page_token
try:
return self._client.body('get', '/accounts:batchGet', params=payload)
except requests.exceptions.RequestException as error:
raise _auth_utils.handle_auth_backend_error(error)
def create_user(self, uid=None, display_name=None, email=None, phone_number=None,
photo_url=None, password=<PASSWORD>, disabled=None, email_verified=None):
"""Creates a new user account with the specified properties."""
payload = {
'localId': _auth_utils.validate_uid(uid),
'displayName': _auth_utils.validate_display_name(display_name),
'email': _auth_utils.validate_email(email),
'phoneNumber': _auth_utils.validate_phone(phone_number),
'photoUrl': _auth_utils.validate_photo_url(photo_url),
'password': _auth_utils.validate_password(password),
'emailVerified': bool(email_verified) if email_verified is not None else None,
'disabled': bool(disabled) if disabled is not None else None,
}
payload = {k: v for k, v in payload.items() if v is not None}
try:
body, http_resp = self._client.body_and_response('post', '/accounts', json=payload)
except requests.exceptions.RequestException as error:
raise _auth_utils.handle_auth_backend_error(error)
else:
if not body or not body.get('localId'):
raise _auth_utils.UnexpectedResponseError(
'Failed to create new user.', http_response=http_resp)
return body.get('localId')
def update_user(self, uid, display_name=None, email=None, phone_number=None,
photo_url=None, password=<PASSWORD>, disabled=None, email_verified=None,
valid_since=None, custom_claims=None):
"""Updates an existing user account with the specified properties"""
payload = {
'localId': _auth_utils.validate_uid(uid, required=True),
'email': _auth_utils.validate_email(email),
'password': _auth_<PASSWORD>(password),
'validSince': _auth_utils.validate_timestamp(valid_since, 'valid_since'),
'emailVerified': bool(email_verified) if email_verified is not None else None,
'disableUser': bool(disabled) if disabled is not None else None,
}
remove = []
if display_name is not None:
if display_name is DELETE_ATTRIBUTE:
remove.append('DISPLAY_NAME')
else:
payload['displayName'] = _auth_utils.validate_display_name(display_name)
if photo_url is not None:
if photo_url is DELETE_ATTRIBUTE:
remove.append('PHOTO_URL')
else:
payload['photoUrl'] = _auth_utils.validate_photo_url(photo_url)
if remove:
payload['deleteAttribute'] = remove
if phone_number is not None:
if phone_number is DELETE_ATTRIBUTE:
payload['deleteProvider'] = ['phone']
else:
payload['phoneNumber'] = _auth_utils.validate_phone(phone_number)
if custom_claims is not None:
if custom_claims is DELETE_ATTRIBUTE:
custom_claims = {}
json_claims = json.dumps(custom_claims) if isinstance(
custom_claims, dict) else custom_claims
payload['customAttributes'] = _auth_utils.validate_custom_claims(json_claims)
payload = {k: v for k, v in payload.items() if v is not None}
try:
body, http_resp = self._client.body_and_response(
'post', '/accounts:update', json=payload)
except requests.exceptions.RequestException as error:
raise _auth_utils.handle_auth_backend_error(error)
else:
if not body or not body.get('localId'):
raise _auth_utils.UnexpectedResponseError(
'Failed to update user: {0}.'.format(uid), http_response=http_resp)
return body.get('localId')
def delete_user(self, uid):
"""Deletes the user identified by the specified user ID."""
_auth_utils.validate_uid(uid, required=True)
try:
body, http_resp = self._client.body_and_response(
'post', '/accounts:delete', json={'localId' : uid})
except requests.exceptions.RequestException as error:
raise _auth_utils.handle_auth_backend_error(error)
else:
if not body or not body.get('kind'):
raise _auth_utils.UnexpectedResponseError(
'Failed to delete user: {0}.'.format(uid), http_response=http_resp)
def import_users(self, users, hash_alg=None):
"""Imports the given list of users to Firebase Auth."""
try:
if not users or len(users) > MAX_IMPORT_USERS_SIZE:
raise ValueError(
'Users must be a non-empty list with no more than {0} elements.'.format(
MAX_IMPORT_USERS_SIZE))
if any([not isinstance(u, _user_import.ImportUserRecord) for u in users]):
raise ValueError('One or more user objects are invalid.')
except TypeError:
raise ValueError('users must be iterable')
payload = {'users': [u.to_dict() for u in users]}
if any(['passwordHash' in u for u in payload['users']]):
if not isinstance(hash_alg, _user_import.UserImportHash):
raise ValueError('A UserImportHash is required to import users with passwords.')
payload.update(hash_alg.to_dict())
try:
body, http_resp = self._client.body_and_response(
'post', '/accounts:batchCreate', json=payload)
except requests.exceptions.RequestException as error:
raise _auth_utils.handle_auth_backend_error(error)
else:
if not isinstance(body, dict):
raise _auth_utils.UnexpectedResponseError(
'Failed to import users.', http_response=http_resp)
return body
def generate_email_action_link(self, action_type, email, action_code_settings=None):
"""Fetches the email action links for types
Args:
action_type: String. Valid values ['VERIFY_EMAIL', 'EMAIL_SIGNIN', 'PASSWORD_RESET']
email: Email of the user for which the action is performed
action_code_settings: ``ActionCodeSettings`` object or dict (optional). Defines whether
the link is to be handled by a mobile app and the additional state information to be
passed in the deep link, etc.
Returns:
link_url: action url to be emailed to the user
Raises:
FirebaseError: If an error occurs while generating the link
ValueError: If the provided arguments are invalid
"""
payload = {
'requestType': _auth_utils.validate_action_type(action_type),
'email': _auth_utils.validate_email(email),
'returnOobLink': True
}
if action_code_settings:
payload.update(encode_action_code_settings(action_code_settings))
try:
body, http_resp = self._client.body_and_response(
'post', '/accounts:sendOobCode', json=payload)
except requests.exceptions.RequestException as error:
raise _auth_utils.handle_auth_backend_error(error)
else:
if not body or not body.get('oobLink'):
raise _auth_utils.UnexpectedResponseError(
'Failed to generate email action link.', http_response=http_resp)
return body.get('oobLink')
class _UserIterator(object):
"""An iterator that allows iterating over user accounts, one at a time.
This implementation loads a page of users into memory, and iterates on them. When the whole
page has been traversed, it loads another page. This class never keeps more than one page
of entries in memory.
"""
def __init__(self, current_page):
if not current_page:
raise ValueError('Current page must not be None.')
self._current_page = current_page
self._index = 0
def next(self):
if self._index == len(self._current_page.users):
if self._current_page.has_next_page:
self._current_page = self._current_page.get_next_page()
self._index = 0
if self._index < len(self._current_page.users):
result = self._current_page.users[self._index]
self._index += 1
return result
raise StopIteration
def __next__(self):
return self.next()
def __iter__(self):
return self | 0.849691 | 0.251269 |
r"""YAML backend:
- Format to support: YAML, http://yaml.org
- Requirements: PyYAML (yaml), http://pyyaml.org
- Development Status :: 5 - Production/Stable
- Limitations: ac_ordered is not effective and just ignored.
- Special options:
- All keyword options of yaml.safe_load, yaml.load, yaml.safe_dump and
yaml.dump should work.
- Use 'ac_safe' boolean keyword option if you prefer to call yaml.safe_load
and yaml.safe_dump instead of yaml.load and yaml.dump
- See also: http://pyyaml.org/wiki/PyYAMLDocumentation
Changelog:
.. versionchanged:: 0.3
- Changed special keyword option 'ac_safe' from 'safe' to avoid
possibility of option conflicts in the future.
"""
from __future__ import absolute_import
import yaml
try:
from yaml import CSafeLoader as Loader, CSafeDumper as Dumper
except ImportError:
from yaml import SafeLoader as Loader, SafeDumper as Dumper
import anyconfig.backend.base
import anyconfig.utils
def _setup_loader_and_dumper(container, loader=Loader, dumper=Dumper):
"""
Force set container (dict, OrderedDict, ...) used to construct python
object from yaml node internally.
.. note::
It cannot be used with ac_safe keyword option at the same time yet.
:param container: Set container used internally
"""
map_tag = yaml.resolver.BaseResolver.DEFAULT_MAPPING_TAG
def construct_mapping(loader, node, deep=False):
"""Constructor to construct python object from yaml mapping node.
:seealso: :meth:`yaml.BaseConstructor.construct_mapping`
"""
if not isinstance(node, yaml.MappingNode):
msg = "expected a mapping node, but found %s" % node.id
raise yaml.constructor.ConstructorError(None, None, msg,
node.start_mark)
mapping = container()
for key_node, value_node in node.value:
key = loader.construct_object(key_node, deep=deep)
try:
hash(key)
except TypeError as exc:
eargs = ("while constructing a mapping",
node.start_mark,
"found unacceptable key (%s)" % exc,
key_node.start_mark)
raise yaml.constructor.ConstructorError(*eargs)
value = loader.construct_object(value_node, deep=deep)
mapping[key] = value
return mapping
def container_representer(dumper, data):
"""Container representer.
"""
return dumper.represent_mapping(map_tag, data.items())
loader.add_constructor(map_tag, construct_mapping)
dumper.add_representer(container, container_representer)
def _yml_fnc(fname, *args, **kwargs):
"""An wrapper of yaml.safe_load, yaml.load, yaml.safe_dump and yaml.dump.
:param fname:
"load" or "dump", not checked but it should be OK.
see also :func:`_yml_load` and :func:`_yml_dump`
:param args: [stream] for load or [cnf, stream] for dump
:param kwargs: keyword args may contain "ac_safe" to load/dump safely
"""
key = "ac_safe"
fnc = getattr(yaml, kwargs.get(key, False) and r"safe_" + fname or fname)
kwargs = anyconfig.utils.filter_options([k for k in kwargs.keys()
if k != key], kwargs)
return fnc(*args, **kwargs)
def _yml_load(stream, container, **kwargs):
"""An wrapper of yaml.safe_load and yaml.load.
:param stream: a file or file-like object to load YAML content
:param container: callble to make a container object
"""
if "ac_safe" in kwargs: # yaml.safe_load does not process Loader opts.
kwargs = {}
else:
maybe_container = kwargs.get("ac_dict", None)
loader = kwargs.get("Loader", Loader)
dumper = kwargs.get("Dumper", Dumper)
if maybe_container is not None and callable(maybe_container):
_setup_loader_and_dumper(maybe_container, loader=loader,
dumper=dumper)
container = maybe_container
return container(_yml_fnc("load", stream, **kwargs))
def _yml_dump(cnf, stream, **kwargs):
"""An wrapper of yaml.safe_dump and yaml.dump.
:param cnf: Mapping object to dump
:param stream: a file or file-like object to dump YAML data
"""
if kwargs.get("ac_safe", False):
cnf = anyconfig.dicts.convert_to(cnf)
return _yml_fnc("dump", cnf, stream, **kwargs)
class Parser(anyconfig.backend.base.FromStreamLoader,
anyconfig.backend.base.ToStreamDumper):
"""
Parser for YAML files.
"""
_type = "yaml"
_extensions = ["yaml", "yml"]
_load_opts = ["Loader", "ac_safe"]
_dump_opts = ["stream", "ac_safe", "Dumper", "default_style",
"default_flow_style", "canonical", "indent", "width",
"allow_unicode", "line_break", "encoding", "explicit_start",
"explicit_end", "version", "tags"]
# _ordered = True # Not yet.
load_from_stream = anyconfig.backend.base.to_method(_yml_load)
dump_to_stream = anyconfig.backend.base.to_method(_yml_dump)
# vim:sw=4:ts=4:et: | anyconfig/backend/yaml.py | r"""YAML backend:
- Format to support: YAML, http://yaml.org
- Requirements: PyYAML (yaml), http://pyyaml.org
- Development Status :: 5 - Production/Stable
- Limitations: ac_ordered is not effective and just ignored.
- Special options:
- All keyword options of yaml.safe_load, yaml.load, yaml.safe_dump and
yaml.dump should work.
- Use 'ac_safe' boolean keyword option if you prefer to call yaml.safe_load
and yaml.safe_dump instead of yaml.load and yaml.dump
- See also: http://pyyaml.org/wiki/PyYAMLDocumentation
Changelog:
.. versionchanged:: 0.3
- Changed special keyword option 'ac_safe' from 'safe' to avoid
possibility of option conflicts in the future.
"""
from __future__ import absolute_import
import yaml
try:
from yaml import CSafeLoader as Loader, CSafeDumper as Dumper
except ImportError:
from yaml import SafeLoader as Loader, SafeDumper as Dumper
import anyconfig.backend.base
import anyconfig.utils
def _setup_loader_and_dumper(container, loader=Loader, dumper=Dumper):
"""
Force set container (dict, OrderedDict, ...) used to construct python
object from yaml node internally.
.. note::
It cannot be used with ac_safe keyword option at the same time yet.
:param container: Set container used internally
"""
map_tag = yaml.resolver.BaseResolver.DEFAULT_MAPPING_TAG
def construct_mapping(loader, node, deep=False):
"""Constructor to construct python object from yaml mapping node.
:seealso: :meth:`yaml.BaseConstructor.construct_mapping`
"""
if not isinstance(node, yaml.MappingNode):
msg = "expected a mapping node, but found %s" % node.id
raise yaml.constructor.ConstructorError(None, None, msg,
node.start_mark)
mapping = container()
for key_node, value_node in node.value:
key = loader.construct_object(key_node, deep=deep)
try:
hash(key)
except TypeError as exc:
eargs = ("while constructing a mapping",
node.start_mark,
"found unacceptable key (%s)" % exc,
key_node.start_mark)
raise yaml.constructor.ConstructorError(*eargs)
value = loader.construct_object(value_node, deep=deep)
mapping[key] = value
return mapping
def container_representer(dumper, data):
"""Container representer.
"""
return dumper.represent_mapping(map_tag, data.items())
loader.add_constructor(map_tag, construct_mapping)
dumper.add_representer(container, container_representer)
def _yml_fnc(fname, *args, **kwargs):
"""An wrapper of yaml.safe_load, yaml.load, yaml.safe_dump and yaml.dump.
:param fname:
"load" or "dump", not checked but it should be OK.
see also :func:`_yml_load` and :func:`_yml_dump`
:param args: [stream] for load or [cnf, stream] for dump
:param kwargs: keyword args may contain "ac_safe" to load/dump safely
"""
key = "ac_safe"
fnc = getattr(yaml, kwargs.get(key, False) and r"safe_" + fname or fname)
kwargs = anyconfig.utils.filter_options([k for k in kwargs.keys()
if k != key], kwargs)
return fnc(*args, **kwargs)
def _yml_load(stream, container, **kwargs):
"""An wrapper of yaml.safe_load and yaml.load.
:param stream: a file or file-like object to load YAML content
:param container: callble to make a container object
"""
if "ac_safe" in kwargs: # yaml.safe_load does not process Loader opts.
kwargs = {}
else:
maybe_container = kwargs.get("ac_dict", None)
loader = kwargs.get("Loader", Loader)
dumper = kwargs.get("Dumper", Dumper)
if maybe_container is not None and callable(maybe_container):
_setup_loader_and_dumper(maybe_container, loader=loader,
dumper=dumper)
container = maybe_container
return container(_yml_fnc("load", stream, **kwargs))
def _yml_dump(cnf, stream, **kwargs):
"""An wrapper of yaml.safe_dump and yaml.dump.
:param cnf: Mapping object to dump
:param stream: a file or file-like object to dump YAML data
"""
if kwargs.get("ac_safe", False):
cnf = anyconfig.dicts.convert_to(cnf)
return _yml_fnc("dump", cnf, stream, **kwargs)
class Parser(anyconfig.backend.base.FromStreamLoader,
anyconfig.backend.base.ToStreamDumper):
"""
Parser for YAML files.
"""
_type = "yaml"
_extensions = ["yaml", "yml"]
_load_opts = ["Loader", "ac_safe"]
_dump_opts = ["stream", "ac_safe", "Dumper", "default_style",
"default_flow_style", "canonical", "indent", "width",
"allow_unicode", "line_break", "encoding", "explicit_start",
"explicit_end", "version", "tags"]
# _ordered = True # Not yet.
load_from_stream = anyconfig.backend.base.to_method(_yml_load)
dump_to_stream = anyconfig.backend.base.to_method(_yml_dump)
# vim:sw=4:ts=4:et: | 0.810854 | 0.243929 |
from __future__ import unicode_literals
from .. import util
import soupsieve as sv
from soupsieve import SelectorSyntaxError
class TestNthChild(util.TestCase):
"""Test `nth` child selectors."""
def test_nth_child(self):
"""Test `nth` child."""
markup = """
<body>
<p id="0"></p>
<p id="1"></p>
<span id="2"></span>
<span id="3"></span>
<span id="4"></span>
<span id="5"></span>
<span id="6"></span>
<p id="7"></p>
<p id="8"></p>
<p id="9"></p>
<p id="10"></p>
<span id="11"></span>
</body>
"""
self.assert_selector(
markup,
"p:nth-child(-2)",
[],
flags=util.HTML
)
self.assert_selector(
markup,
"p:nth-child(2)",
['1'],
flags=util.HTML
)
def test_nth_child_odd(self):
"""Test `nth` child odd."""
markup = """
<body>
<p id="0"></p>
<p id="1"></p>
<span id="2"></span>
<span id="3"></span>
<span id="4"></span>
<span id="5"></span>
<span id="6"></span>
<p id="7"></p>
<p id="8"></p>
<p id="9"></p>
<p id="10"></p>
<span id="11"></span>
</body>
"""
self.assert_selector(
markup,
"p:nth-child(odd)",
['0', '8', '10'],
flags=util.HTML
)
def test_nth_child_even(self):
"""Test `nth` child even."""
markup = """
<body>
<p id="0"></p>
<p id="1"></p>
<span id="2"></span>
<span id="3"></span>
<span id="4"></span>
<span id="5"></span>
<span id="6"></span>
<p id="7"></p>
<p id="8"></p>
<p id="9"></p>
<p id="10"></p>
<span id="11"></span>
</body>
"""
self.assert_selector(
markup,
"p:nth-child(even)",
['1', '7', '9'],
flags=util.HTML
)
def test_nth_child_complex(self):
"""Test `nth` child complex."""
markup = """
<body>
<p id="0"></p>
<p id="1"></p>
<span id="2"></span>
<span id="3"></span>
<span id="4"></span>
<span id="5"></span>
<span id="6"></span>
<p id="7"></p>
<p id="8"></p>
<p id="9"></p>
<p id="10"></p>
<span id="11"></span>
</body>
"""
self.assert_selector(
markup,
"p:nth-child(2n-5)",
['0', '8', '10'],
flags=util.HTML
)
self.assert_selector(
markup,
"p:nth-child(-2n+20)",
['1', '7', '9'],
flags=util.HTML
)
self.assert_selector(
markup,
"p:nth-child(50n-20)",
[],
flags=util.HTML
)
self.assert_selector(
markup,
"p:nth-child(-2n-2)",
[],
flags=util.HTML
)
self.assert_selector(
markup,
"p:nth-child(9n - 1)",
['7'],
flags=util.HTML
)
self.assert_selector(
markup,
"p:nth-child(2n + 1)",
['0', '8', '10'],
flags=util.HTML
)
self.assert_selector(
markup,
"p:nth-child(-n+3)",
['0', '1'],
flags=util.HTML
)
self.assert_selector(
markup,
"span:nth-child(-n+3)",
['2'],
flags=util.HTML
)
self.assert_selector(
markup,
"body *:nth-child(-n+3)",
['0', '1', '2'],
flags=util.HTML
)
def test_nth_child_no_parent(self):
"""Test `nth` child with no parent."""
markup = """
<body>
<p id="0"></p>
<p id="1"></p>
<span id="2"></span>
<span id="3"></span>
<span id="4"></span>
<span id="5"></span>
<span id="6"></span>
<p id="7"></p>
<p id="8"></p>
<p id="9"></p>
<p id="10"></p>
<span id="11"></span>
</body>
"""
for parser in util.available_parsers('html.parser', 'lxml', 'html5lib'):
# Paragraph is the root. There is no document.
markup = """<p id="1">text</p>"""
soup = self.soup(markup, parser)
fragment = soup.p.extract()
self.assertTrue(sv.match("p:nth-child(1)", fragment, flags=sv.DEBUG))
def test_nth_child_with_bad_parameters(self):
"""Test that pseudo class fails with bad parameters (basically it doesn't match)."""
self.assert_raises(':nth-child(a)', SelectorSyntaxError)
class TestNthChildQuirks(TestNthChild):
"""Test `nth` child selectors with quirks."""
def setUp(self):
"""Setup."""
self.purge()
self.quirks = True | venv/lib/python3.6/site-packages/tests/test_level3/test_nth_child.py | from __future__ import unicode_literals
from .. import util
import soupsieve as sv
from soupsieve import SelectorSyntaxError
class TestNthChild(util.TestCase):
"""Test `nth` child selectors."""
def test_nth_child(self):
"""Test `nth` child."""
markup = """
<body>
<p id="0"></p>
<p id="1"></p>
<span id="2"></span>
<span id="3"></span>
<span id="4"></span>
<span id="5"></span>
<span id="6"></span>
<p id="7"></p>
<p id="8"></p>
<p id="9"></p>
<p id="10"></p>
<span id="11"></span>
</body>
"""
self.assert_selector(
markup,
"p:nth-child(-2)",
[],
flags=util.HTML
)
self.assert_selector(
markup,
"p:nth-child(2)",
['1'],
flags=util.HTML
)
def test_nth_child_odd(self):
"""Test `nth` child odd."""
markup = """
<body>
<p id="0"></p>
<p id="1"></p>
<span id="2"></span>
<span id="3"></span>
<span id="4"></span>
<span id="5"></span>
<span id="6"></span>
<p id="7"></p>
<p id="8"></p>
<p id="9"></p>
<p id="10"></p>
<span id="11"></span>
</body>
"""
self.assert_selector(
markup,
"p:nth-child(odd)",
['0', '8', '10'],
flags=util.HTML
)
def test_nth_child_even(self):
"""Test `nth` child even."""
markup = """
<body>
<p id="0"></p>
<p id="1"></p>
<span id="2"></span>
<span id="3"></span>
<span id="4"></span>
<span id="5"></span>
<span id="6"></span>
<p id="7"></p>
<p id="8"></p>
<p id="9"></p>
<p id="10"></p>
<span id="11"></span>
</body>
"""
self.assert_selector(
markup,
"p:nth-child(even)",
['1', '7', '9'],
flags=util.HTML
)
def test_nth_child_complex(self):
"""Test `nth` child complex."""
markup = """
<body>
<p id="0"></p>
<p id="1"></p>
<span id="2"></span>
<span id="3"></span>
<span id="4"></span>
<span id="5"></span>
<span id="6"></span>
<p id="7"></p>
<p id="8"></p>
<p id="9"></p>
<p id="10"></p>
<span id="11"></span>
</body>
"""
self.assert_selector(
markup,
"p:nth-child(2n-5)",
['0', '8', '10'],
flags=util.HTML
)
self.assert_selector(
markup,
"p:nth-child(-2n+20)",
['1', '7', '9'],
flags=util.HTML
)
self.assert_selector(
markup,
"p:nth-child(50n-20)",
[],
flags=util.HTML
)
self.assert_selector(
markup,
"p:nth-child(-2n-2)",
[],
flags=util.HTML
)
self.assert_selector(
markup,
"p:nth-child(9n - 1)",
['7'],
flags=util.HTML
)
self.assert_selector(
markup,
"p:nth-child(2n + 1)",
['0', '8', '10'],
flags=util.HTML
)
self.assert_selector(
markup,
"p:nth-child(-n+3)",
['0', '1'],
flags=util.HTML
)
self.assert_selector(
markup,
"span:nth-child(-n+3)",
['2'],
flags=util.HTML
)
self.assert_selector(
markup,
"body *:nth-child(-n+3)",
['0', '1', '2'],
flags=util.HTML
)
def test_nth_child_no_parent(self):
"""Test `nth` child with no parent."""
markup = """
<body>
<p id="0"></p>
<p id="1"></p>
<span id="2"></span>
<span id="3"></span>
<span id="4"></span>
<span id="5"></span>
<span id="6"></span>
<p id="7"></p>
<p id="8"></p>
<p id="9"></p>
<p id="10"></p>
<span id="11"></span>
</body>
"""
for parser in util.available_parsers('html.parser', 'lxml', 'html5lib'):
# Paragraph is the root. There is no document.
markup = """<p id="1">text</p>"""
soup = self.soup(markup, parser)
fragment = soup.p.extract()
self.assertTrue(sv.match("p:nth-child(1)", fragment, flags=sv.DEBUG))
def test_nth_child_with_bad_parameters(self):
"""Test that pseudo class fails with bad parameters (basically it doesn't match)."""
self.assert_raises(':nth-child(a)', SelectorSyntaxError)
class TestNthChildQuirks(TestNthChild):
"""Test `nth` child selectors with quirks."""
def setUp(self):
"""Setup."""
self.purge()
self.quirks = True | 0.822153 | 0.430447 |
from __future__ import print_function
from __future__ import unicode_literals
import numpy as np
import matplotlib.pyplot as plt
from .utils import Utils
class StructureFunction:
"""
This class provides methods for computing and analyzing struture functions
Args:
mrq (MultiResolutionQuantity): multiresolution quantity used to compute
the structure function
q (numpy.array) : list of exponents for which to compute the
structure function
j1 (int) : smallest scale analysis
j2 (int) : largest scale analysis
wtype (int) : 0 for ordinary regression, 1 for weighted regression
values (numpy.array) : values[ind_q, ind_j] = values of S(j, q), with q = self.q[ind_q]
and j = self.j[ind_j]
logvalues (numpy.array) : logvalues[ind_q, ind_j] = values of log_2 (S(j, q)),
with q = self.q[ind_q] and j = self.j[ind_j]
"""
def __init__(self, mrq, q, j1, j2, wtype):
self.mrq = mrq
self.q = q
self.j1 = j1
self.j2 = j2
self.j = np.array(list(mrq.values))
self.wtype = wtype
self.values = np.zeros( (len(self.q), len(self.j)) )
self.logvalues = np.zeros( (len(self.q), len(self.j)) )
self.zeta = []
self.utils = Utils() # used for linear regression
self._compute()
self._compute_zeta()
def _compute(self):
for ind_q, q in enumerate(self.q):
for ind_j, j in enumerate(self.j):
c_j = self.mrq.values[j]
s_j_q = np.mean(np.abs(c_j)**q)
self.values[ind_q, ind_j] = s_j_q
self.logvalues = np.log2(self.values)
def _compute_zeta(self):
"""
Compute the value of the scale function zeta(q) for all q
"""
self.zeta = np.zeros(len(self.q))
self.intercept = np.zeros(len(self.q))
x = np.arange(self.j1, self.j2+1)
if self.wtype == 1:
nj = self.mrq.get_nj_interv(self.j1, self.j2)
else:
nj = np.ones(len(x))
ind_j1 = self.j1-1
ind_j2 = self.j2-1
for ind_q, q in enumerate(self.q):
y = self.logvalues[ind_q,ind_j1:ind_j2+1]
slope, intercept = self.utils.linear_regression(x, y, nj)
self.zeta[ind_q] = slope
self.intercept[ind_q] = intercept
def plot(self, figlabel_structure = None, figlabel_scaling = None):
"""
Plots the structure functions.
Args:
fignum(int): figure number; NOTE: fignum+1 can also be used to plot the scaling function
"""
if figlabel_structure is None:
figlabel_structure = 'Structure Functions'
if figlabel_scaling is None:
figlabel_scaling = 'Scaling Function'
if len(self.q) > 1:
plot_dim_1 = 4
plot_dim_2 = int(np.ceil(len(self.q) / 4.0))
else:
plot_dim_1 = 1
plot_dim_2 = 1
fig, axes = plt.subplots(plot_dim_1,
plot_dim_2,
num = figlabel_structure,
squeeze = False)
fig.suptitle(self.mrq.name + ' - structure functions log_2[S(j,q)]')
x = self.j
for ind_q, q in enumerate(self.q):
y = self.logvalues[ind_q, :]
ax = axes[ind_q % 4][ind_q // 4]
ax.plot(x, y, 'r--.')
ax.set_xlabel('j')
ax.set_ylabel('q = ' + str(q))
ax.grid()
plt.draw()
if len(self.zeta) > 0:
# plot regression line
x0 = self.j1
x1 = self.j2
slope = self.zeta[ind_q]
intercept = self.intercept[ind_q]
y0 = slope*x0 + intercept
y1 = slope*x1 + intercept
legend = 'slope = '+'%.5f' % (slope)
ax.plot([x0, x1], [y0, y1], color='k',
linestyle='-', linewidth=2, label = legend)
ax.legend()
if len(self.q) > 1:
plt.figure(figlabel_scaling)
plt.plot(self.q, self.zeta, 'k--.')
plt.xlabel('q')
plt.ylabel('zeta(q)')
plt.suptitle(self.mrq.name + ' - scaling function')
plt.grid()
plt.draw() | mfanalysis/structurefunction.py | from __future__ import print_function
from __future__ import unicode_literals
import numpy as np
import matplotlib.pyplot as plt
from .utils import Utils
class StructureFunction:
"""
This class provides methods for computing and analyzing struture functions
Args:
mrq (MultiResolutionQuantity): multiresolution quantity used to compute
the structure function
q (numpy.array) : list of exponents for which to compute the
structure function
j1 (int) : smallest scale analysis
j2 (int) : largest scale analysis
wtype (int) : 0 for ordinary regression, 1 for weighted regression
values (numpy.array) : values[ind_q, ind_j] = values of S(j, q), with q = self.q[ind_q]
and j = self.j[ind_j]
logvalues (numpy.array) : logvalues[ind_q, ind_j] = values of log_2 (S(j, q)),
with q = self.q[ind_q] and j = self.j[ind_j]
"""
def __init__(self, mrq, q, j1, j2, wtype):
self.mrq = mrq
self.q = q
self.j1 = j1
self.j2 = j2
self.j = np.array(list(mrq.values))
self.wtype = wtype
self.values = np.zeros( (len(self.q), len(self.j)) )
self.logvalues = np.zeros( (len(self.q), len(self.j)) )
self.zeta = []
self.utils = Utils() # used for linear regression
self._compute()
self._compute_zeta()
def _compute(self):
for ind_q, q in enumerate(self.q):
for ind_j, j in enumerate(self.j):
c_j = self.mrq.values[j]
s_j_q = np.mean(np.abs(c_j)**q)
self.values[ind_q, ind_j] = s_j_q
self.logvalues = np.log2(self.values)
def _compute_zeta(self):
"""
Compute the value of the scale function zeta(q) for all q
"""
self.zeta = np.zeros(len(self.q))
self.intercept = np.zeros(len(self.q))
x = np.arange(self.j1, self.j2+1)
if self.wtype == 1:
nj = self.mrq.get_nj_interv(self.j1, self.j2)
else:
nj = np.ones(len(x))
ind_j1 = self.j1-1
ind_j2 = self.j2-1
for ind_q, q in enumerate(self.q):
y = self.logvalues[ind_q,ind_j1:ind_j2+1]
slope, intercept = self.utils.linear_regression(x, y, nj)
self.zeta[ind_q] = slope
self.intercept[ind_q] = intercept
def plot(self, figlabel_structure = None, figlabel_scaling = None):
"""
Plots the structure functions.
Args:
fignum(int): figure number; NOTE: fignum+1 can also be used to plot the scaling function
"""
if figlabel_structure is None:
figlabel_structure = 'Structure Functions'
if figlabel_scaling is None:
figlabel_scaling = 'Scaling Function'
if len(self.q) > 1:
plot_dim_1 = 4
plot_dim_2 = int(np.ceil(len(self.q) / 4.0))
else:
plot_dim_1 = 1
plot_dim_2 = 1
fig, axes = plt.subplots(plot_dim_1,
plot_dim_2,
num = figlabel_structure,
squeeze = False)
fig.suptitle(self.mrq.name + ' - structure functions log_2[S(j,q)]')
x = self.j
for ind_q, q in enumerate(self.q):
y = self.logvalues[ind_q, :]
ax = axes[ind_q % 4][ind_q // 4]
ax.plot(x, y, 'r--.')
ax.set_xlabel('j')
ax.set_ylabel('q = ' + str(q))
ax.grid()
plt.draw()
if len(self.zeta) > 0:
# plot regression line
x0 = self.j1
x1 = self.j2
slope = self.zeta[ind_q]
intercept = self.intercept[ind_q]
y0 = slope*x0 + intercept
y1 = slope*x1 + intercept
legend = 'slope = '+'%.5f' % (slope)
ax.plot([x0, x1], [y0, y1], color='k',
linestyle='-', linewidth=2, label = legend)
ax.legend()
if len(self.q) > 1:
plt.figure(figlabel_scaling)
plt.plot(self.q, self.zeta, 'k--.')
plt.xlabel('q')
plt.ylabel('zeta(q)')
plt.suptitle(self.mrq.name + ' - scaling function')
plt.grid()
plt.draw() | 0.773858 | 0.614799 |
import binascii
import codecs
import hashlib
import struct
import abc
import dataclasses
from typing import Dict, Callable, Any, Optional
from keylime import config
from keylime import keylime_logging
from keylime.failure import Failure, Component
logger = keylime_logging.init_logging("ima")
TCG_EVENT_NAME_LEN_MAX = 255
SHA_DIGEST_LEN = 20
MD5_DIGEST_LEN = 16
START_HASH = (codecs.decode(b'0000000000000000000000000000000000000000', 'hex'))
FF_HASH = (codecs.decode(b'ffffffffffffffffffffffffffffffffffffffff', 'hex'))
NULL_BYTE = ord('\0')
COLON_BYTE = ord(':')
@dataclasses.dataclass
class Validator:
functions: Dict[Any, Callable]
def get_validator(self, class_type) -> Callable:
validator = self.functions.get(class_type, None)
if validator is None:
logger.warning(f"No validator was implemented for: {class_type} . Using always false validator!")
failure = Failure(Component.IMA, ["validation"])
failure.add_event("no_validator", f"No validator was implemented for: {class_type} . Using always false validator!", True)
return lambda *_: failure
return validator
class ParserError(TypeError):
"""Is thrown when a type could not be constructed successfully."""
class Mode(abc.ABC):
@abc.abstractmethod
def is_data_valid(self, validator: Validator):
pass
@abc.abstractmethod
def hash(self) -> bytes:
pass
class Type(abc.ABC):
@abc.abstractmethod
def struct(self):
pass
class HexData(Type):
data: bytes
def __init__(self, data: str):
try:
self.data = codecs.decode(data.encode("utf-8"), "hex")
except binascii.Error as e:
raise ParserError(f"Provided data was not valid hex: {data}") from e
def __str__(self):
return self.data.decode("utf-8")
def struct(self):
return struct.pack(f"<I{len(self.data)}s",
len(self.data),
self.data)
class Signature(HexData):
"""
Class for type "sig".
"""
def __init__(self, data: str):
super().__init__(data)
# basic checks on signature
fmt = '>BBBIH'
hdrlen = struct.calcsize(fmt)
if len(self.data) < hdrlen:
raise ParserError("Invalid signature: header too short")
_, _, _, _, sig_size = struct.unpack(fmt, self.data[:hdrlen])
if hdrlen + sig_size != len(self.data):
raise ParserError("Invalid signature: malformed header")
class Buffer(HexData):
"""
Class for type "buf".
"""
class Name(Type):
"""
Class for type "n" and "n-ng".
"""
name: str
legacy: bool = False
def __init__(self, name: str, legacy=False):
self.name = name
self.legacy = legacy
def __str__(self):
return self.name
def struct(self):
# The old "n" option is fixed length.
if self.legacy:
return struct.pack(f"{len(self.name)}sB{TCG_EVENT_NAME_LEN_MAX - len(self.name)}s",
self.name.encode("utf-8"),
NULL_BYTE,
bytearray(TCG_EVENT_NAME_LEN_MAX - len(self.name)))
return struct.pack(f"<I{len(self.name)}sB",
len(self.name) + 1,
self.name.encode("utf-8"),
NULL_BYTE)
class Digest:
"""
Class for types "d" and "d-ng" with and without algorithm
"""
hash: bytes
algorithm: Optional[str] = None
legacy: bool = False
def __init__(self, digest: str, legacy=False):
self.legacy = legacy
tokens = digest.split(":")
if len(tokens) == 1:
try:
self.hash = codecs.decode(tokens[0].encode("utf-8"), "hex")
except binascii.Error as e:
raise ParserError(f"Digest hash is not valid hex. Got: {tokens[0]}") from e
if not (len(self.hash) == SHA_DIGEST_LEN or len(self.hash) == MD5_DIGEST_LEN):
raise ParserError(
"Cannot create Digest. No hash algorithm is provided and hash does not belong to a md5 or sha1 hash.")
elif len(tokens) == 2:
try:
self.hash = codecs.decode(tokens[1].encode("utf-8"), "hex")
except binascii.Error as e:
raise ParserError(f"Digest hash is not valid hex. Got: {tokens[1]}") from e
self.algorithm = tokens[0]
else:
raise ParserError(f"Cannot create Digest expected 1 or 2 tokens got: {len(tokens)} for {digest}")
def struct(self):
# The legacy format "d" has fixed length, so it does not contain a length attribute
if self.legacy:
return struct.pack(f"<{len(self.hash)}s", self.hash)
if self.algorithm is None:
return struct.pack(f"<I{len(self.hash)}s", len(self.hash), self.hash)
# After the ':' must be a '\O':
# https://elixir.bootlin.com/linux/v5.12.10/source/security/integrity/ima/ima_template_lib.c#L230
return struct.pack(f"<I{len(self.algorithm)}sBB{len(self.hash)}s",
len(self.algorithm) + 2 + len(self.hash),
self.algorithm.encode("utf-8"),
COLON_BYTE,
NULL_BYTE,
self.hash)
class Ima(Mode):
"""
Class for "ima". Contains the digest and a path.
"""
digest: Digest
path: Name
def __init__(self, data: str):
tokens = data.split()
if len(tokens) != 2:
raise ParserError()
self.digest = Digest(tokens[0], legacy=True)
self.path = Name(tokens[1], legacy=True)
def hash(self):
tohash = self.digest.struct() + self.path.struct()
return hashlib.sha1(tohash).digest()
def is_data_valid(self, validator: Validator):
return validator.get_validator(type(self))(self.digest, self.path)
class ImaNg(Mode):
"""
Class for "ima-ng". Contains the digest and a path.
"""
digest: Digest
path: Name
def __init__(self, data: str):
tokens = data.split()
if len(tokens) != 2:
raise ParserError(f"Cannot create ImaSig expected 2 tokens got: {len(tokens)}.")
self.digest = Digest(tokens[0])
self.path = Name(tokens[1])
def hash(self):
tohash = self.digest.struct() + self.path.struct()
return hashlib.sha1(tohash).digest()
def is_data_valid(self, validator):
return validator.get_validator(type(self))(self.digest, self.path)
class ImaSig(Mode):
"""
Class for "ima-sig" template. Nearly the same as ImaNg but can contain a optional signature.
"""
digest: Digest
path: Name
signature: Optional[Signature] = None
def __init__(self, data: str):
tokens = data.split(maxsplit=4)
num_tokens = len(tokens)
if num_tokens == 2:
self.digest = Digest(tokens[0])
self.path = Name(tokens[1])
elif num_tokens <= 1:
raise ParserError(f"Cannot create ImaSig expected 2 or 3 tokens got: {len(tokens)}.")
else:
self.digest = Digest(tokens[0])
signature = self.create_Signature(tokens[-1])
if signature:
self.signature = signature
if num_tokens == 3:
self.path = Name(tokens[1])
else:
# first part of data is digest , last is signature, in between is path
self.path = data.split(maxsplit=1)[1].rsplit(maxsplit=1)[0]
else:
# first part is data, last part is path
self.path = data.split(maxsplit=1)[1]
def create_Signature(self, hexstring):
""" Create the Signature object if the hexstring is a valid signature """
try:
return Signature(hexstring)
except ParserError:
pass
return None
def hash(self):
tohash = self.digest.struct() + self.path.struct()
# If no signature is there we sill have to add the entry for it
if self.signature is None:
tohash += struct.pack("<I0s", 0, b'')
else:
tohash += self.signature.struct()
return hashlib.sha1(tohash).digest()
def is_data_valid(self, validator):
return validator.get_validator(type(self))(self.digest, self.path, self.signature)
class ImaBuf(Mode):
"""
Class for "ima-buf". Contains a digest, buffer name and the buffer itself.
For validation the buffer must be done based on the name because IMA only provides it as an byte array.
"""
digest: Digest
name: Name
data: Buffer
def __init__(self, data: str):
tokens = data.split(maxsplit=5)
if len(tokens) != 3:
raise ParserError(f"Cannot create ImaBuf expected 3 tokens got: {len(tokens)}.")
self.digest = Digest(tokens[0])
self.name = Name(tokens[1])
self.data = Buffer(tokens[2])
def hash(self):
tohash = self.digest.struct() + self.name.struct() + self.data.struct()
return hashlib.sha1(tohash).digest()
def is_data_valid(self, validator: Validator):
return validator.get_validator(type(self))(self.digest, self.name, self.data)
class Entry:
"""
IMA Entry. Contains the PCR, template hash and mode.
"""
pcr: str
template_hash: bytes
mode: Mode
validator: Validator
mode_lookup = {
"ima": Ima,
"ima-ng": ImaNg,
"ima-sig": ImaSig,
"ima-buf": ImaBuf
}
def __init__(self, data: str, validator=None):
self.validator = validator
tokens = data.split(maxsplit=3)
if len(tokens) != 4:
raise ParserError(f"Cannot create Entry expected 4 tokens got: {len(tokens)}.")
self.pcr = tokens[0]
try:
self.template_hash = codecs.decode(tokens[1].encode(), "hex")
except binascii.Error as e:
raise ParserError(f"Cannot create Entry expected 4 tokens got: {len(tokens)}.") from e
mode = self.mode_lookup.get(tokens[2], None)
if mode is None:
raise ParserError(f"No parser for mode {tokens[2]} implemented.")
self.mode = mode(tokens[3])
# Set correct hash for time of measure, time of use (ToMToU) errors
# and if a file is already opened for write.
# https://elixir.bootlin.com/linux/v5.12.12/source/security/integrity/ima/ima_main.c#L101
if self.template_hash == START_HASH:
self.template_hash = FF_HASH
def invalid(self):
failure = Failure(Component.IMA, ["validation"])
# Ignore template hash for ToMToU errors
if self.template_hash == FF_HASH:
logger.warning("Skipped template_hash validation entry with FF_HASH")
# By default ToMToU errors are not treated as a failure
if config.getboolean("cloud_verifier", "tomtou_errors", False):
failure.add_event("tomtou", "hash validation was skipped", True)
return failure
if self.template_hash != self.mode.hash():
failure.add_event("ima_hash",
{"message": "IMA hash does not match the calculated hash.",
"expected": self.template_hash, "got": self.mode.hash()}, True)
return failure
if self.validator is None:
failure.add_event("no_validator", "No validator specified", True)
return failure
failure.merge(self.mode.is_data_valid(self.validator))
return failure | keylime/ima_ast.py | import binascii
import codecs
import hashlib
import struct
import abc
import dataclasses
from typing import Dict, Callable, Any, Optional
from keylime import config
from keylime import keylime_logging
from keylime.failure import Failure, Component
logger = keylime_logging.init_logging("ima")
TCG_EVENT_NAME_LEN_MAX = 255
SHA_DIGEST_LEN = 20
MD5_DIGEST_LEN = 16
START_HASH = (codecs.decode(b'0000000000000000000000000000000000000000', 'hex'))
FF_HASH = (codecs.decode(b'ffffffffffffffffffffffffffffffffffffffff', 'hex'))
NULL_BYTE = ord('\0')
COLON_BYTE = ord(':')
@dataclasses.dataclass
class Validator:
functions: Dict[Any, Callable]
def get_validator(self, class_type) -> Callable:
validator = self.functions.get(class_type, None)
if validator is None:
logger.warning(f"No validator was implemented for: {class_type} . Using always false validator!")
failure = Failure(Component.IMA, ["validation"])
failure.add_event("no_validator", f"No validator was implemented for: {class_type} . Using always false validator!", True)
return lambda *_: failure
return validator
class ParserError(TypeError):
"""Is thrown when a type could not be constructed successfully."""
class Mode(abc.ABC):
@abc.abstractmethod
def is_data_valid(self, validator: Validator):
pass
@abc.abstractmethod
def hash(self) -> bytes:
pass
class Type(abc.ABC):
@abc.abstractmethod
def struct(self):
pass
class HexData(Type):
data: bytes
def __init__(self, data: str):
try:
self.data = codecs.decode(data.encode("utf-8"), "hex")
except binascii.Error as e:
raise ParserError(f"Provided data was not valid hex: {data}") from e
def __str__(self):
return self.data.decode("utf-8")
def struct(self):
return struct.pack(f"<I{len(self.data)}s",
len(self.data),
self.data)
class Signature(HexData):
"""
Class for type "sig".
"""
def __init__(self, data: str):
super().__init__(data)
# basic checks on signature
fmt = '>BBBIH'
hdrlen = struct.calcsize(fmt)
if len(self.data) < hdrlen:
raise ParserError("Invalid signature: header too short")
_, _, _, _, sig_size = struct.unpack(fmt, self.data[:hdrlen])
if hdrlen + sig_size != len(self.data):
raise ParserError("Invalid signature: malformed header")
class Buffer(HexData):
"""
Class for type "buf".
"""
class Name(Type):
"""
Class for type "n" and "n-ng".
"""
name: str
legacy: bool = False
def __init__(self, name: str, legacy=False):
self.name = name
self.legacy = legacy
def __str__(self):
return self.name
def struct(self):
# The old "n" option is fixed length.
if self.legacy:
return struct.pack(f"{len(self.name)}sB{TCG_EVENT_NAME_LEN_MAX - len(self.name)}s",
self.name.encode("utf-8"),
NULL_BYTE,
bytearray(TCG_EVENT_NAME_LEN_MAX - len(self.name)))
return struct.pack(f"<I{len(self.name)}sB",
len(self.name) + 1,
self.name.encode("utf-8"),
NULL_BYTE)
class Digest:
"""
Class for types "d" and "d-ng" with and without algorithm
"""
hash: bytes
algorithm: Optional[str] = None
legacy: bool = False
def __init__(self, digest: str, legacy=False):
self.legacy = legacy
tokens = digest.split(":")
if len(tokens) == 1:
try:
self.hash = codecs.decode(tokens[0].encode("utf-8"), "hex")
except binascii.Error as e:
raise ParserError(f"Digest hash is not valid hex. Got: {tokens[0]}") from e
if not (len(self.hash) == SHA_DIGEST_LEN or len(self.hash) == MD5_DIGEST_LEN):
raise ParserError(
"Cannot create Digest. No hash algorithm is provided and hash does not belong to a md5 or sha1 hash.")
elif len(tokens) == 2:
try:
self.hash = codecs.decode(tokens[1].encode("utf-8"), "hex")
except binascii.Error as e:
raise ParserError(f"Digest hash is not valid hex. Got: {tokens[1]}") from e
self.algorithm = tokens[0]
else:
raise ParserError(f"Cannot create Digest expected 1 or 2 tokens got: {len(tokens)} for {digest}")
def struct(self):
# The legacy format "d" has fixed length, so it does not contain a length attribute
if self.legacy:
return struct.pack(f"<{len(self.hash)}s", self.hash)
if self.algorithm is None:
return struct.pack(f"<I{len(self.hash)}s", len(self.hash), self.hash)
# After the ':' must be a '\O':
# https://elixir.bootlin.com/linux/v5.12.10/source/security/integrity/ima/ima_template_lib.c#L230
return struct.pack(f"<I{len(self.algorithm)}sBB{len(self.hash)}s",
len(self.algorithm) + 2 + len(self.hash),
self.algorithm.encode("utf-8"),
COLON_BYTE,
NULL_BYTE,
self.hash)
class Ima(Mode):
"""
Class for "ima". Contains the digest and a path.
"""
digest: Digest
path: Name
def __init__(self, data: str):
tokens = data.split()
if len(tokens) != 2:
raise ParserError()
self.digest = Digest(tokens[0], legacy=True)
self.path = Name(tokens[1], legacy=True)
def hash(self):
tohash = self.digest.struct() + self.path.struct()
return hashlib.sha1(tohash).digest()
def is_data_valid(self, validator: Validator):
return validator.get_validator(type(self))(self.digest, self.path)
class ImaNg(Mode):
"""
Class for "ima-ng". Contains the digest and a path.
"""
digest: Digest
path: Name
def __init__(self, data: str):
tokens = data.split()
if len(tokens) != 2:
raise ParserError(f"Cannot create ImaSig expected 2 tokens got: {len(tokens)}.")
self.digest = Digest(tokens[0])
self.path = Name(tokens[1])
def hash(self):
tohash = self.digest.struct() + self.path.struct()
return hashlib.sha1(tohash).digest()
def is_data_valid(self, validator):
return validator.get_validator(type(self))(self.digest, self.path)
class ImaSig(Mode):
"""
Class for "ima-sig" template. Nearly the same as ImaNg but can contain a optional signature.
"""
digest: Digest
path: Name
signature: Optional[Signature] = None
def __init__(self, data: str):
tokens = data.split(maxsplit=4)
num_tokens = len(tokens)
if num_tokens == 2:
self.digest = Digest(tokens[0])
self.path = Name(tokens[1])
elif num_tokens <= 1:
raise ParserError(f"Cannot create ImaSig expected 2 or 3 tokens got: {len(tokens)}.")
else:
self.digest = Digest(tokens[0])
signature = self.create_Signature(tokens[-1])
if signature:
self.signature = signature
if num_tokens == 3:
self.path = Name(tokens[1])
else:
# first part of data is digest , last is signature, in between is path
self.path = data.split(maxsplit=1)[1].rsplit(maxsplit=1)[0]
else:
# first part is data, last part is path
self.path = data.split(maxsplit=1)[1]
def create_Signature(self, hexstring):
""" Create the Signature object if the hexstring is a valid signature """
try:
return Signature(hexstring)
except ParserError:
pass
return None
def hash(self):
tohash = self.digest.struct() + self.path.struct()
# If no signature is there we sill have to add the entry for it
if self.signature is None:
tohash += struct.pack("<I0s", 0, b'')
else:
tohash += self.signature.struct()
return hashlib.sha1(tohash).digest()
def is_data_valid(self, validator):
return validator.get_validator(type(self))(self.digest, self.path, self.signature)
class ImaBuf(Mode):
"""
Class for "ima-buf". Contains a digest, buffer name and the buffer itself.
For validation the buffer must be done based on the name because IMA only provides it as an byte array.
"""
digest: Digest
name: Name
data: Buffer
def __init__(self, data: str):
tokens = data.split(maxsplit=5)
if len(tokens) != 3:
raise ParserError(f"Cannot create ImaBuf expected 3 tokens got: {len(tokens)}.")
self.digest = Digest(tokens[0])
self.name = Name(tokens[1])
self.data = Buffer(tokens[2])
def hash(self):
tohash = self.digest.struct() + self.name.struct() + self.data.struct()
return hashlib.sha1(tohash).digest()
def is_data_valid(self, validator: Validator):
return validator.get_validator(type(self))(self.digest, self.name, self.data)
class Entry:
"""
IMA Entry. Contains the PCR, template hash and mode.
"""
pcr: str
template_hash: bytes
mode: Mode
validator: Validator
mode_lookup = {
"ima": Ima,
"ima-ng": ImaNg,
"ima-sig": ImaSig,
"ima-buf": ImaBuf
}
def __init__(self, data: str, validator=None):
self.validator = validator
tokens = data.split(maxsplit=3)
if len(tokens) != 4:
raise ParserError(f"Cannot create Entry expected 4 tokens got: {len(tokens)}.")
self.pcr = tokens[0]
try:
self.template_hash = codecs.decode(tokens[1].encode(), "hex")
except binascii.Error as e:
raise ParserError(f"Cannot create Entry expected 4 tokens got: {len(tokens)}.") from e
mode = self.mode_lookup.get(tokens[2], None)
if mode is None:
raise ParserError(f"No parser for mode {tokens[2]} implemented.")
self.mode = mode(tokens[3])
# Set correct hash for time of measure, time of use (ToMToU) errors
# and if a file is already opened for write.
# https://elixir.bootlin.com/linux/v5.12.12/source/security/integrity/ima/ima_main.c#L101
if self.template_hash == START_HASH:
self.template_hash = FF_HASH
def invalid(self):
failure = Failure(Component.IMA, ["validation"])
# Ignore template hash for ToMToU errors
if self.template_hash == FF_HASH:
logger.warning("Skipped template_hash validation entry with FF_HASH")
# By default ToMToU errors are not treated as a failure
if config.getboolean("cloud_verifier", "tomtou_errors", False):
failure.add_event("tomtou", "hash validation was skipped", True)
return failure
if self.template_hash != self.mode.hash():
failure.add_event("ima_hash",
{"message": "IMA hash does not match the calculated hash.",
"expected": self.template_hash, "got": self.mode.hash()}, True)
return failure
if self.validator is None:
failure.add_event("no_validator", "No validator specified", True)
return failure
failure.merge(self.mode.is_data_valid(self.validator))
return failure | 0.797872 | 0.207074 |
import colorsys
import sys
# Color scheme formula:
# dictionary of all the keys found in the color.conf file, with as value
# a tuple of hue, saturation, and value adjustments
recipe1 = {
"dmenu color": {
"c_m_normal_bg": (0, -0.5, -0.7),
"c_m_normal_fg": (0, -0.8, 0),
"c_m_selected_bg": (0, -0.3, 1),
"c_m_selected_fg": (0, -1, -1),
},
"window colors": {
"c_c_focus_active_border": (0, -0.1, -0.1),
"c_c_focus_active_bg": (0, -0.1, -0.1),
"c_c_focus_active_text": (0, -1, -1),
"c_c_focus_active_indic": (0, -1, 0),
"c_c_focus_inactive_border": (0, -0.4, -0.4),
"c_c_focus_inactive_bg": (0, -0.5, -0.5),
"c_c_focus_inactive_text": (0, -0.6, 0),
"c_c_focus_inactive_indic": (0, -0.559, 0.212),
"c_c_focused_border": (0, -0.6, -0.6),
"c_c_focused_bg": (0, -0.7, -0.7),
"c_c_focused_text": (0, -0.8, -0.4),
"c_c_focused_indic": (0, -0.5, -0.4),
"c_c_urgent_border": (-0.5, 0.062, 0.169),
"c_c_urgent_bg": (-0.5, 0.062, 0.169),
"c_c_urgent_text": (-0.5, -0.590, 0.639),
"c_c_urgent_indic": (-0.5, -0.205, 0.412),
"c_c_placeholder_border": (0, -0.641, -0.361),
"c_c_placeholder_bg": (0, -0.641, -0.314),
"c_c_placeholder_text": (0, -0.641, 0.639),
"c_c_placeholder_indic": (0, -0.641, -0.361),
"c_c_bg": (0, 0.287, -0.196),
},
"bar colors": {
"c_b_bg": (0, -0.4, -0.9),
"c_b_status_text": (0, -0.9, 0.8),
"c_b_separator": (0, -0.5, -0.5),
"c_b_focused_ws_border": (0, -0.1, -0.1),
"c_b_focused_ws_bg": (0, -0.1, -0.1),
"c_b_focused_ws_text": (0, -1, -1),
"c_b_active_ws_border": (0, -0.5, -0.5),
"c_b_active_ws_bg": (0, -0.6, -0.6),
"c_b_active_ws_text": (0, -1, 1),
"c_b_inactive_ws_border": (0, -0.8, -0.7),
"c_b_inactive_ws_bg": (0, -0.8, -0.8),
"c_b_inactive_ws_text": (0, -0.9, -0.3),
"c_b_urgent_ws_border": (-0.5, 0, 0),
"c_b_urgent_ws_bg": (-0.5, 0, -0.2),
"c_b_urgent_ws_text": (-0.5, -0.8, 1),
"c_b_binding_mode_border": (-0.5, 0, 0),
"c_b_binding_mode_bg": (-0.5, 0, -0.2),
"c_b_binding_mode_text": (-0.5, -0.8, 1),
}
}
def main():
if len(sys.argv) < 2:
print("Please provide a hex color to start from.")
exit(1)
base_color = sys.argv[1]
# Trim leading '#'
if base_color[0] == '#': base_color = base_color[1:]
try:
hex_to_rgb(base_color)
except ValueError:
print(f"Invalid base hex color #{base_color}")
exit(1)
base_color = normalize_color(base_color)
if len(sys.argv) == 2:
scheme = generate_scheme(base_color, recipe1)
for l in scheme: print(l)
elif sys.argv[2] == "reverse":
if len(sys.argv) < 4:
print("Please provide a filename with a colorscheme to reverse")
exit(1)
filename = sys.argv[3]
reverse_scheme = reverse_engineer_scheme(base_color, filename)
for l in reverse_scheme: print(l)
def get_longest_color_name(recipe):
longest_name_len = 1
for r_name, s_recipe in recipe.items():
local_longest = max([len(n) for n in s_recipe.keys()])
if local_longest > longest_name_len:
longest_name_len = local_longest
return longest_name_len
def generate_scheme(base_hex_color, recipe):
file_header = "# Colors "
line_length = 79
longest_name_len = get_longest_color_name(recipe)
scheme_lines = [
f"{file_header:-<{line_length}}",
"",
f"# This scheme was generated with #{base_hex_color} as a base color.",
""
]
for section_heading, sub_recipe in recipe.items():
scheme_lines.append(f"# {section_heading}")
scheme_lines.extend(
generate_sub_scheme(
base_hex_color, sub_recipe, longest_name_len))
scheme_lines.append("")
return scheme_lines
def generate_sub_scheme(base_hex_color, sub_recipe, longest_name_len):
base_hsv = hex_to_hsv(base_hex_color)
scheme_list = []
for color_name, adjustments in sub_recipe.items():
new_color = hsv_to_hex(*adjust_hsv(*base_hsv, *adjustments))
scheme_list.append(
"set " \
f"${color_name: <{longest_name_len}} "
f"{new_color}")
return scheme_list
def reverse_engineer_scheme(base_hex_color, filename):
lines = []
with open(filename) as f: lines = f.readlines()
lines = [l.strip() for l in lines]
base_h, base_s, base_v = hex_to_hsv(base_hex_color)
named_hex_colors = {}
adjustments = []
for l in lines:
if not l.startswith("set $"): continue
name = l[5:-6].strip()
hex_color = l[-6:]
named_hex_colors[name] = hex_color
for n, hex_color in named_hex_colors.items():
h, s, v = hex_to_hsv(hex_color)
adjustments.append(
f"\"${n}\": ("
f"{(h - base_h):.3f}, "
f"{(s - base_s):.3f}, "
f"{(v - base_v):.3f}),")
return adjustments
def normalize_color(hex_color):
h, s, v = hex_to_hsv(hex_color)
return hsv_to_hex(h, 1.0 if s > 0 else 0, 1.0)
def adjust_hsv(h, s, v, h_adj, s_adj, v_adj):
h += h_adj
# If it's over or under, wrap around
h = h if h >= 0 else 1 - (abs(h) % 1)
h = h if h <= 1 else h % 1
s += s_adj
# Clip to 0..1.0
s = s if s >= 0 else 0
s = s if s <= 1.0 else 1.0
v += v_adj
# Clip to 0..1.0
v = v if v >= 0 else 0
v = v if v <= 1.0 else 1.0
return h, s, v
def hex_to_rgb(hex_color):
return int(hex_color[0:2], 16) / 255.0,\
int(hex_color[2:4], 16) / 255.0,\
int(hex_color[4:6], 16) / 255.0
def rgb_to_hex(r, g, b):
return f"{hex(int(r * 255))[2:].upper():0>2}" \
f"{hex(int(g * 255))[2:].upper():0>2}" \
f"{hex(int(b * 255))[2:].upper():0>2}"
def hex_to_hsv(hex_color):
return colorsys.rgb_to_hsv(*hex_to_rgb(hex_color))
def hsv_to_hex(h, s, v):
return rgb_to_hex(*colorsys.hsv_to_rgb(h, s, v))
main() | .config/i3/config.d/available/colorgen.py |
import colorsys
import sys
# Color scheme formula:
# dictionary of all the keys found in the color.conf file, with as value
# a tuple of hue, saturation, and value adjustments
recipe1 = {
"dmenu color": {
"c_m_normal_bg": (0, -0.5, -0.7),
"c_m_normal_fg": (0, -0.8, 0),
"c_m_selected_bg": (0, -0.3, 1),
"c_m_selected_fg": (0, -1, -1),
},
"window colors": {
"c_c_focus_active_border": (0, -0.1, -0.1),
"c_c_focus_active_bg": (0, -0.1, -0.1),
"c_c_focus_active_text": (0, -1, -1),
"c_c_focus_active_indic": (0, -1, 0),
"c_c_focus_inactive_border": (0, -0.4, -0.4),
"c_c_focus_inactive_bg": (0, -0.5, -0.5),
"c_c_focus_inactive_text": (0, -0.6, 0),
"c_c_focus_inactive_indic": (0, -0.559, 0.212),
"c_c_focused_border": (0, -0.6, -0.6),
"c_c_focused_bg": (0, -0.7, -0.7),
"c_c_focused_text": (0, -0.8, -0.4),
"c_c_focused_indic": (0, -0.5, -0.4),
"c_c_urgent_border": (-0.5, 0.062, 0.169),
"c_c_urgent_bg": (-0.5, 0.062, 0.169),
"c_c_urgent_text": (-0.5, -0.590, 0.639),
"c_c_urgent_indic": (-0.5, -0.205, 0.412),
"c_c_placeholder_border": (0, -0.641, -0.361),
"c_c_placeholder_bg": (0, -0.641, -0.314),
"c_c_placeholder_text": (0, -0.641, 0.639),
"c_c_placeholder_indic": (0, -0.641, -0.361),
"c_c_bg": (0, 0.287, -0.196),
},
"bar colors": {
"c_b_bg": (0, -0.4, -0.9),
"c_b_status_text": (0, -0.9, 0.8),
"c_b_separator": (0, -0.5, -0.5),
"c_b_focused_ws_border": (0, -0.1, -0.1),
"c_b_focused_ws_bg": (0, -0.1, -0.1),
"c_b_focused_ws_text": (0, -1, -1),
"c_b_active_ws_border": (0, -0.5, -0.5),
"c_b_active_ws_bg": (0, -0.6, -0.6),
"c_b_active_ws_text": (0, -1, 1),
"c_b_inactive_ws_border": (0, -0.8, -0.7),
"c_b_inactive_ws_bg": (0, -0.8, -0.8),
"c_b_inactive_ws_text": (0, -0.9, -0.3),
"c_b_urgent_ws_border": (-0.5, 0, 0),
"c_b_urgent_ws_bg": (-0.5, 0, -0.2),
"c_b_urgent_ws_text": (-0.5, -0.8, 1),
"c_b_binding_mode_border": (-0.5, 0, 0),
"c_b_binding_mode_bg": (-0.5, 0, -0.2),
"c_b_binding_mode_text": (-0.5, -0.8, 1),
}
}
def main():
if len(sys.argv) < 2:
print("Please provide a hex color to start from.")
exit(1)
base_color = sys.argv[1]
# Trim leading '#'
if base_color[0] == '#': base_color = base_color[1:]
try:
hex_to_rgb(base_color)
except ValueError:
print(f"Invalid base hex color #{base_color}")
exit(1)
base_color = normalize_color(base_color)
if len(sys.argv) == 2:
scheme = generate_scheme(base_color, recipe1)
for l in scheme: print(l)
elif sys.argv[2] == "reverse":
if len(sys.argv) < 4:
print("Please provide a filename with a colorscheme to reverse")
exit(1)
filename = sys.argv[3]
reverse_scheme = reverse_engineer_scheme(base_color, filename)
for l in reverse_scheme: print(l)
def get_longest_color_name(recipe):
longest_name_len = 1
for r_name, s_recipe in recipe.items():
local_longest = max([len(n) for n in s_recipe.keys()])
if local_longest > longest_name_len:
longest_name_len = local_longest
return longest_name_len
def generate_scheme(base_hex_color, recipe):
file_header = "# Colors "
line_length = 79
longest_name_len = get_longest_color_name(recipe)
scheme_lines = [
f"{file_header:-<{line_length}}",
"",
f"# This scheme was generated with #{base_hex_color} as a base color.",
""
]
for section_heading, sub_recipe in recipe.items():
scheme_lines.append(f"# {section_heading}")
scheme_lines.extend(
generate_sub_scheme(
base_hex_color, sub_recipe, longest_name_len))
scheme_lines.append("")
return scheme_lines
def generate_sub_scheme(base_hex_color, sub_recipe, longest_name_len):
base_hsv = hex_to_hsv(base_hex_color)
scheme_list = []
for color_name, adjustments in sub_recipe.items():
new_color = hsv_to_hex(*adjust_hsv(*base_hsv, *adjustments))
scheme_list.append(
"set " \
f"${color_name: <{longest_name_len}} "
f"{new_color}")
return scheme_list
def reverse_engineer_scheme(base_hex_color, filename):
lines = []
with open(filename) as f: lines = f.readlines()
lines = [l.strip() for l in lines]
base_h, base_s, base_v = hex_to_hsv(base_hex_color)
named_hex_colors = {}
adjustments = []
for l in lines:
if not l.startswith("set $"): continue
name = l[5:-6].strip()
hex_color = l[-6:]
named_hex_colors[name] = hex_color
for n, hex_color in named_hex_colors.items():
h, s, v = hex_to_hsv(hex_color)
adjustments.append(
f"\"${n}\": ("
f"{(h - base_h):.3f}, "
f"{(s - base_s):.3f}, "
f"{(v - base_v):.3f}),")
return adjustments
def normalize_color(hex_color):
h, s, v = hex_to_hsv(hex_color)
return hsv_to_hex(h, 1.0 if s > 0 else 0, 1.0)
def adjust_hsv(h, s, v, h_adj, s_adj, v_adj):
h += h_adj
# If it's over or under, wrap around
h = h if h >= 0 else 1 - (abs(h) % 1)
h = h if h <= 1 else h % 1
s += s_adj
# Clip to 0..1.0
s = s if s >= 0 else 0
s = s if s <= 1.0 else 1.0
v += v_adj
# Clip to 0..1.0
v = v if v >= 0 else 0
v = v if v <= 1.0 else 1.0
return h, s, v
def hex_to_rgb(hex_color):
return int(hex_color[0:2], 16) / 255.0,\
int(hex_color[2:4], 16) / 255.0,\
int(hex_color[4:6], 16) / 255.0
def rgb_to_hex(r, g, b):
return f"{hex(int(r * 255))[2:].upper():0>2}" \
f"{hex(int(g * 255))[2:].upper():0>2}" \
f"{hex(int(b * 255))[2:].upper():0>2}"
def hex_to_hsv(hex_color):
return colorsys.rgb_to_hsv(*hex_to_rgb(hex_color))
def hsv_to_hex(h, s, v):
return rgb_to_hex(*colorsys.hsv_to_rgb(h, s, v))
main() | 0.345436 | 0.214136 |
import signal
import sys
import unittest
import warnings
from unittest import mock
import asyncio
from asyncio import base_subprocess
from asyncio import subprocess
from test.test_asyncio import utils as test_utils
from test import support
if sys.platform != 'win32':
from asyncio import unix_events
# Program blocking
PROGRAM_BLOCKED = [sys.executable, '-c', 'import time; time.sleep(3600)']
# Program copying input to output
PROGRAM_CAT = [
sys.executable, '-c',
';'.join(('import sys',
'data = sys.stdin.buffer.read()',
'sys.stdout.buffer.write(data)'))]
class TestSubprocessTransport(base_subprocess.BaseSubprocessTransport):
def _start(self, *args, **kwargs):
self._proc = mock.Mock()
self._proc.stdin = None
self._proc.stdout = None
self._proc.stderr = None
self._proc.pid = -1
class SubprocessTransportTests(test_utils.TestCase):
def setUp(self):
super().setUp()
self.loop = self.new_test_loop()
self.set_event_loop(self.loop)
def create_transport(self, waiter=None):
protocol = mock.Mock()
protocol.connection_made._is_coroutine = False
protocol.process_exited._is_coroutine = False
transport = TestSubprocessTransport(
self.loop, protocol, ['test'], False,
None, None, None, 0, waiter=waiter)
return (transport, protocol)
def test_proc_exited(self):
waiter = asyncio.Future(loop=self.loop)
transport, protocol = self.create_transport(waiter)
transport._process_exited(6)
self.loop.run_until_complete(waiter)
self.assertEqual(transport.get_returncode(), 6)
self.assertTrue(protocol.connection_made.called)
self.assertTrue(protocol.process_exited.called)
self.assertTrue(protocol.connection_lost.called)
self.assertEqual(protocol.connection_lost.call_args[0], (None,))
self.assertFalse(transport.is_closing())
self.assertIsNone(transport._loop)
self.assertIsNone(transport._proc)
self.assertIsNone(transport._protocol)
# methods must raise ProcessLookupError if the process exited
self.assertRaises(ProcessLookupError,
transport.send_signal, signal.SIGTERM)
self.assertRaises(ProcessLookupError, transport.terminate)
self.assertRaises(ProcessLookupError, transport.kill)
transport.close()
def test_subprocess_repr(self):
waiter = asyncio.Future(loop=self.loop)
transport, protocol = self.create_transport(waiter)
transport._process_exited(6)
self.loop.run_until_complete(waiter)
self.assertEqual(
repr(transport),
"<TestSubprocessTransport pid=-1 returncode=6>"
)
transport._returncode = None
self.assertEqual(
repr(transport),
"<TestSubprocessTransport pid=-1 running>"
)
transport._pid = None
transport._returncode = None
self.assertEqual(
repr(transport),
"<TestSubprocessTransport not started>"
)
transport.close()
class SubprocessMixin:
def test_stdin_stdout(self):
args = PROGRAM_CAT
async def run(data):
proc = await asyncio.create_subprocess_exec(
*args,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
loop=self.loop)
# feed data
proc.stdin.write(data)
await proc.stdin.drain()
proc.stdin.close()
# get output and exitcode
data = await proc.stdout.read()
exitcode = await proc.wait()
return (exitcode, data)
task = run(b'some data')
task = asyncio.wait_for(task, 60.0, loop=self.loop)
exitcode, stdout = self.loop.run_until_complete(task)
self.assertEqual(exitcode, 0)
self.assertEqual(stdout, b'some data')
def test_communicate(self):
args = PROGRAM_CAT
async def run(data):
proc = await asyncio.create_subprocess_exec(
*args,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
loop=self.loop)
stdout, stderr = await proc.communicate(data)
return proc.returncode, stdout
task = run(b'some data')
task = asyncio.wait_for(task, 60.0, loop=self.loop)
exitcode, stdout = self.loop.run_until_complete(task)
self.assertEqual(exitcode, 0)
self.assertEqual(stdout, b'some data')
def test_shell(self):
create = asyncio.create_subprocess_shell('exit 7',
loop=self.loop)
proc = self.loop.run_until_complete(create)
exitcode = self.loop.run_until_complete(proc.wait())
self.assertEqual(exitcode, 7)
def test_start_new_session(self):
# start the new process in a new session
create = asyncio.create_subprocess_shell('exit 8',
start_new_session=True,
loop=self.loop)
proc = self.loop.run_until_complete(create)
exitcode = self.loop.run_until_complete(proc.wait())
self.assertEqual(exitcode, 8)
def test_kill(self):
args = PROGRAM_BLOCKED
create = asyncio.create_subprocess_exec(*args, loop=self.loop)
proc = self.loop.run_until_complete(create)
proc.kill()
returncode = self.loop.run_until_complete(proc.wait())
if sys.platform == 'win32':
self.assertIsInstance(returncode, int)
# expect 1 but sometimes get 0
else:
self.assertEqual(-signal.SIGKILL, returncode)
def test_terminate(self):
args = PROGRAM_BLOCKED
create = asyncio.create_subprocess_exec(*args, loop=self.loop)
proc = self.loop.run_until_complete(create)
proc.terminate()
returncode = self.loop.run_until_complete(proc.wait())
if sys.platform == 'win32':
self.assertIsInstance(returncode, int)
# expect 1 but sometimes get 0
else:
self.assertEqual(-signal.SIGTERM, returncode)
@unittest.skipIf(sys.platform == 'win32', "Don't have SIGHUP")
def test_send_signal(self):
# bpo-31034: Make sure that we get the default signal handler (killing
# the process). The parent process may have decided to ignore SIGHUP,
# and signal handlers are inherited.
old_handler = signal.signal(signal.SIGHUP, signal.SIG_DFL)
try:
code = 'import time; print("sleeping", flush=True); time.sleep(3600)'
args = [sys.executable, '-c', code]
create = asyncio.create_subprocess_exec(*args,
stdout=subprocess.PIPE,
loop=self.loop)
proc = self.loop.run_until_complete(create)
async def send_signal(proc):
# basic synchronization to wait until the program is sleeping
line = await proc.stdout.readline()
self.assertEqual(line, b'sleeping\n')
proc.send_signal(signal.SIGHUP)
returncode = await proc.wait()
return returncode
returncode = self.loop.run_until_complete(send_signal(proc))
self.assertEqual(-signal.SIGHUP, returncode)
finally:
signal.signal(signal.SIGHUP, old_handler)
def prepare_broken_pipe_test(self):
# buffer large enough to feed the whole pipe buffer
large_data = b'x' * support.PIPE_MAX_SIZE
# the program ends before the stdin can be feeded
create = asyncio.create_subprocess_exec(
sys.executable, '-c', 'pass',
stdin=subprocess.PIPE,
loop=self.loop)
proc = self.loop.run_until_complete(create)
return (proc, large_data)
def test_stdin_broken_pipe(self):
proc, large_data = self.prepare_broken_pipe_test()
async def write_stdin(proc, data):
await asyncio.sleep(0.5, loop=self.loop)
proc.stdin.write(data)
await proc.stdin.drain()
coro = write_stdin(proc, large_data)
# drain() must raise BrokenPipeError or ConnectionResetError
with test_utils.disable_logger():
self.assertRaises((BrokenPipeError, ConnectionResetError),
self.loop.run_until_complete, coro)
self.loop.run_until_complete(proc.wait())
def test_communicate_ignore_broken_pipe(self):
proc, large_data = self.prepare_broken_pipe_test()
# communicate() must ignore BrokenPipeError when feeding stdin
with test_utils.disable_logger():
self.loop.run_until_complete(proc.communicate(large_data))
self.loop.run_until_complete(proc.wait())
def test_pause_reading(self):
limit = 10
size = (limit * 2 + 1)
async def test_pause_reading():
code = '\n'.join((
'import sys',
'sys.stdout.write("x" * %s)' % size,
'sys.stdout.flush()',
))
connect_read_pipe = self.loop.connect_read_pipe
async def connect_read_pipe_mock(*args, **kw):
transport, protocol = await connect_read_pipe(*args, **kw)
transport.pause_reading = mock.Mock()
transport.resume_reading = mock.Mock()
return (transport, protocol)
self.loop.connect_read_pipe = connect_read_pipe_mock
proc = await asyncio.create_subprocess_exec(
sys.executable, '-c', code,
stdin=asyncio.subprocess.PIPE,
stdout=asyncio.subprocess.PIPE,
limit=limit,
loop=self.loop)
stdout_transport = proc._transport.get_pipe_transport(1)
stdout, stderr = await proc.communicate()
# The child process produced more than limit bytes of output,
# the stream reader transport should pause the protocol to not
# allocate too much memory.
return (stdout, stdout_transport)
# Issue #22685: Ensure that the stream reader pauses the protocol
# when the child process produces too much data
stdout, transport = self.loop.run_until_complete(test_pause_reading())
self.assertEqual(stdout, b'x' * size)
self.assertTrue(transport.pause_reading.called)
self.assertTrue(transport.resume_reading.called)
def test_stdin_not_inheritable(self):
# asyncio issue #209: stdin must not be inheritable, otherwise
# the Process.communicate() hangs
async def len_message(message):
code = 'import sys; data = sys.stdin.read(); print(len(data))'
proc = await asyncio.create_subprocess_exec(
sys.executable, '-c', code,
stdin=asyncio.subprocess.PIPE,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
close_fds=False,
loop=self.loop)
stdout, stderr = await proc.communicate(message)
exitcode = await proc.wait()
return (stdout, exitcode)
output, exitcode = self.loop.run_until_complete(len_message(b'abc'))
self.assertEqual(output.rstrip(), b'3')
self.assertEqual(exitcode, 0)
def test_empty_input(self):
async def empty_input():
code = 'import sys; data = sys.stdin.read(); print(len(data))'
proc = await asyncio.create_subprocess_exec(
sys.executable, '-c', code,
stdin=asyncio.subprocess.PIPE,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
close_fds=False,
loop=self.loop)
stdout, stderr = await proc.communicate(b'')
exitcode = await proc.wait()
return (stdout, exitcode)
output, exitcode = self.loop.run_until_complete(empty_input())
self.assertEqual(output.rstrip(), b'0')
self.assertEqual(exitcode, 0)
def test_cancel_process_wait(self):
# Issue #23140: cancel Process.wait()
async def cancel_wait():
proc = await asyncio.create_subprocess_exec(
*PROGRAM_BLOCKED,
loop=self.loop)
# Create an internal future waiting on the process exit
task = self.loop.create_task(proc.wait())
self.loop.call_soon(task.cancel)
try:
await task
except asyncio.CancelledError:
pass
# Cancel the future
task.cancel()
# Kill the process and wait until it is done
proc.kill()
await proc.wait()
self.loop.run_until_complete(cancel_wait())
def test_cancel_make_subprocess_transport_exec(self):
async def cancel_make_transport():
coro = asyncio.create_subprocess_exec(*PROGRAM_BLOCKED,
loop=self.loop)
task = self.loop.create_task(coro)
self.loop.call_soon(task.cancel)
try:
await task
except asyncio.CancelledError:
pass
# ignore the log:
# "Exception during subprocess creation, kill the subprocess"
with test_utils.disable_logger():
self.loop.run_until_complete(cancel_make_transport())
def test_cancel_post_init(self):
async def cancel_make_transport():
coro = self.loop.subprocess_exec(asyncio.SubprocessProtocol,
*PROGRAM_BLOCKED)
task = self.loop.create_task(coro)
self.loop.call_soon(task.cancel)
try:
await task
except asyncio.CancelledError:
pass
# ignore the log:
# "Exception during subprocess creation, kill the subprocess"
with test_utils.disable_logger():
self.loop.run_until_complete(cancel_make_transport())
test_utils.run_briefly(self.loop)
def test_close_kill_running(self):
async def kill_running():
create = self.loop.subprocess_exec(asyncio.SubprocessProtocol,
*PROGRAM_BLOCKED)
transport, protocol = await create
kill_called = False
def kill():
nonlocal kill_called
kill_called = True
orig_kill()
proc = transport.get_extra_info('subprocess')
orig_kill = proc.kill
proc.kill = kill
returncode = transport.get_returncode()
transport.close()
await transport._wait()
return (returncode, kill_called)
# Ignore "Close running child process: kill ..." log
with test_utils.disable_logger():
returncode, killed = self.loop.run_until_complete(kill_running())
self.assertIsNone(returncode)
# transport.close() must kill the process if it is still running
self.assertTrue(killed)
test_utils.run_briefly(self.loop)
def test_close_dont_kill_finished(self):
async def kill_running():
create = self.loop.subprocess_exec(asyncio.SubprocessProtocol,
*PROGRAM_BLOCKED)
transport, protocol = await create
proc = transport.get_extra_info('subprocess')
# kill the process (but asyncio is not notified immediately)
proc.kill()
proc.wait()
proc.kill = mock.Mock()
proc_returncode = proc.poll()
transport_returncode = transport.get_returncode()
transport.close()
return (proc_returncode, transport_returncode, proc.kill.called)
# Ignore "Unknown child process pid ..." log of SafeChildWatcher,
# emitted because the test already consumes the exit status:
# proc.wait()
with test_utils.disable_logger():
result = self.loop.run_until_complete(kill_running())
test_utils.run_briefly(self.loop)
proc_returncode, transport_return_code, killed = result
self.assertIsNotNone(proc_returncode)
self.assertIsNone(transport_return_code)
# transport.close() must not kill the process if it finished, even if
# the transport was not notified yet
self.assertFalse(killed)
# Unlike SafeChildWatcher, FastChildWatcher does not pop the
# callbacks if waitpid() is called elsewhere. Let's clear them
# manually to avoid a warning when the watcher is detached.
if (sys.platform != 'win32' and
isinstance(self, SubprocessFastWatcherTests)):
asyncio.get_child_watcher()._callbacks.clear()
def _test_popen_error(self, stdin):
if sys.platform == 'win32':
target = 'asyncio.windows_utils.Popen'
else:
target = 'subprocess.Popen'
with mock.patch(target) as popen:
exc = ZeroDivisionError
popen.side_effect = exc
create = asyncio.create_subprocess_exec(sys.executable, '-c',
'pass', stdin=stdin,
loop=self.loop)
with warnings.catch_warnings(record=True) as warns:
with self.assertRaises(exc):
self.loop.run_until_complete(create)
self.assertEqual(warns, [])
def test_popen_error(self):
# Issue #24763: check that the subprocess transport is closed
# when BaseSubprocessTransport fails
self._test_popen_error(stdin=None)
def test_popen_error_with_stdin_pipe(self):
# Issue #35721: check that newly created socket pair is closed when
# Popen fails
self._test_popen_error(stdin=subprocess.PIPE)
def test_read_stdout_after_process_exit(self):
async def execute():
code = '\n'.join(['import sys',
'for _ in range(64):',
' sys.stdout.write("x" * 4096)',
'sys.stdout.flush()',
'sys.exit(1)'])
fut = asyncio.create_subprocess_exec(
sys.executable, '-c', code,
stdout=asyncio.subprocess.PIPE,
loop=self.loop)
process = await fut
while True:
data = await process.stdout.read(65536)
if data:
await asyncio.sleep(0.3, loop=self.loop)
else:
break
self.loop.run_until_complete(execute())
if sys.platform != 'win32':
# Unix
class SubprocessWatcherMixin(SubprocessMixin):
Watcher = None
def setUp(self):
super().setUp()
policy = asyncio.get_event_loop_policy()
self.loop = policy.new_event_loop()
self.set_event_loop(self.loop)
watcher = self.Watcher()
watcher.attach_loop(self.loop)
policy.set_child_watcher(watcher)
self.addCleanup(policy.set_child_watcher, None)
class SubprocessSafeWatcherTests(SubprocessWatcherMixin,
test_utils.TestCase):
Watcher = unix_events.SafeChildWatcher
class SubprocessFastWatcherTests(SubprocessWatcherMixin,
test_utils.TestCase):
Watcher = unix_events.FastChildWatcher
else:
# Windows
class SubprocessProactorTests(SubprocessMixin, test_utils.TestCase):
def setUp(self):
super().setUp()
self.loop = asyncio.ProactorEventLoop()
self.set_event_loop(self.loop)
if __name__ == '__main__':
unittest.main() | toolchain/riscv/MSYS/python/Lib/test/test_asyncio/test_subprocess.py | import signal
import sys
import unittest
import warnings
from unittest import mock
import asyncio
from asyncio import base_subprocess
from asyncio import subprocess
from test.test_asyncio import utils as test_utils
from test import support
if sys.platform != 'win32':
from asyncio import unix_events
# Program blocking
PROGRAM_BLOCKED = [sys.executable, '-c', 'import time; time.sleep(3600)']
# Program copying input to output
PROGRAM_CAT = [
sys.executable, '-c',
';'.join(('import sys',
'data = sys.stdin.buffer.read()',
'sys.stdout.buffer.write(data)'))]
class TestSubprocessTransport(base_subprocess.BaseSubprocessTransport):
def _start(self, *args, **kwargs):
self._proc = mock.Mock()
self._proc.stdin = None
self._proc.stdout = None
self._proc.stderr = None
self._proc.pid = -1
class SubprocessTransportTests(test_utils.TestCase):
def setUp(self):
super().setUp()
self.loop = self.new_test_loop()
self.set_event_loop(self.loop)
def create_transport(self, waiter=None):
protocol = mock.Mock()
protocol.connection_made._is_coroutine = False
protocol.process_exited._is_coroutine = False
transport = TestSubprocessTransport(
self.loop, protocol, ['test'], False,
None, None, None, 0, waiter=waiter)
return (transport, protocol)
def test_proc_exited(self):
waiter = asyncio.Future(loop=self.loop)
transport, protocol = self.create_transport(waiter)
transport._process_exited(6)
self.loop.run_until_complete(waiter)
self.assertEqual(transport.get_returncode(), 6)
self.assertTrue(protocol.connection_made.called)
self.assertTrue(protocol.process_exited.called)
self.assertTrue(protocol.connection_lost.called)
self.assertEqual(protocol.connection_lost.call_args[0], (None,))
self.assertFalse(transport.is_closing())
self.assertIsNone(transport._loop)
self.assertIsNone(transport._proc)
self.assertIsNone(transport._protocol)
# methods must raise ProcessLookupError if the process exited
self.assertRaises(ProcessLookupError,
transport.send_signal, signal.SIGTERM)
self.assertRaises(ProcessLookupError, transport.terminate)
self.assertRaises(ProcessLookupError, transport.kill)
transport.close()
def test_subprocess_repr(self):
waiter = asyncio.Future(loop=self.loop)
transport, protocol = self.create_transport(waiter)
transport._process_exited(6)
self.loop.run_until_complete(waiter)
self.assertEqual(
repr(transport),
"<TestSubprocessTransport pid=-1 returncode=6>"
)
transport._returncode = None
self.assertEqual(
repr(transport),
"<TestSubprocessTransport pid=-1 running>"
)
transport._pid = None
transport._returncode = None
self.assertEqual(
repr(transport),
"<TestSubprocessTransport not started>"
)
transport.close()
class SubprocessMixin:
def test_stdin_stdout(self):
args = PROGRAM_CAT
async def run(data):
proc = await asyncio.create_subprocess_exec(
*args,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
loop=self.loop)
# feed data
proc.stdin.write(data)
await proc.stdin.drain()
proc.stdin.close()
# get output and exitcode
data = await proc.stdout.read()
exitcode = await proc.wait()
return (exitcode, data)
task = run(b'some data')
task = asyncio.wait_for(task, 60.0, loop=self.loop)
exitcode, stdout = self.loop.run_until_complete(task)
self.assertEqual(exitcode, 0)
self.assertEqual(stdout, b'some data')
def test_communicate(self):
args = PROGRAM_CAT
async def run(data):
proc = await asyncio.create_subprocess_exec(
*args,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
loop=self.loop)
stdout, stderr = await proc.communicate(data)
return proc.returncode, stdout
task = run(b'some data')
task = asyncio.wait_for(task, 60.0, loop=self.loop)
exitcode, stdout = self.loop.run_until_complete(task)
self.assertEqual(exitcode, 0)
self.assertEqual(stdout, b'some data')
def test_shell(self):
create = asyncio.create_subprocess_shell('exit 7',
loop=self.loop)
proc = self.loop.run_until_complete(create)
exitcode = self.loop.run_until_complete(proc.wait())
self.assertEqual(exitcode, 7)
def test_start_new_session(self):
# start the new process in a new session
create = asyncio.create_subprocess_shell('exit 8',
start_new_session=True,
loop=self.loop)
proc = self.loop.run_until_complete(create)
exitcode = self.loop.run_until_complete(proc.wait())
self.assertEqual(exitcode, 8)
def test_kill(self):
args = PROGRAM_BLOCKED
create = asyncio.create_subprocess_exec(*args, loop=self.loop)
proc = self.loop.run_until_complete(create)
proc.kill()
returncode = self.loop.run_until_complete(proc.wait())
if sys.platform == 'win32':
self.assertIsInstance(returncode, int)
# expect 1 but sometimes get 0
else:
self.assertEqual(-signal.SIGKILL, returncode)
def test_terminate(self):
args = PROGRAM_BLOCKED
create = asyncio.create_subprocess_exec(*args, loop=self.loop)
proc = self.loop.run_until_complete(create)
proc.terminate()
returncode = self.loop.run_until_complete(proc.wait())
if sys.platform == 'win32':
self.assertIsInstance(returncode, int)
# expect 1 but sometimes get 0
else:
self.assertEqual(-signal.SIGTERM, returncode)
@unittest.skipIf(sys.platform == 'win32', "Don't have SIGHUP")
def test_send_signal(self):
# bpo-31034: Make sure that we get the default signal handler (killing
# the process). The parent process may have decided to ignore SIGHUP,
# and signal handlers are inherited.
old_handler = signal.signal(signal.SIGHUP, signal.SIG_DFL)
try:
code = 'import time; print("sleeping", flush=True); time.sleep(3600)'
args = [sys.executable, '-c', code]
create = asyncio.create_subprocess_exec(*args,
stdout=subprocess.PIPE,
loop=self.loop)
proc = self.loop.run_until_complete(create)
async def send_signal(proc):
# basic synchronization to wait until the program is sleeping
line = await proc.stdout.readline()
self.assertEqual(line, b'sleeping\n')
proc.send_signal(signal.SIGHUP)
returncode = await proc.wait()
return returncode
returncode = self.loop.run_until_complete(send_signal(proc))
self.assertEqual(-signal.SIGHUP, returncode)
finally:
signal.signal(signal.SIGHUP, old_handler)
def prepare_broken_pipe_test(self):
# buffer large enough to feed the whole pipe buffer
large_data = b'x' * support.PIPE_MAX_SIZE
# the program ends before the stdin can be feeded
create = asyncio.create_subprocess_exec(
sys.executable, '-c', 'pass',
stdin=subprocess.PIPE,
loop=self.loop)
proc = self.loop.run_until_complete(create)
return (proc, large_data)
def test_stdin_broken_pipe(self):
proc, large_data = self.prepare_broken_pipe_test()
async def write_stdin(proc, data):
await asyncio.sleep(0.5, loop=self.loop)
proc.stdin.write(data)
await proc.stdin.drain()
coro = write_stdin(proc, large_data)
# drain() must raise BrokenPipeError or ConnectionResetError
with test_utils.disable_logger():
self.assertRaises((BrokenPipeError, ConnectionResetError),
self.loop.run_until_complete, coro)
self.loop.run_until_complete(proc.wait())
def test_communicate_ignore_broken_pipe(self):
proc, large_data = self.prepare_broken_pipe_test()
# communicate() must ignore BrokenPipeError when feeding stdin
with test_utils.disable_logger():
self.loop.run_until_complete(proc.communicate(large_data))
self.loop.run_until_complete(proc.wait())
def test_pause_reading(self):
limit = 10
size = (limit * 2 + 1)
async def test_pause_reading():
code = '\n'.join((
'import sys',
'sys.stdout.write("x" * %s)' % size,
'sys.stdout.flush()',
))
connect_read_pipe = self.loop.connect_read_pipe
async def connect_read_pipe_mock(*args, **kw):
transport, protocol = await connect_read_pipe(*args, **kw)
transport.pause_reading = mock.Mock()
transport.resume_reading = mock.Mock()
return (transport, protocol)
self.loop.connect_read_pipe = connect_read_pipe_mock
proc = await asyncio.create_subprocess_exec(
sys.executable, '-c', code,
stdin=asyncio.subprocess.PIPE,
stdout=asyncio.subprocess.PIPE,
limit=limit,
loop=self.loop)
stdout_transport = proc._transport.get_pipe_transport(1)
stdout, stderr = await proc.communicate()
# The child process produced more than limit bytes of output,
# the stream reader transport should pause the protocol to not
# allocate too much memory.
return (stdout, stdout_transport)
# Issue #22685: Ensure that the stream reader pauses the protocol
# when the child process produces too much data
stdout, transport = self.loop.run_until_complete(test_pause_reading())
self.assertEqual(stdout, b'x' * size)
self.assertTrue(transport.pause_reading.called)
self.assertTrue(transport.resume_reading.called)
def test_stdin_not_inheritable(self):
# asyncio issue #209: stdin must not be inheritable, otherwise
# the Process.communicate() hangs
async def len_message(message):
code = 'import sys; data = sys.stdin.read(); print(len(data))'
proc = await asyncio.create_subprocess_exec(
sys.executable, '-c', code,
stdin=asyncio.subprocess.PIPE,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
close_fds=False,
loop=self.loop)
stdout, stderr = await proc.communicate(message)
exitcode = await proc.wait()
return (stdout, exitcode)
output, exitcode = self.loop.run_until_complete(len_message(b'abc'))
self.assertEqual(output.rstrip(), b'3')
self.assertEqual(exitcode, 0)
def test_empty_input(self):
async def empty_input():
code = 'import sys; data = sys.stdin.read(); print(len(data))'
proc = await asyncio.create_subprocess_exec(
sys.executable, '-c', code,
stdin=asyncio.subprocess.PIPE,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
close_fds=False,
loop=self.loop)
stdout, stderr = await proc.communicate(b'')
exitcode = await proc.wait()
return (stdout, exitcode)
output, exitcode = self.loop.run_until_complete(empty_input())
self.assertEqual(output.rstrip(), b'0')
self.assertEqual(exitcode, 0)
def test_cancel_process_wait(self):
# Issue #23140: cancel Process.wait()
async def cancel_wait():
proc = await asyncio.create_subprocess_exec(
*PROGRAM_BLOCKED,
loop=self.loop)
# Create an internal future waiting on the process exit
task = self.loop.create_task(proc.wait())
self.loop.call_soon(task.cancel)
try:
await task
except asyncio.CancelledError:
pass
# Cancel the future
task.cancel()
# Kill the process and wait until it is done
proc.kill()
await proc.wait()
self.loop.run_until_complete(cancel_wait())
def test_cancel_make_subprocess_transport_exec(self):
async def cancel_make_transport():
coro = asyncio.create_subprocess_exec(*PROGRAM_BLOCKED,
loop=self.loop)
task = self.loop.create_task(coro)
self.loop.call_soon(task.cancel)
try:
await task
except asyncio.CancelledError:
pass
# ignore the log:
# "Exception during subprocess creation, kill the subprocess"
with test_utils.disable_logger():
self.loop.run_until_complete(cancel_make_transport())
def test_cancel_post_init(self):
async def cancel_make_transport():
coro = self.loop.subprocess_exec(asyncio.SubprocessProtocol,
*PROGRAM_BLOCKED)
task = self.loop.create_task(coro)
self.loop.call_soon(task.cancel)
try:
await task
except asyncio.CancelledError:
pass
# ignore the log:
# "Exception during subprocess creation, kill the subprocess"
with test_utils.disable_logger():
self.loop.run_until_complete(cancel_make_transport())
test_utils.run_briefly(self.loop)
def test_close_kill_running(self):
async def kill_running():
create = self.loop.subprocess_exec(asyncio.SubprocessProtocol,
*PROGRAM_BLOCKED)
transport, protocol = await create
kill_called = False
def kill():
nonlocal kill_called
kill_called = True
orig_kill()
proc = transport.get_extra_info('subprocess')
orig_kill = proc.kill
proc.kill = kill
returncode = transport.get_returncode()
transport.close()
await transport._wait()
return (returncode, kill_called)
# Ignore "Close running child process: kill ..." log
with test_utils.disable_logger():
returncode, killed = self.loop.run_until_complete(kill_running())
self.assertIsNone(returncode)
# transport.close() must kill the process if it is still running
self.assertTrue(killed)
test_utils.run_briefly(self.loop)
def test_close_dont_kill_finished(self):
async def kill_running():
create = self.loop.subprocess_exec(asyncio.SubprocessProtocol,
*PROGRAM_BLOCKED)
transport, protocol = await create
proc = transport.get_extra_info('subprocess')
# kill the process (but asyncio is not notified immediately)
proc.kill()
proc.wait()
proc.kill = mock.Mock()
proc_returncode = proc.poll()
transport_returncode = transport.get_returncode()
transport.close()
return (proc_returncode, transport_returncode, proc.kill.called)
# Ignore "Unknown child process pid ..." log of SafeChildWatcher,
# emitted because the test already consumes the exit status:
# proc.wait()
with test_utils.disable_logger():
result = self.loop.run_until_complete(kill_running())
test_utils.run_briefly(self.loop)
proc_returncode, transport_return_code, killed = result
self.assertIsNotNone(proc_returncode)
self.assertIsNone(transport_return_code)
# transport.close() must not kill the process if it finished, even if
# the transport was not notified yet
self.assertFalse(killed)
# Unlike SafeChildWatcher, FastChildWatcher does not pop the
# callbacks if waitpid() is called elsewhere. Let's clear them
# manually to avoid a warning when the watcher is detached.
if (sys.platform != 'win32' and
isinstance(self, SubprocessFastWatcherTests)):
asyncio.get_child_watcher()._callbacks.clear()
def _test_popen_error(self, stdin):
if sys.platform == 'win32':
target = 'asyncio.windows_utils.Popen'
else:
target = 'subprocess.Popen'
with mock.patch(target) as popen:
exc = ZeroDivisionError
popen.side_effect = exc
create = asyncio.create_subprocess_exec(sys.executable, '-c',
'pass', stdin=stdin,
loop=self.loop)
with warnings.catch_warnings(record=True) as warns:
with self.assertRaises(exc):
self.loop.run_until_complete(create)
self.assertEqual(warns, [])
def test_popen_error(self):
# Issue #24763: check that the subprocess transport is closed
# when BaseSubprocessTransport fails
self._test_popen_error(stdin=None)
def test_popen_error_with_stdin_pipe(self):
# Issue #35721: check that newly created socket pair is closed when
# Popen fails
self._test_popen_error(stdin=subprocess.PIPE)
def test_read_stdout_after_process_exit(self):
async def execute():
code = '\n'.join(['import sys',
'for _ in range(64):',
' sys.stdout.write("x" * 4096)',
'sys.stdout.flush()',
'sys.exit(1)'])
fut = asyncio.create_subprocess_exec(
sys.executable, '-c', code,
stdout=asyncio.subprocess.PIPE,
loop=self.loop)
process = await fut
while True:
data = await process.stdout.read(65536)
if data:
await asyncio.sleep(0.3, loop=self.loop)
else:
break
self.loop.run_until_complete(execute())
if sys.platform != 'win32':
# Unix
class SubprocessWatcherMixin(SubprocessMixin):
Watcher = None
def setUp(self):
super().setUp()
policy = asyncio.get_event_loop_policy()
self.loop = policy.new_event_loop()
self.set_event_loop(self.loop)
watcher = self.Watcher()
watcher.attach_loop(self.loop)
policy.set_child_watcher(watcher)
self.addCleanup(policy.set_child_watcher, None)
class SubprocessSafeWatcherTests(SubprocessWatcherMixin,
test_utils.TestCase):
Watcher = unix_events.SafeChildWatcher
class SubprocessFastWatcherTests(SubprocessWatcherMixin,
test_utils.TestCase):
Watcher = unix_events.FastChildWatcher
else:
# Windows
class SubprocessProactorTests(SubprocessMixin, test_utils.TestCase):
def setUp(self):
super().setUp()
self.loop = asyncio.ProactorEventLoop()
self.set_event_loop(self.loop)
if __name__ == '__main__':
unittest.main() | 0.334481 | 0.183082 |
import argparse
def str2bool(v):
if v.lower() in ('yes', 'true', 't', 'y', '1'):
return True
elif v.lower() in ('no', 'false', 'f', 'n', '0'):
return False
else:
raise argparse.ArgumentTypeError('Boolean value expected.')
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument('--world-size', default=-1, type=int,
help='number of nodes for distributed training')
parser.add_argument('--rank', default=-1, type=int,
help='node rank for distributed training')
parser.add_argument('--loca_rank', default=-1, type=int,
help='node rank for distributed training')
parser.add_argument('--dist-url', default='tcp://192.168.3.11:23456', type=str,
help='url used to set up distributed training')
parser.add_argument('--dist-backend', default='nccl', type=str,
help='distributed backend')
parser.add_argument('--seed', default=12345, type=int,
help='seed for initializing training. ')
parser.add_argument('--gpu', default=None, type=int,
help='GPU id to use.')
parser.add_argument('--multiprocessing-distributed', action='store_true',
help='Use multi-processing distributed training to launch '
'N processes per node, which has N GPUs. This is the '
'fastest way to use PyTorch for either single node or '
'multi node data parallel training')
parser.add_argument(
'--max_epoch',
type=int,
default=200,
help='number of epochs of training')
parser.add_argument(
'--max_iter',
type=int,
default=None,
help='set the max iteration number')
parser.add_argument(
'-gen_bs',
'--gen_batch_size',
type=int,
default=64,
help='size of the batches')
parser.add_argument(
'-dis_bs',
'--dis_batch_size',
type=int,
default=64,
help='size of the batches')
parser.add_argument(
'-bs',
'--batch_size',
type=int,
default=64,
help='size of the batches to load dataset')
parser.add_argument(
'--g_lr',
type=float,
default=0.0002,
help='adam: gen learning rate')
parser.add_argument(
'--wd',
type=float,
default=0,
help='adamw: gen weight decay')
parser.add_argument(
'--d_lr',
type=float,
default=0.0002,
help='adam: disc learning rate')
parser.add_argument(
'--ctrl_lr',
type=float,
default=3.5e-4,
help='adam: ctrl learning rate')
parser.add_argument(
'--lr_decay',
action='store_true',
help='learning rate decay or not')
parser.add_argument(
'--beta1',
type=float,
default=0.0,
help='adam: decay of first order momentum of gradient')
parser.add_argument(
'--beta2',
type=float,
default=0.9,
help='adam: decay of first order momentum of gradient')
parser.add_argument(
'--num_workers',
type=int,
default=8,
help='number of cpu threads to use during batch generation')
parser.add_argument(
'--latent_dim',
type=int,
default=128,
help='dimensionality of the latent space')
parser.add_argument(
'--img_size',
type=int,
default=32,
help='size of each image dimension')
parser.add_argument(
'--channels',
type=int,
default=3,
help='number of image channels')
parser.add_argument(
'--n_critic',
type=int,
default=1,
help='number of training steps for discriminator per iter')
parser.add_argument(
'--val_freq',
type=int,
default=20,
help='interval between each validation')
parser.add_argument(
'--print_freq',
type=int,
default=100,
help='interval between each verbose')
parser.add_argument(
'--load_path',
type=str,
help='The reload model path')
parser.add_argument(
'--class_name',
type=str,
help='The class name to load in UniMiB dataset')
parser.add_argument(
'--augment_times',
type=int,
default=None,
help='The times of augment signals compare to original data')
parser.add_argument(
'--exp_name',
type=str,
help='The name of exp')
parser.add_argument(
'--d_spectral_norm',
type=str2bool,
default=False,
help='add spectral_norm on discriminator?')
parser.add_argument(
'--g_spectral_norm',
type=str2bool,
default=False,
help='add spectral_norm on generator?')
parser.add_argument(
'--dataset',
type=str,
default='cifar10',
help='dataset type')
parser.add_argument(
'--data_path',
type=str,
default='./data',
help='The path of data set')
parser.add_argument('--init_type', type=str, default='normal',
choices=['normal', 'orth', 'xavier_uniform', 'false'],
help='The init type')
parser.add_argument('--gf_dim', type=int, default=64,
help='The base channel num of gen')
parser.add_argument('--df_dim', type=int, default=64,
help='The base channel num of disc')
parser.add_argument(
'--gen_model',
type=str,
help='path of gen model')
parser.add_argument(
'--dis_model',
type=str,
help='path of dis model')
parser.add_argument(
'--controller',
type=str,
default='controller',
help='path of controller')
parser.add_argument('--eval_batch_size', type=int, default=100)
parser.add_argument('--num_eval_imgs', type=int, default=50000)
parser.add_argument(
'--bottom_width',
type=int,
default=4,
help="the base resolution of the GAN")
parser.add_argument('--random_seed', type=int, default=12345)
# search
parser.add_argument('--shared_epoch', type=int, default=15,
help='the number of epoch to train the shared gan at each search iteration')
parser.add_argument('--grow_step1', type=int, default=25,
help='which iteration to grow the image size from 8 to 16')
parser.add_argument('--grow_step2', type=int, default=55,
help='which iteration to grow the image size from 16 to 32')
parser.add_argument('--max_search_iter', type=int, default=90,
help='max search iterations of this algorithm')
parser.add_argument('--ctrl_step', type=int, default=30,
help='number of steps to train the controller at each search iteration')
parser.add_argument('--ctrl_sample_batch', type=int, default=1,
help='sample size of controller of each step')
parser.add_argument('--hid_size', type=int, default=100,
help='the size of hidden vector')
parser.add_argument('--baseline_decay', type=float, default=0.9,
help='baseline decay rate in RL')
parser.add_argument('--rl_num_eval_img', type=int, default=5000,
help='number of images to be sampled in order to get the reward')
parser.add_argument('--num_candidate', type=int, default=10,
help='number of candidate architectures to be sampled')
parser.add_argument('--topk', type=int, default=5,
help='preserve topk models architectures after each stage' )
parser.add_argument('--entropy_coeff', type=float, default=1e-3,
help='to encourage the exploration')
parser.add_argument('--dynamic_reset_threshold', type=float, default=1e-3,
help='var threshold')
parser.add_argument('--dynamic_reset_window', type=int, default=500,
help='the window size')
parser.add_argument('--arch', nargs='+', type=int,
help='the vector of a discovered architecture')
parser.add_argument('--optimizer', type=str, default="adam",
help='optimizer')
parser.add_argument('--loss', type=str, default="hinge",
help='loss function')
parser.add_argument('--n_classes', type=int, default=0,
help='classes')
parser.add_argument('--phi', type=float, default=1,
help='wgan-gp phi')
parser.add_argument('--grow_steps', nargs='+', type=int,
help='the vector of a discovered architecture')
parser.add_argument('--D_downsample', type=str, default="avg",
help='downsampling type')
parser.add_argument('--fade_in', type=float, default=1,
help='fade in step')
parser.add_argument('--d_depth', type=int, default=7,
help='Discriminator Depth')
parser.add_argument('--g_depth', type=str, default="5,4,2",
help='Generator Depth')
parser.add_argument('--g_norm', type=str, default="ln",
help='Generator Normalization')
parser.add_argument('--d_norm', type=str, default="ln",
help='Discriminator Normalization')
parser.add_argument('--g_act', type=str, default="gelu",
help='Generator activation Layer')
parser.add_argument('--d_act', type=str, default="gelu",
help='Discriminator activation layer')
parser.add_argument('--patch_size', type=int, default=4,
help='Discriminator Depth')
parser.add_argument('--fid_stat', type=str, default="None",
help='Discriminator Depth')
parser.add_argument('--diff_aug', type=str, default="None",
help='differentiable augmentation type')
parser.add_argument('--accumulated_times', type=int, default=1,
help='gradient accumulation')
parser.add_argument('--g_accumulated_times', type=int, default=1,
help='gradient accumulation')
parser.add_argument('--num_landmarks', type=int, default=64,
help='number of landmarks')
parser.add_argument('--d_heads', type=int, default=4,
help='number of heads')
parser.add_argument('--dropout', type=float, default=0.,
help='dropout ratio')
parser.add_argument('--ema', type=float, default=0.995,
help='ema')
parser.add_argument('--ema_warmup', type=float, default=0.,
help='ema warm up')
parser.add_argument('--ema_kimg', type=int, default=500,
help='ema thousand images')
parser.add_argument('--latent_norm',action='store_true',
help='latent vector normalization')
parser.add_argument('--ministd',action='store_true',
help='mini batch std')
parser.add_argument('--g_mlp', type=int, default=4,
help='generator mlp ratio')
parser.add_argument('--d_mlp', type=int, default=4,
help='discriminator mlp ratio')
parser.add_argument('--g_window_size', type=int, default=8,
help='generator mlp ratio')
parser.add_argument('--d_window_size', type=int, default=8,
help='discriminator mlp ratio')
parser.add_argument('--show', action='store_true',
help='show')
opt = parser.parse_args()
return opt | cfg.py |
import argparse
def str2bool(v):
if v.lower() in ('yes', 'true', 't', 'y', '1'):
return True
elif v.lower() in ('no', 'false', 'f', 'n', '0'):
return False
else:
raise argparse.ArgumentTypeError('Boolean value expected.')
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument('--world-size', default=-1, type=int,
help='number of nodes for distributed training')
parser.add_argument('--rank', default=-1, type=int,
help='node rank for distributed training')
parser.add_argument('--loca_rank', default=-1, type=int,
help='node rank for distributed training')
parser.add_argument('--dist-url', default='tcp://192.168.3.11:23456', type=str,
help='url used to set up distributed training')
parser.add_argument('--dist-backend', default='nccl', type=str,
help='distributed backend')
parser.add_argument('--seed', default=12345, type=int,
help='seed for initializing training. ')
parser.add_argument('--gpu', default=None, type=int,
help='GPU id to use.')
parser.add_argument('--multiprocessing-distributed', action='store_true',
help='Use multi-processing distributed training to launch '
'N processes per node, which has N GPUs. This is the '
'fastest way to use PyTorch for either single node or '
'multi node data parallel training')
parser.add_argument(
'--max_epoch',
type=int,
default=200,
help='number of epochs of training')
parser.add_argument(
'--max_iter',
type=int,
default=None,
help='set the max iteration number')
parser.add_argument(
'-gen_bs',
'--gen_batch_size',
type=int,
default=64,
help='size of the batches')
parser.add_argument(
'-dis_bs',
'--dis_batch_size',
type=int,
default=64,
help='size of the batches')
parser.add_argument(
'-bs',
'--batch_size',
type=int,
default=64,
help='size of the batches to load dataset')
parser.add_argument(
'--g_lr',
type=float,
default=0.0002,
help='adam: gen learning rate')
parser.add_argument(
'--wd',
type=float,
default=0,
help='adamw: gen weight decay')
parser.add_argument(
'--d_lr',
type=float,
default=0.0002,
help='adam: disc learning rate')
parser.add_argument(
'--ctrl_lr',
type=float,
default=3.5e-4,
help='adam: ctrl learning rate')
parser.add_argument(
'--lr_decay',
action='store_true',
help='learning rate decay or not')
parser.add_argument(
'--beta1',
type=float,
default=0.0,
help='adam: decay of first order momentum of gradient')
parser.add_argument(
'--beta2',
type=float,
default=0.9,
help='adam: decay of first order momentum of gradient')
parser.add_argument(
'--num_workers',
type=int,
default=8,
help='number of cpu threads to use during batch generation')
parser.add_argument(
'--latent_dim',
type=int,
default=128,
help='dimensionality of the latent space')
parser.add_argument(
'--img_size',
type=int,
default=32,
help='size of each image dimension')
parser.add_argument(
'--channels',
type=int,
default=3,
help='number of image channels')
parser.add_argument(
'--n_critic',
type=int,
default=1,
help='number of training steps for discriminator per iter')
parser.add_argument(
'--val_freq',
type=int,
default=20,
help='interval between each validation')
parser.add_argument(
'--print_freq',
type=int,
default=100,
help='interval between each verbose')
parser.add_argument(
'--load_path',
type=str,
help='The reload model path')
parser.add_argument(
'--class_name',
type=str,
help='The class name to load in UniMiB dataset')
parser.add_argument(
'--augment_times',
type=int,
default=None,
help='The times of augment signals compare to original data')
parser.add_argument(
'--exp_name',
type=str,
help='The name of exp')
parser.add_argument(
'--d_spectral_norm',
type=str2bool,
default=False,
help='add spectral_norm on discriminator?')
parser.add_argument(
'--g_spectral_norm',
type=str2bool,
default=False,
help='add spectral_norm on generator?')
parser.add_argument(
'--dataset',
type=str,
default='cifar10',
help='dataset type')
parser.add_argument(
'--data_path',
type=str,
default='./data',
help='The path of data set')
parser.add_argument('--init_type', type=str, default='normal',
choices=['normal', 'orth', 'xavier_uniform', 'false'],
help='The init type')
parser.add_argument('--gf_dim', type=int, default=64,
help='The base channel num of gen')
parser.add_argument('--df_dim', type=int, default=64,
help='The base channel num of disc')
parser.add_argument(
'--gen_model',
type=str,
help='path of gen model')
parser.add_argument(
'--dis_model',
type=str,
help='path of dis model')
parser.add_argument(
'--controller',
type=str,
default='controller',
help='path of controller')
parser.add_argument('--eval_batch_size', type=int, default=100)
parser.add_argument('--num_eval_imgs', type=int, default=50000)
parser.add_argument(
'--bottom_width',
type=int,
default=4,
help="the base resolution of the GAN")
parser.add_argument('--random_seed', type=int, default=12345)
# search
parser.add_argument('--shared_epoch', type=int, default=15,
help='the number of epoch to train the shared gan at each search iteration')
parser.add_argument('--grow_step1', type=int, default=25,
help='which iteration to grow the image size from 8 to 16')
parser.add_argument('--grow_step2', type=int, default=55,
help='which iteration to grow the image size from 16 to 32')
parser.add_argument('--max_search_iter', type=int, default=90,
help='max search iterations of this algorithm')
parser.add_argument('--ctrl_step', type=int, default=30,
help='number of steps to train the controller at each search iteration')
parser.add_argument('--ctrl_sample_batch', type=int, default=1,
help='sample size of controller of each step')
parser.add_argument('--hid_size', type=int, default=100,
help='the size of hidden vector')
parser.add_argument('--baseline_decay', type=float, default=0.9,
help='baseline decay rate in RL')
parser.add_argument('--rl_num_eval_img', type=int, default=5000,
help='number of images to be sampled in order to get the reward')
parser.add_argument('--num_candidate', type=int, default=10,
help='number of candidate architectures to be sampled')
parser.add_argument('--topk', type=int, default=5,
help='preserve topk models architectures after each stage' )
parser.add_argument('--entropy_coeff', type=float, default=1e-3,
help='to encourage the exploration')
parser.add_argument('--dynamic_reset_threshold', type=float, default=1e-3,
help='var threshold')
parser.add_argument('--dynamic_reset_window', type=int, default=500,
help='the window size')
parser.add_argument('--arch', nargs='+', type=int,
help='the vector of a discovered architecture')
parser.add_argument('--optimizer', type=str, default="adam",
help='optimizer')
parser.add_argument('--loss', type=str, default="hinge",
help='loss function')
parser.add_argument('--n_classes', type=int, default=0,
help='classes')
parser.add_argument('--phi', type=float, default=1,
help='wgan-gp phi')
parser.add_argument('--grow_steps', nargs='+', type=int,
help='the vector of a discovered architecture')
parser.add_argument('--D_downsample', type=str, default="avg",
help='downsampling type')
parser.add_argument('--fade_in', type=float, default=1,
help='fade in step')
parser.add_argument('--d_depth', type=int, default=7,
help='Discriminator Depth')
parser.add_argument('--g_depth', type=str, default="5,4,2",
help='Generator Depth')
parser.add_argument('--g_norm', type=str, default="ln",
help='Generator Normalization')
parser.add_argument('--d_norm', type=str, default="ln",
help='Discriminator Normalization')
parser.add_argument('--g_act', type=str, default="gelu",
help='Generator activation Layer')
parser.add_argument('--d_act', type=str, default="gelu",
help='Discriminator activation layer')
parser.add_argument('--patch_size', type=int, default=4,
help='Discriminator Depth')
parser.add_argument('--fid_stat', type=str, default="None",
help='Discriminator Depth')
parser.add_argument('--diff_aug', type=str, default="None",
help='differentiable augmentation type')
parser.add_argument('--accumulated_times', type=int, default=1,
help='gradient accumulation')
parser.add_argument('--g_accumulated_times', type=int, default=1,
help='gradient accumulation')
parser.add_argument('--num_landmarks', type=int, default=64,
help='number of landmarks')
parser.add_argument('--d_heads', type=int, default=4,
help='number of heads')
parser.add_argument('--dropout', type=float, default=0.,
help='dropout ratio')
parser.add_argument('--ema', type=float, default=0.995,
help='ema')
parser.add_argument('--ema_warmup', type=float, default=0.,
help='ema warm up')
parser.add_argument('--ema_kimg', type=int, default=500,
help='ema thousand images')
parser.add_argument('--latent_norm',action='store_true',
help='latent vector normalization')
parser.add_argument('--ministd',action='store_true',
help='mini batch std')
parser.add_argument('--g_mlp', type=int, default=4,
help='generator mlp ratio')
parser.add_argument('--d_mlp', type=int, default=4,
help='discriminator mlp ratio')
parser.add_argument('--g_window_size', type=int, default=8,
help='generator mlp ratio')
parser.add_argument('--d_window_size', type=int, default=8,
help='discriminator mlp ratio')
parser.add_argument('--show', action='store_true',
help='show')
opt = parser.parse_args()
return opt | 0.564098 | 0.155046 |
import os
if os.sep==".":
endsep = "/"
else:
endsep = "."
def whichdb(filename):
"""Guess which db package to use to open a db file.
Return values:
- None if the database file can't be read;
- empty string if the file can be read but can't be recognized
- the module name (e.g. "dbm" or "gdbm") if recognized.
Importing the given module may still fail, and opening the
database using that module may still fail.
"""
import struct
# Check for dbm first -- this has a .pag and a .dir file
try:
f = open(filename + endsep + "pag", "rb")
f.close()
f = open(filename + endsep + "dir", "rb")
f.close()
return "dbm"
except IOError:
pass
# Check for dumbdbm next -- this has a .dir and and a .dat file
try:
f = open(filename + endsep + "dat", "rb")
f.close()
f = open(filename + endsep + "dir", "rb")
try:
if f.read(1) in ["'", '"']:
return "dumbdbm"
finally:
f.close()
except IOError:
pass
# See if the file exists, return None if not
try:
f = open(filename, "rb")
except IOError:
return None
# Read the start of the file -- the magic number
s16 = f.read(16)
f.close()
s = s16[0:4]
# Return "" if not at least 4 bytes
if len(s) != 4:
return ""
# Convert to 4-byte int in native byte order -- return "" if impossible
try:
(magic,) = struct.unpack("=l", s)
except struct.error:
return ""
# Check for GNU dbm
if magic == 0x13579ace:
return "gdbm"
# Check for BSD hash
if magic in (0x00061561, 0x61150600):
return "dbhash"
# BSD hash v2 has a 12-byte NULL pad in front of the file type
try:
(magic,) = struct.unpack("=l", s16[-4:])
except struct.error:
return ""
# Check for BSD hash
if magic in (0x00061561, 0x61150600):
return "dbhash"
# Unknown
return "" | Lib/whichdb.py |
import os
if os.sep==".":
endsep = "/"
else:
endsep = "."
def whichdb(filename):
"""Guess which db package to use to open a db file.
Return values:
- None if the database file can't be read;
- empty string if the file can be read but can't be recognized
- the module name (e.g. "dbm" or "gdbm") if recognized.
Importing the given module may still fail, and opening the
database using that module may still fail.
"""
import struct
# Check for dbm first -- this has a .pag and a .dir file
try:
f = open(filename + endsep + "pag", "rb")
f.close()
f = open(filename + endsep + "dir", "rb")
f.close()
return "dbm"
except IOError:
pass
# Check for dumbdbm next -- this has a .dir and and a .dat file
try:
f = open(filename + endsep + "dat", "rb")
f.close()
f = open(filename + endsep + "dir", "rb")
try:
if f.read(1) in ["'", '"']:
return "dumbdbm"
finally:
f.close()
except IOError:
pass
# See if the file exists, return None if not
try:
f = open(filename, "rb")
except IOError:
return None
# Read the start of the file -- the magic number
s16 = f.read(16)
f.close()
s = s16[0:4]
# Return "" if not at least 4 bytes
if len(s) != 4:
return ""
# Convert to 4-byte int in native byte order -- return "" if impossible
try:
(magic,) = struct.unpack("=l", s)
except struct.error:
return ""
# Check for GNU dbm
if magic == 0x13579ace:
return "gdbm"
# Check for BSD hash
if magic in (0x00061561, 0x61150600):
return "dbhash"
# BSD hash v2 has a 12-byte NULL pad in front of the file type
try:
(magic,) = struct.unpack("=l", s16[-4:])
except struct.error:
return ""
# Check for BSD hash
if magic in (0x00061561, 0x61150600):
return "dbhash"
# Unknown
return "" | 0.564819 | 0.143427 |
from __future__ import print_function
import os
import os.path
from os.path import join
import platform
from setuptools import setup
from setuptools import Extension
from Cython.Build import cythonize
home_dir = os.getenv('HOME')
print('home_dir:', home_dir)
torch_install_dir = os.getenv('TORCH_INSTALL')
if torch_install_dir is None:
raise Exception('Please ensure TORCH_INSTALL env var is defined')
osfamily = platform.uname()[0]
print('torch_install:', torch_install_dir)
print('os family', osfamily)
cython_present = True
compile_options = []
osfamily = platform.uname()[0]
if osfamily == 'Windows':
compile_options.append('/EHsc')
elif osfamily == 'Linux':
compile_options.append('-std=c++0x')
compile_options.append('-g')
if 'DEBUG' in os.environ:
compile_options.append('-O0')
else:
pass
# put other options etc here if necessary
runtime_library_dirs = []
libraries = []
# libraries.append('mylib')
# libraries.append('clnnWrapper')
libraries.append('TH')
libraries.append('THCl')
libraries.append('PyTorchNative')
# libraries.append('PyTorch')
library_dirs = []
library_dirs.append('cbuild')
library_dirs.append(join(torch_install_dir, 'lib'))
if osfamily == 'Linux':
runtime_library_dirs = ['.']
if osfamily == 'Windows':
libraries.append('winmm')
sources = ["PyClTorch.cxx", "clnnWrapper.cpp"]
if cython_present:
sources = ["PyClTorch.pyx", "clnnWrapper.cpp"]
ext_modules = [
Extension("PyClTorch",
sources=sources,
include_dirs=[
join(torch_install_dir, 'include'),
join(torch_install_dir, 'include/TH'),
join(torch_install_dir, 'include/THCl'),
'/usr/include/lua5.1',
'pytorch/src'],
library_dirs=library_dirs,
libraries=libraries,
extra_compile_args=compile_options,
runtime_library_dirs=runtime_library_dirs,
language="c++"),
# Extension("GlobalState",
# sources=['GlobalState.pyx'],
# include_dirs=[
# home_dir + '/torch/install/include/TH',
# home_dir + '/torch/install/include/THCl',
# '../pytorch'],
# library_dirs=library_dirs,
# libraries=libraries,
# extra_compile_args=compile_options,
# runtime_library_dirs=runtime_library_dirs,
# language="c++"),
]
ext_modules = cythonize(ext_modules)
setup(
name='PyClTorch',
version='SNAPSHOT',
author="<NAME>",
author_email="<EMAIL>",
description=(
'Python wrappers for cltorch'),
license='BSD2',
url='https://github.com/hughperkins/pycltorch',
long_description='',
classifiers=[
],
install_requires=[],
scripts=[],
ext_modules=ext_modules,
) | setup.py |
from __future__ import print_function
import os
import os.path
from os.path import join
import platform
from setuptools import setup
from setuptools import Extension
from Cython.Build import cythonize
home_dir = os.getenv('HOME')
print('home_dir:', home_dir)
torch_install_dir = os.getenv('TORCH_INSTALL')
if torch_install_dir is None:
raise Exception('Please ensure TORCH_INSTALL env var is defined')
osfamily = platform.uname()[0]
print('torch_install:', torch_install_dir)
print('os family', osfamily)
cython_present = True
compile_options = []
osfamily = platform.uname()[0]
if osfamily == 'Windows':
compile_options.append('/EHsc')
elif osfamily == 'Linux':
compile_options.append('-std=c++0x')
compile_options.append('-g')
if 'DEBUG' in os.environ:
compile_options.append('-O0')
else:
pass
# put other options etc here if necessary
runtime_library_dirs = []
libraries = []
# libraries.append('mylib')
# libraries.append('clnnWrapper')
libraries.append('TH')
libraries.append('THCl')
libraries.append('PyTorchNative')
# libraries.append('PyTorch')
library_dirs = []
library_dirs.append('cbuild')
library_dirs.append(join(torch_install_dir, 'lib'))
if osfamily == 'Linux':
runtime_library_dirs = ['.']
if osfamily == 'Windows':
libraries.append('winmm')
sources = ["PyClTorch.cxx", "clnnWrapper.cpp"]
if cython_present:
sources = ["PyClTorch.pyx", "clnnWrapper.cpp"]
ext_modules = [
Extension("PyClTorch",
sources=sources,
include_dirs=[
join(torch_install_dir, 'include'),
join(torch_install_dir, 'include/TH'),
join(torch_install_dir, 'include/THCl'),
'/usr/include/lua5.1',
'pytorch/src'],
library_dirs=library_dirs,
libraries=libraries,
extra_compile_args=compile_options,
runtime_library_dirs=runtime_library_dirs,
language="c++"),
# Extension("GlobalState",
# sources=['GlobalState.pyx'],
# include_dirs=[
# home_dir + '/torch/install/include/TH',
# home_dir + '/torch/install/include/THCl',
# '../pytorch'],
# library_dirs=library_dirs,
# libraries=libraries,
# extra_compile_args=compile_options,
# runtime_library_dirs=runtime_library_dirs,
# language="c++"),
]
ext_modules = cythonize(ext_modules)
setup(
name='PyClTorch',
version='SNAPSHOT',
author="<NAME>",
author_email="<EMAIL>",
description=(
'Python wrappers for cltorch'),
license='BSD2',
url='https://github.com/hughperkins/pycltorch',
long_description='',
classifiers=[
],
install_requires=[],
scripts=[],
ext_modules=ext_modules,
) | 0.239527 | 0.046747 |
import os
import pickle
from argparse import ArgumentParser
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
import tqdm
from torch.nn.utils.rnn import pack_padded_sequence
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter
from utils.data import ECGDataset, pad_batch_sequence, save_ecg_example
from utils.models import InverseCNNGenerator, DenseCritic
from torch_two_sample.statistics_diff import MMDStatistic
def get_argument_parser():
# TODO description to all params
# parameters for training
parser = ArgumentParser()
parser.add_argument("--out_dir",
help="Path to dir where models checkpoints, generated examples "
"and tensorboard logs will be stored",
type=str,
default="./out")
parser.add_argument("--model_name", default="dense_vs_dense_gan")
# dataset params
parser.add_argument("--real_dataset",
help="Path to .pickle file with ecg data from prepare_data script",
type=str)
parser.add_argument("--real_labels",
help="Path to .csv file with diagnosis labels from prepare_data script",
type=str)
parser.add_argument("--labels_dim", default=7, type=int)
parser.add_argument("--lead_n", default=12, type=int)
# general params
parser.add_argument("--device",
default=torch.device('cuda:0' if torch.cuda.is_available() else 'cpu'))
parser.add_argument("--n_epochs", default=2000, type=int)
parser.add_argument("--batch_size", default=26, type=int)
parser.add_argument("--lr", default=0.00005, type=float)
# generator params
parser.add_argument("--gen_h_dim", default=256, type=int)
parser.add_argument("--gen_l_dim", default=100, type=int)
# discriminator params
parser.add_argument("--dis_h_dim", default=100, type=int)
# parser.add_argument("--dis_encoder_h_dim", default=128, type=int)
parser.add_argument("--continue_from", default=None, type=str)
parser.add_argument("--seq_len", default=1500, type=int)
return parser
if __name__ == "__main__":
args = get_argument_parser().parse_args()
os.makedirs(os.path.join(args.out_dir, 'pictures'), exist_ok=True)
os.makedirs(os.path.join(args.out_dir, 'models'), exist_ok=True)
tb_path = os.path.join(args.out_dir, 'tensorboard')
os.makedirs(tb_path, exist_ok=True)
tb_writer = SummaryWriter(os.path.join(tb_path, args.model_name))
if torch.cuda.device_count() > 0:
torch.cuda.manual_seed_all(123)
torch.manual_seed(123)
# init GAN models
if args.continue_from:
G = torch.load(open(args.continue_from, "rb"), map_location=args.device)['g_model']
G.device = args.device
D = torch.load(open(args.continue_from, "rb"), map_location=args.device)['d_model']
D.device = args.device
else:
G = InverseCNNGenerator(noise_size=args.gen_l_dim,
label_size=args.labels_dim,
hidden_size=args.gen_h_dim,
lead_n=args.lead_n,
device=args.device)
with torch.no_grad():
noise = torch.rand(args.batch_size, args.gen_l_dim, device=args.device)
fake_seq = G(noise, torch.randint(low=0, high=1, size=(args.batch_size, 7),device=args.device).float())
D = DenseCritic(input_size=fake_seq.size(1),
label_size=args.labels_dim,
hidden_size=args.dis_h_dim,
lead_n=args.lead_n,
device=args.device)
with torch.no_grad():
noise = torch.rand(args.batch_size, args.gen_l_dim, device=args.device)
fake_seq = G(noise, torch.randint(low=0, high=1, size=(args.batch_size, 7),device=args.device).float())
# load our real examples
real_data_dict = pickle.load(open(args.real_dataset, 'rb'))
real_dataset = ECGDataset(real_data_dict, args.real_labels, seq_len=fake_seq.size(1))
# loss and data loader setup
criterion = nn.BCELoss()
mmd = MMDStatistic(args.batch_size, args.batch_size)
real_data_loader = DataLoader(real_dataset, batch_size=args.batch_size, drop_last=True, shuffle=True)
G_optimizer = optim.Adam(G.parameters(), lr=args.lr)
D_optimizer = optim.Adam(D.parameters(), lr=args.lr)
best_stat = None
# train loop
for epoch in tqdm.tqdm(range(args.n_epochs), position=0):
# sequences in true_data_loader already padded thanks to pad_batch_sequence function
stat_list = []
for real_seqs, real_labels in tqdm.tqdm(real_data_loader, position=1):
torch.cuda.empty_cache()
"""------------------------------ Discriminator step --------------------------------------"""
# Generate fake sample,
real_seqs = real_seqs.to(args.device)
real_labels = real_labels.to(args.device)
noise = torch.rand(args.batch_size, args.gen_l_dim, device=args.device)
fake_seq = G(noise, real_labels)
# After that we can make predictions for our fake examples
d_fake_predictions = D(fake_seq, real_labels)
d_fake_target = torch.zeros_like(d_fake_predictions)
# ... and real ones
d_real_predictions = D(real_seqs, real_labels)
d_real_target = torch.ones_like(d_real_predictions)
# Now we can calculate loss for discriminator
d_fake_loss = criterion(d_fake_predictions, d_fake_target)
d_real_loss = criterion(d_real_predictions, d_real_target)
d_loss = d_real_loss + d_fake_loss
statistic = mmd(fake_seq.contiguous().view(args.batch_size, -1), real_seqs.view(args.batch_size, -1), [1.])
stat_list.append(statistic.item())
tb_writer.add_scalar("D_loss", d_loss.item(), global_step=epoch)
# tb_writer.add_scalar("MMD", statistic.item(), global_step=epoch)
# And make back-propagation according to calculated loss
d_loss.backward()
D_optimizer.step()
# Housekeeping - reset gradient
D_optimizer.zero_grad()
G.zero_grad()
""" ---------------------------- Generator step ---------------------------------------------"""
# Generate fake sample
noise = torch.rand(args.batch_size, args.gen_l_dim, device=args.device)
fake_seq = G(noise, real_labels)
# After that we can make predictions for our fake examples
d_fake_predictions = D(fake_seq, real_labels)
g_target = torch.ones_like(d_fake_predictions)
# Now we can calculate loss for generator
g_loss = criterion(d_fake_predictions, g_target)
tb_writer.add_scalar("G_loss", g_loss.item(), global_step=epoch)
# And make back-propagation according to calculated loss
g_loss.backward()
G_optimizer.step()
# Housekeeping - reset gradient
G_optimizer.zero_grad()
D.zero_grad()
# plot example and save checkpoint each odd epoch
if best_stat is None:
# print()
best_stat = np.mean(stat_list)
torch.save({
'epoch': epoch,
'stat_value': best_stat,
"d_model": D,
"d_loss": d_loss,
"d_optimizer": D_optimizer,
"g_model": G,
"g_loss": g_loss,
"g_optimizer": G_optimizer,
}, os.path.join(args.out_dir, f"models/{args.model_name}_best_for_mmd_checkpoint.pkl"))
elif np.mean(stat_list) < best_stat:
best_stat = np.mean(stat_list)
torch.save({
'epoch': epoch,
'stat_value': best_stat,
"d_model": D,
"d_loss": d_loss,
"d_optimizer": D_optimizer,
"g_model": G,
"g_loss": g_loss,
"g_optimizer": G_optimizer,
}, os.path.join(args.out_dir, f"models/{args.model_name}_best_for_mmd_checkpoint.pkl"))
tb_writer.add_scalar("MMD", np.mean(stat_list), global_step=epoch)
if epoch % 50 == 0 or epoch == args.n_epochs:
print(f'Epoch-{epoch}; D_loss: {d_loss.data.cpu().numpy()}; G_loss: {g_loss.data.cpu().numpy()}')
torch.save({
'epoch': epoch,
'stat_value': np.mean(stat_list),
"d_model": D,
"d_loss": d_loss,
"d_optimizer": D_optimizer,
"g_model": G,
"g_loss": g_loss,
"g_optimizer": G_optimizer,
}, os.path.join(args.out_dir, f"models/{args.model_name}_epoch_{epoch}_checkpoint.pkl"))
with torch.no_grad():
noise = torch.rand(args.batch_size, args.gen_l_dim, device=args.device)
fake_seq = G(noise, real_labels)
_seq = fake_seq[0].cpu().numpy() # batch_first :^)
# _label = _labels[0].cpu().numpy()
fig = save_ecg_example(_seq, f"pictures/{args.model_name}_epoch_{epoch}_example")
tb_writer.add_figure("generated_example", fig, global_step=epoch)
# TODO use visualize func here | experiments/training_scripts/cgan/cnn_vs_dense_gan_train.py | import os
import pickle
from argparse import ArgumentParser
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
import tqdm
from torch.nn.utils.rnn import pack_padded_sequence
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter
from utils.data import ECGDataset, pad_batch_sequence, save_ecg_example
from utils.models import InverseCNNGenerator, DenseCritic
from torch_two_sample.statistics_diff import MMDStatistic
def get_argument_parser():
# TODO description to all params
# parameters for training
parser = ArgumentParser()
parser.add_argument("--out_dir",
help="Path to dir where models checkpoints, generated examples "
"and tensorboard logs will be stored",
type=str,
default="./out")
parser.add_argument("--model_name", default="dense_vs_dense_gan")
# dataset params
parser.add_argument("--real_dataset",
help="Path to .pickle file with ecg data from prepare_data script",
type=str)
parser.add_argument("--real_labels",
help="Path to .csv file with diagnosis labels from prepare_data script",
type=str)
parser.add_argument("--labels_dim", default=7, type=int)
parser.add_argument("--lead_n", default=12, type=int)
# general params
parser.add_argument("--device",
default=torch.device('cuda:0' if torch.cuda.is_available() else 'cpu'))
parser.add_argument("--n_epochs", default=2000, type=int)
parser.add_argument("--batch_size", default=26, type=int)
parser.add_argument("--lr", default=0.00005, type=float)
# generator params
parser.add_argument("--gen_h_dim", default=256, type=int)
parser.add_argument("--gen_l_dim", default=100, type=int)
# discriminator params
parser.add_argument("--dis_h_dim", default=100, type=int)
# parser.add_argument("--dis_encoder_h_dim", default=128, type=int)
parser.add_argument("--continue_from", default=None, type=str)
parser.add_argument("--seq_len", default=1500, type=int)
return parser
if __name__ == "__main__":
args = get_argument_parser().parse_args()
os.makedirs(os.path.join(args.out_dir, 'pictures'), exist_ok=True)
os.makedirs(os.path.join(args.out_dir, 'models'), exist_ok=True)
tb_path = os.path.join(args.out_dir, 'tensorboard')
os.makedirs(tb_path, exist_ok=True)
tb_writer = SummaryWriter(os.path.join(tb_path, args.model_name))
if torch.cuda.device_count() > 0:
torch.cuda.manual_seed_all(123)
torch.manual_seed(123)
# init GAN models
if args.continue_from:
G = torch.load(open(args.continue_from, "rb"), map_location=args.device)['g_model']
G.device = args.device
D = torch.load(open(args.continue_from, "rb"), map_location=args.device)['d_model']
D.device = args.device
else:
G = InverseCNNGenerator(noise_size=args.gen_l_dim,
label_size=args.labels_dim,
hidden_size=args.gen_h_dim,
lead_n=args.lead_n,
device=args.device)
with torch.no_grad():
noise = torch.rand(args.batch_size, args.gen_l_dim, device=args.device)
fake_seq = G(noise, torch.randint(low=0, high=1, size=(args.batch_size, 7),device=args.device).float())
D = DenseCritic(input_size=fake_seq.size(1),
label_size=args.labels_dim,
hidden_size=args.dis_h_dim,
lead_n=args.lead_n,
device=args.device)
with torch.no_grad():
noise = torch.rand(args.batch_size, args.gen_l_dim, device=args.device)
fake_seq = G(noise, torch.randint(low=0, high=1, size=(args.batch_size, 7),device=args.device).float())
# load our real examples
real_data_dict = pickle.load(open(args.real_dataset, 'rb'))
real_dataset = ECGDataset(real_data_dict, args.real_labels, seq_len=fake_seq.size(1))
# loss and data loader setup
criterion = nn.BCELoss()
mmd = MMDStatistic(args.batch_size, args.batch_size)
real_data_loader = DataLoader(real_dataset, batch_size=args.batch_size, drop_last=True, shuffle=True)
G_optimizer = optim.Adam(G.parameters(), lr=args.lr)
D_optimizer = optim.Adam(D.parameters(), lr=args.lr)
best_stat = None
# train loop
for epoch in tqdm.tqdm(range(args.n_epochs), position=0):
# sequences in true_data_loader already padded thanks to pad_batch_sequence function
stat_list = []
for real_seqs, real_labels in tqdm.tqdm(real_data_loader, position=1):
torch.cuda.empty_cache()
"""------------------------------ Discriminator step --------------------------------------"""
# Generate fake sample,
real_seqs = real_seqs.to(args.device)
real_labels = real_labels.to(args.device)
noise = torch.rand(args.batch_size, args.gen_l_dim, device=args.device)
fake_seq = G(noise, real_labels)
# After that we can make predictions for our fake examples
d_fake_predictions = D(fake_seq, real_labels)
d_fake_target = torch.zeros_like(d_fake_predictions)
# ... and real ones
d_real_predictions = D(real_seqs, real_labels)
d_real_target = torch.ones_like(d_real_predictions)
# Now we can calculate loss for discriminator
d_fake_loss = criterion(d_fake_predictions, d_fake_target)
d_real_loss = criterion(d_real_predictions, d_real_target)
d_loss = d_real_loss + d_fake_loss
statistic = mmd(fake_seq.contiguous().view(args.batch_size, -1), real_seqs.view(args.batch_size, -1), [1.])
stat_list.append(statistic.item())
tb_writer.add_scalar("D_loss", d_loss.item(), global_step=epoch)
# tb_writer.add_scalar("MMD", statistic.item(), global_step=epoch)
# And make back-propagation according to calculated loss
d_loss.backward()
D_optimizer.step()
# Housekeeping - reset gradient
D_optimizer.zero_grad()
G.zero_grad()
""" ---------------------------- Generator step ---------------------------------------------"""
# Generate fake sample
noise = torch.rand(args.batch_size, args.gen_l_dim, device=args.device)
fake_seq = G(noise, real_labels)
# After that we can make predictions for our fake examples
d_fake_predictions = D(fake_seq, real_labels)
g_target = torch.ones_like(d_fake_predictions)
# Now we can calculate loss for generator
g_loss = criterion(d_fake_predictions, g_target)
tb_writer.add_scalar("G_loss", g_loss.item(), global_step=epoch)
# And make back-propagation according to calculated loss
g_loss.backward()
G_optimizer.step()
# Housekeeping - reset gradient
G_optimizer.zero_grad()
D.zero_grad()
# plot example and save checkpoint each odd epoch
if best_stat is None:
# print()
best_stat = np.mean(stat_list)
torch.save({
'epoch': epoch,
'stat_value': best_stat,
"d_model": D,
"d_loss": d_loss,
"d_optimizer": D_optimizer,
"g_model": G,
"g_loss": g_loss,
"g_optimizer": G_optimizer,
}, os.path.join(args.out_dir, f"models/{args.model_name}_best_for_mmd_checkpoint.pkl"))
elif np.mean(stat_list) < best_stat:
best_stat = np.mean(stat_list)
torch.save({
'epoch': epoch,
'stat_value': best_stat,
"d_model": D,
"d_loss": d_loss,
"d_optimizer": D_optimizer,
"g_model": G,
"g_loss": g_loss,
"g_optimizer": G_optimizer,
}, os.path.join(args.out_dir, f"models/{args.model_name}_best_for_mmd_checkpoint.pkl"))
tb_writer.add_scalar("MMD", np.mean(stat_list), global_step=epoch)
if epoch % 50 == 0 or epoch == args.n_epochs:
print(f'Epoch-{epoch}; D_loss: {d_loss.data.cpu().numpy()}; G_loss: {g_loss.data.cpu().numpy()}')
torch.save({
'epoch': epoch,
'stat_value': np.mean(stat_list),
"d_model": D,
"d_loss": d_loss,
"d_optimizer": D_optimizer,
"g_model": G,
"g_loss": g_loss,
"g_optimizer": G_optimizer,
}, os.path.join(args.out_dir, f"models/{args.model_name}_epoch_{epoch}_checkpoint.pkl"))
with torch.no_grad():
noise = torch.rand(args.batch_size, args.gen_l_dim, device=args.device)
fake_seq = G(noise, real_labels)
_seq = fake_seq[0].cpu().numpy() # batch_first :^)
# _label = _labels[0].cpu().numpy()
fig = save_ecg_example(_seq, f"pictures/{args.model_name}_epoch_{epoch}_example")
tb_writer.add_figure("generated_example", fig, global_step=epoch)
# TODO use visualize func here | 0.530723 | 0.137504 |
from __future__ import absolute_import, division, print_function, unicode_literals
from urllib.parse import parse_qsl
from django import forms
from django.contrib import admin
from django.db import connection, transaction
from .constants import CHOICE_ATTRIBUTE_OPTIONS, SIMPLE_ATTRIBUTE_OPTIONS
from .models import Attribute, AttributeGroup, AttributeOption, ChoiceAttribute, SimpleAttribute
class AttributeGroupAdmin(admin.ModelAdmin):
list_display = ('label', 'position')
fields = ('label', 'position')
ordering = ('position',)
actions = None
def has_delete_permission(self, request, obj=None):
return False
class AddFormMixin:
def get_form(self, request, obj=None, **kwargs):
"""
Use special form during user creation
"""
defaults = {}
if obj is None:
if self.add_form:
defaults['form'] = self.add_form
else:
raise ValueError('Missing `add_form` class attribute')
defaults.update(kwargs)
return super().get_form(request, obj, **defaults)
class AttributeMixin:
list_display = ('label', 'attribute_group', 'result_type', 'required', 'searchable', 'orderable', 'position')
fields = ('attribute_group', 'label', 'result_type', 'position', 'required', 'searchable', 'orderable')
list_filter = ('attribute_group', 'required', 'searchable', 'orderable')
ordering = ('attribute_group', 'position', 'id')
class AttributeAddForm(forms.ModelForm):
class Meta:
model = Attribute
fields = ()
def __init__(self, *args, **kwargs):
initial = kwargs.get('initial', {})
if '_changelist_filters' in initial:
changelist_filters = parse_qsl(initial.get('_changelist_filters'))
attribute_group_id = [
attr_id for key, attr_id in changelist_filters if key == 'attribute_group__id__exact'
][0]
if attribute_group_id:
attributegroup_obj = AttributeGroup.objects.get(id=attribute_group_id)
kwargs['initial'].update({'attribute_group': attributegroup_obj})
super().__init__(*args, **kwargs)
class SimpleAttributeAdmin(AddFormMixin, AttributeMixin, admin.ModelAdmin):
add_form = AttributeAddForm
actions = None
def formfield_for_choice_field(self, db_field, request, **kwargs):
if db_field.name == 'result_type':
kwargs['choices'] = SIMPLE_ATTRIBUTE_OPTIONS
return super().formfield_for_choice_field(db_field, request, **kwargs)
class ChoiceAttributeAdmin(AddFormMixin, AttributeMixin, admin.ModelAdmin):
add_form = AttributeAddForm
actions = None
def formfield_for_choice_field(self, db_field, request, **kwargs):
if db_field.name == 'result_type':
kwargs['choices'] = CHOICE_ATTRIBUTE_OPTIONS
return super().formfield_for_choice_field(db_field, request, **kwargs)
class AttributeOptionAddForm(forms.ModelForm):
class Meta:
model = AttributeOption
fields = ()
def __init__(self, *args, **kwargs):
initial = kwargs.get('initial', {})
if '_changelist_filters' in initial:
changelist_filters = parse_qsl(initial.get('_changelist_filters'))
attribute_id = [attr_id for key, attr_id in changelist_filters if key == 'attribute__id__exact'][0]
if attribute_id:
attribute_obj = Attribute.objects.get(id=attribute_id)
kwargs['initial'].update({'attribute': attribute_obj})
super().__init__(*args, **kwargs)
class AttributeOptionAdmin(AddFormMixin, admin.ModelAdmin):
fields = ('attribute', 'option', 'value', 'description', 'position')
list_filter = ('attribute', )
list_display = ('attribute', 'option', 'value', 'description', 'position')
ordering = ('attribute', 'position')
list_select_related = ('attribute', )
add_form = AttributeOptionAddForm
actions = None
def _perform_update(self, webuser_id, attr_name, current_option_val, new_option_val):
with transaction.atomic():
with connection.cursor() as cursor:
# get all features that match the criteria
cursor.execute(
'select core_utils.update_dropdown_option_value(%s, %s, %s, %s);',
(webuser_id, attr_name, current_option_val, new_option_val)
)
def delete_model(self, request, obj):
super().delete_model(request, obj)
attr_name = obj.attribute.key
current_option_val = obj.option
new_option_val = None
self._perform_update(request.user.pk, attr_name, current_option_val, new_option_val)
def save_model(self, request, obj, form, change):
super().save_model(request, obj, form, change)
if change is True:
attr_name = obj.attribute.key
current_option_val = form.initial.get('option')
new_option_val = obj.option
if current_option_val != new_option_val:
self._perform_update(request.user.pk, attr_name, current_option_val, new_option_val)
admin.site.register(AttributeGroup, AttributeGroupAdmin)
admin.site.register(SimpleAttribute, SimpleAttributeAdmin)
admin.site.register(ChoiceAttribute, ChoiceAttributeAdmin)
admin.site.register(AttributeOption, AttributeOptionAdmin) | django_project/src/attributes/admin.py | from __future__ import absolute_import, division, print_function, unicode_literals
from urllib.parse import parse_qsl
from django import forms
from django.contrib import admin
from django.db import connection, transaction
from .constants import CHOICE_ATTRIBUTE_OPTIONS, SIMPLE_ATTRIBUTE_OPTIONS
from .models import Attribute, AttributeGroup, AttributeOption, ChoiceAttribute, SimpleAttribute
class AttributeGroupAdmin(admin.ModelAdmin):
list_display = ('label', 'position')
fields = ('label', 'position')
ordering = ('position',)
actions = None
def has_delete_permission(self, request, obj=None):
return False
class AddFormMixin:
def get_form(self, request, obj=None, **kwargs):
"""
Use special form during user creation
"""
defaults = {}
if obj is None:
if self.add_form:
defaults['form'] = self.add_form
else:
raise ValueError('Missing `add_form` class attribute')
defaults.update(kwargs)
return super().get_form(request, obj, **defaults)
class AttributeMixin:
list_display = ('label', 'attribute_group', 'result_type', 'required', 'searchable', 'orderable', 'position')
fields = ('attribute_group', 'label', 'result_type', 'position', 'required', 'searchable', 'orderable')
list_filter = ('attribute_group', 'required', 'searchable', 'orderable')
ordering = ('attribute_group', 'position', 'id')
class AttributeAddForm(forms.ModelForm):
class Meta:
model = Attribute
fields = ()
def __init__(self, *args, **kwargs):
initial = kwargs.get('initial', {})
if '_changelist_filters' in initial:
changelist_filters = parse_qsl(initial.get('_changelist_filters'))
attribute_group_id = [
attr_id for key, attr_id in changelist_filters if key == 'attribute_group__id__exact'
][0]
if attribute_group_id:
attributegroup_obj = AttributeGroup.objects.get(id=attribute_group_id)
kwargs['initial'].update({'attribute_group': attributegroup_obj})
super().__init__(*args, **kwargs)
class SimpleAttributeAdmin(AddFormMixin, AttributeMixin, admin.ModelAdmin):
add_form = AttributeAddForm
actions = None
def formfield_for_choice_field(self, db_field, request, **kwargs):
if db_field.name == 'result_type':
kwargs['choices'] = SIMPLE_ATTRIBUTE_OPTIONS
return super().formfield_for_choice_field(db_field, request, **kwargs)
class ChoiceAttributeAdmin(AddFormMixin, AttributeMixin, admin.ModelAdmin):
add_form = AttributeAddForm
actions = None
def formfield_for_choice_field(self, db_field, request, **kwargs):
if db_field.name == 'result_type':
kwargs['choices'] = CHOICE_ATTRIBUTE_OPTIONS
return super().formfield_for_choice_field(db_field, request, **kwargs)
class AttributeOptionAddForm(forms.ModelForm):
class Meta:
model = AttributeOption
fields = ()
def __init__(self, *args, **kwargs):
initial = kwargs.get('initial', {})
if '_changelist_filters' in initial:
changelist_filters = parse_qsl(initial.get('_changelist_filters'))
attribute_id = [attr_id for key, attr_id in changelist_filters if key == 'attribute__id__exact'][0]
if attribute_id:
attribute_obj = Attribute.objects.get(id=attribute_id)
kwargs['initial'].update({'attribute': attribute_obj})
super().__init__(*args, **kwargs)
class AttributeOptionAdmin(AddFormMixin, admin.ModelAdmin):
fields = ('attribute', 'option', 'value', 'description', 'position')
list_filter = ('attribute', )
list_display = ('attribute', 'option', 'value', 'description', 'position')
ordering = ('attribute', 'position')
list_select_related = ('attribute', )
add_form = AttributeOptionAddForm
actions = None
def _perform_update(self, webuser_id, attr_name, current_option_val, new_option_val):
with transaction.atomic():
with connection.cursor() as cursor:
# get all features that match the criteria
cursor.execute(
'select core_utils.update_dropdown_option_value(%s, %s, %s, %s);',
(webuser_id, attr_name, current_option_val, new_option_val)
)
def delete_model(self, request, obj):
super().delete_model(request, obj)
attr_name = obj.attribute.key
current_option_val = obj.option
new_option_val = None
self._perform_update(request.user.pk, attr_name, current_option_val, new_option_val)
def save_model(self, request, obj, form, change):
super().save_model(request, obj, form, change)
if change is True:
attr_name = obj.attribute.key
current_option_val = form.initial.get('option')
new_option_val = obj.option
if current_option_val != new_option_val:
self._perform_update(request.user.pk, attr_name, current_option_val, new_option_val)
admin.site.register(AttributeGroup, AttributeGroupAdmin)
admin.site.register(SimpleAttribute, SimpleAttributeAdmin)
admin.site.register(ChoiceAttribute, ChoiceAttributeAdmin)
admin.site.register(AttributeOption, AttributeOptionAdmin) | 0.631594 | 0.069038 |
from pathlib import Path
import shutil
import click
import numpy as np
import numpy.lib.format as fmt
def get_header(files, axis):
"""get header for concatenated file
Parameters
----------
files : path-like
npy files to concatenate
axis : int, default=0
axis to cocatenate along
Returns
-------
dict
datatype descr, fortran order and shape, for concatenated file
"""
dtypes, shapes, forders = [], [], []
for file in files:
f = np.load(file, 'r')
dtypes.append(f.dtype)
shapes.append(f.shape)
forders.append(f.flags['F_CONTIGUOUS'])
if all(dtype==dtypes[0] for dtype in dtypes):
dtype = dtypes[0]
else:
raise ValueError('All files must have the same dtype')
if all(forder==forders[0] for forder in forders):
forder = forders[0]
else:
raise ValueError('All files must have the same fortran order')
if all(len(shape)==len(shapes[0]) for shape in shapes):
ndims = len(shapes[0])
else:
raise ValueError('All files must have the same number of dimensions')
if all(
all(shape[axis_]==shapes[0][axis_] for shape in shapes)
for axis_ in range(ndims) if axis_!=axis
):
shape = list(shapes[0])
shape[axis] = sum(shape_[axis] for shape_ in shapes)
shape = tuple(shape)
else:
raise ValueError('All files must have the same shape along the concatenation axis')
header = {'descr': fmt.dtype_to_descr(dtype), 'fortran_order': forder, 'shape': shape}
return header
@click.command('concat')
@click.argument('files', nargs=-1)
@click.option('-o','--output', default='concat.bin')
@click.option('-f','--force',is_flag=True,default=False)
@click.option('-t','--type',default='raw',type=click.Choice(['raw','npy']))
@click.option('-a','--axis',default=0,type=int)
def concat(files, output, force, type, axis):
output = Path(output)
files = [Path(file) for file in files]
if any(not file.is_file() for file in files):
raise FileNotFoundError('One or more files not found')
if output.is_file() and not force:
raise FileExistsError('Use -f to overwrite existing file')
print('Concatenating')
for idx, file in enumerate(files):
print('\t', idx+1, file.name)
print('Into','\n\t',output.name)
with open(output, 'wb') as outputfile:
if type=='npy':
fmt.write_array_header_2_0(outputfile, get_header(files, axis))
for file in files:
with open(file, 'rb') as inputfile:
if type=='npy': inputfile.seek(128)
shutil.copyfileobj(inputfile, outputfile)
print('Concatenation complete') | simianpy/scripts/util/concat.py | from pathlib import Path
import shutil
import click
import numpy as np
import numpy.lib.format as fmt
def get_header(files, axis):
"""get header for concatenated file
Parameters
----------
files : path-like
npy files to concatenate
axis : int, default=0
axis to cocatenate along
Returns
-------
dict
datatype descr, fortran order and shape, for concatenated file
"""
dtypes, shapes, forders = [], [], []
for file in files:
f = np.load(file, 'r')
dtypes.append(f.dtype)
shapes.append(f.shape)
forders.append(f.flags['F_CONTIGUOUS'])
if all(dtype==dtypes[0] for dtype in dtypes):
dtype = dtypes[0]
else:
raise ValueError('All files must have the same dtype')
if all(forder==forders[0] for forder in forders):
forder = forders[0]
else:
raise ValueError('All files must have the same fortran order')
if all(len(shape)==len(shapes[0]) for shape in shapes):
ndims = len(shapes[0])
else:
raise ValueError('All files must have the same number of dimensions')
if all(
all(shape[axis_]==shapes[0][axis_] for shape in shapes)
for axis_ in range(ndims) if axis_!=axis
):
shape = list(shapes[0])
shape[axis] = sum(shape_[axis] for shape_ in shapes)
shape = tuple(shape)
else:
raise ValueError('All files must have the same shape along the concatenation axis')
header = {'descr': fmt.dtype_to_descr(dtype), 'fortran_order': forder, 'shape': shape}
return header
@click.command('concat')
@click.argument('files', nargs=-1)
@click.option('-o','--output', default='concat.bin')
@click.option('-f','--force',is_flag=True,default=False)
@click.option('-t','--type',default='raw',type=click.Choice(['raw','npy']))
@click.option('-a','--axis',default=0,type=int)
def concat(files, output, force, type, axis):
output = Path(output)
files = [Path(file) for file in files]
if any(not file.is_file() for file in files):
raise FileNotFoundError('One or more files not found')
if output.is_file() and not force:
raise FileExistsError('Use -f to overwrite existing file')
print('Concatenating')
for idx, file in enumerate(files):
print('\t', idx+1, file.name)
print('Into','\n\t',output.name)
with open(output, 'wb') as outputfile:
if type=='npy':
fmt.write_array_header_2_0(outputfile, get_header(files, axis))
for file in files:
with open(file, 'rb') as inputfile:
if type=='npy': inputfile.seek(128)
shutil.copyfileobj(inputfile, outputfile)
print('Concatenation complete') | 0.592195 | 0.291371 |
'''Autogenerates mock interface implementations for MSHTML interfaces.'''
import os
import string
import sys
import com_mock
# Adjust our module path so we can import com_mock.
script_dir = os.path.abspath(os.path.dirname(__file__))
client_root = os.path.normpath(os.path.join(script_dir, '../../..'))
# The interfaces we want mocked. These have to be declared in MsHTML.h,
# and this will only work for IDispatch-derived interfaces.
# Any interface "IFoo" named here will have a corresponding IFooMockImpl
# mock implementation class in the generated output file.
_INTERFACES = [
'IHTMLDocument2',
'IHTMLDocument3',
'IHTMLDOMNode',
'IHTMLElement',
'IHTMLElementCollection',
'IHTMLStyleElement',
'IHTMLStyleSheet',
'IHTMLWindow2',
]
# Find the path to the MSHTML.h include file.
_MSHTML_PATH = None
include_dirs = os.environ['INCLUDE'].split(';')
for include_dir in include_dirs:
candidate_path = os.path.join(include_dir, 'MsHTML.h')
if os.path.exists(candidate_path):
_MSHTML_PATH = candidate_path
if not _MSHTML_PATH:
print >> sys.stderr, "Could not find MsHTML.h in any INCLUDE path."
sys.exit(2)
# Template string for output file header.
_HEADER_TEMPLATE = '''\
// This file is autogenerated by ${file} ** DO NOT EDIT **
'''
# Template string for output file footer.
_FOOTER_TEMPLATE = ''
# Template string for mock interface definition.
_INTERFACE_TEMPLATE = '''\
class ${interface}MockImpl
: public IDispatchImpl<${interface},
&IID_${interface},
&LIBID_MSHTML,
4, 0> { // Version 4.0 of the typelib.
public:
${mocks}
};
'''
def Main():
mocker = com_mock.Mocker()
mocker.AddHeaders([_MSHTML_PATH])
header_template = string.Template(_HEADER_TEMPLATE)
print header_template.substitute(file = __file__)
interface_template = string.Template(_INTERFACE_TEMPLATE)
for interface in _INTERFACES:
mocks = '\n'.join(mocker.MockInterface(interface))
print interface_template.substitute(interface = interface, mocks = mocks)
footer_template = string.Template(_FOOTER_TEMPLATE)
print footer_template.substitute(file = os.path.abspath(__file__))
if __name__ == '__main__':
Main() | ceee/testing/utils/mshtml_mocks.py | '''Autogenerates mock interface implementations for MSHTML interfaces.'''
import os
import string
import sys
import com_mock
# Adjust our module path so we can import com_mock.
script_dir = os.path.abspath(os.path.dirname(__file__))
client_root = os.path.normpath(os.path.join(script_dir, '../../..'))
# The interfaces we want mocked. These have to be declared in MsHTML.h,
# and this will only work for IDispatch-derived interfaces.
# Any interface "IFoo" named here will have a corresponding IFooMockImpl
# mock implementation class in the generated output file.
_INTERFACES = [
'IHTMLDocument2',
'IHTMLDocument3',
'IHTMLDOMNode',
'IHTMLElement',
'IHTMLElementCollection',
'IHTMLStyleElement',
'IHTMLStyleSheet',
'IHTMLWindow2',
]
# Find the path to the MSHTML.h include file.
_MSHTML_PATH = None
include_dirs = os.environ['INCLUDE'].split(';')
for include_dir in include_dirs:
candidate_path = os.path.join(include_dir, 'MsHTML.h')
if os.path.exists(candidate_path):
_MSHTML_PATH = candidate_path
if not _MSHTML_PATH:
print >> sys.stderr, "Could not find MsHTML.h in any INCLUDE path."
sys.exit(2)
# Template string for output file header.
_HEADER_TEMPLATE = '''\
// This file is autogenerated by ${file} ** DO NOT EDIT **
'''
# Template string for output file footer.
_FOOTER_TEMPLATE = ''
# Template string for mock interface definition.
_INTERFACE_TEMPLATE = '''\
class ${interface}MockImpl
: public IDispatchImpl<${interface},
&IID_${interface},
&LIBID_MSHTML,
4, 0> { // Version 4.0 of the typelib.
public:
${mocks}
};
'''
def Main():
mocker = com_mock.Mocker()
mocker.AddHeaders([_MSHTML_PATH])
header_template = string.Template(_HEADER_TEMPLATE)
print header_template.substitute(file = __file__)
interface_template = string.Template(_INTERFACE_TEMPLATE)
for interface in _INTERFACES:
mocks = '\n'.join(mocker.MockInterface(interface))
print interface_template.substitute(interface = interface, mocks = mocks)
footer_template = string.Template(_FOOTER_TEMPLATE)
print footer_template.substitute(file = os.path.abspath(__file__))
if __name__ == '__main__':
Main() | 0.303525 | 0.050729 |
import torch
import torch.nn as nn
from torch.nn.utils import weight_norm
from audio_zen.fvcore.nn import FlopCountAnalysis, flop_count_str
class Chomp1d(nn.Module):
def __init__(self, chomp_size):
super(Chomp1d, self).__init__()
self.chomp_size = chomp_size
def forward(self, x):
return x[:, :, :-self.chomp_size].contiguous()
class TemporalBlock(nn.Module):
def __init__(self, n_inputs, n_outputs, kernel_size, stride, dilation, padding, dropout=0.2):
super(TemporalBlock, self).__init__()
self.conv1 = weight_norm(
nn.Conv1d(n_inputs, n_outputs, kernel_size, stride=stride, padding=padding, dilation=dilation)
)
self.chomp1 = Chomp1d(padding)
self.relu1 = nn.ReLU()
self.dropout1 = nn.Dropout(dropout)
self.conv2 = weight_norm(nn.Conv1d(n_outputs, n_outputs, kernel_size,
stride=stride, padding=padding, dilation=dilation))
self.chomp2 = Chomp1d(padding)
self.relu2 = nn.ReLU()
self.dropout2 = nn.Dropout(dropout)
self.net = nn.Sequential(self.conv1, self.chomp1, self.relu1, self.dropout1,
self.conv2, self.chomp2, self.relu2, self.dropout2)
self.downsample = nn.Conv1d(n_inputs, n_outputs, kernel_size=1) if n_inputs != n_outputs else None
self.relu = nn.ReLU()
self.init_weights()
def init_weights(self):
self.conv1.weight.data.normal_(0, 0.01)
self.conv2.weight.data.normal_(0, 0.01)
if self.downsample is not None:
self.downsample.weight.data.normal_(0, 0.01)
def forward(self, x):
out = self.net(x)
res = x if self.downsample is None else self.downsample(x)
return self.relu(out + res)
class TemporalConvNet(nn.Module):
def __init__(self, num_inputs, num_channels, kernel_size=2, dropout=0.2):
"""
Args:
num_inputs:
num_channels: The list of all channels?
kernel_size:
dropout:
Inputs: x
- x: x has a dimension of [B, C, T]
"""
super(TemporalConvNet, self).__init__()
layers = []
num_levels = len(num_channels)
for i in range(num_levels):
dilation_size = 2 ** i
in_channels = num_inputs if i == 0 else num_channels[i - 1]
out_channels = num_channels[i]
layers += [TemporalBlock(in_channels, out_channels, kernel_size, stride=1, dilation=dilation_size,
padding=(kernel_size-1) * dilation_size, dropout=dropout)]
self.network = nn.Sequential(*layers)
def forward(self, x):
return self.network(x)
class CausalConvBlock(nn.Module):
def __init__(self, in_channels, out_channels, encoder_activate_function, **kwargs):
"""
Args:
in_channels:
out_channels:
encoder_activate_function:
**kwargs:
"""
super().__init__()
self.conv = nn.Conv2d(
in_channels=in_channels,
out_channels=out_channels,
kernel_size=(3, 2),
stride=(2, 1),
padding=(0, 1),
**kwargs # 这里不是左右 pad，而是上下 pad 为 0，左右分别 pad 1...
)
self.norm = nn.BatchNorm2d(out_channels)
self.activation = getattr(nn, encoder_activate_function)()
def forward(self, x):
"""
2D Causal convolution.
Args:
x: [B, C, F, T]
Returns:
[B, C, F, T]
"""
x = self.conv(x)
x = x[:, :, :, :-1] # chomp size
x = self.norm(x)
x = self.activation(x)
return x
class CausalTransConvBlock(nn.Module):
def __init__(self, in_channels, out_channels, is_last=False, output_padding=(0, 0)):
super().__init__()
self.conv = nn.ConvTranspose2d(
in_channels=in_channels,
out_channels=out_channels,
kernel_size=(3, 2),
stride=(2, 1),
output_padding=output_padding
)
self.norm = nn.BatchNorm2d(out_channels)
if is_last:
self.activation = nn.ReLU()
else:
self.activation = nn.ELU()
def forward(self, x):
"""
2D Causal convolution.
Args:
x: [B, C, F, T]
Returns:
[B, C, F, T]
"""
x = self.conv(x)
x = x[:, :, :, :-1] # chomp size
x = self.norm(x)
x = self.activation(x)
return x | audio_zen/model/module/causal_conv.py | import torch
import torch.nn as nn
from torch.nn.utils import weight_norm
from audio_zen.fvcore.nn import FlopCountAnalysis, flop_count_str
class Chomp1d(nn.Module):
def __init__(self, chomp_size):
super(Chomp1d, self).__init__()
self.chomp_size = chomp_size
def forward(self, x):
return x[:, :, :-self.chomp_size].contiguous()
class TemporalBlock(nn.Module):
def __init__(self, n_inputs, n_outputs, kernel_size, stride, dilation, padding, dropout=0.2):
super(TemporalBlock, self).__init__()
self.conv1 = weight_norm(
nn.Conv1d(n_inputs, n_outputs, kernel_size, stride=stride, padding=padding, dilation=dilation)
)
self.chomp1 = Chomp1d(padding)
self.relu1 = nn.ReLU()
self.dropout1 = nn.Dropout(dropout)
self.conv2 = weight_norm(nn.Conv1d(n_outputs, n_outputs, kernel_size,
stride=stride, padding=padding, dilation=dilation))
self.chomp2 = Chomp1d(padding)
self.relu2 = nn.ReLU()
self.dropout2 = nn.Dropout(dropout)
self.net = nn.Sequential(self.conv1, self.chomp1, self.relu1, self.dropout1,
self.conv2, self.chomp2, self.relu2, self.dropout2)
self.downsample = nn.Conv1d(n_inputs, n_outputs, kernel_size=1) if n_inputs != n_outputs else None
self.relu = nn.ReLU()
self.init_weights()
def init_weights(self):
self.conv1.weight.data.normal_(0, 0.01)
self.conv2.weight.data.normal_(0, 0.01)
if self.downsample is not None:
self.downsample.weight.data.normal_(0, 0.01)
def forward(self, x):
out = self.net(x)
res = x if self.downsample is None else self.downsample(x)
return self.relu(out + res)
class TemporalConvNet(nn.Module):
def __init__(self, num_inputs, num_channels, kernel_size=2, dropout=0.2):
"""
Args:
num_inputs:
num_channels: The list of all channels?
kernel_size:
dropout:
Inputs: x
- x: x has a dimension of [B, C, T]
"""
super(TemporalConvNet, self).__init__()
layers = []
num_levels = len(num_channels)
for i in range(num_levels):
dilation_size = 2 ** i
in_channels = num_inputs if i == 0 else num_channels[i - 1]
out_channels = num_channels[i]
layers += [TemporalBlock(in_channels, out_channels, kernel_size, stride=1, dilation=dilation_size,
padding=(kernel_size-1) * dilation_size, dropout=dropout)]
self.network = nn.Sequential(*layers)
def forward(self, x):
return self.network(x)
class CausalConvBlock(nn.Module):
def __init__(self, in_channels, out_channels, encoder_activate_function, **kwargs):
"""
Args:
in_channels:
out_channels:
encoder_activate_function:
**kwargs:
"""
super().__init__()
self.conv = nn.Conv2d(
in_channels=in_channels,
out_channels=out_channels,
kernel_size=(3, 2),
stride=(2, 1),
padding=(0, 1),
**kwargs # 这里不是左右 pad，而是上下 pad 为 0，左右分别 pad 1...
)
self.norm = nn.BatchNorm2d(out_channels)
self.activation = getattr(nn, encoder_activate_function)()
def forward(self, x):
"""
2D Causal convolution.
Args:
x: [B, C, F, T]
Returns:
[B, C, F, T]
"""
x = self.conv(x)
x = x[:, :, :, :-1] # chomp size
x = self.norm(x)
x = self.activation(x)
return x
class CausalTransConvBlock(nn.Module):
def __init__(self, in_channels, out_channels, is_last=False, output_padding=(0, 0)):
super().__init__()
self.conv = nn.ConvTranspose2d(
in_channels=in_channels,
out_channels=out_channels,
kernel_size=(3, 2),
stride=(2, 1),
output_padding=output_padding
)
self.norm = nn.BatchNorm2d(out_channels)
if is_last:
self.activation = nn.ReLU()
else:
self.activation = nn.ELU()
def forward(self, x):
"""
2D Causal convolution.
Args:
x: [B, C, F, T]
Returns:
[B, C, F, T]
"""
x = self.conv(x)
x = x[:, :, :, :-1] # chomp size
x = self.norm(x)
x = self.activation(x)
return x | 0.953449 | 0.419707 |
import cPickle
from fltk import *
Fl.scheme('plastic')
class Subject:
def __init__(self):
self.observers = []
def attach(self, observer):
self.observers.append(observer)
def detach(self, observer):
self.observers.remove(observer)
def notify(self, event=None):
for observer in self.observers:
observer.update(event, self)
class Observer:
def update(self, event, subject):
raise NotImplementedError("Must subclass me")
class BaseSettings:
def __init__(self):
self.x = 100; self.y = 100; self.w = 800; self.h = 650
def load(self, fileName):
try:
self.__dict__.update(cPickle.load(open(fileName, 'r')).__dict__)
except:
pass
def save(self, fileName):
cPickle.dump(self, open(fileName, 'w'))
def setToApp(self, window):
window.position(self.x, self.y)
window.size(self.w, self.h)
def getFromApp(self, window):
self.x = window.x(); self.y = window.y(); self.w = window.w(); self.h = window.h()
class BaseWnd(Fl_Window):
def __init__(self, rect=None, title='BaseWnd', settings=BaseSettings()):
Fl_Window.__init__(self, 100, 100, 600, 400, title)
self.settingsFile = ''
if rect == None:
self.settingsFile = title+'.settings'
else:
self.position(rect[0], rect[1])
self.size(rect[2], rect[3])
# self.settingsFile = title+'.settings'
# if rect[0]!=None and rect[1]!=None:
# self.position(rect[0], rect[1])
# if rect[2]!=None and rect[3]!=None:
# self.size(rect[2], rect[3])
self.settings = settings
self.callback(self.onClose)
def show(self):
if len(self.settingsFile)>0:
self.settings.load(self.settingsFile)
self.settings.setToApp(self)
Fl_Window.show(self)
def onClose(self, data):
if len(self.settingsFile)>0:
self.settings.getFromApp(self)
self.settings.save(self.settingsFile)
self.default_callback(self, data) | PyCommon/modules/GUI/ysBaseUI.py | import cPickle
from fltk import *
Fl.scheme('plastic')
class Subject:
def __init__(self):
self.observers = []
def attach(self, observer):
self.observers.append(observer)
def detach(self, observer):
self.observers.remove(observer)
def notify(self, event=None):
for observer in self.observers:
observer.update(event, self)
class Observer:
def update(self, event, subject):
raise NotImplementedError("Must subclass me")
class BaseSettings:
def __init__(self):
self.x = 100; self.y = 100; self.w = 800; self.h = 650
def load(self, fileName):
try:
self.__dict__.update(cPickle.load(open(fileName, 'r')).__dict__)
except:
pass
def save(self, fileName):
cPickle.dump(self, open(fileName, 'w'))
def setToApp(self, window):
window.position(self.x, self.y)
window.size(self.w, self.h)
def getFromApp(self, window):
self.x = window.x(); self.y = window.y(); self.w = window.w(); self.h = window.h()
class BaseWnd(Fl_Window):
def __init__(self, rect=None, title='BaseWnd', settings=BaseSettings()):
Fl_Window.__init__(self, 100, 100, 600, 400, title)
self.settingsFile = ''
if rect == None:
self.settingsFile = title+'.settings'
else:
self.position(rect[0], rect[1])
self.size(rect[2], rect[3])
# self.settingsFile = title+'.settings'
# if rect[0]!=None and rect[1]!=None:
# self.position(rect[0], rect[1])
# if rect[2]!=None and rect[3]!=None:
# self.size(rect[2], rect[3])
self.settings = settings
self.callback(self.onClose)
def show(self):
if len(self.settingsFile)>0:
self.settings.load(self.settingsFile)
self.settings.setToApp(self)
Fl_Window.show(self)
def onClose(self, data):
if len(self.settingsFile)>0:
self.settings.getFromApp(self)
self.settings.save(self.settingsFile)
self.default_callback(self, data) | 0.18451 | 0.065247 |
class MkldnnTest(object):
mkldnn_target_test_filename = 'mkl-dnn-c'
def __init__(self, target):
self.target = target
def tear_down(self):
self.target.run('rm /tmp/%s' % self.mkldnn_target_test_filename)
def test_mkldnn_can_compile_and_execute(self):
mkldnn_src_dir = '/usr/src/debug/onednn/'
mkldnn_src_test_filename = 'api.c'
mkldnn_src_test_file = ''
(__, output) = self.target.run('cd %s; find -name %s' % (mkldnn_src_dir, mkldnn_src_test_filename))
if 'No such file or directory' in output:
return -1, output
mkldnn_src_test_file = os.path.join(mkldnn_src_dir, output)
(status, output) = self.target.run('gcc %s -o /tmp/%s -ldnnl' % (mkldnn_src_test_file, self.mkldnn_target_test_filename))
if status:
return status, output
(status, output) = self.target.run('cd /tmp; ./%s' % self.mkldnn_target_test_filename)
return status, output
def test_mkldnn_benchdnn_package_available(self):
(status, output) = self.target.run('ls /usr/bin/mkl-dnn/tests/benchdnn')
return status, output
def _run_mkldnn_benchdnn_test(self, cmd):
(status, output) = self.target.run('cd /usr/bin/mkl-dnn/tests/benchdnn; %s' % cmd)
return status, output
def test_mkldnn_conv_api(self):
return self._run_mkldnn_benchdnn_test('./benchdnn --conv --batch=inputs/conv/test_conv_3d')
def test_mkldnn_bnorm_api(self):
return self._run_mkldnn_benchdnn_test('./benchdnn --bnorm --batch=inputs/bnorm/test_bnorm_regressions')
def test_mkldnn_deconv_api(self):
return self._run_mkldnn_benchdnn_test('./benchdnn --deconv --batch=inputs/deconv/test_deconv_bfloat16')
def test_mkldnn_ip_api(self):
return self._run_mkldnn_benchdnn_test('./benchdnn --ip --batch=inputs/ip/test_ip_bfloat16')
def test_mkldnn_reorder_api(self):
return self._run_mkldnn_benchdnn_test('./benchdnn --reorder --batch=inputs/reorder/test_reorder_bfloat16')
def test_mkldnn_rnn_api(self):
return self._run_mkldnn_benchdnn_test('./benchdnn --rnn --batch=inputs/rnn/test_rnn_all')
def test_mkldnn_shuffle_api(self):
return self._run_mkldnn_benchdnn_test('./benchdnn --shuffle --batch=inputs/shuffle/test_shuffle_bfloat16') | lib/oeqa/runtime/miutils/tests/mkl_dnn_test.py | class MkldnnTest(object):
mkldnn_target_test_filename = 'mkl-dnn-c'
def __init__(self, target):
self.target = target
def tear_down(self):
self.target.run('rm /tmp/%s' % self.mkldnn_target_test_filename)
def test_mkldnn_can_compile_and_execute(self):
mkldnn_src_dir = '/usr/src/debug/onednn/'
mkldnn_src_test_filename = 'api.c'
mkldnn_src_test_file = ''
(__, output) = self.target.run('cd %s; find -name %s' % (mkldnn_src_dir, mkldnn_src_test_filename))
if 'No such file or directory' in output:
return -1, output
mkldnn_src_test_file = os.path.join(mkldnn_src_dir, output)
(status, output) = self.target.run('gcc %s -o /tmp/%s -ldnnl' % (mkldnn_src_test_file, self.mkldnn_target_test_filename))
if status:
return status, output
(status, output) = self.target.run('cd /tmp; ./%s' % self.mkldnn_target_test_filename)
return status, output
def test_mkldnn_benchdnn_package_available(self):
(status, output) = self.target.run('ls /usr/bin/mkl-dnn/tests/benchdnn')
return status, output
def _run_mkldnn_benchdnn_test(self, cmd):
(status, output) = self.target.run('cd /usr/bin/mkl-dnn/tests/benchdnn; %s' % cmd)
return status, output
def test_mkldnn_conv_api(self):
return self._run_mkldnn_benchdnn_test('./benchdnn --conv --batch=inputs/conv/test_conv_3d')
def test_mkldnn_bnorm_api(self):
return self._run_mkldnn_benchdnn_test('./benchdnn --bnorm --batch=inputs/bnorm/test_bnorm_regressions')
def test_mkldnn_deconv_api(self):
return self._run_mkldnn_benchdnn_test('./benchdnn --deconv --batch=inputs/deconv/test_deconv_bfloat16')
def test_mkldnn_ip_api(self):
return self._run_mkldnn_benchdnn_test('./benchdnn --ip --batch=inputs/ip/test_ip_bfloat16')
def test_mkldnn_reorder_api(self):
return self._run_mkldnn_benchdnn_test('./benchdnn --reorder --batch=inputs/reorder/test_reorder_bfloat16')
def test_mkldnn_rnn_api(self):
return self._run_mkldnn_benchdnn_test('./benchdnn --rnn --batch=inputs/rnn/test_rnn_all')
def test_mkldnn_shuffle_api(self):
return self._run_mkldnn_benchdnn_test('./benchdnn --shuffle --batch=inputs/shuffle/test_shuffle_bfloat16') | 0.302906 | 0.147187 |
from django.db import models
from archfinch.main.models import Item, SlicedRawManager
from archfinch.users.models import User
from archfinch.links.thresholds import *
class LinkManager(SlicedRawManager):
def recommended_generic(self, category=None, tags=None, new=False):
'''
Fetches links recommended generally (not for a specific user).
'''
where = []
params = {}
if category is not None:
where.append('mi.category_id = %(category_id)s')
params['category_id'] = category.id
if tags:
for tag in tags:
where.append('EXISTS (SELECT 1 FROM main_tagged mtgd WHERE mi.id = mtgd.item_id AND mtgd.tag_id = %d)' % (int(tag.id)))
elif not new:
# front page
where.append('wilson_score(mi.id, true) >= %(threshold_frontpage)s')
params['threshold_frontpage'] = threshold_frontpage
if where:
where = 'WHERE '+' AND '.join(where)
else:
where = ''
# Select items in order of their recommendation to self
#
# recommendation =
# sum (rating-3)*similarity for all similar users
#
# where
# rating: what the user has rated the item
# similarity: similarity between the user and self
recommended = Link.objects.slicedraw("""
SELECT * FROM (SELECT mi.id, mi.category_id, mi.parent_id, mi.name, ll.item_ptr_id, ll.time,
mc.element_singular AS category_element
FROM main_item mi
INNER JOIN main_category mc
ON mc.id=mi.category_id
INNER JOIN links_link ll
ON ll.item_ptr_id=mi.id
"""+where+"""
ORDER BY time DESC) AS recommended""",
params)
return recommended
def recommended(self, user, category=None, category_id=None, tags=None, followed=False, new=False):
'''
Fetches links recommended for the user.
'''
where = ''
joins = ''
params = {'user_id': user.id}
if category is not None and category:
category_id = category.id
if category_id is not None:
where += ' AND mi.category_id = %(category_id)s'
params['category_id'] = category_id
followed_or = False
show_submissions = False
if tags:
for tag in tags:
where += ' AND EXISTS (SELECT 1 FROM main_tagged mtgd WHERE mi.id = mtgd.item_id AND mtgd.tag_id = %d)' % (int(tag.id))
elif not followed and not new:
# front page
where += ' AND wilson_score(mi.id, true) >= %(threshold_frontpage)s'
params['threshold_frontpage'] = threshold_frontpage
# add the user's follows to their frontpage
followed = True
followed_or = True
show_submissions = True
if followed and user.tagfollow_set.exists():
if followed_or:
where += ' OR'
else:
where += ' AND'
where += ' EXISTS (SELECT 1 FROM main_tagged mtgd WHERE mi.id = mtgd.item_id AND mtgd.tag_id in %(followed_tag_ids)s)'
params['followed_tag_ids'] = tuple(map(lambda follow: follow.tag.id, user.tagfollow_set.all()))
if show_submissions:
where += ' OR mi.submitter_id = %(user_id)s'
# Select items in order of their recommendation to self
#
# recommendation =
# sum (rating-3)*similarity for all similar users
#
# where
# rating: what the user has rated the item
# similarity: similarity between the user and self
recommended = Link.objects.slicedraw("""
SELECT mi.id, mi.category_id, mi.parent_id, mi.name, ll.item_ptr_id, ll.time,
mis.comment_count, mis.popular_tags as _popular_tags, url, image, submitter_id,
au.username AS submitter_username,
COALESCE((SELECT rating FROM main_opinion mo WHERE mo.user_id=%(user_id)s AND mo.item_id=mi.id)) AS rating,
mc.element_singular AS category_element
FROM main_item mi
INNER JOIN main_category mc
ON mc.id=mi.category_id
INNER JOIN links_link ll
ON ll.item_ptr_id=mi.id
INNER JOIN main_itemstats mis
ON mi.id=mis.item_id
INNER JOIN auth_user au
ON au.id=mi.submitter_id
WHERE
NOT EXISTS (SELECT 1 FROM main_tagblock mtb, main_tagged mtgd WHERE mtgd.tag_id=mtb.tag_id AND mtb.user_id=%(user_id)s AND mtgd.item_id=ll.item_ptr_id)
"""+where+"""
ORDER BY time DESC
""",
params)
return recommended
class ImageURLField(models.CharField):
"""Image URL field, stored as url,width,height in the database"""
__metaclass__ = models.SubfieldBase
def to_python(self, value):
if value is None: return
if not isinstance(value, basestring): return value
fields = value.split(',')
if len(fields) < 3:
return {'url': fields[0]}
return {'url': fields[0], 'width': int(fields[1]), 'height': int(fields[2])}
def get_prep_value(self, value):
if value is None: return
try:
return ','.join([value['url'], str(value['width']), str(value['height'])])
except KeyError:
return value['url']
class Link(Item):
url = models.URLField(verify_exists=False, max_length=1000, blank=True, null=True)
time = models.DateTimeField(auto_now_add=True, unique=False)
thumbnail = ImageURLField(max_length=1000, blank=True, null=True)
image = ImageURLField(max_length=1000, blank=True, null=True)
html = models.TextField(max_length=1000, blank=True, null=True)
objects = LinkManager()
def age(self):
import datetime
age = (datetime.datetime.now() - self.time)
return age.seconds+age.days*60*60*24
def views(self):
age = self.age()
multiplier = 113 + self.id % 20
if age < 15*60:
views = (age/900.)**2 * multiplier
elif age < 60*60*24:
views = (age/900.) * multiplier
else:
views = 96 * multiplier + age/360.
return int(views) | links/models.py | from django.db import models
from archfinch.main.models import Item, SlicedRawManager
from archfinch.users.models import User
from archfinch.links.thresholds import *
class LinkManager(SlicedRawManager):
def recommended_generic(self, category=None, tags=None, new=False):
'''
Fetches links recommended generally (not for a specific user).
'''
where = []
params = {}
if category is not None:
where.append('mi.category_id = %(category_id)s')
params['category_id'] = category.id
if tags:
for tag in tags:
where.append('EXISTS (SELECT 1 FROM main_tagged mtgd WHERE mi.id = mtgd.item_id AND mtgd.tag_id = %d)' % (int(tag.id)))
elif not new:
# front page
where.append('wilson_score(mi.id, true) >= %(threshold_frontpage)s')
params['threshold_frontpage'] = threshold_frontpage
if where:
where = 'WHERE '+' AND '.join(where)
else:
where = ''
# Select items in order of their recommendation to self
#
# recommendation =
# sum (rating-3)*similarity for all similar users
#
# where
# rating: what the user has rated the item
# similarity: similarity between the user and self
recommended = Link.objects.slicedraw("""
SELECT * FROM (SELECT mi.id, mi.category_id, mi.parent_id, mi.name, ll.item_ptr_id, ll.time,
mc.element_singular AS category_element
FROM main_item mi
INNER JOIN main_category mc
ON mc.id=mi.category_id
INNER JOIN links_link ll
ON ll.item_ptr_id=mi.id
"""+where+"""
ORDER BY time DESC) AS recommended""",
params)
return recommended
def recommended(self, user, category=None, category_id=None, tags=None, followed=False, new=False):
'''
Fetches links recommended for the user.
'''
where = ''
joins = ''
params = {'user_id': user.id}
if category is not None and category:
category_id = category.id
if category_id is not None:
where += ' AND mi.category_id = %(category_id)s'
params['category_id'] = category_id
followed_or = False
show_submissions = False
if tags:
for tag in tags:
where += ' AND EXISTS (SELECT 1 FROM main_tagged mtgd WHERE mi.id = mtgd.item_id AND mtgd.tag_id = %d)' % (int(tag.id))
elif not followed and not new:
# front page
where += ' AND wilson_score(mi.id, true) >= %(threshold_frontpage)s'
params['threshold_frontpage'] = threshold_frontpage
# add the user's follows to their frontpage
followed = True
followed_or = True
show_submissions = True
if followed and user.tagfollow_set.exists():
if followed_or:
where += ' OR'
else:
where += ' AND'
where += ' EXISTS (SELECT 1 FROM main_tagged mtgd WHERE mi.id = mtgd.item_id AND mtgd.tag_id in %(followed_tag_ids)s)'
params['followed_tag_ids'] = tuple(map(lambda follow: follow.tag.id, user.tagfollow_set.all()))
if show_submissions:
where += ' OR mi.submitter_id = %(user_id)s'
# Select items in order of their recommendation to self
#
# recommendation =
# sum (rating-3)*similarity for all similar users
#
# where
# rating: what the user has rated the item
# similarity: similarity between the user and self
recommended = Link.objects.slicedraw("""
SELECT mi.id, mi.category_id, mi.parent_id, mi.name, ll.item_ptr_id, ll.time,
mis.comment_count, mis.popular_tags as _popular_tags, url, image, submitter_id,
au.username AS submitter_username,
COALESCE((SELECT rating FROM main_opinion mo WHERE mo.user_id=%(user_id)s AND mo.item_id=mi.id)) AS rating,
mc.element_singular AS category_element
FROM main_item mi
INNER JOIN main_category mc
ON mc.id=mi.category_id
INNER JOIN links_link ll
ON ll.item_ptr_id=mi.id
INNER JOIN main_itemstats mis
ON mi.id=mis.item_id
INNER JOIN auth_user au
ON au.id=mi.submitter_id
WHERE
NOT EXISTS (SELECT 1 FROM main_tagblock mtb, main_tagged mtgd WHERE mtgd.tag_id=mtb.tag_id AND mtb.user_id=%(user_id)s AND mtgd.item_id=ll.item_ptr_id)
"""+where+"""
ORDER BY time DESC
""",
params)
return recommended
class ImageURLField(models.CharField):
"""Image URL field, stored as url,width,height in the database"""
__metaclass__ = models.SubfieldBase
def to_python(self, value):
if value is None: return
if not isinstance(value, basestring): return value
fields = value.split(',')
if len(fields) < 3:
return {'url': fields[0]}
return {'url': fields[0], 'width': int(fields[1]), 'height': int(fields[2])}
def get_prep_value(self, value):
if value is None: return
try:
return ','.join([value['url'], str(value['width']), str(value['height'])])
except KeyError:
return value['url']
class Link(Item):
url = models.URLField(verify_exists=False, max_length=1000, blank=True, null=True)
time = models.DateTimeField(auto_now_add=True, unique=False)
thumbnail = ImageURLField(max_length=1000, blank=True, null=True)
image = ImageURLField(max_length=1000, blank=True, null=True)
html = models.TextField(max_length=1000, blank=True, null=True)
objects = LinkManager()
def age(self):
import datetime
age = (datetime.datetime.now() - self.time)
return age.seconds+age.days*60*60*24
def views(self):
age = self.age()
multiplier = 113 + self.id % 20
if age < 15*60:
views = (age/900.)**2 * multiplier
elif age < 60*60*24:
views = (age/900.) * multiplier
else:
views = 96 * multiplier + age/360.
return int(views) | 0.331877 | 0.122392 |
import traceback
import sys
import time
import datetime
import string
import sqlite3
'''USER CONFIGURATION'''
#TIMESTAMP = '%A %d %B %Y'
TIMESTAMP = '%a %d %b %Y'
#The time format.
# "%A %d %B %Y" = "Wendesday 04 June 2014"
#http://docs.python.org/2/library/time.html#time.strftime
HEADER = ""
#Put this at the top of the .txt file
FORMAT = "_timestamp_: [_title_](_slink_) - /u/_author_ (+_score_)"
FORMAT_HTML = "_timestamp_: <a href=\"_shortlink_\">[_flairtext_] _title_</a> - <a href=\"_authorlink_\">_author_</a> (+_score_)<br>"
HTMLHEADER = '<html style="font-family:Consolas;font-size:10pt;">'
TSFORMAT = ""
#USE THESE INJECTORS TO CREATE CUSTOM OUTPUT
#_timestamp_ which follows the TIMESTAMP format
#_title_
#_url_
#_subreddit_
#_shortlink_
#_author_
#_authorlink_
#_numcomments_
#_score_
#_flairtext_
#_flaircss_
READ_FROM_FILE = ""
PRINTFILE = ""
SCORETHRESH = 0
HTMLMODE = False
USERMODE = False
BREAKDOWNMODE = False
EXTENSION = '.txt'
# Variables are input by user during the
# inputvars() method
'''All done!'''
class Post:
#Generic class to convert SQL columns into an object
pass
sql = None
cur = None
# 0 - idint
# 1 - idstr
# 2 - created
# 3 - self
# 4 - nsfw
# 5 - author
# 6 - title
# 7 - url
# 8 - selftext
# 9 - score
# 10 - subreddit
# 11 - distinguished
# 12 - textlen
# 13 - num_comments
# 14 - flair_text
# 15 - flair_css_class
def createpost(postdata):
post = Post()
post.id = postdata[1]
if 't3_' in post.id or 't1_' in post.id:
post.fullname = post.id
post.id = post.id.split('_')[1]
else:
post.fullname = 't3_' + post.id
post.type = int(post.fullname.split('_')[0][-1])
post.created_utc = postdata[2]
post.is_self = postdata[3]
post.over_18 = postdata[4]
post.author = postdata[5]
post.title = postdata[6]
post.title = post.title.replace('\n', '')
post.url = postdata[7]
post.selftext = postdata[8]
post.score = postdata[9]
post.subreddit = postdata[10]
post.distinguished = postdata[11]
post.textlen = postdata[12]
post.num_comments = postdata[13]
post.link_flair_text = postdata[14]
post.link_flair_css_class = postdata[15]
post.short_link = 'http://redd.it/' + post.id
return post
def preparefile(filesuffix):
filesuffix += EXTENSION
listfile = open(PRINTFILE + filesuffix, 'w', encoding='utf-8')
if HTMLMODE is True:
print(HTMLHEADER, file=listfile)
return listfile
def closefile(listfile):
if HTMLMODE is True:
print('</html>', file=listfile)
listfile.close()
def work(listfile):
if HEADER != '':
print(HEADER, file=listfile)
previous_timestamp = ''
while True:
post = cur.fetchone()
if post is None:
break
post = createpost(post)
if post.score < SCORETHRESH:
continue
if post.type != 3:
continue
timestamp = post.created_utc
timestamp = datetime.datetime.fromtimestamp(int(timestamp)).strftime(TIMESTAMP)
if HTMLMODE:
final = FORMAT_HTML
else:
final = FORMAT
if timestamp != previous_timestamp:
final = TSFORMAT + final
final = final.replace('_timestamp_', timestamp)
final = final.replace('_title_', post.title)
flair_text = post.link_flair_text if post.link_flair_text else ""
flair_css = post.link_flair_css_class if post.link_flair_css_class else ""
post.link_flair_text = flair_text
post.link_flair_css_class = flair_css
final = final.replace('_flairtext_', flair_text)
final = final.replace('_flaircss_', flair_css)
authorlink = 'http://reddit.com/u/' + post.author
final = final.replace('_author_', post.author)
final = final.replace('_authorlink_', authorlink)
final = final.replace('_subreddit_', post.subreddit)
url = post.url
if url is None:
url = post.short_link
else:
url = url.replace('http://www.reddit.com', 'http://np.reddit.com')
final = final.replace('_url_', url)
shortlink = post.short_link
#slink = slink.replace('http://', 'http://np.')
final = final.replace('_slink_', shortlink)
final = final.replace('_flairtext_', flair_text)
final = final.replace('_score_', str(post.score))
final = final.replace('_numcomments_', str(post.num_comments))
print(final, file=listfile)
previous_timestamp = timestamp
def writefiles():
print('Writing time files')
listfile = preparefile('_date')
cur.execute('SELECT * FROM posts WHERE score >= ? ORDER BY created DESC', [SCORETHRESH])
work(listfile)
closefile(listfile)
print('Writing title files')
listfile = preparefile('_title')
cur.execute('SELECT * FROM posts WHERE score >= ? ORDER BY title ASC', [SCORETHRESH])
work(listfile)
closefile(listfile)
print('Writing score files')
listfile = preparefile('_score')
cur.execute('SELECT * FROM posts WHERE score >= ? ORDER BY score DESC', [SCORETHRESH])
work(listfile)
closefile(listfile)
if USERMODE is False:
print('Writing author files')
listfile = preparefile('_author')
cur.execute('SELECT * FROM posts WHERE score >= ? ORDER BY author ASC', [SCORETHRESH])
work(listfile)
closefile(listfile)
if USERMODE is True:
print('Writing subreddit files')
listfile = preparefile('_subreddit')
cur.execute('SELECT * FROM posts WHERE score >= ? ORDER BY subreddit ASC', [SCORETHRESH])
work(listfile)
closefile(listfile)
print('Writing flair file')
listfile = preparefile('_flair')
cur.execute('SELECT * FROM posts WHERE score >= ? AND flair_text IS NOT NULL ORDER BY flair_text, created ASC', [SCORETHRESH])
work(listfile)
cur.execute('SELECT * FROM posts WHERE score >= ? AND flair_text IS NULL ORDER BY flair_text, created ASC', [SCORETHRESH])
work(listfile)
closefile(listfile)
print('Done.')
def breakdown(doreturn=False, mode='user'):
print('\nBreaking it down...')
listfile = preparefile('')
if mode == 'subreddit':
cur.execute('SELECT * FROM posts WHERE score >= ? ORDER BY author ASC', [SCORETHRESH])
if mode == 'user':
cur.execute('SELECT * FROM posts WHERE score >= ? ORDER BY subreddit ASC', [SCORETHRESH])
count_submissions = 0
count_comments = 0
previous = ''
breakdowndict = {}
while True:
post = cur.fetchone()
if post is None:
breakdowndict[previous] = {'submissions':count_submissions, 'comments':count_comments}
break
post = createpost(post)
if mode == 'subreddit':
relevant = post.author
elif mode == 'user':
relevant = post.subreddit
if relevant != previous:
breakdowndict[previous] = {'submissions':count_submissions, 'comments':count_comments}
previous = relevant
count_submissions = 0
count_comments = 0
if post.type == 1:
count_comments += 1
if post.type == 3:
count_submissions += 1
del breakdowndict['']
if doreturn is True:
return breakdowndict
keys = list(breakdowndict.keys())
longestkey = max([len(k) for k in keys])
keys.sort(key=lambda x: (breakdowndict[x]['submissions'] + breakdowndict[x]['comments'], x), reverse=True)
out = []
for k in keys:
relevant = (' '*(longestkey-len(k))) + ('"%s"' % k)
submissions = breakdowndict[k]['submissions']
comments = breakdowndict[k]['comments']
o = '%s:{%s:%d, %s:%d}' % (relevant, '"submissions"', submissions, '"comments"', comments)
out.append(o)
out = ',\n'.join(out)
out = '{\n' + out + '\n}'
print(out, file=listfile)
#json.dump(breakdowndict, listfile, sort_keys=True, indent=4)
def inputvars():
global READ_FROM_FILE
global PRINTFILE
global SCORETHRESH
global HTMLMODE
global USERMODE
global BREAKDOWNMODE
global EXTENSION
global sql
global cur
try:
READ_FROM_FILE = sys.argv[1]
except IndexError:
READ_FROM_FILE = input('] Input database = ')
if READ_FROM_FILE[-3:] != '.db':
READ_FROM_FILE += '.db'
filename = READ_FROM_FILE.replace('\\', '/')
filename = filename.split('/')[-1]
if filename[0] == '@':
USERMODE = True
try:
PRINTFILE = sys.argv[2]
except IndexError:
PRINTFILE = input('] Output filename = ')
try:
SCORETHRESH = int(sys.argv[3])
except IndexError:
SCORETHRESH = int(input('] Score threshold = '))
HTMLMODE = '.html' in PRINTFILE
BREAKDOWNMODE = '.json' in PRINTFILE
if HTMLMODE:
EXTENSION = '.html'
PRINTFILE = PRINTFILE.replace('.html', '')
elif BREAKDOWNMODE:
EXTENSION = '.json'
PRINTFILE = PRINTFILE.replace('.json', '')
else:
EXTENSION = '.txt'
PRINTFILE = PRINTFILE.replace('.txt', '')
sql = sqlite3.connect(READ_FROM_FILE)
cur = sql.cursor()
def main():
inputvars()
if BREAKDOWNMODE is False:
writefiles()
else:
if USERMODE is True:
breakdown(mode='user')
else:
breakdown(mode='subreddit')
if __name__ == '__main__':
main() | Redmash/redmash_db.py | import traceback
import sys
import time
import datetime
import string
import sqlite3
'''USER CONFIGURATION'''
#TIMESTAMP = '%A %d %B %Y'
TIMESTAMP = '%a %d %b %Y'
#The time format.
# "%A %d %B %Y" = "Wendesday 04 June 2014"
#http://docs.python.org/2/library/time.html#time.strftime
HEADER = ""
#Put this at the top of the .txt file
FORMAT = "_timestamp_: [_title_](_slink_) - /u/_author_ (+_score_)"
FORMAT_HTML = "_timestamp_: <a href=\"_shortlink_\">[_flairtext_] _title_</a> - <a href=\"_authorlink_\">_author_</a> (+_score_)<br>"
HTMLHEADER = '<html style="font-family:Consolas;font-size:10pt;">'
TSFORMAT = ""
#USE THESE INJECTORS TO CREATE CUSTOM OUTPUT
#_timestamp_ which follows the TIMESTAMP format
#_title_
#_url_
#_subreddit_
#_shortlink_
#_author_
#_authorlink_
#_numcomments_
#_score_
#_flairtext_
#_flaircss_
READ_FROM_FILE = ""
PRINTFILE = ""
SCORETHRESH = 0
HTMLMODE = False
USERMODE = False
BREAKDOWNMODE = False
EXTENSION = '.txt'
# Variables are input by user during the
# inputvars() method
'''All done!'''
class Post:
#Generic class to convert SQL columns into an object
pass
sql = None
cur = None
# 0 - idint
# 1 - idstr
# 2 - created
# 3 - self
# 4 - nsfw
# 5 - author
# 6 - title
# 7 - url
# 8 - selftext
# 9 - score
# 10 - subreddit
# 11 - distinguished
# 12 - textlen
# 13 - num_comments
# 14 - flair_text
# 15 - flair_css_class
def createpost(postdata):
post = Post()
post.id = postdata[1]
if 't3_' in post.id or 't1_' in post.id:
post.fullname = post.id
post.id = post.id.split('_')[1]
else:
post.fullname = 't3_' + post.id
post.type = int(post.fullname.split('_')[0][-1])
post.created_utc = postdata[2]
post.is_self = postdata[3]
post.over_18 = postdata[4]
post.author = postdata[5]
post.title = postdata[6]
post.title = post.title.replace('\n', '')
post.url = postdata[7]
post.selftext = postdata[8]
post.score = postdata[9]
post.subreddit = postdata[10]
post.distinguished = postdata[11]
post.textlen = postdata[12]
post.num_comments = postdata[13]
post.link_flair_text = postdata[14]
post.link_flair_css_class = postdata[15]
post.short_link = 'http://redd.it/' + post.id
return post
def preparefile(filesuffix):
filesuffix += EXTENSION
listfile = open(PRINTFILE + filesuffix, 'w', encoding='utf-8')
if HTMLMODE is True:
print(HTMLHEADER, file=listfile)
return listfile
def closefile(listfile):
if HTMLMODE is True:
print('</html>', file=listfile)
listfile.close()
def work(listfile):
if HEADER != '':
print(HEADER, file=listfile)
previous_timestamp = ''
while True:
post = cur.fetchone()
if post is None:
break
post = createpost(post)
if post.score < SCORETHRESH:
continue
if post.type != 3:
continue
timestamp = post.created_utc
timestamp = datetime.datetime.fromtimestamp(int(timestamp)).strftime(TIMESTAMP)
if HTMLMODE:
final = FORMAT_HTML
else:
final = FORMAT
if timestamp != previous_timestamp:
final = TSFORMAT + final
final = final.replace('_timestamp_', timestamp)
final = final.replace('_title_', post.title)
flair_text = post.link_flair_text if post.link_flair_text else ""
flair_css = post.link_flair_css_class if post.link_flair_css_class else ""
post.link_flair_text = flair_text
post.link_flair_css_class = flair_css
final = final.replace('_flairtext_', flair_text)
final = final.replace('_flaircss_', flair_css)
authorlink = 'http://reddit.com/u/' + post.author
final = final.replace('_author_', post.author)
final = final.replace('_authorlink_', authorlink)
final = final.replace('_subreddit_', post.subreddit)
url = post.url
if url is None:
url = post.short_link
else:
url = url.replace('http://www.reddit.com', 'http://np.reddit.com')
final = final.replace('_url_', url)
shortlink = post.short_link
#slink = slink.replace('http://', 'http://np.')
final = final.replace('_slink_', shortlink)
final = final.replace('_flairtext_', flair_text)
final = final.replace('_score_', str(post.score))
final = final.replace('_numcomments_', str(post.num_comments))
print(final, file=listfile)
previous_timestamp = timestamp
def writefiles():
print('Writing time files')
listfile = preparefile('_date')
cur.execute('SELECT * FROM posts WHERE score >= ? ORDER BY created DESC', [SCORETHRESH])
work(listfile)
closefile(listfile)
print('Writing title files')
listfile = preparefile('_title')
cur.execute('SELECT * FROM posts WHERE score >= ? ORDER BY title ASC', [SCORETHRESH])
work(listfile)
closefile(listfile)
print('Writing score files')
listfile = preparefile('_score')
cur.execute('SELECT * FROM posts WHERE score >= ? ORDER BY score DESC', [SCORETHRESH])
work(listfile)
closefile(listfile)
if USERMODE is False:
print('Writing author files')
listfile = preparefile('_author')
cur.execute('SELECT * FROM posts WHERE score >= ? ORDER BY author ASC', [SCORETHRESH])
work(listfile)
closefile(listfile)
if USERMODE is True:
print('Writing subreddit files')
listfile = preparefile('_subreddit')
cur.execute('SELECT * FROM posts WHERE score >= ? ORDER BY subreddit ASC', [SCORETHRESH])
work(listfile)
closefile(listfile)
print('Writing flair file')
listfile = preparefile('_flair')
cur.execute('SELECT * FROM posts WHERE score >= ? AND flair_text IS NOT NULL ORDER BY flair_text, created ASC', [SCORETHRESH])
work(listfile)
cur.execute('SELECT * FROM posts WHERE score >= ? AND flair_text IS NULL ORDER BY flair_text, created ASC', [SCORETHRESH])
work(listfile)
closefile(listfile)
print('Done.')
def breakdown(doreturn=False, mode='user'):
print('\nBreaking it down...')
listfile = preparefile('')
if mode == 'subreddit':
cur.execute('SELECT * FROM posts WHERE score >= ? ORDER BY author ASC', [SCORETHRESH])
if mode == 'user':
cur.execute('SELECT * FROM posts WHERE score >= ? ORDER BY subreddit ASC', [SCORETHRESH])
count_submissions = 0
count_comments = 0
previous = ''
breakdowndict = {}
while True:
post = cur.fetchone()
if post is None:
breakdowndict[previous] = {'submissions':count_submissions, 'comments':count_comments}
break
post = createpost(post)
if mode == 'subreddit':
relevant = post.author
elif mode == 'user':
relevant = post.subreddit
if relevant != previous:
breakdowndict[previous] = {'submissions':count_submissions, 'comments':count_comments}
previous = relevant
count_submissions = 0
count_comments = 0
if post.type == 1:
count_comments += 1
if post.type == 3:
count_submissions += 1
del breakdowndict['']
if doreturn is True:
return breakdowndict
keys = list(breakdowndict.keys())
longestkey = max([len(k) for k in keys])
keys.sort(key=lambda x: (breakdowndict[x]['submissions'] + breakdowndict[x]['comments'], x), reverse=True)
out = []
for k in keys:
relevant = (' '*(longestkey-len(k))) + ('"%s"' % k)
submissions = breakdowndict[k]['submissions']
comments = breakdowndict[k]['comments']
o = '%s:{%s:%d, %s:%d}' % (relevant, '"submissions"', submissions, '"comments"', comments)
out.append(o)
out = ',\n'.join(out)
out = '{\n' + out + '\n}'
print(out, file=listfile)
#json.dump(breakdowndict, listfile, sort_keys=True, indent=4)
def inputvars():
global READ_FROM_FILE
global PRINTFILE
global SCORETHRESH
global HTMLMODE
global USERMODE
global BREAKDOWNMODE
global EXTENSION
global sql
global cur
try:
READ_FROM_FILE = sys.argv[1]
except IndexError:
READ_FROM_FILE = input('] Input database = ')
if READ_FROM_FILE[-3:] != '.db':
READ_FROM_FILE += '.db'
filename = READ_FROM_FILE.replace('\\', '/')
filename = filename.split('/')[-1]
if filename[0] == '@':
USERMODE = True
try:
PRINTFILE = sys.argv[2]
except IndexError:
PRINTFILE = input('] Output filename = ')
try:
SCORETHRESH = int(sys.argv[3])
except IndexError:
SCORETHRESH = int(input('] Score threshold = '))
HTMLMODE = '.html' in PRINTFILE
BREAKDOWNMODE = '.json' in PRINTFILE
if HTMLMODE:
EXTENSION = '.html'
PRINTFILE = PRINTFILE.replace('.html', '')
elif BREAKDOWNMODE:
EXTENSION = '.json'
PRINTFILE = PRINTFILE.replace('.json', '')
else:
EXTENSION = '.txt'
PRINTFILE = PRINTFILE.replace('.txt', '')
sql = sqlite3.connect(READ_FROM_FILE)
cur = sql.cursor()
def main():
inputvars()
if BREAKDOWNMODE is False:
writefiles()
else:
if USERMODE is True:
breakdown(mode='user')
else:
breakdown(mode='subreddit')
if __name__ == '__main__':
main() | 0.104924 | 0.083143 |
import numpy as np
from pathlib import Path
import matplotlib.pyplot as plt
import math
from MiniFramework.NeuralNet_4_0 import *
from MiniFramework.ActivationLayer import *
from MiniFramework.ClassificationLayer import *
from MiniFramework.DataReader_2_0 import *
train_data_name = "../../Data/ch10.train.npz"
test_data_name = "../../Data/ch10.test.npz"
def DrawTwoCategoryPoints(X1, X2, Y, xlabel="x1", ylabel="x2", title=None, show=False, isPredicate=False):
colors = ['b', 'r']
shapes = ['o', 'x']
assert(X1.shape[0] == X2.shape[0] == Y.shape[0])
count = X1.shape[0]
for i in range(count):
j = (int)(round(Y[i]))
if j < 0:
j = 0
if isPredicate:
plt.scatter(X1[i], X2[i], color=colors[j], marker='^', s=200, zorder=10)
else:
plt.scatter(X1[i], X2[i], color=colors[j], marker=shapes[j], zorder=10)
# end for
plt.xlabel(xlabel)
plt.ylabel(ylabel)
if title is not None:
plt.title(title)
if show:
plt.show()
def ShowDataHelper(x1,x2,y,title,xlabel,ylabel,show,grid=True):
fig = plt.figure(figsize=(6,6))
if grid:
plt.grid()
DrawTwoCategoryPoints(x1,x2,y,xlabel,ylabel,title,show)
def Prepare3DData(net, count):
x = np.linspace(0,1,count)
y = np.linspace(0,1,count)
X, Y = np.meshgrid(x, y)
if net is not None:
input = np.hstack((X.ravel().reshape(count*count,1),Y.ravel().reshape(count*count,1)))
net.inference(input)
return X, Y
def ShowResult2D(net, dr):
ShowDataHelper(dr.XTrain[:,0], dr.XTrain[:,1], dr.YTrain[:,0],
"Classifier Result", "x1", "x2", False, False)
count = 50
X,Y = Prepare3DData(net, count)
Z = net.output.reshape(count,count)
plt.contourf(X, Y, Z, cmap=plt.cm.Spectral, zorder=1)
plt.show()
#end def
def load_data():
dataReader = DataReader_2_0(train_data_name, test_data_name)
dataReader.ReadData()
dataReader.NormalizeX()
dataReader.Shuffle()
dataReader.GenerateValidationSet()
return dataReader
def model(dataReader):
num_input = 2
num_hidden = 3
num_output = 1
max_epoch = 1000
batch_size = 5
learning_rate = 0.1
params = HyperParameters_4_0(
learning_rate, max_epoch, batch_size,
net_type=NetType.BinaryClassifier,
init_method=InitialMethod.Xavier,
stopper=Stopper(StopCondition.StopLoss, 0.02))
net = NeuralNet_4_0(params, "Arc")
fc1 = FcLayer_1_0(num_input, num_hidden, params)
net.add_layer(fc1, "fc1")
sigmoid1 = ActivationLayer(Sigmoid())
net.add_layer(sigmoid1, "sigmoid1")
fc2 = FcLayer_1_0(num_hidden, num_output, params)
net.add_layer(fc2, "fc2")
logistic = ClassificationLayer(Logistic())
net.add_layer(logistic, "logistic")
net.train(dataReader, checkpoint=10, need_test=True)
return net
if __name__ == '__main__':
dr = load_data()
net = model(dr)
net.ShowLossHistory()
ShowResult2D(net, dr) | 基础教程/A2-神经网络基本原理/第7步 - 深度神经网络/src/ch14-DnnBasic/Level3_ch10.py |
import numpy as np
from pathlib import Path
import matplotlib.pyplot as plt
import math
from MiniFramework.NeuralNet_4_0 import *
from MiniFramework.ActivationLayer import *
from MiniFramework.ClassificationLayer import *
from MiniFramework.DataReader_2_0 import *
train_data_name = "../../Data/ch10.train.npz"
test_data_name = "../../Data/ch10.test.npz"
def DrawTwoCategoryPoints(X1, X2, Y, xlabel="x1", ylabel="x2", title=None, show=False, isPredicate=False):
colors = ['b', 'r']
shapes = ['o', 'x']
assert(X1.shape[0] == X2.shape[0] == Y.shape[0])
count = X1.shape[0]
for i in range(count):
j = (int)(round(Y[i]))
if j < 0:
j = 0
if isPredicate:
plt.scatter(X1[i], X2[i], color=colors[j], marker='^', s=200, zorder=10)
else:
plt.scatter(X1[i], X2[i], color=colors[j], marker=shapes[j], zorder=10)
# end for
plt.xlabel(xlabel)
plt.ylabel(ylabel)
if title is not None:
plt.title(title)
if show:
plt.show()
def ShowDataHelper(x1,x2,y,title,xlabel,ylabel,show,grid=True):
fig = plt.figure(figsize=(6,6))
if grid:
plt.grid()
DrawTwoCategoryPoints(x1,x2,y,xlabel,ylabel,title,show)
def Prepare3DData(net, count):
x = np.linspace(0,1,count)
y = np.linspace(0,1,count)
X, Y = np.meshgrid(x, y)
if net is not None:
input = np.hstack((X.ravel().reshape(count*count,1),Y.ravel().reshape(count*count,1)))
net.inference(input)
return X, Y
def ShowResult2D(net, dr):
ShowDataHelper(dr.XTrain[:,0], dr.XTrain[:,1], dr.YTrain[:,0],
"Classifier Result", "x1", "x2", False, False)
count = 50
X,Y = Prepare3DData(net, count)
Z = net.output.reshape(count,count)
plt.contourf(X, Y, Z, cmap=plt.cm.Spectral, zorder=1)
plt.show()
#end def
def load_data():
dataReader = DataReader_2_0(train_data_name, test_data_name)
dataReader.ReadData()
dataReader.NormalizeX()
dataReader.Shuffle()
dataReader.GenerateValidationSet()
return dataReader
def model(dataReader):
num_input = 2
num_hidden = 3
num_output = 1
max_epoch = 1000
batch_size = 5
learning_rate = 0.1
params = HyperParameters_4_0(
learning_rate, max_epoch, batch_size,
net_type=NetType.BinaryClassifier,
init_method=InitialMethod.Xavier,
stopper=Stopper(StopCondition.StopLoss, 0.02))
net = NeuralNet_4_0(params, "Arc")
fc1 = FcLayer_1_0(num_input, num_hidden, params)
net.add_layer(fc1, "fc1")
sigmoid1 = ActivationLayer(Sigmoid())
net.add_layer(sigmoid1, "sigmoid1")
fc2 = FcLayer_1_0(num_hidden, num_output, params)
net.add_layer(fc2, "fc2")
logistic = ClassificationLayer(Logistic())
net.add_layer(logistic, "logistic")
net.train(dataReader, checkpoint=10, need_test=True)
return net
if __name__ == '__main__':
dr = load_data()
net = model(dr)
net.ShowLossHistory()
ShowResult2D(net, dr) | 0.511717 | 0.461563 |
import os.path
import random
from os.path import join
import numpy as np
from bert4keras.backend import keras, K
from bert4keras.layers import Loss
from bert4keras.models import build_transformer_model
from bert4keras.tokenizers import Tokenizer
from bert4keras.optimizers import Adam, extend_with_weight_decay
from bert4keras.snippets import DataGenerator, sequence_padding
from bert4keras.snippets import text_segmentate, truncate_sequences
from bert4keras.snippets import AutoRegressiveDecoder
import jieba
from shutil import copy
jieba.initialize()
# 基本信息
maxlen = 100
batch_size = 32
epochs = 50
save_dir = "./output/roformer_base"
model_dir = "./model_data/public_model/chinese_roformer-char_L-12_H-768_A-12"
# bert配置
config_path = join(model_dir, 'bert_config.json')
checkpoint_path = join(model_dir, 'bert_model.ckpt')
dict_path = join(model_dir, 'vocab.txt')
steps_per_epoch = 90000 // batch_size
# 建立分词器
tokenizer = Tokenizer(dict_path, do_lower_case=True)
if not os.path.exists(save_dir):
os.makedirs(save_dir)
# 获取一部分待编码的句子
with open("./model_data/hold_out/dev.txt", "r", encoding="utf8") as fr:
dev_data = [line.strip().split("\t")[::-1] for line in fr] # title,query
def split(text):
"""分割句子
"""
seps, strips = u'\n。！？!?；;，, ', u'；;，, '
return text_segmentate(text, maxlen * 1.2, seps, strips)
def corpus():
"""读取语料
"""
with open("./model_data/hold_out/train.txt", "r", encoding="utf8") as fr:
data = [line.strip().split("\t")[::-1] for line in fr]
print("data example:{}", data[0])
while True:
random.shuffle(data)
for item in data:
yield item
def masked_encode(text):
"""wwm随机mask
"""
words = jieba.lcut(text)
rands = np.random.random(len(words))
source, target = [tokenizer._token_start_id], [0]
for r, w in zip(rands, words):
ids = tokenizer.encode(w)[0][1:-1]
if r < 0.15 * 0.8:
source.extend([tokenizer._token_mask_id] * len(ids))
target.extend(ids)
elif r < 0.15 * 0.9:
source.extend(ids)
target.extend(ids)
elif r < 0.15:
source.extend(
np.random.choice(tokenizer._vocab_size - 1, size=len(ids)) + 1
)
target.extend(ids)
else:
source.extend(ids)
target.extend([0] * len(ids))
source = source[:maxlen - 1] + [tokenizer._token_end_id]
target = target[:maxlen - 1] + [0]
return source, target
class data_generator(DataGenerator):
"""数据生成器
"""
def __init__(self, *args, **kwargs):
super(data_generator, self).__init__(*args, **kwargs)
self.some_samples = []
def __iter__(self, random=False):
batch_token_ids, batch_segment_ids = [], []
for is_end, (text, synonym) in self.sample(random):
for i in range(2):
if np.random.random() < 0.5:
text_ids = masked_encode(text)[0]
else:
text_ids = tokenizer.encode(text)[0]
synonym_ids = tokenizer.encode(synonym)[0][1:]
truncate_sequences(maxlen * 2, -2, text_ids, synonym_ids)
token_ids = text_ids + synonym_ids
segment_ids = [0] * len(text_ids) + [1] * len(synonym_ids)
batch_token_ids.append(token_ids)
batch_segment_ids.append(segment_ids)
self.some_samples.append(synonym)
if len(self.some_samples) > 1000:
self.some_samples.pop(0)
text, synonym = synonym, text
if len(batch_token_ids) == self.batch_size or is_end:
batch_token_ids = sequence_padding(batch_token_ids)
batch_segment_ids = sequence_padding(batch_segment_ids)
yield [batch_token_ids, batch_segment_ids], None
batch_token_ids, batch_segment_ids = [], []
class TotalLoss(Loss):
"""loss分两部分，一是seq2seq的交叉熵，二是相似度的交叉熵。
"""
def compute_loss(self, inputs, mask=None):
loss1 = self.compute_loss_of_seq2seq(inputs, mask)
loss2 = self.compute_loss_of_similarity(inputs, mask)
self.add_metric(loss1, name='seq2seq_loss')
self.add_metric(loss2, name='similarity_loss')
return loss1 + loss2
def compute_loss_of_seq2seq(self, inputs, mask=None):
y_true, y_mask, _, y_pred = inputs
y_true = y_true[:, 1:] # 目标token_ids
y_mask = y_mask[:, 1:] # segment_ids，刚好指示了要预测的部分
y_pred = y_pred[:, :-1] # 预测序列，错开一位
loss = K.sparse_categorical_crossentropy(
y_true, y_pred, from_logits=True
)
loss = K.sum(loss * y_mask) / K.sum(y_mask)
return loss
def compute_loss_of_similarity(self, inputs, mask=None):
_, _, y_pred, _ = inputs
y_true = self.get_labels_of_similarity(y_pred) # 构建标签
y_pred = K.l2_normalize(y_pred, axis=1) # 句向量归一化
similarities = K.dot(y_pred, K.transpose(y_pred)) # 相似度矩阵
similarities = similarities - K.eye(K.shape(y_pred)[0]) * 1e12 # 排除对角线
similarities = similarities * 20 # scale
loss = K.categorical_crossentropy(
y_true, similarities, from_logits=True
)
return loss
def get_labels_of_similarity(self, y_pred):
idxs = K.arange(0, K.shape(y_pred)[0])
idxs_1 = idxs[None, :]
idxs_2 = (idxs + 1 - idxs % 2 * 2)[:, None]
labels = K.equal(idxs_1, idxs_2)
labels = K.cast(labels, K.floatx())
return labels
# 建立加载模型
roformer = build_transformer_model(
config_path,
checkpoint_path,
model='roformer',
application='unilm',
with_pool='linear',
with_mlm='linear',
dropout_rate=0.2,
ignore_invalid_weights=True,
return_keras_model=False,
)
encoder = keras.models.Model(roformer.inputs, roformer.outputs[0])
seq2seq = keras.models.Model(roformer.inputs, roformer.outputs[1])
outputs = TotalLoss([2, 3])(roformer.inputs + roformer.outputs)
model = keras.models.Model(roformer.inputs, outputs)
AdamW = extend_with_weight_decay(Adam, 'AdamW')
optimizer = AdamW(learning_rate=1e-5, weight_decay_rate=0.01)
model.compile(optimizer=optimizer)
model.summary()
class SynonymsGenerator(AutoRegressiveDecoder):
"""seq2seq解码器
"""
@AutoRegressiveDecoder.wraps(default_rtype='logits')
def predict(self, inputs, output_ids, step):
token_ids, segment_ids = inputs
token_ids = np.concatenate([token_ids, output_ids], 1)
segment_ids = np.concatenate([segment_ids, np.ones_like(output_ids)], 1)
return self.last_token(seq2seq).predict([token_ids, segment_ids])
def generate(self, text, n=1, topp=0.95):
token_ids, segment_ids = tokenizer.encode(text, maxlen=maxlen)
output_ids = self.random_sample([token_ids, segment_ids], n,
topp=topp) # 基于随机采样
return [tokenizer.decode(ids) for ids in output_ids]
synonyms_generator = SynonymsGenerator(
start_id=None, end_id=tokenizer._token_end_id, maxlen=maxlen
)
def gen_synonyms(text, n=100, k=20):
""""含义： 产生sent的n个相似句，然后返回最相似的k个。
做法：用seq2seq生成，并用encoder算相似度并排序。
效果：
>>> gen_synonyms(u'微信和支付宝哪个好？')
[
u'微信和支付宝，哪个好?',
u'微信和支付宝哪个好',
u'支付宝和微信哪个好',
u'支付宝和微信哪个好啊',
u'微信和支付宝那个好用？',
u'微信和支付宝哪个好用',
u'支付宝和微信那个更好',
u'支付宝和微信哪个好用',
u'微信和支付宝用起来哪个好？',
u'微信和支付宝选哪个好',
]
"""
r = synonyms_generator.generate(text, n)
r = [i for i in set(r) if i != text]
r = [text] + r
X, S = [], []
for t in r:
x, s = tokenizer.encode(t)
X.append(x)
S.append(s)
X = sequence_padding(X)
S = sequence_padding(S)
Z = encoder.predict([X, S])
Z /= (Z ** 2).sum(axis=1, keepdims=True) ** 0.5
argsort = np.dot(Z[1:], -Z[0]).argsort()
return [r[i + 1] for i in argsort[:k]]
def just_show():
"""随机观察一些样本的效果
"""
S = random.sample(dev_data, 3)
for title, query in S:
try:
print(u'标题：%s' % title)
print("标准问句:{}".format(query))
print(u'生成的问题：')
print(gen_synonyms(title, 10, 10))
print()
except:
pass
class Evaluate(keras.callbacks.Callback):
"""评估模型
"""
def __init__(self):
self.lowest = 1e10
def on_epoch_end(self, epoch, logs=None):
# model.save_weights(join(save_dir, 'latest_model.weights'))
if epoch % 4 == 0:
roformer.save_weights_as_checkpoint(join(save_dir, "epoch-{}/bert_model.ckpt".format(epoch + 1)))
copy(config_path, join(save_dir, "epoch-{}/bert_config.json".format(epoch + 1)))
copy(dict_path, join(save_dir, "epoch-{}/vocab.txt".format(epoch + 1)))
# 保存最优
if logs['loss'] <= self.lowest:
self.lowest = logs['loss']
roformer.save_weights_as_checkpoint(join(save_dir, "best_model/bert_model.ckpt".format(epoch + 1)))
copy(config_path, join(save_dir, "best_model/bert_config.json".format(epoch + 1)))
copy(dict_path, join(save_dir, "best_model/vocab.txt".format(epoch + 1)))
# 演示效果
just_show()
if __name__ == '__main__':
train_generator = data_generator(corpus(), batch_size)
evaluator = Evaluate()
model.fit_generator(
train_generator.forfit(),
steps_per_epoch=steps_per_epoch,
epochs=epochs,
callbacks=[evaluator]
) | main.py | import os.path
import random
from os.path import join
import numpy as np
from bert4keras.backend import keras, K
from bert4keras.layers import Loss
from bert4keras.models import build_transformer_model
from bert4keras.tokenizers import Tokenizer
from bert4keras.optimizers import Adam, extend_with_weight_decay
from bert4keras.snippets import DataGenerator, sequence_padding
from bert4keras.snippets import text_segmentate, truncate_sequences
from bert4keras.snippets import AutoRegressiveDecoder
import jieba
from shutil import copy
jieba.initialize()
# 基本信息
maxlen = 100
batch_size = 32
epochs = 50
save_dir = "./output/roformer_base"
model_dir = "./model_data/public_model/chinese_roformer-char_L-12_H-768_A-12"
# bert配置
config_path = join(model_dir, 'bert_config.json')
checkpoint_path = join(model_dir, 'bert_model.ckpt')
dict_path = join(model_dir, 'vocab.txt')
steps_per_epoch = 90000 // batch_size
# 建立分词器
tokenizer = Tokenizer(dict_path, do_lower_case=True)
if not os.path.exists(save_dir):
os.makedirs(save_dir)
# 获取一部分待编码的句子
with open("./model_data/hold_out/dev.txt", "r", encoding="utf8") as fr:
dev_data = [line.strip().split("\t")[::-1] for line in fr] # title,query
def split(text):
"""分割句子
"""
seps, strips = u'\n。！？!?；;，, ', u'；;，, '
return text_segmentate(text, maxlen * 1.2, seps, strips)
def corpus():
"""读取语料
"""
with open("./model_data/hold_out/train.txt", "r", encoding="utf8") as fr:
data = [line.strip().split("\t")[::-1] for line in fr]
print("data example:{}", data[0])
while True:
random.shuffle(data)
for item in data:
yield item
def masked_encode(text):
"""wwm随机mask
"""
words = jieba.lcut(text)
rands = np.random.random(len(words))
source, target = [tokenizer._token_start_id], [0]
for r, w in zip(rands, words):
ids = tokenizer.encode(w)[0][1:-1]
if r < 0.15 * 0.8:
source.extend([tokenizer._token_mask_id] * len(ids))
target.extend(ids)
elif r < 0.15 * 0.9:
source.extend(ids)
target.extend(ids)
elif r < 0.15:
source.extend(
np.random.choice(tokenizer._vocab_size - 1, size=len(ids)) + 1
)
target.extend(ids)
else:
source.extend(ids)
target.extend([0] * len(ids))
source = source[:maxlen - 1] + [tokenizer._token_end_id]
target = target[:maxlen - 1] + [0]
return source, target
class data_generator(DataGenerator):
"""数据生成器
"""
def __init__(self, *args, **kwargs):
super(data_generator, self).__init__(*args, **kwargs)
self.some_samples = []
def __iter__(self, random=False):
batch_token_ids, batch_segment_ids = [], []
for is_end, (text, synonym) in self.sample(random):
for i in range(2):
if np.random.random() < 0.5:
text_ids = masked_encode(text)[0]
else:
text_ids = tokenizer.encode(text)[0]
synonym_ids = tokenizer.encode(synonym)[0][1:]
truncate_sequences(maxlen * 2, -2, text_ids, synonym_ids)
token_ids = text_ids + synonym_ids
segment_ids = [0] * len(text_ids) + [1] * len(synonym_ids)
batch_token_ids.append(token_ids)
batch_segment_ids.append(segment_ids)
self.some_samples.append(synonym)
if len(self.some_samples) > 1000:
self.some_samples.pop(0)
text, synonym = synonym, text
if len(batch_token_ids) == self.batch_size or is_end:
batch_token_ids = sequence_padding(batch_token_ids)
batch_segment_ids = sequence_padding(batch_segment_ids)
yield [batch_token_ids, batch_segment_ids], None
batch_token_ids, batch_segment_ids = [], []
class TotalLoss(Loss):
"""loss分两部分，一是seq2seq的交叉熵，二是相似度的交叉熵。
"""
def compute_loss(self, inputs, mask=None):
loss1 = self.compute_loss_of_seq2seq(inputs, mask)
loss2 = self.compute_loss_of_similarity(inputs, mask)
self.add_metric(loss1, name='seq2seq_loss')
self.add_metric(loss2, name='similarity_loss')
return loss1 + loss2
def compute_loss_of_seq2seq(self, inputs, mask=None):
y_true, y_mask, _, y_pred = inputs
y_true = y_true[:, 1:] # 目标token_ids
y_mask = y_mask[:, 1:] # segment_ids，刚好指示了要预测的部分
y_pred = y_pred[:, :-1] # 预测序列，错开一位
loss = K.sparse_categorical_crossentropy(
y_true, y_pred, from_logits=True
)
loss = K.sum(loss * y_mask) / K.sum(y_mask)
return loss
def compute_loss_of_similarity(self, inputs, mask=None):
_, _, y_pred, _ = inputs
y_true = self.get_labels_of_similarity(y_pred) # 构建标签
y_pred = K.l2_normalize(y_pred, axis=1) # 句向量归一化
similarities = K.dot(y_pred, K.transpose(y_pred)) # 相似度矩阵
similarities = similarities - K.eye(K.shape(y_pred)[0]) * 1e12 # 排除对角线
similarities = similarities * 20 # scale
loss = K.categorical_crossentropy(
y_true, similarities, from_logits=True
)
return loss
def get_labels_of_similarity(self, y_pred):
idxs = K.arange(0, K.shape(y_pred)[0])
idxs_1 = idxs[None, :]
idxs_2 = (idxs + 1 - idxs % 2 * 2)[:, None]
labels = K.equal(idxs_1, idxs_2)
labels = K.cast(labels, K.floatx())
return labels
# 建立加载模型
roformer = build_transformer_model(
config_path,
checkpoint_path,
model='roformer',
application='unilm',
with_pool='linear',
with_mlm='linear',
dropout_rate=0.2,
ignore_invalid_weights=True,
return_keras_model=False,
)
encoder = keras.models.Model(roformer.inputs, roformer.outputs[0])
seq2seq = keras.models.Model(roformer.inputs, roformer.outputs[1])
outputs = TotalLoss([2, 3])(roformer.inputs + roformer.outputs)
model = keras.models.Model(roformer.inputs, outputs)
AdamW = extend_with_weight_decay(Adam, 'AdamW')
optimizer = AdamW(learning_rate=1e-5, weight_decay_rate=0.01)
model.compile(optimizer=optimizer)
model.summary()
class SynonymsGenerator(AutoRegressiveDecoder):
"""seq2seq解码器
"""
@AutoRegressiveDecoder.wraps(default_rtype='logits')
def predict(self, inputs, output_ids, step):
token_ids, segment_ids = inputs
token_ids = np.concatenate([token_ids, output_ids], 1)
segment_ids = np.concatenate([segment_ids, np.ones_like(output_ids)], 1)
return self.last_token(seq2seq).predict([token_ids, segment_ids])
def generate(self, text, n=1, topp=0.95):
token_ids, segment_ids = tokenizer.encode(text, maxlen=maxlen)
output_ids = self.random_sample([token_ids, segment_ids], n,
topp=topp) # 基于随机采样
return [tokenizer.decode(ids) for ids in output_ids]
synonyms_generator = SynonymsGenerator(
start_id=None, end_id=tokenizer._token_end_id, maxlen=maxlen
)
def gen_synonyms(text, n=100, k=20):
""""含义： 产生sent的n个相似句，然后返回最相似的k个。
做法：用seq2seq生成，并用encoder算相似度并排序。
效果：
>>> gen_synonyms(u'微信和支付宝哪个好？')
[
u'微信和支付宝，哪个好?',
u'微信和支付宝哪个好',
u'支付宝和微信哪个好',
u'支付宝和微信哪个好啊',
u'微信和支付宝那个好用？',
u'微信和支付宝哪个好用',
u'支付宝和微信那个更好',
u'支付宝和微信哪个好用',
u'微信和支付宝用起来哪个好？',
u'微信和支付宝选哪个好',
]
"""
r = synonyms_generator.generate(text, n)
r = [i for i in set(r) if i != text]
r = [text] + r
X, S = [], []
for t in r:
x, s = tokenizer.encode(t)
X.append(x)
S.append(s)
X = sequence_padding(X)
S = sequence_padding(S)
Z = encoder.predict([X, S])
Z /= (Z ** 2).sum(axis=1, keepdims=True) ** 0.5
argsort = np.dot(Z[1:], -Z[0]).argsort()
return [r[i + 1] for i in argsort[:k]]
def just_show():
"""随机观察一些样本的效果
"""
S = random.sample(dev_data, 3)
for title, query in S:
try:
print(u'标题：%s' % title)
print("标准问句:{}".format(query))
print(u'生成的问题：')
print(gen_synonyms(title, 10, 10))
print()
except:
pass
class Evaluate(keras.callbacks.Callback):
"""评估模型
"""
def __init__(self):
self.lowest = 1e10
def on_epoch_end(self, epoch, logs=None):
# model.save_weights(join(save_dir, 'latest_model.weights'))
if epoch % 4 == 0:
roformer.save_weights_as_checkpoint(join(save_dir, "epoch-{}/bert_model.ckpt".format(epoch + 1)))
copy(config_path, join(save_dir, "epoch-{}/bert_config.json".format(epoch + 1)))
copy(dict_path, join(save_dir, "epoch-{}/vocab.txt".format(epoch + 1)))
# 保存最优
if logs['loss'] <= self.lowest:
self.lowest = logs['loss']
roformer.save_weights_as_checkpoint(join(save_dir, "best_model/bert_model.ckpt".format(epoch + 1)))
copy(config_path, join(save_dir, "best_model/bert_config.json".format(epoch + 1)))
copy(dict_path, join(save_dir, "best_model/vocab.txt".format(epoch + 1)))
# 演示效果
just_show()
if __name__ == '__main__':
train_generator = data_generator(corpus(), batch_size)
evaluator = Evaluate()
model.fit_generator(
train_generator.forfit(),
steps_per_epoch=steps_per_epoch,
epochs=epochs,
callbacks=[evaluator]
) | 0.538012 | 0.17441 |
from widgets.MessageFrame import MessageFrame
from widgets.ConsoleFrame import ConsoleFrame
from widgets.PCANSettingsWindow import PCANSettingsWindow
from lib.PCAN_RS_232 import PCAN_RS_232
from tkinter import *
from widgets.InformationFrame import InformationFrame
from widgets.ButtonFrame import ButtonFrame
from serial import SerialException
class App(Tk):
def __init__(self):
super().__init__()
self.title("PCAN-RS-232 Interface")
self.geometry('960x420')
self.resizable(FALSE, FALSE)
# Create main containers
self.button_frame = ButtonFrame(self, bg="#004080", pady=3)
self.center_frame = ConsoleFrame(self, padx=3, pady=3)
self.can_msg_frame = MessageFrame(self, bg="#004080", pady=3)
self.btm_frame = InformationFrame(self, bg="#004080", pady=3)
# Layout containers
self.button_frame.place(x=0, y=0, width=210, height=390)
self.center_frame.place(x=210, y=0, width=540, height=390)
self.can_msg_frame.place(x=750, y=0, width=210, height=390)
self.btm_frame.place(x=0, y=390, width=960, height=30)
# Initialize application variables
self._PORT = StringVar(value="COM1") # Default: COM1
self._BAUDRATE = StringVar(value="57600") # Default: 57600
self._TIMEOUT = StringVar(value="1") # Default: 1 (s)
try:
self.pcan = PCAN_RS_232(self._PORT.get(), int(self._BAUDRATE.get()), int(self._TIMEOUT.get()))
self.center_frame.begin(self.pcan)
except SerialException: # Default device not found
self.pcan_window = PCANSettingsWindow(self) # Open a window to configure PCAN settings
# ===PCAN INTERACTION FUNCTIONS===
def update_pcan_settings(self):
try:
self.pcan = PCAN_RS_232(self._PORT.get(), int(self._BAUDRATE.get()), int(self._TIMEOUT.get()))
self.center_frame.begin(self.pcan)
return True
except SerialException:
return False
# ===WIDGET INTERFACE FUNCTIONS===
def update_pcan_status(self):
_stat = self.pcan.get_status_flags()
if _stat != -1:
self.btm_frame.pcan_status.set(_stat)
self.btm_frame.cmd_feedback.set("Received PCAN status")
else:
self.btm_frame.cmd_feedback.set("FAILED to get PCAN status")
def update_pcan_open(self, open):
_res = self.pcan.open_channel() if open else self.pcan.close_channel()
if _res != -1: # Channel successfully opened/closed
_text = "Opened CAN Channel" if open else "Closed CAN channel"
self.btm_frame.cmd_feedback.set(_text)
return True
else:
_text = "FAILED to open CAN channel" if open else "FAILED to close CAN channel"
self.btm_frame.cmd_feedback.set(_text)
return False
def update_pcan_info(self):
_sn = self.pcan.get_serial_number()
_info = self.pcan.get_version_info()
print(_info) # DEBUG
if _info != -1:
self.btm_frame.pcan_sn.set(_sn)
self.btm_frame.pcan_hw_version.set(_info[0])
self.btm_frame.pcan_sw_version.set(_info[1])
self.btm_frame.cmd_feedback.set("Received PCAN info")
else:
self.btm_frame.cmd_feedback.set("FAILED to get PCAN info")
def update_acceptance_mask(self, mask):
_res = self.pcan.set_acceptance_mask_register(mask)
if _res != -1: # Acceptance mask register successfuly set
self.btm_frame.cmd_feedback.set("Set mask to " + mask)
else:
self.btm_frame.cmd_feedback.set("FAILED to set acceptance mask")
return _res
def update_acceptance_code(self, code):
_res = self.pcan.set_acceptance_code_register(code)
if _res != -1: # Acceptance code register successfuly set
self.btm_frame.cmd_feedback.set("Set code to "+ code)
else:
self.btm_frame.cmd_feedback.set("FAILED to set acceptance code")
return _res
def update_auto_poll(self, en: bool):
_res = self.pcan.set_auto_poll(en)
if _res != -1: # Auto poll successfully set
_text = "ENABLED auto poll feature" if en else "DISABLED auto poll feature"
self.btm_frame.cmd_feedback.set(_text)
else:
self.btm_frame.cmd_feedback.set("FAILED to set auto poll")
return _res
def update_auto_startup(self, en: bool):
_res = self.pcan.set_auto_startup(en)
if _res != -1: # Auto startup successfully set
_text = "ENABLED auto startup feature" if en else "DISABLED auto startup feature"
self.btm_frame.cmd_feedback.set(_text)
else:
self.btm_frame.cmd_feedback.set("FAILED to set auto startup")
return _res
def update_can_baudrate(self, n: str):
_res = self.pcan.set_can_bitrate(n)
if _res != -1: # CAN baudrate successfully set
self.btm_frame.cmd_feedback.set("Set CAN baudrate") # TODO: Include baudrate
else:
self.btm_frame.cmd_feedback.set("FAILED to set CAN baudrate")
return _res
def update_uart_baudrate(self, n: str):
_res = self.pcan.set_uart_bitrate(n)
# TODO: Edit application baudrate to reflect new set baudrate!!!!!!!!!!
if _res != -1: # UART baudrate successfully set
self.btm_frame.cmd_feedback.set("Set UART baudrate") # TODO: Include baudrate
else:
self.btm_frame.cmd_feedback.set("FAILED to set UART baudrate")
return _res
def update_filter_mode(self, n: bool):
_res = self.pcan.set_filter_mode(n)
if _res != -1: # Filter mode successfully set
_text = "Set mode to Single Filter" if n else "Set mode to Dual Filter"
self.btm_frame.cmd_feedback.set(_text)
else:
self.btm_frame.cmd_feedback.set("FAILED to set filter mode")
return _res
def update_timestamp(self, n: bool):
_res = self.pcan.enable_timestamps(n)
if _res != -1: # Filter mode successfully set
_text = "Enabled timestamp feature" if n else "Disabled timestamp feature"
self.btm_frame.cmd_feedback.set(_text)
else:
self.btm_frame.cmd_feedback.set("FAILED to timestamp feature")
return _res
def update_eeprom(self, n: str):
if self.pcan.write_to_eeprom(n) != -1:
if n == '0': self.btm_frame.cmd_feedback.set("Saved settings to EEPROM")
elif n == '1': self.btm_frame.cmd_feedback.set("Reloaded factory settings")
elif n == '2': self.btm_frame.cmd_feedback.set("Deleted all settings")
else:
self.btm_frame.cmd_feedback.set("FAILED to command EEPROM")
def transmit_message(self, msg):
if self.pcan.send_message(msg) != -1: # Message successfully sent
self.btm_frame.cmd_feedback.set("Sent message")
else:
self.btm_frame.cmd_feedback.set("FAILED to send message")
_app = App()
try:
if __name__ == '__main__':
_app.mainloop() # Begin interface application
finally: # On app close
try:
_app.update_pcan_open(False) # Close CAN connection
_app.update_eeprom('1') # Reset to factory-default settings
except:
pass | PCAN_Interface_Application.py | from widgets.MessageFrame import MessageFrame
from widgets.ConsoleFrame import ConsoleFrame
from widgets.PCANSettingsWindow import PCANSettingsWindow
from lib.PCAN_RS_232 import PCAN_RS_232
from tkinter import *
from widgets.InformationFrame import InformationFrame
from widgets.ButtonFrame import ButtonFrame
from serial import SerialException
class App(Tk):
def __init__(self):
super().__init__()
self.title("PCAN-RS-232 Interface")
self.geometry('960x420')
self.resizable(FALSE, FALSE)
# Create main containers
self.button_frame = ButtonFrame(self, bg="#004080", pady=3)
self.center_frame = ConsoleFrame(self, padx=3, pady=3)
self.can_msg_frame = MessageFrame(self, bg="#004080", pady=3)
self.btm_frame = InformationFrame(self, bg="#004080", pady=3)
# Layout containers
self.button_frame.place(x=0, y=0, width=210, height=390)
self.center_frame.place(x=210, y=0, width=540, height=390)
self.can_msg_frame.place(x=750, y=0, width=210, height=390)
self.btm_frame.place(x=0, y=390, width=960, height=30)
# Initialize application variables
self._PORT = StringVar(value="COM1") # Default: COM1
self._BAUDRATE = StringVar(value="57600") # Default: 57600
self._TIMEOUT = StringVar(value="1") # Default: 1 (s)
try:
self.pcan = PCAN_RS_232(self._PORT.get(), int(self._BAUDRATE.get()), int(self._TIMEOUT.get()))
self.center_frame.begin(self.pcan)
except SerialException: # Default device not found
self.pcan_window = PCANSettingsWindow(self) # Open a window to configure PCAN settings
# ===PCAN INTERACTION FUNCTIONS===
def update_pcan_settings(self):
try:
self.pcan = PCAN_RS_232(self._PORT.get(), int(self._BAUDRATE.get()), int(self._TIMEOUT.get()))
self.center_frame.begin(self.pcan)
return True
except SerialException:
return False
# ===WIDGET INTERFACE FUNCTIONS===
def update_pcan_status(self):
_stat = self.pcan.get_status_flags()
if _stat != -1:
self.btm_frame.pcan_status.set(_stat)
self.btm_frame.cmd_feedback.set("Received PCAN status")
else:
self.btm_frame.cmd_feedback.set("FAILED to get PCAN status")
def update_pcan_open(self, open):
_res = self.pcan.open_channel() if open else self.pcan.close_channel()
if _res != -1: # Channel successfully opened/closed
_text = "Opened CAN Channel" if open else "Closed CAN channel"
self.btm_frame.cmd_feedback.set(_text)
return True
else:
_text = "FAILED to open CAN channel" if open else "FAILED to close CAN channel"
self.btm_frame.cmd_feedback.set(_text)
return False
def update_pcan_info(self):
_sn = self.pcan.get_serial_number()
_info = self.pcan.get_version_info()
print(_info) # DEBUG
if _info != -1:
self.btm_frame.pcan_sn.set(_sn)
self.btm_frame.pcan_hw_version.set(_info[0])
self.btm_frame.pcan_sw_version.set(_info[1])
self.btm_frame.cmd_feedback.set("Received PCAN info")
else:
self.btm_frame.cmd_feedback.set("FAILED to get PCAN info")
def update_acceptance_mask(self, mask):
_res = self.pcan.set_acceptance_mask_register(mask)
if _res != -1: # Acceptance mask register successfuly set
self.btm_frame.cmd_feedback.set("Set mask to " + mask)
else:
self.btm_frame.cmd_feedback.set("FAILED to set acceptance mask")
return _res
def update_acceptance_code(self, code):
_res = self.pcan.set_acceptance_code_register(code)
if _res != -1: # Acceptance code register successfuly set
self.btm_frame.cmd_feedback.set("Set code to "+ code)
else:
self.btm_frame.cmd_feedback.set("FAILED to set acceptance code")
return _res
def update_auto_poll(self, en: bool):
_res = self.pcan.set_auto_poll(en)
if _res != -1: # Auto poll successfully set
_text = "ENABLED auto poll feature" if en else "DISABLED auto poll feature"
self.btm_frame.cmd_feedback.set(_text)
else:
self.btm_frame.cmd_feedback.set("FAILED to set auto poll")
return _res
def update_auto_startup(self, en: bool):
_res = self.pcan.set_auto_startup(en)
if _res != -1: # Auto startup successfully set
_text = "ENABLED auto startup feature" if en else "DISABLED auto startup feature"
self.btm_frame.cmd_feedback.set(_text)
else:
self.btm_frame.cmd_feedback.set("FAILED to set auto startup")
return _res
def update_can_baudrate(self, n: str):
_res = self.pcan.set_can_bitrate(n)
if _res != -1: # CAN baudrate successfully set
self.btm_frame.cmd_feedback.set("Set CAN baudrate") # TODO: Include baudrate
else:
self.btm_frame.cmd_feedback.set("FAILED to set CAN baudrate")
return _res
def update_uart_baudrate(self, n: str):
_res = self.pcan.set_uart_bitrate(n)
# TODO: Edit application baudrate to reflect new set baudrate!!!!!!!!!!
if _res != -1: # UART baudrate successfully set
self.btm_frame.cmd_feedback.set("Set UART baudrate") # TODO: Include baudrate
else:
self.btm_frame.cmd_feedback.set("FAILED to set UART baudrate")
return _res
def update_filter_mode(self, n: bool):
_res = self.pcan.set_filter_mode(n)
if _res != -1: # Filter mode successfully set
_text = "Set mode to Single Filter" if n else "Set mode to Dual Filter"
self.btm_frame.cmd_feedback.set(_text)
else:
self.btm_frame.cmd_feedback.set("FAILED to set filter mode")
return _res
def update_timestamp(self, n: bool):
_res = self.pcan.enable_timestamps(n)
if _res != -1: # Filter mode successfully set
_text = "Enabled timestamp feature" if n else "Disabled timestamp feature"
self.btm_frame.cmd_feedback.set(_text)
else:
self.btm_frame.cmd_feedback.set("FAILED to timestamp feature")
return _res
def update_eeprom(self, n: str):
if self.pcan.write_to_eeprom(n) != -1:
if n == '0': self.btm_frame.cmd_feedback.set("Saved settings to EEPROM")
elif n == '1': self.btm_frame.cmd_feedback.set("Reloaded factory settings")
elif n == '2': self.btm_frame.cmd_feedback.set("Deleted all settings")
else:
self.btm_frame.cmd_feedback.set("FAILED to command EEPROM")
def transmit_message(self, msg):
if self.pcan.send_message(msg) != -1: # Message successfully sent
self.btm_frame.cmd_feedback.set("Sent message")
else:
self.btm_frame.cmd_feedback.set("FAILED to send message")
_app = App()
try:
if __name__ == '__main__':
_app.mainloop() # Begin interface application
finally: # On app close
try:
_app.update_pcan_open(False) # Close CAN connection
_app.update_eeprom('1') # Reset to factory-default settings
except:
pass | 0.298287 | 0.075892 |
from __future__ import absolute_import, division, print_function, unicode_literals
import sys
import os
import json
import utility
import re
import requests
sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "lib"))
from splunklib.six.moves.urllib.parse import quote_plus
from splunklib.searchcommands import dispatch, GeneratingCommand, Configuration, Option
from splunklib.binding import HTTPError
import logging
import splunk
def setup_logging():
"""
setup_logging as found on http://dev.splunk.com/view/logging/SP-CAAAFCN
"""
logger = logging.getLogger('splunk.shareprivateobjects')
SPLUNK_HOME = os.environ['SPLUNK_HOME']
LOGGING_DEFAULT_CONFIG_FILE = os.path.join(SPLUNK_HOME, 'etc', 'log.cfg')
LOGGING_LOCAL_CONFIG_FILE = os.path.join(SPLUNK_HOME, 'etc', 'log-local.cfg')
LOGGING_STANZA_NAME = 'python'
LOGGING_FILE_NAME = "changedispatch.log"
BASE_LOG_PATH = os.path.join('var', 'log', 'splunk')
LOGGING_FORMAT = "%(asctime)s %(levelname)-s\t %(message)s"
splunk_log_handler = logging.handlers.RotatingFileHandler(os.path.join(SPLUNK_HOME, BASE_LOG_PATH, LOGGING_FILE_NAME), mode='a')
splunk_log_handler.setFormatter(logging.Formatter(LOGGING_FORMAT))
logger.addHandler(splunk_log_handler)
splunk.setupSplunkLogger(logger, LOGGING_DEFAULT_CONFIG_FILE, LOGGING_LOCAL_CONFIG_FILE, LOGGING_STANZA_NAME)
return logger
logger = setup_logging()
@Configuration(type='reporting')
class ChangeDispatchTTLCommand(GeneratingCommand):
appname = Option(require=True)
newttl = Option(require=True)
savedsearch = Option(require=True)
owner = Option(require=False)
sharing = Option(require=False)
def generate(self):
"""
The logic is:
If the requested savedsearch is owned by the current user, or the requesting user is an admin user, then
change the dispatch.ttl value of the saved search to the requested newttl value passed in
If the optional sharing level is not specified check for the savedsearch in the user context
If the owner is specified run the REST call with the specified context, only someone with admin access can use this option
"""
(username, roles) = utility.determine_username(self.service)
#Restricting this option to admin only use
if self.owner is not None:
if not 'admin' in roles:
yield {'result': 'The owner passed in was %s but the user %s does not have the admin role. You may only change the TTL of your own saved searches' % (self.owner, username) }
return
if self.sharing is not None and self.sharing != 'user':
context = 'nobody'
else:
if self.owner is not None:
context = self.owner
else:
context = username
url = 'https://localhost:8089/servicesNS/%s/%s/' % (context, self.appname)
url = url + 'saved/searches/%s/?output_mode=json' % (quote_plus(self.savedsearch))
headers = { 'Authorization': 'Splunk ' + self._metadata.searchinfo.session_key }
attempt = requests.get(url, verify=False, headers=headers)
if attempt.status_code != 200:
yield {'result': 'Unknown failure, received a non-200 response code of %s on the URL %s, text result is %s' % (attempt.status_code, url, attempt.text)}
return
#We received a response but we now need the details on owner, sharing level and the app context it came from
acl = json.loads(attempt.text)['entry'][0]['acl']
obj_sharing = acl['sharing']
obj_owner = acl['owner']
obj_app = acl['app']
#We advised an explicit sharing level, but the saved search we found does not match the expected level
if self.sharing is not None and obj_sharing != self.sharing:
yield {'result': 'Object found but sharing level is %s, expected sharing level of %s, not changing dispatch.ttl in app %s' % (obj_sharing, self.sharing, self.appname) }
return
#Does the owner of the object match the person logged in?
#While technically a user could change the dispatch.ttl if they have write access, we don't want to offer this option
if obj_owner != username:
#admins are allowed to change dispatch.ttl of any saved search they wish
if not 'admin' in roles:
yield {'result': 'Object found but owner is %s, user is %s, not changing dispatch.ttl in app %s as you do not have the admin role' % (obj_owner, username, self.appname) }
return
#Make sure the dispatch.ttl value looks valid
if not re.match(r"^[0-9]+p?$", self.newttl):
yield {'result': 'The requested new TTL value of %s did not match the regular expression, ttl values are in seconds and can end in a p for execution period.' % (self.newttl) }
return
#If the saved search is currently app level we must use the nobody context or we create an empty saved search in private context...
if obj_sharing != 'user':
#A globally shared object may appear to be in this app but could be from a different app
#we must post the correct app context otherwise we create an empty saved search with a modified dispatch.ttl in the wrong app
#To make it simple for the user we do this for them rather than request them to use the correct app name...
if obj_app != self.appname:
context = 'nobody/' + obj_app
else:
context = 'nobody/' + self.appname
else:
context = obj_owner + '/' + self.appname
#At this point we have run our checks so are happy to change the dispatch.ttl value
data = { 'dispatch.ttl': self.newttl, 'output_mode': 'json' }
url = 'https://localhost:8089/servicesNS/%s/' % (context)
url = url + 'saved/searches/%s' % (quote_plus(self.savedsearch))
attempt = requests.post(url, verify=False, data=data, headers=headers)
if attempt.status_code != 200:
yield {'result': 'Unknown failure, received a non-200 response code of %s on the URL %s, text result is %s' % (attempt.status_code, url, attempt.text)}
return
else:
logger.info("app=%s savedsearch='%s' owner=%s has had the TTL value changed to newttl=%s via url='%s' sharing_arg=%s owner_arg=%s username=%s" % (self.appname, self.savedsearch, obj_owner, self.newttl, url, self.sharing, self.owner, username))
ttl = json.loads(attempt.text)['entry'][0]['content']['dispatch.ttl']
yield {'result': 'TTL updated, new value is showing as %s for saved search %s in app %s with owner %s' % (ttl, self.savedsearch, self.appname, obj_owner) }
dispatch(ChangeDispatchTTLCommand, sys.argv, sys.stdin, sys.stdout, __name__) | bin/changedispatchttl.py | from __future__ import absolute_import, division, print_function, unicode_literals
import sys
import os
import json
import utility
import re
import requests
sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "lib"))
from splunklib.six.moves.urllib.parse import quote_plus
from splunklib.searchcommands import dispatch, GeneratingCommand, Configuration, Option
from splunklib.binding import HTTPError
import logging
import splunk
def setup_logging():
"""
setup_logging as found on http://dev.splunk.com/view/logging/SP-CAAAFCN
"""
logger = logging.getLogger('splunk.shareprivateobjects')
SPLUNK_HOME = os.environ['SPLUNK_HOME']
LOGGING_DEFAULT_CONFIG_FILE = os.path.join(SPLUNK_HOME, 'etc', 'log.cfg')
LOGGING_LOCAL_CONFIG_FILE = os.path.join(SPLUNK_HOME, 'etc', 'log-local.cfg')
LOGGING_STANZA_NAME = 'python'
LOGGING_FILE_NAME = "changedispatch.log"
BASE_LOG_PATH = os.path.join('var', 'log', 'splunk')
LOGGING_FORMAT = "%(asctime)s %(levelname)-s\t %(message)s"
splunk_log_handler = logging.handlers.RotatingFileHandler(os.path.join(SPLUNK_HOME, BASE_LOG_PATH, LOGGING_FILE_NAME), mode='a')
splunk_log_handler.setFormatter(logging.Formatter(LOGGING_FORMAT))
logger.addHandler(splunk_log_handler)
splunk.setupSplunkLogger(logger, LOGGING_DEFAULT_CONFIG_FILE, LOGGING_LOCAL_CONFIG_FILE, LOGGING_STANZA_NAME)
return logger
logger = setup_logging()
@Configuration(type='reporting')
class ChangeDispatchTTLCommand(GeneratingCommand):
appname = Option(require=True)
newttl = Option(require=True)
savedsearch = Option(require=True)
owner = Option(require=False)
sharing = Option(require=False)
def generate(self):
"""
The logic is:
If the requested savedsearch is owned by the current user, or the requesting user is an admin user, then
change the dispatch.ttl value of the saved search to the requested newttl value passed in
If the optional sharing level is not specified check for the savedsearch in the user context
If the owner is specified run the REST call with the specified context, only someone with admin access can use this option
"""
(username, roles) = utility.determine_username(self.service)
#Restricting this option to admin only use
if self.owner is not None:
if not 'admin' in roles:
yield {'result': 'The owner passed in was %s but the user %s does not have the admin role. You may only change the TTL of your own saved searches' % (self.owner, username) }
return
if self.sharing is not None and self.sharing != 'user':
context = 'nobody'
else:
if self.owner is not None:
context = self.owner
else:
context = username
url = 'https://localhost:8089/servicesNS/%s/%s/' % (context, self.appname)
url = url + 'saved/searches/%s/?output_mode=json' % (quote_plus(self.savedsearch))
headers = { 'Authorization': 'Splunk ' + self._metadata.searchinfo.session_key }
attempt = requests.get(url, verify=False, headers=headers)
if attempt.status_code != 200:
yield {'result': 'Unknown failure, received a non-200 response code of %s on the URL %s, text result is %s' % (attempt.status_code, url, attempt.text)}
return
#We received a response but we now need the details on owner, sharing level and the app context it came from
acl = json.loads(attempt.text)['entry'][0]['acl']
obj_sharing = acl['sharing']
obj_owner = acl['owner']
obj_app = acl['app']
#We advised an explicit sharing level, but the saved search we found does not match the expected level
if self.sharing is not None and obj_sharing != self.sharing:
yield {'result': 'Object found but sharing level is %s, expected sharing level of %s, not changing dispatch.ttl in app %s' % (obj_sharing, self.sharing, self.appname) }
return
#Does the owner of the object match the person logged in?
#While technically a user could change the dispatch.ttl if they have write access, we don't want to offer this option
if obj_owner != username:
#admins are allowed to change dispatch.ttl of any saved search they wish
if not 'admin' in roles:
yield {'result': 'Object found but owner is %s, user is %s, not changing dispatch.ttl in app %s as you do not have the admin role' % (obj_owner, username, self.appname) }
return
#Make sure the dispatch.ttl value looks valid
if not re.match(r"^[0-9]+p?$", self.newttl):
yield {'result': 'The requested new TTL value of %s did not match the regular expression, ttl values are in seconds and can end in a p for execution period.' % (self.newttl) }
return
#If the saved search is currently app level we must use the nobody context or we create an empty saved search in private context...
if obj_sharing != 'user':
#A globally shared object may appear to be in this app but could be from a different app
#we must post the correct app context otherwise we create an empty saved search with a modified dispatch.ttl in the wrong app
#To make it simple for the user we do this for them rather than request them to use the correct app name...
if obj_app != self.appname:
context = 'nobody/' + obj_app
else:
context = 'nobody/' + self.appname
else:
context = obj_owner + '/' + self.appname
#At this point we have run our checks so are happy to change the dispatch.ttl value
data = { 'dispatch.ttl': self.newttl, 'output_mode': 'json' }
url = 'https://localhost:8089/servicesNS/%s/' % (context)
url = url + 'saved/searches/%s' % (quote_plus(self.savedsearch))
attempt = requests.post(url, verify=False, data=data, headers=headers)
if attempt.status_code != 200:
yield {'result': 'Unknown failure, received a non-200 response code of %s on the URL %s, text result is %s' % (attempt.status_code, url, attempt.text)}
return
else:
logger.info("app=%s savedsearch='%s' owner=%s has had the TTL value changed to newttl=%s via url='%s' sharing_arg=%s owner_arg=%s username=%s" % (self.appname, self.savedsearch, obj_owner, self.newttl, url, self.sharing, self.owner, username))
ttl = json.loads(attempt.text)['entry'][0]['content']['dispatch.ttl']
yield {'result': 'TTL updated, new value is showing as %s for saved search %s in app %s with owner %s' % (ttl, self.savedsearch, self.appname, obj_owner) }
dispatch(ChangeDispatchTTLCommand, sys.argv, sys.stdin, sys.stdout, __name__) | 0.390011 | 0.075551 |
import asyncio
import voluptuous as vol
from homeassistant.components.knx import ATTR_DISCOVER_DEVICES, DATA_KNX
from homeassistant.components.switch import PLATFORM_SCHEMA, SwitchDevice
from homeassistant.const import CONF_NAME
from homeassistant.core import callback
import homeassistant.helpers.config_validation as cv
CONF_ADDRESS = 'address'
CONF_STATE_ADDRESS = 'state_address'
DEFAULT_NAME = 'KNX Switch'
DEPENDENCIES = ['knx']
PLATFORM_SCHEMA = PLATFORM_SCHEMA.extend({
vol.Required(CONF_ADDRESS): cv.string,
vol.Optional(CONF_NAME, default=DEFAULT_NAME): cv.string,
vol.Optional(CONF_STATE_ADDRESS): cv.string,
})
@asyncio.coroutine
def async_setup_platform(hass, config, async_add_devices, discovery_info=None):
"""Set up switch(es) for KNX platform."""
if discovery_info is not None:
async_add_devices_discovery(hass, discovery_info, async_add_devices)
else:
async_add_devices_config(hass, config, async_add_devices)
@callback
def async_add_devices_discovery(hass, discovery_info, async_add_devices):
"""Set up switches for KNX platform configured via xknx.yaml."""
entities = []
for device_name in discovery_info[ATTR_DISCOVER_DEVICES]:
device = hass.data[DATA_KNX].xknx.devices[device_name]
entities.append(KNXSwitch(hass, device))
async_add_devices(entities)
@callback
def async_add_devices_config(hass, config, async_add_devices):
"""Set up switch for KNX platform configured within platform."""
import xknx
switch = xknx.devices.Switch(
hass.data[DATA_KNX].xknx,
name=config.get(CONF_NAME),
group_address=config.get(CONF_ADDRESS),
group_address_state=config.get(CONF_STATE_ADDRESS))
hass.data[DATA_KNX].xknx.devices.add(switch)
async_add_devices([KNXSwitch(hass, switch)])
class KNXSwitch(SwitchDevice):
"""Representation of a KNX switch."""
def __init__(self, hass, device):
"""Initialize of KNX switch."""
self.device = device
self.hass = hass
self.async_register_callbacks()
@callback
def async_register_callbacks(self):
"""Register callbacks to update hass after device was changed."""
@asyncio.coroutine
def after_update_callback(device):
"""Call after device was updated."""
# pylint: disable=unused-argument
yield from self.async_update_ha_state()
self.device.register_device_updated_cb(after_update_callback)
@property
def name(self):
"""Return the name of the KNX device."""
return self.device.name
@property
def available(self):
"""Return true if entity is available."""
return self.hass.data[DATA_KNX].connected
@property
def should_poll(self):
"""Return the polling state. Not needed within KNX."""
return False
@property
def is_on(self):
"""Return true if device is on."""
return self.device.state
@asyncio.coroutine
def async_turn_on(self, **kwargs):
"""Turn the device on."""
yield from self.device.set_on()
@asyncio.coroutine
def async_turn_off(self, **kwargs):
"""Turn the device off."""
yield from self.device.set_off() | homeassistant/components/switch/knx.py | import asyncio
import voluptuous as vol
from homeassistant.components.knx import ATTR_DISCOVER_DEVICES, DATA_KNX
from homeassistant.components.switch import PLATFORM_SCHEMA, SwitchDevice
from homeassistant.const import CONF_NAME
from homeassistant.core import callback
import homeassistant.helpers.config_validation as cv
CONF_ADDRESS = 'address'
CONF_STATE_ADDRESS = 'state_address'
DEFAULT_NAME = 'KNX Switch'
DEPENDENCIES = ['knx']
PLATFORM_SCHEMA = PLATFORM_SCHEMA.extend({
vol.Required(CONF_ADDRESS): cv.string,
vol.Optional(CONF_NAME, default=DEFAULT_NAME): cv.string,
vol.Optional(CONF_STATE_ADDRESS): cv.string,
})
@asyncio.coroutine
def async_setup_platform(hass, config, async_add_devices, discovery_info=None):
"""Set up switch(es) for KNX platform."""
if discovery_info is not None:
async_add_devices_discovery(hass, discovery_info, async_add_devices)
else:
async_add_devices_config(hass, config, async_add_devices)
@callback
def async_add_devices_discovery(hass, discovery_info, async_add_devices):
"""Set up switches for KNX platform configured via xknx.yaml."""
entities = []
for device_name in discovery_info[ATTR_DISCOVER_DEVICES]:
device = hass.data[DATA_KNX].xknx.devices[device_name]
entities.append(KNXSwitch(hass, device))
async_add_devices(entities)
@callback
def async_add_devices_config(hass, config, async_add_devices):
"""Set up switch for KNX platform configured within platform."""
import xknx
switch = xknx.devices.Switch(
hass.data[DATA_KNX].xknx,
name=config.get(CONF_NAME),
group_address=config.get(CONF_ADDRESS),
group_address_state=config.get(CONF_STATE_ADDRESS))
hass.data[DATA_KNX].xknx.devices.add(switch)
async_add_devices([KNXSwitch(hass, switch)])
class KNXSwitch(SwitchDevice):
"""Representation of a KNX switch."""
def __init__(self, hass, device):
"""Initialize of KNX switch."""
self.device = device
self.hass = hass
self.async_register_callbacks()
@callback
def async_register_callbacks(self):
"""Register callbacks to update hass after device was changed."""
@asyncio.coroutine
def after_update_callback(device):
"""Call after device was updated."""
# pylint: disable=unused-argument
yield from self.async_update_ha_state()
self.device.register_device_updated_cb(after_update_callback)
@property
def name(self):
"""Return the name of the KNX device."""
return self.device.name
@property
def available(self):
"""Return true if entity is available."""
return self.hass.data[DATA_KNX].connected
@property
def should_poll(self):
"""Return the polling state. Not needed within KNX."""
return False
@property
def is_on(self):
"""Return true if device is on."""
return self.device.state
@asyncio.coroutine
def async_turn_on(self, **kwargs):
"""Turn the device on."""
yield from self.device.set_on()
@asyncio.coroutine
def async_turn_off(self, **kwargs):
"""Turn the device off."""
yield from self.device.set_off() | 0.668231 | 0.107017 |
"""Tests using pytest_resilient_circuits"""
from __future__ import print_function
import pytest
from resilient_circuits.util import get_config_data, get_function_definition
from resilient_circuits import SubmitTestFunction, FunctionResult
PACKAGE_NAME = "fn_codegen_test"
FUNCTION_NAME = "utilities_base64_to_artifact"
# Read the default configuration-data section from the package
config_data = get_config_data(PACKAGE_NAME)
# Provide a simulation of the Resilient REST API (uncomment to connect to a real appliance)
resilient_mock = "pytest_resilient_circuits.BasicResilientMock"
def call_utilities_base64_to_artifact_function(circuits, function_params, timeout=10):
# Fire a message to the function
evt = SubmitTestFunction("utilities_base64_to_artifact", function_params)
circuits.manager.fire(evt)
event = circuits.watcher.wait("utilities_base64_to_artifact_result", parent=evt, timeout=timeout)
assert event
assert isinstance(event.kwargs["result"], FunctionResult)
pytest.wait_for(event, "complete", True)
return event.kwargs["result"].value
class TestUtilitiesBase64ToArtifact:
""" Tests for the utilities_base64_to_artifact function"""
def test_function_definition(self):
""" Test that the package provides customization_data that defines the function """
func = get_function_definition(PACKAGE_NAME, FUNCTION_NAME)
assert func is not None
@pytest.mark.parametrize("base64content, incident_id, artifact_file_type, file_name, content_type, description, expected_results", [
("text", 123, 'Email Attachment', "text", "text", {"type": "text", "content": "line1\nline2"}, {"value": "xyz"}),
("text", 123, 'Malware Sample', "text", "text", {"type": "text", "content": "line1\nline2"}, {"value": "xyz"})
])
def test_success(self, circuits_app, base64content, incident_id, artifact_file_type, file_name, content_type, description, expected_results):
""" Test calling with sample values for the parameters """
function_params = {
"base64content": base64content,
"incident_id": incident_id,
"artifact_file_type": artifact_file_type,
"file_name": file_name,
"content_type": content_type,
"description": description
}
results = call_utilities_base64_to_artifact_function(circuits_app, function_params)
assert(expected_results == results) | fn_codegen_test/tests/test_utilities_base64_to_artifact.py | """Tests using pytest_resilient_circuits"""
from __future__ import print_function
import pytest
from resilient_circuits.util import get_config_data, get_function_definition
from resilient_circuits import SubmitTestFunction, FunctionResult
PACKAGE_NAME = "fn_codegen_test"
FUNCTION_NAME = "utilities_base64_to_artifact"
# Read the default configuration-data section from the package
config_data = get_config_data(PACKAGE_NAME)
# Provide a simulation of the Resilient REST API (uncomment to connect to a real appliance)
resilient_mock = "pytest_resilient_circuits.BasicResilientMock"
def call_utilities_base64_to_artifact_function(circuits, function_params, timeout=10):
# Fire a message to the function
evt = SubmitTestFunction("utilities_base64_to_artifact", function_params)
circuits.manager.fire(evt)
event = circuits.watcher.wait("utilities_base64_to_artifact_result", parent=evt, timeout=timeout)
assert event
assert isinstance(event.kwargs["result"], FunctionResult)
pytest.wait_for(event, "complete", True)
return event.kwargs["result"].value
class TestUtilitiesBase64ToArtifact:
""" Tests for the utilities_base64_to_artifact function"""
def test_function_definition(self):
""" Test that the package provides customization_data that defines the function """
func = get_function_definition(PACKAGE_NAME, FUNCTION_NAME)
assert func is not None
@pytest.mark.parametrize("base64content, incident_id, artifact_file_type, file_name, content_type, description, expected_results", [
("text", 123, 'Email Attachment', "text", "text", {"type": "text", "content": "line1\nline2"}, {"value": "xyz"}),
("text", 123, 'Malware Sample', "text", "text", {"type": "text", "content": "line1\nline2"}, {"value": "xyz"})
])
def test_success(self, circuits_app, base64content, incident_id, artifact_file_type, file_name, content_type, description, expected_results):
""" Test calling with sample values for the parameters """
function_params = {
"base64content": base64content,
"incident_id": incident_id,
"artifact_file_type": artifact_file_type,
"file_name": file_name,
"content_type": content_type,
"description": description
}
results = call_utilities_base64_to_artifact_function(circuits_app, function_params)
assert(expected_results == results) | 0.807157 | 0.418697 |
from __future__ import annotations # postpone evaluation of annotations
import logging
from typing import Any, Dict, List, Optional, Tuple
import cv2
import numpy as np
import numpy.typing as npt
from pyquaternion import Quaternion
from scipy import ndimage
from scipy.spatial.transform import Rotation as R
from sqlalchemy import Column, inspect
from sqlalchemy.orm import relationship
from sqlalchemy.schema import ForeignKey
from sqlalchemy.types import Float, Integer
from nuplan.database.common import sql_types
from nuplan.database.common.utils import simple_repr
from nuplan.database.maps_db.gpkg_mapsdb import GPKGMapsDB
from nuplan.database.maps_db.utils import build_lane_segments_from_blps, connect_blp_predecessor, connect_blp_successor
from nuplan.database.nuplan_db.models import Base, Image, generate_multi_scale_connections
from nuplan.database.nuplan_db.utils import crop_rect, get_candidates
from nuplan.database.nuplan_db.vector_map_np import VectorMapNp
logger = logging.getLogger()
class EgoPose(Base):
"""
Ego vehicle pose at a particular timestamp. Given with respect to global coordinate system.
"""
__tablename__ = "ego_pose"
token = Column(sql_types.HexLen8, primary_key=True) # type: str
timestamp = Column(Integer) # field type: int
x = Column(Float) # type: float
y = Column(Float) # type: float
z = Column(Float) # type: float
qw: float = Column(Float)
qx: float = Column(Float)
qy: float = Column(Float)
qz: float = Column(Float)
vx = Column(Float) # type: float
vy = Column(Float) # type: float
vz = Column(Float) # type: float
acceleration_x = Column(Float) # type: float
acceleration_y = Column(Float) # type: float
acceleration_z = Column(Float) # type: float
angular_rate_x = Column(Float) # type: float
angular_rate_y = Column(Float) # type: float
angular_rate_z = Column(Float) # type: float
epsg = Column(Integer) # type: int
log_token = Column(sql_types.HexLen8, ForeignKey("log.token"), nullable=False) # type: str
image = relationship(
"Image", foreign_keys="Image.ego_pose_token", back_populates="ego_pose", uselist=False
) # type: Image
@property
def _session(self) -> Any:
"""
Get the underlying session.
:return: The underlying session.
"""
return inspect(self).session
def __repr__(self) -> str:
"""
Return the string representation.
:return: The string representation.
"""
desc: str = simple_repr(self)
return desc
@property
def quaternion(self) -> Quaternion:
"""
Get the orientation of ego vehicle as quaternion respect to global coordinate system.
:return: The orientation in quaternion.
"""
return Quaternion(self.qw, self.qx, self.qy, self.qz)
@property
def translation_np(self) -> npt.NDArray[np.float64]:
"""
Position of ego vehicle respect to global coordinate system.
:return: <np.float: 3> Translation.
"""
return np.array([self.x, self.y, self.z])
@property
def trans_matrix(self) -> npt.NDArray[np.float64]:
"""
Get the transformation matrix.
:return: <np.float: 4, 4>. Transformation matrix.
"""
tm: npt.NDArray[np.float64] = self.quaternion.transformation_matrix
tm[:3, 3] = self.translation_np
return tm
@property
def trans_matrix_inv(self) -> npt.NDArray[np.float64]:
"""
Get the inverse transformation matrix.
:return: <np.float: 4, 4>. Inverse transformation matrix.
"""
tm: npt.NDArray[np.float64] = np.eye(4)
rot_inv = self.quaternion.rotation_matrix.T
tm[:3, :3] = rot_inv
tm[:3, 3] = rot_inv.dot(np.transpose(-self.translation_np))
return tm
def rotate_2d_points2d_to_ego_vehicle_frame(self, points2d: npt.NDArray[np.float64]) -> npt.NDArray[np.float64]:
"""
Rotate 2D points from global frame to ego-vehicle frame.
:param points2d: <np.float: num_points, 2>. 2D points in global frame.
:return: <np.float: num_points, 2>. 2D points rotated to ego-vehicle frame.
"""
# Add zeros to the z dimension to make them 3D points.
points3d: npt.NDArray[np.float32] = np.concatenate((points2d, np.zeros_like(points2d[:, 0:1])), axis=-1)
# We need to extract the rotation around the z-axis only. since we are cropping a 2D map.
# Construct scipy rotation instance using the rotation matrix from quaternion.
rotation = R.from_matrix(self.quaternion.rotation_matrix.T)
# Extract the angle of rotation around z-axis from the rotation.
ego_rotation_angle = rotation.as_euler('zxy', degrees=True)[0]
# Construct scipy rotation instance using ego_rotation_angle.
xy_rotation = R.from_euler('z', ego_rotation_angle, degrees=True)
# Rotate the corner points of the desired map crop to align with ego pose.
rotated_points3d = xy_rotation.apply(points3d)
# Remove the z dimension.
rotated_points2d: npt.NDArray[np.float64] = rotated_points3d[:, :2]
return rotated_points2d
def get_map_crop(
self,
maps_db: Optional[GPKGMapsDB],
xrange: Tuple[float, float],
yrange: Tuple[float, float],
map_layer_name: str,
rotate_face_up: bool,
target_imsize_xy: Optional[Tuple[float, float]] = None,
) -> Tuple[Optional[npt.NDArray[np.float64]], npt.NDArray[np.float64], Tuple[float, ...]]:
"""
This function returns the crop of the map centered at the current ego-pose with the given xrange and yrange.
:param maps_db: Map database associated with this database.
:param xrange: The range in x direction in meters relative to the current ego-pose. Eg: (-60, 60]).
:param yrange: The range in y direction in meters relative to the current ego-pose Eg: (-60, 60).
:param map_layer_name: A relevant map layer. Eg: 'drivable_area' or 'intensity'.
:param rotate_face_up: Boolean indicating whether to rotate the image face up with respect to ego-pose.
:param target_imsize_xy: The target grid xy dimensions for the output array. The xy resolution in meters / grid
may be scaled by zooming to the desired dimensions.
:return: (map_crop, map_translation, map_scale). Where:
map_crop: The desired crop of the map.
map_translation: The translation in map coordinates from the origin to the ego-pose.
map_scale: Map scale (inverse of the map precision). This will be a tuple specifying the zoom in both the x
and y direction if the target_imsize_xy parameter was set, which causes the resolution to change.
map_scale and map_translation are useful for transforming objects like pointcloud/boxes to the map_crop.
Refer to render_on_map().
"""
if maps_db is None:
precision: float = 1
def to_pixel_coords(x: float, y: float) -> Tuple[float, float]:
"""
Get the image coordinates given the x-y coordinates of point. This implementation simply returns the
same coordinates.
:param x: Global x coordinate.
:param y: Global y coordinate.
:return: Pixel coordinates in map.
"""
return x, y
else:
map_layer = maps_db.load_layer(self.log.map_version, map_layer_name)
precision = map_layer.precision
to_pixel_coords = map_layer.to_pixel_coords
map_scale: Tuple[float, ...] = (1.0 / precision, 1.0 / precision, 1.0)
ego_translation = self.translation_np
center_x, center_y = to_pixel_coords(ego_translation[0], ego_translation[1])
center_x, center_y = int(center_x), int(center_y)
top_left = int(xrange[0] * map_scale[0]), int(yrange[0] * map_scale[1])
bottom_right = int(xrange[1] * map_scale[0]), int(yrange[1] * map_scale[1])
# We need to extract the rotation around the z-axis only. since we are cropping a 2D map.
# Construct scipy rotation instance using the rotation matrix from quaternion.
rotation = R.from_matrix(self.quaternion.rotation_matrix.T)
# Extract the angle of rotation around z-axis from the rotation.
ego_rotation_angle = rotation.as_euler('zxy', degrees=True)[0]
# Construct scipy rotation instance using ego_rotation_angle.
xy_rotation = R.from_euler('z', ego_rotation_angle, degrees=True)
map_rotate = 0
# Rotate the corner points of the desired map crop to align with ego pose.
rotated = xy_rotation.apply(
[
[top_left[0], top_left[1], 0],
[top_left[0], bottom_right[1], 0],
[bottom_right[0], top_left[1], 0],
[bottom_right[0], bottom_right[1], 0],
]
)[:, :2]
# Construct minAreaRect using 4 corner points
rect = cv2.minAreaRect(np.hstack([rotated[:, :1] + center_x, rotated[:, 1:] + center_y]).astype(int))
rect_angle = rect[2]
# Due to rounding error, the dimensions returned by cv2 may be off by 1, therefore it's better to manually
# calculate the cropped dimensions instead of relying on the values returned by cv2 in rect[1]
cropped_dimensions: npt.NDArray[np.float32] = np.array(
[map_scale[0] * (xrange[1] - xrange[0]), map_scale[1] * (yrange[1] - yrange[0])]
)
rect = (rect[0], cropped_dimensions, rect_angle)
# In OpenCV 4.4, the angle returned by cv2.minAreaRect is [-90,0). In OpenCV 4.5, the angle returned
# appears to be [0, 90), though this isn't documented anywhere. To be compatible with both versions,
# we adjust the angle to be [-90,0) if it isn't already.
rect_angle = rect[2]
cropped_dimensions = np.array([map_scale[0] * (xrange[1] - xrange[0]), map_scale[1] * (yrange[1] - yrange[0])])
if rect_angle >= 0:
rect = (rect[0], cropped_dimensions, rect_angle - 90)
else:
rect = (rect[0], cropped_dimensions, rect_angle)
# We construct rect using cv2.minAreaRect, which takes only 4 unordered corner points, and can not consider
# the angle of the required rect. The range of of 'angle' in cv2.minAreaRect is [-90,0).
# A good explanation for the angle can be found at :
# https://namkeenman.wordpress.com/2015/12/18/open-cv-determine-angle-of-rotatedrect-minarearect/
# Hence, we have to manually rotate the map after cropping based on the initial rotation angle.
if ego_rotation_angle < -90:
map_rotate = -90
if -90 < ego_rotation_angle < 0:
map_rotate = 0
if 0 < ego_rotation_angle < 90:
map_rotate = 90
if 90 < ego_rotation_angle < 180:
map_rotate = 180
if map_layer is None:
map_crop = None
else:
# Crop the rect using minAreaRect.
map_crop = crop_rect(map_layer.data, rect)
# Rotate the cropped map using adjusted angles,
# since the angle is reset in cv2.minAreaRect every 90 degrees.
map_crop = ndimage.rotate(map_crop, map_rotate, reshape=False)
if rotate_face_up:
# The map_crop is aligned with the ego_pose, but ego_pose is facing towards the right of the canvas,
# but we need ego_pose to be facing up, hence rotating an extra 90 degrees.
map_crop = np.rot90(map_crop)
# These are in units of pixels, where x points to the right and y points *down*.
if map_layer is None:
map_upper_left_offset_from_global_coordinate_origin = np.zeros((2,))
else:
map_upper_left_offset_from_global_coordinate_origin = np.array(
[-map_layer.transform_matrix[0, -1], map_layer.transform_matrix[1, -1]]
)
ego_offset_from_map_upper_left: npt.NDArray[np.float32] = np.array([center_x, -center_y])
crop_upper_left_offset_from_ego: npt.NDArray[np.float32] = np.array(
[xrange[0] * map_scale[0], yrange[0] * map_scale[1]]
)
map_translation: npt.NDArray[np.float64] = (
-map_upper_left_offset_from_global_coordinate_origin
- ego_offset_from_map_upper_left
- crop_upper_left_offset_from_ego
)
map_translation_with_z: npt.NDArray[np.float64] = np.array(
[map_translation[0], map_translation[1], 0]
) # add z-coordinate
if target_imsize_xy is not None:
zoom_size_x = target_imsize_xy[0] / cropped_dimensions[0]
zoom_size_y = target_imsize_xy[1] / cropped_dimensions[1]
map_crop = ndimage.zoom(map_crop, [zoom_size_x, zoom_size_y])
map_scale = (zoom_size_x, zoom_size_y)
return map_crop, map_translation_with_z, map_scale
def get_vector_map(
self,
maps_db: Optional[GPKGMapsDB],
xrange: Tuple[float, float],
yrange: Tuple[float, float],
connection_scales: Optional[List[int]] = None,
) -> VectorMapNp:
"""
This function returns the crop of baseline paths (blps) map centered at the current ego-pose with
the given xrange and yrange.
:param maps_db: Map database associated with this database.
:param xrange: The range in x direction in meters relative to the current ego-pose. Eg: [-60, 60].
:param yrange: The range in y direction in meters relative to the current ego-pose Eg: [-60, 60].
:param connection_scales: Connection scales to generate. Use the 1-hop connections if it's left empty.
:return: Vector map data including lane segment coordinates and connections within the given range.
"""
# load geopandas data
map_version = self.lidar_pc.log.map_version.replace('.gpkg', '')
blps_gdf = maps_db.load_vector_layer(map_version, 'baseline_paths') # type: ignore
lane_poly_gdf = maps_db.load_vector_layer(map_version, 'lanes_polygons') # type: ignore
intersections_gdf = maps_db.load_vector_layer(map_version, 'intersections') # type: ignore
lane_connectors_gdf = maps_db.load_vector_layer(map_version, 'lane_connectors') # type: ignore
lane_groups_gdf = maps_db.load_vector_layer(map_version, 'lane_groups_polygons') # type: ignore
if (
(blps_gdf is None)
or (lane_poly_gdf is None)
or (intersections_gdf is None)
or (lane_connectors_gdf is None)
or (lane_groups_gdf is None)
):
# This sample has no vector map.
coords: npt.NDArray[np.float32] = np.empty([0, 2, 2], dtype=np.float32)
if not connection_scales:
# Use the 1-hop connections if connection_scales is not specified.
connection_scales = [1]
multi_scale_connections: Dict[int, Any] = {
scale: np.empty([0, 2], dtype=np.int64) for scale in connection_scales
}
return VectorMapNp(
coords=coords,
multi_scale_connections=multi_scale_connections,
)
# data enhancement
blps_in_lanes = blps_gdf[blps_gdf['lane_fid'].notna()]
blps_in_intersections = blps_gdf[blps_gdf['lane_connector_fid'].notna()]
# enhance blps_in_lanes
lane_group_info = lane_poly_gdf[['lane_fid', 'lane_group_fid']]
blps_in_lanes = blps_in_lanes.merge(lane_group_info, on='lane_fid', how='outer')
# enhance blps_in_intersections
lane_connectors_gdf['lane_connector_fid'] = lane_connectors_gdf['fid']
lane_conns_info = lane_connectors_gdf[
['lane_connector_fid', 'intersection_fid', 'exit_lane_fid', 'entry_lane_fid']
]
# Convert the exit_fid field of both data frames to the same dtype for merging.
lane_conns_info = lane_conns_info.astype({'lane_connector_fid': int})
blps_in_intersections = blps_in_intersections.astype({'lane_connector_fid': int})
blps_in_intersections = blps_in_intersections.merge(lane_conns_info, on='lane_connector_fid', how='outer')
# enhance blps_connection info
lane_blps_info = blps_in_lanes[['fid', 'lane_fid']]
from_blps_info = lane_blps_info.rename(columns={'fid': 'from_blp', 'lane_fid': 'exit_lane_fid'})
to_blps_info = lane_blps_info.rename(columns={'fid': 'to_blp', 'lane_fid': 'entry_lane_fid'})
blps_in_intersections = blps_in_intersections.merge(from_blps_info, on='exit_lane_fid', how='inner')
blps_in_intersections = blps_in_intersections.merge(to_blps_info, on='entry_lane_fid', how='inner')
# Select in-range blps
candidate_lane_groups, candidate_intersections = get_candidates(
self.translation_np, xrange, yrange, lane_groups_gdf, intersections_gdf
)
candidate_blps_in_lanes = blps_in_lanes[
blps_in_lanes['lane_group_fid'].isin(candidate_lane_groups['fid'].astype(int))
]
candidate_blps_in_intersections = blps_in_intersections[
blps_in_intersections['intersection_fid'].isin(candidate_intersections['fid'].astype(int))
]
ls_coordinates_list: List[List[List[float]]] = []
ls_connections_list: List[List[int]] = []
ls_groupings_list: List[List[int]] = []
cross_blp_connection: Dict[str, List[int]] = dict()
# generate lane_segments from blps in lanes
build_lane_segments_from_blps(
candidate_blps_in_lanes, ls_coordinates_list, ls_connections_list, ls_groupings_list, cross_blp_connection
)
# generate lane_segments from blps in intersections
build_lane_segments_from_blps(
candidate_blps_in_intersections,
ls_coordinates_list,
ls_connections_list,
ls_groupings_list,
cross_blp_connection,
)
# generate connections between blps
for blp_id, blp_info in cross_blp_connection.items():
# Add predecessors
connect_blp_predecessor(blp_id, candidate_blps_in_intersections, cross_blp_connection, ls_connections_list)
# Add successors
connect_blp_successor(blp_id, candidate_blps_in_intersections, cross_blp_connection, ls_connections_list)
ls_coordinates: npt.NDArray[np.float64] = np.asarray(ls_coordinates_list, self.translation_np.dtype)
ls_connections: npt.NDArray[np.int64] = np.asarray(ls_connections_list, np.int64)
# Transform the lane coordinates from global frame to ego vehicle frame.
# Flatten ls_coordinates from (num_ls, 2, 2) to (num_ls * 2, 2) for easier processing.
ls_coordinates = ls_coordinates.reshape(-1, 2)
ls_coordinates = ls_coordinates - self.translation_np[:2]
ls_coordinates = self.rotate_2d_points2d_to_ego_vehicle_frame(ls_coordinates)
ls_coordinates = ls_coordinates.reshape(-1, 2, 2).astype(np.float32)
if connection_scales:
# Generate multi-scale connections.
multi_scale_connections = generate_multi_scale_connections(ls_connections, connection_scales)
else:
# Use the 1-hop connections if connection_scales is not specified.
multi_scale_connections = {1: ls_connections}
return VectorMapNp(
coords=ls_coordinates,
multi_scale_connections=multi_scale_connections,
)
Image.ego_pose = relationship("EgoPose", foreign_keys=[Image.ego_pose_token], back_populates="image") | nuplan/database/nuplan_db/ego_pose.py | from __future__ import annotations # postpone evaluation of annotations
import logging
from typing import Any, Dict, List, Optional, Tuple
import cv2
import numpy as np
import numpy.typing as npt
from pyquaternion import Quaternion
from scipy import ndimage
from scipy.spatial.transform import Rotation as R
from sqlalchemy import Column, inspect
from sqlalchemy.orm import relationship
from sqlalchemy.schema import ForeignKey
from sqlalchemy.types import Float, Integer
from nuplan.database.common import sql_types
from nuplan.database.common.utils import simple_repr
from nuplan.database.maps_db.gpkg_mapsdb import GPKGMapsDB
from nuplan.database.maps_db.utils import build_lane_segments_from_blps, connect_blp_predecessor, connect_blp_successor
from nuplan.database.nuplan_db.models import Base, Image, generate_multi_scale_connections
from nuplan.database.nuplan_db.utils import crop_rect, get_candidates
from nuplan.database.nuplan_db.vector_map_np import VectorMapNp
logger = logging.getLogger()
class EgoPose(Base):
"""
Ego vehicle pose at a particular timestamp. Given with respect to global coordinate system.
"""
__tablename__ = "ego_pose"
token = Column(sql_types.HexLen8, primary_key=True) # type: str
timestamp = Column(Integer) # field type: int
x = Column(Float) # type: float
y = Column(Float) # type: float
z = Column(Float) # type: float
qw: float = Column(Float)
qx: float = Column(Float)
qy: float = Column(Float)
qz: float = Column(Float)
vx = Column(Float) # type: float
vy = Column(Float) # type: float
vz = Column(Float) # type: float
acceleration_x = Column(Float) # type: float
acceleration_y = Column(Float) # type: float
acceleration_z = Column(Float) # type: float
angular_rate_x = Column(Float) # type: float
angular_rate_y = Column(Float) # type: float
angular_rate_z = Column(Float) # type: float
epsg = Column(Integer) # type: int
log_token = Column(sql_types.HexLen8, ForeignKey("log.token"), nullable=False) # type: str
image = relationship(
"Image", foreign_keys="Image.ego_pose_token", back_populates="ego_pose", uselist=False
) # type: Image
@property
def _session(self) -> Any:
"""
Get the underlying session.
:return: The underlying session.
"""
return inspect(self).session
def __repr__(self) -> str:
"""
Return the string representation.
:return: The string representation.
"""
desc: str = simple_repr(self)
return desc
@property
def quaternion(self) -> Quaternion:
"""
Get the orientation of ego vehicle as quaternion respect to global coordinate system.
:return: The orientation in quaternion.
"""
return Quaternion(self.qw, self.qx, self.qy, self.qz)
@property
def translation_np(self) -> npt.NDArray[np.float64]:
"""
Position of ego vehicle respect to global coordinate system.
:return: <np.float: 3> Translation.
"""
return np.array([self.x, self.y, self.z])
@property
def trans_matrix(self) -> npt.NDArray[np.float64]:
"""
Get the transformation matrix.
:return: <np.float: 4, 4>. Transformation matrix.
"""
tm: npt.NDArray[np.float64] = self.quaternion.transformation_matrix
tm[:3, 3] = self.translation_np
return tm
@property
def trans_matrix_inv(self) -> npt.NDArray[np.float64]:
"""
Get the inverse transformation matrix.
:return: <np.float: 4, 4>. Inverse transformation matrix.
"""
tm: npt.NDArray[np.float64] = np.eye(4)
rot_inv = self.quaternion.rotation_matrix.T
tm[:3, :3] = rot_inv
tm[:3, 3] = rot_inv.dot(np.transpose(-self.translation_np))
return tm
def rotate_2d_points2d_to_ego_vehicle_frame(self, points2d: npt.NDArray[np.float64]) -> npt.NDArray[np.float64]:
"""
Rotate 2D points from global frame to ego-vehicle frame.
:param points2d: <np.float: num_points, 2>. 2D points in global frame.
:return: <np.float: num_points, 2>. 2D points rotated to ego-vehicle frame.
"""
# Add zeros to the z dimension to make them 3D points.
points3d: npt.NDArray[np.float32] = np.concatenate((points2d, np.zeros_like(points2d[:, 0:1])), axis=-1)
# We need to extract the rotation around the z-axis only. since we are cropping a 2D map.
# Construct scipy rotation instance using the rotation matrix from quaternion.
rotation = R.from_matrix(self.quaternion.rotation_matrix.T)
# Extract the angle of rotation around z-axis from the rotation.
ego_rotation_angle = rotation.as_euler('zxy', degrees=True)[0]
# Construct scipy rotation instance using ego_rotation_angle.
xy_rotation = R.from_euler('z', ego_rotation_angle, degrees=True)
# Rotate the corner points of the desired map crop to align with ego pose.
rotated_points3d = xy_rotation.apply(points3d)
# Remove the z dimension.
rotated_points2d: npt.NDArray[np.float64] = rotated_points3d[:, :2]
return rotated_points2d
def get_map_crop(
self,
maps_db: Optional[GPKGMapsDB],
xrange: Tuple[float, float],
yrange: Tuple[float, float],
map_layer_name: str,
rotate_face_up: bool,
target_imsize_xy: Optional[Tuple[float, float]] = None,
) -> Tuple[Optional[npt.NDArray[np.float64]], npt.NDArray[np.float64], Tuple[float, ...]]:
"""
This function returns the crop of the map centered at the current ego-pose with the given xrange and yrange.
:param maps_db: Map database associated with this database.
:param xrange: The range in x direction in meters relative to the current ego-pose. Eg: (-60, 60]).
:param yrange: The range in y direction in meters relative to the current ego-pose Eg: (-60, 60).
:param map_layer_name: A relevant map layer. Eg: 'drivable_area' or 'intensity'.
:param rotate_face_up: Boolean indicating whether to rotate the image face up with respect to ego-pose.
:param target_imsize_xy: The target grid xy dimensions for the output array. The xy resolution in meters / grid
may be scaled by zooming to the desired dimensions.
:return: (map_crop, map_translation, map_scale). Where:
map_crop: The desired crop of the map.
map_translation: The translation in map coordinates from the origin to the ego-pose.
map_scale: Map scale (inverse of the map precision). This will be a tuple specifying the zoom in both the x
and y direction if the target_imsize_xy parameter was set, which causes the resolution to change.
map_scale and map_translation are useful for transforming objects like pointcloud/boxes to the map_crop.
Refer to render_on_map().
"""
if maps_db is None:
precision: float = 1
def to_pixel_coords(x: float, y: float) -> Tuple[float, float]:
"""
Get the image coordinates given the x-y coordinates of point. This implementation simply returns the
same coordinates.
:param x: Global x coordinate.
:param y: Global y coordinate.
:return: Pixel coordinates in map.
"""
return x, y
else:
map_layer = maps_db.load_layer(self.log.map_version, map_layer_name)
precision = map_layer.precision
to_pixel_coords = map_layer.to_pixel_coords
map_scale: Tuple[float, ...] = (1.0 / precision, 1.0 / precision, 1.0)
ego_translation = self.translation_np
center_x, center_y = to_pixel_coords(ego_translation[0], ego_translation[1])
center_x, center_y = int(center_x), int(center_y)
top_left = int(xrange[0] * map_scale[0]), int(yrange[0] * map_scale[1])
bottom_right = int(xrange[1] * map_scale[0]), int(yrange[1] * map_scale[1])
# We need to extract the rotation around the z-axis only. since we are cropping a 2D map.
# Construct scipy rotation instance using the rotation matrix from quaternion.
rotation = R.from_matrix(self.quaternion.rotation_matrix.T)
# Extract the angle of rotation around z-axis from the rotation.
ego_rotation_angle = rotation.as_euler('zxy', degrees=True)[0]
# Construct scipy rotation instance using ego_rotation_angle.
xy_rotation = R.from_euler('z', ego_rotation_angle, degrees=True)
map_rotate = 0
# Rotate the corner points of the desired map crop to align with ego pose.
rotated = xy_rotation.apply(
[
[top_left[0], top_left[1], 0],
[top_left[0], bottom_right[1], 0],
[bottom_right[0], top_left[1], 0],
[bottom_right[0], bottom_right[1], 0],
]
)[:, :2]
# Construct minAreaRect using 4 corner points
rect = cv2.minAreaRect(np.hstack([rotated[:, :1] + center_x, rotated[:, 1:] + center_y]).astype(int))
rect_angle = rect[2]
# Due to rounding error, the dimensions returned by cv2 may be off by 1, therefore it's better to manually
# calculate the cropped dimensions instead of relying on the values returned by cv2 in rect[1]
cropped_dimensions: npt.NDArray[np.float32] = np.array(
[map_scale[0] * (xrange[1] - xrange[0]), map_scale[1] * (yrange[1] - yrange[0])]
)
rect = (rect[0], cropped_dimensions, rect_angle)
# In OpenCV 4.4, the angle returned by cv2.minAreaRect is [-90,0). In OpenCV 4.5, the angle returned
# appears to be [0, 90), though this isn't documented anywhere. To be compatible with both versions,
# we adjust the angle to be [-90,0) if it isn't already.
rect_angle = rect[2]
cropped_dimensions = np.array([map_scale[0] * (xrange[1] - xrange[0]), map_scale[1] * (yrange[1] - yrange[0])])
if rect_angle >= 0:
rect = (rect[0], cropped_dimensions, rect_angle - 90)
else:
rect = (rect[0], cropped_dimensions, rect_angle)
# We construct rect using cv2.minAreaRect, which takes only 4 unordered corner points, and can not consider
# the angle of the required rect. The range of of 'angle' in cv2.minAreaRect is [-90,0).
# A good explanation for the angle can be found at :
# https://namkeenman.wordpress.com/2015/12/18/open-cv-determine-angle-of-rotatedrect-minarearect/
# Hence, we have to manually rotate the map after cropping based on the initial rotation angle.
if ego_rotation_angle < -90:
map_rotate = -90
if -90 < ego_rotation_angle < 0:
map_rotate = 0
if 0 < ego_rotation_angle < 90:
map_rotate = 90
if 90 < ego_rotation_angle < 180:
map_rotate = 180
if map_layer is None:
map_crop = None
else:
# Crop the rect using minAreaRect.
map_crop = crop_rect(map_layer.data, rect)
# Rotate the cropped map using adjusted angles,
# since the angle is reset in cv2.minAreaRect every 90 degrees.
map_crop = ndimage.rotate(map_crop, map_rotate, reshape=False)
if rotate_face_up:
# The map_crop is aligned with the ego_pose, but ego_pose is facing towards the right of the canvas,
# but we need ego_pose to be facing up, hence rotating an extra 90 degrees.
map_crop = np.rot90(map_crop)
# These are in units of pixels, where x points to the right and y points *down*.
if map_layer is None:
map_upper_left_offset_from_global_coordinate_origin = np.zeros((2,))
else:
map_upper_left_offset_from_global_coordinate_origin = np.array(
[-map_layer.transform_matrix[0, -1], map_layer.transform_matrix[1, -1]]
)
ego_offset_from_map_upper_left: npt.NDArray[np.float32] = np.array([center_x, -center_y])
crop_upper_left_offset_from_ego: npt.NDArray[np.float32] = np.array(
[xrange[0] * map_scale[0], yrange[0] * map_scale[1]]
)
map_translation: npt.NDArray[np.float64] = (
-map_upper_left_offset_from_global_coordinate_origin
- ego_offset_from_map_upper_left
- crop_upper_left_offset_from_ego
)
map_translation_with_z: npt.NDArray[np.float64] = np.array(
[map_translation[0], map_translation[1], 0]
) # add z-coordinate
if target_imsize_xy is not None:
zoom_size_x = target_imsize_xy[0] / cropped_dimensions[0]
zoom_size_y = target_imsize_xy[1] / cropped_dimensions[1]
map_crop = ndimage.zoom(map_crop, [zoom_size_x, zoom_size_y])
map_scale = (zoom_size_x, zoom_size_y)
return map_crop, map_translation_with_z, map_scale
def get_vector_map(
self,
maps_db: Optional[GPKGMapsDB],
xrange: Tuple[float, float],
yrange: Tuple[float, float],
connection_scales: Optional[List[int]] = None,
) -> VectorMapNp:
"""
This function returns the crop of baseline paths (blps) map centered at the current ego-pose with
the given xrange and yrange.
:param maps_db: Map database associated with this database.
:param xrange: The range in x direction in meters relative to the current ego-pose. Eg: [-60, 60].
:param yrange: The range in y direction in meters relative to the current ego-pose Eg: [-60, 60].
:param connection_scales: Connection scales to generate. Use the 1-hop connections if it's left empty.
:return: Vector map data including lane segment coordinates and connections within the given range.
"""
# load geopandas data
map_version = self.lidar_pc.log.map_version.replace('.gpkg', '')
blps_gdf = maps_db.load_vector_layer(map_version, 'baseline_paths') # type: ignore
lane_poly_gdf = maps_db.load_vector_layer(map_version, 'lanes_polygons') # type: ignore
intersections_gdf = maps_db.load_vector_layer(map_version, 'intersections') # type: ignore
lane_connectors_gdf = maps_db.load_vector_layer(map_version, 'lane_connectors') # type: ignore
lane_groups_gdf = maps_db.load_vector_layer(map_version, 'lane_groups_polygons') # type: ignore
if (
(blps_gdf is None)
or (lane_poly_gdf is None)
or (intersections_gdf is None)
or (lane_connectors_gdf is None)
or (lane_groups_gdf is None)
):
# This sample has no vector map.
coords: npt.NDArray[np.float32] = np.empty([0, 2, 2], dtype=np.float32)
if not connection_scales:
# Use the 1-hop connections if connection_scales is not specified.
connection_scales = [1]
multi_scale_connections: Dict[int, Any] = {
scale: np.empty([0, 2], dtype=np.int64) for scale in connection_scales
}
return VectorMapNp(
coords=coords,
multi_scale_connections=multi_scale_connections,
)
# data enhancement
blps_in_lanes = blps_gdf[blps_gdf['lane_fid'].notna()]
blps_in_intersections = blps_gdf[blps_gdf['lane_connector_fid'].notna()]
# enhance blps_in_lanes
lane_group_info = lane_poly_gdf[['lane_fid', 'lane_group_fid']]
blps_in_lanes = blps_in_lanes.merge(lane_group_info, on='lane_fid', how='outer')
# enhance blps_in_intersections
lane_connectors_gdf['lane_connector_fid'] = lane_connectors_gdf['fid']
lane_conns_info = lane_connectors_gdf[
['lane_connector_fid', 'intersection_fid', 'exit_lane_fid', 'entry_lane_fid']
]
# Convert the exit_fid field of both data frames to the same dtype for merging.
lane_conns_info = lane_conns_info.astype({'lane_connector_fid': int})
blps_in_intersections = blps_in_intersections.astype({'lane_connector_fid': int})
blps_in_intersections = blps_in_intersections.merge(lane_conns_info, on='lane_connector_fid', how='outer')
# enhance blps_connection info
lane_blps_info = blps_in_lanes[['fid', 'lane_fid']]
from_blps_info = lane_blps_info.rename(columns={'fid': 'from_blp', 'lane_fid': 'exit_lane_fid'})
to_blps_info = lane_blps_info.rename(columns={'fid': 'to_blp', 'lane_fid': 'entry_lane_fid'})
blps_in_intersections = blps_in_intersections.merge(from_blps_info, on='exit_lane_fid', how='inner')
blps_in_intersections = blps_in_intersections.merge(to_blps_info, on='entry_lane_fid', how='inner')
# Select in-range blps
candidate_lane_groups, candidate_intersections = get_candidates(
self.translation_np, xrange, yrange, lane_groups_gdf, intersections_gdf
)
candidate_blps_in_lanes = blps_in_lanes[
blps_in_lanes['lane_group_fid'].isin(candidate_lane_groups['fid'].astype(int))
]
candidate_blps_in_intersections = blps_in_intersections[
blps_in_intersections['intersection_fid'].isin(candidate_intersections['fid'].astype(int))
]
ls_coordinates_list: List[List[List[float]]] = []
ls_connections_list: List[List[int]] = []
ls_groupings_list: List[List[int]] = []
cross_blp_connection: Dict[str, List[int]] = dict()
# generate lane_segments from blps in lanes
build_lane_segments_from_blps(
candidate_blps_in_lanes, ls_coordinates_list, ls_connections_list, ls_groupings_list, cross_blp_connection
)
# generate lane_segments from blps in intersections
build_lane_segments_from_blps(
candidate_blps_in_intersections,
ls_coordinates_list,
ls_connections_list,
ls_groupings_list,
cross_blp_connection,
)
# generate connections between blps
for blp_id, blp_info in cross_blp_connection.items():
# Add predecessors
connect_blp_predecessor(blp_id, candidate_blps_in_intersections, cross_blp_connection, ls_connections_list)
# Add successors
connect_blp_successor(blp_id, candidate_blps_in_intersections, cross_blp_connection, ls_connections_list)
ls_coordinates: npt.NDArray[np.float64] = np.asarray(ls_coordinates_list, self.translation_np.dtype)
ls_connections: npt.NDArray[np.int64] = np.asarray(ls_connections_list, np.int64)
# Transform the lane coordinates from global frame to ego vehicle frame.
# Flatten ls_coordinates from (num_ls, 2, 2) to (num_ls * 2, 2) for easier processing.
ls_coordinates = ls_coordinates.reshape(-1, 2)
ls_coordinates = ls_coordinates - self.translation_np[:2]
ls_coordinates = self.rotate_2d_points2d_to_ego_vehicle_frame(ls_coordinates)
ls_coordinates = ls_coordinates.reshape(-1, 2, 2).astype(np.float32)
if connection_scales:
# Generate multi-scale connections.
multi_scale_connections = generate_multi_scale_connections(ls_connections, connection_scales)
else:
# Use the 1-hop connections if connection_scales is not specified.
multi_scale_connections = {1: ls_connections}
return VectorMapNp(
coords=ls_coordinates,
multi_scale_connections=multi_scale_connections,
)
Image.ego_pose = relationship("EgoPose", foreign_keys=[Image.ego_pose_token], back_populates="image") | 0.953286 | 0.389488 |
from pprint import pprint
import pandas as pd
import ccxt
from model import Balance
class ApiClient(ccxt.cryptopia):
def __init__(self, apikey=None, secret=None, **config):
super().__init__(config)
if apikey is not None and secret is not None:
self.apiKey = apikey
self.secret = secret
self.enableRateLimit = True
def get_balance(self, currency=None):
balance = self.fetch_balance()
del balance['info'], balance['used'], balance['free'], balance['total']
result = {k: v for k, v in balance.items() if v['total'] > 0.0}
if currency is not None:
result = Balance(**balance.get(currency, {}))
return result
def get_ticker(self, symbol=None, hours=24):
params = dict(params={'hours': hours})
result = dict()
if symbol is None:
data = self.fetch_tickers(params=params)
for k, v in data.items():
base, quote = k.split('/')
if quote in ['BTC', 'USDT']:
min_volume = 25000 if 'USDT' in quote else 0.1
if v['quoteVolume'] > min_volume:
del v['info'], v['askVolume'], v['bidVolume'], v['previousClose']
result.update({k: v})
else:
data = self.fetch_ticker(symbol, params=params)
del data['info']
return pd.DataFrame(result)
def get_market_history(self, symbol=None, limit=100):
params = dict(params={'limit': limit})
result = dict()
if symbol is None:
data = self.fetch_tickers(params=params)
for k, v in data.items():
base, quote = k.split('/')
if quote in ['BTC', 'USDT']:
min_volume = 25000 if 'USDT' in quote else 0.1
if v['quoteVolume'] > min_volume:
del v['info'], v['askVolume'], v['bidVolume'], v['previousClose']
result.update({k: v})
else:
data = self.fetch_ticker(symbol, params=params)
del data['info']
return pd.DataFrame(result)
if __name__ == '__main__':
pd.set_option('precision', 8)
api = ApiClient()
ticker = api.get_ticker()
# btc_exchange = ticker.query('')
print(ticker.sort_values(by='baseVolume', axis=1, ascending=False).first_valid_index())
# api.get_ticker('DGB/BTC') | clitopia/api.py | from pprint import pprint
import pandas as pd
import ccxt
from model import Balance
class ApiClient(ccxt.cryptopia):
def __init__(self, apikey=None, secret=None, **config):
super().__init__(config)
if apikey is not None and secret is not None:
self.apiKey = apikey
self.secret = secret
self.enableRateLimit = True
def get_balance(self, currency=None):
balance = self.fetch_balance()
del balance['info'], balance['used'], balance['free'], balance['total']
result = {k: v for k, v in balance.items() if v['total'] > 0.0}
if currency is not None:
result = Balance(**balance.get(currency, {}))
return result
def get_ticker(self, symbol=None, hours=24):
params = dict(params={'hours': hours})
result = dict()
if symbol is None:
data = self.fetch_tickers(params=params)
for k, v in data.items():
base, quote = k.split('/')
if quote in ['BTC', 'USDT']:
min_volume = 25000 if 'USDT' in quote else 0.1
if v['quoteVolume'] > min_volume:
del v['info'], v['askVolume'], v['bidVolume'], v['previousClose']
result.update({k: v})
else:
data = self.fetch_ticker(symbol, params=params)
del data['info']
return pd.DataFrame(result)
def get_market_history(self, symbol=None, limit=100):
params = dict(params={'limit': limit})
result = dict()
if symbol is None:
data = self.fetch_tickers(params=params)
for k, v in data.items():
base, quote = k.split('/')
if quote in ['BTC', 'USDT']:
min_volume = 25000 if 'USDT' in quote else 0.1
if v['quoteVolume'] > min_volume:
del v['info'], v['askVolume'], v['bidVolume'], v['previousClose']
result.update({k: v})
else:
data = self.fetch_ticker(symbol, params=params)
del data['info']
return pd.DataFrame(result)
if __name__ == '__main__':
pd.set_option('precision', 8)
api = ApiClient()
ticker = api.get_ticker()
# btc_exchange = ticker.query('')
print(ticker.sort_values(by='baseVolume', axis=1, ascending=False).first_valid_index())
# api.get_ticker('DGB/BTC') | 0.251464 | 0.109301 |
REQUIREMENTS_MAP = {
'appengine':
{'module_name': 'load_appengine_pipeline',
'depends_on': 'projects',
'api_name': 'appengine_api',
'dao_name': 'appengine_dao'},
'backend_services':
{'module_name': 'load_backend_services_pipeline',
'depends_on': 'projects',
'api_name': 'compute_api',
'dao_name': 'backend_service_dao'},
'bigquery_datasets':
{'module_name': 'load_bigquery_datasets_pipeline',
'depends_on': 'projects',
'api_name': 'bigquery_api',
'dao_name': 'dao'},
'buckets':
{'module_name': 'load_projects_buckets_pipeline',
'depends_on': 'projects',
'api_name': 'gcs_api',
'dao_name': 'project_dao'},
'buckets_acls':
{'module_name': 'load_projects_buckets_acls_pipeline',
'depends_on': 'buckets',
'api_name': 'gcs_api',
'dao_name': 'bucket_dao'},
'cloudsql':
{'module_name': 'load_projects_cloudsql_pipeline',
'depends_on': 'projects',
'api_name': 'cloudsql_api',
'dao_name': 'cloudsql_dao'},
'firewall_rules':
{'module_name': 'load_firewall_rules_pipeline',
'depends_on': 'projects',
'api_name': 'compute_api',
'dao_name': 'project_dao'},
'folder_iam_policies':
{'module_name': 'load_folder_iam_policies_pipeline',
'depends_on': 'folders',
'api_name': 'crm_api',
'dao_name': 'folder_dao'},
'folders':
{'module_name': 'load_folders_pipeline',
'depends_on': 'organizations',
'api_name': 'crm_api',
'dao_name': 'folder_dao'},
'forwarding_rules':
{'module_name': 'load_forwarding_rules_pipeline',
'depends_on': 'projects',
'api_name': 'compute_api',
'dao_name': 'forwarding_rules_dao'},
'ke':
{'module_name': 'load_ke_pipeline',
'depends_on': 'projects',
'api_name': 'ke_api',
'dao_name': 'ke_dao'},
'group_members':
{'module_name': 'load_group_members_pipeline',
'depends_on': 'groups',
'api_name': 'admin_api',
'dao_name': 'dao'},
'groups':
{'module_name': 'load_groups_pipeline',
'depends_on': 'organizations',
'api_name': 'admin_api',
'dao_name': 'dao'},
'instance_group_managers':
{'module_name': 'load_instance_group_managers_pipeline',
'depends_on': 'projects',
'api_name': 'compute_api',
'dao_name': 'instance_group_manager_dao'},
'instance_groups':
{'module_name': 'load_instance_groups_pipeline',
'depends_on': 'projects',
'api_name': 'compute_api',
'dao_name': 'instance_group_dao'},
'instance_templates':
{'module_name': 'load_instance_templates_pipeline',
'depends_on': 'projects',
'api_name': 'compute_api',
'dao_name': 'instance_template_dao'},
'instances':
{'module_name': 'load_instances_pipeline',
'depends_on': 'projects',
'api_name': 'compute_api',
'dao_name': 'instance_dao'},
'org_iam_policies':
{'module_name': 'load_org_iam_policies_pipeline',
'depends_on': 'organizations',
'api_name': 'crm_api',
'dao_name': 'organization_dao'},
'organizations':
{'module_name': 'load_orgs_pipeline',
'depends_on': None,
'api_name': 'crm_api',
'dao_name': 'organization_dao'},
'projects':
{'module_name': 'load_projects_pipeline',
'depends_on': 'folders',
'api_name': 'crm_api',
'dao_name': 'project_dao'},
'projects_iam_policies':
{'module_name': 'load_projects_iam_policies_pipeline',
'depends_on': 'projects',
'api_name': 'crm_api',
'dao_name': 'project_dao'},
'service_accounts':
{'module_name': 'load_service_accounts_pipeline',
'depends_on': 'projects',
'api_name': 'iam_api',
'dao_name': 'service_account_dao'},
} | google/cloud/security/inventory/pipeline_requirements_map.py | REQUIREMENTS_MAP = {
'appengine':
{'module_name': 'load_appengine_pipeline',
'depends_on': 'projects',
'api_name': 'appengine_api',
'dao_name': 'appengine_dao'},
'backend_services':
{'module_name': 'load_backend_services_pipeline',
'depends_on': 'projects',
'api_name': 'compute_api',
'dao_name': 'backend_service_dao'},
'bigquery_datasets':
{'module_name': 'load_bigquery_datasets_pipeline',
'depends_on': 'projects',
'api_name': 'bigquery_api',
'dao_name': 'dao'},
'buckets':
{'module_name': 'load_projects_buckets_pipeline',
'depends_on': 'projects',
'api_name': 'gcs_api',
'dao_name': 'project_dao'},
'buckets_acls':
{'module_name': 'load_projects_buckets_acls_pipeline',
'depends_on': 'buckets',
'api_name': 'gcs_api',
'dao_name': 'bucket_dao'},
'cloudsql':
{'module_name': 'load_projects_cloudsql_pipeline',
'depends_on': 'projects',
'api_name': 'cloudsql_api',
'dao_name': 'cloudsql_dao'},
'firewall_rules':
{'module_name': 'load_firewall_rules_pipeline',
'depends_on': 'projects',
'api_name': 'compute_api',
'dao_name': 'project_dao'},
'folder_iam_policies':
{'module_name': 'load_folder_iam_policies_pipeline',
'depends_on': 'folders',
'api_name': 'crm_api',
'dao_name': 'folder_dao'},
'folders':
{'module_name': 'load_folders_pipeline',
'depends_on': 'organizations',
'api_name': 'crm_api',
'dao_name': 'folder_dao'},
'forwarding_rules':
{'module_name': 'load_forwarding_rules_pipeline',
'depends_on': 'projects',
'api_name': 'compute_api',
'dao_name': 'forwarding_rules_dao'},
'ke':
{'module_name': 'load_ke_pipeline',
'depends_on': 'projects',
'api_name': 'ke_api',
'dao_name': 'ke_dao'},
'group_members':
{'module_name': 'load_group_members_pipeline',
'depends_on': 'groups',
'api_name': 'admin_api',
'dao_name': 'dao'},
'groups':
{'module_name': 'load_groups_pipeline',
'depends_on': 'organizations',
'api_name': 'admin_api',
'dao_name': 'dao'},
'instance_group_managers':
{'module_name': 'load_instance_group_managers_pipeline',
'depends_on': 'projects',
'api_name': 'compute_api',
'dao_name': 'instance_group_manager_dao'},
'instance_groups':
{'module_name': 'load_instance_groups_pipeline',
'depends_on': 'projects',
'api_name': 'compute_api',
'dao_name': 'instance_group_dao'},
'instance_templates':
{'module_name': 'load_instance_templates_pipeline',
'depends_on': 'projects',
'api_name': 'compute_api',
'dao_name': 'instance_template_dao'},
'instances':
{'module_name': 'load_instances_pipeline',
'depends_on': 'projects',
'api_name': 'compute_api',
'dao_name': 'instance_dao'},
'org_iam_policies':
{'module_name': 'load_org_iam_policies_pipeline',
'depends_on': 'organizations',
'api_name': 'crm_api',
'dao_name': 'organization_dao'},
'organizations':
{'module_name': 'load_orgs_pipeline',
'depends_on': None,
'api_name': 'crm_api',
'dao_name': 'organization_dao'},
'projects':
{'module_name': 'load_projects_pipeline',
'depends_on': 'folders',
'api_name': 'crm_api',
'dao_name': 'project_dao'},
'projects_iam_policies':
{'module_name': 'load_projects_iam_policies_pipeline',
'depends_on': 'projects',
'api_name': 'crm_api',
'dao_name': 'project_dao'},
'service_accounts':
{'module_name': 'load_service_accounts_pipeline',
'depends_on': 'projects',
'api_name': 'iam_api',
'dao_name': 'service_account_dao'},
} | 0.276007 | 0.057679 |
import requests
from tx.router import plugin_config, plugin
from tx.router.logging import l
import logging
import connexion
import sys
from werkzeug.datastructures import Headers
from flask import Response, request
from tempfile import TemporaryFile
logger = logging.getLogger()
logger.setLevel(logging.INFO)
def set_forwarded_path_header(f):
def func(name, path, headers, *args, **kwargs):
forwarded_path0_slash = connexion.request.headers.get("X-Forwarded-Path", "")
forwarded_path0 = forwarded_path0_slash.rstrip("/")
forwarded_path = f"{forwarded_path0}/v1/plugin/{name}"
headers0 = {**headers, "X-Forwarded-Path": forwarded_path}
logger.debug("headers0 = " + str(headers0))
return f(name, path, headers0, *args, **kwargs)
return func
@l("get", "backend")
@set_forwarded_path_header
def get_plugin(name, path, headers, kwargs={}):
pc = plugin_config.get_plugin_config(name)
if pc is None:
return "not found", 404
port = pc.get("port", None)
if port is None:
raise RuntimeError("plugin doesn't have port")
resp = requests.get("http://{host}:{port}/{path}".format(host=pc["name"], port=port, path=path), headers=headers, params=kwargs, stream=True)
return Response(resp.iter_content(chunk_size=1024*1024), status=resp.status_code, headers=Headers(resp.headers.items()))
@l("post", "backend")
@set_forwarded_path_header
def post_plugin(name, path, headers, stream, kwargs={}):
return base_plugin(requests.post, name, path, headers, stream, kwargs)
def base_plugin(method, name, path, headers, stream, kwargs):
pc = plugin_config.get_plugin_config(name)
if pc is None:
return "not found", 404
port = pc.get("port", None)
if port is None:
raise RuntimeError("plugin doesn't have port")
with TemporaryFile() as f:
chunk_size = 4096
while True:
chunk = stream.read(chunk_size)
if len(chunk) == 0:
break
f.write(chunk)
f.seek(0, 0)
resp = method("http://{host}:{port}/{path}".format(host=pc["name"], port=port, path=path), headers=headers, params=kwargs, data=f, stream=True)
return Response(resp.iter_content(chunk_size=1024*1024), status=resp.status_code, headers=Headers(resp.headers.items()))
@l("delete", "backend")
@set_forwarded_path_header
def delete_plugin(name, path, headers, stream, kwargs={}):
return base_plugin(requests.delete, name, path, headers, stream, kwargs)
def get_plugin_config(name):
pc = plugin_config.get_plugin_config(name)
pc["_id"] = str(pc["_id"])
return pc
def fil(name, name_regex):
fils = []
if name_regex is not None:
fils.append({"name": {"$regex": name_regex}})
if name is not None:
fils.append({"name": name})
if len(fils) == 0:
return {}
else:
return {"$and": fils}
def get_plugin_configs(name=None, name_regex=None):
ps = plugin_config.get_plugin_configs(fil(name, name_regex))
for pc in ps:
pc["_id"] = str(pc["_id"])
return ps
def add_plugin_configs(body):
pc = plugin_config.add_plugin_configs(body)
return len(pc)
def delete_plugin_config(name=None, name_regex=None):
return delete_plugin_configs(name=name, name_regex=name_regex)
def delete_plugin_configs(name=None, name_regex=None):
return plugin_config.delete_plugin_configs(fil(name, name_regex))
def update_plugin_config(name, body):
plugin_config.replace_plugin_config(name, body)
def get_plugin_container(name):
pc = plugin_config.get_plugin_config(name)
container = plugin.get_container(pc)
if container is not None:
return {
"status": container.status
}
else:
return None
def add_plugin_container(name):
pc = plugin_config.get_plugin_config(name)
plugin.run_container(pc)
def delete_plugin_container(name):
pc = plugin_config.get_plugin_config(name)
plugin.stop_container(pc)
plugin.remove_container(pc)
def get_containers():
containers = []
for pc in plugin_config.get_plugin_configs({}):
container = plugin.get_container(pc)
if container is not None:
cs = {
"status": container.status
}
else:
cs = None
containers.append({
"name": pc["name"],
"container": cs
})
return containers
def add_containers():
for pc in plugin_config.get_plugin_configs({}):
plugin.run_container(pc)
def delete_containers():
for pc in plugin_config.get_plugin_configs({}):
plugin.stop_container(pc)
plugin.remove_container(pc) | api/__init__.py | import requests
from tx.router import plugin_config, plugin
from tx.router.logging import l
import logging
import connexion
import sys
from werkzeug.datastructures import Headers
from flask import Response, request
from tempfile import TemporaryFile
logger = logging.getLogger()
logger.setLevel(logging.INFO)
def set_forwarded_path_header(f):
def func(name, path, headers, *args, **kwargs):
forwarded_path0_slash = connexion.request.headers.get("X-Forwarded-Path", "")
forwarded_path0 = forwarded_path0_slash.rstrip("/")
forwarded_path = f"{forwarded_path0}/v1/plugin/{name}"
headers0 = {**headers, "X-Forwarded-Path": forwarded_path}
logger.debug("headers0 = " + str(headers0))
return f(name, path, headers0, *args, **kwargs)
return func
@l("get", "backend")
@set_forwarded_path_header
def get_plugin(name, path, headers, kwargs={}):
pc = plugin_config.get_plugin_config(name)
if pc is None:
return "not found", 404
port = pc.get("port", None)
if port is None:
raise RuntimeError("plugin doesn't have port")
resp = requests.get("http://{host}:{port}/{path}".format(host=pc["name"], port=port, path=path), headers=headers, params=kwargs, stream=True)
return Response(resp.iter_content(chunk_size=1024*1024), status=resp.status_code, headers=Headers(resp.headers.items()))
@l("post", "backend")
@set_forwarded_path_header
def post_plugin(name, path, headers, stream, kwargs={}):
return base_plugin(requests.post, name, path, headers, stream, kwargs)
def base_plugin(method, name, path, headers, stream, kwargs):
pc = plugin_config.get_plugin_config(name)
if pc is None:
return "not found", 404
port = pc.get("port", None)
if port is None:
raise RuntimeError("plugin doesn't have port")
with TemporaryFile() as f:
chunk_size = 4096
while True:
chunk = stream.read(chunk_size)
if len(chunk) == 0:
break
f.write(chunk)
f.seek(0, 0)
resp = method("http://{host}:{port}/{path}".format(host=pc["name"], port=port, path=path), headers=headers, params=kwargs, data=f, stream=True)
return Response(resp.iter_content(chunk_size=1024*1024), status=resp.status_code, headers=Headers(resp.headers.items()))
@l("delete", "backend")
@set_forwarded_path_header
def delete_plugin(name, path, headers, stream, kwargs={}):
return base_plugin(requests.delete, name, path, headers, stream, kwargs)
def get_plugin_config(name):
pc = plugin_config.get_plugin_config(name)
pc["_id"] = str(pc["_id"])
return pc
def fil(name, name_regex):
fils = []
if name_regex is not None:
fils.append({"name": {"$regex": name_regex}})
if name is not None:
fils.append({"name": name})
if len(fils) == 0:
return {}
else:
return {"$and": fils}
def get_plugin_configs(name=None, name_regex=None):
ps = plugin_config.get_plugin_configs(fil(name, name_regex))
for pc in ps:
pc["_id"] = str(pc["_id"])
return ps
def add_plugin_configs(body):
pc = plugin_config.add_plugin_configs(body)
return len(pc)
def delete_plugin_config(name=None, name_regex=None):
return delete_plugin_configs(name=name, name_regex=name_regex)
def delete_plugin_configs(name=None, name_regex=None):
return plugin_config.delete_plugin_configs(fil(name, name_regex))
def update_plugin_config(name, body):
plugin_config.replace_plugin_config(name, body)
def get_plugin_container(name):
pc = plugin_config.get_plugin_config(name)
container = plugin.get_container(pc)
if container is not None:
return {
"status": container.status
}
else:
return None
def add_plugin_container(name):
pc = plugin_config.get_plugin_config(name)
plugin.run_container(pc)
def delete_plugin_container(name):
pc = plugin_config.get_plugin_config(name)
plugin.stop_container(pc)
plugin.remove_container(pc)
def get_containers():
containers = []
for pc in plugin_config.get_plugin_configs({}):
container = plugin.get_container(pc)
if container is not None:
cs = {
"status": container.status
}
else:
cs = None
containers.append({
"name": pc["name"],
"container": cs
})
return containers
def add_containers():
for pc in plugin_config.get_plugin_configs({}):
plugin.run_container(pc)
def delete_containers():
for pc in plugin_config.get_plugin_configs({}):
plugin.stop_container(pc)
plugin.remove_container(pc) | 0.308086 | 0.082033 |
from base.base_model import BaseModel
import tensorflow as tf
class Denoising(BaseModel):
def __init__(self, config):
super(Denoising, self).__init__(config)
self.build_model()
self.init_saver()
def build_model(self):
# Placeholders
self.is_training = tf.placeholder(tf.bool)
self.image_input = tf.placeholder(
tf.float32, shape=[None] + self.config.trainer.image_dims, name="x"
)
self.init_kernel = tf.random_normal_initializer(mean=0.0, stddev=0.02)
# Full Model Scope
with tf.variable_scope("Denoising", reuse=tf.AUTO_REUSE):
# First Convolution + ReLU layer
net = tf.layers.Conv2D(
filters=63,
kernel_size=3,
strides=1,
kernel_initializer=self.init_kernel,
padding="same",
)(self.image_input)
net = tf.nn.relu(features=net)
# 1 Convolution of the image
net_input = tf.layers.Conv2D(
filters=1,
kernel_size=3,
strides=1,
kernel_initializer=self.init_kernel,
padding="same",
)(self.image_input)
net_layer_1 = tf.layers.Conv2D(
filters=1,
kernel_size=3,
strides=1,
kernel_initializer=self.init_kernel,
padding="same",
)(net)
# Add to the image
self.output = net_input + net_layer_1
for i in range(19):
net = tf.layers.Conv2D(
filters=63,
kernel_size=3,
strides=1,
kernel_initializer=self.init_kernel,
padding="same",
)(net)
net = tf.nn.relu(features=net)
net_1 = tf.layers.Conv2D(
filters=1,
kernel_size=3,
strides=1,
kernel_initializer=self.init_kernel,
padding="same",
)(net)
self.output += net_1
self.output += self.image_input
# Loss Function
with tf.name_scope("Loss_Function"):
delta = self.output - self.image_input
delta = tf.layers.Flatten()(delta)
self.loss = tf.reduce_mean(tf.norm(delta, ord=2, axis=1, keepdims=False))
# Optimizer
with tf.name_scope("Optimizer"):
self.optimizer = tf.train.AdamOptimizer(
self.config.trainer.l_rate,
beta1=self.config.trainer.optimizer_adam_beta1,
beta2=self.config.trainer.optimizer_adam_beta2,
)
# Collect All Variables
all_variables = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES)
self.update_ops = tf.get_collection(
tf.GraphKeys.UPDATE_OPS, scope="Denoising"
)
with tf.control_dependencies(self.update_ops):
self.optimizer.minimize(
self.loss,
var_list=all_variables,
global_step=self.global_step_tensor,
)
# Summary
with tf.name_scope("Summary"):
with tf.name_scope("Loss"):
tf.summary.scalar("Loss", self.loss, ["loss"])
with tf.name_scope("Image"):
tf.summary.image("Input_Image", self.image_input, 3, ["image"])
tf.summary.image("Output_Image", self.output, 3, ["image"])
self.summary_op_im = tf.summary.merge_all("image")
self.summary_op_loss = tf.summary.merge_all("loss")
self.summary_all = tf.summary.merge([self.summary_op_im, self.summary_op_loss])
def init_saver(self):
# here you initialize the tensorflow saver that will be used in saving the checkpoints.
self.saver = tf.train.Saver(max_to_keep=self.config.log.max_to_keep) | models/denoising.py | from base.base_model import BaseModel
import tensorflow as tf
class Denoising(BaseModel):
def __init__(self, config):
super(Denoising, self).__init__(config)
self.build_model()
self.init_saver()
def build_model(self):
# Placeholders
self.is_training = tf.placeholder(tf.bool)
self.image_input = tf.placeholder(
tf.float32, shape=[None] + self.config.trainer.image_dims, name="x"
)
self.init_kernel = tf.random_normal_initializer(mean=0.0, stddev=0.02)
# Full Model Scope
with tf.variable_scope("Denoising", reuse=tf.AUTO_REUSE):
# First Convolution + ReLU layer
net = tf.layers.Conv2D(
filters=63,
kernel_size=3,
strides=1,
kernel_initializer=self.init_kernel,
padding="same",
)(self.image_input)
net = tf.nn.relu(features=net)
# 1 Convolution of the image
net_input = tf.layers.Conv2D(
filters=1,
kernel_size=3,
strides=1,
kernel_initializer=self.init_kernel,
padding="same",
)(self.image_input)
net_layer_1 = tf.layers.Conv2D(
filters=1,
kernel_size=3,
strides=1,
kernel_initializer=self.init_kernel,
padding="same",
)(net)
# Add to the image
self.output = net_input + net_layer_1
for i in range(19):
net = tf.layers.Conv2D(
filters=63,
kernel_size=3,
strides=1,
kernel_initializer=self.init_kernel,
padding="same",
)(net)
net = tf.nn.relu(features=net)
net_1 = tf.layers.Conv2D(
filters=1,
kernel_size=3,
strides=1,
kernel_initializer=self.init_kernel,
padding="same",
)(net)
self.output += net_1
self.output += self.image_input
# Loss Function
with tf.name_scope("Loss_Function"):
delta = self.output - self.image_input
delta = tf.layers.Flatten()(delta)
self.loss = tf.reduce_mean(tf.norm(delta, ord=2, axis=1, keepdims=False))
# Optimizer
with tf.name_scope("Optimizer"):
self.optimizer = tf.train.AdamOptimizer(
self.config.trainer.l_rate,
beta1=self.config.trainer.optimizer_adam_beta1,
beta2=self.config.trainer.optimizer_adam_beta2,
)
# Collect All Variables
all_variables = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES)
self.update_ops = tf.get_collection(
tf.GraphKeys.UPDATE_OPS, scope="Denoising"
)
with tf.control_dependencies(self.update_ops):
self.optimizer.minimize(
self.loss,
var_list=all_variables,
global_step=self.global_step_tensor,
)
# Summary
with tf.name_scope("Summary"):
with tf.name_scope("Loss"):
tf.summary.scalar("Loss", self.loss, ["loss"])
with tf.name_scope("Image"):
tf.summary.image("Input_Image", self.image_input, 3, ["image"])
tf.summary.image("Output_Image", self.output, 3, ["image"])
self.summary_op_im = tf.summary.merge_all("image")
self.summary_op_loss = tf.summary.merge_all("loss")
self.summary_all = tf.summary.merge([self.summary_op_im, self.summary_op_loss])
def init_saver(self):
# here you initialize the tensorflow saver that will be used in saving the checkpoints.
self.saver = tf.train.Saver(max_to_keep=self.config.log.max_to_keep) | 0.886899 | 0.191045 |
import requests
import json
import re
import youtube_dl
print("Youtube Pocket - youtube music/playlist downloader\n")
USER_AGENT = "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/50.0.2661.102 Safari/537.36"
VID_PATTERN = r"^(https?:\/\/)?(www\.)?(youtube\.com|youtu\.be)\/(embed\/|v\/|(watch\?([a-zA-Z0-9_=;\-]+&)*v=))?(?P<video_id>[a-zA-Z0-9_\-]{11,})(\?[a-zA-Z0-9_=\-]+)?(?:&[a-zA-Z0-9_=;\-]+)*(?:\#[a-zA-Z0-9_=;\-]+)*$"
LID_PATTERN = r"^(https?:\/\/)?(www\.)?youtube\.com\/(watch\?|playlist\?)([a-zA-Z0-9_=;\-]+&)*list=(?P<playlist_id>[a-zA-Z0-9_\-]{18,})(\?[a-zA-Z0-9_=\-]+)?(?:&[a-zA-Z0-9_=;\-]+)*(?:\#[a-zA-Z0-9_=;\-]+)*$"
YT_DATA_PATTERN = r"var ytInitialData = (?P<JsonData>.*?);<\/script>"
class Video(object):
def __init__(self, vid = None, title = None, length_text = None):
self.id = vid
self.title = title
self.length_text = length_text
def get_data(url):
global USER_AGENT, YT_DATA_PATTERN
response = requests.get(url, headers = {"user-agent" : USER_AGENT})
if not response.ok:
return None
raw_content = response.text
data = json.loads(re.search(YT_DATA_PATTERN, raw_content).group("JsonData"))
return data
def get_playlist_video(lid):
url = "https://www.youtube.com/playlist?list=" + lid
data = get_data(url)
vid = data["contents"]["twoColumnBrowseResultsRenderer"]["tabs"][0]["tabRenderer"]["content"]["sectionListRenderer"]["contents"][0]["itemSectionRenderer"]["contents"][0]["playlistVideoListRenderer"]["contents"][0]["playlistVideoRenderer"]["videoId"]
return vid
CRAWL_URL = input("URL: ")
# CRAWL_URL = "https://www.youtube.com/watch?v=wvrQU9VCts0&list=PL2mVqrrF_bnn5qt_fqHZNRzWjKp4jqfyF"
# CRAWL_URL = "https://www.youtube.com/playlist?list=PL2mVqrrF_bnn5qt_fqHZNRzWjKp4jqfyF"
# CRAWL_URL = "https://www.youtube.com/watch?v=wvrQU9VCts0"
prog_vid = re.compile(VID_PATTERN)
prog_lid = re.compile(LID_PATTERN)
video_id = None
playlist_id = None
while not prog_vid.match(CRAWL_URL) and not prog_lid.match(CRAWL_URL):
print("Invalid URL")
CRAWL_URL = input("URL: ")
video_id = re.match(VID_PATTERN, CRAWL_URL)
if video_id:
video_id = video_id.group("video_id")
playlist_id = re.match(LID_PATTERN, CRAWL_URL)
if playlist_id:
playlist_id = playlist_id.group("playlist_id")
if playlist_id:
if not video_id:
video_id = get_playlist_video(playlist_id)
CRAWL_URL = "https://www.youtube.com/watch?v=" + video_id + "&list=" + playlist_id
elif video_id:
CRAWL_URL = "https://www.youtube.com/watch?v=" + video_id
else:
exit()
print("Requsteing: {}".format(CRAWL_URL))
DATA = get_data(CRAWL_URL)
try:
cur_video = DATA["contents"]["twoColumnWatchNextResults"]["results"]["results"]["contents"]
cur_video_info = cur_video[0]["videoPrimaryInfoRenderer"]
owner_info = cur_video[1]["videoSecondaryInfoRenderer"]
recommend_video = DATA["contents"]["twoColumnWatchNextResults"]["secondaryResults"]["secondaryResults"]["results"]
playlist = DATA["contents"]["twoColumnWatchNextResults"]["playlist"]["playlist"]
except Exception as e:
print(e)
videos = []
for vi in playlist["contents"]:
video_info = vi["playlistPanelVideoRenderer"]
videos.append(Video(vid = video_info["videoId"], title = video_info["title"]["simpleText"], length_text = video_info["lengthText"]["simpleText"]))
print("Downloading playlist: {0} with {1} videos\n".format(playlist["title"], playlist["totalVideos"]))
i = 1
for vi in videos:
print("# {0} [Processing] {1}".format(i, vi.title))
ydl_opts = {"format": "mp4", "outtmpl": "{0}-{1}.%(ext)s".format(vi.title, vi.length_text)}
with youtube_dl.YoutubeDL(ydl_opts) as ydl:
url = "https://www.youtube.com/watch?v=" + vi.id
ydl.download([url])
i += 1
print("")
print("Download complete!") | test_data/get_data_test.py | import requests
import json
import re
import youtube_dl
print("Youtube Pocket - youtube music/playlist downloader\n")
USER_AGENT = "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/50.0.2661.102 Safari/537.36"
VID_PATTERN = r"^(https?:\/\/)?(www\.)?(youtube\.com|youtu\.be)\/(embed\/|v\/|(watch\?([a-zA-Z0-9_=;\-]+&)*v=))?(?P<video_id>[a-zA-Z0-9_\-]{11,})(\?[a-zA-Z0-9_=\-]+)?(?:&[a-zA-Z0-9_=;\-]+)*(?:\#[a-zA-Z0-9_=;\-]+)*$"
LID_PATTERN = r"^(https?:\/\/)?(www\.)?youtube\.com\/(watch\?|playlist\?)([a-zA-Z0-9_=;\-]+&)*list=(?P<playlist_id>[a-zA-Z0-9_\-]{18,})(\?[a-zA-Z0-9_=\-]+)?(?:&[a-zA-Z0-9_=;\-]+)*(?:\#[a-zA-Z0-9_=;\-]+)*$"
YT_DATA_PATTERN = r"var ytInitialData = (?P<JsonData>.*?);<\/script>"
class Video(object):
def __init__(self, vid = None, title = None, length_text = None):
self.id = vid
self.title = title
self.length_text = length_text
def get_data(url):
global USER_AGENT, YT_DATA_PATTERN
response = requests.get(url, headers = {"user-agent" : USER_AGENT})
if not response.ok:
return None
raw_content = response.text
data = json.loads(re.search(YT_DATA_PATTERN, raw_content).group("JsonData"))
return data
def get_playlist_video(lid):
url = "https://www.youtube.com/playlist?list=" + lid
data = get_data(url)
vid = data["contents"]["twoColumnBrowseResultsRenderer"]["tabs"][0]["tabRenderer"]["content"]["sectionListRenderer"]["contents"][0]["itemSectionRenderer"]["contents"][0]["playlistVideoListRenderer"]["contents"][0]["playlistVideoRenderer"]["videoId"]
return vid
CRAWL_URL = input("URL: ")
# CRAWL_URL = "https://www.youtube.com/watch?v=wvrQU9VCts0&list=PL2mVqrrF_bnn5qt_fqHZNRzWjKp4jqfyF"
# CRAWL_URL = "https://www.youtube.com/playlist?list=PL2mVqrrF_bnn5qt_fqHZNRzWjKp4jqfyF"
# CRAWL_URL = "https://www.youtube.com/watch?v=wvrQU9VCts0"
prog_vid = re.compile(VID_PATTERN)
prog_lid = re.compile(LID_PATTERN)
video_id = None
playlist_id = None
while not prog_vid.match(CRAWL_URL) and not prog_lid.match(CRAWL_URL):
print("Invalid URL")
CRAWL_URL = input("URL: ")
video_id = re.match(VID_PATTERN, CRAWL_URL)
if video_id:
video_id = video_id.group("video_id")
playlist_id = re.match(LID_PATTERN, CRAWL_URL)
if playlist_id:
playlist_id = playlist_id.group("playlist_id")
if playlist_id:
if not video_id:
video_id = get_playlist_video(playlist_id)
CRAWL_URL = "https://www.youtube.com/watch?v=" + video_id + "&list=" + playlist_id
elif video_id:
CRAWL_URL = "https://www.youtube.com/watch?v=" + video_id
else:
exit()
print("Requsteing: {}".format(CRAWL_URL))
DATA = get_data(CRAWL_URL)
try:
cur_video = DATA["contents"]["twoColumnWatchNextResults"]["results"]["results"]["contents"]
cur_video_info = cur_video[0]["videoPrimaryInfoRenderer"]
owner_info = cur_video[1]["videoSecondaryInfoRenderer"]
recommend_video = DATA["contents"]["twoColumnWatchNextResults"]["secondaryResults"]["secondaryResults"]["results"]
playlist = DATA["contents"]["twoColumnWatchNextResults"]["playlist"]["playlist"]
except Exception as e:
print(e)
videos = []
for vi in playlist["contents"]:
video_info = vi["playlistPanelVideoRenderer"]
videos.append(Video(vid = video_info["videoId"], title = video_info["title"]["simpleText"], length_text = video_info["lengthText"]["simpleText"]))
print("Downloading playlist: {0} with {1} videos\n".format(playlist["title"], playlist["totalVideos"]))
i = 1
for vi in videos:
print("# {0} [Processing] {1}".format(i, vi.title))
ydl_opts = {"format": "mp4", "outtmpl": "{0}-{1}.%(ext)s".format(vi.title, vi.length_text)}
with youtube_dl.YoutubeDL(ydl_opts) as ydl:
url = "https://www.youtube.com/watch?v=" + vi.id
ydl.download([url])
i += 1
print("")
print("Download complete!") | 0.138258 | 0.096323 |
import os
import sys
import platform
import re
import argparse
import threading
import queue
import webbrowser
import logging
import ipaddress
from PIL import Image, ImageTk
import tkinterdnd2 as tkdnd
import tkinter as tk
import tkinter.ttk as ttk
from tkinter.simpledialog import Dialog as BaseDialog
from tkinter.messagebox import showinfo
from tkinter.filedialog import askdirectory, askopenfilenames
from tkinter.scrolledtext import ScrolledText
import appdirs
from . import init_config, save_config, gConfig
from . import hdpitk
from . import about
from . import hfs
from .netdrop import NetDropServer, NetDropClient
from .transport import get_broadcast_address, human_size
logger = logging.getLogger(__name__)
class GUIProgressBar(ttk.Progressbar):
def __init__(self, parent, **kwargs):
self.parent = parent
self.style = ttk.Style()
# add label in the layout
self.style.layout(
'text.Horizontal.TProgressbar',
[
(
'Horizontal.Progressbar.trough',
{
'children': [
('Horizontal.Progressbar.pbar', {'side': 'left', 'sticky': 'ns'})
],
'sticky': 'nswe'
}
),
(
'Horizontal.Progressbar.label',
{'sticky': ''}
),
]
)
super().__init__(parent, style='text.Horizontal.TProgressbar', **kwargs)
self.interval = 100
self.step_count = 0
self.time_index = 0
self.speed = ''
self.count = [0] * (1000 // self.interval)
self.parent.after(self.interval, self.on_timer_update)
def on_timer_update(self):
if self.step_count >= 0:
self.parent.after(self.interval, self.on_timer_update)
self.speed = f'{human_size(sum(self.count)):>9}/s'
self.count[self.time_index] = self.step_count
self.step_count = 0
# 0 ~ 9
self.time_index = (self.time_index + 1) % (1000 // self.interval)
self.parent.on_progressbar_update_speed(self.speed)
def update(self, step):
self.step_count += step
self.parent.on_progressbar_update(step)
def write(self, message, file=None):
logger.info(message)
def close(self):
if not self.speed:
# transfer complete less than a second
self.count[self.time_index] = self.step_count
speed = sum(self.count) / (len([x for x in self.count if x != 0]) * self.interval / 1000)
self.speed = f'{human_size(speed):>9}/s'
self.step_count = -1
self.parent.on_progressbar_close(self.speed.strip())
class GUINetDropServer(NetDropServer):
def __init__(self, parent, *args):
self.parent = parent
super().__init__(*args)
def init_bar(self, max_value):
progress = GUIProgressBar(
self.parent.host_client, orient=tk.HORIZONTAL,
maximum=max_value,
mode='determinate')
progress.grid(row=1, column=1, sticky='nsew')
progress.lift()
self.parent.host_client.progress = progress
return progress
def add_node(self, node):
super().add_node(node)
self.parent.on_add_node(node)
def remove_node(self, node):
super().remove_node(node)
self.parent.on_remove_node(node)
def recv_finish_text(self, from_addr):
text = super().recv_finish_text(from_addr)
self.parent.on_recv_text(text, from_addr)
return text
def recv_finish(self, from_addr, err):
self.parent.host_client.result = (from_addr, err)
super().recv_finish(from_addr, err)
class GUINetDropClient(NetDropClient):
def __init__(self, parent, ip, mode, cert=None, key=None):
self.parent = parent
super().__init__(ip, mode.lower(), ssl_ck=(cert, key))
def init_bar(self, max_value):
progress = GUIProgressBar(
self.parent, orient=tk.HORIZONTAL,
maximum=max_value,
mode='determinate')
progress.grid(row=1, column=1, sticky='nsew')
progress.lift()
self.parent.progress = progress
return progress
def send_finish(self, err):
self.parent.result = (None, err)
super().send_finish(err)
IMAGES = {
'back': 'BackTile.png',
'pc': 'PcLogo.png',
'android': 'AndroidLogo.png',
'apple': 'AppleLogo.png',
'darwin': 'AppleLogo.png',
'blackberry': 'BlackberryLogo.png',
'ip': 'IpLogo.png',
'linux': 'LinuxLogo.png',
'smartphone': 'SmartphoneLogo.png',
'unknown': 'UnknownLogo.png',
'windows': 'WindowsLogo.png',
'windowsphone': 'WindowsPhoneLogo.png',
'config': 'ConfigIcon.png',
'openfolder': 'OpenFolderIcon.png',
'hfs': 'hfs.png',
}
class NdropImage():
@classmethod
def get_os_image(cls, name):
image_dir = os.path.join(os.path.dirname(__file__), 'image')
back_path = os.path.join(image_dir, IMAGES['back'])
back_im = Image.open(back_path)
fore_path = os.path.join(
image_dir,
IMAGES.get(name.lower()) or IMAGES['unknown']
)
fore_im = Image.open(fore_path)
image = Image.new("RGBA", fore_im.size)
image.alpha_composite(back_im.resize(fore_im.size))
image.alpha_composite(fore_im)
return ImageTk.PhotoImage(image)
@classmethod
def get_image(cls, name, background=None):
image_dir = os.path.join(os.path.dirname(__file__), 'image')
fore_path = os.path.join(image_dir, IMAGES[name.lower()])
fore_im = Image.open(fore_path)
background = background or 'white'
image = Image.new("RGBA", fore_im.size, color=background)
image.alpha_composite(fore_im)
return ImageTk.PhotoImage(image)
class AutoScrollbar(ttk.Scrollbar):
# a scrollbar that hides itself if it's not needed. only
# works if you use the grid geometry manager.
def set(self, lo, hi):
if float(lo) <= 0.0 and float(hi) >= 1.0:
# grid_remove is currently missing from Tkinter!
self.tk.call("grid", "remove", self)
else:
self.grid()
super().set(lo, hi)
def pack(self, **kw):
raise tk.TclError("cannot use pack with this widget")
def place(self, **kw):
raise tk.TclError("cannot use place with this widget")
class ScrolledWindow(ttk.Frame):
"""
https://stackoverflow.com/questions/16188420/tkinter-scrollbar-for-frame
1. Master widget gets scrollbars and a canvas. Scrollbars are connected
to canvas scrollregion.
2. self.scrollwindow is created and inserted into canvas
Usage Guideline:
Assign any widgets as children of <ScrolledWindow instance>.scrollwindow
to get them inserted into canvas
__init__(self, parent, canv_w = 400, canv_h = 400, *args, **kwargs)
docstring:
Parent = master of scrolled window
canv_w - width of canvas
canv_h - height of canvas
"""
def __init__(self, parent, canv_w=400, canv_h=400, xbar=False, ybar=True, *args, **kwargs):
"""Parent=master of scrolled window
canv_w - width of canvas
canv_h - height of canvas
"""
super().__init__(parent, *args, **kwargs)
# creating a canvas
self.canv = tk.Canvas(self)
self.canv.config(
relief='flat',
takefocus=0,
borderwidth=0,
highlightthickness=0,
width=10,
heigh=10)
# placing a canvas into frame
self.canv.columnconfigure(0, weight=1)
self.canv.grid(column=0, row=0, sticky='nsew')
self.canv.bind('<Configure>', self._configure_canvas)
# creating a scrollbars
if xbar:
self.xscrlbr = AutoScrollbar(self,
orient='horizontal',
command=self.canv.xview)
self.xscrlbr.grid(column=0, row=1, sticky='ew')
self.canv.config(xscrollcommand=self.xscrlbr.set)
if ybar:
self.yscrlbr = AutoScrollbar(self,
orient='vertical',
command=self.canv.yview)
self.yscrlbr.grid(column=1, row=0, sticky='ns')
self.canv.config(yscrollcommand=self.yscrlbr.set)
# creating a frame to inserto to canvas
self.scrollwindow = ttk.Frame(self.canv)
self.scrollwindow.bind('<Configure>', self._configure_window)
self.scrollwindow.bind('<Enter>', self._bound_to_mousewheel)
self.scrollwindow.bind('<Leave>', self._unbound_to_mousewheel)
self.scrollwindow.columnconfigure(0, weight=1)
self.item_window = self.canv.create_window(0, 0, window=self.scrollwindow, anchor='nw')
if ybar:
self.yscrlbr.lift(self.scrollwindow)
if xbar:
self.xscrlbr.lift(self.scrollwindow)
self.rowconfigure(0, weight=1)
self.columnconfigure(0, weight=1)
def _bound_to_mousewheel(self, event):
# windows, macos
self.canv.bind_all("<MouseWheel>", self._on_mousewheel)
# linux
self.canv.bind_all("<Button-4>", self._on_mousewheel)
self.canv.bind_all("<Button-5>", self._on_mousewheel)
def _unbound_to_mousewheel(self, event):
self.canv.unbind_all("<MouseWheel>")
self.canv.unbind_all("<Button-4>")
self.canv.unbind_all("<Button-5>")
def _on_mousewheel(self, event):
if sys.platform == 'darwin':
# macos
delta = -1 * event.delta
elif event.num == 5:
# linux up
delta = 1
elif event.num == 4:
# linux down
delta = -1
else:
# windows
delta = -1 * (event.delta // 120)
self.canv.yview_scroll(delta, "units")
def _configure_window(self, event):
# canvas will expand on both direction
self.canv.configure(scrollregion=self.canv.bbox("all"))
def _configure_canvas(self, event):
self.canv.itemconfig(self.item_window, width=event.width)
class Client(ttk.Frame):
node = None
progress = None
agent = None
def __init__(self, parent, node, *args, **kwargs):
super().__init__(parent, *args, **kwargs)
self.parent = parent
self.node = node
self.queue = queue.SimpleQueue()
self.virtual_event = '<<client_queue_event>>'
self.bind(self.virtual_event, self.queue_handler)
self.image = NdropImage.get_os_image(node['operating_system'])
self.style = ttk.Style()
self.style.configure('client.TLabel', background='white')
self.label_image = ttk.Label(self, image=self.image, style='client.TLabel')
self.label_image.grid(row=0, column=0, rowspan=2, sticky='w')
if node['mode'] == '?':
text = f'{node.get("user")}\n@{node["name"]}'
else:
text = f'{node.get("mode")}\n@{node["name"]}'
label_text = ttk.Label(
self, text=text,
anchor='w', style='client.TLabel', justify=tk.LEFT)
label_text.grid(row=0, column=1, sticky='ew')
self.status = tk.StringVar()
if self.node['ip'] == '?':
self.status.set('ready')
else:
self.status.set(f'{self.node["ip"]} - ready')
label_status = ttk.Label(
self, textvariable=self.status,
anchor='w', style='client.TLabel', justify=tk.LEFT)
label_status.grid(row=1, column=1, sticky='nsew')
self.rowconfigure(1, weight=1)
self.columnconfigure(1, weight=1)
if self.node['mode'] == 'NitroShare':
self.dnd_types = [tkdnd.DND_FILES]
else:
# permit DND defaultly
self.dnd_types = [tkdnd.DND_FILES, tkdnd.DND_TEXT]
for widget in [self] + list(self.children.values()):
widget.bind('<Button-1>', self.click)
widget.drop_target_register(*self.dnd_types)
widget.dnd_bind('<<DropEnter>>', self.drop_enter)
widget.dnd_bind('<<DropPosition>>', self.drop_position)
widget.dnd_bind('<<Drop:DND_Files>>', self.drop_files)
widget.dnd_bind('<<Drop:DND_Text>>', self.drop_text)
def bind_tree(self, widget, event, callback):
widget.bind(event, callback)
for child in widget.children.values():
bind_tree(child, event, callback)
def queue_handler(self, event):
item = self.queue.get_nowait()
if self.progress:
if item[0] == 'step':
self.progress.step(item[1])
elif item[0] == 'speed':
self.progress.style.configure('text.Horizontal.TProgressbar', text=item[1])
elif item[0] == 'close':
self.progress.destroy()
self.progress = None
self.agent = None
from_addr, err = self.result
self.status.set(f'{self.node["ip"]} - {err} - {item[1]}')
def on_progressbar_update_speed(self, speed):
self.queue.put_nowait(('speed', speed))
self.event_generate(self.virtual_event)
def on_progressbar_update(self, step):
self.queue.put_nowait(('step', step))
self.event_generate(self.virtual_event)
def on_progressbar_close(self, speed):
self.queue.put_nowait(('close', speed))
self.event_generate(self.virtual_event)
def click(self, event):
if self.agent:
logger.info('| => %(mode)s@%(name)s(%(ip)s)' % self.node)
return
if self.node['type'] == 'host':
logger.info('%(mode)s@%(name)s(%(ip)s)' % self.node)
return
if self.node['type'] == 'ip':
title = 'Send'
else:
title = 'Send to %(ip)s (%(mode)s)' % self.node
dlg = SendDialog(self, title)
dlg.show()
if self.node['type'] == 'ip':
if self.node['ip'] == '?':
self.status.set('ready')
if self.node['operating_system'] != 'Unknwon':
self.node['operating_system'] = 'Unknwon'
self.image = NdropImage.get_os_image(self.node['operating_system'])
self.label_image.configure(image=self.image)
else:
self.status.set('%(ip)s - ready' % self.node)
if self.node['operating_system'] != 'ip':
self.node['operating_system'] = 'ip'
self.image = NdropImage.get_os_image(self.node['operating_system'])
self.label_image.configure(image=self.image)
else:
self.status.set(f'{self.node["ip"]} - ready')
def in_dnd_types(self, dnd_type, dnd_types):
for types in dnd_types:
if dnd_type in types:
return True
def drop_position(self, event):
if self.agent:
# be trasfering
return tkdnd.REFUSE_DROP
if self.node['type'] == 'host':
return tkdnd.REFUSE_DROP
if self.node['ip'] == '?':
return tkdnd.REFUSE_DROP
# deny dnd_text for mode nitroshare
if self.node['mode'] == 'NitroShare':
if self.in_dnd_types('CF_UNICODETEXT', event.types) or \
self.in_dnd_types('CF_TEXT', event.types):
return tkdnd.REFUSE_DROP
return event.action
def drop_enter(self, event):
event.widget.focus_force()
return event.action
def drop_text(self, event):
if event.data:
self.send_text(event.data)
return tkdnd.COPY
def drop_files(self, event):
if event.data:
drop_files = self.tk.splitlist(event.data)
self.send_files(drop_files)
return tkdnd.COPY
def send_text(self, text):
if self.agent:
return
agent = GUINetDropClient(self, self.node['ip'], self.node['mode'])
threading.Thread(
name='Ndrop client',
target=agent.send_text,
args=(text, ),
).start()
def send_files(self, files):
self.agent = GUINetDropClient(self, self.node['ip'], self.node['mode'])
threading.Thread(
name='Ndrop client',
target=self.agent.send_files,
args=(files, ),
).start()
class Dialog(BaseDialog):
def __init__(self, parent, title=None):
tk.Toplevel.__init__(self, parent)
# remain invisible for now
self.withdraw()
# If the master is not viewable, don't
# make the child transient, or else it
# would be opened withdrawn
if parent.winfo_viewable():
self.transient(parent)
if title:
self.title(title)
self.parent = parent
self.result = None
body = ttk.Frame(self)
self.initial_focus = self.body(body)
body.pack(padx=5, pady=5)
self.buttonbox()
if not self.initial_focus:
self.initial_focus = self
self.protocol("WM_DELETE_WINDOW", self.cancel)
if self.parent is not None:
self.geometry("+%d+%d" % (parent.winfo_rootx() + 50,
parent.winfo_rooty() + 50))
def show(self, modal=True):
if self.is_visible():
return
# become visible now
self.deiconify()
self.initial_focus.focus_set()
# wait for window to appear on screen before calling grab_set
self.wait_visibility()
self.grab_set()
if modal:
self.wait_window(self)
def hide(self):
if not self.is_visible():
return
self.withdraw()
self.grab_release()
if self.parent is not None:
self.parent.focus_set()
def is_visible(self):
return self.state() == 'normal'
class SettingDialog(Dialog):
def __init__(self, master, title=None, **kwargs):
target_dir = kwargs.get('target_dir', '')
self.target_dir = tk.StringVar()
self.target_dir.set(target_dir)
hdpi = 1 if kwargs.get('enable_hdpi') else 0
self.hdpi = tk.IntVar()
self.hdpi.set(hdpi)
node_by_text = 1 if kwargs.get('create_node_by_text') else 0
self.node_by_text = tk.IntVar()
self.node_by_text.set(node_by_text)
super().__init__(master, title)
def body(self, master):
label = ttk.Label(master, text='Saved folder:')
label.grid(row=0, sticky='w')
entry = ttk.Entry(master, textvariable=self.target_dir, width=40)
entry.grid(row=1, column=0, sticky='ew')
button = ttk.Button(master, text='Change folder')
button.grid(row=2, column=0, sticky='e')
button.bind('<Button-1>', self.change_folder)
checkbox = ttk.Checkbutton(master, text='Enable HDPI', variable=self.hdpi)
checkbox.grid(row=3, column=0, sticky='ew')
checkbox = ttk.Checkbutton(master, text='Create node by recving TEXT', variable=self.node_by_text)
checkbox.grid(row=4, column=0, sticky='ew')
master.rowconfigure(1, weight=1)
master.columnconfigure(0, weight=1)
master.pack(fill=tk.BOTH)
def buttonbox(self):
"""replace origin wdiget with ttk"""
box = ttk.Frame(self)
w = ttk.Button(box, text="OK", width=10, command=self.ok, default=tk.ACTIVE)
w.pack(side=tk.LEFT, padx=5, pady=5)
w = ttk.Button(box, text="Cancel", width=10, command=self.cancel)
w.pack(side=tk.LEFT, padx=5, pady=5)
self.bind("<Return>", self.ok)
self.bind("<Escape>", self.cancel)
box.pack()
def apply(self):
target_dir = self.target_dir.get()
hdpi = self.hdpi.get()
node_by_text = self.node_by_text.get()
self.result = (
os.path.normpath(target_dir),
hdpi == 1,
node_by_text == 1,
)
def change_folder(self, event):
folder = askdirectory(initialdir=self.target_dir.get())
if folder:
self.target_dir.set(os.path.normpath(folder))
class SendDialog(Dialog):
def __init__(self, parent, title=None, **kwargs):
self.dest_ip = tk.StringVar()
if parent.node['ip'] != '?':
self.dest_ip.set(parent.node['ip'])
self.mode = tk.StringVar()
if parent.node['mode'] != '?':
self.mode.set(parent.node['mode'])
self.parent = parent
super().__init__(parent, title)
def body(self, master):
label = ttk.Label(master, text='IP:')
label.grid(row=0, column=0, sticky='w', padx=5, pady=5)
entry = ttk.Entry(master, textvariable=self.dest_ip, width=20)
entry.grid(row=0, column=1, sticky='ew', padx=5, pady=5)
label = ttk.Label(master, text='Mode:')
label.grid(row=0, column=2, sticky='w', padx=5, pady=5)
choices = ['Dukto', 'NitroShare']
if not self.mode.get():
self.mode.set(choices[0])
combo = ttk.Combobox(master, values=choices, textvariable=self.mode, width=10, state="readonly")
combo.grid(row=0, column=3, sticky='ew', padx=5, pady=5)
combo.bind("<<ComboboxSelected>>", self.mode_selected)
self.textbox = ScrolledText(master, width=60, height=10)
self.textbox.grid(row=1, column=0, columnspan=4, sticky='nsew', padx=5, pady=5)
self.btn_text = ttk.Button(master, text="Send TEXT", command=self.send_text)
self.btn_text.grid(row=2, column=0, columnspan=4, sticky='ew', padx=5, pady=5)
btn_files = ttk.Button(master, text="Send Files", command=self.send_files)
btn_files.grid(row=3, column=0, columnspan=4, sticky='ew', padx=5, pady=5)
btn_folder = ttk.Button(master, text="Send Folder", command=self.send_folder)
btn_folder.grid(row=4, column=0, columnspan=4, sticky='ew', padx=5, pady=5)
master.rowconfigure(1, weight=1)
master.columnconfigure(1, weight=1)
master.pack(fill=tk.BOTH, expand=1)
if self.parent.node['type'] == 'guest':
entry.configure(state='disabled')
combo.configure(state='disabled')
if self.mode.get() == 'NitroShare':
self.textbox.configure(state='disabled')
self.btn_text.configure(state='disabled')
return entry
def buttonbox(self):
self.bind('<Escape>', self.cancel)
def mode_selected(self, event):
if self.mode.get() == 'NitroShare':
self.textbox.configure(state='disabled')
self.btn_text.configure(state='disabled')
else:
self.textbox.configure(state='normal')
self.btn_text.configure(state='normal')
def update_ip(self):
if self.parent.node['type'] == 'ip':
dest_ip = self.dest_ip.get()
if dest_ip:
try:
ipaddr = ipaddress.ip_address(dest_ip)
except ValueError:
return
self.parent.node['ip'] = str(ipaddr)
else:
self.parent.node['ip'] = '?'
return
mode = self.mode.get()
self.parent.node['mode'] = mode
return True
def send_text(self):
if self.update_ip():
text = self.textbox.get('1.0', 'end-1c')
self.cancel()
self.parent.send_text(text)
def send_files(self):
if self.update_ip():
files = askopenfilenames()
if files:
self.cancel()
self.parent.send_files(files)
def send_folder(self):
if self.update_ip():
folder = askdirectory()
if folder:
self.cancel()
self.parent.send_files([folder])
class MessageDialog(Dialog):
def __init__(self, master, title=None, message=None, **kwargs):
super().__init__(master, title)
self.master = master
self.message_queue = queue.Queue()
self.queue_handler = QueueHandler(self.message_queue)
if message:
self.message_queue.put_nowait(message)
self.master.after(100, self.poll_queue)
def display(self, message):
self.textbox.configure(state='normal')
self.textbox.insert(tk.END, message + '\n')
self.textbox.configure(state='disabled')
# Autoscroll to the bottom
self.textbox.yview(tk.END)
def poll_queue(self):
# Check every 100ms if there is a new message in the queue to display
while True:
try:
message = self.message_queue.get(block=False)
except queue.Empty:
break
else:
self.display(message)
self.master.after(100, self.poll_queue)
def body(self, master):
self.textbox = ScrolledText(master, width=60, height=10, state='disabled')
self.textbox.grid(row=0, sticky='nsew')
master.rowconfigure(0, weight=1)
master.columnconfigure(0, weight=1)
master.pack(fill=tk.BOTH, expand=1)
def buttonbox(self):
"""replace origin wdiget with ttk"""
box = ttk.Frame(self)
w = ttk.Button(box, text="OK", width=10, command=self.hide, default=tk.ACTIVE)
w.pack(side=tk.LEFT, padx=5, pady=5)
self.bind("<Return>", self.hide)
self.bind("<Escape>", self.hide)
box.pack()
class HFSDialog(Dialog):
def __init__(self, master, title=None, **kwargs):
# Create a logging handler using a queue
self.log_queue = queue.Queue()
self.queue_handler = QueueHandler(self.log_queue)
formatter = logging.Formatter('%(message)s')
self.queue_handler.setFormatter(formatter)
hfs_logger = logging.getLogger('%s.hfs' % __name__.rpartition('.')[0])
hfs_logger.addHandler(self.queue_handler)
logger.info('-- HFS server start --')
listen = '0.0.0.0'
cert = None
key = None
self.hfs_server = hfs.start(listen,
root_path=gConfig.app['target_dir'],
cert=cert, key=key,
daemon=True)
self.master = master
self.master.after(100, self.poll_log_queue)
super().__init__(master, title)
def display(self, record):
msg = self.queue_handler.format(record)
self.scrolled_text.configure(state='normal')
self.scrolled_text.insert(tk.END, msg + '\n', record.levelname)
self.scrolled_text.configure(state='disabled')
# Autoscroll to the bottom
self.scrolled_text.yview(tk.END)
def poll_log_queue(self):
# Check every 100ms if there is a new message in the queue to display
while True:
try:
record = self.log_queue.get(block=False)
except queue.Empty:
break
else:
self.display(record)
if self.hfs_server:
self.master.after(100, self.poll_log_queue)
def body(self, master):
self.scrolled_text = ScrolledText(master, width=60, height=10, state='disabled')
self.scrolled_text.grid(row=0, sticky='nsew')
master.rowconfigure(0, weight=1)
master.columnconfigure(0, weight=1)
master.pack(fill=tk.BOTH, expand=1)
def buttonbox(self):
box = ttk.Frame(self)
w = ttk.Button(box, text="OK", width=10, command=self.ok, default=tk.ACTIVE)
w.pack(side=tk.LEFT, padx=5, pady=5)
self.bind("<Return>", self.ok)
box.pack()
def apply(self):
self.result = None
self.hfs_server.shutdown()
self.hfs_server = None
logger.info('-- HFS server close --')
class QueueHandler(logging.Handler):
def __init__(self, log_queue):
super().__init__()
self.log_queue = log_queue
def emit(self, record):
self.log_queue.put(record)
def bind_tree(widget, event, callback):
widget.bind(event, callback)
for child in widget.children.values():
bind_tree(child, event, callback)
class GuiApp(tkdnd.Tk):
host_client = None
ip_client = None
message_box = None
def __init__(self, *args):
super().__init__(*args)
self.title('%s v%s' % (about.name.capitalize(), about.version))
image_dir = os.path.join(os.path.dirname(__file__), 'image')
icon_path = os.path.join(image_dir, 'ndrop.ico')
self.iconphoto(True, ImageTk.PhotoImage(Image.open(icon_path)))
self.geometry('320x360')
self.queue = queue.SimpleQueue()
uname = platform.uname()
ipaddrs, _ = get_broadcast_address()
host_node = {}
host_node['user'] = 'You'
host_node['name'] = uname.node
host_node['operating_system'] = uname.system
host_node['mode'] = '?'
host_node['ip'] = ', '.join(ipaddrs)
host_node['type'] = 'host'
self.host_client = Client(self, host_node)
self.host_client.grid(row=0, column=0, sticky='ew', padx=10, pady=10)
sep = ttk.Separator(self)
sep.grid(row=1, column=0, sticky='ew', padx=40, pady=0)
frame = ScrolledWindow(self, xbar=False, ybar=True)
frame.grid(sticky='ewns')
self.frame = frame.scrollwindow
ip_node = {}
ip_node['user'] = 'IP connection'
ip_node['name'] = 'Send data to a remote device.'
ip_node['operating_system'] = 'Unknown'
ip_node['mode'] = '?'
ip_node['ip'] = '?'
ip_node['type'] = 'ip'
self.ip_client = Client(self.frame, ip_node)
self.ip_client.grid(sticky='ew', padx=10, pady=5)
s = ttk.Style()
s.configure('footer.TFrame', background='green')
s.configure('footer.TLabel', background='green')
footer = ttk.Frame(self, style='footer.TFrame')
footer.grid(sticky='ew')
self.image_openfolder = NdropImage.get_image('openfolder', background='green')
label = ttk.Label(footer, image=self.image_openfolder, style='footer.TLabel')
label.grid(row=0, column=1, padx=10, pady=5)
label.bind('<Button-1>', self.open_folder)
self.image_config = NdropImage.get_image('config', background='green')
label = ttk.Label(footer, image=self.image_config, style='footer.TLabel')
label.grid(row=0, column=2, padx=10, pady=5)
label.bind('<Button-1>', self.show_config)
self.image_hfs = NdropImage.get_image('hfs', background='green')
label = ttk.Label(footer, image=self.image_hfs, style='footer.TLabel')
label.grid(row=0, column=3, padx=10, pady=5)
label.bind('<Button-1>', self.show_hfs)
footer.columnconfigure(0, weight=1)
footer.columnconfigure(4, weight=1)
self.rowconfigure(2, weight=1)
self.columnconfigure(0, weight=1)
self.bind('<<server_queue_event>>', self.queue_handler)
def on_add_node(self, node):
self.queue.put_nowait(('add_node', node))
self.event_generate('<<server_queue_event>>')
def on_remove_node(self, node):
self.queue.put_nowait(('remove_node', node))
self.event_generate('<<server_queue_event>>')
def on_recv_text(self, text, from_addr):
self.queue.put_nowait(('recv_text', text, from_addr))
self.event_generate('<<server_queue_event>>')
def open_folder(self, event):
webbrowser.open(gConfig.app['target_dir'])
def show_config(self, event):
dlg = SettingDialog(
self, 'Settings',
target_dir=gConfig.app['target_dir'],
enable_hdpi=gConfig.app['enable_hdpi'],
create_node_by_text=gConfig.app['create_node_by_text'],
)
dlg.show()
if dlg.result:
target_dir, hdpi, node_by_text = dlg.result
if gConfig.app['enable_hdpi'] != hdpi:
showinfo('Information', 'Close and open app again for HDPI')
gConfig.app['target_dir'] = target_dir
gConfig.app['enable_hdpi'] = hdpi
gConfig.app['create_node_by_text'] = node_by_text
save_config()
self.server.saved_to(gConfig.app['target_dir'])
def show_hfs(self, event):
dlg = HFSDialog(self, 'HFS')
dlg.show()
def queue_handler(self, event):
item = self.queue.get_nowait()
if item[0] == 'add_node':
node = item[1]
for client in self.frame.winfo_children():
if client.node['ip'] == node['ip'] and \
client.node['mode'] == node['mode']:
if client.node['type'] == 'text' and node['type'] == 'guest':
# destroy text client and create guest client
client.destroy()
else:
return
client = Client(self.frame, node)
pad = (10, 5)
client.grid(sticky='ew', padx=pad[0], pady=pad[1])
elif item[0] == 'remove_node':
node = item[1]
for client in self.frame.winfo_children():
if not client.progress and \
client.node['type'] == 'guest' and \
client.node['ip'] == node['ip'] and \
client.node['mode'] == node['mode']:
client.destroy()
elif item[0] == 'recv_text':
text = item[1]
from_addr = '%s:%s' % item[2]
if gConfig.app['create_node_by_text']:
# add node
recv_node = {}
recv_node['user'] = 'Unknown'
recv_node['name'] = 'Unknown'
recv_node['operating_system'] = 'ip'
recv_node['mode'] = 'Dukto'
recv_node['ip'] = item[2][0]
recv_node['type'] = 'text'
self.on_add_node(recv_node)
message = f'{from_addr:21}: {text}'
if not self.message_box:
self.message_box = MessageDialog(self, title='Recv TEXT')
self.message_box.message_queue.put_nowait(message)
self.message_box.show(modal=False)
def run(self):
listen = '0.0.0.0'
mode = None
cert = None
key = None
self.server = GUINetDropServer(self, listen, mode, (cert, key))
self.server.saved_to(gConfig.app['target_dir'])
threading.Thread(
name='Ndrop server',
target=self.server.wait_for_request,
daemon=True,
).start()
self.mainloop()
def run():
print(about.banner)
init_config()
app_logger = logging.getLogger(__name__.rpartition('.')[0])
app_logger.setLevel(logging.INFO)
FORMAT = ' * %(message)s'
handler = logging.StreamHandler(sys.stderr)
handler.setFormatter(logging.Formatter(fmt=FORMAT))
app_logger.addHandler(handler)
app = GuiApp()
if gConfig.app.get('enable_hdpi'):
hdpitk.MakeTkDPIAware(app)
app.run()
if __name__ == '__main__':
run() | ndrop/__main_tk__.py |
import os
import sys
import platform
import re
import argparse
import threading
import queue
import webbrowser
import logging
import ipaddress
from PIL import Image, ImageTk
import tkinterdnd2 as tkdnd
import tkinter as tk
import tkinter.ttk as ttk
from tkinter.simpledialog import Dialog as BaseDialog
from tkinter.messagebox import showinfo
from tkinter.filedialog import askdirectory, askopenfilenames
from tkinter.scrolledtext import ScrolledText
import appdirs
from . import init_config, save_config, gConfig
from . import hdpitk
from . import about
from . import hfs
from .netdrop import NetDropServer, NetDropClient
from .transport import get_broadcast_address, human_size
logger = logging.getLogger(__name__)
class GUIProgressBar(ttk.Progressbar):
def __init__(self, parent, **kwargs):
self.parent = parent
self.style = ttk.Style()
# add label in the layout
self.style.layout(
'text.Horizontal.TProgressbar',
[
(
'Horizontal.Progressbar.trough',
{
'children': [
('Horizontal.Progressbar.pbar', {'side': 'left', 'sticky': 'ns'})
],
'sticky': 'nswe'
}
),
(
'Horizontal.Progressbar.label',
{'sticky': ''}
),
]
)
super().__init__(parent, style='text.Horizontal.TProgressbar', **kwargs)
self.interval = 100
self.step_count = 0
self.time_index = 0
self.speed = ''
self.count = [0] * (1000 // self.interval)
self.parent.after(self.interval, self.on_timer_update)
def on_timer_update(self):
if self.step_count >= 0:
self.parent.after(self.interval, self.on_timer_update)
self.speed = f'{human_size(sum(self.count)):>9}/s'
self.count[self.time_index] = self.step_count
self.step_count = 0
# 0 ~ 9
self.time_index = (self.time_index + 1) % (1000 // self.interval)
self.parent.on_progressbar_update_speed(self.speed)
def update(self, step):
self.step_count += step
self.parent.on_progressbar_update(step)
def write(self, message, file=None):
logger.info(message)
def close(self):
if not self.speed:
# transfer complete less than a second
self.count[self.time_index] = self.step_count
speed = sum(self.count) / (len([x for x in self.count if x != 0]) * self.interval / 1000)
self.speed = f'{human_size(speed):>9}/s'
self.step_count = -1
self.parent.on_progressbar_close(self.speed.strip())
class GUINetDropServer(NetDropServer):
def __init__(self, parent, *args):
self.parent = parent
super().__init__(*args)
def init_bar(self, max_value):
progress = GUIProgressBar(
self.parent.host_client, orient=tk.HORIZONTAL,
maximum=max_value,
mode='determinate')
progress.grid(row=1, column=1, sticky='nsew')
progress.lift()
self.parent.host_client.progress = progress
return progress
def add_node(self, node):
super().add_node(node)
self.parent.on_add_node(node)
def remove_node(self, node):
super().remove_node(node)
self.parent.on_remove_node(node)
def recv_finish_text(self, from_addr):
text = super().recv_finish_text(from_addr)
self.parent.on_recv_text(text, from_addr)
return text
def recv_finish(self, from_addr, err):
self.parent.host_client.result = (from_addr, err)
super().recv_finish(from_addr, err)
class GUINetDropClient(NetDropClient):
def __init__(self, parent, ip, mode, cert=None, key=None):
self.parent = parent
super().__init__(ip, mode.lower(), ssl_ck=(cert, key))
def init_bar(self, max_value):
progress = GUIProgressBar(
self.parent, orient=tk.HORIZONTAL,
maximum=max_value,
mode='determinate')
progress.grid(row=1, column=1, sticky='nsew')
progress.lift()
self.parent.progress = progress
return progress
def send_finish(self, err):
self.parent.result = (None, err)
super().send_finish(err)
IMAGES = {
'back': 'BackTile.png',
'pc': 'PcLogo.png',
'android': 'AndroidLogo.png',
'apple': 'AppleLogo.png',
'darwin': 'AppleLogo.png',
'blackberry': 'BlackberryLogo.png',
'ip': 'IpLogo.png',
'linux': 'LinuxLogo.png',
'smartphone': 'SmartphoneLogo.png',
'unknown': 'UnknownLogo.png',
'windows': 'WindowsLogo.png',
'windowsphone': 'WindowsPhoneLogo.png',
'config': 'ConfigIcon.png',
'openfolder': 'OpenFolderIcon.png',
'hfs': 'hfs.png',
}
class NdropImage():
@classmethod
def get_os_image(cls, name):
image_dir = os.path.join(os.path.dirname(__file__), 'image')
back_path = os.path.join(image_dir, IMAGES['back'])
back_im = Image.open(back_path)
fore_path = os.path.join(
image_dir,
IMAGES.get(name.lower()) or IMAGES['unknown']
)
fore_im = Image.open(fore_path)
image = Image.new("RGBA", fore_im.size)
image.alpha_composite(back_im.resize(fore_im.size))
image.alpha_composite(fore_im)
return ImageTk.PhotoImage(image)
@classmethod
def get_image(cls, name, background=None):
image_dir = os.path.join(os.path.dirname(__file__), 'image')
fore_path = os.path.join(image_dir, IMAGES[name.lower()])
fore_im = Image.open(fore_path)
background = background or 'white'
image = Image.new("RGBA", fore_im.size, color=background)
image.alpha_composite(fore_im)
return ImageTk.PhotoImage(image)
class AutoScrollbar(ttk.Scrollbar):
# a scrollbar that hides itself if it's not needed. only
# works if you use the grid geometry manager.
def set(self, lo, hi):
if float(lo) <= 0.0 and float(hi) >= 1.0:
# grid_remove is currently missing from Tkinter!
self.tk.call("grid", "remove", self)
else:
self.grid()
super().set(lo, hi)
def pack(self, **kw):
raise tk.TclError("cannot use pack with this widget")
def place(self, **kw):
raise tk.TclError("cannot use place with this widget")
class ScrolledWindow(ttk.Frame):
"""
https://stackoverflow.com/questions/16188420/tkinter-scrollbar-for-frame
1. Master widget gets scrollbars and a canvas. Scrollbars are connected
to canvas scrollregion.
2. self.scrollwindow is created and inserted into canvas
Usage Guideline:
Assign any widgets as children of <ScrolledWindow instance>.scrollwindow
to get them inserted into canvas
__init__(self, parent, canv_w = 400, canv_h = 400, *args, **kwargs)
docstring:
Parent = master of scrolled window
canv_w - width of canvas
canv_h - height of canvas
"""
def __init__(self, parent, canv_w=400, canv_h=400, xbar=False, ybar=True, *args, **kwargs):
"""Parent=master of scrolled window
canv_w - width of canvas
canv_h - height of canvas
"""
super().__init__(parent, *args, **kwargs)
# creating a canvas
self.canv = tk.Canvas(self)
self.canv.config(
relief='flat',
takefocus=0,
borderwidth=0,
highlightthickness=0,
width=10,
heigh=10)
# placing a canvas into frame
self.canv.columnconfigure(0, weight=1)
self.canv.grid(column=0, row=0, sticky='nsew')
self.canv.bind('<Configure>', self._configure_canvas)
# creating a scrollbars
if xbar:
self.xscrlbr = AutoScrollbar(self,
orient='horizontal',
command=self.canv.xview)
self.xscrlbr.grid(column=0, row=1, sticky='ew')
self.canv.config(xscrollcommand=self.xscrlbr.set)
if ybar:
self.yscrlbr = AutoScrollbar(self,
orient='vertical',
command=self.canv.yview)
self.yscrlbr.grid(column=1, row=0, sticky='ns')
self.canv.config(yscrollcommand=self.yscrlbr.set)
# creating a frame to inserto to canvas
self.scrollwindow = ttk.Frame(self.canv)
self.scrollwindow.bind('<Configure>', self._configure_window)
self.scrollwindow.bind('<Enter>', self._bound_to_mousewheel)
self.scrollwindow.bind('<Leave>', self._unbound_to_mousewheel)
self.scrollwindow.columnconfigure(0, weight=1)
self.item_window = self.canv.create_window(0, 0, window=self.scrollwindow, anchor='nw')
if ybar:
self.yscrlbr.lift(self.scrollwindow)
if xbar:
self.xscrlbr.lift(self.scrollwindow)
self.rowconfigure(0, weight=1)
self.columnconfigure(0, weight=1)
def _bound_to_mousewheel(self, event):
# windows, macos
self.canv.bind_all("<MouseWheel>", self._on_mousewheel)
# linux
self.canv.bind_all("<Button-4>", self._on_mousewheel)
self.canv.bind_all("<Button-5>", self._on_mousewheel)
def _unbound_to_mousewheel(self, event):
self.canv.unbind_all("<MouseWheel>")
self.canv.unbind_all("<Button-4>")
self.canv.unbind_all("<Button-5>")
def _on_mousewheel(self, event):
if sys.platform == 'darwin':
# macos
delta = -1 * event.delta
elif event.num == 5:
# linux up
delta = 1
elif event.num == 4:
# linux down
delta = -1
else:
# windows
delta = -1 * (event.delta // 120)
self.canv.yview_scroll(delta, "units")
def _configure_window(self, event):
# canvas will expand on both direction
self.canv.configure(scrollregion=self.canv.bbox("all"))
def _configure_canvas(self, event):
self.canv.itemconfig(self.item_window, width=event.width)
class Client(ttk.Frame):
node = None
progress = None
agent = None
def __init__(self, parent, node, *args, **kwargs):
super().__init__(parent, *args, **kwargs)
self.parent = parent
self.node = node
self.queue = queue.SimpleQueue()
self.virtual_event = '<<client_queue_event>>'
self.bind(self.virtual_event, self.queue_handler)
self.image = NdropImage.get_os_image(node['operating_system'])
self.style = ttk.Style()
self.style.configure('client.TLabel', background='white')
self.label_image = ttk.Label(self, image=self.image, style='client.TLabel')
self.label_image.grid(row=0, column=0, rowspan=2, sticky='w')
if node['mode'] == '?':
text = f'{node.get("user")}\n@{node["name"]}'
else:
text = f'{node.get("mode")}\n@{node["name"]}'
label_text = ttk.Label(
self, text=text,
anchor='w', style='client.TLabel', justify=tk.LEFT)
label_text.grid(row=0, column=1, sticky='ew')
self.status = tk.StringVar()
if self.node['ip'] == '?':
self.status.set('ready')
else:
self.status.set(f'{self.node["ip"]} - ready')
label_status = ttk.Label(
self, textvariable=self.status,
anchor='w', style='client.TLabel', justify=tk.LEFT)
label_status.grid(row=1, column=1, sticky='nsew')
self.rowconfigure(1, weight=1)
self.columnconfigure(1, weight=1)
if self.node['mode'] == 'NitroShare':
self.dnd_types = [tkdnd.DND_FILES]
else:
# permit DND defaultly
self.dnd_types = [tkdnd.DND_FILES, tkdnd.DND_TEXT]
for widget in [self] + list(self.children.values()):
widget.bind('<Button-1>', self.click)
widget.drop_target_register(*self.dnd_types)
widget.dnd_bind('<<DropEnter>>', self.drop_enter)
widget.dnd_bind('<<DropPosition>>', self.drop_position)
widget.dnd_bind('<<Drop:DND_Files>>', self.drop_files)
widget.dnd_bind('<<Drop:DND_Text>>', self.drop_text)
def bind_tree(self, widget, event, callback):
widget.bind(event, callback)
for child in widget.children.values():
bind_tree(child, event, callback)
def queue_handler(self, event):
item = self.queue.get_nowait()
if self.progress:
if item[0] == 'step':
self.progress.step(item[1])
elif item[0] == 'speed':
self.progress.style.configure('text.Horizontal.TProgressbar', text=item[1])
elif item[0] == 'close':
self.progress.destroy()
self.progress = None
self.agent = None
from_addr, err = self.result
self.status.set(f'{self.node["ip"]} - {err} - {item[1]}')
def on_progressbar_update_speed(self, speed):
self.queue.put_nowait(('speed', speed))
self.event_generate(self.virtual_event)
def on_progressbar_update(self, step):
self.queue.put_nowait(('step', step))
self.event_generate(self.virtual_event)
def on_progressbar_close(self, speed):
self.queue.put_nowait(('close', speed))
self.event_generate(self.virtual_event)
def click(self, event):
if self.agent:
logger.info('| => %(mode)s@%(name)s(%(ip)s)' % self.node)
return
if self.node['type'] == 'host':
logger.info('%(mode)s@%(name)s(%(ip)s)' % self.node)
return
if self.node['type'] == 'ip':
title = 'Send'
else:
title = 'Send to %(ip)s (%(mode)s)' % self.node
dlg = SendDialog(self, title)
dlg.show()
if self.node['type'] == 'ip':
if self.node['ip'] == '?':
self.status.set('ready')
if self.node['operating_system'] != 'Unknwon':
self.node['operating_system'] = 'Unknwon'
self.image = NdropImage.get_os_image(self.node['operating_system'])
self.label_image.configure(image=self.image)
else:
self.status.set('%(ip)s - ready' % self.node)
if self.node['operating_system'] != 'ip':
self.node['operating_system'] = 'ip'
self.image = NdropImage.get_os_image(self.node['operating_system'])
self.label_image.configure(image=self.image)
else:
self.status.set(f'{self.node["ip"]} - ready')
def in_dnd_types(self, dnd_type, dnd_types):
for types in dnd_types:
if dnd_type in types:
return True
def drop_position(self, event):
if self.agent:
# be trasfering
return tkdnd.REFUSE_DROP
if self.node['type'] == 'host':
return tkdnd.REFUSE_DROP
if self.node['ip'] == '?':
return tkdnd.REFUSE_DROP
# deny dnd_text for mode nitroshare
if self.node['mode'] == 'NitroShare':
if self.in_dnd_types('CF_UNICODETEXT', event.types) or \
self.in_dnd_types('CF_TEXT', event.types):
return tkdnd.REFUSE_DROP
return event.action
def drop_enter(self, event):
event.widget.focus_force()
return event.action
def drop_text(self, event):
if event.data:
self.send_text(event.data)
return tkdnd.COPY
def drop_files(self, event):
if event.data:
drop_files = self.tk.splitlist(event.data)
self.send_files(drop_files)
return tkdnd.COPY
def send_text(self, text):
if self.agent:
return
agent = GUINetDropClient(self, self.node['ip'], self.node['mode'])
threading.Thread(
name='Ndrop client',
target=agent.send_text,
args=(text, ),
).start()
def send_files(self, files):
self.agent = GUINetDropClient(self, self.node['ip'], self.node['mode'])
threading.Thread(
name='Ndrop client',
target=self.agent.send_files,
args=(files, ),
).start()
class Dialog(BaseDialog):
def __init__(self, parent, title=None):
tk.Toplevel.__init__(self, parent)
# remain invisible for now
self.withdraw()
# If the master is not viewable, don't
# make the child transient, or else it
# would be opened withdrawn
if parent.winfo_viewable():
self.transient(parent)
if title:
self.title(title)
self.parent = parent
self.result = None
body = ttk.Frame(self)
self.initial_focus = self.body(body)
body.pack(padx=5, pady=5)
self.buttonbox()
if not self.initial_focus:
self.initial_focus = self
self.protocol("WM_DELETE_WINDOW", self.cancel)
if self.parent is not None:
self.geometry("+%d+%d" % (parent.winfo_rootx() + 50,
parent.winfo_rooty() + 50))
def show(self, modal=True):
if self.is_visible():
return
# become visible now
self.deiconify()
self.initial_focus.focus_set()
# wait for window to appear on screen before calling grab_set
self.wait_visibility()
self.grab_set()
if modal:
self.wait_window(self)
def hide(self):
if not self.is_visible():
return
self.withdraw()
self.grab_release()
if self.parent is not None:
self.parent.focus_set()
def is_visible(self):
return self.state() == 'normal'
class SettingDialog(Dialog):
def __init__(self, master, title=None, **kwargs):
target_dir = kwargs.get('target_dir', '')
self.target_dir = tk.StringVar()
self.target_dir.set(target_dir)
hdpi = 1 if kwargs.get('enable_hdpi') else 0
self.hdpi = tk.IntVar()
self.hdpi.set(hdpi)
node_by_text = 1 if kwargs.get('create_node_by_text') else 0
self.node_by_text = tk.IntVar()
self.node_by_text.set(node_by_text)
super().__init__(master, title)
def body(self, master):
label = ttk.Label(master, text='Saved folder:')
label.grid(row=0, sticky='w')
entry = ttk.Entry(master, textvariable=self.target_dir, width=40)
entry.grid(row=1, column=0, sticky='ew')
button = ttk.Button(master, text='Change folder')
button.grid(row=2, column=0, sticky='e')
button.bind('<Button-1>', self.change_folder)
checkbox = ttk.Checkbutton(master, text='Enable HDPI', variable=self.hdpi)
checkbox.grid(row=3, column=0, sticky='ew')
checkbox = ttk.Checkbutton(master, text='Create node by recving TEXT', variable=self.node_by_text)
checkbox.grid(row=4, column=0, sticky='ew')
master.rowconfigure(1, weight=1)
master.columnconfigure(0, weight=1)
master.pack(fill=tk.BOTH)
def buttonbox(self):
"""replace origin wdiget with ttk"""
box = ttk.Frame(self)
w = ttk.Button(box, text="OK", width=10, command=self.ok, default=tk.ACTIVE)
w.pack(side=tk.LEFT, padx=5, pady=5)
w = ttk.Button(box, text="Cancel", width=10, command=self.cancel)
w.pack(side=tk.LEFT, padx=5, pady=5)
self.bind("<Return>", self.ok)
self.bind("<Escape>", self.cancel)
box.pack()
def apply(self):
target_dir = self.target_dir.get()
hdpi = self.hdpi.get()
node_by_text = self.node_by_text.get()
self.result = (
os.path.normpath(target_dir),
hdpi == 1,
node_by_text == 1,
)
def change_folder(self, event):
folder = askdirectory(initialdir=self.target_dir.get())
if folder:
self.target_dir.set(os.path.normpath(folder))
class SendDialog(Dialog):
def __init__(self, parent, title=None, **kwargs):
self.dest_ip = tk.StringVar()
if parent.node['ip'] != '?':
self.dest_ip.set(parent.node['ip'])
self.mode = tk.StringVar()
if parent.node['mode'] != '?':
self.mode.set(parent.node['mode'])
self.parent = parent
super().__init__(parent, title)
def body(self, master):
label = ttk.Label(master, text='IP:')
label.grid(row=0, column=0, sticky='w', padx=5, pady=5)
entry = ttk.Entry(master, textvariable=self.dest_ip, width=20)
entry.grid(row=0, column=1, sticky='ew', padx=5, pady=5)
label = ttk.Label(master, text='Mode:')
label.grid(row=0, column=2, sticky='w', padx=5, pady=5)
choices = ['Dukto', 'NitroShare']
if not self.mode.get():
self.mode.set(choices[0])
combo = ttk.Combobox(master, values=choices, textvariable=self.mode, width=10, state="readonly")
combo.grid(row=0, column=3, sticky='ew', padx=5, pady=5)
combo.bind("<<ComboboxSelected>>", self.mode_selected)
self.textbox = ScrolledText(master, width=60, height=10)
self.textbox.grid(row=1, column=0, columnspan=4, sticky='nsew', padx=5, pady=5)
self.btn_text = ttk.Button(master, text="Send TEXT", command=self.send_text)
self.btn_text.grid(row=2, column=0, columnspan=4, sticky='ew', padx=5, pady=5)
btn_files = ttk.Button(master, text="Send Files", command=self.send_files)
btn_files.grid(row=3, column=0, columnspan=4, sticky='ew', padx=5, pady=5)
btn_folder = ttk.Button(master, text="Send Folder", command=self.send_folder)
btn_folder.grid(row=4, column=0, columnspan=4, sticky='ew', padx=5, pady=5)
master.rowconfigure(1, weight=1)
master.columnconfigure(1, weight=1)
master.pack(fill=tk.BOTH, expand=1)
if self.parent.node['type'] == 'guest':
entry.configure(state='disabled')
combo.configure(state='disabled')
if self.mode.get() == 'NitroShare':
self.textbox.configure(state='disabled')
self.btn_text.configure(state='disabled')
return entry
def buttonbox(self):
self.bind('<Escape>', self.cancel)
def mode_selected(self, event):
if self.mode.get() == 'NitroShare':
self.textbox.configure(state='disabled')
self.btn_text.configure(state='disabled')
else:
self.textbox.configure(state='normal')
self.btn_text.configure(state='normal')
def update_ip(self):
if self.parent.node['type'] == 'ip':
dest_ip = self.dest_ip.get()
if dest_ip:
try:
ipaddr = ipaddress.ip_address(dest_ip)
except ValueError:
return
self.parent.node['ip'] = str(ipaddr)
else:
self.parent.node['ip'] = '?'
return
mode = self.mode.get()
self.parent.node['mode'] = mode
return True
def send_text(self):
if self.update_ip():
text = self.textbox.get('1.0', 'end-1c')
self.cancel()
self.parent.send_text(text)
def send_files(self):
if self.update_ip():
files = askopenfilenames()
if files:
self.cancel()
self.parent.send_files(files)
def send_folder(self):
if self.update_ip():
folder = askdirectory()
if folder:
self.cancel()
self.parent.send_files([folder])
class MessageDialog(Dialog):
def __init__(self, master, title=None, message=None, **kwargs):
super().__init__(master, title)
self.master = master
self.message_queue = queue.Queue()
self.queue_handler = QueueHandler(self.message_queue)
if message:
self.message_queue.put_nowait(message)
self.master.after(100, self.poll_queue)
def display(self, message):
self.textbox.configure(state='normal')
self.textbox.insert(tk.END, message + '\n')
self.textbox.configure(state='disabled')
# Autoscroll to the bottom
self.textbox.yview(tk.END)
def poll_queue(self):
# Check every 100ms if there is a new message in the queue to display
while True:
try:
message = self.message_queue.get(block=False)
except queue.Empty:
break
else:
self.display(message)
self.master.after(100, self.poll_queue)
def body(self, master):
self.textbox = ScrolledText(master, width=60, height=10, state='disabled')
self.textbox.grid(row=0, sticky='nsew')
master.rowconfigure(0, weight=1)
master.columnconfigure(0, weight=1)
master.pack(fill=tk.BOTH, expand=1)
def buttonbox(self):
"""replace origin wdiget with ttk"""
box = ttk.Frame(self)
w = ttk.Button(box, text="OK", width=10, command=self.hide, default=tk.ACTIVE)
w.pack(side=tk.LEFT, padx=5, pady=5)
self.bind("<Return>", self.hide)
self.bind("<Escape>", self.hide)
box.pack()
class HFSDialog(Dialog):
def __init__(self, master, title=None, **kwargs):
# Create a logging handler using a queue
self.log_queue = queue.Queue()
self.queue_handler = QueueHandler(self.log_queue)
formatter = logging.Formatter('%(message)s')
self.queue_handler.setFormatter(formatter)
hfs_logger = logging.getLogger('%s.hfs' % __name__.rpartition('.')[0])
hfs_logger.addHandler(self.queue_handler)
logger.info('-- HFS server start --')
listen = '0.0.0.0'
cert = None
key = None
self.hfs_server = hfs.start(listen,
root_path=gConfig.app['target_dir'],
cert=cert, key=key,
daemon=True)
self.master = master
self.master.after(100, self.poll_log_queue)
super().__init__(master, title)
def display(self, record):
msg = self.queue_handler.format(record)
self.scrolled_text.configure(state='normal')
self.scrolled_text.insert(tk.END, msg + '\n', record.levelname)
self.scrolled_text.configure(state='disabled')
# Autoscroll to the bottom
self.scrolled_text.yview(tk.END)
def poll_log_queue(self):
# Check every 100ms if there is a new message in the queue to display
while True:
try:
record = self.log_queue.get(block=False)
except queue.Empty:
break
else:
self.display(record)
if self.hfs_server:
self.master.after(100, self.poll_log_queue)
def body(self, master):
self.scrolled_text = ScrolledText(master, width=60, height=10, state='disabled')
self.scrolled_text.grid(row=0, sticky='nsew')
master.rowconfigure(0, weight=1)
master.columnconfigure(0, weight=1)
master.pack(fill=tk.BOTH, expand=1)
def buttonbox(self):
box = ttk.Frame(self)
w = ttk.Button(box, text="OK", width=10, command=self.ok, default=tk.ACTIVE)
w.pack(side=tk.LEFT, padx=5, pady=5)
self.bind("<Return>", self.ok)
box.pack()
def apply(self):
self.result = None
self.hfs_server.shutdown()
self.hfs_server = None
logger.info('-- HFS server close --')
class QueueHandler(logging.Handler):
def __init__(self, log_queue):
super().__init__()
self.log_queue = log_queue
def emit(self, record):
self.log_queue.put(record)
def bind_tree(widget, event, callback):
widget.bind(event, callback)
for child in widget.children.values():
bind_tree(child, event, callback)
class GuiApp(tkdnd.Tk):
host_client = None
ip_client = None
message_box = None
def __init__(self, *args):
super().__init__(*args)
self.title('%s v%s' % (about.name.capitalize(), about.version))
image_dir = os.path.join(os.path.dirname(__file__), 'image')
icon_path = os.path.join(image_dir, 'ndrop.ico')
self.iconphoto(True, ImageTk.PhotoImage(Image.open(icon_path)))
self.geometry('320x360')
self.queue = queue.SimpleQueue()
uname = platform.uname()
ipaddrs, _ = get_broadcast_address()
host_node = {}
host_node['user'] = 'You'
host_node['name'] = uname.node
host_node['operating_system'] = uname.system
host_node['mode'] = '?'
host_node['ip'] = ', '.join(ipaddrs)
host_node['type'] = 'host'
self.host_client = Client(self, host_node)
self.host_client.grid(row=0, column=0, sticky='ew', padx=10, pady=10)
sep = ttk.Separator(self)
sep.grid(row=1, column=0, sticky='ew', padx=40, pady=0)
frame = ScrolledWindow(self, xbar=False, ybar=True)
frame.grid(sticky='ewns')
self.frame = frame.scrollwindow
ip_node = {}
ip_node['user'] = 'IP connection'
ip_node['name'] = 'Send data to a remote device.'
ip_node['operating_system'] = 'Unknown'
ip_node['mode'] = '?'
ip_node['ip'] = '?'
ip_node['type'] = 'ip'
self.ip_client = Client(self.frame, ip_node)
self.ip_client.grid(sticky='ew', padx=10, pady=5)
s = ttk.Style()
s.configure('footer.TFrame', background='green')
s.configure('footer.TLabel', background='green')
footer = ttk.Frame(self, style='footer.TFrame')
footer.grid(sticky='ew')
self.image_openfolder = NdropImage.get_image('openfolder', background='green')
label = ttk.Label(footer, image=self.image_openfolder, style='footer.TLabel')
label.grid(row=0, column=1, padx=10, pady=5)
label.bind('<Button-1>', self.open_folder)
self.image_config = NdropImage.get_image('config', background='green')
label = ttk.Label(footer, image=self.image_config, style='footer.TLabel')
label.grid(row=0, column=2, padx=10, pady=5)
label.bind('<Button-1>', self.show_config)
self.image_hfs = NdropImage.get_image('hfs', background='green')
label = ttk.Label(footer, image=self.image_hfs, style='footer.TLabel')
label.grid(row=0, column=3, padx=10, pady=5)
label.bind('<Button-1>', self.show_hfs)
footer.columnconfigure(0, weight=1)
footer.columnconfigure(4, weight=1)
self.rowconfigure(2, weight=1)
self.columnconfigure(0, weight=1)
self.bind('<<server_queue_event>>', self.queue_handler)
def on_add_node(self, node):
self.queue.put_nowait(('add_node', node))
self.event_generate('<<server_queue_event>>')
def on_remove_node(self, node):
self.queue.put_nowait(('remove_node', node))
self.event_generate('<<server_queue_event>>')
def on_recv_text(self, text, from_addr):
self.queue.put_nowait(('recv_text', text, from_addr))
self.event_generate('<<server_queue_event>>')
def open_folder(self, event):
webbrowser.open(gConfig.app['target_dir'])
def show_config(self, event):
dlg = SettingDialog(
self, 'Settings',
target_dir=gConfig.app['target_dir'],
enable_hdpi=gConfig.app['enable_hdpi'],
create_node_by_text=gConfig.app['create_node_by_text'],
)
dlg.show()
if dlg.result:
target_dir, hdpi, node_by_text = dlg.result
if gConfig.app['enable_hdpi'] != hdpi:
showinfo('Information', 'Close and open app again for HDPI')
gConfig.app['target_dir'] = target_dir
gConfig.app['enable_hdpi'] = hdpi
gConfig.app['create_node_by_text'] = node_by_text
save_config()
self.server.saved_to(gConfig.app['target_dir'])
def show_hfs(self, event):
dlg = HFSDialog(self, 'HFS')
dlg.show()
def queue_handler(self, event):
item = self.queue.get_nowait()
if item[0] == 'add_node':
node = item[1]
for client in self.frame.winfo_children():
if client.node['ip'] == node['ip'] and \
client.node['mode'] == node['mode']:
if client.node['type'] == 'text' and node['type'] == 'guest':
# destroy text client and create guest client
client.destroy()
else:
return
client = Client(self.frame, node)
pad = (10, 5)
client.grid(sticky='ew', padx=pad[0], pady=pad[1])
elif item[0] == 'remove_node':
node = item[1]
for client in self.frame.winfo_children():
if not client.progress and \
client.node['type'] == 'guest' and \
client.node['ip'] == node['ip'] and \
client.node['mode'] == node['mode']:
client.destroy()
elif item[0] == 'recv_text':
text = item[1]
from_addr = '%s:%s' % item[2]
if gConfig.app['create_node_by_text']:
# add node
recv_node = {}
recv_node['user'] = 'Unknown'
recv_node['name'] = 'Unknown'
recv_node['operating_system'] = 'ip'
recv_node['mode'] = 'Dukto'
recv_node['ip'] = item[2][0]
recv_node['type'] = 'text'
self.on_add_node(recv_node)
message = f'{from_addr:21}: {text}'
if not self.message_box:
self.message_box = MessageDialog(self, title='Recv TEXT')
self.message_box.message_queue.put_nowait(message)
self.message_box.show(modal=False)
def run(self):
listen = '0.0.0.0'
mode = None
cert = None
key = None
self.server = GUINetDropServer(self, listen, mode, (cert, key))
self.server.saved_to(gConfig.app['target_dir'])
threading.Thread(
name='Ndrop server',
target=self.server.wait_for_request,
daemon=True,
).start()
self.mainloop()
def run():
print(about.banner)
init_config()
app_logger = logging.getLogger(__name__.rpartition('.')[0])
app_logger.setLevel(logging.INFO)
FORMAT = ' * %(message)s'
handler = logging.StreamHandler(sys.stderr)
handler.setFormatter(logging.Formatter(fmt=FORMAT))
app_logger.addHandler(handler)
app = GuiApp()
if gConfig.app.get('enable_hdpi'):
hdpitk.MakeTkDPIAware(app)
app.run()
if __name__ == '__main__':
run() | 0.472683 | 0.082401 |